existing hydrological models: Topics by Science.gov

Sample records for existing hydrological models

A RETROSPECTIVE ANALYSIS OF MODEL UNCERTAINTY FOR FORECASTING HYDROLOGIC CHANGE

EPA Science Inventory

GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate pot...
HYDROLOGIC MODEL UNCERTAINTY ASSOCIATED WITH SIMULATING FUTURE LAND-COVER/USE SCENARIOS: A RETROSPECTIVE ANALYSIS

EPA Science Inventory

GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate pot...
Publishing and sharing of hydrologic models through WaterHUB

NASA Astrophysics Data System (ADS)

Merwade, V.; Ruddell, B. L.; Song, C.; Zhao, L.; Kim, J.; Assi, A.

2011-12-01

Most hydrologists use hydrologic models to simulate the hydrologic processes to understand hydrologic pathways and fluxes for research, decision making and engineering design. Once these tasks are complete including publication of results, the models generally are not published or made available to the public for further use and improvement. Although publication or sharing of models is not required for journal publications, sharing of models may open doors for new collaborations, and avoids duplication of efforts if other researchers are interested in simulating a particular watershed for which a model already exists. For researchers, who are interested in sharing models, there are limited avenues to publishing their models to the wider community. Towards filling this gap, a prototype cyberinfrastructure (CI), called WaterHUB, is developed for sharing hydrologic data and modeling tools in an interactive environment. To test the utility of WaterHUB for sharing hydrologic models, a system to publish and share SWAT (Soil Water Assessment Tool) is developed. Users can utilize WaterHUB to search and download existing SWAT models, and also upload new SWAT models. Metadata such as the name of the watershed, name of the person or agency who developed the model, simulation period, time step, and list of calibrated parameters also published with individual model.
Hydrological and geomorphological controls of malaria transmission

NASA Astrophysics Data System (ADS)

Smith, M. W.; Macklin, M. G.; Thomas, C. J.

2013-01-01

Malaria risk is linked inextricably to the hydrological and geomorphological processes that form vector breeding sites. Yet environmental controls of malaria transmission are often represented by temperature and rainfall amounts, ignoring hydrological and geomorphological influences altogether. Continental-scale studies incorporate hydrology implicitly through simple minimum rainfall thresholds, while community-scale coupled hydrological and entomological models do not represent the actual diversity of the mosquito vector breeding sites. The greatest range of malaria transmission responses to environmental factors is observed at the catchment scale where seemingly contradictory associations between rainfall and malaria risk can be explained by hydrological and geomorphological processes that govern surface water body formation and persistence. This paper extends recent efforts to incorporate ecological factors into malaria-risk models, proposing that the same detailed representation be afforded to hydrological and, at longer timescales relevant for predictions of climate change impacts, geomorphological processes. We review existing representations of environmental controls of malaria and identify a range of hydrologically distinct vector breeding sites from existing literature. We illustrate the potential complexity of interactions among hydrology, geomorphology and vector breeding sites by classifying a range of water bodies observed in a catchment in East Africa. Crucially, the mechanisms driving surface water body formation and destruction must be considered explicitly if we are to produce dynamic spatial models of malaria risk at catchment scales.
A new fit-for-purpose model testing framework: Decision Crash Tests

NASA Astrophysics Data System (ADS)

Tolson, Bryan; Craig, James

2016-04-01

Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building decisions. In one case, we show the set of model building decisions has a low probability to correctly support the upgrade decision. In the other case, we show evidence suggesting another set of model building decisions has a high probability to correctly support the decision. The proposed DCT framework focuses on what model users typically care about: the management decision in question. The DCT framework will often be very strict and will produce easy to interpret results enabling clear unsuitability determinations. In the past, hydrologic modelling progress has necessarily meant new models and model building methods. Continued progress in hydrologic modelling requires finding clear evidence to motivate researchers to disregard unproductive models and methods and the DCT framework is built to produce this kind of evidence. References: Andréassian, V., C. Perrin, L. Berthet, N. Le Moine, J. Lerat, C. Loumagne, L. Oudin, T. Mathevet, M.-H. Ramos, and A. Valéry (2009), Crash tests for a standardized evaluation of hydrological models. Hydrology and Earth System Sciences, 13, 1757-1764. Klemeš, V. (1986), Operational testing of hydrological simulation models. Hydrological Sciences Journal, 31 (1), 13-24.
VERIFICATION OF THE HYDROLOGIC EVALUATION OF LANDFILL PERFORMANCE (HELP) MODEL USING FIELD DATA

EPA Science Inventory

The report describes a study conducted to verify the Hydrologic Evaluation of Landfill Performance (HELP) computer model using existing field data from a total of 20 landfill cells at 7 sites in the United States. Simulations using the HELP model were run to compare the predicted...
Application of remote sensing to hydrology. [for the formulation of watershed behavior models

NASA Technical Reports Server (NTRS)

Ambaruch, R.; Simmons, J. W.

1973-01-01

Streamflow forecasting and hydrologic modelling are considered in a feasibility assessment of using the data produced by remote observation from space and/or aircraft to reduce the time and expense normally involved in achieving the ability to predict the hydrological behavior of an ungaged watershed. Existing watershed models are described, and both stochastic and parametric techniques are discussed towards the selection of a suitable simulation model. Technical progress and applications are reported and recommendations are made for additional research.
Distributed Hydrologic Modeling Apps for Decision Support in the Cloud

NASA Astrophysics Data System (ADS)

Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.

2013-12-01

Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it requires the use of additional software. In particular, there are at least three elements that are needed: a geospatially enabled database, a map server, and geoprocessing toolbox. We recommend a software stack for geospatial web application development comprising: MapServer, PostGIS, and 52 North with Python as the scripting language to tie them together. Another hurdle that must be cleared is managing the cloud-computing load. We are using HTCondor as a solution to this end. Finally, we are creating a scripting environment wherein developers will be able to create apps that use existing hydrologic models in our system with minimal effort. This capability will be accomplished by creating a plugin for a Python content management system called CKAN. We are currently developing cyberinfrastructure that utilizes this stack and greatly lowers the investment required to deploy cloud-based modeling apps. This material is based upon work supported by the National Science Foundation under Grant No. 1135482
Sensitivity of effective rainfall amount to land use description using GIS tool. Case of a small mediterranean catchment

NASA Astrophysics Data System (ADS)

Payraudeau, S.; Tournoud, M. G.; Cernesson, F.

Distributed modelling in hydrology assess catchment subdivision to take into account physic characteristics. In this paper, we test the effect of land use aggregation scheme on catchment hydrological response. Evolution of intra-subcatchment land use is studied using statistic and entropy methods. The SCS-CN method is used to calculate effective rainfall which is here assimilated to hydrological response. Our purpose is to determine the existence of a critical threshold-area appropriate for the application of hydrological modelling. Land use aggregation effects on effective rainfall is assessed on small mediterranean catchment. The results show that land use aggregation and land use classification type have significant effects on hydrological modelling and in particular on effective rainfall modelling.
Towards methodical modelling: Differences between the structure and output dynamics of multiple conceptual models

NASA Astrophysics Data System (ADS)

Knoben, Wouter; Woods, Ross; Freer, Jim

2016-04-01

Conceptual hydrologic models consist of a certain arrangement of spatial and temporal dynamics consisting of stores, fluxes and transformation functions, depending on the modeller's choices and intended use. They have the advantages of being computationally efficient, being relatively easy model structures to reconfigure and having relatively low input data demands. This makes them well-suited for large-scale and large-sample hydrology, where appropriately representing the dominant hydrologic functions of a catchment is a main concern. Given these requirements, the number of parameters in the model cannot be too high, to avoid equifinality and identifiability issues. This limits the number and level of complexity of dominant hydrologic processes the model can represent. Specific purposes and places thus require a specific model and this has led to an abundance of conceptual hydrologic models. No structured overview of these models exists and there is no clear method to select appropriate model structures for different catchments. This study is a first step towards creating an overview of the elements that make up conceptual models, which may later assist a modeller in finding an appropriate model structure for a given catchment. To this end, this study brings together over 30 past and present conceptual models. The reviewed model structures are simply different configurations of three basic model elements (stores, fluxes and transformation functions), depending on the hydrologic processes the models are intended to represent. Differences also exist in the inner workings of the stores, fluxes and transformations, i.e. the mathematical formulations that describe each model element's intended behaviour. We investigate the hypothesis that different model structures can produce similar behavioural simulations. This can clarify the overview of model elements by grouping elements which are similar, which can improve model structure selection.
Designing hydrologic monitoring networks to maximize predictability of hydrologic conditions in a data assimilation system: a case study from South Florida, U.S.A

NASA Astrophysics Data System (ADS)

Flores, A. N.; Pathak, C. S.; Senarath, S. U.; Bras, R. L.

2009-12-01

Robust hydrologic monitoring networks represent a critical element of decision support systems for effective water resource planning and management. Moreover, process representation within hydrologic simulation models is steadily improving, while at the same time computational costs are decreasing due to, for instance, readily available high performance computing resources. The ability to leverage these increasingly complex models together with the data from these monitoring networks to provide accurate and timely estimates of relevant hydrologic variables within a multiple-use, managed water resources system would substantially enhance the information available to resource decision makers. Numerical data assimilation techniques provide mathematical frameworks through which uncertain model predictions can be constrained to observational data to compensate for uncertainties in the model forcings and parameters. In ensemble-based data assimilation techniques such as the ensemble Kalman Filter (EnKF), information in observed variables such as canal, marsh and groundwater stages are propagated back to the model states in a manner related to: (1) the degree of certainty in the model state estimates and observations, and (2) the cross-correlation between the model states and the observable outputs of the model. However, the ultimate degree to which hydrologic conditions can be accurately predicted in an area of interest is controlled, in part, by the configuration of the monitoring network itself. In this proof-of-concept study we developed an approach by which the design of an existing hydrologic monitoring network is adapted to iteratively improve the predictions of hydrologic conditions within an area of the South Florida Water Management District (SFWMD). The objective of the network design is to minimize prediction errors of key hydrologic states and fluxes produced by the spatially distributed Regional Simulation Model (RSM), developed specifically to simulate the hydrologic conditions in several intensively managed and hydrologically complex watersheds within the SFWMD system. In a series of synthetic experiments RSM is used to generate the notionally true hydrologic state and the relevant observational data. The EnKF is then used as the mechanism to fuse RSM hydrologic estimates with data from the candidate network. The performance of the candidate network is measured by the prediction errors of the EnKF estimates of hydrologic states, relative to the notionally true scenario. The candidate network is then adapted by relocating existing observational sites to unobserved areas where predictions of local hydrologic conditions are most uncertain and the EnKF procedure repeated. Iteration of the monitoring network continues until further improvements in EnKF-based predictions of hydrologic conditions are negligible.
Extending data worth methods to select multiple observations targeting specific hydrological predictions of interest

NASA Astrophysics Data System (ADS)

Vilhelmsen, Troels N.; Ferré, Ty P. A.

2016-04-01

Hydrological models are often developed to forecasting future behavior in response due to natural or human induced changes in stresses affecting hydrologic systems. Commonly, these models are conceptualized and calibrated based on existing data/information about the hydrological conditions. However, most hydrologic systems lack sufficient data to constrain models with adequate certainty to support robust decision making. Therefore, a key element of a hydrologic study is the selection of additional data to improve model performance. Given the nature of hydrologic investigations, it is not practical to select data sequentially, i.e. to choose the next observation, collect it, refine the model, and then repeat the process. Rather, for timing and financial reasons, measurement campaigns include multiple wells or sampling points. There is a growing body of literature aimed at defining the expected data worth based on existing models. However, these are almost all limited to identifying single additional observations. In this study, we present a methodology for simultaneously selecting multiple potential new observations based on their expected ability to reduce the uncertainty of the forecasts of interest. This methodology is based on linear estimates of the predictive uncertainty, and it can be used to determine the optimal combinations of measurements (location and number) established to reduce the uncertainty of multiple predictions. The outcome of the analysis is an estimate of the optimal sampling locations; the optimal number of samples; as well as a probability map showing the locations within the investigated area that are most likely to provide useful information about the forecasting of interest.
Comprehensive Representation of Hydrologic and Geomorphic Process Coupling in Numerical Models: Internal Dynamics and Basin Evolution

NASA Astrophysics Data System (ADS)

Istanbulluoglu, E.; Vivoni, E. R.; Ivanov, V. Y.; Bras, R. L.

2005-12-01

Landscape morphology has an important control on the spatial and temporal organization of basin hydrologic response to climate forcing, affecting soil moisture redistribution as well as vegetation function. On the other hand, erosion, driven by hydrology and modulated by vegetation, produces landforms over geologic time scales that reflect characteristic signatures of the dominant land forming process. Responding to extreme climate events or anthropogenic disturbances of the land surface, infrequent but rapid forms of erosion (e.g., arroyo development, landsliding) can modify topography such that basin hydrology is significantly influenced. Despite significant advances in both hydrologic and geomorphic modeling over the past two decades, the dynamic interactions between basin hydrology, geomorphology and terrestrial ecology are not adequately captured in current model frameworks. In order to investigate hydrologic-geomorphic-ecologic interactions at the basin scale we present initial efforts in integrating the CHILD landscape evolution model (Tucker et al. 2001) with the tRIBS hydrology model (Ivanov et al. 2004), both developed in a common software environment. In this talk, we present preliminary results of the numerical modeling of the coupled evolution of basin hydro-geomorphic response and resulting landscape morphology in two sets of examples. First, we discuss the long-term evolution of both the hydrologic response and the resulting basin morphology from an initially uplifted plateau. In the second set of modeling experiments, we implement changes in climate and land-use to an existing topography and compare basin hydrologic response to the model results when landscape form is fixed (e.g. no coupling between hydrology and geomorphology). Model results stress the importance of internal basin dynamics, including runoff generation mechanisms and hydrologic states, in shaping hydrologic response as well as the importance of employing comprehensive conceptualizations of hydrology in modeling landscape evolution.
Mountain Hydrology of the Semi-Arid Western U.S.: Research Needs, Opportunities and Challenges

NASA Astrophysics Data System (ADS)

Bales, R.; Dozier, J.; Molotch, N.; Painter, T.; Rice, R.

2004-12-01

In the semi-arid Western U.S., water resources are being stressed by the combination of climate warming, changing land use, and population growth. Multiple consensus planning documents point to this region as perhaps the highest priority for new hydrologic understanding. Three main hydrologic issues illustrate research needs in the snow-driven hydrology of the region. First, despite the hydrologic importance of mountainous regions, the processes controlling their energy, water and biogeochemical fluxes are not well understood. Second, there exists a need to realize, at various spatial and temporal scales, the feedback systems between hydrological fluxes and biogeochemical and ecological processes. Third, the paucity of adequate observation networks in mountainous regions hampers improvements in understanding these processes. For example, we lack an adequate description of factors controlling the partitioning of snowmelt into runoff versus infiltration and evapotranspiration, and need strategies to accurately measure the variability of precipitation, snow cover and soil moisture. The amount of mountain-block and mountain-front recharge and how recharge patterns respond to climate variability are poorly known across the mountainous West. Moreover, hydrologic modelers and those measuring important hydrologic variables from remote sensing and distributed in situ sites have failed to bridge rifts between modeling needs and available measurements. Research and operational communities will benefit from data fusion/integration, improved measurement arrays, and rapid data access. For example, the hydrologic modeling community would advance if given new access to single rather than disparate sources of bundles of cutting-edge remote sensing retrievals of snow covered area and albedo, in situ measurements of snow water equivalent and precipitation, and spatio-temporal fields of variables that drive models. In addition, opportunities exist for the deployment of new technologies, taking advantage of research in spatially distributed sensor networks that can enhance data recovery and analysis.
Open source data assimilation framework for hydrological modeling

NASA Astrophysics Data System (ADS)

Ridler, Marc; Hummel, Stef; van Velzen, Nils; Katrine Falk, Anne; Madsen, Henrik

2013-04-01

An open-source data assimilation framework is proposed for hydrological modeling. Data assimilation (DA) in hydrodynamic and hydrological forecasting systems has great potential to improve predictions and improve model result. The basic principle is to incorporate measurement information into a model with the aim to improve model results by error minimization. Great strides have been made to assimilate traditional in-situ measurements such as discharge, soil moisture, hydraulic head and snowpack into hydrologic models. More recently, remotely sensed data retrievals of soil moisture, snow water equivalent or snow cover area, surface water elevation, terrestrial water storage and land surface temperature have been successfully assimilated in hydrological models. The assimilation algorithms have become increasingly sophisticated to manage measurement and model bias, non-linear systems, data sparsity (time & space) and undetermined system uncertainty. It is therefore useful to use a pre-existing DA toolbox such as OpenDA. OpenDA is an open interface standard for (and free implementation of) a set of tools to quickly implement DA and calibration for arbitrary numerical models. The basic design philosophy of OpenDA is to breakdown DA into a set of building blocks programmed in object oriented languages. To implement DA, a model must interact with OpenDA to create model instances, propagate the model, get/set variables (or parameters) and free the model once DA is completed. An open-source interface for hydrological models exists capable of all these tasks: OpenMI. OpenMI is an open source standard interface already adopted by key hydrological model providers. It defines a universal approach to interact with hydrological models during simulation to exchange data during runtime, thus facilitating the interactions between models and data sources. The interface is flexible enough so that models can interact even if the model is coded in a different language, represent processes from a different domain or have different spatial and temporal resolutions. An open source framework that bridges OpenMI and OpenDA is presented. The framework provides a generic and easy means for any OpenMI compliant model to assimilate observation measurements. An example test case will be presented using MikeSHE, and OpenMI compliant fully coupled integrated hydrological model that can accurately simulate the feedback dynamics of overland flow, unsaturated zone and saturated zone.
An integrated model of soil, hydrology, and vegetation for carbon dynamics in wetland ecosystems

Treesearch

Yu Zhang; Changsheng Li; Carl C. Trettin; Harbin Li; Ge Sun

2002-01-01

Wetland ecosystems are an important component in global carbon (C) cycles and may exert a large influence on global clinlate change. Predictions of C dynamics require us to consider interactions among many critical factors of soil, hydrology, and vegetation. However, few such integrated C models exist for wetland ecosystems. In this paper, we report a simulation model...
SWATShare- A Platform for Collaborative Hydrology Research and Education with Cyber-enabled Sharing, Running and Visualization of SWAT Models

NASA Astrophysics Data System (ADS)

Rajib, M. A.; Merwade, V.; Song, C.; Zhao, L.; Kim, I. L.; Zhe, S.

2014-12-01

Setting up of any hydrologic model requires a large amount of efforts including compilation of all the data, creation of input files, calibration and validation. Given the amount of efforts involved, it is possible that models for a watershed get created multiple times by multiple groups or organizations to accomplish different research, educational or policy goals. To reduce the duplication of efforts and enable collaboration among different groups or organizations around an already existing hydrology model, a platform is needed where anyone can search for existing models, perform simple scenario analysis and visualize model results. The creator and users of a model on such a platform can then collaborate to accomplish new research or educational objectives. From this perspective, a prototype cyber-infrastructure (CI), called SWATShare, is developed for sharing, running and visualizing Soil Water Assessment Tool (SWAT) models in an interactive GIS-enabled web environment. Users can utilize SWATShare to publish or upload their own models, search and download existing SWAT models developed by others, run simulations including calibration using high performance resources provided by XSEDE and Cloud. Besides running and sharing, SWATShare hosts a novel spatio-temporal visualization system for SWAT model outputs. In temporal scale, the system creates time-series plots for all the hydrology and water quality variables available along the reach as well as in watershed-level. In spatial scale, the system can dynamically generate sub-basin level thematic maps for any variable at any user-defined date or date range; and thereby, allowing users to run animations or download the data for subsequent analyses. In addition to research, SWATShare can also be used within a classroom setting as an educational tool for modeling and comparing the hydrologic processes under different geographic and climatic settings. SWATShare is publicly available at https://www.water-hub.org/swatshare.
Integrating wetland connectivity into models for watershed-scale analyses: Current and future approaches

EPA Science Inventory

Geographically isolated wetlands (GIW), or wetlands embedded in uplands, exist along a spatial and temporal hydrologic connectivity continuum to downstream waters. Via these connections and disconnections, GIWs provide numerous hydrological, biogeochemical, and biological functio...
Quantifying and Generalizing Hydrologic Responses to Dam Regulation using a Statistical Modeling Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

McManamay, Ryan A

2014-01-01

Despite the ubiquitous existence of dams within riverscapes, much of our knowledge about dams and their environmental effects remains context-specific. Hydrology, more than any other environmental variable, has been studied in great detail with regard to dam regulation. While much progress has been made in generalizing the hydrologic effects of regulation by large dams, many aspects of hydrology show site-specific fidelity to dam operations, small dams (including diversions), and regional hydrologic regimes. A statistical modeling framework is presented to quantify and generalize hydrologic responses to varying degrees of dam regulation. Specifically, the objectives were to 1) compare the effects ofmore » local versus cumulative dam regulation, 2) determine the importance of different regional hydrologic regimes in influencing hydrologic responses to dams, and 3) evaluate how different regulation contexts lead to error in predicting hydrologic responses to dams. Overall, model performance was poor in quantifying the magnitude of hydrologic responses, but performance was sufficient in classifying hydrologic responses as negative or positive. Responses of some hydrologic indices to dam regulation were highly dependent upon hydrologic class membership and the purpose of the dam. The opposing coefficients between local and cumulative-dam predictors suggested that hydrologic responses to cumulative dam regulation are complex, and predicting the hydrology downstream of individual dams, as opposed to multiple dams, may be more easy accomplished using statistical approaches. Results also suggested that particular contexts, including multipurpose dams, high cumulative regulation by multiple dams, diversions, close proximity to dams, and certain hydrologic classes are all sources of increased error when predicting hydrologic responses to dams. Statistical models, such as the ones presented herein, show promise in their ability to model the effects of dam regulation effects at large spatial scales as to generalize the directionality of hydrologic responses.« less
Accelerating advances in continental domain hydrologic modeling

USGS Publications Warehouse

Archfield, Stacey A.; Clark, Martyn; Arheimer, Berit; Hay, Lauren E.; McMillan, Hilary; Kiang, Julie E.; Seibert, Jan; Hakala, Kirsti; Bock, Andrew R.; Wagener, Thorsten; Farmer, William H.; Andreassian, Vazken; Attinger, Sabine; Viglione, Alberto; Knight, Rodney; Markstrom, Steven; Over, Thomas M.

2015-01-01

In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.

lumpR 2.0.0: an R package facilitating landscape discretisation for hillslope-based hydrological models

NASA Astrophysics Data System (ADS)

Pilz, Tobias; Francke, Till; Bronstert, Axel

2017-08-01

The characteristics of a landscape pose essential factors for hydrological processes. Therefore, an adequate representation of the landscape of a catchment in hydrological models is vital. However, many of such models exist differing, amongst others, in spatial concept and discretisation. The latter constitutes an essential pre-processing step, for which many different algorithms along with numerous software implementations exist. In that context, existing solutions are often model specific, commercial, or depend on commercial back-end software, and allow only a limited or no workflow automation at all. Consequently, a new package for the scientific software and scripting environment R, called lumpR, was developed. lumpR employs an algorithm for hillslope-based landscape discretisation directed to large-scale application via a hierarchical multi-scale approach. The package addresses existing limitations as it is free and open source, easily extendible to other hydrological models, and the workflow can be fully automated. Moreover, it is user-friendly as the direct coupling to a GIS allows for immediate visual inspection and manual adjustment. Sufficient control is furthermore retained via parameter specification and the option to include expert knowledge. Conversely, completely automatic operation also allows for extensive analysis of aspects related to landscape discretisation. In a case study, the application of the package is presented. A sensitivity analysis of the most important discretisation parameters demonstrates its efficient workflow automation. Considering multiple streamflow metrics, the employed model proved reasonably robust to the discretisation parameters. However, parameters determining the sizes of subbasins and hillslopes proved to be more important than the others, including the number of representative hillslopes, the number of attributes employed for the lumping algorithm, and the number of sub-discretisations of the representative hillslopes.
Marrying Hydrological Modelling and Integrated Assessment for the needs of Water Resource Management

NASA Astrophysics Data System (ADS)

Croke, B. F. W.; Blakers, R. S.; El Sawah, S.; Fu, B.; Guillaume, J. H. A.; Kelly, R. A.; Patrick, M. J.; Ross, A.; Ticehurst, J.; Barthel, R.; Jakeman, A. J.

2014-09-01

This paper discusses the integration of hydrology with other disciplines using an Integrated Assessment (IA) and modelling approach to the management and allocation of water resources. Recent developments in the field of socio-hydrology aim to develop stronger relationships between hydrology and the human dimensions of Water Resource Management (WRM). This should build on an existing wealth of knowledge and experience of coupled human-water systems. To further strengthen this relationship and contribute to this broad body of knowledge, we propose a strong and durable "marriage" between IA and hydrology. The foundation of this marriage requires engagement with appropriate concepts, model structures, scales of analyses, performance evaluation and communication - and the associated tools and models that are needed for pragmatic deployment or operation. To gain insight into how this can be achieved, an IA case study in water allocation in the Lower Namoi catchment, NSW, Australia is presented.
Assessing Hydrologic Impacts of Land Configuration Changes Using an Integrated Hydrologic Model at the Rocky Flats Environmental Technology Site, Colorado

NASA Astrophysics Data System (ADS)

Prucha, R. H.; Dayton, C. S.; Hawley, C. M.

2002-12-01

The Rocky Flats Environmental Technology Site (RFETS) in Golden, Colorado, a former Department of Energy nuclear weapons manufacturing facility, is currently undergoing closure. The natural semi-arid interaction between surface and subsurface flow at RFETS is complex and complicated by the industrial modifications to the flow system. Using a substantial site data set, a distributed parameter, fully-integrated hydrologic model was developed to assess the hydrologic impact of different hypothetical site closure configurations on the current flow system and to better understand the integrated hydrologic behavior of the system. An integrated model with this level of detail has not been previously developed in a semi-arid area, and a unique, but comprehensive, approach was required to calibrate and validate the model. Several hypothetical scenarios were developed to simulate hydrologic effects of modifying different aspects of the site. For example, some of the simulated modifications included regrading the current land surface, changing the existing surface channel network, removing subsurface trenches and gravity drain flow systems, installing a slurry wall and geotechnical cover, changing the current vegetative cover, and converting existing buildings and pavement to permeable soil areas. The integrated flow model was developed using a rigorous physically-based code so that realistic design parameters can simulate these changes. This code also permitted evaluation of changes to complex integrated hydrologic system responses that included channelized and overland flow, pond levels, unsaturated zone storage, groundwater heads and flow directions, and integrated water balances for key areas. Results generally show that channel flow offsite decreases substantially for different scenarios, while groundwater heads generally increase within the reconfigured industrial area most of which is then discharged as evapotranspiration. These changes have significant implications to site closure and operation.
Tracking unaccounted water use in data sparse arid environment

NASA Astrophysics Data System (ADS)

Hafeez, M. M.; Edraki, M.; Ullah, M. K.; Chemin, Y.; Sixsmith, J.; Faux, R.

2009-12-01

Hydrological knowledge of irrigated farms within the inundation plains of the Murray Darling Basin (MDB) is very limited in quality and reliability of the observation network that has been declining rapidly over the past decade. This paper focuses on Land Surface Diversions (LSD) that encompass all forms of surface water diversion except the direct extraction of water from rivers, watercourses and lakes by farmers for the purposes of irrigation and stock and domestic supply. Its accurate measurement is very challenging, due to the practical difficulties associated with separating the different components of LSD and estimating them accurately for a large catchment. The inadequacy of current methods of measuring and monitoring LSD poses severe limitations on existing and proposed policies for managing such diversions. It is commonly believed that LSD comprises 20-30% of total diversions from river valleys in the MDB areas. But, scientific estimates of LSD do not exist, because they were considered unimportant prior the onset of recent draught in Australia. There is a need to develop hydrological water balance models through the coupling of hydrological variables derived from on ground hydrological measurements and remote sensing techniques to accurately model LSD. Typically, the hydrological water balance components for farm/catchment scale models includes: irrigation inflow, outflow, rainfall, runoff, evapotranspiration, soil moisture change and deep percolation. The actual evapotranspiration (ETa) is the largest and single most important component of hydrological water balance model. An accurate quantification of all components of hydrological water balance model at farm/catchment scale is of prime importance to estimate the volume of LSD. A hydrological water balance model is developed to calculate LSD at 6 selected pilot farms. The catchment hydrological water balance model is being developed by using selected parameters derived from hydrological water balance model at farm scale. LSD results obtained through the modelling process have been compared with LSD estimates measured with the ground observed data at 6 pilot farms. The differences between the values are between 3 to 5 percent of the water inputs which is within the confidence limit expected from such analysis. Similarly, the LSD values at the catchment scale have been estimated with a great confidence. The hydrological water balance models at farm and catchment scale provide reliable quantification of LSD. Improved LSD estimates can guide water management decisions at farm to catchment scale and could be instrumental for enhancing the integrity of the water allocation process and making them fairer and equitable across stakeholders.
Evaluation of Potential Evapotranspiration from a Hydrologic Model on a National Scale

NASA Astrophysics Data System (ADS)

Hakala, K. A.; Hay, L.; Markstrom, S. L.

2014-12-01

The US Geological Survey has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development and facilitate the application of simulations on the scale of the continental US. The NHM has a consistent geospatial fabric for modeling, consisting of over 100,000 hydrologic response units (HRUs). Each HRU requires accurate parameter estimates, some of which are attained from automated calibration. However, improved calibration can be achieved by initially utilizing as many parameters as possible from national data sets. This presentation investigates the effectiveness of calculating potential evapotranspiration (PET) parameters based on mean monthly values from the NOAA PET Atlas. Additional PET products are then used to evaluate the PET parameters. Effectively utilizing existing national-scale data sets can simplify the effort in establishing a robust NHM.
Study plan for the regional aquifer-system analysis of alluvial basins in south-central Arizona and adjacent states

USGS Publications Warehouse

Anderson, T.W.

1980-01-01

The U.S. Geological Survey has started a 4-year study of the alluvial basins in south-central Arizona and parts of California , Nevada, and New Mexico to describe the hydrologic setting, available groundwater resources, and effects of historical development on the groundwater system. To aid in the study, mathematical models of selected basins will be developed for appraising local and regional flow systems. Major components necessary to accomplish the study objectives include the accumulation of existing data on groundwater quantity and quality, entering the data into a computer file, identification of data deficiencies, and development of a program to remedy the deficiencies by collection of additional data. The approach to the study will be to develop and calibrate models of selected basins for which sufficient data exist and to develop interpretation-transfer techniques whereby general predevelopment and postdevelopment conceptual models of the hydrologic system in other basins may be synthesized. The end result of the project will be a better definition of the hydrologic parameters and a better understanding of the workings of the hydrologic system. The models can be used to study the effects of management alternatives and water-resources development on the system. (USGS)
Hydrologic filtering of fish life history strategies across the United States: implications for stream flow alteration

DOE PAGES

McManamay, Ryan A.; Frimpong, Emmanuel A.

2015-01-01

Lotic fish have developed life history strategies adapted to the natural variation in stream flow regimes. The natural timing, duration, and magnitude of flow events has contributed to the diversity, production, and composition of fish assemblages over time. Studies evaluating the role of hydrology in structuring fish assemblages have been more common at the local or regional scale with very few studies conducted at the continental scale. Furthermore, quantitative linkages between natural hydrologic patterns and fish assemblages are rarely used to make predictions of ecological consequences of hydrologic alterations. We ask two questions: (1) what is the relative role ofmore » hydrology in structuring fish assemblages at large scales? and (2) can relationships between fish assemblages and natural hydrology be utilized to predict fish assemblage responses to hydrologic disturbance? We developed models to relate fish life histories and reproductive strategies to landscape and hydrologic variables separately and then combined. Models were then used to predict the ecological consequences of altered hydrology due to dam regulation. Although hydrology plays a considerable role in structuring fish assemblages, the performance of models using only hydrologic variables was lower than that of models constructed using landscape variables. Isolating the relative importance of hydrology in structuring fish assemblages at the continental scale is difficult since hydrology is interrelated to many landscape factors. By applying models to dam-regulated hydrologic data, we observed some consistent predicted responses in fish life history strategies and modes of reproduction. In agreement with existing literature, equilibrium strategists are predicted to increase following dam regulation, whereas opportunistic and periodic species are predicted to decrease. In addition, dam regulation favors the selection of reproductive strategies with extended spawning seasons and preference for stable conditions.« less
Hydrologic filtering of fish life history strategies across the United States: implications for stream flow alteration

DOE Office of Scientific and Technical Information (OSTI.GOV)

McManamay, Ryan A.; Frimpong, Emmanuel A.

Lotic fish have developed life history strategies adapted to the natural variation in stream flow regimes. The natural timing, duration, and magnitude of flow events has contributed to the diversity, production, and composition of fish assemblages over time. Studies evaluating the role of hydrology in structuring fish assemblages have been more common at the local or regional scale with very few studies conducted at the continental scale. Furthermore, quantitative linkages between natural hydrologic patterns and fish assemblages are rarely used to make predictions of ecological consequences of hydrologic alterations. We ask two questions: (1) what is the relative role ofmore » hydrology in structuring fish assemblages at large scales? and (2) can relationships between fish assemblages and natural hydrology be utilized to predict fish assemblage responses to hydrologic disturbance? We developed models to relate fish life histories and reproductive strategies to landscape and hydrologic variables separately and then combined. Models were then used to predict the ecological consequences of altered hydrology due to dam regulation. Although hydrology plays a considerable role in structuring fish assemblages, the performance of models using only hydrologic variables was lower than that of models constructed using landscape variables. Isolating the relative importance of hydrology in structuring fish assemblages at the continental scale is difficult since hydrology is interrelated to many landscape factors. By applying models to dam-regulated hydrologic data, we observed some consistent predicted responses in fish life history strategies and modes of reproduction. In agreement with existing literature, equilibrium strategists are predicted to increase following dam regulation, whereas opportunistic and periodic species are predicted to decrease. In addition, dam regulation favors the selection of reproductive strategies with extended spawning seasons and preference for stable conditions.« less
Genetic Programming for Automatic Hydrological Modelling

NASA Astrophysics Data System (ADS)

Chadalawada, Jayashree; Babovic, Vladan

2017-04-01

One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development, Water Resources Research, 47(11).
Integrating wetland connectivity into models for watershed ...

EPA Pesticide Factsheets

Geographically isolated wetlands (GIW), or wetlands embedded in uplands, exist along a spatial and temporal hydrologic connectivity continuum to downstream waters. Via these connections and disconnections, GIWs provide numerous hydrological, biogeochemical, and biological functions linked to human health and watershed-scale ecosystem services. Often, a clear demonstration of these functions and the individual and cumulative effects of GIWs on downstream waters is required for their protection or restoration. Measurements alone are typically too resource intensive to do this. In this presentation, we discuss the use of various modeling approaches to quantify the hydrologic connectivity of GIWs and their associated watershed-scale cumulative effects. Our goal is to improve the science behind understanding the functions and connectivity of GIWs via models that are complemented with various types of novel data. We synthesize what is meant by GIW connectivity and its broad significance to science and decision-making. We further discuss case studies that provide insights to diverse modeling approaches, with varying levels of complexity, for how to estimate GIW connectivity and associated watershed-scale impacts to hydrology. We finally provide insights to the key opportunities and priorities for integrating GIW connectivity into the next generation of models. Geographically isolated wetlands (GIW), or wetlands embedded in uplands, exist along a spatial and temporal h
Evaluation of Potential Evapotranspiration from a Hydrologic Model on a National Scale

NASA Astrophysics Data System (ADS)

Hakala, Kirsti; Markstrom, Steven; Hay, Lauren

2015-04-01

The U.S. Geological Survey has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development and facilitate the application of simulations on the scale of the continental U.S. The NHM has a consistent geospatial fabric for modeling, consisting of over 100,000 hydrologic response units HRUs). Each HRU requires accurate parameter estimates, some of which are attained from automated calibration. However, improved calibration can be achieved by initially utilizing as many parameters as possible from national data sets. This presentation investigates the effectiveness of calculating potential evapotranspiration (PET) parameters based on mean monthly values from the NOAA PET Atlas. Additional PET products are then used to evaluate the PET parameters. Effectively utilizing existing national-scale data sets can simplify the effort in establishing a robust NHM.
An ecohydrologic model for a shallow groundwater urban environment.

PubMed

Arden, Sam; Ma, Xin Cissy; Brown, Mark

2014-01-01

The urban environment is a patchwork of natural and artificial surfaces that results in complex interactions with and impacts to natural hydrologic cycles. Evapotranspiration is a major hydrologic flow that is often altered through urbanization, although the mechanisms of change are sometimes difficult to tease out due to difficulty in effectively simulating soil-plant-atmosphere interactions. This paper introduces a simplified yet realistic model that is a combination of existing surface runoff and ecohydrology models designed to increase the quantitative understanding of complex urban hydrologic processes. Results demonstrate that the model is capable of simulating the long-term variability of major hydrologic fluxes as a function of impervious surface, temperature, water table elevation, canopy interception, soil characteristics, precipitation and complex mechanisms of plant water uptake. These understandings have potential implications for holistic urban water system management.
A question driven socio-hydrological modeling process

NASA Astrophysics Data System (ADS)

Garcia, M.; Portney, K.; Islam, S.

2016-01-01

Human and hydrological systems are coupled: human activity impacts the hydrological cycle and hydrological conditions can, but do not always, trigger changes in human systems. Traditional modeling approaches with no feedback between hydrological and human systems typically cannot offer insight into how different patterns of natural variability or human-induced changes may propagate through this coupled system. Modeling of coupled human-hydrological systems, also called socio-hydrological systems, recognizes the potential for humans to transform hydrological systems and for hydrological conditions to influence human behavior. However, this coupling introduces new challenges and existing literature does not offer clear guidance regarding model conceptualization. There are no universally accepted laws of human behavior as there are for the physical systems; furthermore, a shared understanding of important processes within the field is often used to develop hydrological models, but there is no such consensus on the relevant processes in socio-hydrological systems. Here we present a question driven process to address these challenges. Such an approach allows modeling structure, scope and detail to remain contingent on and adaptive to the question context. We demonstrate the utility of this process by revisiting a classic question in water resources engineering on reservoir operation rules: what is the impact of reservoir operation policy on the reliability of water supply for a growing city? Our example model couples hydrological and human systems by linking the rate of demand decreases to the past reliability to compare standard operating policy (SOP) with hedging policy (HP). The model shows that reservoir storage acts both as a buffer for variability and as a delay triggering oscillations around a sustainable level of demand. HP reduces the threshold for action thereby decreasing the delay and the oscillation effect. As a result, per capita demand decreases during periods of water stress are more frequent but less drastic and the additive effect of small adjustments decreases the tendency of the system to overshoot available supplies. This distinction between the two policies was not apparent using a traditional noncoupled model.
Modeling Pre- and Post- Wildfire Hydrologic Response to Vegetation Change in the Valles Caldera National Preserve, NM

NASA Astrophysics Data System (ADS)

Gregory, A. E.; Benedict, K. K.; Zhang, S.; Savickas, J.

2017-12-01

Large scale, high severity wildfires in forests have become increasingly prevalent in the western United States due to fire exclusion. Although past work has focused on the immediate consequences of wildfire (ie. runoff magnitude and debris flow), little has been done to understand the post wildfire hydrologic consequences of vegetation regrowth. Furthermore, vegetation is often characterized by static parameterizations within hydrological models. In order to understand the temporal relationship between hydrologic processes and revegetation, we modularized and partially automated the hydrologic modeling process to increase connectivity between remotely sensed data, the Virtual Watershed Platform (a data management resource, called the VWP), input meteorological data, and the Precipitation-Runoff Modeling System (PRMS). This process was used to run simulations in the Valles Caldera of NM, an area impacted by the 2011 Las Conchas Fire, in PRMS before and after the Las Conchas to evaluate hydrologic process changes. The modeling environment addressed some of the existing challenges faced by hydrological modelers. At present, modelers are somewhat limited in their ability to push the boundaries of hydrologic understanding. Specific issues faced by modelers include limited computational resources to model processes at large spatial and temporal scales, data storage capacity and accessibility from the modeling platform, computational and time contraints for experimental modeling, and the skills to integrate modeling software in ways that have not been explored. By taking an interdisciplinary approach, we were able to address some of these challenges by leveraging the skills of hydrologic, data, and computer scientists; and the technical capabilities provided by a combination of on-demand/high-performance computing, distributed data, and cloud services. The hydrologic modeling process was modularized to include options for distributing meteorological data, parameter space experimentation, data format transformation, looping, validation of models and containerization for enabling new analytic scenarios. The user interacts with the modules through Jupyter Notebooks which can be connected to an on-demand computing and HPC environment, and data services built as part of the VWP.
Facilitating hydrological data analysis workflows in R: the RHydro package

NASA Astrophysics Data System (ADS)

Buytaert, Wouter; Moulds, Simon; Skoien, Jon; Pebesma, Edzer; Reusser, Dominik

2015-04-01

The advent of new technologies such as web-services and big data analytics holds great promise for hydrological data analysis and simulation. Driven by the need for better water management tools, it allows for the construction of much more complex workflows, that integrate more and potentially more heterogeneous data sources with longer tool chains of algorithms and models. With the scientific challenge of designing the most adequate processing workflow comes the technical challenge of implementing the workflow with a minimal risk for errors. A wide variety of new workbench technologies and other data handling systems are being developed. At the same time, the functionality of available data processing languages such as R and Python is increasing at an accelerating pace. Because of the large diversity of scientific questions and simulation needs in hydrology, it is unlikely that one single optimal method for constructing hydrological data analysis workflows will emerge. Nevertheless, languages such as R and Python are quickly gaining popularity because they combine a wide array of functionality with high flexibility and versatility. The object-oriented nature of high-level data processing languages makes them particularly suited for the handling of complex and potentially large datasets. In this paper, we explore how handling and processing of hydrological data in R can be facilitated further by designing and implementing a set of relevant classes and methods in the experimental R package RHydro. We build upon existing efforts such as the sp and raster packages for spatial data and the spacetime package for spatiotemporal data to define classes for hydrological data (HydroST). In order to handle simulation data from hydrological models conveniently, a HM class is defined. Relevant methods are implemented to allow for an optimal integration of the HM class with existing model fitting and simulation functionality in R. Lastly, we discuss some of the design challenges of the RHydro package, including integration with big data technologies, web technologies, and emerging data models in hydrology.
ERM model analysis for adaptation to hydrological model errors

NASA Astrophysics Data System (ADS)

Baymani-Nezhad, M.; Han, D.

2018-05-01

Hydrological conditions are changed continuously and these phenomenons generate errors on flood forecasting models and will lead to get unrealistic results. Therefore, to overcome these difficulties, a concept called model updating is proposed in hydrological studies. Real-time model updating is one of the challenging processes in hydrological sciences and has not been entirely solved due to lack of knowledge about the future state of the catchment under study. Basically, in terms of flood forecasting process, errors propagated from the rainfall-runoff model are enumerated as the main source of uncertainty in the forecasting model. Hence, to dominate the exciting errors, several methods have been proposed by researchers to update the rainfall-runoff models such as parameter updating, model state updating, and correction on input data. The current study focuses on investigations about the ability of rainfall-runoff model parameters to cope with three types of existing errors, timing, shape and volume as the common errors in hydrological modelling. The new lumped model, the ERM model, has been selected for this study to evaluate its parameters for its use in model updating to cope with the stated errors. Investigation about ten events proves that the ERM model parameters can be updated to cope with the errors without the need to recalibrate the model.
Reviewing innovative Earth observation solutions for filling science-policy gaps in hydrology

NASA Astrophysics Data System (ADS)

Lehmann, Anthony; Giuliani, Gregory; Ray, Nicolas; Rahman, Kazi; Abbaspour, Karim C.; Nativi, Stefano; Craglia, Massimo; Cripe, Douglas; Quevauviller, Philippe; Beniston, Martin

2014-10-01

Improved data sharing is needed for hydrological modeling and water management that require better integration of data, information and models. Technological advances in Earth observation and Web technologies have allowed the development of Spatial Data Infrastructures (SDIs) for improved data sharing at various scales. International initiatives catalyze data sharing by promoting interoperability standards to maximize the use of data and by supporting easy access to and utilization of geospatial data. A series of recent European projects are contributing to the promotion of innovative Earth observation solutions and the uptake of scientific outcomes in policy. Several success stories involving different hydrologists' communities can be reported around the World. Gaps still exist in hydrological, agricultural, meteorological and climatological data access because of various issues. While many sources of data exists at all scales it remains difficult and time-consuming to assemble hydrological information for most projects. Furthermore, data and sharing formats remain very heterogeneous. Improvements require implementing/endorsing some commonly agreed standards and documenting data with adequate metadata. The brokering approach allows binding heterogeneous resources published by different data providers and adapting them to tools and interfaces commonly used by consumers of these resources. The challenge is to provide decision-makers with reliable information, based on integrated data and tools derived from both Earth observations and scientific models. Successful SDIs rely therefore on various aspects: a shared vision between all participants, necessity to solve a common problem, adequate data policies, incentives, and sufficient resources. New data streams from remote sensing or crowd sourcing are also producing valuable information to improve our understanding of the water cycle, while field sensors are developing rapidly and becoming less costly. More recent data standards are enhancing interoperability between hydrology and other scientific disciplines, while solutions exist to communicate uncertainty of data and models, which is an essential pre-requisite for decision-making. Distributed computing infrastructures can handle complex and large hydrological data and models, while Web Processing Services bring the flexibility to develop and execute simple to complex workflows over the Internet. The need for capacity building at human, infrastructure and institutional levels is also a major driver for reinforcing the commitment to SDI concepts.
[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

PubMed

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.
Advancing Data Assimilation in Operational Hydrologic Forecasting: Progresses, Challenges, and Emerging Opportunities

NASA Technical Reports Server (NTRS)

Liu, Yuqiong; Weerts, A.; Clark, M.; Hendricks Franssen, H.-J; Kumar, S.; Moradkhani, H.; Seo, D.-J.; Schwanenberg, D.; Smith, P.; van Dijk, A. I. J. M.;

2012-01-01

Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, the Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical aspects in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers, DA developers, and operational forecasters.

Alternative spatial configurations to reflect landscape structure in a hydrological model: SUMMA applications to the Reynolds Creek Watershed and the Columbia River Basin

NASA Astrophysics Data System (ADS)

Nijssen, Bart; Clark, Martyn; Mizukami, Naoki; Chegwidden, Oriana

2016-04-01

Most existing hydrological models use a fixed representation of landscape structure. For example, high-resolution, spatially-distributed models may use grid cells that exchange moisture through the saturated subsurface or may divide the landscape into hydrologic response units that only exchange moisture through surface channels. Alternatively, many regional models represent the landscape through coarse elements that do not model any moisture exchange between these model elements. These spatial organizations are often represented at a low-level in the model code and its data structures, which makes it difficult to evaluate different landscape representations using the same hydrological model. Instead, such experimentation requires the use of multiple, different hydrological models, which in turn complicates the analysis, because differences in model outcomes are no longer constrained by differing spatial representations. This inflexibility in the representation of landscape structure also limits a model's capability for scaling local processes to regional outcomes. In this study, we used the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to evaluate different model spatial configurations to represent landscape structure and to evaluate scaling behavior. SUMMA can represent the moisture exchange between arbitrarily shaped landscape elements in a number of different ways, while using the same model parameterizations for vertical fluxes. This allows us to isolate the effects of changes in landscape representations on modeled hydrological fluxes and states. We examine the effects of spatial configuration in Reynolds Creek, Idaho, USA, which is a research watershed with gaged areas from 1-20 km2. We then use the same modeling system to evaluate scaling behavior in simulated hydrological fluxes in the Columbia River Basin, Pacific Northwest, USA. This basin drains more than 500,000 km2 and includes the Reynolds Creek Watershed.

Lacustrine flow (divers, side scan sonar, hydrogeology, water penetrating radar) used to understand the location of a drowned person

NASA Astrophysics Data System (ADS)

Ruffell, Alastair

2014-05-01

An unusual application of hydrological understanding to a police search is described. The lacustrine search for a missing person provided reports of bottom-water currents in the lake and contradictory indications from cadaver dogs. A hydrological model of the area was developed using pre-existing information from side scan sonar, a desktop hydrogeological study and deployment of water penetrating radar (WPR). These provided a hydrological theory for the initial search involving subaqueous groundwater flow, focused on an area of bedrock surrounded by sediment, on the lake floor. The work shows the value a hydrological explanation has to a police search operation (equally to search and rescue). With hindsight, the desktop study should have preceded the search, allowing better understanding of water conditions. The ultimate reason for lacustrine flow in this location is still not proven, but the hydrological model explained the problems encountered in the initial search.
New Perspectives of "old" Data Sources: the Dataset of Long-Term Research Watersheds in the Former Soviet Union for the Task of Hydrological Models Development, Verification and Comparison

NASA Astrophysics Data System (ADS)

Lebedeva, L.; Semenova, O.

2013-12-01

Lack of detailed process-oriented observational data is often claimed as one of the major obstacle for further advance of hydrological process understanding and development of deterministic models that do not rely on calibration. New sources of hydrological information (satellites, radars etc.) have the perspectives for the future but can not completely replace conventional and experimental observations at the moment. Long-term data-rich research catchments remain valuable if not the only source of information for development, verification, regionalization and comparison of different hydrological and environmental models. There existed the set of more than 20 such basins that were operated according to single observational program from the 1930-1950th to 1990th in the former Soviet Union. Research basins, so called water-balance stations, covered all main climatic and landscape zones such as taiga, forest-steppe, steppe, desert, mountains and permafrost regions. Each station conducted broad range of standard, special and experimental hydrometeorological field studies including spatially distributed meteorological observations, soil and snow variable states, measurements of the groundwater levels, hydrochemistry, evapotranspiration, discharges in several, often nested, slope- and small-scale watersheds, etc. The data were accompanied by the descriptions of observational techniques and landscapes allowing linking natural conditions with dominant hydrological processes. Each station is representative for larger area and the results of local studies could be transferred to other basins in similar conditions. Till recently the data existed only in hard copies in Russian language therefore they are not enough explored yet. We are currently digitizing main part of the observational and supportive materials and make it available for any scientific purpose via website http://hydrograph-model.ru/. We propose to hydrological community to use the data for comprehensive intercomparison studies of our models and their modules to reject inadequate algorithms and advance our process understanding and modeling efforts in different environments.
Hydrologic Design in the Anthropocene

NASA Astrophysics Data System (ADS)

Vogel, R. M.; Farmer, W. H.; Read, L.

2014-12-01

In an era dubbed the Anthropocene, the natural world is being transformed by a myriad of human influences. As anthropogenic impacts permeate hydrologic systems, hydrologists are challenged to fully account for such changes and develop new methods of hydrologic design. Deterministic watershed models (DWM), which can account for the impacts of changes in land use, climate and infrastructure, are becoming increasing popular for the design of flood and/or drought protection measures. As with all models that are calibrated to existing datasets, DWMs are subject to model error or uncertainty. In practice, the model error component of DWM predictions is typically ignored yet DWM simulations which ignore model error produce model output which cannot reproduce the statistical properties of the observations they are intended to replicate. In the context of hydrologic design, we demonstrate how ignoring model error can lead to systematic downward bias in flood quantiles, upward bias in drought quantiles and upward bias in water supply yields. By reincorporating model error, we document how DWM models can be used to generate results that mimic actual observations and preserve their statistical behavior. In addition to use of DWM for improved predictions in a changing world, improved communication of the risk and reliability is also needed. Traditional statements of risk and reliability in hydrologic design have been characterized by return periods, but such statements often assume that the annual probability of experiencing a design event remains constant throughout the project horizon. We document the general impact of nonstationarity on the average return period and reliability in the context of hydrologic design. Our analyses reveal that return periods do not provide meaningful expressions of the likelihood of future hydrologic events. Instead, knowledge of system reliability over future planning horizons can more effectively prepare society and communicate the likelihood of future hydrologic events of interest.
Decadal predictability of river discharge with climate oscillations over the 20th and early 21st century

NASA Astrophysics Data System (ADS)

Wanders, Niko; Wada, Yoshihide

2015-12-01

Long-term hydrological forecasts are important to increase our resilience and preparedness to extreme hydrological events. The skill in these forecasts is still limited due to large uncertainties inherent in hydrological models and poor predictability of long-term meteorological conditions. Here we show that strong (lagged) correlations exist between four different major climate oscillation modes and modeled and observed discharge anomalies over a 100 year period. The strongest correlations are found between the El Niño-Southern Oscillation signal and river discharge anomalies all year round, while North Atlantic Oscillation and Antarctic Oscillation time series are strongly correlated with winter discharge anomalies. The correlation signal is significant for periods up to 5 years for some regions, indicating a high added value of this information for long-term hydrological forecasting. The results suggest that long-term hydrological forecasting could be significantly improved by including the climate oscillation signals and thus improve our preparedness for hydrological extremes in the near future.
An overview of current applications, challenges, and future trends in distributed process-based models in hydrology

USGS Publications Warehouse

Fatichi, Simone; Vivoni, Enrique R.; Odgen, Fred L; Ivanov, Valeriy Y; Mirus, Benjamin B.; Gochis, David; Downer, Charles W; Camporese, Matteo; Davison, Jason H; Ebel, Brian A.; Jones, Norm; Kim, Jongho; Mascaro, Giuseppe; Niswonger, Richard G.; Restrepo, Pedro; Rigon, Riccardo; Shen, Chaopeng; Sulis, Mauro; Tarboton, David

2016-01-01

Process-based hydrological models have a long history dating back to the 1960s. Criticized by some as over-parameterized, overly complex, and difficult to use, a more nuanced view is that these tools are necessary in many situations and, in a certain class of problems, they are the most appropriate type of hydrological model. This is especially the case in situations where knowledge of flow paths or distributed state variables and/or preservation of physical constraints is important. Examples of this include: spatiotemporal variability of soil moisture, groundwater flow and runoff generation, sediment and contaminant transport, or when feedbacks among various Earth’s system processes or understanding the impacts of climate non-stationarity are of primary concern. These are situations where process-based models excel and other models are unverifiable. This article presents this pragmatic view in the context of existing literature to justify the approach where applicable and necessary. We review how improvements in data availability, computational resources and algorithms have made detailed hydrological simulations a reality. Avenues for the future of process-based hydrological models are presented suggesting their use as virtual laboratories, for design purposes, and with a powerful treatment of uncertainty.
Florida Bay salinity and Everglades wetlands hydrology circa 1900 CE: A compilation of paleoecology-based statistical modeling analyses

USGS Publications Warehouse

Marshall, F.E.; Wingard, G.L.

2012-01-01

The upgraded method of coupled paleosalinity and hydrologic models was applied to the analysis of the circa-1900 CE segments of five estuarine sediment cores collected in Florida Bay. Comparisons of the observed mean stage (water level) data to the paleoecology-based model's averaged output show that the estimated stage in the Everglades wetlands was 0.3 to 1.6 feet higher at different locations. Observed mean flow data compared to the paleoecology-based model output show an estimated flow into Shark River Slough at Tamiami Trail of 401 to 2,539 cubic feet per second (cfs) higher than existing flows, and at Taylor Slough Bridge an estimated flow of 48 to 218 cfs above existing flows. For salinity in Florida Bay, the difference between paleoecology-based and observed mean salinity varies across the bay, from an aggregated average salinity of 14.7 less than existing in the northeastern basin to 1.0 less than existing in the western basin near the transition into the Gulf of Mexico. When the salinity differences are compared by region, the difference between paleoecology-based conditions and existing conditions are spatially consistent.
Coupling high-resolution hydraulic and hydrologic models for flash flood forecasting and inundation mapping in urban areas - A case study for the City of Fort Worth

NASA Astrophysics Data System (ADS)

Nazari, B.; Seo, D.; Cannon, A.

2013-12-01

With many diverse features such as channels, pipes, culverts, buildings, etc., hydraulic modeling in urban areas for inundation mapping poses significant challenges. Identifying the practical extent of the details to be modeled in order to obtain sufficiently accurate results in a timely manner for effective emergency management is one of them. In this study we assess the tradeoffs between model complexity vs. information content for decision making in applying high-resolution hydrologic and hydraulic models for real-time flash flood forecasting and inundation mapping in urban areas. In a large urban area such as the Dallas-Fort Worth Metroplex (DFW), there exists very large spatial variability in imperviousness depending on the area of interest. As such, one may expect significant sensitivity of hydraulic model results to the resolution and accuracy of hydrologic models. In this work, we present the initial results from coupling of high-resolution hydrologic and hydraulic models for two 'hot spots' within the City of Fort Worth for real-time inundation mapping.
visCOS: An R-package to evaluate model performance of hydrological models

NASA Astrophysics Data System (ADS)

Klotz, Daniel; Herrnegger, Mathew; Wesemann, Johannes; Schulz, Karsten

2016-04-01

The evaluation of model performance is a central part of (hydrological) modelling. Much attention has been given to the development of evaluation criteria and diagnostic frameworks. (Klemeš, 1986; Gupta et al., 2008; among many others). Nevertheless, many applications exist for which objective functions do not yet provide satisfying summaries. Thus, the necessity to visualize results arises in order to explore a wider range of model capacities, be it strengths or deficiencies. Visualizations are usually devised for specific projects and these efforts are often not distributed to a broader community (e.g. via open source software packages). Hence, the opportunity to explicitly discuss a state-of-the-art presentation technique is often missed. We therefore present a comprehensive R-package for evaluating model performance by visualizing and exploring different aspects of hydrological time-series. The presented package comprises a set of useful plots and visualization methods, which complement existing packages, such as hydroGOF (Zambrano-Bigiarini et al., 2012). It is derived from practical applications of the hydrological models COSERO and COSEROreg (Kling et al., 2014). visCOS, providing an interface in R, represents an easy-to-use software package for visualizing and assessing model performance and can be implemented in the process of model calibration or model development. The package provides functions to load hydrological data into R, clean the data, process, visualize, explore and finally save the results in a consistent way. Together with an interactive zoom function of the time series, an online calculation of the objective functions for variable time-windows is included. Common hydrological objective functions, such as the Nash-Sutcliffe Efficiency and the Kling-Gupta Efficiency, can also be evaluated and visualized in different ways for defined sub-periods like hydrological years or seasonal sections. Many hydrologists use long-term water-balances as a pivotal tool in model evaluation. They allow inferences about different systematic model-shortcomings and are an efficient way for communicating these in practice (Schulz et al., 2015). The evaluation and construction of such water balances is implemented with the presented package. During the (manual) calibration of a model or in the scope of model development, many model runs and iterations are necessary. Thus, users are often interested in comparing different model results in a visual way in order to learn about the model and to analyse parameter-changes on the output. A method to illuminate these differences and the evolution of changes is also included. References: • Gupta, H.V.; Wagener, T.; Liu, Y. (2008): Reconciling theory with observations: elements of a diagnostic approach to model evaluation, Hydrol. Process. 22, doi: 10.1002/hyp.6989. • Klemeš, V. (1986): Operational testing of hydrological simulation models, Hydrolog. Sci. J., doi: 10.1080/02626668609491024. • Kling, H.; Stanzel, P.; Fuchs, M.; and Nachtnebel, H. P. (2014): Performance of the COSERO precipitation-runoff model under non-stationary conditions in basins with different climates, Hydrolog. Sci. J., doi: 10.1080/02626667.2014.959956. • Schulz, K., Herrnegger, M., Wesemann, J., Klotz, D. Senoner, T. (2015): Kalibrierung COSERO - Mur für Pro Vis, Verbund Trading GmbH (Abteilung STG), final report, Institute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Applied Life Sciences, Vienna, Austria, 217pp. • Zambrano-Bigiarini, M; Bellin, A. (2010): Comparing Goodness-of-fit Measures for Calibration of Models Focused on Extreme Events. European Geosciences Union (EGU), Geophysical Research Abstracts 14, EGU2012-11549-1.
Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

NASA Astrophysics Data System (ADS)

Qi, W.; Zhang, C.; Fu, G.; Sweetapple, C.; Zhou, H.

2016-02-01

The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash-Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A better precipitation product does not guarantee a better discharge simulation because of interactions. It is also found that a good discharge simulation depends on a good coalition of a hydrological model and a precipitation product, suggesting that, although the satellite-based precipitation products are not as accurate as the gauge-based products, they could have better performance in discharge simulations when appropriately combined with hydrological models. This information is revealed for the first time and very beneficial for precipitation product applications.
[Research progress on hydrological scaling].

PubMed

Liu, Jianmei; Pei, Tiefan

2003-12-01

With the development of hydrology and the extending effect of mankind on environment, scale issue has become a great challenge to many hydrologists due to the stochasticism and complexity of hydrological phenomena and natural catchments. More and more concern has been given to the scaling issues to gain a large-scale (or small-scale) hydrological characteristic from a certain known catchments, but hasn't been solved successfully. The first part of this paper introduced some concepts about hydrological scale, scale issue and scaling. The key problem is the spatial heterogeneity of catchments and the temporal and spatial variability of hydrological fluxes. Three approaches to scale were put forward in the third part, which were distributed modeling, fractal theory and statistical self similarity analyses. Existing problems and future research directions were proposed in the last part.
A micro-hydrology computation ordering algorithm

NASA Astrophysics Data System (ADS)

Croley, Thomas E.

1980-11-01

Discrete-distributed-parameter models are essential for watershed modelling where practical consideration of spatial variations in watershed properties and inputs is desired. Such modelling is necessary for analysis of detailed hydrologic impacts from management strategies and land-use effects. Trade-offs between model validity and model complexity exist in resolution of the watershed. Once these are determined, the watershed is then broken into sub-areas which each have essentially spatially-uniform properties. Lumped-parameter (micro-hydrology) models are applied to these sub-areas and their outputs are combined through the use of a computation ordering technique, as illustrated by many discrete-distributed-parameter hydrology models. Manual ordering of these computations requires fore-thought, and is tedious, error prone, sometimes storage intensive and least adaptable to changes in watershed resolution. A programmable algorithm for ordering micro-hydrology computations is presented that enables automatic ordering of computations within the computer via an easily understood and easily implemented "node" definition, numbering and coding scheme. This scheme and the algorithm are detailed in logic flow-charts and an example application is presented. Extensions and modifications of the algorithm are easily made for complex geometries or differing microhydrology models. The algorithm is shown to be superior to manual ordering techniques and has potential use in high-resolution studies.
Holistic uncertainty analysis in river basin modeling for climate vulnerability assessment

NASA Astrophysics Data System (ADS)

Taner, M. U.; Wi, S.; Brown, C.

2017-12-01

The challenges posed by uncertain future climate are a prominent concern for water resources managers. A number of frameworks exist for assessing the impacts of climate-related uncertainty, including internal climate variability and anthropogenic climate change, such as scenario-based approaches and vulnerability-based approaches. While in many cases climate uncertainty may be dominant, other factors such as future evolution of the river basin, hydrologic response and reservoir operations are potentially significant sources of uncertainty. While uncertainty associated with modeling hydrologic response has received attention, very little attention has focused on the range of uncertainty and possible effects of the water resources infrastructure and management. This work presents a holistic framework that allows analysis of climate, hydrologic and water management uncertainty in water resources systems analysis with the aid of a water system model designed to integrate component models for hydrology processes and water management activities. The uncertainties explored include those associated with climate variability and change, hydrologic model parameters, and water system operation rules. A Bayesian framework is used to quantify and model the uncertainties at each modeling steps in integrated fashion, including prior and the likelihood information about model parameters. The framework is demonstrated in a case study for the St. Croix Basin located at border of United States and Canada.
A balanced water layer concept for subglacial hydrology in large scale ice sheet models

NASA Astrophysics Data System (ADS)

Goeller, S.; Thoma, M.; Grosfeld, K.; Miller, H.

2012-12-01

There is currently no doubt about the existence of a wide-spread hydrological network under the Antarctic ice sheet, which lubricates the ice base and thus leads to increased ice velocities. Consequently, ice models should incorporate basal hydrology to obtain meaningful results for future ice dynamics and their contribution to global sea level rise. Here, we introduce the balanced water layer concept, covering two prominent subglacial hydrological features for ice sheet modeling on a continental scale: the evolution of subglacial lakes and balance water fluxes. We couple it to the thermomechanical ice-flow model RIMBAY and apply it to a synthetic model domain inspired by the Gamburtsev Mountains, Antarctica. In our experiments we demonstrate the dynamic generation of subglacial lakes and their impact on the velocity field of the overlaying ice sheet, resulting in a negative ice mass balance. Furthermore, we introduce an elementary parametrization of the water flux-basal sliding coupling and reveal the predominance of the ice loss through the resulting ice streams against the stabilizing influence of less hydrologically active areas. We point out, that established balance flux schemes quantify these effects only partially as their ability to store subglacial water is lacking.
Internal Catchment Process Simulation in a Snow-Dominated Basin: Performance Evaluation with Spatiotemporally Variable Runoff Generation and Groundwater Dynamics

NASA Astrophysics Data System (ADS)

Kuras, P. K.; Weiler, M.; Alila, Y.; Spittlehouse, D.; Winkler, R.

2006-12-01

Hydrologic models have been increasingly used in forest hydrology to overcome the limitations of paired watershed experiments, where vegetative recovery and natural variability obscure the inferences and conclusions that can be drawn from such studies. Models, however, are also plagued by uncertainty stemming from a limited understanding of hydrological processes in forested catchments and parameter equifinality is a common concern. This has created the necessity to improve our understanding of how hydrological systems work, through the development of hydrological measures, analyses and models that address the question: are we getting the right answers for the right reasons? Hence, physically-based, spatially-distributed hydrologic models should be validated with high-quality experimental data describing multiple concurrent internal catchment processes under a range of hydrologic regimes. The distributed hydrology soil vegetation model (DHSVM) frequently used in forest management applications is an example of a process-based model used to address the aforementioned circumstances, and this study takes a novel approach at collectively examining the ability of a pre-calibrated model application to realistically simulate outlet flows along with the spatial-temporal variation of internal catchment processes including: continuous groundwater dynamics at 9 locations, stream and road network flow at 67 locations for six individual days throughout the freshet, and pre-melt season snow distribution. Model efficiency was improved over prior evaluations due to continuous efforts in improving the quality of meteorological data in the watershed. Road and stream network flows were very well simulated for a range of hydrological conditions, and the spatial distribution of the pre-melt season snowpack was in general agreement with observed values. The model was effective in simulating the spatial variability of subsurface flow generation, except at locations where strong stream-groundwater interactions existed, as the model is not capable of simulating such processes and subsurface flows always drain to the stream network. The model has proven overall to be quite capable in realistically simulating internal catchment processes in the watershed, which creates more confidence in future model applications exploring the effects of various forest management scenarios on the watershed's hydrological processes.
Correcting Inadequate Model Snow Process Descriptions Dramatically Improves Mountain Hydrology Simulations

NASA Astrophysics Data System (ADS)

Pomeroy, J. W.; Fang, X.

2014-12-01

The vast effort in hydrology devoted to parameter calibration as a means to improve model performance assumes that the models concerned are not fundamentally wrong. By focussing on finding optimal parameter sets and ascribing poor model performance to parameter or data uncertainty, these efforts may fail to consider the need to improve models with more intelligent descriptions of hydrological processes. To test this hypothesis, a flexible physically based hydrological model including a full suite of snow hydrology processes as well as warm season, hillslope and groundwater hydrology was applied to Marmot Creek Research Basin, Canadian Rocky Mountains where excellent driving meteorology and basin biophysical descriptions exist. Model parameters were set from values found in the basin or from similar environments; no parameters were calibrated. The model was tested against snow surveys and streamflow observations. The model used algorithms that describe snow redistribution, sublimation and forest canopy effects on snowmelt and evaporative processes that are rarely implemented in hydrological models. To investigate the contribution of these processes to model predictive capability, the model was "falsified" by deleting parameterisations for forest canopy snow mass and energy, blowing snow, intercepted rain evaporation, and sublimation. Model falsification by ignoring forest canopy processes contributed to a large increase in SWE errors for forested portions of the research basin with RMSE increasing from 19 to 55 mm and mean bias (MB) increasing from 0.004 to 0.62. In the alpine tundra portion, removing blowing processes resulted in an increase in model SWE MB from 0.04 to 2.55 on north-facing slopes and -0.006 to -0.48 on south-facing slopes. Eliminating these algorithms degraded streamflow prediction with the Nash Sutcliffe efficiency dropping from 0.58 to 0.22 and MB increasing from 0.01 to 0.09. These results show dramatic model improvements by including snow redistribution and melt processes associated with wind transport and forest canopies. As most hydrological models do not currently include these processes, it is suggested that modellers first improve the realism of model structures before trying to optimise what are inherently inadequate simulations of hydrology.
A Community Publication and Dissemination System for Hydrology Education Materials

NASA Astrophysics Data System (ADS)

Ruddell, B. L.

2015-12-01

Hosted by CUAHSI and the Science Education Resource Center (SERC), federated by the National Science Digital Library (NSDL), and allied with the Water Data Center (WDC), Hydrologic Information System (HIS), and HydroShare projects, a simple cyberinfrastructure has been launched for the publication and dissemination of data and model driven university hydrology education materials. This lightweight system's metadata describes learning content as a data-driven module with defined data inputs and outputs. This structure allows a user to mix and match modules to create sequences of content that teach both hydrology and computer learning outcomes. Importantly, this modular infrastructure allows an instructor to substitute a module based on updated computer methods for one based on outdated computer methods, hopefully solving the problem of rapid obsolescence that has hampered previous community efforts. The prototype system is now available from CUAHSI and SERC, with some example content. The system is designed to catalog, link to, make visible, and make accessible the existing and future contributions of the community; this system does not create content. Submissions from hydrology educators are eagerly solicited, especially for existing content.
On the information content of hydrological signatures and their relationship to catchment attributes

NASA Astrophysics Data System (ADS)

Addor, Nans; Clark, Martyn P.; Prieto, Cristina; Newman, Andrew J.; Mizukami, Naoki; Nearing, Grey; Le Vine, Nataliya

2017-04-01

Hydrological signatures, which are indices characterizing hydrologic behavior, are increasingly used for the evaluation, calibration and selection of hydrological models. Their key advantage is to provide more direct insights into specific hydrological processes than aggregated metrics (e.g., the Nash-Sutcliffe efficiency). A plethora of signatures now exists, which enable characterizing a variety of hydrograph features, but also makes the selection of signatures for new studies challenging. Here we propose that the selection of signatures should be based on their information content, which we estimated using several approaches, all leading to similar conclusions. To explore the relationship between hydrological signatures and the landscape, we extended a previously published data set of hydrometeorological time series for 671 catchments in the contiguous United States, by characterizing the climatic conditions, topography, soil, vegetation and stream network of each catchment. This new catchment attributes data set will soon be in open access, and we are looking forward to introducing it to the community. We used this data set in a data-learning algorithm (random forests) to explore whether hydrological signatures could be inferred from catchment attributes alone. We find that some signatures can be predicted remarkably well by random forests and, interestingly, the same signatures are well captured when simulating discharge using a conceptual hydrological model. We discuss what this result reveals about our understanding of hydrological processes shaping hydrological signatures. We also identify which catchment attributes exert the strongest control on catchment behavior, in particular during extreme hydrological events. Overall, climatic attributes have the most significant influence, and strongly condition how well hydrological signatures can be predicted by random forests and simulated by the hydrological model. In contrast, soil characteristics at the catchment scale are not found to be significant predictors by random forests, which raises questions on how to best use soil data for hydrological modeling, for instance for parameter estimation. We finally demonstrate that signatures with high spatial variability are poorly captured by random forests and model simulations, which makes their regionalization delicate. We conclude with a ranking of signatures based on their information content, and propose that the signatures with high information content are best suited for model calibration, model selection and understanding hydrologic similarity.
Using the cloud to speed-up calibration of watershed-scale hydrologic models (Invited)

NASA Astrophysics Data System (ADS)

Goodall, J. L.; Ercan, M. B.; Castronova, A. M.; Humphrey, M.; Beekwilder, N.; Steele, J.; Kim, I.

2013-12-01

This research focuses on using the cloud to address computational challenges associated with hydrologic modeling. One example is calibration of a watershed-scale hydrologic model, which can take days of execution time on typical computers. While parallel algorithms for model calibration exist and some researchers have used multi-core computers or clusters to run these algorithms, these solutions do not fully address the challenge because (i) calibration can still be too time consuming even on multicore personal computers and (ii) few in the community have the time and expertise needed to manage a compute cluster. Given this, another option for addressing this challenge that we are exploring through this work is the use of the cloud for speeding-up calibration of watershed-scale hydrologic models. The cloud used in this capacity provides a means for renting a specific number and type of machines for only the time needed to perform a calibration model run. The cloud allows one to precisely balance the duration of the calibration with the financial costs so that, if the budget allows, the calibration can be performed more quickly by renting more machines. Focusing specifically on the SWAT hydrologic model and a parallel version of the DDS calibration algorithm, we show significant speed-up time across a range of watershed sizes using up to 256 cores to perform a model calibration. The tool provides a simple web-based user interface and the ability to monitor the calibration job submission process during the calibration process. Finally this talk concludes with initial work to leverage the cloud for other tasks associated with hydrologic modeling including tasks related to preparing inputs for constructing place-based hydrologic models.
On modeling complex interplay in small-scale self-organized socio-hydrological systems

NASA Astrophysics Data System (ADS)

Muneepeerakul, Rachata

2017-04-01

Successful and sustainable socio-hydrological systems, as in any coupled natural human-systems, require effective governance, which depends on the existence of proper infrastructure (both hard and soft). Recent work has addressed systems in which resource users and the organization responsible for maintaining the infrastructure are separate entities. However, many socio-hydrological systems, especially in developing countries, are small and without such formal division of labor; rather, such division of labor typically arises from self-organization within the population. In this work, we modify and mathematically operationalize a conceptual framework by developing a system of differential equations that capture the strategic behavior within such a self-organized population, its interplay with infrastructure characteristics and hydrological dynamics, and feedbacks between these elements. The model yields a number of insightful conditions related to long-term sustainability and collapse of the socio-hydrological system in the form of relationships between biophysical and social factors. These relationships encapsulate nonlinear interactions of these factors. The modeling framework is grounded in a solid conceptual foundation upon which additional modifications and realism can be built for potential reconciliation between socio-hydrology with other related fields and further applications.
An approach to predict water quality in data-sparse catchments using hydrological catchment similarity

NASA Astrophysics Data System (ADS)

Pohle, Ina; Glendell, Miriam; Stutter, Marc I.; Helliwell, Rachel C.

2017-04-01

An understanding of catchment response to climate and land use change at a regional scale is necessary for the assessment of mitigation and adaptation options addressing diffuse nutrient pollution. It is well documented that the physicochemical properties of a river ecosystem respond to change in a non-linear fashion. This is particularly important when threshold water concentrations, relevant to national and EU legislation, are exceeded. Large scale (regional) model assessments required for regulatory purposes must represent the key processes and mechanisms that are more readily understood in catchments with water quantity and water quality data monitored at high spatial and temporal resolution. While daily discharge data are available for most catchments in Scotland, nitrate and phosphorus are mostly available on a monthly basis only, as typified by regulatory monitoring. However, high resolution (hourly to daily) water quantity and water quality data exist for a limited number of research catchments. To successfully implement adaptation measures across Scotland, an upscaling from data-rich to data-sparse catchments is required. In addition, the widespread availability of spatial datasets affecting hydrological and biogeochemical responses (e.g. soils, topography/geomorphology, land use, vegetation etc.) provide an opportunity to transfer predictions between data-rich and data-sparse areas by linking processes and responses to catchment attributes. Here, we develop a framework of catchment typologies as a prerequisite for transferring information from data-rich to data-sparse catchments by focusing on how hydrological catchment similarity can be used as an indicator of grouped behaviours in water quality response. As indicators of hydrological catchment similarity we use flow indices derived from observed discharge data across Scotland as well as hydrological model parameters. For the latter, we calibrated the lumped rainfall-runoff model TUWModel using multiple objective functions. The relationships between indicators of hydrological catchment similarity, physical catchment characteristics and nitrate and phosphorus concentrations in rivers are then investigated using multivariate statistics. This understanding of the relationship between catchment characteristics, hydrological processes and water quality will allow us to implement more efficient regulatory water quality monitoring strategies, to improve existing water quality models and to model mitigation and adaptation scenarios to global change in data-sparse catchments.

Catchment Integration of Sensor Array Observations to Understand Hydrologic Connectivity

NASA Astrophysics Data System (ADS)

Redfern, S.; Livneh, B.; Molotch, N. P.; Suding, K.; Neff, J. C.; Hinckley, E. L. S.

2017-12-01

Hydrologic connectivity and the land surface water balance are likely to be impacted by climate change in the coming years. Although recent work has started to demonstrate that climate modulates connectivity, we still lack knowledge of how local ecology will respond to environmental and atmospheric changes and subsequently interact with connectivity. The overarching goal of this research is to address and forecast how climate change will affect hydrologic connectivity in an alpine environment, through the use of near-surface observations (temperature, humidity, soil moisture, snow depth) from a new 16-sensor array (plus 5 precipitation gauges), together with a distributed hydrologic model, over a small catchment on Colorado's Niwot Ridge (above 3000m). Model simulations will be constrained to distributed sensor measurements taken in the study area and calibrated with streamflow. Periods of wetting and dry-down will be analyzed to identify signatures of connectivity across the landscape, its seasonal signals and its sensitivity to land cover. Further work will aim to develop future hydrologic projections, compare model output with related observations, conduct multi-physics experiments, and continue to expand the existing sensor network.
A Fresh Start for Flood Estimation in Ungauged Basins

NASA Astrophysics Data System (ADS)

Woods, R. A.

2017-12-01

The two standard methods for flood estimation in ungauged basins, regression-based statistical models and rainfall-runoff models using a design rainfall event, have survived relatively unchanged as the methods of choice for more than 40 years. Their technical implementation has developed greatly, but the models' representation of hydrological processes has not, despite a large volume of hydrological research. I suggest it is time to introduce more hydrology into flood estimation. The reliability of the current methods can be unsatisfactory. For example, despite the UK's relatively straightforward hydrology, regression estimates of the index flood are uncertain by +/- a factor of two (for a 95% confidence interval), an impractically large uncertainty for design. The standard error of rainfall-runoff model estimates is not usually known, but available assessments indicate poorer reliability than statistical methods. There is a practical need for improved reliability in flood estimation. Two promising candidates to supersede the existing methods are (i) continuous simulation by rainfall-runoff modelling and (ii) event-based derived distribution methods. The main challenge with continuous simulation methods in ungauged basins is to specify the model structure and parameter values, when calibration data are not available. This has been an active area of research for more than a decade, and this activity is likely to continue. The major challenges for the derived distribution method in ungauged catchments include not only the correct specification of model structure and parameter values, but also antecedent conditions (e.g. seasonal soil water balance). However, a much smaller community of researchers are active in developing or applying the derived distribution approach, and as a result slower progress is being made. A change in needed: surely we have learned enough about hydrology in the last 40 years that we can make a practical hydrological advance on our methods for flood estimation! A shift to new methods for flood estimation will not be taken lightly by practitioners. However, the standard for change is clear - can we develop new methods which give significant improvements in reliability over those existing methods which are demonstrably unsatisfactory?
Water allocation assessment in low flow river under data scarce conditions: a study of hydrological simulation in Mediterranean basin.

PubMed

Bangash, Rubab F; Passuello, Ana; Hammond, Michael; Schuhmacher, Marta

2012-12-01

River Francolí is a small river in Catalonia (northeastern Spain) with an average annual low flow (~2 m(3)/s). The purpose of the River Francolí watershed assessments is to support and inform region-wide planning efforts from the perspective of water protection, climate change and water allocation. In this study, a hydrological model of the Francolí River watershed was developed for use as a tool for watershed planning, water resource assessment, and ultimately, water allocation purposes using hydrological data from 2002 to 2006 inclusive. The modeling package selected for this application is DHI's MIKE BASIN. This model is a strategic scale water resource management simulation model, which includes modeling of both land surface and subsurface hydrological processes. Topographic, land use, hydrological, rainfall, and meteorological data were used to develop the model segmentation and input. Due to the unavailability of required catchment runoff data, the NAM rainfall-runoff model was used to calculate runoff of all the sub-watersheds. The results reveal a potential pressure on the availability of groundwater and surface water in the lower part of River Francolí as was expected by the IPCC for Mediterranean river basins. The study also revealed that due to the complex hydrological regime existing in the study area and data scarcity, a comprehensive physically based method was required to better represent the interaction between groundwater and surface water. The combined ArcGIS/MIKE BASIN models appear as a useful tool to assess the hydrological cycle and to better understand water allocation to different sectors in the Francolí River watershed. Copyright © 2012 Elsevier B.V. All rights reserved.
Data-base development for water-quality modeling of the Patuxent River basin, Maryland

USGS Publications Warehouse

Fisher, G.T.; Summers, R.M.

1987-01-01

Procedures and rationale used to develop a data base and data management system for the Patuxent Watershed Nonpoint Source Water Quality Monitoring and Modeling Program of the Maryland Department of the Environment and the U.S. Geological Survey are described. A detailed data base and data management system has been developed to facilitate modeling of the watershed for water quality planning purposes; statistical analysis; plotting of meteorologic, hydrologic and water quality data; and geographic data analysis. The system is Maryland 's prototype for development of a basinwide water quality management program. A key step in the program is to build a calibrated and verified water quality model of the basin using the Hydrological Simulation Program--FORTRAN (HSPF) hydrologic model, which has been used extensively in large-scale basin modeling. The compilation of the substantial existing data base for preliminary calibration of the basin model, including meteorologic, hydrologic, and water quality data from federal and state data bases and a geographic information system containing digital land use and soils data is described. The data base development is significant in its application of an integrated, uniform approach to data base management and modeling. (Lantz-PTT)
Estimating Water Storage Capacity of Existing and Potentially Restorable Wetland Depressions in a Subbasin of the Red River of the North

USGS Publications Warehouse

Gleason, Robert A.; Tangen, Brian A.; Laubhan, Murray K.; Kermes, Kevin E.; Euliss, Ned H.

2007-01-01

Executive Summary Concern over flooding along rivers in the Prairie Pothole Region has stimulated interest in developing spatially distributed hydrologic models to simulate the effects of wetland water storage on peak river flows. Such models require spatial data on the storage volume and interception area of existing and restorable wetlands in the watershed of interest. In most cases, information on these model inputs is lacking because resolution of existing topographic maps is inadequate to estimate volume and areas of existing and restorable wetlands. Consequently, most studies have relied on wetland area to volume or interception area relationships to estimate wetland basin storage characteristics by using available surface area data obtained as a product from remotely sensed data (e.g., National Wetlands Inventory). Though application of areal input data to estimate volume and interception areas is widely used, a drawback is that there is little information available to provide guidance regarding the application, limitations, and biases associated with such approaches. Another limitation of previous modeling efforts is that water stored by wetlands within a watershed is treated as a simple lump storage component that is filled prior to routing overflow to a pour point or gaging station. This approach does not account for dynamic wetland processes that influence water stored in prairie wetlands. Further, most models have not considered the influence of human-induced hydrologic changes, such as land use, that greatly influence quantity of surface water inputs and, ultimately, the rate that a wetland basin fills and spills. The goals of this study were to (1) develop and improve methodologies for estimating and spatially depicting wetland storage volumes and interceptions areas and (2) develop models and approaches for estimating/simulating the water storage capacity of potentially restorable and existing wetlands under various restoration, land use, and climatic scenarios. To address these goals, we developed models and approaches to spatially represent storage volumes and interception areas of existing and potentially restorable wetlands in the upper Mustinka subbasin within Grant County, Minn. We then developed and applied a model to simulate wetland water storage increases that would result from restoring 25 and 50 percent of the farmed and drained wetlands in the upper Mustinka subbasin. The model simulations were performed during the growing season (May-October) for relatively wet (1993; 0.79 m of precipitation) and dry (1987; 0.40 m of precipitation) years. Results from the simulations indicated that the 25 percent restoration scenario would increase water storage by 21-24 percent and that a 50 percent scenario would increase storage by 34-38 percent. Additionally, we estimated that wetlands in the subbasin have potential to store 11.57-20.98 percent of the total precipitation that fell over the entire subbasin area (52,758 ha). Our simulation results indicated that there is considerable potential to enhance water storage in the subbasin; however, evaluation and calibration of the model is necessary before simulation results can be applied to management and planning decisions. In this report we present guidance for the development and application of models (e.g., surface area-volume predictive models, hydrology simulation model) to simulate wetland water storage to provide a basis from which to understand and predict the effects of natural or human-induced hydrologic alterations. In developing these approaches, we tried to use simple and widely available input data to simulate wetland hydrology and predict wetland water storage for a specific precipitation event or a series of events. Further, the hydrology simulation model accounted for land use and soil type, which influence surface water inputs to wetlands. Although information presented in this report is specific to the Mustinka subbasin, the approaches
Brokering as a framework for hydrological model repeatability

NASA Astrophysics Data System (ADS)

Fuka, Daniel; Collick, Amy; MacAlister, Charlotte; Braeckel, Aaron; Wright, Dawn; Jodha Khalsa, Siri; Boldrini, Enrico; Easton, Zachary

2015-04-01

Data brokering aims to provide those in the the sciences with quick and repeatable access to data that represents physical, biological, and chemical characteristics; specifically to accelerate scientific discovery. Environmental models are useful tools to understand the behavior of hydrological systems. Unfortunately, parameterization of these hydrological models requires many different data, from different sources, and from different disciplines (e.g., atmospheric, geoscience, ecology). In basin scale hydrological modeling, the traditional procedure for model initialization starts with obtaining elevation models, land-use characterizations, soils maps, and weather data. It is often the researcher's past experience with these datasets that determines which datasets will be used in a study, and often newer, or more suitable data products will exist. An added complexity is that various science communities have differing data formats, storage protocols, and manipulation methods, which makes use by a non native user exceedingly difficult and time consuming. We demonstrate data brokering as a means to address several of these challenges. We present two test case scenarios in which researchers attempt to reproduce hydrological model results using 1) general internet based data gathering techniques, and 2) a scientific data brokering interface. We show that data brokering can increase the efficiency with which data are obtained, models are initialized, and results are analyzed. As an added benefit, it appears brokering can significantly increase the repeatability of a given study.
Revising Hydrology of a Land Surface Model

NASA Astrophysics Data System (ADS)

Le Vine, Nataliya; Butler, Adrian; McIntyre, Neil; Jackson, Christopher

2015-04-01

Land Surface Models (LSMs) are key elements in guiding adaptation to the changing water cycle and the starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, before this potential is realised, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. An important limitation is the simplistic or non-existent representation of the deep subsurface in LSMs; and another is the lack of connection of LSM parameterisations to relevant hydrological information. In this context, the paper uses a case study of the JULES (Joint UK Land Environmental Simulator) LSM applied to the Kennet region in Southern England. The paper explores the assumptions behind JULES hydrology, adapts the model structure and optimises the coupling with the ZOOMQ3D regional groundwater model. The analysis illustrates how three types of information can be used to improve the model's hydrology: a) observations, b) regionalized information, and c) information from an independent physics-based model. It is found that: 1) coupling to the groundwater model allows realistic simulation of streamflows; 2) a simple dynamic lower boundary improves upon JULES' stationary unit gradient condition; 3) a 1D vertical flow in the unsaturated zone is sufficient; however there is benefit in introducing a simple dual soil moisture retention curve; 4) regionalized information can be used to describe soil spatial heterogeneity. It is concluded that relatively simple refinements to the hydrology of JULES and its parameterisation method can provide a substantial step forward in realising its potential as a high-resolution multi-purpose model.
An open source hydroeconomic model for California's water supply system: PyVIN

NASA Astrophysics Data System (ADS)

Dogan, M. S.; White, E.; Herman, J. D.; Hart, Q.; Merz, J.; Medellin-Azuara, J.; Lund, J. R.

2016-12-01

Models help operators and decision makers explore and compare different management and policy alternatives, better allocate scarce resources, and predict the future behavior of existing or proposed water systems. Hydroeconomic models are useful tools to increase benefits or decrease costs of managing water. Bringing hydrology and economics together, these models provide a framework for different disciplines that share similar objectives. This work proposes a new model to evaluate operation and adaptation strategies under existing and future hydrologic conditions for California's interconnected water system. This model combines the network structure of CALVIN, a statewide optimization model for California's water infrastructure, along with an open source solver written in the Python programming language. With the flexibilities of the model, reservoir operations, including water supply and hydropower, groundwater pumping, and the Delta water operations and requirements can now be better represented. Given time series of hydrologic inputs to the model, typical outputs include urban, agricultural and wildlife refuge water deliveries and shortage costs, conjunctive use of surface and groundwater systems, and insights into policy and management decisions, such as capacity expansion and groundwater management policies. Water market operations also represented in the model, allocating water from lower-valued users to higher-valued users. PyVIN serves as a cross-platform, extensible model to evaluate systemwide water operations. PyVIN separates data from the model structure, enabling model to be easily applied to other parts of the world where water is a scarce resource.
Integrated modeling of storm drain and natural channel networks for real-time flash flood forecasting in large urban areas

NASA Astrophysics Data System (ADS)

Habibi, H.; Norouzi, A.; Habib, A.; Seo, D. J.

2016-12-01

To produce accurate predictions of flooding in urban areas, it is necessary to model both natural channel and storm drain networks. While there exist many urban hydraulic models of varying sophistication, most of them are not practical for real-time application for large urban areas. On the other hand, most distributed hydrologic models developed for real-time applications lack the ability to explicitly simulate storm drains. In this work, we develop a storm drain model that can be coupled with distributed hydrologic models such as the National Weather Service Hydrology Laboratory's Distributed Hydrologic Model, for real-time flash flood prediction in large urban areas to improve prediction and to advance the understanding of integrated response of natural channels and storm drains to rainfall events of varying magnitude and spatiotemporal extent in urban catchments of varying sizes. The initial study area is the Johnson Creek Catchment (40.1 km2) in the City of Arlington, TX. For observed rainfall, the high-resolution (500 m, 1 min) precipitation data from the Dallas-Fort Worth Demonstration Network of the Collaborative Adaptive Sensing of the Atmosphere radars is used.
Understanding the Impacts of Climate Change and Land Use Dynamics Using a Fully Coupled Hydrologic Feedback Model between Surface and Subsurface Systems

NASA Astrophysics Data System (ADS)

Park, C.; Lee, J.; Koo, M.

