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Sample records for advanced hydrology model

  1. Accelerating advances in continental domain hydrologic modeling

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    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.

  2. Advancing reservoir operation description in physically based hydrological models

    NASA Astrophysics Data System (ADS)

    Anghileri, Daniela; Giudici, Federico; Castelletti, Andrea; Burlando, Paolo

    2016-04-01

    Last decades have seen significant advances in our capacity of characterizing and reproducing hydrological processes within physically based models. Yet, when the human component is considered (e.g. reservoirs, water distribution systems), the associated decisions are generally modeled with very simplistic rules, which might underperform in reproducing the actual operators' behaviour on a daily or sub-daily basis. For example, reservoir operations are usually described by a target-level rule curve, which represents the level that the reservoir should track during normal operating conditions. The associated release decision is determined by the current state of the reservoir relative to the rule curve. This modeling approach can reasonably reproduce the seasonal water volume shift due to reservoir operation. Still, it cannot capture more complex decision making processes in response, e.g., to the fluctuations of energy prices and demands, the temporal unavailability of power plants or varying amount of snow accumulated in the basin. In this work, we link a physically explicit hydrological model with detailed hydropower behavioural models describing the decision making process by the dam operator. In particular, we consider two categories of behavioural models: explicit or rule-based behavioural models, where reservoir operating rules are empirically inferred from observational data, and implicit or optimization based behavioural models, where, following a normative economic approach, the decision maker is represented as a rational agent maximising a utility function. We compare these two alternate modelling approaches on the real-world water system of Lake Como catchment in the Italian Alps. The water system is characterized by the presence of 18 artificial hydropower reservoirs generating almost 13% of the Italian hydropower production. Results show to which extent the hydrological regime in the catchment is affected by different behavioural models and reservoir

  3. Global scale hydrology - Advances in land surface modeling

    SciTech Connect

    Wood, E.F. )

    1991-01-01

    Research into global scale hydrology is an expanding area that includes researchers from the meteorology, climatology, ecology and hydrology communities. This paper reviews research in this area carried out in the United States during the last IUGG quadrennial period of 1987-1990. The review covers the representation of land-surface hydrologic processes for general circulation models (GCMs), sensitivity analysis of these representations on global hydrologic fields like precipitation, regional studies of climate that have global hydrologic implications, recent field studies and experiments whose aims are the improved understanding of land surface-atmospheric interactions, and the use of remotely sensed data for the further understanding of the spatial variability of surface hydrologic processes that are important at regional and global climate scales. 76 refs.

  4. Advancing Collaboration through Hydrologic Data and Model Sharing

    NASA Astrophysics Data System (ADS)

    Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Band, L. E.; Merwade, V.; Couch, A.; Hooper, R. P.; Maidment, D. R.; Dash, P. K.; Stealey, M.; Yi, H.; Gan, T.; Castronova, A. M.; Miles, B.; Li, Z.; Morsy, M. M.

    2015-12-01

    HydroShare is an online, collaborative system for open sharing of hydrologic data, analytical tools, and models. It supports the sharing of and collaboration around "resources" which are defined primarily by standardized metadata, content data models for each resource type, and an overarching resource data model based on the Open Archives Initiative's Object Reuse and Exchange (OAI-ORE) standard and a hierarchical file packaging system called "BagIt". HydroShare expands the data sharing capability of the CUAHSI Hydrologic Information System by broadening the classes of data accommodated to include geospatial and multidimensional space-time datasets commonly used in hydrology. HydroShare also includes new capability for sharing models, model components, and analytical tools and will take advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. It also supports web services and server/cloud based computation operating on resources for the execution of hydrologic models and analysis and visualization of hydrologic data. HydroShare uses iRODS as a network file system for underlying storage of datasets and models. Collaboration is enabled by casting datasets and models as "social objects". Social functions include both private and public sharing, formation of collaborative groups of users, and value-added annotation of shared datasets and models. The HydroShare web interface and social media functions were developed using the Django web application framework coupled to iRODS. Data visualization and analysis is supported through the Tethys Platform web GIS software stack. Links to external systems are supported by RESTful web service interfaces to HydroShare's content. This presentation will introduce the HydroShare functionality developed to date and describe ongoing development of functionality to support collaboration and integration of data and models.

  5. Advances in Modeling of Coupled Hydrologic-Socioeconomic Systems

    NASA Astrophysics Data System (ADS)

    Amadio, Mattia; Mysiak, Jaroslav; Pecora, Silvano; Agnetti, Alberto

    2013-04-01

    River flooding is the most common natural disaster in Europe, causing deaths and huge amount of economic losses. Disastrous flood events are often related to extreme meteorological conditions; therefore, climate change is expected to have an important influence over the intensity and frequency of major floods. While approximated large-scale assessments of flood risk scenarios have been carried out, the knowledge of the effects at smaller scales is poor or incomplete, with few localized studies. Also, the methods are still coarse and uneven. The approach of this study starts from the definition of the risk paradigm and the elaboration of local climatic scenarios to track a methodology aimed at elaborating and combining the three elements concurring to the determination of risk: hydrological hazard, value exposure and vulnerability. First, hydrological hazard scenarios are provided by hydrological and hydrodynamic models, used in to a flood forecasting system capable to define "what-if" scenario in a flexible way. These results are then integrated with land-use data (exposure) and depth-damage functions (vulnerability) in a GIS environment, to assess the final risk value (potential flood damage) and visualize it in form of risk maps. In this paper results from a pilot study in the Polesine area are presented, where four simulated levee breach scenarios are compared. The outcomes of the analysis may be instrumental to authorities to increase the knowledge of possible direct losses and guide decision making and planning processes also. As future perspective, the employed methodology can also be extended at the basin scale through integration with the existent flood warning system to gain a real-time estimate of floods direct costs.

  6. Demasking the integrated value of discharge - Advanced sensitivity analysis on the components of hydrological models

    NASA Astrophysics Data System (ADS)

    Guse, Björn; Pfannerstill, Matthias; Gafurov, Abror; Fohrer, Nicola; Gupta, Hoshin

    2016-04-01

    The hydrologic response variable most often used in sensitivity analysis is discharge which provides an integrated value of all catchment processes. The typical sensitivity analysis evaluates how changes in the model parameters affect the model output. However, due to discharge being the aggregated effect of all hydrological processes, the sensitivity signal of a certain model parameter can be strongly masked. A more advanced form of sensitivity analysis would be achieved if we could investigate how the sensitivity of a certain modelled process variable relates to the changes in a parameter. Based on this, the controlling parameters for different hydrological components could be detected. Towards this end, we apply the approach of temporal dynamics of parameter sensitivity (TEDPAS) to calculate the daily sensitivities for different model outputs with the FAST method. The temporal variations in parameter dominance are then analysed for both the modelled hydrological components themselves, and also for the rates of change (derivatives) in the modelled hydrological components. The daily parameter sensitivities are then compared with the modelled hydrological components using regime curves. Application of this approach shows that when the corresponding modelled process is investigated instead of discharge, we obtain both an increased indication of parameter sensitivity, and also a clear pattern showing how the seasonal patterns of parameter dominance change over time for each hydrological process. By relating these results with the model structure, we can see that the sensitivity of model parameters is influenced by the function of the parameter. While capacity parameters show more sensitivity to the modelled hydrological component, flux parameters tend to have a higher sensitivity to rates of change in the modelled hydrological component. By better disentangling the information hidden in the discharge values, we can use sensitivity analyses to obtain a clearer signal

  7. Advancement of Satellite-based Rainfall Applications for Hydrologic Modeling in Topographically Complex Regions

    NASA Astrophysics Data System (ADS)

    Yilmaz, Koray; Derin, Yagmur

    2014-05-01

    Accuracy and reliability of hydrological modeling studies heavily depends on quality and availability of precipitation estimates. However hydrological studies in developing countries, especially over complex topography, are limited due to unavailability and scarcity of ground-based networks. In this study we evaluate three different satellite-based rainfall retrieval algorithms namely, Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA), NOAA/Climate Prediction Center Morphing Method (CMORPH) and EUMETSAT's Multi-Sensor Precipitation Estimate (MPE) over orographically complex Western Black Sea Basin in Turkey, using a relatively dense rain gauge network. Our results indicated that satellite-based products significantly underestimated the rainfall in regions characterized by orographic rainfall and overestimated the rainfall in the drier regions with seasonal dependency. Further, we devised a new bias adjustment algorithm for the satellite-based rainfall products based on the "physiographic similarity" concept. Our results showed that proposed bias adjustment algorithm is better suited to regions with complex topography and provided improved results compared to the baseline "inverse distance weighting" method. To evaluate the utility of satellite-based products in hydrologic modeling studies, we implemented the MIKE SHE-MIKE 11 integrated fully distributed physically based hydrological model in the study region driven by ground-based and satellite-based precipitation estimates. Model parameter estimation was performed using a constrained calibration approach guided by multiple "signature measures" to estimate model parameters in a hydrologically meaningful way rather than using the traditional "statistical" objective functions that largely mask valuable hydrologic information during calibration process. In this presentation we will provide a discussion of evaluation and bias correction of the satellite-based precipitation products and

  8. Modular Curriculum for Hydrologic Advancement (MOCHA)

    NASA Astrophysics Data System (ADS)

    Kelleher, C.; Wagener, T.; Gooseff, M.; McGlynn, B.; Marshall, L.; Meixner, T.; McGuire, K.; Sharma, P.; Zuppe, S.; Pfeiffer, C.

    2008-12-01

    In-class hydrology education is typically strongly biased towards the instructor's background and overcoming this limitation is burdensome within the time-constraints academia. This problem is particularly true for academics in tenure-track positions when most of the material development must occur. To overcome this challenge and advance a broader perspective of hydrology education, we are in the process of establishing the Modular Curriculum for Hydrologic Advancement (MOCHA). The objective is to create an evolving core curriculum for hydrology education freely available to, developed, and reviewed by the worldwide hydrologic community. We seek to establish an online faculty learning community for hydrology education and a modular core curriculum based on modern pedagogical standards. The goal of this effort is to support hydrology faculty in educating hydrologists that can solve today's and tomorrow's interdisciplinary problems that go far beyond the traditional disciplinary biased hydrology education most of us have experienced.

  9. Advancing Ensemble Streamflow Prediction with Stochastic Meteorological Forcings for Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Caraway, N.; Wood, A. W.; Rajagopalan, B.; Zagona, E. A.; Daugherty, L.

    2012-12-01

    River Forecast Centers of National Weather Service (NWS) produce seasonal streamflow forecasts via a method called Ensemble Streamflow Prediction (ESP). NWS ESP forces the temperature index Snow17 and Sacramento Soil Moisture Accounting model (SAC-SMA) models with historical weather sequences for the forecasting period, starting from models' current watershed initial conditions, to produce ensemble streamflow forecasts. There are two major drawbacks of this method: (i) the ensembles are limited to the length of historical, limiting ensemble variability and (ii) incorporating seasonal climate forecasts (e.g., El Nino Southern Oscillation) relies on adjustment or weighting of ESP streamflow sequences. These drawbacks motivate the research presented here, which has two components: (i) a multi-site stochastic weather generator and (ii) generation of ensemble weather forecast inputs to the NWS model to produce ensemble streamflow forecasts. We enhanced the K-nearest neighbor bootstrap based stochastic generator include: (i) clustering the forecast locations into climatologically homogeneous regions to better capture the spatial heterogeneity and, (ii) conditioning the weather forecasts on a probabilistic seasonal climate forecast. This multi-site stochastic weather generator runs in R and the NWS models run within the new Community Hydrologic Prediction System, a forecasting sequence we label WG-ESP. The WG-ESP framework was applied to generate ensemble forecasts of spring season (April-July) streamflow in the San Juan River Basin, one of the major tributaries of the Colorado River, for the period 1981-2010. The hydrologic model requires daily weather sequences at 66 locations in the basin. The enhanced daily weather generator sequences captured the distributional properties and spatial dependence of the climatological ESP, and also generated weather sequences consistent with conditioning on seasonal climate forecasts. Spring season ensemble forecast lead times from

  10. Using Small Unmanned Aerial Systems to Advance Hydrological Models in Coastal Watersheds

    NASA Astrophysics Data System (ADS)

    Moorhead, R.; Hathcock, L.; Coffey, J. J.; Hood, R. E.; van Cooten, S.; Choate, K.; Rawson, H.; Kosturock, A.

    2014-12-01

    Small unmanned aerial systems (sUASs) have the potential to provide highly useful information for models of earth systems that vary over time intervals of days and for which sub-meter resolution is crucial. In particular, the state of coastal watershed plains are highly dependent on vegetation type and cover, soil type, weather, river flooding, and coastal inundation. The vegetation type and cover affect the drying potential, as well as the watershed's resistance to flood water movement. The soil type, soil moisture, and pond depths affect the ability of the watershed to absorb river flood waters and inundation from the sea. In this presentation we will describe a data collection campaign and model modification effort for hydrological models in a coastal watershed. The data collection campaign is obtaining data bimonthly using multiple UASs to capture the state of the watershed quicker. In particular, the vegetation cover and the extent of the water surface expression are captured at approximately a 1 inch spatial resolution over a few days with sUASs that can image 1-2 square miles per hour. The vegetation data provides a time-varying input to improve the estimation of the roughness coefficient and the dry potential from the traditionally static datasets. By correlating the high spatio-temporal resolution surface water expression with data from approximately ten river gauges, models can be improved and validated under more conditions. The presentation will also discuss the requisite sUAS capabilities and our experience in using them.

  11. The Modular Curriculum for Hydrologic Advancement (MOCHA)

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    In-class hydrology education is typically strongly biased towards the instructor's background and overcoming this limitation is overly burdensome within the time-constraints of the academic life. This is particularly true for academics in tenure-track positions when most of the material development has to occur. To overcome this issue, we are in the process of establishing the Modular Curriculum for Hydrologic Advancement (MOCHA). Our overall objective is to create an evolving core curriculum for hydrology education freely available to and developed and reviewed by the worldwide hydrologic community. We seek to establish an online faculty learning community for hydrology education and a modular core curriculum based on modern pedagogical standards. The goal of this effort is to support hydrology faculty in educating hydrologists that can solve today's and tomorrow's interdisciplinary problems that go far beyond the traditional disciplinary biased hydrology education most of us have experienced.

  12. Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model

    NASA Astrophysics Data System (ADS)

    Ragettli, S.; Pellicciotti, F.; Immerzeel, W. W.; Miles, E. S.; Petersen, L.; Heynen, M.; Shea, J. M.; Stumm, D.; Joshi, S.; Shrestha, A.

    2015-04-01

    The hydrology of high-elevation watersheds of the Hindu Kush-Himalaya region (HKH) is poorly known. The correct representation of internal states and process dynamics in glacio-hydrological models can often not be verified due to missing in situ measurements. We use a new set of detailed ground data from the upper Langtang valley in Nepal to systematically guide a state-of-the art glacio-hydrological model through a parameter assigning process with the aim to understand the hydrology of the catchment and contribution of snow and ice processes to runoff. 14 parameters are directly calculated on the basis of local data, and 13 parameters are calibrated against 5 different datasets of in situ or remote sensing data. Spatial fields of debris thickness are reconstructed through a novel approach that employs data from an Unmanned Aerial Vehicle (UAV), energy balance modeling and statistical techniques. The model is validated against measured catchment runoff (Nash-Sutcliffe efficiency 0.87) and modeled snow cover is compared to Landsat snow cover. The advanced representation of processes allowed assessing the role played by avalanching for runoff for the first time for a Himalayan catchment (5% of annual water inputs to the hydrological system are due to snow redistribution) and to quantify the hydrological significance of sub-debris ice melt (9% of annual water inputs). Snowmelt is the most important contributor to total runoff during the hydrological year 2012/2013 (representing 40% of all sources), followed by rainfall (34%) and ice melt (26%). A sensitivity analysis is used to assess the efficiency of the monitoring network and identify the timing and location of field measurements that constrain model uncertainty. The methodology to set up a glacio-hydrological model in high-elevation regions presented in this study can be regarded as a benchmark for modelers in the HKH seeking to evaluate their calibration approach, their experimental setup and thus to reduce the

  13. Hydrological models are mediating models

    NASA Astrophysics Data System (ADS)

    Babel, L. V.; Karssenberg, D.

    2013-08-01

    Despite the increasing role of models in hydrological research and decision-making processes, only few accounts of the nature and function of models exist in hydrology. Earlier considerations have traditionally been conducted while making a clear distinction between physically-based and conceptual models. A new philosophical account, primarily based on the fields of physics and economics, transcends classes of models and scientific disciplines by considering models as "mediators" between theory and observations. The core of this approach lies in identifying models as (1) being only partially dependent on theory and observations, (2) integrating non-deductive elements in their construction, and (3) carrying the role of instruments of scientific enquiry about both theory and the world. The applicability of this approach to hydrology is evaluated in the present article. Three widely used hydrological models, each showing a different degree of apparent physicality, are confronted to the main characteristics of the "mediating models" concept. We argue that irrespective of their kind, hydrological models depend on both theory and observations, rather than merely on one of these two domains. Their construction is additionally involving a large number of miscellaneous, external ingredients, such as past experiences, model objectives, knowledge and preferences of the modeller, as well as hardware and software resources. We show that hydrological models convey the role of instruments in scientific practice by mediating between theory and the world. It results from these considerations that the traditional distinction between physically-based and conceptual models is necessarily too simplistic and refers at best to the stage at which theory and observations are steering model construction. The large variety of ingredients involved in model construction would deserve closer attention, for being rarely explicitly presented in peer-reviewed literature. We believe that devoting

  14. Advanced flood forecasting in Alpine watersheds by coupling meteorological observations and forecasts with a distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Jasper, Karsten; Gurtz, Joachim; Lang, Herbert

    2002-10-01

    Flood forecasting may be improved by coupling atmospheric and hydrological models. To investigate the current potential of such an approach in complex mountain watersheds, the authors carried out a number of combined high-resolution one-way driven model experiments to generate runoff hydrographs for seven extreme flood events which occurred in the Lago Maggiore basin between 1993 and 2000. The Alpine Ticino-Verzasca-Maggia basin (2627 km 2) is located directly to the south of the main Alpine ridge embracing a great part of the drainage area of Lago Maggiore. For this basin, the grid-based hydrological catchment model WaSiM-ETH was employed to determine the continuous runoff hydrographs. In the model experiments, two different sets of meteorological input data were used: (1) surface observation data from station measurements and from weather radar, and (2) forecast data from five different high-resolution numerical weather prediction (NWP) models with grid cell sizes between 2 and 14 km. This paper presents and compares selected results of these flood runoff simulations with particular attention to the experimental design of the model coupling. The configuration and initialization of the hydrological model runs are outlined as well as the down-scale techniques which proved to provide an adequate spatial interpolation of the meteorological variables onto the 500 m×500 m grid of the hydrological model. In order to evaluate the various hydrological model results as generated from the different outputs from the five NWP models, some coupled experiments with 'non-standard' NWP model outputs have been carried out. In particular, the results of these sensitivity studies point to inherent limits of high-resolution flood runoff predictions in complex mountain terrain.

  15. A University Consortium for the Advancement of Hydrologic Research

    NASA Astrophysics Data System (ADS)

    Hooper, R. P.; Wilson, J.; Band, L.; Reckhow, K.

    2003-12-01

    Seventy-six research universities across the United States have joined to form the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI), a non-profit corporation. With support from the National Science Foundation, CUAHSI has embarked upon the design and development of programs to enable hydrologic research at larger spatial scales over longer time periods than has been within the grasp of individual investigators. The guiding principle of this design has been an embracing of the entire hydrologic cycle to enable research at the interfaces among traditional hydrologic subdisciplines and between hydrologic science and allied disciplines in the earth and life sciences. To improve our predictive understanding of hydrologic phenomena, the fundamental approach that has been adopted is the development of multidisciplinary, coherent data sets to enable testing of hypotheses in different hydrologic settings across a range of spatial and temporal scales. Four mutually supportive program elements have been conceived: a network of hydrologic observatories (the subject of this special session) designed strategically to collect additional data at large scales (on the order of 10,000 km2) and to leverage existing investments in small-scale intensive studies and in larger scale monitoring activities; hydrologic information systems to develop a comprehensive data model for integrating disparate data types, to develop the cyberinfrastructure necessary for systematic data collection and dissemination and to support community models; hydrologic measurement technology facility to broker instrumentation services from existing sources, to provide cutting edge tools along with the necessary support to use them, and to develop new hydrologic instrumentation needed to advance the science; and hydrologic synthesis center to provide a venue for hydrologic sciences from a range of disciplines to work on topics ranging from inter-observatory comparison to evolving

  16. Soil hydrology: Recent methodological advances, challenges, and perspectives

    NASA Astrophysics Data System (ADS)

    Vereecken, H.; Huisman, J. A.; Hendricks Franssen, H. J.; Brüggemann, N.; Bogena, H. R.; Kollet, S.; Javaux, M.; van der Kruk, J.; Vanderborght, J.

    2015-04-01

    Technological and methodological progress is essential to improve our understanding of fundamental processes in natural and engineering sciences. In this paper, we will address the potential of new technological and methodological advancements in soil hydrology to move forward our understanding of soil water related processes across a broad range of scales. We will focus on advancements made in quantifying root water uptake processes, subsurface lateral flow, and deep drainage at the field and catchment scale, respectively. We will elaborate on the value of establishing a science-driven network of hydrological observatories to test fundamental hypotheses, to study organizational principles of soil hydrologic processes at catchment scale, and to provide data for the development and validation of models. Finally, we discuss recent developments in data assimilation methods, which provide new opportunities to better integrate observations and models and to improve predictions of the short-term evolution of hydrological processes.

  17. PATHS groundwater hydrologic model

    SciTech Connect

    Nelson, R.W.; Schur, J.A.

    1980-04-01

    A preliminary evaluation capability for two-dimensional groundwater pollution problems was developed as part of the Transport Modeling Task for the Waste Isolation Safety Assessment Program (WISAP). Our approach was to use the data limitations as a guide in setting the level of modeling detail. PATHS Groundwater Hydrologic Model is the first level (simplest) idealized hybrid analytical/numerical model for two-dimensional, saturated groundwater flow and single component transport; homogeneous geology. This document consists of the description of the PATHS groundwater hydrologic model. The preliminary evaluation capability prepared for WISAP, including the enhancements that were made because of the authors' experience using the earlier capability is described. Appendixes A through D supplement the report as follows: complete derivations of the background equations are provided in Appendix A. Appendix B is a comprehensive set of instructions for users of PATHS. It is written for users who have little or no experience with computers. Appendix C is for the programmer. It contains information on how input parameters are passed between programs in the system. It also contains program listings and test case listing. Appendix D is a definition of terms.

  18. Improving the representation of hydrologic processes in Earth System Models

    NASA Astrophysics Data System (ADS)

    Clark, Martyn P.; Fan, Ying; Lawrence, David M.; Adam, Jennifer C.; Bolster, Diogo; Gochis, David J.; Hooper, Richard P.; Kumar, Mukesh; Leung, L. Ruby; Mackay, D. Scott; Maxwell, Reed M.; Shen, Chaopeng; Swenson, Sean C.; Zeng, Xubin

    2015-08-01

    Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale land models (as a component of Earth System Models, or ESMs) do not yet reflect the best hydrologic process understanding or utilize the large amount of hydrologic observations for model testing. This paper discusses the opportunities and key challenges to improve hydrologic process representations and benchmarking in ESM land models, suggesting that (1) land model development can benefit from recent advances in hydrology, both through incorporating key processes (e.g., groundwater-surface water interactions) and new approaches to describe multiscale spatial variability and hydrologic connectivity; (2) accelerating model advances requires comprehensive hydrologic benchmarking in order to systematically evaluate competing alternatives, understand model weaknesses, and prioritize model development needs, and (3) stronger collaboration is needed between the hydrology and ESM modeling communities, both through greater engagement of hydrologists in ESM land model development, and through rigorous evaluation of ESM hydrology performance in research watersheds or Critical Zone Observatories. Such coordinated efforts in advancing hydrology in ESMs have the potential to substantially impact energy, carbon, and nutrient cycle prediction capabilities through the fundamental role hydrologic processes play in regulating these cycles.

  19. Advanced Hydrologic Prediction Services (AHPS) Science Infusion Strategy

    NASA Astrophysics Data System (ADS)

    Schaake, J.; Smith, G.; Carter, G.

    2002-05-01

    NWS is implementing an Advanced Hydrologic Prediction Services (AHPS) Science initiative to meet NWS Vision 2005 goals and related hydrologic services requirements, including the goal of being a world leader using state of the art forecast science and technology. AHPS includes a science infusion strategy to meet the following objectives: extend forecast lead time, improve forecast accuracy, and provide better information for user decisions. AHPS will meet these goals by implementing hydrologic forecast models tuned to local conditions and operated to account for uncertainty in hydrologic forecasts. AHPS will use ensemble weather and climate forecasts of precipitation and other conditions, such as air temperature, that affect the forecasts. This ensemble approach to weather, climate and water forecasting will provide a probabilistic basis for AHPS forecast products. Meeting AHPS goals and objectives requires an infusion of new science into the existing forecast system. Three AHPS requirements for science infusion are: 1. Quantify the uncertainty of river forecasts and provide users with a clear view of future hydrologic conditions together with hard evidence that AHPS products are based on valid forecast probability information; 2. Reduce the space and time scale, improve the accuracy, and extend the lead time of hydrologic forecasts. Demonstrate that new improvements to hydrologic forecast procedures add value to the forecasts and meet user requirements; 3. Improve the ability of forecasters to use the tools provided by integrating these into an efficient operational forecast system that includes automatic techniques for data quality control, access to data, model calibration, data assimilation, processing of ensemble forecasts, verification of forecasts and monitoring of all stages of the forecast process.

  20. Model Calibration in Watershed Hydrology

    NASA Technical Reports Server (NTRS)

    Yilmaz, Koray K.; Vrugt, Jasper A.; Gupta, Hoshin V.; Sorooshian, Soroosh

    2009-01-01

    Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated water, energy, and vegetation processes in a watershed. A consequence of process aggregation is that the model parameters often do not represent directly measurable entities and must, therefore, be estimated using measurements of the system inputs and outputs. During this process, known as model calibration, the parameters are adjusted so that the behavior of the model approximates, as closely and consistently as possible, the observed response of the hydrologic system over some historical period of time. This Chapter reviews the current state-of-the-art of model calibration in watershed hydrology with special emphasis on our own contributions in the last few decades. We discuss the historical background that has led to current perspectives, and review different approaches for manual and automatic single- and multi-objective parameter estimation. In particular, we highlight the recent developments in the calibration of distributed hydrologic models using parameter dimensionality reduction sampling, parameter regularization and parallel computing.

  1. A Hydrological Perspective to Advance Understanding of the Water Cycle

    NASA Astrophysics Data System (ADS)

    Berghuijs, W.

    2014-12-01

    In principle hydrologists are scientists that study relationships within the water cycle. Yet, current technology makes it tempting for hydrology students to lose their "hydrological perspective" and become instead full-time computer programmers or statisticians. I assert that students should ensure their hydrological perspective thrives, notwithstanding the importance and possibilities of current technology. This perspective is necessary to advance the science of hydrology. As other hydrologists have pondered similar views before, I make no claims of originality here. I just hope that in presenting my perspective on this issue I may spark the interest of other early career hydrologists.

  2. Improving the representation of hydrologic processes in Earth System Models

    SciTech Connect

    Clark, Martyn P.; Fan, Ying; Lawrence, David M.; Adam, Jennifer C.; Bolster, Diogo; Gochis, David J.; Hooper, Richard P.; Kumar, Mukesh; Leung, L. Ruby; Mackay, D. Scott; Maxwell, Reed M.; Shen, Chaopeng; Swenson, Sean C.; Zeng, Xubin

    2015-08-21

    Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale models, such as the land components of Earth System Models (ESMs), do not yet represent the terrestrial water cycle in a fully integrated manner or resolve the finer-scale processes that can dominate large-scale water budgets. This paper reviews the current representation of hydrologic processes in ESMs and identifies the key opportunities for improvement. This review suggests that (1) the development of ESMs has not kept pace with modeling advances in hydrology, both through neglecting key processes (e.g., groundwater) and neglecting key aspects of spatial variability and hydrologic connectivity; and (2) many modeling advances in hydrology can readily be incorporated into ESMs and substantially improve predictions of the water cycle. Accelerating modeling advances in ESMs requires comprehensive hydrologic benchmarking activities, in order to systematically evaluate competing modeling alternatives, understand model weaknesses, and prioritize model development needs. This demands stronger collaboration, both through greater engagement of hydrologists in ESM development and through more detailed evaluation of ESM processes in research watersheds. Advances in the representation of hydrologic process in ESMs can substantially improve energy, carbon and nutrient cycle prediction capabilities through the fundamental role the water cycle plays in regulating these cycles.

  3. 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.

  4. A physical interpretation of hydrologic model complexity

    NASA Astrophysics Data System (ADS)

    Moayeri, MohamadMehdi; Pande, Saket

    2015-04-01

    It is intuitive that instability of hydrological system representation, in the sense of how perturbations in input forcings translate into perturbation in a hydrologic response, may depend on its hydrological characteristics. Responses of unstable systems are thus complex to model. We interpret complexity in this context and define complexity as a measure of instability in hydrological system representation. We provide algorithms to quantify model complexity in this context. We use Sacramento soil moisture accounting model (SAC-SMA) parameterized for MOPEX basins and quantify complexities of corresponding models. Relationships between hydrologic characteristics of MOPEX basins such as location, precipitation seasonality index, slope, hydrologic ratios, saturated hydraulic conductivity and NDVI and respective model complexities are then investigated. We hypothesize that complexities of basin specific SAC-SMA models correspond to aforementioned hydrologic characteristics, thereby suggesting that model complexity, in the context presented here, may have a physical interpretation.

  5. Attribution of hydrologic trends using integrated hydrologic and economic models

    NASA Astrophysics Data System (ADS)

    Maneta, M. P.; Brugger, D. R.; Silverman, N. L.

    2014-12-01

    Hydrologic change has been detected in many regions of the world in the form of trends in annual streamflows, varying depths to the regional water table, or other alterations of the hydrologic balance. Most models used to investigate these changes implement sophisticated descriptions of the physical system but use simplified descriptions of the socioeconomic system. These simplifications come in the form of prescribed water diversions and land use change scenarios, which provide little insight into coupled natural-human systems and have limited predictive capabilities. We present an integrated model that adds realism to the description of the hydrologic system in agricultural regions by incorporating a component that updates the allocation of land and water to crops in response to hydroclimatic (water available) and economic conditions (prices of commodities and agricultural inputs). This component assumes that farmers allocate resources to maximize their net revenues, thus justifying the use of optimality conditions to constrain the parameters of an empirical production function that captures the economic behavior of farmers. Because the model internalizes the feedback between climate, agricultural markets, and farming activity into the hydrologic system, it can be used to understand to what extent human economic activity can exacerbate or buffer the regional hydrologic impacts of climate change in agricultural regions. It can also help in the attribution of causes of hydrologic change. These are important issues because local policy and management cannot solve climate change, but they can address land use and agricultural water use. We demonstrate the model in a case study.

  6. Advancing representation of hydrologic processes in the Soil and Water Assessment Tool (SWAT) through integration of the TOPographic MODEL (TOPMODEL) features

    USGS Publications Warehouse

    Chen, J.; Wu, Y.

    2012-01-01

    This paper presents a study of the integration of the Soil and Water Assessment Tool (SWAT) model and the TOPographic MODEL (TOPMODEL) features for enhancing the physical representation of hydrologic processes. In SWAT, four hydrologic processes, which are surface runoff, baseflow, groundwater re-evaporation and deep aquifer percolation, are modeled by using a group of empirical equations. The empirical equations usually constrain the simulation capability of relevant processes. To replace these equations and to model the influences of topography and water table variation on streamflow generation, the TOPMODEL features are integrated into SWAT, and a new model, the so-called SWAT-TOP, is developed. In the new model, the process of deep aquifer percolation is removed, the concept of groundwater re-evaporation is refined, and the processes of surface runoff and baseflow are remodeled. Consequently, three parameters in SWAT are discarded, and two new parameters to reflect the TOPMODEL features are introduced. SWAT-TOP and SWAT are applied to the East River basin in South China, and the results reveal that, compared with SWAT, the new model can provide a more reasonable simulation of the hydrologic processes of surface runoff, groundwater re-evaporation, and baseflow. This study evidences that an established hydrologic model can be further improved by integrating the features of another model, which is a possible way to enhance our understanding of the workings of catchments.