2011-12-01

Climate is the most critical driving force of the hydrologic system of the Earth. Since the industrial revolution, the impacts of anthropogenic activities to the Earth environment have been expanded and accelerated. Especially, the global emission of carbon dioxide into the atmosphere is known to have significantly increased temperature and affected the hydrologic system. Many hydrologists have contributed to the studies regarding the climate change on the hydrologic system since the Intergovernmental Panel on Climate Change (IPCC) was created in 1988. Among many components in the hydrologic system groundwater and its response to the climate change and anthropogenic activities are not fully understood due to the complexity of subsurface conditions between the surface and the groundwater table. A new spatio-temporal hydrologic model has been developed to estimate the impacts of climate change and land use dynamics on the groundwater. The model consists of two sub-models: a surface model and a subsurface model. The surface model involves three surface processes: interception, runoff, and evapotranspiration, and the subsurface model does also three subsurface processes: soil moisture balance, recharge, and groundwater flow. The surface model requires various input data including land use, soil types, vegetation types, topographical elevations, and meteorological data. The surface model simulates daily hydrological processes for rainfall interception, surface runoff varied by land use change and crop growth, and evapotranspiration controlled by soil moisture balance. The daily soil moisture balance is a key element to link two sub-models as it calculates infiltration and groundwater recharge by considering a time delay routing through a vadose zone down to the groundwater table. MODFLOW is adopted to simulate groundwater flow and interaction with surface water components as well. The model is technically flexible to add new model or modify existing model as it is developed with an object-oriented language - Python. The model also can easily be localized by simple modification of soil and crop properties. The actual application of the model after calibration was successful and results showed reliable water balance and interaction between the surface and subsurface hydrologic systems.
A high-resolution European dataset for hydrologic modeling

NASA Astrophysics Data System (ADS)

Ntegeka, Victor; Salamon, Peter; Gomes, Goncalo; Sint, Hadewij; Lorini, Valerio; Thielen, Jutta

2013-04-01

There is an increasing demand for large scale hydrological models not only in the field of modeling the impact of climate change on water resources but also for disaster risk assessments and flood or drought early warning systems. These large scale models need to be calibrated and verified against large amounts of observations in order to judge their capabilities to predict the future. However, the creation of large scale datasets is challenging for it requires collection, harmonization, and quality checking of large amounts of observations. For this reason, only a limited number of such datasets exist. In this work, we present a pan European, high-resolution gridded dataset of meteorological observations (EFAS-Meteo) which was designed with the aim to drive a large scale hydrological model. Similar European and global gridded datasets already exist, such as the HadGHCND (Caesar et al., 2006), the JRC MARS-STAT database (van der Goot and Orlandi, 2003) and the E-OBS gridded dataset (Haylock et al., 2008). However, none of those provide similarly high spatial resolution and/or a complete set of variables to force a hydrologic model. EFAS-Meteo contains daily maps of precipitation, surface temperature (mean, minimum and maximum), wind speed and vapour pressure at a spatial grid resolution of 5 x 5 km for the time period 1 January 1990 - 31 December 2011. It furthermore contains calculated radiation, which is calculated by using a staggered approach depending on the availability of sunshine duration, cloud cover and minimum and maximum temperature, and evapotranspiration (potential evapotranspiration, bare soil and open water evapotranspiration). The potential evapotranspiration was calculated using the Penman-Monteith equation with the above-mentioned meteorological variables. The dataset was created as part of the development of the European Flood Awareness System (EFAS) and has been continuously updated throughout the last years. The dataset variables are used as inputs to the hydrological calibration and validation of EFAS as well as for establishing long-term discharge "proxy" climatologies which can then in turn be used for statistical analysis to derive return periods or other time series derivatives. In addition, this dataset will be used to assess climatological trends in Europe. Unfortunately, to date no baseline dataset at the European scale exists to test the quality of the herein presented data. Hence, a comparison against other existing datasets can therefore only be an indication of data quality. Due to availability, a comparison was made for precipitation and temperature only, arguably the most important meteorological drivers for hydrologic models. A variety of analyses was undertaken at country scale against data reported to EUROSTAT and E-OBS datasets. The comparison revealed that while the datasets showed overall similar temporal and spatial patterns, there were some differences in magnitudes especially for precipitation. It is not straightforward to define the specific cause for these differences. However, in most cases the comparatively low observation station density appears to be the principal reason for the differences in magnitude.
Mountain hydrology of the western United States

USGS Publications Warehouse

Bales, Roger C.; Molotch, Noah P.; Painter, Thomas H; Dettinger, Michael D.; Rice, Robert; Dozier, Jeff

2006-01-01

Climate change and climate variability, population growth, and land use change drive the need for new hydrologic knowledge and understanding. In the mountainous West and other similar areas worldwide, three pressing hydrologic needs stand out: first, to better understand the processes controlling the partitioning of energy and water fluxes within and out from these systems; second, to better understand feedbacks between hydrological fluxes and biogeochemical and ecological processes; and, third, to enhance our physical and empirical understanding with integrated measurement strategies and information systems. We envision an integrative approach to monitoring, modeling, and sensing the mountain environment that will improve understanding and prediction of hydrologic fluxes and processes. Here extensive monitoring of energy fluxes and hydrologic states are needed to supplement existing measurements, which are largely limited to streamflow and snow water equivalent. Ground‐based observing systems must be explicitly designed for integration with remotely sensed data and for scaling up to basins and whole ranges.
High resolution modeling of reservoir storage and extent dynamics at the continental scale

NASA Astrophysics Data System (ADS)

Shin, S.; Pokhrel, Y. N.

2017-12-01

Over the past decade, significant progress has been made in developing reservoir schemes in large scale hydrological models to better simulate hydrological fluxes and storages in highly managed river basins. These schemes have been successfully used to study the impact of reservoir operation on global river basins. However, improvements in the existing schemes are needed for hydrological fluxes and storages, especially at the spatial resolution to be used in hyper-resolution hydrological modeling. In this study, we developed a reservoir routing scheme with explicit representation of reservoir storage and extent at the grid scale of 5km or less. Instead of setting reservoir area to a fixed value or diagnosing it using the area-storage equation, which is a commonly used approach in the existing reservoir schemes, we explicitly simulate the inundated storage and area for all grid cells that are within the reservoir extent. This approach enables a better simulation of river-floodplain-reservoir storage by considering both the natural flood and man-made reservoir storage. Results of the seasonal dynamics of reservoir storage, river discharge at the downstream of dams, and the reservoir inundation extent are evaluated with various datasets from ground-observations and satellite measurements. The new model captures the dynamics of these variables with a good accuracy for most of the large reservoirs in the western United States. It is expected that the incorporation of the newly developed reservoir scheme in large-scale land surface models (LSMs) will lead to improved simulation of river flow and terrestrial water storage in highly managed river basins.
The need for a European data platform for hydrological observatories

NASA Astrophysics Data System (ADS)

Blöschl, Günter; Bogena, Heye; Jensen, Karsten; Zacharias, Steffen; Kunstmann, Harald; Heinrich, Ingo; Kunkel, Ralf; Vereecken, Harry

2017-04-01

Experimental research in hydrology is amazingly fragmented and disperse. Typically, individual research groups establish and operate their own hydrological test sites and observatories with dedicated funding and specific research questions in mind. Once funding ceases, provisions for archiving and exchanging the data also soon run out and often data are lost or are no longer accessible to the research community. This has not only resulted in missed opportunities for exploring and mining hydrological data but also in a general difficulty in synthesizing research findings from different locations around the world. Many reasons for this fragmentation can be put forward, including the site-specific nature of hydrological processes, the particular types of research funding and the professional education in diverse departments. However, opportunities exist for making hydrological data more accessible and valuable to the research community, for example for designing cross-catchment experiments that build on a common data base and for the development and validation of hydrological models. A number of abundantly instrumented hydrological observatories, including the TERENO catchments in Germany, the HOBE catchment in Denmark and the HOAL catchment in Austria, have, in a first step, started to join forces to serve as a community-driven nucleus for a European data platform of hydrological observatories. The common data platform aims at making data of existing hydrological observatories accessible and available to the research community, thereby providing new opportunities for the design of cross-catchment experiments and model validation efforts. Tangible instruments for implementing this platform include a common data portal, for which the TEODOOR portal (http://www.tereno.net/) is currently used. Intangible instruments include a strong motivational basis. As with any community initiative, it is important to align expectations and to provide incentives to all involved. It is argued that the main incentives lie in the shared learning from contrasting environments, which is at the heart of obtaining hydrological research findings that are generalizable beyond individual locations. From a more practical perspective, experience can be shared with testing measurement technologies and experimental design. Benefits to the wider community include a more coherent research thrust brought about by a common, accessible data set, a more long-term vision of experimental research, as well as greater visibility of experimental research. The common data platform is a first step towards a larger network of hydrological observatories. The larger network could involve a more aligned research collaboration including exchange of models, exchange of students, a joint research agenda and joint long-term projects. Ultimately, the aim is to align experimental research in hydrology to strengthen the discipline of hydrology as a whole.
Identification and quantification of the hydrological impacts of imperviousness in urban catchments: a review.

PubMed

Jacobson, Carol R

2011-06-01

Urbanisation produces numerous changes in the natural environments it replaces. The impacts include habitat fragmentation and changes to both the quality and quantity of the stormwater runoff, and result in changes to hydrological systems. This review integrates research in relatively diverse areas to examine how the impacts of urban imperviousness on hydrological systems can be quantified and modelled. It examines the nature of reported impacts of urbanisation on hydrological systems over four decades, including the effects of changes in imperviousness within catchments, and some inconsistencies in studies of the impacts of urbanisation. The distribution of imperviousness within urban areas is important in understanding the impacts of urbanisation and quantification requires detailed characterisation of urban areas. As a result most mapping of urban areas uses remote sensing techniques and this review examines a range of techniques using medium and high resolution imagery, including spectral unmixing. The third section examines the ways in which scientists and hydrological and environmental engineers model and quantify water flows in urban areas, the nature of hydrological models and methods for their calibration. The final section examines additional factors which influence the impact of impervious surfaces and some uncertainties that exist in current knowledge. Copyright © 2011 Elsevier Ltd. All rights reserved.
Global operational hydrological forecasts through eWaterCycle

NASA Astrophysics Data System (ADS)

van de Giesen, Nick; Bierkens, Marc; Donchyts, Gennadii; Drost, Niels; Hut, Rolf; Sutanudjaja, Edwin

2015-04-01

Central goal of the eWaterCycle project (www.ewatercycle.org) is the development of an operational hyper-resolution hydrological global model. This model is able to produce 14 day ensemble forecasts based on a hydrological model and operational weather data (presently NOAA's Global Ensemble Forecast System). Special attention is paid to prediction of situations in which water related issues are relevant, such as floods, droughts, navigation, hydropower generation, and irrigation stress. Near-real time satellite data will be assimilated in the hydrological simulations, which is a feature that will be presented for the first time at EGU 2015. First, we address challenges that are mainly computer science oriented but have direct practical hydrological implications. An important feature in this is the use of existing standards and open-source software to the maximum extent possible. For example, we use the Community Surface Dynamics Modeling System (CSDMS) approach to coupling models (Basic Model Interface (BMI)). The hydrological model underlying the project is PCR-GLOBWB, built by Utrecht University. This is the motor behind the predictions and state estimations. Parts of PCR-GLOBWB have been re-engineered to facilitate running it in a High Performance Computing (HPC) environment, run parallel on multiple nodes, as well as to use BMI. Hydrological models are not very CPU intensive compared to, say, atmospheric models. They are, however, memory hungry due to the localized processes and associated effective parameters. To accommodate this memory need, especially in an ensemble setting, a variation on the traditional Ensemble Kalman Filter was developed that needs much less on-chip memory. Due to the operational nature, the coupling of the hydrological model with hydraulic models is very important. The idea is not to run detailed hydraulic routing schemes over the complete globe but to have on-demand simulation prepared off-line with respect to topography and parameterizations. This allows for very detailed simulations at hectare to meter scales, where and when this is needed. At EGU 2015, the operational global eWaterCycle model will be presented for the first time, including forecasts at high resolution, the innovative data assimilation approach, and on-demand coupling with hydraulic models.
An integrated approach to conjunctive-use analysis with the one-water hydrologic flow model, MODFLOW-OWHM

USGS Publications Warehouse

Boyce, Scott E.; Hanson, Randall T.

2015-01-01

The MODFLOW-2005 (MF) family of hydrologic simulators has diverged into multiple versions designed for specific needs, thus limiting their use to their respective designs. The One-Water Hydrologic Flow Model (MF-OWHM v1.0) is an integrated hydrologic flow model that is an enhanced fusion of multiple MF versions. While maintaining compatibility with existing MF versions, MF-OWHM includes: linkages for coupled heads, flows, and deformation; facilitation of self-updating models, additional observation and parameter options for higher-order calibrations; and redesigned code for faster simulations. This first release of MF-OWHM incorporates MODFLOW-2005 and the Farm Process (MF-FMP2), with new features (FMP3), combined with Local Grid Refinement (MF-LGR), Streamflow Routing (SFR), Surfacewater Routing Process (SWR), Seawater Intrusion (SWI), Riparian Evapotranspiration (RIP-ET), the Newton Formulation (MF-NWT), and more. MF-OWHM represents a complete integrated hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for consumption by agriculture and natural vegetation on the landscape, and for potable and other uses. By retaining and keeping track of the water during simulation of the hydrosphere, MF-OWHM accounts for “all of the water everywhere and all of the time.” This provides the foundation needed to address integrated hydrologic problems such as evaluation of conjunctive-use alternatives and sustainability analysis, including potential adaptation and mitigation strategies, and best management practices.
Understanding the Amazon Hydrology for Sustainable Hydropower Development

NASA Astrophysics Data System (ADS)

Pokhrel, Y. N.; Chaudhari, S. N.

2017-12-01

Construction of 147 new hydropower dams, many of which are large, has been proposed in the Amazon river basin, despite the continuous stacking of negative impacts from the existing ones. These dams are continued to be built in a way that disrupts river ecology, causes large-scale deforestation, and negatively affects both the food systems nearby and downstream communities. In this study, we explore the impacts of the existing and proposed hydropower dams on the hydrological fluxes across the Amazonian Basin by incorporating human impact modules in an extensively validated regional hydrological model called LEAF-Hydro-Flood (LHF). We conduct two simulations, one in offline mode, forced by observed meteorological data for the historical period of 2000-2016 and the other in a coupled mode using the Weather Research and Forecasting (WRF) regional climate model. We mainly analyze terrestrial water storage and streamflow changes during the period of dam operations with and without human impacts. It is certain that the Amazon will undergo some major hydrological changes such as decrease in streamflow downstream in the coming decades caused due to these proposed dams. This study helps us understand and represent processes in a predictable manner, and provides the ability to evaluate future scenarios with dams and other major human influences while considering climate change in the basin. It also provides important insights on how to redesign the hydropower systems to make them truly renewable in terms of energy production, hydrology and ecology.
Toward seamless hydrologic predictions across spatial scales

NASA Astrophysics Data System (ADS)

Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Zink, Matthias; Wanders, Niko; Eisner, Stephanie; Müller Schmied, Hannes; Sutanudjaja, Edwin H.; Warrach-Sagi, Kirsten; Attinger, Sabine

2017-09-01

Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.
Can the super model (SUMO) method improve hydrological simulations? Exploratory tests with the GR hydrological models

NASA Astrophysics Data System (ADS)

Santos, Léonard; Thirel, Guillaume; Perrin, Charles

2017-04-01

Errors made by hydrological models may come from a problem in parameter estimation, uncertainty on observed measurements, numerical problems and from the model conceptualization that simplifies the reality. Here we focus on this last issue of hydrological modeling. One of the solutions to reduce structural uncertainty is to use a multimodel method, taking advantage of the great number and the variability of existing hydrological models. In particular, because different models are not similarly good in all situations, using multimodel approaches can improve the robustness of modeled outputs. Traditionally, in hydrology, multimodel methods are based on the output of the model (the simulated flow series). The aim of this poster is to introduce a different approach based on the internal variables of the models. The method is inspired by the SUper MOdel (SUMO, van den Berge et al., 2011) developed for climatology. The idea of the SUMO method is to correct the internal variables of a model taking into account the values of the internal variables of (an)other model(s). This correction is made bilaterally between the different models. The ensemble of the different models constitutes a super model in which all the models exchange information on their internal variables with each other at each time step. Due to this continuity in the exchanges, this multimodel algorithm is more dynamic than traditional multimodel methods. The method will be first tested using two GR4J models (in a state-space representation) with different parameterizations. The results will be presented and compared to traditional multimodel methods that will serve as benchmarks. In the future, other rainfall-runoff models will be used in the super model. References van den Berge, L. A., Selten, F. M., Wiegerinck, W., and Duane, G. S. (2011). A multi-model ensemble method that combines imperfect models through learning. Earth System Dynamics, 2(1) :161-177.

Establishing a Framework for Community Modeling in Hydrologic Science: Recommendations from the CUAHSI CHyMP Initiative

NASA Astrophysics Data System (ADS)

Arrigo, J. S.; Famiglietti, J. S.; Murdoch, L. C.; Lakshmi, V.; Hooper, R. P.

2012-12-01

The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) continues a major effort towards supporting Community Hydrologic Modeling. From 2009 - 2011, the Community Hydrologic Modeling Platform (CHyMP) initiative held three workshops, the ultimate goal of which was to produce recommendations and an implementation plan to establish a community modeling program that enables comprehensive simulation of water anywhere on the North American continent. Such an effort would include connections to and advances in global climate models, biogeochemistry, and efforts of other disciplines that require an understanding of water patterns and processes in the environment. To achieve such a vision will require substantial investment in human and cyber-infrastructure and significant advances in the science of hydrologic modeling and spatial scaling. CHyMP concluded with a final workshop, held March 2011, and produced several recommendations. CUAHSI and the university community continue to advance community modeling and implement these recommendations through several related and follow on efforts. Key results from the final 2011 workshop included agreement among participants that the community is ready to move forward with implementation. It is recognized that initial implementation of this larger effort can begin with simulation capabilities that currently exist, or that can be easily developed. CHyMP identified four key activities in support of community modeling: benchmarking, dataset evaluation and development, platform evaluation, and developing a national water model framework. Key findings included: 1) The community supported the idea of a National Water Model framework; a community effort is needed to explore what the ultimate implementation of a National Water Model is. A true community modeling effort would support the modeling of "water anywhere" and would include all relevant scales and processes. 2) Implementation of a community modeling program could initially focus on continental scale modeling of water quantity (rather than quality). The goal of this initial model is the comprehensive description of water stores and fluxes in such a way to permit linkage to GCM's, biogeochemical, ecological, and geomorphic models. This continental scale focus allows systematic evaluation of our current state of knowledge and data, leverages existing efforts done by large scale modelers, contributes to scientific discovery that informs globally and societal relevant questions, and provides an initial framework to evaluate hydrologic information relevant to other disciplines and a structure into which to incorporate other classes of hydrologic models. 3) Dataset development will be a key aspect of any successful national water model implementation. Our current knowledge of the subsurface is limiting our ability to truly integrate soil and groundwater into large scale models, and to answering critical science questions with societal relevance (i.e. groundwater's influence on climate). 4) The CHyMP workshops and efforts to date have achieved collaboration between university scientists, government agencies and the private sector that must be maintained. Follow on efforts in community modeling should aim at leveraging and maintaining this collaboration for maximum scientific and societal benefit.
GSFLOW - Coupled Ground-Water and Surface-Water Flow Model Based on the Integration of the Precipitation-Runoff Modeling System (PRMS) and the Modular Ground-Water Flow Model (MODFLOW-2005)

USGS Publications Warehouse

Markstrom, Steven L.; Niswonger, Richard G.; Regan, R. Steven; Prudic, David E.; Barlow, Paul M.

2008-01-01

The need to assess the effects of variability in climate, biota, geology, and human activities on water availability and flow requires the development of models that couple two or more components of the hydrologic cycle. An integrated hydrologic model called GSFLOW (Ground-water and Surface-water FLOW) was developed to simulate coupled ground-water and surface-water resources. The new model is based on the integration of the U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) and the U.S. Geological Survey Modular Ground-Water Flow Model (MODFLOW). Additional model components were developed, and existing components were modified, to facilitate integration of the models. Methods were developed to route flow among the PRMS Hydrologic Response Units (HRUs) and between the HRUs and the MODFLOW finite-difference cells. This report describes the organization, concepts, design, and mathematical formulation of all GSFLOW model components. An important aspect of the integrated model design is its ability to conserve water mass and to provide comprehensive water budgets for a location of interest. This report includes descriptions of how water budgets are calculated for the integrated model and for individual model components. GSFLOW provides a robust modeling system for simulating flow through the hydrologic cycle, while allowing for future enhancements to incorporate other simulation techniques.
Evaluation TRMM Rainfall Data In Hydrological Modeling For An Ungaged In Lhasa River Basin

NASA Astrophysics Data System (ADS)

Ji, H. J.; Liu, J.

2017-12-01

Evaluation TRMM Rainfall Data In Hydrological Modeling For An Ungaged In Lhasa River BasinHaijuan Ji1* Jintao Liu1,2 Shanshan Xu1___________________ 1College of Hydrology and Water Resources, Hohai University, Nanjing 210098, People's Republic of China 2State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, People's Republic of China ___________________ * Corresponding author. Tel.: +86-025-83786973; Fax: +86-025-83786606. E-mail address: Hhu201510@163.com (H.J. Ji). Abstract: The Tibetan Plateau plays an important role in regulating the regional hydrological processes due to its high elevations and being the headwaters of many major Asian river basins. If familiar with the distribution of hydrological characteristics, will help us improve the level of development and utilization the water resources. However, there exist glaciers and snow with few sites. It is significance for us to understand the glacier and snow hydrological process in order to recognize the evolution of water resources in the Tibetan. This manuscript takes Lhasa River as the study area, taking use of ground, remote sensing and assimilation data, taking advantage of high precision TRMM precipitation data and MODIS snow cover data, first, according to the data from ground station evaluation of TRMM data in the application of the accuracy of the Lhasa River, and based on MODIS data fusion of multi source microwave snow making cloudless snow products, which are used for discriminant and analysis glacier and snow regulation mechanism on day scale, add snow and glacier unit into xinanjing model, this model can simulate the study region's runoff evolution, parameter sensitivity even spatial variation of hydrological characteristics the next ten years on region grid scale. The results of hydrological model in Lhasa River can simulate the glacier and snow runoff variation in high cold region better, to enhance the predictive ability of the spring snow disaster.
Practical guidance on representing the heteroscedasticity of residual errors of hydrological predictions

NASA Astrophysics Data System (ADS)

McInerney, David; Thyer, Mark; Kavetski, Dmitri; Kuczera, George

2016-04-01

Appropriate representation of residual errors in hydrological modelling is essential for accurate and reliable probabilistic streamflow predictions. In particular, residual errors of hydrological predictions are often heteroscedastic, with large errors associated with high runoff events. Although multiple approaches exist for representing this heteroscedasticity, few if any studies have undertaken a comprehensive evaluation and comparison of these approaches. This study fills this research gap by evaluating a range of approaches for representing heteroscedasticity in residual errors. These approaches include the 'direct' weighted least squares approach and 'transformational' approaches, such as logarithmic, Box-Cox (with and without fitting the transformation parameter), logsinh and the inverse transformation. The study reports (1) theoretical comparison of heteroscedasticity approaches, (2) empirical evaluation of heteroscedasticity approaches using a range of multiple catchments / hydrological models / performance metrics and (3) interpretation of empirical results using theory to provide practical guidance on the selection of heteroscedasticity approaches. Importantly, for hydrological practitioners, the results will simplify the choice of approaches to represent heteroscedasticity. This will enhance their ability to provide hydrological probabilistic predictions with the best reliability and precision for different catchment types (e.g. high/low degree of ephemerality).
Integrating hydrologic modeling web services with online data sharing to prepare, store, and execute models in hydrology

NASA Astrophysics Data System (ADS)

Gan, T.; Tarboton, D. G.; Dash, P. K.; Gichamo, T.; Horsburgh, J. S.

2017-12-01

Web based apps, web services and online data and model sharing technology are becoming increasingly available to support research. This promises benefits in terms of collaboration, platform independence, transparency and reproducibility of modeling workflows and results. However, challenges still exist in real application of these capabilities and the programming skills researchers need to use them. In this research we combined hydrologic modeling web services with an online data and model sharing system to develop functionality to support reproducible hydrologic modeling work. We used HydroDS, a system that provides web services for input data preparation and execution of a snowmelt model, and HydroShare, a hydrologic information system that supports the sharing of hydrologic data, model and analysis tools. To make the web services easy to use, we developed a HydroShare app (based on the Tethys platform) to serve as a browser based user interface for HydroDS. In this integration, HydroDS receives web requests from the HydroShare app to process the data and execute the model. HydroShare supports storage and sharing of the results generated by HydroDS web services. The snowmelt modeling example served as a use case to test and evaluate this approach. We show that, after the integration, users can prepare model inputs or execute the model through the web user interface of the HydroShare app without writing program code. The model input/output files and metadata describing the model instance are stored and shared in HydroShare. These files include a Python script that is automatically generated by the HydroShare app to document and reproduce the model input preparation workflow. Once stored in HydroShare, inputs and results can be shared with other users, or published so that other users can directly discover, repeat or modify the modeling work. This approach provides a collaborative environment that integrates hydrologic web services with a data and model sharing system to enable model development and execution. The entire system comprised of the HydroShare app, HydroShare and HydroDS web services is open source and contributes to capability for web based modeling research.
An Iterative Local Updating Ensemble Smoother for Estimation and Uncertainty Assessment of Hydrologic Model Parameters With Multimodal Distributions

NASA Astrophysics Data System (ADS)

Zhang, Jiangjiang; Lin, Guang; Li, Weixuan; Wu, Laosheng; Zeng, Lingzao

2018-03-01

Ensemble smoother (ES) has been widely used in inverse modeling of hydrologic systems. However, for problems where the distribution of model parameters is multimodal, using ES directly would be problematic. One popular solution is to use a clustering algorithm to identify each mode and update the clusters with ES separately. However, this strategy may not be very efficient when the dimension of parameter space is high or the number of modes is large. Alternatively, we propose in this paper a very simple and efficient algorithm, i.e., the iterative local updating ensemble smoother (ILUES), to explore multimodal distributions of model parameters in nonlinear hydrologic systems. The ILUES algorithm works by updating local ensembles of each sample with ES to explore possible multimodal distributions. To achieve satisfactory data matches in nonlinear problems, we adopt an iterative form of ES to assimilate the measurements multiple times. Numerical cases involving nonlinearity and multimodality are tested to illustrate the performance of the proposed method. It is shown that overall the ILUES algorithm can well quantify the parametric uncertainties of complex hydrologic models, no matter whether the multimodal distribution exists.
Balancing model complexity and measurements in hydrology

NASA Astrophysics Data System (ADS)

Van De Giesen, N.; Schoups, G.; Weijs, S. V.

2012-12-01

The Data Processing Inequality implies that hydrological modeling can only reduce, and never increase, the amount of information available in the original data used to formulate and calibrate hydrological models: I(X;Z(Y)) ≤ I(X;Y). Still, hydrologists around the world seem quite content building models for "their" watersheds to move our discipline forward. Hydrological models tend to have a hybrid character with respect to underlying physics. Most models make use of some well established physical principles, such as mass and energy balances. One could argue that such principles are based on many observations, and therefore add data. These physical principles, however, are applied to hydrological models that often contain concepts that have no direct counterpart in the observable physical universe, such as "buckets" or "reservoirs" that fill up and empty out over time. These not-so-physical concepts are more like the Artificial Neural Networks and Support Vector Machines of the Artificial Intelligence (AI) community. Within AI, one quickly came to the realization that by increasing model complexity, one could basically fit any dataset but that complexity should be controlled in order to be able to predict unseen events. The more data are available to train or calibrate the model, the more complex it can be. Many complexity control approaches exist in AI, with Solomonoff inductive inference being one of the first formal approaches, the Akaike Information Criterion the most popular, and Statistical Learning Theory arguably being the most comprehensive practical approach. In hydrology, complexity control has hardly been used so far. There are a number of reasons for that lack of interest, the more valid ones of which will be presented during the presentation. For starters, there are no readily available complexity measures for our models. Second, some unrealistic simplifications of the underlying complex physics tend to have a smoothing effect on possible model outcomes, thereby preventing the most obvious results of over-fitting. Thirdly, dependence within and between time series poses an additional analytical problem. Finally, there are arguments to be made that the often discussed "equifinality" in hydrological models is simply a different manifestation of the lack of complexity control. In turn, this points toward a general idea, which is actually quite popular in sciences other than hydrology, that additional data gathering is a good way to increase the information content of our descriptions of hydrological reality.
Does the Danube exist? Versions of reality given by various regional climate models and climatological data sets

NASA Astrophysics Data System (ADS)

Lucarini, Valerio; Danihlik, Robert; Kriegerova, Ida; Speranza, Antonio

2007-07-01

We present an auditing (intercomparison and verification) of several regional climate models (RCMs) nested into the same run of the same atmospheric global circulation model (AGCM) regarding their representation of the statistical properties of the hydrological balance of the Danube river basin for 1961-1990. We also consider the data sets produced by the driving AGCM, by the European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalyses. The hydrological balance is computed by integrating the precipitation and evaporation fields over the area of interest. Large discrepancies exist among RCMs for the monthly climatology as well as for the mean and variability of the annual balances, and only few data sets are consistent with the observed discharge values of the Danube at its Delta, even if the driving AGCM provides itself an excellent estimate. We find consistently that, for a given model, increases in the resolution do not alter the net water balance, while speeding up the hydrological cycle through the enhancement of both precipitation and evaporation by the same amount. Since the considered approach relies on the mass conservation principle and bypasses the details of the air-land interface modeling, we propose that the atmospheric components of RCMs still face difficulties in representing the water balance even on a relatively large scale. Their reliability on smaller river basins may be even more problematic. Moreover, since for some models the hydrological balance estimates obtained with the runoff fields do not agree with those obtained via precipitation and evaporation, some deficiencies of the land models are also apparent. The driving AGCM greatly overperforms the NCEP-NCAR and ECMWF 40-year (ERA-40) reanalyses, which result to be largely inadequate for representing the hydrology of the Danube river basin, both for the reconstruction of the long-term averages and of the seasonal cycle. The reanalyses cannot in any sense be used as verification. We suggest that these results should be carefully considered in the perspective of auditing climate models and assessing their ability to simulate future climate changes.
Acting, predicting and intervening in a socio-hydrological world

NASA Astrophysics Data System (ADS)

Lane, S. N.

2014-03-01

This paper asks a simple question: if humans and their actions co-evolve with hydrological systems (Sivapalan et al., 2012), what is the role of hydrological scientists, who are also humans, within this system? To put it more directly, as traditionally there is a supposed separation of scientists and society, can we maintain this separation as socio-hydrologists studying a socio-hydrological world? This paper argues that we cannot, using four linked sections. The first section draws directly upon the concern of science-technology studies to make a case to the (socio-hydrological) community that we need to be sensitive to constructivist accounts of science in general and socio-hydrology in particular. I review three positions taken by such accounts and apply them to hydrological science, supported with specific examples: (a) the ways in which scientific activities frame socio-hydrological research, such that at least some of the knowledge that we obtain is constructed by precisely what we do; (b) the need to attend to how socio-hydrological knowledge is used in decision-making, as evidence suggests that hydrological knowledge does not flow simply from science into policy; and (c) the observation that those who do not normally label themselves as socio-hydrologists may actually have a profound knowledge of socio-hydrology. The second section provides an empirical basis for considering these three issues by detailing the history of the practice of roughness parameterisation, using parameters like Manning's n, in hydrological and hydraulic models for flood inundation mapping. This history sustains the third section that is a more general consideration of one type of socio-hydrological practice: predictive modelling. I show that as part of a socio-hydrological analysis, hydrological prediction needs to be thought through much more carefully: not only because hydrological prediction exists to help inform decisions that are made about water management; but also because those predictions contain assumptions, the predictions are only correct in so far as those assumptions hold, and for those assumptions to hold, the socio-hydrological system (i.e. the world) has to be shaped so as to include them. Here, I add to the "normal" view that ideally our models should represent the world around us, to argue that for our models (and hence our predictions) to be valid, we have to make the world look like our models. Decisions over how the world is modelled may transform the world as much as they represent the world. Thus, socio-hydrological modelling has to become a socially accountable process such that the world is transformed, through the implications of modelling, in a fair and just manner. This leads into the final section of the paper where I consider how socio-hydrological research may be made more socially accountable, in a way that is both sensitive to the constructivist critique (Sect. 1), but which retains the contribution that hydrologists might make to socio-hydrological studies. This includes (1) working with conflict and controversy in hydrological science, rather than trying to eliminate them; (2) using hydrological events to avoid becoming locked into our own frames of explanation and prediction; (3) being empirical and experimental but in a socio-hydrological sense; and (4) co-producing socio-hydrological predictions. I will show how this might be done through a project that specifically developed predictive models for making interventions in river catchments to increase high river flow attenuation. Therein, I found myself becoming detached from my normal disciplinary networks and attached to the co-production of a predictive hydrological model with communities normally excluded from the practice of hydrological science.
Integrating the social sciences to understand human-water dynamics

NASA Astrophysics Data System (ADS)

Carr, G.; Kuil, L., Jr.

2017-12-01

Many interesting and exciting socio-hydrological models have been developed in recent years. Such models often aim to capture the dynamic interplay between people and water for a variety of hydrological settings. As such, peoples' behaviours and decisions are brought into the models as drivers of and/or respondents to the hydrological system. To develop and run such models over a sufficiently long time duration to observe how the water-human system evolves the human component is often simplified according to one or two key behaviours, characteristics or decisions (e.g. a decision to move away from a drought or flood area; a decision to pump groundwater, or a decision to plant a less water demanding crop). To simplify the social component, socio-hydrological modellers often pull knowledge and understanding from existing social science theories. This requires them to negotiate complex territory, where social theories may be underdeveloped, contested, dynamically evolving, or case specific and difficult to generalise or upscale. A key question is therefore, how can this process be supported so that the resulting socio-hydrological models adequately describe the system and lead to meaningful understanding of how and why it behaves as it does? Collaborative interdisciplinary research teams that bring together social and natural scientists are likely to be critical. Joint development of the model framework requires specific attention to clarification to expose all underlying assumptions, constructive discussion and negotiation to reach agreement on the modelled system and its boundaries. Mutual benefits to social scientists can be highlighted, i.e. socio-hydrological work can provide insights for further exploring and testing social theories. Collaborative work will also help ensure underlying social theory is made explicit, and may identify ways to include and compare multiple theories. As socio-hydrology progresses towards supporting policy development, approaches that brings in stakeholders and non-scientist participants to develop the conceptual modelling framework will become essential. They are also critical for fully understanding human-water dynamics.
Data-based discharge extrapolation: estimating annual discharge for a partially gauged large river basin from its small sub-basins

NASA Astrophysics Data System (ADS)

Gong, L.

2013-12-01

Large-scale hydrological models and land surface models are by far the only tools for accessing future water resources in climate change impact studies. Those models estimate discharge with large uncertainties, due to the complex interaction between climate and hydrology, the limited quality and availability of data, as well as model uncertainties. A new purely data-based scale-extrapolation method is proposed, to estimate water resources for a large basin solely from selected small sub-basins, which are typically two-orders-of-magnitude smaller than the large basin. Those small sub-basins contain sufficient information, not only on climate and land surface, but also on hydrological characteristics for the large basin In the Baltic Sea drainage basin, best discharge estimation for the gauged area was achieved with sub-basins that cover 2-4% of the gauged area. There exist multiple sets of sub-basins that resemble the climate and hydrology of the basin equally well. Those multiple sets estimate annual discharge for gauged area consistently well with 5% average error. The scale-extrapolation method is completely data-based; therefore it does not force any modelling error into the prediction. The multiple predictions are expected to bracket the inherent variations and uncertainties of the climate and hydrology of the basin. The method can be applied in both un-gauged basins and un-gauged periods with uncertainty estimation.
Spatially explicit simulation of hydrologically controlled carbon and nitrogen cycles and associated feedback mechanisms in a boreal ecosystem

NASA Astrophysics Data System (ADS)

Govind, Ajit; Chen, Jing Ming; Ju, Weimin

2009-06-01

Ecosystem models that simulate biogeochemical processes usually ignore hydrological controls that govern them. It is quite possible that topographically driven water fluxes significantly influence the spatial distribution of C sources and sinks because of their large contribution to the local water balance. To investigate this, we simulated biogeochemical processes along with the associated feedback mechanisms in a boreal ecosystem using a spatially explicit hydroecological model, boreal ecosystem productivity simulator (BEPS)-TerrainLab V2.0, that has a tight coupling of ecophysiological, hydrological, and biogeochemical processes. First, the simulated dynamics of snowpack, soil temperature, net ecosystem productivity (NEP), and total ecosystem respiration (TER) were validated with high-frequency measurements for 2 years. The model was able to explain 80% of the variability in NEP and 84% of the variability in TER. Further, we investigated the influence of topographically driven subsurface base flow on soil C and N cycling and on the spatiotemporal patterns of C sources and sinks using three hydrological modeling scenarios that differed in hydrological conceptualizations. In general, the scenarios that had nonexplicit hydrological representation overestimated NEP, as opposed to the scenario that had an explicit (realistic) representation. The key processes controlling the NEP differences were attributed to the combined effects of variations in photosynthesis (due to changes in stomatal conductance and nitrogen (N) availability), heterotrophic respiration, and autotrophic respiration, all of which occur simultaneously affecting NEP. Feedback relationships were also found to exacerbate the differences. We identified six types of NEP differences (biases), of which the most commonly found was due to an underestimation of the existing C sources, highlighting the vulnerability of regional-scale ecosystem models that ignore hydrological processes.
Quantitative and qualitative synthesis of socio-hydrological research

NASA Astrophysics Data System (ADS)

Xu, L.; Gober, P.; Wheater, H. S.; Kajikawa, Y.

2017-12-01

The challenge of climate change adaptation has raised awareness of the feedbacks and interconnections in complex human-natural coupled water systems. This has reinforced the call for a socio-hydrological approach to better understand, and represent in models, the associated system dynamics. Such models can potentially provide the tools to link knowledge about complex water systems to decision-making and policy frameworks. Socio-hydrology, as the subfield of human-natural coupled systems analysis, has been dramatically developed in the past few years. The purpose of this study is to empirically examine work that has been framed under the umbrella of socio-hydrology, to provide insights into the participants and their disciplinary perspectives, and to draw conclusions about where the field is headed. In doing so, we used a combined quantitative and qualitative approach to synthesise current knowledge of socio-hydrology and to propose some promising future directions in this subfield of water sciences. The general statistics of the existing literature showed that socio-hydrological research has become an emerging topic and is drawing more concern and engagement of hydrologists. However, the participation of social scientists is inadequate and greater cross-disciplinary integration is desirable. Current concerns in this subfield of water research centre on two basic challenges: (1) the need to embrace the social dimensions of water-related risks, and (2) the importance of interactions and feedbacks in dynamic socio-hydrological systems. A third challenge identified here relates to the large-scale implications of 1) and 2) above, i.e. virtual water flows as a mechanism to track the human use of water at the global scale. Accordingly, we propose five potential directions with regard to socio-hydrological models, interdisciplinary collaboration and transdisciplinary studies, the science-policy interface, resilience in socio-hydrological systems, and data sharing for human-water system studies.
Seamless hydrological predictions for a monsoon driven catchment in North-East India

NASA Astrophysics Data System (ADS)

Köhn, Lisei; Bürger, Gerd; Bronstert, Axel

2016-04-01

Improving hydrological forecasting systems on different time scales is interesting and challenging with regards to humanitarian as well as scientific aspects. In meteorological research, short-, medium-, and long-term forecasts are now being merged to form a system of seamless weather and climate predictions. Coupling of these meteorological forecasts with a hydrological model leads to seamless predictions of streamflow, ranging from one day to a season. While there are big efforts made to analyse the uncertainties of probabilistic streamflow forecasts, knowledge of the single uncertainty contributions from meteorological and hydrological modeling is still limited. The overarching goal of this project is to gain knowledge in this subject by decomposing and quantifying the overall predictive uncertainty into its single factors for the entire seamless forecast horizon. Our study area is the Mahanadi River Basin in North-East India, which is prone to severe floods and droughts. Improved streamflow forecasts on different time scales would contribute to early flood warning as well as better water management operations in the agricultural sector. Because of strong inter-annual monsoon variations in this region, which are, unlike the mid-latitudes, partly predictable from long-term atmospheric-oceanic oscillations, the Mahanadi catchment represents an ideal study site. Regionalized precipitation forecasts are obtained by applying the method of expanded downscaling to the ensemble prediction systems of ECMWF and NCEP. The semi-distributed hydrological model HYPSO-RR, which was developed in the Eco-Hydrological Simulation Environment ECHSE, is set up for several sub-catchments of the Mahanadi River Basin. The model is calibrated automatically using the Dynamically Dimensioned Search algorithm, with a modified Nash-Sutcliff efficiency as objective function. Meteorological uncertainty is estimated from the existing ensemble simulations, while the hydrological uncertainty is derived from a statistical post-processor. After running the hydrological model with the precipitation forecasts and applying the hydrological post-processor, the predictive uncertainty of the streamflow forecast can be analysed. The decomposition of total uncertainty is done using a two-way analysis of variance. In this contribution we present the model set-up and the first results of our hydrological forecasts with up to a 180 days lead time, which are derived by using 15 downscaled members of the ECMWF multi-model seasonal forecast ensemble as model input.
Quantification of effective plant rooting depth: advancing global hydrological modelling

NASA Astrophysics Data System (ADS)

Yang, Y.; Donohue, R. J.; McVicar, T.

2017-12-01

Plant rooting depth (Zr) is a key parameter in hydrological and biogeochemical models, yet the global spatial distribution of Zr is largely unknown due to the difficulties in its direct measurement. Moreover, Zr observations are usually only representative of a single plant or several plants, which can differ greatly from the effective Zr over a modelling unit (e.g., catchment or grid-box). Here, we provide a global parameterization of an analytical Zr model that balances the marginal carbon cost and benefit of deeper roots, and produce a climatological (i.e., 1982-2010 average) global Zr map. To test the Zr estimates, we apply the estimated Zr in a highly transparent hydrological model (i.e., the Budyko-Choudhury-Porporato (BCP) model) to estimate mean annual actual evapotranspiration (E) across the globe. We then compare the estimated E with both water balance-based E observations at 32 major catchments and satellite grid-box retrievals across the globe. Our results show that the BCP model, when implemented with Zr estimated herein, optimally reproduced the spatial pattern of E at both scales and provides improved model outputs when compared to BCP model results from two already existing global Zr datasets. These results suggest that our Zr estimates can be effectively used in state-of-the-art hydrological models, and potentially biogeochemical models, where the determination of Zr currently largely relies on biome type-based look-up tables.
Citizen observatory of water as a data engine supporting the people-hydrology nexus: experience of the WeSenseIt project

NASA Astrophysics Data System (ADS)

Ferri, Michele; Baruffi, Francesco; Norbiato, Daniele; Monego, Martina; Tomei, Giovanni; Solomatine, Dimitri; Alfonso, Leonardo; Mazzoleni, Maurizio; Chacon, Juan Carlos; Wehn, Uta; Ciravegna, Fabio

2016-04-01

Citizen observatories (COs) present an interesting case of strong multi-facet feedback between the physical (water) system and humans. CO is a form of crowdsourcing ensuring a data flow from citizens observing environment (e.g. water level in a river) to a central data processing unit which is typically part of a more complex social arrangement (e.g. water authorities responsible for flood forecasting). The EU-funded project WeSenseIt (www.wesenseit.eu) aims at developing technologies and tools supporting creation of such COs [1,2,3,4]. Citizens which form a CO play the role of "social sensors" which however are very specific. The data streams from such sensors have varying temporal and spatial coverage and information value (uncertainty). The crowdsourced data can be of course simply visualized and presented to public, but it is much more interesting to consider cases when such data are assimilated into the existing forecasting systems, e.g. flood early warning systems based on hydrological and hydraulic models. COs may also affect water management and governance [4], and in fact can be seen as data engines supporting the people-hydrology nexus. In the framework of WeSenseIt project several approaches were developed allowing for optimal assimilation of intermittent data streams with varying spatial coverage into distributed hydrological models [1, 2]. The mentioned specific features of CO data required updates of the existing data assimilation algorithms (Ensemble Kalman Filter was used as the basic algorithm). The developed algorithms have been implemented in the operational flood forecasting systems of the Alto Adriatico Water Authority (AAWA), Venice. In this paper we analyse various scenarios of employing citizens data (COs) for flood forecasting. This study is partly supported by the FP7 European Project WeSenseIt Citizen Water Observatory (www.http://wesenseit.eu/). References [1] Mazzoleni, M., Alfonso, L., Chacon-Hurtado, J., Solomatine, D. (2015). Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models. Advances in Water Res., 83, 323-339 (Online on September 1, 2015). [2] Mazzoleni M., Verlaan M., Alfonso L., Monego M., Norbiato D., Ferri M., and Solomatine D.P. (2015) Can assimilation of crowdsourced streamflow observations in hydrological modelling improve flood prediction?, Hydrology and Earth System Sciences, under review. [3] Mazzoleni M., Alfonso L. and Solomatine D.P. (2015) Effect of spatial distribution and quality of sensors on the assimilation of distributed streamflow observations in hydrological modeling, Hydrological Sciences Journal, under review. [4] Wehn, U., McCarty, S., Lanfranchi, V. and Tapsell, S. (2015) Citizen observatories as facilitators of change in water governance? Experiences from three European cases, Special Issue on ICTs and Water, Journal of Environmental Engineering and Management, 2073-2086.
GIS Based Distributed Runoff Predictions in Variable Source Area Watersheds Employing the SCS-Curve Number

NASA Astrophysics Data System (ADS)

Steenhuis, T. S.; Mendoza, G.; Lyon, S. W.; Gerard Marchant, P.; Walter, M. T.; Schneiderman, E.

2003-04-01

Because the traditional Soil Conservation Service Curve Number (SCS-CN) approach continues to be ubiquitously used in GIS-BASED water quality models, new application methods are needed that are consistent with variable source area (VSA) hydrological processes in the landscape. We developed within an integrated GIS modeling environment a distributed approach for applying the traditional SCS-CN equation to watersheds where VSA hydrology is a dominant process. Spatial representation of hydrologic processes is important for watershed planning because restricting potentially polluting activities from runoff source areas is fundamental to controlling non-point source pollution. The methodology presented here uses the traditional SCS-CN method to predict runoff volume and spatial extent of saturated areas and uses a topographic index to distribute runoff source areas through watersheds. The resulting distributed CN-VSA method was incorporated in an existing GWLF water quality model and applied to sub-watersheds of the Delaware basin in the Catskill Mountains region of New York State. We found that the distributed CN-VSA approach provided a physically-based method that gives realistic results for watersheds with VSA hydrology.
Modelling the effects of Prairie wetlands on streamflow

NASA Astrophysics Data System (ADS)

Shook, K.; Pomeroy, J. W.

2015-12-01

Recent research has demonstrated that the contributing areas of Prairie streams dominated by depressional (wetland) storage demonstrate hysteresis with respect to catchment water storage. As such contributing fractions can vary over time from a very small percentage of catchment area to the entire catchment during floods. However, catchments display complex memories of past storage states and their contributing fractions cannot be modelled accurately by any single-valued function. The Cold Regions Hydrological Modelling platform, CRHM, which is capable of modelling all of the hydrological processes of cold regions using a hydrological response unit discretization of the catchment, was used to further investigate dynamical contributing area response to hydrological processes. Contributing fraction in CRHM is also controlled by the episodic nature of runoff generation in this cold, sub-humid environment where runoff is dominated by snowmelt over frozen soils, snowdrifts define the contributing fraction in late spring, unfrozen soils have high water holding capacity and baseflow from sub-surface flow does not exist. CRHM was improved by adding a conceptual model of individual Prairie depression fill and spill runoff generation that displays hysteresis in the storage - contributing fraction relationship and memory of storage state. The contributing area estimated by CRHM shows strong sensitivity to hydrological inputs, storage and the threshold runoff rate chosen. The response of the contributing area to inputs from various runoff generating processes from snowmelt to rain-on-snow to rainfall with differing degrees of spatial variation was investigated as was the importance of the memory of storage states on streamflow generation. The importance of selecting hydrologically and ecologically meaningful runoff thresholds in estimating contributing area is emphasized.
Application of commercial microwave link (CML) derived precipitation data in a hydrology model

NASA Astrophysics Data System (ADS)

Smiatek, Gerhard; Chwala, Christian; Kunstmann, Harald

2017-04-01

In 2016 very local and extremely intensive convective events caused severe flooding in the Alpine space. Despite the large number of monitoring stations most of the rainfall events were not captured accurately by the existing rain gauge network. As the number of traditional precipitation monitoring sites is in general decreasing, novel rain monitoring techniques are gaining attention. One of the new techniques is the rainfall estimation from signal attenuation in commercial microwave link (CML) networks operated by cellular phone companies. In this contribution, we use CML-derived rainfall information to improve the streamflow forecast of the distributed hydrology model WaSiM-ETH in hindcasting and nowcasting modes. Our model domain covers the complex terrain of the Ammer catchment located in the German Alps. The hydrology model is operated with a spatial resolution of 100m and with an hourly time step. We present two alternative methods of rainfall estimation from CMLs and compare the results to data from rain gauges and a weather radar. Finally, we show the impact of the rainfall data sets on the hydrology model initialization and in discharge simulations of the Ammer River for selected episodes in 2015 and 2016. We found that the densification of the observation network by the CML observations leads to a significant improvement of the model performance.
Model‐based analysis of the influence of catchment properties on hydrologic partitioning across five mountain headwater subcatchments

PubMed Central

Wagener, Thorsten; McGlynn, Brian

2015-01-01

Abstract Ungauged headwater basins are an abundant part of the river network, but dominant influences on headwater hydrologic response remain difficult to predict. To address this gap, we investigated the ability of a physically based watershed model (the Distributed Hydrology‐Soil‐Vegetation Model) to represent controls on metrics of hydrologic partitioning across five adjacent headwater subcatchments. The five study subcatchments, located in Tenderfoot Creek Experimental Forest in central Montana, have similar climate but variable topography and vegetation distribution. This facilitated a comparative hydrology approach to interpret how parameters that influence partitioning, detected via global sensitivity analysis, differ across catchments. Model parameters were constrained a priori using existing regional information and expert knowledge. Influential parameters were compared to perceptions of catchment functioning and its variability across subcatchments. Despite between‐catchment differences in topography and vegetation, hydrologic partitioning across all metrics and all subcatchments was sensitive to a similar subset of snow, vegetation, and soil parameters. Results also highlighted one subcatchment with low certainty in parameter sensitivity, indicating that the model poorly represented some complexities in this subcatchment likely because an important process is missing or poorly characterized in the mechanistic model. For use in other basins, this method can assess parameter sensitivities as a function of the specific ungauged system to which it is applied. Overall, this approach can be employed to identify dominant modeled controls on catchment response and their agreement with system understanding. PMID:27642197

Hydrological Aspects of Weather Prediction and Flood Warnings: Report of the Ninth Prospectus Development Team of the U.S. Weather Research Program

USGS Publications Warehouse

Droegemeier, K.K.; Smith, J.D.; Businger, S.; Doswell, C.; Doyle, J.; Duffy, C.; Foufoula-Georgiou, E.; Graziano, T.; James, L.D.; Krajewski, V.; LeMone, M.; Lettenmaier, D.; Mass, C.; Pielke, R.; Ray, P.; Rutledge, S.; Schaake, J.; Zipser, E.

2000-01-01

Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme temperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has increased during the past few years and shows no sign of abating. Although the scientific questions associated with flooding and its accurate prediction are many and complex, an unprecedented opportunity now exists - in light of new observational and computing systems and infrastructures, a much improved understanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation systems - to attack the flood forecasting problem in a comprehensive manner that will yield significant new scientific insights and corresponding practical benefits. The authors present herein a set of recommendations for advancing our understanding of floods via the creation of natural laboratories situated in a variety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratropical cyclones, orographic forcing, and hurricanes and tropical cyclones following landfall. Although the particular research strategies applied within each laboratory setting will necessarily vary, all will share the following principal elements: (a) exploitation of those couplings important to flooding that exist between meteorological and hydrological processes and models; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitation fields and rates, along with the use of this information in hydrological models and for improving and validating microphysical algorithms in meteorological models; (c) comparisons of quantitative precipitation estimation algorithms from both research (especially multiparameter) and operational radars against gauge data as well as output produced by meso- and storm-scale models; (d) use of data from dense, temporary river gauge networks to trace the fate of rain from its starting location in small basins to the entire stream and river network; and (e) sensitivity testing in the design and implementation of separate as well as coupled meteorological and hydrologic models, the latter designed to better represent those nonlinear feedbacks between the atmosphere and land that are known to play an important role in runoff prediction. Vital to this effort will be the creation of effective and sustained linkages between the historically separate though scientifically related disciplines of meteorology and hydrology, as well as their observational infrastructures and research methodologies.
Hydrological Aspects of Weather Prediction and Flood Warnings: Report of the Ninth Prospectus Development Team of the U.S. Weather Research Program.

NASA Astrophysics Data System (ADS)

Droegemeier, K. K.; Smith, J. D.; Businger, S.; Doswell, C., III; Doyle, J.; Duffy, C.; Foufoula-Georgiou, E.; Graziano, T.; James, L. D.; Krajewski, V.; Lemone, M.; Lettenmaier, D.; Mass, C.; Pielke, R., Sr.; Ray, P.; Rutledge, S.; Schaake, J.; Zipser, E.

2000-11-01

Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme temperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has increased during the past few years and shows no sign of abating. Although the scientific questions associated with flooding and its accurate prediction are many and complex, an unprecedented opportunity now exists-in light of new observational and computing systems and infrastructures, a much improved understanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation systems-to attack the flood forecasting problem in a comprehensive manner that will yield significant new scientific insights and corresponding practical benefits. The authors present herein a set of recommendations for advancing our understanding of floods via the creation of natural laboratories situated in a variety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratropical cyclones, orographic forcing, and hurricanes and tropical cyclones following landfall. Although the particular research strategies applied within each laboratory setting will necessarily vary, all will share the following principal elements: (a) exploitation of those couplings important to flooding that exist between meteorological and hydrological processes and models; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitation fields and rates, along with the use of this information in hydrological models and for improving and validating microphysical algorithms in meteorological models; (c) comparisons of quantitative precipitation estimation algorithms from both research (especially multiparameter) and operational radars against gauge data as well as output produced by meso- and storm-scale models; (d) use of data from dense, temporary river gauge networks to trace the fate of rain from its starting location in small basins to the entire stream and river network; and (e) sensitivity testing in the design and implementation of separate as well as coupled meteorological and hydrologic models, the latter designed to better represent those nonlinear feedbacks between the atmosphere and land that are known to play an important role in runoff prediction. Vital to this effort will be the creation of effective and sustained linkages between the historically separate though scientifically related disciplines of meteorology and hydrology, as well as their observational infrastructures and research methodologies.
Hydrologic modeling to screen potential environmental management methods for malaria vector control in Niger

NASA Astrophysics Data System (ADS)

Gianotti, Rebecca L.; Bomblies, Arne; Eltahir, Elfatih A. B.

2009-08-01

This paper describes the first use of Hydrology-Entomology and Malaria Transmission Simulator (HYDREMATS), a physically based distributed hydrology model, to investigate environmental management methods for malaria vector control in the Sahelian village of Banizoumbou, Niger. The investigation showed that leveling of topographic depressions where temporary breeding habitats form during the rainy season, by altering pool basin microtopography, could reduce the pool persistence time to less than the time needed for establishment of mosquito breeding, approximately 7 days. Undertaking soil surface plowing can also reduce pool persistence time by increasing the infiltration rate through an existing pool basin. Reduction of the pool persistence time to less than the rainfall interstorm period increases the frequency of pool drying events, removing habitat for subadult mosquitoes. Both management approaches could potentially be considered within a given context. This investigation demonstrates that management methods that modify the hydrologic environment have significant potential to contribute to malaria vector control in water-limited, Sahelian Africa.
Evaluation of Proteus as a Tool for the Rapid Development of Models of Hydrologic Systems

NASA Astrophysics Data System (ADS)

Weigand, T. M.; Farthing, M. W.; Kees, C. E.; Miller, C. T.

2013-12-01

Models of modern hydrologic systems can be complex and involve a variety of operators with varying character. The goal is to implement approximations of such models that are both efficient for the developer and computationally efficient, which is a set of naturally competing objectives. Proteus is a Python-based toolbox that supports prototyping of model formulations as well as a wide variety of modern numerical methods and parallel computing. We used Proteus to develop numerical approximations for three models: Richards' equation, a brine flow model derived using the Thermodynamically Constrained Averaging Theory (TCAT), and a multiphase TCAT-based tumor growth model. For Richards' equation, we investigated discontinuous Galerkin solutions with higher order time integration based on the backward difference formulas. The TCAT brine flow model was implemented using Proteus and a variety of numerical methods were compared to hand coded solutions. Finally, an existing tumor growth model was implemented in Proteus to introduce more advanced numerics and allow the code to be run in parallel. From these three example models, Proteus was found to be an attractive open-source option for rapidly developing high quality code for solving existing and evolving computational science models.
A cost-effectiveness comparison of existing and Landsat-aided snow water content estimation systems

NASA Technical Reports Server (NTRS)

Sharp, J. M.; Thomas, R. W.

1975-01-01

This study describes how Landsat imagery can be cost-effectively employed to augment an operational hydrologic model. Attention is directed toward the estimation of snow water content, a major predictor variable in the volumetric runoff forecasting model presently used by the California Department of Water Resources. A stratified double sampling scheme is supplemented with qualitative and quantitative analyses of existing operations to develop a comparison between the existing and satellite-aided approaches to snow water content estimation. Results show a decided advantage for the Landsat-aided approach.
Parallelization of a Fully-Distributed Hydrologic Model using Sub-basin Partitioning

NASA Astrophysics Data System (ADS)

Vivoni, E. R.; Mniszewski, S.; Fasel, P.; Springer, E.; Ivanov, V. Y.; Bras, R. L.

2005-12-01

A primary obstacle towards advances in watershed simulations has been the limited computational capacity available to most models. The growing trend of model complexity, data availability and physical representation has not been matched by adequate developments in computational efficiency. This situation has created a serious bottleneck which limits existing distributed hydrologic models to small domains and short simulations. In this study, we present novel developments in the parallelization of a fully-distributed hydrologic model. Our work is based on the TIN-based Real-time Integrated Basin Simulator (tRIBS), which provides continuous hydrologic simulation using a multiple resolution representation of complex terrain based on a triangulated irregular network (TIN). While the use of TINs reduces computational demand, the sequential version of the model is currently limited over large basins (>10,000 km2) and long simulation periods (>1 year). To address this, a parallel MPI-based version of the tRIBS model has been implemented and tested using high performance computing resources at Los Alamos National Laboratory. Our approach utilizes domain decomposition based on sub-basin partitioning of the watershed. A stream reach graph based on the channel network structure is used to guide the sub-basin partitioning. Individual sub-basins or sub-graphs of sub-basins are assigned to separate processors to carry out internal hydrologic computations (e.g. rainfall-runoff transformation). Routed streamflow from each sub-basin forms the major hydrologic data exchange along the stream reach graph. Individual sub-basins also share subsurface hydrologic fluxes across adjacent boundaries. We demonstrate how the sub-basin partitioning provides computational feasibility and efficiency for a set of test watersheds in northeastern Oklahoma. We compare the performance of the sequential and parallelized versions to highlight the efficiency gained as the number of processors increases. We also discuss how the coupled use of TINs and parallel processing can lead to feasible long-term simulations in regional watersheds while preserving basin properties at high-resolution.
Testing the effects of in-stream sediment sources and sinks on simulated watershed sediment yield using the coupled U.S. Army Corps of Engineers GSSHA Model and SEDLIB Sediment Transport Library

NASA Astrophysics Data System (ADS)

Floyd, I. E.; Downer, C. W.; Brown, G.; Pradhan, N. R.

2017-12-01

The Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model is the US Army Corps of Engineers' (USACE)'s only fully coupled overland/in-stream sediment transport model. While the overland sediment transport formulation in GSSHA is considered state of the art, the existing in-stream sediment transport formulation is less robust. A major omission in the formulation of the existing GSSHA in-stream model is the lack of in-stream sources of fine materials. In this effort, we enhanced the in-stream sediment transport capacity of GSSHA by linking GSSHA to the SEDLIB sediment transport library. SEDLIB was developed at the Coastal and Hydraulics Laboratory (CHL) under the System Wide Water Resources Program (SWWRP) and Flood and Coastal (F&C) research program. It is designed to provide a library of sediment flux formulations for hydraulic and hydrologic models, such as GSSHA. This new version of GSSHA, with the updated in-stream sediment transport simulation capability afforded by the linkage to SEDLIB, was tested in against observations in an experimental watershed that had previously been used as a test bed for GSSHA. The results show a significant improvement in the ability to model in-stream sources of fine sediment. This improved capability will broaden the applicability of GSSHA to larger watersheds and watersheds with complex sediment dynamics, such as those subjected to fire hydrology.
The impacts of precipitation amount simulation on hydrological modeling in Nordic watersheds

NASA Astrophysics Data System (ADS)

Li, Zhi; Brissette, Fancois; Chen, Jie

2013-04-01

Stochastic modeling of daily precipitation is very important for hydrological modeling, especially when no observed data are available. Precipitation is usually modeled by two component model: occurrence generation and amount simulation. For occurrence simulation, the most common method is the first-order two-state Markov chain due to its simplification and good performance. However, various probability distributions have been reported to simulate precipitation amount, and spatiotemporal differences exist in the applicability of different distribution models. Therefore, assessing the applicability of different distribution models is necessary in order to provide more accurate precipitation information. Six precipitation probability distributions (exponential, Gamma, Weibull, skewed normal, mixed exponential, and hybrid exponential/Pareto distributions) are directly and indirectly evaluated on their ability to reproduce the original observed time series of precipitation amount. Data from 24 weather stations and two watersheds (Chute-du-Diable and Yamaska watersheds) in the province of Quebec (Canada) are used for this assessment. Various indices or statistics, such as the mean, variance, frequency distribution and extreme values are used to quantify the performance in simulating the precipitation and discharge. Performance in reproducing key statistics of the precipitation time series is well correlated to the number of parameters of the distribution function, and the three-parameter precipitation models outperform the other models, with the mixed exponential distribution being the best at simulating daily precipitation. The advantage of using more complex precipitation distributions is not as clear-cut when the simulated time series are used to drive a hydrological model. While the advantage of using functions with more parameters is not nearly as obvious, the mixed exponential distribution appears nonetheless as the best candidate for hydrological modeling. The implications of choosing a distribution function with respect to hydrological modeling and climate change impact studies are also discussed.
Towards a Dynamic Digital Observatory: Synthesizing Community Data and Model Development in the Susquehanna River Basin and Chesapeake Bay

NASA Astrophysics Data System (ADS)

Dressler, K. A.; Piasecki, M.; Bhatt, G.; Duffy, C. J.; Reed, P. M.

2007-12-01

Physically-based fully-distributed hydrologic models simulate hydrologic state variables spatiotemporally using information on forcing (climate) and landscape (topography, land use, hydrogeology) heterogeneities. Incorporating physical data layers in the hydrologic model requires intensive data development. Traditionally, GIS has been used for data management, data analysis and visualization; however, proprietary data structures, platform dependence, isolated data model and non-dynamic data-interaction with pluggable software components of existing GIS frameworks, makes it restrictive to perform sophisticated numerical modeling. In this effort we present a "tightly-coupled" GIS interface to Penn State Integrated Hydrologic Model (PIHM; www.pihm.psu.edu) called PIHMgis which is open source, platform independent and extensible. The tight coupling between GIS and the model is achieved by developing a shared data-model and hydrologic-model data structure. Domain discretization is fundamental to the approach and an unstructured triangular irregular network (e.g. Delaunay triangles) is generated with both geometric and parametric constraints. A local prismatic control volume is formed by vertical projection of the Delaunay triangles forming each layer of the model. Given a set of constraints (e.g. river network support, watershed boundary, altitude zones, ecological regions, hydraulic properties, climate zones, etc), an "optimal" mesh is generated. Time variant forcing for the model is typically derived from time series data available at points that are transferred onto a grid. Therefore, the modeling environment can use the Observations Database model developed by the Hydrologic Information Systems group of the Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. (CUAHSI). As part of a initial testbed series the database has been implemented in support for the Susquehanna and Chesapeake Bay watersheds and is now being populated by national (USGS-NWIS; EPA- STORET), regional (Chesapeake Information Management System, CIMS; National Air Deposition Program, NADP), and local (RTH-Net, Burd Run) datasets. The data can be searched side by side in a one-stop-querying- center, www.hydroseek.org , another application developed as part of the CUAHSI HIS effort. The ultimate goal is to populate the observations database with as many catalogues (i.e. collections of information on what data sources contain) as possible including the build out of the local data sources, i.e. the Susquehanna River Basin Hydrologic Observatory System (SRBHOS) time series server.
A two-step sensitivity analysis for hydrological signatures in Jinhua River Basin, East China

NASA Astrophysics Data System (ADS)

Pan, S.; Fu, G.; Chiang, Y. M.; Xu, Y. P.

2016-12-01

Owing to model complexity and large number of parameters, calibration and sensitivity analysis are difficult processes for distributed hydrological models. In this study, a two-step sensitivity analysis approach is proposed for analyzing the hydrological signatures in Jinhua River Basin, East China, using the Distributed Hydrology-Soil-Vegetation Model (DHSVM). A rough sensitivity analysis is firstly conducted to obtain preliminary influential parameters via Analysis of Variance. The number of parameters was greatly reduced from eighteen-three to sixteen. Afterwards, the sixteen parameters are further analyzed based on a variance-based global sensitivity analysis, i.e., Sobol's sensitivity analysis method, to achieve robust sensitivity rankings and parameter contributions. Parallel-Computing is applied to reduce computational burden in variance-based sensitivity analysis. The results reveal that only a few number of model parameters are significantly sensitive, including rain LAI multiplier, lateral conductivity, porosity, field capacity, wilting point of clay loam, understory monthly LAI, understory minimum resistance and root zone depths of croplands. Finally several hydrological signatures are used for investigating the performance of DHSVM. Results show that high value of efficiency criteria didn't indicate excellent performance of hydrological signatures. For most samples from Sobol's sensitivity analysis, water yield was simulated very well. However, lowest and maximum annual daily runoffs were underestimated. Most of seven-day minimum runoffs were overestimated. Nevertheless, good performances of the three signatures above still exist in a number of samples. Analysis of peak flow shows that small and medium floods are simulated perfectly while slight underestimations happen to large floods. The work in this study helps to further multi-objective calibration of DHSVM model and indicates where to improve the reliability and credibility of model simulation.
A Cyber Enabled Collaborative Environment for Creating, Sharing and Using Data and Modeling Driven Curriculum Modules for Hydrology Education

NASA Astrophysics Data System (ADS)

Merwade, V.; Ruddell, B. L.; Fox, S.; Iverson, E. A. R.

2014-12-01

With the access to emerging datasets and computational tools, there is a need to bring these capabilities into hydrology classrooms. However, developing curriculum modules using data and models to augment classroom teaching is hindered by a steep technology learning curve, rapid technology turnover, and lack of an organized community cyberinfrastructure (CI) for the dissemination, publication, and sharing of the latest tools and curriculum material for hydrology and geoscience education. The objective of this project is to overcome some of these limitations by developing a cyber enabled collaborative environment for publishing, sharing and adoption of data and modeling driven curriculum modules in hydrology and geosciences classroom. The CI is based on Carleton College's Science Education Resource Center (SERC) Content Management System. Building on its existing community authoring capabilities the system is being extended to allow assembly of new teaching activities by drawing on a collection of interchangeable building blocks; each of which represents a step in the modeling process. Currently the system hosts more than 30 modules or steps, which can be combined to create multiple learning units. Two specific units: Unit Hydrograph and Rational Method, have been used in undergraduate hydrology class-rooms at Purdue University and Arizona State University. The structure of the CI and the lessons learned from its implementation, including preliminary results from student assessments of learning will be presented.
Assessing the impacts of climate change in Mediterranean catchments under conditions of data scarcity - The Gaza case study

NASA Astrophysics Data System (ADS)

Gampe, David; Ludwig, Ralf

2013-04-01

According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. While there is scientific consensus that climate induced changes on the hydrology of Mediterranean regions are presently occurring and are projected to amplify in the future, very little knowledge is available about the quantification of these changes, which is hampered by a lack of suitable and cost effective hydrological monitoring and modeling systems. The European FP7-project CLIMB is aiming to analyze climate induced changes on the hydrology of the Mediterranean Basins by investigating seven test sites located in the countries Italy, France, Turkey, Tunisia, Gaza and Egypt. CLIMB employs a combination of novel geophysical field monitoring concepts, remote sensing techniques and integrated hydrologic modeling to improve process descriptions and understanding and to quantify existing uncertainties in climate change impact analysis. One of those seven sites is the Gaza Strip, located in the Eastern Mediterranean and part of the Palestinian Autonomous Area, covers an area of 365km² with a length of 35km and 6 to 12km in width. Elevation ranges from sea level up to 104m in the East of the test site. Mean annual precipitation varies from 235mm in the South to 420mm in the North of the area. The inter annual variability of rainfall and the rapid population growth in an highly agricultural used area represent the major challenges in this area. The physically based Water Simulation Model WaSiM Vers. 2 (Schulla & Jasper (1999)) is setup to model current and projected future hydrological conditions. The availability of measured meteorological and hydrological data is poor as common to many Mediterranean catchments. The lack of available measured input data hampers the calibration of the model setup and the validation of model outputs. WaSiM was driven with meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. State of the art remote sensing techniques and field measuring techniques were applied to improve the quality of hydrological input parameters. For the parameterization of the vegetation the Leaf Area Index (LAI) is a crucial component. However, the LAI is difficult to access at field scale, hence a simple remote sensing approach, using the Normalized Difference Vegetation Index (NDVI) and MODIS LAI information, was applied for the parameterization in WaSiM. As no permanent streams, hence no discharge measurements, exist in the Gaza Strip, the actual evapotranspiration (ETact) outputs of the model were used for model validation. Landsat TM images were applied to calculate the actual monthly mean ETact rates using the triangle method (Jiang and Islam, 1999). Simulated spatial ETact patterns and those derived from remote sensing show a good fit especially for the growing season.
Hydrologic cost-effectiveness ratio favors switchgrass production on marginal croplands over existing grasslands

PubMed Central

Yimam, Yohannes Tadesse; Ochsner, Tyson E.; Fox, Garey A.

2017-01-01

Switchgrass (Panicum virgatum L.) has attracted attention as a promising second generation biofuel feedstock. Both existing grasslands and marginal croplands have been suggested as targets for conversion to switchgrass, but the resulting production potentials and hydrologic impacts are not clear. The objectives of this study were to model switchgrass production on existing grasslands (scenario-I) and on marginal croplands that have severe to very severe limitations for crop production (scenario-II) and to evaluate the effects on evapotranspiration (ET) and streamflow. The Soil and Water Assessment Tool (SWAT) was applied to the 1063 km2 Skeleton Creek watershed in north-central Oklahoma, a watershed dominated by grasslands (35%) and winter wheat cropland (47%). The simulated average annual yield (2002–2011) for rainfed Alamo switchgrass for both scenarios was 12 Mg ha-1. Yield varied spatially under scenario-I from 6.1 to 15.3 Mg ha-1, while under scenario-II the range was from 8.2 to 13.8 Mg ha-1. Comparison of average annual ET and streamflow between the baseline simulation (existing land use) and scenario-I showed that scenario-I had 5.6% (37 mm) higher average annual ET and 27.7% lower streamflow, representing a 40.7 million m3 yr-1 streamflow reduction. Compared to the baseline, scenario-II had only 0.5% higher ET and 3.2% lower streamflow, but some monthly impacts were larger. In this watershed, the water yield reduction per ton of biomass production (i.e. hydrologic cost-effectiveness ratio) was more than 5X greater under scenario-I than under scenario-II. These results suggest that, from a hydrologic perspective, it may be preferable to convert marginal cropland to switchgrass production rather than converting existing grasslands. PMID:28792541
Hydrologic cost-effectiveness ratio favors switchgrass production on marginal croplands over existing grasslands.

PubMed

Yimam, Yohannes Tadesse; Ochsner, Tyson E; Fox, Garey A

2017-01-01

Switchgrass (Panicum virgatum L.) has attracted attention as a promising second generation biofuel feedstock. Both existing grasslands and marginal croplands have been suggested as targets for conversion to switchgrass, but the resulting production potentials and hydrologic impacts are not clear. The objectives of this study were to model switchgrass production on existing grasslands (scenario-I) and on marginal croplands that have severe to very severe limitations for crop production (scenario-II) and to evaluate the effects on evapotranspiration (ET) and streamflow. The Soil and Water Assessment Tool (SWAT) was applied to the 1063 km2 Skeleton Creek watershed in north-central Oklahoma, a watershed dominated by grasslands (35%) and winter wheat cropland (47%). The simulated average annual yield (2002-2011) for rainfed Alamo switchgrass for both scenarios was 12 Mg ha-1. Yield varied spatially under scenario-I from 6.1 to 15.3 Mg ha-1, while under scenario-II the range was from 8.2 to 13.8 Mg ha-1. Comparison of average annual ET and streamflow between the baseline simulation (existing land use) and scenario-I showed that scenario-I had 5.6% (37 mm) higher average annual ET and 27.7% lower streamflow, representing a 40.7 million m3 yr-1 streamflow reduction. Compared to the baseline, scenario-II had only 0.5% higher ET and 3.2% lower streamflow, but some monthly impacts were larger. In this watershed, the water yield reduction per ton of biomass production (i.e. hydrologic cost-effectiveness ratio) was more than 5X greater under scenario-I than under scenario-II. These results suggest that, from a hydrologic perspective, it may be preferable to convert marginal cropland to switchgrass production rather than converting existing grasslands.
A new framework for modeling decentralized low impact developments using Soil and Water Assessment Tool

USDA-ARS?s Scientific Manuscript database

Assessing the performance of Low Impact Development (LID) practices at a catchment scale is important in managing urban watersheds. Few modeling tools exist that are capable of explicitly representing the hydrological mechanisms of LIDs while considering the diverse land uses of urban watersheds. ...
Geospatial Data Standards for Indian Water Resources Systems

NASA Astrophysics Data System (ADS)

Goyal, A.; Tyagi, H.; Gosain, A. K.; Khosa, R.

2016-12-01

Sustainable management of water resources is fundamental to the socio-economic development of any nation. There is an increasing degree of dependency on digital geographical data for monitoring, planning, managing and preserving the water resources and environmental quality. But the rising sophistication associated with the sharing of geospatial data among organizations or users, demands development of data standards for seamless information exchange among collaborators. Therefore, due to the realization that these datasets are vital for efficient use of Geographical Information Systems, there is a growing emphasis on data standards for modeling, encoding and communicating spatial data. Real world hydrologic interactions represented in a digital framework requires geospatial standards that may vary in contexts like: governance, resource inventory, cultural diversity, identifiers, role and scale. Though the prevalent standards for the hydrology data facilitate a particular need in a particular context but they lack a holistic approach. However, several worldwide initiatives such as Consortium for the Advancement of Hydrologic Sciences Inc. (USA), Infrastructure for Spatial Information in the European Community (Europe), Australian Water Resources Information System, etc., endeavour to address this issue of hydrology specific spatial data standards in a wholesome manner. But unfortunately there is no such provision for hydrology data exchange within the Indian community. Moreover, these standards somehow fail in providing powerful communication of the spatial hydrologic data. This study thus investigates the shortcomings of the existing industry standards for the hydrologic data models and then demonstrates a set of requirements for effective exchange of the hydrologic information in the Indian scenario.
OpenFLUID: an open-source software environment for modelling fluxes in landscapes

NASA Astrophysics Data System (ADS)

Fabre, Jean-Christophe; Rabotin, Michaël; Crevoisier, David; Libres, Aline; Dagès, Cécile; Moussa, Roger; Lagacherie, Philippe; Raclot, Damien; Voltz, Marc

2013-04-01

Integrative landscape functioning has become a common concept in environmental management. Landscapes are complex systems where many processes interact in time and space. In agro-ecosystems, these processes are mainly physical processes, including hydrological-processes, biological processes and human activities. Modelling such systems requires an interdisciplinary approach, coupling models coming from different disciplines, developed by different teams. In order to support collaborative works, involving many models coupled in time and space for integrative simulations, an open software modelling platform is a relevant answer. OpenFLUID is an open source software platform for modelling landscape functioning, mainly focused on spatial fluxes. It provides an advanced object-oriented architecture allowing to i) couple models developed de novo or from existing source code, and which are dynamically plugged to the platform, ii) represent landscapes as hierarchical graphs, taking into account multi-scale, spatial heterogeneities and landscape objects connectivity, iii) run and explore simulations in many ways : using the OpenFLUID software interfaces for users (command line interface, graphical user interface), or using external applications such as GNU R through the provided ROpenFLUID package. OpenFLUID is developed in C++ and relies on open source libraries only (Boost, libXML2, GLib/GTK, OGR/GDAL, …). For modelers and developers, OpenFLUID provides a dedicated environment for model development, which is based on an open source toolchain, including the Eclipse editor, the GCC compiler and the CMake build system. OpenFLUID is distributed under the GPLv3 open source license, with a special exception allowing to plug existing models licensed under any license. It is clearly in the spirit of sharing knowledge and favouring collaboration in a community of modelers. OpenFLUID has been involved in many research applications, such as modelling of hydrological network transfer, diagnosis and prediction of water quality taking into account human activities, study of the effect of spatial organization on hydrological fluxes, modelling of surface-subsurface water exchanges, … At LISAH research unit, OpenFLUID is the supporting development platform of the MHYDAS model, which is a distributed model for agrosystems (Moussa et al., 2002, Hydrological Processes, 16, 393-412). OpenFLUID web site : http://www.openfluid-project.org
Real Time Land-Surface Hydrologic Modeling Over Continental US

NASA Technical Reports Server (NTRS)

Houser, Paul R.

1998-01-01

The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.
Modular GIS Framework for National Scale Hydrologic and Hydraulic Modeling Support

NASA Astrophysics Data System (ADS)

Djokic, D.; Noman, N.; Kopp, S.

2015-12-01

Geographic information systems (GIS) have been extensively used for pre- and post-processing of hydrologic and hydraulic models at multiple scales. An extensible GIS-based framework was developed for characterization of drainage systems (stream networks, catchments, floodplain characteristics) and model integration. The framework is implemented as a set of free, open source, Python tools and builds on core ArcGIS functionality and uses geoprocessing capabilities to ensure extensibility. Utilization of COTS GIS core capabilities allows immediate use of model results in a variety of existing online applications and integration with other data sources and applications.The poster presents the use of this framework to downscale global hydrologic models to local hydraulic scale and post process the hydraulic modeling results and generate floodplains at any local resolution. Flow forecasts from ECMWF or WRF-Hydro are downscaled and combined with other ancillary data for input into the RAPID flood routing model. RAPID model results (stream flow along each reach) are ingested into a GIS-based scale dependent stream network database for efficient flow utilization and visualization over space and time. Once the flows are known at localized reaches, the tools can be used to derive the floodplain depth and extent for each time step in the forecast at any available local resolution. If existing rating curves are available they can be used to relate the flow to the depth of flooding, or synthetic rating curves can be derived using the tools in the toolkit and some ancillary data/assumptions. The results can be published as time-enabled spatial services to be consumed by web applications that use floodplain information as an input. Some of the existing online presentation templates can be easily combined with available online demographic and infrastructure data to present the impact of the potential floods on the local community through simple, end user products. This framework has been successfully used in both the data rich environments as well as in locales with minimum available spatial and hydrographic data.
The framework of a UAS-aided flash flood modeling system for coastal regions

NASA Astrophysics Data System (ADS)

Zhang, H.; Xu, H.

2016-02-01

Flash floods cause severe economic damage and are one of the leading causes of fatalities connected with natural disasters in the Gulf Coast region. Current flash flood modeling systems rely on empirical hydrological models driven by precipitation estimates only. Although precipitation is the driving factor for flash floods, soil moisture, urban drainage system and impervious surface have been recognized to have significant impacts on the development of flash floods. We propose a new flash flooding modeling system that integrates 3-D hydrological simulation with satellite and multi-UAS observations. It will have three advantages over existing modeling systems. First, it will incorporate 1-km soil moisture data through integrating satellite images from European SMOS mission and NASA's SMAP mission. The utilization of high-resolution satellite images will provide essential information to determine antecedent soil moisture condition, which is an essential control on flood generation. Second, this system is able to adjust flood forecasting based on real-time inundation information collected by multi-UAS. A group of UAS will be deployed during storm events to capture the changing extent of flooded areas and water depth at multiple critical locations simultaneously. Such information will be transmitted to a hydrological model to validate and improve flood simulation. Third, the backbone of this system is a state-of-the-art 3-D hydrological model that assimilates the hydrological information from satellites and multi-UAS. The model is able to address surface water-groundwater interactions and reflect the effects of various infrastructures. Using Web-GIS technologies, the modeling results will be available online as interactive flood maps accessible to the public. To support the development and verification of this modeling system, surface and subsurface hydrological observations will be conducted in a number of small watersheds in the Coastal Bend region. We envision this system will provide an innovative means to benefit the forecasting, evaluation and mitigation of flash floods in costal regions.

How will climate change affect watershed mercury export in a representative Coastal Plain watershed?

NASA Astrophysics Data System (ADS)

Golden, H. E.; Knightes, C. D.; Conrads, P. A.; Feaster, T.; Davis, G. M.; Benedict, S. T.; Bradley, P. M.

2012-12-01

Future climate change is expected to drive variations in watershed hydrological processes and water quality across a wide range of physiographic provinces, ecosystems, and spatial scales. How such shifts in climatic conditions will impact watershed mercury (Hg) dynamics and hydrologically-driven Hg transport is a significant concern. We simulate the responses of watershed hydrological and total Hg (HgT) fluxes and concentrations to a unified set of past and future climate change projections in a Coastal Plain basin using multiple watershed models. We use two statistically downscaled global precipitation and temperature models, ECHO, a hybrid of the ECHAM4 and HOPE-G models, and the Community Climate System Model (CCSM3) across two thirty-year simulations (1980 to 2010 and 2040 to 2070). We apply three watershed models to quantify and bracket potential changes in hydrologic and HgT fluxes, including the Visualizing Ecosystems for Land Management Assessment Model for Hg (VELMA-Hg), the Grid Based Mercury Model (GBMM), and TOPLOAD, a water quality constituent model linked to TOPMODEL hydrological simulations. We estimate a decrease in average annual HgT fluxes in response to climate change using the ECHO projections and an increase with the CCSM3 projections in the study watershed. Average monthly HgT fluxes increase using both climate change projections between in the late spring (March through May), when HgT concentrations and flow are high. Results suggest that hydrological transport associated with changes in precipitation and temperature is the primary mechanism driving HgT flux response to climate change. Our multiple model/multiple projection approach allows us to bracket the relative response of HgT fluxes to climate change, thereby illustrating the uncertainty associated with the projections. In addition, our approach allows us to examine potential variations in climate change-driven water and HgT export based on different conceptualizations of watershed HgT dynamics and the representative mathematical structures underpinning existing watershed Hg models.
Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty: STRUCTURAL UNCERTAINTY DIAGNOSTICS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2016-04-01

In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integratemore » expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.« less
A priori discretization error metrics for distributed hydrologic modeling applications

NASA Astrophysics Data System (ADS)

Liu, Hongli; Tolson, Bryan A.; Craig, James R.; Shafii, Mahyar

2016-12-01

Watershed spatial discretization is an important step in developing a distributed hydrologic model. A key difficulty in the spatial discretization process is maintaining a balance between the aggregation-induced information loss and the increase in computational burden caused by the inclusion of additional computational units. Objective identification of an appropriate discretization scheme still remains a challenge, in part because of the lack of quantitative measures for assessing discretization quality, particularly prior to simulation. This study proposes a priori discretization error metrics to quantify the information loss of any candidate discretization scheme without having to run and calibrate a hydrologic model. These error metrics are applicable to multi-variable and multi-site discretization evaluation and provide directly interpretable information to the hydrologic modeler about discretization quality. The first metric, a subbasin error metric, quantifies the routing information loss from discretization, and the second, a hydrological response unit (HRU) error metric, improves upon existing a priori metrics by quantifying the information loss due to changes in land cover or soil type property aggregation. The metrics are straightforward to understand and easy to recode. Informed by the error metrics, a two-step discretization decision-making approach is proposed with the advantage of reducing extreme errors and meeting the user-specified discretization error targets. The metrics and decision-making approach are applied to the discretization of the Grand River watershed in Ontario, Canada. Results show that information loss increases as discretization gets coarser. Moreover, results help to explain the modeling difficulties associated with smaller upstream subbasins since the worst discretization errors and highest error variability appear in smaller upstream areas instead of larger downstream drainage areas. Hydrologic modeling experiments under candidate discretization schemes validate the strong correlation between the proposed discretization error metrics and hydrologic simulation responses. Discretization decision-making results show that the common and convenient approach of making uniform discretization decisions across the watershed performs worse than the proposed non-uniform discretization approach in terms of preserving spatial heterogeneity under the same computational cost.
The origin of high and low flows in the river Rhine: particle tracing and water quality calculations in a distributed hydrological model

NASA Astrophysics Data System (ADS)

Schellekens, Jaap; van Gils, Jos; Christophe, Christophe; Sperna-Weiland, Frederiek; Winsemius, Hessel

2013-04-01

The ability to quickly link a complete water quality model to any distributed hydrological model can be of great value. It provides the hydrological modeller with more information on the performance of the model by being able to add particle tracing and independent mass balance calculations to an existing distributed hydrological model. It also allows for full catchment water quality calculations forced by emissions to different hydrological compartments, taking into account the relevant processes in the different compartments of the hydrological model. A combined distributed hydrological model and hydrochemical model (Delwaq) have been combined within the modeling framework OpenStreams to model large scale hydrological processes in the Rhine basin upstream of the Dutch border at Lobith. Several models have been setup to evaluate (1) the origin of high and low flows in the Rhine basin based on subcatchment contribution and (2) the contribution of different land covers to the total flow with special reference to urban land cover. In addition (3) the relative share of fast and slow runoff components in the total river discharge has been quantified, as well as the age of these two fractions, both as a function of time. Finally (4) the transmission of a pollutant released in infiltrating water and undergoing sorption has been simulated, as a first test for implementing full water quality modelling. The results of a thirty-five year run using daily time steps for 1975 to 2010 were analysed for monthly average contribution to the total flow of each subcatchment and the different land cover types both for average flow conditions and for the top ten and bottom ten flow percentiles. Furthermore, a number of high and low flow events have been analysed in detail. They reveal the large contribution of the basin area upstream of Basel to the dry season flow, especially during the driest summers. Flood conditions in the basin have a more varied origin with the Moselle being the main contributor. The amount of urban land cover (6.7%) generated a fairly large amount of (quick) runoff. In times up to 21 % of the flow at Lobith is generated in urban areas. The location of urban areas (in general close to the river) in combination with the associated impermeable surfaces most probably cause the relatively large contribution of urban areas. The fast runoff fraction at Lobith has an average age between 5 and 25 days, depending on the hydrology within the year, while the slow runoff fraction shows an average age between 300 and 600 days, again depending on the hydrology within the year. The time needed to flush out 90% of the total volume of water from the basin is about 20 years.
Modeling the effect of glacier recession on streamflow response using a coupled glacio-hydrological model

DOE PAGES

Frans, Chris D.; Clarke, Garry K. C.; Burns, P.; ...

2014-02-27

Here, we describe an integrated spatially distributed hydrologic and glacier dynamic model, and use it to investigate the effect of glacier recession on streamflow variations for the Upper Bow River basin, a tributary of the South Saskatchewan River. Several recent studies have suggested that observed decreases in summer flows in the South Saskatchewan River are partly due to the retreat of glaciers in the river's headwaters. Modeling the effect of glacier changes on streamflow response in river basins such as the South Saskatchewan is complicated due to the inability of most existing physically-based distributed hydrologic models to represent glacier dynamics.more » We compare predicted variations in glacier extent, snow water equivalent and streamflow discharge made with the integrated model with satellite estimates of glacier area and terminus position, observed streamflow and snow water equivalent measurements over the period of 1980 2007. Simulations with the coupled hydrology-glacier model reduce the uncertainty in streamflow predictions. Our results suggested that on average, the glacier melt contribution to the Bow River flow upstream of Lake Louise is about 30% in summer. For warm and dry years, however, the glacier melt contribution can be as large as 50% in August, whereas for cold years, it can be as small as 20% and the timing of glacier melt signature can be delayed by a month.« less
Estimates of natural salinity and hydrology in a subtropical estuarine ecosystem: implications for Greater Everglades restoration

USGS Publications Warehouse

Marshall, Frank E.; Wingard, G. Lynn; Pitts, Patrick A.

2014-01-01

Disruption of the natural patterns of freshwater flow into estuarine ecosystems occurred in many locations around the world beginning in the twentieth century. To effectively restore these systems, establishing a pre-alteration perspective allows managers to develop science-based restoration targets for salinity and hydrology. This paper describes a process to develop targets based on natural hydrologic functions by coupling paleoecology and regression models using the subtropical Greater Everglades Ecosystem as an example. Paleoecological investigations characterize the circa 1900 CE (pre-alteration) salinity regime in Florida Bay based on molluscan remains in sediment cores. These paleosalinity estimates are converted into time series estimates of paleo-based salinity, stage, and flow using numeric and statistical models. Model outputs are weighted using the mean square error statistic and then combined. Results indicate that, in the absence of water management, salinity in Florida Bay would be about 3 to 9 salinity units lower than current conditions. To achieve this target, upstream freshwater levels must be about 0.25 m higher than indicated by recent observed data, with increased flow inputs to Florida Bay between 2.1 and 3.7 times existing flows. This flow deficit is comparable to the average volume of water currently being diverted from the Everglades ecosystem by water management. The products (paleo-based Florida Bay salinity and upstream hydrology) provide estimates of pre-alteration hydrology and salinity that represent target restoration conditions. This method can be applied to any estuarine ecosystem with available paleoecologic data and empirical and/or model-based hydrologic data.
Integrated hydrologic modeling of a transboundary aquifer system —Lower Rio Grande

USGS Publications Warehouse

Hanson, Randall T.; Schmid, Wolfgang; Knight, Jacob E.; Maddock, Thomas

2013-01-01

For more than 30 years the agreements developed for the aquifer systems of the lower Rio Grande and related river compacts of the Rio Grande River have evolved into a complex setting of transboundary conjunctive use. The conjunctive use now includes many facets of water rights, water use, and emerging demands between the states of New Mexico and Texas, the United States and Mexico, and various water-supply agencies. The analysis of the complex relations between irrigation and streamflow supplyand-demand components and the effects of surface-water and groundwater use requires an integrated hydrologic model to track all of the use and movement of water. MODFLOW with the Farm Process (MFFMP) provides the integrated approach needed to assess the stream-aquifer interactions that are dynamically affected by irrigation demands on streamflow allotments that are supplemented with groundwater pumpage. As a first step to the ongoing full implementation of MF-FMP by the USGS, the existing model (LRG_2007) was modified to include some FMP features, demonstrating the ability to simulate the existing streamflow-diversion relations known as the D2 and D3 curves, departure of downstream deliveries from these curves during low allocation years and with increasing efficiency upstream, and the dynamic relation between surface-water conveyance and estimates of pumpage and recharge. This new MF-FMP modeling framework can now internally analyze complex relations within the Lower Rio Grande Hydrologic Model (LRGHM_2011) that previous techniques had limited ability to assess.
Monitoring Precipitation from Space: targeting Hydrology Community?

NASA Astrophysics Data System (ADS)

Hong, Y.; Turk, J.

2005-12-01

During the past decades, advances in space, sensor and computer technology have made it possible to estimate precipitation nearly globally from a variety of observations in a relatively direct manner. The success of Tropical Precipitation Measuring Mission (TRMM) has been a significant advance for modern precipitation estimation algorithms to move toward daily quarter degree measurements, while the need for precipitation data at temporal-spatial resolutions compatible with hydrologic modeling has been emphasized by the end user: hydrology community. Can the future deployment of Global Precipitation Measurement constellation of low-altitude orbiting satellites (covering 90% of the global with a sampling interval of less than 3-hours), in conjunction with the existing suite of geostationary satellites, results in significant improvements in scale and accuracy of precipitation estimates suitable for hydrology applications? This presentation will review the current state of satellite-derived precipitation estimation and demonstrate the early results and primary barriers to full global high-resolution precipitation coverage. An attempt to facilitate the communication between data producers and users will be discussed by developing an 'end-to-end' uncertainty propagation analysis framework to quantify both the precipitation estimation error structure and the error influence on hydrological modeling.
Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models

USGS Publications Warehouse

Clark, Martyn P.; Slater, Andrew G.; Rupp, David E.; Woods, Ross A.; Vrugt, Jasper A.; Gupta, Hoshin V.; Wagener, Thorsten; Hay, Lauren E.

2008-01-01

The problems of identifying the most appropriate model structure for a given problem and quantifying the uncertainty in model structure remain outstanding research challenges for the discipline of hydrology. Progress on these problems requires understanding of the nature of differences between models. This paper presents a methodology to diagnose differences in hydrological model structures: the Framework for Understanding Structural Errors (FUSE). FUSE was used to construct 79 unique model structures by combining components of 4 existing hydrological models. These new models were used to simulate streamflow in two of the basins used in the Model Parameter Estimation Experiment (MOPEX): the Guadalupe River (Texas) and the French Broad River (North Carolina). Results show that the new models produced simulations of streamflow that were at least as good as the simulations produced by the models that participated in the MOPEX experiment. Our initial application of the FUSE method for the Guadalupe River exposed relationships between model structure and model performance, suggesting that the choice of model structure is just as important as the choice of model parameters. However, further work is needed to evaluate model simulations using multiple criteria to diagnose the relative importance of model structural differences in various climate regimes and to assess the amount of independent information in each of the models. This work will be crucial to both identifying the most appropriate model structure for a given problem and quantifying the uncertainty in model structure. To facilitate research on these problems, the FORTRAN‐90 source code for FUSE is available upon request from the lead author.
A model for seasonal changes in GPS positions and seismic wave speeds due to thermoelastic and hydrologic variations

USGS Publications Warehouse

Tsai, V.C.

2011-01-01

It is known that GPS time series contain a seasonal variation that is not due to tectonic motions, and it has recently been shown that crustal seismic velocities may also vary seasonally. In order to explain these changes, a number of hypotheses have been given, among which thermoelastic and hydrology-induced stresses and strains are leading candidates. Unfortunately, though, since a general framework does not exist for understanding such seasonal variations, it is currently not possible to quickly evaluate the plausibility of these hypotheses. To fill this gap in the literature, I generalize a two-dimensional thermoelastic strain model to provide an analytic solution for the displacements and wave speed changes due to either thermoelastic stresses or hydrologic loading, which consists of poroelastic stresses and purely elastic stresses. The thermoelastic model assumes a periodic surface temperature, and the hydrologic models similarly assume a periodic near-surface water load. Since all three models are two-dimensional and periodic, they are expected to only approximate any realistic scenario; but the models nonetheless provide a quantitative framework for estimating the effects of thermoelastic and hydrologic variations. Quantitative comparison between the models and observations is further complicated by the large uncertainty in some of the relevant parameters. Despite this uncertainty, though, I find that maximum realistic thermoelastic effects are unlikely to explain a large fraction of the observed annual variation in a typical GPS displacement time series or of the observed annual variations in seismic wave speeds in southern California. Hydrologic loading, on the other hand, may be able to explain a larger fraction of both the annual variations in displacements and seismic wave speeds. Neither model is likely to explain all of the seismic wave speed variations inferred from observations. However, more definitive conclusions cannot be made until the model parameters are better constrained. Copyright ?? 2011 by the American Geophysical Union.
StreamFlow 1.0: an extension to the spatially distributed snow model Alpine3D for hydrological modelling and deterministic stream temperature prediction

NASA Astrophysics Data System (ADS)

Gallice, Aurélien; Bavay, Mathias; Brauchli, Tristan; Comola, Francesco; Lehning, Michael; Huwald, Hendrik

2016-12-01

Climate change is expected to strongly impact the hydrological and thermal regimes of Alpine rivers within the coming decades. In this context, the development of hydrological models accounting for the specific dynamics of Alpine catchments appears as one of the promising approaches to reduce our uncertainty of future mountain hydrology. This paper describes the improvements brought to StreamFlow, an existing model for hydrological and stream temperature prediction built as an external extension to the physically based snow model Alpine3D. StreamFlow's source code has been entirely written anew, taking advantage of object-oriented programming to significantly improve its structure and ease the implementation of future developments. The source code is now publicly available online, along with a complete documentation. A special emphasis has been put on modularity during the re-implementation of StreamFlow, so that many model aspects can be represented using different alternatives. For example, several options are now available to model the advection of water within the stream. This allows for an easy and fast comparison between different approaches and helps in defining more reliable uncertainty estimates of the model forecasts. In particular, a case study in a Swiss Alpine catchment reveals that the stream temperature predictions are particularly sensitive to the approach used to model the temperature of subsurface flow, a fact which has been poorly reported in the literature to date. Based on the case study, StreamFlow is shown to reproduce hourly mean discharge with a Nash-Sutcliffe efficiency (NSE) of 0.82 and hourly mean temperature with a NSE of 0.78.
Development of a Sediment Transport Component for DHSVM

NASA Astrophysics Data System (ADS)

Doten, C. O.; Bowling, L. C.; Maurer, E. P.; Voisin, N.; Lettenmaier, D. P.

2003-12-01

The effect of forest management and disturbance on aquatic resources is a problem of considerable, contemporary, scientific and public concern in the West. Sediment generation is one of the factors linking land surface conditions with aquatic systems, with implications for fisheries protection and enhancement. Better predictive techniques that allow assessment of the effects of fire and logging, in particular, on sediment transport could help to provide a more scientific basis for the management of forests in the West. We describe the development of a sediment transport component for the Distributed Hydrology Soil Vegetation Model (DHSVM), a spatially distributed hydrologic model that was developed specifically for assessment of the hydrologic consequences of forest management. The sediment transport module extends the hydrologic dynamics of DHSVM to predict sediment generation in response to dynamic meteorological inputs and hydrologic conditions via mass wasting and surface erosion from forest roads and hillslopes. The mass wasting component builds on existing stochastic slope stability models, by incorporating distributed basin hydrology (from DHSVM), and post-failure, rule-based redistribution of sediment downslope. The stochastic nature of the mass wasting component allows specification of probability distributions that describe the spatial variability of soil and vegetation characteristics used in the infinite slope model. The forest roads and hillslope surface erosion algorithms account for erosion from rain drop impact and overland erosion. A simple routing scheme is used to transport eroded sediment from mass wasting and forest roads surface erosion that reaches the channel system to the basin outlet. A sensitivity analysis of the model input parameters and forest cover conditions is described for the Little Wenatchee River basin in the northeastern Washington Cascades.
An Integrated Ensemble-Based Operational Framework to Predict Urban Flooding: A Case Study of Hurricane Sandy in the Passaic and Hackensack River Basins

NASA Astrophysics Data System (ADS)

Saleh, F.; Ramaswamy, V.; Georgas, N.; Blumberg, A. F.; Wang, Y.

2016-12-01

Advances in computational resources and modeling techniques are opening the path to effectively integrate existing complex models. In the context of flood prediction, recent extreme events have demonstrated the importance of integrating components of the hydrosystem to better represent the interactions amongst different physical processes and phenomena. As such, there is a pressing need to develop holistic and cross-disciplinary modeling frameworks that effectively integrate existing models and better represent the operative dynamics. This work presents a novel Hydrologic-Hydraulic-Hydrodynamic Ensemble (H3E) flood prediction framework that operationally integrates existing predictive models representing coastal (New York Harbor Observing and Prediction System, NYHOPS), hydrologic (US Army Corps of Engineers Hydrologic Modeling System, HEC-HMS) and hydraulic (2-dimensional River Analysis System, HEC-RAS) components. The state-of-the-art framework is forced with 125 ensemble meteorological inputs from numerical weather prediction models including the Global Ensemble Forecast System, the European Centre for Medium-Range Weather Forecasts (ECMWF), the Canadian Meteorological Centre (CMC), the Short Range Ensemble Forecast (SREF) and the North American Mesoscale Forecast System (NAM). The framework produces, within a 96-hour forecast horizon, on-the-fly Google Earth flood maps that provide critical information for decision makers and emergency preparedness managers. The utility of the framework was demonstrated by retrospectively forecasting an extreme flood event, hurricane Sandy in the Passaic and Hackensack watersheds (New Jersey, USA). Hurricane Sandy caused significant damage to a number of critical facilities in this area including the New Jersey Transit's main storage and maintenance facility. The results of this work demonstrate that ensemble based frameworks provide improved flood predictions and useful information about associated uncertainties, thus improving the assessment of risks as when compared to a deterministic forecast. The work offers perspectives for short-term flood forecasts, flood mitigation strategies and best management practices for climate change scenarios.
The water-energy nexus at water supply and its implications on the integrated water and energy management.

PubMed

Khalkhali, Masoumeh; Westphal, Kirk; Mo, Weiwei

2018-09-15

Water and energy are highly interdependent in the modern world, and hence, it is important to understand their constantly changing and nonlinear interconnections to inform the integrated management of water and energy. In this study, a hydrologic model, a water systems model, and an energy model were developed and integrated into a system dynamics modeling framework. This framework was then applied to a water supply system in the northeast US to capture its water-energy interactions under a set of future population, climate, and system operation scenarios. A hydrologic model was first used to simulate the system's hydrologic inflows and outflows under temperature and precipitation changes on a weekly-basis. A water systems model that combines the hydrologic model and management rules (e.g., water release and transfer) was then developed to dynamically simulate the system's water storage and water head. Outputs from the water systems model were used in the energy model to estimate hydropower generation. It was found that critical water-energy synergies and tradeoffs exist, and there is a possibility for integrated water and energy management to achieve better outcomes. This analysis also shows the importance of a holistic understanding of the systems as a whole, which would allow utility managers to make proactive long-term management decisions. The modeling framework is generalizable to other water supply systems with hydropower generation capacities to inform the integrated management of water and energy resources. Copyright © 2018 Elsevier B.V. All rights reserved.
Applying Hillslope Hydrology to Bridge between Ecosystem and Grid-Scale Processes within an Earth System Model

NASA Astrophysics Data System (ADS)

Subin, Z. M.; Sulman, B. N.; Malyshev, S.; Shevliakova, E.

2013-12-01

Soil moisture is a crucial control on surface energy fluxes, vegetation properties, and soil carbon cycling. Its interactions with ecosystem processes are highly nonlinear across a large range, as both drought stress and anoxia can impede vegetation and microbial growth. Earth System Models (ESMs) generally only represent an average soil-moisture state in grid cells at scales of 50-200 km, and as a result are not able to adequately represent the effects of subgrid heterogeneity in soil moisture, especially in regions with large wetland areas. We addressed this deficiency by developing the first ESM-coupled subgrid hillslope-hydrological model, TiHy (Tiled-hillslope Hydrology), embedded within the Geophysical Fluid Dynamics Laboratory (GFDL) land model. In each grid cell, one or more representative hillslope geometries are discretized into land model tiles along an upland-to-lowland gradient. These geometries represent ~1 km hillslope-scale hydrological features and allow for flexible representation of hillslope profile and plan shapes, in addition to variation of subsurface properties among or within hillslopes. Each tile (which may represent ~100 m along the hillslope) has its own surface fluxes, vegetation state, and vertically-resolved state variables for soil physics and biogeochemistry. Resolution of water state in deep layers (~200 m) down to bedrock allows for physical integration of groundwater transport with unsaturated overlying dynamics. Multiple tiles can also co-exist at the same vertical position along the hillslope, allowing the simulation of ecosystem heterogeneity due to disturbance. The hydrological model is coupled to the vertically-resolved Carbon, Organisms, Respiration, and Protection in the Soil Environment (CORPSE) model, which captures non-linearity resulting from interactions between vertically-heterogeneous soil carbon and water profiles. We present comparisons of simulated water table depth to observations. We examine sensitivities to alternative parameterizations of hillslope geometry, macroporosity, and surface runoff / inundation, and to the choice of global topographic dataset and groundwater hydraulic conductivity distribution. Simulated groundwater dynamics among hillslopes tend to cluster into three regimes of wet and well-drained, wet but poorly-drained, and dry. In the base model configuration, near-surface gridcell-mean water tables exist in an excessively large area compared to observations, including large areas of the Eastern U.S. and Northern Europe. However, in better-drained areas, the decrease in water table depth along the hillslope gradient allows for realistic increases in ecosystem water availability and soil carbon downslope. The inclusion of subgrid hydrology can increase the equilibrium 0-2 m global soil carbon stock by a large factor, due to the nonlinear effect of anoxia. We conclude that this innovative modeling framework allows for the inclusion of hillslope-scale processes and the potential for wetland dynamics in an ESM without need for a high-resolution 3-dimensional groundwater model. Future work will include investigating the potential for future changes in land carbon fluxes caused by the effects of changing hydrological regime, particularly in peatland-rich areas poorly treated by current ESMs.
CEREF: A hybrid data-driven model for forecasting annual streamflow from a socio-hydrological system

NASA Astrophysics Data System (ADS)

Zhang, Hongbo; Singh, Vijay P.; Wang, Bin; Yu, Yinghao

2016-09-01

Hydrological forecasting is complicated by flow regime alterations in a coupled socio-hydrologic system, encountering increasingly non-stationary, nonlinear and irregular changes, which make decision support difficult for future water resources management. Currently, many hybrid data-driven models, based on the decomposition-prediction-reconstruction principle, have been developed to improve the ability to make predictions of annual streamflow. However, there exist many problems that require further investigation, the chief among which is the direction of trend components decomposed from annual streamflow series and is always difficult to ascertain. In this paper, a hybrid data-driven model was proposed to capture this issue, which combined empirical mode decomposition (EMD), radial basis function neural networks (RBFNN), and external forces (EF) variable, also called the CEREF model. The hybrid model employed EMD for decomposition and RBFNN for intrinsic mode function (IMF) forecasting, and determined future trend component directions by regression with EF as basin water demand representing the social component in the socio-hydrologic system. The Wuding River basin was considered for the case study, and two standard statistical measures, root mean squared error (RMSE) and mean absolute error (MAE), were used to evaluate the performance of CEREF model and compare with other models: the autoregressive (AR), RBFNN and EMD-RBFNN. Results indicated that the CEREF model had lower RMSE and MAE statistics, 42.8% and 7.6%, respectively, than did other models, and provided a superior alternative for forecasting annual runoff in the Wuding River basin. Moreover, the CEREF model can enlarge the effective intervals of streamflow forecasting compared to the EMD-RBFNN model by introducing the water demand planned by the government department to improve long-term prediction accuracy. In addition, we considered the high-frequency component, a frequent subject of concern in EMD-based forecasting, and results showed that removing high-frequency component is an effective measure to improve forecasting precision and is suggested for use with the CEREF model for better performance. Finally, the study concluded that the CEREF model can be used to forecast non-stationary annual streamflow change as a co-evolution of hydrologic and social systems with better accuracy. Also, the modification about removing high-frequency can further improve the performance of the CEREF model. It should be noted that the CEREF model is beneficial for data-driven hydrologic forecasting in complex socio-hydrologic systems, and as a simple data-driven socio-hydrologic forecasting model, deserves more attention.
Environmental Flows: Evaluating Long-Term Baselines for Hydrological Regime Change in the Southern United States

NASA Astrophysics Data System (ADS)

Deines, A. M.; Morrison, A. M.; Menzie, C.

2016-12-01

The wide variety of ecosystem services associated with running fresh waters are dependent on an assortment of flow conditions including timing and duration of seasonal floods as well as intermittent flows, such as storm peaks. Modern methods of assessing environmental flows consider hydrological regime change by comparing actual or simulated baseline flow conditions against putatively altered regime flows. These calculated flow changes are used as inputs to models of ecosystem responses such as for fish populations, inundated habitat area, or nutrient supplies. However, common and recommended tools and software used to make flow comparisons between putative regimes lack robust mechanisms for evaluating the significance of hydrological regime change in the context of long-term (multiple decades, centuries, or greater) trends, such as climatic conditions, or the facility to determine the existence and causes of regime changes when no obvious discontinuity exists, such as the construction of a dam. As such, environmental flow decisions based on short (recent) baseline records or baseline records assumed to represent stable hydrological conditions may lead to inefficient water use and ecosystem services distribution. Here we examine long-term patterns in discharge, the frequency and severity of regional droughts, and the Atlantic Multidecadal Oscillation to better understand the occurrence and causes of hydrological regime change in rivers in the Southern United States. For each river we ask: 1) Has hydrological regime change occurred? 2) To what degree is observed regime change associated with regional climatic drivers? 3) How might environmental flows suggested by current methods (e.g. the USGS Hydroecological Integrity Assessment or the Indicators of Hydrologic Alteration software) compare with flows derived by additional consideration of long-term drivers of hydrological change? We discuss the different temporal scales through which climate can influence a hydrological regime and provide insights for evaluating or planning expected future flow regimes under potential conditions of water scarcity.
Understanding of Coupled Terrestrial Carbon, Nitrogen and Water Dynamics—An Overview

PubMed Central

Chen, Baozhang; Coops, Nicholas C.

2009-01-01

Coupled terrestrial carbon (C), nitrogen (N) and hydrological processes play a crucial role in the climate system, providing both positive and negative feedbacks to climate change. In this review we summarize published research results to gain an increased understanding of the dynamics between vegetation and atmosphere processes. A variety of methods, including monitoring (e.g., eddy covariance flux tower, remote sensing, etc.) and modeling (i.e., ecosystem, hydrology and atmospheric inversion modeling) the terrestrial carbon and water budgeting, are evaluated and compared. We highlight two major research areas where additional research could be focused: (i) Conceptually, the hydrological and biogeochemical processes are closely linked, however, the coupling processes between terrestrial C, N and hydrological processes are far from well understood; and (ii) there are significant uncertainties in estimates of the components of the C balance, especially at landscape and regional scales. To address these two questions, a synthetic research framework is needed which includes both bottom-up and top-down approaches integrating scalable (footprint and ecosystem) models and a spatially nested hierarchy of observations which include multispectral remote sensing, inventories, existing regional clusters of eddy-covariance flux towers and CO2 mixing ratio towers and chambers. PMID:22291528
Understanding of coupled terrestrial carbon, nitrogen and water dynamics-an overview.

PubMed

Chen, Baozhang; Coops, Nicholas C

2009-01-01

Coupled terrestrial carbon (C), nitrogen (N) and hydrological processes play a crucial role in the climate system, providing both positive and negative feedbacks to climate change. In this review we summarize published research results to gain an increased understanding of the dynamics between vegetation and atmosphere processes. A variety of methods, including monitoring (e.g., eddy covariance flux tower, remote sensing, etc.) and modeling (i.e., ecosystem, hydrology and atmospheric inversion modeling) the terrestrial carbon and water budgeting, are evaluated and compared. We highlight two major research areas where additional research could be focused: (i) Conceptually, the hydrological and biogeochemical processes are closely linked, however, the coupling processes between terrestrial C, N and hydrological processes are far from well understood; and (ii) there are significant uncertainties in estimates of the components of the C balance, especially at landscape and regional scales. To address these two questions, a synthetic research framework is needed which includes both bottom-up and top-down approaches integrating scalable (footprint and ecosystem) models and a spatially nested hierarchy of observations which include multispectral remote sensing, inventories, existing regional clusters of eddy-covariance flux towers and CO(2) mixing ratio towers and chambers.
Setting up a hydrological model based on global data for the Ayeyarwady basin in Myanmar

NASA Astrophysics Data System (ADS)

ten Velden, Corine; Sloff, Kees; Nauta, Tjitte

2017-04-01

The use of global datasets in local hydrological modelling can be of great value. It opens up the possibility to include data for areas where local data is not or only sparsely available. In hydrological modelling the existence of both static physical data such as elevation and land use, and dynamic meteorological data such as precipitation and temperature, is essential for setting up a hydrological model, but often such data is difficult to obtain at the local level. For the Ayeyarwady catchment in Myanmar a distributed hydrological model (Wflow: https://github.com/openstreams/wflow) was set up with only global datasets, as part of a water resources study. Myanmar is an emerging economy, which has only recently become more receptive to foreign influences. It has a very limited hydrometeorological measurement network, with large spatial and temporal gaps, and data that are of uncertain quality and difficult to obtain. The hydrological model was thus set up based on resampled versions of the SRTM digital elevation model, the GlobCover land cover dataset and the HWSD soil dataset. Three global meteorological datasets were assessed and compared for use in the hydrological model: TRMM, WFDEI and MSWEP. The meteorological datasets were assessed based on their conformity with several precipitation station measurements, and the overall model performance was assessed by calculating the NSE and RVE based on discharge measurements of several gauging stations. The model was run for the period 1979-2012 on a daily time step, and the results show an acceptable applicability of the used global datasets in the hydrological model. The WFDEI forcing dataset gave the best results, with a NSE of 0.55 at the outlet of the model and a RVE of 8.5%, calculated over the calibration period 2006-2012. As a general trend the modelled discharge at the upstream stations tends to be underestimated, and at the downstream stations slightly overestimated. The quality of the discharge measurements that form the basis for the performance calculations is uncertain; data analysis suggests that rating curves are not frequently updated. The modelling results are not perfect and there is ample room for improvement, but the results are reasonable given the notion that setting up a hydrological model for this area would not have been possible without the use of global datasets due to the lack of available local data. The resulting hydrological model then enabled the set-up of the RIBASIM water allocation model for the Ayeyarwady basin in order to assess its water resources. The study discussed here is a first step; ideally this is followed up by a more thorough calibration and validation with the limited local measurements available, e.g. a precipitation correction based on the available rainfall measurements, to ensure the integration of global and local data.

A comparison of operational and LANDSAT-aided snow water content estimation systems. [Feather River Basin, California

NASA Technical Reports Server (NTRS)

Sharp, J. M.; Thomas, R. W.

1975-01-01

How LANDSAT imagery can be cost effectively employed to augment an operational hydrologic model is described. Attention is directed toward the estimation of snow water content, a major predictor variable in the volumetric runoff forecasting model. A stratified double sampling scheme is supplemented with qualitative and quantitative analyses of existing operations to develop a comparison between the existing and satellite-aided approaches to snow water content estimation. Results show a decided advantage for the LANDSAT-aided approach.
Coupling of snow and permafrost processes using the Basic Modeling Interface (BMI)

NASA Astrophysics Data System (ADS)

Wang, K.; Overeem, I.; Jafarov, E. E.; Piper, M.; Stewart, S.; Clow, G. D.; Schaefer, K. M.

2017-12-01

We developed a permafrost modeling tool based by implementing the Kudryavtsev empirical permafrost active layer depth model (the so-called "Ku" component). The model is specifically set up to have a basic model interface (BMI), which enhances the potential coupling to other earth surface processes model components. This model is accessible through the Web Modeling Tool in Community Surface Dynamics Modeling System (CSDMS). The Kudryavtsev model has been applied for entire Alaska to model permafrost distribution at high spatial resolution and model predictions have been verified by Circumpolar Active Layer Monitoring (CALM) in-situ observations. The Ku component uses monthly meteorological forcing, including air temperature, snow depth, and snow density, and predicts active layer thickness (ALT) and temperature on the top of permafrost (TTOP), which are important factors in snow-hydrological processes. BMI provides an easy approach to couple the models with each other. Here, we provide a case of coupling the Ku component to snow process components, including the Snow-Degree-Day (SDD) method and Snow-Energy-Balance (SEB) method, which are existing components in the hydrological model TOPOFLOW. The work flow is (1) get variables from meteorology component, set the values to snow process component, and advance the snow process component, (2) get variables from meteorology and snow component, provide these to the Ku component and advance, (3) get variables from snow process component, set the values to meteorology component, and advance the meteorology component. The next phase is to couple the permafrost component with fully BMI-compliant TOPOFLOW hydrological model, which could provide a useful tool to investigate the permafrost hydrological effect.
HydroShare for iUTAH: Collaborative Publication, Interoperability, and Reuse of Hydrologic Data and Models for a Large, Interdisciplinary Water Research Project

NASA Astrophysics Data System (ADS)

Horsburgh, J. S.; Jones, A. S.

2016-12-01

Data and models used within the hydrologic science community are diverse. New research data and model repositories have succeeded in making data and models more accessible, but have been, in most cases, limited to particular types or classes of data or models and also lack the type of collaborative, and iterative functionality needed to enable shared data collection and modeling workflows. File sharing systems currently used within many scientific communities for private sharing of preliminary and intermediate data and modeling products do not support collaborative data capture, description, visualization, and annotation. More recently, hydrologic datasets and models have been cast as "social objects" that can be published, collaborated around, annotated, discovered, and accessed. Yet it can be difficult using existing software tools to achieve the kind of collaborative workflows and data/model reuse that many envision. HydroShare is a new, web-based system for sharing hydrologic data and models with specific functionality aimed at making collaboration easier and achieving new levels of interactive functionality and interoperability. Within HydroShare, we have developed new functionality for creating datasets, describing them with metadata, and sharing them with collaborators. HydroShare is enabled by a generic data model and content packaging scheme that supports describing and sharing diverse hydrologic datasets and models. Interoperability among the diverse types of data and models used by hydrologic scientists is achieved through the use of consistent storage, management, sharing, publication, and annotation within HydroShare. In this presentation, we highlight and demonstrate how the flexibility of HydroShare's data model and packaging scheme, HydroShare's access control and sharing functionality, and versioning and publication capabilities have enabled the sharing and publication of research datasets for a large, interdisciplinary water research project called iUTAH (innovative Urban Transitions and Aridregion Hydro-sustainability). We discuss the experiences of iUTAH researchers now using HydroShare to collaboratively create, curate, and publish datasets and models in a way that encourages collaboration, promotes reuse, and meets funding agency requirements.
Physically-based extreme flood frequency with stochastic storm transposition and paleoflood data on large watersheds

NASA Astrophysics Data System (ADS)

England, John F.; Julien, Pierre Y.; Velleux, Mark L.

2014-03-01

Traditionally, deterministic flood procedures such as the Probable Maximum Flood have been used for critical infrastructure design. Some Federal agencies now use hydrologic risk analysis to assess potential impacts of extreme events on existing structures such as large dams. Extreme flood hazard estimates and distributions are needed for these efforts, with very low annual exceedance probabilities (⩽10-4) (return periods >10,000 years). An integrated data-modeling hydrologic hazard framework for physically-based extreme flood hazard estimation is presented. Key elements include: (1) a physically-based runoff model (TREX) coupled with a stochastic storm transposition technique; (2) hydrometeorological information from radar and an extreme storm catalog; and (3) streamflow and paleoflood data for independently testing and refining runoff model predictions at internal locations. This new approach requires full integration of collaborative work in hydrometeorology, flood hydrology and paleoflood hydrology. An application on the 12,000 km2 Arkansas River watershed in Colorado demonstrates that the size and location of extreme storms are critical factors in the analysis of basin-average rainfall frequency and flood peak distributions. Runoff model results are substantially improved by the availability and use of paleoflood nonexceedance data spanning the past 1000 years at critical watershed locations.
Monthly land cover-specific evapotranspiration models derived from global eddy flux measurements and remote sensing data

Treesearch

Yuan Fang; Ge Sun; Peter Caldwell; Steven G. McNulty; Asko Noormets; Jean-Christophe Domec; John King; Zhiqiang Zhang; Xudong Zhang; Guanghui Lin; Guangsheng Zhou; Jingfeng Xiao; Jiquan Chen

2015-01-01

Evapotranspiration (ET) is arguably the most uncertain ecohydrologic variable for quantifying watershed water budgets. Although numerous ET and hydrological models exist, accurately predicting the effects of global change on water use and availability remains challenging because of model deficiency and/or a lack of input parameters. The objective of this study was to...
Advancing an Information Model for Environmental Observations

NASA Astrophysics Data System (ADS)

Horsburgh, J. S.; Aufdenkampe, A. K.; Hooper, R. P.; Lehnert, K. A.; Schreuders, K.; Tarboton, D. G.; Valentine, D. W.; Zaslavsky, I.

2011-12-01

Observational data are fundamental to hydrology and water resources, and the way they are organized, described, and shared either enables or inhibits the analyses that can be performed using the data. The CUAHSI Hydrologic Information System (HIS) project is developing cyberinfrastructure to support hydrologic science by enabling better access to hydrologic data. HIS is composed of three major components. HydroServer is a software stack for publishing time series of hydrologic observations on the Internet as well as geospatial data using standards-based web feature, map, and coverage services. HydroCatalog is a centralized facility that catalogs the data contents of individual HydroServers and enables search across them. HydroDesktop is a client application that interacts with both HydroServer and HydroCatalog to discover, download, visualize, and analyze hydrologic observations published on one or more HydroServers. All three components of HIS are founded upon an information model for hydrologic observations at stationary points that specifies the entities, relationships, constraints, rules, and semantics of the observational data and that supports its data services. Within this information model, observations are described with ancillary information (metadata) about the observations to allow them to be unambiguously interpreted and used, and to provide traceable heritage from raw measurements to useable information. Physical implementations of this information model include the Observations Data Model (ODM) for storing hydrologic observations, Water Markup Language (WaterML) for encoding observations for transmittal over the Internet, the HydroCatalog metadata catalog database, and the HydroDesktop data cache database. The CUAHSI HIS and this information model have now been in use for several years, and have been deployed across many different academic institutions as well as across several national agency data repositories. Additionally, components of the HIS have been modified to support data management for the Critical Zone Observatories (CZOs). This paper will present limitations of the existing information model used by the CUAHSI HIS that have been uncovered through its deployment and use, as well as new advances to the information model, including: better representation of both in situ observations from field sensors and observations derived from environmental samples, extensibility in attributes used to describe observations, and observation provenance. These advances have been developed by the HIS team and the broader scientific community and will enable the information model to accommodate and better describe wider classes of environmental observations and to better meet the needs of the hydrologic science and CZO communities.
Coupled local facilitation and global hydrologic inhibition drive landscape geometry in a patterned peatland

NASA Astrophysics Data System (ADS)

Acharya, S.; Kaplan, D. A.; Casey, S.; Cohen, M. J.; Jawitz, J. W.

2015-05-01

Self-organized landscape patterning can arise in response to multiple processes. Discriminating among alternative patterning mechanisms, particularly where experimental manipulations are untenable, requires process-based models. Previous modeling studies have attributed patterning in the Everglades (Florida, USA) to sediment redistribution and anisotropic soil hydraulic properties. In this work, we tested an alternate theory, the self-organizing-canal (SOC) hypothesis, by developing a cellular automata model that simulates pattern evolution via local positive feedbacks (i.e., facilitation) coupled with a global negative feedback based on hydrology. The model is forced by global hydroperiod that drives stochastic transitions between two patch types: ridge (higher elevation) and slough (lower elevation). We evaluated model performance using multiple criteria based on six statistical and geostatistical properties observed in reference portions of the Everglades landscape: patch density, patch anisotropy, semivariogram ranges, power-law scaling of ridge areas, perimeter area fractal dimension, and characteristic pattern wavelength. Model results showed strong statistical agreement with reference landscapes, but only when anisotropically acting local facilitation was coupled with hydrologic global feedback, for which several plausible mechanisms exist. Critically, the model correctly generated fractal landscapes that had no characteristic pattern wavelength, supporting the invocation of global rather than scale-specific negative feedbacks.
Coupled local facilitation and global hydrologic inhibition drive landscape geometry in a patterned peatland

NASA Astrophysics Data System (ADS)

Acharya, S.; Kaplan, D. A.; Casey, S.; Cohen, M. J.; Jawitz, J. W.

2015-01-01

Self-organized landscape patterning can arise in response to multiple processes. Discriminating among alternative patterning mechanisms, particularly where experimental manipulations are untenable, requires process-based models. Previous modeling studies have attributed patterning in the Everglades (Florida, USA) to sediment redistribution and anisotropic soil hydraulic properties. In this work, we tested an alternate theory, the self-organizing canal (SOC) hypothesis, by developing a cellular automata model that simulates pattern evolution via local positive feedbacks (i.e., facilitation) coupled with a global negative feedback based on hydrology. The model is forced by global hydroperiod that drives stochastic transitions between two patch types: ridge (higher elevation) and slough (lower elevation). We evaluated model performance using multiple criteria based on six statistical and geostatistical properties observed in reference portions of the Everglades landscape: patch density, patch anisotropy, semivariogram ranges, power-law scaling of ridge areas, perimeter area fractal dimension, and characteristic pattern wavelength. Model results showed strong statistical agreement with reference landscapes, but only when anisotropically acting local facilitation was coupled with hydrologic global feedback, for which several plausible mechanisms exist. Critically, the model correctly generated fractal landscapes that had no characteristic pattern wavelength, supporting the invocation of global rather than scale-specific negative feedbacks.
Probabilistic graphs as a conceptual and computational tool in hydrology and water management

NASA Astrophysics Data System (ADS)

Schoups, Gerrit

2014-05-01

Originally developed in the fields of machine learning and artificial intelligence, probabilistic graphs constitute a general framework for modeling complex systems in the presence of uncertainty. The framework consists of three components: 1. Representation of the model as a graph (or network), with nodes depicting random variables in the model (e.g. parameters, states, etc), which are joined together by factors. Factors are local probabilistic or deterministic relations between subsets of variables, which, when multiplied together, yield the joint distribution over all variables. 2. Consistent use of probability theory for quantifying uncertainty, relying on basic rules of probability for assimilating data into the model and expressing unknown variables as a function of observations (via the posterior distribution). 3. Efficient, distributed approximation of the posterior distribution using general-purpose algorithms that exploit model structure encoded in the graph. These attributes make probabilistic graphs potentially useful as a conceptual and computational tool in hydrology and water management (and beyond). Conceptually, they can provide a common framework for existing and new probabilistic modeling approaches (e.g. by drawing inspiration from other fields of application), while computationally they can make probabilistic inference feasible in larger hydrological models. The presentation explores, via examples, some of these benefits.
Creating Data and Modeling Enabled Hydrology Instruction Using Collaborative Approach

NASA Astrophysics Data System (ADS)

Merwade, V.; Rajib, A.; Ruddell, B. L.; Fox, S.

2017-12-01

Hydrology instruction typically involves teaching of the hydrologic cycle and the processes associated with it such as precipitation, evapotranspiration, infiltration, runoff generation and hydrograph analysis. With the availability of observed and remotely sensed data related to many hydrologic fluxes, there is an opportunity to use these data for place based learning in hydrology classrooms. However, it is not always easy and possible for an instructor to complement an existing hydrology course with new material that requires both the time and technical expertise, which the instructor may not have. The work presented here describes an effort where students create the data and modeling driven instruction material as a part of their class assignment for a hydrology course at Purdue University. The data driven hydrology education project within Science Education Resources Center (SERC) is used as a platform to publish and share the instruction material so it can be used by future students in the same course or any other course anywhere in the world. Students in the class were divided into groups, and each group was assigned a topic such as precipitation, evapotranspiration, streamflow, flow duration curve and frequency analysis. Each student in the group was then asked to get data and do some analysis for an area with specific landuse characteristic such as urban, rural and agricultural. The student contribution were then organized into learning units such that someone can do a flow duration curve analysis or flood frequency analysis to see how it changes for rural area versus urban area. The hydrology education project within SERC cyberinfrastructure enables any other instructor to adopt this material as is or through modification to suit his/her place based instruction needs.
Glaciers and small ice caps in the macro-scale hydrological cycle - an assessment of present conditions and future changes

NASA Astrophysics Data System (ADS)

Lammers, Richard; Hock, Regine; Prusevich, Alexander; Bliss, Andrew; Radic, Valentina; Glidden, Stanley; Grogan, Danielle; Frolking, Steve

2014-05-01

Glacier and small ice cap melt water contributions to the global hydrologic cycle are an important component of human water supply and for sea level rise. This melt water is used in many arid and semi-arid parts of the world for direct human consumption as well as indirect consumption by irrigation for crops, serving as frozen reservoirs of water that supplement runoff during warm and dry periods of summer when it is needed the most. Additionally, this melt water reaching the oceans represents a direct input to sea level rise and therefore accurate estimates of this contribution have profound economic and geopolitical implications. It has been demonstrated that, on the scale of glacierized river catchments, land surface hydrological models can successfully simulate glacier contribution to streamflow. However, at global scales, the implementation of glacier melt in hydrological models has been rudimentary or non-existent. In this study, a global glacier mass balance model is coupled with the University of New Hampshire Water Balance/Transport Model (WBM) to assess recent and projected future glacier contributions to the hydrological cycle over the global land surface (excluding the ice sheets of Greenland and Antarctica). For instance, results of WBM simulations indicate that seasonal glacier melt water in many arid climate watersheds comprises 40 % or more of their discharge. Implicitly coupled glacier and WBM models compute monthly glacier mass changes and resulting runoff at the glacier terminus for each individual glacier from the globally complete Randolph Glacier Inventory including over 200 000 glaciers. The time series of glacier runoff is aggregated over each hydrological modeling unit and delivered to the hydrological model for routing downstream and mixing with non-glacial contribution of runoff to each drainage basin outlet. WBM tracks and uses glacial and non-glacial components of the in-stream water for filling reservoirs, transfers of water between drainage basins (inter-basin hydrological transfers), and irrigation along the global system of rivers with net discharge to the ocean. Climate scenarios from global climate models prepared for IPCC AR5 are used to explore an expected range of possible future glacier outflow variability to estimate the impacts on human use of these valuable waters and their poorly understood net contribution to sea level change.
Assessment of the Impacts of Climate Change on Stream Discharge and Water Quality in an Arid, Urbanized Watershed

NASA Astrophysics Data System (ADS)

Ranatunga, T.; Tong, S.; Yang, J.

2011-12-01

Hydrologic and water quality models can provide a general framework to conceptualize and investigate the relationships between climate and water resources. Under a hot and dry climate, highly urbanized watersheds are more vulnerable to changes in climate, such as excess heat and drought. In this study, a comprehensive watershed model, Hydrological Simulation Program FORTRAN (HSPF), is used to assess the impacts of future climate change on the stream discharge and water quality in Las Vegas Wash in Nevada, the only surface water body that drains from the Las Vegas Valley (an area with rapid population growth and urbanization) to Lake Mead. In this presentation, the process of model building, calibration and validation, the generation of climate change scenarios, and the assessment of future climate change effects on stream hydrology and quality are demonstrated. The hydrologic and water quality model is developed based on the data from current national databases and existing major land use categories of the watershed. The model is calibrated for stream discharge, nutrients (nitrogen and phosphorus) and sediment yield. The climate change scenarios are derived from the outputs of the Global Climate Models (GCM) and Regional Climate Models (RCM) simulations, and from the recent assessment reports from the Intergovernmental Panel on Climate Change (IPCC). The Climate Assessment Tool from US EPA's BASINS is used to assess the effects of likely future climate scenarios on the water quantity and quality in Las Vegas Wash. Also the presentation discusses the consequences of these hydrologic changes, including the deficit supplies of clean water during peak seasons of water demand, increased eutrophication potentials, wetland deterioration, and impacts on wild life habitats.
PRMS-IV, the precipitation-runoff modeling system, version 4

USGS Publications Warehouse

Markstrom, Steven L.; Regan, R. Steve; Hay, Lauren E.; Viger, Roland J.; Webb, Richard M.; Payn, Robert A.; LaFontaine, Jacob H.

2015-01-01

Computer models that simulate the hydrologic cycle at a watershed scale facilitate assessment of variability in climate, biota, geology, and human activities on water availability and flow. This report describes an updated version of the Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of various combinations of climate and land use on streamflow and general watershed hydrology. Several new model components were developed, and all existing components were updated, to enhance performance and supportability. This report describes the history, application, concepts, organization, and mathematical formulation of the Precipitation-Runoff Modeling System and its model components. This updated version provides improvements in (1) system flexibility for integrated science, (2) verification of conservation of water during simulation, (3) methods for spatial distribution of climate boundary conditions, and (4) methods for simulation of soil-water flow and storage.
Water Quality Assessment in the Vouga Catchment (Portugal) through the Integration of Hydrologic Modeling, Economic Valuation, and Optimization Methods

NASA Astrophysics Data System (ADS)

Hawtree, Daniel; Julich, Stefan; Rocha, João; Roebeling, Peter; Feger, Karl-Heinz

2016-04-01

Hydrologic model assessments of the impacts of land-cover / use change (LCLUC) are fundamental for the development of catchment management plans, which are increasingly needed for meeting water quality standards (i.e. Water Framework Directive). These assessments can be difficult to conduct at the spatial scale required for such plans, due to data limitations and the challenge of up-scaling from field / small scale studies to larger regions. Furthermore, such hydrologic assessments are of limited practical use if the financial impacts of any potential land-cover / management changes on local stakeholders are adequately quantified and taken into planning consideration. To address these challenges, this study presents an approach that integrates hydrologic modeling, economic valuation, and landscape optimization methods. This approach is applied to the Vouga catchment, a large (2,298 km^2) mixed land-use catchment in north-central Portugal. The Vouga has high nutrient (nitrogen and phosphorus) impacts in a number of reaches, which have negative impacts on downstream wetlands and groundwater supplies. To examine potential improvements to water quality, the Soil and Water Assessment Tool (SWAT) was calibrated over a five period (2002 - 2007) to establish the baseline hydrologic and nutrient fluxes. This calibration relies upon the up-scaling of findings from previous field studies (on vegetation and soils), hydrologic assessments, and modeling studies. The agricultural income for local stakeholders was estimated from existing land-cover and management approaches is made, to establish the baseline financial conditions. An optimization algorithm is then applied to the baseline scenario using both the biophysical and financial information, which seeks to determine various (most) optimal states. The preliminary results from this work are presented, and the advantages and challenges of using such an approach for scenario analysis for catchment management are discussed
Characterizing Satellite Rainfall Errors based on Land Use and Land Cover and Tracing Error Source in Hydrologic Model Simulation

NASA Astrophysics Data System (ADS)

Gebregiorgis, A. S.; Peters-Lidard, C. D.; Tian, Y.; Hossain, F.

2011-12-01

Hydrologic modeling has benefited from operational production of high resolution satellite rainfall products. The global coverage, near-real time availability, spatial and temporal sampling resolutions have advanced the application of physically based semi-distributed and distributed hydrologic models for wide range of environmental decision making processes. Despite these successes, the existence of uncertainties due to indirect way of satellite rainfall estimates and hydrologic models themselves remain a challenge in making meaningful and more evocative predictions. This study comprises breaking down of total satellite rainfall error into three independent components (hit bias, missed precipitation and false alarm), characterizing them as function of land use and land cover (LULC), and tracing back the source of simulated soil moisture and runoff error in physically based distributed hydrologic model. Here, we asked "on what way the three independent total bias components, hit bias, missed, and false precipitation, affect the estimation of soil moisture and runoff in physically based hydrologic models?" To understand the clear picture of the outlined question above, we implemented a systematic approach by characterizing and decomposing the total satellite rainfall error as a function of land use and land cover in Mississippi basin. This will help us to understand the major source of soil moisture and runoff errors in hydrologic model simulation and trace back the information to algorithm development and sensor type which ultimately helps to improve algorithms better and will improve application and data assimilation in future for GPM. For forest and woodland and human land use system, the soil moisture was mainly dictated by the total bias for 3B42-RT, CMORPH, and PERSIANN products. On the other side, runoff error was largely dominated by hit bias than the total bias. This difference occurred due to the presence of missed precipitation which is a major contributor to the total bias both during the summer and winter seasons. Missed precipitation, most likely light rain and rain over snow cover, has significant effect on soil moisture and are less capable of producing runoff that results runoff dependency on the hit bias only.
A novel land surface-hydrologic-sediment dynamics model for stream corridor conservation assessment and its first application

NASA Astrophysics Data System (ADS)

Smithgall, K.; Shen, C.; Langendoen, E. J.; Johnson, P. A.

2015-12-01

Nationally and in the Chesapeake Bay (CB), Stream Corridor restoration costs unsustainable amount of public resources, but decisions are often made with inadequate knowledge of regional-scale system behavior. Bank erosion is a significant issue relevant to sediment and nutrient pollution, aquatic and riparian habitat and stream health. Existing modeling effort either focuses only on reach-scale responses or overly simplifies the descriptions for bank failure mechanics. In this work we present a novel regional-scale processes model integrating hydrology, vegetation dynamics, hydraulics, bank mechanics and sediment transport, based on a coupling between Community Land Model, Process-based Adaptive Watershed Simulator and CONservational Channel Evolution and Pollutant Transport System (CLM + PAWS + CONCEPTS, CPC). We illustrate the feasibility of this modeling platform in a Valley and Ridge basin in Pennsylvania, USA, with channel geometry data collected in 2004 and 2014. The simulations are able to reproduce essential pattern of the observed trends. We study the causes of the noticeable evolution of a relocated channel and the hydrologic controls. Bridging processes on multiple scales, the CPC model creates a new, integrated system that may serve as a confluence point for inter-disciplinary research.
A multicomponent coupled model of glacier hydrology 1. Theory and synthetic examples

NASA Astrophysics Data System (ADS)

Flowers, Gwenn E.; Clarke, Garry K. C.

2002-11-01

Basal hydrology is acknowledged as a fundamental control on glacier dynamics, especially in cases where surface meltwater reaches the bed. For many glaciers at midlatitudes, basal drainage is influenced by subaerial, englacial, and subsurface water flow. One of the major shortcomings of existing basal hydrology models is the treatment of the glacier bed as an isolated system. We present theoretical and computational models that couple glacier surface runoff, englacial water storage and transport, subglacial drainage, and subsurface groundwater flow. Each of the four model components is represented as a two-dimensional, vertically integrated layer that communicates with its neighbors through water exchange. Governing equations are derived from the law of mass conservation and are expressed as a balance between the internal distribution of water and external sources. The numerical exposition of this theory is a time-dependent finite difference model that can be used to simulate glacier drainage. In this paper we outline the theory and conduct simple tests using an idealized glacier geometry. In the companion paper, the model is tailored to Trapridge Glacier, Yukon Territory, Canada, where results are compared with measurements of subglacial water pressure.
Development of Hydrological Model of Klang River Valley for flood forecasting

NASA Astrophysics Data System (ADS)

Mohammad, M.; Andras, B.

2012-12-01

This study is to review the impact of climate change and land used on flooding through the Klang River and to compare the changes in the existing river system in Klang River Basin with the Storm water Management and Road Tunnel (SMART) which is now already operating in the city centre of Kuala Lumpur. Klang River Basin is the most urbanized region in Malaysia. More than half of the basin has been urbanized on the land that is prone to flooding. Numerous flood mitigation projects and studies have been carried out to enhance the existing flood forecasting and mitigation project. The objective of this study is to develop a hydrological model for flood forecasting in Klang Basin Malaysia. Hydrological modelling generally requires large set of input data and this is more often a challenge for a developing country. Due to this limitation, the Tropical Rainfall Measuring Mission (TRMM) rainfall measurement, initiated by the US space agency NASA and Japanese space agency JAXA was used in this study. TRMM data was transformed and corrected by quantile to quantile transformation. However, transforming the data based on ground measurement doesn't make any significant improvement and the statistical comparison shows only 10% difference. The conceptual HYMOD model was used in this study and calibrated using ROPE algorithm. But, using the whole time series of the observation period in this area resulted in insufficient performance. The depth function which used in ROPE algorithm are then used to identified and calibrated using only unusual event to observed the improvement and efficiency of the model.
Compilation of watershed models for tributaries to the Great Lakes, United States, as of 2010, and identification of watersheds for future modeling for the Great Lakes Restoration Initiative

USGS Publications Warehouse

Coon, William F.; Murphy, Elizabeth A.; Soong, David T.; Sharpe, Jennifer B.

2011-01-01

As part of the Great Lakes Restoration Initiative (GLRI) during 2009–10, the U.S. Geological Survey (USGS) compiled a list of existing watershed models that had been created for tributaries within the United States that drain to the Great Lakes. Established Federal programs that are overseen by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Army Corps of Engineers (USACE) are responsible for most of the existing watershed models for specific tributaries. The NOAA Great Lakes Environmental Research Laboratory (GLERL) uses the Large Basin Runoff Model to provide data for the management of water levels in the Great Lakes by estimating United States and Canadian inflows to the Great Lakes from 121 large watersheds. GLERL also simulates streamflows in 34 U.S. watersheds by a grid-based model, the Distributed Large Basin Runoff Model. The NOAA National Weather Service uses the Sacramento Soil Moisture Accounting model to predict flows at river forecast sites. The USACE created or funded the creation of models for at least 30 tributaries to the Great Lakes to better understand sediment erosion, transport, and aggradation processes that affect Federal navigation channels and harbors. Many of the USACE hydrologic models have been coupled with hydrodynamic and sediment-transport models that simulate the processes in the stream and harbor near the mouth of the modeled tributary. Some models either have been applied or have the capability of being applied across the entire Great Lakes Basin; they are (1) the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model, which was developed by the USGS; (2) the High Impact Targeting (HIT) and Digital Watershed models, which were developed by the Institute of Water Research at Michigan State University; (3) the Long-Term Hydrologic Impact Assessment (L–THIA) model, which was developed by researchers at Purdue University; and (4) the Water Erosion Prediction Project (WEPP) model, which was developed by the National Soil Erosion Research Laboratory of the U.S. Department of Agriculture. During 2010, the USGS used the Precipitation-Runoff Modeling System (PRMS) to create a hydrologic model for the Lake Michigan Basin to assess the probable effects of climate change on future groundwater and surface-water resources. The Water Availability Tool for Environmental Resources (WATER) model and the Analysis of Flows In Networks of CHannels (AFINCH) program also were used to support USGS GLRI projects that required estimates of streamflows throughout the Great Lakes Basin. This information on existing watershed models, along with an assessment of geologic, soils, and land-use data across the Great Lakes Basin and the identification of problems that exist in selected tributary watersheds that could be addressed by a watershed model, was used to identify three watersheds in the Great Lakes Basin for future modeling by the USGS. These watersheds are the Kalamazoo River Basin in Michigan, the Tonawanda Creek Basin in New York, and the Bad River Basin in Wisconsin. These candidate watersheds have hydrogeologic, land-type, and soil characteristics that make them distinct from each other, but that are representative of other tributary watersheds within the Great Lakes Basin. These similarities in the characteristics among nearby watersheds will enhance the usefulness of a model by improving the likelihood that parameter values from a previously modeled watershed could reliably be used in the creation of a model of another watershed in the same region. The software program Hydrological Simulation Program–Fortran (HSPF) was selected to simulate the hydrologic, sedimentary, and water-quality processes in these selected watersheds. HSPF is a versatile, process-based, continuous-simulation model that has been used extensively by the scientific community, has the ongoing technical support of the U.S. Environmental Protection Agency and USGS, and provides a means to evaluate the effects that land-use changes or management practices might have on the simulated processes.
Development of an Integrated Hydrologic Modeling System for Rainfall-Runoff Simulation

NASA Astrophysics Data System (ADS)

Lu, B.; Piasecki, M.

2008-12-01

This paper aims to present the development of an integrated hydrological model which involves functionalities of digital watershed processing, online data retrieval, hydrologic simulation and post-event analysis. The proposed system is intended to work as a back end to the CUAHSI HIS cyberinfrastructure developments. As a first step into developing this system, a physics-based distributed hydrologic model PIHM (Penn State Integrated Hydrologic Model) is wrapped into OpenMI(Open Modeling Interface and Environment ) environment so as to seamlessly interact with OpenMI compliant meteorological models. The graphical user interface is being developed from the openGIS application called MapWindows which permits functionality expansion through the addition of plug-ins. . Modules required to set up through the GUI workboard include those for retrieving meteorological data from existing database or meteorological prediction models, obtaining geospatial data from the output of digital watershed processing, and importing initial condition and boundary condition. They are connected to the OpenMI compliant PIHM to simulate rainfall-runoff processes and includes a module for automatically displaying output after the simulation. Online databases are accessed through the WaterOneFlow web services, and the retrieved data are either stored in an observation database(OD) following the schema of Observation Data Model(ODM) in case for time series support, or a grid based storage facility which may be a format like netCDF or a grid-based-data database schema . Specific development steps include the creation of a bridge to overcome interoperability issue between PIHM and the ODM, as well as the embedding of TauDEM (Terrain Analysis Using Digital Elevation Models) into the model. This module is responsible for developing watershed and stream network using digital elevation models. Visualizing and editing geospatial data is achieved by the usage of MapWinGIS, an ActiveX control developed by MapWindow team. After applying to the practical watershed, the performance of the model can be tested by the post-event analysis module.

Strategies for Large Scale Implementation of a Multiscale, Multiprocess Integrated Hydrologic Model

NASA Astrophysics Data System (ADS)

Kumar, M.; Duffy, C.

2006-05-01

Distributed models simulate hydrologic state variables in space and time while taking into account the heterogeneities in terrain, surface, subsurface properties and meteorological forcings. Computational cost and complexity associated with these model increases with its tendency to accurately simulate the large number of interacting physical processes at fine spatio-temporal resolution in a large basin. A hydrologic model run on a coarse spatial discretization of the watershed with limited number of physical processes needs lesser computational load. But this negatively affects the accuracy of model results and restricts physical realization of the problem. So it is imperative to have an integrated modeling strategy (a) which can be universally applied at various scales in order to study the tradeoffs between computational complexity (determined by spatio- temporal resolution), accuracy and predictive uncertainty in relation to various approximations of physical processes (b) which can be applied at adaptively different spatial scales in the same domain by taking into account the local heterogeneity of topography and hydrogeologic variables c) which is flexible enough to incorporate different number and approximation of process equations depending on model purpose and computational constraint. An efficient implementation of this strategy becomes all the more important for Great Salt Lake river basin which is relatively large (~89000 sq. km) and complex in terms of hydrologic and geomorphic conditions. Also the types and the time scales of hydrologic processes which are dominant in different parts of basin are different. Part of snow melt runoff generated in the Uinta Mountains infiltrates and contributes as base flow to the Great Salt Lake over a time scale of decades to centuries. The adaptive strategy helps capture the steep topographic and climatic gradient along the Wasatch front. Here we present the aforesaid modeling strategy along with an associated hydrologic modeling framework which facilitates a seamless, computationally efficient and accurate integration of the process model with the data model. The flexibility of this framework leads to implementation of multiscale, multiresolution, adaptive refinement/de-refinement and nested modeling simulations with least computational burden. However, performing these simulations and related calibration of these models over a large basin at higher spatio- temporal resolutions is computationally intensive and requires use of increasing computing power. With the advent of parallel processing architectures, high computing performance can be achieved by parallelization of existing serial integrated-hydrologic-model code. This translates to running the same model simulation on a network of large number of processors thereby reducing the time needed to obtain solution. The paper also discusses the implementation of the integrated model on parallel processors. Also will be discussed the mapping of the problem on multi-processor environment, method to incorporate coupling between hydrologic processes using interprocessor communication models, model data structure and parallel numerical algorithms to obtain high performance.
The Rise of Complexity in Flood Forecasting: Opportunities, Challenges and Tradeoffs

NASA Astrophysics Data System (ADS)

Wood, A. W.; Clark, M. P.; Nijssen, B.

2017-12-01

Operational flood forecasting is currently undergoing a major transformation. Most national flood forecasting services have relied for decades on lumped, highly calibrated conceptual hydrological models running on local office computing resources, providing deterministic streamflow predictions at gauged river locations that are important to stakeholders and emergency managers. A variety of recent technological advances now make it possible to run complex, high-to-hyper-resolution models for operational hydrologic prediction over large domains, and the US National Weather Service is now attempting to use hyper-resolution models to create new forecast services and products. Yet other `increased-complexity' forecasting strategies also exist that pursue different tradeoffs between model complexity (i.e., spatial resolution, physics) and streamflow forecast system objectives. There is currently a pressing need for a greater understanding in the hydrology community of the opportunities, challenges and tradeoffs associated with these different forecasting approaches, and for a greater participation by the hydrology community in evaluating, guiding and implementing these approaches. Intermediate-resolution forecast systems, for instance, use distributed land surface model (LSM) physics but retain the agility to deploy ensemble methods (including hydrologic data assimilation and hindcast-based post-processing). Fully coupled numerical weather prediction (NWP) systems, another example, use still coarser LSMs to produce ensemble streamflow predictions either at the model scale or after sub-grid scale runoff routing. Based on the direct experience of the authors and colleagues in research and operational forecasting, this presentation describes examples of different streamflow forecast paradigms, from the traditional to the recent hyper-resolution, to illustrate the range of choices facing forecast system developers. We also discuss the degree to which the strengths and weaknesses of each strategy map onto the requirements for different types of forecasting services (e.g., flash flooding, river flooding, seasonal water supply prediction).
Significance of direct and indirect impacts of climate change on groundwater resources in the Olifants River basin: A review

NASA Astrophysics Data System (ADS)

Nkhonjera, German K.; Dinka, Megersa O.

2017-11-01

This paper considers the extent and usefulness of reviewing existing literature on the significance of direct and indirect impacts of climate change on groundwater resources with emphasis on examples from the Olifants River basin. Here, the existing literature were extensively reviewed, with discussions centred mainly on the impacts of climate change on groundwater resources and challenges in modelling climate change impacts on groundwater resources. Since in the hydrological cycle, the hydrological components such as evaporation, temperature, precipitation, and groundwater, are the major drivers of the present and future climate, a detailed discussion is done on the impact of climate change on these hydrological components to determine to what extent the hydrological cycle has already been affected as a result of climate change. The uncertainties, constraints and limitations in climate change research have also been reviewed. In addition to the research gaps discussed here, the emphasis on the need of extensive climate change research on the continent, especially as climate change impacts on groundwater, is discussed. Overall, the importance of conducting further research in climate change, understanding the significance of the impact of climate change on water resources such as groundwater, and taking actions to effectively meet the adaptation needs of the people, emerge as an important theme in this review.
A probabilistic approach for shallow rainfall-triggered landslide modeling at basin scale. A case study in the Luquillo Forest, Puerto Rico

NASA Astrophysics Data System (ADS)

Dialynas, Y. G.; Arnone, E.; Noto, L. V.; Bras, R. L.

2013-12-01

Slope stability depends on geotechnical and hydrological factors that exhibit wide natural spatial variability, yet sufficient measurements of the related parameters are rarely available over entire study areas. The uncertainty associated with the inability to fully characterize hydrologic behavior has an impact on any attempt to model landslide hazards. This work suggests a way to systematically account for this uncertainty in coupled distributed hydrological-stability models for shallow landslide hazard assessment. A probabilistic approach for the prediction of rainfall-triggered landslide occurrence at basin scale was implemented in an existing distributed eco-hydrological and landslide model, tRIBS-VEGGIE -landslide (Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator - VEGetation Generator for Interactive Evolution). More precisely, we upgraded tRIBS-VEGGIE- landslide to assess the likelihood of shallow landslides by accounting for uncertainty related to geotechnical and hydrological factors that directly affect slope stability. Natural variability of geotechnical soil characteristics was considered by randomizing soil cohesion and friction angle. Hydrological uncertainty related to the estimation of matric suction was taken into account by considering soil retention parameters as correlated random variables. The probability of failure is estimated through an assumed theoretical Factor of Safety (FS) distribution, conditioned on soil moisture content. At each cell, the temporally variant FS statistics are approximated by the First Order Second Moment (FOSM) method, as a function of parameters statistical properties. The model was applied on the Rio Mameyes Basin, located in the Luquillo Experimental Forest in Puerto Rico, where previous landslide analyses have been carried out. At each time step, model outputs include the probability of landslide occurrence across the basin, and the most probable depth of failure at each soil column. The use of the proposed probabilistic approach for shallow landslide prediction is able to reveal and quantify landslide risk at slopes assessed as stable by simpler deterministic methods.
Short-term Hydropower Reservoir Operations in Chile's Central Interconnected System: Tradeoffs between Hydrologic Alteration and Economic Performance

NASA Astrophysics Data System (ADS)

Olivares, M. A.

2011-12-01

Hydropower accounts for about 50% of the installed capacity in Chile's Central Interconnected System (CIS) and new developments are envisioned in the near future. Large projects involving reservoirs are perceived negatively by the general public. In terms of operations, hydropower scheduling takes place at monthly, weekly, daily and hourly intervals, and operations at each level affect different environmental processes. Due to its ability to quickly and inexpensively respond to short-term changes in demand, hydropower reservoirs often are operated to provide power during periods of peak demand. This operational scheme, known as hydropeaking, changes the hydrologic regime by altering the rate and frequency of changes in flow magnitude on short time scales. To mitigate impacts on downstream ecosystems, operational constraints -typically minimum instream flows and maximum ramping rates- are imposed on hydropower plants. These operational restrictions limit reduce operational flexibility and can reduce the economic value of energy generation by imposing additional costs on the operation of interconnected power systems. Methods to predict the degree of hydrologic alteration rely on statistical analyses of instream flow time series. Typically, studies on hydrologic alteration use historical operational records for comparison between pre- and post-dam conditions. Efforts to assess hydrologic alteration based on future operational schemes of reservoirs are scarce. This study couples two existing models: a mid-term operations planning and a short-term economic dispatch to simulate short-term hydropower reservoir operations under different future scenarios. Scenarios of possible future configurations of the Chilean CIS are defined with emphasis on the introduction of non-conventional renewables (particularly wind energy) and large hydropower projects in Patagonia. Both models try to reproduce the actual decision making process in the Chilean Central Interconnected System (CIS). Chile's CIS is structured as a mandatory pool with audited costs and therefore the economic dispatch can be formulated as a cost minimization problem. Consequently, hydropower reservoir operations are controlled by the ISO. Reservoirs with the most potential to cause short-term hydrologic alteration were identified from existing operational records. These records have also been used to validate our simulated operations. Results in terms of daily and subdaily hydrologic alteration as well as the economic performance of the CIS are presented for alternative energy matrix scenarios. Tradeoff curves representing the compromise between indicators of hydrologic alteration and economic indicators of the CIS operation are developed.
Development of an Improved Irrigation Subroutine in SWAT to Simulate the Hydrology of Rice Paddy Grown under Submerged Conditions

NASA Astrophysics Data System (ADS)

Muraleedharan, B. V.; Kathirvel, K.; Narasimhan, B.; Nallasamy, N. D.

2014-12-01

Soil Water Assessment Tool (SWAT) is a basin scale, distributed hydrological model commonly used to predict the effect of management decisions on the hydrologic response of watersheds. Hydrologic response is decided by the various components of water balance. In the case of watersheds located in south India as well as in several other tropical countries around the world, paddy is one of the dominant crop controlling the hydrologic response of a watershed. Hence, the suitability of SWAT in replicating the hydrology of paddy fields needs to be verified. Rice paddy fields are subjected to flooding method of irrigation, while the irrigation subroutines in SWAT are developed to simulate crops grown under non flooding conditions. Moreover irrigation is represented well in field scale models, while it is poorly represented within watershed models like SWAT. Reliable simulation of flooding method of irrigation and hydrology of the fields will assist in effective water resources management of rice paddy fields which are one of the major consumers of surface and ground water resources. The current study attempts to modify the irrigation subroutine in SWAT so as to simulate flooded irrigation condition. A field water balance study was conducted on representative fields located within Gadana, a subbasin located in Tamil Nadu (southern part of India) and dominated by rice paddy based irrigation systems. The water balance of irrigated paddy fields simulated with SWAT was compared with the water balance derived by rice paddy based crop growth model named ORYZA. The variation in water levels along with the soil moisture variation predicted by SWAT was evaluated with respect to the estimates derived from ORYZA. The water levels were further validated with field based water balance measurements taken on a daily scale. It was observed that the modified irrigation subroutine was able to simulate irrigation of rice paddy within SWAT in a realistic way compared to the existing method.
A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Heng; Ye, Ming; Walker, Anthony P.

Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averagingmore » methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less
Modeling the hydrological and mechanical effect of roots on shallow landslides

NASA Astrophysics Data System (ADS)

Arnone, E.; Caracciolo, D.; Noto, L. V.; Preti, F.; Bras, R. L.

2016-11-01

This study proposes a new methodology for estimating the additional shear strength (or cohesion) exerted by vegetation roots on slope stability analysis within a coupled hydrological-stability model. The mechanical root cohesion is estimated within a Fiber Bundle Model framework that allows for the evaluation of the root strength as a function of stress-strain relationships of populations of fibers. The use of such model requires the knowledge of the root architecture. A branching topology model based on Leonardo's rule is developed, providing an estimation of the amount of roots and the distribution of diameters with depth. The proposed methodology has been implemented into an existing distributed hydrological-stability model able to simulate the dynamics of factor of safety as a function of soil moisture dynamics. The model also accounts for the hydrological effects of vegetation, which reduces soil water content via root water uptake, thus increasing the stability. The entire methodology has been tested in a synthetic hillslope with two configurations of vegetation type, i.e., trees and shrubs, which have been compared to a configuration without vegetation. The vegetation has been characterized using roots data of two mediterranean plant species. The results demonstrate the capabilities of the topological model in accurately reproducing the observed root structure of the analyzed species. For the environmental setting modeled, the effects of root uptake might be more significant than the mechanical reinforcement; the additional resistance depends strictly on the vegetation root depth. Finally, for the simulated climatic environment, landslides are seasonal, in agreement with past observations.
PBSM3D: A finite volume, scalar-transport blowing snow model for use with variable resolution meshes

NASA Astrophysics Data System (ADS)

Marsh, C.; Wayand, N. E.; Pomeroy, J. W.; Wheater, H. S.; Spiteri, R. J.

2017-12-01

Blowing snow redistribution results in heterogeneous snowcovers that are ubiquitous in cold, windswept environments. Capturing this spatial and temporal variability is important for melt and runoff simulations. Point scale blowing snow transport models are difficult to apply in fully distributed hydrological models due to landscape heterogeneity and complex wind fields. Many existing distributed snow transport models have empirical wind flow and/or simplified wind direction algorithms that perform poorly in calculating snow redistribution where there are divergent wind flows, sharp topography, and over large spatial extents. Herein, a steady-state scalar transport model is discretized using the finite volume method (FVM), using parameterizations from the Prairie Blowing Snow Model (PBSM). PBSM has been applied in hydrological response units and grids to prairie, arctic, glacier, and alpine terrain and shows a good capability to represent snow redistribution over complex terrain. The FVM discretization takes advantage of the variable resolution mesh in the Canadian Hydrological Model (CHM) to ensure efficient calculations over small and large spatial extents. Variable resolution unstructured meshes preserve surface heterogeneity but result in fewer computational elements versus high-resolution structured (raster) grids. Snowpack, soil moisture, and streamflow observations were used to evaluate CHM-modelled outputs in a sub-arctic and an alpine basin. Newly developed remotely sensed snowcover indices allowed for validation over large basins. CHM simulations of snow hydrology were improved by inclusion of the blowing snow model. The results demonstrate the key role of snow transport processes in creating pre-melt snowcover heterogeneity and therefore governing post-melt soil moisture and runoff generation dynamics.
Short-term forecasting tools for agricultural nutrient management

USDA-ARS?s Scientific Manuscript database

The advent of real time/short term farm management tools is motivated by the need to protect water quality above and beyond the general guidance offered by existing nutrient management plans. Advances in high performance computing and hydrologic/climate modeling have enabled rapid dissemination of ...
A Narrowing Target for Early Mars Climate Models: Which Models Survive Confrontation with Improved Hydrology Constraints?

NASA Astrophysics Data System (ADS)

Kite, E. S.; Goldblatt, C.; Gao, P.; Mayer, D. P.; Sneed, J.; Wilson, S. A.

2016-12-01

The wettest climates in Mars' geologic history represent habitability optima, and also set the tightest constraints on climate models. For lake-forming climates on Early Mars, geologic data constrain discharge, duration, intermittency, and the number of lake-forming events. We synthesise new and existing data to suggest that post-Noachian lake-forming climates were widely separated in time, lasted >10^4 yr individually, were few in number, but cumulatively lasted <10^7 yr (to allow olivine to survive globally). We compare these data against existing models, set out a new model involving methane bursts, and conclude with future directions for Early Mars geologic analysis and modelling work.
Virginia flow-ecology modeling results—An initial assessment of flow reduction effects on aquatic biota

USGS Publications Warehouse

Rapp, Jennifer L.; Reilly, Pamela A.

2017-11-14

BackgroundThe U.S. Geological Survey (USGS), in cooperation with the Virginia Department of Environmental Quality (DEQ), reviewed a previously compiled set of linear regression models to assess their utility in defining the response of the aquatic biological community to streamflow depletion.As part of the 2012 Virginia Healthy Watersheds Initiative (HWI) study conducted by Tetra Tech, Inc., for the U.S. Environmental Protection Agency (EPA) and Virginia DEQ, a database with computed values of 72 hydrologic metrics, or indicators of hydrologic alteration (IHA), 37 fish metrics, and 64 benthic invertebrate metrics was compiled and quality assured. Hydrologic alteration was represented by simulation of streamflow record for a pre-water-withdrawal condition (baseline) without dams or developed land, compared to the simulated recent-flow condition (2008 withdrawal simulation) including dams and altered landscape to calculate a percent alteration of flow. Biological samples representing the existing populations represent a range of alteration in the biological community today.For this study, all 72 IHA metrics, which included more than 7,272 linear regression models, were considered. This extensive dataset provided the opportunity for hypothesis testing and prioritization of flow-ecology relations that have the potential to explain the effect(s) of hydrologic alteration on biological metrics in Virginia streams.
Error reduction and representation in stages (ERRIS) in hydrological modelling for ensemble streamflow forecasting

NASA Astrophysics Data System (ADS)

Li, Ming; Wang, Q. J.; Bennett, James C.; Robertson, David E.

2016-09-01

This study develops a new error modelling method for ensemble short-term and real-time streamflow forecasting, called error reduction and representation in stages (ERRIS). The novelty of ERRIS is that it does not rely on a single complex error model but runs a sequence of simple error models through four stages. At each stage, an error model attempts to incrementally improve over the previous stage. Stage 1 establishes parameters of a hydrological model and parameters of a transformation function for data normalization, Stage 2 applies a bias correction, Stage 3 applies autoregressive (AR) updating, and Stage 4 applies a Gaussian mixture distribution to represent model residuals. In a case study, we apply ERRIS for one-step-ahead forecasting at a range of catchments. The forecasts at the end of Stage 4 are shown to be much more accurate than at Stage 1 and to be highly reliable in representing forecast uncertainty. Specifically, the forecasts become more accurate by applying the AR updating at Stage 3, and more reliable in uncertainty spread by using a mixture of two Gaussian distributions to represent the residuals at Stage 4. ERRIS can be applied to any existing calibrated hydrological models, including those calibrated to deterministic (e.g. least-squares) objectives.
Empirical tools for simulating salinity in the estuaries in Everglades National Park, Florida

NASA Astrophysics Data System (ADS)

Marshall, F. E.; Smith, D. T.; Nickerson, D. M.

2011-12-01

Salinity in a shallow estuary is affected by upland freshwater inputs (surface runoff, stream/canal flows, groundwater), atmospheric processes (precipitation, evaporation), marine connectivity, and wind patterns. In Everglades National Park (ENP) in South Florida, the unique Everglades ecosystem exists as an interconnected system of fresh, brackish, and salt water marshes, mangroves, and open water. For this effort a coastal aquifer conceptual model of the Everglades hydrologic system was used with traditional correlation and regression hydrologic techniques to create a series of multiple linear regression (MLR) salinity models from observed hydrologic, marine, and weather data. The 37 ENP MLR salinity models cover most of the estuarine areas of ENP and produce daily salinity simulations that are capable of estimating 65-80% of the daily variability in salinity depending upon the model. The Root Mean Squared Error is typically about 2-4 salinity units, and there is little bias in the predictions. However, the absolute error of a model prediction in the nearshore embayments and the mangrove zone of Florida Bay may be relatively large for a particular daily simulation during the seasonal transitions. Comparisons show that the models group regionally by similar independent variables and salinity regimes. The MLR salinity models have approximately the same expected range of simulation accuracy and error as higher spatial resolution salinity models.
Database of small research watersheds for the territory of former Soviet Union as a source of data for improving hydrological models and their parameterizations in different geographical conditions

NASA Astrophysics Data System (ADS)

Lebedeva, Liudmila; Semenova, Olga

2013-04-01

One of widely claimed problems in modern modelling hydrology is lack of available information to investigate hydrological processes and improve their representation in the models. In spite of this, one hardly might confidently say that existing "traditional" data sources have been already fully analyzed and made use of. There existed the network of research watersheds in USSR called water-balance stations where comprehensive and extensive hydrometeorological measurements were conducted according to more or less single program during the last 40-60 years. The program (where not ceased) includes observations of discharges in several, often nested and homogeneous, small watersheds, meteorological elements, evaporation, soil temperature and moisture, snow depths, etc. The network covered different climatic and landscape zones and was established in the middle of the last century with the aim of investigation of the runoff formation in different conditions. Until recently the long-term observational data accompanied by descriptions and maps had existed only in hard copies. It partly explains why these datasets are not enough exploited yet and very rarely or even never were used for the purposes of hydrological modelling although they seem to be much more promising than implementation of the completely new measuring techniques not detracting from its importance. The goal of the presented work is development of a database of observational data and supportive materials from small research watersheds across the territory of the former Soviet Union. The first version of the database will include the following information for 12 water-balance stations across Russia, Ukraine, Kazahstan and Turkmenistan: daily values of discharges (one or several watersheds), air temperature, humidity, precipitation (one or several gauges), soil and snow state variables, soil and snow evaporation. The stations will cover desert and semi desert, steppe and forest steppe, forest, permafrost and mountainous zones. Supportive material will include maps of watershed boundaries and location of observational sites. Text descriptions of the data, measuring techniques and hydrometeorological conditions related to each of the water-balance station will accompany the datasets. The database is supposed to be expanded with time in number of the stations (by 20) and available data series for each of them. It will be uploaded to the internet with open access to everyone interested in. Such a database allows one to test hydrological models and separate modules for their adequacy and workability in different conditions and can serve as a base for models comparison and evaluation. Special profit of the database will gain models that don't rely on calibration but on the adequate process representation and use of the observable parameters. One of such models, process-based Hydrograph model, will be tested against the data from every watershed from the developed database. The aim of the Hydrograph model application to the as many as possible number of research data-rich watersheds in different climatic zones is both amending the algorithms and creation and adjustment of the model parameters that allow using the model across the geographic spectrum.
A Comparison of Groundwater Storage Using GRACE Data, Groundwater Levels, and a Hydrological Model in Californias Central Valley

NASA Technical Reports Server (NTRS)

Kuss, Amber; Brandt, William; Randall, Joshua; Floyd, Bridget; Bourai, Abdelwahab; Newcomer, Michelle; Skiles, Joseph; Schmidt, Cindy

2011-01-01

The Gravity Recovery and Climate Experiment (GRACE) measures changes in total water storage (TWS) remotely, and may provide additional insight to the use of well-based data in California's agriculturally productive Central Valley region. Under current California law, well owners are not required to report groundwater extraction rates, making estimation of total groundwater extraction difficult. As a result, other groundwater change detection techniques may prove useful. From October 2002 to September 2009, GRACE was used to map changes in TWS for the three hydrological regions (the Sacramento River Basin, the San Joaquin River Basin, and the Tulare Lake Basin) encompassing the Central Valley aquifer. Net groundwater storage changes were calculated from the changes in TWS for each of the three hydrological regions and by incorporating estimates for additional components of the hydrological budget including precipitation, evapotranspiration, soil moisture, snow pack, and surface water storage. The calculated changes in groundwater storage were then compared to simulated values from the California Department of Water Resource's Central Valley Groundwater- Surface Water Simulation Model (C2VSIM) and their Water Data Library (WDL) Geographic Information System (GIS) change in storage tool. The results from the three methods were compared. Downscaling GRACE data into the 21 smaller Central Valley sub-regions included in C2VSIM was also evaluated. This work has the potential to improve California's groundwater resource management and use of existing hydrological models for the Central Valley.
Field Scale Optimization for Long-Term Sustainability of Best Management Practices in Watersheds

NASA Astrophysics Data System (ADS)

Samuels, A.; Babbar-Sebens, M.

2012-12-01

Agricultural and urban land use changes have led to disruption of natural hydrologic processes and impairment of streams and rivers. Multiple previous studies have evaluated Best Management Practices (BMPs) as means for restoring existing hydrologic conditions and reducing impairment of water resources. However, planning of these practices have relied on watershed scale hydrologic models for identifying locations and types of practices at scales much coarser than the actual field scale, where landowners have to plan, design and implement the practices. Field scale hydrologic modeling provides means for identifying relationships between BMP type, spatial location, and the interaction between BMPs at a finer farm/field scale that is usually more relevant to the decision maker (i.e. the landowner). This study focuses on development of a simulation-optimization approach for field-scale planning of BMPs in the School Branch stream system of Eagle Creek Watershed, Indiana, USA. The Agricultural Policy Environmental Extender (APEX) tool is used as the field scale hydrologic model, and a multi-objective optimization algorithm is used to search for optimal alternatives. Multiple climate scenarios downscaled to the watershed-scale are used to test the long term performance of these alternatives and under extreme weather conditions. The effectiveness of these BMPs under multiple weather conditions are included within the simulation-optimization approach as a criteria/goal to assist landowners in identifying sustainable design of practices. The results from these scenarios will further enable efficient BMP planning for current and future usage.
Including policy and management in socio-hydrology models: initial conceptualizations

NASA Astrophysics Data System (ADS)

Hermans, Leon; Korbee, Dorien

2017-04-01

Socio-hydrology studies the interactions in coupled human-water systems. So far, the use of dynamic models that capture the direct feedback between societal and hydrological systems has been dominant. What has not yet been included with any particular emphasis, is the policy or management layer, which is a central element in for instance integrated water resources management (IWRM) or adaptive delta management (ADM). Studying the direct interactions between human-water systems generates knowledges that eventually helps influence these interactions in ways that may ensure better outcomes - for society and for the health and sustainability of water systems. This influence sometimes occurs through spontaneous emergence, uncoordinated by societal agents - private sector, citizens, consumers, water users. However, the term 'management' in IWRM and ADM also implies an additional coordinated attempt through various public actors. This contribution is a call to include the policy and management dimension more prominently into the research focus of the socio-hydrology field, and offers first conceptual variables that should be considered in attempts to include this policy or management layer in socio-hydrology models. This is done by drawing on existing frameworks to study policy processes throughout both planning and implementation phases. These include frameworks such as the advocacy coalition framework, collective learning and policy arrangements, which all emphasis longer-term dynamics and feedbacks between actor coalitions in strategic planning and implementation processes. A case about longter-term dynamics in the management of the Haringvliet in the Netherlands is used to illustrate the paper.
A novel spatial performance metric for robust pattern optimization of distributed hydrological models

NASA Astrophysics Data System (ADS)

Stisen, S.; Demirel, C.; Koch, J.

2017-12-01

Evaluation of performance is an integral part of model development and calibration as well as it is of paramount importance when communicating modelling results to stakeholders and the scientific community. There exists a comprehensive and well tested toolbox of metrics to assess temporal model performance in the hydrological modelling community. On the contrary, the experience to evaluate spatial performance is not corresponding to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study aims at making a contribution towards advancing spatial pattern oriented model evaluation for distributed hydrological models. This is achieved by introducing a novel spatial performance metric which provides robust pattern performance during model calibration. The promoted SPAtial EFficiency (spaef) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multi-component approach is necessary in order to adequately compare spatial patterns. spaef, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are tested in a spatial pattern oriented model calibration of a catchment model in Denmark. The calibration is constrained by a remote sensing based spatial pattern of evapotranspiration and discharge timeseries at two stations. Our results stress that stand-alone metrics tend to fail to provide holistic pattern information to the optimizer which underlines the importance of multi-component metrics. The three spaef components are independent which allows them to complement each other in a meaningful way. This study promotes the use of bias insensitive metrics which allow comparing variables which are related but may differ in unit in order to optimally exploit spatial observations made available by remote sensing platforms. We see great potential of spaef across environmental disciplines dealing with spatially distributed modelling.
Applying Multimodel Ensemble from Regional Climate Models for Improving Runoff Projections on Semiarid Regions of Spain

NASA Astrophysics Data System (ADS)

Garcia Galiano, S. G.; Olmos, P.; Giraldo Osorio, J. D.

2015-12-01

In the Mediterranean area, significant changes on temperature and precipitation are expected throughout the century. These trends could exacerbate the existing conditions in regions already vulnerable to climatic variability, reducing the water availability. Improving knowledge about plausible impacts of climate change on water cycle processes at basin scale, is an important step for building adaptive capacity to the impacts in this region, where severe water shortages are expected for the next decades. RCMs ensemble in combination with distributed hydrological models with few parameters, constitutes a valid and robust methodology to increase the reliability of climate and hydrological projections. For reaching this objective, a novel methodology for building Regional Climate Models (RCMs) ensembles of meteorological variables (rainfall an temperatures), was applied. RCMs ensembles are justified for increasing the reliability of climate and hydrological projections. The evaluation of RCMs goodness-of-fit to build the ensemble is based on empirical probability density functions (PDF) extracted from both RCMs dataset and a highly resolution gridded observational dataset, for the time period 1961-1990. The applied method is considering the seasonal and annual variability of the rainfall and temperatures. The RCMs ensembles constitute the input to a distributed hydrological model at basin scale, for assessing the runoff projections. The selected hydrological model is presenting few parameters in order to reduce the uncertainties involved. The study basin corresponds to a head basin of Segura River Basin, located in the South East of Spain. The impacts on runoff and its trend from observational dataset and climate projections, were assessed. Considering the control period 1961-1990, plausible significant decreases in runoff for the time period 2021-2050, were identified.

Investigating the Capacity of Hydrological Models to Project Impacts of Climate Change in the Context of Water Allocation

NASA Astrophysics Data System (ADS)

Velez, Carlos; Maroy, Edith; Rocabado, Ivan; Pereira, Fernando

2017-04-01

To analyse the impacts of climate changes, hydrological models are used to project the hydrology responds under future conditions that normally differ from those for which they were calibrated. The challenge is to assess the validity of the projected effects when there is not data to validate it. A framework for testing the ability of models to project climate change was proposed by Refsgaard et al., (2014). The authors recommend the use of the differential-split sample test (DSST) in order to build confidence in the model projections. The method follow three steps: 1. A small number of sub-periods are selected according to one climate characteristics, 2. The calibration - validation test is applied on these periods, 3. The validation performances are compered to evaluate whether they vary significantly when climatic characteristics differ between calibration and validation. DSST rely on the existing records of climate and hydrological variables; and performances are estimated based on indicators of error between observed and simulated variables. Other authors suggest that, since climate models are not able to reproduce single events but rather statistical properties describing the climate, this should be reflected when testing hydrological models. Thus, performance criteria such as RMSE should be replaced by for instance flow duration curves or other distribution functions. Using this type of performance criteria, Van Steenbergen and Willems, (2012) proposed a method to test the validity of hydrological models in a climate changing context. The method is based on the evaluation of peak flow increases due to different levels of rainfall increases. In contrast to DSST, this method use the projected climate variability and it is especially useful to compare different modelling tools. In the framework of a water allocation project for the region of Flanders (Belgium) we calibrated three hydrological models: NAM, PDM and VHM; for 67 gauged sub-catchments with approx. 40 years of records. This paper investigates the capacity of the three hydrological models to project the impacts of climate change scenarios. It is proposed a general testing framework which combine the use of the existing information through an adapted form of DSST with the approach proposed by Van Steenbergen and Willems, (2012) adapted to assess statistical properties of flows useful in the context of water allocation. To assess the model we use robustness criteria based on a Log Nash-Sutcliffe, BIAS on cummulative volumes and relative changes based on Q50/Q90 estimated from the duration curve. The three conceptual rainfall-runoff models yielded different results per sub-catchments. A relation was found between robustness criteria and changes in mean rainfall and changes in mean potential evapotranspiration. Biases are greatly affected by changes in precipitation, especially when the climate scenarios involve changes in precipitation volume beyond the range used for calibration. Using the combine approach we were able to classify the modelling tools per sub-catchments and create an ensemble of best models to project the impacts of climate variability for the catchments of 10 main rivers in Flanders. Thus, managers could understand better the usability of the modelling tools and the credibility of its outputs for water allocation applications. References Refsgaard, J.C., Madsen, H., Andréassian, V., Arnbjerg-Nielsen, K., Davidson, T.A., Drews, M., Hamilton, D.P., Jeppesen, E., Kjellström, E., Olesen, J.E., Sonnenborg, T.O., Trolle, D., Willems, P., Christensen, J.H., 2014. A framework for testing the ability of models to project climate change and its impacts. Clim. Change. Van Steenbergen, N., Willems, P., 2012. Method for testing the accuracy of rainfall - runoff models in predicting peak flow changes due to rainfall changes , in a climate changing context. J. Hydrol. 415, 425-434.
Assessing the impacts of climate change in Mediterranean catchments under conditions of data scarcity

NASA Astrophysics Data System (ADS)

Meyer, Swen; Ludwig, Ralf

2013-04-01

According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. While there is scientific consensus that climate induced changes on the hydrology of Mediterranean regions are presently occurring and are projected to amplify in the future, very little knowledge is available about the quantification of these changes, which is hampered by a lack of suitable and cost effective hydrological monitoring and modeling systems. The European FP7-project CLIMB is aiming to analyze climate induced changes on the hydrology of the Mediterranean Basins by investigating 7 test sites located in the countries Italy, France, Turkey, Tunisia, Gaza and Egypt. CLIMB employs a combination of novel geophysical field monitoring concepts, remote sensing techniques and integrated hydrologic modeling to improve process descriptions and understanding and to quantify existing uncertainties in climate change impact analysis. The Rio Mannu Basin, located in Sardinia; Italy, is one test site of the CLIMB project. The catchment has a size of 472.5 km2, it ranges from 62 to 946 meters in elevation, at mean annual temperatures of 16°C and precipitation of about 700 mm, the annual runoff volume is about 200 mm. The physically based Water Simulation Model WaSiM Vers. 2 (Schulla & Jasper (1999)) was setup to model current and projected future hydrological conditions. The availability of measured meteorological and hydrological data is poor as common to many Mediterranean catchments. The lack of available measured input data hampers the calibration of the model setup and the validation of model outputs. State of the art remote sensing techniques and field measuring techniques were applied to improve the quality of hydrological input parameters. In a field campaign about 250 soil samples were collected and lab-analyzed. Different geostatistical regionalization methods were tested to improve the model setup. The soil parameterization of the model was tested against publically available soil data. Results show a significant improvement of modeled soil moisture outputs. To validate WaSiMs evapotranspiration (ETact) outputs, Landsat TM images were used to calculate the actual monthly mean ETact rates using the triangle method (Jiang and Islam, 1999). Simulated spatial ETact patterns and those derived from remote sensing show a good fit especially for the growing season. WaSiM was driven with the meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. Output results were analyzed for climate induced changes on selected hydrological variables. While the climate projections reveal increased precipitation rates in the spring season, first simulation results show an earlier onset and an increased duration of the dry season, imposing an increased irrigation demand and higher vulnerability of agricultural productivity.
An Efficient Approach to Modeling the Topographic Control of Surface Hydrology for Regional and Global Climate Modeling.