  7. Challenges and Opportunities for Hydrology Education in a Changing World - The Modular Curriculum for Hydrologic Advancement

    NASA Astrophysics Data System (ADS)

    McGlynn, Brian; Wagener, Thorsten; Marshall, Lucy; McGuire, Kevin; Meixner, Thomas; Weiler, Markus; Gooseff, Michael; Kelleher, Christa; Gregg, Susan

    2010-05-01

    ‘It takes a village to raise a child', but who does it take to educate a hydrologist who can solve today's and tomorrow's problems? Hydrology is inherently an interdisciplinary science, and therefore requires interdisciplinary training. We believe that the demands on current and future hydrologists will continue to increase, while training at undergraduate and graduate levels has not kept pace. How do we, as university faculty, educate hydrologists capable of solving complex problems in an interdisciplinary environment considering that current educators have often been taught in narrow traditional disciplines? We suggest a unified community effort to change the way that hydrologists are educated. The complexity of the task is ever increasing. Analysis techniques and tools required for solving emerging problems have to evolve away from focusing mainly on the analysis of past behavior because baselines are shifting as the world changes. The difficulties of providing an appropriate education are also increasing, especially given the growing demands on faculty time. To support hydrology educators and improve hydrology education, we have started a faculty community of educators (REACH) and implemented the Modular Curriculum for Hydrologic Advancement (MOCHA, http://www.mocha.psu.edu/). The goal of this effort is to support hydrology faculty as they educate hydrologists that can solve interdisciplinary problems that go far beyond the traditional disciplinary biased hydrology education most of us have experienced as students. Our current objective is to create an evolving core curriculum for university hydrology education, based on modern pedagogical standards, freely available to and developed and reviewed by the worldwide hydrologic community. We seek to establish an online faculty learning community for hydrology education and capacity building. In this presentation we discuss the results of a recent survey on current hydrology education (to compare with the state of

  8. Advances in river ice hydrology 1999-2003

    NASA Astrophysics Data System (ADS)

    Morse, Brian; Hicks, Faye

    2005-01-01

    In the period 1999 to 2003, river ice has continued to have important socio-economic impacts in Canada and other Nordic countries. Concurrently, there have been many important advances in all areas of Canadian research into river ice engineering and hydrology. For example: (1) River ice processes were highlighted in two special journal issues (Canadian Journal of Civil Engineering in 2003 and Hydrological Processes in 2002) and at five conferences (Canadian Committee on River Ice Processes and the Environment in 1999, 2001 and 2003, and International Association of Hydraulic Research in 2000 and 2002). (2) A number of workers have clearly advanced our understanding of river ice processes by bringing together disparate information in comprehensive review articles. (3) There have been significant advances in river ice modelling. For example, both one-dimensional (e.g. RIVICE, RIVJAM, ICEJAM, HEC-RAS, etc.) and two-dimensional (2-D; www.river2d.ca) public-domain ice-jam models are now available. Work is ongoing to improve RIVER2D, and a commercial 2-D ice-process model is being developed. (4) The 1999-2003 period is notable for the number of distinctly hydrological and ecological studies. On the quantitative side, many are making efforts to determine streamflow during the winter period. On the ecological side, some new publications have addressed the link to water quality (temperature, dissolved oxygen, nutrients and pollutants), and others have dealt with sediment transport and geomorphology (particularly as it relates to break-up), stream ecology (plants, food cycle, etc.) and fish habitat.There is the growing recognition, that these types of study require collaborative efforts. In our view, the main areas requiring further work are: (1) to interface geomorphological and habitat models with quantitative river ice hydrodynamic models; (2) to develop a manager's toolbox (database management, remote sensing, forecasting, intervention methodologies, etc.) to enable

  9. Uncertainty Analysis of the Ensemble Hydrological Forecasts in the Coupled Meteorological-Hydrological Modelling Environment

    NASA Astrophysics Data System (ADS)

    Xuan, Y.; Cluckie, I. D.

    2006-12-01

    The advances in meso-scale numerical weather predication render hydrologists the capability to incorporate high-resolution NWP directly into flood forecasting systems in order to obtain an extended lead time. However, such a direct application of rainfall outputs from the NWP model can contribute considerable uncertainties to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be highlighted by the scaling process. In this research, the ensemble hydrological forecasts driven by the ensemble weather prediction are investigated in an effort trying to understand both the potential and the implication of the ensemble rainfall inputs to the hydrological modelling systems in terms of uncertainty propagation. A data-rich catchment facilitated with dense rainguage network as well as high resolution weather radar was chosen to run the ensemble hydrological simulations of a distributed hydrological model driven by the high resolution NWP predictions. The uncertainties of the amount and the location/timing of the rainfall prediction are discussed whith the results showing that: (1) the hydrological model driven by the short-range NWP can produce forecasts comparable with those from a raingauge-driven one; (2) the ensemble hydrological forecast is able to disseminate abundant information with regard to the nature of the weather system and the confidence of the forecast itself; and (3) the uncertainties as well as systematical biases sometimes are significantly large and, as such, extra efforts need to be made to improve the quality of such a system.

  10. 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.

  11. ARCHES: Advancing Research & Capacity in Hydrologic Education and Science

    NASA Astrophysics Data System (ADS)

    Milewski, A.; Fryar, A. E.; Durham, M. C.; Schroeder, P.; Agouridis, C.; Hanley, C.; Rotz, R. R.

    2013-12-01

    Educating young scientists and building capacity on a global scale is pivotal towards better understanding and managing our water resources. Based on this premise the ARCHES (Advancing Research & Capacity in Hydrologic Education and Science) program has been established. This abstract provides an overview of the program, links to access information, and describes the activities and outcomes of student participants from the Middle East and North Africa. The ARCHES program (http://arches.wrrs.uga.edu) is an integrated hydrologic education approach using online courses, field programs, and various hands-on workshops. The program aims to enable young scientists to effectively perform the high level research that will ultimately improve quality of life, enhance science-based decision making, and facilitate collaboration. Three broad, interlinked sets of activities are incorporated into the ARCHES program: (A1) the development of technical expertise, (A2) the development of professional contacts and skills, and (A3) outreach and long-term sustainability. The development of technical expertise (A1) is implemented through three progressive instructional sections. Section 1: Students were guided through a series of online lectures and exercises (Moodle: http://wrrs.uga.edu/moodle) covering three main topics (Remote Sensing, GIS, and Hydrologic Modeling). Section 2: Students participated in a hands-on workshop hosted at the University of Georgia's Water Resources and Remote Sensing Laboratory (WRRSL). Using ENVI, ArcGIS, and ArcSWAT, students completed a series of lectures and real-world applications (e.g., Development of Hydrologic Models). Section 3: Students participated in field studies (e.g., measurements of infiltration, recharge, streamflow, and water-quality parameters) conducted by U.S. partners and international collaborators in the participating countries. The development of professional contacts and skills (A2) was achieved through the promotion of networking

  12. 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.; van Velzen, N.; He, M.; Lee, H.; Noh, S. J.; Rakovec, O.; Restrepo, P.

    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

  13. Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Weerts, A. H.; Clark, M.; Hendricks Franssen, H.-J.; Kumar, S.; Moradkhani, H.; Seo, D.-J.; Schwanenberg, D.; Smith, P.; van Dijk, A. I. J. M.; van Velzen, N.; He, M.; Lee, H.; Noh, S. J.; Rakovec, O.; Restrepo, P.

    2012-03-01

    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 into operational forecast systems to improve the skill of forecasts to better inform 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 considerations 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 modelling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers

  14. Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Weerts, A. H.; Clark, M.; Hendricks Franssen, H.-J.; Kumar, S.; Moradkhani, H.; Seo, D.-J.; Schwanenberg, D.; Smith, P.; van Dijk, A. I. J. M.; van Velzen, N.; He, M.; Lee, H.; Noh, S. J.; Rakovec, O.; Restrepo, P.

    2012-10-01

    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

  15. Evaluating spatial patterns in hydrological modeling

    NASA Astrophysics Data System (ADS)

    Koch, Julian; Stisen, Simon; Høgh Jensen, Karsten

    2014-05-01

    Recent advances in hydrological modeling towards fully distributed grid based model codes, increased availability of spatially distributed data (remote sensing and intensive field studies) and more computational power allow a shift towards a spatial model evaluation away from the traditional aggregated evaluation. The consideration of spatially aggregated observations, in form of river discharge, in the evaluation process does not ensure a correct simulation of catchment-inherent distributed variables. The integration of spatial data and hydrological models is limited due to a lack of suitable metrics to evaluate similarity of spatial patterns. This study is engaged with the development of a novel set of performance metrics that capture spatial patterns and go beyond global statistics. The metrics are required to be easy, flexible and especially targeted to compare observed and simulated spatial patterns of hydrological variables. Four quantitative methodologies for comparing spatial patterns are brought forward: (1) A fuzzy set approach that incorporates both fuzziness of location and fuzziness of category. (2) Kappa statistic that expresses the similarity between two maps based on a contingency table (error matrix). (3) An extended version of (2) by considering both fuzziness in location and fuzziness in category. (4) Increasing the information content of a single cell by aggregating neighborhood cells at different window sizes; then computing mean and standard deviation. The identified metrics are tested on observed and simulated land surface temperature maps in a groundwater dominated catchment in western Denmark. The observed data originates from the MODIS satellite and MIKE SHE, a coupled and fully distributed hydrological model, serves as the modelling tool. Synthetic land surface temperature maps are generated to further address strengths and weaknesses of the metrics. The metrics are tested in different parameter optimizing frameworks, where they are

  16. Remote sensing applications to hydrologic modeling

    NASA Technical Reports Server (NTRS)

    Dozier, J.; Estes, J. E.; Simonett, D. S.; Davis, R.; Frew, J.; Marks, D.; Schiffman, K.; Souza, M.; Witebsky, E.

    1977-01-01

    An energy balance snowmelt model for rugged terrain was devised and coupled to a flow model. A literature review of remote sensing applications to hydrologic modeling was included along with a software development outline.

  17. Application of hydrologic forecast model.

    PubMed

    Hua, Xu; Hengxin, Xue; Zhiguo, Chen

    2012-01-01

    In order to overcome the shortcoming of the solution may be trapped into the local minimization in the traditional TSK (Takagi-Sugeno-Kang) fuzzy inference training, this paper attempts to consider the TSK fuzzy system modeling approach based on the visual system principle and the Weber law. This approach not only utilizes the strong capability of identifying objects of human eyes, but also considers the distribution structure of the training data set in parameter regulation. In order to overcome the shortcoming of it adopting the gradient learning algorithm with slow convergence rate, a novel visual TSK fuzzy system model based on evolutional learning is proposed by introducing the particle swarm optimization algorithm. The main advantage of this method lies in its very good optimization, very strong noise immunity and very good interpretability. The new method is applied to long-term hydrological forecasting examples. The simulation results show that the method is feasible and effective, the new method not only inherits the advantages of traditional visual TSK fuzzy models but also has the better global convergence and accuracy than the traditional model. PMID:22699326

  18. CUAHSI's Hydrologic Measurement Facility: Putting Advanced Tools in Scientists' Hands

    NASA Astrophysics Data System (ADS)

    Hooper, R. P.; Robinson, D.; Selker, J.; Duncan, J.

    2006-05-01

    Like related environmental sciences, the hydrologic sciences community has been defining environmental observatories and the support components necessary for their successful implementation, such as informatics (cyberinfrastructure) and instrumentation. Unlike programs, such as NEON and OOI, that have been pursuing large-scale capital funding through the Major Research Equipment program of the National Science Foundation, CUAHSI has been pursuing incremental development of observatories that has allowed us to pilot different parts of these support functions, namely Hydrologic Information Systems and a Hydrologic Measurement Facility (HMF), the subject of this paper. The approach has allowed us to gain greater specificity of the requirements for these facilities and their operational challenges. The HMF is developing the foundation to support innovative research across the breadth of the Hydrologic Community, including classic PI-driven projects as well as over 20 grass-roots observatories that have been developing over the past 2 years. HMF is organized around three basic areas: water cycle instrumentation, biogeochemistry and geophysics. Committees have been meeting to determined the most effective manner to deliver instrumentation, whether by special instrumentation packages proposed by host institutions; collaborative agreements with federal agencies; and contributions from industrial partners. These efforts are guided by the results of a community wide survey conducted in Nov-Dec 2005, and a series of ongoing workshops. The survey helped identify the types of equipment that will advance hydrological sciences and are often beyond the capabilities of individual PI's. Respondents to the survey indicated they were keen for HMF to focus on providing supported equipment such as atmospheric profilers like LIDAR, geophysical instrumentation ranging from airborne sensors to ground-penetrating radar, and field-deployed mass spectrophotometers. A recently signed agreement

  19. Capabilities and limitations of detailed hillslope hydrological modelling

    NASA Astrophysics Data System (ADS)

    Bronstert, Axel

    1999-01-01

    Hillslope hydrological modelling is considered to be of great importance for the understanding and quantification of hydrological processes in hilly or mountainous landscapes. In recent years a few comprehensive hydrological models have been developed at the hillslope scale which have resulted in an advanced representation of hillslope hydrological processes (including their interactions), and in some operational applications, such as in runoff and erosion studies at the field scale or lateral flow simulation in environmental and geotechnical engineering. An overview of the objectives of hillslope hydrological modelling is given, followed by a brief introduction of an exemplary comprehensive hillslope model, which stimulates a series of hydrological processes such as interception, evapotranspiration, infiltration into the soil matrix and into macropores, lateral and vertical subsurface soil water flow both in the matrix and preferential flow paths, surface runoff and channel discharge. Several examples of this model are presented and discussed in order to determine the model's capabilities and limitations. Finally, conclusions about the limitations of detailed hillslope modelling are drawn and an outlook on the future prospects of hydrological models on the hillslope scale is given.The model presented performed reasonable calculations of Hortonian surface runoff and subsequent erosion processes, given detailed information of initial soil water content and soil hydraulic conditions. The vertical and lateral soil moisture dynamics were also represented quite well. However, the given examples of model applications show that quite detailed climatic and soil data are required to obtain satisfactory results. The limitations of detailed hillslope hydrological modelling arise from different points: difficulties in the representations of certain processes (e.g. surface crusting, unsaturated-saturated soil moisture flow, macropore flow), problems of small-scale variability

  20. Hydrological modelling of urbanized catchments: A review and future directions

    NASA Astrophysics Data System (ADS)

    Salvadore, Elga; Bronders, Jan; Batelaan, Okke

    2015-10-01

    In recent years, the conceptual detail of hydrological models has dramatically increased as a result of improved computational techniques and the availability of spatially-distributed digital data. Nevertheless modelling spatially-distributed hydrological processes can be challenging, particularly in strongly heterogeneous urbanized areas. Multiple interactions occur between urban structures and the water system at various temporal and spatial scales. So far, no universal methodology exists for simulating the urban water system at catchment scale. This paper reviews the state of the art on the scientific knowledge and practice of modelling the urban hydrological system at the catchment scale, with the purpose of identifying current limitations and defining a blueprint for future modelling advances. We compare conceptual descriptions of urban physical hydrological processes on basis of a selection of 43 modelling approaches. The complexity of the urban water system at the catchment scale results in an incomplete understanding of the interaction between urban and natural hydrological systems, and in a high degree of uncertainty. Data availability is still a strong limitation since current modelling practice recognizes the need for high spatial and temporal resolution. Spatio-temporal gaps exist between the physical scales of hydrological processes and the resolution of applied models. Therefore urban hydrology is often simplified either as a study of surface runoff over impervious surfaces or hydraulics of piped systems. Many approaches target very specific objectives and the level of detail in representing physical processes is not consistent. Based on our analysis, we propose a blueprint for a highly complex integrated urban hydrological model. We regard flexibility, in terms of model structure and data assimilation, as the key characteristic for overcoming these limitations. We advocate the use of modular, process-based approaches, which are flexible and adaptable

  1. Hydrologic Modeling of Boreal Forest Ecosystems

    NASA Technical Reports Server (NTRS)

    Haddeland, I.; Lettenmaier, D. P.

    1995-01-01

    This study focused on the hydrologic response, including vegetation water use, of two test regions within the Boreal-Ecosystem-Atmosphere Study (BOREAS) region in the Canadian boreal forest, one north of Prince Albert, Saskatchewan, and the other near Thompson, Manitoba. Fluxes of moisture and heat were studied using a spatially distributed hydrology soil-vegetation-model (DHSVM).

  2. Hydrological partitioning in the critical zone: Recent advances and opportunities for developing transferable understanding of water cycle dynamics

    NASA Astrophysics Data System (ADS)

    Brooks, Paul D.; Chorover, Jon; Fan, Ying; Godsey, Sarah E.; Maxwell, Reed M.; McNamara, James P.; Tague, Christina

    2015-09-01

    Hydrology is an integrative discipline linking the broad array of water-related research with physical, ecological, and social sciences. The increasing breadth of hydrological research, often where subdisciplines of hydrology partner with related sciences, reflects the central importance of water to environmental science, while highlighting the fractured nature of the discipline itself. This lack of coordination among hydrologic subdisciplines has hindered the development of hydrologic theory and integrated models capable of predicting hydrologic partitioning across time and space. The recent development of the concept of the critical zone (CZ), an open system extending from the top of the canopy to the base of groundwater, brings together multiple hydrological subdisciplines with related physical and ecological sciences. Observations obtained by CZ researchers provide a diverse range of complementary process and structural data to evaluate both conceptual and numerical models. Consequently, a cross-site focus on "critical zone hydrology" has potential to advance the discipline of hydrology and to facilitate the transition of CZ observatories into a research network with immediate societal relevance. Here we review recent work in catchment hydrology and hydrochemistry, hydrogeology, and ecohydrology that highlights a common knowledge gap in how precipitation is partitioned in the critical zone: "how is the amount, routing, and residence time of water in the subsurface related to the biogeophysical structure of the CZ?" Addressing this question will require coordination among hydrologic subdisciplines and interfacing sciences, and catalyze rapid progress in understanding current CZ structure and predicting how climate and land cover changes will affect hydrologic partitioning.

  3. Snow Hydrology in a General Circulation Model.

    NASA Astrophysics Data System (ADS)

    Marshall, Susan; Roads, John O.; Glatzmaier, Gary

    1994-08-01

    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 snow pack. 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.

  4. 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.

  5. Advances in borehole geophysics for hydrology

    SciTech Connect

    Nelson, P.H.

    1982-01-01

    Borehole geophysical methods provide vital subsurface information on rock properties, fluid movement, and the condition of engineered borehole structures. Within the first category, salient advances include the continuing improvement of the borehole televiewer, refinement of the electrical conductivity dipmeter for fracture characterization, and the development of a gigahertz-frequency electromagnetic propagation tool for water saturation measurements. The exploration of the rock mass between boreholes remains a challenging problem with high potential; promising methods are now incorporating high-density spatial sampling and sophisticated data processing. Flow-rate measurement methods appear adequate for all but low-flow situations. At low rates the tagging method seems the most attractive. The current exploitation of neutron-activation techniques for tagging means that the wellbore fluid itself is tagged, thereby eliminating the mixing of an alien fluid into the wellbore. Another method uses the acoustic noise generated by flow through constrictions and in and behind casing to detect and locate flaws in the production system. With the advent of field-recorded digital data, the interpretation of logs from sedimentary sequences is now reaching a sophisticated level with the aid of computer processing and the application of statistical methods. Lagging behind are interpretive schemes for the low-porosity, fracture-controlled igneous and metamorphic rocks encountered in the geothermal reservoirs and in potential waste-storage sites. Progress is being made on the general problem of fracture detection by use of electrical and acoustical techniques, but the reliable definition of permeability continues to be an elusive goal.

  6. Using climate model ensemble forecasts for seasonal hydrologic prediction

    NASA Astrophysics Data System (ADS)

    Wood, Andrew Whitaker

    Seasonal hydrologic forecasting has long played an invaluable role in the development and use of water resources. Despite notable advances in the science and practice of climate prediction, current approaches of hydrologists and water managers largely fail to incorporate seasonal climate forecast information that has become operationally available during the last decade. This study is motivated by the view that a combination of hydrologic and climate prediction methods affords a new opportunity to improve hydrologic forecast skill. A relatively direct statistical approach for achieving this combination (i.e., downscaling) was formulated that used ensemble climate model forecasts with a six month lead time produced by the NCEP/CPC Global Spectral Model (GSM) as input to the macroscale Variable Infiltration Capacity hydrologic model to produce ensemble runoff and streamflow forecasts. The approach involved the bias correction of climate model precipitation and temperature fields, and spatial and temporal disaggregation from monthly climate model scale (about 2 degrees latitude by longitude) fields to daily hydrology model scale (1/8 degrees) inputs. A qualitative evaluation of the approach in the eastern U.S. suggested that it was successful in translating climate forecast signals to local hydrologic variables and streamflow, but that the dominant influence on forecast results tended to be persistence in initial hydrologic conditions. The suitability of the statistical downscaling approach for supporting hydrologic simulation was then assessed (using a continuous retrospective 20-year climate simulation from the DOE Parallel Climate Model) relative to dynamical downscaling via a regional, meso-scale climate model. The statistical approach generally outperformed the dynamical approach, in that the dynamical approach alone required additional bias-correction to reproduce the retrospective hydrology as well as the statistical approach. Finally, using 21 years of

  7. Inter-comparison of subglacial hydrological models

    NASA Astrophysics Data System (ADS)

    de Fleurian, Basile; Werder, Mauro

    2016-04-01

    The recent emergence of a number of subglacial hydrological models allows us to obtain theoretical insights on basal processes; for instance on the coupling between water pressure and the sliding of glaciers. In ice-flow models, it is relatively clear what the simulated physics ought to be. Conversely, the physical processes incorporated into subglacial hydrology models are diverse as it is yet unclear which ones are of relevance for a particular setting. An inter-comparison of hydrology models will therefore need a somewhat different approach to the one used in the many ice-flow model inter-comparisons (EISMINT, ISMIP, etc.). Here, we present a set of experiments that will allow the comparison of the behavior of different hydrology models. The design of the benchmark aims at allowing the participation of a wide range of models based on different physical approaches. We aim at evaluating the models with a focus on the effective pressure which has the most impact on the dynamics of glaciers. The aim of this inter-comparison is to provide modellers with the necessary data to make an informed decision on which subglacial hydrology model to use for a particular study.

  8. Hydrology

    NASA Astrophysics Data System (ADS)

    Brutsaert, Wilfried

    2005-08-01

    Water in its different forms has always been a source of wonder, curiosity and practical concern for humans everywhere. Hydrology - An Introduction presents a coherent introduction to the fundamental principles of hydrology, based on the course that Wilfried Brutsaert has taught at Cornell University for the last thirty years. Hydrologic phenomena are dealt with at spatial and temporal scales at which they occur in nature. The physics and mathematics necessary to describe these phenomena are introduced and developed, and readers will require a working knowledge of calculus and basic fluid mechanics. The book will be invaluable as a textbook for entry-level courses in hydrology directed at advanced seniors and graduate students in physical science and engineering. In addition, the book will be more broadly of interest to professional scientists and engineers in hydrology, environmental science, meteorology, agronomy, geology, climatology, oceanology, glaciology and other earth sciences. Emphasis on fundamentals Clarification of the underlying physical processes Applications of fluid mechanics in the natural environment

  9. Recent advances in understanding Antarctic subglacial lakes and hydrology.

    PubMed

    Siegert, Martin J; Ross, Neil; Le Brocq, Anne M

    2016-01-28

    It is now well documented that over 400 subglacial lakes exist across the bed of the Antarctic Ice Sheet. They comprise a variety of sizes and volumes (from the approx. 250 km long Lake Vostok to bodies of water less than 1 km in length), relate to a number of discrete topographic settings (from those contained within valleys to lakes that reside in broad flat terrain) and exhibit a range of dynamic behaviours (from 'active' lakes that periodically outburst some or all of their water to those isolated hydrologically for millions of years). Here we critique recent advances in our understanding of subglacial lakes, in particular since the last inventory in 2012. We show that within 3 years our knowledge of the hydrological processes at the ice-sheet base has advanced considerably. We describe evidence for further 'active' subglacial lakes, based on satellite observation of ice-surface changes, and discuss why detection of many 'active' lakes is not resolved in traditional radio-echo sounding methods. We go on to review evidence for large-scale subglacial water flow in Antarctica, including the discovery of ancient channels developed by former hydrological processes. We end by predicting areas where future discoveries may be possible, including the detection, measurement and significance of groundwater (i.e. water held beneath the ice-bed interface). PMID:26667914

  10. Recent advances in understanding Antarctic subglacial lakes and hydrology

    PubMed Central

    Siegert, Martin J.; Ross, Neil; Le Brocq, Anne M.

    2016-01-01

    It is now well documented that over 400 subglacial lakes exist across the bed of the Antarctic Ice Sheet. They comprise a variety of sizes and volumes (from the approx. 250 km long Lake Vostok to bodies of water less than 1 km in length), relate to a number of discrete topographic settings (from those contained within valleys to lakes that reside in broad flat terrain) and exhibit a range of dynamic behaviours (from ‘active’ lakes that periodically outburst some or all of their water to those isolated hydrologically for millions of years). Here we critique recent advances in our understanding of subglacial lakes, in particular since the last inventory in 2012. We show that within 3 years our knowledge of the hydrological processes at the ice-sheet base has advanced considerably. We describe evidence for further ‘active’ subglacial lakes, based on satellite observation of ice-surface changes, and discuss why detection of many ‘active’ lakes is not resolved in traditional radio-echo sounding methods. We go on to review evidence for large-scale subglacial water flow in Antarctica, including the discovery of ancient channels developed by former hydrological processes. We end by predicting areas where future discoveries may be possible, including the detection, measurement and significance of groundwater (i.e. water held beneath the ice-bed interface). PMID:26667914

  11. Uncertainty of the hydrological response to climate change conditions; 605 basins, 3 hydrological models, 5 climate models, 5 hydrological variables

    NASA Astrophysics Data System (ADS)

    Melsen, Lieke; Mizukami, Naoki; Newman, Andrew; Clark, Martyn; Teuling, Adriaan

    2016-04-01

    Many studies investigated the effect of a changing climate on the hydrological response of a catchment and uncertainty of the effect coming from hydrologic modelling (e.g., forcing, hydrologic model structures, and parameters). However, most past studies used only a single or a small number of catchments. To go beyond the case-study, and to assess the uncertainty involved in modelling the hydrological impact of climate change more comprehensively, we studied 605 basins over a wide range of climate regimes throughout the contiguous USA. We used three different widely-used hydrological models (VIC, HBV, SAC), which we forced with five distinct climate model outputs. The hydrological models have been run for a base period (1986-2008) for which observations were available, and for a future period (2070-2099). Instead of calibrating each hydrological model for each basin, the model has been run with a parameter sample (varying from 1600 to 1900 samples dependent on the number of free parameters in the model). Five hydrological states and fluxes were stored; discharge, evapotranspiration, soil moisture, SWE and snow melt, and 15 different metrics and signatures have been obtained for each model run. With the results, we conduct a sensitivity analysis over the change in signatures from the future period compared to the base period. In this way, we can identify the parameters that are responsible for certain projected changes, and identify the processes responsible for this change. By using three different models, in which VIC is most distinctive in including explicit vegetation parameters, we can compare different process representations and the effect on the projected hydrological change.

  12. On the Use of Models in Hydrology.

    ERIC Educational Resources Information Center

    de Marsily, G.

    1994-01-01

    This discussion article addresses the nature of models used in hydrology. It proposes a minimalist classification of models into two categories: models built on data from observations of the processes involved, and those for which there are no observation data on any of these processes, at the scale of interest. (LZ)

  13. Satellite-derived potential evapotranspiration for distributed hydrologic runoff modeling

    NASA Astrophysics Data System (ADS)

    Spies, R. R.; Franz, K. J.; Bowman, A.; Hogue, T. S.; Kim, J.

    2012-12-01

    Distributed models have the ability of incorporating spatially variable data, especially high resolution forcing inputs such as precipitation, temperature and evapotranspiration in hydrologic modeling. Use of distributed hydrologic models for operational streamflow prediction has been partially hindered by a lack of readily available, spatially explicit input observations. Potential evapotranspiration (PET), for example, is currently accounted for through PET input grids that are based on monthly climatological values. The goal of this study is to assess the use of satellite-based PET estimates that represent the temporal and spatial variability, as input to the National Weather Service (NWS) Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM). Daily PET grids are generated for six watersheds in the upper Mississippi River basin using a method that applies only MODIS satellite-based observations and the Priestly Taylor formula (MODIS-PET). The use of MODIS-PET grids will be tested against the use of the current climatological PET grids for simulating basin discharge. Gridded surface temperature forcing data are derived by applying the inverse distance weighting spatial prediction method to point-based station observations from the Automated Surface Observing System (ASOS) and Automated Weather Observing System (AWOS). Precipitation data are obtained from the Climate Prediction Center's (CPC) Climatology-Calibrated Precipitation Analysis (CCPA). A-priori gridded parameters for the Sacramento Soil Moisture Accounting Model (SAC-SMA), Snow-17 model, and routing model are initially obtained from the Office of Hydrologic Development and further calibrated using an automated approach. The potential of the MODIS-PET to be used in an operational distributed modeling system will be assessed with the long-term goal of promoting research to operations transfers and advancing the science of hydrologic forecasting.

  14. Dynamic Multicriteria Evaluation of Conceptual Hydrological Models

    NASA Astrophysics Data System (ADS)

    de Vos, N. J.; Rientjes, T. H.; Fenicia, F.; Gupta, H. V.

    2007-12-01

    Accurate and precise forecasts of river streamflows are crucial for successful management of water resources and under the threat of hydrological extremes such as floods and droughts. Conceptual rainfall-runoff models are the most popular approach in flood forecasting. However, the calibration and evaluation of such models is often oversimplified by the use of performance statistics that largely ignore the dynamic character of a watershed system. This research aims to find novel ways of model evaluation by identifying periods of hydrologic similarity and customizing evaluation within each period using multiple criteria. A dynamic approach to hydrologic model identification, calibration and testing can be realized by applying clustering algorithms (e.g., Self-Organizing Map, Fuzzy C-means algorithm) to hydrological data. These algorithms are able to identify clusters in the data that represent periods of hydrological similarity. In this way, dynamic catchment system behavior can be simplified within the clusters that are identified. Although clustering requires a number of subjective choices, new insights into the hydrological functioning of a catchment can be obtained. Finally, separate model multi-criteria calibration and evaluation is performed for each of the clusters. Such a model evaluation procedure shows to be reliable and gives much-needed feedback on exactly where certain model structures fail. Several clustering algorithms were tested on two data sets of meso-scale and large-scale catchments. The results show that the clustering algorithms define categories that reflect hydrological process understanding: dry/wet seasons, rising/falling hydrograph limbs, precipitation-driven/ non-driven periods, etc. The results of various clustering algorithms are compared and validated using expert knowledge. Calibration results on a conceptual hydrological model show that the common practice of single-criteria calibration over the complete time series fails to perform

  15. 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

  16. Improving hydrology models for a changing climate

    NASA Astrophysics Data System (ADS)

    Palus, Shannon

    2014-12-01

    Changes over time in the relationship between rainfall and catchment runoff pose a significant challenge for hydrological models, which are often calibrated under the assumption that the future relationship will be consistent with that of the past. In a recent paper, Westra et al. outlined a method for diagnosing, interpreting, and improving the capacity of models to develop predictions under such conditions.

  17. Treatments of Precipitation Inputs to Hydrologic Models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hydrological models are used to assess many water resources problems from agricultural use and water quality to engineering issues. The success of these models are dependent on correct parameterization; the most sensitive being the rainfall input time series. These records can come from land-based ...

  18. Hydrological Modeling and Repeatability with Brokering

    NASA Astrophysics Data System (ADS)

    Easton, Z. M.; Collick, A.; Srinivasan, R.; Braeckel, A.; Nativi, S.; McAlister, C.; Wright, D. J.; Khalsa, S. J. S.; Fuka, D.

    2014-12-01

    Data brokering aims to provide those in the hydrological sciences with access to relevant data to represent physical, biological, and chemical characteristics researchers need to accelerate discovery in their domain. Environmental models are useful tools to understand the behavior of hydrological systems. Unfortunately, parameterization of these models requires many different data sources from different disciplines (e.g., atmospheric, geoscience, ecology). In 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, more suitable data products exist. An added complexity is that various science communities have differing data formats, storage protocols and manipulation methods, which makes use by a non domain scientist difficult and time consuming. We propose 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 increases the efficiency with which data are collected, models are initialized, and results are analyzed. As an added benefit, it appears brokering significantly increases the repeatability of a study.

  19. Multi-criteria evaluation of hydrological models

    NASA Astrophysics Data System (ADS)

    Rakovec, Oldrich; Clark, Martyn; Weerts, Albrecht; Hill, Mary; Teuling, Ryan; Uijlenhoet, Remko

    2013-04-01

    Over the last years, there is a tendency in the hydrological community to move from the simple conceptual models towards more complex, physically/process-based hydrological models. This is because conceptual models often fail to simulate the dynamics of the observations. However, there is little agreement on how much complexity needs to be considered within the complex process-based models. One way to proceed to is to improve understanding of what is important and unimportant in the models considered. The aim of this ongoing study is to evaluate structural model adequacy using alternative conceptual and process-based models of hydrological systems, with an emphasis on understanding how model complexity relates to observed hydrological processes. Some of the models require considerable execution time and the computationally frugal sensitivity analysis, model calibration and uncertainty quantification methods are well-suited to providing important insights for models with lengthy execution times. The current experiment evaluates two version of the Framework for Understanding Structural Errors (FUSE), which both enable running model inter-comparison experiments. One supports computationally efficient conceptual models, and the second supports more-process-based models that tend to have longer execution times. The conceptual FUSE combines components of 4 existing conceptual hydrological models. The process-based framework consists of different forms of Richard's equations, numerical solutions, groundwater parameterizations and hydraulic conductivity distribution. The hydrological analysis of the model processes has evolved from focusing only on simulated runoff (final model output), to also including other criteria such as soil moisture and groundwater levels. Parameter importance and associated structural importance are evaluated using different types of sensitivity analyses techniques, making use of both robust global methods (e.g. Sobol') as well as several

  20. Approaches to modelling hydrology and ecosystem interactions

    NASA Astrophysics Data System (ADS)

    Silberstein, Richard P.

    2014-05-01

    As the pressures of industry, agriculture and mining on groundwater resources increase there is a burgeoning un-met need to be able to capture these multiple, direct and indirect stresses in a formal framework that will enable better assessment of impact scenarios. While there are many catchment hydrological models and there are some models that represent ecological states and change (e.g. FLAMES, Liedloff and Cook, 2007), these have not been linked in any deterministic or substantive way. Without such coupled eco-hydrological models quantitative assessments of impacts from water use intensification on water dependent ecosystems under changing climate are difficult, if not impossible. The concept would include facility for direct and indirect water related stresses that may develop around mining and well operations, climate stresses, such as rainfall and temperature, biological stresses, such as diseases and invasive species, and competition such as encroachment from other competing land uses. Indirect water impacts could be, for example, a change in groundwater conditions has an impact on stream flow regime, and hence aquatic ecosystems. This paper reviews previous work examining models combining ecology and hydrology with a view to developing a conceptual framework linking a biophysically defensable model that combines ecosystem function with hydrology. The objective is to develop a model capable of representing the cumulative impact of multiple stresses on water resources and associated ecosystem function.

  1. Detecting hydrological changes through conceptual model

    NASA Astrophysics Data System (ADS)

    Viola, Francesco; Caracciolo, Domenico; Pumo, Dario; Francipane, Antonio; Valerio Noto, Leonardo

    2015-04-01

    Natural changes and human modifications in hydrological systems coevolve and interact in a coupled and interlinked way. If, on one hand, climatic changes are stochastic, non-steady, and affect the hydrological systems, on the other hand, human-induced changes due to over-exploitation of soils and water resources modifies the natural landscape, water fluxes and its partitioning. Indeed, the traditional assumption of static systems in hydrological analysis, which has been adopted for long time, fails whenever transient climatic conditions and/or land use changes occur. Time series analysis is a way to explore environmental changes together with societal changes; unfortunately, the not distinguishability between causes restrict the scope of this method. In order to overcome this limitation, it is possible to couple time series analysis with an opportune hydrological model, such as a conceptual hydrological model, which offers a schematization of complex dynamics acting within a basin. Assuming that model parameters represent morphological basin characteristics and that calibration is a way to detect hydrological signature at a specific moment, it is possible to argue that calibrating the model over different time windows could be a method for detecting potential hydrological changes. In order to test the capabilities of a conceptual model in detecting hydrological changes, this work presents different "in silico" experiments. A synthetic-basin is forced with an ensemble of possible future scenarios generated with a stochastic weather generator able to simulate steady and non-steady climatic conditions. The experiments refer to Mediterranean climate, which is characterized by marked seasonality, and consider the outcomes of the IPCC 5th report for describing climate evolution in the next century. In particular, in order to generate future climate change scenarios, a stochastic downscaling in space and time is carried out using realizations of an ensemble of General

  2. Inverse distributed hydrological modelling of Alpine catchments

    NASA Astrophysics Data System (ADS)

    Kunstmann, H.; Krause, J.; Mayr, S.

    2006-06-01

    Even in physically based distributed hydrological models, various remaining parameters must be estimated for each sub-catchment. This can involve tremendous effort, especially when the number of sub-catchments is large and the applied hydrological model is computationally expensive. Automatic parameter estimation tools can significantly facilitate the calibration process. Hence, we combined the nonlinear parameter estimation tool PEST with the distributed hydrological model WaSiM. PEST is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. WaSiM is a fully distributed hydrological model using physically based algorithms for most of the process descriptions. WaSiM was applied to the alpine/prealpine Ammer River catchment (southern Germany, 710 km2 in a 100×100 m2 horizontal resolution. The catchment is heterogeneous in terms of geology, pedology and land use and shows a complex orography (the difference of elevation is around 1600 m). Using the developed PEST-WaSiM interface, the hydrological model was calibrated by comparing simulated and observed runoff at eight gauges for the hydrologic year 1997 and validated for the hydrologic year 1993. For each sub-catchment four parameters had to be calibrated: the recession constants of direct runoff and interflow, the drainage density, and the hydraulic conductivity of the uppermost aquifer. Additionally, five snowmelt specific parameters were adjusted for the entire catchment. Altogether, 37 parameters had to be calibrated. Additional a priori information (e.g. from flood hydrograph analysis) narrowed the parameter space of the solutions and improved the non-uniqueness of the fitted values. A reasonable quality of fit was achieved. Discrepancies between modelled and observed runoff were also due to the small number of meteorological stations and corresponding interpolation artefacts in the orographically complex terrain. Application of a 2-dimensional numerical

  3. Flexibility on storage-release based distributed hydrologic modeling with object-oriented approach

    Technology Transfer Automated Retrieval System (TEKTRAN)

    With the availability of advanced hydrologic data in the public domain such as remotely sensed and climate change scenario data, there is a need for a modeling framework that is capable of using these data to simulate and extend hydrologic processes with multidisciplinary approaches for sustainable ...

  4. Catchment classification by means of hydrological models

    NASA Astrophysics Data System (ADS)

    Hellebrand, Hugo; Ley, Rita; Casper, Markus

    2013-04-01

    An important hydrological objective is catchment classification that will serve as a basis for the regionalisation of discharge parameters or model parameters. The main task of this study is the development and assessment of two classification approaches with respect to their efficiency in catchment classification. The study area in western Germany comprises about 80 catchments that range in size from 8 km2 up to 1500 km2, covering a wide range of geological substrata, soils, landscapes and mean annual precipitation. In a first approach Self Organising Maps (SOMs) use discharge characteristics or catchment characteristics to classify the catchments of the study area. Next, a reference hydrological model calibrates the catchments of the study area and tests the possibilities of parameter transfer. Compared to the transfer of parameters outside a class, for most catchments the model performance improves when parameters within a class are transferred. Thus, it should be possible to distinguish catchment classes by means of a hydrological model. The classification results of the SOM are compared to the classification results of the reference hydrological model in order to determine the latter validity. The second approach builds on the first approach in such a way that it uses the Superflex Modelling Framework instead of only one reference model. Within this framework multiple conceptual model structures can be calibrated and adapted. Input data for each calibration of a catchment are hourly time series of runoff, precipitation and evaporation for at least eight years. The calibration of multiple models for each catchment and their comparison allows for the assessment of the influence of different model structures on model performance. Learning loops analyse model performance and adapt model structures accordingly with a view to performance improvement. The result of the modelling exercise is a best performing model structure for each catchment that serves as a basis

  5. Optimal combinations of specialized conceptual hydrological models

    NASA Astrophysics Data System (ADS)

    Kayastha, Nagendra; Lal Shrestha, Durga; Solomatine, Dimitri

    2010-05-01

    In hydrological modelling it is a usual practice to use a single lumped conceptual model for hydrological simulations at all regimes. However often the simplicity of the modelling paradigm leads to errors in represent all the complexity of the physical processes in the catchment. A solution could be to model various hydrological processes separately by differently parameterized models, and to combine them. Different hydrological models have varying performance in reproducing catchment response. Generally it cannot be represented precisely in different segments of the hydrograph: some models performed well in simulating the peak flows, while others do well in capturing the low flows. Better performance can be achieved if a model being applied to the catchment using different model parameters that are calibrated using criteria favoring high or low flows. In this work we use a modular approach to simulate hydrology of a catchment, wherein multiple models are applied to replicate the catchment responses and each "specialist" model is calibrated according to a specific objective function which is chosen in a way that forces the model to capture certain aspects of the hydrograph, and outputs of models are combined using so-called "fuzzy committee". Such multi-model approach has been already previously implemented in the development of data driven and conceptual models (Fenicia et al., 2007), but its perfomance was considered only during the calibration period. In this study we tested an application to conceptual models in both calibration and verification period. In addition, we tested the sensitivity of the result to the use of different weightings used in the objective functions formulations, and memberbship functions used in the committee. The study was carried out for Bagamati catchment in Nepal and Brue catchment in United Kingdoms with the MATLAB-based implementation of HBV model. Multi-objective evolutionary optimization genetic algorithm (Deb, 2001) was used to

  6. Inverse distributed hydrological modelling of alpine catchments

    NASA Astrophysics Data System (ADS)

    Kunstmann, H.; Krause, J.; Mayr, S.

    2005-12-01

    Even in physically based distributed hydrological models, various remaining parameters must be estimated for each sub-catchment. This can involve tremendous effort, especially when the number of sub-catchments is large and the applied hydrological model is computationally expensive. Automatic parameter estimation tools can significantly facilitate the calibration process. Hence, we combined the nonlinear parameter estimation tool PEST with the distributed hydrological model WaSiM. PEST is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. WaSiM is a fully distributed hydrological model using physically based algorithms for most of the process descriptions. WaSiM was applied to the alpine/prealpine Ammer River catchment (southern Germany, 710 km2) in a 100×100 m2 horizontal resolution. The catchment is heterogeneous in terms of geology, pedology and land use and shows a complex orography (the difference of elevation is around 1600 m). Using the developed PEST-WaSiM interface, the hydrological model was calibrated by comparing simulated and observed runoff at eight gauges for the hydrologic year 1997 and validated for the hydrologic year 1993. For each sub-catchment four parameters had to be calibrated: the recession constants of direct runoff and interflow, the drainage density, and the hydraulic conductivity of the uppermost aquifer. Additionally, five snowmelt specific parameters were adjusted for the entire catchment. Altogether, 37 parameters had to be calibrated. Additional a priori information (e.g. from flood hydrograph analysis) narrowed the parameter space of the solutions and improved the non-uniqueness of the fitted values. A reasonable quality of fit was achieved. Discrepancies between modelled and observed runoff were also due to the small number of meteorological stations and corresponding interpolation artefacts in the orographically complex terrain. A detailed covariance analysis was performed

  7. 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.

    2012-02-01

    Protection from hydrological extremes and the sustainable supply of hydrological services in the presence of climate change and increasing population pressure 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 predicted by some. Surveys of the current educational basis, however, also clearly demonstrate that hydrology education is not yet prepared to deal with this challenge. We present our own vision of the necessary future 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, surveys, discussion and assessment to provide a holistic baseline for future hydrology education.

  8. TUWmodel: an educational hydrologic model in R

    NASA Astrophysics Data System (ADS)

    Parajka, J.; Rogger, M.; Kobler, U.; Salinas, J.; Nester, T.; Bloeschl, G.

    2013-12-01

    In order to show the advantages of using hydrologic models in R environment, particularly for educational purposes, we have implemented a conceptual rainfall-runoff model, originally written in Fortran language into R. This hydrologic model is used in many scientific studies and operational engineering applications in Austria. The model consisting of a snow, a soil moisture and a flow routing routine and run on a daily time step in a lumped or a semi-lumped way. The R environment allows to compile and use this model on different platforms and operating system, taking advantage of many additional routines already available in R (i.e. visualisation or optimisation tools). In this poster we present a set of examples that are used in a graduate level course on engineering hydrology at the Vienna University of Technology, which include: - Multi-objective calibration of the model; - Manual vs. automatic calibration; - Visualisation of model outputs and efficiencies; - Model application in ungauged catchments; - Operational runoff forecast. The flexibility of R is ideal for education, since students can easily play with the extensive list of existing functionalities and define new functions and extensions.

  9. 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

  10. Legacy model integration for enhancing hydrologic interdisciplinary research

    NASA Astrophysics Data System (ADS)

    Dozier, A.; Arabi, M.; David, O.

    2013-12-01

    Many challenges are introduced to interdisciplinary research in and around the hydrologic science community due to advances in computing technology and modeling capabilities in different programming languages, across different platforms and frameworks by researchers in a variety of fields with a variety of experience in computer programming. Many new hydrologic models as well as optimization, parameter estimation, and uncertainty characterization techniques are developed in scripting languages such as Matlab, R, Python, or in newer languages such as Java and the .Net languages, whereas many legacy models have been written in FORTRAN and C, which complicates inter-model communication for two-way feedbacks. However, most hydrologic researchers and industry personnel have little knowledge of the computing technologies that are available to address the model integration process. Therefore, the goal of this study is to address these new challenges by utilizing a novel approach based on a publish-subscribe-type system to enhance modeling capabilities of legacy socio-economic, hydrologic, and ecologic software. Enhancements include massive parallelization of executions and access to legacy model variables at any point during the simulation process by another program without having to compile all the models together into an inseparable 'super-model'. Thus, this study provides two-way feedback mechanisms between multiple different process models that can be written in various programming languages and can run on different machines and operating systems. Additionally, a level of abstraction is given to the model integration process that allows researchers and other technical personnel to perform more detailed and interactive modeling, visualization, optimization, calibration, and uncertainty analysis without requiring deep understanding of inter-process communication. To be compatible, a program must be written in a programming language with bindings to a common

  11. Optimizing hydrological consistency by incorporating hydrological signatures into model calibration objectives

    NASA Astrophysics Data System (ADS)

    Shafii, Mahyar; Tolson, Bryan A.

    2015-05-01

    The simulated outcome of a calibrated hydrologic model should be hydrologically consistent with the measured response data. Hydrologic modelers typically calibrate models to optimize residual-based goodness-of-fit measures, e.g., the Nash-Sutcliffe efficiency measure, and then evaluate the obtained results with respect to hydrological signatures, e.g., the flow duration curve indices. The literature indicates that the consideration of a large number of hydrologic signatures has not been addressed in a full multiobjective optimization context. This research develops a model calibration methodology to achieve hydrological consistency using goodness-of-fit measures, many hydrological signatures, as well as a level of acceptability for each signature. The proposed framework relies on a scoring method that transforms any hydrological signature to a calibration objective. These scores are used to develop the hydrological consistency metric, which is maximized to obtain hydrologically consistent parameter sets during calibration. This consistency metric is implemented in different signature-based calibration formulations that adapt the sampling according to hydrologic signature values. These formulations are compared with the traditional formulations found in the literature for seven case studies. The results reveal that Pareto dominance-based multiobjective optimization yields the highest level of consistency among all formulations. Furthermore, it is found that the choice of optimization algorithms does not affect the findings of this research.

  12. Improving subsurface hydrology in Earth System Models

    NASA Astrophysics Data System (ADS)

    Volk, J. M.; Clark, M. P.; Swenson, S. C.; Lawrence, D. M.; Tyler, S. W.

    2015-12-01

    Hydrologic processes that govern storage and transport of soil water and groundwater can have strong dynamic relationships with biogeochemical and atmospheric processes. This understanding has lead to a push to improve subsurface hydrologic parametrization in Earth System Models. Here we present results related to improving the implementation of soil moisture distribution, groundwater recharge/discharge, and subsurface drainage in the Community Land Model (CLM) which is the land surface model in the Community Earth System Model. First we identified geo-climatically different locations around the world to develop test cases. For each case we compare the vertical soil moisture distribution from the different implementations of 1D Richards equation, considering the boundary conditions, the treatment of the groundwater sink term, the vertical discretization, and the time stepping schemes. Generally, large errors in the hydrologic mass balance within the soil column occur when there is a large vertical gradient in soil moisture or when there is a shallow water table within a soil column. We then test the sensitivity of the algorithmic parameters that control temporal discretization and error tolerance of the adaptive time-stepping scheme to help optimize its computational efficiency. In addition, we vary the spatial discretization of soil layers (i.e. quantity of layers and their thicknesses) to better understand the sensitivity of vertical discretization of soil columns on soil moisture variability in ESMs. We present multivariate and multi-scale evaluation for the different model options and suggest ways to move forward with future model improvements.

  13. Towards Better Coupling of Hydrological Simulation Models

    NASA Astrophysics Data System (ADS)

    Penton, D.; Stenson, M.; Leighton, B.; Bridgart, R.

    2012-12-01

    Standards for model interoperability and scientific workflow software provide techniques and tools for coupling hydrological simulation models. However, model builders are yet to realize the benefits of these and continue to write ad hoc implementations and scripts. Three case studies demonstrate different approaches to coupling models, the first using tight interfaces (OpenMI), the second using a scientific workflow system (Trident) and the third using a tailored execution engine (Delft Flood Early Warning System - Delft-FEWS). No approach was objectively better than any other approach. The foremost standard for coupling hydrological models is the Open Modeling Interface (OpenMI), which defines interfaces for models to interact. An implementation of the OpenMI standard involves defining interchange terms and writing a .NET/Java wrapper around the model. An execution wrapper such as OatC.GUI or Pipistrelle executes the models. The team built two OpenMI implementations for eWater Source river system models. Once built, it was easy to swap river system models. The team encountered technical challenges with versions of the .Net framework (3.5 calling 4.0) and with the performance of the execution wrappers when running daily simulations. By design, the OpenMI interfaces are general, leaving significant decisions around the semantics of the interfaces to the implementer. Increasingly, scientific workflow tools such as Kepler, Taverna and Trident are able to replace custom scripts. These tools aim to improve the provenance and reproducibility of processing tasks. In particular, Taverna and the myExperiment website have had success making many bioinformatics workflows reusable and sharable. The team constructed Trident activities for hydrological software including IQQM, REALM and eWater Source. They built an activity generator for model builders to build activities for particular river systems. The models were linked at a simulation level, without any daily time

  14. Enhancements for Hydrological Modeling in ESMF

    NASA Astrophysics Data System (ADS)

    Deluca, C.; Oehmke, R.; Neckels, D.; Theurich, G.; O'Kuinghttons, R.; de Fainchtein, R.; Murphy, S.; Dunlap, R.

    2008-12-01

    Hydrological systems connect Earth's global physical phenomena with the local environmental impacts that affect our food, health, finances, and homes. The scales and processes that hydrological modelers must span are reflected in the challenges of developing infrastructure for this community. The basic requirements - the need to assemble and couple model components, the need for efficient I/O, the need for integrated visualization, analysis, and data services - are shared with other domains, such as climate and space weather. Where hydrology goes beyond other domains is in its terrific heterogeneity. The diversity of models, data structures, grids, computing platforms, computing languages, and specialized sub-domains involved is daunting. It's not surprising that the hydrological community has spawned a variety of different integrative efforts and frameworks, with distinctly different approaches. This talk will outline how the Earth System Modeling Framework (ESMF), which began in realm of high performance computing for the climate and weather domain, has begun to address the needs of hydrological modelers. We will describe ESMF's new mesh and observational data stream data structures, which join its structured grids and lower-level, index-space constructs as options for data representation, and the flexible, parallel regridding services that can interpolate data between them. The ESMF team is exploring a service oriented architecture approach to computing language and platform diversity, and to interfacing with other standard frameworks. We have also implemented C interfaces for optimized coupling between C and Fortran codes on traditional high performance computing platforms. To address the variety of components available, distributed communities, and integration with data and other services, ESMF has been exhancing its ability to store and write standard component and field metadata, and to link that metadata with full-service science portals. This enables

  15. Grid-Xinanjiang Distributed Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Li, Z.; Yao, C.; Yu, Z.

    2009-12-01

    The grid-based distributed Xinanjiang (Grid-Xinanjiang) model by combining the well-tested conceptual rainfall-runoff model and the physically based flow routing model has been developed for hydrologic processes simulation and flood forecasting. The DEM is utilized to derive the flow direction, routing sequencing, hillslope and channel slopes. The developed model includes canopy interception, direct channel precipitation, evapotranspiration, as well as runoff generation via saturation excess mechanism. The diffusion wave considering the influent of upstream inflow, direct channel precipitation and flow partition to the channels is developed to route the hillslope and channel flow on a cell basis. The Grid-Xinanjiang model is applied at a 1-km grid scale in a nested basin located in Huaihe basin, China. The basin with the drainage area of 2692.7 km2, contains five internal points where observed streamflow data are available, and is used to evaluate the developed model for its’ ability on the simulation of hydrologic processes within the basin. Calibration and verification of the Grid-Xinanjiang model are carried out at both daily and hourly time steps. The model is assessed by comparing streamflow and water stage simulation to observations at the basin outlet and gauging stations within the basin and also compared with these simulated with the original Xinanjiang model. The results indicate that the parameter estimation approach is efficient and the developed model can forecast the streamflow and stage hydrograph well.

  16. Operational hydrological ensemble forecasts in France, taking into account rainfall and hydrological model uncertainties.

    NASA Astrophysics Data System (ADS)

    Mathevet, T.; Garavaglia, F.; Gailhard, J.; Garçon, R.; Dubus, L.

    2009-09-01

    In operational conditions, the actual quality of meteorological and hydrological forecasts do not allow decision-making in a certain future. In this context, meteorological and hydrological ensemble forecasts allow a better representation of forecasts uncertainties. Compared to classical deterministic forecasts, ensemble forecasts improve the human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. In this paper, we present a hydrological ensemble forecasting system under development at EDF (French Hydropower Company). Our results were updated, taking into account a longer rainfall forecasts archive. Our forecasting system both takes into account rainfall forecasts uncertainties and hydrological model forecasts uncertainties. Hydrological forecasts were generated using the MORDOR model (Andreassian et al., 2006), developed at EDF and used on a daily basis in operational conditions on a hundred of watersheds. Two sources of rainfall forecasts were used : one is based on ECMWF forecasts, another is based on an analogues approach (Obled et al., 2002). Two methods of hydrological model forecasts uncertainty estimation were used : one is based on the use of equifinal parameter sets (Beven & Binley, 1992), the other is based on the statistical modelisation of the hydrological forecast empirical uncertainty (Montanari et al., 2004 ; Schaefli et al., 2007). Daily operational hydrological 7-day ensemble forecasts during 4 years (from 2005 to 2008) in few alpine watersheds were evaluated. Finally, we present a way to combine rainfall and hydrological model forecast uncertainties to achieve a good probabilistic calibration. Our results show that the combination of ECMWF and analogues-based rainfall forecasts allow a good probabilistic calibration of rainfall forecasts. They show also that the statistical modeling of the hydrological forecast empirical

  17. Proving the ecosystem value through hydrological modelling

    NASA Astrophysics Data System (ADS)

    Dorner, W.; Spachinger, K.; Porter, M.; Metzka, R.

    2008-11-01

    Ecosystems provide valuable functions. Also natural floodplains and river structures offer different types of ecosystem functions such as habitat function, recreational area and natural detention. From an economic stand point the loss (or rehabilitation) of these natural systems and their provided natural services can be valued as a damage (or benefit). Consequently these natural goods and services must be economically valued in project assessments e.g. cost-benefit-analysis or cost comparison. Especially in smaller catchments and river systems exists significant evidence that natural flood detention reduces flood risk and contributes to flood protection. Several research projects evaluated the mitigating effect of land use, river training and the loss of natural flood plains on development, peak and volume of floods. The presented project analysis the hypothesis that ignoring natural detention and hydrological ecosystem services could result in economically inefficient solutions for flood protection and mitigation. In test areas, subcatchments of the Danube in Germany, a combination of hydrological and hydrodynamic models with economic evaluation techniques was applied. Different forms of land use, river structure and flood protection measures were assed and compared from a hydrological and economic point of view. A hydrodynamic model was used to simulate flows to assess the extent of flood affected areas and damages to buildings and infrastructure as well as to investigate the impacts of levees and river structure on a local scale. These model results provided the basis for an economic assessment. Different economic valuation techniques, such as flood damage functions, cost comparison method and substation-approach were used to compare the outcomes of different hydrological scenarios from an economic point of view and value the ecosystem service. The results give significant evidence that natural detention must be evaluated as part of flood mitigation projects

  18. Pursuing the method of multiple working hypotheses for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Clark, M. P.; Kavetski, D.; Fenicia, F.

    2012-12-01

    Ambiguities in the representation of environmental processes have manifested themselves in a plethora of hydrological models, differing in almost every aspect of their conceptualization and implementation. The current overabundance of models is symptomatic of an insufficient scientific understanding of environmental dynamics at the catchment scale, which can be attributed to difficulties in measuring and representing the heterogeneity encountered in natural systems. This presentation advocates using the method of multiple working hypotheses for systematic and stringent testing of model alternatives in hydrology. We discuss how the multiple hypothesis approach provides the flexibility to formulate alternative representations (hypotheses) describing both individual processes and the overall system. When combined with incisive diagnostics to scrutinize multiple model representations against observed data, this provides hydrologists with a powerful and systematic approach for model development and improvement. Multiple hypothesis frameworks also support a broader coverage of the model hypothesis space and hence improve the quantification of predictive uncertainty arising from system and component non-identifiabilities. As part of discussing the advantages and limitations of multiple hypothesis frameworks, we critically review major contemporary challenges in hydrological hypothesis-testing, including exploiting different types of data to investigate the fidelity of alternative process representations, accounting for model structure ambiguities arising from major uncertainties in environmental data, quantifying regional differences in dominant hydrological processes, and the grander challenge of understanding the self-organization and optimality principles that may functionally explain and describe the heterogeneities evident in most environmental systems. We assess recent progress in these research directions, and how new advances are possible using multiple hypothesis

  19. Pursuing the method of multiple working hypotheses for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Clark, Martyn P.; Kavetski, Dmitri; Fenicia, Fabrizio

    2011-09-01

    Ambiguities in the representation of environmental processes have manifested themselves in a plethora of hydrological models, differing in almost every aspect of their conceptualization and implementation. The current overabundance of models is symptomatic of an insufficient scientific understanding of environmental dynamics at the catchment scale, which can be attributed to difficulties in measuring and representing the heterogeneity encountered in natural systems. This commentary advocates using the method of multiple working hypotheses for systematic and stringent testing of model alternatives in hydrology. We discuss how the multiple-hypothesis approach provides the flexibility to formulate alternative representations (hypotheses) describing both individual processes and the overall system. When combined with incisive diagnostics to scrutinize multiple model representations against observed data, this provides hydrologists with a powerful and systematic approach for model development and improvement. Multiple-hypothesis frameworks also support a broader coverage of the model hypothesis space and hence improve the quantification of predictive uncertainty arising from system and component nonidentifiabilities. As part of discussing the advantages and limitations of multiple-hypothesis frameworks, we critically review major contemporary challenges in hydrological hypothesis-testing, including exploiting different types of data to investigate the fidelity of alternative process representations, accounting for model structure ambiguities arising from major uncertainties in environmental data, quantifying regional differences in dominant hydrological processes, and the grander challenge of understanding the self-organization and optimality principles that may functionally explain and describe the heterogeneities evident in most environmental systems. We assess recent progress in these research directions, and how new advances are possible using multiple

  20. Precipitation forecasts and their uncertainty as input into hydrological models

    NASA Astrophysics Data System (ADS)

    Kobold, M.; Sušelj, K.

    2005-10-01

    Torrential streams and fast runoff are characteristic of most Slovenian rivers and extensive damage is caused almost every year by rainstorms affecting different regions of Slovenia. Rainfall-runoff models which are tools for runoff calculation can be used for flood forecasting. In Slovenia, the lag time between rainfall and runoff is only a few hours and on-line data are used only for now-casting. Predicted precipitation is necessary in flood forecasting some days ahead. The ECMWF (European Centre for Medium-Range Weather Forecasts) model gives general forecasts several days ahead while more detailed precipitation data with the ALADIN/SI model are available for two days ahead. Combining the weather forecasts with the information on catchment conditions and a hydrological forecasting model can give advance warning of potential flooding notwithstanding a certain degree of uncertainty in using precipitation forecasts based on meteorological models. Analysis of the sensitivity of the hydrological model to the rainfall error has shown that the deviation in runoff is much larger than the rainfall deviation. Therefore, verification of predicted precipitation for large precipitation events was performed with the ECMWF model. Measured precipitation data were interpolated on a regular grid and compared with the results from the ECMWF model. The deviation in predicted precipitation from interpolated measurements is shown with the model bias resulting from the inability of the model to predict the precipitation correctly and a bias for horizontal resolution of the model and natural variability of precipitation.

  1. Multivariate Probabilistic Analysis of an Hydrological Model

    NASA Astrophysics Data System (ADS)

    Franceschini, Samuela; Marani, Marco

    2010-05-01

    Model predictions derived based on rainfall measurements and hydrological model results are often limited by the systematic error of measuring instruments, by the intrinsic variability of the natural processes and by the uncertainty of the mathematical representation. We propose a means to identify such sources of uncertainty and to quantify their effects based on point-estimate approaches, as a valid alternative to cumbersome Montecarlo methods. We present uncertainty analyses on the hydrologic response to selected meteorological events, in the mountain streamflow-generating portion of the Brenta basin at Bassano del Grappa, Italy. The Brenta river catchment has a relatively uniform morphology and quite a heterogeneous rainfall-pattern. In the present work, we evaluate two sources of uncertainty: data uncertainty (the uncertainty due to data handling and analysis) and model uncertainty (the uncertainty related to the formulation of the model). We thus evaluate the effects of the measurement error of tipping-bucket rain gauges, the uncertainty in estimating spatially-distributed rainfall through block kriging, and the uncertainty associated with estimated model parameters. To this end, we coupled a deterministic model based on the geomorphological theory of the hydrologic response to probabilistic methods. In particular we compare the results of Monte Carlo Simulations (MCS) to the results obtained, in the same conditions, using Li's Point Estimate Method (LiM). The LiM is a probabilistic technique that approximates the continuous probability distribution function of the considered stochastic variables by means of discrete points and associated weights. This allows to satisfactorily reproduce results with only few evaluations of the model function. The comparison between the LiM and MCS results highlights the pros and cons of using an approximating method. LiM is less computationally demanding than MCS, but has limited applicability especially when the model

  2. Play with hydrologic models in R

    NASA Astrophysics Data System (ADS)

    Viglione, A.; Parajka, J.; Nester, T.; Blöschl, G.

    2012-04-01

    The aim of this poster is to show the advantages of building hydrologic models using the R environment for educational purposes. As an example we consider a conceptual rainfall-runoff model (HBV type) that was originally written in the fortran language and is used in many scientific studies and practical engineering applications in Austria. A simplified version of the model was built into a R package and compiled for different platforms and operating systems. The model runs on a daily time step and consists of a snow routine, a soil moisture routine and a flow routing routine. In this poster we present a set of examples that have been used in a graduate level course on engineering hydrology at the Vienna University of Technology. These include: - Multi-objective calibration of the model; - Manual vs. automatic calibration; - Visualisation of model outputs and efficiency; - Model application in ungauged catchments; - Operational forecast. The flexibility of R is ideal for education, since students can easily play with the extensive list of existing functionalities and define new functions and extensions.

  3. Modeling residual hydrologic errors with Bayesian inference

    NASA Astrophysics Data System (ADS)

    Smith, Tyler; Marshall, Lucy; Sharma, Ashish

    2015-09-01

    Hydrologic modelers are confronted with the challenge of producing estimates of the uncertainty associated with model predictions across an array of catchments and hydrologic flow regimes. Formal Bayesian approaches are commonly employed for parameter calibration and uncertainty analysis, but are often criticized for making strong assumptions about the nature of model residuals via the likelihood function that may not be well satisfied (or even checked). This technical note outlines a residual error model (likelihood function) specification framework that aims to provide guidance for the application of more appropriate residual error models through a nested approach that is both flexible and extendible. The framework synthesizes many previously employed residual error models and has been applied to four synthetic datasets (of differing error structure) and a real dataset from the Black River catchment in Queensland, Australia. Each residual error model was investigated and assessed under a top-down approach focused on its ability to properly characterize the errors. The results of these test applications indicate that a multifaceted assessment strategy is necessary to determine the adequacy of an individual likelihood function.