NASA Astrophysics Data System (ADS)

Stieglitz, Marc; Rind, David; Famiglietti, James; Rosenzweig, Cynthia

1997-01-01

The current generation of land-surface models used in GCMs view the soil column as the fundamental hydrologic unit. While this may be effective in simulating such processes as the evolution of ground temperatures and the growth/ablation of a snowpack at the soil plot scale, it effectively ignores the role topography plays in the development of soil moisture heterogeneity and the subsequent impacts of this soil moisture heterogeneity on watershed evapotranspiration and the partitioning of surface fluxes. This view also ignores the role topography plays in the timing of discharge and the partitioning of discharge into surface runoff and baseflow. In this paper an approach to land-surface modeling is presented that allows us to view the watershed as the fundamental hydrologic unit. The analytic form of TOPMODEL equations are incorporated into the soil column framework and the resulting model is used to predict the saturated fraction of the watershed and baseflow in a consistent fashion. Soil moisture heterogeneity represented by saturated lowlands subsequently impacts the partitioning of surface fluxes, including evapotranspiration and runoff. The approach is computationally efficient, allows for a greatly improved simulation of the hydrologic cycle, and is easily coupled into the existing framework of the current generation of single column land-surface models. Because this approach uses the statistics of the topography rather than the details of the topography, it is compatible with the large spatial scales of today's regional and global climate models. Five years of meteorological and hydrological data from the Sleepers River watershed located in the northeastern United States where winter snow cover is significant were used to drive the new model. Site validation data were sufficient to evaluate model performance with regard to various aspects of the watershed water balance, including snowpack growth/ablation, the spring snowmelt hydrograph, storm hydrographs, and the seasonal development of watershed evapotranspiration and soil moisture.
Meta-analysis of field-saturated hydraulic conductivity recovery following wildland fire: Applications for hydrologic model parameterization and resilience assessment

USGS Publications Warehouse

Ebel, Brian A.; Martin, Deborah

2017-01-01

Hydrologic recovery after wildfire is critical for restoring the ecosystem services of protecting of human lives and infrastructure from hazards and delivering water supply of sufficient quality and quantity. Recovery of soil-hydraulic properties, such as field-saturated hydraulic conductivity (Kfs), is a key factor for assessing the duration of watershed-scale flash flood and debris flow risks after wildfire. Despite the crucial role of Kfs in parameterizing numerical hydrologic models to predict the magnitude of postwildfire run-off and erosion, existing quantitative relations to predict Kfsrecovery with time since wildfire are lacking. Here, we conduct meta-analyses of 5 datasets from the literature that measure or estimate Kfs with time since wildfire for longer than 3-year duration. The meta-analyses focus on fitting 2 quantitative relations (linear and non-linear logistic) to explain trends in Kfs temporal recovery. The 2 relations adequately described temporal recovery except for 1 site where macropore flow dominated infiltration and Kfs recovery. This work also suggests that Kfs can have low hydrologic resistance (large postfire changes), and moderate to high hydrologic stability (recovery time relative to disturbance recurrence interval) and resilience (recovery of hydrologic function and provision of ecosystem services). Future Kfs relations could more explicitly incorporate processes such as soil-water repellency, ground cover and soil structure regeneration, macropore recovery, and vegetation regrowth.
Simulating the influence of groundwater table fluctuation on vapor intrusion

NASA Astrophysics Data System (ADS)

Huo, J.

2017-12-01

The migration of volatile chemicals from groundwater to an overlying building is a commonly existing phenomenon around the world. Due to the distinction of hydrologic conditions among vapor intrusion sites, it is necessary to consider the effect of dominant hydrologic factors in order to obtain a precise site evaluation and a health risk assessment during the screening process. This study mainly discusses the impact of groundwater table fluctuation and other hydrological factors including porosity, permeability and soil moisture on the vapor intrusion transport. A two-dimensional model is configured to inject different typical volatile organic contaminants from EPA's Vapor Intrusion Database. Through quantifying the contaminant vapor concentration attenuation factors under the effect of groundwater table fluctuation, this study provides suggestions for indoor air sample and vapor intrusion assessment.
Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

DOE PAGES

Xi, Maolong; Lu, Dan; Gui, Dongwei; ...

2016-11-27

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less
Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

NASA Astrophysics Data System (ADS)

Xi, Maolong; Lu, Dan; Gui, Dongwei; Qi, Zhiming; Zhang, Guannan

2017-01-01

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so as to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.
Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xi, Maolong; Lu, Dan; Gui, Dongwei

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less
On the Representation of Subgrid Microtopography Effects in Process-based Hydrologic Models

NASA Astrophysics Data System (ADS)

Jan, A.; Painter, S. L.; Coon, E. T.

2017-12-01

Increased availability of high-resolution digital elevation are enabling process-based hydrologic modeling on finer and finer scales. However, spatial variability in surface elevation (microtopography) exists below the scale of a typical hyper-resolution grid cell and has the potential to play a significant role in water retention, runoff, and surface/subsurface interactions. Though the concept of microtopographic features (depressions, obstructions) and the associated implications on flow and discharge are well established, representing those effects in watershed-scale integrated surface/subsurface hydrology models remains a challenge. Using the complex and coupled hydrologic environment of the Arctic polygonal tundra as an example, we study the effects of submeter topography and present a subgrid model parameterized by small-scale spatial heterogeneities for use in hyper-resolution models with polygons at a scale of 15-20 meters forming the surface cells. The subgrid model alters the flow and storage terms in the diffusion wave equation for surface flow. We compare our results against sub-meter scale simulations (acts as a benchmark for our simulations) and hyper-resolution models without the subgrid representation. The initiation of runoff in the fine-scale simulations is delayed and the recession curve is slowed relative to simulated runoff using the hyper-resolution model with no subgrid representation. Our subgrid modeling approach improves the representation of runoff and water retention relative to models that ignore subgrid topography. We evaluate different strategies for parameterizing subgrid model and present a classification-based method to efficiently move forward to larger landscapes. This work was supported by the Interoperable Design of Extreme-scale Application Software (IDEAS) project and the Next-Generation Ecosystem Experiments-Arctic (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the DOE Office of Science.
Dynamic Hydrological Discharge Modelling for Fully Coupled Paleoclimate Runs of the Last Glacial Cycle

NASA Astrophysics Data System (ADS)

Riddick, Thomas; Brovkin, Victor; Hagemann, Stefan; Mikolajewicz, Uwe

2017-04-01

The continually evolving large ice sheets present in the Northern Hemisphere during the last glacial cycle caused significant changes to river pathways both through directly blocking rivers and through glacial isostatic adjustment. These river pathway changes are believed to of had a significant impact on the evolution of ocean circulation through changing the pattern of fresh water discharge into the oceans. A fully coupled ESM simulation of the last glacial cycle thus requires a hydrological discharge model that uses a set of river pathways that evolve with the earth's changing orography while being able to reproduce the known present-day river network given the present-day orography. Here we present a method for dynamically modelling hydrological discharge that meets such requirements by applying relative manual corrections to an evolving fine scale orography (accounting for the changing ice sheets and isostatic rebound) each time the river directions are recalculated. The corrected orography thus produced is then used to create a set of fine scale river pathways and these are then upscaled to a course scale. An existing present-day hydrological discharge model within the JSBACH3 land surface model is run using the course scale river pathways generated. This method will be used in fully coupled paleoclimate runs made using MPI-ESM1 as part of the PalMod project. Tests show this procedure reproduces the known present-day river network to a sufficient degree of accuracy.
Evaluation of fine soil moisture data from the IFloodS (NASA GPM) Ground Validation campaign using a fully-distributed ecohydrological model

NASA Astrophysics Data System (ADS)

Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L.

2014-12-01

The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units.
Modelling the interaction between flooding events and economic growth

NASA Astrophysics Data System (ADS)

Grames, J.; Prskawetz, A.; Grass, D.; Blöschl, G.

2015-06-01

Socio-hydrology describes the interaction between the socio-economy and water. Recent models analyze the interplay of community risk-coping culture, flooding damage and economic growth (Di Baldassarre et al., 2013; Viglione et al., 2014). These models descriptively explain the feedbacks between socio-economic development and natural disasters like floods. Contrary to these descriptive models, our approach develops an optimization model, where the intertemporal decision of an economic agent interacts with the hydrological system. In order to build this first economic growth model describing the interaction between the consumption and investment decisions of an economic agent and the occurrence of flooding events, we transform an existing descriptive stochastic model into an optimal deterministic model. The intermediate step is to formulate and simulate a descriptive deterministic model. We develop a periodic water function to approximate the former discrete stochastic time series of rainfall events. Due to the non-autonomous exogenous periodic rainfall function the long-term path of consumption and investment will be periodic.
Performance of the Hydrological Portion of a Simple Water Quality Model in Different Climatic Regions

NASA Astrophysics Data System (ADS)

Moore, K.; Pierson, D.; Pettersson, K.; Naden, P.; Allott, N.; Jennings, E.; Tamm, T.; Järvet, A.; Nickus, U.; Thies, H.; Arvola, L.; Järvinen, M.; Schneiderman, E.; Zion, M.; Lounsbury, D.

2004-05-01

We are applying an existing watershed model in the EU CLIME (Climate and Lake Impacts in Europe) project to evaluate the effects of weather on seasonal and annual delivery of N, P, and DOC to lakes. Model calibration is based on long-term records of weather and water quality data collected from sites in different climatic regions spread across Europe and in New York State. The overall aim of the CLIME project is to develop methods and models to support lake and catchment management under current climate conditions and make predictions under future climate scenarios. Scientists from 10 partner countries are collaborating on developing a consistent approach to defining model parameters for the Generalized Watershed Loading Functions (GWLF) model, one of a larger suite of models used in the project. An example of the approach for the hydrological portion of the GWLF model will be presented, with consideration of the balance between model simplicity, ease of use, data requirements, and realistic predictions.
Hydrology Analysis and Modelling for Klang River Basin Flood Hazard Map

NASA Astrophysics Data System (ADS)

Sidek, L. M.; Rostam, N. E.; Hidayah, B.; Roseli, ZA; Majid, W. H. A. W. A.; Zahari, N. Z.; Salleh, S. H. M.; Ahmad, R. D. R.; Ahmad, M. N.

2016-03-01

Flooding, a common environmental hazard worldwide has in recent times, increased as a result of climate change and urbanization with the effects felt more in developing countries. As a result, the explosive of flooding to Tenaga Nasional Berhad (TNB) substation is increased rapidly due to existing substations are located in flood prone area. By understanding the impact of flood to their substation, TNB has provided the non-structure mitigation with the integration of Flood Hazard Map with their substation. Hydrology analysis is the important part in providing runoff as the input for the hydraulic part.
A Budyko-type Model for Human Water Consumption

NASA Astrophysics Data System (ADS)

Lei, X.; Zhao, J.; Wang, D.; Sivapalan, M.

2017-12-01

With the expansion of human water footprint, water crisis is no longer only a conflict or competition for water between different economic sectors, but also increasingly between human and the environment. In order to describe the emergent dynamics and patterns of the interaction, a theoretical framework that encapsulates the physical and societal controls impacting human water consumption is needed. In traditional hydrology, Budyko-type models are simple but efficient descriptions of vegetation-mediated hydrologic cycle in catchments, i.e., the partitioning of mean annual precipitation into runoff and evapotranspiration. Plant water consumption plays a crucial role in the process. Hypothesized similarities between human-water and vegetation-water interactions, including water demand, constraints and system functioning, give the idea of corresponding Budyko-type framework for human water consumption at the catchment scale. Analogous to variables of Budyko-type models for hydrologic cycle, water demand, water consumption, environmental water use and available water are corresponding to potential evaporation, actual evaporation, runoff and precipitation respectively. Human water consumption data, economic and hydro-meteorological data for 51 human-impacted catchments and 10 major river basins in China are assembled to look for the existence of a Budyko-type relationship for human water consumption, and to seek explanations for the spread in the observed relationship. Guided by this, a Budyko-type analytical model is derived based on application of an optimality principle, that of maximum water benefit. The model derived has the same functional form and mathematical features as those that apply for the original Budyko model. Parameters of the new Budyko-type model for human consumption are linked to economic and social factors. The results of this paper suggest that the functioning of both social and hydrologic subsystems within catchment systems can be explored within a common conceptual framework, thus providing a unified socio-hydrologic basis for the study of coupled human-water systems. The exploration of the theoretical connections between the two subsystems pushes the water system modeling from a problem-solving orientation to puzzle-solving orientation.
Inter-model variability in hydrological extremes projections for Amazonian sub-basins

NASA Astrophysics Data System (ADS)

Andres Rodriguez, Daniel; Garofolo, Lucas; Lázaro de Siqueira Júnior, José; Samprogna Mohor, Guilherme; Tomasella, Javier

2014-05-01

Irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process drive uncertainties in Climate Change projections. Such uncertainties affect the impact studies, mainly when associated to extreme events, and difficult the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. The use of different climate model's projections allows to aboard uncertainties issues allowing the use of multiple runs to explore a wide range of potential impacts and its implications for potential vulnerabilities. Statistical approaches for analyses of extreme values are usually based on stationarity assumptions. However, nonstationarity is relevant at the time scales considered for extreme value analyses and could have great implications in dynamic complex systems, mainly under climate change transformations. Because this, it is required to consider the nonstationarity in the statistical distribution parameters. We carried out a study of the dispersion in hydrological extremes projections using climate change projections from several climate models to feed the Distributed Hydrological Model of the National Institute for Spatial Research, MHD-INPE, applied in Amazonian sub-basins. This model is a large-scale hydrological model that uses a TopModel approach to solve runoff generation processes at the grid-cell scale. MHD-INPE model was calibrated for 1970-1990 using observed meteorological data and comparing observed and simulated discharges by using several performance coeficients. Hydrological Model integrations were performed for present historical time (1970-1990) and for future period (2010-2100). Because climate models simulate the variability of the climate system in statistical terms rather than reproduce the historical behavior of climate variables, the performances of the model's runs during the historical period, when feed with climate model data, were tested using descriptors of the Flow Duration Curves. The analyses of projected extreme values were carried out considering the nonstationarity of the GEV distribution parameters and compared with extremes events in present time. Results show inter-model variability in a broad dispersion on projected extreme's values. Such dispersion implies different degrees of socio-economic impacts associated to extreme hydrological events. Despite the no existence of one optimum result, this variability allows the analyses of adaptation strategies and its potential vulnerabilities.
Conceptual model of a coastal hydrosystem in a semi-arid environment subjected to the climate change: the case of Lavrion, Greece

NASA Astrophysics Data System (ADS)

Pouliaris, Christos; Schumann, Philipp; Danneberg, Nils-Christian; Foglia, Laura; Kallioras, Andreas; Schüth, Christoph

2015-04-01

Groundwater management in arid areas has become a major issue worldwide, and it is expected to be exacerbated due to climate change. Low annual precipitation and high evaporation potential are the key features of these areas, with additional pressure added to the system due to abstractions for irrigation and water supply purposes. Typical example of such scenarios exist in the Mediterranean area, where drought and water scarcity, especially in the warm period of the hydrological year, give rise to major management issues in coastal areas. Among the different solutions, the implementation of Managed Aquifer Recharge (MAR) schemes have been suggested in the EU FP7 project MARSOL (Demonstrating Managed Aquifer Recharge as a Solution to Water Scarcity and Drought). In the project, different sites across the Mediterranean are tested for investigating the viability of various MAR techniques in different hydrological systems facing qualitative and quantitative deterioration of their groundwater resources. The coastal hydrosystem of Lavrion was selected due to its typical Mediterranean characteristics (climatic, hydrologic, hydrogeological, geological etc.); all within a rather small area of extent ( < 50km2), that render it as a reference site for hydrologic modeling applications. It consists of a set of aquifer layers (karstified limestone and alluvial) which are hydraulically connected to the sea and an ephemeral torrent (wadi) that flows through a typical small Mediterranean alluvial valley. The major water resources problems of the area are mainly qualitative issues of the groundwaters; in specific: (i) seawater intrusion, (ii) nitrate contamination and (iii) heavy metal pollution due to past and recent mining and metallurgical activities The modelling approach will include the development of three distinct models that will be integrated. The aim is to depict how systems with characteristics like the ones mentioned above perform and, which different scenarios can be applied, aiming at identifying the most viable (with respect to water budget) MAR strategy for the specific area. Meteorological data, field data and site investigations provide the input data for all the different models. The field activities already conducted included: an inventory of all existing pumping wells; the development of a monitoring network for qualitative and quantitative environmental data acquisition at different scales and hydrologic zones; installation of multi-level piezometers for tailored monitoring of the seawater wedge; and geophysical surveys of subsurface characterization. The combination of literature review and field investigations led to the development of the conceptual model of the area along with the realization of the spatial distribution of each model. The hydraulic connections of the two aquifers, the surface water system and the sea have been identified and the upcoming activities aim in quantifying them and include them in the models being under development. The groundwater chemical characteristics have been examined, with results showing the major influence from seawater intrusion. All the data mentioned above are used for the development of the integrated hydrological model of the Lavrion area.
Development of an integrated model for the Campaspe catchment: a tool to help improve understanding of the interaction between society, policy, farming decision, ecology, hydrology and climate

NASA Astrophysics Data System (ADS)

Iwanaga, Takuya; Zare, Fateme; Croke, Barry; Fu, Baihua; Merritt, Wendy; Partington, Daniel; Ticehurst, Jenifer; Jakeman, Anthony

2018-06-01

Management of water resources requires understanding of the hydrology and hydrogeology, as well as the policy and human drivers and their impacts. This understanding requires relevant inputs from a wide range of disciplines, which will vary depending on the specific case study. One approach to gain understanding of the impact of climate and society on water resources is through the use of an integrated modelling process that engages stakeholders and experts in specifics of problem framing, co-design of the underpinning conceptual model, and discussion of the ensuing results. In this study, we have developed such an integrated modelling process for the Campaspe basin in northern Victoria, Australia. The numerical model built has a number of components:
- - Node/link based surface water hydrology module based on the IHACRES rainfall-streamflow model
- - Distributed groundwater model for the lower catchment (MODFLOW)
- - Farm decision optimisation module (to determine irrigation requirements)
- - Policy module (setting conditions on availability of water based on existing rules)
- - Ecology module (determining the impacts of available streamflow on platypus, fish and river red gum trees)
The integrated model is component based and has been developed in Python, with the MODFLOW and surface water hydrology model run in external programs, controlled by the master program (in Python). The integrated model has been calibrated using historical data, with the intention of exploring the impact of various scenarios (future climate scenarios, different policy options, water management options) on the water resources. The scenarios were selected based on workshops with, and a social survey of, stakeholders in the basin regarding what would be socially acceptable and physically plausible options for changes in management. An example of such a change is the introduction of a managed aquifer recharge system to capture dam overflows, and store at least a portion of this in the aquifer, thereby increasing the groundwater resource as well as reducing the impact of existing pumping levels.
Operational flash flood forecasting platform based on grid technology

NASA Astrophysics Data System (ADS)

Thierion, V.; Ayral, P.-A.; Angelini, V.; Sauvagnargues-Lesage, S.; Nativi, S.; Payrastre, O.

2009-04-01

Flash flood events of south of France such as the 8th and 9th September 2002 in the Grand Delta territory caused important economic and human damages. Further to this catastrophic hydrological situation, a reform of flood warning services have been initiated (set in 2006). Thus, this political reform has transformed the 52 existing flood warning services (SAC) in 22 flood forecasting services (SPC), in assigning them territories more hydrological consistent and new effective hydrological forecasting mission. Furthermore, national central service (SCHAPI) has been created to ease this transformation and support local services in their new objectives. New functioning requirements have been identified: - SPC and SCHAPI carry the responsibility to clearly disseminate to public organisms, civil protection actors and population, crucial hydrologic information to better anticipate potential dramatic flood event, - a new effective hydrological forecasting mission to these flood forecasting services seems essential particularly for the flash floods phenomenon. Thus, models improvement and optimization was one of the most critical requirements. Initially dedicated to support forecaster in their monitoring mission, thanks to measuring stations and rainfall radar images analysis, hydrological models have to become more efficient in their capacity to anticipate hydrological situation. Understanding natural phenomenon occuring during flash floods mainly leads present hydrological research. Rather than trying to explain such complex processes, the presented research try to manage the well-known need of computational power and data storage capacities of these services. Since few years, Grid technology appears as a technological revolution in high performance computing (HPC) allowing large-scale resource sharing, computational power using and supporting collaboration across networks. Nowadays, EGEE (Enabling Grids for E-science in Europe) project represents the most important effort in term of grid technology development. This paper presents an operational flash flood forecasting platform which have been developed in the framework of CYCLOPS European project providing one of virtual organizations of EGEE project. This platform has been designed to enable multi-simulations processes to ease forecasting operations of several supervised watersheds on Grand Delta (SPC-GD) territory. Grid technology infrastructure, in providing multiple remote computing elements enables the processing of multiple rainfall scenarios, derived to the original meteorological forecasting transmitted by Meteo-France, and their respective hydrological simulations. First results show that from one forecasting scenario, this new presented approach can permit simulations of more than 200 different scenarios to support forecasters in their aforesaid mission and appears as an efficient hydrological decision-making tool. Although, this system seems operational, model validity has to be confirmed. So, further researches are necessary to improve models core to be more efficient in term of hydrological aspects. Finally, this platform could be an efficient tool for developing others modelling aspects as calibration or data assimilation in real time processing.
Temporal Variation and Scaling of Hydrological Variables in a Typical Watershed

NASA Astrophysics Data System (ADS)

Yang, C.; Zhang, Y. K.; Liang, X.; Liu, J.

2016-12-01

Temporal variations of the main hydrological variables over 16 years were systematically investigated based on the results from an integrated hydrological modeling at the Sagehen Creek Watershed in northern Sierra Nevada. Temporal scaling of these variables and damping effects of the hydrological system as well as its subsystems, i.e., the land surface, unsaturated zone, and saturated zone, were analyzed with spectral analyses. It was found that the hydrological system may act as a cascade of hierarchical fractal filters which sequentially transfer a non-fractal or less correlated fractal hydrological signal to a more correlated fractal signal. Temporal scaling of infiltration (I), actual evapotraspiration (ET), recharge (R), baseflow (BF), streamflow (SF) exist and the temporal autocorrelation of these variables increase as water moves through the system. The degree of the damping effect of the subsystems is different and is strongest in the unsaturated zone compared with that of the land surface and saturated zone. The temporal scaling of the groundwater levels (h) also exists and is strongly affected by the river: the temporal autocorrelation of h near the river is similar to that of the river stage fluctuations and increases away from the river. There is a break in the temporal scaling of h near the river at low frequencies due to the effect of the river. Temporal variations of the soil moisture (θ) is more complicated: the value of the scaling exponent (β) for θ increases with depth as water moves downwards and its high-frequency fluctuations are damped by the unsaturated zone. The temporal fluctuations of precipitation (P) and I are fractional Gauss noise (fGn), those of ET, R, BF, and SF are fractional Brownian motion (fBm), and those of h away from the river are 2nd-order fBm based on the values of β obtained in this study. Keywords: Temporal variations, Scaling, Damping effect, Hydrological system.

Project 5322 Mid-Term Report: Key Eco-Hydrological Parameters Retrieval And Land Data Assimilation System Development In A Typical Inland River Basin Of Chinas Arid Region

NASA Astrophysics Data System (ADS)

Faivre, R.; Colin, J.; Menenti, M.; Lindenbergh, R.; Van Den Bergh, L.; Yu, H.; Jia, L.; Xin, L.

2010-10-01

Improving the understanding and the monitoring of high elevation regions hydrology is of major relevance from both societal and environmental points of view for many Asian countries, in particular in terms of flood and drought, but also in terms of food security in a chang- ing environment. Satellite and airborne remote sensing technologies are of utmost for such a challenge. Exist- ing imaging spectro-radiometers, radars, microwave ra- diometers and backscatter LIDAR provide a very com- prehensive suite of measurements over a wide rage of wavelengths, time frequencies and spatial resolu- tions. It is however needed to devise new algorithms to convert these radiometric measurements into useful eco-hydrological quantitative parameters for hydrologi- cal modeling and water management. The DRAGON II project entitled Key Eco-Hydrological Parameters Re- trieval and Land Data Assimilation System Development in a Typical Inland River Basin of Chinas Arid Region (ID 5322) aims at improving the monitoring, understand- ing, and predictability of hydrological and ecological pro- cesses at catchment scale, and promote the applicability of quantitative remote sensing in watershed science. Ex- isting Earth Observation platforms provided by the Euro- pean Space Agency as well as prototype airborne systems developed in China - ENVISAT/AATSR, ALOS/PRISM and PALSAR, Airborne LIDAR - are used and combined to retrieve advanced land surface physical properties over high elevation arid regions of China. The existing syn- ergies between this project, the CEOP-AEGIS project (FP7) and the WATER project (CAS) provide incentives for innovative studies. The investigations presented in the following report focus on the development of advanced and innovative methodologies and algorithms to monitor both the state and the trend of key eco-hydrological vari- ables: 3D vegetation properties, land surface evaporation, glacier mass balance and drought indicators.
Predicting Low Flow Conditions from Climatic Indices - Indicator-Based Modeling for Climate Change Impact Assessment

NASA Astrophysics Data System (ADS)

Fangmann, Anne; Haberlandt, Uwe

2014-05-01

In the face of climate change, the assessment of future hydrological regimes has become indispensable in the field of water resources management. Investigation of potential change is vital for proper planning, especially with regard to hydrological extremes. Commonly, projection of future streamflow is done applying process-based hydrological models, using climate model data as input, whose complex model structures generally require excessive amounts of time and effort for set-up and computation. This study aims at identifying practical alternatives to the employment of sophisticated models by considering simpler, yet sufficiently accurate methods for modeling rainfall-runoff relations with regard to hydrological extremes. The focus is thereby put on the prediction of low flow periods, which are, in contrast to flood events, characterized by extended durations and spatial dimensions. The models to be established in this study base on indicators, which characterize both meteorological and hydrological conditions within dry periods. This approach makes direct use of the coupling between atmospheric driving forces and streamflow response with the underlying presumption that low-precipitation and high-evaporation periods result in diminished flow, implying that relationships exist between the properties of both meteorological and hydrological events (duration, volume, severity etc.). Eventually, optimal combinations of meteorological indicators are sought that are suitable to predict various low flow characteristics with satisfactory accuracy. Two approaches for model specification are tested: a) multiple linear regression, and b) Fuzzy logic. The data used for this study are daily time series of mean discharge obtained from 294 gauges with variable record length situated in the federal state of Lower Saxony, Germany, as well as interpolated climate variables available for a period from 1951 to 2011. After extraction of a variety of indicators from the available discharge and climate time series on a bi-annual basis, regression and Fuzzy models are fit. Fitting is done in two variations: locally at each of the watersheds in the study area, and regionally, yielding one specific model expression for the entire study area. Models for the individual stations perform well using only the meteorological indicators as predictor variables, while the regional models require the additional input of catchment descriptors to account for the variability of the rainfall-runoff translation processes between the catchments.
A hybrid framework for quantifying the influence of data in hydrological model calibration

NASA Astrophysics Data System (ADS)

Wright, David P.; Thyer, Mark; Westra, Seth; McInerney, David

2018-06-01

Influence diagnostics aim to identify a small number of influential data points that have a disproportionate impact on the model parameters and/or predictions. The key issues with current influence diagnostic techniques are that the regression-theory approaches do not provide hydrologically relevant influence metrics, while the case-deletion approaches are computationally expensive to calculate. The main objective of this study is to introduce a new two-stage hybrid framework that overcomes these challenges, by delivering hydrologically relevant influence metrics in a computationally efficient manner. Stage one uses computationally efficient regression-theory influence diagnostics to identify the most influential points based on Cook's distance. Stage two then uses case-deletion influence diagnostics to quantify the influence of points using hydrologically relevant metrics. To illustrate the application of the hybrid framework, we conducted three experiments on 11 hydro-climatologically diverse Australian catchments using the GR4J hydrological model. The first experiment investigated how many data points from stage one need to be retained in order to reliably identify those points that have the hightest influence on hydrologically relevant metrics. We found that a choice of 30-50 is suitable for hydrological applications similar to those explored in this study (30 points identified the most influential data 98% of the time and reduced the required recalibrations by 99% for a 10 year calibration period). The second experiment found little evidence of a change in the magnitude of influence with increasing calibration period length from 1, 2, 5 to 10 years. Even for 10 years the impact of influential points can still be high (>30% influence on maximum predicted flows). The third experiment compared the standard least squares (SLS) objective function with the weighted least squares (WLS) objective function on a 10 year calibration period. In two out of three flow metrics there was evidence that SLS, with the assumption of homoscedastic residual error, identified data points with higher influence (largest changes of 40%, 10%, and 44% for the maximum, mean, and low flows, respectively) than WLS, with the assumption of heteroscedastic residual errors (largest changes of 26%, 6%, and 6% for the maximum, mean, and low flows, respectively). The hybrid framework complements existing model diagnostic tools and can be applied to a wide range of hydrological modelling scenarios.
Representing macropore flow at the catchment scale: a comparative modeling study

NASA Astrophysics Data System (ADS)

Liu, D.; Li, H. Y.; Tian, F.; Leung, L. R.

2017-12-01

Macropore flow is an important hydrological process that generally enhances the soil infiltration capacity and velocity of subsurface water. Up till now, macropore flow is mostly simulated with high-resolution models. One possible drawback of this modeling approach is the difficulty to effectively represent the overall typology and connectivity of the macropore networks. We hypothesize that modeling macropore flow directly at the catchment scale may be complementary to the existing modeling strategy and offer some new insights. Tsinghua Representative Elementary Watershed model (THREW model) is a semi-distributed hydrology model, where the fundamental building blocks are representative elementary watersheds (REW) linked by the river channel network. In THREW, all the hydrological processes are described with constitutive relationships established directly at the REW level, i.e., catchment scale. In this study, the constitutive relationship of macropore flow drainage is established as part of THREW. The enhanced THREW model is then applied at two catchments with deep soils but distinct climates, the humid Asu catchment in the Amazon River basin, and the arid Wei catchment in the Yellow River basin. The Asu catchment has an area of 12.43km2 with mean annual precipitation of 2442mm. The larger Wei catchment has an area of 24800km2 but with mean annual precipitation of only 512mm. The rainfall-runoff processes are simulated at a hourly time step from 2002 to 2005 in the Asu catchment and from 2001 to 2012 in the Wei catchment. The role of macropore flow on the catchment hydrology will be analyzed comparatively over the Asu and Wei catchments against the observed streamflow, evapotranspiration and other auxiliary data.
Large-watershed flood simulation and forecasting based on different-resolution distributed hydrological model

NASA Astrophysics Data System (ADS)

Li, J.

2017-12-01

Large-watershed flood simulation and forecasting is very important for a distributed hydrological model in the application. There are some challenges including the model's spatial resolution effect, model performance and accuracy and so on. To cope with the challenge of the model's spatial resolution effect, different model resolution including 1000m*1000m, 600m*600m, 500m*500m, 400m*400m, 200m*200m were used to build the distributed hydrological model—Liuxihe model respectively. The purpose is to find which one is the best resolution for Liuxihe model in Large-watershed flood simulation and forecasting. This study sets up a physically based distributed hydrological model for flood forecasting of the Liujiang River basin in south China. Terrain data digital elevation model (DEM), soil type and land use type are downloaded from the website freely. The model parameters are optimized by using an improved Particle Swarm Optimization(PSO) algorithm; And parameter optimization could reduce the parameter uncertainty that exists for physically deriving model parameters. The different model resolution (200m*200m—1000m*1000m ) are proposed for modeling the Liujiang River basin flood with the Liuxihe model in this study. The best model's spatial resolution effect for flood simulation and forecasting is 200m*200m.And with the model's spatial resolution reduction, the model performance and accuracy also become worse and worse. When the model resolution is 1000m*1000m, the flood simulation and forecasting result is the worst, also the river channel divided based on this resolution is differs from the actual one. To keep the model with an acceptable performance, minimum model spatial resolution is needed. The suggested threshold model spatial resolution for modeling the Liujiang River basin flood is a 500m*500m grid cell, but the model spatial resolution with a 200m*200m grid cell is recommended in this study to keep the model at a best performance.
Landscape modeling for Everglades ecosystem restoration

USGS Publications Warehouse

DeAngelis, D.L.; Gross, L.J.; Huston, M.A.; Wolff, W.F.; Fleming, D.M.; Comiskey, E.J.; Sylvester, S.M.

1998-01-01

A major environmental restoration effort is under way that will affect the Everglades and its neighboring ecosystems in southern Florida. Ecosystem and population-level modeling is being used to help in the planning and evaluation of this restoration. The specific objective of one of these modeling approaches, the Across Trophic Level System Simulation (ATLSS), is to predict the responses of a suite of higher trophic level species to several proposed alterations in Everglades hydrology. These include several species of wading birds, the snail kite, Cape Sable seaside sparrow, Florida panther, white-tailed deer, American alligator, and American crocodile. ATLSS is an ecosystem landscape-modeling approach and uses Geographic Information System (GIS) vegetation data and existing hydrology models for South Florida to provide the basic landscape for these species. A method of pseudotopography provides estimates of water depths through time at 28 ?? 28-m resolution across the landscape of southern Florida. Hydrologic model output drives models of habitat and prey availability for the higher trophic level species. Spatially explicit, individual-based computer models simulate these species. ATLSS simulations can compare the landscape dynamic spatial pattern of the species resulting from different proposed water management strategies. Here we compare the predicted effects of one possible change in water management in South Florida with the base case of no change. Preliminary model results predict substantial differences between these alternatives in some biotic spatial patterns. ?? 1998 Springer-Verlag.
Hydrological modelling improvements required in basins in the Hindukush-Karakoram-Himalayas region

NASA Astrophysics Data System (ADS)

Khan, Asif; Richards, Keith S.; McRobie, Allan; Booij, Martijn

2016-04-01

Millions of people rely on river water originating from basins in the Hindukush-Karakoram-Himalayas (HKH), where snow- and ice-melt are significant flow components. One such basin is the Upper Indus Basin (UIB), where snow- and ice-melt can contribute more than 80% of total flow. Containing some of the world's largest alpine glaciers, this basin may be highly susceptible to global warming and climate change, and reliable predictions of future water availability are vital for resource planning for downstream food and energy needs in a changing climate, but depend on significantly improved hydrological modelling. However, a critical assessment of available hydro-climatic data and hydrological modelling in the HKH region has identified five major failings in many published hydro-climatic studies, even those appearing in reputable international journals. The main weaknesses of these studies are: i) incorrect basin areas; ii) under-estimated precipitation; iii) incorrectly-defined glacier boundaries; iv) under-estimated snow-cover data; and v) use of biased melt factors for snow and ice during the summer months. This paper illustrates these limitations, which have either resulted in modelled flows being under-estimates of measured flows, leading to an implied severe water scarcity; or have led to the use of unrealistically high degree-day factors and over-estimates of glacier melt contributions, implying unrealistic melt rates. These effects vary amongst sub-basins. Forecasts obtained from these models cannot be used reliably in policy making or water resource development, and need revision. Detailed critical analysis and improvement of existing hydrological modelling may be equally necessary in other mountain regions across the world.
Impact of Landslides Induced by Earthquake on Hydrologic Response in a Mountainous Catchment

NASA Astrophysics Data System (ADS)

Qian, Q.; Su, D.; Ran, Q.

2013-12-01

The changes of the underlying surface conditions (topography, vegetation cover rate, etc.), which were caused by the numerous landslides in the Wenchuan earthquake, may influence the hydrologic response and then change the flash flood or other kinds of the disaster risk in the affected areas. The Jianpinggou catchment, located in Sichuan China, is selected as the study area for this paper. It is a steep-slope mountainous catchment, flash flood is the main disaster, and sometimes causes the debris flow. The distribution of the landslides in this catchment is obtained from the remote sensing image data. The changes of topography are obtained from the comparisons among the different periods of digital elevation models (DEMs). A physical-based model, the Integrated Hydrology Model (InHM), is used to simulate the hydrologic response before and after the landslide, respectively. The influence of the underlying surface conditions is then discussed based on the output data, such as the hydrograph, distributed water depth and local runoff. The study leads to the following generalized conclusions: 1) the impact of the landslides on hydrologic response does exist, and the greater the proportion of surface flow in the total runoff is, the greater the impact will be; 2) the peak flow from the outlet increased after the landslide, but the shape of the hydrograph has little change; 3) the effect of the landslides on the local runoff is relatively obvious, and this elevates the local flash floods risk; 4) the difference of hydrologic responses between the two periods (before and after the landslide occurring) becomes larger with the increasing rainfall, with a threshold of rapid growth at the rainfall frequencies of once in every 50 years, but there is a limit. The improved understanding of the impact of landslides on the hydrologic response in Jianpinggou catchment provides valuable theoretical support for the storm flood forecast.
Towards real-time assimilation of crowdsourced observations in hydrological modeling

NASA Astrophysics Data System (ADS)

Mazzoleni, Maurizio; Verlaan, Martin; Alfonso, Leonardo; Norbiato, Daniele; Monego, Martina; Ferri, Michele; Solomatine, Dimitri

2016-04-01

The continued technological advances have stimulated the spread of low-cost sensors that can be used by citizens to provide crowdsourced observations (CO) of different hydrological variables. An example of such low-cost sensors is a staff gauge connected to a QR code on which people can read the water level indication and send the measurement via a mobile phone application. The goal of this study is to assess the combined effect of the assimilation of CO coming from a distributed network of low-cost sensors, and the existing streamflow observations from physical sensors, on the performance of a semi-distributed hydrological model. The methodology is applied to the Bacchiglione catchment, North East of Italy, where an early warning system is used by the Alto Adriatico Water Authority to issue forecasted water level along the river network which cross important cities such as Vicenza and Padua. In this study, forecasted precipitation values are used as input in the hydrological model to estimate the simulated streamflow hydrograph used as boundary condition for the hydraulic model. Observed precipitation values are used to generate realistic synthetic streamflow values with various characteristics of arrival frequency and accuracy, to simulate CO coming at irregular time steps. These observations are assimilated into the semi-distributed model using a Kalman filter based method. The results of this study show that CO, asynchronous in time and with variable accuracy, can still improve flood prediction when integrated in hydrological models. When both physical and low-cost sensors are located at the same places, the assimilation of CO gives the same model improvement than the assimilation of physical observations only for high number of non-intermittent sensors. However, the integration of observations from low-cost sensors and single physical sensors can improve the flood prediction even when small a number of intermittent CO are available. This study is part of the FP7 European Project WeSenseIt Citizen Water Observatory (www.http://wesenseit.eu/).
Results and Lessons Learned from a Coupled Social and Physical Hydrology Model: Testing Alternative Water Management Policies and Institutional Structures Using Agent-Based Modeling and Regional Hydrology

NASA Astrophysics Data System (ADS)

Murphy, J.; Lammers, R. B.; Prousevitch, A.; Ozik, J.; Altaweel, M.; Collier, N. T.; Kliskey, A. D.; Alessa, L.

2015-12-01

Water Management in the U.S. Southwest is under increasing scrutiny as many areas endure persistent drought. The impact of these prolonged dry conditions is a product of regional climate and hydrological conditions, but also of a highly engineered water management infrastructure and a complex web of social arrangements whereby water is allocated, shared, exchanged, used, re-used, and finally consumed. We coupled an agent-based model with a regional hydrological model to understand the dynamics in one richly studied and highly populous area: southern Arizona, U.S.A., including metropolitan Phoenix and Tucson. There, multiple management entities representing an array of municipalities and other water providers and customers, including private companies and Native American tribes are enmeshed in a complex legal and economic context in which water is bought, leased, banked, and exchanged in a variety of ways and on multiple temporal and physical scales. A recurrent question in the literature of adaptive management is the impact of management structure on overall system performance. To explore this, we constructed an agent-based model to capture this social complexity, and coupled this with a physical hydrological model that we used to drive the system under a variety of water stress scenarios and to assess the regional impact of the social system's performance. We report the outcomes of ensembles of runs in which varieties of alternative policy constraints and management strategies are considered. We hope to contribute to policy discussions in this area and connected and legislatively similar areas (such as California) as current conditions change and existing legal and policy structures are revised. Additionally, we comment on the challenges of integrating models that ostensibly are in different domains (physical and social) but that independently represent a system in which physical processes and human actions are closely intertwined and difficult to disentangle.
The role of hydrological and water quality models in the application of the ecosystem services framework for the EU Water Framework Directive

NASA Astrophysics Data System (ADS)

Hallouin, Thibault; Bruen, Michael; Feeley, Hugh B.; Christie, Michael; Bullock, Craig; Kelly, Fiona; Kelly-Quinn, Mary

2017-04-01

The hydrological cycle is intimately linked with environmental processes that are essential for human welfare in many regards including, among others, the provision of safe water from surface and subsurface waterbodies, rain-fed agricultural production, or the provision of aquatic-sourced food. As well as being a receiver of these natural benefits, the human population is also a manager of the water and other natural resources and, as such, can affect their future sustainable provision. With global population growth and climate change, both the dependence of the human population on water resources and the threat they pose to these resources are likely to intensify so that the sustainability of the coupled natural and human system is threatened. In the European Union, the Water Framework Directive is driving policy and encouraging member states to manage their water resources wisely in order to maintain or restore ecological quality. To this end, the ecosystem services framework can be a useful tool to link the requirements in terms of ecological status into more tangible descriptors, that is the ecosystem services. In the ESManage Project, existing environmental system models such as hydrological models and water quality models are used as the basis to quantify the provision of many hydrological and aquatic ecosystem services by constructing indicators for the ecosystem services from the modelled environmental variables. By allowing different management options and policies to be compared, these models can be a valuable source of information for policy makers when they are used for climate and land use scenario analyses. Not all hydrological models developed for flood forecasting are suitable for this application and inappropriate models can lead to questionable conclusions. This paper demonstrates the readily available capabilities of a specially developed catchment hydrological model coupled with a water quality model to quantify a wide range of biophysically quantifiable water-related ecosystem services such as water provision (river flows, groundwater recharge and vegetation transpiration), flood regulation or nutrient and sediment retention. This combination of models will be used to carry out scenario analyses on IPCC climate change scenarios as well as various land use scenarios. Results will be presented for a test catchment in the Republic of Ireland.
Study of rainfall-induced landslide: a review

NASA Astrophysics Data System (ADS)

Tohari, A.

2018-02-01

Rainfall-induced landslides pose a substantial risk to people and infrastructure. For this reason, there have been numerous studies to understand the landslide mechanism. Most of them were performed on the numerical analysis and laboratory experiment. This paper presents a review of existing research on field hydrological condition of soil slopes leading to the initiation of rainfall-induced landslide. Existing methods to study field hydrological response of slopes are first reviewed, emphasizing their limitations and suitability of application. The typical hydrological response profiles in the slope are then discussed. Subsequently, some significant findings on hydrological condition leading to rainfall-induced landslides are summarized and discussed. Finally, several research topics are recommended for future study.
Evaluation of the land surface water budget in NCEP/NCAR and NCEP/DOE reanalyses using an off-line hydrologic model

NASA Astrophysics Data System (ADS)

Maurer, Edwin P.; O'Donnell, Greg M.; Lettenmaier, Dennis P.; Roads, John O.

2001-08-01

The ability of the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis (NRA1) and the follow-up NCEP/Department of Energy (DOE) reanalysis (NRA2), to reproduce the hydrologic budgets over the Mississippi River basin is evaluated using a macroscale hydrology model. This diagnosis is aided by a relatively unconstrained global climate simulation using the NCEP global spectral model, and a more highly constrained regional climate simulation using the NCEP regional spectral model, both employing the same land surface parameterization (LSP) as the reanalyses. The hydrology model is the variable infiltration capacity (VIC) model, which is forced by gridded observed precipitation and temperature. It reproduces observed streamflow, and by closure is constrained to balance other terms in the surface water and energy budgets. The VIC-simulated surface fluxes therefore provide a benchmark for evaluating the predictions from the reanalyses and the climate models. The comparisons, conducted for the 10-year period 1988-1997, show the well-known overestimation of summer precipitation in the southeastern Mississippi River basin, a consistent overestimation of evapotranspiration, and an underprediction of snow in NRA1. These biases are generally lower in NRA2, though a large overprediction of snow water equivalent exists. NRA1 is subject to errors in the surface water budget due to nudging of modeled soil moisture to an assumed climatology. The nudging and precipitation bias alone do not explain the consistent overprediction of evapotranspiration throughout the basin. Another source of error is the gravitational drainage term in the NCEP LSP, which produces the majority of the model's reported runoff. This may contribute to an overprediction of persistence of surface water anomalies in much of the basin. Residual evapotranspiration inferred from an atmospheric balance of NRA1, which is more directly related to observed atmospheric variables, matches the VIC prediction much more closely than the coupled models. However, the persistence of the residual evapotranspiration is much less than is predicted by the hydrological model or the climate models.
A Lifecycle Approach to Brokered Data Management for Hydrologic Modeling Data Using Open Standards.

NASA Astrophysics Data System (ADS)

Blodgett, D. L.; Booth, N.; Kunicki, T.; Walker, J.

2012-12-01

The U.S. Geological Survey Center for Integrated Data Analytics has formalized an information management-architecture to facilitate hydrologic modeling and subsequent decision support throughout a project's lifecycle. The architecture is based on open standards and open source software to decrease the adoption barrier and to build on existing, community supported software. The components of this system have been developed and evaluated to support data management activities of the interagency Great Lakes Restoration Initiative, Department of Interior's Climate Science Centers and WaterSmart National Water Census. Much of the research and development of this system has been in cooperation with international interoperability experiments conducted within the Open Geospatial Consortium. Community-developed standards and software, implemented to meet the unique requirements of specific disciplines, are used as a system of interoperable, discipline specific, data types and interfaces. This approach has allowed adoption of existing software that satisfies the majority of system requirements. Four major features of the system include: 1) assistance in model parameter and forcing creation from large enterprise data sources; 2) conversion of model results and calibrated parameters to standard formats, making them available via standard web services; 3) tracking a model's processes, inputs, and outputs as a cohesive metadata record, allowing provenance tracking via reference to web services; and 4) generalized decision support tools which rely on a suite of standard data types and interfaces, rather than particular manually curated model-derived datasets. Recent progress made in data and web service standards related to sensor and/or model derived station time series, dynamic web processing, and metadata management are central to this system's function and will be presented briefly along with a functional overview of the applications that make up the system. As the separate pieces of this system progress, they will be combined and generalized to form a sort of social network for nationally consistent hydrologic modeling.
Humans in Biogeophysical Models: Colonial Period Human-Environment Interactions in the Northeastern United States

NASA Astrophysics Data System (ADS)

Parolari, A.; Greco, F.; Green, M.; Lally, M.; Hermans, C.

2008-12-01

Earth system models increasingly require representation of human activities and the important role they play in the environment. At the most fundamental level, human decisions are driven by the need to acquire basic resources - nutrients, energy, water, and space - each derived from the biogeophysical setting. Modern theories in Ecological Economics place these basic resources at the base of a consumption hierarchy (from subsistence to luxury resources) on which societies and economies are built. Human decisions at all levels of this hierarchy are driven by dynamic environmental, social, and economic factors. Therefore, models merging socio-economic and biogeophysical dynamics are required to predict the evolving relationship between humans and the hydrologic cycle. To provide an example, our study focuses on changes to the hydrologic cycle during the United States colonial period (1600 to 1800). Both direct, intentional, human water use (e.g. water supply, irrigation, or hydropower) and indirect, unintentional effects resulting from the use of other resources (e.g. deforestation or beaver trapping) are considered. We argue that water was not the limiting resource to either the Native or Colonist population growth. However, food and tobacco production and harvesting of beaver pelts led to indirect interventions and consequent changes in the hydrologic cycle. The analysis presented here suggests the importance of incorporating human decision- making dynamics with existing geophysical models to fully understand trajectories of human-environment interactions. Predictive tools of this type are critical to characterizing the long-term signature of humans on the landscape and hydrologic cycle.
A mangrove creek restoration plan utilizing hydraulic modeling.

PubMed

Marois, Darryl E; Mitsch, William J

2017-11-01

Despite the valuable ecosystem services provided by mangrove ecosystems they remain threatened around the globe. Urban development has been a primary cause for mangrove destruction and deterioration in south Florida USA for the last several decades. As a result, the restoration of mangrove forests has become an important topic of research. Using field sampling and remote-sensing we assessed the past and present hydrologic conditions of a mangrove creek and its connected mangrove forest and brackish marsh systems located on the coast of Naples Bay in southwest Florida. We concluded that the hydrology of these connected systems had been significantly altered from its natural state due to urban development. We propose here a mangrove creek restoration plan that would extend the existing creek channel 1.1 km inland through the adjacent mangrove forest and up to an adjacent brackish marsh. We then tested the hydrologic implications using a hydraulic model of the mangrove creek calibrated with tidal data from Naples Bay and water levels measured within the creek. The calibrated model was then used to simulate the resulting hydrology of our proposed restoration plan. Simulation results showed that the proposed creek extension would restore a twice-daily flooding regime to a majority of the adjacent mangrove forest and that there would still be minimal tidal influence on the brackish marsh area, keeping its salinity at an acceptable level. This study demonstrates the utility of combining field data and hydraulic modeling to aid in the design of mangrove restoration plans.
Development and Application of a Process-based River System Model at a Continental Scale

NASA Astrophysics Data System (ADS)

Kim, S. S. H.; Dutta, D.; Vaze, J.; Hughes, J. D.; Yang, A.; Teng, J.

2014-12-01

Existing global and continental scale river models, mainly designed for integrating with global climate model, are of very course spatial resolutions and they lack many important hydrological processes, such as overbank flow, irrigation diversion, groundwater seepage/recharge, which operate at a much finer resolution. Thus, these models are not suitable for producing streamflow forecast at fine spatial resolution and water accounts at sub-catchment levels, which are important for water resources planning and management at regional and national scale. A large-scale river system model has been developed and implemented for water accounting in Australia as part of the Water Information Research and Development Alliance between Australia's Bureau of Meteorology (BoM) and CSIRO. The model, developed using node-link architecture, includes all major hydrological processes, anthropogenic water utilisation and storage routing that influence the streamflow in both regulated and unregulated river systems. It includes an irrigation model to compute water diversion for irrigation use and associated fluxes and stores and a storage-based floodplain inundation model to compute overbank flow from river to floodplain and associated floodplain fluxes and stores. An auto-calibration tool has been built within the modelling system to automatically calibrate the model in large river systems using Shuffled Complex Evolution optimiser and user-defined objective functions. The auto-calibration tool makes the model computationally efficient and practical for large basin applications. The model has been implemented in several large basins in Australia including the Murray-Darling Basin, covering more than 2 million km2. The results of calibration and validation of the model shows highly satisfactory performance. The model has been operalisationalised in BoM for producing various fluxes and stores for national water accounting. This paper introduces this newly developed river system model describing the conceptual hydrological framework, methods used for representing different hydrological processes in the model and the results and evaluation of the model performance. The operational implementation of the model for water accounting is discussed.
Multi-criteria decision analysis using hydrological indicators for decision support - a conceptual framework.

NASA Astrophysics Data System (ADS)

Butchart-Kuhlmann, Daniel; Kralisch, Sven; Meinhardt, Markus; Fleischer, Melanie

2017-04-01

Assessing the quantity and quality of water available in water stressed environments under various potential climate and land-use changes is necessary for good water and environmental resources management and governance. Within the region covered by the Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) project, such areas are common. One goal of the SASSCAL project is to develop and provide an integrated decision support system (DSS) with which decision makers (DMs) within a given catchment can obtain objective information regarding potential changes in water flow quantity and timing. The SASSCAL DSS builds upon existing data storage and distribution capability, through the SASSCAL Information System (IS), as well as the J2000 hydrological model. Using output from validated J2000 models, the SASSCAL DSS incorporates the calculation of a range of hydrological indicators based upon Indicators of Hydrological Alteration/Environmental Flow Components (IHA/EFC) calculated for a historic time series (pre-impact) and a set of model simulations based upon a selection of possible climate and land-use change scenarios (post-impact). These indicators, obtained using the IHA software package, are then used as input for a multi-criteria decision analysis (MCDA) undertaken using the open source diviz software package. The results of these analyses will provide DMs with an indication as to how various hydrological indicators within a catchment may be altered under different future scenarios, as well providing a ranking of how each scenario is preferred according to different DM preferences. Scenarios are represented through a combination of model input data and parameter settings in J2000, and preferences are represented through criteria weighting in the MCDA. Here, the methodology is presented and applied to the J2000 Luanginga model results using a set of hypothetical decision maker preference values as input for an MCDA based on the PROMETHEE II outranking method. Future work on the SASSCAL DSS will entail automation of this process, as well as its application to other hydrological models and land-use and/or climate change scenarios.
Development of a new IHA method for impact assessment of climate change on flow regime

NASA Astrophysics Data System (ADS)

Yang, Tao; Cui, Tong; Xu, Chong-Yu; Ciais, Philippe; Shi, Pengfei

2017-09-01

The Indicators of Hydrologic Alteration (IHA) based on 33 parameters in five dimensions (flow magnitude, timing, duration, frequency and change rate) have been widely used in evaluation of hydrologic alteration in river systems. Yet, inter-correlation seriously exists amongst those parameters, therefore constantly underestimates or overestimates actual hydrological changes. Toward the end, a new method (Representative-IHA, RIHA) is developed by removing repetitions based on Criteria Importance Through Intercriteria Correlation (CRITIC) algorithm. RIHA is testified in evaluating effects of future climate change on hydro-ecology in the Niger River of Africa. Future flows are projected using three watershed hydrological models forced by five general circulation models (GCMs) under three Representative Concentration Pathways (RCPs) scenarios. Results show that: (1) RIHA is able to eliminate self-correlations amongst IHA indicators and identify the dominant characteristics of hydrological alteration in the Upper Niger River, (2) March streamflow, September streamflow, December streamflow, 30-day annual maximum, low pluses duration and fall rates tends to increase over the period 2010-2099, while July streamflow and 90-day annual minimum streamflow shows decrease, (3) the Niger River will undergo moderate flow alteration under RCP8.5 in 2050s and 2080s and low alteration other scenarios, (4) future flow alteration may induce increase water temperatures, reduction dissolved oxygen and food resources. Consequently, aquatic biodiversity and fish community of Upper Niger River would become more vulnerable in the future. The new method enables more scientific evaluation for multi-dimensional hydrologic alteration under the context of climate change.
Optimizing Use of Water Management Systems during Changes of Hydrological Conditions

NASA Astrophysics Data System (ADS)

Výleta, Roman; Škrinár, Andrej; Danáčová, Michaela; Valent, Peter

2017-10-01

When designing the water management systems and their components, there is a need of more detail research on hydrological conditions of the river basin, runoff of which creates the main source of water in the reservoir. Over the lifetime of the water management systems the hydrological time series are never repeated in the same form which served as the input for the design of the system components. The design assumes the observed time series to be representative at the time of the system use. However, it is rather unrealistic assumption, because the hydrological past will not be exactly repeated over the design lifetime. When designing the water management systems, the specialists may occasionally face the insufficient or oversized capacity design, possibly wrong specification of the management rules which may lead to their non-optimal use. It is therefore necessary to establish a comprehensive approach to simulate the fluctuations in the interannual runoff (taking into account the current dry and wet periods) in the form of stochastic modelling techniques in water management practice. The paper deals with the methodological procedure of modelling the mean monthly flows using the stochastic Thomas-Fiering model, while modification of this model by Wilson-Hilferty transformation of independent random number has been applied. This transformation usually applies in the event of significant asymmetry in the observed time series. The methodological procedure was applied on the data acquired at the gauging station of Horné Orešany in the Parná Stream. Observed mean monthly flows for the period of 1.11.1980 - 31.10.2012 served as the model input information. After extrapolation the model parameters and Wilson-Hilferty transformation parameters the synthetic time series of mean monthly flows were simulated. Those have been compared with the observed hydrological time series using basic statistical characteristics (e. g. mean, standard deviation and skewness) for testing the quality of the model simulation. The synthetic hydrological series of monthly flows were created having the same statistical properties as the time series observed in the past. The compiled model was able to take into account the diversity of extreme hydrological situations in a form of synthetic series of mean monthly flows, while the occurrence of a set of flows was confirmed, which could and may occur in the future. The results of stochastic modelling in the form of synthetic time series of mean monthly flows, which takes into account the seasonal fluctuations of runoff within the year, could be applicable in engineering hydrology (e. g. for optimum use of the existing water management system that is related to reassessment of economic risks of the system).

High-Resolution Assimilation of GRACE Terrestrial Water Storage Observations to Represent Local-Scale Water Table Depths

NASA Astrophysics Data System (ADS)

Stampoulis, D.; Reager, J. T., II; David, C. H.; Famiglietti, J. S.; Andreadis, K.

2017-12-01

Despite the numerous advances in hydrologic modeling and improvements in Land Surface Models, an accurate representation of the water table depth (WTD) still does not exist. Data assimilation of observations of the joint NASA and DLR mission, Gravity Recovery and Climate Experiment (GRACE) leads to statistically significant improvements in the accuracy of hydrologic models, ultimately resulting in more reliable estimates of water storage. However, the usually shallow groundwater compartment of the models presents a problem with GRACE assimilation techniques, as these satellite observations account for much deeper aquifers. To improve the accuracy of groundwater estimates and allow the representation of the WTD at fine spatial scales we implemented a novel approach that enables a large-scale data integration system to assimilate GRACE data. This was achieved by augmenting the Variable Infiltration Capacity (VIC) hydrologic model, which is the core component of the Regional Hydrologic Extremes Assessment System (RHEAS), a high-resolution modeling framework developed at the Jet Propulsion Laboratory (JPL) for hydrologic modeling and data assimilation. The model has insufficient subsurface characterization and therefore, to reproduce groundwater variability not only in shallow depths but also in deep aquifers, as well as to allow GRACE assimilation, a fourth soil layer of varying depth ( 1000 meters) was added in VIC as the bottom layer. To initialize a water table in the model we used gridded global WTD data at 1 km resolution which were spatially aggregated to match the model's resolution. Simulations were then performed to test the augmented model's ability to capture seasonal and inter-annual trends of groundwater. The 4-layer version of VIC was run with and without assimilating GRACE Total Water Storage anomalies (TWSA) over the Central Valley in California. This is the first-ever assimilation of GRACE TWSA for the determination of realistic water table depths, at fine scales that are required for local water management. In addition, Open Loop and GRACE-assimilation simulations of water table depth were compared to in-situ data over the state of California, derived from observation wells operated/maintained by the U.S. Geological Service.
Groundwater discharge in high-mountain watersheds: A valuable resource for downstream semi-arid zones. The case of the Bérchules River in Sierra Nevada (Southern Spain).

PubMed

Jódar, Jorge; Cabrera, José Antonio; Martos-Rosillo, Sergio; Ruiz-Constán, Ana; González-Ramón, Antonio; Lambán, Luis Javier; Herrera, Christian; Custodio, Emilio

2017-09-01

Aquifers in permeable formations developed in high-mountain watersheds slow down the transfer of snowmelt to rivers, modifying rivers' flow pattern. To gain insight into the processes that control the hydrologic response of such systems the role played by groundwater in an alpine basin located at the southeastern part of the Iberian Peninsula is investigated. As data in these environments is generally scarce and its variability is high, simple lumped parameter hydrological models that consider the groundwater component and snow accumulation and melting are needed. Instead of using existing models that use many parameters, the Témez lumped hydrological model of common use in Spain and Ibero-American countries is selected and modified to consider snow to get a simplified tool to separate hydrograph components. The result is the TDD model (Témez-Degree Day) which is applied in a high mountain watershed with seasonal snow cover in Southern Spain to help in quantifying groundwater recharge and determining the groundwater contribution to the outflow. Average groundwater recharge is about 23% of the precipitation, and groundwater contribution to total outflow ranges between 70 and 97%. Direct surface runoff is 1% of precipitation. These values depend on the existence of snow. Results are consistent with those obtained with chloride atmospheric deposition mass balances by other authors. They highlight the important role of groundwater in high mountain areas, which is enhanced by seasonal snow cover. Results compare well with other areas. This effect is often neglected in water planning, but can be easily taken into account just by extending the water balance tool in use, or any other, following the procedure that has being developed. Copyright © 2017 Elsevier B.V. All rights reserved.
Spatially-varied erosion modeling using WEPP for timber harvested and burned hillslopes

Treesearch

Peter R. Robichaud; T. M. Monroe

1997-01-01

Spatially-varied hydrologic surface conditions exist on steep hillslopes after timber harvest operation and site preparation burning treatments. Site preparation burning creates low- and high-severity burn surface conditions or disturbances. In this study, a hillslope was divided into multiple combinations of surface conditions to determine how their spatial...
Effects of land use on lake nutrients: The importance of scale, hydrologic connectivity, and region

USGS Publications Warehouse

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Wagner, Tyler; Webster, Katherine E.; Bremigan, Mary Tate

2015-01-01

Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales.
Effects of Land Use on Lake Nutrients: The Importance of Scale, Hydrologic Connectivity, and Region

PubMed Central

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Wagner, Tyler; Webster, Katherine E.; Bremigan, Mary Tate

2015-01-01

Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales. PMID:26267813
Error discrimination of an operational hydrological forecasting system at a national scale

NASA Astrophysics Data System (ADS)

Jordan, F.; Brauchli, T.

2010-09-01

The use of operational hydrological forecasting systems is recommended for hydropower production as well as flood management. However, the forecast uncertainties can be important and lead to bad decisions such as false alarms and inappropriate reservoir management of hydropower plants. In order to improve the forecasting systems, it is important to discriminate the different sources of uncertainties. To achieve this task, reanalysis of past predictions can be realized and provide information about the structure of the global uncertainty. In order to discriminate between uncertainty due to the weather numerical model and uncertainty due to the rainfall-runoff model, simulations assuming perfect weather forecast must be realized. This contribution presents the spatial analysis of the weather uncertainties and their influence on the river discharge prediction of a few different river basins where an operational forecasting system exists. The forecast is based on the RS 3.0 system [1], [2], which is also running the open Internet platform www.swissrivers.ch [3]. The uncertainty related to the hydrological model is compared to the uncertainty related to the weather prediction. A comparison between numerous weather prediction models [4] at different lead times is also presented. The results highlight an important improving potential of both forecasting components: the hydrological rainfall-runoff model and the numerical weather prediction models. The hydrological processes must be accurately represented during the model calibration procedure, while weather prediction models suffer from a systematic spatial bias. REFERENCES [1] Garcia, J., Jordan, F., Dubois, J. & Boillat, J.-L. 2007. "Routing System II, Modélisation d'écoulements dans des systèmes hydrauliques", Communication LCH n° 32, Ed. Prof. A. Schleiss, Lausanne [2] Jordan, F. 2007. Modèle de prévision et de gestion des crues - optimisation des opérations des aménagements hydroélectriques à accumulation pour la réduction des débits de crue, thèse de doctorat n° 3711, Ecole Polytechnique Fédérale, Lausanne [3] Keller, R. 2009. "Le débit des rivières au peigne fin", Revue Technique Suisse, N°7/8 2009, Swiss engineering RTS, UTS SA, Lausanne, p. 11 [4] Kaufmann, P., Schubiger, F. & Binder, P. 2003. Precipitation forecasting by a mesoscale numerical weather prediction (NWP) model : eight years of experience, Hydrology and Earth System
Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops

USGS Publications Warehouse

Duan, Q.; Schaake, J.; Andreassian, V.; Franks, S.; Goteti, G.; Gupta, H.V.; Gusev, Y.M.; Habets, F.; Hall, A.; Hay, L.; Hogue, T.; Huang, M.; Leavesley, G.; Liang, X.; Nasonova, O.N.; Noilhan, J.; Oudin, L.; Sorooshian, S.; Wagener, T.; Wood, E.F.

2006-01-01

The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrologic models and in land surface parameterization schemes of atmospheric models. The MOPEX science strategy involves three major steps: data preparation, a priori parameter estimation methodology development, and demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrologic basins in the United States (US) and in other countries. This database is being continuously expanded to include more basins in all parts of the world. A number of international MOPEX workshops have been convened to bring together interested hydrologists and land surface modelers from all over world to exchange knowledge and experience in developing a priori parameter estimation techniques. This paper describes the results from the second and third MOPEX workshops. The specific objective of these workshops is to examine the state of a priori parameter estimation techniques and how they can be potentially improved with observations from well-monitored hydrologic basins. Participants of the second and third MOPEX workshops were provided with data from 12 basins in the southeastern US and were asked to carry out a series of numerical experiments using a priori parameters as well as calibrated parameters developed for their respective hydrologic models. Different modeling groups carried out all the required experiments independently using eight different models, and the results from these models have been assembled for analysis in this paper. This paper presents an overview of the MOPEX experiment and its design. The main experimental results are analyzed. A key finding is that existing a priori parameter estimation procedures are problematic and need improvement. Significant improvement of these procedures may be achieved through model calibration of well-monitored hydrologic basins. This paper concludes with a discussion of the lessons learned, and points out further work and future strategy. ?? 2005 Elsevier Ltd. All rights reserved.
Using large hydrological datasets to create a robust, physically based, spatially distributed model for Great Britain

NASA Astrophysics Data System (ADS)

Lewis, Elizabeth; Kilsby, Chris; Fowler, Hayley

2014-05-01

The impact of climate change on hydrological systems requires further quantification in order to inform water management. This study intends to conduct such analysis using hydrological models. Such models are of varying forms, of which conceptual, lumped parameter models and physically-based models are two important types. The majority of hydrological studies use conceptual models calibrated against measured river flow time series in order to represent catchment behaviour. This method often shows impressive results for specific problems in gauged catchments. However, the results may not be robust under non-stationary conditions such as climate change, as physical processes and relationships amenable to change are not accounted for explicitly. Moreover, conceptual models are less readily applicable to ungauged catchments, in which hydrological predictions are also required. As such, the physically based, spatially distributed model SHETRAN is used in this study to develop a robust and reliable framework for modelling historic and future behaviour of gauged and ungauged catchments across the whole of Great Britain. In order to achieve this, a large array of data completely covering Great Britain for the period 1960-2006 has been collated and efficiently stored ready for model input. The data processed include a DEM, rainfall, PE and maps of geology, soil and land cover. A desire to make the modelling system easy for others to work with led to the development of a user-friendly graphical interface. This allows non-experts to set up and run a catchment model in a few seconds, a process that can normally take weeks or months. The quality and reliability of the extensive dataset for modelling hydrological processes has also been evaluated. One aspect of this has been an assessment of error and uncertainty in rainfall input data, as well as the effects of temporal resolution in precipitation inputs on model calibration. SHETRAN has been updated to accept gridded rainfall inputs, and UKCP09 gridded daily rainfall data has been disaggregated using hourly records to analyse the implications of using realistic sub-daily variability. Furthermore, the development of a comprehensive dataset and computationally efficient means of setting up and running catchment models has allowed for examination of how a robust parameter scheme may be derived. This analysis has been based on collective parameterisation of multiple catchments in contrasting hydrological settings and subject to varied processes. 350 gauged catchments all over the UK have been simulated, and a robust set of parameters is being sought by examining the full range of hydrological processes and calibrating to a highly diverse flow data series. The modelling system will be used to generate flow time series based on historical input data and also downscaled Regional Climate Model (RCM) forecasts using the UKCP09 Weather Generator. This will allow for analysis of flow frequency and associated future changes, which cannot be determined from the instrumental record or from lumped parameter model outputs calibrated only to historical catchment behaviour. This work will be based on the existing and functional modelling system described following some further improvements to calibration, particularly regarding simulation of groundwater-dominated catchments.
Hydrological modelling in forested systems | Science ...

EPA Pesticide Factsheets

This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological processes. The focus of this chapter is on process-based models and approaches, specifically 'forest hydrology models'; that is, physically based simulation tools that quantify compartments of the forest hydrological cycle. Physically based models can be considered those that describe the conservation of mass, momentum and/or energy. The purpose of this chapter is to provide a brief overview of forest hydrology modeling approaches for answering important global research and management questions. The focus of this chapter is on process-based models and approaches, specifically “forest hydrology models”, i.e., physically-based simulation tools that quantify compartments of the forest hydrological cycle.
From hydrodynamic to hydrological modelling: Investigating long-term hydrological regimes of key wetlands in the Macquarie Marshes, a semi-arid lowland floodplain in Australia

NASA Astrophysics Data System (ADS)

Wen, Li; Macdonald, Rohan; Morrison, Tim; Hameed, Tahir; Saintilan, Neil; Ling, Joanne

2013-09-01

The Macquarie Marshes is an intermittently flooded wetland complex covering nearly 200,000 ha. It is one of the largest semi-permanent wetland systems in the Murray-Darling Basin, Australia, and portions of the Marshes are listed as internationally important under the Ramsar Convention. Previous studies indicate that the Marshes have undergone accelerated ecological degradation since the 1980s. The ecological degradation is documented in declining biodiversity, encroaching of terrestrial species, colonisation of exotic species, and deterioration of floodplain forests. There is strong evidence that reduction in river flows is the principal cause of the decrease in ecological values. Although the streams are relatively well gauged and modelled, the lack of hydrological records within the Marshes hampers any attempts to quantitatively investigate the relationship between hydrological variation and ecosystem integrity. To enable a better understanding of the long-term hydrological variations within the key wetland systems, and in particular, to investigate the impacts of the different water management policies (e.g. environmental water) on wetlands, a river system model including the main wetland systems was needed. The morphological complex nature of the Marshes means that the approximation of hydrological regimes within wetlands using stream hydrographs would have been difficult and inaccurate. In this study, we built a coupled 1D/2D MIKE FLOOD floodplain hydrodynamic model based on a 1 m DEM derived from a LiDAR survey. Hydrological characteristics of key constituent wetlands such as the correlation between water level and inundation area, relationships between stream and wetlands and among wetlands were estimated using time series extracted from hydrodynamic simulations. These relationships were then introduced into the existing river hydrological model (IQQM) to represent the wetlands. The model was used in this study to simulate the daily behaviours of inflow/outflow, volume, and inundated area for key wetlands within the Marshes under natural conditions and recent water management practices for the period of July 1 1991 to June 30 2009. The results revealed that the recent water management practices have induced large changes to wetland hydrology. The most noticeable changes include the dramatic reductions in high flows (i.e. flows with less than 25% exceedence, reduction ranges from 85% to 98% of the high flow peak depending on the location), areal inundation extent (ranging from 13% to 79% depending on climatic conditions), and flow rising/falling rates (over 90% for high flows). Our analysis also highlighted that the impacts of water management practices on some of the flow variables for wetland habitats contrasted with those for instream habitats. For example, we did not find any evident alterations in the low flows (i.e. 75% exceedence) attributable to water management.
A Semiarid Long-Term Hydrologic Observatory at the Continental Scale: The Upper Río Grande Basin

NASA Astrophysics Data System (ADS)

Hogan, J. F.; Vivoni, E. R.; Bowman, R. S.; Coonrod, J.; Thomson, B. M.; Samani, Z.; Ferre, P. T.; Phillips, F. M.; Rango, A.; Rasmussen, R.; Springer, E. P.; Small, E. E.

2004-12-01

Water availability is critical in arid and semiarid regions, which comprise 35 percent of the land area of the globe. In the Southwestern US, climate variability and landscape heterogeneity lead to strong gradients in hydrological processes, which in turn impact land-atmosphere interactions, ecological dynamics, biogeochemical cycles and geomorphic change. This complexity presents a fundamental challenge to our understanding of hydrology, one that is best addressed through long-term, systematic field and remote-sensing observations and numerical-model investigations. In this poster, we will present our plans to study the interaction of climate-landscape-vegetation and water using a nested set of instrumented sites within the Upper Río Grande, a continental-scale semiarid watershed. This complex watershed extends from the snow-dominated headwater basins in San Juan Mountains of southern Colorado, through the Chihuahuan Desert in New Mexico, Texas and Mexico, to the desert valley alluvial basins southeast of El Paso, Texas. As part of the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) plan for a network of Long-Term Hydrologic Observatories (LTHOs), the Upper Río Grande would represent the combination of mountain landscapes, semiarid to arid alluvial basin aquifers and riparian corridors that are characteristic of the Western United States. We will describe existing hydrologic, ecologic and atmospheric measurement infrastructure in the watershed and discuss plans for integrating these into a coherent network that provides a core set of scientific data products for the hydrologic community. Data products generated by the Upper Río Grande LTHO will also aid in the testing of coupled numerical models of the atmosphere-surface-groundwater system applied at high resolution over the region. The Upper Río Grande presents unique opportunities to test hydrologic hypotheses concerning surface water-groundwater interactions and their control on runoff response, solute transport and reactivity, and riparian ecological communities
On using TRMM data and rainfall forecasts from meteorological models in data-scarce transboundary catchments - an example of Bangladesh

NASA Astrophysics Data System (ADS)

Bhattacharya, Biswa; Tohidul Islam, Md.

2014-05-01

This research focuses on the flood risk of the Haor region in the north-eastern part of Bangladesh. The prediction of the hydrological variables at different spatial and temporal scales in the Haor region is dependent on the influence of several upstream rivers in the Meghalaya catchment in India. Limitation in hydro-meteorological data collection and data sharing issues between the two countries dominate the feasibility of hydrological studies, particularly for near-realtime predictions. One of the possible solutions seems to be in making use of the variety of satellite based and meteorological model products for rainfall. The abundance of a variety of rainfall products provides a good basis of hydrological modelling of a part of the Ganges and Brahmaputra basin. In this research the TRMM data and rainfall forecasts from ECMWF have been compared with the scarce rain gauge data from the upstream Meghalaya catchment. Subsequently, the TRMM data and rainfall forecasts from ECMWF have been used as the meteorological input to a rainfall-runoff model of the Meghalaya catchment. The rainfall-runoff model of Meghalaya has been developed using the DEM data from SRTM. The generated runoff at the outlet of Meghalaya has been used as the upstream boundary condition in the existing rainfall-runoff model of the Haor region. The simulation results have been compared with the existing results based on simulations without any information of the rainfall-runoff in the upstream Meghalaya catchment. The comparison showed that the forecasting lead time has been substantially increased. As per the existing results the forecasting lead time at a number of locations in the catchment was about 6 to 8 hours. With the new results the forecasting lead time has gone up, with different levels of accuracy, to about 24 hours. This additional lead time will be highly beneficial in managing flood risk of the Haor region of Bangladesh. The research shows that satellite based rainfall products and rainfall forecasts from meteorological models can be very useful in flood risk management, particularly for data scarce regions and/or transboundary regions with data sharing issues. Keywords: flood risk management, TRMM, ECMWF, flood forecasting, Haor, Bangladesh. Abbreviations: TRMM: Tropical Rainfall Measuring Mission ECMWF: European Centre for Medium-Range Weather Forecasts DEM: Digital Elevation Model SRTM: Shuttle Radar Topography Mission
On the probabilistic structure of water age

NASA Astrophysics Data System (ADS)

Porporato, Amilcare; Calabrese, Salvatore

2015-05-01

The age distribution of water in hydrologic systems has received renewed interest recently, especially in relation to watershed response to rainfall inputs. The purpose of this contribution is first to draw attention to existing theories of age distributions in population dynamics, fluid mechanics and stochastic groundwater, and in particular to the McKendrick-von Foerster equation and its generalizations and solutions. A second and more important goal is to clarify that, when hydrologic fluxes are modeled by means of time-varying stochastic processes, the age distributions must themselves be treated as random functions. Once their probabilistic structure is obtained, it can be used to characterize the variability of age distributions in real systems and thus help quantify the inherent uncertainty in the field determination of water age. We illustrate these concepts with reference to a stochastic storage model, which has been used as a minimalist model of soil moisture and streamflow dynamics.
Identification of hydrological model parameter variation using ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Deng, Chao; Liu, Pan; Guo, Shenglian; Li, Zejun; Wang, Dingbao

2016-12-01

Hydrological model parameters play an important role in the ability of model prediction. In a stationary context, parameters of hydrological models are treated as constants; however, model parameters may vary with time under climate change and anthropogenic activities. The technique of ensemble Kalman filter (EnKF) is proposed to identify the temporal variation of parameters for a two-parameter monthly water balance model (TWBM) by assimilating the runoff observations. Through a synthetic experiment, the proposed method is evaluated with time-invariant (i.e., constant) parameters and different types of parameter variations, including trend, abrupt change and periodicity. Various levels of observation uncertainty are designed to examine the performance of the EnKF. The results show that the EnKF can successfully capture the temporal variations of the model parameters. The application to the Wudinghe basin shows that the water storage capacity (SC) of the TWBM model has an apparent increasing trend during the period from 1958 to 2000. The identified temporal variation of SC is explained by land use and land cover changes due to soil and water conservation measures. In contrast, the application to the Tongtianhe basin shows that the estimated SC has no significant variation during the simulation period of 1982-2013, corresponding to the relatively stationary catchment properties. The evapotranspiration parameter (C) has temporal variations while no obvious change patterns exist. The proposed method provides an effective tool for quantifying the temporal variations of the model parameters, thereby improving the accuracy and reliability of model simulations and forecasts.
Climate change and northern prairie wetlands: Simulations of long-term dynamics

USGS Publications Warehouse

Poiani, Karen A.; Johnson, W. Carter; Swanson, George A.; Winter, Thomas C.

1996-01-01

A mathematical model (WETSIM 2.0) was used to simulate wetland hydrology and vegetation dynamics over a 32-yr period (1961–1992) in a North Dakota prairie wetland. A hydrology component of the model calculated changes in water storage based on precipitation, evapotranspiration, snowpack, surface runoff, and subsurface inflow. A spatially explicit vegetation component in the model calculated changes in distribution of vegetative cover and open water, depending on water depth, seasonality, and existing type of vegetation.The model reproduced four known dry periods and one extremely wet period during the three decades. One simulated dry period in the early 1980s did not actually occur. Simulated water levels compared favorably with continuous observed water levels outside the calibration period (1990–1992). Changes in vegetative cover were realistic except for years when simulated water levels were significantly different than actual levels. These generally positive results support the use of the model for exploring the effects of possible climate changes on wetland resources.
The ecological limits of hydrologic alteration (ELOHA): A new framework for developing regional environmental flow standards

USGS Publications Warehouse

Poff, N.L.; Richter, B.D.; Arthington, A.H.; Bunn, S.E.; Naiman, R.J.; Kendy, E.; Acreman, M.; Apse, C.; Bledsoe, B.P.; Freeman, Mary C.; Henriksen, J.; Jacobson, R.B.; Kennen, J.G.; Merritt, D.M.; O'Keeffe, J. H.; Olden, J.D.; Rogers, K.; Tharme, R.E.; Warner, A.

2010-01-01

The flow regime is a primary determinant of the structure and function of aquatic and riparian ecosystems for streams and rivers. Hydrologic alteration has impaired riverine ecosystems on a global scale, and the pace and intensity of human development greatly exceeds the ability of scientists to assess the effects on a river-by-river basis. Current scientific understanding of hydrologic controls on riverine ecosystems and experience gained from individual river studies support development of environmental flow standards at the regional scale. 2. This paper presents a consensus view from a group of international scientists on a new framework for assessing environmental flow needs for many streams and rivers simultaneously to foster development and implementation of environmental flow standards at the regional scale. This framework, the ecological limits of hydrologic alteration (ELOHA), is a synthesis of a number of existing hydrologic techniques and environmental flow methods that are currently being used to various degrees and that can support comprehensive regional flow management. The flexible approach allows scientists, water-resource managers and stakeholders to analyse and synthesise available scientific information into ecologically based and socially acceptable goals and standards for management of environmental flows. 3. The ELOHA framework includes the synthesis of existing hydrologic and ecological databases from many rivers within a user-defined region to develop scientifically defensible and empirically testable relationships between flow alteration and ecological responses. These relationships serve as the basis for the societally driven process of developing regional flow standards. This is to be achieved by first using hydrologic modelling to build a 'hydrologic foundation' of baseline and current hydrographs for stream and river segments throughout the region. Second, using a set of ecologically relevant flow variables, river segments within the region are classified into a few distinctive flow regime types that are expected to have different ecological characteristics. These river types can be further subclassified according to important geomorphic features that define hydraulic habitat features. Third, the deviation of current-condition flows from baseline-condition flow is determined. Fourth, flow alteration-ecological response relationships are developed for each river type, based on a combination of existing hydroecological literature, expert knowledge and field studies across gradients of hydrologic alteration. 4. Scientific uncertainty will exist in the flow alteration-ecological response relationships, in part because of the confounding of hydrologic alteration with other important environmental determinants of river ecosystem condition (e.g. temperature). Application of the ELOHA framework should therefore occur in a consensus context where stakeholders and decision-makers explicitly evaluate acceptable risk as a balance between the perceived value of the ecological goals, the economic costs involved and the scientific uncertainties in functional relationships between ecological responses and flow alteration. 5. The ELOHA framework also should proceed in an adaptive management context, where collection of monitoring data or targeted field sampling data allows for testing of the proposed flow alteration-ecological response relationships. This empirical validation process allows for a fine-tuning of environmental flow management targets. The ELOHA framework can be used both to guide basic research in hydroecology and to further implementation of more comprehensive environmental flow management of freshwater sustainability on a global scale. ?? 2009 Blackwell Publishing Ltd.
Simulated Hydrologic Responses to Climate Variations and Change in the Merced, Carson, and American River Basins, Sierra Nevada, California, 1900-2099

NASA Astrophysics Data System (ADS)

Dettinger, M. D.; Cayan, D. R.; Cayan, D. R.; Meyer, M. K.

2001-12-01

Sensitivities of river basins in the Sierra Nevada of California to historical and future climate variations and changes are analyzed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-year period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th Century until about 1975, when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st Century with an attendant +2.5ºC warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. In contrast, a control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995, yields climate and streamflow-timing conditions much like the 1980s and 1990s throughout its duration. Long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. The various projected trends in the business-as-usual simulations become readily visible above simulated natural climatic and hydrologic variability by about 2020.
A hydrologic network supporting spatially referenced regression modeling in the Chesapeake Bay watershed

USGS Publications Warehouse

Brakebill, J.W.; Preston, S.D.

2003-01-01

The U.S. Geological Survey has developed a methodology for statistically relating nutrient sources and land-surface characteristics to nutrient loads of streams. The methodology is referred to as SPAtially Referenced Regressions On Watershed attributes (SPARROW), and relates measured stream nutrient loads to nutrient sources using nonlinear statistical regression models. A spatially detailed digital hydrologic network of stream reaches, stream-reach characteristics such as mean streamflow, water velocity, reach length, and travel time, and their associated watersheds supports the regression models. This network serves as the primary framework for spatially referencing potential nutrient source information such as atmospheric deposition, septic systems, point-sources, land use, land cover, and agricultural sources and land-surface characteristics such as land use, land cover, average-annual precipitation and temperature, slope, and soil permeability. In the Chesapeake Bay watershed that covers parts of Delaware, Maryland, Pennsylvania, New York, Virginia, West Virginia, and Washington D.C., SPARROW was used to generate models estimating loads of total nitrogen and total phosphorus representing 1987 and 1992 land-surface conditions. The 1987 models used a hydrologic network derived from an enhanced version of the U.S. Environmental Protection Agency's digital River Reach File, and course resolution Digital Elevation Models (DEMs). A new hydrologic network was created to support the 1992 models by generating stream reaches representing surface-water pathways defined by flow direction and flow accumulation algorithms from higher resolution DEMs. On a reach-by-reach basis, stream reach characteristics essential to the modeling were transferred to the newly generated pathways or reaches from the enhanced River Reach File used to support the 1987 models. To complete the new network, watersheds for each reach were generated using the direction of surface-water flow derived from the DEMs. This network improves upon existing digital stream data by increasing the level of spatial detail and providing consistency between the reach locations and topography. The hydrologic network also aids in illustrating the spatial patterns of predicted nutrient loads and sources contributed locally to each stream, and the percentages of nutrient load that reach Chesapeake Bay.
Quantifying human impact on hydrological drought using an Earth System Model

NASA Astrophysics Data System (ADS)

van Huijgevoort, Marjolein; Chaney, Nathaniel; Malyshev, Sergey; Shevliakova, Elena; Milly, Chris

2017-04-01

Predicting the human impact on the present and future hydrological cycle remains a significant scientific challenge. Anthropogenic impact includes water management practices like diverting water for irrigation, abstraction of groundwater, and reservoirs. Hydrological extremes, in particular, are heavily affected by water management practices, due to the existing stress on the system during droughts and floods. Therefore, to prepare adaptation plans for hydrological extremes in the future, it is essential to account for water management and other human influences in Earth System Models. In this study we have implemented water management practices in the state-of-the-art GFDL land model, which includes terrestrial water, energy, and carbon balances. Both irrigation practices and reservoirs have been added in the land surface model component of the model. Irrigation amounts are determined from the soil water balance, the evaporative demand of the vegetation and fractional coverage of croplands. The resulting water demand is fulfilled by abstractions from surface water and groundwater. Reservoir outflow is dynamically coupled to the downstream water demand and available reservoir storage. Retrospective model simulations over the contiguous United States indicate a strong human influence on hydrological drought. A water management attribution analysis shows a significant impact on the water availability, mostly in the Midwest of the United States and California. Implementation of reservoirs alters the flow regime, thereby decreasing the short-term drought impact, however, in the case of multi-year drought, impacts are delayed due to the dependency on the reservoir outflow. Irrigation, on the other hand, decreases the water availability in rivers due to increased evapotranspiration leading to a higher drought impact. The average increase in evapotranspiration amounted up to 2 mm/day for cropland areas in California and Texas. Overall, the results show the importance of including water management in global scale models. This new modelling framework can be used to understand how humans will impact future water availability, water scarcity, and drought. Next steps will include coupled model simulations to investigate the human impact on feedbacks in land-atmosphere interactions.
Hydrology of Fritchie Marsh, coastal Louisiana

USGS Publications Warehouse

Kuniansky, E.L.

1985-01-01

Fritchie Marsh, near Slidell, Louisiana, is being considered as a disposal site for sewage effluent. A two-dimensional, finite element, surface water modeling systems was used to solve the shallow water equations for flow. Factors affecting flow patterns are channel locations, inlets, outlets, islands, marsh vegetation, marsh geometry, stage of the West Pearl River, flooding over the lower Pearl River basin, gravity tides, wind-induced currents, and sewage discharge to the marsh. Four steady-state simulations were performed for two hydrologic events at two rates of sewage discharge. The events, near tide with no wind or rain and neap tide with a tide differential across the marsh, were selected as worst-case events for sewage effluent dispersion and were assumed as steady state events. Because inflows and outflows to the marsh are tidally affected, steady state simulations cannot fully define the hydraulic characteristics of the marsh for all hydrologic events. Model results and field data indicate that, during near tide with little or no rain, large parts of the marsh are stagnant; and sewage effluent, at existing and projected flows, has minimal effect on marsh flows. (USGS)

Monitoring Soil Infiltration In Semi-Arid Regions With Meteosat And A Coupled Model Approach Using PROMET And SLC

NASA Astrophysics Data System (ADS)

Klug, P.; Bach, H.; Migdall, S.

2013-12-01

In arid regions the infiltration of sparse rainfalls and resulting ground water recharge is a critical quantity for the water cycle. With the PROMET model the infiltration process can be simulated in detail, since 4 soil layers together with the hourly calculation time step allow simulating the vertical water transport. Wet soils are darker than dry soils. Using the SLC reflectance model this effect can be simulated and compared to temporal high resolution time series of measured reflectances from Meteosat in order to monitor the drying process. This study demonstrates how MSG can be used to better parameterize the simulation of the infiltration process and reduce uncertainties in ground water recharge estimation. The study is carried out in the frame of the EU FP7 project CLIMB (Climate Induced Changes on the Hydrology of Mediterranean Basins). According to climate projections, Mediterranean countries are at risk of changes in the hydrological budget, the agricultural productivity and drinking water supply in the future. The CLIMB FP-7 project coordinated by the University of Munich (LMU) aims at employing integrated hydrological modelling in a new framework to reduce existing uncertainties in climate change impact analysis of the Mediterranean region [1, 2].
A Flexible Framework Hydrological Informatic Modeling System - HIMS

NASA Astrophysics Data System (ADS)

WANG, L.; Wang, Z.; Changming, L.; Li, J.; Bai, P.

2017-12-01

Simulating water cycling process temporally and spatially fitting for the characteristics of the study area was important for floods prediction and streamflow simulation with high accuracy, as soil properties, land scape, climate, and land managements were the critical factors influencing the non-linear relationship of rainfall-runoff at watershed scales. Most existing hydrological models cannot simulate water cycle process at different places with customized mechanisms with fixed single structure and mode. This study develops Hydro-Informatic Modeling System (HIMS) model with modular of each critical hydrological process with multiple choices for various scenarios to solve this problem. HIMS has the structure accounting for two runoff generation mechanisms of infiltration excess and saturation excess and estimated runoff with different methods including Time Variance Gain Model (TVGM), LCM which has good performance at ungauged areas, besides the widely used Soil Conservation Service-Curve Number (SCS-CN) method. Channel routing model contains the most widely used Muskingum, and kinematic wave equation with new solving method. HIMS model performance with its symbolic runoff generation model LCM was evaluated through comparison with the observed streamflow datasets of Lasha river watershed at hourly, daily, and monthly time steps. Comparisons between simulational and obervational streamflows were found with NSE higher than 0.87 and WE within ±20%. Water balance analysis about precipitation, streamflow, actual evapotranspiration (ET), and soil moisture change was conducted temporally at annual time step and it has been proved that HIMS model performance was reliable through comparison with literature results at the Lhasa River watershed.
Contribution of lateral terrestrial water flows to the regional hydrological cycle: A joint soil-atmospheric moisture tagging procedure with WRF-Hydro

NASA Astrophysics Data System (ADS)

Arnault, Joel; Wei, Jianhui; Zhang, Zhenyu; Wagner, Sven; Kunstmann, Harald

2017-04-01

Water resources management requires an accurate knowledge of the behavior of the regional hydrological cycle components, including precipitation, evapotranspiration, river discharge and soil water storage. Atmospheric models such as the Weather Research and Forecasting (WRF) model provide a tool to evaluate these components. The main drawback of these atmospheric models, however, is that the terrestrial segment of the hydrological cycle is reduced to vertical infiltration, and that lateral terrestrial water flows are neglected. Recent model developments have focused on coupled atmospheric-hydrological modeling systems, such as WRF-hydro, in order to take into account subsurface, overland and river flow. The aim of this study is to investigate the contribution of lateral terrestrial water flows to the regional hydrological cycle, with the help of a joint soil-atmospheric moisture tagging procedure. This procedure is the extended version of an existing atmospheric moisture tagging method developed in WRF and WRF-Hydro (Arnault et al. 2017). It is used to quantify the partitioning of precipitation into water stored in the soil, runoff, evapotranspiration, and potentially subsequent precipitation through regional recycling. An application to a high precipitation event on 23 June 2009 in the upper Danube river basin, Germany and Austria, is presented. Precipitating water during this day is tagged for the period 2009-2011. Its contribution to runoff and evapotranspiration decreases with time, but is still not negligible in the summer 2011. At the end of the study period, less than 5 % of the precipitating water on 23 June 2009 remains in the soil. The additionally resolved lateral terrestrial water flows in WRF-Hydro modify the partitioning between surface and underground runoff, in association with a slight increase of evapotranspiration and recycled precipitation. Reference: Arnault, J., R. Knoche, J. Wei, and H. Kunstmann (2016), Evaporation tagging and atmospheric water budget analysis with WRF: A regional precipitation recycling study for West Africa, Water Resour. Res., 52, 1544-1567, doi:10.1002/2015WR017704.
Assessing the Impact of Land Use and Land Cover Change on Global Water Resources

NASA Astrophysics Data System (ADS)

Batra, N.; Yang, Y. E.; Choi, H. I.; Islam, A.; Charlotte, D. F.; Cai, X.; Kumar, P.

2007-12-01

Land use and land cover changes (LULCC) significantly modify the hydrological regime of the watersheds, affecting water resources and environment from regional to global scale. This study seeks to advance and integrate water and energy cycle observation, scientific understanding, and human impacts to assess future water availability. To achieve the research objective, we integrate and interpret past and current space based and in situ observations into a global hydrologic model (GHM). GHM is developed with enhanced spatial and temporal resolution, physical complexity, hydrologic theory and processes to quantify the impact of LULCC on physical variables: surface runoff, subsurface flow, groundwater, infiltration, ET, soil moisture, etc. Coupled with the common land model (CLM), a 3-dimensional volume averaged soil-moisture transport (VAST) model is expanded to incorporate the lateral flow and subgrid heterogeneity. The model consists of 11 soil-hydrology layers to predict lateral as well as vertical moisture flux transport based on Richard's equations. The primary surface boundary conditions (SBCs) include surface elevation and its derivatives, land cover category, sand and clay fraction profiles, bedrock depth and fractional vegetation cover. A consistent global GIS-based dataset is constructed for the SBCs of the model from existing observational datasets comprising of various resolutions, map projections and data formats. Global ECMWF data at 6-hour time steps for the period 1971 through 2000 is processed to get the forcing data which includes incoming longwave and shortwave radiation, precipitation, air temperature, pressure, wind components, boundary layer height and specific humidity. Land use land cover data, generated using IPCC scenarios for every 10 years from 2000 to 2100 is used for future assessment on water resources. Alterations due to LULCC on surface water balance components: ET, groundwater recharge and runoff are then addressed in the study. Land use change disrupts the hydrological cycle through increasing the water yield at some places leading to floods while diminishing, or even eliminating the low flow at other places.
Designing Hydrologic Observatories as a Community Resource

NASA Astrophysics Data System (ADS)

Hooper, R. P.; Duncan, J. M.

2004-12-01

CUAHSI convened a workshop in August 2004 to explore what makes a successful hydrologic observatory. Because of their high cost, only a small number of observatories will be operated, at least initially. (CUAHSI has recommended a pilot network of 5 observatories to develop operational experience and an eventual network of approximately 15 sites.) Because hydrologic scientists can work "in their backyard" (unlike oceanographers or astronomers), hydrologic observatories must offer significant advantages over current methods of field work to successfully attract researchers. Twenty-four teams of scientists submitted "prospectuses" of potential locations for hydrologic observatories for consideration by network attendees. These documents (available at http://www.cuahsi.org) were marketing documents to the workshop participants, who voted for a hypothetical network of 5 observatories from the 24 proposed sites. This network formed the basis for a day of discussions on necessary attributes of core data and how to form a network of observatories from a collection of sites that are designed and implemented individually. Key findings included: 1) Core data must be balanced among disciplines. Although the hydrologic cycle is an organizing principle for the design of HOs, physical data cannot dominate the core data; chemical and biological data, although more expensive to collect, must be given equal footing. 2) New data collection must strategically leverage existing data. Resources are always limited, so that a successful HO must carefully target gaps in existing data, as determined by an explicitly stated conceptual model, and fill them rather than designing an independent study. 3) Site logistics must support remote researchers. Significant resources will be necessary for on-site staff to handle housing, transportation, permitting and other needs. 4) Network-level hypotheses are required early in the implementation of HOs. A network will only emerge around hypotheses. Network-level hypotheses are currently being solicited by CUAHSI to help inform proposing team of important community questions.
Flexible hydrological modeling - Disaggregation from lumped catchment scale to higher spatial resolutions

NASA Astrophysics Data System (ADS)

Tran, Quoc Quan; Willems, Patrick; Pannemans, Bart; Blanckaert, Joris; Pereira, Fernando; Nossent, Jiri; Cauwenberghs, Kris; Vansteenkiste, Thomas

2015-04-01

Based on an international literature review on model structures of existing rainfall-runoff and hydrological models, a generalized model structure is proposed. It consists of different types of meteorological components, storage components, splitting components and routing components. They can be spatially organized in a lumped way, or on a grid, spatially interlinked by source-to-sink or grid-to-grid (cell-to-cell) routing. The grid size of the model can be chosen depending on the application. The user can select/change the spatial resolution depending on the needs and/or the evaluation of the accuracy of the model results, or use different spatial resolutions in parallel for different applications. Major research questions addressed during the study are: How can we assure consistent results of the model at any spatial detail? How can we avoid strong or sudden changes in model parameters and corresponding simulation results, when one moves from one level of spatial detail to another? How can we limit the problem of overparameterization/equifinality when we move from the lumped model to the spatially distributed model? The proposed approach is a step-wise one, where first the lumped conceptual model is calibrated using a systematic, data-based approach, followed by a disaggregation step where the lumped parameters are disaggregated based on spatial catchment characteristics (topography, land use, soil characteristics). In this way, disaggregation can be done down to any spatial scale, and consistently among scales. Only few additional calibration parameters are introduced to scale the absolute spatial differences in model parameters, but keeping the relative differences as obtained from the spatial catchment characteristics. After calibration of the spatial model, the accuracies of the lumped and spatial models were compared for peak, low and cumulative runoff total and sub-flows (at downstream and internal gauging stations). For the distributed models, additional validation on spatial results was done for the groundwater head values at observation wells. To ensure that the lumped model can produce results as accurate as the spatially distributed models or close regardless to the number of parameters and implemented physical processes, it was checked whether the structure of the lumped models had to be adjusted. The concept has been implemented in a PCRaster - Python platform and tested for two Belgian case studies (catchments of the rivers Dijle and Grote Nete). So far, use is made of existing model structures (NAM, PDM, VHM and HBV). Acknowledgement: These results were obtained within the scope of research activities for the Flemish Environment Agency (VMM) - division Operational Water Management on "Next Generation hydrological modeling", in cooperation with IMDC consultants, and for Flanders Hydraulics Research (Waterbouwkundig Laboratorium) on "Effect of climate change on the hydrological regime of navigable watercourses in Belgium".
Hydrological cycle in the Danube basin in present and projected future climate conditions: a models' intercomparison perspective

NASA Astrophysics Data System (ADS)

Lucarini, V.

2010-09-01

We present an intercomparison and verification analysis of several GCMs and RCMs included in the 4th IPCC assessment report on their representation of the hydrological cycle on the Danube river basin for present and (in the case of the GCMs) projected future climate conditions. The basin-scale properties of the hydrological cycle are computed by spatially integrating the precipitation, evaporation, and runoff fields using the Voronoi-Thiessen tessellation formalism. Large discrepancies exist among RCMs for the monthly climatology as well as for the mean and variability of the annual balances, and only few data sets are consistent with the observed discharge values of the Danube at its Delta. This occurs in spite of common nesting of the RCMs into the same run of the same AGCM, and even if the driving AGCM provides itself an excellent estimate. We find consistently that, for a given model, increases in the resolution do not alter the net water balance, while speeding up the hydrological cycle through the enhancement of both precipitation and evaporation by the same amount. We propose that the atmospheric components of RCMs still face difficulties in representing the water balance even on a relatively large scale. Moreover, since for some models the hydrological balance estimates obtained with the runoff fields do not agree with those obtained via precipitation and evaporation, some deficiencies of the land models are also apparent. In the case of the GCMs, the span of the model- simulated mean annual water balances is of the same order of magnitude of the observed Danube discharge of the Delta; the true value is within the range simulated by the models. Some land components seem to have deficiencies since there are cases of violation of water conservation when annual means are considered. The overall performance and the degree of agreement of the GCMs are, surprisingly, comparable to those of the RCMs. Both RCMs and GCMs greatly outperform the NCEP-NCAR and ERA-40 reanalyses in representing the present climate conditions. The reanalyses result to be largely inadequate for describing the hydrology of the Danube river basin, both for the reconstruction of the long-term averages and of the seasonal cycle. The reanalyses cannot in any sense be used as verification. In global warming conditions, for basically all models the water balance decreases, whereas its interannual variability increases. Changes in the strength of the hydrological cycle are not consistent among models: it is confirmed that capturing the impact of climate change on the hydrological cycle is not an easy task over land areas. We note that for some of the diagnostics the ensemble mean does not represent any sort of "average" model, and it often falls between the models’ clusters. We suggest that these results should be carefully considered in the perspective of auditing climate models and assessing their ability to simulate future climate changes.
A framework for modelling the complexities of food and water security under globalisation

NASA Astrophysics Data System (ADS)

Dermody, Brian J.; Sivapalan, Murugesu; Stehfest, Elke; van Vuuren, Detlef P.; Wassen, Martin J.; Bierkens, Marc F. P.; Dekker, Stefan C.

2018-01-01

We present a new framework for modelling the complexities of food and water security under globalisation. The framework sets out a method to capture regional and sectoral interdependencies and cross-scale feedbacks within the global food system that contribute to emergent water use patterns. The framework integrates aspects of existing models and approaches in the fields of hydrology and integrated assessment modelling. The core of the framework is a multi-agent network of city agents connected by infrastructural trade networks. Agents receive socio-economic and environmental constraint information from integrated assessment models and hydrological models respectively and simulate complex, socio-environmental dynamics that operate within those constraints. The emergent changes in food and water resources are aggregated and fed back to the original models with minimal modification of the structure of those models. It is our conviction that the framework presented can form the basis for a new wave of decision tools that capture complex socio-environmental change within our globalised world. In doing so they will contribute to illuminating pathways towards a sustainable future for humans, ecosystems and the water they share.
Assessing the vulnerability of watersheds to climate change: results of national forest watershed vulnerability pilot assessments

Treesearch

Michael J. Furniss; Ken B. Roby; Dan Cenderelli; John Chatel; Caty F. Clifton; Alan Clingenpeel; Polly E. Hays; Dale Higgins; Ken Hodges; Carol Howe; Laura Jungst; Joan Louie; Christine Mai; Ralph Martinez; Kerry Overton; Brian P. Staab; Rory Steinke; Mark Weinhold

2013-01-01

Existing models and predictions project serious changes to worldwide hydrologic processes as a result of global climate change. Projections indicate that significant change may threaten National Forest System watersheds that are an important source of water used to support people, economies, and ecosystems.Wildland managers are expected to anticipate and...
Modeling wildfire regimes in forest landscapes: abstracting a complex reality

Treesearch

Donald McKenzie; Ajith H. Perera

2015-01-01

Fire is a natural disturbance that is nearly ubiquitous in terrestrial ecosystems. The capacity to burn exists virtually wherever vegetation grows. In some forested landscapes, fi re is a principal driver of rapid ecosystem change, resetting succession ( McKenzie et al. 1996a ) and changing wildlife habitat (Cushman et al. 2011 ), hydrology ( Feikema et al. 2013 ),...
Operational Research: Evaluating Multimodel Implementations for 24/7 Runtime Environments

NASA Astrophysics Data System (ADS)

Burkhart, J. F.; Helset, S.; Abdella, Y. S.; Lappegard, G.

2016-12-01

We present a new open source framework for operational hydrologic rainfall-runoff modeling. The Statkraft Hydrologic Forecasting Toolbox (Shyft) is unique from existing frameworks in that two primary goals are to provide: i) modern, professionally developed source code, and ii) a platform that is robust and ready for operational deployment. Developed jointly between Statkraft AS and The University of Oslo, the framework is currently in operation in both private and academic environments. The hydrology presently available in the distribution is simple and proven. Shyft provides a platform for distributed hydrologic modeling in a highly efficient manner. In it's current operational deployment at Statkraft, Shyft is used to provide daily 10-day forecasts for critical reservoirs. In a research setting, we have developed a novel implementation of the SNICAR model to assess the impact of aerosol deposition on snow packs. Several well known rainfall-runoff algorithms are available for use, allowing for intercomparing different approaches based on available data and the geographical environment. The well known HBV model is a default option, and other routines with more localized methods handling snow and evapotranspiration, or simplifications of catchment scale processes are included. For the latter, we have implemented the Kirchner response routine. Being developed in Norway, a variety snow-melt routines, including simplified degree day models or more advanced energy balance models, may be selected. Ensemble forecasts, multi-model implementations, and statistical post-processing routines enable a robust toolbox for investigating optimal model configurations in an operational setting. The Shyft core is written in modern templated C++ and has Python wrappers developed for easy access to module sub-routines. The code is developed such that the modules that make up a "method stack" are easy to modify and customize, allowing one to create new methods and test them rapidly. Due to the simple architecture and ease of access to the module routines, we see Shyft as an optimal choice to evaluate new hydrologic routines in an environment requiring robust, professionally developed software and welcome further community participation.
AutoRoute Rapid Flood Inundation Model

DTIC Science & Technology

2013-03-01

Res. 33(2): 309-319. U.S. Army Engineer Hydrologic Engineering Center. 2010. “ HEC - RAS : River Analysis System, User’s Manual, Version 4.1.” Davis...cross-section data does not exist. As such, the AutoRoute model is not meant to be as accurate as models such as HEC - RAS (U.S. Army Engineer...such as HEC - RAS assume that the defined low point of cross sections must be connected. However, in this approach the channel is assumed to be defined
Classical and generalized Horton laws for peak flows in rainfall-runoff events.

PubMed

Gupta, Vijay K; Ayalew, Tibebu B; Mantilla, Ricardo; Krajewski, Witold F

2015-07-01

The discovery of the Horton laws for hydrologic variables has greatly lagged behind geomorphology, which began with Robert Horton in 1945. We define the classical and the generalized Horton laws for peak flows in rainfall-runoff events, which link self-similarity in network geomorphology with river basin hydrology. Both the Horton laws are tested in the Iowa River basin in eastern Iowa that drains an area of approximately 32 400 km(2) before it joins the Mississippi River. The US Geological Survey continuously monitors the basin through 34 stream gauging stations. We select 51 rainfall-runoff events for carrying out the tests. Our findings support the existence of the classical and the generalized Horton laws for peak flows, which may be considered as a new hydrologic discovery. Three different methods are illustrated for estimating the Horton peak-flow ratio due to small sample size issues in peak flow data. We illustrate an application of the Horton laws for diagnosing parameterizations in a physical rainfall-runoff model. The ideas and developments presented here offer exciting new directions for hydrologic research and education.
Evolving soils and hydrologic connectivity in semiarid hillslopes

NASA Astrophysics Data System (ADS)

Saco, Patricia M.

2015-04-01

Soil moisture availability is essential for the stability and resilience of semiarid ecosystems. In these ecosystems the amount of soil moisture available for vegetation growth and survival is intrinsically related to the way water is redistributed, that is from source to sink areas, and therefore prescribed by the hydrologic connectivity of the landscape. Recent studies have shown that hydrologic connectivity is highly dynamic and linked to the coevolution of geomorphic, soil and vegetation structures at a variety of spatial and temporal scales. This study investigates the effect of evolving soil depths on hydrologic connectivity using a modelling framework. The focus is on Australian semiarid hillslopes with patterned vegetation that result from coevolving landforms, soils, water redistribution, and vegetation patterns. We present and analyse results from simulations using a coupled landform evolution-dynamic vegetation model, which includes a soil depth evolution module and accounts for soil production and sediment erosion and deposition processes. We analyse the effect of soils depths on surface connectivity for a range of biotic (plant functional type strategies) and abiotic (slope and erodibility) conditions. The analysis shows that different plant functional types, through their varying facilitation strategies, have a profound effect on soils depths and therefore affect hydrologic connectivity and soil moisture patterns. This interplay becomes particularly important for systems that coevolve to have very shallow soils. In this case soil depth becomes the key factor prescribing surface connectivity and available soil moisture for plants, which affect the recovery of the system after disturbance. Conditions for the existence of threshold behaviour for which small perturbations can trigger a sudden increase in hydrologic connectivity, reduced soil moisture availability and decrease in productivity leading to degraded states are investigated. Critical implications for effective restoration efforts are discussed.
Simulated hydrologic responses to climate variations and change in the Merced, Carson, and American River basins, Sierra Nevada, California, 1900-2099 *

USGS Publications Warehouse

Dettinger, M.D.; Cayan, D.R.; Meyer, M.K.; Jeton, A.

2004-01-01

Hydrologic responses of river basins in the Sierra Nevada of California to historical and future climate variations and changes are assessed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-yr period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th century until about 1975 when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st century with an attendant +2.5??C warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. The various projected trends in the business-as-usual simulations become readily visible despite realistic simulated natural climatic and hydrologic variability by about 2025. In contrast to these changes that are mostly associated with streamflow timing, long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. A control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995 yields climate and streamflow timing conditions much like the 1980s and 1990s throughout its duration. The availability of continuous climate-change projection outputs and careful design of initial conditions and control experiments, like those utilized here, promise to improve the quality and usability of future climate-change impact assessments.
Global scale groundwater flow model

NASA Astrophysics Data System (ADS)

Sutanudjaja, Edwin; de Graaf, Inge; van Beek, Ludovicus; Bierkens, Marc

2013-04-01

As the world's largest accessible source of freshwater, groundwater plays vital role in satisfying the basic needs of human society. It serves as a primary source of drinking water and supplies water for agricultural and industrial activities. During times of drought, groundwater sustains water flows in streams, rivers, lakes and wetlands, and thus supports ecosystem habitat and biodiversity, while its large natural storage provides a buffer against water shortages. Yet, the current generation of global scale hydrological models does not include a groundwater flow component that is a crucial part of the hydrological cycle and allows the simulation of groundwater head dynamics. In this study we present a steady-state MODFLOW (McDonald and Harbaugh, 1988) groundwater model on the global scale at 5 arc-minutes resolution. Aquifer schematization and properties of this groundwater model were developed from available global lithological model (e.g. Dürr et al., 2005; Gleeson et al., 2010; Hartmann and Moorsdorff, in press). We force the groundwtaer model with the output from the large-scale hydrological model PCR-GLOBWB (van Beek et al., 2011), specifically the long term net groundwater recharge and average surface water levels derived from routed channel discharge. We validated calculated groundwater heads and depths with available head observations, from different regions, including the North and South America and Western Europe. Our results show that it is feasible to build a relatively simple global scale groundwater model using existing information, and estimate water table depths within acceptable accuracy in many parts of the world.
Century long observation constrained global dynamic downscaling and hydrologic implication

NASA Astrophysics Data System (ADS)

Kim, H.; Yoshimura, K.; Chang, E.; Famiglietti, J. S.; Oki, T.

2012-12-01

It has been suggested that greenhouse gas induced warming climate causes the acceleration of large scale hydrologic cycles, and, indeed, many regions on the Earth have been suffered by hydrologic extremes getting more frequent. However, historical observations are not able to provide enough information in comprehensive manner to understand their long-term variability and/or global distributions. In this study, a century long high resolution global climate data is developed in order to break through existing limitations. 20th Century Reanalysis (20CR) which has relatively low spatial resolution (~2.0°) and longer term availability (140 years) is dynamically downscaled into global T248 (~0.5°) resolution using Experimental Climate Prediction Center (ECPC) Global Spectral Model (GSM) by spectral nudging data assimilation technique. Also, Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU) observational data are adopted to reduce model dependent uncertainty. Downscaled product successfully represents realistic geographical detail keeping low frequency signal in mean state and spatiotemporal variability, while previous bias correction method fails to reproduce high frequency variability. Newly developed data is used to investigate how long-term large scale terrestrial hydrologic cycles have been changed globally and how they have been interacted with various climate modes, such as El-Niño Southern Oscillation (ENSO) and Atlantic Multidecadal Oscillation (AMO). As a further application, it will be used to provide atmospheric boundary condition of multiple land surface models in the Global Soil Wetness Project Phase 3 (GSWP3).
Water resources in the twenty-first century; a study of the implications of climate uncertainty

USGS Publications Warehouse

Moss, Marshall E.; Lins, Harry F.

1989-01-01

The interactions of the water resources on and within the surface of the Earth with the atmosphere that surrounds it are exceedingly complex. Increased uncertainty can be attached to the availability of water of usable quality in the 21st century, therefore, because of potential anthropogenic changes in the global climate system. For the U.S. Geological Survey to continue to fulfill its mission with respect to assessing the Nation's water resources, an expanded program to study the hydrologic implications of climate uncertainty will be required. The goal for this program is to develop knowledge and information concerning the potential water-resources implications for the United States of uncertainties in climate that may result from both anthropogenic and natural changes of the Earth's atmosphere. Like most past and current water-resources programs of the Geological Survey, the climate-uncertainty program should be composed of three elements: (1) research, (2) data collection, and (3) interpretive studies. However, unlike most other programs, the climate-uncertainty program necessarily will be dominated by its research component during its early years. Critical new concerns to be addressed by the research component are (1) areal estimates of evapotranspiration, (2) hydrologic resolution within atmospheric (climatic) models at the global scale and at mesoscales, (3) linkages between hydrology and climatology, and (4) methodology for the design of data networks that will help to track the impacts of climate change on water resources. Other ongoing activities in U.S. Geological Survey research programs will be enhanced to make them more compatible with climate-uncertainty research needs. The existing hydrologic data base of the Geological Survey serves as a key element in assessing hydrologic and climatologic change. However, this data base has evolved in response to other needs for hydrologic information and probably is not as sensitive to climate change as is desirable. Therefore, as measurement and network-design methodologies are improved to account for climate-change potential, new data-collection activities will be added to the existing programs. One particular area of data-collection concern pertains to the phenomenon of evapotranspiration. Interpretive studies of the hydrologic implications of climate uncertainty will be initiated by establishing several studies at the river-basin scale in diverse hydroclimatic and demographic settings. These studies will serve as tests of the existing methodologies for studying the impacts of climate change and also will help to define subsequent research priorities. A prototype for these studies was initiated in early 1988 in the Delaware River basin.
Groundwater flow and solute transport modelling from within R: Development of the RMODFLOW and RMT3DMS packages.

NASA Astrophysics Data System (ADS)

Rogiers, Bart

2015-04-01

Since a few years, an increasing number of contributed R packages is becoming available, in the field of hydrology. Hydrological time series analysis packages, lumped conceptual rainfall-runoff models, distributed hydrological models, weather generators, and different calibration and uncertainty estimation methods are all available. Also a few packages are available for solving partial differential equations. Subsurface hydrological modelling is however still seldomly performed in R, or with codes interfaced with R, despite the fact that excellent geostatistical packages, model calibration/inversion options and state-of-the-art visualization libraries are available. Moreover, other popular scientific programming languages like matlab and python have packages for pre- and post-processing files of MODFLOW (Harbaugh 2005) and MT3DMS (Zheng 2010) models. To fill this gap, we present here the development versions of the RMODFLOW and RMT3DMS packages, which allow pre- and post-processing MODFLOW and MT3DMS input and output files from within R. File reading and writing functions are currently available for different packages, and plotting functions are foreseen making use of the ggplot2 package (plotting system based on the grammar of graphics; Wickham 2009). The S3 generic-function object oriented programming style is used for this. An example is provided, making modifications to an existing model, and visualization of the model output. References Harbaugh, A. (2005). MODFLOW-2005: The US Geological Survey Modular Ground-water Model--the Ground-water Flow Process, U.S. Geological Survey Techniques and Methods 6-A16 (p. 253). Wickham, H. (2009). ggplot2: elegant graphics for data analysis. Springer New York, 2009. Zheng, C. (2010). MT3DMS v5.3, a modular three-dimensional multispecies transport model for simulation of advection, dispersion and chemical reactions of contaminants in groundwater systems. Supplemental User's Guide. (p. 56).
Small scale green infrastructure design to meet different urban hydrological criteria.

PubMed

Jia, Z; Tang, S; Luo, W; Li, S; Zhou, M

2016-04-15

As small scale green infrastructures, rain gardens have been widely advocated for urban stormwater management in the contemporary low impact development (LID) era. This paper presents a simple method that consists of hydrological models and the matching plots of nomographs to provide an informative and practical tool for rain garden sizing and hydrological evaluation. The proposed method considers design storms, infiltration rates and the runoff contribution area ratio of the rain garden, allowing users to size a rain garden for a specific site with hydrological reference and predict overflow of the rain garden under different storms. The nomographs provide a visual presentation on the sensitivity of different design parameters. Subsequent application of the proposed method to a case study conducted in a sub-humid region in China showed that, the method accurately predicted the design storms for the existing rain garden, the predicted overflows under large storm events were within 13-50% of the measured volumes. The results suggest that the nomographs approach is a practical tool for quick selection or assessment of design options that incorporate key hydrological parameters of rain gardens or other infiltration type green infrastructure. The graphic approach as displayed by the nomographs allow urban planners to demonstrate the hydrological effect of small scale green infrastructure and gain more support for promoting low impact development. Copyright © 2016 Elsevier Ltd. All rights reserved.

Developing a Virtual Network of Research Observatories

NASA Astrophysics Data System (ADS)

Hooper, R. P.; Kirschtl, D.

2008-12-01

The hydrologic community has been discussing the concept of a network of observatories for the advancement of hydrologic science in areas of scaling processes, in testing generality of hypotheses, and in examining non-linear couplings between hydrologic, biotic, and human systems. The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) is exploring the formation of a virtual network of observatories, formed from existing field studies without regard to funding source. Such a network would encourage sharing of data, metadata, field methods, and data analysis techniques to enable multidisciplinary synthesis, meta-analysis, and scientific collaboration in hydrologic and environmental science and engineering. The virtual network would strive to provide both the data and the environmental context of the data through advanced cyberinfrastructure support. The foundation for this virtual network is Water Data Services that enable the publication of time-series data collected at fixed points using a services-oriented architecture. These publication services, developed in the CUAHSI Hydrologic Information Systems project, permit the discovery of data from both academic and government sources through a single portal. Additional services under consideration are publication of geospatial data sets, immersive environments based upon site digital elevation models, and a common web portal to member sites populated with structured data about the site (such as land use history and geologic setting) to permit understanding the environmental context of the data being shared.
Developing New Modelling Tools for Environmental Flow Assessment in Regulated Salmon Rivers

NASA Astrophysics Data System (ADS)

Geris, Josie; Soulsby, Chris; Tetzlaff, Doerthe

2013-04-01

There is a strong political drive in Scotland to meet all electricity demands from renewable sources by 2020. In Scotland, hydropower generation has a long history and is a key component of this strategy. However, many rivers sustain freshwater communities that have both high conservation status and support economically important Atlantic salmon fisheries. Both new and existing hydropower schemes must be managed in accordance with the European Union's Water Framework Directive (WFD), which requires that all surface water bodies achieve good ecological status or maintain good ecological potential. Unfortunately, long-term river flow monitoring is sparse in the Scottish Highlands and there are limited data for defining environmental flows. The River Tay is the most heavily regulated catchment in the UK. To support hydropower generation, it has an extensive network of inter- and intra- catchment transfers, in addition to a large number of regulating reservoirs for which abstraction legislation often only requires minimum compensation flows. The Tay is also considered as one of Scotland's most important rivers for Atlantic salmon (Salmo salar), and there is considerable uncertainty as to how best change reservoir operations to improve the ecological potential of the river system. It is now usually considered that environmental flows require more than a minimum compensation flow, and instead should cover a range of hydrological flow aspects that represent ecologically relevant streamflow attributes, including magnitude, timing, duration, frequency and rate of change. For salmon, these hydrological indices are of particular interest, with requirements varying at different stages of their life cycle. To meet the WFD requirements, rationally alter current abstraction licences and provide an evidence base for regulating new hydropower schemes, advanced definitions for abstraction limits and ecologically appropriate flow releases are desirable. However, a good understanding of the natural flow variability and the hydrological impacts of the regulation is unavailable, partly because pre-regulation data of existing hydropower schemes are lacking. Here we develop a novel modelling approach for characterising natural flow regimes and defining hydrological flow indices. This allows us to quantitatively assess the impacts of hydropower to better inform environmental flow requirements for the Atlantic salmon river ecosystem. Results are presented for the River Lyon (390 km2), a regulated headwater catchment of the River Tay. The HBV hydrological rainfall-runoff model is used to simulate flows, based on calibrated parameters from regulated flow data, with the current hydropower scheme active. For this, the HBV model is adapted to be able to incorporate water transfers and regulated flows. The natural hydrological indices are derived from the simulated pre-regulation data, and compared with those of the regulated data to investigate the impact of the regulation on these at different critical times for Atlantic salmon. The sensitivity of the system to change is also investigated to explore the extent to which flow variables can be modified without major degradation to the river's ecosystem, while still maintaining viable hydropower generation. The modelling approach presented will provide the basis for assessing impacts on hydrological flow indices and informing environmental flows in regions with similar heavily regulated mountain river ecosystems.
A study of the break-up characteristics of Chena River Basin using ERTS imagery

NASA Technical Reports Server (NTRS)

Carlson, R. F. (Principal Investigator); Kane, D. L.; Wendler, G.

1973-01-01

The author has identified the following significant results. The Chena River Basin was selected because of the availability of ground truth data for comparison. Very good agreement for snow distribution and rates of ablation was found between the ERTS-1 imagery, the snowmelt model, and field measurements. Monitoring snowmelt rates for relatively small basins appears to be practical. The main limitation of the ERTS-1 imagery is the interval of coverage. More frequent overflights providing coverage are needed for the study of transient hydrologic events. ERTS-1 data is most useful when used in conjunction with snowmelt prediction models and existing snow course data. These results should prove very useful in preliminary assessment of hydrologic conditions in ungaged watersheds and will provide a tool for month-to-month volume forecasting.
Assessment of Vulnerability to Climate Change Effects on Urban Stormwater Infrastructure in City of Las Vegas, NV

NASA Astrophysics Data System (ADS)

Thakali, R.; Kalra, A.; Mastino, L.; Velotta, M.; Ahmad, S.

2016-12-01

In the spring of 2016 the City of Las Vegas and the Southern Illinois University began collaborating on a project that seeks to assess the city's current vulnerability to drought, extreme heat, and extreme precipitation patterns, as well as the response mechanisms that are already in place within its jurisdiction. The document analyzes a series of scenarios to assess to what extent the vulnerability of four Key Planning Areas will change in the long term (30-50 years), what will be the most affected city operations, and what mechanisms the City will need to put into place to adapt to such changes. As part of the vulnerability report, this study assessed the impacts of climate change in the existing stormwater system of the Gowan watershed within City of Las Vegas, NV, by assessing projected design storms. The climate change projection for the region was evaluated using the high-resolution North American Regional Climate Change Assessment Program (NARCCAP) climate model data. The design storms (6h 100y) were calculated using the best fitted probability distribution among twenty-seven distributions for the historic and future NARCCAP climate model projection. North American Regional Reanalysis (NARR) data were used to assess the performance of NARCCAP data. The projected design storms were implemented in an existing U.S. Army Corps of Engineers' Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model developed by Clark County Regional Flood Control District (CCRFCD), Las Vegas. The simulation results showed an increase in the design storms which exceeded the capacity of existing stormwater infrastructure.
Polar motion interpretation using gravimetric observations

NASA Astrophysics Data System (ADS)

Seoane, L.; Bizouard, C.; Gambis, D.

2008-04-01

Polar motion is interpreted as the effect of i) the Earth’s inertia moment changes asso- ciated with the so-called mass term of the Earth’s angular momentum ii) the Earth’s relative angular momentum in the terrestrial frame. Thanks to the GRACE mission and in a lesser extent to LAGEOS missions, the mass term is determined since 2002, independently from any geophysical model. Besides the modeled excitations of the polar motion, i.e the atmospheric angular momentum (AAM), the Oceanic Angular Momentum (OAM), the Hydrological Angular Momentum (HAM), this gravimetric mass term is a new kind of information which can be matched to the observed excitation of the polar motion after removal of the effect of the relative angular momentum, mostly caused by the wind and the oceanic cur- rents. Such comparison, already performed by various authors, is updated for the last releases (RL04) of the gravity field changes i.e. those of the GFZ, CSR, JPL and explored for the mixed LAGEOS-GRACE solution of the GRGS. We confirm that a fair general agreement, especially for the y-component of the equatorial excitation. After removing the modeled oceanic and atmospheric excitations from the signals, we obtain the non-modeled excitation, mostly of hydrological nature; this allows us to compare them to the existing hydrological models, differences might comes from others Earth’s phenomena, for example, earthquakes.
Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

NASA Astrophysics Data System (ADS)

Hao, Zengchao; Singh, Vijay P.; Xia, Youlong

2018-03-01

Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.
Implications of GRACE Satellite Gravity Measurements for Diverse Hydrological Applications

NASA Astrophysics Data System (ADS)

Yirdaw-Zeleke, Sitotaw

Soil moisture plays a major role in the hydrologic water balance and is the basis for most hydrological models. It influences the partitioning of energy and moisture inputs at the land surface. Because of its importance, it has been used as a key variable for many hydrological studies such as flood forecasting, drought studies and the determination of groundwater recharge. Therefore, spatially distributed soil moisture with reasonable temporal resolution is considered a valuable source of information for hydrological model parameterization and validation. Unfortunately, soil moisture is difficult to measure and remains essentially unmeasured over spatial and temporal scales needed for a number of hydrological model applications. In 2002, the Gravity Recovery And Climate Experiment (GRACE) satellite platform was launched to measure, among other things, the gravitational field of the earth. Over its life span, these orbiting satellites have produced time series of mass changes of the earth-atmosphere system. The subsequent outcome of this, after integration over a number of years, is a time series of highly refined images of the earth's mass distribution. In addition to quantifying the static distribution of mass, the month-to-month variation in the earth's gravitational field are indicative of the integrated value of the subsurface total water storage for specific catchments. Utilization of these natural changes in the earth's gravitational field entails the transformation of the derived GRACE geopotential spherical harmonic coefficients into spatially varying time series estimates of total water storage. These remotely sensed basin total water storage estimates can be routinely validated against independent estimates of total water storage from an atmospheric-based water balance approach or from well calibrated macroscale hydrologic models. The hydrological relevance and implications of remotely estimated GRACE total water storage over poorly gauged, wetland-dominated watershed as well as over a deltaic region underlain by a thick sand aquifer in Western Canada are the focus of this thesis. The domain of the first case study was the Mackenzie River Basin wherein the GRACE total water storage estimates were successfully inter-compared and validated with the atmospheric based water balance. These were then used to assess the WAT-CLASS hydrological model estimates of total water storage. The outcome of this inter-comparison revealed the potential application of the GRACE-based approach for the closure of the hydrological water balance of the Mackenzie River Basin as well as a dependable source of data for the calibration of traditional hydrological models. The Mackenzie River Basin result led to a second case study where the GRACE-based total water storage was validated using storage estimated from the atmospheric-based water balance P--E computations in conjunction with the measured streamflow records for the Saskatchewan River Basin at its Grand Rapids outlet in Manitoba. The fallout from this comparison was then applied to the characterization of the Prairie-wide 2002/2003 drought enabling the development of a new drought index now known as the Total Storage Deficit Index (TSDI). This study demonstrated the potential application of the GRACE-based technique as a tool for drought characterization in the Canadian Prairies. Finally, the hydroinformatic approach based on the artificial neural network (ANN) enabled the downscaling of the groundwater component from the total water storage estimate from the remote sensing satellite, GRACE. This was subsequently explored as an alternate source of calibration and validation for a hydrological modeling application over the Assiniboine Delta Aquifer in Manitoba. Interestingly, a high correlation exists between the simulated groundwater storage from the coupled hydrological model, CLM-PF and the downscaled groundwater time series storage from the remote sensing satellite GRACE over this 4,000 km2 deltaic basin in Canada.
A Participatory Modeling Application of a Distributed Hydrologic Model in Nuevo Leon, Mexico for the 2010 Hurricane Alex Flood Event

NASA Astrophysics Data System (ADS)

Baish, A. S.; Vivoni, E. R.; Payan, J. G.; Robles-Morua, A.; Basile, G. M.

2011-12-01

A distributed hydrologic model can help bring consensus among diverse stakeholders in regional flood planning by producing quantifiable sets of alternative futures. This value is acute in areas with high uncertainties in hydrologic conditions and sparse observations. In this study, we conduct an application of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS) in the Santa Catarina basin of Nuevo Leon, Mexico, where Hurricane Alex in July 2010 led to catastrophic flooding of the capital city of Monterrey. Distributed model simulations utilize best-available information on the regional topography, land cover, and soils obtained from Mexican government agencies or analysis of remotely-sensed imagery from MODIS and ASTER. Furthermore, we developed meteorological forcing for the flood event based on multiple data sources, including three local gauge networks, satellite-based estimates from TRMM and PERSIANN, and the North American Land Data Assimilation System (NLDAS). Remotely-sensed data allowed us to quantify rainfall distributions in the upland, rural portions of the Santa Catarina that are sparsely populated and ungauged. Rural areas had significant contributions to the flood event and as a result were considered by stakeholders for flood control measures, including new reservoirs and upland vegetation management. Participatory modeling workshops with the stakeholders revealed a disconnect between urban and rural populations in regard to understanding the hydrologic conditions of the flood event and the effectiveness of existing and potential flood control measures. Despite these challenges, the use of the distributed flood forecasts developed within this participatory framework facilitated building consensus among diverse stakeholders and exploring alternative futures in the basin.
Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modelling heteroscedastic residual errors

NASA Astrophysics Data System (ADS)

David, McInerney; Mark, Thyer; Dmitri, Kavetski; George, Kuczera

2017-04-01

This study provides guidance to hydrological researchers which enables them to provide probabilistic predictions of daily streamflow with the best reliability and precision for different catchment types (e.g. high/low degree of ephemerality). Reliable and precise probabilistic prediction of daily catchment-scale streamflow requires statistical characterization of residual errors of hydrological models. It is commonly known that hydrological model residual errors are heteroscedastic, i.e. there is a pattern of larger errors in higher streamflow predictions. Although multiple approaches exist for representing this heteroscedasticity, few studies have undertaken a comprehensive evaluation and comparison of these approaches. This study fills this research gap by evaluating 8 common residual error schemes, including standard and weighted least squares, the Box-Cox transformation (with fixed and calibrated power parameter, lambda) and the log-sinh transformation. Case studies include 17 perennial and 6 ephemeral catchments in Australia and USA, and two lumped hydrological models. We find the choice of heteroscedastic error modelling approach significantly impacts on predictive performance, though no single scheme simultaneously optimizes all performance metrics. The set of Pareto optimal schemes, reflecting performance trade-offs, comprises Box-Cox schemes with lambda of 0.2 and 0.5, and the log scheme (lambda=0, perennial catchments only). These schemes significantly outperform even the average-performing remaining schemes (e.g., across ephemeral catchments, median precision tightens from 105% to 40% of observed streamflow, and median biases decrease from 25% to 4%). Theoretical interpretations of empirical results highlight the importance of capturing the skew/kurtosis of raw residuals and reproducing zero flows. Recommendations for researchers and practitioners seeking robust residual error schemes for practical work are provided.
Flood-hazard analysis of four headwater streams draining the Argonne National Laboratory property, DuPage County, Illinois

USGS Publications Warehouse

Soong, David T.; Murphy, Elizabeth A.; Straub, Timothy D.; Zeeb, Hannah L.

2016-11-22

Results of a flood-hazard analysis conducted by the U.S. Geological Survey, in cooperation with the Argonne National Laboratory, for four headwater streams within the Argonne National Laboratory property indicate that the 1-percent and 0.2-percent annual exceedance probability floods would cause multiple roads to be overtopped. Results indicate that most of the effects on the infrastructure would be from flooding of Freund Brook. Flooding on the Northeast and Southeast Drainage Ways would be limited to overtopping of one road crossing for each of those streams. The Northwest Drainage Way would be the least affected with flooding expected to occur in open grass or forested areas.The Argonne Site Sustainability Plan outlined the development of hydrologic and hydraulic models and the creation of flood-plain maps of the existing site conditions as a first step in addressing resiliency to possible climate change impacts as required by Executive Order 13653 “Preparing the United States for the Impacts of Climate Change.” The Hydrological Simulation Program-FORTRAN is the hydrologic model used in the study, and the Hydrologic Engineering Center‒River Analysis System (HEC–RAS) is the hydraulic model. The model results were verified by comparing simulated water-surface elevations to observed water-surface elevations measured at a network of five crest-stage gages on the four study streams. The comparison between crest-stage gage and simulated elevations resulted in an average absolute difference of 0.06 feet and a maximum difference of 0.19 feet.In addition to the flood-hazard model development and mapping, a qualitative stream assessment was conducted to evaluate stream channel and substrate conditions in the study reaches. This information can be used to evaluate erosion potential.
Merging of rain gauge and radar data for urban hydrological modelling

NASA Astrophysics Data System (ADS)

Berndt, Christian; Haberlandt, Uwe

2015-04-01

Urban hydrological processes are generally characterised by short response times and therefore rainfall data with a high resolution in space and time are required for their modelling. In many smaller towns, no recordings of rainfall data exist within the urban catchment. Precipitation radar helps to provide extensive rainfall data with a temporal resolution of five minutes, but the rainfall amounts can be highly biased and hence the data should not be used directly as a model input. However, scientists proposed several methods for adjusting radar data to station measurements. This work tries to evaluate rainfall inputs for a hydrological model regarding the following two different applications: Dimensioning of urban drainage systems and analysis of single event flow. The input data used for this analysis can be divided into two groups: Methods, which rely on station data only (Nearest Neighbour Interpolation, Ordinary Kriging), and methods, which incorporate station as well as radar information (Conditional Merging, Bias correction of radar data based on quantile mapping with rain gauge recordings). Additionally, rainfall intensities that were directly obtained from radar reflectivities are used. A model of the urban catchment of the city of Brunswick (Lower Saxony, Germany) is utilised for the evaluation. First results show that radar data cannot help with the dimensioning task of sewer systems since rainfall amounts of convective events are often overestimated. Gauges in catchment proximity can provide more reliable rainfall extremes. Whether radar data can be helpful to simulate single event flow depends strongly on the data quality and thus on the selected event. Ordinary Kriging is often not suitable for the interpolation of rainfall data in urban hydrology. This technique induces a strong smoothing of rainfall fields and therefore a severe underestimation of rainfall intensities for convective events.
Rainfall disaggregation for urban hydrology: Effects of spatial consistence

NASA Astrophysics Data System (ADS)

Müller, Hannes; Haberlandt, Uwe

2015-04-01

For urban hydrology rainfall time series with a high temporal resolution are crucial. Observed time series of this kind are very short in most cases, so they cannot be used. On the contrary, time series with lower temporal resolution (daily measurements) exist for much longer periods. The objective is to derive time series with a long duration and a high resolution by disaggregating time series of the non-recording stations with information of time series of the recording stations. The multiplicative random cascade model is a well-known disaggregation model for daily time series. For urban hydrology it is often assumed, that a day consists of only 1280 minutes in total as starting point for the disaggregation process. We introduce a new variant for the cascade model, which is functional without this assumption and also outperforms the existing approach regarding time series characteristics like wet and dry spell duration, average intensity, fraction of dry intervals and extreme value representation. However, in both approaches rainfall time series of different stations are disaggregated without consideration of surrounding stations. This yields in unrealistic spatial patterns of rainfall. We apply a simulated annealing algorithm that has been used successfully for hourly values before. Relative diurnal cycles of the disaggregated time series are resampled to reproduce the spatial dependence of rainfall. To describe spatial dependence we use bivariate characteristics like probability of occurrence, continuity ratio and coefficient of correlation. Investigation area is a sewage system in Northern Germany. We show that the algorithm has the capability to improve spatial dependence. The influence of the chosen disaggregation routine and the spatial dependence on overflow occurrences and volumes of the sewage system will be analyzed.
Multi-model approach to assess the impact of climate change on runoff

NASA Astrophysics Data System (ADS)

Dams, J.; Nossent, J.; Senbeta, T. B.; Willems, P.; Batelaan, O.

2015-10-01

The assessment of climate change impacts on hydrology is subject to uncertainties related to the climate change scenarios, stochastic uncertainties of the hydrological model and structural uncertainties of the hydrological model. This paper focuses on the contribution of structural uncertainty of hydrological models to the overall uncertainty of the climate change impact assessment. To quantify the structural uncertainty of hydrological models, four physically based hydrological models (SWAT, PRMS and a semi- and fully distributed version of the WetSpa model) are set up for a catchment in Belgium. Each model is calibrated using four different objective functions. Three climate change scenarios with a high, mean and low hydrological impact are statistically perturbed from a large ensemble of climate change scenarios and are used to force the hydrological models. This methodology allows assessing and comparing the uncertainty introduced by the climate change scenarios with the uncertainty introduced by the hydrological model structure. Results show that the hydrological model structure introduces a large uncertainty on both the average monthly discharge and the extreme peak and low flow predictions under the climate change scenarios. For the low impact climate change scenario, the uncertainty range of the mean monthly runoff is comparable to the range of these runoff values in the reference period. However, for the mean and high impact scenarios, this range is significantly larger. The uncertainty introduced by the climate change scenarios is larger than the uncertainty due to the hydrological model structure for the low and mean hydrological impact scenarios, but the reverse is true for the high impact climate change scenario. The mean and high impact scenarios project increasing peak discharges, while the low impact scenario projects increasing peak discharges only for peak events with return periods larger than 1.6 years. All models suggest for all scenarios a decrease of the lowest flows, except for the SWAT model with the mean hydrological impact climate change scenario. The results of this study indicate that besides the uncertainty introduced by the climate change scenarios also the hydrological model structure uncertainty should be taken into account in the assessment of climate change impacts on hydrology. To make it more straightforward and transparent to include model structural uncertainty in hydrological impact studies, there is a need for hydrological modelling tools that allow flexible structures and methods to validate model structures in their ability to assess impacts under unobserved future climatic conditions.
Scots pine (Pinus sylvestris L.) based reconstruction of 130 years of water table fluctuations in a peatland and its relevance for moisture variability assessments

NASA Astrophysics Data System (ADS)

Tamkevičiūtė, Marija; Edvardsson, Johannes; Pukienė, Rūtilė; Taminskas, Julius; Stoffel, Markus; Corona, Christophe; Kibirkštis, Gintautas

2018-03-01

Continuous water-table (WT) measurements from peatlands are scarce and - if existing at all -very short. Consequently, proxy indicators are critically needed to simulate hydrological changes in peatlands over longer time periods. In this study, we demonstrate that tree-ring width (TRW) records of Scots pine (Pinus sylvestris L.) growing in the Čepkeliai peatland (southern Lithuania) can be used as a proxy to reconstruct hydrological variability in a raised bog environment. A two-step modelling procedure was applied to extend existing measurements and to develop a new and longer peatland WT time series. To this end, we used instrumental WT measurements extending back to 2002, meteorological records, a P-PET (difference between precipitation and potential evapotranspiration) series covering the period 1935-2014, so as to construct a tree-ring based time series of WT fluctuations at the site for the period 1870-2014. Strongest correlations were obtained between average annual WT measured at the bog margin and total P-PET over 7 years (r = 0.923, p < 0.00001), as well as between modelled WT and standardized TRW data with a two years lag (r = -0.602, p < 0.001) for those periods where WT fluctuated at the level of pine roots which is typically at <50 cm depth below the peat surface. Our results suggest that moisture is a limiting factor for tree growth at peatlands, but below a certain WT level (<50 cm under the soil surface), drought becomes a limiting factor instead. To validate the WT reconstruction from the Čepkeliai bog, results were compared to Nemunas river runoff since CE 1812 (r = 0.39, p < 0.00001, 1870-2014). We conclude that peatlands can act both as sinks and sources of greenhouse gases in case that hydrological conditions change, but that hydrological lags and complex feedbacks still hamper our understanding of several processes affecting the hydrology and carbon budget in peatlands. We therefore call for the development of further proxy records of water-table variability in peatlands to improve our understanding of peatland responses to climatic changes.
Hydrological research in Ethiopia

NASA Astrophysics Data System (ADS)

Gebremichael, M.

2012-12-01

Almost all major development problems in Ethiopia are water-related: food insecurity, low economic development, recurrent droughts, disastrous floods, poor health conditions, and low energy condition. In order to develop and manage existing water resources in a sustainable manner, knowledge is required about water availability, water quality, water demand in various sectors, and the impacts of water resource projects on health and the environment. The lack of ground-based data has been a major challenge for generating this knowledge. Current advances in remote sensing and computer simulation technology could provide alternative source of datasets. In this talk, I will present the challenges and opportunities in using remote sensing datasets and hydrological models in regions such as Africa where ground-based datasets are scarce.
Assessment of Flood Mitigation Solutions Using a Hydrological Model and Refined 2D Hydrodynamic Simulations

NASA Astrophysics Data System (ADS)

Khuat Duy, B.; Archambeau, P.; Dewals, B. J.; Erpicum, S.; Pirotton, M.

2009-04-01

Following recurrent inundation problems on the Berwinne catchment, in Belgium, a combined hydrologic and hydrodynamic study has been carried out in order to find adequate solutions for the floods mitigation. Thanks to detailed 2D simulations, the effectiveness of the solutions can be assessed not only in terms of discharge and height reductions in the river, but also with other aspects such as the inundated surfaces reduction and the decrease of inundated buildings and roads. The study is carried out in successive phases. First, the hydrological runoffs are generated using a physically based and spatially distributed multi-layer model solving depth-integrated equations for overland flow, subsurface flow and baseflow. Real floods events are simulated using rainfall series collected at 8 stations (over 20 years of available data). The hydrological inputs are routed through the river network (and through the sewage network if relevant) with the 1D component of the modelling system, which solves the Saint-Venant equations for both free-surface and pressurized flows in a unified way. On the main part of the river, the measured river cross-sections are included in the modelling, and existing structures along the river (such as bridges, sluices or pipes) are modelled explicitely with specific cross sections. Two gauging stations with over 15 years of continuous measurements allow the calibration of both the hydrologic and hydrodynamic models. Second, the flood mitigation solutions are tested in the simulations in the case of an extreme flooding event, and their effects are assessed using detailed 2D simulations on a few selected sensitive areas. The digital elevation model comes from an airborne laser survey with a spatial resolution of 1 point per square metre and is completed in the river bed with a bathymetry interpolated from cross-section data. The upstream discharge is extracted from the 1D simulation for the selected rainfall event. The study carried out with this methodology allowed to assess the suggested solutions with multiple effectiveness criteria and therefore constitutes a very useful support for decision makers.
Subglacial Hydrology Model Intercomparison Project (SHMIP)

NASA Astrophysics Data System (ADS)

Werder, Mauro A.; de Fleurian, Basile; Creyts, Timothy T.; Damsgaard, Anders; Delaney, Ian; Dow, Christine F.; Gagliardini, Olivier; Hoffman, Matthew J.; Seguinot, Julien; Sommers, Aleah; Irarrazaval Bustos, Inigo; Downs, Jakob

2017-04-01

The SHMIP project is the first intercomparison project of subglacial drainage models (http://shmip.bitbucket.org). Its synthetic test suites and evaluation were designed such that any subglacial hydrology model producing effective pressure can participate. In contrast to ice deformation, the physical processes of subglacial hydrology (which in turn impacts basal sliding of glaciers) are poorly known. A further complication is that different glacial and geological settings can lead to different drainage physics. The aim of the project is therefore to qualitatively compare the outputs of the participating models for a wide range of water forcings and glacier geometries. This will allow to put existing studies, which use different drainage models, into context and will allow new studies to select the most suitable model for the problem at hand. We present the results from the just completed intercomparison exercise. Twelve models participated: eight 2D and four 1D models; nine include both an efficient and inefficient system, the other three one of the systems; all but two models use R-channels as efficient system, and/or a linked-cavity like inefficient system, one exception uses porous layers with different characteristic for each of the systems, the other exception is based on canals. The main variable used for the comparison is effective pressure, as that is a direct proxy for basal sliding of glaciers. The models produce large differences in the effective pressure fields, in particular for higher water input scenarios. This shows that the selection of a subglacial drainage model will likely impact the conclusions of a study significantly.
Cumuilative Effects of Impoundments on the Hydrology of Riparian Wetlands along the Marmaton River, west-central Missouri

USGS Publications Warehouse

Heimann, David C.; Krempa, Heather M.

2011-01-01

The effects of proposed impoundments and resulting streamflow regulation on riparian wetlands in the Marmaton River Basin, Missouri, USA were determined using measurements and numerical simulations of wetland water budgets. Calibrated and validated Soil-Plant-Air-Water (SPAW) models were used to simulate daily water depths of four riparian wetlands for Current (model scenario of existing impoundments) and Proposed (model scenario of existing and proposed impoundments) impoundment conditions. The simulated frequency of flooding decreased 19–65% at the wetlands following the additions of proposed impoundments. The reduced flooding resulted in decreases in wetland water depths at all sites during the 10 simulated growing seasons under Proposed conditions with an average duration of continuous water-depth declines of 289 days at the upstream (most regulated) site. Downstream wetlands within the zone of least regulation had an average duration of water level decreases of about 20 days. Decreased water levels under Proposed conditions resulted in a range of 65–365 additional dry days at the study wetlands during the simulated 10-year period of Proposed conditions. The areas of the four wetlands meeting the hydrologic criteria of a formal jurisdictional wetland definition decreased ranging from zero to 31% under Proposed impoundment conditions.
Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

NASA Technical Reports Server (NTRS)

Pokhrel, Yadu N.; Hanasaki, Naota; Wada, Yoshihide; Kim, Hyungjun

2016-01-01

The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.
A priori discretization quality metrics for distributed hydrologic modeling applications

NASA Astrophysics Data System (ADS)

Liu, Hongli; Tolson, Bryan; Craig, James; Shafii, Mahyar; Basu, Nandita

2016-04-01

In distributed hydrologic modelling, a watershed is treated as a set of small homogeneous units that address the spatial heterogeneity of the watershed being simulated. The ability of models to reproduce observed spatial patterns firstly depends on the spatial discretization, which is the process of defining homogeneous units in the form of grid cells, subwatersheds, or hydrologic response units etc. It is common for hydrologic modelling studies to simply adopt a nominal or default discretization strategy without formally assessing alternative discretization levels. This approach lacks formal justifications and is thus problematic. More formalized discretization strategies are either a priori or a posteriori with respect to building and running a hydrologic simulation model. A posteriori approaches tend to be ad-hoc and compare model calibration and/or validation performance under various watershed discretizations. The construction and calibration of multiple versions of a distributed model can become a seriously limiting computational burden. Current a priori approaches are more formalized and compare overall heterogeneity statistics of dominant variables between candidate discretization schemes and input data or reference zones. While a priori approaches are efficient and do not require running a hydrologic model, they do not fully investigate the internal spatial pattern changes of variables of interest. Furthermore, the existing a priori approaches focus on landscape and soil data and do not assess impacts of discretization on stream channel definition even though its significance has been noted by numerous studies. The primary goals of this study are to (1) introduce new a priori discretization quality metrics considering the spatial pattern changes of model input data; (2) introduce a two-step discretization decision-making approach to compress extreme errors and meet user-specified discretization expectations through non-uniform discretization threshold modification. The metrics for the first time provides quantification of the routing relevant information loss due to discretization according to the relationship between in-channel routing length and flow velocity. Moreover, it identifies and counts the spatial pattern changes of dominant hydrological variables by overlaying candidate discretization schemes upon input data and accumulating variable changes in area-weighted way. The metrics are straightforward and applicable to any semi-distributed or fully distributed hydrological model with grid scales are greater than input data resolutions. The discretization metrics and decision-making approach are applied to the Grand River watershed located in southwestern Ontario, Canada where discretization decisions are required for a semi-distributed modelling application. Results show that discretization induced information loss monotonically increases as discretization gets rougher. With regards to routing information loss in subbasin discretization, multiple interesting points rather than just the watershed outlet should be considered. Moreover, subbasin and HRU discretization decisions should not be considered independently since subbasin input significantly influences the complexity of HRU discretization result. Finally, results show that the common and convenient approach of making uniform discretization decisions across the watershed domain performs worse compared to a metric informed non-uniform discretization approach as the later since is able to conserve more watershed heterogeneity under the same model complexity (number of computational units).

Advancing the Implementation of Hydrologic Models as Web-based Applications

NASA Astrophysics Data System (ADS)

Dahal, P.; Tarboton, D. G.; Castronova, A. M.

2017-12-01

Advanced computer simulations are required to understand hydrologic phenomenon such as rainfall-runoff response, groundwater hydrology, snow hydrology, etc. Building a hydrologic model instance to simulate a watershed requires investment in data (diverse geospatial datasets such as terrain, soil) and computer resources, typically demands a wide skill set from the analyst, and the workflow involved is often difficult to reproduce. This work introduces a web-based prototype infrastructure in the form of a web application that provides researchers with easy to use access to complete hydrological modeling functionality. This includes creating the necessary geospatial and forcing data, preparing input files for a model by applying complex data preprocessing, running the model for a user defined watershed, and saving the results to a web repository. The open source Tethys Platform was used to develop the web app front-end Graphical User Interface (GUI). We used HydroDS, a webservice that provides data preparation processing capability to support backend computations used by the app. Results are saved in HydroShare, a hydrologic information system that supports the sharing of hydrologic data, model and analysis tools. The TOPographic Kinematic APproximation and Integration (TOPKAPI) model served as the example for which we developed a complete hydrologic modeling service to demonstrate the approach. The final product is a complete modeling system accessible through the web to create input files, and run the TOPKAPI hydrologic model for a watershed of interest. We are investigating similar functionality for the preparation of input to Regional Hydro-Ecological Simulation System (RHESSys). Key Words: hydrologic modeling, web services, hydrologic information system, HydroShare, HydroDS, Tethys Platform
The Mica Creek Experimental Watershed: An Outdoor Laboratory for the Investigation of Hydrologic Processes in a Continental/Maritime Mountainous Environment

NASA Astrophysics Data System (ADS)

Link, T. E.; Gravelle, J.; Hubbart, J.; Warnsing, A.; Du, E.; Boll, J.; Brooks, E.; Cundy, T.

2004-12-01

Experimental catchments have proven to be extremely useful for investigations focused on fundamental hydrologic processes and on the impacts of land cover change on hydrologic regimes and water quality. Recent studies have illustrated how watershed responses to experimental treatments vary greatly between watersheds with differing physical, ecological and hydroclimatic characteristics. Meteorological and hydrological data within catchments are needed to help identify how hydrologic mechanisms may be altered by land cover alterations, and to both constrain and develop spatially-distributed physically based models. Existing instrumentation at the Mica Creek Experimental Watershed (MCEW) in northern Idaho is a fourth-order catchment that is undergoing expansion to produce a comprehensive dataset for model development and testing. The experimental catchments encompass a 28 km2 area spanning elevations from 975 to 1725 m msl. Snow processes dominate the hydrology of the catchment and climate conditions in the winter alternate between cold, dry continental and warm, moist maritime weather systems. Landcover is dominated by 80 year old second growth conifer forests, with partially cut (thinned) and clear-cut sub-catchments. Climate and precipitation data are collected at a SNOTEL site, three primary, and seven supplemental meteorological stations stratified by elevation and canopy cover. Manual snow depth measurements are recorded every 1-2 weeks during snowmelt, stratified by aspect, elevation and canopy cover. An air temperature transect spans three second-order sub-catchments to track air temperature lapse rate dynamics. Precipitation gauge arrays are installed within thinned and closed-canopy stands to track throughfall and interception loss. Nine paired and nested sub-catchments are monitored for flow, temperature, sediment, and nutrients. Hydroclimatic data are augmented by LiDAR and hyperspectral imagery for determination of canopy and topographic structure. Results will serve as a key dataset to assess how canopy conditions affect surface hydrology in complex snow-dominated catchments in the intermountain western U.S.
Impact of land-use and climatic changes on hydrology of the Himalayan Basin: A case study of the Kosi Basin

NASA Astrophysics Data System (ADS)

Sharma, Keshav Prasad

1997-10-01

Land-use and climatic changes are of major concern in the Himalayan region because of their potential impacts on a predominantly agriculture-based economy and a regional hydrology dominated by strong seasonality. Such concerns are not limited to any particular basin but exist throughout the region including the downstream plain areas. As a representative basin of the Himalayas, we studied the Kosi basin (54,000 km2) located in the mountainous area of the central Himalayan region. We analyzed climatic and hydrologic information to assess the impacts of existing and potential future land-use and climatic changes over the basin. The assessment of anthropogenic inputs showed that the population grew at a compound growth rate of about one percent per annum over the basin during the last four decades. The comparison of land-use data based on the surveys made in the 1960s, and the surveys of 1978-79 did not reveal noticeable trends in land-use change. Analysis of meteorological and hydrological trends using parametric and nonparametric statistics for monthly data from 1947 to 1993 showed some increasing tendency for temperature and precipitation. Statistical tests of hydrological trends indicated an overall decrease of discharge along mainstem Kosi River and its major tributaries. The decreasing trends of streamflow were more significant during low-flow months. Statistical analysis of homogeneity showed that the climatological as well as the hydrological trends were more localized in nature lacking distinct basinwide significance. Statistical analysis of annual sediment time series, available for a single station on the Kosi River did not reveal a significant trend. We used water balance, statistical correlation, and distributed deterministic modeling approaches to analyze the hydrological sensitivity of the basin to possible land-use and climatic changes. The results indicated a stronger influence of basin characteristics compared to climatic characteristics on flow regime. Among the climatic variables, hydrologic response was much more sensitive to changes in precipitation, and the response was more significant in the drier areas of the basin. Rapid retreat of glaciers due to potential global warming was shown to be as important as projected deforestation scenarios in regulating sediment flux over the basin.
Effect and relevance of the artificial drainage system when assessing the hydrologic impact of the imperviousness distribution within the watershed

NASA Astrophysics Data System (ADS)

Thenoux, M.; Gironas, J. A.; Mejia, A.

2013-12-01

Cities and urban growth have relevant environmental and social impacts, which could eventually be enhanced or reduced during the urban planning process. From the point of view of hydrology, impermeability and natural soil compaction are one of the main problems that urbanization brings to watershed. Previous studies demonstrate and quantify the impacts of the distribution of imperviousness in a watershed, both on runoff volumes and flow, and the quality and integrity of streams and receiving bodies. Moreover, some studies have investigated the optimal distribution of imperviousness, based on simulating different scenarios of land use change and its effects on runoff, mostly at the outlet of the watershed. However, these studies typically do not address the impact of artificial drainage system associated with the imperviousness scenarios, despite it is known that storm sewer coverage affects the flow accumulation and generation of flow hydrographs. This study seeks to quantify the effects and relevance of the artificial system when it comes to assess the hydrological impacts of the spatial distribution of imperviousness and to determine the characteristics of this influence. For this purpose, an existing model to generate imperviousness distribution scenarios is coupled with a model developed to automatically generate artificial drainage networks. These models are applied to a natural watershed to generate a variety of imperviousness and storm sewer layout scenarios, which are evaluate with a morphoclimatic instantaneous unit hydrograph model. We first tested the ability of this approach to represent the joint effects of imperviousness (i.e. level and distribution) and storm sewer coverage. We then quantified the effects of these variables on the hydrological response, considering also different return period in order to take into account the variability of the precipitation regime. Overall, we show that the layout and spatial coverage of the storm sewer system affect the hydrologic response, and that these effects depend on the degree of imperviousness and the characteristics of the precipitation. Results of this research improve our understanding on how urban planning decisions can contribute to minimize the hydrologic and environmental impacts of urban development.
Daily Streamflow Predictions in an Ungauged Watershed in Northern California Using the Precipitation-Runoff Modeling System (PRMS): Calibration Challenges when nearby Gauged Watersheds are Hydrologically Dissimilar

NASA Astrophysics Data System (ADS)

Dhakal, A. S.; Adera, S.

2017-12-01

Accurate daily streamflow prediction in ungauged watersheds with sparse information is challenging. The ability of a hydrologic model calibrated using nearby gauged watersheds to predict streamflow accurately depends on hydrologic similarities between the gauged and ungauged watersheds. This study examines daily streamflow predictions using the Precipitation-Runoff Modeling System (PRMS) for the largely ungauged San Antonio Creek watershed, a 96 km2 sub-watershed of the Alameda Creek watershed in Northern California. The process-based PRMS model is being used to improve the accuracy of recent San Antonio Creek streamflow predictions generated by two empirical methods. Although San Antonio Creek watershed is largely ungauged, daily streamflow data exists for hydrologic years (HY) 1913 - 1930. PRMS was calibrated for HY 1913 - 1930 using streamflow data, modern-day land use and PRISM precipitation distribution, and gauged precipitation and temperature data from a nearby watershed. The PRMS model was then used to generate daily streamflows for HY 1996-2013, during which the watershed was ungauged, and hydrologic responses were compared to two nearby gauged sub-watersheds of Alameda Creek. Finally, the PRMS-predicted daily flows between HY 1996-2013 were compared to the two empirically-predicted streamflow time series: (1) the reservoir mass balance method and (2) correlation of historical streamflows from 80 - 100 years ago between San Antonio Creek and a nearby sub-watershed located in Alameda Creek. While the mass balance approach using reservoir storage and transfers is helpful for estimating inflows to the reservoir, large discrepancies in daily streamflow estimation can arise. Similarly, correlation-based predicted daily flows which rely on a relationship from flows collected 80-100 years ago may not represent current watershed hydrologic conditions. This study aims to develop a method of streamflow prediction in the San Antonio Creek watershed by examining PRMS's model outputs as well as empirically generated flow data for their use in water resources management decisions. PRMS is also being used to better understand the streamflow patterns in the San Antonio Creek watershed for a variety of antecedent soil moisture conditions as the creek is generally dry between late Spring and early Fall.
Threshold effects of flood duration on the vegetation and soils of the Upper Mississippi River floodplain, USA

USGS Publications Warehouse

De Jager, Nathan R.; Thomsen, Meredith; Yin, Yao

2012-01-01

Our results suggest that there is a threshold along the elevation gradient of this floodplain, corresponding with flood durations lasting ~40% of the growing season. At lower elevation sites, flooding exerts primary control over forest soils and vegetation, restricting the former to silt plus clay with higher organic matter and the latter to a few highly flood tolerant species. The existence of such thresholds have implications for management of floodplain soil nutrient dynamics and plant diversity under existing hydrologic regimes, more natural hydrologic regimes and more extreme hydrologic regimes that may result from climate change.
Assessing the potential hydrological impact of the Gibe III Dam on Lake Turkana water level using multi-source satellite data

USGS Publications Warehouse

Velpuri, Naga Manohar; Senay, Gabriel B.

2012-01-01

Lake Turkana, the largest desert lake in the world, is fed by ungauged or poorly gauged river systems. To meet the demand of electricity in the East African region, Ethiopia is currently building the Gibe III hydroelectric dam on the Omo River, which supplies more than 80% of the inflows to Lake Turkana. On completion, the Gibe III dam will be the tallest dam in Africa with a height of 241 m. However, the nature of interactions and potential impacts of regulated inflows to Lake Turkana are not well understood due to its remote location and unavailability of reliable in-situ datasets. In this study, we used 12 years (1998–2009) of existing multi-source satellite and model-assimilated global weather data. We use calibrated multi-source satellite data-driven water balance model for Lake Turkana that takes into account model routed runoff, lake/reservoir evapotranspiration, direct rain on lakes/reservoirs and releases from the dam to compute lake water levels. The model evaluates the impact of Gibe III dam using three different approaches such as (a historical approach, a knowledge-based approach, and a nonparametric bootstrap resampling approach) to generate rainfall-runoff scenarios. All the approaches provided comparable and consistent results. Model results indicated that the hydrological impact of the dam on Lake Turkana would vary with the magnitude and distribution of rainfall post-dam commencement. On average, the reservoir would take up to 8–10 months, after commencement, to reach a minimum operation level of 201 m depth of water. During the dam filling period, the lake level would drop up to 2 m (95% confidence) compared to the lake level modelled without the dam. The lake level variability caused by regulated inflows after the dam commissioning were found to be within the natural variability of the lake of 4.8 m. Moreover, modelling results indicated that the hydrological impact of the Gibe III dam would depend on the initial lake level at the time of dam commencement. Areas along the Lake Turkana shoreline that are vulnerable to fluctuations in lake levels were also identified. This study demonstrates the effectiveness of using existing multi-source satellite data in a basic modeling framework to assess the potential hydrological impact of an upstream dam on a terminal downstream lake. The results obtained from this study could also be used to evaluate alternate dam-filling scenarios and assess the potential impact of the dam on Lake Turkana under different operational strategies.
Mapping (un)certainties in the sign of hydrological projections

NASA Astrophysics Data System (ADS)

Melsen, Lieke; Addor, Nans; Mizukami, Naoki; Newman, Andrew; Torfs, Paul; Clark, Martyn; Uijlenhoet, Remko; Teuling, Ryan

2017-04-01

While hydrological projections are of vital importance, particularly for water infrastructure design and food production, they are also prone to different sources of uncertainty. Using a multi-model set-up we investigated the uncertainty in hydrological projections for the period 2070-2100 associated with the parameterization of hydrological models, hydrological model structure, and General Circulation Models (GCMs) needed to force the hydrological model, for 605 basins throughout the contiguous United States. The use of such a large sample of basins gave us the opportunity to recognize spatial patterns in the results, and to attribute the uncertainty to particular hydrological processes. We investigated the sign of the projected change in mean annual runoff. The parameterization influenced the sign of change in 5 to 34% of the basins, depending on the hydrological model and GCM forcing. The hydrological model structure led to uncertainty in the sign of the change in 13 to 26% of the basins, depending on GCM forcing. This uncertainty could largely be attributed to the conceptualization of snow processes in the hydrological models. In 14% of the basins, none of the hydrological models was behavioural, which could be related to catchments with high aridity and intermittent flow behaviour. In 41 to 69% of the basins, the sign of the change was uncertain due to GCM forcing, which could be attributed to disagreement among the climate models regarding the projected change in precipitation. The results demonstrate that even the sign of change in mean annual runoff is highly uncertain in the majority of the investigated basins. If we want to use hydrological projections for water management purposes, including the design of water infrastructure, we clearly need to increase our understanding of climate and hydrological processes and their feedbacks.
Outflow Channels Influencing Martian Climate: Global Circulation Model Simulations with Emplaced Water

NASA Technical Reports Server (NTRS)

Santiago, D. L.; Colaprete, A.; Haberle, R. M.; Sloan, L. C.; Asphaug, E. I.

2005-01-01

The existence of surface water on Mars in past geologic epochs is inferred on the basis of geomorphologic interpretation of spaceflight images, and is supported by the recent Mars Odyssey identification of ice-rich soils [1]. The Mars Exploration Rovers have provided further chemical evidence for past surface hydrologic activity [2]. One issue is whether this water-rich climate ever existed in a steady state, or whether it was triggered by catastrophic events such as large impacts [3], and/ or catastrophic outburst floods, the topic of consideration here.
Impacts of climate and land-use changes on the hydrological dynamics in the upper Citarum River basin based on the J2000 hydrological model

NASA Astrophysics Data System (ADS)

Magenika Julian, Miga; Fink, Manfred; Fischer, Christian; Krause, Peter; Flügel, Wolfgang-Albert

2015-04-01

Changes of land-use and climate will most likely result in changes of the hydrological dynamics in river basins. Such changes can be noticed in the upper Citarum River basin (UCB), Java Island, Indonesia. This basin covers 1821km2 and is located in a hilly area of the backcountry of Jakarta. Between 2005 and 2009, the basin's forest cover has been reduced by 5.0%, residential areas grew around 8.2% expanding around the existing residential areas, and 3.9% of shrubland was converted into agricultural areas. From 1985 through 2009, the mean annual air temperature increased by 0.01° C/year; whereas, precipitation slightly decreased by 6.8mm/year. The process-oriented hydrological model JAMS/J2000 was adapted and implemented to assess the impact of land-use change and climate variability on the hydrological dynamics of this basin, including consideration of the temporal and spatial distributions. For this assessment, three scenarios based on realistic events were investigated; these consisted of the following (i) land-use changes in 2005 versus 2009; (ii) temperature increase from 1984 to 2009, while keeping a precipitation constant from year 1984; and (iii) variability of precipitation from 1984 to 2009, while keeping temperature constant from year 1984. The model-input conditions of land-use, precipitation, and temperature changes where applied individually, holding the other factors constant. Model simulations were conducted for the UCB. The J2000 model for the UCB was calibrated and validated using a split-sample approach. For model calibration and validation, fairly good objective functions were achieved: i.e. Nash-Sutcliffe efficiencies (E) by 0.79 and 0.76, log E of 0.89 and 0.84, coefficient of determination of 0.79 and 0.77, and a percent bias of -1.4% and -1.1%. From the model-simulation results, it was concluded that the land-use changes resulted in a slight increase in stream discharge (4.6%) and a decrease of evaporation of 3.7%. The analysis of the different runoff components indicated that, in particular, the amount of overland flow was estimated to increase 7.9%, primarily because of the significant expansion of residential areas. The individual effects of precipitation and temperature changes on the hydrological dynamics was evaluated for four five-year periods (1989-1993, 1994-1998, 1999-2003, and 2004-2009) for comparison with conditions for the first five-year period (1984-1988). The effect of a temperature increase from 1989 to 2009 on stream discharge was small, resulting in a reduction of about 1%. The increase of precipitation from 1985 to 1999 was affecting stream discharge by a small increase (2%). Through this application of the J2000, which proved to be an appropriate tool to assess environmental (land-use and climate) changes on the basin's hydrological dynamics, we could show that in the Indonesian test basin the observed change in land-use change might have a greater impact on hydrological dynamics than the impact of climate change. For future study, it is recommended to assess hydrological changes under the projected future climate and land-use conditions. Coupling effects of climate and land-use changes should be considered and assessed individually when quantifying the resultant hydrological changes estimated by the model.
Pan-Arctic river discharge: Prioritizing monitoring of future climate change hot spots

NASA Astrophysics Data System (ADS)

Bring, Arvid; Shiklomanov, Alexander; Lammers, Richard B.

2017-01-01

The Arctic freshwater cycle is changing rapidly, which will require adequate monitoring of river flows to detect, observe, and understand changes and provide adaptation information. There has, however, been little detail about where the greatest flow changes are projected, and where monitoring therefore may need to be strengthened. In this study, we used a set of recent climate model runs and an advanced macro-scale hydrological model to analyze how flows across the continental pan-Arctic are projected to change and where the climate models agree on significant changes. We also developed a method to identify where monitoring stations should be placed to observe these significant changes, and compared this set of suggested locations with the existing network of monitoring stations. Overall, our results reinforce earlier indications of large increases in flow over much of the Arctic, but we also identify some areas where projections agree on significant changes but disagree on the sign of change. For monitoring, central and eastern Siberia, Alaska, and central Canada are hot spots for the highest changes. To take advantage of existing networks, a number of stations across central Canada and western and central Siberia could form a prioritized set. Further development of model representation of high-latitude hydrology would improve confidence in the areas we identify here. Nevertheless, ongoing observation programs may consider these suggested locations in efforts to improve monitoring of the rapidly changing Arctic freshwater cycle.
Pan-Arctic River Discharge: Where Can We Improve Monitoring of Future Change?

NASA Astrophysics Data System (ADS)

Bring, A.; Shiklomanov, A. I.; Lammers, R. B.

2016-12-01

The Arctic freshwater cycle is changing rapidly, which will require adequate monitoring of river flow to detect, observe and understand changes and provide adaptation information. There has however been little detail about where the greatest flow changes are projected, and where monitoring therefore may need to be strengthened. In this study, we used a set of recent climate model runs and an advanced macro-scale hydrological model to analyze how flows across the continental pan-Arctic are projected to change, and where the climate models agree on significant changes. We also developed a method to identify where monitoring stations should be placed to observe these significant changes, and compared this set of suggested locations with the existing network of monitoring stations. Overall, our results reinforce earlier indications of large increases in flow over much of the Arctic, but we also identify some areas where projections agree on significant changes but disagree on the sign of change. For monitoring, central and eastern Siberia, Alaska and central Canada are hot spots for the highest changes. To take advantage of existing networks, a number of stations across central Canada and western and central Siberia could form a prioritized set. Further development of model representation of high-latitude hydrology would improve confidence in the areas we identify here. Nevertheless, ongoing observation programs may consider these suggested locations in efforts to improve monitoring of the rapidly changing Arctic freshwater cycle.
Modeling and Remote Sensing of Surface Water Dynamics in the Mekong River Basin

NASA Astrophysics Data System (ADS)

Pokhrel, Y. N.

2017-12-01

The Mekong river is one of the most complex river systems in the world that is shared by six nations in Southeast Asia. The river still remains relatively undammed (most existing dams are in the tributaries and are small), and its hydrology today is dominated by large natural flow variations that support the highly productive agricultural and riverine ecological systems; however, this is changing due to the alterations in land use and construction of new dams both in the tributaries the mainstream (16 mainstream and 110 tributary dams are planned to be completed by 2030). Understanding the changes in surface water dynamics is therefore crucial to provide realistic future predictions of changes in downstream floodplain and riverine ecology due to the construction of dams in the upstream. In this study, we use an integrated hydrological model and remote sensing data to examine the critical role of surface water systems in modulating the river-floodplain ecology in the lower reach of the basin, with a focus on the Tonle Sap lake. We present results on the changes in the seasonality and long-term trend in river-floodplain inundation extent over the past few decades. These results provide new insights on the changing hydrology of the Mekong and important implications for potential future hydrologic changes under accelerating human activities and climate change.
Scale effect challenges in urban hydrology highlighted with a distributed hydrological model

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire

2018-01-01

Hydrological models are extensively used in urban water management, development and evaluation of future scenarios and research activities. There is a growing interest in the development of fully distributed and grid-based models. However, some complex questions related to scale effects are not yet fully understood and still remain open issues in urban hydrology. In this paper we propose a two-step investigation framework to illustrate the extent of scale effects in urban hydrology. First, fractal tools are used to highlight the scale dependence observed within distributed data input into urban hydrological models. Then an intensive multi-scale modelling work is carried out to understand scale effects on hydrological model performance. Investigations are conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model is implemented at 17 spatial resolutions ranging from 100 to 5 m. Results clearly exhibit scale effect challenges in urban hydrology modelling. The applicability of fractal concepts highlights the scale dependence observed within distributed data. Patterns of geophysical data change when the size of the observation pixel changes. The multi-scale modelling investigation confirms scale effects on hydrological model performance. Results are analysed over three ranges of scales identified in the fractal analysis and confirmed through modelling. This work also discusses some remaining issues in urban hydrology modelling related to the availability of high-quality data at high resolutions, and model numerical instabilities as well as the computation time requirements. The main findings of this paper enable a replacement of traditional methods of model calibration by innovative methods of model resolution alteration based on the spatial data variability and scaling of flows in urban hydrology.
Measuring water and sediment discharge from a road plot with a settling basin and tipping bucket

Treesearch

Thomas A. Black; Charles H. Luce

2013-01-01

A simple empirical method quantifies water and sediment production from a forest road surface, and is well suited for calibration and validation of road sediment models. To apply this quantitative method, the hydrologic technician installs bordered plots on existing typical road segments and measures coarse sediment production in a settling tank. When a tipping bucket...
Hydrological modelling in forested systems

EPA Science Inventory

This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological p...
A comparison of two infiltration models applied to simulation of overland flow over a two-dimensional flume.

PubMed

Mallari, K J B; Kim, H; Pak, G; Aksoy, H; Yoon, J

2015-01-01

At the hillslope scale, where the rill-interrill configuration plays a significant role, infiltration is one of the major hydrologic processes affecting the generation of overland flow. As such, it is important to achieve a good understanding and accurate modelling of this process. Horton's infiltration has been widely used in many hydrologic models, though it has been occasionally found limited in handling adequately the antecedent moisture conditions (AMC) of soil. Holtan's model, conversely, is thought to be able to provide better estimation of infiltration rates as it can directly account for initial soil water content in its formulation. In this study, the Holtan model is coupled to an existing overland flow model, originally using Horton's model to account for infiltration, in an attempt to improve the prediction of runoff. For calibration and validation, experimental data from a two-dimensional flume which is incorporated with hillslope configuration have been used. Calibration and validation results showed that Holtan's model was able to improve the modelling results with better performance statistics than the Horton-coupled model. Holtan's infiltration equation, which allows accounting for AMC, provided an advantage and resulted in better runoff prediction of the model.
Validation of SWAT+ at field level and comparison with previous SWAT models in simulating hydrologic quantity

NASA Astrophysics Data System (ADS)

GAO, J.; White, M. J.; Bieger, K.; Yen, H.; Arnold, J. G.

2017-12-01

Over the past 20 years, the Soil and Water Assessment Tool (SWAT) has been adopted by many researches to assess water quantity and quality in watersheds around the world. As the demand increases in facilitating model support, maintenance, and future development, the SWAT source code and data have undergone major modifications over the past few years. To make the model more flexible in terms of interactions of spatial units and processes occurring in watersheds, a completely revised version of SWAT (SWAT+) was developed to improve SWAT's ability in water resource modelling and management. There are only several applications of SWAT+ in large watersheds, however, no study pays attention to validate the new model at field level and assess its performance. To test the basic hydrologic function of SWAT+, it was implemented in five field cases across five states in the U.S. and compared the SWAT+ created results with that from the previous models at the same fields. Additionally, an automatic calibration tool was used to test which model is easier to be calibrated well in a limited number of parameter adjustments. The goal of the study was to evaluate the performance of SWAT+ in simulating stream flow on field level at different geographical locations. The results demonstrate that SWAT+ demonstrated similar performance with previous SWAT model, but the flexibility offered by SWAT+ via the connection of different spatial objects can result in a more accurate simulation of hydrological processes in spatial, especially for watershed with artificial facilities. Autocalibration shows that SWAT+ is much easier to obtain a satisfied result compared with the previous SWAT. Although many capabilities have already been enhanced in SWAT+, there exist inaccuracies in simulation. This insufficiency will be improved with advancements in scientific knowledge on hydrologic process in specific watersheds. Currently, SWAT+ is prerelease, and any errors are being addressed.
Improving student comprehension of the interconnectivity of the hydrologic cycle with a novel 'hydrology toolbox', integrated watershed model, and companion textbook

NASA Astrophysics Data System (ADS)

Huning, L. S.; Margulis, S. A.

2013-12-01

Concepts in introductory hydrology courses are often taught in the context of process-based modeling that ultimately is integrated into a watershed model. In an effort to reduce the learning curve associated with applying hydrologic concepts to real-world applications, we developed and incorporated a 'hydrology toolbox' that complements a new, companion textbook into introductory undergraduate hydrology courses. The hydrology toolbox contains the basic building blocks (functions coded in MATLAB) for an integrated spatially-distributed watershed model that makes hydrologic topics (e.g. precipitation, snow, radiation, evaporation, unsaturated flow, infiltration, groundwater, and runoff) more user-friendly and accessible for students. The toolbox functions can be used in a modular format so that students can study individual hydrologic processes and become familiar with the hydrology toolbox. This approach allows such courses to emphasize understanding and application of hydrologic concepts rather than computer coding or programming. While topics in introductory hydrology courses are often introduced and taught independently or semi-independently, they are inherently interconnected. These toolbox functions are therefore linked together at the end of the course to reinforce a holistic understanding of how these hydrologic processes are measured, interconnected, and modeled. They are integrated into a spatially-distributed watershed model or numerical laboratory where students can explore a range of topics such as rainfall-runoff modeling, urbanization, deforestation, watershed response to changes in parameters or forcings, etc. Model output can readily be visualized and analyzed by students to understand watershed response in a real river basin or a simple 'toy' basin. These tools complement the textbook, each of which has been well received by students in multiple hydrology courses with various disciplinary backgrounds. The same governing equations that students have studied in the textbook and used in the toolbox have been encapsulated in the watershed model. Therefore, the combination of the hydrology toolbox, integrated watershed model, and textbook tends to eliminate the potential disconnect between process-based modeling and an 'off-the-shelf' watershed model.
Wetland Hydrology | Science Inventory | US EPA

EPA Pesticide Factsheets

This chapter discusses the state of the science in wetland hydrology by touching upon the major hydraulic and hydrologic processes in these complex ecosystems, their measurement/estimation techniques, and modeling methods. It starts with the definition of wetlands, their benefits and types, and explains the role and importance of hydrology on wetland functioning. The chapter continues with the description of wetland hydrologic terms and related estimation and modeling techniques. The chapter provides a quick but valuable information regarding hydraulics of surface and subsurface flow, groundwater seepage/discharge, and modeling groundwater/surface water interactions in wetlands. Because of the aggregated effects of the wetlands at larger scales and their ecosystem services, wetland hydrology at the watershed scale is also discussed in which we elaborate on the proficiencies of some of the well-known watershed models in modeling wetland hydrology. This chapter can serve as a useful reference for eco-hydrologists, wetland researchers and decision makers as well as watershed hydrology modelers. In this chapter, the importance of hydrology for wetlands and their functional role are discussed. Wetland hydrologic terms and the major components of water budget in wetlands and how they can be estimated/modeled are also presented. Although this chapter does not provide a comprehensive coverage of wetland hydrology, it provides a quick understanding of the basic co

From Process Models to Decision Making: The Use of Data Mining Techniques for Developing Effect Decision Support Systems

NASA Astrophysics Data System (ADS)

Conrads, P. A.; Roehl, E. A.

2010-12-01

Natural-resource managers face the difficult problem of controlling the interactions between hydrologic and man-made systems in ways that preserve resources while optimally meeting the needs of disparate stakeholders. Finding success depends on obtaining and employing detailed scientific knowledge about the cause-effect relations that govern the physics of these hydrologic systems. This knowledge is most credible when derived from large field-based datasets that encompass the wide range of variability in the parameters of interest. The means of converting data into knowledge of the hydrologic system often involves developing computer models that predict the consequences of alternative management practices to guide resource managers towards the best path forward. Complex hydrologic systems are typically modeled using computer programs that implement traditional, generalized, physical equations, which are calibrated to match the field data as closely as possible. This type of model commonly is limited in terms of demonstrable predictive accuracy, development time, and cost. The science of data mining presents a powerful complement to physics-based models. Data mining is a relatively new science that assists in converting large databases into knowledge and is uniquely able to leverage the real-time, multivariate data now being collected for hydrologic systems. In side-by-side comparisons with state-of-the-art physics-based hydrologic models, the authors have found data-mining solutions have been substantially more accurate, less time consuming to develop, and embeddable into spreadsheets and sophisticated decision support systems (DSS), making them easy to use by regulators and stakeholders. Three data-mining applications will be presented that demonstrate how data-mining techniques can be applied to existing environmental databases to address regional concerns of long-term consequences. In each case, data were transformed into information, and ultimately, into knowledge. In each case, DSSs were developed that facilitated the use of simulation models and analysis of model output to a broad range of end users with various technical abilities. When compared to other modeling projects of comparable scope and complexity, these DSSs were able to pass through needed technical reviews much more quickly. Unlike programs such as finite-element flow models, DSSs are by design open systems that are easy to use and readily disseminated directly to decision makers. The DSSs provide direct coupling of predictive models with the real-time databases that drive them, graphical user interfaces for point-and-click program control, and streaming displays of numerical and graphical results so that users can monitor the progress of long-term simulations. Customizations for specific problems include numerical optimization loops that invert predictive models; integrations with a three-dimensional finite-element flow model, GIS packages, and a plant ecology model; and color contouring of simulation output data.
Uncertainty Propagation of Non-Parametric-Derived Precipitation Estimates into Multi-Hydrologic Model Simulations

NASA Astrophysics Data System (ADS)

Bhuiyan, M. A. E.; Nikolopoulos, E. I.; Anagnostou, E. N.

2017-12-01

Quantifying the uncertainty of global precipitation datasets is beneficial when using these precipitation products in hydrological applications, because precipitation uncertainty propagation through hydrologic modeling can significantly affect the accuracy of the simulated hydrologic variables. In this research the Iberian Peninsula has been used as the study area with a study period spanning eleven years (2000-2010). This study evaluates the performance of multiple hydrologic models forced with combined global rainfall estimates derived based on a Quantile Regression Forests (QRF) technique. In QRF technique three satellite precipitation products (CMORPH, PERSIANN, and 3B42 (V7)); an atmospheric reanalysis precipitation and air temperature dataset; satellite-derived near-surface daily soil moisture data; and a terrain elevation dataset are being utilized in this study. A high-resolution, ground-based observations driven precipitation dataset (named SAFRAN) available at 5 km/1 h resolution is used as reference. Through the QRF blending framework the stochastic error model produces error-adjusted ensemble precipitation realizations, which are used to force four global hydrological models (JULES (Joint UK Land Environment Simulator), WaterGAP3 (Water-Global Assessment and Prognosis), ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) and SURFEX (Stands for Surface Externalisée) ) to simulate three hydrologic variables (surface runoff, subsurface runoff and evapotranspiration). The models are forced with the reference precipitation to generate reference-based hydrologic simulations. This study presents a comparative analysis of multiple hydrologic model simulations for different hydrologic variables and the impact of the blending algorithm on the simulated hydrologic variables. Results show how precipitation uncertainty propagates through the different hydrologic model structures to manifest in reduction of error in hydrologic variables.
HydroViz: A web-based hydrologic observatory for enhancing hydrology and earth-science education

NASA Astrophysics Data System (ADS)

Habib, E. H.; Ma, Y.; Williams, D.