  4. An operational GLS model for hydrologic regression

    USGS Publications Warehouse

    Tasker, Gary D.; Stedinger, J.R.

    1989-01-01

    Recent Monte Carlo studies have documented the value of generalized least squares (GLS) procedures to estimate empirical relationships between streamflow statistics and physiographic basin characteristics. This paper presents a number of extensions of the GLS method that deal with realities and complexities of regional hydrologic data sets that were not addressed in the simulation studies. These extensions include: (1) a more realistic model of the underlying model errors; (2) smoothed estimates of cross correlation of flows; (3) procedures for including historical flow data; (4) diagnostic statistics describing leverage and influence for GLS regression; and (5) the formulation of a mathematical program for evaluating future gaging activities. ?? 1989.

  5. Physical models for classroom teaching in hydrology

    NASA Astrophysics Data System (ADS)

    Rodhe, A.

    2012-09-01

    Hydrology teaching benefits from the fact that many important processes can be illustrated and explained with simple physical models. A set of mobile physical models has been developed and used during many years of lecturing at basic university level teaching in hydrology. One model, with which many phenomena can be demonstrated, consists of a 1.0-m-long plexiglass container containing an about 0.25-m-deep open sand aquifer through which water is circulated. The model can be used for showing the groundwater table and its influence on the water content in the unsaturated zone and for quantitative determination of hydraulic properties such as the storage coefficient and the saturated hydraulic conductivity. It is also well suited for discussions on the runoff process and the significance of recharge and discharge areas for groundwater. The flow paths of water and contaminant dispersion can be illustrated in tracer experiments using fluorescent or colour dye. This and a few other physical models, with suggested demonstrations and experiments, are described in this article. The finding from using models in classroom teaching is that it creates curiosity among the students, promotes discussions and most likely deepens the understanding of the basic processes.

  6. Modeling of surface microtopography and its impacts on hydrologic processes

    NASA Astrophysics Data System (ADS)

    Habtezion, Noah Lebassi

    Understanding the impacts of surface microtopography on hydrologic processes is critical. The objectives of this thesis research are: (1) to evaluate the effects of DEM resolution on microtopographic characteristics, hydrologic connectivity, and modeling of hydrologic processes; and (2) to assess the influences of multiple rainfall events on surface and subsurface hydrologic processes with the use of a puddle-to-puddle (P2P) modeling system. The change in DEM resolution has a significant effect on how surface microtopography is depicted, which in turn alters the hydrologic response of a topographic surface. The smoothing of reduced DEM resolution tends to enhance hydrologic connectivity, reduce the depression storage and infiltration, and increase surface runoff. Temporal rainfall distribution results in spatio-temporal variations in soil water dynamics, depression storage, infiltration, hydrologic connectivity, and surface runoff. The reduction in ponding time and infiltration, and the enhancement of hydrologic connectivity further caused earlier and greater surface runoff generation.

  7. A Smallholder Socio-hydrological Modelling Framework

    NASA Astrophysics Data System (ADS)

    Pande, S.; Savenije, H.; Rathore, P.

    2014-12-01

    Small holders are farmers who own less than 2 ha of farmland. They often have low productivity and thus remain at subsistence level. A fact that nearly 80% of Indian farmers are smallholders, who merely own a third of total farmlands and belong to the poorest quartile, but produce nearly 40% of countries foodgrains underlines the importance of understanding the socio-hydrology of a small holder. We present a framework to understand the socio-hydrological system dynamics of a small holder. It couples the dynamics of 6 main variables that are most relevant at the scale of a small holder: local storage (soil moisture and other water storage), capital, knowledge, livestock production, soil fertility and grass biomass production. The model incorporates rule-based adaptation mechanisms (for example: adjusting expenditures on food and fertilizers, selling livestocks etc.) of small holders when they face adverse socio-hydrological conditions, such as low annual rainfall, higher intra-annual variability in rainfall or variability in agricultural prices. It allows us to study sustainability of small holder farming systems under various settings. We apply the framework to understand the socio-hydrology of small holders in Aurangabad, Maharashtra, India. This district has witnessed suicides of many sugarcane farmers who could not extricate themselves out of the debt trap. These farmers lack irrigation and are susceptible to fluctuating sugar prices and intra-annual hydroclimatic variability. This presentation discusses two aspects in particular: whether government interventions to absolve the debt of farmers is enough and what is the value of investing in local storages that can buffer intra-annual variability in rainfall and strengthening the safety-nets either by creating opportunities for alternative sources of income or by crop diversification.

  8. Hybrid Modelling Approach to Prairie hydrology: Fusing Data-driven and Process-based Hydrological Models

    NASA Astrophysics Data System (ADS)

    Mekonnen, B.; Nazemi, A.; Elshorbagy, A.; Mazurek, K.; Putz, G.

    2012-04-01

    Modeling the hydrological response in prairie regions, characterized by flat and undulating terrain, and thus, large non-contributing areas, is a known challenge. The hydrological response (runoff) is the combination of the traditional runoff from the hydrologically contributing area and the occasional overflow from the non-contributing area. This study provides a unique opportunity to analyze the issue of fusing the Soil and Water Assessment Tool (SWAT) and Artificial Neural Networks (ANNs) in a hybrid structure to model the hydrological response in prairie regions. A hybrid SWAT-ANN model is proposed, where the SWAT component and the ANN module deal with the effective (contributing) area and the non-contributing area, respectively. The hybrid model is applied to the case study of Moose Jaw watershed, located in southern Saskatchewan, Canada. As an initial exploration, a comparison between ANN and SWAT models is established based on addressing the daily runoff (streamflow) prediction accuracy using multiple error measures. This is done to identify the merits and drawbacks of each modeling approach. It has been found out that the SWAT model has better performance during the low flow periods but with degraded efficiency during periods of high flows. The case is different for the ANN model as ANNs exhibit improved simulation during high flow periods but with biased estimates during low flow periods. The modelling results show that the new hybrid SWAT-ANN model is capable of exploiting the strengths of both SWAT and ANN models in an integrated framrwork. The new hybrid SWAT-ANN model simulates daily runoff quite satisfactorily with NSE measures of 0.80 and 0.83 during calibration and validation periods, respectively. Furthermore, an experimental assessment was performed to identify the effects of the ANN training method on the performance of the hybrid model as well as the parametric identifiability. Overall, the results obtained in this study suggest that the fusion

  9. Modeling hydrologic and ecologic responses using a new eco-hydrological model for identification of droughts

    NASA Astrophysics Data System (ADS)

    Sawada, Yohei; Koike, Toshio; Jaranilla-Sanchez, Patricia Ann

    2014-07-01

    Drought severely damages water and agricultural resources, and both hydrological and ecological responses are important for its understanding. First, precipitation deficit induces soil moisture deficiency and high plant water stress causing agricultural droughts. Second, hydrological drought characterized by deficit of river discharge and groundwater follows agricultural drought. However, contributions of vegetation dynamics to these processes at basin scale have not been quantified. To address this issue, we develop an eco-hydrological model that can calculate river discharge, groundwater, energy flux, and vegetation dynamics as diagnostic variables at basin scale within a distributed hydrological modeling framework. The model is applied to drought analysis in the Medjerda River basin. From model inputs and outputs, we calculate drought indices for different drought types. The model shows reliable accuracy in reproducing observed river discharge in long-term (19 year) simulation. Moreover, the drought index calculated from the model-estimated annual peak of leaf area index correlates well (correlation coefficient r = 0.89) with the drought index from nationwide annual crop production, which demonstrates that the modeled leaf area index is capable of representing agricultural droughts related to historical food shortages. We show that vegetation dynamics have a more rapid response to meteorological droughts than river discharge and groundwater dynamics in the Medjerda basin because vegetation dynamics are sensitive to soil moisture in surface layers, whereas soil moisture in deeper layers strongly contributes to streamflow and groundwater level. Our modeling framework can contribute to analyze drought progress, although analyses for other climate conditions are needed.

  10. A multicomponent coupled model of glacier hydrology

    NASA Astrophysics Data System (ADS)

    Flowers, Gwenn Elizabeth

    Multiple lines of evidence suggest a causal link between subglacial hydrology and phenomena such as fast-flowing ice. This evidence includes a measured correlation between water under alpine glaciers and their motion, the presence of saturated sediment beneath Antaxctic ice streams, and geologic signatures of enhanced paleo-ice flow over deformable substrates. The complexity of the glacier bed as a three-component mixture presents an obstacle to unraveling these conundra. Inadequate representations of hydrology, in part, prevent us from closing the gap between empirical descriptions and a comprehensive consistent framework for understanding the dynamics of glacierized systems. I have developed a distributed numerical model that solves equations governing glacier surface runoff, englacial water transport, subglacial drainage, and subsurface groundwater flow. Ablation and precipitation drive the surface model through a temperature-index parameterization. Water is permitted to flow over and off the glacier, or to the bed through a system of crevasses, pipes, and fractures. A macroporous sediment horizon transports subglacial water to the ice margin or to an underlying aquifer. Governing equations are derived from the law of mass conservation and are expressed as a balance between the internal redistribution of water and external sources. Each of the four model components is represented as a two-dimensional, vertically-integrated layer that communicates with its neighbors through water exchange. Stacked together, these layers approximate a three-dimensional system. I tailor the model to Trapridge Glacier, where digital maps of the surface and bed have been derived from ice-penetrating radar data. Observations of subglacial water pressure provide additional constraints on model parameters and a basis for comparison of simulations with real data. Three classical idealizations of glacier geometry are used for simple model experiments. Equilibrium tests emphasize geometric

  11. Attributing spatial patterns of hydrological model performance

    NASA Astrophysics Data System (ADS)

    Eisner, S.; Malsy, M.; Flörke, M.

    2013-12-01

    Global hydrological models and land surface models are used to understand and simulate the global terrestrial water cycle. They are, in particular, applied to assess the current state of global water resources, to identify anthropogenic pressures on the global water system, and to assess impacts of global and climate change on water resources. Especially in data-scarce regions, the growing availability of remote sensing products, e.g. GRACE estimates of changes in terrestrial water storage, evaporation or soil moisture estimates, has added valuable information to force and constrain these models as they facilitate the calibration and validation of simulated states and fluxes other than stream flow at large spatial scales. Nevertheless, observed discharge records provide important evidence to evaluate the quality of water availability estimates and to quantify the uncertainty associated with these estimates. Most large scale modelling approaches are constrained by simplified physical process representations and they implicitly rely on the assumption that the same model structure is valid and can be applied globally. It is therefore important to understand why large scale hydrological models perform good or poor in reproducing observed runoff and discharge fields in certain regions, and to explore and explain spatial patterns of model performance. We present an extensive evaluation of the global water model WaterGAP (Water - Global Assessment and Prognosis) to simulate 20th century discharges. The WaterGAP modeling framework comprises a hydrology model and several water use models and operates in its current version, WaterGAP3, on a 5 arc minute global grid and . Runoff generated on the individual grid cells is routed along a global drainage direction map taking into account retention in natural surface water bodies, i.e. lakes and wetlands, as well as anthropogenic impacts, i.e. flow regulation and water abstraction for agriculture, industry and domestic purposes as

  12. Hydrology

    ERIC Educational Resources Information Center

    Sharp, John M., Jr.

    1978-01-01

    The past year saw a re-emphasis on the practical aspects of hydrology due to regional drought patterns, urban flooding, and agricultural and energy demands on water resources. Highlights of hydrologic symposia, publications, and events are included. (MA)

  13. Improving Hydrology in Land Ice Models

    NASA Astrophysics Data System (ADS)

    Price, Stephen; Flowers, Gwenn; Schoof, Christian

    2011-05-01

    Community Earth System Model Land Ice Working Group Meeting; Boulder, Colorado, 13 January 2011 ; Recent observations indicate that mass loss from glaciers and ice sheets (“land ice”) is increasing. The drivers of these changes are not well understood, and modeling the land ice response to them remains challenging. As a result, the Intergovernmental Panel on Climate Change explicitly avoided speculating on 21st-century sea level rise from ice dynamical processes in its fourth assessment report. The mismatch between observations of land ice change and model skill at mimicking those changes is behind recent efforts to develop next-generation land ice models. Necessary improvements to existing models include improved dynamics, coupling to climate models, and better representations of important boundary conditions and physical processes. Basal sliding, the primary control on the rate of land ice delivery to the oceans, is one such boundary condition that is largely controlled by land ice hydrology.

  14. Adaptable Web Modules to Stimulate Active Learning in Engineering Hydrology using Data and Model Simulations of Three Regional Hydrologic Systems

    NASA Astrophysics Data System (ADS)

    Habib, E. H.; Tarboton, D. G.; Lall, U.; Bodin, M.; Rahill-Marier, B.; Chimmula, S.; Meselhe, E. A.; Ali, A.; Williams, D.; Ma, Y.

    2013-12-01

    The hydrologic community has long recognized the need for broad reform in hydrologic education. A paradigm shift is critically sought in undergraduate hydrology and water resource education by adopting context-rich, student-centered, and active learning strategies. Hydrologists currently deal with intricate issues rooted in complex natural ecosystems containing a multitude of interconnected processes. Advances in the multi-disciplinary field include observational settings such as Critical Zone and Water, Sustainability and Climate Observatories, Hydrologic Information Systems, instrumentation and modeling methods. These research advances theory and practices call for similar efforts and improvements in hydrologic education. The typical, text-book based approach in hydrologic education has focused on specific applications and/or unit processes associated with the hydrologic cycle with idealizations, rather than the contextual relations in the physical processes and the spatial and temporal dynamics connecting climate and ecosystems. An appreciation of the natural variability of these processes will lead to graduates with the ability to develop independent learning skills and understanding. This appreciation cannot be gained in curricula where field components such as observational and experimental data are deficient. These types of data are also critical when using simulation models to create environments that support this type of learning. Additional sources of observations in conjunction with models and field data are key to students understanding of the challenges associated with using models to represent such complex systems. Recent advances in scientific visualization and web-based technologies provide new opportunities for the development of active learning techniques utilizing ongoing research. The overall goal of the current study is to develop visual, case-based, data and simulation driven learning experiences to instructors and students through a web

  15. Coupled land surface/hydrologic/atmospheric models

    NASA Technical Reports Server (NTRS)

    Pielke, Roger; Steyaert, Lou; Arritt, Ray; Lahtakia, Mercedes; Smith, Chris; Ziegler, Conrad; Soong, Su Tzai; Avissar, Roni; Wetzel, Peter; Sellers, Piers

    1993-01-01

    The topics covered include the following: prototype land cover characteristics data base for the conterminous United States; surface evapotranspiration effects on cumulus convection and implications for mesoscale models; the use of complex treatment of surface hydrology and thermodynamics within a mesoscale model and some related issues; initialization of soil-water content for regional-scale atmospheric prediction models; impact of surface properties on dryline and MCS evolution; a numerical simulation of heavy precipitation over the complex topography of California; representing mesoscale fluxes induced by landscape discontinuities in global climate models; emphasizing the role of subgrid-scale heterogeneity in surface-air interaction; and problems with modeling and measuring biosphere-atmosphere exchanges of energy, water, and carbon on large scales.

  16. Integrating an open source dynamic river model in hydrology modeling frameworks

    NASA Astrophysics Data System (ADS)

    Liu, Frank; Hodges, Ben

    2014-05-01

    A challenge for hydrology modeling is linking landscape runoff models with river network models. Although some hydrological models directly implement a river routing scheme within their code, such a monolithic approach is too rigid because it does not allow the latest river routing advances to be used. Unlike the 2D interface between atmospheric and landscape models, the interface between landscape runoff models and river network models is more difficult to define. In this PICO presentation, we address problems with model interfaces, which are related to issues such as time and space-scale differences between the models. We also provide an overview of SPRINT, an open source river network model, which has adapted the model interface architecture and numerical methods widely used in semiconductor microchip design. Finally, we propose two model integration mechanisms: the file-based "net-list" and the API (application programming interface) approach.

  17. Toward an Online Community of Educators: The Modular Curriculum for Hydrologic Advancement (MOCHA)

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

    The field of hydrology encompasses a wide range of departments and disciplines, ranging from civil engineering to geography to geosciences. As a consequence, in-class hydrology education is often strongly biased towards the background of a single instructor, limiting the educational experience of the students and not allowing for a holistic approach to hydrology education. Recently established, the Modular Curriculum for Hydrologic Advancement (MOCHA) creates an online community of hydrologists from a range of backgrounds and disciplines to define the boundaries of an unbiased hydrology education and to jointly develop resources to overcome previous instructional limitations (http://www.mocha.psu.edu/). Our first objective is to create an evolving core curriculum for hydrology education freely available to, developed, evolved and reviewed by the worldwide hydrologic community. On a larger scale, we hope to raise the standard of hydrology education and to foster international collaboration and exchange. Our work began with an initial survey including over 100 hydrology educators to assess the state of current hydrology education. Based on the survey results, the MOCHA project was designed and implemented, and initial teaching material and pedagogical guidelines for good practice in teaching were prepared. This past fall and spring, we piloted the website and teaching material across several universities. The web-based MOCHA project has recently been opened to solicit contributions from the global hydrology community. Our presentation will focus on the overall vision behind MOCHA, lessons learned from our initial piloting, and current steps to achieve our vision.

  18. A Hypothesis-based Approach to Hydrological Model Development: The Case for Flexible Model Structures

    NASA Astrophysics Data System (ADS)

    Clark, M. P.; Kavetski, D.; Fenicia, F.

    2010-12-01

    Ambiguities in the appropriate representation of environmental processes have manifested themselves in a plethora of hydrological models, differing in almost every aspect of their conceptualization and implementation. This current overabundance of models is symptomatic of insufficient scientific understanding of environmental dynamics at the catchment scale, which can be attributed to difficulties in quantifying the impact of sub-catchment heterogeneities on the catchment’s hydrological response. In this presentation we advocate the use of flexible modeling frameworks during the development and subsequent refinement of catchment-scale hydrological models. We argue that the ability of flexible modeling frameworks to decompose a model into its constituent hypotheses, necessarily combined with incisive diagnostics to scrutinize these individual hypotheses against observed data, provides hydrologists with a very powerful and systematic approach for improving process representation in models. Flexible models also support a broader coverage of the model hypothesis space and hence facilitate a more comprehensive quantification of the predictive uncertainty associated with system and component non-identifiabilities that plague many model analyses. As part of our discussion of the advantages and limitations of flexible model frameworks, we critically review major contemporary challenges in hydrological hypothesis-testing, including exploiting data to investigate the fidelity of alternative process representations, accounting for model structure ambiguities arising from uncertainty in environmental data, and the challenge of understanding regional differences in dominant hydrological processes. We assess recent progress in these research directions, and how such progress can be exploited within flexible model applications to advance the community’s quest for more scientifically defensible catchment-scale hydrological models.

  19. 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

  20. From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

    NASA Astrophysics Data System (ADS)

    Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

    2016-02-01

    This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the

  1. Calibration of hydrological model with programme PEST

    NASA Astrophysics Data System (ADS)

    Brilly, Mitja; Vidmar, Andrej; Kryžanowski, Andrej; Bezak, Nejc; Šraj, Mojca

    2016-04-01

    PEST is tool based on minimization of an objective function related to the root mean square error between the model output and the measurement. We use "singular value decomposition", section of the PEST control file, and Tikhonov regularization method for successfully estimation of model parameters. The PEST sometimes failed if inverse problems were ill-posed, but (SVD) ensures that PEST maintains numerical stability. The choice of the initial guess for the initial parameter values is an important issue in the PEST and need expert knowledge. The flexible nature of the PEST software and its ability to be applied to whole catchments at once give results of calibration performed extremely well across high number of sub catchments. Use of parallel computing version of PEST called BeoPEST was successfully useful to speed up calibration process. BeoPEST employs smart slaves and point-to-point communications to transfer data between the master and slaves computers. The HBV-light model is a simple multi-tank-type model for simulating precipitation-runoff. It is conceptual balance model of catchment hydrology which simulates discharge using rainfall, temperature and estimates of potential evaporation. Version of HBV-light-CLI allows the user to run HBV-light from the command line. Input and results files are in XML form. This allows to easily connecting it with other applications such as pre and post-processing utilities and PEST itself. The procedure was applied on hydrological model of Savinja catchment (1852 km2) and consists of twenty one sub-catchments. Data are temporary processed on hourly basis.

  2. Plant adaptive behaviour in hydrological models (Invited)

    NASA Astrophysics Data System (ADS)

    van der Ploeg, M. J.; Teuling, R.

    2013-12-01

    Models that will be able to cope with future precipitation and evaporation regimes need a solid base that describes the essence of the processes involved [1]. Micro-behaviour in the soil-vegetation-atmosphere system may have a large impact on patterns emerging at larger scales. A complicating factor in the micro-behaviour is the constant interaction between vegetation and geology in which water plays a key role. The resilience of the coupled vegetation-soil system critically depends on its sensitivity to environmental changes. As a result of environmental changes vegetation may wither and die, but such environmental changes may also trigger gene adaptation. Constant exposure to environmental stresses, biotic or abiotic, influences plant physiology, gene adaptations, and flexibility in gene adaptation [2-6]. Gene expression as a result of different environmental conditions may profoundly impact drought responses across the same plant species. Differences in response to an environmental stress, has consequences for the way species are currently being treated in models (single plant to global scale). In particular, model parameters that control root water uptake and plant transpiration are generally assumed to be a property of the plant functional type. Assigning plant functional types does not allow for local plant adaptation to be reflected in the model parameters, nor does it allow for correlations that might exist between root parameters and soil type. Models potentially provide a means to link root water uptake and transport to large scale processes (e.g. Rosnay and Polcher 1998, Feddes et al. 2001, Jung 2010), especially when powered with an integrated hydrological, ecological and physiological base. We explore the experimental evidence from natural vegetation to formulate possible alternative modeling concepts. [1] Seibert, J. 2000. Multi-criteria calibration of a conceptual runoff model using a genetic algorithm. Hydrology and Earth System Sciences 4(2): 215

  3. Hydrological modelling in sandstone rocks watershed

    NASA Astrophysics Data System (ADS)

    Ponížilová, Iva; Unucka, Jan

    2015-04-01

    The contribution is focused on the modelling of surface and subsurface runoff in the Ploučnice basin. The used rainfall-runoff model is HEC-HMS comprising of the method of SCS CN curves and a recession method. The geological subsurface consisting of sandstone is characterised by reduced surface runoff and, on the contrary, it contributes to subsurface runoff. The aim of this paper is comparison of the rate of influence of sandstone on reducing surface runoff. The recession method for subsurface runoff was used to determine the subsurface runoff. The HEC-HMS model allows semi- and fully distributed approaches to schematisation of the watershed and rainfall situations. To determine the volume of runoff the method of SCS CN curves is used, which results depend on hydrological conditions of the soils. The rainfall-runoff model assuming selection of so-called methods of event of the SCS-CN type is used to determine the hydrograph and peak flow rate based on simulation of surface runoff in precipitation exceeding the infiltration capacity of the soil. The recession method is used to solve the baseflow (subsurface) runoff. The method is based on the separation of hydrograph to direct runoff and subsurface or baseflow runoff. The study area for the simulation of runoff using the method of SCS CN curves to determine the hydrological transformation is the Ploučnice basin. The Ploučnice is a hydrologically significant river in the northern part of the Czech Republic, it is a right tributary of the Elbe river with a total basin area of 1.194 km2. The average value of CN curves for the Ploučnice basin is 72. The geological structure of the Ploučnice basin is predominantly formed by Mesozoic sandstone. Despite significant initial loss of rainfall the basin response to the causal rainfall was demonstrated by a rapid rise of the surface runoff from the watershed and reached culmination flow. Basically, only surface runoff occures in the catchment during the initial phase of

  4. Hydrological model uncertainty assessment in southern Africa

    NASA Astrophysics Data System (ADS)

    Hughes, D. A.; Kapangaziwiri, E.; Sawunyama, T.

    2010-06-01

    The importance of hydrological uncertainty analysis has been emphasized in recent years and there is an urgent need to incorporate uncertainty estimation into water resources assessment procedures used in the southern Africa region. The region is characterized by a paucity of accurate data and limited human resources, but the need for informed development decisions is critical to social and economic development. One of the main sources of uncertainty is related to the estimation of the parameters of hydrological models. This paper proposes a framework for establishing parameter values, exploring parameter inter-dependencies and setting parameter uncertainty bounds for a monthly time-step rainfall-runoff model (Pitman model) that is widely used in the region. The method is based on well-documented principles of sensitivity and uncertainty analysis, but recognizes the limitations that exist within the region (data scarcity and accuracy, model user attitudes, etc.). Four example applications taken from different climate and physiographic regions of South Africa illustrate that the methods are appropriate for generating behavioural stream flow simulations which include parameter uncertainty. The parameters that dominate the model response and their degree of uncertainty vary between regions. Some of the results suggest that the uncertainty bounds will be too wide for effective water resources decision making. Further work is required to reduce some of the subjectivity in the methods and to investigate other approaches for constraining the uncertainty. The paper recognizes that probability estimates of uncertainty and methods to include input climate data uncertainties need to be incorporated into the framework in the future.

  5. Modeling hydrologic processes at the residential scale

    NASA Astrophysics Data System (ADS)

    Xiao, Q.; McPherson, G.; Simpson, J.; Ustin, S.

    2003-12-01

    In California, urbanization has led to polluted runoff, flooding during winter, and water shortages during summer. There is growing interest in application of microscale hydrologic solutions that eliminate storm runoff and conserve water at the source. In this study, a physically-based numerical model was developed to better understand hydrologic processes at the residential scale and the interaction of these processes among different Best Management Practices (BMPs). This model calculates all in-flow and out-flow using an hourly interval over a full year or for specific storm events. Water enters the system via precipitation and irrigation and leaves the system via evapotranspiration, surface and subsurface runoff, and from percolation to groundwater. The model was applied to two single-family residential parcels in Los Angeles. Two years of data collected from the control and treatment sites were used to calibrate and validate the model. More than 97% of storm runoff to the street was eliminated with installation of low-cost BMPs (i.e., rain gutters that direct roof runoff to a lawn retention basin and a driveway interceptor that directs runoff to a drywell in the lawn retention basin). Evaluated individually, the driveway interceptor was the most effective BMP for storm runoff reduction (65%), followed by the rain gutter installation (28%), and lawn converted to retention basin (12%). Installation of an 11 m3 cistern did not substantially reduce runoff, but did provide storage for 9% of annual irrigation demand. Simulated landscape irrigation demand was reduced 53% by increasing efficiency through use of a drip irrigation system for shrubs, and adjusting monthly application rates based on evapotranspirational water demand. The model showed that infiltration and surface runoff processes were particularly sensitive to the soil's physical properties and its effective depth. If the existing loam soil were replaced by clay soil annual runoff discharge to the street

  6. 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.

  7. 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

    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.

  8. Constraining hydrologic models using thermal analysis

    SciTech Connect

    Doughty, Christine; Karasaki, Kenzi

    2002-12-12

    Starting with regional geographic, geologic, hydrologic, geophysical, and meteorological data for the Tono area in Gifu, Japan, we develop a numerical model to simulate subsurface flow and transport in a 4 km by 6 km by 3 km thick fractured granite rock mass overlain by sedimentary layers. Individual fractures are not modeled explicitly. Rather, continuum permeability and porosity distributions are assigned stochastically, based on well-test data and fracture density measurements. The primary goal of the study is to simulate steady-state groundwater flow through the site, then calculate travel times to the model boundaries from specified monitoring points. The lateral boundaries of the model follow topographic features such as ridgelines and rivers. Assigning lateral boundary conditions is a major point of uncertainty in model construction. We evaluate two models with opposing boundary conditions: mostly closed and mostly open boundaries. The two models show vastly different spatial distributions of groundwater flow, so we would like to find a means of choosing the more realistic model. Surface recharge is much larger for the closed model, but field recharge data are of too limited spatial extent to provide a definitive model constraint. Temperature profiles in 16 boreholes show consistent trends with conduction-dominated (linear) temperature profiles below depths of about 300 m. The open and closed models predict strongly different temperature versus depth profiles; with the closed model showing a strong convective signature produced by widespread surface recharge effects to the depth. The open model shows more linear temperature profiles, better agreeing with measurements from the field. Based on this data we can eliminate from consideration the closed model, at least in its present form in which surface recharge penetrates deep into the model.

  9. Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change

    NASA Astrophysics Data System (ADS)

    Karlsson, Ida B.; Sonnenborg, Torben O.; Refsgaard, Jens Christian; Trolle, Dennis; Børgesen, Christen Duus; Olesen, Jørgen E.; Jeppesen, Erik; Jensen, Karsten H.

    2016-04-01

    Impact studies of the hydrological response of future climate change are important for the water authorities when risk assessment, management and adaptation to a changing climate are carried out. The objective of this study was to model the combined effect of land use and climate changes on hydrology for a 486 km2 catchment in Denmark and to evaluate the sensitivity of the results to the choice of hydrological model. Three hydrological models, NAM, SWAT and MIKE SHE, were constructed and calibrated using similar methods. Each model was forced with results from four climate models and four land use scenarios. The results revealed that even though the hydrological models all showed similar performance during calibration, the mean discharge response to climate change varied up to 30%, and the variations were even higher for extreme events (1th and 99th percentile). Land use changes appeared to cause little change in mean hydrological responses and little variation between hydrological models. Differences in hydrological model responses to land use were, however, significant for extremes due to dissimilarities in hydrological model structure and process equations. The climate model choice remained the dominant factor for mean discharge, low and high flows as well as hydraulic head at the end of the century.

  10. Improvements of Physically-Based Hydrological Modelling using the ACRU Agro-Hydrological Modelling System

    NASA Astrophysics Data System (ADS)

    Bonifacio, C. M. T.; Kienzle, S. W.; Xu, W.; Zhang, J.

    2014-12-01

    The uncertainty of future water availability due to climate change in the Upper Oldman River Basin in Alberta, Canada, and downstream users is considered in this study. A changing climate can significantly perturb hydrological response within a region, thereby affecting the available water resources within southern Alberta. The ACRU agro-hydrological modelling system is applied to simulate historical (1950-2010) and future (2041-2070) streamflows and volumes of a major irrigation reservoir. Like many highly complex, process-based distributed models, major limitations include the data availability and data quality at finer spatial resolutions. With the use of a scripting language, certain limitations can be greatly reduced. Three phases of the project will be emphasized. First, the assimilation of solar radiation, relative humidity, sunshine hours and wind speed daily data into the Canadian 10KM daily climate data that contains daily precipitation, maximum and minimum temperature data for the period 1950-2010, so as to enable potential evapotranspiration calculations using the Penman-Monteith equation. Second, the downscaling of five regional climate model (RCM) data to match the 10KM spatial resolution was undertaken. Third, a total of 1722 hydrological response units (HRUs) were delineated within the 4403 km2 large upper Oldman River Basin. In all phases of model input data parameterization and calibration, the automation of known external procedures greatly decreased erroneous model inputs and increased the efficiency of validating the quality of input data to be used within the ACRU model.

  11. A unified approach for process-based hydrologic modeling: 1. Modeling concept

    NASA Astrophysics Data System (ADS)

    Clark, Martyn P.; Nijssen, Bart; Lundquist, Jessica D.; Kavetski, Dmitri; Rupp, David E.; Woods, Ross A.; Freer, Jim E.; Gutmann, Ethan D.; Wood, Andrew W.; Brekke, Levi D.; Arnold, Jeffrey R.; Gochis, David J.; Rasmussen, Roy M.

    2015-04-01

    This work advances a unified approach to process-based hydrologic modeling to enable controlled and systematic evaluation of multiple model representations (hypotheses) of hydrologic processes and scaling behavior. Our approach, which we term the Structure for Unifying Multiple Modeling Alternatives (SUMMA), formulates a general set of conservation equations, providing the flexibility to experiment with different spatial representations, different flux parameterizations, different model parameter values, and different time stepping schemes. In this paper, we introduce the general approach used in SUMMA, detailing the spatial organization and model simplifications, and how different representations of multiple physical processes can be combined within a single modeling framework. We discuss how SUMMA can be used to systematically pursue the method of multiple working hypotheses in hydrology. In particular, we discuss how SUMMA can help tackle major hydrologic modeling challenges, including defining the appropriate complexity of a model, selecting among competing flux parameterizations, representing spatial variability across a hierarchy of scales, identifying potential improvements in computational efficiency and numerical accuracy as part of the numerical solver, and improving understanding of the various sources of model uncertainty.

  12. RHydro - Hydrological models and tools to represent and analyze hydrological data in R

    NASA Astrophysics Data System (ADS)

    Reusser, D. E.; Buytaert, W.; Vitolo, C.