2010-12-01

The main goal of this study is to develop a virtual hydrologic observatory (HydroViz) that integrates hydrologic field observations with numerical simulations by taking advantage of advances in hydrologic field & remote sensing data, computer modeling, scientific visualization, and web resources and internet accessibility. The HydroViz system is a web-based teaching tool that can run on any web browsers. It leverages the strength of Google Earth to provide authentic and hands-on activities to improve learning. Evaluation of the HydroViz was performed in three engineering courses (a senior level course and two Introductory courses at two different universities). Evaluation results indicate that HydroViz provides an improvement over existing engineering hydrology curriculum. HydroViz was effective in facilitating students’ learning and understanding of hydrologic concepts & increasing related skills. HydroViz was much more effective for students in engineering hydrology classes rather than at the freshmen introduction to civil engineering class. We found that HydroViz has great potential for freshmen audience. Even though HydroViz was challenging to some freshmen, most of them still learned the key concepts and the tool increased the enthusiasm for half of the freshmen. The evaluation provided suggestions to create a simplified version of HydroViz for freshmen-level courses students. It identified concepts and tasks that might be too challenging or irrelevant to the freshmen and areas where we could provide more guidance in the tool. After the first round of evaluation, the development team has made significant improvements to HydroViz, which would further improve its effectiveness for next round of class applications which is planned for the Fall of 2010 to take place in 5 classes at 4 different institutions.
Impact of a statistical bias correction on the projected simulated hydrological changes obtained from three GCMs and two hydrology models

NASA Astrophysics Data System (ADS)

Hagemann, Stefan; Chen, Cui; Haerter, Jan O.; Gerten, Dieter; Heinke, Jens; Piani, Claudio

2010-05-01

Future climate model scenarios depend crucially on their adequate representation of the hydrological cycle. Within the European project "Water and Global Change" (WATCH) special care is taken to couple state-of-the-art climate model output to a suite of hydrological models. This coupling is expected to lead to a better assessment of changes in the hydrological cycle. However, due to the systematic model errors of climate models, their output is often not directly applicable as input for hydrological models. Thus, the methodology of a statistical bias correction has been developed, which can be used for correcting climate model output to produce internally consistent fields that have the same statistical intensity distribution as the observations. As observations, global re-analysed daily data of precipitation and temperature are used that are obtained in the WATCH project. We will apply the bias correction to global climate model data of precipitation and temperature from the GCMs ECHAM5/MPIOM, CNRM-CM3 and LMDZ-4, and intercompare the bias corrected data to the original GCM data and the observations. Then, the orginal and the bias corrected GCM data will be used to force two global hydrology models: (1) the hydrological model of the Max Planck Institute for Meteorology (MPI-HM) consisting of the Simplified Land surface (SL) scheme and the Hydrological Discharge (HD) model, and (2) the dynamic vegetation model LPJmL operated by the Potsdam Institute for Climate Impact Research. The impact of the bias correction on the projected simulated hydrological changes will be analysed, and the resulting behaviour of the two hydrology models will be compared.
Continental scale data assimilation of discharge and its effect on flow predictions

NASA Astrophysics Data System (ADS)

Weerts, Albrecht; Schellekens, Jaap; van Dijk, Albert

2017-04-01

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist (Emmerton et al., 2016). Current global flood forecasting system heavily rely on forecast forcing (precipitation, temperature, reference potential evaporation) to derive initial state estimates of the hydrological model for the next forecast (e.g. by glueing the first day of subsequent forecast as proxy for the historical observed forcing). It is clear that this approach is not perfect and that data assimilation can help to overcome some of the weaknesses of this approach. So far most hydrologic da studies have focused mostly on catchment scale. Here we conduct a da experiment by assimilating multiple streamflow observations across the contiguous united states (CONUS) and Europe into a global hydrological model (W3RA) and run with and without localization method using OpenDA in the global flood forecasting information system (GLOFFIS). It is shown that assimilation of streamflow holds considerable potential for improving global scale flood forecasting (improving NSE scores from 0 to 0.7 and beyond). Weakness in the model (e.g. structural problems and missing processes) and forcing that influence the performance will be highlighted.
Continental scale data assimilation of discharge and its effect on flow predictions across the contiguous US (CONUS)

NASA Astrophysics Data System (ADS)

Weerts, A.; Schellekens, J.; van Dijk, A.; Molenaar, R.

2016-12-01

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist (Emmerton et al., 2016). Current global flood forecasting system heavily rely on forecast forcing (precipitation, temperature, reference potential evaporation) to derive initial state estimates of the hydrological model for the next forecast (e.g. by glueing the first day of subsequent forecast as proxy for the historical observed forcing). It is clear that this approach is not perfect and that data assimilation can help to overcome some of the weaknesses of this approach. So far most hydrologic da studies have focused mostly on catchment scale. Here we conduct a da experiment by assimilating multiple streamflow observations across the contiguous united states (CONUS) into a global hydrological model (W3RA) and run with and without localization method using OpenDA in the global flood forecasting information system (GLOFFIS). It is shown that assimilation of streamflow holds considerable potential for improving global scale flood forecasting (improving NSE scores from 0 to 0.7 and beyond). Weakness in the model (e.g. structural problems and missing processes) and forcing that influence the performance will be highlighted.
Temporal variations in the potential hydrological performance of extensive green roof systems

NASA Astrophysics Data System (ADS)

De-Ville, Simon; Menon, Manoj; Stovin, Virginia

2018-03-01

Existing literature provides contradictory information about variation in potential green roof hydrological performance over time. This study has evaluated a long-term hydrological monitoring record from a series of extensive green roof test beds to identify long-term evolutions and sub-annual (seasonal) variations in potential hydrological performance. Monitoring of nine differently-configured extensive green roof test beds took place over a period of 6 years in Sheffield, UK. Long-term evolutions and sub-annual trends in maximum potential retention performance were identified through physical monitoring of substrate field capacity over time. An independent evaluation of temporal variations in detention performance was undertaken through the fitting of reservoir-routing model parameters. Aggregation of the resulting retention and detention variations permitted the prediction of extensive green roof hydrological performance in response to a 1-in-30-year 1-h summer design storm for Sheffield, UK, which facilitated the comparison of multi and sub-annual hydrological performance variations. Sub-annual (seasonal) variation was found to be significantly greater than long-term evolution. Potential retention performance increased by up to 12% after 5-years, whilst the maximum sub-annual variation in potential retention was 27%. For vegetated roof configurations, a 4% long-term improvement was observed for detention performance, compared to a maximum 63% sub-annual variation. Consistent long-term reductions in detention performance were observed in unvegetated roof configurations, with a non-standard expanded-clay substrate experiencing a 45% reduction in peak attenuation over 5-years. Conventional roof configurations exhibit stable long-term hydrological performance, but are nonetheless subject to sub-annual variation.
HEPEX - achievements and challenges!

NASA Astrophysics Data System (ADS)

Pappenberger, Florian; Ramos, Maria-Helena; Thielen, Jutta; Wood, Andy; Wang, Qj; Duan, Qingyun; Collischonn, Walter; Verkade, Jan; Voisin, Nathalie; Wetterhall, Fredrik; Vuillaume, Jean-Francois Emmanuel; Lucatero Villasenor, Diana; Cloke, Hannah L.; Schaake, John; van Andel, Schalk-Jan

2014-05-01

HEPEX is an international initiative bringing together hydrologists, meteorologists, researchers and end-users to develop advanced probabilistic hydrological forecast techniques for improved flood, drought and water management. HEPEX was launched in 2004 as an independent, cooperative international scientific activity. During the first meeting, the overarching goal was defined as: "to develop and test procedures to produce reliable hydrological ensemble forecasts, and to demonstrate their utility in decision making related to the water, environmental and emergency management sectors." The applications of hydrological ensemble predictions span across large spatio-temporal scales, ranging from short-term and localized predictions to global climate change and regional modeling. Within the HEPEX community, information is shared through its blog (www.hepex.org), meetings, testbeds and intercompaison experiments, as well as project reportings. Key questions of HEPEX are: * What adaptations are required for meteorological ensemble systems to be coupled with hydrological ensemble systems? * How should the existing hydrological ensemble prediction systems be modified to account for all sources of uncertainty within a forecast? * What is the best way for the user community to take advantage of ensemble forecasts and to make better decisions based on them? This year HEPEX celebrates its 10th year anniversary and this poster will present a review of the main operational and research achievements and challenges prepared by Hepex contributors on data assimilation, post-processing of hydrologic predictions, forecast verification, communication and use of probabilistic forecasts in decision-making. Additionally, we will present the most recent activities implemented by Hepex and illustrate how everyone can join the community and participate to the development of new approaches in hydrologic ensemble prediction.
[Advance in researches on the effect of forest on hydrological process].

PubMed

Zhang, Zhiqiang; Yu, Xinxiao; Zhao, Yutao; Qin, Yongsheng

2003-01-01

According to the effects of forest on hydrological process, forest hydrology can be divided into three related aspects: experimental research on the effects of forest changing on hydrological process quantity and water quality; mechanism study on the effects of forest changing on hydrological cycle, and establishing and exploitating physical-based distributed forest hydrological model for resource management and engineering construction. Orientation experiment research can not only support the first-hand data for forest hydrological model, but also make clear the precipitation-runoff mechanisms. Research on runoff mechanisms can be valuable for the exploitation and improvement of physical based hydrological models. Moreover, the model can also improve the experimental and runoff mechanism researches. A review of above three aspects are summarized in this paper.
Watershed-Scale Heterogeneity of the Biophysical Controls on Soil Respiration

NASA Astrophysics Data System (ADS)

Riveros, D. A.; Pacific, V. J.; McGlynn, B. L.; Welsch, D. L.; Epstein, H. E.; Muth, D. J.; Marshall, L.; Wraith, J.

2006-12-01

Large gaps exist in our understanding of the variability of soil respiration response to changing hydrologic conditions across spatial and temporal scales. Determining the linkages between the hydrologic cycle and the biophysical controls of soil respiration from the local point, to the plot, to the watershed scale is critical to understanding the dynamics of net ecosystem CO2 exchange (NEE). To study the biophysical controls of soil respiration, we measured soil CO2 concentration, soil CO2 flux, dissolved CO2 in stream water, soil moisture, soil temperature, groundwater dynamics, and precipitation at 20-minute intervals throughout the growing season at 4 sites and at weekly intervals at 62 sites covering the range of topographic position, slope, aspect, land cover, and upslope accumulated area conditions in a 555-ha subalpine watershed in central Montana. Our goal was to quantify watershed-scale heterogeneity in soil CO2 concentrations and surface efflux and gain understanding of the biophysical controls on soil respiration. We seek to improve our ability to evaluate and predict soil respiration responses to a dynamic hydrologic cycle across multiple temporal and spatial scales. We found that time lags between biophysical controls and soil respiration can occur from hourly to daily scales. The sensitivity of soil respiration to changes in environmental conditions is controlled by the antecedent soil moisture and by topographic position. At the watershed scale, significant differences in soil respiration exist between upland (dry) and lowland (wet) sites. However, differences in the magnitude and timing of soil respiration also exist within upland settings due to heterogeneity in soil temperature, soil moisture, and soil organic matter. Finally, we used a process-based model to simulate respiration at different times of the year across spatial locations. Our simulations highlight the importance of autotrophic and heterotrophic respiration (production) over diffusivity and soil physical properties (transport). Our work begins to address the disconnect between point, footprint, watershed scale estimates of ecosystem respiration and the role of a dynamic hydrologic cycle.
Remotely Measuring Trash Fluxes in the Flood Canals of Megacities with Time Lapse Cameras and Computer Vision Algorithms - a Case Study from Jakarta, Indonesia.

NASA Astrophysics Data System (ADS)

Sedlar, F.; Turpin, E.; Kerkez, B.

2014-12-01

As megacities around the world continue to develop at breakneck speeds, future development, investment, and social wellbeing are threatened by a number of environmental and social factors. Chief among these is frequent, persistent, and unpredictable urban flooding. Jakarta, Indonesia with a population of 28 million, is a prime example of a city plagued by such flooding. Yet although Jakarta has ample hydraulic infrastructure already in place with more being constructed, the increasingly severity of the flooding it experiences is not from a lack of hydraulic infrastructure but rather a failure of existing infrastructure. As was demonstrated during the most recent floods in Jakarta, the infrastructure failure is often the result of excessive amounts of trash in the flood canals. This trash clogs pumps and reduces the overall system capacity. Despite this critical weakness of flood control in Jakarta, no data exists on the overall amount of trash in the flood canals, much less on how it varies temporally and spatially. The recent availability of low cost photography provides a means to obtain such data. Time lapse photography postprocessed with computer vision algorithms yields a low cost, remote, and automatic solution to measuring the trash fluxes. When combined with the measurement of key hydrological parameters, a thorough understanding of the relationship between trash fluxes and the hydrology of massive urban areas becomes possible. This work examines algorithm development, quantifying trash parameters, and hydrological measurements followed by data assimilation into existing hydraulic and hydrological models of Jakarta. The insights afforded from such an approach allows for more efficient operating of hydraulic infrastructure, knowledge of when and where critical levels of trash originate from, and the opportunity for community outreach - which is ultimately needed to reduce the trash in the flood canals of Jakarta and megacities around the world.
Coupling of the simultaneous heat and water model with a distributed hydrological model and evaluation of the combined model in a cold region watershed

USDA-ARS?s Scientific Manuscript database

To represent the effects of frozen soil on hydrology in cold regions, a new physically based distributed hydrological model has been developed by coupling the simultaneous heat and water model (SHAW) with the geomorphology based distributed hydrological model (GBHM), under the framework of the water...
A senstitivity study of the ground hydrologic model using data generated by an atmospheric general circulation model. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Sun, S. F.

1985-01-01

The Ground Hydrologic Model (GHM) developed for use in an atmospheric general circulation model (GCM) has been refined. A series of sensitivity studies of the new version of the GHM were conducted for the purpose of understanding the role played by various physical parameters in the GHM. The following refinements have been made: (1) the GHM is coupled directly with the planetary boundary layer (PBL); (2) a bulk vegetation layer is added with a more realistic large-scale parameterization; and (3) the infiltration rate is modified. This version GHM has been tested using input data derived from a GCM simulation run for eight North America regions for 45 days. The results are compared with those of the resident GHM in the GCM. The daily average of grid surface temperatures from both models agree reasonably well in phase and magnitude. However, large difference exists in one or two regions on some days. The daily average evapotranspiration is in general 10 to 30% less than the corresponding value given by the resident GHM.
Documentation of the dynamic parameter, water-use, stream and lake flow routing, and two summary output modules and updates to surface-depression storage simulation and initial conditions specification options with the Precipitation-Runoff Modeling System (PRMS)

USGS Publications Warehouse

Regan, R. Steve; LaFontaine, Jacob H.

2017-10-05

This report documents seven enhancements to the U.S. Geological Survey (USGS) Precipitation-Runoff Modeling System (PRMS) hydrologic simulation code: two time-series input options, two new output options, and three updates of existing capabilities. The enhancements are (1) new dynamic parameter module, (2) new water-use module, (3) new Hydrologic Response Unit (HRU) summary output module, (4) new basin variables summary output module, (5) new stream and lake flow routing module, (6) update to surface-depression storage and flow simulation, and (7) update to the initial-conditions specification. This report relies heavily upon U.S. Geological Survey Techniques and Methods, book 6, chapter B7, which documents PRMS version 4 (PRMS-IV). A brief description of PRMS is included in this report.
Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain

NASA Astrophysics Data System (ADS)

Prudhomme, C.; Haxton, T.; Crooks, S.; Jackson, C.; Barkwith, A.; Williamson, J.; Kelvin, J.; Mackay, J.; Wang, L.; Young, A.; Watts, G.

2012-12-01

The dataset Future Flows Hydrology was developed as part of the project "Future Flows and Groundwater Levels" to provide a consistent set of transient daily river flow and monthly groundwater levels projections across England, Wales and Scotland to enable the investigation of the role of climate variability on river flow and groundwater levels nationally and how this may change in the future. Future Flows Hydrology is derived from Future Flows Climate, a national ensemble projection derived from the Hadley Centre's ensemble projection HadRM3-PPE to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications. Three hydrological models and one groundwater level model were used to derive Future Flows Hydrology, with 30 river sites simulated by two hydrological models to enable assessment of hydrological modelling uncertainty in studying the impact of climate change on the hydrology. Future Flows Hydrology contains an 11-member ensemble of transient projections from January 1951 to December 2098, each associated with a single realisation from a different variant of HadRM3 and a single hydrological model. Daily river flows are provided for 281 river catchments and monthly groundwater levels at 24 boreholes as .csv files containing all 11 ensemble members. When separate simulations are done with two hydrological models, two separate .csv files are provided. Because of potential biases in the climate-hydrology modelling chain, catchment fact sheets are associated with each ensemble. These contain information on the uncertainty associated with the hydrological modelling when driven using observed climate and Future Flows Climate for a period representative of the reference time slice 1961-1990 as described by key hydrological statistics. Graphs of projected changes for selected hydrological indicators are also provided for the 2050s time slice. Limitations associated with the dataset are provided, along with practical recommendation of use. Future Flows Hydrology is freely available for non-commercial use under certain licensing conditions. For each study site, catchment averages of daily precipitation and monthly potential evapotranspiration, used to drive the hydrological models, are made available, so that hydrological modelling uncertainty under climate change conditions can be explored further. doi:10.5285/f3723162-4fed-4d9d-92c6-dd17412fa37b.
Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain

NASA Astrophysics Data System (ADS)

Prudhomme, C.; Haxton, T.; Crooks, S.; Jackson, C.; Barkwith, A.; Williamson, J.; Kelvin, J.; Mackay, J.; Wang, L.; Young, A.; Watts, G.

2013-03-01

The dataset Future Flows Hydrology was developed as part of the project "Future Flows and Groundwater Levels'' to provide a consistent set of transient daily river flow and monthly groundwater level projections across England, Wales and Scotland to enable the investigation of the role of climate variability on river flow and groundwater levels nationally and how this may change in the future. Future Flows Hydrology is derived from Future Flows Climate, a national ensemble projection derived from the Hadley Centre's ensemble projection HadRM3-PPE to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications. Three hydrological models and one groundwater level model were used to derive Future Flows Hydrology, with 30 river sites simulated by two hydrological models to enable assessment of hydrological modelling uncertainty in studying the impact of climate change on the hydrology. Future Flows Hydrology contains an 11-member ensemble of transient projections from January 1951 to December 2098, each associated with a single realisation from a different variant of HadRM3 and a single hydrological model. Daily river flows are provided for 281 river catchments and monthly groundwater levels at 24 boreholes as .csv files containing all 11 ensemble members. When separate simulations are done with two hydrological models, two separate .csv files are provided. Because of potential biases in the climate-hydrology modelling chain, catchment fact sheets are associated with each ensemble. These contain information on the uncertainty associated with the hydrological modelling when driven using observed climate and Future Flows Climate for a period representative of the reference time slice 1961-1990 as described by key hydrological statistics. Graphs of projected changes for selected hydrological indicators are also provided for the 2050s time slice. Limitations associated with the dataset are provided, along with practical recommendation of use. Future Flows Hydrology is freely available for non-commercial use under certain licensing conditions. For each study site, catchment averages of daily precipitation and monthly potential evapotranspiration, used to drive the hydrological models, are made available, so that hydrological modelling uncertainty under climate change conditions can be explored further. doi:10.5285/f3723162-4fed-4d9d-92c6-dd17412fa37b
On the importance of appropriate precipitation gauge catch correction for hydrological modelling at mid to high latitudes

NASA Astrophysics Data System (ADS)

Stisen, S.; Højberg, A. L.; Troldborg, L.; Refsgaard, J. C.; Christensen, B. S. B.; Olsen, M.; Henriksen, H. J.

2012-11-01

Precipitation gauge catch correction is often given very little attention in hydrological modelling compared to model parameter calibration. This is critical because significant precipitation biases often make the calibration exercise pointless, especially when supposedly physically-based models are in play. This study addresses the general importance of appropriate precipitation catch correction through a detailed modelling exercise. An existing precipitation gauge catch correction method addressing solid and liquid precipitation is applied, both as national mean monthly correction factors based on a historic 30 yr record and as gridded daily correction factors based on local daily observations of wind speed and temperature. The two methods, named the historic mean monthly (HMM) and the time-space variable (TSV) correction, resulted in different winter precipitation rates for the period 1990-2010. The resulting precipitation datasets were evaluated through the comprehensive Danish National Water Resources model (DK-Model), revealing major differences in both model performance and optimised model parameter sets. Simulated stream discharge is improved significantly when introducing the TSV correction, whereas the simulated hydraulic heads and multi-annual water balances performed similarly due to recalibration adjusting model parameters to compensate for input biases. The resulting optimised model parameters are much more physically plausible for the model based on the TSV correction of precipitation. A proxy-basin test where calibrated DK-Model parameters were transferred to another region without site specific calibration showed better performance for parameter values based on the TSV correction. Similarly, the performances of the TSV correction method were superior when considering two single years with a much dryer and a much wetter winter, respectively, as compared to the winters in the calibration period (differential split-sample tests). We conclude that TSV precipitation correction should be carried out for studies requiring a sound dynamic description of hydrological processes, and it is of particular importance when using hydrological models to make predictions for future climates when the snow/rain composition will differ from the past climate. This conclusion is expected to be applicable for mid to high latitudes, especially in coastal climates where winter precipitation types (solid/liquid) fluctuate significantly, causing climatological mean correction factors to be inadequate.
Multi-model ensemble hydrological simulation using a BP Neural Network for the upper Yalongjiang River Basin, China

NASA Astrophysics Data System (ADS)

Li, Zhanjie; Yu, Jingshan; Xu, Xinyi; Sun, Wenchao; Pang, Bo; Yue, Jiajia

2018-06-01

Hydrological models are important and effective tools for detecting complex hydrological processes. Different models have different strengths when capturing the various aspects of hydrological processes. Relying on a single model usually leads to simulation uncertainties. Ensemble approaches, based on multi-model hydrological simulations, can improve application performance over single models. In this study, the upper Yalongjiang River Basin was selected for a case study. Three commonly used hydrological models (SWAT, VIC, and BTOPMC) were selected and used for independent simulations with the same input and initial values. Then, the BP neural network method was employed to combine the results from the three models. The results show that the accuracy of BP ensemble simulation is better than that of the single models.
Preliminary testing of flow-ecology hypotheses developed for the GCP LCC region

USGS Publications Warehouse

Brewer, Shannon K.; Davis, Mary

2014-01-01

The Ecological Limits of Hydrological Alteration (ELOHA) framework calls for the development of flow-ecology hypotheses to support protection of the flow regime from ecologically harmful alteration due to human activities. As part of a larger instream flow project for the Gulf Coast Prairie Landscape Conservation Cooperative (GCP LCC), regional flow-ecology hypotheses were developed for fish, mussels, birds, and riparian vegetation (Davis and Brewer 20141). The objective of this study was to assess the usefulness of existing ecological and hydrological data to test these hypotheses or others that may be developed in the future. Several databases related to biological collections and hydrologic data from Oklahoma, Texas, and Louisiana were compiled. State fish-community data from Oklahoma and Louisiana were summarized and paired with existing USGS gage data having at least a 40-year period of record that could be separated into reference and current conditions for comparison. The objective of this study was not to conduct exhaustive analyses of these data, the hypotheses, or analyses interpretation, but rather to use these data to determine if existing data were adequate to statistically test the regional flow-ecology hypotheses. The regional flow-ecology hypotheses were developed for the GCP LCC by a committee chaired by Shannon Brewer and Mary Davis (Davis and Brewer 2014). Existing data were useful for informing the hypotheses and suggest support for some hypotheses, but also highlight the need for additional testing and development as some results contradicted hypotheses. Results presented here suggest existing data are adequate to support some flow-ecology hypotheses; however, lack of sampling effort reported with the fish collections and the need for ecoregion-specific analyses suggest more data would be beneficial to analyses in some ecoregions. Additional fish sampling data from Texas and Louisiana will be available for future analyses and may ameliorate some of the data concerns and improve hypothesis interpretation. If the regional hydrologic model currently under development by the U.S. Geological Survey for the South-Central Climate Science Center is improved to produce daily hydrographs, it will enable use of fish data at ungaged locations. In future efforts, exhaustive analyses using these data, in addition to the development of more complex multivariate hypotheses, would be beneficial to understanding data gaps, particularly as relevant to species of conservation concern.
Techniques for assessing water resource potentials in the developing countries: with emphasis on streamflow, erosion and sediment transport, water movement in unsaturated soils, ground water, and remote sensing in hydrologic applications

USGS Publications Warehouse

Taylor, George C.

1971-01-01

Hydrologic instrumentation and methodology for assessing water-resource potentials have originated largely in the developed countries of the temperature zone. The developing countries lie largely in the tropic zone, which contains the full gamut of the earth's climatic environments, including most of those of the temperate zone. For this reason, most hydrologic techniques have world-wide applicability. Techniques for assessing water-resource potentials for the high priority goals of economic growth are well established in the developing countries--but much more are well established in the developing countries--but much more so in some than in other. Conventional techniques for measurement and evaluation of basic hydrologic parameters are now well-understood in the developing countries and are generally adequate for their current needs and those of the immediate future. Institutional and economic constraints, however, inhibit growth of sustained programs of hydrologic data collection and application of the data to problems in engineering technology. Computer-based technology, including processing of hydrologic data and mathematical modelling of hydrologic parameters i also well-begun in many developing countries and has much wider potential application. In some developing counties, however, there is a tendency to look on the computer as a panacea for deficiencies in basic hydrologic data collection programs. This fallacy must be discouraged, as the computer is a tool and not a "magic box." There is no real substitute for sound programs of basic data collection. Nuclear and isotopic techniques are being used increasingly in the developed countries in the measurement and evaluation of virtually all hydrologic parameter in which conventional techniques have been used traditionally. Even in the developed countries, however, many hydrologists are not using nuclear techniques, simply because they lack knowledge of the principles involved and of the potential benefits. Nuclear methodology in hydrologic applications is generally more complex than the conventional and hence requires a high level of technical expertise for effective use. Application of nuclear techniques to hydrologic problems in the developing countries is likely to be marginal for some years to come, owing to the higher costs involved and expertise required. Nuclear techniques, however, would seem to have particular promise in studies of water movement in unsaturated soils and of erosion and sedimentation where conventional techniques are inadequate, inefficient and in some cases costly. Remote sensing offers great promise for synoptic evaluations of water resources and hydrologic processes, including the transient phenomena of the hydrologic cycle. Remote sensing is not, however, a panacea for deficiencies in hydrologic data programs in the developing countries. Rather it is a means for extending and augmenting on-the-ground observations ans surveys (ground truth) to evaluated water resources and hydrologic processes on a regionall or even continental scale. With respect to economic growth goals in developing countries, there are few identifiable gaps in existing hydrologic instrumentation and methodology insofar as appraisal, development and management of available water resources are concerned. What is needed is acceleration of institutional development and professional motivation toward more effective use of existing and proven methodology. Moreover, much sophisticated methodology can be applied effectively in the developing countries only when adequate levels of indigenous scientific skills have been reached and supportive institutional frameworks are evolved to viability.

Flood design recipes vs. reality: can predictions for ungauged basins be trusted?

NASA Astrophysics Data System (ADS)

Efstratiadis, A.; Koussis, A. D.; Koutsoyiannis, D.; Mamassis, N.

2014-06-01

Despite the great scientific and technological advances in flood hydrology, everyday engineering practices still follow simplistic approaches that are easy to formally implement in ungauged areas. In general, these "recipes" have been developed many decades ago, based on field data from typically few experimental catchments. However, many of them have been neither updated nor validated across all hydroclimatic and geomorphological conditions. This has an obvious impact on the quality and reliability of hydrological studies, and, consequently, on the safety and cost of the related flood protection works. Preliminary results, based on historical flood data from Cyprus and Greece, indicate that a substantial revision of many aspects of flood engineering procedures is required, including the regionalization formulas as well as the modelling concepts themselves. In order to provide a consistent design framework and to ensure realistic predictions of the flood risk (a key issue of the 2007/60/EU Directive) in ungauged basins, it is necessary to rethink the current engineering practices. In this vein, the collection of reliable hydrological data would be essential for re-evaluating the existing "recipes", taking into account local peculiarities, and for updating the modelling methodologies as needed.
Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS)

USGS Publications Warehouse

Regan, R. Steven; Markstrom, Steven L.; Hay, Lauren E.; Viger, Roland J.; Norton, Parker A.; Driscoll, Jessica M.; LaFontaine, Jacob H.

2018-01-08

This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.
ENKI - An Open Source environmental modelling platfom

NASA Astrophysics Data System (ADS)

Kolberg, S.; Bruland, O.

2012-04-01

The ENKI software framework for implementing spatio-temporal models is now released under the LGPL license. Originally developed for evaluation and comparison of distributed hydrological model compositions, ENKI can be used for simulating any time-evolving process over a spatial domain. The core approach is to connect a set of user specified subroutines into a complete simulation model, and provide all administrative services needed to calibrate and run that model. This includes functionality for geographical region setup, all file I/O, calibration and uncertainty estimation etc. The approach makes it easy for students, researchers and other model developers to implement, exchange, and test single routines and various model compositions in a fixed framework. The open-source license and modular design of ENKI will also facilitate rapid dissemination of new methods to institutions engaged in operational water resource management. ENKI uses a plug-in structure to invoke separately compiled subroutines, separately built as dynamic-link libraries (dlls). The source code of an ENKI routine is highly compact, with a narrow framework-routine interface allowing the main program to recognise the number, types, and names of the routine's variables. The framework then exposes these variables to the user within the proper context, ensuring that distributed maps coincide spatially, time series exist for input variables, states are initialised, GIS data sets exist for static map data, manually or automatically calibrated values for parameters etc. By using function calls and memory data structures to invoke routines and facilitate information flow, ENKI provides good performance. For a typical distributed hydrological model setup in a spatial domain of 25000 grid cells, 3-4 time steps simulated per second should be expected. Future adaptation to parallel processing may further increase this speed. New modifications to ENKI include a full separation of API and user interface, making it possible to run ENKI from GIS programs and other software environments. ENKI currently compiles under Windows and Visual Studio only, but ambitions exist to remove the platform and compiler dependencies.
Predicting hydrological and erosional risks in fire-affected watersheds: recent advances and research gaps

NASA Astrophysics Data System (ADS)

Nunes, João Pedro; Keizer, Jan Jacob

2017-04-01

Models can be invaluable tools to assess and manage the impacts of forest fires on hydrological and erosion processes. Immediately after fires, models can be used to identify priority areas for post-fire interventions or assess the risks of flooding and downstream contamination. In the long term, models can be used to evaluate the long-term implications of a fire regime for soil protection, surface water quality and potential management risks, or determine how changes to fire regimes, caused e.g. by climate change, can impact soil and water quality. However, several challenges make post-fire modelling particularly difficult: • Fires change vegetation cover and properties, such as by changing soil water repellency or by adding an ash layer over the soil; these processes, however are not described in currently used models, so that existing models need to be modified and tested. • Vegetation and soils recover with time since fire, changing important model parameters, so that the recovery processes themselves also need to be simulated, including the role of post-fire interventions. • During the window of vegetation and soil disturbance, particular weather conditions, such as the occurrence of severe droughts or extreme rainfall events, can have a large impact on the amount of runoff and erosion produced in burnt areas, so that models that smooth out these peak responses and rather simulate "long-term" average processes are less useful. • While existing models can simulate reasonable well slope-scale runoff generation and associated sediment losses and their catchment-scale routing, few models can accommodate the role of the ash layer or its transport by overland flow, in spite of its importance for soil fertility losses and downstream contamination. This presentation will provide an overview of the importance of post-fire hydrological and erosion modelling as well as of the challenges it faces and of recent efforts made to overcome these challenges. It will illustrate these challenges with two examples: probabilistic approaches to simulate the impact of different vegetation regrowth and post-fire climate combinations on runoff and erosion; and model developments for post-fire soil water repellency with different levels of complexity. It will also present an inventory of the current state-of-the-art and propose future research directions, both on post-fire models themselves and on their integration with other models in large-scale water resource assessment management.
Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

NASA Astrophysics Data System (ADS)

Mortensen, Eric; Wu, Shu; Notaro, Michael; Vavrus, Stephen; Montgomery, Rob; De Piérola, José; Sánchez, Carlos; Block, Paul

2018-01-01

Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semiarid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal meteorological drought. Meteorological droughts in this region are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region's hydrologic cycle. An extensive season-ahead precipitation prediction model is developed to help bolster the existing capacity of stakeholders to plan for and mitigate deleterious impacts of drought. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to 11 potential predictors to produce an ensemble forecast of regional January-March precipitation totals. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. The information provided by the developed model and ancillary modeling efforts, such as extending the lead time of and spatially disaggregating precipitation predictions to the local level as well as forecasting the number of wet-dry days per rainy season, may further assist regional stakeholders and policymakers in preparing for drought.
The NASA GPM Iowa Flood Studies Experiment

NASA Astrophysics Data System (ADS)

Petersen, W. A.; Krajewski, W. F.; Peters-Lidard, C. D.; Rutledge, S. A.; Wolff, D. B.

2013-12-01

The overarching objective of NASA Global Precipitation Measurement Mission (GPM) integrated hydrologic ground validation (GV) is to provide a better understanding of the strengths and limitations of the satellite products, in the context of hydrologic applications. Accordingly, the NASA GPM GV program recently completed the first of several hydrology-oriented field efforts: the Iowa Flood Studies (IFloodS) experiment. IFloodS was conducted in central Iowa during the months of April-June, 2013. IFloodS science objectives focused on: a) The collection of reference multi-parameter radar, rain gauge, disdrometer, soil moisture, and hydrologic network measurements to quantify the physical character and space/time variability of rain (e.g., rates, drop size distributions, processes), land surface- state and hydrologic response; b) Application of the ground reference measurements to assessment of satellite-based rainfall estimation uncertainties; c) Propagation of both ground and satellite rainfall estimation uncertainties in coupled hydrologic prediction models to assess impacts on predictive skill; and d) Evaluation of rainfall properties such as rate and accumulation relative to basin hydrologic characteristics in modeled flood genesis. IFloodS observational objectives were achieved via deployments of the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars (operating in coordinated scanning modes), four University of Iowa X-band dual-polarimetric radars, four Micro Rain Radars, a network of 25 paired rain gauge platforms with attendant soil moisture and temperature probes, a network of six 2D Video and 14 Parsivel disdrometers, and 15 USDA-ARS rain gauge and soil-moisture stations (collaboration with the USDA-ARS and NASA Soil Moisture Active-Passive mission). The aforementioned platforms complemented existing operational WSR-88D S-band polarimetric radar, USGS streamflow, and Iowa Flood Center-affiliated stream monitoring and rainfall measurements. Coincident low-earth orbiter microwave, geostationary infrared, and derived satellite-algorithm rainfall products were also archived during the experiment. Twice daily NASA Unified Weather Research and Forecasting model simulations were conducted to provide weather forecast guidance and a coupled atmospheric/land-surface model simulation benchmark. During the experiment the IFloodS observational domain experienced heavy rainfall (> 250-300 mm) and significant flooding. Deployed observational assets, especially the research radars performed well throughout the experiment, sampling a broad range of precipitation system types including multi-day mixtures of rain and snow, warm-season mesoscale convective systems, and supercell thunderstorms. The variety of regimes and large rain accumulations sampled creates a rich source of data for testing both satellite products and coupled atmospheric, land system, and hydrologic models. In this study we will provide an overview of the IFloodS experiment, datasets, and preliminary observational results.
A WorkFlow Engine Oriented Modeling System for Hydrologic Sciences

NASA Astrophysics Data System (ADS)

Lu, B.; Piasecki, M.

2009-12-01

In recent years the use of workflow engines for carrying out modeling and data analyses tasks has gained increased attention in the science and engineering communities. Tasks like processing raw data coming from sensors and passing these raw data streams to filters for QA/QC procedures possibly require multiple and complicated steps that need to be repeated over and over again. A workflow sequence that carries out a number of steps of various complexity is an ideal approach to deal with these tasks because the sequence can be stored, called up and repeated over again and again. This has several advantages: for one it ensures repeatability of processing steps and with that provenance, an issue that is increasingly important in the science and engineering communities. It also permits the hand off of lengthy and time consuming tasks that can be error prone to a chain of processing actions that are carried out automatically thus reducing the chance for error on the one side and freeing up time to carry out other tasks on the other hand. This paper aims to present the development of a workflow engine embedded modeling system which allows to build up working sequences for carrying out numerical modeling tasks regarding to hydrologic science. Trident, which facilitates creating, running and sharing scientific data analysis workflows, is taken as the central working engine of the modeling system. Current existing functionalities of the modeling system involve digital watershed processing, online data retrieval, hydrologic simulation and post-event analysis. They are stored as sequences or modules respectively. The sequences can be invoked to implement their preset tasks in orders, for example, triangulating a watershed from raw DEM. Whereas the modules encapsulated certain functions can be selected and connected through a GUI workboard to form sequences. This modeling system is demonstrated by setting up a new sequence for simulating rainfall-runoff processes which involves embedded Penn State Integrated Hydrologic Model(PIHM) module for hydrologic simulation as a kernel, DEM processing sub-sequence which prepares geospatial data for PIHM, data retrieval module which access time series data from online data repository via web services or from local database, post- data management module which stores , visualizes and analyzes model outputs.
Tools for Virtual Collaboration Designed for High Resolution Hydrologic Research with Continental-Scale Data Support

NASA Astrophysics Data System (ADS)

Duffy, Christopher; Leonard, Lorne; Shi, Yuning; Bhatt, Gopal; Hanson, Paul; Gil, Yolanda; Yu, Xuan

2015-04-01

Using a series of recent examples and papers we explore some progress and potential for virtual (cyber-) collaboration inspired by access to high resolution, harmonized public-sector data at continental scales [1]. The first example describes 7 meso-scale catchments in Pennsylvania, USA where the watershed is forced by climate reanalysis and IPCC future climate scenarios (Intergovernmental Panel on Climate Change). We show how existing public-sector data and community models are currently able to resolve fine-scale eco-hydrologic processes regarding wetland response to climate change [2]. The results reveal that regional climate change is only part of the story, with large variations in flood and drought response associated with differences in terrain, physiography, landuse and/or hydrogeology. The importance of community-driven virtual testbeds are demonstrated in the context of Critical Zone Observatories, where earth scientists from around the world are organizing hydro-geophysical data and model results to explore new processes that couple hydrologic models with land-atmosphere interaction, biogeochemical weathering, carbon-nitrogen cycle, landscape evolution and ecosystem services [3][4]. Critical Zone cyber-research demonstrates how data-driven model development requires a flexible computational structure where process modules are relatively easy to incorporate and where new data structures can be implemented [5]. From the perspective of "Big-Data" the paper points out that extrapolating results from virtual observatories to catchments at continental scales, will require centralized or cloud-based cyberinfrastructure as a necessary condition for effectively sharing petabytes of data and model results [6]. Finally we outline how innovative cyber-science is supporting earth-science learning, sharing and exploration through the use of on-line tools where hydrologists and limnologists are sharing data and models for simulating the coupled impacts of catchment hydrology on lake eco-hydrology (NSF-INSPIRE, IIS1344272). The research attempts to use a virtual environment (www.organicdatascience.org) to break down disciplinary barriers and support emergent communities of science. [1] Source: Leonard and Duffy, 2013, Environmental Modelling & Software; [2] Source: Yu et al, 2014, Computers in Geoscience; [3] Source: Duffy et al, 2014, Procedia Earth and Planetary Science; [4] Source: Shi et al, Journal of Hydrometeorology, 2014; [5] Source: Bhatt et al, 2014, Environmental Modelling & Software ; [6] Leonard and Duffy, 2014, Environmental Modelling and Software.
Evolution of Root Zone Storage after Land Use Change

NASA Astrophysics Data System (ADS)

Nijzink, R.; Hutton, C.; Capell, R.; Pechlivanidis, I.; Hrachowitz, M.; Savenije, H.

2015-12-01

It has been acknowledged for some time that a coupling exists between vegetation, climate and hydrological processes (e.g. Eagleson, 1982a, Rodriguez-Iturbe,2001 ). Recently, Gao et al.(2014) demonstrated that one of the core parameters of hydrological functioning, the catchment-scale root zone water storage capacity, can be estimated based on climate data alone. It was shown that ecosystems develop root zone storage capacities that allow vegetation to bridge droughts with return periods of about 20 years. As a consequence, assuming that the evaporative demand determines the root zone storage capacity, land use changes, such as deforestation, should have an effect on the development of this capacity . In this study it was tested to which extent deforestation affects root zone storage capacities. To do so, four different hydrological models were calibrated in a moving window approach after deforestation occurred. In this way, model based estimates of the storage capacity in time were obtained. This was compared with short term estimates of root zone storage capacities based on a climate based method similar to Gao et al.(2014). In addition, the equilibrium root zone storage capacity was determined with the total time series of an unaffected control catchment. Preliminary results indicate that models tend to adjust their storage capacity to the values found by the climate based method. This is strong evidence that the root zone storage is determined by the evaporative demand of vegetation. Besides, root zones storage capacities develop towards an equilibrium value where the ecosystem is in balance, further highlighting the evolving, time dynamic character of hydrological systems.
High-quality unsaturated zone hydraulic property data for hydrologic applications

USGS Publications Warehouse

Perkins, Kimberlie; Nimmo, John R.

2009-01-01

In hydrologic studies, especially those using dynamic unsaturated zone moisture modeling, calculations based on property transfer models informed by hydraulic property databases are often used in lieu of measured data from the site of interest. Reliance on database-informed predicted values has become increasingly common with the use of neural networks. High-quality data are needed for databases used in this way and for theoretical and property transfer model development and testing. Hydraulic properties predicted on the basis of existing databases may be adequate in some applications but not others. An obvious problem occurs when the available database has few or no data for samples that are closely related to the medium of interest. The data set presented in this paper includes saturated and unsaturated hydraulic conductivity, water retention, particle-size distributions, and bulk properties. All samples are minimally disturbed, all measurements were performed using the same state of the art techniques and the environments represented are diverse.
Statistical attribution analysis of the nonstationarity of the annual runoff series of the Weihe River.

PubMed

Xiong, Lihua; Jiang, Cong; Du, Tao

2014-01-01

Time-varying moments models based on Pearson Type III and normal distributions respectively are built under the generalized additive model in location, scale and shape (GAMLSS) framework to analyze the nonstationarity of the annual runoff series of the Weihe River, the largest tributary of the Yellow River. The detection of nonstationarities in hydrological time series (annual runoff, precipitation and temperature) from 1960 to 2009 is carried out using a GAMLSS model, and then the covariate analysis for the annual runoff series is implemented with GAMLSS. Finally, the attribution of each covariate to the nonstationarity of annual runoff is analyzed quantitatively. The results demonstrate that (1) obvious change-points exist in all three hydrological series, (2) precipitation, temperature and irrigated area are all significant covariates of the annual runoff series, and (3) temperature increase plays the main role in leading to the reduction of the annual runoff series in the study basin, followed by the decrease of precipitation and the increase of irrigated area.
On the probabilistic structure of water age: Probabilistic Water Age

DOE Office of Scientific and Technical Information (OSTI.GOV)

Porporato, Amilcare; Calabrese, Salvatore

We report the age distribution of water in hydrologic systems has received renewed interest recently, especially in relation to watershed response to rainfall inputs. The purpose of this contribution is first to draw attention to existing theories of age distributions in population dynamics, fluid mechanics and stochastic groundwater, and in particular to the McKendrick-von Foerster equation and its generalizations and solutions. A second and more important goal is to clarify that, when hydrologic fluxes are modeled by means of time-varying stochastic processes, the age distributions must themselves be treated as random functions. Once their probabilistic structure is obtained, it canmore » be used to characterize the variability of age distributions in real systems and thus help quantify the inherent uncertainty in the field determination of water age. Finally, we illustrate these concepts with reference to a stochastic storage model, which has been used as a minimalist model of soil moisture and streamflow dynamics.« less
On the probabilistic structure of water age: Probabilistic Water Age

DOE PAGES

Porporato, Amilcare; Calabrese, Salvatore

2015-04-23

We report the age distribution of water in hydrologic systems has received renewed interest recently, especially in relation to watershed response to rainfall inputs. The purpose of this contribution is first to draw attention to existing theories of age distributions in population dynamics, fluid mechanics and stochastic groundwater, and in particular to the McKendrick-von Foerster equation and its generalizations and solutions. A second and more important goal is to clarify that, when hydrologic fluxes are modeled by means of time-varying stochastic processes, the age distributions must themselves be treated as random functions. Once their probabilistic structure is obtained, it canmore » be used to characterize the variability of age distributions in real systems and thus help quantify the inherent uncertainty in the field determination of water age. Finally, we illustrate these concepts with reference to a stochastic storage model, which has been used as a minimalist model of soil moisture and streamflow dynamics.« less
Using SERC for creating and publishing student generated hydrology instruction materials

NASA Astrophysics Data System (ADS)

Merwade, V.; Rajib, A.; Ruddell, B.; Fox, S.

2016-12-01

Hydrology instruction typically involves teaching of the hydrologic cycle and the processes associated with it such as precipitation, evapotranspiration, infiltration, runoff generation and hydrograph analysis. With the availability of observed and remotely sensed data in public domain, there is an opportunity to incorporate place-based learning in hydrology classrooms. However, it is not always easy and possible for an instructor to complement an existing hydrology course with new material that requires both time and technical expertise, which the instructor may not have. The work presented here describes an effort where students created the data and modeling driven instruction materials as part of their class assignment for a hydrology course at Purdue University. Students in the class were divided into groups, and each group was assigned a topic such as precipitation, evapotranspiration, streamflow, flow duration curve and flood frequency analysis. Each of the student groups was then instructed to produce an instruction material showing ways to extract/process relevant data and perform some analysis for an area with specific land use characteristic. The student contributions were then organized into learning units such that someone can do a flow duration curve analysis or flood frequency analysis and see how it changes for rural area versus urban area. Science Education Resource Center (SERC) is used as a platform to publish and share these instruction materials so it can be used as-is or through modification by any instructor or student in relevant coursework anywhere in the world.
Identifying natural flow regimes using fish communities

NASA Astrophysics Data System (ADS)

Chang, Fi-John; Tsai, Wen-Ping; Wu, Tzu-Ching; Chen, Hung-kwai; Herricks, Edwin E.

2011-10-01

SummaryModern water resources management has adopted natural flow regimes as reasonable targets for river restoration and conservation. The characterization of a natural flow regime begins with the development of hydrologic statistics from flow records. However, little guidance exists for defining the period of record needed for regime determination. In Taiwan, the Taiwan Eco-hydrological Indicator System (TEIS), a group of hydrologic statistics selected for fisheries relevance, is being used to evaluate ecological flows. The TEIS consists of a group of hydrologic statistics selected to characterize the relationships between flow and the life history of indigenous species. Using the TEIS and biosurvey data for Taiwan, this paper identifies the length of hydrologic record sufficient for natural flow regime characterization. To define the ecological hydrology of fish communities, this study connected hydrologic statistics to fish communities by using methods to define antecedent conditions that influence existing community composition. A moving average method was applied to TEIS statistics to reflect the effects of antecedent flow condition and a point-biserial correlation method was used to relate fisheries collections with TEIS statistics. The resulting fish species-TEIS (FISH-TEIS) hydrologic statistics matrix takes full advantage of historical flows and fisheries data. The analysis indicates that, in the watersheds analyzed, averaging TEIS statistics for the present year and 3 years prior to the sampling date, termed MA(4), is sufficient to develop a natural flow regime. This result suggests that flow regimes based on hydrologic statistics for the period of record can be replaced by regimes developed for sampled fish communities.
Coupled Crop/Hydrology Model to Estimate Expanded Irrigation Impact on Water Resources

NASA Astrophysics Data System (ADS)

Handyside, C. T.; Cruise, J.

2017-12-01

A coupled agricultural and hydrologic systems model is used to examine the environmental impact of irrigation in the Southeast. A gridded crop model for the Southeast is used to determine regional irrigation demand. This irrigation demand is used in a regional hydrologic model to determine the hydrologic impact of irrigation. For the Southeast to maintain/expand irrigated agricultural production and provide adaptation to climate change and climate variability it will require integrated agricultural and hydrologic system models that can calculate irrigation demand and the impact of the this demand on the river hydrology. These integrated models can be used as (1) historical tools to examine vulnerability of expanded irrigation to past climate extremes (2) future tools to examine the sustainability of expanded irrigation under future climate scenarios and (3) a real-time tool to allow dynamic water resource management. Such tools are necessary to assure stakeholders and the public that irrigation can be carried out in a sustainable manner. The system tools to be discussed include a gridded version of the crop modeling system (DSSAT). The gridded model is referred to as GriDSSAT. The irrigation demand from GriDSSAT is coupled to a regional hydrologic model developed by the Eastern Forest Environmental Threat Assessment Center of the USDA Forest Service) (WaSSI). The crop model provides the dynamic irrigation demand which is a function of the weather. The hydrologic model includes all other competing uses of water. Examples of use the crop model coupled with the hydrologic model include historical analyses which show the change in hydrology as additional acres of irrigated land are added to water sheds. The first order change in hydrology is computed in terms of changes in the Water Availability Stress Index (WASSI) which is the ratio of water demand (irrigation, public water supply, industrial use, etc.) and water availability from the hydrologic model. Also, statistics such as the number of times certain WASSI thresholds are exceeded are calculated to show the impact of expanded irrigation during times of hydrologic drought and the coincident use of water by other sectors. Also, integrated downstream impacts of irrigation are also calculated through changes in flows through the whole river systems.
Modeling the effect of land use change on hydrology of a forested watershed in coastal South Carolina.

Treesearch

Zhaohua Dai; Devendra M. Amatya; Ge Sun; Changsheng Li; Carl C. Trettin; Harbin Li

2009-01-01

Since hydrology is one of main factors controlling wetland functions, hydrologic models are useful for evaluating the effects of land use change on we land ecosystems. We evaluated two process-based hydrologic models with...
Framework for a hydrologic climate-response network in New England

USGS Publications Warehouse

Lent, Robert M.; Hodgkins, Glenn A.; Dudley, Robert W.; Schalk, Luther F.

2015-01-01

Many climate-related hydrologic variables in New England have changed in the past century, and many are expected to change during the next century. It is important to understand and monitor these changes because they can affect human water supply, hydroelectric power generation, transportation infrastructure, and stream and riparian ecology. This report describes a framework for hydrologic monitoring in New England by means of a climate-response network. The framework identifies specific inland hydrologic variables that are sensitive to climate variation; identifies geographic regions with similar hydrologic responses; proposes a fixed-station monitoring network composed of existing streamflow, groundwater, lake ice, snowpack, and meteorological data-collection stations for evaluation of hydrologic response to climate variation; and identifies streamflow basins for intensive, process-based studies and for estimates of future hydrologic conditions.
On the deterministic and stochastic use of hydrologic models

USGS Publications Warehouse

Farmer, William H.; Vogel, Richard M.

2016-01-01

Environmental simulation models, such as precipitation-runoff watershed models, are increasingly used in a deterministic manner for environmental and water resources design, planning, and management. In operational hydrology, simulated responses are now routinely used to plan, design, and manage a very wide class of water resource systems. However, all such models are calibrated to existing data sets and retain some residual error. This residual, typically unknown in practice, is often ignored, implicitly trusting simulated responses as if they are deterministic quantities. In general, ignoring the residuals will result in simulated responses with distributional properties that do not mimic those of the observed responses. This discrepancy has major implications for the operational use of environmental simulation models as is shown here. Both a simple linear model and a distributed-parameter precipitation-runoff model are used to document the expected bias in the distributional properties of simulated responses when the residuals are ignored. The systematic reintroduction of residuals into simulated responses in a manner that produces stochastic output is shown to improve the distributional properties of the simulated responses. Every effort should be made to understand the distributional behavior of simulation residuals and to use environmental simulation models in a stochastic manner.
Hydrological Modeling of Storm Water Drainage System due to Frequent and Intense Precipitation of Dhaka city using Storm Water Management Model (SWMM)

NASA Astrophysics Data System (ADS)

Hossain, S., Jr.

2015-12-01

Rainfall induced flooding during rainy season is a regular phenomenon in Dhaka City. Almost every year a significant part of the city suffers badly with drainage congestion. There are some highly dense areas with lower ground elevation which submerge under water even with an intense precipitation of few hours. The higher areas also suffer with the drainage problem due to inadequate maintenance of the system and encroachment or illegal filling up of the drainage canals and lakes. Most part of the city suffered from long term urban flooding during historical extreme rainfall events in September 2004, 2007 and July 2009. The situation is likely to worsen in the future due to Climate Change, which may lead to more frequent and intense precipitation. To assess the major and minor drainage systems and elements of the urban basins using the hydrodynamic modelling and, through this, identifying the flooding events and areas, taking into account the current situation and future flood or drainage scenarios. Stormwater modeling has a major role in preventing issues such as flash floods and urban water-quality problems. Stormwater models of a lowered spatial resolution would thus appear valuable if only their ability to provide realistic results could be proved. The present scenario of urban morphology of Dhaka city and existing drainage system is complex for hydrological and hydrodynamic modeling. Furthermore limitations of background data and uncertain future urban scenarios may confine the potential outputs of a model. Although several studies were carried out including modeling for drainage master planning, a detail model for whole DAP (Detaile Area Plan) of Dhaka city area is not available. The model developed under this study is covering the existing drainage system in the study area as well as natural flows in the fringe area. A good number of models are available for hydrological and hydraulic analysis of urban areas. These are MIKE 11, MOUSE, HEC-RAS, HEC HMS and EPA SWMM. EPA-SWMM is used for the study area which is mostly developed and consists pipe networks, open channels and water bodies. This study proposes a methodology for rapid catchment delineation and stormwater management model (SWMM) set-up in a large urban area with model calibration and validation.

Mapping the global depth to bedrock for land surface modelling

NASA Astrophysics Data System (ADS)

Shangguan, W.; Hengl, T.; Yuan, H.; Dai, Y. J.; Zhang, S.

2017-12-01

Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of Depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 130,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surfacee reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forests and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas.
Mapping the global depth to bedrock for land surface modeling

NASA Astrophysics Data System (ADS)

Shangguan, Wei; Hengl, Tomislav; Mendes de Jesus, Jorge; Yuan, Hua; Dai, Yongjiu

2017-03-01

Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 1,30,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surface reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forest and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250 m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas.
Opportunities and challenges for extended-range predictions of tropical cyclone impacts on hydrological predictions

NASA Astrophysics Data System (ADS)

Tsai, Hsiao-Chung; Elsberry, Russell L.

2013-12-01

SummaryAn opportunity exists to extend support to the decision-making processes of water resource management and hydrological operations by providing extended-range tropical cyclone (TC) formation and track forecasts in the western North Pacific from the 51-member ECMWF 32-day ensemble. A new objective verification technique demonstrates that the ECMWF ensemble can predict most of the formations and tracks of the TCs during July 2009 to December 2010, even for most of the tropical depressions. Due to the relatively large number of false-alarm TCs in the ECMWF ensemble forecasts that would cause problems for support of hydrological operations, characteristics of these false alarms are discussed. Special attention is given to the ability of the ECMWF ensemble to predict periods of no-TCs in the Taiwan area, since water resource management decisions also depend on the absence of typhoon-related rainfall. A three-tier approach is proposed to provide support for hydrological operations via extended-range forecasts twice weekly on the 30-day timescale, twice-daily on the 15-day timescale, and up to four times a day with a consensus of high-resolution deterministic models.
Integrating hydrology into catchment scale studies - need for new paradigms?

NASA Astrophysics Data System (ADS)

Teutsch, G.

2009-04-01

Until the seventies, scientific development in the field of groundwater hydrology concentrated mainly on a better understanding of the physics of subsurface flow in homogeneous or simply stratified porous respectively fractured media. Then, since mid of the seventies, a much more complex vision of groundwater hydrology gradually developed. A more realistic description of the subsurface including its heterogeneity, predominant physico-chemical-biological reactions and also technologies for the efficient clean-up of contaminants developed during the past 30 years, much facilitated by the advancement in numerical modelling techniques and the boost in computer power. Even though the advancements in this field have been very significant, a new grand challenge evolved during the past 10 years trying to bring together the fields needed to build Integrated Watershed Management Systems (IWMS). The fundamental conceptual question is: Do we need new approaches to groundwater hydrology, maybe even new paradigms in order to successfully build IWMS - or can we simply extrapolate our existing concepts and tool-sets to the scale of catchments and watersheds and simply add some interfaces to adjacent disciplines like economy, ecology and others? This lecture tries to provide some of the answers by describing some successful examples.
A "total parameter estimation" method in the varification of distributed hydrological models

NASA Astrophysics Data System (ADS)

Wang, M.; Qin, D.; Wang, H.

2011-12-01

Conventionally hydrological models are used for runoff or flood forecasting, hence the determination of model parameters are common estimated based on discharge measurements at the catchment outlets. With the advancement in hydrological sciences and computer technology, distributed hydrological models based on the physical mechanism such as SWAT, MIKESHE, and WEP, have gradually become the mainstream models in hydrology sciences. However, the assessments of distributed hydrological models and model parameter determination still rely on runoff and occasionally, groundwater level measurements. It is essential in many countries, including China, to understand the local and regional water cycle: not only do we need to simulate the runoff generation process and for flood forecasting in wet areas, we also need to grasp the water cycle pathways and consumption process of transformation in arid and semi-arid regions for the conservation and integrated water resources management. As distributed hydrological model can simulate physical processes within a catchment, we can get a more realistic representation of the actual water cycle within the simulation model. Runoff is the combined result of various hydrological processes, using runoff for parameter estimation alone is inherits problematic and difficult to assess the accuracy. In particular, in the arid areas, such as the Haihe River Basin in China, runoff accounted for only 17% of the rainfall, and very concentrated during the rainy season from June to August each year. During other months, many of the perennial rivers within the river basin dry up. Thus using single runoff simulation does not fully utilize the distributed hydrological model in arid and semi-arid regions. This paper proposed a "total parameter estimation" method to verify the distributed hydrological models within various water cycle processes, including runoff, evapotranspiration, groundwater, and soil water; and apply it to the Haihe river basin in China. The application results demonstrate that this comprehensive testing method is very useful in the development of a distributed hydrological model and it provides a new way of thinking in hydrological sciences.
NATIONAL WATER INFORMATION SYSTEM OF THE U. S. GEOLOGICAL SURVEY.

USGS Publications Warehouse

Edwards, Melvin D.

1985-01-01

National Water Information System (NWIS) has been designed as an interactive, distributed data system. It will integrate the existing, diverse data-processing systems into a common system. It will also provide easier, more flexible use as well as more convenient access and expanded computing, dissemination, and data-analysis capabilities. The NWIS is being implemented as part of a Distributed Information System (DIS) being developed by the Survey's Water Resources Division. The NWIS will be implemented on each node of the distributed network for the local processing, storage, and dissemination of hydrologic data collected within the node's area of responsibility. The processor at each node will also be used to perform hydrologic modeling, statistical data analysis, text editing, and some administrative work.
Assimilation of remote sensing observations into a continuous distributed hydrological model: impacts on the hydrologic cycle

NASA Astrophysics Data System (ADS)

Laiolo, Paola; Gabellani, Simone; Campo, Lorenzo; Cenci, Luca; Silvestro, Francesco; Delogu, Fabio; Boni, Giorgio; Rudari, Roberto

2015-04-01

The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce in-situ data. This work investigates the impact of the assimilation of different remote sensing products on the hydrological cycle by using a continuous physically based distributed hydrological model. Three soil moisture products derived by ASCAT (Advanced SCATterometer) are used to update the model state variables. The satellite-derived products are assimilated into the hydrological model using different assimilation techniques: a simple nudging and the Ensemble Kalman Filter. Moreover two assimilation strategies are evaluated to assess the impact of assimilating the satellite products at model spatial resolution or at the satellite scale. The experiments are carried out for three Italian catchments on multi year period. The benefits on the model predictions of discharge, LST, evapotranspiration and soil moisture dynamics are tested and discussed.
ENVIRONMENTAL ISOTOPES FOR RESOLUTION OF HYDROLOGY PROBLEMS

EPA Science Inventory

The use of environmental isotopes as tracers in the hydrosphere is increasing as analytical instrumentation improves and more applications are discovered. There exists still misconceptions on the role of isotopes in resolving hydrology problems. Naturally occurring isotopes in th...
Jump-Diffusion models and structural changes for asset forecasting in hydrology

NASA Astrophysics Data System (ADS)

Tranquille Temgoua, André Guy; Martel, Richard; Chang, Philippe J. J.; Rivera, Alfonso

2017-04-01

Impacts of climate change on surface water and groundwater are of concern in many regions of the world since water is an essential natural resource. Jump-Diffusion models are generally used in economics and other related fields but not in hydrology. The potential application could be made for hydrologic data series analysis and forecast. The present study uses Jump-Diffusion models by adding structural changes to detect fluctuations in hydrologic processes in relationship with climate change. The model implicitly assumes that modifications in rivers' flowrates can be divided into three categories: (a) normal changes due to irregular precipitation events especially in tropical regions causing major disturbance in hydrologic processes (this component is modelled by a discrete Brownian motion); (b) abnormal, sudden and non-persistent modifications in hydrologic proceedings are handled by Poisson processes; (c) the persistence of hydrologic fluctuations characterized by structural changes in hydrological data related to climate variability. The objective of this paper is to add structural changes in diffusion models with jumps, in order to capture the persistence of hydrologic fluctuations. Indirectly, the idea is to observe if there are structural changes of discharge/recharge over the study area, and to find an efficient and flexible model able of capturing a wide variety of hydrologic processes. Structural changes in hydrological data are estimated using the method of nonlinear discrete filters via Method of Simulated Moments (MSM). An application is given using sensitive parameters such as baseflow index and recession coefficient to capture discharge/recharge. Historical dataset are examined by the Volume Spread Analysis (VSA) to detect real time and random perturbations in hydrologic processes. The application of the method allows establishing more accurate hydrologic parameters. The impact of this study is perceptible in forecasting floods and groundwater recession. Keywords: hydrologic processes, Jump-Diffusion models, structural changes, forecast, climate change
Python package for model STructure ANalysis (pySTAN)

NASA Astrophysics Data System (ADS)

Van Hoey, Stijn; van der Kwast, Johannes; Nopens, Ingmar; Seuntjens, Piet

2013-04-01

The selection and identification of a suitable hydrological model structure is more than fitting parameters of a model structure to reproduce a measured hydrograph. The procedure is highly dependent on various criteria, i.e. the modelling objective, the characteristics and the scale of the system under investigation as well as the available data. Rigorous analysis of the candidate model structures is needed to support and objectify the selection of the most appropriate structure for a specific case (or eventually justify the use of a proposed ensemble of structures). This holds both in the situation of choosing between a limited set of different structures as well as in the framework of flexible model structures with interchangeable components. Many different methods to evaluate and analyse model structures exist. This leads to a sprawl of available methods, all characterized by different assumptions, changing conditions of application and various code implementations. Methods typically focus on optimization, sensitivity analysis or uncertainty analysis, with backgrounds from optimization, machine-learning or statistics amongst others. These methods also need an evaluation metric (objective function) to compare the model outcome with some observed data. However, for current methods described in literature, implementations are not always transparent and reproducible (if available at all). No standard procedures exist to share code and the popularity (and amount of applications) of the methods is sometimes more dependent on the availability than the merits of the method. Moreover, new implementations of existing methods are difficult to verify and the different theoretical backgrounds make it difficult for environmental scientists to decide about the usefulness of a specific method. A common and open framework with a large set of methods can support users in deciding about the most appropriate method. Hence, it enables to simultaneously apply and compare different methods on a fair basis. We developed and present pySTAN (python framework for STructure Analysis), a python package containing a set of functions for model structure evaluation to provide the analysis of (hydrological) model structures. A selected set of algorithms for optimization, uncertainty and sensitivity analysis is currently available, together with a set of evaluation (objective) functions and input distributions to sample from. The methods are implemented model-independent and the python language provides the wrapper functions to apply administer external model codes. Different objective functions can be considered simultaneously with both statistical metrics and more hydrology specific metrics. By using so-called reStructuredText (sphinx documentation generator) and Python documentation strings (docstrings), the generation of manual pages is semi-automated and a specific environment is available to enhance both the readability and transparency of the code. It thereby enables a larger group of users to apply and compare these methods and to extend the functionalities.
Upscaling from research watersheds: an essential stage of trustworthy general-purpose hydrologic model building

NASA Astrophysics Data System (ADS)

McNamara, J. P.; Semenova, O.; Restrepo, P. J.

2011-12-01

Highly instrumented research watersheds provide excellent opportunities for investigating hydrologic processes. A danger, however, is that the processes observed at a particular research watershed are too specific to the watershed and not representative even of the larger scale watershed that contains that particular research watershed. Thus, models developed based on those partial observations may not be suitable for general hydrologic use. Therefore demonstrating the upscaling of hydrologic process from research watersheds to larger watersheds is essential to validate concepts and test model structure. The Hydrograph model has been developed as a general-purpose process-based hydrologic distributed system. In its applications and further development we evaluate the scaling of model concepts and parameters in a wide range of hydrologic landscapes. All models, either lumped or distributed, are based on a discretization concept. It is common practice that watersheds are discretized into so called hydrologic units or hydrologic landscapes possessing assumed homogeneous hydrologic functioning. If a model structure is fixed, the difference in hydrologic functioning (difference in hydrologic landscapes) should be reflected by a specific set of model parameters. Research watersheds provide the possibility for reasonable detailed combining of processes into some typical hydrologic concept such as hydrologic units, hydrologic forms, and runoff formation complexes in the Hydrograph model. And here by upscaling we imply not the upscaling of a single process but upscaling of such unified hydrologic functioning. The simulation of runoff processes for the Dry Creek research watershed, Idaho, USA (27 km2) was undertaken using the Hydrograph model. The information on the watershed was provided by Boise State University and included a GIS database of watershed characteristics and a detailed hydrometeorological observational dataset. The model provided good simulation results in terms of runoff and variable states of soil and snow over a simulation period 2000 - 2009. The parameters of the model were hand-adjusted based on rational sense, observational data and available understanding of underlying processes. For the first run some processes as riparian vegetation impact on runoff and streamflow/groundwater interaction were handled in a conceptual way. It was shown that the use of Hydrograph model which requires modest amount of parameter calibration may serve also as a quality control for observations. Based on the obtained parameters values and process understanding at the research watershed the model was applied to the larger scale watersheds located in similar environment - the Boise River at South Fork (1660 km2) and Twin Springs (2155 km2). The evaluation of the results of such upscaling will be presented.
Development of a biosphere hydrological model considering vegetation dynamics and its evaluation at basin scale under climate change

NASA Astrophysics Data System (ADS)

Li, Qiaoling; Ishidaira, Hiroshi

2012-01-01

SummaryThe biosphere and hydrosphere are intrinsically coupled. The scientific question is if there is a substantial change in one component such as vegetation cover, how will the other components such as transpiration and runoff generation respond, especially under climate change conditions? Stand-alone hydrological models have a detailed description of hydrological processes but do not sufficiently parameterize vegetation as a dynamic component. Dynamic global vegetation models (DGVMs) are able to simulate transient structural changes in major vegetation types but do not simulate runoff generation reliably. Therefore, both hydrological models and DGVMs have their limitations as well as advantages for addressing this question. In this study a biosphere hydrological model (LPJH) is developed by coupling a prominent DGVM (Lund-Postdam-Jena model referred to as LPJ) with a stand-alone hydrological model (HYMOD), with the objective of analyzing the role of vegetation in the hydrological processes at basin scale and evaluating the impact of vegetation change on the hydrological processes under climate change. The application and validation of the LPJH model to four basins representing a variety of climate and vegetation conditions shows that the performance of LPJH is much better than that of the original LPJ and is similar to that of stand-alone hydrological models for monthly and daily runoff simulation at the basin scale. It is argued that the LPJH model gives more reasonable hydrological simulation since it considers both the spatial variability of soil moisture and vegetation dynamics, which make the runoff generation mechanism more reliable. As an example, it is shown that changing atmospheric CO 2 content alone would result in runoff increases in humid basins and decreases in arid basins. Theses changes are mainly attributable to changes in transpiration driven by vegetation dynamics, which are not simulated in stand-alone hydrological models. Therefore LPJH potentially provides a powerful tool for simulating vegetation response to climate changes in the biosphere hydrological cycle.
An Educational Model for Hands-On Hydrology Education

NASA Astrophysics Data System (ADS)

AghaKouchak, A.; Nakhjiri, N.; Habib, E. H.

2014-12-01

This presentation provides an overview of a hands-on modeling tool developed for students in civil engineering and earth science disciplines to help them learn the fundamentals of hydrologic processes, model calibration, sensitivity analysis, uncertainty assessment, and practice conceptual thinking in solving engineering problems. The toolbox includes two simplified hydrologic models, namely HBV-EDU and HBV-Ensemble, designed as a complement to theoretical hydrology lectures. The models provide an interdisciplinary application-oriented learning environment that introduces the hydrologic phenomena through the use of a simplified conceptual hydrologic model. The toolbox can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for teaching more advanced topics including uncertainty analysis, and ensemble simulation. Both models have been administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of hydrology.
Hydropower potential mapping in mountain basins by high-resolution hydrological and GIS analysis

NASA Astrophysics Data System (ADS)

Claps, P.; Gallo, E.; Ganora, D.; Laio, F.; Masoero, A.

2013-12-01

Even in regions with mature hydropower development, needs for stable renewable power sources suggest to revise plans of exploitation of water resources, in compliance to the framework of international and national environmental regulations. This goal requires high-resolution hydrological analysis, that allows to : i) comply with the effects of existing hydropower plants or of other types of water withdrawals; ii) to assist the planner to figure out potential of new plants with still high marginal efficiency; iii) to assist the regulator in the process of comparing projects based on different solutions and different underlying hydrologic estimation methods. Flow duration curves (FDC) are the tool usually adopted to represent water availability and variability for hydropower purposes. They are usually determined in ungauged basins by means of regional statistical analysis. For this study, a 'spatially smooth' regional estimation method (SSEM) has been developed for FDC estimation, with some evolutions from a previous version: i) the method keeps the estimates of mean annual runoff congruent in the confluences by considering only raster-summable explanatory variables; ii) the presence of existing reservoirs and hydropower plants is taken into account by restoring the ';natural' statistics of the curve. The SSEM reconstructs the the FDC in ungauged basins using its L-moments from regressions on geomorphoclimatic descriptors. Relations are obtained on more than 100 gauged basins located in Northwestern Italy. To support the assessment of residual hydropower potential on two specific mountain watersheds the model has been applied extensively (Hi-Res) by mapping the estimated mean flow for each pixel of a DEM-derived river network raster model. 25000 sections were then identified over the network extracted from a 50m-resolution DTM. Spatial algorithms and data management were developed using Free&OpenSource Software (FOSS) (GRASS GIS and PostgreSQL/PostGIS), with the spatial database required to store perimeters and other descriptors needed for the hydrological estimation. Specific efforts have been devoted to spatial representation of the available potential using different flow-(elevation drop) relations for each pixel (along-river path, straight within floating window, in-valley constrained, etc.). This representation expands the information content and the domain of application of the classical hydrodynamic curve ( elevation-drop/ contributing area). Specific and abrupt changes due to existing plants are then clearly represented to provide a complete picture of the available potential for planning and regulation purposes.
Using a coupled groundwater/surfacewater model to predict climate-change impacts to lakes in the Trout Lake watershed, Northern Wisconsin

USGS Publications Warehouse

Walker, John F.; Hunt, Randall J.; Markstrom, Steven L.; Hay, Lauren E.; Doherty, John

2009-01-01

A major focus of the U.S. Geological Survey’s Trout Lake Water, Energy, and Biogeochemical Budgets (WEBB) project is the development of a watershed model to allow predictions of hydrologic response to future conditions including land-use and climate change. The coupled groundwater/surface-water model GSFLOW was chosen for this purpose because it could easily incorporate an existing groundwater flow model and it provides for simulation of surface-water processes. The Trout Lake watershed in northern Wisconsin is underlain by a highly conductive outwash sand aquifer. In this area, streamflow is dominated by groundwater contributions; however, surface runoff occurs during intense rainfall periods and spring snowmelt. Surface runoff also occurs locally near stream/lake areas where the unsaturated zone is thin. A diverse data set, collected from 1992 to 2007 for the Trout Lake WEBB project and the co-located and NSF-funded North Temperate Lakes LTER project, includes snowpack, solar radiation, potential evapotranspiration, lake levels, groundwater levels, and streamflow. The timeseries processing software TSPROC (Doherty 2003) was used to distill the large time series data set to a smaller set of observations and summary statistics that captured the salient hydrologic information. The timeseries processing reduced hundreds of thousands of observations to less than 5,000. Model calibration included specific predictions for several lakes in the study area using the PEST parameter estimation suite of software (Doherty 2007). The calibrated model was used to simulate the hydrologic response in the study lakes to a variety of climate change scenarios culled from the IPCC Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Solomon et al. 2007). Results from the simulations indicate climate change could result in substantial changes to the lake levels and components of the hydrologic budget of a seepage lake in the flow system. For a drainage lake lower in the flow system, the impacts of climate change are diminished.
Development of Joint Climate and Discharge Projections for the International Rhine River Basin - the CHR RheinBlick2050 Project

NASA Astrophysics Data System (ADS)

Görgen, K.; Pfister, L.

2008-12-01

The anticipated climate change will lead to modified hydro-meteorological regimes that influence discharge behaviour and hydraulics of rivers. This has variable impacts on managed (anthropogenic) and unmanaged (natural) systems, depending on their sensitivity and vulnerability (ecology, economy, infrastructure, transport, energy production, water management, etc.). Decision makers in these contexts need adequate adaptation strategies to minimize adverse effects of climate change, i.e. an improved knowledge on the potential impacts including uncertainties means an extension of the informed options open to users. The goal of the highly applied study presented here is the development of joint, consistent climate and discharge projections for the international Rhine River catchments (Switzerland, France, Germany, Netherlands) in order to assess future changes of hydro-meteorological regimes in the meso- and macroscale Rhine River catchments and to derive and improve the understanding of such impacts on hydrologic and hydraulic processes. The RheinBlick2050 project is an international effort initiated by the International Commission for the Hydrology of the Rhine Basin (CHR) in close cooperation with the International Commission for the Protection of the Rhine. The core experiment design foresees a data-synthesis, multi-model approach where (transient) (bias- corrected) regional climate change projections are used as forcing data for existing calibrated hydrological (and hydraulic) models at a daily temporal resolution over mesoscale catchments of the Rhine River. Mainly for validation purposes, hydro-meteorological observations from national weather services are compiled into a new consistent 5 km x 5 km reference dataset from 1961 to 2005. RCM data are mainly used from the ENSEMBLES project and other existing dynamical downscaling model runs to derive probabilistic ensembles and thereby also access uncertainties on a regional scale. A benchmarking is helping to identify those atmospheric forcing data that ideally suit the needs for the subsequent hydrological model runs with the LARSIM and HBV models and evaluate those simulations too. As a result, usable information and quantifiable statements (e.g. extreme value statistics, uncertainty assessment, validation), that might form the basis for further planning or policy relevant decisions, are to be derived. Our analyses are highly influenced by the requirements of the potential users and stakeholders from government agencies who shall make use of the data and results. Here we present first results of the application of the complete data processing and modelling chain towards discharge projections on a subset of input data, albeit still without any bias correction applied to the meteorological forcing data.
Research on Multi Hydrological Models Applicability and Modelling Data Uncertainty Analysis for Flash Flood Simulation in Hilly Area

NASA Astrophysics Data System (ADS)

Ye, L.; Wu, J.; Wang, L.; Song, T.; Ji, R.

2017-12-01

Flooding in small-scale watershed in hilly area is characterized by short time periods and rapid rise and recession due to the complex underlying surfaces, various climate type and strong effect of human activities. It is almost impossible for a single hydrological model to describe the variation of flooding in both time and space accurately for all the catchments in hilly area because the hydrological characteristics can vary significantly among different catchments. In this study, we compare the performance of 5 hydrological models with varying degrees of complexity for simulation of flash flood for 14 small-scale watershed in China in order to find the relationship between the applicability of the hydrological models and the catchments characteristics. Meanwhile, given the fact that the hydrological data is sparse in hilly area, the effect of precipitation data, DEM resolution and their interference on the uncertainty of flood simulation is also illustrated. In general, the results showed that the distributed hydrological model (HEC-HMS in this study) performed better than the lumped hydrological models. Xinajiang and API models had good simulation for the humid catchments when long-term and continuous rainfall data is provided. Dahuofang model can simulate the flood peak well while the runoff generation module is relatively poor. In addition, the effect of diverse modelling data on the simulations is not simply superposed, and there is a complex interaction effect among different modelling data. Overall, both the catchment hydrological characteristics and modelling data situation should be taken into consideration in order to choose the suitable hydrological model for flood simulation for small-scale catchment in hilly area.
Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models

USGS Publications Warehouse

Rakovec, O.; Hill, Mary C.; Clark, M.P.; Weerts, A. H.; Teuling, A. J.; Uijlenhoet, R.

2014-01-01

This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based “local” methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative “bucket-style” hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models.
Climatic impact of Amazon deforestation - a mechanistic model study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ning Zeng; Dickinson, R.E.; Xubin Zeng

1996-04-01

Recent general circulation model (GCM) experiments suggest a drastic change in the regional climate, especially the hydrological cycle, after hypothesized Amazon basinwide deforestation. To facilitate the theoretical understanding os such a change, we develop an intermediate-level model for tropical climatology, including atmosphere-land-ocean interaction. The model consists of linearized steady-state primitive equations with simplified thermodynamics. A simple hydrological cycle is also included. Special attention has been paid to land-surface processes. It generally better simulates tropical climatology and the ENSO anomaly than do many of the previous simple models. The climatic impact of Amazon deforestation is studied in the context of thismore » model. Model results show a much weakened Atlantic Walker-Hadley circulation as a result of the existence of a strong positive feedback loop in the atmospheric circulation system and the hydrological cycle. The regional climate is highly sensitive to albedo change and sensitive to evapotranspiration change. The pure dynamical effect of surface roughness length on convergence is small, but the surface flow anomaly displays intriguing features. Analysis of the thermodynamic equation reveals that the balance between convective heating, adiabatic cooling, and radiation largely determines the deforestation response. Studies of the consequences of hypothetical continuous deforestation suggest that the replacement of forest by desert may be able to sustain a dry climate. Scaling analysis motivated by our modeling efforts also helps to interpret the common results of many GCM simulations. When a simple mixed-layer ocean model is coupled with the atmospheric model, the results suggest a 1{degrees}C decrease in SST gradient across the equatorial Atlantic Ocean in response to Amazon deforestation. The magnitude depends on the coupling strength. 66 refs., 16 figs., 4 tabs.« less
Dependence of Wetland Vegetation on Hydrological Regime in a Large Floodplain Lake (Poyang Lake) in the Middle Yangtze River

NASA Astrophysics Data System (ADS)

Zhang, Q.; Tan, Z.; Xu, X.

2017-12-01

Exemplified in the Yangtze River floodplain lake, Poyang Lake, investigations were carried out to examine the dependence of vegetation on hydrological variables. The Lake is one of the few lakes that remain naturally connected to the Yangtze River. The Lake surface expanses to 4000 km2 in wet seasons, and reduces to less than 1000 km2 in dry seasons, creating some 3000 km2 vital wetland habitats for many animals. Remote sensing was used to obtain the spatial distribution of wetland vegetations. A lake hydrodynamic model using MIKE 21 was employed to determine the variability of wetland inundation. In-situ high time frequency observations of climate, soil moisture, and groundwater depth were also conducted in a typical wetland transect of 1 km long. Vegetations were sampled periodically to obtain species composition, diversity and biomass. Results showed that the spatial distribution of vegetation highly depended on the inundation duration and depth. Optimal hydrological variables existed for the typical vegetations in Poyang Lake wetland. Numerical simulations using HYDRUS-1D further demonstrated that both groundwater depth and soil moisture had significant effects on the growth of vegetation and the water demand in terms of transpiration, even in a wet climate zone such as middle Yangtze River. It was found that the optimal groundwater depths existed for both above- and belowground biomass. Simulation scenarios indicated that climate changes and human modification of hydrology would affect the water usage of vegetation and may cause a strategic adaptation of the vegetation to the stressed hydrological conditions. The study revealed new knowledge on the high dependence of wetland vegetation on both surface water regime and groundwater depths, in wet climate zone. Outcomes of this study may provide support for an integrated management of balancing water resources development and wetland sustainability maintenance in Poyang Lake, and other floodplain wetlands, with strong natural and human interferences.

Development of efficient and cost-effective distributed hydrological modeling tool MWEasyDHM based on open-source MapWindow GIS

NASA Astrophysics Data System (ADS)

Lei, Xiaohui; Wang, Yuhui; Liao, Weihong; Jiang, Yunzhong; Tian, Yu; Wang, Hao

2011-09-01

Many regions are still threatened with frequent floods and water resource shortage problems in China. Consequently, the task of reproducing and predicting the hydrological process in watersheds is hard and unavoidable for reducing the risks of damage and loss. Thus, it is necessary to develop an efficient and cost-effective hydrological tool in China as many areas should be modeled. Currently, developed hydrological tools such as Mike SHE and ArcSWAT (soil and water assessment tool based on ArcGIS) show significant power in improving the precision of hydrological modeling in China by considering spatial variability both in land cover and in soil type. However, adopting developed commercial tools in such a large developing country comes at a high cost. Commercial modeling tools usually contain large numbers of formulas, complicated data formats, and many preprocessing or postprocessing steps that may make it difficult for the user to carry out simulation, thus lowering the efficiency of the modeling process. Besides, commercial hydrological models usually cannot be modified or improved to be suitable for some special hydrological conditions in China. Some other hydrological models are open source, but integrated into commercial GIS systems. Therefore, by integrating hydrological simulation code EasyDHM, a hydrological simulation tool named MWEasyDHM was developed based on open-source MapWindow GIS, the purpose of which is to establish the first open-source GIS-based distributed hydrological model tool in China by integrating modules of preprocessing, model computation, parameter estimation, result display, and analysis. MWEasyDHM provides users with a friendly manipulating MapWindow GIS interface, selectable multifunctional hydrological processing modules, and, more importantly, an efficient and cost-effective hydrological simulation tool. The general construction of MWEasyDHM consists of four major parts: (1) a general GIS module for hydrological analysis, (2) a preprocessing module for modeling inputs, (3) a model calibration module, and (4) a postprocessing module. The general GIS module for hydrological analysis is developed on the basis of totally open-source GIS software, MapWindow, which contains basic GIS functions. The preprocessing module is made up of three submodules including a DEM-based submodule for hydrological analysis, a submodule for default parameter calculation, and a submodule for the spatial interpolation of meteorological data. The calibration module contains parallel computation, real-time computation, and visualization. The postprocessing module includes model calibration and model results spatial visualization using tabular form and spatial grids. MWEasyDHM makes it possible for efficient modeling and calibration of EasyDHM, and promises further development of cost-effective applications in various watersheds.
Multi-frequency electrical and electromagnetic measurements for imaging water flows: application to catchment and landslide hydrology.

NASA Astrophysics Data System (ADS)

Lajaunie, Myriam; Sailhac, Pascal; Malet, Jean-Philippe; Larnier, Hugo; Gance, Julien; Gautier, Stéphanie; Pierret, Marie-Claire

2017-04-01

Imaging water flows in mountainous watersheds is a difficult task, not only because of the topography and the dimensions of the existing structures, but also because the soils and rocks consist of unsaturated porous and heterogeneous fractured media, leading to multi-scale water-flow properties. In addition, these properties can change in time, in relation to temperature, rainfall and biological forcings. Electrical properties are relevant proxies of the subsurface hydrological properties. In order to image water flows, we consider measurements of the complex electrical conductivity (conduction and polarization/chargeability effects) which translate into a frequency dependance of the conductivity at the sample scale. We further discuss the combined use of electromagnetic (CS-AMT) and electric (DC and IP) measurements at the slope scale. The solving of processing, calibration and modelling issues allows the estimation of hydrological properties (i.e. permeability, soil humidity) giving master constraints for slope-scale hydrological modelling. We illustrate the application of these methods for the identification of the hydrological role of weathered structures of granitic catchments (e.g. Strengbach, Vosges mountains, ca. 80 km from Strasbourg, North East France) where new AMT processing has been developed in the AMT dead band to improve DC electrical imaging. We also illustrate the use of these methods to document the seasonal regime of the groundwater of the Lodève landslide (unstable slope located at Pégairolles, foot of the Cévennes mountain, ca. 80 km from Montpellier, South of France) where a new detailed time-lapse DC and IP setup (surface and borehole) is being tested. The works are supported by the research projects HYDROCRISZTO and HYDROSLIDE, and the large infrastructure project CRITEX.
Groundwater discharge and hydrologic partition of the lakes in desert environment: Insights from stable 18O/2H and radium isotopes

NASA Astrophysics Data System (ADS)

Luo, Xin; Jiao, Jiu Jimmy; Wang, Xu-sheng; Liu, Kun; Lian, Ergang; Yang, Shouye

2017-03-01

Studies of isotope characteristics of lake water in a desert can provide important information on groundwater discharge and hydrologic partition of the lakes in the desert. This paper presents the investigation of 18O and 2H stable isotopes and radiogenic radium of different water endmembers in three representative lakes of Badain-E, Badain-W and Sumujilin-S in the Badain Jaran Desert (BJD), the fourth largest desert in the world. A stable 18O and 2H isotopic buildup model is constructed to classify the hydrologic conditions of the desert lakes by estimating the ratio between groundwater discharge rate (Fin) and lake surface evaporation (E). Then the radium mass balance models are developed to quantify Fin. Based on the obtained Fin/E and Fin, Badain-E, Badain-W and Sumujilin-S are classified as flowing through, terminal and desiccating lakes, respectively, and their hydrologic partition is obtained. The groundwater discharge rate of Badain-E, Badain-W and Sumujilin-S, is estimated to be 8-10 mm d-1, 4-5 mm d-1, and 7-8 mm d-1, respectively. The total groundwater discharge to the lake areas in the BJD is about 1.68 × 105 m3 d-1. The flow-through condition explains the existence of the fresh lakes, while the terminal and desiccating conditions lead to the lake salinization over time. This study represents the first attempt to couple both stable and radium isotopic approaches to investigate the groundwater discharge and hydrologic partition of desert lakes in the BJD and is instructional to lake studies in other deserts in the world.
QUAL-NET, a high temporal-resolution eutrophication model for large hydrographic networks

NASA Astrophysics Data System (ADS)

Minaudo, Camille; Curie, Florence; Jullian, Yann; Gassama, Nathalie; Moatar, Florentina

2018-04-01

To allow climate change impact assessment of water quality in river systems, the scientific community lacks efficient deterministic models able to simulate hydrological and biogeochemical processes in drainage networks at the regional scale, with high temporal resolution and water temperature explicitly determined. The model QUALity-NETwork (QUAL-NET) was developed and tested on the Middle Loire River Corridor, a sub-catchment of the Loire River in France, prone to eutrophication. Hourly variations computed efficiently by the model helped disentangle the complex interactions existing between hydrological and biological processes across different timescales. Phosphorus (P) availability was the most constraining factor for phytoplankton development in the Loire River, but simulating bacterial dynamics in QUAL-NET surprisingly evidenced large amounts of organic matter recycled within the water column through the microbial loop, which delivered significant fluxes of available P and enhanced phytoplankton growth. This explained why severe blooms still occur in the Loire River despite large P input reductions since 1990. QUAL-NET could be used to study past evolutions or predict future trajectories under climate change and land use scenarios.
Effect of spatial organisation behaviour on upscaling the overland flow formation in an arable land

NASA Astrophysics Data System (ADS)

Silasari, Rasmiaditya; Blöschl, Günter

2014-05-01

Overland flow during rainfall events on arable land is important to investigate as it affects the land erosion process and water quality in the river. The formation of overland flow may happen through different ways (i.e. Hortonian overland flow, saturation excess overland flow) which is influenced by the surface and subsurface soil characteristics (i.e. land cover, soil infiltration rate). As the soil characteristics vary throughout the entire catchment, it will form distinct spatial patterns with organised or random behaviour. During the upscaling of hydrological processes from plot to catchment scale, this behaviour will become substantial since organised patterns will result in higher spatial connectivity and thus higher conductivity. However, very few of the existing studies explicitly address this effect of spatial organisations of the patterns in upscaling the hydrological processes to the catchment scale. This study will assess the upscaling of overland flow formation with concerns of spatial organisation behaviour of the patterns by application of direct field observations under natural conditions using video camera and soil moisture sensors and investigation of the underlying processes using a physical-based hydrology model. The study area is a Hydrological Open Air Laboratory (HOAL) located at Petzenkirchen, Lower Austria. It is a 64 ha catchment with land use consisting of arable land (87%), forest (6%), pasture (5%) and paved surfaces (2%). A video camera is installed 7m above the ground on a weather station mast in the middle of the arable land to monitor the overland flow patterns during rainfall events in a 2m x 6m plot scale. Soil moisture sensors with continuous measurement at different depth (5, 10, 20 and 50cm) are installed at points where the field is monitored by the camera. The patterns of overland flow formation and subsurface flow state at the plot scale will be generated using a coupled surface-subsurface flow physical-based hydrology model. The observation data will be assimilated into the model to verify the corresponding processes between surface and subsurface flow during the rainfall events. The patterns of conductivity then will be analyzed at catchment scale using the spatial stochastic analysis based on the classification of soil characteristics of the entire catchment. These patterns of conductivity then will be applied in the model at catchment scale to see how the organisational behaviour can affect the spatial connectivity of the hydrological processes and the results of the catchment response. A detailed modelling of the underlying processes in the physical-based model will allow us to see the direct effect of the spatial connectivity to the occurring surface and subsurface flow. This will improve the analysis of the effect of spatial organisations of the patterns in upscaling the hydrological processes from plot to catchment scale.
Development of a distributed biosphere hydrological model and its evaluation with the Southern Great Plains Experiments (SGP97 and SGP99)

USDA-ARS?s Scientific Manuscript database

A distributed biosphere hydrological model, the so called water and energy budget-based distributed hydrological model (WEB-DHM), has been developed by fully coupling a biosphere scheme (SiB2) with a geomorphology-based hydrological model (GBHM). SiB2 describes the transfer of turbulent fluxes (ener...
Hydrological excitation of polar motion by different variables of the GLDAS models

NASA Astrophysics Data System (ADS)

Wińska, Małgorzata; Nastula, Jolanta

Continental hydrological loading, by land water, snow, and ice, is an element that is strongly needed for a full understanding of the excitation of polar motion. In this study we compute different estimations of hydrological excitation functions of polar motion (Hydrological Angular Momentum - HAM) using various variables from the Global Land Data Assimilation System (GLDAS) models of land hydrosphere. The main aim of this study is to show the influence of different variables for example: total evapotranspiration, runoff, snowmelt, soil moisture to polar motion excitations in annual and short term scale. In our consideration we employ several realizations of the GLDAS model as: GLDAS Common Land Model (CLM), GLDAS Mosaic Model, GLDAS National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic Research Lab Model (Noah), GLDAS Variable Infiltration Capacity (VIC) Model. Hydrological excitation functions of polar motion, both global and regional, are determined by using selected variables of these GLDAS realizations. First we compare a timing, spectra and phase diagrams of different regional and global HAMs with each other. Next, we estimate, the hydrological signal in geodetically observed polar motion excitation by subtracting the atmospheric -- AAM (pressure + wind) and oceanic -- OAM (bottom pressure + currents) contributions. Finally, the hydrological excitations are compared to these hydrological signal in observed polar motion excitation series. The results help us understand which variables of considered hydrological models are the most important for the polar motion excitation and how well we can close polar motion excitation budget in the seasonal and inter-annual spectral ranges.
Reactive iron transport in an acidic mountain stream in Summit County, Colorado: A hydrologic perspective

USGS Publications Warehouse

McKnight, Diane M.; Bencala, K.E.