    2012-04-01

    In hydrology, basic equations and procedures keep being implemented from scratch by scientist, with the potential for errors and inefficiency. The use of libraries can overcome these problems. As an example, hydrological libraries could contain: 1. Major representations of hydrological processes such as infiltration, sub-surface runoff and routing algorithms. 2. Scaling functions, for instance to combine remote sensing precipitation fields with rain gauge data 3. Data consistency checks 4. Performance measures. Here we present a beginning for such a library implemented in the high level data programming language R. Currently, Top-model, the abc-Model, HBV, a multi-model ensamble called FUSE, data import routines for WaSiM-ETH as well basic visualization and evaluation tools are implemented. Care is taken to make functions and models compatible with other existing frameworks in hydrology, such as for example Hydromad.

  13. Ensemble evaluation of hydrological model hypotheses

    NASA Astrophysics Data System (ADS)

    Krueger, Tobias; Freer, Jim; Quinton, John N.; MacLeod, Christopher J. A.; Bilotta, Gary S.; Brazier, Richard E.; Butler, Patricia; Haygarth, Philip M.

    2010-07-01

    It is demonstrated for the first time how model parameter, structural and data uncertainties can be accounted for explicitly and simultaneously within the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. As an example application, 72 variants of a single soil moisture accounting store are tested as simplified hypotheses of runoff generation at six experimental grassland field-scale lysimeters through model rejection and a novel diagnostic scheme. The fields, designed as replicates, exhibit different hydrological behaviors which yield different model performances. For fields with low initial discharge levels at the beginning of events, the conceptual stores considered reach their limit of applicability. Conversely, one of the fields yielding more discharge than the others, but having larger data gaps, allows for greater flexibility in the choice of model structures. As a model learning exercise, the study points to a "leaking" of the fields not evident from previous field experiments. It is discussed how understanding observational uncertainties and incorporating these into model diagnostics can help appreciate the scale of model structural error.

  14. Monthly Hydrological Model Evaluation through Mapping the Hydrological Pattern to Information Space

    NASA Astrophysics Data System (ADS)

    Pan, B.; Cong, Z.

    2014-12-01

    Conceptual and stochastic monthly hydrological models have been widely used for climatic change impact exploration and long-range stream flow forecast. With disparate philosophies and different but insufficient inputs, most of the existing models are capable of generating satisfying outputs, which reveals a relatively robust idiosyncrasy of hydrological pattern over monthly time scale. This research uses the epistemic-aleatory uncertainties evaluation framework to examine the information source sink terms and flows of 6 conceptual monthly water balance models and a seasonal autoregressive stochastic hydrologic model over 19 basins in Jiangxi Province, China and the experiment basins of MOPEX project. By using the stream technique of Lisp, we constructed two programming paradigms into which the hydrological models mentioned above could be fitted. We focus on detecting and explaining the best achievable predictive performances and data-revealed insufficient of the models in each paradigm, especially the hydrological meaning of the iteration variables in these models. Finally, we make an attempt to compare and connect these two paradigms against the backdrop of algorithmic information theory to help us form a better understanding of monthly hydrological pattern.

  15. A hydrological model of New Zealand

    NASA Astrophysics Data System (ADS)

    Woods, R. A.; Tarboton, D. G.; Ibbitt, R. P.; Wild, M.; Henderson, R. D.; Turner, R.

    2003-04-01

    We present initial results from a hydrological model of New Zealand, using Topnet, a variant of TOPMODEL, linked to a kinematic wave channel network routing algorithm. This model run uses daily timesteps for the period 1985-2001, and subdivides the country into approximately 35,000 sub-catchments of 7-10 sq km each. The sub-catchments are linked by 55,000 river reaches, which route sub-catchment runoff. The model subcatchments and reaches are defined automatically by DEM analyses, and initial estimates of model parameters are defined by GIS overlay, coupled with purpose-built model assembly code, and lookup tables for model parameters. A daily simulation for 1 year over New Zealand takes two hours on a standard desktop computer. The model is forced by gridded daily rainfall and temperature data, and it calculates daily water balance for each of the sub-catchments (rain, evaporation, throughfall, infiltration, soil drainage, surface runoff, subsurface runoff, and changes in storage in the canopy, root zone, and saturated storage), as well as daily flows in each river reach. The model as currently implemented does not include snow, glaciers, or deep groundwater flow (i.e. across sub-catchment boundaries). The first applications of the model are for developing an annual water balance of New Zealand for the period 1994-2001, at the regional scale, and for driving a high-spatial resolution, daily time-stepping national erosion model. We are moving to further applications for water resource modeling (e.g. impact of abstraction and/or storage), and for flood forecasting, using hourly rainfall from a mesoscale atmospheric model.

  16. Modeling the Interactions between Hydrological Extremes, Water Management and Society.

    NASA Astrophysics Data System (ADS)

    Martinez, Fabian; Di Baldassarre, Giuliano; Kalantari, Zahra

    2016-04-01

    Over the past years, several studies have focused on exploring human impacts on the hydrological regime. Even though the dominant hydrological processes are mostly well understood, there are still several challenges related to modeling the coevolution of human impacts on (and responses to) hydrological extremes, such as floods and droughts. Some initial modeling attempts have proved to capture the essential dynamics emerging from two-way feedbacks between hydrological and social processes. However, they have predominantly focused on flooding. This research aims to develop a new conceptual model unraveling the interplay between hydrological extremes (floods and droughts) and human societies in a changing climate. In particular, this socio-hydrological model aims at understanding, and predicting the dynamics of coupled human-water systems to explain and capture how the occurrence of hydrological extremes changes water management approach, and how such a change (in turn) mitigates the impacts of hydrological extremes. The conceptual model is then applied to a case study to test its ability in simulating the dynamics emerging from the interplay between hydrological and social processes.

  17. Hydrological Modelling of Ganga River basin.

    NASA Astrophysics Data System (ADS)

    Anand, J.; Gosain, A. K.; Khosa, R.

    2015-12-01

    Application of a hydrological model, Soil and Water Assessment Tool (SWAT) to the Ganga basin having a total drainage area of around 1.08 M sq. km extending over Tibet, Nepal, India and Bangladesh has been made. The model is calibrated to determine the spatial deviations in runoff at sub-basin level, and to capture the water balance of the river basin. Manual calibration approach was used for calibrating the SWAT model by following multi-step procedure to get to the realistic present situation as close as possible. Simulations were then further made with and without proposed future projects to obtain various scenarios. The various statistical parameters used for the evaluation of the monthly runoff simulation showed that SWAT performed well in mimicking the monthly stream flow for Ganga River basin. The model under predicted the flows in the non-perennial region during non-monsoon season, due to low rainfall and regulated flows and seepage taking place from the reservoirs. The impacts of the interventions, both existing as well as proposed, on the water balance of the basin were evaluated and quantified. The derived results suggest that there is a substantial reduction in overall water resources availability in the study basin on account of the current level of development and further, future developments, as are being proposed, may require a careful study of their potential impact on currently sanctioned water use. The present study showcases that efficacy of the model for simulating the stream flow is admirable.

  18. An integrated hydrologic modeling framework for coupling SWAT with MODFLOW

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil and Water Assessment Tool (SWAT), MODFLOW, and Energy Balance based Evapotranspiration (EB_ET) models are extensively used to estimate different components of the hydrological cycle. Surface and subsurface hydrological processes are modeled in SWAT but limited to the extent of shallow aquif...

  19. 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...

  20. Multi-Objective Calibrationo of Hydrologic Model Using Satellite Data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hydrologic modeling often involves a large number of parameters, some of which cannot be measured directly and may vary with land cover, soil or even seasons. Therefore parameter estimation is a critical step in applying a hydrologic model to any study area. Parameter estimation is typically done by...

  1. Modelling the hydrological cycle in assessments of climate change

    NASA Technical Reports Server (NTRS)

    Rind, D.; Rosenzweig, C.; Goldberg, R.

    1992-01-01

    The predictions of climate change studies depend crucially on the hydrological cycles embedded in the different models used. It is shown here that uncertainties in hydrological processes and inconsistencies in both climate and impact models limit confidence in current assessments of climate change. A future course of action to remedy this problem is suggested.

  2. A question driven socio-hydrological modeling process

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

    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 and 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 the choice of modeling structure, scope, and detail. 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 and adaptive to the question context. We demonstrate its utility by exploring a question: 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

  3. Hydrology

    ERIC Educational Resources Information Center

    Sharp, John M.

    1977-01-01

    Lists many recent research projects in hydrology, including flow in fractured media, improvements in remote-sensing techniques, effects of urbanization on water resources, and developments in drainage basins. (MLH)

  4. Assessing spatial patterns to characterize performance in hydrological modeling

    NASA Astrophysics Data System (ADS)

    Koch, Julian; Stisen, Simon; Høgh Jensen, Karsten

    2014-05-01

    In Hydrology, spatially distributed models are traditionally evaluated against a single spatially aggregated catchment scale observation in form of river discharge with the conviction that it features the correct simulation of catchment-inherent distributed variables. Recent advances in fully distributed grid based model codes, the availability of spatially distributed data (remote sensing and intensive field studies) and computational power allow a shift towards a spatial model evaluation away from the traditional aggregated evaluation. The need of this paradigm shift is demanded in literature; however no single spatial performance metric was identified yet that proofed suitable for comparing observed and simulated spatial patterns. The goal of this study is to develop and test simple and flexible metrics for assessing spatial patterns of distributed hydrological variables that go beyond global statistics. These metrics, individually or collectively can later be used as performance criteria in the calibration process of hydrological models. Observed and simulated land surface temperature, by the MODIS satellite and by MIKE SHE, a coupled and fully distributed hydrological model, respectively are used as a benchmark to test promising spatial metrics. Additionally a synthetic dataset which contains systematic temperature perturbations, e.g. a general bias or a shift/displacement of data, is generated to test strengths and weaknesses of the spatial metrics. Four quantitative methodologies for comparing spatial patterns are brought forward in this study: (1) A fuzzy set approach that incorporates both fuzziness of location and fuzziness of category. (2) Kappa statistic that expresses the similarity between two maps based on a contingency table (error matrix). (3) An extended version of (2) by considering both fuzziness in location and fuzziness in category. (4) Increasing the information content of a single cell by aggregating neighborhood cells at different window

  5. 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

  6. Data Mining of Hydrological Model Performances

    NASA Astrophysics Data System (ADS)

    Vitolo, Claudia; Buytaert, Wouter

    2013-04-01

    Multi-objective criteria have long been used to infer hydrological simulations and fit the natural world. On the other hand, modelling frameworks are also becoming more and more popular as identification of the processes occurring in a catchment is still a very uncertain matter. In theory, multi-objective criteria and multi-model frameworks should be used in combination so that the 'representation' of the catchment is fitted to the observations, not only the simulated results. In practise those approaches are highly computationally demanding. The modeller is often obliged to find a compromise reducing either the number of objective functions or model structures taken into consideration. This compromise is becoming obsolete using parallel computing. In the present study we investigate the extend to which model selection algorithms and regionalisation techniques can be improved by such facilities and highlight the challenges that still need to be addressed. The model simulations are obtained using an ensemble of conceptual lumped models (FUSE by Clark et al. 2008), but techniques and suggestions are of general use and applicable to any modelling frameworks. In particular we developed a novel model selection algorithm tuned to drastically reduce the subjectivity in the analysis. The procedure was automated and coupled with redundancy reduction techniques such as PCA and Cluster Analysis. Results show that the actual model 'representation' has the shape of a set of complementing model structures. It is also possible to capture intra-annum dynamics of the response as the algorithm recognises subtle variations in the selected model structures in different seasons. Similar variations can be found analysing different catchments. This suggests the same methodology would be suitable for analysing spatial patterns in the distribution of suitable model structures and maybe long term dynamics in relation with expedited climate modifications. Although the mentioned methodology

  7. Improvement of Continuous Hydrologic Models and HMS SMA Parameters Reduction

    NASA Astrophysics Data System (ADS)

    Rezaeian Zadeh, Mehdi; Zia Hosseinipour, E.; Abghari, Hirad; Nikian, Ashkan; Shaeri Karimi, Sara; Moradzadeh Azar, Foad

    2010-05-01

    Hydrological models can help us to predict stream flows and associated runoff volumes of rainfall events within a watershed. There are many different reasons why we need to model the rainfall-runoff processes of for a watershed. However, the main reason is the limitation of hydrological measurement techniques and the costs of data collection at a fine scale. Generally, we are not able to measure all that we would like to know about a given hydrological systems. This is very particularly the case for ungauged catchments. Since the ultimate aim of prediction using models is to improve decision-making about a hydrological problem, therefore, having a robust and efficient modeling tool becomes an important factor. Among several hydrologic modeling approaches, continuous simulation has the best predictions because it can model dry and wet conditions during a long-term period. Continuous hydrologic models, unlike event based models, account for a watershed's soil moisture balance over a long-term period and are suitable for simulating daily, monthly, and seasonal streamflows. In this paper, we describe a soil moisture accounting (SMA) algorithm added to the hydrologic modeling system (HEC-HMS) computer program. As is well known in the hydrologic modeling community one of the ways for improving a model utility is the reduction of input parameters. The enhanced model developed in this study is applied to Khosrow Shirin Watershed, located in the north-west part of Fars Province in Iran, a data limited watershed. The HMS SMA algorithm divides the potential path of rainfall onto a watershed into five zones. The results showed that the output of HMS SMA is insensitive with the variation of many parameters such as soil storage and soil percolation rate. The study's objective is to remove insensitive parameters from the model input using Multi-objective sensitivity analysis. Keywords: Continuous Hydrologic Modeling, HMS SMA, Multi-objective sensitivity analysis, SMA Parameters

  8. Complexity of groundwater models in catchment hydrological models

    NASA Astrophysics Data System (ADS)

    Attinger, Sabine; Herold, Christian; Kumar, Rohini; Mai, Juliane; Ross, Katharina; Samaniego, Luis; Zink, Matthias

    2015-04-01

    In catchment hydrological models, groundwater is usually modeled very simple: it is conceptualized as a linear reservoir that gets the water from the upper unsaturated zone reservoir and releases water to the river system as baseflow. The baseflow is only a minor component of the total river flow and groundwater reservoir parameters are therefore difficult to be inversely estimated by means of river flow data only. In addition, the modelled values of the absolute height of the water filling the groundwater reservoir - in other words the groundwater levels - are of limited meaning due to coarse or no spatial resolution of groundwater and due to the fact that only river flow data are used for the calibration. The talk focuses on the question: Which complexity in terms of model complexity and model resolution is necessary to characterize groundwater processes and groundwater responses adequately in distributed catchment hydrological models? Starting from a spatially distributed catchment hydrological model with a groundwater compartment that is conceptualized as a linear reservoir we stepwise increase the groundwater model complexity and its spatial resolution to investigate which resolution, which complexity and which data are needed to reproduce baseflow and groundwater level data adequately.

  9. From local hydrological process analysis to regional hydrological model application in Benin: Concept, results and perspectives

    NASA Astrophysics Data System (ADS)

    Bormann, H.; Faß, T.; Giertz, S.; Junge, B.; Diekkrüger, B.; Reichert, B.; Skowronek, A.

    This paper presents the concept, first results and perspectives of the hydrological sub-project of the IMPETUS-Benin project which is part of the GLOWA program funded by the German ministry of education and research. In addition to the research concept, first results on field hydrology, pedology, hydrogeology and hydrological modelling are presented, focusing on the understanding of the actual hydrological processes. For analysing the processes a 30 km 2 catchment acting as a super test site was chosen which is assumed to be representative for the entire catchment of about 15,000 km 2. First results of the field investigations show that infiltration, runoff generation and soil erosion strongly depend on land cover and land use which again influence the soil properties significantly. A conceptual hydrogeological model has been developed summarising the process knowledge on runoff generation and subsurface hydrological processes. This concept model shows a dominance of fast runoff components (surface runoff and interflow), a groundwater recharge along preferential flow paths, temporary interaction between surface and groundwater and separate groundwater systems on different scales (shallow, temporary groundwater on local scale and permanent, deep groundwater on regional scale). The findings of intensive measurement campaigns on soil hydrology, groundwater dynamics and soil erosion have been integrated into different, scale-dependent hydrological modelling concepts applied at different scales in the target region (upper Ouémé catchment in Benin, about 15,000 km 2). The models have been applied and successfully validated. They will be used for integrated scenario analyses in the forthcoming project phase to assess the impacts of global change on the regional water cycle and on typical problem complexes such as food security in West African countries.

  10. Building Community Around Hydrologic Data Models Within CUAHSI

    NASA Astrophysics Data System (ADS)

    Maidment, D.

    2007-12-01

    The Consortium of Universities for the Advancement of Hydrologic Science, Inc (CUAHSI) has a Hydrologic Information Systems project which aims to provide better data access and capacity for data synthesis for the nation's water information, both that collected by academic investigators and that collected by water agencies. These data include observations of streamflow, water quality, groundwater levels, weather and climate and aquatic biology. Each water agency or research investigator has a unique method of formatting their data (syntactic heterogeneity) and describing their variables (semantic heterogeneity). The result is a large agglomeration of data in many formats and descriptions whose full content is hard to interpret and analyze. CUAHSI is helping to resolve syntactic heterogeneity through the development of WaterML, a standard XML markup language for communicating water observations data through web services, and a standard relational database structure for archiving data called the Observations Data Model. Variables in these data archiving and communicating systems are indexed against a controlled vocabulary of descriptive terms to provide the capacity to synthesize common data types from disparate data sources.

  11. Comparison of global optimization approaches for robust calibration of hydrologic model parameters

    NASA Astrophysics Data System (ADS)

    Jung, I. W.

    2015-12-01

    Robustness of the calibrated parameters of hydrologic models is necessary to provide a reliable prediction of future performance of watershed behavior under varying climate conditions. This study investigated calibration performances according to the length of calibration period, objective functions, hydrologic model structures and optimization methods. To do this, the combination of three global optimization methods (i.e. SCE-UA, Micro-GA, and DREAM) and four hydrologic models (i.e. SAC-SMA, GR4J, HBV, and PRMS) was tested with different calibration periods and objective functions. Our results showed that three global optimization methods provided close calibration performances under different calibration periods, objective functions, and hydrologic models. However, using the agreement of index, normalized root mean square error, Nash-Sutcliffe efficiency as the objective function showed better performance than using correlation coefficient and percent bias. Calibration performances according to different calibration periods from one year to seven years were hard to generalize because four hydrologic models have different levels of complexity and different years have different information content of hydrological observation. Acknowledgements This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

  12. Advances in Watershed Models and Modeling

    NASA Astrophysics Data System (ADS)

    Yeh, G. T.; Zhang, F.

    2015-12-01

    The development of watershed models and their applications to real-world problems has evolved significantly since 1960's. Watershed models can be classified based on what media are included, what processes are dealt with, and what approaches are taken. In term of media, a watershed may include segregated overland regime, river-canal-open channel networks, ponds-reservoirs-small lakes, and subsurface media. It may also include integrated media of all these or a partial set of these as well as man-made control structures. In term of processes, a watershed model may deal with coupled or decoupled hydrological and biogeochemical cycles. These processes include fluid flow, thermal transport, salinity transport, sediment transport, reactive transport, and biota and microbe kinetics. In terms of approaches, either parametric or physics-based approach can be taken. This talk discusses the evolution of watershed models in the past sixty years. The advances of watershed models center around their increasing design capability to foster these segregated or integrated media and coupled or decoupled processes. Widely used models developed by academia, research institutes, government agencies, and private industries will be reviewed in terms of the media and processes included as well as approaches taken. Many types of potential benchmark problems in general can be proposed and will be discussed. This presentation will focus on three benchmark problems of biogeochemical cycles. These three problems, dealing with water quality transport, will be formulated in terms of reactive transport. Simulation results will be illustrated using WASH123D, a watershed model developed and continuously updated by the author and his PhD graduates. Keywords: Hydrological Cycles, Biogeochemical Cycles, Biota Kinetics, Parametric Approach, Physics-based Approach, Reactive Transport.

  13. Does model performance improve with complexity? A case study with three hydrological models

    NASA Astrophysics Data System (ADS)

    Orth, Rene; Staudinger, Maria; Seneviratne, Sonia I.; Seibert, Jan; Zappa, Massimiliano

    2015-04-01

    In recent decades considerable progress has been made in climate model development. Following the massive increase in computational power, models became more sophisti- cated. At the same time also simple conceptual models have advanced. In this study we validate and compare three hydrological models of different complexity to investigate whether their performance varies accordingly. For this purpose we use runoff and also soil moisture measurements, which allow a truly independent validation, from several sites across Switzerland. The models are calibrated in similar ways with the same runoff data. Our results show that the more complex models HBV and PREVAH outperform the simple water balance model (SWBM) in case of runoff but not for soil moisture. Furthermore the most sophisticated PREVAH model shows an added value compared to the HBV model only in case of soil moisture. Focusing on extreme events we find generally improved performance of the SWBM during drought conditions and degraded agreement with observations during wet extremes. For the more complex models we find the opposite behavior, probably because they were primarily developed for predic- tion of runoff extremes. As expected given their complexity, HBV and PREVAH have more problems with over-fitting. All models show a tendency towards better perfor- mance in lower altitudes as opposed to (pre-)alpine sites. The results vary considerably across the investigated sites. In contrast, the different metrics we consider to estimate the agreement between models and observations lead to similar conclusions, indicating that the performance of the considered models is similar at different time scales as well as for anomalies and long-term means. We conclude that added complexity does not necessarily lead to improved performance of hydrological models, and that performance can vary greatly depending on the considered hydrological variable (e.g. runoff vs. soil moisture) or hydrological conditions (floods vs

  14. Does model performance improve with complexity? A case study with three hydrological models

    NASA Astrophysics Data System (ADS)

    Orth, Rene; Staudinger, Maria; Seneviratne, Sonia I.; Seibert, Jan; Zappa, Massimiliano

    2015-04-01

    In recent decades considerable progress has been made in climate model development. Following the massive increase in computational power, models became more sophisticated. At the same time also simple conceptual models have advanced. In this study we validate and compare three hydrological models of different complexity to investigate whether their performance varies accordingly. For this purpose we use runoff and also soil moisture measurements, which allow a truly independent validation, from several sites across Switzerland. The models are calibrated in similar ways with the same runoff data. Our results show that the more complex models HBV and PREVAH outperform the simple water balance model (SWBM) in case of runoff but not for soil moisture. Furthermore the most sophisticated PREVAH model shows an added value compared to the HBV model only in case of soil moisture. Focusing on extreme events we find generally improved performance of the SWBM during drought conditions and degraded agreement with observations during wet extremes. For the more complex models we find the opposite behavior, probably because they were primarily developed for prediction of runoff extremes. As expected given their complexity, HBV and PREVAH have more problems with over-fitting. All models show a tendency towards better performance in lower altitudes as opposed to (pre-) alpine sites. The results vary considerably across the investigated sites. In contrast, the different metrics we consider to estimate the agreement between models and observations lead to similar conclusions, indicating that the performance of the considered models is similar at different time scales as well as for anomalies and long-term means. We conclude that added complexity does not necessarily lead to improved performance of hydrological models, and that performance can vary greatly depending on the considered hydrological variable (e.g. runoff vs. soil moisture) or hydrological conditions (floods vs. droughts).

  15. Comparing Sediment Yield Predictions from Different Hydrologic Modeling Schemes

    NASA Astrophysics Data System (ADS)

    Dahl, T. A.; Kendall, A. D.; Hyndman, D. W.

    2015-12-01

    Sediment yield, or the delivery of sediment from the landscape to a river, is a difficult process to accurately model. It is primarily a function of hydrology and climate, but influenced by landcover and the underlying soils. These additional factors make it much more difficult to accurately model than water flow alone. It is not intuitive what impact different hydrologic modeling schemes may have on the prediction of sediment yield. Here, two implementations of the Modified Universal Soil Loss Equation (MUSLE) are compared to examine the effects of hydrologic model choice. Both the Soil and Water Assessment Tool (SWAT) and the Landscape Hydrology Model (LHM) utilize the MUSLE for calculating sediment yield. SWAT is a lumped parameter hydrologic model developed by the USDA, which is commonly used for predicting sediment yield. LHM is a fully distributed hydrologic model developed primarily for integrated surface and groundwater studies at the watershed to regional scale. SWAT and LHM models were developed and tested for two large, adjacent watersheds in the Great Lakes region; the Maumee River and the St. Joseph River. The models were run using a variety of single model and ensemble downscaled climate change scenarios from the Coupled Model Intercomparison Project 5 (CMIP5). The initial results of this comparison are discussed here.

  16. Hydrological modeling of the Jiaoyi watershed (China) using HSPF model.

    PubMed

    Yan, Chang-An; Zhang, Wanchang; Zhang, Zhijie

    2014-01-01

    A watershed hydrological model, hydrological simulation program-Fortran (HSPF), was applied to simulate the spatial and temporal variation of hydrological processes in the Jiaoyi watershed of Huaihe River Basin, the heaviest shortage of water resources and polluted area in China. The model was calibrated using the years 2001-2004 and validated with data from 2005 to 2006. Calibration and validation results showed that the model generally simulated mean monthly and daily runoff precisely due to the close matching hydrographs between simulated and observed runoff, as well as the excellent evaluation indicators such as Nash-Sutcliffe efficiency (NSE), coefficient of correlation (R (2)), and the relative error (RE). The similar simulation results between calibration and validation period showed that all the calibrated parameters had a certain representation in Jiaoyi watershed. Additionally, the simulation in rainy months was more accurate than the drought months. Another result in this paper was that HSPF was also capable of estimating the water balance components reasonably and realistically in space through the whole watershed. The calibrated model can be used to explore the effects of climate change scenarios and various watershed management practices on the water resources and water environment in the basin. PMID:25013863

  17. Hydrological Modeling of the Jiaoyi Watershed (China) Using HSPF Model

    PubMed Central

    Yan, Chang-An; Zhang, Wanchang; Zhang, Zhijie

    2014-01-01

    A watershed hydrological model, hydrological simulation program-Fortran (HSPF), was applied to simulate the spatial and temporal variation of hydrological processes in the Jiaoyi watershed of Huaihe River Basin, the heaviest shortage of water resources and polluted area in China. The model was calibrated using the years 2001–2004 and validated with data from 2005 to 2006. Calibration and validation results showed that the model generally simulated mean monthly and daily runoff precisely due to the close matching hydrographs between simulated and observed runoff, as well as the excellent evaluation indicators such as Nash-Sutcliffe efficiency (NSE), coefficient of correlation (R2), and the relative error (RE). The similar simulation results between calibration and validation period showed that all the calibrated parameters had a certain representation in Jiaoyi watershed. Additionally, the simulation in rainy months was more accurate than the drought months. Another result in this paper was that HSPF was also capable of estimating the water balance components reasonably and realistically in space through the whole watershed. The calibrated model can be used to explore the effects of climate change scenarios and various watershed management practices on the water resources and water environment in the basin. PMID:25013863

  18. Revisiting an interdisciplinary hydrological modelling project. A socio-hydrology (?) example from the early 2000s

    NASA Astrophysics Data System (ADS)

    Seidl, Roman; Barthel, Roland

    2016-04-01

    Interdisciplinary scientific and societal knowledge plays an increasingly important role in global change research. Also, in the field of water resources interdisciplinarity as well as cooperation with stakeholders from outside academia have been recognized as important. In this contribution, we revisit an integrated regional modelling system (DANUBIA), which was developed by an interdisciplinary team of researchers and relied on stakeholder participation in the framework of the GLOWA-Danube project from 2001 to 2011 (Mauser and Prasch 2016). As the model was developed before the current increase in literature on participatory modelling and interdisciplinarity, we ask how a socio-hydrology approach would have helped and in what way it would have made the work different. The present contribution firstly presents the interdisciplinary concept of DANUBIA, mainly with focus on the integration of human behaviour in a spatially explicit, process-based numerical modelling system (Roland Barthel, Janisch, Schwarz, Trifkovic, Nickel, Schulz, and Mauser 2008; R. Barthel, Nickel, Meleg, Trifkovic, and Braun 2005). Secondly, we compare the approaches to interdisciplinarity in GLOWA-Danube with concepts and ideas presented by socio-hydrology. Thirdly, we frame DANUBIA and a review of key literature on socio-hydrology in the context of a survey among hydrologists (N = 184). This discussion is used to highlight gaps and opportunities of the socio-hydrology approach. We show that the interdisciplinary aspect of the project and the participatory process of stakeholder integration in DANUBIA were not entirely successful. However, important insights were gained and important lessons were learnt. Against the background of these experiences we feel that in its current state, socio-hydrology is still lacking a plan for knowledge integration. Moreover, we consider necessary that socio-hydrology takes into account the lessons learnt from these earlier examples of knowledge integration

  19. Uses and limitations of the soil survey in hydrologic modeling

    NASA Astrophysics Data System (ADS)

    Brooks, E.; Boll, J.

    2009-12-01

    One of the greatest challenges in hydrologic modeling is characterizing the effects of soil structure of hydrologic flow paths in complex watersheds. The Predictions in Ungauged Basins (PUB) initiative is pushing scientists to come up with innovative ways to reduce model calibration and predictive uncertainty and improve process understanding. Some of these innovative approaches have included incorporating ‘soft data’ as information for developing conceptual watershed frameworks and guiding calibration. In this study we examine the uses and limitations of the soil survey in hydrologic modeling. County soil surveys were initiated in 1899 and now digital maps are available throughout most of the US. Although these surveys were initially meant to guide selection and development of land, these surveys now include a great wealth of information from specific physical properties to indicators of saturation and development of perched water tables. To what degree does the information in the soil survey improve understanding of dominant hydrologic processes in a watershed? At what point must a hydrologist exercise discretion in using this information? We will discuss the extent to which the soil survey can be used to 1.) conceptualize the basic hydrology of a watershed, 2.) provide input data to a process-based hydrologic model, and 3.) validate spatial predictions of runoff and erosion from distributed hydrologic models. We will demonstrate each of these uses through case studies from multiple ecological regions across the country.

  20. Climate model uncertainty versus conceptual geological uncertainty in hydrological modeling

    NASA Astrophysics Data System (ADS)

    Sonnenborg, T. O.; Seifert, D.; Refsgaard, J. C.

    2015-09-01

    Projections of climate change impact are associated with a cascade of uncertainties including in CO2 emission scenarios, climate models, downscaling and impact models. The relative importance of the individual uncertainty sources is expected to depend on several factors including the quantity that is projected. In the present study the impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Each projection of future climate is a result of a GCM-RCM model combination (from the ENSEMBLES project) forced by the same CO2 scenario (A1B). The changes from the reference period (1991-2010) to the future period (2081-2100) in projected hydrological variables are evaluated and the effects of geological model and climate model uncertainties are quantified. The results show that uncertainty propagation is context-dependent. While the geological conceptualization is the dominating uncertainty source for projection of travel time and capture zones, the uncertainty due to the climate models is more important for groundwater hydraulic heads and stream flow.

  1. Climate model uncertainty vs. conceptual geological uncertainty in hydrological modeling

    NASA Astrophysics Data System (ADS)

    Sonnenborg, T. O.; Seifert, D.; Refsgaard, J. C.

    2015-04-01

    Projections of climate change impact are associated with a cascade of uncertainties including CO2 emission scenario, climate model, downscaling and impact model. The relative importance of the individual uncertainty sources is expected to depend on several factors including the quantity that is projected. In the present study the impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Each projection of future climate is a result of a GCM-RCM model combination (from the ENSEMBLES project) forced by the same CO2 scenario (A1B). The changes from the reference period (1991-2010) to the future period (2081-2100) in projected hydrological variables are evaluated and the effects of geological model and climate model uncertainties are quantified. The results show that uncertainty propagation is context dependent. While the geological conceptualization is the dominating uncertainty source for projection of travel time and capture zones, the uncertainty on the climate models is more important for groundwater hydraulic heads and stream flow.