1989-01-01

A pH perturbation experiment was conducted in an acidic, metal-enriched, mountain stream to identify relative rates of chemical and hydrologic processes as they influence iron transport. During the experiment the pH was lowered from 4.2 to 3.2 for three hours by injection of sulfuric acid. Amorphous iron oxides are abundant on the streambed, and dissolution and photoreduction reactions resulted in a rapid increase in the dissolved iron concentration. The increase occurred simultaneously with the decrease in pH. Ferrous iron was the major aqueous iron species. The changes in the iron concentration during the experiment indicate that variation exists in the solubility properties of the hydrous iron oxides on the streambed with dissolution of at least two compartments of hydrous iron oxides contributing to the iron pulse. Spatial variations of the hydrologic properties along the stream were quantified by simulating the transport of a coinjected tracer, lithium. A simulation of iron transport, as a conservative solute, indicated that hydrologie transport had a significant role in determining downstream changes in the iron pulse. The rapidity of the changes in iron concentration indicates that a model based on dynamic equilibrium may be adequate for simulating iron transport in acid streams. A major challenge for predictive solute transport models of geochemical processes may be due to substantial spatial and seasonal variations in chemical properties of the reactive hydrous oxides in such streams, and in the physical and hydrologic properties of the stream. ?? 1989.
Examining dynamic interactions among experimental factors influencing hydrologic data assimilation with the ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Wang, S.; Huang, G. H.; Baetz, B. W.; Cai, X. M.; Ancell, B. C.; Fan, Y. R.

2017-11-01

The ensemble Kalman filter (EnKF) is recognized as a powerful data assimilation technique that generates an ensemble of model variables through stochastic perturbations of forcing data and observations. However, relatively little guidance exists with regard to the proper specification of the magnitude of the perturbation and the ensemble size, posing a significant challenge in optimally implementing the EnKF. This paper presents a robust data assimilation system (RDAS), in which a multi-factorial design of the EnKF experiments is first proposed for hydrologic ensemble predictions. A multi-way analysis of variance is then used to examine potential interactions among factors affecting the EnKF experiments, achieving optimality of the RDAS with maximized performance of hydrologic predictions. The RDAS is applied to the Xiangxi River watershed which is the most representative watershed in China's Three Gorges Reservoir region to demonstrate its validity and applicability. Results reveal that the pairwise interaction between perturbed precipitation and streamflow observations has the most significant impact on the performance of the EnKF system, and their interactions vary dynamically across different settings of the ensemble size and the evapotranspiration perturbation. In addition, the interactions among experimental factors vary greatly in magnitude and direction depending on different statistical metrics for model evaluation including the Nash-Sutcliffe efficiency and the Box-Cox transformed root-mean-square error. It is thus necessary to test various evaluation metrics in order to enhance the robustness of hydrologic prediction systems.
The impact of green roof ageing on substrate characteristics and hydrological performance

NASA Astrophysics Data System (ADS)

De-Ville, Simon; Menon, Manoj; Jia, Xiaodong; Reed, George; Stovin, Virginia

2017-04-01

Green roofs contribute to stormwater management through the retention of rainfall and the detention of runoff. However, there is very limited knowledge concerning the evolution of green roof hydrological performance with system age. This study presents a non-invasive technique which allows for repeatable determination of key substrate characteristics over time, and evaluates the impact of observed substrate changes on hydrological performance. The physical properties of 12 green roof substrate cores have been evaluated using non-invasive X-ray microtomography (XMT) imaging. The cores comprised three replicates of two contrasting substrate types at two different ages: unused virgin samples; and 5-year-old samples from existing green roof test beds. Whilst significant structural differences (density, pore and particle sizes, tortuosity) between virgin and aged samples of a crushed brick substrate were observed, these differences did not significantly affect hydrological characteristics (maximum water holding capacity and saturated hydraulic conductivity). A contrasting substrate based upon a light expanded clay aggregate experienced increases in the number of fine particles and pores over time, which led to increases in maximum water holding capacity of 7%. In both substrates, the saturated hydraulic conductivity estimated from the XMT images was lower in aged compared with virgin samples. Comparisons between physically-derived and XMT-derived substrate hydrological properties showed that similar values and trends in the data were identified, confirming the suitability of the non-invasive XMT technique for monitoring changes in engineered substrates over time. The observed effects of ageing on hydrological performance were modelled as two distinct hydrological processes, retention and detention. Retention performance was determined via a moisture-flux model using physically-derived values of virgin and aged maximum water holding capacity. Increased water holding capacity with age increases the potential for retention performance. However, seasonal variations in retention performance greatly exceed those associated with the observed age-related increases in water holding capacity (+72% vs +7% respectively). Detention performance was determined via an unsaturated-flow finite element model, using van Genuchten parameters and XMT-derived values of saturated hydraulic conductivity. Reduced saturated hydraulic conductivity increases detention performance. For a 1-hour 30-year design storm, the peak runoff was found to be 33% lower for the aged brick-based substrate compared with its virgin counterpart.
The hydrological cycle in the high Pamir Mountains: how temperature and seasonal precipitation distribution influence stream flow in the Gunt catchment, Tajikistan

NASA Astrophysics Data System (ADS)

Pohl, E.; Knoche, M.; Gloaguen, R.; Andermann, C.; Krause, P.

2014-12-01

Complex climatic interactions control hydrological processes in high mountains that in their turn regulate the erosive forces shaping the relief. To unravel the hydrological cycle of a glaciated watershed (Gunt River) considered representative of the Pamirs' hydrologic regime we developed a remote sensing-based approach. At the boundary between two distinct climatic zones dominated by Westerlies and Indian summer monsoon, the Pamir is poorly instrumented and only a few in situ meteorological and hydrological data are available. We adapted a suitable conceptual distributed hydrological model (J2000g). Interpolations of the few available in situ data are inadequate due to strong, relief induced, spatial heterogeneities. Instead we use raster data, preferably from remote sensing sources depending on availability and validation. We evaluate remote sensing-based precipitation and temperature products. MODIS MOD11 surface temperatures show good agreement with in situ data, perform better than other products and represent a good proxy for air temperatures. For precipitation we tested remote sensing products as well as the HAR10 climate model data and the interpolation-based APHRODITE dataset. All products show substantial differences both in intensity and seasonal distribution with in-situ data. Despite low resolutions, the datasets are able to sustain high model efficiencies (NSE ≥0.85). In contrast to neighbouring regions in the Himalayas or the Hindukush, discharge is dominantly the product of snow and glacier melt and thus temperature is the essential controlling factor. 80% of annual precipitation is provided as snow in winter and spring contrasting peak discharges during summer. Hence, precipitation and discharge are negatively correlated and display complex hysteresis effects that allow to infer the effect of inter-annual climatic variability on river flow. We infer the existence of two subsurface reservoirs. The groundwater reservoir (providing 40% of annual discharge) recharges in spring and summer and releases slowly during fall and winter. A not fully constrained shallow reservoir with very rapid retention times buffers melt waters during spring and summer. This study highlights the importance of a better understanding of the hydrologic cycle to constrain natural hazards such as floods and landslides as well as water availability in the downstream areas. The negative glacier mass balance (-0.6 m w.e. yr-1) indicates glacier retreat, that will effect the currently 30% contribution of glacier melt to stream flow.
Using an Integrated Hydrologic-Economic Model to Develop Minimum Cost Water Supply Portfolios and Manage Supply Risk

NASA Astrophysics Data System (ADS)

Characklis, G. W.; Ramsey, J.

2004-12-01

Water scarcity has become a reality in many areas as a result of population growth, fewer available sources, and reduced tolerance for the environmental impacts of developing the new supplies that do exist. As a result, successfully managing future water supply risk will become more dependent on coordinating the use of existing resources. Toward that end, flexible supply strategies that can rapidly respond to hydrologic variability will provide communities with increasing economic advantages, particularly if the frequency of more extreme events (e.g., drought) increases due to global climate change. Markets for established commodities (e.g., oil, gas) often provide a framework for efficiently responding to changes in supply and demand. Water markets, however, have remained relatively crude, with most transactions involving permanent transfers and long regulatory processes. Recently, interest in the use of flexible short-term transfers (e.g., leases, options) has begun to motivate consideration of more sophisticated strategies for managing supply risk, strategies similar to those used in more mature markets. In this case, communities can benefit from some of the advantages that water enjoys over other commodities, in particular, the ability to accurately characterize the stochastic nature of supply and demand through hydrologic modeling. Hydrologic-economic models are developed for two different water scarce regions supporting active water markets: Edward Aquifer and Lower Rio Grande Valley. These models are used to construct portfolios of water supply transfers (e.g., permanent transfers, options, and spot leases) that minimize the cost of meeting a probabilistic reliability constraint. Real and simulated spot price distributions allow each type of transfer to be priced in a manner consistent with financial theory (e.g., Black-Scholes). Market simulations are integrated with hydrologic models such that variability in supply and demand are linked with price behavior. Decisions on when and how much water to lease (or exercise, in the case of options) are made on the basis of anticipatory rules based on the ratio of expected supply to expected demand, and are used to evaluate the economic consequences of a utilityAƒAøAøâ_sA¬Aøâ_zAøs attitude toward risk. The marginal cost of supply reliability is also explored by varying the water supply reliability constraint, an important consideration as the rising expense of new source development may encourage some communities to accept a nominal number of supply shortfalls. Results demonstrate how changes in the distribution of various transfer types within a portfolio can affect its cost and reliability. Results also suggest that substantial savings can be obtained through the use of market-based risk management strategies, with optimal portfolio costs averaging as much as 35 percent less than the costs of meeting reliability targets through the maintenance of firm capacity. Both the conceptual and modeling approach described in this work are likely to have increasing application as water scarcity continues to drive the search for more efficient approaches to water resource management.
Prediction of soil stability and erosion in semiarid regions using numerical hydrological model (MCAT) and airborne hyperspectral imagery

NASA Astrophysics Data System (ADS)

Brook, Anna; Wittenberg, Lea

2015-04-01

Long-term environmental monitoring is addressed to identify physical and biological changes and progresses taking place in the ecosystem. This basic action of landscape monitoring is an essential part of the systematic long-term surveillance, aiming to evaluate, assess and predict the spatial change and progresses. Indeed, it provides a context for wide range of diverse studies and research frameworks from regional or global scale. Spatial-temporal trends and changes at various scales (massive to less certain) require establishing consistent baseline data over time. One of the spatial cases of landscape monitoring is dedicated to soil formation and pedological progresses. It is previously acknowledged that changes in soil affect the functionality of the environment, so monitoring changes recently become important cause considerable resources in areas such as environmental management, sustainability services, and protecting the environment healthy. Given the above, it can be concluded that monitoring changes in the base for sustainable development. The hydrological response of bare soils and watersheds in semiarid regions to intense rainfall events is known to be complex due to multiply physical and structural impacts and feedbacks. As a result, the comprehensive evaluations of mathematical models including detailed consideration of uncertainties in the modeling of hydrological and environmental systems are of increasing importance. The presented method incorporates means of remote sensing data, hydrological and climate data and implementing dedicated and integrative Monte Carlo Analysis Toolbox (MCAT) model for semiarid region. Complexity of practical models to represent spatial systems requires an extensive understanding of the spatial phenomena, while providing realistic balance of sensitivity and corresponding uncertainty levels. Nowadays a large number of dedicated mathematical models applied to assess environmental hydrological process. Among the most promising models is the MCAT, which is a MATLAB library of visual and numerical analysis tools for the evaluation of hydrological and environmental models. The model applied in this paper presents an innovative infrastructural system for predicting soil stability and erosion impacts. This integrated model is applicable to mixed areas with spatially varying soil properties, landscape, and land-cover characteristics. Data from a semiarid site in southern Israel was used to evaluate the model and analyze fundamental erosion mechanisms. The findings estimate the sensitivity of the suggested model to the physical parameters and encourage the use of hyperspectral remote sensing imagery (HSI). The proposed model is integrated according to the following stages: 1. The soil texture, aggregation, soil moisture estimated via airborne HSI data, including soil surface clay and calcium carbonate erosions; 2. The mechanical stability of soil assessed via pedo-transfer function corresponding to load dependent changes in soil physical properties due to pre-compression stress (set of equations study shear strength parameters take into account soil texture, aggregation, soil moisture and ecological soil variables); 3. The precipitation-related runoff model program (RMP) satisfactorily reproduces the observed seasonal mean and variation of surface runoff for the current climate simulation; 4. The Monte Carlo Analysis Toolbox (MCAT), a library of visual and numerical analysis tools for the evaluation of hydrological and environmental models, is proposed as a tool for integrate all the approaches to an applicable model. The presented model overcomes the limitations of existing modeling methods by integrating physical data produced via HSI and yet stays generic in terms of space and time independency.
Lowering the Barrier for Standards-Compliant and Discoverable Hydrological Data Publication

NASA Astrophysics Data System (ADS)

Kadlec, J.

2013-12-01

The growing need for sharing and integration of hydrological and climate data across multiple organizations has resulted in the development of distributed, services-based, standards-compliant hydrological data management and data hosting systems. The problem with these systems is complicated set-up and deployment. Many existing systems assume that the data publisher has remote-desktop access to a locally managed server and experience with computer network setup. For corporate websites, shared web hosting services with limited root access provide an inexpensive, dynamic web presence solution using the Linux, Apache, MySQL and PHP (LAMP) software stack. In this paper, we hypothesize that a webhosting service provides an optimal, low-cost solution for hydrological data hosting. We propose a software architecture of a standards-compliant, lightweight and easy-to-deploy hydrological data management system that can be deployed on the majority of existing shared internet webhosting services. The architecture and design is validated by developing Hydroserver Lite: a PHP and MySQL-based hydrological data hosting package that is fully standards-compliant and compatible with the Consortium of Universities for Advancement of Hydrologic Sciences (CUAHSI) hydrologic information system. It is already being used for management of field data collection by students of the McCall Outdoor Science School in Idaho. For testing, the Hydroserver Lite software has been installed on multiple different free and low-cost webhosting sites including Godaddy, Bluehost and 000webhost. The number of steps required to set-up the server is compared with the number of steps required to set-up other standards-compliant hydrologic data hosting systems including THREDDS, IstSOS and MapServer SOS.
Data-Driven Model Uncertainty Estimation in Hydrologic Data Assimilation

NASA Astrophysics Data System (ADS)

Pathiraja, S.; Moradkhani, H.; Marshall, L.; Sharma, A.; Geenens, G.

2018-02-01

The increasing availability of earth observations necessitates mathematical methods to optimally combine such data with hydrologic models. Several algorithms exist for such purposes, under the umbrella of data assimilation (DA). However, DA methods are often applied in a suboptimal fashion for complex real-world problems, due largely to several practical implementation issues. One such issue is error characterization, which is known to be critical for a successful assimilation. Mischaracterized errors lead to suboptimal forecasts, and in the worst case, to degraded estimates even compared to the no assimilation case. Model uncertainty characterization has received little attention relative to other aspects of DA science. Traditional methods rely on subjective, ad hoc tuning factors or parametric distribution assumptions that may not always be applicable. We propose a novel data-driven approach (named SDMU) to model uncertainty characterization for DA studies where (1) the system states are partially observed and (2) minimal prior knowledge of the model error processes is available, except that the errors display state dependence. It includes an approach for estimating the uncertainty in hidden model states, with the end goal of improving predictions of observed variables. The SDMU is therefore suited to DA studies where the observed variables are of primary interest. Its efficacy is demonstrated through a synthetic case study with low-dimensional chaotic dynamics and a real hydrologic experiment for one-day-ahead streamflow forecasting. In both experiments, the proposed method leads to substantial improvements in the hidden states and observed system outputs over a standard method involving perturbation with Gaussian noise.
Modelling the effect of fire frequency on runoff and erosion in north-central Portugal using the revised Morgan-Morgan-Finney

NASA Astrophysics Data System (ADS)

Hosseini, Mohammadreza; Nunes, João Pedro; González Pelayo, Oscar; Keizer, Jan Jacob; Ritsema, Coen; Geissen, Violette

2017-04-01

Models can be valuable for foreseeing the hydrological effects of fires and to plan and execute post-fire management alternatives. In this study, the revised Morgan-Morgan-Finney (MMF) model was utilized to simulate runoff and soil erosion in recently burned maritime pine plantations with different fire regimes, in a wet Mediterranean area of north-central Portugal. The MMF model was adjusted for burned zones in order to accommodate seasonal patterns in runoff and soil erosion, attributed to changes in soil water repellency and vegetation recovery. The model was then assessed by applying it for a sum of 18 experimental micro-plots (0.25 m2) at 9 1x-burnt and 9 4x-burnt slopes, using both literature-based and calibrated parameters, with the collected data used to assess the robustness of each parameterization. The estimate of erosion was more exact than that of runoff, with a general Nash-Sutcliffe efficiency of 0.54. Slope angle and the soil's effective hydrological depth (which relies on upon vegetation and additionally crop cover) were found to be the primary parameters enhancing model results, and different hydrological depths were expected to separate between the two differentiating fire regimes. This relative analysis demonstrated that most existing benchmark parameters can be utilized to apply MMF in burnt pine regions with moderate severity to support post-fire management; however it also showed that further endeavours ought to concentrate on mapping soil depth and vegetation cover to enhance these simulations.
A Framework For Analysis Of Coastal Infrastructure Vunerabilty To Global Sea Level Rise

NASA Astrophysics Data System (ADS)

Obrien, P. S.; White, K. D.; Veatch, W.; Marzion, R.; Moritz, H.; Moritz, H. R.

2017-12-01

Recorded impacts of global sea rise on coastal water levels have been documented over the past 100 to 150 years. In the recent 40 years the assumption of hydrologic stationarity has been recognized as invalid. New coastal infrastructure designs must recognize the paradigm shift from hydrologic stationarity to non-stationarity in coastal hydrology. A framework for the evaluation of existing coastal infrastructure is proposed to effectively assess design vulnerability. Two data sets developed from existing structures are chosen to test a proposed framework for vunerabilty to global sea level rise, with the proposed name Climate Preparedness and Resilience Register (CPRR). The CPRR framework consists of four major elements; Datum Adjustment, Coastal Water Levels, Scenario Projections and Performance Thresholds.
System dynamics modeling of nitrogen removal in a stormwater infiltration basin with biosorption-activated media.

PubMed

Xuan, Zhemin; Chang, Ni-Bin; Wanielista, Martin P; Williams, Evan Shane

2013-07-01

Stormwater infiltration basins, one of the typical stormwater best management practices, are commonly constructed for surface water pollution control, flood mitigation, and groundwater restoration in rural or residential areas. These basins have soils with better infiltration capacity than the native soil; however, the ever-increasing contribution of nutrients to groundwater from stormwater due to urban expansion makes existing infiltration basins unable to meet groundwater quality criteria related to environmental sustainability and public health. This issue requires retrofitting current infiltration basins for flood control as well as nutrient control before the stormwater enters the groundwater. An existing stormwater infiltration basin in north-central Florida was selected, retrofitted, and monitored to identify subsurface physiochemical and biological processes during 2007-2010 to investigate nutrient control processes. This implementation in the nexus of contaminant hydrology and ecological engineering adopted amended soil layers packed with biosorption activated media (BAM; tire crumb, silt, clay, and sand) to perform nutrient removal in a partitioned forebay using a berm. This study presents an infiltration basin-nitrogen removal (IBNR) model, a system dynamics model that simulates nitrogen cycling in this BAM-based stormwater infiltration basin with respect to changing hydrologic conditions and varying dissolved nitrogen concentrations. Modeling outputs of IBNR indicate that denitrification is the biogeochemical indicator in the BAM layer that accounted for a loss of about one third of the total dissolved nitrogen mass input. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
An empirical perspective for understanding climate change impacts in Switzerland

USGS Publications Warehouse

Henne, Paul; Bigalke, Moritz; Büntgen, Ulf; Colombaroli, Daniele; Conedera, Marco; Feller, Urs; Frank, David; Fuhrer, Jürg; Grosjean, Martin; Heiri, Oliver; Luterbacher, Jürg; Mestrot, Adrien; Rigling, Andreas; Rössler, Ole; Rohr, Christian; Rutishauser, This; Schwikowski, Margit; Stampfli, Andreas; Szidat, Sönke; Theurillat, Jean-Paul; Weingartner, Rolf; Wilcke, Wolfgan; Tinner, Willy

2018-01-01

Planning for the future requires a detailed understanding of how climate change affects a wide range of systems at spatial scales that are relevant to humans. Understanding of climate change impacts can be gained from observational and reconstruction approaches and from numerical models that apply existing knowledge to climate change scenarios. Although modeling approaches are prominent in climate change assessments, observations and reconstructions provide insights that cannot be derived from simulations alone, especially at local to regional scales where climate adaptation policies are implemented. Here, we review the wealth of understanding that emerged from observations and reconstructions of ongoing and past climate change impacts in Switzerland, with wider applicability in Europe. We draw examples from hydrological, alpine, forest, and agricultural systems, which are of paramount societal importance, and are projected to undergo important changes by the end of this century. For each system, we review existing model-based projections, present what is known from observations, and discuss how empirical evidence may help improve future projections. A particular focus is given to better understanding thresholds, tipping points and feedbacks that may operate on different time scales. Observational approaches provide the grounding in evidence that is needed to develop local to regional climate adaptation strategies. Our review demonstrates that observational approaches should ideally have a synergistic relationship with modeling in identifying inconsistencies in projections as well as avenues for improvement. They are critical for uncovering unexpected relationships between climate and agricultural, natural, and hydrological systems that will be important to society in the future.
Evaluation of Hydrologic Simulations Developed Using Multi-Model Synthesis and Remotely-Sensed Data within a Portfolio of Calibration Strategies

NASA Astrophysics Data System (ADS)

Lafontaine, J.; Hay, L.; Markstrom, S. L.

2016-12-01

The United States Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the conterminous United States (CONUS). As many stream reaches in the CONUS are either not gaged, or are substantially impacted by water use or flow regulation, ancillary information must be used to determine reasonable parameter estimations for streamflow simulations. Hydrologic models for 1,576 gaged watersheds across the CONUS were developed to test the feasibility of improving streamflow simulations linking physically-based hydrologic models with remotely-sensed data products (i.e. snow water equivalent). Initially, the physically-based models were calibrated to measured streamflow data to provide a baseline for comparison across multiple calibration strategy tests. In addition, not all ancillary datasets are appropriate for application to all parts of the CONUS (e.g. snow water equivalent in the southeastern U.S., where snow is a rarity). As it is not expected that any one data product or model simulation will be sufficient for representing hydrologic behavior across the entire CONUS, a systematic evaluation of which data products improve hydrologic simulations for various regions across the CONUS was performed. The resulting portfolio of calibration strategies can be used to guide selection of an appropriate combination of modeled and measured information for hydrologic model development and calibration. In addition, these calibration strategies have been developed to be flexible so that new data products can be assimilated. This analysis provides a foundation to understand how well models work when sufficient streamflow data are not available and could be used to further inform hydrologic model parameter development for ungaged areas.

Development and comparison of Bayesian modularization method in uncertainty assessment of hydrological models

NASA Astrophysics Data System (ADS)

Li, L.; Xu, C.-Y.; Engeland, K.

2012-04-01

With respect to model calibration, parameter estimation and analysis of uncertainty sources, different approaches have been used in hydrological models. Bayesian method is one of the most widely used methods for uncertainty assessment of hydrological models, which incorporates different sources of information into a single analysis through Bayesian theorem. However, none of these applications can well treat the uncertainty in extreme flows of hydrological models' simulations. This study proposes a Bayesian modularization method approach in uncertainty assessment of conceptual hydrological models by considering the extreme flows. It includes a comprehensive comparison and evaluation of uncertainty assessments by a new Bayesian modularization method approach and traditional Bayesian models using the Metropolis Hasting (MH) algorithm with the daily hydrological model WASMOD. Three likelihood functions are used in combination with traditional Bayesian: the AR (1) plus Normal and time period independent model (Model 1), the AR (1) plus Normal and time period dependent model (Model 2) and the AR (1) plus multi-normal model (Model 3). The results reveal that (1) the simulations derived from Bayesian modularization method are more accurate with the highest Nash-Sutcliffe efficiency value, and (2) the Bayesian modularization method performs best in uncertainty estimates of entire flows and in terms of the application and computational efficiency. The study thus introduces a new approach for reducing the extreme flow's effect on the discharge uncertainty assessment of hydrological models via Bayesian. Keywords: extreme flow, uncertainty assessment, Bayesian modularization, hydrological model, WASMOD
On the Hydrologic Adjustment of Climate-Model Projections: The Potential Pitfall of Potential Evapotranspiration

USGS Publications Warehouse

Milly, Paul C.D.; Dunne, Krista A.

2011-01-01

Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement ("downscaling"), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median -11%) caused by the hydrologic model’s apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen–Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors’ findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climate-change impacts on water.
Design and Implementation of Hydrologic Process Knowledge-base Ontology: A case study for the Infiltration Process

NASA Astrophysics Data System (ADS)

Elag, M.; Goodall, J. L.

2013-12-01

Hydrologic modeling often requires the re-use and integration of models from different disciplines to simulate complex environmental systems. Component-based modeling introduces a flexible approach for integrating physical-based processes across disciplinary boundaries. Several hydrologic-related modeling communities have adopted the component-based approach for simulating complex physical systems by integrating model components across disciplinary boundaries in a workflow. However, it is not always straightforward to create these interdisciplinary models due to the lack of sufficient knowledge about a hydrologic process. This shortcoming is a result of using informal methods for organizing and sharing information about a hydrologic process. A knowledge-based ontology provides such standards and is considered the ideal approach for overcoming this challenge. The aims of this research are to present the methodology used in analyzing the basic hydrologic domain in order to identify hydrologic processes, the ontology itself, and how the proposed ontology is integrated with the Water Resources Component (WRC) ontology. The proposed ontology standardizes the definitions of a hydrologic process, the relationships between hydrologic processes, and their associated scientific equations. The objective of the proposed Hydrologic Process (HP) Ontology is to advance the idea of creating a unified knowledge framework for components' metadata by introducing a domain-level ontology for hydrologic processes. The HP ontology is a step toward an explicit and robust domain knowledge framework that can be evolved through the contribution of domain users. Analysis of the hydrologic domain is accomplished using the Formal Concept Approach (FCA), in which the infiltration process, an important hydrologic process, is examined. Two infiltration methods, the Green-Ampt and Philip's methods, were used to demonstrate the implementation of information in the HP ontology. Furthermore, a SPARQL service is provided for semantic-based querying of the ontology.
Hydrological threats to riparian wetlands of international importance - a global quantitative and qualitative analysis

NASA Astrophysics Data System (ADS)

Schneider, Christof; Flörke, Martina; De Stefano, Lucia; Petersen-Perlman, Jacob D.

2017-06-01

Riparian wetlands have been disappearing at an accelerating rate. Their ecological integrity as well as their vital ecosystem services for humankind depend on regular patterns of inundation and drying provided by natural flow regimes. However, river hydrology has been altered worldwide. Dams cause less variable flow regimes and water abstractions decrease the amount of flow so that ecologically important flood pulses are often reduced. Given growing population pressure and projected climate change, immediate action is required. However, the implementation of counteractive measures is often a complex task. This study develops a screening tool for assessing hydrological threats to riparian wetlands on global scales. The approach is exemplified on 93 Ramsar sites, many of which are located in transboundary basins. First, the WaterGAP3 hydrological modeling framework is used to quantitatively compare current and future modified flow regimes to reference flow conditions. In our simulations current water resource management seriously impairs riparian wetland inundation at 29 % of the analyzed sites. A further 8 % experience significantly reduced flood pulses. In the future, eastern Europe, western Asia, as well as central South America could be hotspots of further flow modifications due to climate change. Second, a qualitative analysis of the 93 sites determined potential impact on overbank flows resulting from planned or proposed dam construction projects. They take place in one-third of the upstream areas and are likely to impair especially wetlands located in South America, Asia, and the Balkan Peninsula. Third, based on the existing legal/institutional framework and water resource availability upstream, further qualitative analysis evaluated the capacity to preserve overbank flows given future streamflow changes due to dam construction and climate change. Results indicate hotspots of vulnerability exist, especially in northern Africa and the Persian Gulf.
Evaluating changes to reservoir rule curves using historical water-level data

USGS Publications Warehouse

Mower, Ethan; Miranda, Leandro E.

2013-01-01

Flood control reservoirs are typically managed through rule curves (i.e. target water levels) which control the storage and release timing of flood waters. Changes to rule curves are often contemplated and requested by various user groups and management agencies with no information available about the actual flood risk of such requests. Methods of estimating flood risk in reservoirs are not easily available to those unfamiliar with hydrological models that track water movement through a river basin. We developed a quantile regression model that uses readily available daily water-level data to estimate risk of spilling. Our model provided a relatively simple process for estimating the maximum applicable water level under a specific flood risk for any day of the year. This water level represents an upper-limit umbrella under which water levels can be operated in a variety of ways. Our model allows the visualization of water-level management under a user-specified flood risk and provides a framework for incorporating the effect of a changing environment on water-level management in reservoirs, but is not designed to replace existing hydrological models. The model can improve communication and collaboration among agencies responsible for managing natural resources dependent on reservoir water levels.
Virtual hydrology observatory: an immersive visualization of hydrology modeling

NASA Astrophysics Data System (ADS)

Su, Simon; Cruz-Neira, Carolina; Habib, Emad; Gerndt, Andreas

2009-02-01

The Virtual Hydrology Observatory will provide students with the ability to observe the integrated hydrology simulation with an instructional interface by using a desktop based or immersive virtual reality setup. It is the goal of the virtual hydrology observatory application to facilitate the introduction of field experience and observational skills into hydrology courses through innovative virtual techniques that mimic activities during actual field visits. The simulation part of the application is developed from the integrated atmospheric forecast model: Weather Research and Forecasting (WRF), and the hydrology model: Gridded Surface/Subsurface Hydrologic Analysis (GSSHA). Both the output from WRF and GSSHA models are then used to generate the final visualization components of the Virtual Hydrology Observatory. The various visualization data processing techniques provided by VTK are 2D Delaunay triangulation and data optimization. Once all the visualization components are generated, they are integrated into the simulation data using VRFlowVis and VR Juggler software toolkit. VR Juggler is used primarily to provide the Virtual Hydrology Observatory application with fully immersive and real time 3D interaction experience; while VRFlowVis provides the integration framework for the hydrologic simulation data, graphical objects and user interaction. A six-sided CAVETM like system is used to run the Virtual Hydrology Observatory to provide the students with a fully immersive experience.
Simulating hydrological processes of a typical small mountainous catchment in Tibetan Plateau

NASA Astrophysics Data System (ADS)

Xu, Y. P.; Bai, Z.; Fu, Q.; Pan, S.; Zhu, C.

2017-12-01

Water cycle of small watersheds with seasonal/permanent frozen soil and snow pack in Tibetan Plateau is seriously affected by climate change. The objective of this study is to find out how much and in what way the frozen soil and snow pack will influence the hydrology of small mountainous catchments in cold regions and how can the performance of simulation by a distributed hydrological model be improved. The Dong catchment, a small catchment located in Tibetan Plateau, is used as a case study. Two measurement stations are set up to collect basic meteorological and hydrological data for the modeling purpose. Annual and interannual variations of runoff indices are first analyzed based on historic data series. The sources of runoff in dry periods and wet periods are analyzed respectively. Then, a distributed hydrology soil vegetation model (DHSVM) is adopted to simulate the hydrological process of Dong catchment based on limited data set. Global sensitivity analysis is applied to help determine the important processes of the catchment. Based on sensitivity analysis results, the Epsilon-Dominance Non-Dominated Sorted Genetic Algorithm II (ɛ-NSGAII) is finally added into the hydrological model to calibrate the hydrological model in a multi-objective way and analyze the performance of DHSVM model. The performance of simulation is evaluated with several evaluation indices. The final results show that frozen soil and snow pack do play an important role in hydrological processes in cold mountainous region, in particular in dry periods without precipitation, while in wet periods precipitation is often the main source of runoff. The results also show that although the DHSVM hydrological model has the potential to model the hydrology well in small mountainous catchments with very limited data in Tibetan Plateau, the simulation of hydrology in dry periods is not very satisfactory due to the model's insufficiency in simulating seasonal frozen soil.
Improving National Water Modeling: An Intercomparison of two High-Resolution, Continental Scale Models, CONUS-ParFlow and the National Water Model

NASA Astrophysics Data System (ADS)

Tijerina, D.; Gochis, D.; Condon, L. E.; Maxwell, R. M.

2017-12-01

Development of integrated hydrology modeling systems that couple atmospheric, land surface, and subsurface flow is growing trend in hydrologic modeling. Using an integrated modeling framework, subsurface hydrologic processes, such as lateral flow and soil moisture redistribution, are represented in a single cohesive framework with surface processes like overland flow and evapotranspiration. There is a need for these more intricate models in comprehensive hydrologic forecasting and water management over large spatial areas, specifically the Continental US (CONUS). Currently, two high-resolution, coupled hydrologic modeling applications have been developed for this domain: CONUS-ParFlow built using the integrated hydrologic model ParFlow and the National Water Model that uses the NCAR Weather Research and Forecasting hydrological extension package (WRF-Hydro). Both ParFlow and WRF-Hydro include land surface models, overland flow, and take advantage of parallelization and high-performance computing (HPC) capabilities; however, they have different approaches to overland subsurface flow and groundwater-surface water interactions. Accurately representing large domains remains a challenge considering the difficult task of representing complex hydrologic processes, computational expense, and extensive data needs; both models have accomplished this, but have differences in approach and continue to be difficult to validate. A further exploration of effective methodology to accurately represent large-scale hydrology with integrated models is needed to advance this growing field. Here we compare the outputs of CONUS-ParFlow and the National Water Model to each other and with observations to study the performance of hyper-resolution models over large domains. Models were compared over a range of scales for major watersheds within the CONUS with a specific focus on the Mississippi, Ohio, and Colorado River basins. We use a novel set of approaches and analysis for this comparison to better understand differences in process and bias. This intercomparison is a step toward better understanding how much water we have and interactions between surface and subsurface. Our goal is to advance our understanding and simulation of the hydrologic system and ultimately improve hydrologic forecasts.
Forecasting seasonal hydrologic response in major river basins

NASA Astrophysics Data System (ADS)

Bhuiyan, A. M.

2014-05-01

Seasonal precipitation variation due to natural climate variation influences stream flow and the apparent frequency and severity of extreme hydrological conditions such as flood and drought. To study hydrologic response and understand the occurrence of extreme hydrological events, the relevant forcing variables must be identified. This study attempts to assess and quantify the historical occurrence and context of extreme hydrologic flow events and quantify the relation between relevant climate variables. Once identified, the flow data and climate variables are evaluated to identify the primary relationship indicators of hydrologic extreme event occurrence. Existing studies focus on developing basin-scale forecasting techniques based on climate anomalies in El Nino/La Nina episodes linked to global climate. Building on earlier work, the goal of this research is to quantify variations in historical river flows at seasonal temporal-scale, and regional to continental spatial-scale. The work identifies and quantifies runoff variability of major river basins and correlates flow with environmental forcing variables such as El Nino, La Nina, sunspot cycle. These variables are expected to be the primary external natural indicators of inter-annual and inter-seasonal patterns of regional precipitation and river flow. Relations between continental-scale hydrologic flows and external climate variables are evaluated through direct correlations in a seasonal context with environmental phenomenon such as sun spot numbers (SSN), Southern Oscillation Index (SOI), and Pacific Decadal Oscillation (PDO). Methods including stochastic time series analysis and artificial neural networks are developed to represent the seasonal variability evident in the historical records of river flows. River flows are categorized into low, average and high flow levels to evaluate and simulate flow variations under associated climate variable variations. Results demonstrated not any particular method is suited to represent scenarios leading to extreme flow conditions. For selected flow scenarios, the persistence model performance may be comparable to more complex multivariate approaches, and complex methods did not always improve flow estimation. Overall model performance indicates inclusion of river flows and forcing variables on average improve model extreme event forecasting skills. As a means to further refine the flow estimation, an ensemble forecast method is implemented to provide a likelihood-based indication of expected river flow magnitude and variability. Results indicate seasonal flow variations are well-captured in the ensemble range, therefore the ensemble approach can often prove efficient in estimating extreme river flow conditions. The discriminant prediction approach, a probabilistic measure to forecast streamflow, is also adopted to derive model performance. Results show the efficiency of the method in terms of representing uncertainties in the forecasts.
Information-Theoretic Benchmarking of Land Surface Models

NASA Astrophysics Data System (ADS)

Nearing, Grey; Mocko, David; Kumar, Sujay; Peters-Lidard, Christa; Xia, Youlong

2016-04-01

Benchmarking is a type of model evaluation that compares model performance against a baseline metric that is derived, typically, from a different existing model. Statistical benchmarking was used to qualitatively show that land surface models do not fully utilize information in boundary conditions [1] several years before Gong et al [2] discovered the particular type of benchmark that makes it possible to *quantify* the amount of information lost by an incorrect or imperfect model structure. This theoretical development laid the foundation for a formal theory of model benchmarking [3]. We here extend that theory to separate uncertainty contributions from the three major components of dynamical systems models [4]: model structures, model parameters, and boundary conditions describe time-dependent details of each prediction scenario. The key to this new development is the use of large-sample [5] data sets that span multiple soil types, climates, and biomes, which allows us to segregate uncertainty due to parameters from the two other sources. The benefit of this approach for uncertainty quantification and segregation is that it does not rely on Bayesian priors (although it is strictly coherent with Bayes' theorem and with probability theory), and therefore the partitioning of uncertainty into different components is *not* dependent on any a priori assumptions. We apply this methodology to assess the information use efficiency of the four land surface models that comprise the North American Land Data Assimilation System (Noah, Mosaic, SAC-SMA, and VIC). Specifically, we looked at the ability of these models to estimate soil moisture and latent heat fluxes. We found that in the case of soil moisture, about 25% of net information loss was from boundary conditions, around 45% was from model parameters, and 30-40% was from the model structures. In the case of latent heat flux, boundary conditions contributed about 50% of net uncertainty, and model structures contributed about 40%. There was relatively little difference between the different models. 1. G. Abramowitz, R. Leuning, M. Clark, A. Pitman, Evaluating the performance of land surface models. Journal of Climate 21, (2008). 2. W. Gong, H. V. Gupta, D. Yang, K. Sricharan, A. O. Hero, Estimating Epistemic & Aleatory Uncertainties During Hydrologic Modeling: An Information Theoretic Approach. Water Resources Research 49, 2253-2273 (2013). 3. G. S. Nearing, H. V. Gupta, The quantity and quality of information in hydrologic models. Water Resources Research 51, 524-538 (2015). 4. H. V. Gupta, G. S. Nearing, Using models and data to learn: A systems theoretic perspective on the future of hydrological science. Water Resources Research 50(6), 5351-5359 (2014). 5. H. V. Gupta et al., Large-sample hydrology: a need to balance depth with breadth. Hydrology and Earth System Sciences Discussions 10, 9147-9189 (2013).
Uncertainty in mixing models: a blessing in disguise?

NASA Astrophysics Data System (ADS)

Delsman, J. R.; Oude Essink, G. H. P.

2012-04-01

Despite the abundance of tracer-based studies in catchment hydrology over the past decades, relatively few studies have addressed the uncertainty associated with these studies in much detail. This uncertainty stems from analytical error, spatial and temporal variance in end-member composition, and from not incorporating all relevant processes in the necessarily simplistic mixing models. Instead of applying standard EMMA methodology, we used end-member mixing model analysis within a Monte Carlo framework to quantify the uncertainty surrounding our analysis. Borrowing from the well-known GLUE methodology, we discarded mixing models that could not satisfactorily explain sample concentrations and analyzed the posterior parameter set. This use of environmental tracers aided in disentangling hydrological pathways in a Dutch polder catchment. This 10 km2 agricultural catchment is situated in the coastal region of the Netherlands. Brackish groundwater seepage, originating from Holocene marine transgressions, adversely affects water quality in this catchment. Current water management practice is aimed at improving water quality by flushing the catchment with fresh water from the river Rhine. Climate change is projected to decrease future fresh water availability, signifying the need for a more sustainable water management practice and a better understanding of the functioning of the catchment. The end-member mixing analysis increased our understanding of the hydrology of the studied catchment. The use of a GLUE-like framework for applying the end-member mixing analysis not only quantified the uncertainty associated with the analysis, the analysis of the posterior parameter set also identified the existence of catchment processes otherwise overlooked.
Daily river flow prediction based on Two-Phase Constructive Fuzzy Systems Modeling: A case of hydrological - meteorological measurements asymmetry

NASA Astrophysics Data System (ADS)

Bou-Fakhreddine, Bassam; Mougharbel, Imad; Faye, Alain; Abou Chakra, Sara; Pollet, Yann

2018-03-01

Accurate daily river flow forecast is essential in many applications of water resources such as hydropower operation, agricultural planning and flood control. This paper presents a forecasting approach to deal with a newly addressed situation where hydrological data exist for a period longer than that of meteorological data (measurements asymmetry). In fact, one of the potential solutions to resolve measurements asymmetry issue is data re-sampling. It is a matter of either considering only the hydrological data or the balanced part of the hydro-meteorological data set during the forecasting process. However, the main disadvantage is that we may lose potentially relevant information from the left-out data. In this research, the key output is a Two-Phase Constructive Fuzzy inference hybrid model that is implemented over the non re-sampled data. The introduced modeling approach must be capable of exploiting the available data efficiently with higher prediction efficiency relative to Constructive Fuzzy model trained over re-sampled data set. The study was applied to Litani River in the Bekaa Valley - Lebanon by using 4 years of rainfall and 24 years of river flow daily measurements. A Constructive Fuzzy System Model (C-FSM) and a Two-Phase Constructive Fuzzy System Model (TPC-FSM) are trained. Upon validating, the second model has shown a primarily competitive performance and accuracy with the ability to preserve a higher day-to-day variability for 1, 3 and 6 days ahead. In fact, for the longest lead period, the C-FSM and TPC-FSM were able of explaining respectively 84.6% and 86.5% of the actual river flow variation. Overall, the results indicate that TPC-FSM model has provided a better tool to capture extreme flows in the process of streamflow prediction.
Coupled Global-Regional Climate Model Simulations of Future Changes in Hydrology over Central America

NASA Astrophysics Data System (ADS)

Oglesby, R. J.; Erickson, D. J.; Hernandez, J. L.; Irwin, D.

2005-12-01

Central America covers a relatively small area, but is topographically very complex, has long coast-lines, large inland bodies of water, and very diverse land cover which is both natural and human-induced. As a result, Central America is plagued by hydrologic extremes, especially major flooding and drought events, in a region where many people still barely manage to eke out a living through subsistence. Therefore, considerable concern exists about whether these extreme events will change, either in magnitude or in number, as climate changes in the future. To address this concern, we have used global climate model simulations of future climate change to drive a regional climate model centered on Central America. We use the IPCC `business as usual' scenario 21st century run made with the NCAR CCSM3 global model to drive the regional model MM5 at 12 km resolution. We chose the `business as usual' scenario to focus on the largest possible changes that are likely to occur. Because we are most interested in near-term changes, our simulations are for the years 2010, 2015, and 2025. A long `present-day run (for 2005) allows us to distinguish between climate variability and any signal due to climate change. Furthermore, a multi-year run with MM5 forced by NCEP reanalyses allows an assessment of how well the coupled global-regional model performs over Central America. Our analyses suggest that the coupled model does a credible job simulating the current climate and hydrologic regime, though lack of sufficient observations strongly complicates this comparison. The suite of model runs for the future years is currently nearing completion, and key results will be presented at the meeting.
Assessment of climate change impacts on meteorological and hydrological droughts in the Jucar River Basin

NASA Astrophysics Data System (ADS)

Marcos-Garcia, Patricia; Pulido-Velazquez, Manuel; Lopez-Nicolas, Antonio

2016-04-01

Extreme natural phenomena, and more specifically droughts, constitute a serious environmental, economic and social issue in Southern Mediterranean countries, common in the Mediterranean Spanish basins due to the high temporal and spatial rainfall variability. Drought events are characterized by their complexity, being often difficult to identify and quantify both in time and space, and an universally accepted definition does not even exist. This fact, along with future uncertainty about the duration and intensity of the phenomena on account of climate change, makes necessary increasing the knowledge about the impacts of climate change on droughts in order to design management plans and mitigation strategies. The present abstract aims to evaluate the impact of climate change on both meteorological and hydrological droughts, through the use of a generalization of the Standardized Precipitation Index (SPI). We use the Standardized Flow Index (SFI) to assess the hydrological drought, using flow time series instead of rainfall time series. In the case of the meteorological droughts, the Standardized Precipitation and Evapotranspiration Index (SPEI) has been applied to assess the variability of temperature impacts. In order to characterize climate change impacts on droughts, we have used projections from the CORDEX project (Coordinated Regional Climate Downscaling Experiment). Future rainfall and temperature time series for short (2011-2040) and medium terms (2041-2070) were obtained, applying a quantile mapping method to correct the bias of these time series. Regarding the hydrological drought, the Témez hydrological model has been applied to simulate the impacts of future temperature and rainfall time series on runoff and river discharges. It is a conceptual, lumped and a few parameters hydrological model. Nevertheless, it is necessary to point out the time difference between the meteorological and the hydrological droughts. The case study is the Jucar river basin (Spain), a highly regulated system with a share of 80% of water use for irrigated agriculture. The results show that the climate change would increase the historical drought impacts in the river basin. Acknowledgments The study has been supported by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) and European FEDER funds.
Using Gridded Snow Covered Area and Snow-Water Equivalence Spatial Data Sets to Improve Snow-Pack Depletion Simulation in a Continental Scale Hydrologic Model

NASA Astrophysics Data System (ADS)

Risley, J. C.; Tracey, J. A.; Markstrom, S. L.; Hay, L.

2014-12-01

Snow cover areal depletion curves were used in a continuous daily hydrologic model to simulate seasonal spring snowmelt during the period between maximum snowpack accumulation and total melt. The curves are defined as the ratio of snow-water equivalence (SWE) divided by the seasonal maximum snow-water equivalence (Ai) (Y axis) versus the percent snow cover area (SCA) (X axis). The slope of the curve can vary depending on local watershed conditions. Windy sparsely vegetated high elevation watersheds, for example, can have a steeper slope than lower elevation forested watersheds. To improve the accuracy of simulated runoff at ungaged watersheds, individual snow cover areal depletion curves were created for over 100,000 hydrologic response units (HRU) in the continental scale U.S. Geological Survey (USGS) National Hydrologic Model (NHM). NHM includes the same components of the USGS Precipitation-Runoff-Modeling System (PRMS), except it uses consistent land surface characterization and model parameterization across the U.S. continent. Weighted-mean daily time series of 1-kilometer gridded SWE, from Snow Data Assimilation System (SNODAS), and 500-meter gridded SCA, from Moderate Resolution Imaging Spectroradiometer (MODIS), for 2003-2014 were computed for each HRU using the USGS Geo Data Portal. Using a screening process, pairs of SWE/Ai and SCA from the snowmelt period of each year were selected. SCA values derived from imagery that did not have any cloud cover and were >0 and <100 percent were selected. Unrealistically low and high SCA values that were paired with high and low SWE/Ai ratios, respectively, were removed. Second order polynomial equations were then fit to the remaining pairs of SWE/Ai and SCA to create a unique curve for each HRU. Simulations comparing these new curves with an existing single default curve in NHM will be made to determine if there are significant improvements in runoff.
On the hydrologic adjustment of climate-model projections: The potential pitfall of potential evapotranspiration

USGS Publications Warehouse

Milly, P.C.D.; Dunne, K.A.

2011-01-01

Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement ("downscaling"), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median 211%) caused by the hydrologic model's apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen-Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors' findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climatechange impacts on water. Copyright ?? 2011, Paper 15-001; 35,952 words, 3 Figures, 0 Animations, 1 Tables.
Exploring the utility of real-time hydrologic data for landslide early warning

NASA Astrophysics Data System (ADS)

Mirus, B. B.; Smith, J. B.; Becker, R.; Baum, R. L.; Koss, E.

2017-12-01

Early warning systems can provide critical information for operations managers, emergency planners, and the public to help reduce fatalities, injuries, and economic losses due to landsliding. For shallow, rainfall-triggered landslides early warning systems typically use empirical rainfall thresholds, whereas the actual triggering mechanism involves the non-linear hydrological processes of infiltration, evapotranspiration, and hillslope drainage that are more difficult to quantify. Because hydrologic monitoring has demonstrated that shallow landslides are often preceded by a rise in soil moisture and pore-water pressures, some researchers have developed early warning criteria that attempt to account for these antecedent wetness conditions through relatively simplistic storage metrics or soil-water balance modeling. Here we explore the potential for directly incorporating antecedent wetness into landslide early warning criteria using recent landslide inventories and in-situ hydrologic monitoring near Seattle, WA, and Portland, OR. We use continuous, near-real-time telemetered soil moisture and pore-water pressure data measured within a few landslide-prone hillslopes in combination with measured and forecasted rainfall totals to inform easy-to-interpret landslide initiation thresholds. Objective evaluation using somewhat limited landslide inventories suggests that our new thresholds based on subsurface hydrologic monitoring and rainfall data compare favorably to the capabilities of existing rainfall-only thresholds for the Seattle area, whereas there are no established rainfall thresholds for the Portland area. This preliminary investigation provides a proof-of-concept for the utility of developing landslide early warning criteria in two different geologic settings using real-time subsurface hydrologic measurements from in-situ instrumentation.
Integrated Hydrographical Basin Management. Study Case - Crasna River Basin

NASA Astrophysics Data System (ADS)

Visescu, Mircea; Beilicci, Erika; Beilicci, Robert

2017-10-01

Hydrographical basins are important from hydrological, economic and ecological points of view. They receive and channel the runoff from rainfall and snowmelt which, when adequate managed, can provide fresh water necessary for water supply, irrigation, food industry, animal husbandry, hydrotechnical arrangements and recreation. Hydrographical basin planning and management follows the efficient use of available water resources in order to satisfy environmental, economic and social necessities and constraints. This can be facilitated by a decision support system that links hydrological, meteorological, engineering, water quality, agriculture, environmental, and other information in an integrated framework. In the last few decades different modelling tools for resolving problems regarding water quantity and quality were developed, respectively water resources management. Watershed models have been developed to the understanding of water cycle and pollution dynamics, and used to evaluate the impacts of hydrotechnical arrangements and land use management options on water quantity, quality, mitigation measures and possible global changes. Models have been used for planning monitoring network and to develop plans for intervention in case of hydrological disasters: floods, flash floods, drought and pollution. MIKE HYDRO Basin is a multi-purpose, map-centric decision support tool for integrated hydrographical basin analysis, planning and management. MIKE HYDRO Basin is designed for analyzing water sharing issues at international, national and local hydrographical basin level. MIKE HYDRO Basin uses a simplified mathematical representation of the hydrographical basin including the configuration of river and reservoir systems, catchment hydrology and existing and potential water user schemes with their various demands including a rigorous irrigation scheme module. This paper analyzes the importance and principles of integrated hydrographical basin management and develop a case study for Crasna river basin, with the use of MIKE HYDRO Basin advanced hydroinformatic tool for integrated hydrographical basin analysis, planning and management.
Singularity-sensitive gauge-based radar rainfall adjustment methods for urban hydrological applications

NASA Astrophysics Data System (ADS)

Wang, L.-P.; Ochoa-Rodríguez, S.; Onof, C.; Willems, P.

2015-09-01

Gauge-based radar rainfall adjustment techniques have been widely used to improve the applicability of radar rainfall estimates to large-scale hydrological modelling. However, their use for urban hydrological applications is limited as they were mostly developed based upon Gaussian approximations and therefore tend to smooth off so-called "singularities" (features of a non-Gaussian field) that can be observed in the fine-scale rainfall structure. Overlooking the singularities could be critical, given that their distribution is highly consistent with that of local extreme magnitudes. This deficiency may cause large errors in the subsequent urban hydrological modelling. To address this limitation and improve the applicability of adjustment techniques at urban scales, a method is proposed herein which incorporates a local singularity analysis into existing adjustment techniques and allows the preservation of the singularity structures throughout the adjustment process. In this paper the proposed singularity analysis is incorporated into the Bayesian merging technique and the performance of the resulting singularity-sensitive method is compared with that of the original Bayesian (non singularity-sensitive) technique and the commonly used mean field bias adjustment. This test is conducted using as case study four storm events observed in the Portobello catchment (53 km2) (Edinburgh, UK) during 2011 and for which radar estimates, dense rain gauge and sewer flow records, as well as a recently calibrated urban drainage model were available. The results suggest that, in general, the proposed singularity-sensitive method can effectively preserve the non-normality in local rainfall structure, while retaining the ability of the original adjustment techniques to generate nearly unbiased estimates. Moreover, the ability of the singularity-sensitive technique to preserve the non-normality in rainfall estimates often leads to better reproduction of the urban drainage system's dynamics, particularly of peak runoff flows.
A Study of Natural and Restored Wetland Hydrology

USGS Publications Warehouse

Bayless, E. Randall; Arihood, Leslie D.; Sidle, William C.; Pavlovic, Noel B.

1999-01-01

The U.S. Geological Survey and the U.S. Environmental Protection Agency are jointly studying the hydrology of a long-existing natural wetland and a recently restored wetland in the Kankakee River Valley in northwestern Indiana. In characterizing the two wetlands, project investigators are testing innovative methods to identify the analytical tools best suited for evaluating the success of wetland restoration. Investigators also are examining and comparing the relations between hydrology and restored wetland vegetation.

The application of remote sensing to the development and formulation of hydrologic planning models

NASA Technical Reports Server (NTRS)

Fowler, T. R.; Castruccio, P. A.; Loats, H. L., Jr.

1977-01-01

The development of a remote sensing model and its efficiency in determining parameters of hydrologic models are reviewed. Procedures for extracting hydrologic data from LANDSAT imagery, and the visual analysis of composite imagery are presented. A hydrologic planning model is developed and applied to determine seasonal variations in watershed conditions. The transfer of this technology to a user community and contract arrangements are discussed.
44 CFR 72.2 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-10-01

... or hydraulic characteristics of a flooding source and thus result in the modification of the existing... hydrologic or hydraulic characteristics of a flooding source and thus result in the modification of the... generally based on physical measures that affect the hydrologic or hydraulic characteristics of a flooding...
44 CFR 72.2 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... or hydraulic characteristics of a flooding source and thus result in the modification of the existing... hydrologic or hydraulic characteristics of a flooding source and thus result in the modification of the... generally based on physical measures that affect the hydrologic or hydraulic characteristics of a flooding...
44 CFR 72.2 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... or hydraulic characteristics of a flooding source and thus result in the modification of the existing... hydrologic or hydraulic characteristics of a flooding source and thus result in the modification of the... generally based on physical measures that affect the hydrologic or hydraulic characteristics of a flooding...
44 CFR 72.2 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... or hydraulic characteristics of a flooding source and thus result in the modification of the existing... hydrologic or hydraulic characteristics of a flooding source and thus result in the modification of the... generally based on physical measures that affect the hydrologic or hydraulic characteristics of a flooding...
44 CFR 72.2 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... or hydraulic characteristics of a flooding source and thus result in the modification of the existing... hydrologic or hydraulic characteristics of a flooding source and thus result in the modification of the... generally based on physical measures that affect the hydrologic or hydraulic characteristics of a flooding...
Probabilistic flood inundation prediction within a coupled hydrodynamic, distributed hydrologic modeling framework

NASA Astrophysics Data System (ADS)

Adams, T. E.

2016-12-01

Accurate and timely predictions of the lateral exent of floodwaters and water level depth in floodplain areas are critical globally. This paper demonstrates the coupling of hydrologic ensembles, derived from the use of numerical weather prediction (NWP) model forcings as input to a fully distributed hydrologic model. Resulting ensemble output from the distributed hydrologic model are used as upstream flow boundaries and lateral inflows to a 1-D hydrodynamic model. An example is presented for the Potomac River in the vicinity of Washington, DC (USA). The approach taken falls within the broader goals of the Hydrologic Ensemble Prediction EXperiment (HEPEX).
Observational breakthroughs lead the way to improved hydrological predictions

NASA Astrophysics Data System (ADS)

Lettenmaier, Dennis P.

2017-04-01

New data sources are revolutionizing the hydrological sciences. The capabilities of hydrological models have advanced greatly over the last several decades, but until recently model capabilities have outstripped the spatial resolution and accuracy of model forcings (atmospheric variables at the land surface) and the hydrologic state variables (e.g., soil moisture; snow water equivalent) that the models predict. This has begun to change, as shown in two examples here: soil moisture and drought evolution over Africa as predicted by a hydrology model forced with satellite-derived precipitation, and observations of snow water equivalent at very high resolution over a river basin in California's Sierra Nevada.
Development of a "Hydrologic Equivalent Wetland" Concept for Modeling Cumulative Effects of Wetlands on Watershed Hydrology

NASA Astrophysics Data System (ADS)

Wang, X.; Liu, T.; Li, R.; Yang, X.; Duan, L.; Luo, Y.

2012-12-01

Wetlands are one of the most important watershed microtopographic features that affect, in combination rather than individually, hydrologic processes (e.g., routing) and the fate and transport of constituents (e.g., sediment and nutrients). Efforts to conserve existing wetlands and/or to restore lost wetlands require that watershed-level effects of wetlands on water quantity and water quality be quantified. Because monitoring approaches are usually cost or logistics prohibitive at watershed scale, distributed watershed models, such as the Soil and Water Assessment Tool (SWAT), can be a best resort if wetlands can be appropriately represented in the models. However, the exact method that should be used to incorporate wetlands into hydrologic models is the subject of much disagreement in the literature. In addition, there is a serious lack of information about how to model wetland conservation-restoration effects using such kind of integrated modeling approach. The objectives of this study were to: 1) develop a "hydrologic equivalent wetland" (HEW) concept; and 2) demonstrate how to use the HEW concept in SWAT to assess effects of wetland restoration within the Broughton's Creek watershed located in southwestern Manitoba of Canada, and of wetland conservation within the upper portion of the Otter Tail River watershed located in northwestern Minnesota of the United States. The HEWs were defined in terms of six calibrated parameters: the fraction of the subbasin area that drains into wetlands (WET_FR), the volume of water stored in the wetlands when filled to their normal water level (WET_NVOL), the volume of water stored in the wetlands when filled to their maximum water level (WET_MXVOL), the longest tributary channel length in the subbasin (CH_L1), Manning's n value for the tributary channels (CH_N1), and Manning's n value for the main channel (CH_N2). The results indicated that the HEW concept allows the nonlinear functional relations between watershed processes and wetland characteristics (e.g., size and morphology) to be accurately represented in the models. The loss of the first 10 to 20% of the wetlands in the Minnesota study area would drastically increase the peak discharge and loadings of sediment, total phosphorus (TP), and total nitrogen (TN). On the other hand, the justifiable reductions of the peak discharge and loadings of sediment, TP, and TN in the Manitoba study area may require that 50 to 80% of the lost wetlands be restored. Further, the comparison between the predicted restoration and conservation effects revealed that wetland conservation seems to deserve a higher priority while both wetland conservation and restoration may be equally important. Moreover, although SWAT was used in this study, the HEW concept is generic and can also be applied with any other hydrologic models.
Flood-inundation and flood-mitigation modeling of the West Branch Wapsinonoc Creek Watershed in West Branch, Iowa

USGS Publications Warehouse

Cigrand, Charles V.

2018-03-26

The U.S. Geological Survey (USGS) in cooperation with the city of West Branch and the Herbert Hoover National Historic Site of the National Park Service assessed flood-mitigation scenarios within the West Branch Wapsinonoc Creek watershed. The scenarios are intended to demonstrate several means of decreasing peak streamflows and improving the conveyance of overbank flows from the West Branch Wapsinonoc Creek and its tributary Hoover Creek where they flow through the city and the Herbert Hoover National Historic Site located within the city.Hydrologic and hydraulic models of the watershed were constructed to assess the flood-mitigation scenarios. To accomplish this, the models used the U.S. Army Corps of Engineers Hydrologic Engineering Center-Hydrologic Modeling System (HEC–HMS) version 4.2 to simulate the amount of runoff and streamflow produced from single rain events. The Hydrologic Engineering Center-River Analysis System (HEC–RAS) version 5.0 was then used to construct an unsteady-state model that may be used for routing streamflows, mapping areas that may be inundated during floods, and simulating the effects of different measures taken to decrease the effects of floods on people and infrastructure.Both models were calibrated to three historic rainfall events that produced peak streamflows ranging between the 2-year and 10-year flood-frequency recurrence intervals at the USGS streamgage (05464942) on Hoover Creek. The historic rainfall events were calibrated by using data from two USGS streamgages along with surveyed high-water marks from one of the events. The calibrated HEC–HMS model was then used to simulate streamflows from design rainfall events of 24-hour duration ranging from a 20-percent to a 1-percent annual exceedance probability. These simulated streamflows were incorporated into the HEC–RAS model.The unsteady-state HEC–RAS model was calibrated to represent existing conditions within the watershed. HEC–RAS model simulations with the existing conditions and streamflows from the design rainfall events were then done to serve as a baseline for evaluating flood-mitigation scenarios. After these simulations were completed, three different flood-mitigation scenarios were developed with HEC–RAS: a detention-storage scenario, a conveyance improvement scenario, and a combination of both. In the detention-storage scenario, four in-channel detention structures were placed upstream from the city of West Branch to attenuate peak streamflows. To investigate possible improvements to conveying floodwaters through the city of West Branch, a section of abandoned railroad embankment and an old truss bridge were removed in the model, because these structures were producing backwater areas during flooding events. The third scenario combines the detention and conveyance scenarios so their joint efficiency could be evaluated. The scenarios with the design rainfall events were run in the HEC–RAS model so their flood-mitigation effects could be analyzed across a wide range of flood magnitudes.
Significance of hydrological model choice and land use changes when doing climate change impact assessment

NASA Astrophysics Data System (ADS)

Bjørnholt Karlsson, Ida; Obel Sonnenborg, Torben; Refsgaard, Jens Christian; Høgh Jensen, Karsten

2014-05-01

Uncertainty in impact studies arises both from Global Climate Models (GCM), emission projections, statistical downscaling, Regional Climate Models (RCM), hydrological models and calibration techniques (Refsgaard et al. 2013). Some of these uncertainties have been evaluated several times in the literature; however few studies have investigated the effect of hydrological model choice on the assessment results (Boorman & Sefton 1997; Jiang et al. 2007; Bastola et al. 2011). These studies have found that model choice results in large differences, up to 70%, in the predicted discharge changes depending on the climate input. The objective of the study is to investigate the impact of climate change on hydrology of the Odense catchment, Denmark both in response to (a) different climate projections (GCM-RCM combinations); (b) different hydrological models and (c) different land use scenarios. This includes: 1. Separation of the climate model signal; the hydrological model signal and the land use signal 2. How do the different hydrological components react under different climate and land use conditions for the different models 3. What land use scenario seems to provide the best adaptation for the challenges of the different future climate change scenarios from a hydrological perspective? Four climate models from the ENSEMBLES project (Hewitt & Griggs 2004): ECHAM5 - HIRHAM5, ECHAM5 - RCA3, ARPEGE - RM5.1 and HadCM3 - HadRM3 are used, assessing the climate change impact in three periods: 1991-2010 (present), 2041-2060 (near future) and 2081-2100 (far future). The four climate models are used in combination with three hydrological models with different conceptual layout: NAM, SWAT and MIKE SHE. Bastola, S., C. Murphy and J. Sweeney (2011). "The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments." Advances in Water Resources 34: 562-576. Boorman, D. B. and C. E. M. Sefton (1997). "Recognising the uncertainty in the quantification of the effects of climate change on hydrological response." Climate Change 35: 415-434. Hewitt, C. D. and D. J. Griggs (2004). "Ensembles-based predictions of climate changes and their impacts." Eos, Transactions American Geophysical Union 85: 1-566. Jiang, T., Y. D. Chen, C. Xu, X. Chen, X. Chen and V. P. Singh (2007). "Comparison of hydrological impacts of climate change simulated by six hydrological models in the Dongjiang Basin, South China." Journal of hydrology 336: 316-333. Refsgaard, J. C., K. Arnbjerg-Nielsen, M. Drews, K. Halsnæs, E. Jeppesen, H. Madsen, A. Markandya, J. E. Olesen, J. R. Porter and J. H. Christensen (2013). "The role of uncertainty in climate change adaptation strategies - A Danish water management example." Mitigation and Adaptation Strategies for Global Change 18: 337-359.
Nonlinear scaling of the Unit Hydrograph Peaking Factor for dam safety

NASA Astrophysics Data System (ADS)

Pradhan, N. R.; Loney, D.

2017-12-01

Existing U.S. Army Corps of Engineers (USACE) policy suggests unit hydrograph peaking factor (UHPF), the ratio of an observed and modeled event unit hydrograph peak, range between 1.25 and 1.50 to ensure dam safety. It is pertinent to investigate the impact of extreme flood events on the validity of this range through physically based rainfall-runoff models not available during the planning and design of most USACE dams. The UHPF range was analyzed by deploying the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model in the Goose Creek, VA, watershed to develop a UHPF relationship with excess rainfall across various return-period events. An effective rainfall factor (ERF) is introduced to validate existing UHPF guidance as well as provide a nonlinear UHPF scaling relation when effective rainfall does not match that of the UH design event.
Projecting the potential evapotranspiration by coupling different formulations and input data reliabilities: The possible uncertainty source for climate change impacts on hydrological regime

NASA Astrophysics Data System (ADS)

Wang, Weiguang; Li, Changni; Xing, Wanqiu; Fu, Jianyu

2017-12-01

Representing atmospheric evaporating capability for a hypothetical reference surface, potential evapotranspiration (PET) determines the upper limit of actual evapotranspiration and is an important input to hydrological models. Due that present climate models do not give direct estimates of PET when simulating the hydrological response to future climate change, the PET must be estimated first and is subject to the uncertainty on account of many existing formulae and different input data reliabilities. Using four different PET estimation approaches, i.e., the more physically Penman (PN) equation with less reliable input variables, more empirical radiation-based Priestley-Taylor (PT) equation with relatively dependable downscaled data, the most simply temperature-based Hamon (HM) equation with the most reliable downscaled variable, and downscaling PET directly by the statistical downscaling model, this paper investigated the differences of runoff projection caused by the alternative PET methods by a well calibrated abcd monthly hydrological model. Three catchments, i.e., the Luanhe River Basin, the Source Region of the Yellow River and the Ganjiang River Basin, representing a large climatic diversity were chosen as examples to illustrate this issue. The results indicated that although similar monthly patterns of PET over the period 2021-2050 for each catchment were provided by the four methods, the magnitudes of PET were still slightly different, especially for spring and summer months in the Luanhe River Basin and the Source Region of the Yellow River with relatively dry climate feature. The apparent discrepancy in magnitude of change in future runoff and even the diverse change direction for summer months in the Luanhe River Basin and spring months in the Source Region of the Yellow River indicated that the PET method related uncertainty occurred, especially in the Luanhe River Basin and the Source Region of the Yellow River with smaller aridity index. Moreover, the possible reason of discrepancies in uncertainty between three catchments was quantitatively discussed by the contribution analysis based on climatic elasticity method. This study can provide beneficial reference to comprehensively understand the impacts of climate change on hydrological regime and thus improve the regional strategy for future water resource management.
Feedback Loop of Data Infilling Using Model Result of Actual Evapotranspiration from Satellites and Hydrological Model

NASA Astrophysics Data System (ADS)

Murdi Hartanto, Isnaeni; Alexandridis, Thomas K.; van Andel, Schalk Jan; Solomatine, Dimitri

2014-05-01

Using satellite data in a hydrological model has long been occurring in modelling of hydrological processes, as a source of low cost regular data. The methods range from using satellite products as direct input, model validation, and data assimilation. However, the satellite data frequently face the missing value problem, whether due to the cloud cover or the limited temporal coverage. The problem could seriously affect its usefulness in hydrological model, especially if the model uses it as direct input, so data infilling becomes one of the important parts in the whole modelling exercise. In this research, actual evapotranspiration product from satellite is directly used as input into a spatially distributed hydrological model, and validated by comparing the catchment's end discharge with measured data. The instantaneous actual evapotranspiration is estimated from MODIS satellite images using a variation of the energy balance model for land (SEBAL). The eight-day cumulative actual evapotranspiration is then obtained by a temporal integration that uses the reference evapotranspiration calculated from meteorological data [1]. However, the above method cannot fill in a cell if the cell is constantly having no-data value during the eight-day periods. The hydrological model requires full set of data without no-data cells, hence, the no-data cells in the satellite's evapotranspiration map need to be filled in. In order to fills the no-data cells, an output of hydrological model is used. The hydrological model is firstly run with reference evapotranspiration as input to calculate discharge and actual evapotranspiration. The no-data cells in the eight-day cumulative map from the satellite are then filled in with the output of the first run of hydrological model. The final data is then used as input in a hydrological model to calculate discharge, thus creating a loop. The method is applied in the case study of Rijnland, the Netherlands where in the winter, cloud cover is persistent and leads to many no-data cells in the satellite products. The Rijnland area is a low-lying area with tight water system control. The satellite data is used as input in a SIMGRO model, a spatially distributed hydrological model that is able to handle the controlled water system and that is suitable for the low-lying areas in the Netherlands. The application in the Rijnland area gives overall a good result of total discharge. By using the method, the hydrological model is improved in term of spatial hydrological state, where the original model is only calibrated to discharge in one location. [1] Alexandridis, T.K., Cherif, I., Chemin, Y., Silleos, G.N., Stavrinos, E. & Zalidis, G.C. (2009). Integrated Methodology for Estimating Water Use in Mediterranean Agricultural Areas. Remote Sensing. 1
Incorporating groundwater flow into the WEPP model

Treesearch

William Elliot; Erin Brooks; Tim Link; Sue Miller

2010-01-01

The water erosion prediction project (WEPP) model is a physically-based hydrology and erosion model. In recent years, the hydrology prediction within the model has been improved for forest watershed modeling by incorporating shallow lateral flow into watershed runoff prediction. This has greatly improved WEPP's hydrologic performance on small watersheds with...
The critical role of fire in catchment coevolution in South Eastern Australia

NASA Astrophysics Data System (ADS)

Nyman, P.; Inbar, A.; Lane, P. N. J.; Sheridan, G. J.

2016-12-01

Temperate south east Australian forested uplands are characterised by complex spatial patterns in forest types, soils and fire regimes, even within areas with similar geologies and landscape position. Preliminary measurements and experiments suggest that positive and negative feedbacks between the vegetation, fuels, fire frequency and soil erosion may control the coevolution of these observed system states. Here we propose the hypotheses that in this landscape post-fire soil erosion has played a dominant role in the coevolved system-state combinations of standing biomass, fire frequency and soil depth. To test the hypothesis a 1D simulation model was developed that links together an ecohydrological model to drive the biomass production and water and energy partitioning, a stochastic fire model that is controlled by climate, fuel load and moisture conditions, and a geomorphic model that controls soil production and fluvial and diffusive sediment transport rates. The model was calibrated to the range of existing observed quasi-equalibrium system-states of soil depth, standing biomass, fuel loading and fire frequency using field measurements from 12 instrumented eco-hydrologic microclimate research sites. The long-term partitioning of rainfall into evaporation, transpiration, and streamflow was calibrated against field and literature values. Fuel moisture and micro-climate variables were calibrated to the field microclimate stations. The calibrated model was able to reasonably replicate the observed quasi-equilibrium system-states and hydrologic outputs using current climate forcings operating over a 10,000 year period, providing confidence in the model structure and performance. The model was then used to test the hypothesis stated above, by alternatively including or excluding the post fire erosion process. An alternate hypothesis, whereby the observed system states are dominated by climate related differences in soil production rates was also tested in this way. The results support the hypothesis that feedbacks between fire, ecology, hydrology and geomorphology have played a critical role in the coevolution of south east Australian forested uplands. Similar pyro-eco-hydrologic feedbacks may play a critical role in catchment coevolution in other forested systems globally.
It takes a community to raise a hydrologist: the Modular Curriculum for Hydrologic Advancement (MOCHA)

NASA Astrophysics Data System (ADS)

Wagener, T.; Kelleher, C.; Weiler, M.; McGlynn, B.; Gooseff, M.; Marshall, L.; Meixner, T.; McGuire, K.; Gregg, S.; Sharma, P.; Zappe, S.

2012-09-01

Protection from hydrological extremes and the sustainable supply of hydrological services in the presence of changing climate and lifestyles as well as rocketing population pressure in many parts of the world are the defining societal challenges for hydrology in the 21st century. A review of the existing literature shows that these challenges and their educational consequences for hydrology were foreseeable and were even predicted by some. However, surveys of the current educational basis for hydrology also clearly demonstrate that hydrology education is not yet ready to prepare students to deal with these challenges. We present our own vision of the necessary evolution of hydrology education, which we implemented in the Modular Curriculum for Hydrologic Advancement (MOCHA). The MOCHA project is directly aimed at developing a community-driven basis for hydrology education. In this paper we combine literature review, community survey, discussion and assessment to provide a holistic baseline for the future of hydrology education. The ultimate objective of our educational initiative is to enable educators to train a new generation of "renaissance hydrologists," who can master the holistic nature of our field and of the problems we encounter.
Hydrologic Process-oriented Optimization of Electrical Resistivity Tomography

NASA Astrophysics Data System (ADS)

Hinnell, A.; Bechtold, M.; Ferre, T. A.; van der Kruk, J.

2010-12-01

Electrical resistivity tomography (ERT) is commonly used in hydrologic investigations. Advances in joint and coupled hydrogeophysical inversion have enhanced the quantitative use of ERT to construct and condition hydrologic models (i.e. identify hydrologic structure and estimate hydrologic parameters). However the selection of which electrical resistivity data to collect and use is often determined by a combination of data requirements for geophysical analysis, intuition on the part of the hydrogeophysicist and logistical constraints of the laboratory or field site. One of the advantages of coupled hydrogeophysical inversion is the direct link between the hydrologic model and the individual geophysical data used to condition the model. That is, there is no requirement to collect geophysical data suitable for independent geophysical inversion. The geophysical measurements collected can be optimized for estimation of hydrologic model parameters rather than to develop a geophysical model. Using a synthetic model of drip irrigation we evaluate the value of individual resistivity measurements to describe the soil hydraulic properties and then use this information to build a data set optimized for characterizing hydrologic processes. We then compare the information content in the optimized data set with the information content in a data set optimized using a Jacobian sensitivity analysis.
Improving Hydrological Simulations by Incorporating GRACE Data for Parameter Calibration

NASA Astrophysics Data System (ADS)

Bai, P.

2017-12-01

Hydrological model parameters are commonly calibrated by observed streamflow data. This calibration strategy is questioned when the modeled hydrological variables of interest are not limited to streamflow. Well-performed streamflow simulations do not guarantee the reliable reproduction of other hydrological variables. One of the reasons is that hydrological model parameters are not reasonably identified. The Gravity Recovery and Climate Experiment (GRACE) satellite-derived total water storage change (TWSC) data provide an opportunity to constrain hydrological model parameterizations in combination with streamflow observations. We constructed a multi-objective calibration scheme based on GRACE-derived TWSC and streamflow observations, with the aim of improving the parameterizations of hydrological models. The multi-objective calibration scheme was compared with the traditional single-objective calibration scheme, which is based only on streamflow observations. Two monthly hydrological models were employed on 22 Chinese catchments with different hydroclimatic conditions. The model evaluation was performed using observed streamflows, GRACE-derived TWSC, and evapotranspiraiton (ET) estimates from flux towers and from the water balance approach. Results showed that the multi-objective calibration provided more reliable TWSC and ET simulations without significant deterioration in the accuracy of streamflow simulations than the single-objective calibration. In addition, the improvements of TWSC and ET simulations were more significant in relatively dry catchments than in relatively wet catchments. This study highlights the importance of including additional constraints besides streamflow observations in the parameter estimation to improve the performances of hydrological models.
An Investigation Into the Ecohydrology of Riparian Wetlands Along the Gila River, NM, USA

NASA Astrophysics Data System (ADS)

Samson, J.; Stone, M. C.

2013-12-01

The dynamism of the Gila River, in southwestern New Mexico, USA, has resulted in the creation of a topographically diverse floodplain that supports an array of riparian wetlands. The purpose of this study is to investigate the ecohydrologic and ecohydraulic processes of two of these wetlands, in order to predict their potential response to anthropogenic or natural changes in hydrology. One represents a natural wetland and the other a wetland that exists only as a result of an anthropogenic modification to the river system. A network of 30 wells and 2 weather stations were installed in early 2013 to provide a high resolution of data on surface water and ground water hydrologic conditions. Phreatic surface contour maps were produced to aid in the visualization of sub-surface gradients. Based on these results, an electrical resistivity investigation was conducted to identify paleoflow channels as well as depth to bedrock and other potential areas of interest. These data formed the development of three dimensional ModFlow models that were used to investigate potential future stream flow scenarios on wetland hydrology. The model outputs are being used in tandem with the results of quarterly ecological surveys on vegetation, algae, benthic, and bird communities, to make predictions of potential changes in community structure and function.

Flood design recipes vs. reality: can predictions for ungauged basins be trusted?

NASA Astrophysics Data System (ADS)

Efstratiadis, A.; Koussis, A. D.; Koutsoyiannis, D.; Mamassis, N.

2013-12-01

Despite the great scientific and technological advances in flood hydrology, everyday engineering practices still follow simplistic approaches, such as the rational formula and the SCS-CN method combined with the unit hydrograph theory that are easy to formally implement in ungauged areas. In general, these "recipes" have been developed many decades ago, based on field data from few experimental catchments. However, many of them have been neither updated nor validated across all hydroclimatic and geomorphological conditions. This has an obvious impact on the quality and reliability of hydrological studies, and, consequently, on the safety and cost of the related flood protection works. Preliminary results, based on historical flood data from Cyprus and Greece, indicate that a substantial revision of many aspects of flood engineering procedures is required, including the regionalization formulas as well as the modelling concepts themselves. In order to provide a consistent design framework and to ensure realistic predictions of the flood risk (a key issue of the 2007/60/EU Directive) in ungauged basins, it is necessary to rethink the current engineering practices. In this vein, the collection of reliable hydrological data would be essential for re-evaluating the existing "recipes", taking into account local peculiarities, and for updating the modelling methodologies as needed.
A study of water balances over the Tigris-Euphrates watershed

NASA Astrophysics Data System (ADS)

Kavvas, M. L.; Chen, Z. Q.; Anderson, M. L.; Ohara, N.; Yoon, J. Y.; Xiang, Fu

Tigris-Euphrates watershed was considered as one hydrologic unit, and a scientific assessment of its water resources was performed. Accordingly, (a) an inventory of land use/land cover, vegetation, soils, and existing hydraulic structures in the watershed was performed; (b) a regional hydroclimate model, RegHCM-TE, of the watershed was developed, and used to reconstruct historical precipitation data, to perform land hydrologic water balance computations for infiltration, soil water storage, actual evapotranspiration, direct runoff as input for streamflow computations, and to estimate irrigation water demands; and (c) a hydrologic model was developed to route streamflows within the river network of the watershed. Also, an algorithm for operating the reservoirs within the watershed was developed, and utilized to perform dynamic water balance studies under various water supply/demand scenarios to establish efficient utilization of the watershed’s water resources to meet the water demands of the riparian countries in the basin. Within this dynamic water balance framework, it is possible to assess and quantify the effect of sequential river flows on the chronologically sequential water balances over the watershed. The water balance study for the natural flow conditions prior to the development of large dams within TE basin, during the 1957-1969 critical period is presented.
Hydrology of the Coastal Lowlands aquifer system in parts of Alabama, Florida, Louisiana, and Mississippi

USGS Publications Warehouse

Martin, Angel; Whiteman, C.D.

1999-01-01

Existing data on water levels, water use, water quality, and aquifer properties were used to construct a multilayer digital model to simulate flow in the aquifer system. The report describes the geohydrologic framework of the aquifer system, and the development, calibration, and sensitivity analysis of the ground-water-flow model, but it is primarily focused on the results of the simulations that show the natural flow of ground water throughout the regional aquifer system and the changes from the natural flow caused by development of ground-water supplies.
Water resources planning for rivers draining into Mobile Bay

NASA Technical Reports Server (NTRS)

April, G. C.

1976-01-01

The application of remote sensing, automatic data processing, modeling and other aerospace related technologies to hydrological engineering and water resource management are discussed for the entire river drainage system which feeds the Mobile Bay estuary. The adaptation and implementation of existing mathematical modeling methods are investigated for the purpose of describing the behavior of Mobile Bay. Of particular importance are the interactions that system variables such as river flow rate, wind direction and speed, and tidal state have on the water movement and quality within the bay system.
Spatial calibration and temporal validation of flow for regional scale hydrologic modeling

USDA-ARS?s Scientific Manuscript database

Physically based regional scale hydrologic modeling is gaining importance for planning and management of water resources. Calibration and validation of such regional scale model is necessary before applying it for scenario assessment. However, in most regional scale hydrologic modeling, flow validat...
Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wood, Andrew W; Leung, Lai R; Sridhar, V

Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel Climate Model (PCM), and the implications of the comparison for a future (2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregationmore » (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly (at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at ½-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able to produce hydrologically plausible results. With the BCSD method, the RCM-derived hydrology was more sensitive to climate change than the PCM-derived hydrology.« less
A Community Data Model for Hydrologic Observations

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Horsburgh, J. S.; Zaslavsky, I.; Maidment, D. R.; Valentine, D.; Jennings, B.

2006-12-01

The CUAHSI Hydrologic Information System project is developing information technology infrastructure to support hydrologic science. Hydrologic information science involves the description of hydrologic environments in a consistent way, using data models for information integration. This includes a hydrologic observations data model for the storage and retrieval of hydrologic observations in a relational database designed to facilitate data retrieval for integrated analysis of information collected by multiple investigators. It is intended to provide a standard format to facilitate the effective sharing of information between investigators and to facilitate analysis of information within a single study area or hydrologic observatory, or across hydrologic observatories and regions. The observations data model is designed to store hydrologic observations and sufficient ancillary information (metadata) about the observations to allow them to be unambiguously interpreted and used and provide traceable heritage from raw measurements to usable information. The design is based on the premise that a relational database at the single observation level is most effective for providing querying capability and cross dimension data retrieval and analysis. This premise is being tested through the implementation of a prototype hydrologic observations database, and the development of web services for the retrieval of data from and ingestion of data into the database. These web services hosted by the San Diego Supercomputer center make data in the database accessible both through a Hydrologic Data Access System portal and directly from applications software such as Excel, Matlab and ArcGIS that have Standard Object Access Protocol (SOAP) capability. This paper will (1) describe the data model; (2) demonstrate the capability for representing diverse data in the same database; (3) demonstrate the use of the database from applications software for the performance of hydrologic analysis across different observation types.
Hydrologic connectivity: Quantitative assessments of hydrologic-enforced drainage structures in an elevation model

USGS Publications Warehouse

Poppenga, Sandra K.; Worstell, Bruce B.

2016-01-01

Elevation data derived from light detection and ranging present challenges for hydrologic modeling as the elevation surface includes bridge decks and elevated road features overlaying culvert drainage structures. In reality, water is carried through these structures; however, in the elevation surface these features impede modeled overland surface flow. Thus, a hydrologically-enforced elevation surface is needed for hydrodynamic modeling. In the Delaware River Basin, hydrologic-enforcement techniques were used to modify elevations to simulate how constructed drainage structures allow overland surface flow. By calculating residuals between unfilled and filled elevation surfaces, artificially pooled depressions that formed upstream of constructed drainage structure features were defined, and elevation values were adjusted by generating transects at the location of the drainage structures. An assessment of each hydrologically-enforced drainage structure was conducted using field-surveyed culvert and bridge coordinates obtained from numerous public agencies, but it was discovered the disparate drainage structure datasets were not comprehensive enough to assess all remotely located depressions in need of hydrologic-enforcement. Alternatively, orthoimagery was interpreted to define drainage structures near each depression, and these locations were used as reference points for a quantitative hydrologic-enforcement assessment. The orthoimagery-interpreted reference points resulted in a larger corresponding sample size than the assessment between hydrologic-enforced transects and field-surveyed data. This assessment demonstrates the viability of rules-based hydrologic-enforcement that is needed to achieve hydrologic connectivity, which is valuable for hydrodynamic models in sensitive coastal regions. Hydrologic-enforced elevation data are also essential for merging with topographic/bathymetric elevation data that extend over vulnerable urbanized areas and dynamic coastal regions.
Hydrological Modeling in the Bull Run Watershed in Support of a Piloting Utility Modeling Applications (PUMA) Project

NASA Astrophysics Data System (ADS)

Nijssen, B.; Chiao, T. H.; Lettenmaier, D. P.; Vano, J. A.