  2. eWaterCycle: Developing a hyper resolution global hydrological model

    NASA Astrophysics Data System (ADS)

    Sutanudjaja, Edwin; Hut, Rolf; Drost, Niels; Steele-Dunne, Susan; de Jong, Kor; van Beek, Ludovicus; Karssenberg, Derek; van de Giesen, Nick; Bierkens, Marc

    2013-04-01

    The development of a high resolution global hydrological model has recently been put forward as Grand Challenge for the hydrological community (Wood et al., 2011). The current version of the global hydrological model PCR-GLOBWB (van Beek et al., 2011) runs at a relatively coarse spatial grid (i.e. 0.1° or about 10 km at the equator), which is well above the hyper resolution envisioned in the Grand Challenge (i.e. 100 m). The eWaterCycle project aims at developing a high resolution global hydrological model allowing for a better representation of the effects of spatial heterogeneity in topography, soil, and vegetation on hydrological dynamics. Here we modify PCR-GLOBWB so that it runs at much higher resolution, on the order of 1 km or finer, that will be relevant for addressing critical water cycle science questions and many hydrological applications such as assessing water resources sustainability, flood and drought frequency under climate change. The development of such a hyper resolution model requires utilizing recent computational advances and massive parallel computer systems. So far, the hydrological community has not yet made full use of such possibilities. The eWaterCycle is a close cooperation between hydrologists (Delft University of Technology and Utrecht University) and the Netherlands eScience Center (NleSC) - that intends to supports and reinforce data-intensive research through creative and innovative use of information and communication technology (ICT). The hyper resolution model built in this project will contribute to the current scientific state-of-the-art by combining hydrological knowledge with ICT challenges. The refinement of the current model would be a huge step forward, because increasing resolution also requires adding an explicit spatial representation of local processes (groundwater flow, water diversions, glaciers, etc.) that will greatly enhance the regional to local applicability of global models. We also argue that the result

  3. Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Vrugt, Jasper A.; Ter Braak, Cajo J. F.; Clark, Martyn P.; Hyman, James M.; Robinson, Bruce A.

    2008-12-01

    There is increasing consensus in the hydrologic literature that an appropriate framework for streamflow forecasting and simulation should include explicit recognition of forcing and parameter and model structural error. This paper presents a novel Markov chain Monte Carlo (MCMC) sampler, entitled differential evolution adaptive Metropolis (DREAM), that is especially designed to efficiently estimate the posterior probability density function of hydrologic model parameters in complex, high-dimensional sampling problems. This MCMC scheme adaptively updates the scale and orientation of the proposal distribution during sampling and maintains detailed balance and ergodicity. It is then demonstrated how DREAM can be used to analyze forcing data error during watershed model calibration using a five-parameter rainfall-runoff model with streamflow data from two different catchments. Explicit treatment of precipitation error during hydrologic model calibration not only results in prediction uncertainty bounds that are more appropriate but also significantly alters the posterior distribution of the watershed model parameters. This has significant implications for regionalization studies. The approach also provides important new ways to estimate areal average watershed precipitation, information that is of utmost importance for testing hydrologic theory, diagnosing structural errors in models, and appropriately benchmarking rainfall measurement devices.

  4. GIS as an Integration Tool for Hydrologic Modeling: Spatial Data Management, Analysis and Visualization

    NASA Astrophysics Data System (ADS)

    Setegn, S. G.; Lawrence, A.; Mahmoudi, M.

    2015-12-01

    The Applied Research Center at Florida International University (ARC-FIU) is supporting the soil and groundwater remediation efforts of the U.S. Department of Energy (DOE) Savannah River Site (SRS) by developing a surface water model to simulate the hydrology and the fate and transport of contaminants and sediment in the Tims Branch watershed. The first phase of model development was initiated in 2014 using the MIKE SHE/MIKE 11 hydrological modeling package which has a geographic information systems (GIS) user interface built into its system that can directly use spatial GIS databases (geodatabases) for model inputs. This study developed an ArcGIS geodatabase to support the hydrological modeling work for SRS. The coupling of a geodatabase with MIKE SHE/MIKE 11 numerical models can serve as an efficient tool that significantly reduces the time needed for data preparation. The geodatabase provides an advanced spatial data structure needed to address the management, processing, and analysis of large GIS and timeseries datasets derived from multiple sources that are used for numerical model calibration, uncertainty analysis, and simulation of flow and contaminant fate and transport during extreme climatic events. The geodatabase developed is based on the ArcHydro and ArcGIS Base Map data models with modifications made for project specific input parameters. The significance of this approach was to ensure its replicability for potential application in other watersheds. This paper describes the process of development of the SRS geodatabase and the application of GIS tools to pre-process and analyze hydrological model data; automate repetitive geoprocessing tasks; and produce maps for visualization of the surface water hydrology of the Tims Branch watershed. Key Words: GIS, hydrological modeling, geodatabase, hydrology, MIKE SHE/MIKE 11

  5. Modeling the hydrological patterns on Pantanal wetlands, Brazil

    NASA Astrophysics Data System (ADS)

    Castro, A. A.; Cuartas, A.; Coe, M. T.; Koumrouyan, A.; Panday, P. K.; Lefebvre, P.; Padovani, C.; Costa, M. H.; de Oliveira, G. S.

    2014-12-01

    The Pantanal of Brazil is one of the world's largest wetland regions. It is located within the 370,000 km2 Alto Paraguai Basin (BAP). In wet years almost 15% of the total area of the basin can be flooded (approximately 53,000 km2). The hydrological cycle is particularly important in the Pantanal in the transport of materials, and the transfer of energy between atmospheric, aquatic, and terrestrial systems. The INLAND (Integrated Land Surface Model) terrestrial ecosystem model is coupled with the THMB hydrological model to examine the hydrological balance and water dynamics for this region. The INLAND model is based on the IBIS dynamic vegetation model, while THMB represents the river, wetland and lake dynamics of the land surface. The modeled hydrological components are validated with surface and satellite-based estimates of precipitation (gridded observations from CRU v. 3.21, reanalysis data from ERA-interim, and TRMM estimates), evapotranspiration (MODIS and Land Flux-Eval dataset), total runoff (discharge data from ANA-Agência Nacional das Águas - Brazil), and terrestrial water storage (GRACE). Results show that the coupled hydrological model adequately represents the water cycle components, the river discharge and flooded areas. Model simulations are further used to study the influences of climatic variations on the hydrological components, river network, and the inundated areas in the Pantanal.

  6. RHydro - Hydrological models and tools to represent and analyze hydrological data in R

    NASA Astrophysics Data System (ADS)

    Reusser, Dominik; Buytaert, Wouter

    2010-05-01

    In hydrology, basic equations and procedures keep being implemented from scratch by scientist, with the potential for errors and inefficiency. The use of libraries can overcome these problems. Other scientific disciplines such as mathematics and physics have benefited significantly from such an approach with freely available implementations for many routines. As an example, hydrological libraries could contain: Major representations of hydrological processes such as infiltration, sub-surface runoff and routing algorithms. Scaling functions, for instance to combine remote sensing precipitation fields with rain gauge data Data consistency checks Performance measures. Here we present a beginning for such a library implemented in the high level data programming language R. Currently, Top-model, data import routines for WaSiM-ETH as well basic visualization and evaluation tools are implemented. The design is such, that a definition of import scripts for additional models is sufficient to have access to the full set of evaluation and visualization tools.

  7. Hydrological responses to dynamically and statistically downscaled climate model output

    USGS Publications Warehouse

    Wilby, R.L.; Hay, L.E.; Gutowski, W.J., Jr.; Arritt, R.W.; Takle, E.S.; Pan, Z.; Leavesley, G.H.; Clark, M.P.

    2000-01-01

    Daily rainfall and surface temperature series were simulated for the Animas River basin, Colorado using dynamically and statistically downscaled output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis. A distributed hydrological model was then applied to the downscaled data. Relative to raw NCEP output, downscaled climate variables provided more realistic stimulations of basin scale hydrology. However, the results highlight the sensitivity of modeled processes to the choice of downscaling technique, and point to the need for caution when interpreting future hydrological scenarios.

  8. Advanced Concept Modeling

    NASA Technical Reports Server (NTRS)

    Chaput, Armand; Johns, Zachary; Hodges, Todd; Selfridge, Justin; Bevirt, Joeben; Ahuja, Vivek

    2015-01-01

    Advanced Concepts Modeling software validation, analysis, and design. This was a National Institute of Aerospace contract with a lot of pieces. Efforts ranged from software development and validation for structures and aerodynamics, through flight control development, and aeropropulsive analysis, to UAV piloting services.

  9. ENHANCING HYDROLOGICAL SIMULATION PROGRAM - FORTRAN MODEL CHANNEL HYDRAULIC REPRESENTATION

    EPA Science Inventory

    The Hydrological Simulation Program– FORTRAN (HSPF) is a comprehensive watershed model that employs depth-area - volume - flow relationships known as the hydraulic function table (FTABLE) to represent the hydraulic characteristics of stream channel cross-sections and reservoirs. ...

  10. Model initialisation, data assimilation and probabilistic flood forecasting for distributed hydrological models

    NASA Astrophysics Data System (ADS)

    Cole, S. J.; Robson, A. J.; Bell, V. A.; Moore, R. J.

    2009-04-01

    The hydrological forecasting component of the Natural Environment Research Council's FREE (Flood Risk from Extreme Events) project "Exploitation of new data sources, data assimilation and ensemble techniques for storm and flood forecasting" addresses the initialisation, data assimilation and uncertainty of hydrological flood models utilising advances in rainfall estimation and forecasting. Progress will be reported on the development and assessment of simple model-initialisation and state-correction methods for a distributed grid-based hydrological model, the G2G Model. The potential of the G2G Model for area-wide flood forecasting is demonstrated through a nationwide application across England and Wales. Probabilistic flood forecasting in spatial form is illustrated through the use of high-resolution NWP rainfalls, and pseudo-ensemble forms of these, as input to the G2G Model. The G2G Model is configured over a large area of South West England and the Boscastle storm of 16 August 2004 is used as a convective case study. Visualisation of probabilistic flood forecasts is achieved through risk maps of flood threshold exceedence that indicate the space-time evolution of flood risk during the event.

  11. Future hydrological extremes: the uncertainty from multiple global climate and global hydrological models

    NASA Astrophysics Data System (ADS)

    Giuntoli, I.; Vidal, J.-P.; Prudhomme, C.; Hannah, D. M.

    2015-05-01

    Projections of changes in the hydrological cycle from global hydrological models (GHMs) driven by global climate models (GCMs) are critical for understanding future occurrence of hydrological extremes. However, uncertainties remain large and need to be better assessed. In particular, recent studies have pointed to a considerable contribution of GHMs that can equal or outweigh the contribution of GCMs to uncertainty in hydrological projections. Using six GHMs and five GCMs from the ISI-MIP multi-model ensemble, this study aims: (i) to assess future changes in the frequency of both high and low flows at the global scale using control and future (RCP8.5) simulations by the 2080s, and (ii) to quantify, for both ends of the runoff spectrum, GCMs and GHMs contributions to uncertainty using a two-way ANOVA. Increases are found in high flows for northern latitudes and in low flows for several hotspots. Globally, the largest source of uncertainty is associated with GCMs, but GHMs are the greatest source in snow-dominated regions. More specifically, results vary depending on the runoff metric, the temporal (annual and seasonal) and regional scale of analysis. For instance, uncertainty contribution from GHMs is higher for low flows than it is for high flows, partly owing to the different processes driving the onset of the two phenomena (e.g. the more direct effect of the GCMs' precipitation variability on high flows). This study provides a comprehensive synthesis of where future hydrological extremes are projected to increase and where the ensemble spread is owed to either GCMs or GHMs. Finally, our results underline the need for improvements in modelling snowmelt and runoff processes to project future hydrological extremes and the importance of using multiple GCMs and GHMs to encompass the uncertainty range provided by these two sources.

  12. Modelling hydrological management for the restoration of acidified floating fens

    NASA Astrophysics Data System (ADS)

    Dekker, Stefan C.; Barendregt, Aat; Bootsma, Margien C.; Schot, Paul P.

    2005-12-01

    Wetlands show a large decline in biodiversity. To protect and restore this biodiversity, many restoration projects are carried out. Hydrology in wetlands controls the chemical and biological processes and may be the most important factor regulating wetland function and development. Hydrological models may be used to simulate these processes and to evaluate management scenarios for restoration. HYDRUS2D, a combined saturated-unsaturated groundwater flow and transport model, is presented. This simulates near-surface hydrological processes in an acidified floating fen, with the aim to evaluate the effect of hydrological restoration in terms of conditions for biodiversity. In the acidified floating fen in the nature reserve Ilperveld (The Netherlands), a trench system was dug for the purpose of creating a runoff channel for acid rainwater in wet periods and to enable circum-neutral surface water to enter the fen in dry periods. The model is calibrated against measured conductivity values for a 5 year period. From the model simulations, it was found that lateral flow in the floating raft is limited. Furthermore, the model shows that the best management option is a combination of trenches and inundation, which gave the best soil water quality in the root zone. It is concluded that hydrological models can be used for the calculation of management scenarios in restoration projects. The combined saturated-unsaturated model concept used in this paper is able to incorporate the governing hydrological processes in the wetland root zones. Copyright

  13. ADVANCED CHEMISTRY BASINS MODEL

    SciTech Connect

    William Goddard III; Lawrence Cathles III; Mario Blanco; Paul Manhardt; Peter Meulbroek; Yongchun Tang

    2004-05-01

    The advanced Chemistry Basin Model project has been operative for 48 months. During this period, about half the project tasks are on projected schedule. On average the project is somewhat behind schedule (90%). Unanticipated issues are causing model integration to take longer then scheduled, delaying final debugging and manual development. It is anticipated that a short extension will be required to fulfill all contract obligations.

  14. Fine-Resolution Hydrologic Modeling of Semiarid River Basins: Preliminary Results from the Upper Rio Grande

    NASA Astrophysics Data System (ADS)

    Wyckoff, R.; Vivoni, E. R.; Rinehart, A.

    2004-12-01

    Water resources management and decision making in arid and semiarid regions require scientific knowledge and predictive capability of the physical processes occurring within hydrologic systems at scales sufficient to capture the variability inherent in the resource and its utilization. Our understanding of the interaction between water supply and demand is aided through numerical models that best represent our current knowledge of the hydrologic, ecological and meteorological processes in river basins. To this end, advances in distributed hydrologic modeling over large regional watersheds can aid in providing estimates of water availability and its susceptibility to climate variations, land-cover change and population growth. In this study, we utilize the TIN-based Real-time Integrated Basin Simulator (tRIBS) model to simulate continuous hydrological processes within subbasins of the Upper Río Grande in north-central New Mexico. First, we introduce the distributed model by highlighting the following salient features: (1) coupled unsaturated and saturated zones through a dynamic water table, (2) coupled energy and hydrologic balance at the land surface and (3) topographically-driven soil moisture redistribution, radiation and evapotranspiration. Accurate terrain representation at fine-resolution is achieved through the use of a triangulated irregular network (TIN) terrain model. Second, we present semiarid case studies in model setup, parameterization and continuous operation for the Upper Río Puerco and Jemez River. These river basins provide test cases for the calibration and validation of the tRIBS model through the use of in-situ measurement networks and long-term rainfall and stream gauging records. We will present the catchment hydrological response and its spatial organization by integrating geospatial data on topography, land-surface properties and precipitation obtained from geographic information systems, gauging networks and remote sensing. Although

  15. 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

  16. Integrating remote sensing, geographic information systems and global positioning system techniques with hydrological modeling

    NASA Astrophysics Data System (ADS)

    Thakur, Jay Krishna; Singh, Sudhir Kumar; Ekanthalu, Vicky Shettigondahalli

    2016-03-01

    Integration of remote sensing (RS), geographic information systems (GIS) and global positioning system (GPS) are emerging research areas in the field of groundwater hydrology, resource management, environmental monitoring and during emergency response. Recent advancements in the fields of RS, GIS, GPS and higher level of computation will help in providing and handling a range of data simultaneously in a time- and cost-efficient manner. This review paper deals with hydrological modeling, uses of remote sensing and GIS in hydrological modeling, models of integrations and their need and in last the conclusion. After dealing with these issues conceptually and technically, we can develop better methods and novel approaches to handle large data sets and in a better way to communicate information related with rapidly decreasing societal resources, i.e. groundwater.

  17. Doing hydrology forwards: Using field experimental data to inform a conceptual model of landscape driven hydrologic connectivity

    NASA Astrophysics Data System (ADS)

    Marshall, L. A.; Smith, T. J.; McGlynn, B. L.; Jencso, K. G.

    2011-12-01

    Given the known tradeoffs between hydrologic model complexity, efficiency, and predictive uncertainty there is an increasing desire to identify conceptual catchment models that accurately reflect catchment processes whilst preserving model identifiability. These models should specify the relationship between catchment form (including landscape topography, vegetation patterns, and stream networks) and hydrologic functioning (including streamflow patterns). We present a new hydrologic modeling approach that uses the distribution of landscape elements along the stream network as a template by which landscape-scale hydrologic connectivity and catchment runoff can be simulated. Here, we define hydrologic connectivity as the transient hydrological linkages between landscape elements and the stream. Our conceptualization emphasizes the importance of hydrologic connections between hillslope-riparian-stream (HRS) zones. Observations indicate that it is the frequency of these HRS hydrologic connections that drive aggregate catchment runoff response, rather than the magnitude of flux at any one connection. We applied the model to the Stringer Creek watershed of the Tenderfoot Creek Experimental Forest (TCEF), located in central Montana, USA. Detailed field observations were used to inform the underpinnings of the model and to corroborate internal consistency of the model's simulations. The ability of the model to simulate internal dynamics without conditioning the parameters on these data indicate the potential of this model to be more convincingly extrapolated to other hydrologic conditions and tested at catchments of varying topographic structure. Current and future work is aimed at further developing the modeling approach and testing the limits of its applicability across space and time.

  18. Hydrologic predictions on ungauged catchments using deterministic distributed modelling system

    NASA Astrophysics Data System (ADS)

    Tachecí, Pavel; Kimlová, Martina

    2010-05-01

    There is a need for warning system giving prediction of flash-flood risk conditions with sufficient advance even in source areas and in small tributaries catchments. New approach is based on combination of numerical weather prediction (NWP) model, radar or rain gauge data with distributed hydrologic mathematical model of particular area. Set of newly developed tools, customized for particular use in the Czech Hydrometeorological Institute (CHMI) environment enhance import of data and presentation of results. This forecast system focuses on hydrological modelling of running water balance in spatially distributed manner. Its computation is repeated day-to-day. Six models of particular basins (800 - 4000 km2), representing different conditions across the Czech Republic territory were calibrated and validated successfully. The Sázava river basin model (4.000 km2) is used for regular testing operation in CHMI Forecast centre since October 2007. Basic size of grid cells used in models is 300x300 m, basic time step of forecast is 1 day, but can be refined according to the input data. Water balance is computed using simplified 2-layer method for unsaturated zone, 2D approximation of Boussinesq equation for saturated zone, diffusion equation for overland flow and 1D kinematic equation for river flow (MIKE 11 model). The whole process of input data processing, model simulation and result generation may be run automatically or in step-by step mode via simple graphical user interface. Three types of input data are supported: •time series (temperature and precipitation) measured at observation stations and stored in CHMI database •radar data products (precipitation intensity field) •results of ALADIN weather forecast model (temperature and precipitation field). For forecast purposes, reference evapotranspiration is approximated according relationship to air temperature for every computational grid cell. The user may choose area (catchment) to be processed and period of

  19. Using satellite precipitation data for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Commandeur, Tom

    2013-04-01

    strategies for the MPE data. Since the MPE data is an estimate rather than a measurement, the data presents the need for validation. Comparison of the MPE data with ground radar and ground measurements will show the usability for hydrological modeling according to realistic scenarios. The end purpose is improving precipitation estimates by calibration, using ground radar and ground measurements where available. This study also researches their relations and combination approach.

  20. Validation of the hydrological cycle of ECMWF and NCEP reanalyses using the MPI hydrological discharge model

    NASA Astrophysics Data System (ADS)

    Hagemann, Stefan; Gates, Lydia Dümenil

    2001-01-01

    To validate the hydrological cycle of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) reanalyses in comparison with observed river discharge, a hydrological discharge model is used to compute the corresponding river discharge. The HD model requires daily time series of surface runoff and drainage from the soil as input fields. As it turned out that a direct application to the reanalyses was not possible, a simplified land surface scheme was developed to compute runoff and drainage fields from daily reanalysis values of total precipitation and 2 m temperature. These fields were then used as input to the global simulation of river discharge with the discharge model. Results show several shortcomings of the two reanalyses in representing the hydrological cycle at the land surface. The water balance is not closed, and the snowmelt is not incorporated in the runoff and drainage fields of either of the two reanalyses. In addition, the NCEP reanalysis overestimates summer precipitation and evapotranspiration for most parts of the Northern Hemisphere, while the ECMWF reanalysis underestimates 2 m temperatures in high latitudes during the winter and spring. In the monsoon region the hydrological cycle is well represented by both reanalyses, especially over India.

  1. Neural network modelling of non-linear hydrological relationships

    NASA Astrophysics Data System (ADS)

    Abrahart, R. J.; See, L. M.

    2007-09-01

    Two recent studies have suggested that neural network modelling offers no worthwhile improvements in comparison to the application of weighted linear transfer functions for capturing the non-linear nature of hydrological relationships. The potential of an artificial neural network to perform simple non-linear hydrological transformations under controlled conditions is examined in this paper. Eight neural network models were developed: four full or partial emulations of a recognised non-linear hydrological rainfall-runoff model; four solutions developed on an identical set of inputs and a calculated runoff coefficient output. The use of different input combinations enabled the competencies of solutions developed on a reduced number of parameters to be assessed. The selected hydrological model had a limited number of inputs and contained no temporal component. The modelling process was based on a set of random inputs that had a uniform distribution and spanned a modest range of possibilities. The initial cloning operations permitted a direct comparison to be performed with the equation-based relationship. It also provided more general information about the power of a neural network to replicate mathematical equations and model modest non-linear relationships. The second group of experiments explored a different relationship that is of hydrological interest; the target surface contained a stronger set of non-linear properties and was more challenging. Linear modelling comparisons were performed against traditional least squares multiple linear regression solutions developed on identical datasets. The reported results demonstrate that neural networks are capable of modelling non-linear hydrological processes and are therefore appropriate tools for hydrological modelling.

  2. Robert Horton and the Application of Distributed Hydrological Models

    NASA Astrophysics Data System (ADS)

    Beven, K. J.

    2004-12-01

    The name of Walter Langbein provides a link with the hydrology of Robert Horton. Langbein both worked with Horton and was the very first recipient of the AGU Horton Medal in 1976. In his response to the award, Langbein paid tribute to Horton's wide ranging interests as evidenced in the "several dozen research files in the National Archive". A recent search of some of these files has revealed some very interesting insights into Horton's hydrological concepts and, in particular, his appreciation of the difficulties involved in hydrological analysis and distributed prediction. Despite modern computer technology and the availability of geographical information systems, these insights are still relevant and important today and should be the basis for an approach to hydrological prediction that recognises the limitations of applying general, but incomplete, theory to specific places. An analysis of the sources of uncertainty in the modelling process leads to some suggestions about how we should proceed in the application of models in the future.

  3. Coupled Hydrological and Hydraulic Modeling for Flood Mapping

    NASA Astrophysics Data System (ADS)

    Drobot, Radu; Draghia, Aurelian

    2014-05-01

    The delineation of the flooded areas involves both hydrological and hydraulic modeling. Usually, the hydrological and hydraulic processes are separately treated. In the proposed methodology, the coupled modeling of the hydrological and hydraulic processes is used. The calibration and validation of the hydrological parameters is undertaken based on historical floods using the corresponding precipitations for the same period. The calibration process was more complicated in the presence of reservoirs, when not only the discharges downstream but also the water level in the reservoirs had to be accurately reproduced. The time step for precipitation is 1 hour, corresponding to the concentration time of the smallest catchments. The maximum annual precipitation for different time steps (1; 3; 6; 24 hours) were statistically processed and based on these results the cumulative rainfall curves and the synthetic hyetographs were derived. The rainfall duration is depending on the concentration time. Mike 11 with UHM module based on SCS model was used for coupled hydrological and hydraulic modeling. The coupled hydrological and hydraulic simulation for the scaled precipitation leads both at the computation of the components which contribute to the generation of the P% flood at the Hydrometric stations as well as to the determination of the discharge hydrograph along the main river. Based on these results the flood hazard maps were obtained using a DTM based on Lidar data. The methodology was applied for a river basin in Romania of 12500 km2.

  4. Hydrologic Modeling Strategy for the Islamic Republic of Mauritania, Africa

    USGS Publications Warehouse

    Friedel, Michael J.

    2008-01-01

    The government of Mauritania is interested in how to maintain hydrologic balance to ensure a long-term stable water supply for minerals-related, domestic, and other purposes. Because of the many complicating and competing natural and anthropogenic factors, hydrologists will perform quantitative analysis with specific objectives and relevant computer models in mind. Whereas various computer models are available for studying water-resource priorities, the success of these models to provide reliable predictions largely depends on adequacy of the model-calibration process. Predictive analysis helps us evaluate the accuracy and uncertainty associated with simulated dependent variables of our calibrated model. In this report, the hydrologic modeling process is reviewed and a strategy summarized for future Mauritanian hydrologic modeling studies.

  5. Research Infrastructure for the Advancement of Hydrologic Science: Planning Highlights and Update

    NASA Astrophysics Data System (ADS)

    Bales, R. C.

    2001-12-01

    In response to the need for research infrastructure in hydrologic sciences, a group of over 35 universities has formed a Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI). With support from the U.S. National Science Foundation, CUAHSI has initiated a science planning process aimed at building research infrastructure in three main areas: i) Long Term Hydrologic Observatories, to provide the consistent, integrated, long-term information from point to continental scales ii) a Hydrologic Information System program, to support the data, information, and analysis requirements of the community and iii) a Hydrologic Measurement Technology program to develop and operate state-of-the-art systems and provide support services for hydrologic research. Scientifically, this infrastructure initiative aims to support research to provide new understanding about priority questions in hydrologic and related sciences, including: i) spatial and temporal properties of precipitation and snow processes, ii) surface water generation and transport at scales from hectares to continental-scale basins, iii) linked water, carbon and other chemical cycles, and changes in response to varying temperature, precipitation and land-use patterns, iii) environmental stresses on aquatic and riparian ecosystems related to groundwater pumping and other perturbations, iv) basin-scale subsurface water and solute movement, particularly as related to patterns of precipitation, evapotranspiration and recharge, and v) feedback between regional evaporation and transpiration and patterns of precipitation and humidity. It has become apparent that the science infrastructure in hydrologic and related sciences is currently inadequate to meet many of these priority science questions and societal needs. Specifically, investments are needed to: i) maintain, supplement and upgrade existing field facilities, ii) establish measurement programs that can deliver consistent data over the long

  6. A unified approach for process-based hydrologic modeling: 2. Model implementation and case studies

    NASA Astrophysics Data System (ADS)

    Clark, Martyn P.; Nijssen, Bart; Lundquist, Jessica D.; Kavetski, Dmitri; Rupp, David E.; Woods, Ross A.; Freer, Jim E.; Gutmann, Ethan D.; Wood, Andrew W.; Gochis, David J.; Rasmussen, Roy M.; Tarboton, David G.; Mahat, Vinod; Flerchinger, Gerald N.; Marks, Danny G.

    2015-04-01

    This work advances a unified approach to process-based hydrologic modeling, which we term the "Structure for Unifying Multiple Modeling Alternatives (SUMMA)." The modeling framework, introduced in the companion paper, uses a general set of conservation equations with flexibility in the choice of process parameterizations (closure relationships) and spatial architecture. This second paper specifies the model equations and their spatial approximations, describes the hydrologic and biophysical process parameterizations currently supported within the framework, and illustrates how the framework can be used in conjunction with multivariate observations to identify model improvements and future research and data needs. The case studies illustrate the use of SUMMA to select among competing modeling approaches based on both observed data and theoretical considerations. Specific examples of preferable modeling approaches include the use of physiological methods to estimate stomatal resistance, careful specification of the shape of the within-canopy and below-canopy wind profile, explicitly accounting for dust concentrations within the snowpack, and explicitly representing distributed lateral flow processes. Results also demonstrate that changes in parameter values can make as much or more difference to the model predictions than changes in the process representation. This emphasizes that improvements in model fidelity require a sagacious choice of both process parameterizations and model parameters. In conclusion, we envisage that SUMMA can facilitate ongoing model development efforts, the diagnosis and correction of model structural errors, and improved characterization of model uncertainty.

  7. Flexibility on storage-release based distributed hydrologic modeling with object-oriented approach

    NASA Astrophysics Data System (ADS)

    Kang, Kwangmin; Merwade, Venkatesh; Chun, Jong Ahn; Timlin, Dennis

    2016-09-01

    With the availability of advanced hydrologic data in public domain such as remote sensed and climate change scenario data, there is a need for a modeling framework that is capable of using these data to simulate and extend hydrologic processes with multidisciplinary approaches for sustainable water resources management. To address this need, a storage-release based distributed hydrologic model (STORE DHM) is developed based on an object-oriented approach. The model is tested for demonstrating model flexibility and extensibility to know how to well integrate object-oriented approach to further hydrologic research issues, e.g., reconstructing missing precipitation in this study, without changing its main frame. Moreover, the STORE DHM is applied to simulate hydrological processes with multiple classes in the Nanticoke watershed. This study also describes a conceptual and structural framework of object-oriented inheritance and aggregation characteristics under the STORE DHM. In addition, NearestMP (missing value estimation based on nearest neighborhood regression) and KernelMP (missing value estimation based on Kernel Function) are proposed for evaluating STORE DHM flexibility. And then, STORE DHM runoff hydrographs compared with NearestMP and KernelMP runoff hydrographs. Overall results from these comparisons show promising hydrograph outputs generated by the proposed two classes. Consequently, this study suggests that STORE DHM with an object-oriented approach will be a comprehensive water resources modeling tools by adding additional classes for toward developing through its flexibility and extensibility.

  8. Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction

    NASA Astrophysics Data System (ADS)

    Xuan, Y.; Cluckie, I. D.; Wang, Y.

    2009-03-01

    Advances in mesoscale numerical weather predication make it possible to provide rainfall forecasts along with many other data fields at increasingly higher spatial resolutions. It is currently possible to incorporate high-resolution NWPs directly into flood forecasting systems in order to obtain an extended lead time. It is recognised, however, that direct application of rainfall outputs from the NWP model can contribute considerable uncertainty to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be magnified by the scaling process. As the ensemble weather forecast has become operationally available, it is of particular interest to the hydrologist to investigate both the potential and implication of ensemble rainfall inputs to the hydrological modelling systems in terms of uncertainty propagation. In this paper, we employ a distributed hydrological model to analyse the performance of the ensemble flow forecasts based on the ensemble rainfall inputs from a short-range high-resolution mesoscale weather model. The results show that: (1) The hydrological model driven by QPF can produce forecasts comparable with those from a raingauge-driven one; (2) The ensemble hydrological forecast is able to disseminate abundant information with regard to the nature of the weather system and the confidence of the forecast itself; and (3) the uncertainties as well as systematic biases are sometimes significant and, as such, extra effort needs to be made to improve the quality of such a system.

  9. Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction

    NASA Astrophysics Data System (ADS)

    Cluckie, I. D.; Xuan, Y.; Wang, Y.

    2006-10-01

    Advances in meso-scale numerical weather predication make it possible to provide rainfall forecasts along with many other data fields at increasingly higher spatial resolutions. It is currently possible to incorporate high-resolution NWPs directly into flood forecasting systems in order to obtain an extended lead time. It is recognised, however, that direct application of rainfall outputs from the NWP model can contribute considerable uncertainty to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be magnified by the scaling process. As the ensemble weather forecast has become operationally available, it is of particular interest to the hydrologist to investigate both the potential and implication of ensemble rainfall inputs to the hydrological modelling systems in terms of uncertainty propagation. In this paper, we employ a distributed hydrological model to analyse the performance of the ensemble flow forecasts based on the ensemble rainfall inputs from a short-range high-resolution mesoscale weather model. The results show that: (1) The hydrological model driven by QPF can produce forecasts comparable with those from a raingauge-driven one; (2) The ensemble hydrological forecast is able to disseminate abundant information with regard to the nature of the weather system and the confidence of the forecast itself; and (3) the uncertainties as well as systematic biases are sometimes significant and, as such, extra effort needs to be made to improve the quality of such a system.

  10. Coupling Hydrologic and Hydrodynamic Models to Estimate PMF

    NASA Astrophysics Data System (ADS)

    Felder, G.; Weingartner, R.

    2015-12-01

    Most sophisticated probable maximum flood (PMF) estimations derive the PMF from the probable maximum precipitation (PMP) by applying deterministic hydrologic models calibrated with observed data. This method is based on the assumption that the hydrological system is stationary, meaning that the system behaviour during the calibration period or the calibration event is presumed to be the same as it is during the PMF. However, as soon as a catchment-specific threshold is reached, the system is no longer stationary. At or beyond this threshold, retention areas, new flow paths, and changing runoff processes can strongly affect downstream peak discharge. These effects can be accounted for by coupling hydrologic and hydrodynamic models, a technique that is particularly promising when the expected peak discharge may considerably exceed the observed maximum discharge. In such cases, the coupling of hydrologic and hydraulic models has the potential to significantly increase the physical plausibility of PMF estimations. This procedure ensures both that the estimated extreme peak discharge does not exceed the physical limit based on riverbed capacity and that the dampening effect of inundation processes on peak discharge is considered. Our study discusses the prospect of considering retention effects on PMF estimations by coupling hydrologic and hydrodynamic models. This method is tested by forcing PREVAH, a semi-distributed deterministic hydrological model, with randomly generated, physically plausible extreme precipitation patterns. The resulting hydrographs are then used to externally force the hydraulic model BASEMENT-ETH (riverbed in 1D, potential inundation areas in 2D). Finally, the PMF estimation results obtained using the coupled modelling approach are compared to the results obtained using ordinary hydrologic modelling.

  11. 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

  12. Sensitivity of climate model to hydrology

    NASA Astrophysics Data System (ADS)

    Ye, Duzheng

    The importance of land—surface processes in affecting climate change has been analyzed and discussed by Namias [1962,1963]. The physics of the land-surface processes affect the climate because the ground hydrology, together with the vegetation and soil, determine the surface moisture availability which, in turn, controls the partition between the sensible and latent heat fluxes [Rowntree, 1984] and also the transfer of momentum. Further the vegetation cover and the soil moisture content can determine the ground surface albedo in snowless conditions. Therefore the heat balance and water balance in the planetary boundary layer are highly influenced by the hydrological processes. Through the planetary boundary layer, the influence of the ground hydrological processes can be felt through the whole troposphere [Yeh, et al., 1984; Rowntree and Bolton, 1983]. Here a crucial factor is the soil moisture content. In the region of dry anomalies, the following sequence of events tends to occur: a decrease of evaporation, a ground surface warming with an increase of sensible heat flux, a wanning of lower layers of the atmosphere with a decrease of relative humidity (due to decrease of evaporation and warming of lower atmophere), a decrease of precipitation with a cooling of the atmosphere higher up (due to decrease of latent heat), and then a change of upper air circulation [Rowntree and Bolton, 1983]. It is the decrease of precipitation which will cause the initial dry anomaly to persist. In the region of moist anomalies, the opposite sequence of events tends to occur.

  13. Strategies for using remotely sensed data in hydrologic models

    NASA Technical Reports Server (NTRS)

    Peck, E. L.; Keefer, T. N.; Johnson, E. R. (Principal Investigator)

    1981-01-01

    Present and planned remote sensing capabilities were evaluated. The usefulness of six remote sensing capabilities (soil moisture, land cover, impervious area, areal extent of snow cover, areal extent of frozen ground, and water equivalent of the snow cover) with seven hydrologic models (API, CREAMS, NWSRFS, STORM, STANFORD, SSARR, and NWSRFS Snowmelt) were reviewed. The results indicate remote sensing information has only limited value for use with the hydrologic models in their present form. With minor modifications to the models the usefulness would be enhanced. Specific recommendations are made for incorporating snow covered area measurements in the NWSRFS Snowmelt model. Recommendations are also made for incorporating soil moisture measurements in NWSRFS. Suggestions are made for incorporating snow covered area, soil moisture, and others in STORM and SSARR. General characteristics of a hydrologic model needed to make maximum use of remotely sensed data are discussed. Suggested goals for improvements in remote sensing for use in models are also established.

  14. Impact of the use of two different hydrological models on scores of hydrological ensemble forecasts

    NASA Astrophysics Data System (ADS)

    Ramos, M. H.; Thirel, G.; Andréassian, V.; Martin, E.

    2009-04-01

    The aim of this study is two-fold. Firstly, a comparative analysis is conducted to assess the quality of streamflow forecasts issued by two different modelling conceptualizations of catchment response, both driven by the same weather ensemble prediction system. Secondly, the results are jointly investigated with a view to providing guidance on the operational use of ensemble forecast products for flood warning at national hydrologic forecasting services. The study is based on weather forecasts from the ensemble prediction system PEARP of Météo-France, which was originally developed to better predict high impact storms in France. PEARP forecasts are based on the global spectral ARPEGE model zoomed over France. Initial perturbations are generated by the singular vector technique. The model runs 11 perturbed members for a forecast range of 60 hours. In this study, the two hydrological modelling approaches used are: 1) the coupled physically-based hydro-meteorological model SAFRAN-ISBA-MODCOU developed at Météo-France and based on a fully distributed catchment model, and 2) the GRPE forecasting system developed at Cemagref and based on a lumped soil-moisture-accounting type rainfall-runoff model. Both models were set up and tested on about 1000 catchments in France. For this study, a common subset of about 250 gauging stations representative of a wide range of upstream areas and hydro-meteorological conditions was selected. The discharges simulated by both systems are compared over an 18-month period (March 2005-September 2006). Skill scores are then computed for the first two days of forecast range and the performance of both hydrologic ensemble forecasting systems is assessed. The results of this experiment are examined with a focus on the setting up of a fully operational product in real-time hydrological forecasting. The combined use of forecasts issued by different systems is a demand of French operational forecasting service to better guide flood warning

  15. Spatial Resolution and Catchment Size Interaction of Soil Hydrological Properties for Hydrological Modeling

    NASA Astrophysics Data System (ADS)

    Libohova, Zamir; Bowling, Laura C.; Owens, Phillip R.; Schoeneberger, Philip; Wysocki, Douglas; Wills, Skye; Lindbo, David

    2016-04-01

    Spatial resolution of soil hydrologic properties is critical for distributed hydrological model streamflow simulations. Soils from US Soil Survey Geographic (SSURGO) Database are mapped at scales varying from 1:12,000 to 65,000. Related to these scales are also soil hydrological properties, which could vary spatially outside of the common SSURGO scale range. The objective of this research was to assess the role of the spatial resolution of soil depth on simulated hydrological response for various watershed sizes using the Distributed Hydrology Soil Vegetation Model (DHSVM). The study site was Hall Creek watershed a 56 km2 in size located in Dubois County in southern Indiana, USA. The watershed size was divided in 55 sub-watersheds varying in size from less than 5 km2 to 56 km2. The grid size spatial resolution of soil hydrological properties varied from 10x10, 30x30 and 90x90m. The simulated streamflow metrics were annual mean, minimum and maximum streamflow, and R-B Flashiness, which measures the variability in streamflow between successive days highlighting the fluctuation of discharge relative to total discharge. The slopes of the regression of simulated stream discharge parameters versus watershed size were used to assess the presence of interaction. In addition, the coefficient of variation was used to assess the variability for the R-B index, annual mean, annual minimum and maximum stream discharge across different model resolutions within each watershed category. The slope for 10x10 and 30x30m spatial resolution for annual mean, and minimum streamflow were not significantly different from zero across all watershed sizes indicating lack of interaction. However, slope for the R-B flashiness was significantly different from zero for the 90x90 m grid size indicating that watershed size change is sensitive at this spatial resolution. The variability of R-B index, annual mean and annual minimum hydrologic metrics decreased with increasing watershed size but

  16. Impact of improved snowmelt modelling in a monthly hydrological model.

    NASA Astrophysics Data System (ADS)

    Folton, Nathalie; Garcia, Florine

    2016-04-01

    The quantification and the management of water resources at the regional scale require hydrological models that are both easy to implement and efficient. To be reliable and robust, these models must be calibrated and validated on a large number of catchments that are representative of various hydro-meteorological conditions, physiographic contexts, and specific hydrological behavior (e.g. mountainous catchments). The GRLoiEau monthly model, with its simple structure and its two free parameters, answer our need of such a simple model. It required the development of a snow routine to model catchments with temporarily snow-covered areas. The snow routine developed here does not claim to represent physical snowmelt processes but rather to simulate them globally on the catchment. The snowmelt equation is based on the degree-day method which is widely used by the hydrological community, in particular in engineering studies (Etchevers 2000). A potential snowmelt (Schaefli et al. 2005) was computed, and the parameters of the snow routine were regionalized for each mountain area. The GRLoiEau parsimonious structure requires meteorological data. They come from the distributed mesoscale atmospheric analysis system SAFRAN, which provides estimations of daily solid and liquid precipitations and temperatures on a regular square grid at the spatial resolution of 8*8 km², throughout France. Potential evapotranspiration was estimated using the formula by Oudin et al. (2005). The aim of this study is to improve the quality of monthly simulations for ungauged basins, in particular for all types of mountain catchments, without increasing the number of free parameters of the model. By using daily SAFRAN data, the production store and snowmelt can be run at a daily time scale. The question then arises whether simulating the monthly flows using a production function at a finer time step would improve the results. And by using the SAFRAN distributed climate series, a distributed approach

  17. A strategy for diagnosing and interpreting hydrological model nonstationarity

    NASA Astrophysics Data System (ADS)

    Westra, Seth; Thyer, Mark; Leonard, Michael; Kavetski, Dmitri; Lambert, Martin

    2014-06-01

    This paper presents a strategy for diagnosing and interpreting hydrological nonstationarity, aiming to improve hydrological models and their predictive ability under changing hydroclimatic conditions. The strategy consists of four elements: (i) detecting potential systematic errors in the calibration data; (ii) hypothesizing a set of "nonstationary" parameterizations of existing hydrological model structures, where one or more parameters vary in time as functions of selected covariates; (iii) trialing alternative stationary model structures to assess whether parameter nonstationarity can be reduced by modifying the model structure; and (iv) selecting one or more models for prediction. The Scott Creek catchment in South Australia and the lumped hydrological model GR4J are used to illustrate the strategy. Streamflow predictions improve significantly when the GR4J parameter describing the maximum capacity of the production store is allowed to vary in time as a combined function of: (i) an annual sinusoid; (ii) the previous 365 day rainfall and potential evapotranspiration; and (iii) a linear trend. This improvement provides strong evidence of model nonstationarity. Based on a range of hydrologically oriented diagnostics such as flow-duration curves, the GR4J model structure was modified by introducing an additional calibration parameter that controls recession behavior and by making actual evapotranspiration dependent only on catchment storage. Model comparison using an information-theoretic measure (the Akaike Information Criterion) and several hydrologically oriented diagnostics shows that the GR4J modifications clearly improve predictive performance in Scott Creek catchment. Based on a comparison of 22 versions of GR4J with different representations of nonstationarity and other modifications, the model selection approach applied in the exploratory period (used for parameter estimation) correctly identifies models that perform well in a much drier independent

  18. Models of atmosphere-ecosystem-hydrology interactions: Approaches and testing

    NASA Technical Reports Server (NTRS)

    Schimel, David S.

    1992-01-01

    Interactions among the atmosphere, terrestrial ecosystems, and the hydrological cycle have been the subject of investigation for many years, although most of the research has had a regional focus. The topic is broad, including the effects of climate and hydrology on vegetation, the effects of vegetation on hydrology, the effects of the hydrological cycle on the atmosphere, and interactions of the cycles via material flux such as solutes and trace gases. The intent of this paper is to identify areas of critical uncertainty, discuss modeling approaches to resolving those problems, and then propose techniques for testing. I consider several interactions specifically to illustrate the range of problems. These areas are as follows: (1) cloud parameterizations and the land surface, (2) soil moisture, and (3) the terrestrial carbon cycle.

  19. Models for hydrologic design of evapotranspiration landfill covers.

    PubMed

    Hauser, Victor L; Gimon, Dianna M; Bonta, James V; Howell, Terry A; Malone, Robert W; Williams, Jimmy R

    2005-09-15

    The technology used in landfill covers is changing, and an alternative cover called the evapotranspiration (ET) landfill cover is coming into use. Important design requirements are prescribed by Federal rules and regulations for conventional landfill covers but not for ET landfill covers. There is no accepted hydrologic model for ET landfill cover design. This paper describes ET cover requirements and design issues, and assesses the accuracy of the EPIC and HELP hydrologic models when used for hydrologic design of ET covers. We tested the models against high-quality field measurements available from lysimeters maintained by the Agricultural Research Service of the U.S. Department of Agriculture at Coshocton, Ohio, and Bushland, Texas. The HELP model produced substantial errors in estimating hydrologic variables. The EPIC model estimated ET and deep percolation with errors less than 7% and 5%, respectively, and accurately matched extreme events with an error of less than 2% of precipitation. The EPIC model is suitable for use in hydrologic design of ET landfill covers. PMID:16201652

  20. Geographically isolated wetlands and watershed hydrology: A modified model analysis

    NASA Astrophysics Data System (ADS)

    Evenson, Grey R.; Golden, Heather E.; Lane, Charles R.; D'Amico, Ellen

    2015-10-01

    Geographically isolated wetlands (GIWs) are defined as wetlands that are completely surrounded by uplands. While GIWs are therefore spatially isolated, field-based studies have observed a continuum of hydrologic connections between these systems and other surface waters. Yet few studies have quantified the watershed-scale aggregate effects of GIWs on downstream hydrology. Further, existing modeling approaches to evaluate GIW effects at a watershed scale have utilized conceptual or spatially disaggregated wetland representations. Working towards wetland model representations that use spatially explicit approaches may improve current scientific understanding concerning GIW effects on the downstream hydrograph. The objective of this study was to quantify the watershed-scale aggregate effects of GIWs on downstream hydrology while emphasizing a spatially explicit representation of GIWs and GIW connectivity relationships. We constructed a hydrologic model for a ∼202 km2 watershed in the Coastal Plain of North Carolina, USA, a watershed with a substantial population of GIWs, using the Soil and Water Assessment Tool (SWAT). We applied a novel representation of GIWs within the model, facilitated by an alternative hydrologic response unit (HRU) definition and modifications to the SWAT source code that extended the model's "pothole" representation. We then executed a series of scenarios to assess the downstream hydrologic effect of various distributions of GIWs within the watershed. Results suggest that: (1) GIWs have seasonally dependent effects on baseflow; (2) GIWs mitigate peak flows; and (3) The presence of GIWs on the landscape impacts the watershed water balance. This work demonstrates a means of GIW simulation with improved spatial detail while showing that GIWs, in-aggregate, have a substantial effect on downstream hydrology in the studied watershed.

  1. Hydrological model uncertainty due to spatial evapotranspiration estimation methods

    NASA Astrophysics Data System (ADS)

    Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub

    2016-05-01

    Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.

  2. Linking Hydrology and Atmospheric Sciences in Continental Water Dynamics Modeling

    NASA Astrophysics Data System (ADS)

    David, C. H.; Gochis, D. J.; Maidment, D. R.; Wilhelmi, O.

    2006-12-01

    Atmospheric observation and model output datasets as well as hydrologic datasets are increasingly becoming available on a continental scale. Although the availability of these datasets could allow large-scale water dynamics modeling, the different objects and semantics used in atmospheric science and hydrology set barriers to their interoperability. Recent work has demonstrated the feasibility for modeling terrestrial water dynamics for the continental United States of America. Continental water dynamics defines the interaction of the hydrosphere, the land surface and subsurface at spatial scales ranging from point to continent. The improved version of the National Hydrographic Dataset (NHDPlus, an integrated suite of geospatial datasets stored in a vector and raster GIS format) was used as hydrologic and elevation data input to the Noah community Land Surface Model, developed at NCAR. Noah was successfully run on a watershed in the Ohio River Basin with NHDPlus inputs. The use of NHDPlus as input data for Noah is a crucial improvement for community modeling efforts allowing users to by-pass much of the time consumed in Digital Elevation Model and hydrological network processing. Furthermore, the community Noah land surface model, in its hydrologically-enhanced configuration, is capable of providing flow inputs for a river dynamics model. Continued enhancement of Noah will, as a consequence, be beneficial to the atmospheric science community as well as to the hydrologic community. Ongoing research foci include using a diversity of weather drivers as an input to Noah, and investigation of how to use land surface model outputs for river forecasting, using both the ArcHydro and OpenMI frameworks.

  3. Modelling hydrological effects of wetland restoration: a differentiated view.

    PubMed

    Staes, J; Rubarenzya, M H; Meire, P; Willems, P

    2009-01-01

    The paper presents findings of a conjunctive hydrological and ecological study into habitat restoration and catchment hydrology. Physically-based, fully distributed hydrological modelling was coupled with spatial analysis and wetland scenario generation techniques to simulate potential effects of restoring lower, middle, and upper catchment wetlands. In the past, anthropogenic interference of this catchments' landscape for agriculture and settlement has left most wetland areas drained, and brought the natural functioning of the ecosystem into conflict with human needs. Many eco-hydrology studies conclude that such disturbances result in a more extreme hydrological regime. The study objectives were to develop and study innovative methods for habitat restoration, and understand the potential hydrological impacts of each approach. The study aims to analyze the scenarios and whether the hydrological response is influenced by the topological placement of the restoration sites. Land-use change scenarios are developed on the basis of physical characteristics and consider the credibility of transitions from current land-use. This study focused on the position of the wetlands in the catchment and hydrological typology. Wetland restoration scenarios are created for different geographical settings within the catchment. A distinction is made between groundwater dependent wetlands and wetlands that are influenced by in-stream water tables or surface water inundations. Results show that there is little effect on the total annual water budget. The results point to river valley rewetting as having the effect of decreasing the paved overland component of stream flow, and increasing the saturated zone flow component. It promoted groundwater recharge. There was no increase of peak flows due to headwater wetlands, contrary to some sources (Bullock & Acreman 2003). The catchments' actual evapotranspiration and root zone water responses were found to be varied over the analysis points

  4. Modeling of reservoir operation in UNH global hydrological model

    NASA Astrophysics Data System (ADS)

    Shiklomanov, Alexander; Prusevich, Alexander; Frolking, Steve; Glidden, Stanley; Lammers, Richard; Wisser, Dominik

    2015-04-01

    Climate is changing and river flow is an integrated characteristic reflecting numerous environmental processes and their changes aggregated over large areas. Anthropogenic impacts on the river flow, however, can significantly exceed the changes associated with climate variability. Besides of irrigation, reservoirs and dams are one of major anthropogenic factor affecting streamflow. They distort hydrological regime of many rivers by trapping of freshwater runoff, modifying timing of river discharge and increasing the evaporation rate. Thus, reservoirs is an integral part of the global hydrological system and their impacts on rivers have to be taken into account for better quantification and understanding of hydrological changes. We developed a new technique, which was incorporated into WBM-TrANS model (Water Balance Model-Transport from Anthropogenic and Natural Systems) to simulate river routing through large reservoirs and natural lakes based on information available from freely accessible databases such as GRanD (the Global Reservoir and Dam database) or NID (National Inventory of Dams for US). Different formulations were applied for unregulated spillway dams and lakes, and for 4 types of regulated reservoirs, which were subdivided based on main purpose including generic (multipurpose), hydropower generation, irrigation and water supply, and flood control. We also incorporated rules for reservoir fill up and draining at the times of construction and decommission based on available data. The model were tested for many reservoirs of different size and types located in various climatic conditions using several gridded meteorological data sets as model input and observed daily and monthly discharge data from GRDC (Global Runoff Data Center), USGS Water Data (US Geological Survey), and UNH archives. The best results with Nash-Sutcliffe model efficiency coefficient in the range of 0.5-0.9 were obtained for temperate zone of Northern Hemisphere where most of large

  5. Understanding uncertainty in process-based hydrological models

    NASA Astrophysics Data System (ADS)

    Clark, M. P.; Kavetski, D.; Slater, A. G.; Newman, A. J.; Marks, D. G.; Landry, C.; Lundquist, J. D.; Rupp, D. E.; Nijssen, B.

    2013-12-01

    Building an environmental model requires making a series of decisions regarding the appropriate representation of natural processes. While some of these decisions can already be based on well-established physical understanding, gaps in our current understanding of environmental dynamics, combined with incomplete knowledge of properties and boundary conditions of most environmental systems, make many important modeling decisions far more ambiguous. There is consequently little agreement regarding what a 'correct' model structure is, especially at relatively larger spatial scales such as catchments and beyond. In current practice, faced with such a range of decisions, different modelers will generally make different modeling decisions, often on an ad hoc basis, based on their balancing of process understanding, the data available to evaluate the model, the purpose of the modeling exercise, and their familiarity with or investment in an existing model infrastructure. This presentation describes development and application of multiple-hypothesis models to evaluate process-based hydrologic models. Our numerical model uses robust solutions of the hydrology and thermodynamic governing equations as the structural core, and incorporates multiple options to represent the impact of different modeling decisions, including multiple options for model parameterizations (e.g., below-canopy wind speed, thermal conductivity, storage and transmission of liquid water through soil, etc.), as well as multiple options for model architecture, that is, the coupling and organization of different model components (e.g., representations of sub-grid variability and hydrologic connectivity, coupling with groundwater, etc.). Application of this modeling framework across a collection of different research basins demonstrates that differences among model parameterizations are often overwhelmed by differences among equally-plausible model parameter sets, while differences in model architecture lead

  6. WEB-DHM: A distributed biosphere hydrological model developed by coupling a simple biosphere scheme with a hillslope hydrological model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  7. Performance measures and criteria for hydrologic and water quality models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Performance measures and criteria are essential for model calibration and validation. This presentation will include a summary of one of the papers that will be included in the 2014 Hydrologic and Water Quality Model Calibration & Validation Guidelines Special Collection of the ASABE Transactions. T...

  8. Hydrologic and water quality teminology as applied to modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A survey of literature and examination in particular of terminology use in a previous special collection of modeling calibration and validation papers has been conducted to arrive at a list of consistent terminology recommended for writing about hydrologic and water quality model calibration and val...

  9. A fully integrated SWAT-MODFLOW hydrologic model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil and Water Assessment Tool (SWAT) and MODFLOW models are being used worldwide for managing surface and groundwater water resources. The SWAT models hydrological processes occurring at the surface including shallow aquifers, while MODFLOW simulate groundwater processes. However, neither SWAT ...

  10. The Use of Simulation Models in Teaching Geomorphology and Hydrology.

    ERIC Educational Resources Information Center

    Kirkby, Mike; Naden, Pam

    1988-01-01

    Learning about the physical environment from computer simulation models is discussed in terms of three stages: exploration, experimentation, and calibration. Discusses the effective use of models and presents two computer simulations written in BBC BASIC, STORFLO (for catchment hydrology) and SLOPEK (for hillslope evolution). (Author/GEA)

  11. A physically-based Distributed Hydrologic Model for Tropical Catchments

    NASA Astrophysics Data System (ADS)

    Abebe, N. A.; Ogden, F. L.

    2010-12-01

    Hydrological models are mathematical formulations intended to represent observed hydrological processes in a watershed. Simulated watersheds in turn vary in their nature based on their geographic location, altitude, climatic variables and geology and soil formation. Due to these variations, available hydrologic models vary in process formulation, spatial and temporal resolution and data demand. Many tropical watersheds are characterized by extensive and persistent biological activity and a large amount of rain. The Agua Salud catchments located within the Panama Canal Watershed, Panama, are such catchments identified by steep rolling topography, deep soils derived from weathered bedrock, and limited exposed bedrock. Tropical soils are highly affected by soil cracks, decayed tree roots and earthworm burrows forming a network of preferential flow paths that drain to a perched water table, which forms at a depth where the vertical hydraulic conductivity is significantly reduced near the bottom of the bioturbation layer. We have developed a physics-based, spatially distributed, multi-layered hydrologic model to simulate the dominant processes in these tropical watersheds. The model incorporates the major flow processes including overland flow, channel flow, matrix and non-Richards film flow infiltration, lateral downslope saturated matrix and non-Darcian pipe flow in the bioturbation layer, and deep saturated groundwater flow. Emphasis is given to the modeling of subsurface unsaturated zone soil moisture dynamics and the saturated preferential lateral flow from the network of macrospores. Preliminary results indicate that the model has the capability to simulate the complex hydrological processes in the catchment and will be a useful tool in the ongoing comprehensive ecohydrological studies in tropical catchments, and help improve our understanding of the hydrological effects of deforestation and aforestation.

  12. Analysis of Streamflow Predictive Uncertainty using Multiple Hydrologic Models in Climate Change Impact Study

    NASA Astrophysics Data System (ADS)

    Yang, P.; Najafi, M.; Moradkhani, H.

    2010-12-01

    Based on the statistically downscaled outputs from 8 global climate model projections and 2 emission scenarios we assess the uncertainties associated with GCMs and hydrologic models by means of multi-modeling. As there is no conceivable reason that any hydrologic model is performing better under all circumstances, four hydrologic models are selected for the hydrologic impact study: the Sacramento Soil Moisture Accounting (SAC-SMA) model, Conceptual HYdrologic MODel (HYMOD), Thornthwaite-Mather model (TM) and the Precipitation Runoff Modeling System (PRMS). Three objective functions are adopted to calibrate each model. The hydrologic model simulations are combined using the Bayesian Model Averaging (BMA) method. This study shows that the application of the BMA in analyzing the models ensemble is useful in minimizing the uncertainty in selecting the hydrologic model selection. It is also concluded that the hydrologic model uncertainty is considerably smaller than GCM uncertainty, except during the dry season.

  13. Application of earth observation products for hydrological modeling of the Oum Er Rbia river basin

    NASA Astrophysics Data System (ADS)

    López López, Patricia; Strohmeier, Stefan; Haddad, Mira; Sutanudjaja, Edwin; Karrou, Mohammed; Sterk, Geert; Schellekens, Jaap; Bierkens, Marc

    2016-04-01

    The increasing water demand over recent decades together with the climate change impacts on water resources lead to a growing shortage of water availability. Investigating and developing novel strategies to assess and manage water resources have turned into a key issue, leading to increasing efforts to enhance and improve hydrological models and datasets. Despite campaigns to increase the quality and the temporal and spatial availability of ground-based hydro-meteorological data, many river basins around the world still have a limited number of in-situ observations. This in turn limits the application of hydrological models. Recently developed global earth observation products may unlock a greater capability of basin scale hydrological modeling for advanced water management. This study aims to evaluate the applicability of earth observation products for hydrological model simulation in comparison with in-situ data for water resources management and water allocation of the Moroccan Oum Er Rbia river basin. Two different hydrological models (SWAT and PCR-GLOBWB) were applied to inter-compare various combinations of in-situ and global earth observation data. Global earth observation products were obtained from various sources including meteorological data from the WATCH Forcing Data methodology applied to ERA-Interim reanalysis data, remotely sensed ESA CCI surface soil moisture Soil Water Index combined product and evapotranspiration data from the FLUXNET global monitoring network. The daily data were provided for the time period from 1979 to 2012. Due to the insufficient in-situ discharge observations available in the basin, local calibration of both hydrological models was based on global evapotranspiration and soil moisture data, covering additional aspects of the hydrological cycle to further reduce modeling uncertainty. Preliminary results indicate that even though significant differences in model estimates were found between SWAT and PCR-GLOBWB, the remotely

  14. Neural Networks for Hydrological Modeling Tool for Operational Purposes

    NASA Astrophysics Data System (ADS)

    Bhatt, Divya; Jain, Ashu

    2010-05-01

    Hydrological models are useful in many water resources applications such as flood control, irrigation and drainage, hydro power generation, water supply, erosion and sediment control, etc. Estimates of runoff are needed in many water resources planning, design development, operation and maintenance activities. Runoff is generally computed using rainfall-runoff models. Computer based hydrologic models have become popular for obtaining hydrological forecasts and for managing water systems. Rainfall-runoff library (RRL) is computer software developed by Cooperative Research Centre for Catchment Hydrology (CRCCH), Australia consisting of five different conceptual rainfall-runoff models, and has been in operation in many water resources applications in Australia. Recently, soft artificial intelligence tools such as Artificial Neural Networks (ANNs) have become popular for research purposes but have not been adopted in operational hydrological forecasts. There is a strong need to develop ANN models based on real catchment data and compare them with the conceptual models actually in use in real catchments. In this paper, the results from an investigation on the use of RRL and ANNs are presented. Out of the five conceptual models in the RRL toolkit, SimHyd model has been used. Genetic Algorithm has been used as an optimizer in the RRL to calibrate the SimHyd model. Trial and error procedures were employed to arrive at the best values of various parameters involved in the GA optimizer to develop the SimHyd model. The results obtained from the best configuration of the SimHyd model are presented here. Feed-forward neural network model structure trained by back-propagation training algorithm has been adopted here to develop the ANN models. The daily rainfall and runoff data derived from Bird Creek Basin, Oklahoma, USA have been employed to develop all the models included here. A wide range of error statistics have been used to evaluate the performance of all the models

  15. Use of hydrologic and hydrodynamic modeling for ecosystem restoration

    USGS Publications Warehouse

    Obeysekera, J.; Kuebler, L.; Ahmed, S.; Chang, M.-L.; Engel, V.; Langevin, C.; Swain, E.; Wan, Y.

    2011-01-01

    Planning and implementation of unprecedented projects for restoring the greater Everglades ecosystem are underway and the hydrologic and hydrodynamic modeling of restoration alternatives has become essential for success of restoration efforts. In view of the complex nature of the South Florida water resources system, regional-scale (system-wide) hydrologic models have been developed and used extensively for the development of the Comprehensive Everglades Restoration Plan. In addition, numerous subregional-scale hydrologic and hydrodynamic models have been developed and are being used for evaluating project-scale water management plans associated with urban, agricultural, and inland costal ecosystems. The authors provide a comprehensive summary of models of all scales, as well as the next generation models under development to meet the future needs of ecosystem restoration efforts in South Florida. The multiagency efforts to develop and apply models have allowed the agencies to understand the complex hydrologic interactions, quantify appropriate performance measures, and use new technologies in simulation algorithms, software development, and GIS/database techniques to meet the future modeling needs of the ecosystem restoration programs. Copyright ?? 2011 Taylor & Francis Group, LLC.

  16. 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.

  17. Assessing the hydrologic restoration of an urbanized area via integrated distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Trinh, D. H.; Chui, T. F. M.

    2013-04-01

    Green structures (e.g. green roof and bio-retention systems) are adopted to mitigate the hydrological impacts of urbanization. However, our current understanding of the urbanization impacts are often process-specific (e.g. peak flow or storm recession), and our characterizations of green structures are often on a local scale. This study uses an integrated distributed hydrological model, Mike SHE, to evaluate the urbanization impacts on both overall water balance and water regime, and also the effectiveness of green structures at a catchment level. Three simulations are carried out for a highly urbanized catchment in the tropics, representing pre-urbanized, urbanized and restored conditions. Urbanization transforms vegetated areas into impervious surfaces, resulting in 20 and 66% reductions in infiltration and base flow respectively, and 60 to 100% increase in peak outlet discharge. Green roofs delay the peak outlet discharge by 2 h and reduce the magnitude by 50%. Bio-retention systems mitigate the peak discharge by 50% and also enhance infiltration by 30%. The combination of green roofs and bio-retention systems even reduces the peak discharge to the pre-urbanized level. The simulation results obtained are independent of field data, enabling a generic model for understanding hydrological changes during the different phases of urbanization. This will benefit catchment level planning of green structures in other urban areas.

  18. Assessing the hydrologic restoration of an urbanized area via an integrated distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Trinh, D. H.; Chui, T. F. M.

    2013-12-01

    Green structures (e.g. green roof and bio-retention systems) are adopted to mitigate the hydrological impacts of urbanization. However, our current understanding of urbanization impacts are often process-specific (e.g. peak flow or storm recession), and our characterizations of green structures are often on a local scale. This study uses an integrated distributed hydrological model, Mike SHE, to evaluate the urbanization impacts on both overall water balance and water regime, and also the effectiveness of green structures at a catchment level. Three simulations are carried out for a highly urbanized catchment in the tropics, representing pre-urbanized, urbanized and restored conditions. Urbanization transforms vegetated areas into impervious surfaces, resulting in 20 and 66% reductions in infiltration and base flow respectively, and 60 to 100% increase in peak outlet discharge. Green roofs delay the peak outlet discharge by 2 h and reduce the magnitude by 50%. Bio-retention systems mitigate the peak discharge by 50% and also enhance infiltration by 30%. The combination of green roofs and bio-retention systems even reduces the peak discharge to the pre-urbanized level. The simulation results obtained are independent of field data, enabling a generic model for understanding hydrological changes during the different phases of urbanization. This will benefit catchment-level planning of green structures in other urban areas.

  19. Improving USGS National Hydrologic Model Parameterization with Satellite-Based Phenology Products

    NASA Astrophysics Data System (ADS)

    Micheletty, P. D.; Hogue, T. S.; Hay, L.; Markstrom, S. L.; Regan, R. S.