2016-12-01

Hydrologic models with varying complexities and structures are commonly used to evaluate the impact of climate change on future hydrology. While the uncertainties in future climate projections are well documented, uncertainties in streamflow projections associated with hydrologic model structure and parameter estimation have received less attention. In this study, we implemented and calibrated three hydrologic models (the Distributed Hydrology Soil Vegetation Model (DHSVM), the Precipitation-Runoff Modeling System (PRMS), and the Variable Infiltration Capacity model (VIC)) for the Bull Run watershed in northern Oregon using consistent data sources and best practice calibration protocols. The project was part of a Piloting Utility Modeling Applications (PUMA) project with the Portland Water Bureau (PWB) under the umbrella of the Water Utility Climate Alliance (WUCA). Ultimately PWB would use the model evaluation to select a model to perform in-house climate change analysis for Bull Run Watershed. This presentation focuses on the experimental design of the comparison project, project findings and the collaboration between the team at the University of Washington and at PWB. After calibration, the three models showed similar capability to reproduce seasonal and inter-annual variations in streamflow, but differed in their ability to capture extreme events. Furthermore, the annual and seasonal hydrologic sensitivities to changes in climate forcings differed among models, potentially attributable to different model representations of snow and vegetation processes.
On the use of three hydrological models as hypotheses to investigate the behaviour of a small Mediterranean catchment

NASA Astrophysics Data System (ADS)

Ruiz Pérez, Guiomar; Latron, Jérôme; Llorens, Pilar; Gallart, Francesc; Francés, Félix

2017-04-01

Selecting an adequate hydrological model is the first step to carry out a rainfall-runoff modelling exercise. A hydrological model is a hypothesis of catchment functioning, encompassing a description of dominant hydrological processes and predicting how these processes interact to produce the catchment's response to external forcing. Current research lines emphasize the importance of multiple working hypotheses for hydrological modelling instead of only using a single model. In line with this philosophy, here different hypotheses were considered and analysed to simulate the nonlinear response of a small Mediterranean catchment and to progress in the analysis of its hydrological behaviour. In particular, three hydrological models were considered representing different potential hypotheses: two lumped models called LU3 and LU4, and one distributed model called TETIS. To determine how well each specific model performed and to assess whether a model was more adequate than another, we raised three complementary tests: one based on the analysis of residual errors series, another based on a sensitivity analysis and the last one based on using multiple evaluation criteria associated to the concept of Pareto frontier. This modelling approach, based on multiple working hypotheses, helped to improve our perceptual model of the catchment behaviour and, furthermore, could be used as a guidance to improve the performance of other environmental models.
Shrink-swell behavior of soil across a vertisol catena

USDA-ARS?s Scientific Manuscript database

Shrinking and swelling of soils and the associated formation and closing of cracks can vary spatially within the smallest hydrologic unit subdivision utilized in surface hydrology models. Usually in the application of surface hydrology models, cracking is not considered to vary within a hydrologic u...
A dam-reservoir module for a semi-distributed hydrological model

NASA Astrophysics Data System (ADS)

de Lavenne, Alban; Thirel, Guillaume; Andréassian, Vazken; Perrin, Charles; Ramos, Maria-Helena

2017-04-01

Developing modeling tools that help to assess the spatial distribution of water resources is a key issue to achieve better solutions for the optimal management of water availability among users in a river basin. Streamflow dynamics depends on (i) the spatial variability of rainfall, (ii) the heterogeneity of catchment behavior and response, and (iii) local human regulations (e.g., reservoirs) that store and control surface water. These aspects can be successfully handled by distributed or semi-distributed hydrological models. In this study, we develop a dam-reservoir module within a semi-distributed rainfall-runoff model (de Lavenne et al. 2016). The model runs at the daily time step, and has five parameters for each sub-catchment as well as a streamflow velocity parameter for flow routing. Its structure is based on two stores, one for runoff production and one for routing. The calibration of the model is performed from upstream to downstream sub-catchments, which efficiently uses spatially-distributed streamflow measurements. In a previous study, Payan et al. (2008) described a strategy to implement a dam module within a lumped rainfall-runoff model. Here we propose to adapt this strategy to a semi-distributed hydrological modelling framework. In this way, the specific location of existing reservoirs inside a river basin is explicitly accounted for. Our goal is to develop a tool that can provide answers to the different issues involved in spatial water management in human-influenced contexts and at large modelling scales. The approach is tested for the Seine basin in France. Results are shown for model performance with and without the dam module. Also, a comparison with the lumped GR5J model highlights the improvements obtained in model performance by considering human influences more explicitly, and by facilitating parameter identifiability. This work opens up new perspectives for streamflow naturalization analyses and scenario-based spatial assessment of water resources under global change. References de Lavenne, A.; Thirel, G.; Andréassian, V.; Perrin, C. & Ramos, M.-H. (2016), 'Spatial variability of the parameters of a semi-distributed hydrological model', PIAHS 373, 87-94. Payan, J.-L.; Perrin, C.; Andréassian, V. & Michel, C. (2008), 'How can man-made water reservoirs be accounted for in a lumped rainfall-runoff model?', Water Resour. Res. 44(3), W03420.
CLIMB - Climate induced changes on the hydrology of mediterranean basins - Reducing uncertainties and quantifying risk

NASA Astrophysics Data System (ADS)

Ludwig, Ralf

2010-05-01

According to future climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. These changes are expected to have severe direct impacts on the management of water resources. Threats include severe droughts and extreme flooding, salinization of coastal aquifers, degradation of fertile soils and desertification due to poor and unsustainable water management practices. It can be foreseen that, unless appropriate adaptation measures are undertaken, the changes in the hydrologic cycle will give rise to an increasing potential for tension and conflict among the political and economic actors in this vulnerable region. The presented project initiative CLIMB, funded under EC's 7th Framework Program (FP7-ENV-2009-1), has started in January 2010. In its 4-year design, it shall analyze ongoing and future climate induced changes in hydrological budgets and extremes across the Mediterranean and neighboring regions. This is undertaken in study sites located in Sardinia, Northern Italy, Southern France, Tunisia, Egypt and the Palestinian-administered area Gaza. The work plan is targeted to selected river or aquifer catchments, where the consortium will employ a combination of novel field monitoring and remote sensing concepts, data assimilation, integrated hydrologic (and biophysical) modeling and socioeconomic factor analyses to reduce existing uncertainties in climate change impact analysis. Advanced climate scenario analysis will be employed and available ensembles of regional climate model simulations will be downscaling. This process will provide the drivers for an ensemble of hydro(-geo)logical models with different degrees of complexity in terms of process description and level of integration. The results of hydrological modeling and socio-economic factor analysis will enable the development of a GIS-based Vulnerability and Risk Assessment Tool. This tool will serve as a platform for the dissemination of project results, including communication with and planning for local and regional stakeholders. An im¬portant output of the research in the individual study sites will be the development of a set of recommendations for an improved monitoring and modeling strategy for climate change impact assessment. CLIMB is forming a cluster of independent projects with WASSERMed from the Environment and CLICO from Social Sciences and Humanities Call of FP7 in 2009. The intention of this clustering is to foster scientific synergy and cooperation between the partner projects to achieve improvements in policy outreach on different spatial scales.
Subdivision of Texas watersheds for hydrologic modeling.

DOT National Transportation Integrated Search

2009-06-01

The purpose of this report is to present a set of findings and examples for subdivision of watersheds for hydrologic modeling. Three approaches were used to examine the impact of watershed subdivision on modeled hydrologic response: (1) An equal-area...
Identifying influential data points in hydrological model calibration and their impact on streamflow predictions

NASA Astrophysics Data System (ADS)

Wright, David; Thyer, Mark; Westra, Seth

2015-04-01

Highly influential data points are those that have a disproportionately large impact on model performance, parameters and predictions. However, in current hydrological modelling practice the relative influence of individual data points on hydrological model calibration is not commonly evaluated. This presentation illustrates and evaluates several influence diagnostics tools that hydrological modellers can use to assess the relative influence of data. The feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration is discussed. Two classes of influence diagnostics are evaluated: (1) computationally demanding numerical "case deletion" diagnostics; and (2) computationally efficient analytical diagnostics, based on Cook's distance. These diagnostics are compared against hydrologically orientated diagnostics that describe changes in the model parameters (measured through the Mahalanobis distance), performance (objective function displacement) and predictions (mean and maximum streamflow). These influence diagnostics are applied to two case studies: a stage/discharge rating curve model, and a conceptual rainfall-runoff model (GR4J). Removing a single data point from the calibration resulted in differences to mean flow predictions of up to 6% for the rating curve model, and differences to mean and maximum flow predictions of up to 10% and 17%, respectively, for the hydrological model. When using the Nash-Sutcliffe efficiency in calibration, the computationally cheaper Cook's distance metrics produce similar results to the case-deletion metrics at a fraction of the computational cost. However, Cooks distance is adapted from linear regression with inherit assumptions on the data and is therefore less flexible than case deletion. Influential point detection diagnostics show great potential to improve current hydrological modelling practices by identifying highly influential data points. The findings of this study establish the feasibility and importance of including influential point detection diagnostics as a standard tool in hydrological model calibration. They provide the hydrologist with important information on whether model calibration is susceptible to a small number of highly influent data points. This enables the hydrologist to make a more informed decision of whether to (1) remove/retain the calibration data; (2) adjust the calibration strategy and/or hydrological model to reduce the susceptibility of model predictions to a small number of influential observations.
Cyberinfrastructure to Support Collaborative and Reproducible Computational Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Goodall, J. L.; Castronova, A. M.; Bandaragoda, C.; Morsy, M. M.; Sadler, J. M.; Essawy, B.; Tarboton, D. G.; Malik, T.; Nijssen, B.; Clark, M. P.; Liu, Y.; Wang, S. W.

2017-12-01

Creating cyberinfrastructure to support reproducibility of computational hydrologic models is an important research challenge. Addressing this challenge requires open and reusable code and data with machine and human readable metadata, organized in ways that allow others to replicate results and verify published findings. Specific digital objects that must be tracked for reproducible computational hydrologic modeling include (1) raw initial datasets, (2) data processing scripts used to clean and organize the data, (3) processed model inputs, (4) model results, and (5) the model code with an itemization of all software dependencies and computational requirements. HydroShare is a cyberinfrastructure under active development designed to help users store, share, and publish digital research products in order to improve reproducibility in computational hydrology, with an architecture supporting hydrologic-specific resource metadata. Researchers can upload data required for modeling, add hydrology-specific metadata to these resources, and use the data directly within HydroShare.org for collaborative modeling using tools like CyberGIS, Sciunit-CLI, and JupyterHub that have been integrated with HydroShare to run models using notebooks, Docker containers, and cloud resources. Current research aims to implement the Structure For Unifying Multiple Modeling Alternatives (SUMMA) hydrologic model within HydroShare to support hypothesis-driven hydrologic modeling while also taking advantage of the HydroShare cyberinfrastructure. The goal of this integration is to create the cyberinfrastructure that supports hypothesis-driven model experimentation, education, and training efforts by lowering barriers to entry, reducing the time spent on informatics technology and software development, and supporting collaborative research within and across research groups.
WEB-DHM: A distributed biosphere hydrological model developed by coupling a simple biosphere scheme with a hillslope hydrological model

USDA-ARS?s Scientific Manuscript database

The coupling of land surface models and hydrological models potentially improves the land surface representation, benefiting both the streamflow prediction capabilities as well as providing improved estimates of water and energy fluxes into the atmosphere. In this study, the simple biosphere model 2...
An integrated crop and hydrologic modeling system to estimate hydrologic impacts of crop irrigation demands

Treesearch

R.T. McNider; C. Handyside; K. Doty; W.L. Ellenburg; J.F. Cruise; J.R. Christy; D. Moss; V. Sharda; G. Hoogenboom; Peter Caldwell

2015-01-01

The present paper discusses a coupled gridded crop modeling and hydrologic modeling system that can examine the benefits of irrigation and costs of irrigation and the coincident impact of the irrigation water withdrawals on surface water hydrology. The system is applied to the Southeastern U.S. The system tools to be discussed include a gridded version (GriDSSAT) of...
iTree-Hydro: Snow hydrology update for the urban forest hydrology model

Treesearch

Yang Yang; Theodore A. Endreny; David J. Nowak

2011-01-01

This article presents snow hydrology updates made to iTree-Hydro, previously called the Urban Forest EffectsâHydrology model. iTree-Hydro Version 1 was a warm climate model developed by the USDA Forest Service to provide a process-based planning tool with robust water quantity and quality predictions given data limitations common to most urban areas. Cold climate...
Liquid water on Mars - an energy balance climate model for CO2/H2O atmospheres

NASA Astrophysics Data System (ADS)

Hoffert, M. I.; Callegari, A. J.; Hsieh, T.; Ziegler, W.

1981-07-01

A simple climatic model is developed for a Mars atmosphere containing CO2 and sufficient liquid water to account for the observed hydrologic surface features by the existence of a CO2/H2O greenhouse effect. A latitude-resolved climate model originally devised for terrestrial climate studies is applied to Martian conditions, with the difference between absorbed solar flux and emitted long-wave flux to space per unit area attributed to the divergence of the meridional heat flux and the poleward heat flux assumed to equal the atmospheric eddy heat flux. The global mean energy balance is calculated as a function of atmospheric pressure to assess the CO2/H2O greenhouse liquid water hypothesis, and some latitude-resolved cases are examined in detail in order to clarify the role of atmospheric transport and temperature-albedo feedback. It is shown that the combined CO2/H2O greenhouse at plausible early surface pressures may account for climates hot enough to support a hydrological cycle and running water at present-day insolation and visible albedo levels.

Thermo-hydrological and chemical (THC) modeling to support Field Test Design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stauffer, Philip H.; Jordan, Amy B.; Harp, Dylan Robert

This report summarizes ongoing efforts to simulate coupled thermal-hydrological-chemical (THC) processes occurring within a hypothetical high-level waste (HLW) repository in bedded salt. The report includes work completed since the last project deliverable, “Coupled model for heat and water transport in a high level waste repository in salt”, a Level 2 milestone submitted to DOE in September 2013 (Stauffer et al., 2013). Since the last deliverable, there have been code updates to improve the integration of the salt module with the pre-existing code and development of quality assurance (QA) tests of constitutive functions and precipitation/dissolution reactions. Simulations of bench-scale experiments, bothmore » historical and currently in the planning stages have been performed. Additional simulations have also been performed on the drift-scale model that incorporate new processes, such as an evaporation function to estimate water vapor removal from the crushed salt backfill and isotopic fractionation of water isotopes. Finally, a draft of a journal paper on the importance of clay dehydration on water availability is included as Appendix I.« less
Liquid water on Mars - An energy balance climate model for CO2/H2O atmospheres

NASA Technical Reports Server (NTRS)

Hoffert, M. I.; Callegari, A. J.; Hsieh, C. T.; Ziegler, W.

1981-01-01

A simple climatic model is developed for a Mars atmosphere containing CO2 and sufficient liquid water to account for the observed hydrologic surface features by the existence of a CO2/H2O greenhouse effect. A latitude-resolved climate model originally devised for terrestrial climate studies is applied to Martian conditions, with the difference between absorbed solar flux and emitted long-wave flux to space per unit area attributed to the divergence of the meridional heat flux and the poleward heat flux assumed to equal the atmospheric eddy heat flux. The global mean energy balance is calculated as a function of atmospheric pressure to assess the CO2/H2O greenhouse liquid water hypothesis, and some latitude-resolved cases are examined in detail in order to clarify the role of atmospheric transport and temperature-albedo feedback. It is shown that the combined CO2/H2O greenhouse at plausible early surface pressures may account for climates hot enough to support a hydrological cycle and running water at present-day insolation and visible albedo levels.
Modeling non-linear growth responses to temperature and hydrology in wetland trees

NASA Astrophysics Data System (ADS)

Keim, R.; Allen, S. T.

2016-12-01

Growth responses of wetland trees to flooding and climate variations are difficult to model because they depend on multiple, apparently interacting factors, but are a critical link in hydrological control of wetland carbon budgets. To more generally understand tree growth to hydrological forcing, we modeled non-linear responses of tree ring growth to flooding and climate at sub-annual time steps, using Vaganov-Shashkin response functions. We calibrated the model to six baldcypress tree-ring chronologies from two hydrologically distinct sites in southern Louisiana, and tested several hypotheses of plasticity in wetlands tree responses to interacting environmental variables. The model outperformed traditional multiple linear regression. More importantly, optimized response parameters were generally similar among sites with varying hydrological conditions, suggesting generality to the functions. Model forms that included interacting responses to multiple forcing factors were more effective than were single response functions, indicating the principle of a single limiting factor is not correct in wetlands and both climatic and hydrological variables must be considered in predicting responses to hydrological or climate change.
Getting the right answers for the right reasons: Linking measurements, analyses, and models to advance the science of hydrology

NASA Astrophysics Data System (ADS)

Kirchner, James W.

2006-03-01

The science of hydrology is on the threshold of major advances, driven by new hydrologic measurements, new methods for analyzing hydrologic data, and new approaches to modeling hydrologic systems. Here I suggest several promising directions forward, including (1) designing new data networks, field observations, and field experiments, with explicit recognition of the spatial and temporal heterogeneity of hydrologic processes, (2) replacing linear, additive "black box" models with "gray box" approaches that better capture the nonlinear and non-additive character of hydrologic systems, (3) developing physically based governing equations for hydrologic behavior at the catchment or hillslope scale, recognizing that they may look different from the equations that describe the small-scale physics, (4) developing models that are minimally parameterized and therefore stand some chance of failing the tests that they are subjected to, and (5) developing ways to test models more comprehensively and incisively. I argue that scientific progress will mostly be achieved through the collision of theory and data, rather than through increasingly elaborate and parameter-rich models that may succeed as mathematical marionettes, dancing to match the calibration data even if their underlying premises are unrealistic. Thus advancing the science of hydrology will require not only developing theories that get the right answers but also testing whether they get the right answers for the right reasons.
Supporting inland waterway transport on German waterways by operational forecasting services - water-levels, discharges, river ice

NASA Astrophysics Data System (ADS)

Meißner, Dennis; Klein, Bastian; Ionita, Monica; Hemri, Stephan; Rademacher, Silke

2017-04-01

Inland waterway transport (IWT) is an important commercial sector significantly vulnerable to hydrological impacts. River ice and floods limit the availability of the waterway network and may cause considerable damages to waterway infrastructure. Low flows significantly affect IWT's operation efficiency usually several months a year due to the close correlation of (low) water levels / water depths and (high) transport costs. Therefore "navigation-related" hydrological forecasts focussing on the specific requirements of water-bound transport (relevant forecast locations, target parameters, skill characteristics etc.) play a major role in order to mitigate IWT's vulnerability to hydro-meteorological impacts. In light of continuing transport growth within the European Union, hydrological forecasts for the waterways are essential to stimulate the use of the free capacity IWT still offers more consequently. An overview of the current operational and pre-operational forecasting systems for the German waterways predicting water levels, discharges and river ice thickness on various time-scales will be presented. While short-term (deterministic) forecasts have a long tradition in navigation-related forecasting, (probabilistic) forecasting services offering extended lead-times are not yet well-established and are still subject to current research and development activities (e.g. within the EU-projects EUPORIAS and IMPREX). The focus is on improving technical aspects as well as on exploring adequate ways of disseminating and communicating probabilistic forecast information. For the German stretch of the River Rhine, one of the most frequented inland waterways worldwide, the existing deterministic forecast scheme has been extended by ensemble forecasts combined with statistical post-processing modules applying EMOS (Ensemble Model Output Statistics) and ECC (Ensemble Copula Coupling) in order to generate water level predictions up to 10 days and to estimate its predictive uncertainty properly. Additionally for the key locations at the international waterways Rhine, Elbe and Danube three competing forecast approaches are currently tested in a pre-operational set-up in order to generate monthly to seasonal (up to 3 months) forecasts: (1) the well-known Ensemble Streamflow Prediction approach (ensemble based on historical meteorology), (2) coupling hydrological models with post-processed outputs from ECMWF's general circulation model (System 4), and (3) a purely statistical approach based on the stable relationship (teleconnection) of global or regional oceanic, climate and hydrological data with river flows. The current results, still pre-operational, reveal the existence of a valuable predictability of water levels and streamflow also at monthly up to seasonal time-scales along the larger rivers used as waterways in Germany. Last but not least insight into the technical set-up of the aforementioned forecasting systems operated at the Federal Institute of Hydrology, which are based on a Delft-FEWS application, will be given focussing on the step-wise extension of the former system by integrating new components in order to meet the growing needs of the customers and to improve and extend the forecast portfolio for waterway users.
Attaining insight into interactions between hydrologic model parameters and geophysical attributes for national-scale model parameter estimation

NASA Astrophysics Data System (ADS)

Mizukami, N.; Clark, M. P.; Newman, A. J.; Wood, A.; Gutmann, E. D.

2017-12-01

Estimating spatially distributed model parameters is a grand challenge for large domain hydrologic modeling, especially in the context of hydrologic model applications such as streamflow forecasting. Multi-scale Parameter Regionalization (MPR) is a promising technique that accounts for the effects of fine-scale geophysical attributes (e.g., soil texture, land cover, topography, climate) on model parameters and nonlinear scaling effects on model parameters. MPR computes model parameters with transfer functions (TFs) that relate geophysical attributes to model parameters at the native input data resolution and then scales them using scaling functions to the spatial resolution of the model implementation. One of the biggest challenges in the use of MPR is identification of TFs for each model parameter: both functional forms and geophysical predictors. TFs used to estimate the parameters of hydrologic models typically rely on previous studies or were derived in an ad-hoc, heuristic manner, potentially not utilizing maximum information content contained in the geophysical attributes for optimal parameter identification. Thus, it is necessary to first uncover relationships among geophysical attributes, model parameters, and hydrologic processes (i.e., hydrologic signatures) to obtain insight into which and to what extent geophysical attributes are related to model parameters. We perform multivariate statistical analysis on a large-sample catchment data set including various geophysical attributes as well as constrained VIC model parameters at 671 unimpaired basins over the CONUS. We first calibrate VIC model at each catchment to obtain constrained parameter sets. Additionally, parameter sets sampled during the calibration process are used for sensitivity analysis using various hydrologic signatures as objectives to understand the relationships among geophysical attributes, parameters, and hydrologic processes.
A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE PAGES

Dai, Heng; Ye, Ming; Walker, Anthony P.; ...

2017-03-28

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less
A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Heng; Ye, Ming; Walker, Anthony P.

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less
Installation Restoration Program. Phase 2. Confirmation/Quantification. Stage 1 for Minot Air Force Base, Minot, North Dakota. Volume 3. Appendices G through M

DTIC Science & Technology

1988-10-01

TOTAL DISSOVLED SOLIDS 3523/017 1896 1918 --- 3538/024 2625 2567 --- IV. PETROLEUM HYDROCARBON DUPLICATE ANALYSIS WAS NOT DONE DUE TO INSUFFICIENT...Characterized existing hydrogeologic conditions, prepared hydrologic budgets, delineated productive aquifers, performed safe yield determinations , and...New Jersey to determine suitability for building construction. * Supervised soil borings program at large waste disposal facility in Model City, New
Development of Predictive Relationships for Flood Hazard Assessments in Ungaged Basins

DTIC Science & Technology

2016-02-01

Hydrological Analysis (GSSHA) model (Downer and Ogden 2004) was deployed in megascale for ungaged basins of the Philippine Islands . The GSSHA...et al. [1988]). STUDY AREA: Two megascale catchments in the Philippine Islands were considered in this study. No stream gage data exists for either...imagery. The Cagayan River Basin on Luzon Island (Figure 1[a]) is the largest river in the Philippines with a drainage area of 27,280 km2
Guidelines for Calculating and Routing a Dam-Break Flood.

DTIC Science & Technology

1977-01-01

flow, Teton Dam . 20. ABSTRACT (Continue an reverse aide If necessary and Identify by block number) This report described procedures necessary to calculate...and route a dam -break flood using an existing generalized unsteady open channel flow model. The recent Teton Dam event was reconstituted to test the...methodology may be obtained from The Hydrologic Engineering Center. The computer program was applied to the Teton Dam data set to demonstrate the level of
A framework for human-hydrologic system model development integrating hydrology and water management: application to the Cutzamala water system in Mexico

NASA Astrophysics Data System (ADS)

Wi, S.; Freeman, S.; Brown, C.

2017-12-01

This study presents a general approach to developing computational models of human-hydrologic systems where human modification of hydrologic surface processes are significant or dominant. A river basin system is represented by a network of human-hydrologic response units (HHRUs) identified based on locations where river regulations happen (e.g., reservoir operation and diversions). Natural and human processes in HHRUs are simulated in a holistic framework that integrates component models representing rainfall-runoff, river routing, reservoir operation, flow diversion and water use processes. We illustrate the approach in a case study of the Cutzamala water system (CWS) in Mexico, a complex inter-basin water transfer system supplying the Mexico City Metropolitan Area (MCMA). The human-hydrologic system model for CWS (CUTZSIM) is evaluated in terms of streamflow and reservoir storages measured across the CWS and to water supplied for MCMA. The CUTZSIM improves the representation of hydrology and river-operation interaction and, in so doing, advances evaluation of system-wide water management consequences under altered climatic and demand regimes. The integrated modeling framework enables evaluation and simulation of model errors throughout the river basin, including errors in representation of the human component processes. Heretofore, model error evaluation, predictive error intervals and the resultant improved understanding have been limited to hydrologic processes. The general framework represents an initial step towards fuller understanding and prediction of the many and varied processes that determine the hydrologic fluxes and state variables in real river basins.
Interaction of hydrological regime and vegetation in a seasonally flooded lake wetland (Poyang Lake) in China

NASA Astrophysics Data System (ADS)

Zhang, Qi

2017-04-01

Hydrological regime has been widely recognized as one of the major forces determining vegetation distribution in seasonally flooded wetlands. To explore the influences of hydrological conditions on the spatial distribution of wetland vegetation, an experimental transect in Poyang Lake wetland, the largest freshwater lake in China, was selected as a study area. In-situ high time frequency observations of climate, soil moisture, groundwater level and surface water level were simultaneously conducted. Vegetation was sampled periodically to obtain species composition, diversity and biomass. Results show that significant hydrological gradient exists along the experimental transect. Both groundwater level and soil moisture demonstrate high correlation with the distribution of different communities of vegetation. Above- and belowground biomass present Gaussian models along the gradient of groundwater depth in growing seasons. It was found that the optimal average groundwater depths for above- and belowground biomass are 0.8 m and 0.5 m, respectively. Numerical simulations using HYDRUS-1D further indicated that the groundwater depths had significant influences on the water usage by vegetation, which suggested the high dependence of wetland vegetation on groundwater, even in a wet climate zone such as Poyang Lake. The study revealed new knowledge on the interaction of hydrological regime and wetland vegetation, and provided scientific support for an integrated management of balancing wetland ecology and water resources development in Poyang Lake, and other lake floodplain wetlands, with strong human interferences.
Comparing Planning Hydrologic Ensembles associated with Paleoclimate, Projected Climate, and blended Climate Information Sets

NASA Astrophysics Data System (ADS)

Brekke, L. D.; Prairie, J.; Pruitt, T.; Rajagopalan, B.; Woodhouse, C.

2008-12-01

Water resources adaptation planning under climate change involves making assumptions about probabilistic water supply conditions, which are linked to a given climate context (e.g., instrument records, paleoclimate indicators, projected climate data, or blend of these). Methods have been demonstrated to associate water supply assumptions with any of these climate information types. Additionally, demonstrations have been offered that represent these information types in a scenario-rich (ensemble) planning framework, either via ensembles (e.g., survey of many climate projections) or stochastic modeling (e.g., based on instrument records or paleoclimate indicators). If the planning goal involves using a hydrologic ensemble that jointly reflects paleoclimate (e.g., lower- frequency variations) and projected climate information (e.g., monthly to annual trends), methods are required to guide how these information types might be translated into water supply assumptions. However, even if such a method exists, there is lack of understanding on how such a hydrologic ensemble might differ from ensembles developed relative to paleoclimate or projected climate information alone. This research explores two questions: (1) how might paleoclimate and projected climate information be blended into an planning hydrologic ensemble, and (2) how does a planning hydrologic ensemble differ when associated with the individual climate information types (i.e. instrumental records, paleoclimate, projected climate, or blend of the latter two). Case study basins include the Gunnison River Basin in Colorado and the Missouri River Basin above Toston in Montana. Presentation will highlight ensemble development methods by information type, and comparison of ensemble results.
Visualizing complex (hydrological) systems with correlation matrices

NASA Astrophysics Data System (ADS)

Haas, J. C.

2016-12-01

When trying to understand or visualize the connections of different aspects of a complex system, this often requires deeper understanding to start with, or - in the case of geo data - complicated GIS software. To our knowledge, correlation matrices have rarely been used in hydrology (e.g. Stoll et al., 2011; van Loon and Laaha, 2015), yet they do provide an interesting option for data visualization and analysis. We present a simple, python based way - using a river catchment as an example - to visualize correlations and similarities in an easy and colorful way. We apply existing and easy to use python packages from various disciplines not necessarily linked to the Earth sciences and can thus quickly show how different aquifers work or react, and identify outliers, enabling this system to also be used for quality control of large datasets. Going beyond earlier work, we add a temporal and spatial element, enabling us to visualize how a system reacts to local phenomena such as for example a river, or changes over time, by visualizing the passing of time in an animated movie. References: van Loon, A.F., Laaha, G.: Hydrological drought severity explained by climate and catchment characteristics, Journal of Hydrology 526, 3-14, 2015, Drought processes, modeling, and mitigation Stoll, S., Hendricks Franssen, H. J., Barthel, R., Kinzelbach, W.: What can we learn from long-term groundwater data to improve climate change impact studies?, Hydrology and Earth System Sciences 15(12), 3861-3875, 2011
Diagnosing the impact of alternative calibration strategies on coupled hydrologic models

NASA Astrophysics Data System (ADS)

Smith, T. J.; Perera, C.; Corrigan, C.

2017-12-01

Hydrologic models represent a significant tool for understanding, predicting, and responding to the impacts of water on society and society on water resources and, as such, are used extensively in water resources planning and management. Given this important role, the validity and fidelity of hydrologic models is imperative. While extensive focus has been paid to improving hydrologic models through better process representation, better parameter estimation, and better uncertainty quantification, significant challenges remain. In this study, we explore a number of competing model calibration scenarios for simple, coupled snowmelt-runoff models to better understand the sensitivity / variability of parameterizations and its impact on model performance, robustness, fidelity, and transferability. Our analysis highlights the sensitivity of coupled snowmelt-runoff model parameterizations to alterations in calibration approach, underscores the concept of information content in hydrologic modeling, and provides insight into potential strategies for improving model robustness / fidelity.
Chemical and isotopic tracers illustrate pathways of nitrogen loss in a cranberry bed

USDA-ARS?s Scientific Manuscript database

Limited research exists on the hydrological processes driving nitrogen (N) loss from cranberry production, which has been identified as a prominent source of watershed N loading in southeastern Massachusetts (MA). To quantify the hydrological processes underlying N export in cranberry farms, the geo...
Revisiting the homogenization of dammed rivers in the southeastern US

Treesearch

Ryan A. McManamay; Donald J. Orth; Charles A. Dolloff

2012-01-01

For some time, ecologists have attempted to make generalizations concerning how disturbances influence natural ecosystems, especially river systems. The existing literature suggests that dams homogenize the hydrologic variability of rivers. However, this might insinuate that dams affect river systems similarly despite a large gradient in natural hydrologic character....
One-day offset in daily hydrologic modeling: An exploration of the issue in automatic model calibration

USDA-ARS?s Scientific Manuscript database

The literature of daily hydrologic modelling illustrates that daily simulation models are incapable of accurately representing hydrograph timing due to relationships between precipitation and watershed hydrologic response. For watersheds with a time of concentration less than 24 hrs and a late day p...
A Flash Flood Study on the Small Montaneous River Catchments in Western Romania

NASA Astrophysics Data System (ADS)

Győri, Maria-Mihaela; Haidu, Ionel; Humbert, Joël

2013-04-01

The present study focuses on flash flood modeling on several mountaneous catchments situated in Western Romania by the use of two methodologies, when rainfall and catchment characteristics are known. Hence, the Soil Conservation Service (SCS) Method and the Rational Method will be employed for the generation of the 1%, 2% and 10% historical flash flood hydrographs on the basis of data spanning from 1989-2009. The SCS Method has been applied on the three gauged catchments in the study area: Petris, Troas and Monorostia making use of the existing interconnection between GIS and the rainfall-runoff models. The DEM, soil data and land use preprocessing in GIS allowed a determination of the hydrologic parameters needed for the rainfall-runoff model, with special emphasis on determining the time of concentration, Lag time and the weighted Curve Number according to Antecedent Moisture Conditions II, adapted for the Romanian territory. HEC-HMS rainfall-runoff model (Hydrologic Engineering Center- Hydrologic Modeling System) facilitates the historical 1%, 2% and 10% flash flood hydrograph generation for the three afore mentioned watersheds. The model is calibrated against measured streamflow data from the three existing gauging stations. The results show a good match between the resulted hydrographs and the observed hydrographs under the form of the Peak Weighted Error RMS values. The hydrographs generated by surface runoff on the ungauged catchments in the area is based on an automation of a workflow in GIS, built with ArcGIS Model Builder graphical interface, as a large part of the functions needed were available as ArcGIS tools. The several components of this model calculate: the runoff depth in mm, the runoff coefficient, the travel time and finally the discharge module which is an application of the rational method, allowing the discharge computation for every cell within the catchment. The result consists of discharges for each isochrones that will be subsequently interpolated in order to obtain the hydrograph of the historical flash floods. The two methodologies employed offer the hydrologist the opportunity of computing the historical hydrographs be it on a section of the river at choice, or for every affluent within the small river basins studied, the graphical data being easily accessed both in GIS and HEC-HMS. The peak discharge values of the main rivers as well as those of their tributaries are of great importance in establishing the hydrologic hazard under the form of floodplain maps that are inexistent for the studied watersheds. Key words: flash flood modeling, ungauged catchments, GIS, HEC-HMS rainfall-runoff model. Aknowledgements This work was possible with the financial support of the Sectoral Operational Programme for Human Resources Development 2007-2013, co-financed by the European Social Fund, under the project number POSDRU/107/1.5/S/76841 with the title "Modern Doctoral Studies: Internationalization and Interdisciplinarity".

A Global Classification System for Catchment Hydrology

NASA Astrophysics Data System (ADS)

Woods, R. A.

2004-05-01

It is a shocking state of affairs - there is no underpinning scientific taxonomy of catchments. There are widely used global classification systems for climate, river morphology, lakes and wetlands, but for river catchments there exists only a plethora of inconsistent, incomplete regional schemes. By proceeding without a common taxonomy for catchments, freshwater science has missed one of its key developmental stages, and has leapt from definition of phenomena to experiments, theories and models, without the theoretical framework of a classification. I propose the development of a global hierarchical classification system for physical aspects of river catchments, to help underpin physical science in the freshwater environment and provide a solid foundation for classification of river ecosystems. Such a classification scheme can open completely new vistas in hydrology: for example it will be possible to (i) rationally transfer experimental knowledge of hydrological processes between basins anywhere in the world, provided they belong to the same class; (ii) perform meaningful meta-analyses in order to reconcile studies that show inconsistent results (iii) generate new testable hypotheses which involve locations worldwide.
Data-based information gain on the response behaviour of hydrological models at catchment scale

NASA Astrophysics Data System (ADS)

Willems, Patrick

2013-04-01

A data-based approach is presented to analyse the response behaviour of hydrological models at the catchment scale. The approach starts with a number of sequential time series processing steps, applied to available rainfall, ETo and river flow observation series. These include separation of the high frequency (e.g., hourly, daily) river flow series into subflows, split of the series in nearly independent quick and slow flow hydrograph periods, and the extraction of nearly independent peak and low flows. Quick-, inter- and slow-subflow recession behaviour, sub-responses to rainfall and soil water storage are derived from the time series data. This data-based information on the catchment response behaviour can be applied on the basis of: - Model-structure identification and case-specific construction of lumped conceptual models for gauged catchments; or diagnostic evaluation of existing model structures; - Intercomparison of runoff responses for gauged catchments in a river basin, in order to identify similarity or significant differences between stations or between time periods, and relate these differences to spatial differences or temporal changes in catchment characteristics; - (based on the evaluation of the temporal changes in previous point:) Detection of temporal changes/trends and identification of its causes: climate trends, or land use changes; - Identification of asymptotic properties of the rainfall-runoff behaviour towards extreme peak or low flow conditions (for a given catchment) or towards extreme catchment conditions (for regionalization, ungauged basin prediction purposes); hence evaluating the performance of the model in making extrapolations beyond the range of available stations' data; - (based on the evaluation in previous point:) Evaluation of the usefulness of the model for making extrapolations to more extreme climate conditions projected by for instance climate models. Examples are provided for river basins in Belgium, Ethiopia, Kenya, Ecuador, Bolivia and China. References: Van Steenbergen, N., Willems, P. (2012), 'Method for testing the accuracy of rainfall-runoff models in predicting peak flow changes due to rainfall changes, in a climate changing context', Journal of Hydrology, 414-415, 425-434, doi:10.1016/j.jhydrol.2011.11.017 Mora, D., Willems, P. (2012), 'Decadal oscillations in rainfall and air temperature in the Paute River Basin - Southern Andes of Ecuador', Theoretical and Applied Climatology, 108(1), 267-282, doi:0.1007/s00704-011-0527-4 Taye, M.T., Willems, P. (2011). 'Influence of climate variability on representative QDF predictions of the upper Blue Nile Basin', Journal of Hydrology, 411, 355-365, doi:10.1016/j.jhydrol.2011.10.019 Taye, M.T., Willems, P. (2012). 'Temporal variability of hydro-climatic extremes in the Blue Nile basin', Water Resources Research, 48, W03513, 13p. Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., Willems, P., De Smedt, F., Batelaan, O. (in press), 'Climate change impact on river flows and catchment hydrology: a comparison of two spatially distributed models', Hydrological Processes; doi: 10.1002/hyp.9480 [in press
Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene

NASA Astrophysics Data System (ADS)

Thompson, S. E.; Sivapalan, M.; Harman, C. J.; Srinivasan, V.; Hipsey, M. R.; Reed, P.; Montanari, A.; Blöschl, G.

2013-12-01

Globally, many different kinds of water resources management issues call for policy- and infrastructure-based responses. Yet responsible decision-making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadal- to century-long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems. These models must be constrained to yield useful insights, despite the many likely sources of uncertainty in their predictions. Chief among these uncertainties are the impacts of the increasing role of human intervention in the global water cycle - a defining challenge for hydrology in the Anthropocene. Here we present a research agenda that proposes a suite of strategies to address these challenges from the perspectives of hydrologic science research. The research agenda focuses on the development of co-evolutionary hydrologic modeling to explore coupling across systems, and to address the implications of this coupling on the long-time behavior of the coupled systems. Three research directions support the development of these models: hydrologic reconstruction, comparative hydrology and model-data learning. These strategies focus on understanding hydrologic processes and feedbacks over long timescales, across many locations, and through strategic coupling of observational and model data in specific systems. We highlight the value of use-inspired and team-based science that is motivated by real-world hydrologic problems but targets improvements in fundamental understanding to support decision-making and management. Fully realizing the potential of this approach will ultimately require detailed integration of social science and physical science understanding of water systems, and is a priority for the developing field of sociohydrology.
Climate change: evaluating your local and regional water resources

USGS Publications Warehouse

Flint, Lorraine E.; Flint, Alan L.; Thorne, James H.

2015-01-01

The BCM is a fine-scale hydrologic model that uses detailed maps of soils, geology, topography, and transient monthly or daily maps of potential evapotranspiration, air temperature, and precipitation to generate maps of recharge, runoff, snow pack, actual evapotranspiration, and climatic water deficit. With these comprehensive environmental inputs and experienced scientific analysis, the BCM provides resource managers with important hydrologic and ecologic understanding of a landscape or basin at hillslope to regional scales. The model is calibrated using historical climate and streamflow data over the range of geologic materials specific to an area. Once calibrated, the model is used to translate climate-change data into hydrologic responses for a defined landscape, to provide managers an understanding of potential ecological risks and threats to water supplies and managed hydrologic systems. Although limited to estimates of unimpaired hydrologic conditions, estimates of impaired conditions, such as agricultural demand, diversions, or reservoir outflows can be incorporated into the calibration of the model to expand its utility. Additionally, the model can be linked to other models, such as groundwater-flow models (that is, MODFLOW) or the integrated hydrologic model (MF-FMP), to provide information about subsurface hydrologic processes. The model can be applied at a relatively small scale, but also can be applied to large-scale national and international river basins.
Mapping (dis)agreement in hydrologic projections

NASA Astrophysics Data System (ADS)

Melsen, Lieke A.; Addor, Nans; Mizukami, Naoki; Newman, Andrew J.; Torfs, Paul J. J. F.; Clark, Martyn P.; Uijlenhoet, Remko; Teuling, Adriaan J.

2018-03-01

Hydrologic projections are of vital socio-economic importance. However, they are also prone to uncertainty. In order to establish a meaningful range of storylines to support water managers in decision making, we need to reveal the relevant sources of uncertainty. Here, we systematically and extensively investigate uncertainty in hydrologic projections for 605 basins throughout the contiguous US. We show that in the majority of the basins, the sign of change in average annual runoff and discharge timing for the period 2070-2100 compared to 1985-2008 differs among combinations of climate models, hydrologic models, and parameters. Mapping the results revealed that different sources of uncertainty dominate in different regions. Hydrologic model induced uncertainty in the sign of change in mean runoff was related to snow processes and aridity, whereas uncertainty in both mean runoff and discharge timing induced by the climate models was related to disagreement among the models regarding the change in precipitation. Overall, disagreement on the sign of change was more widespread for the mean runoff than for the discharge timing. The results demonstrate the need to define a wide range of quantitative hydrologic storylines, including parameter, hydrologic model, and climate model forcing uncertainty, to support water resource planning.
Regionalization of land-use impacts on streamflow using a network of paired catchments

NASA Astrophysics Data System (ADS)

Ochoa-Tocachi, Boris F.; Buytaert, Wouter; De Bièvre, Bert

2016-09-01

Quantifying the impact of land use and cover (LUC) change on catchment hydrological response is essential for land-use planning and management. Yet hydrologists are often not able to present consistent and reliable evidence to support such decision-making. The issue tends to be twofold: a scarcity of relevant observations, and the difficulty of regionalizing any existing observations. This study explores the potential of a paired catchment monitoring network to provide statistically robust, regionalized predictions of LUC change impact in an environment of high hydrological variability. We test the importance of LUC variables to explain hydrological responses and to improve regionalized predictions using 24 catchments distributed along the Tropical Andes. For this, we calculate first 50 physical catchment properties, and then select a subset based on correlation analysis. The reduced set is subsequently used to regionalize a selection of hydrological indices using multiple linear regression. Contrary to earlier studies, we find that incorporating LUC variables in the regional model structures increases significantly regression performance and predictive capacity for 66% of the indices. For the runoff ratio, baseflow index, and slope of the flow duration curve, the mean absolute error reduces by 53% and the variance of the residuals by 79%, on average. We attribute the explanatory capacity of LUC in the regional model to the pairwise monitoring setup, which increases the contrast of the land-use signal in the data set. As such, it may be a useful strategy to optimize data collection to support watershed management practices and improve decision-making in data-scarce regions.
A new PUB-working group on SLope InterComparison Experiments (SLICE)

NASA Astrophysics Data System (ADS)

McGuire, K.; Retter, M.; Freer, J.; Troch, P.; McDonnell, J.

2006-05-01

The International Association of Hydrological Sciences (IAHS) decade on Prediction in Ungauged Basins (PUB) has the scientific goal to shift hydrology from calibration reliant models to new and rich understanding- based models. To support this, six PUB science themes have been developed under the PUB Science Steering group. Theme 1 covers basin inter-comparison and classification. The SLope InterComparison Experiment (SLICE) is a newly-formed working group aligned with theme 1. Its 2- year target is to promote the improved understanding of regional hydrological characteristics via hillslope inter- comparison studies and top-down analysis of data from hillslope experiments from around the world. It will further deliver the major building blocks of a catchment classification system. A first workshop of SLICE took place 26-28 September 2005 at the HJ Andrews Experimental Forest, Oregon, USA. 40 participants from seven countries were in attendance. The program consisted of keynote presentations on the state-of-the-art of hillslope hydrology, outlining a hillslope classification system, and through small group discussion, a focus on the following questions: a.) How can we capture flow path heterogeneity at the hillslope scale with residence time distributions? b.) Can networks help characterize hillslope subsurface systems? c.) What patterns are useful to characterize in a hillslope comparison context? d.) How does bedrock permeability condition hillslope response? e.) Can we actually observe pressure waves in the field and/or how likely are they to exist at the hillslope continuum scale? The poster presents an overview of the workshop outcomes and directions of future work.
Using high resolution DEMs to assess the effects of roads and trails on hydrological pathways that contribute to gully development

NASA Astrophysics Data System (ADS)

Sidle, R. C.; Jarihani, B.

2017-12-01

Dry savannas of northern Queensland, Australia experience severe gully erosion, particularly areas that have been heavily grazed. Field surveys have also noted the influence of unpaved roads and cattle trails on concentrating storm runoff into gully systems. To better quantify the effect of these roads and trails we use high resolution digital elevation models (DEMs) to develop indices of hydrological connectivity (IC) throughout drainage areas above and downstream of gully systems. High resolution (0.5m) DEMs from LiDAR were used to extract road and trail networks and drone-based very high resolution (0.1m) DEMs were used to extract cattle trials. IC is a function of the ratio of upslope to downslope sediment routing functions, which are based on upslope area, mean slope gradient, a weighting factor related to impedance to overland flow, and flow path distance (for the downstream function). Maps of IC within the heavily grazed Weany Creek catchment (13 km2) of northeast Queensland show that existing roads can increase hydrologic connectivity to gully systems. Furthermore, by adding roads and cattle trails into existing DEMs, we show how the extent and location of these curvilinear features affect overland flow concentration. Our findings can inform important hydrogeomorphic issues such as which gullies will likely headcut or expand and where new gullies may arise. Our analysis can also contribute to better management practices for grazing and road location.
Recession-based hydrological models for estimating low flows in ungauged catchments in the Himalayas

NASA Astrophysics Data System (ADS)

Rees, H. G.; Holmes, M. G. R.; Young, A. R.; Kansakar, S. R.

The Himalayan region of Nepal and northern India experiences hydrological extremes from monsoonal floods during July to September, when most of the annual precipitation falls, to periods of very low flows during the dry season (December to February). While the monsoon floods cause acute disasters such as loss of human life and property, mudslides and infrastructure damage, the lack of water during the dry season has a chronic impact on the lives of local people. The management of water resources in the region is hampered by relatively sparse hydrometerological networks and consequently, many resource assessments are required in catchments where no measurements exist. A hydrological model for estimating dry season flows in ungauged catchments, based on recession curve behaviour, has been developed to address this problem. Observed flows were fitted to a second order storage model to enable average annual recession behaviour to be examined. Regionalised models were developed, using a calibration set of 26 catchments, to predict three recession curve parameters: the storage constant; the initial recession flow and the start date of the recession. Relationships were identified between: the storage constant and catchment area; the initial recession flow and elevation (acting as a surrogate for rainfall); and the start date of the recession and geographic location. An independent set of 13 catchments was used to evaluate the robustness of the models. The regional models predicted the average volume of water in an annual recession period (1st of October to the 1st of February) with an average error of 8%, while mid-January flows were predicted to within ±50% for 79% of the catchments in the data set.
Insights about data assimilation frameworks for integrating GRACE with hydrological models

NASA Astrophysics Data System (ADS)

Schumacher, Maike; Kusche, Jürgen; Van Dijk, Albert I. J. M.; Döll, Petra; Schuh, Wolf-Dieter

2016-04-01

Improving the understanding of changes in the water cycle represents a challenging objective that requires merging information from various disciplines. Debates exist on selecting an appropriate assimilation technique to integrate GRACE-derived terrestrial water storage changes (TWSC) into hydrological models in order to downscale and disaggregate GRACE TWSC, overcome model limitations, and improve monitoring and forecast skills. Yet, the effect of the specific data assimilation technique in conjunction with ill-conditioning, colored noise, resolution mismatch between GRACE and model, and other complications is still unclear. Due to its simplicity, ensemble Kalman filters or smoothers (EnKF/S) are often applied. In this study, we show that modification of the filter approach might open new avenues to improve the integration process. Particularly, we discuss an improved calibration and data assimilation (C/DA) framework (Schumacher et al., 2016), which is based on the EnKF and was extended by the square root analysis scheme (SQRA) and the singular evolutive interpolated Kalman (SEIK) filter. In addition, we discuss an off-line data blending approach (Van Dijk et al., 2014) that offers the chance to merge multi-model ensembles with GRACE observations. The investigations include: (i) a theoretical comparison, focusing on similarities and differences of the conceptual formulation of the filter algorithms, (ii) a practical comparison, for which the approaches were applied to an ensemble of runs of the WaterGAP Global Hydrology Model (WGHM), as well as (iii) an impact assessment of the GRACE error structure on C/DA results. First, a synthetic experiment over the Mississippi River Basin (USA) was used to gain insights about the C/DA set-up before applying it to real data. The results indicated promising performances when considering alternative methods, e.g. applying the SEIK algorithm improved the correlation coefficient and root mean square error (RMSE) of TWSC by 0.1 and 6 mm, with respect to the EnKF. We successfully transferred our framework to the Murray-Darling Basin (Australia), one of the largest and driest river basins over the world. Finally, we provide recommendations on an optimal C/DA strategy for real GRACE data integrations. Schumacher M, Kusche J, Döll P (2016): A Systematic Impact Assessment of GRACE Error Correlation on Data Assimilation in Hydrological Models. J Geod Van Dijk AIJM, Renzullo LJ, Wada Y, Tregoning P (2014): A global water cycle reanalysis (2003-2012) merging satellite gravimetry and altimetry observations with a hydrological multi-model ensemble. Hydrol Earth Syst Sci
Integrating retention soil filters into urban hydrologic models - Relevant processes and important parameters

NASA Astrophysics Data System (ADS)

Bachmann-Machnik, Anna; Meyer, Daniel; Waldhoff, Axel; Fuchs, Stephan; Dittmer, Ulrich

2018-04-01

Retention Soil Filters (RSFs), a form of vertical flow constructed wetlands specifically designed for combined sewer overflow (CSO) treatment, have proven to be an effective tool to mitigate negative impacts of CSOs on receiving water bodies. Long-term hydrologic simulations are used to predict the emissions from urban drainage systems during planning of stormwater management measures. So far no universally accepted model for RSF simulation exists. When simulating hydraulics and water quality in RSFs, an appropriate level of detail must be chosen for reasonable balancing between model complexity and model handling, considering the model input's level of uncertainty. The most crucial parameters determining the resultant uncertainties of the integrated sewer system and filter bed model were identified by evaluating a virtual drainage system with a Retention Soil Filter for CSO treatment. To determine reasonable parameter ranges for RSF simulations, data of 207 events from six full-scale RSF plants in Germany were analyzed. Data evaluation shows that even though different plants with varying loading and operation modes were examined, a simple model is sufficient to assess relevant suspended solids (SS), chemical oxygen demand (COD) and NH4 emissions from RSFs. Two conceptual RSF models with different degrees of complexity were assessed. These models were developed based on evaluation of data from full scale RSF plants and column experiments. Incorporated model processes are ammonium adsorption in the filter layer and degradation during subsequent dry weather period, filtration of SS and particulate COD (XCOD) to a constant background concentration and removal of solute COD (SCOD) by a constant removal rate during filter passage as well as sedimentation of SS and XCOD in the filter overflow. XCOD, SS and ammonium loads as well as ammonium concentration peaks are discharged primarily via RSF overflow not passing through the filter bed. Uncertainties of the integrated simulation of the sewer system and RSF model mainly originate from the model parameters of the hydrologic sewer system model.
Multi-site calibration, validation, and sensitivity analysis of the MIKE SHE Model for a large watershed in northern China

Treesearch

S. Wang; Z. Zhang; G. Sun; P. Strauss; J. Guo; Y. Tang; A. Yao

2012-01-01

Model calibration is essential for hydrologic modeling of large watersheds in a heterogeneous mountain environment. Little guidance is available for model calibration protocols for distributed models that aim at capturing the spatial variability of hydrologic processes. This study used the physically-based distributed hydrologic model, MIKE SHE, to contrast a lumped...
Evaluating effects of potential changes in streamflow regime on fish and aquatic-invertebrate assemblages in the New Jersey Pinelands

USGS Publications Warehouse

Kennen, Jonathan G.; Riskin, Melissa L.

2010-01-01

Changes in water demand associated with population growth and changes in land-use practices in the Pinelands region of southern New Jersey will have a direct effect on stream hydrology. The most pronounced and measurable hydrologic effect is likely to be flow reductions associated with increasing water extraction. Because water-supply needs will continue to grow along with population in the Pinelands area, the goal of maintaining a sustainable balance between the availability of water to protect existing aquatic assemblages while conserving the surficial aquifer for long-term support of human water use needs to be addressed. Although many aquatic fauna have shown resilience and resistance to short-term changes in flows associated with water withdrawals, sustained effects associated with ongoing water-development processes are not well understood. In this study, the U.S. Geological Survey sampled forty-three 100-meter-long stream reaches during high- and low-flow periods across a designed hydrologic gradient ranging from small- (4.1 square kilometers (1.6 square miles)) to medium- (66.3 square kilometers (25.6 square miles)) sized Pinelands stream basins. This design, which uses basin size as a surrogate for water availability, provided an opportunity to evaluate the possible effects of potential variation in stream hydrology on fish and aquatic-invertebrate assemblage response in New Jersey Pinelands streams where future water extraction is expected based on known build-out scenarios. Multiple-regression models derived from extracted non-metric multidimensional scaling axis scores of fish and aquatic invertebrates indicate that some variability in aquatic-assemblage composition across the hydrologic gradient is associated with anthropogenic disturbance, such as urbanization, changes in stream chemistry, and concomitant changes in high-flow runoff patterns. To account for such underlying effects in the study models, any flow parameter or assemblage attribute that was found to be significantly correlated (|rho| = 0.5000) to known anthropogenic drivers (for example, the amount of urbanization in the basin) was eliminated from analysis. A reduced set of low- and annual-flow hydrologic variables, found to be unrelated to anthropogenic influences, was used to develop assemblage-response models. Many linear (monotonic) and curvilinear bivariate flow-ecology response models were developed for fish and invertebrate assemblages. For example, the duration and magnitude of low-flow events were significant predictors of invertebrate-assemblage complexity (for example, invertebrate-species richness, Plecoptera richness, and Ephemeroptera abundance); however, response models between flow attributes and fish-assemblage structure were, in all cases, more poorly fit. Annual flow variability also was important, especially variability across mean minimum monthly flows and annual mean streamflow. In general, all response models followed upward or downward trends that would be expected given hydrologic changes in Pinelands streams. This study demonstrates that the structural and functional response of aquatic assemblages of the Pinelands ecosystem resulting from changes in water-use practices associated with population growth and increased water extraction may be predictable.
Hydrological Modelling using HEC-HMS for Flood Risk Assessment of Segamat Town, Malaysia

NASA Astrophysics Data System (ADS)

Romali, N. S.; Yusop, Z.; Ismail, A. Z.

2018-03-01

This paper presents an assessment of the applicability of using Hydrologic Modelling System developed by the Hydrologic Engineering Center (HEC-HMS) for hydrological modelling of Segamat River. The objective of the model application is to assist in the assessment of flood risk by providing the peak flows of 2011 Segamat flood for the generation of flood mapping of Segamat town. The capability of the model was evaluated by comparing the historical observed data with the simulation results of the selected flood events. The model calibration and validation efficiency was verified using Nash-Sutcliffe model efficiency coefficient. The results demonstrate the interest to implement the hydrological model for assessing flood risk where the simulated peak flow result is in agreement with historical observed data. The model efficiency of the calibrated and validated exercises is 0.90 and 0.76 respectively, which is acceptable.
Is there a `universal' dynamic zero-parameter hydrological model? Evaluation of a dynamic Budyko model in US and India

NASA Astrophysics Data System (ADS)

Patnaik, S.; Biswal, B.; Sharma, V. C.

2017-12-01

River flow varies greatly in space and time, and the single biggest challenge for hydrologists and ecologists around the world is the fact that most rivers are either ungauged or poorly gauged. Although it is relatively easier to predict long-term average flow of a river using the `universal' zero-parameter Budyko model, lack of data hinders short-term flow prediction at ungauged locations using traditional hydrological models as they require observed flow data for model calibration. Flow prediction in ungauged basins thus requires a dynamic 'zero-parameter' hydrological model. One way to achieve this is to regionalize a dynamic hydrological model's parameters. However, a regionalization method based zero-parameter dynamic hydrological model is not `universal'. An alternative attempt was made recently to develop a zero-parameter dynamic model by defining an instantaneous dryness index as a function of antecedent rainfall and solar energy inputs with the help of a decay function and using the original Budyko function. The model was tested first in 63 US catchments and later in 50 Indian catchments. The median Nash-Sutcliffe efficiency (NSE) was found to be close to 0.4 in both the cases. Although improvements need to be incorporated in order to use the model for reliable prediction, the main aim of this study was to rather understand hydrological processes. The overall results here seem to suggest that the dynamic zero-parameter Budyko model is `universal.' In other words natural catchments around the world are strikingly similar to each other in the way they respond to hydrologic inputs; we thus need to focus more on utilizing catchment similarities in hydrological modelling instead of over parameterizing our models.
The Impact of Microwave-Derived Surface Soil Moisture on Watershed Hydrological Modeling

NASA Technical Reports Server (NTRS)

ONeill, P. E.; Hsu, A. Y.; Jackson, T. J.; Wood, E. F.; Zion, M.

1997-01-01

The usefulness of incorporating microwave-derived soil moisture information in a semi-distributed hydrological model was demonstrated for the Washita '92 experiment in the Little Washita River watershed in Oklahoma. Initializing the hydrological model with surface soil moisture fields from the ESTAR airborne L-band microwave radiometer on a single wet day at the start of the study period produced more accurate model predictions of soil moisture than a standard hydrological initialization with streamflow data over an eight-day soil moisture drydown.
Hydrologic restoration in a dynamic subtropical mangrove-to-marsh ecotone

USGS Publications Warehouse

Howard, Rebecca J.; Day, Richard H.; Krauss, Ken W.; From, Andrew S.; Allain, Larry K.; Cormier, Nicole

2017-01-01

Extensive hydrologic modifications in coastal regions across the world have occurred to support infrastructure development, altering the function of many coastal wetlands. Wetland restoration success is dependent on the existence of hydrologic regimes that support development of appropriate soils and the growth and persistence of wetland vegetation. In Florida, United States, the Comprehensive Everglades Restoration Program (CERP) seeks to restore, protect, and preserve water resources of the greater Everglades region. Herein we describe vegetation dynamics in a mangrove-to-marsh ecotone within the impact area of a CERP hydrologic restoration project currently under development. Vegetation communities are also described for a similar area outside the project area. We found that vegetation shifts within the impact area occurred over a 7-year period; cover of herbaceous species varied by location, and an 88% increase in the total number of mangrove seedlings was documented. We attribute these shifts to the existing modified hydrologic regime, which is characterized by a low volume of freshwater sheet flow compared with historical conditions (i.e. before modification), as well as increased tidal influence. We also identified a significant trend of decreasing soil surface elevation at the impact area. The CERP restoration project is designed to increase freshwater sheet flow to the impact area. Information from our study characterizing existing vegetation dynamics prior to implementation of the restoration project is required to allow documentation of long-term project effects on plant community composition and structure within a framework of background variation, thereby allowing assessment of the project's success in restoring critical ecosystem functions.
Inter-sectoral comparison of model uncertainty of climate change impacts in Africa

NASA Astrophysics Data System (ADS)

van Griensven, Ann; Vetter, Tobias; Piontek, Franzisca; Gosling, Simon N.; Kamali, Bahareh; Reinhardt, Julia; Dinkneh, Aklilu; Yang, Hong; Alemayehu, Tadesse

2016-04-01

We present the model results and their uncertainties of an inter-sectoral impact model inter-comparison initiative (ISI-MIP) for climate change impacts in Africa. The study includes results on hydrological, crop and health aspects. The impact models used ensemble inputs consisting of 20 time series of daily rainfall and temperature data obtained from 5 Global Circulation Models (GCMs) and 4 Representative concentration pathway (RCP). In this study, we analysed model uncertainty for the Regional Hydrological Models, Global Hydrological Models, Malaria models and Crop models. For the regional hydrological models, we used 2 African test cases: the Blue Nile in Eastern Africa and the Niger in Western Africa. For both basins, the main sources of uncertainty are originating from the GCM and RCPs, while the uncertainty of the regional hydrological models is relatively low. The hydrological model uncertainty becomes more important when predicting changes on low flows compared to mean or high flows. For the other sectors, the impact models have the largest share of uncertainty compared to GCM and RCP, especially for Malaria and crop modelling. The overall conclusion of the ISI-MIP is that it is strongly advised to use ensemble modeling approach for climate change impact studies throughout the whole modelling chain.
Accounting for spatial correlation errors in the assimilation of GRACE into hydrological models through localization

NASA Astrophysics Data System (ADS)

Khaki, M.; Schumacher, M.; Forootan, E.; Kuhn, M.; Awange, J. L.; van Dijk, A. I. J. M.

2017-10-01

Assimilation of terrestrial water storage (TWS) information from the Gravity Recovery And Climate Experiment (GRACE) satellite mission can provide significant improvements in hydrological modelling. However, the rather coarse spatial resolution of GRACE TWS and its spatially correlated errors pose considerable challenges for achieving realistic assimilation results. Consequently, successful data assimilation depends on rigorous modelling of the full error covariance matrix of the GRACE TWS estimates, as well as realistic error behavior for hydrological model simulations. In this study, we assess the application of local analysis (LA) to maximize the contribution of GRACE TWS in hydrological data assimilation. For this, we assimilate GRACE TWS into the World-Wide Water Resources Assessment system (W3RA) over the Australian continent while applying LA and accounting for existing spatial correlations using the full error covariance matrix. GRACE TWS data is applied with different spatial resolutions including 1° to 5° grids, as well as basin averages. The ensemble-based sequential filtering technique of the Square Root Analysis (SQRA) is applied to assimilate TWS data into W3RA. For each spatial scale, the performance of the data assimilation is assessed through comparison with independent in-situ ground water and soil moisture observations. Overall, the results demonstrate that LA is able to stabilize the inversion process (within the implementation of the SQRA filter) leading to less errors for all spatial scales considered with an average RMSE improvement of 54% (e.g., 52.23 mm down to 26.80 mm) for all the cases with respect to groundwater in-situ measurements. Validating the assimilated results with groundwater observations indicates that LA leads to 13% better (in terms of RMSE) assimilation results compared to the cases with Gaussian errors assumptions. This highlights the great potential of LA and the use of the full error covariance matrix of GRACE TWS estimates for improved data assimilation results.
Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene

NASA Astrophysics Data System (ADS)

Thompson, S. E.; Sivapalan, M.; Harman, C. J.; Srinivasan, V.; Hipsey, M. R.; Reed, P.; Montanari, A.; Blöschl, G.

2013-06-01

Globally, many different kinds of water resources management issues call for policy and infrastructure based responses. Yet responsible decision making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadal-to-century long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems. These models must be constrained to yield useful insights, despite the many likely sources of uncertainty in their predictions. Chief among these uncertainties are the impacts of the increasing role of human intervention in the global water cycle - a defining challenge for hydrology in the Anthropocene. Here we present a research agenda that proposes a suite of strategies to address these challenges. The research agenda focuses on the development of co-evolutionary hydrologic modeling to explore coupling across systems, and to address the implications of this coupling on the long-time behavior of the coupled systems. Three research directions support the development of these models: hydrologic reconstruction, comparative hydrology and model-data learning. These strategies focus on understanding hydrologic processes and feedbacks over long timescales, across many locations, and through strategic coupling of observational and model data in specific systems. We highlight the value of use-inspired and team-based science that is motivated by real-world hydrologic problems but targets improvements in fundamental understanding to support decision-making and management.

Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Gutmann, Ethan D.; Mendoza, Pablo A.; Newman, Andrew J.; Nijssen, Bart; Livneh, Ben; Hay, Lauren E.; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.
Improved Ground Hydrology Calculations for Global Climate Models (GCMs): Soil Water Movement and Evapotranspiration.

NASA Astrophysics Data System (ADS)

Abramopoulos, F.; Rosenzweig, C.; Choudhury, B.

1988-09-01

A physically based ground hydrology model is developed to improve the land-surface sensible and latent heat calculations in global climate models (GCMs). The processes of transpiration, evaporation from intercepted precipitation and dew, evaporation from bare soil, infiltration, soil water flow, and runoff are explicitly included in the model. The amount of detail in the hydrologic calculations is restricted to a level appropriate for use in a GCM, but each of the aforementioned processes is modeled on the basis of the underlying physical principles. Data from the Goddard Institute for Space Studies (GISS) GCM are used as inputs for off-line tests of the ground hydrology model in four 8° × 10° regions (Brazil, Sahel, Sahara, and India). Soil and vegetation input parameters are calculated as area-weighted means over the 8° × 10° gridhox. This compositing procedure is tested by comparing resulting hydrological quantities to ground hydrology model calculations performed on the 1° × 1° cells which comprise the 8° × 10° gridbox. Results show that the compositing procedure works well except in the Sahel where lower soil water levels and a heterogeneous land surface produce more variability in hydrological quantities, indicating that a resolution better than 8° × 10° is needed for that region. Modeled annual and diurnal hydrological cycles compare well with observations for Brazil, where real world data are available. The sensitivity of the ground hydrology model to several of its input parameters was tested; it was found to be most sensitive to the fraction of land covered by vegetation and least sensitive to the soil hydraulic conductivity and matric potential.
Development of Hydro-Informatic Modelling System and its Application

NASA Astrophysics Data System (ADS)

Wang, Z.; Liu, C.; Zheng, H.; Zhang, L.; Wu, X.

2009-12-01

The understanding of hydrological cycle is the core of hydrology and the scientific base of water resources management. Meanwhile, simulation of hydrological cycle has long been regarded as an important tool for the assessment, utilization and protection of water resources. In this paper, a new tool named Hydro-Informatic Modelling System (HIMS) has been developed and introduced with case studies in the Yellow River Basin in China and 331 catchments in Australia. The case studies showed that HIMS can be employed as an integrated platform for hydrological simulation in different regions. HIMS is a modular based framework of hydrological model designed for different utilization such as flood forecasting, water resources planning and evaluating hydrological impacts of climate change and human activities. The unique of HIMS is its flexibility in providing alternative modules in the simulation of hydrological cycle, which successfully overcome the difficulties in the availability of input data, the uncertainty of parameters, and the difference of rainfall-runoff processes. The modular based structure of HIMS makes it possible for developing new hydrological models by the users.
Comparisons of regional Hydrological Angular Momentum (HAM) of the different models

NASA Astrophysics Data System (ADS)

Nastula, J.; Kolaczek, B.; Popinski, W.

2006-10-01

In the paper hydrological excitations of the polar motion (HAM) were computed from various hydrological data series (NCEP, ECMWF, CPC water storage and LaD World Simulations of global continental water). HAM series obtained from these four models and the geodetic excitation function GEOD computed from the polar motion COMB03 data were compared in the seasonal spectral band. The results show big differences of these hydrological excitation functions as well as of their spectra in the seasonal spectra band. Seasonal oscillations of the global geophysical excitation functions (AAM + OAM + HAM) in all cases besides the NCEP/NCAR model are smaller than the geodetic excitation function. It means that these models need further improvement and perhaps not only hydrological models need improvements.
Elk River Watershed - Flood Study

NASA Astrophysics Data System (ADS)

Barnes, C. C.; Byrne, J. M.; MacDonald, R. J.; Lewis, D.

2014-12-01

Flooding has the potential to cause significant impacts to economic activities as well as to disrupt or displace populations. Changing climate regimes such as extreme precipitation events increase flood vulnerability and put additional stresses on infrastructure. Potential flooding from just under 100 (2009 NPRI Reviewed Facility Data Release, Environment Canada) toxic tailings ponds located in Canada increase risk to human safety and the environment. One such geotechnical failure spilt billions of litres of toxic tailings into the Fraser River watershed, British Columbia, when a tailings pond dam breach occurred in August 2014. Damaged and washed out roadways cut access to essential services as seen by the extensive floods that occurred in Saskatchewan and Manitoba in July 2014, and in Southern Alberta in 2013. Recovery efforts from events such as these can be lengthy, and have substantial social and economic impacts both in loss of revenue and cost of repair. The objective of this study is to investigate existing conditions in the Elk River watershed and model potential future hydrological changes that can increase flood risk hazards. By analyzing existing hydrology, meteorology, land cover, land use, economic, and settlement patterns a baseline is established for existing conditions in the Elk River watershed. Coupling the Generate Earth Systems Science (GENESYS) high-resolution spatial hydrometeorological model with flood hazard analysis methodology, high-resolution flood vulnerability base line maps are created using historical climate conditions. Further work in 2015 will examine possible impacts for a range of climate change and land use change scenarios to define changes to future flood risk and vulnerability.
Pursuing realistic hydrologic model under SUPERFLEX framework in a semi-humid catchment in China

NASA Astrophysics Data System (ADS)

Wei, Lingna; Savenije, Hubert H. G.; Gao, Hongkai; Chen, Xi

2016-04-01

Model realism is pursued perpetually by hydrologists for flood and drought prediction, integrated water resources management and decision support of water security. "Physical-based" distributed hydrologic models are speedily developed but they also encounter unneglectable challenges, for instance, computational time with low efficiency and parameters uncertainty. This study step-wisely tested four conceptual hydrologic models under the framework of SUPERFLEX in a small semi-humid catchment in southern Huai River basin of China. The original lumped FLEXL has hypothesized model structure of four reservoirs to represent canopy interception, unsaturated zone, subsurface flow of fast and slow components and base flow storage. Considering the uneven rainfall in space, the second model (FLEXD) is developed with same parameter set for different rain gauge controlling units. To reveal the effect of topography, terrain descriptor of height above the nearest drainage (HAND) combined with slope is applied to classify the experimental catchment into two landscapes. Then the third one (FLEXTOPO) builds different model blocks in consideration of the dominant hydrologic process corresponding to the topographical condition. The fourth one named FLEXTOPOD integrating the parallel framework of FLEXTOPO in four controlled units is designed to interpret spatial variability of rainfall patterns and topographic features. Through pairwise comparison, our results suggest that: (1) semi-distributed models (FLEXD and FLEXTOPOD) taking precipitation spatial heterogeneity into account has improved model performance with parsimonious parameter set, and (2) hydrologic model architecture with flexibility to reflect perceived dominant hydrologic processes can include the local terrain circumstances for each landscape. Hence, the modeling actions are coincided with the catchment behaviour and close to the "reality". The presented methodology is regarding hydrologic model as a tool to test our hypothesis and deepen our understanding of hydrologic processes, which will be helpful to improve modeling realism.
Long-Term Interactions of Streamflow Generation and River Basin Morphology

NASA Astrophysics Data System (ADS)

Huang, X.; Niemann, J.

2005-12-01

It is well known that the spatial patterns and dynamics of streamflow generation processes depend on river basin topography, but the impact of streamflow generation processes on the long-term evolution of river basins has not drawn as much attention. Fluvial erosion processes are driven by streamflow, which can be produced by Horton runoff, Dunne runoff, and groundwater discharge. In this analysis, we hypothesize that the dominant streamflow generation process in a basin affects the spatial patterns of fluvial erosion and that the nature of these patterns changes for storm events with differing return periods. Furthermore, we hypothesize that differences in the erosion patterns modify the topography over the long term in a way that promotes and/or inhibits the other streamflow generation mechanisms. In order to test these hypotheses, a detailed hydrologic model is imbedded into an existing landscape evolution model. Precipitation events are simulated with a Poisson process and have random intensities and durations. The precipitation is partitioned between Horton runoff and infiltration to groundwater using a specified infiltration capacity. Groundwater flow is described by a two-dimensional Dupuit equation for a homogeneous, isotropic, unconfined aquifer with an irregular underlying impervious layer. Dunne runoff occurs when precipitation falls on locations where the water table reaches the land surface. The combined hydrologic/geomorphic model is applied to the WE-38 basin, an experimental watershed in Pennsylvania that has substantial available hydrologic data. First, the hydrologic model is calibrated to reproduce the observed streamflow for 1990 using the observed rainfall as the input. Then, the relative roles of Horton runoff, Dunne runoff, and groundwater discharge are controlled by varying the infiltration capacity of the soil. For each infiltration capacity, the hydrologic and geomorphic behavior of the current topography is analyzed and the long-term evolution of the basin is simulated. The results indicate that the topography can be divided into three types of locations (unsaturated, saturated, and intermittently saturated) which control the patterns of streamflow generation for events with different return periods. The results also indicate that the streamflow generation processes can produce different geomorphic effective events at upstream and downstream locations. The model also suggests that a topography dominated by groundwater discharge evolves over a long period of time to a shape that tends to inhibit the development of saturated areas and Dunne runoff.
Modeling In-Stream Hydro-Geomorphic Processes After 2012 Waldo Canyon Fire, Colorado

NASA Astrophysics Data System (ADS)

Nourbakhshbeidokhti, S.; Kinoshita, A. M.; Chin, A.

2016-12-01

Wildfires can have significant impacts on hydrologic and geomorphic processes. Post-fire sediment transport and runoff generation vary by burn severity, precipitation, and vegetation. A need exists to understand these variable relationships and improve parameterization of post-fire hydro-geomorphic models. This research aims to model pre-fire geomorphic and hydrologic processes in Williams Canyon, a watershed burned by the 2012 Waldo Canyon Fire in Colorado. We develop the KINematic Runoff and EROSion (KINEROS) model with Geographical Information System (GIS)-based information, including a Digital Elevation Model, land cover, soil classification, precipitation, and soil burn severity for a local reference watershed that is unburned. We transfer these parameters to a channel reach in Williams Canyon (Williams Downstream) and adjust them toward post-fire conditions. We model runoff and sediment yield for several storms following the fire. Three post-fire terrestrial Light Detection and Ranging (LiDAR) images (21 April 2013, 14 September 2013, and 16 September 2014) are used to estimate total erosion and deposition at the reach scale. We use the LiDAR-based information to calibrate the post-fire model. Preliminary modeling results indicate 3870-125 kg/ha of sediment in the Williams Downstream reach. The uncalibrated model overestimated (410% in the first year) and underestimated (87.2% in the second year) the erosion. Model calibration reduced the Root Mean Square Error (RMSE) of sediment to 0.016% for the first year and 0.09% for the second year. The parameters calibrated for the Williams Downstream channel reach will be used to develop models for seven other channel reaches within the area burned by the Waldo Canyon Fire, where the performance can be evaluated with LiDAR estimates. Results of this research will enhance our understanding of wildfire disturbance on coupled hydrologic and geomorphic processes. Findings will also improve model parameterization that can be used to guide post-fire management and predictions.
Hydrological system dynamics of glaciated Karnali River Basin Nepal Himalaya using J2000 Hydrological model

NASA Astrophysics Data System (ADS)

Khatiwada, K. R.; Nepal, S.; Panthi, J., Sr.; Shrestha, M.

2015-12-01

Hydrological modelling plays an important role in understanding hydrological processes of a catchment. In the context of climate change, the understanding of hydrological characteristic of the catchment is very vital to understand how the climate change will affect the hydrological regime. This research facilitates in better understanding of the hydrological system dynamics of a himalayan mountainous catchment in western Nepal. The Karnali River, longest river flowing inside Nepal, is one of the three major basins of Nepal, having the area of 45269 sq. km. is unique. The basin has steep topography and high mountains to the northern side. The 40% of the basin is dominated by forest land while other land cover are: grass land, bare rocky land etc. About 2% of the areas in basin is covered by permanent glacier apart from that about 12% of basin has the snow and ice cover. There are 34 meteorological stations distributed across the basin. A process oriented distributed J2000 hydrologial model has been applied to understand the hydrological system dynamics. The model application provides distributed output of various hydrological components. The J2000 model applies Hydrological Response Unit (HRU) as a modelling entity. With 6861 HRU and 1010 reaches, the model was calibrated (1981-1999) and validated (2000-2004) at a daily scale using split-sample test. The model is able to capture the overall hydrological dynamics well. The rising limbs and recession limbs are simulated equally and with satisfactory ground water conditions. Based on the graphical and statistical evaluation of the model performance the model is able to simulate hydrological processes fairly well. Calibration shows that Nash Sutcliffe efficiency is 0.91, coefficient of determination is 0.92 Initial observation shows that during the pre-monsoon season(March to May) the glacial runoff is 25% of the total discharge while in the monsoon(June to September) season it is only 13%. The surface runoff contributed about 40%, 20% in subsurface while there is about 13% in the base flow. For better understanding and interpretation of the area there is still need of further coherent research and analysis for land use change and future climate change impact in the glaciered alpine catchment of Himalayan region.
Hydrological modeling in forested systems

Treesearch

H.E. Golden; G.R. Evenson; S. Tian; Devendra Amatya; Ge Sun

2015-01-01

Characterizing and quantifying interactions among components of the forest hydrological cycle is complex and usually requires a combination of field monitoring and modelling approaches (Weiler and McDonnell, 2004; National Research Council, 2008). Models are important tools for testing hypotheses, understanding hydrological processes and synthesizing experimental data...
Comparing simple and complex approaches to simulate the impacts of soil water repellency on runoff and erosion in burnt Mediterranean forest slopes

NASA Astrophysics Data System (ADS)

Nunes, João Pedro; Catarina Simões Vieira, Diana; Keizer, Jan Jacob

2017-04-01

Fires impact soil hydrological properties, enhancing soil water repellency and therefore increasing the potential for surface runoff generation and soil erosion. In consequence, the successful application of hydrological models to post-fire conditions requires the appropriate simulation of the effects of soil water repellency on soil hydrology. This work compared three approaches to model soil water repellency impacts on soil hydrology in burnt eucalypt and pine forest slopes in central Portugal: 1) Daily approach, simulating repellency as a function of soil moisture, and influencing the maximum soil available water holding capacity. It is based on the Thornthwaite-Mather soil water modelling approach, and is parameterized with the soil's wilting point and field capacity, and a parameter relating soil water repellency with water holding capacity. It was tested with soil moisture data from burnt and unburnt hillslopes. This approach was able to simulate post-fire soil moisture patterns, which the model without repellency was unable to do. However, model parameters were different between the burnt and unburnt slopes, indicating that more research is needed to derive standardized parameters from commonly measured soil and vegetation properties. 2) Seasonal approach, pre-determining repellency at the seasonal scale (3 months) in four classes (from none to extreme). It is based on the Morgan-Morgan-Finney (MMF) runoff and erosion model, applied at the seasonal scale and is parameterized with a parameter relating repellency class with field capacity. It was tested with runoff and erosion data from several experimental plots, and led to important improvements on runoff prediction over an approach with constant field capacity for all seasons (calibrated for repellency effects), but only slight improvements in erosion predictions. In contrast with the daily approach, the parameters could be reproduced between different sites 3) Constant approach, specifying values for soil water repellency for the three years after the fire, and keeping them constant throughout the year. It is based on a daily Curve Number (CN) approach, and was incorporated directly in the Soil and Water Assessment Tool (SWAT) model and tested with erosion data from a burnt hillslope. This approach was able to successfully reproduce soil erosion. The results indicate that simplified approaches can be used to adapt existing models for post-fire simulation, taking repellency into account. Taking into account the seasonality of repellency seems more important to simulate surface runoff than erosion, possibly since simulating the larger runoff rates correctly is sufficient for erosion simulation. The constant approach can be applied directly in the parameterization of existing runoff and erosion models for soil loss and sediment yield prediction, while the seasonal approach can readily be developed as a next step, with further work being needed to assess if the approach and associated parameters can be applied in multiple post-fire environments.
Snow hydrology in a general circulation model

NASA Technical Reports Server (NTRS)

Marshall, Susan; Roads, John O.; Glatzmaier, Gary

1994-01-01

A snow hydrology has been implemented in an atmospheric general circulation model (GCM). The snow hydrology consists of parameterizations of snowfall and snow cover fraction, a prognostic calculation of snow temperature, and a model of the snow mass and hydrologic budgets. Previously, only snow albedo had been included by a specified snow line. A 3-year GCM simulation with this now more complete surface hydrology is compared to a previous GCM control run with the specified snow line, as well as with observations. In particular, the authors discuss comparisons of the atmospheric and surface hydrologic budgets and the surface energy budget for U.S. and Canadian areas. The new snow hydrology changes the annual cycle of the surface moisture and energy budgets in the model. There is a noticeable shift in the runoff maximum from winter in the control run to spring in the snow hydrology run. A substantial amount of GCM winter precipitation is now stored in the seasonal snowpack. Snow cover also acts as an important insulating layer between the atmosphere and the ground. Wintertime soil temperatures are much higher in the snow hydrology experiment than in the control experiment. Seasonal snow cover is important for dampening large fluctuations in GCM continental skin temperature during the Northern Hemisphere winter. Snow depths and snow extent show good agreement with observations over North America. The geographic distribution of maximum depths is not as well simulated by the model due, in part, to the coarse resolution of the model. The patterns of runoff are qualitatively and quantitatively similar to observed patterns of streamflow averaged over the continental United States. The seasonal cycles of precipitation and evaporation are also reasonably well simulated by the model, although their magnitudes are larger than is observed. This is due, in part, to a cold bias in this model, which results in a dry model atmosphere and enhances the hydrologic cycle everywhere.
Multivariate stochastic analysis for Monthly hydrological time series at Cuyahoga River Basin

NASA Astrophysics Data System (ADS)

zhang, L.

2011-12-01

Copula has become a very powerful statistic and stochastic methodology in case of the multivariate analysis in Environmental and Water resources Engineering. In recent years, the popular one-parameter Archimedean copulas, e.g. Gumbel-Houggard copula, Cook-Johnson copula, Frank copula, the meta-elliptical copula, e.g. Gaussian Copula, Student-T copula, etc. have been applied in multivariate hydrological analyses, e.g. multivariate rainfall (rainfall intensity, duration and depth), flood (peak discharge, duration and volume), and drought analyses (drought length, mean and minimum SPI values, and drought mean areal extent). Copula has also been applied in the flood frequency analysis at the confluences of river systems by taking into account the dependence among upstream gauge stations rather than by using the hydrological routing technique. In most of the studies above, the annual time series have been considered as stationary signal which the time series have been assumed as independent identically distributed (i.i.d.) random variables. But in reality, hydrological time series, especially the daily and monthly hydrological time series, cannot be considered as i.i.d. random variables due to the periodicity existed in the data structure. Also, the stationary assumption is also under question due to the Climate Change and Land Use and Land Cover (LULC) change in the fast years. To this end, it is necessary to revaluate the classic approach for the study of hydrological time series by relaxing the stationary assumption by the use of nonstationary approach. Also as to the study of the dependence structure for the hydrological time series, the assumption of same type of univariate distribution also needs to be relaxed by adopting the copula theory. In this paper, the univariate monthly hydrological time series will be studied through the nonstationary time series analysis approach. The dependence structure of the multivariate monthly hydrological time series will be studied through the copula theory. As to the parameter estimation, the maximum likelihood estimation (MLE) will be applied. To illustrate the method, the univariate time series model and the dependence structure will be determined and tested using the monthly discharge time series of Cuyahoga River Basin.
Five Guidelines for Selecting Hydrological Signatures

NASA Astrophysics Data System (ADS)

McMillan, H. K.; Westerberg, I.; Branger, F.

2017-12-01

Hydrological signatures are index values derived from observed or modeled series of hydrological data such as rainfall, flow or soil moisture. They are designed to extract relevant information about hydrological behavior, such as to identify dominant processes, and to determine the strength, speed and spatiotemporal variability of the rainfall-runoff response. Hydrological signatures play an important role in model evaluation. They allow us to test whether particular model structures or parameter sets accurately reproduce the runoff generation processes within the watershed of interest. Most modeling studies use a selection of different signatures to capture different aspects of the catchment response, for example evaluating overall flow distribution as well as high and low flow extremes and flow timing. Such studies often choose their own set of signatures, or may borrow subsets of signatures used in multiple other works. The link between signature values and hydrological processes is not always straightforward, leading to uncertainty and variability in hydrologists' signature choices. In this presentation, we aim to encourage a more rigorous approach to hydrological signature selection, which considers the ability of signatures to represent hydrological behavior and underlying processes for the catchment and application in question. To this end, we propose a set of guidelines for selecting hydrological signatures. We describe five criteria that any hydrological signature should conform to: Identifiability, Robustness, Consistency, Representativeness, and Discriminatory Power. We describe an example of the design process for a signature, assessing possible signature designs against the guidelines above. Due to their ubiquity, we chose a signature related to the Flow Duration Curve, selecting the FDC mid-section slope as a proposed signature to quantify catchment overall behavior and flashiness. We demonstrate how assessment against each guideline could be used to compare or choose between alternative signature definitions. We believe that reaching a consensus on selection criteria for hydrological signatures will assist modelers to choose between competing signatures, facilitate comparison between hydrological studies, and help hydrologists to fully evaluate their models.
Changes to Watershed Hydrology due to Changing Snowmelt Patterns, Michigan, US

NASA Astrophysics Data System (ADS)

Ford, C.; Kendall, A. D.; Hyndman, D. W.

2017-12-01

With increasing temperatures and changing precipitation patterns associated with global climate change, the future of hydrologic resources related to snowmelt is less certain than ever. Most existing snowmelt hydrology research focuses on mountainous regions such as the western United States, where snowpack is a primary reservoir of available freshwater. Less research has been done on snowmelt hydrology in non-mountainous, temperate middle to upper latitude regions such as the Midwestern US, where snowmelt is still an important contributor to water budgets (and critically summer water supplies). This study examines the changes to watershed hydrology due to changing snowmelt patterns in Michigan, which has a tension line between seasonally-persistent snowpacks in the north, and episodic snowpacks in the south. This transition varies in space and time, and is likely moving northward as a consequence of climate change. Changes to snow and winter weather were statistically determined from output of the NOAA's Snow Data Assimilation System (SNODAS) model along with historical weather data from the Global Historical Climatology Network. Stream data from the USGS, combined with in-house monitoring data from groundwater and soil moisture networks provide insight into the hydrologic changes. Snowmelt in years with warmer winter temperatures tend to end earlier in the year, resulting in earlier peak stream flows. These changes become more noticeable in the northern regions of the state, where snowfall amounts can be amongst the largest in the country. This study also examines the changing spatial transition zone between regions with snow lasting throughout the season and regions with a more episodic snow presence. In an area with some of the largest freshwater resources in the world, significant changes to streamflow and groundwater recharge could impact already stressed ecosystems and local water supplies.
Socio-hydrological modelling of floods: investigating community resilience, adaptation capacity and risk

NASA Astrophysics Data System (ADS)

Ciullo, Alessio; Viglione, Alberto; Castellarin, Attilio

2016-04-01

Changes in flood risk occur because of changes in climate and hydrology, and in societal exposure and vulnerability. Research on change in flood risk has demonstrated that the mutual interactions and continuous feedbacks between floods and societies has to be taken into account in flood risk management. The present work builds on an existing conceptual model of an hypothetical city located in the proximity of a river, along whose floodplains the community evolves over time. The model reproduces the dynamic co-evolution of four variables: flooding, population density of the flooplain, amount of structural protection measures and memory of floods. These variables are then combined in a way to mimic the temporal change of community resilience, defined as the (inverse of the) amount of time for the community to recover from a shock, and adaptation capacity, defined as ratio between damages due to subsequent events. Also, temporal changing exposure, vulnerability and probability of flooding are also modelled, which results in a dynamically varying flood-risk. Examples are provided that show how factors such as collective memory and risk taking attitude influence the dynamics of community resilience, adaptation capacity and risk.
A comparison of tools for modeling freshwater ecosystem services.

PubMed

Vigerstol, Kari L; Aukema, Juliann E

2011-10-01

Interest in ecosystem services has grown tremendously among a wide range of sectors, including government agencies, NGO's and the business community. Ecosystem services entailing freshwater (e.g. flood control, the provision of hydropower, and water supply), as well as carbon storage and sequestration, have received the greatest attention in both scientific and on-the-ground applications. Given the newness of the field and the variety of tools for predicting water-based services, it is difficult to know which tools to use for different questions. There are two types of freshwater-related tools--traditional hydrologic tools and newer ecosystem services tools. Here we review two of the most prominent tools of each type and their possible applications. In particular, we compare the data requirements, ease of use, questions addressed, and interpretability of results among the models. We discuss the strengths, challenges and most appropriate applications of the different models. Traditional hydrological tools provide more detail whereas ecosystem services tools tend to be more accessible to non-experts and can provide a good general picture of these ecosystem services. We also suggest gaps in the modeling toolbox that would provide the greatest advances by improving existing tools. Copyright © 2011 Elsevier Ltd. All rights reserved.
Modeling effectiveness of management practices for flood mitigation using GIS spatial analysis functions in Upper Cilliwung watershed

NASA Astrophysics Data System (ADS)

Darma Tarigan, Suria

2016-01-01

Flooding is caused by excessive rainfall flowing downstream as cumulative surface runoff. Flooding event is a result of complex interaction of natural system components such as rainfall events, land use, soil, topography and channel characteristics. Modeling flooding event as a result of interaction of those components is a central theme in watershed management. The model is usually used to test performance of various management practices in flood mitigation. There are various types of management practices for flood mitigation including vegetative and structural management practices. Existing hydrological model such as SWAT and HEC-HMS models have limitation to accommodate discrete management practices such as infiltration well, small farm reservoir, silt pits in its analysis due to the lumped structure of these models. Aim of this research is to use raster spatial analysis functions of Geo-Information System (RGIS-HM) to model flooding event in Ciliwung watershed and to simulate impact of discrete management practices on surface runoff reduction. The model was validated using flooding data event of Ciliwung watershed on 29 January 2004. The hourly hydrograph data and rainfall data were available during period of model validation. The model validation provided good result with Nash-Suthcliff efficiency of 0.8. We also compared the RGIS-HM with Netlogo Hydrological Model (NL-HM). The RGIS-HM has similar capability with NL-HM in simulating discrete management practices in watershed scale.
Testing the Structure of Hydrological Models using Genetic Programming

NASA Astrophysics Data System (ADS)

Selle, B.; Muttil, N.

2009-04-01

Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that genetic programming can be used to test the structure hydrological models and to identify dominant processes in hydrological systems. To test this, genetic programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, water table depths and water ponding times during surface irrigation. Using genetic programming, a simple model of deep percolation was consistently evolved in multiple model runs. This simple and interpretable model confirmed the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that genetic programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.
On the importance of methods in hydrological modelling. Perspectives from a case study

NASA Astrophysics Data System (ADS)

Fenicia, Fabrizio; Kavetski, Dmitri

2017-04-01

The hydrological community generally appreciates that developing any non-trivial hydrological model requires a multitude of modelling choices. These choices may range from a (seemingly) straightforward application of mass conservation, to the (often) guesswork-like selection of constitutive functions, parameter values, etc. The application of a model itself requires a myriad of methodological choices - the selection of numerical solvers, objective functions for model calibration, validation approaches, performance metrics, etc. Not unreasonably, hydrologists embarking on ever ambitious projects prioritize hydrological insight over the morass of methodological choices. Perhaps to emphasize "ideas" over "methods", some journals have even reduced the fontsize of the methodology sections of its articles. However, the very nature of modelling is that seemingly routine methodological choices can significantly affect the conclusions of case studies and investigations - making it dangerous to skimp over methodological details in an enthusiastic rush towards the next great hydrological idea. This talk shares modelling insights from a hydrological study of a 300 km2 catchment in Luxembourg, where the diversity of hydrograph dynamics observed at 10 locations begs the question of whether external forcings or internal catchment properties act as dominant controls on streamflow generation. The hydrological insights are fascinating (at least to us), but in this talk we emphasize the impact of modelling methodology on case study conclusions and recommendations. How did we construct our prior set of hydrological model hypotheses? What numerical solver was implemented and why was an objective function based on Bayesian theory deployed? And what would have happened had we omitted model cross-validation, or not used a systematic hypothesis testing approach?

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