    2014-12-01

    Hydrologists and water resource engineers are simulating hydrologic processes at the continental scale assisted by the advancement of high-performance computing and the accessibility of large-scale climate and hydrologic datasets. The United States Geological Survey (USGS) is developing a National Hydrologic Model (NHM) that supports coordinated, comprehensive, and consistent hydrologic model development and simulations of the conterminous United States (CONUS). The goal of this project is to improve model parameterization and ultimately streamflow predictions across the CONUS using remotely sensed data products. The current work will specifically improve estimates of the growing season in the NHM through the integration of satellite-based phenology products developed at the USGS Earth Resources Observation and Science (EROS) Center. Currently, the NHM defines the growing season using one of three temperature-index methods: 1) first and last freezing air temperatures; 2) temperature threshold for a specified begin and end month; and 3) dynamic specification. The USGS/EROS RSP products are based on a timeseries analysis of the normalized difference vegetation index (NDVI) from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors. Using the phenological metrics derived from AVHRR, we define a new growing season parameter set for the CONUS from 1989 to 2013, which ultimately will enhance estimations of daily transpiration rates throughout the model domain. Using default temperature-index based estimates of growing season and RSP derived estimates, we provide statistical evaluation and comparison of the NHM simulations related to growing season. The RSP growing season dates may improve model hydrologic simulations especially in drought periods when water availability, demand, and usage are critical, or in areas where the temperature-index based growing season estimates lack skill, such as some

  20. The reduction of hydrological models for less tedious practical applications

    NASA Astrophysics Data System (ADS)

    Delay, Frederick; Ackerer, Philippe

    2016-02-01

    This work evidences that inconsistencies may persist between the complexity of hydrological models and available data for model documentation and application. For example, the integrated hydrological models handle the whole water dynamics over a watershed, but are only conditioned on data that incompletely record the dimensions of the flow. It is suggested to reduce this type of model by aggregating the physical background to diminish its Euclidean dimension. Paradoxically, the complexity in the physics of a model may also result in some reduction. For example, handling a flow by relying upon a dual continuum approach conceals the structural heterogeneity of the reservoir in the model equations. The parameterization at the scale of the aquifer becomes much simpler and the model reduction is here associated with diminishing the effort to condition the model onto data.

  1. Using Advances in Research on Louisiana Coastal Restoration and Protection to Develop Undergraduate Hydrology Education Experiences Delivered via a Web Interface

    NASA Astrophysics Data System (ADS)

    Bodin, M.; Habib, E. H.; Meselhe, E. A.; Visser, J.; Chimmula, S.

    2014-12-01

    Utilizing advances in hydrologic research and technology, learning modules can be developed to deliver visual, case-based, data and simulation driven educational experiences. This paper focuses on the development of web modules based on case studies in Coastal Louisiana, one of three ecosystems that comprise an ongoing hydrology education online system called HydroViz. The Chenier Plain ecosystem in Coastal Louisiana provides an abundance of concepts and scenarios appropriate for use in many undergraduate water resource and hydrology curricula. The modules rely on a set of hydrologic data collected within the Chenier Plain along with inputs and outputs of eco-hydrology and vegetation-change simulation models that were developed to analyze different restoration and protection projects within the 2012 Louisiana Costal Master Plan. The modules begin by investigating the basic features of the basin and it hydrologic characteristics. The eco-hydrology model is then introduced along with its governing equations, numerical solution scheme and how it represents the study domain. Concepts on water budget in a coastal basin are then introduced using the simulation model inputs, outputs and boundary conditions. The complex relationships between salinity, water level and vegetation changes are then investigated through the use of the simulation models and associated field data. Other student activities focus on using the simulation models to evaluate tradeoffs and impacts of actual restoration and protection projects that were proposed as part of 2012 Louisiana Master Plan. The hands-on learning activities stimulate student learning of hydrologic and water management concepts by providing real-world context and opportunity to build fundamental knowledge as well as practical skills. The modules are delivered through a carefully designed user interface using open source and free technologies which enable wide dissemination and encourage adaptation by others.

  2. A multiple hypotheses uncertainty analysis in hydrological modelling: about model structure, landscape parameterization, and numerical integration

    NASA Astrophysics Data System (ADS)

    Pilz, Tobias; Francke, Till; Bronstert, Axel

    2016-04-01

    Until today a large number of competing computer models has been developed to understand hydrological processes and to simulate and predict streamflow dynamics of rivers. This is primarily the result of a lack of a unified theory in catchment hydrology due to insufficient process understanding and uncertainties related to model development and application. Therefore, the goal of this study is to analyze the uncertainty structure of a process-based hydrological catchment model employing a multiple hypotheses approach. The study focuses on three major problems that have received only little attention in previous investigations. First, to estimate the impact of model structural uncertainty by employing several alternative representations for each simulated process. Second, explore the influence of landscape discretization and parameterization from multiple datasets and user decisions. Third, employ several numerical solvers for the integration of the governing ordinary differential equations to study the effect on simulation results. The generated ensemble of model hypotheses is then analyzed and the three sources of uncertainty compared against each other. To ensure consistency and comparability all model structures and numerical solvers are implemented within a single simulation environment. First results suggest that the selection of a sophisticated numerical solver for the differential equations positively affects simulation outcomes. However, already some simple and easy to implement explicit methods perform surprisingly well and need less computational efforts than more advanced but time consuming implicit techniques. There is general evidence that ambiguous and subjective user decisions form a major source of uncertainty and can greatly influence model development and application at all stages.

  3. Development of human impact modeling in global hydrology

    NASA Astrophysics Data System (ADS)

    Bierkens, M. F.; Wada, Y.

    2015-12-01

    During the late 1980s and early 1990s, awareness of the shortage of global water resources lead to the first detailed global water resources assessments comparing water availability with water use. These first efforts mostly relied on statistics of water use and observations of meteorological and hydrological variables. Shortly thereafter, the first macroscale hydrological models (MHM) appeared. In these models, blue water (i.e., surface water and renewable groundwater) availability was calculated by proxy by accumulating runoff over a stream network and comparing it with population densities or with estimated water demand. In this talk we review the evolution of human impact modelling in global hydrology, e.g.: confronting yearly water demand with water availability using a water scarcity index; calculating a water scarcity index at monthly time scale; adding groundwater depletion; adding dams and reservoirs; fully integrating water use (abstraction, application, consumption, return flow) in the hydrology; simulating the effects of land use change. A number of challenges are identified that hamper the further development of current water use modelling as well as prohibit realistic modelling of future water use. We also speculate on pathways to overcome these challenges.

  4. High resolution distributed hydrological modeling for river flood forecasting

    NASA Astrophysics Data System (ADS)

    Chen, Y.

    2014-12-01

    High resolution distributed hydrological model can finely describe the river basin hydrological processes, thus having the potential to improve the flood forecasting capabilities, and is regarded as the next generation flood forecast model. But there are great challenges in deploying it in real-time river flood forecasting, such as the awesome computation resources requirement, parameter determination, high resolution precipitation assimilation and uncertainty controls. Liuxihe Model is a physically-based distributed hydrological model proposed mainly for catchment flood forecasting, which is a process-based hydrological model. In this study, based on Liuxihe Model, a parallel computation algorithm for Liuxihe model flood forecasting is proposed, and a cloudy computation system is developed on a high performance computer, this largely improves the applicability of Liuxihe Model in large river. Without the parallel computation, the Liuxihe Model is computationally incapable in application to rivers with drainage area bigger than 10,000km2 at the grid size of 100m. With the parallel computation, the Liuxihe Model is used in a river with a drainage area of 60,000km2, and could be expended indefinitely. Based on this achievement, a model parameter calibration method by using Particle Swale Optimization is proposed and tested in several rivers in southern China with drainage areas ranging from several hundreds to tens thousands km2, and with the model parameter optimization, the model performance has been approved largely. The modeling approach is also tested for coupling radar-based precipitation estimation/prediction for small catchment flash forecasting and for coupling quantitative precipitation estimation/prediction from meteorological model for large river flood forecasting.

  5. Simultaneous estimation of both hydrological and ecological parameters in an ecohydrological model by assimilating microwave signal

    NASA Astrophysics Data System (ADS)

    Sawada, Yohei; Koike, Toshio

    2014-07-01

    To improve the skill of reproducing land-atmosphere interactions in weather, seasonal, and climate prediction systems, it is necessary to simulate correctly and simultaneously the surface soil moisture (SSM) and terrestrial biomass in land surface models. Despite the performance of hydrological and ecosystem models depends highly on parameter calibration, a method for parameter estimation in ungauged areas has yet to be established. We develop an autocalibration system that can simultaneously estimate both hydrological and ecological parameters by assimilating a microwave signal that is sensitive to both SSM and terrestrial biomass. This system comprises a hydrological model that has a physically based, sophisticated soil hydrology scheme, a dynamic vegetation model that can estimate vegetation growth and senescence, and a radiative transfer model that can convert land surface condition into brightness temperatures in the microwave region. By assimilating microwave signals from the Advanced Microwave Scanning Radiometer for Earth Observing System, the system simultaneously optimizes the parameters of these models. We test this approach at three in situ observation sites under different hydroclimatic conditions. Estimated SSM exhibits good agreement with ground-based in situ observed SSM, and estimated leaf area index (LAI) is also improved by the optimization, compared with satellite-observed LAI. The root-mean-square error of SSM and LAI at all sites, estimated by the model with optimized parameters, is much less than that estimated by the model with default parameters. Using microwave satellite brightness temperature data sets, this system offers the potential to calibrate parameters of both hydrological and ecosystem models globally.

  6. New Hydrologic Insights to Advance Geophysical Investigation of the Unsaturated Zone

    NASA Astrophysics Data System (ADS)

    Nimmo, J. R.; Perkins, K. S.

    2015-12-01

    Advances in hydrology require information from the unsaturated zone, especially for problems related to groundwater contamination, water-supply sustainability, and ecohydrology. Unsaturated-zone processes are notoriously difficult to quantify; soils and rocks are visually opaque, spatially variable in the extreme, and easily disturbed by instrument installation. Thus there is great value in noninvasive techniques that produce water-related data of high density in space and time. Methods based on resistivity and electromagnetic waves have already produced significant new understanding of percolation processes, root-zone water retention, influences of evapotranspiration on soil-water, and effects of preferential flow. Further developments are underway for such purposes as noninvasive application to greater depths, increased resolution, adaptation for lab-scale experiments, and calibration in heterogeneous media. Beyond these, however, there is need for a stronger marriage of hydrologic and geophysical knowledge and perspective. Possible means to greater and faster progress include: Apply the latest hydrologic understanding, both pore-scale and macroscopic, to the detection of preferential flow paths and their degree of activation. In the continuing advancement of hardware and techniques, draw creatively from developments in such fields as high-energy physics, medical imaging, astrogeology, high-tech semiconductors, and bioinstrumentation. Sidestep the imaging process where possible to measure essential properties and fluxes more directly. Pose questions that have a strong end-use character, like "how does storm intensity relate to aquifer recharge rate" rather than "what is the shape of the wetting front". The greatest advances in geophysical investigation of the unsaturated zone will come from methods informed by the latest understanding of unsaturated systems and processes, and aimed as directly as possible at the answers to important hydrologic questions.

  7. Remote sensing and hydrological modeling of burn scars

    NASA Astrophysics Data System (ADS)

    Miller, Mary Ellen

    This study examined the potential usefulness of combining remote sensing data with hydrologic models and mapping tools available from Geographic Information Systems (GIS), to evaluate the effects of wildfire. Four subprojects addressed this issue: (1) validation of burn scar maps derived from the Advanced Very High Resolution Radiometer (AVHRR) with the National Fire Occurrence Database; (2) testing the potential of thermal MODIS (Moderate Resolution Imaging Spectroradiometer) data for near-real time burn scar and fire severity mapping; (3) evaluation of Landsat derived burn severity maps within WEPP through the Geo-spatial interface for the Water Erosion Prediction Project (GeoWEPP), and (4) predicting potential post-fire erosion for western U.S. forests utilizing existing datasets and models. Wildfire poses incredibly complex management problems in all of its stages. Today's land managers have the option of trying to mitigate the effects of a severe fire before it occurs by fuel management practices. This process is expensive especially considering the uncertainty of when and where the next fire in a given region will occur. When a wildfire does occur, deciding when to let it burn and when to suppress it may lead to controversial decisions. In addition to the threat to life and property from the fire itself, smoke emissions from large fires can cause air quality problems in distant airsheds. Even after the fire is extinguished, erosion and water quality problems may pose difficult management questions. Contributions stemming from these studies include improved burn scar maps for studying historical fire extent and demonstration of the feasibility of using thermal satellite data to predict burn scar extent when clouds and smoke obscure visible bands. The incorporation of Landsat derived burn severity maps was shown to improve post-fire erosion modeling results. Finally the potential post-fire burn severity and erosion risk maps generated for western US forests

  8. Rapid Prototyping of Hydrologic Model Interfaces with IPython

    NASA Astrophysics Data System (ADS)

    Farthing, M. W.; Winters, K. D.; Ahmadia, A. J.; Hesser, T.; Howington, S. E.; Johnson, B. D.; Tate, J.; Kees, C. E.

    2014-12-01

    A significant gulf still exists between the state of practice and state of the art in hydrologic modeling. Part of this gulf is due to the lack of adequate pre- and post-processing tools for newly developed computational models. The development of user interfaces has traditionally lagged several years behind the development of a particular computational model or suite of models. As a result, models with mature interfaces often lack key advancements in model formulation, solution methods, and/or software design and technology. Part of the problem has been a focus on developing monolithic tools to provide comprehensive interfaces for the entire suite of model capabilities. Such efforts require expertise in software libraries and frameworks for creating user interfaces (e.g., Tcl/Tk, Qt, and MFC). These tools are complex and require significant investment in project resources (time and/or money) to use. Moreover, providing the required features for the entire range of possible applications and analyses creates a cumbersome interface. For a particular site or application, the modeling requirements may be simplified or at least narrowed, which can greatly reduce the number and complexity of options that need to be accessible to the user. However, monolithic tools usually are not adept at dynamically exposing specific workflows. Our approach is to deliver highly tailored interfaces to users. These interfaces may be site and/or process specific. As a result, we end up with many, customized interfaces rather than a single, general-use tool. For this approach to be successful, it must be efficient to create these tailored interfaces. We need technology for creating quality user interfaces that is accessible and has a low barrier for integration into model development efforts. Here, we present efforts to leverage IPython notebooks as tools for rapid prototyping of site and application-specific user interfaces. We provide specific examples from applications in near

  9. A surface hydrology model for regional vector borne disease models

    NASA Astrophysics Data System (ADS)

    Tompkins, Adrian; Asare, Ernest; Bomblies, Arne; Amekudzi, Leonard

    2016-04-01

    Small, sun-lit temporary pools that form during the rainy season are important breeding sites for many key mosquito vectors responsible for the transmission of malaria and other diseases. The representation of this surface hydrology in mathematical disease models is challenging, due to their small-scale, dependence on the terrain and the difficulty of setting soil parameters. Here we introduce a model that represents the temporal evolution of the aggregate statistics of breeding sites in a single pond fractional coverage parameter. The model is based on a simple, geometrical assumption concerning the terrain, and accounts for the processes of surface runoff, pond overflow, infiltration and evaporation. Soil moisture, soil properties and large-scale terrain slope are accounted for using a calibration parameter that sets the equivalent catchment fraction. The model is calibrated and then evaluated using in situ pond measurements in Ghana and ultra-high (10m) resolution explicit simulations for a village in Niger. Despite the model's simplicity, it is shown to reproduce the variability and mean of the pond aggregate water coverage well for both locations and validation techniques. Example malaria simulations for Uganda will be shown using this new scheme with a generic calibration setting, evaluated using district malaria case data. Possible methods for implementing regional calibration will be briefly discussed.

  10. eWaterCycle: Developing a hyper resolution global hydrological model

    NASA Astrophysics Data System (ADS)

    Drost, N.; Sutanudjaja, E.; Hut, R.; Steele-Dunne, S. C.; de Jong, K.; Van Beek, L. P.; Karssenberg, D.; Bierkens, M. F.; Van De Giesen, N.

    2013-12-01

    The development of a high resolution global hydrological model has recently been put forward as Grand Challenge for the hydrological community (Wood et al., 2011). The eWaterCycle project aims at developing a high resolution global hydrological model allowing for a better representation of the effects of spatial heterogeneity in topography, soil, and vegetation on hydrological dynamics. The original version of the global hydrological model PCR-GLOBWB (van Beek et al., 2011) runs at a relatively coarse spatial grid (i.e. 0.5° or about 50 km at the equator), which is well below the hyper resolution envisioned in the Grand Challenge (i.e. 100 m). The development of such a hyper resolution model requires utilizing recent computational advances and massive parallel computer systems. So far, the hydrological community has not yet made full use of such possibilities. The eWaterCycle is a close cooperation between hydrologists (Delft University of Technology and Utrecht University) and the Netherlands eScience Center (NLeSC) - that intends to supports and reinforce data-intensive research through creative and innovative use of information and communication technology (ICT). In this project, we modify and extend PCR-GLOBWB so that it runs at much higher resolution, on the order of 1 km or finer. This model refinement is a huge step forward as increasing resolution also requires adding an explicit spatial representation of local processes (groundwater flow, water diversions, glaciers, etc.) that greatly enhance the regional to local applicability of the model. In this project, we also aim to run the model operationally with a data assimilation scheme that incorporates satellite soil moisture observations and other relevant variables. The outcome of the eWaterCycle project will be relevant for addressing critical water cycle science questions and hydrological applications such as assessing water resources sustainability, flood and drought frequency under climate change. For

  11. Reducing equifinality of hydrological models by integrating Functional Streamflow Disaggregation

    NASA Astrophysics Data System (ADS)

    Lüdtke, Stefan; Apel, Heiko; Nied, Manuela; Carl, Peter; Merz, Bruno

    2014-05-01

    A universal problem of the calibration of hydrological models is the equifinality of different parameter sets derived from the calibration of models against total runoff values. This is an intrinsic problem stemming from the quality of the calibration data and the simplified process representation by the model. However, discharge data contains additional information which can be extracted by signal processing methods. An analysis specifically developed for the disaggregation of runoff time series into flow components is the Functional Streamflow Disaggregation (FSD; Carl & Behrendt, 2008). This method is used in the calibration of an implementation of the hydrological model SWIM in a medium sized watershed in Thailand. FSD is applied to disaggregate the discharge time series into three flow components which are interpreted as base flow, inter-flow and surface runoff. In addition to total runoff, the model is calibrated against these three components in a modified GLUE analysis, with the aim to identify structural model deficiencies, assess the internal process representation and to tackle equifinality. We developed a model dependent (MDA) approach calibrating the model runoff components against the FSD components, and a model independent (MIA) approach comparing the FSD of the model results and the FSD of calibration data. The results indicate, that the decomposition provides valuable information for the calibration. Particularly MDA highlights and discards a number of standard GLUE behavioural models underestimating the contribution of soil water to river discharge. Both, MDA and MIA yield to a reduction of the parameter ranges by a factor up to 3 in comparison to standard GLUE. Based on these results, we conclude that the developed calibration approach is able to reduce the equifinality of hydrological model parameterizations. The effect on the uncertainty of the model predictions is strongest by applying MDA and shows only minor reductions for MIA. Besides

  12. Impact of multicollinearity on small sample hydrologic regression models

    NASA Astrophysics Data System (ADS)

    Kroll, Charles N.; Song, Peter

    2013-06-01

    Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.

  13. The Western States Water Mission: A Hyper-Resolution Hydrological Modeling and Data Integration Platform

    NASA Astrophysics Data System (ADS)

    Famiglietti, James; Basilio, Ralph; Trangsrud, Amy; Andreadis, Kostas; Cricthon, Dan; David, Cedric; Farr, Thomas; Malhotra, Shan; Neff, Kirstin; Reager, John

    2016-04-01

    Hydrological remote sensing has advanced significantly over the last decade, and will continue to grow with number of recent and near-future launched. Arguably, a platform for synthesizing remote observations is an important step towards improved modeling, understanding and prediction of terrestrial hydrology. In this presentation we describe the new NASA Western States Water Mission, a high-resolution, catchment-based modeling and data assimilation platform implemented for the western United States. Model structure will be described, as well as early results that include assimilation of satellite snow observations. A key feature of model development has been its treatment as a 'flight project' which enables leveraging of important NASA systems engineering and project management expertise.

  14. Hydrologic and water quality models: Performance measures and evaluation criteria

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Performance measures and corresponding criteria constitute an important aspect of calibration and validation of any hydrological and water quality (H/WQ) model. As new and improved methods and information are developed, it is essential that performance measures and criteria be updated. Therefore, th...

  15. Information and complexity measures for hydrologic model evaluation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hydrological models are commonly evaluated through the residual-based performance measures such as the root-mean square error or efficiency criteria. Such measures, however, do not evaluate the degree of similarity of patterns in simulated and measured time series. The objective of this study was to...

  16. Hydrologic and water quality models: Use, calibration, and validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper introduces a special collection of 22 research articles that present and discuss calibration and validation concepts in detail for hydrologic and water quality models by their developers and presents a broad framework for developing the American Society of Agricultural and Biological Engi...

  17. Green roof hydrologic performance and modeling: a review.

    PubMed

    Li, Yanling; Babcock, Roger W

    2014-01-01

    Green roofs reduce runoff from impervious surfaces in urban development. This paper reviews the technical literature on green roof hydrology. Laboratory experiments and field measurements have shown that green roofs can reduce stormwater runoff volume by 30 to 86%, reduce peak flow rate by 22 to 93% and delay the peak flow by 0 to 30 min and thereby decrease pollution, flooding and erosion during precipitation events. However, the effectiveness can vary substantially due to design characteristics making performance predictions difficult. Evaluation of the most recently published study findings indicates that the major factors affecting green roof hydrology are precipitation volume, precipitation dynamics, antecedent conditions, growth medium, plant species, and roof slope. This paper also evaluates the computer models commonly used to simulate hydrologic processes for green roofs, including stormwater management model, soil water atmosphere and plant, SWMS-2D, HYDRUS, and other models that are shown to be effective for predicting precipitation response and economic benefits. The review findings indicate that green roofs are effective for reduction of runoff volume and peak flow, and delay of peak flow, however, no tool or model is available to predict expected performance for any given anticipated system based on design parameters that directly affect green roof hydrology. PMID:24569270

  18. Hydrologic and water quality modeling: spatial and temporal considerations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hydrologic and water quality models are used to help manage water resources by investigating the effects of climate, land use, land management, and water management on water resources. Each water-related issue is better investigated at a specific scale, which can vary spatially from point to watersh...

  19. Hydrological modeling using a multi-site stochastic weather generator

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Weather data is usually required at several locations over a large watershed, especially when using distributed models for hydrological simulations. In many applications, spatially correlated weather data can be provided by a multi-site stochastic weather generator which considers the spatial correl...

  20. Generating distributed forcing fields for spatial hydrologic modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spatial hydrologic modeling requires the development of distributed forcing fields of weather and precipitation. This is particularly difficult in mountainous regions of the western US, where measurement sites are limited and the landscape is dominated by complex terrain and variations in vegetatio...

  1. Modeling the Hydrologic Processes of a Permeable Pavement System

    EPA Science Inventory

    A permeable pavement system can capture stormwater to reduce runoff volume and flow rate, improve onsite groundwater recharge, and enhance pollutant controls within the site. A new unit process model for evaluating the hydrologic performance of a permeable pavement system has be...

  2. Sharing hydrological knowledge: an international comparison of hydrological models in the Meuse River Basin

    NASA Astrophysics Data System (ADS)

    Bouaziz, Laurène; Sperna Weiland, Frederiek; Drogue, Gilles; Brauer, Claudia; Weerts, Albrecht

    2015-04-01

    International collaboration between institutes and universities working and studying the same transboundary basin is needed for consensus building around possible effects of climate change and climate adaptation measures. Education, experience and expert knowledge of the hydrological community have resulted in the development of a great variety of model concepts, calibration and analysis techniques. Intercomparison could be a first step into consensus modeling or an ensemble based modeling strategy. Besides these practical objectives, such an intercomparison offers the opportunity to explore different ranges of models and learn from each other, hopefully increasing the insight into the hydrological processes that play a role in the transboundary basin. In this experiment, different international research groups applied their rainfall-runoff model in the Ourthe, a Belgium sub-catchment of the Meuse. Data preparation involved the interpolation of hourly precipitation station data collected and owned by the Service Public de Wallonie1 and the freely available E-OBS dataset for daily temperature (Haylock et al., 2008). Daily temperature was disaggregated to hourly values and potential evaporation was derived with the Hargreaves formula. The data was made available to the researchers through an FTP server. The protocol for the modeling involved a split-sample calibration and validation for pre-defined periods. Objective functions for calibration were fixed but the calibration algorithm was a free choice of the research groups. The selection of calibration algorithm was considered model dependent because lumped as well as computationally less efficient distributed models were used. For each model, an ensemble of best performing parameter sets was selected and several performance metrics enabled to assess the models' abilities to simulate discharge. The aim of this experiment is to identify those model components and structures that increase model performance and may best

  3. Coupling Radar Rainfall to Hydrological Models for Water Abstraction Management

    NASA Astrophysics Data System (ADS)

    Asfaw, Alemayehu; Shucksmith, James; Smith, Andrea; MacDonald, Ken

    2015-04-01

    The impacts of climate change and growing water use are likely to put considerable pressure on water resources and the environment. In the UK, a reform to surface water abstraction policy has recently been proposed which aims to increase the efficiency of using available water resources whilst minimising impacts on the aquatic environment. Key aspects to this reform include the consideration of dynamic rather than static abstraction licensing as well as introducing water trading concepts. Dynamic licensing will permit varying levels of abstraction dependent on environmental conditions (i.e. river flow and quality). The practical implementation of an effective dynamic abstraction strategy requires suitable flow forecasting techniques to inform abstraction asset management. Potentially the predicted availability of water resources within a catchment can be coupled to predicted demand and current storage to inform a cost effective water resource management strategy which minimises environmental impacts. The aim of this work is to use a historical analysis of UK case study catchment to compare potential water resource availability using modelled dynamic abstraction scenario informed by a flow forecasting model, against observed abstraction under a conventional abstraction regime. The work also demonstrates the impacts of modelling uncertainties on the accuracy of predicted water availability over range of forecast lead times. The study utilised a conceptual rainfall-runoff model PDM - Probability-Distributed Model developed by Centre for Ecology & Hydrology - set up in the Dove River catchment (UK) using 1km2 resolution radar rainfall as inputs and 15 min resolution gauged flow data for calibration and validation. Data assimilation procedures are implemented to improve flow predictions using observed flow data. Uncertainties in the radar rainfall data used in the model are quantified using artificial statistical error model described by Gaussian distribution and

  4. Test plan for hydrologic modeling of protective barriers

    SciTech Connect

    Fayer, M.J.

    1990-03-01

    Pacific Northwest Laboratory prepared this test plan for the Model Applications and Validation Task of the Hanford Protective Barriers Program, which is managed by Westinghouse Hanford Company. The objectives of this plan are to outline the conceptual hydrologic model of protective barriers, discuss the available computer codes, describe the interrelationships between the modeling task and the other tasks of the Protective Barriers Program, present the barrier modeling tests, and estimate the schedule and costs of the hydrologic modeling task for planning purposes by the Protective Barriers Program. The purpose of the tests is to validate models that will be used to confirm the long-term performance of the barrier in minimizing drainage. A second purpose of the tests is to provide information to other parts of the Protective Barriers Program that require such information. 26 refs., 2 figs., 3 tabs.

  5. A visual interface for the SUPERFLEX hydrological modelling framework

    NASA Astrophysics Data System (ADS)

    Gao, H.; Fenicia, F.; Kavetski, D.; Savenije, H. H. G.

    2012-04-01

    The SUPERFLEX framework is a modular modelling system for conceptual hydrological modelling at the catchment scale. This work reports the development of a visual interface for the SUPERFLEX model. This aims to enhance the communication between the hydrologic experimentalists and modelers, in particular further bridging the gap between the field soft data and the modeler's knowledge. In collaboration with field experimentalists, modelers can visually and intuitively hypothesize different model architectures and combinations of reservoirs, select from a library of constructive functions to describe the relationship between reservoirs' storage and discharge, specify the shape of lag functions and, finally, set parameter values. The software helps hydrologists take advantage of any existing insights into the study site, translate it into a conceptual hydrological model and implement it within a computationally robust algorithm. This tool also helps challenge and contrast competing paradigms such as the "uniqueness of place" vs "one model fits all". Using this interface, hydrologists can test different hypotheses and model representations, and stepwise build deeper understanding of the watershed of interest.

  6. JAMS - a software platform for modular hydrological modelling

    NASA Astrophysics Data System (ADS)

    Kralisch, Sven; Fischer, Christian

    2015-04-01

    Current challenges of understanding and assessing the impacts of climate and land use changes on environmental systems demand for an ever-increasing integration of data and process knowledge in corresponding simulation models. Software frameworks that allow for a seamless creation of integrated models based on less complex components (domain models, process simulation routines) have therefore gained increasing attention during the last decade. JAMS is an Open-Source software framework that has been especially designed to cope with the challenges of eco-hydrological modelling. This is reflected by (i) its flexible approach for representing time and space, (ii) a strong separation of process simulation components from the declarative description of more complex models using domain specific XML, (iii) powerful analysis and visualization functions for spatial and temporal input and output data, and (iv) parameter optimization and uncertainty analysis functions commonly used in environmental modelling. Based on JAMS, different hydrological and nutrient-transport simulation models were implemented and successfully applied during the last years. We will present the JAMS core concepts and give an overview of models, simulation components and support tools available for that framework. Sample applications will be used to underline the advantages of component-based model designs and to show how JAMS can be used to address the challenges of integrated hydrological modelling.

  7. Geographically Isolated Wetlands and Catchment Hydrology: A Modified Model Analyses

    NASA Astrophysics Data System (ADS)

    Evenson, G.; Golden, H. E.; Lane, C.; D'Amico, E.

    2014-12-01

    Geographically isolated wetlands (GIWs), typically defined as depressional wetlands surrounded by uplands, support an array of hydrological and ecological processes. However, key research questions concerning the hydrological connectivity of GIWs and their impacts on downgradient surface waters remain unanswered. This is particularly important for regulation and management of these systems. For example, in the past decade United States Supreme Court decisions suggest that GIWs can be afforded protection if significant connectivity exists between these waters and traditional navigable waters. Here we developed a simulation procedure to quantify the effects of various spatial distributions of GIWs across the landscape on the downgradient hydrograph using a refined version of the Soil and Water Assessment Tool (SWAT), a catchment-scale hydrological simulation model. We modified the SWAT FORTRAN source code and employed an alternative hydrologic response unit (HRU) definition to facilitate an improved representation of GIW hydrologic processes and connectivity relationships to other surface waters, and to quantify their downgradient hydrological effects. We applied the modified SWAT model to an ~ 202 km2 catchment in the Coastal Plain of North Carolina, USA, exhibiting a substantial population of mapped GIWs. Results from our series of GIW distribution scenarios suggest that: (1) Our representation of GIWs within SWAT conforms to field-based characterizations of regional GIWs in most respects; (2) GIWs exhibit substantial seasonally-dependent effects upon downgradient base flow; (3) GIWs mitigate peak flows, particularly following high rainfall events; and (4) The presence of GIWs on the landscape impacts the catchment water balance (e.g., by increasing groundwater outflows). Our outcomes support the hypothesis that GIWs have an important catchment-scale effect on downgradient streamflow.

  8. Program plan and summary, remote fluvial experimental (REFLEX) series: Research experiments using advanced remote sensing technologies with emphasis on hydrologic transport, and hydrologic-ecologic interactions

    SciTech Connect

    Wobber, F.J.

    1986-10-01

    This document describes research designed to evaluate advanced remote sensing technologies for environmental research. A series of Remote Fluvial Experiments (REFLEX) - stressing new applications of remote sensing systems and use of advanced digital analysis methods - are described. Program strategy, experiments, research areas, and future initiatives are summarized. The goals of REFLEX are: (1) to apply new and developing aerial and satellite remote sensing technologies - including both advanced sensor systems and digital/optical processing - for interdisciplinary scientific experiments in hydrology and to hydrologic/ecologic interactions; (2) to develop new concepts for processing and analyzing remote sensing data for general scientific application; and (3) to demonstrate innovative analytical technologies that advance the state of the art in applying information from remote sensing systems, for example, supercomputer processing and analysis.

  9. Spatial transferability of landscape-based hydrological models

    NASA Astrophysics Data System (ADS)

    Gao, Hongkai; Hrachowitz, Markus; Fenicia, Fabrizio; Gharari, Shervan; Sriwongsitanon, Nutchanart; Savenije, Hubert

    2015-04-01

    Landscapes, mainly distinguished by land surface topography and vegetation cover, are crucial in defining runoff generation mechanisms, interception capacity and transpiration processes. Landscapes information provides modelers with a way to take into account catchment heterogeneity, while simultaneously keeping model complexity low. A landscape-based hydrological modelling framework (FLEX-Topo), with parallel model structures, was developed and tested in various catchments with diverse climate, topography and land cover conditions. Landscape classification is the basic and most crucial procedure to create a tailor-made model for a certain catchment, as it explicitly relates hydrologic similarity to landscape similarity, which is the base of this type of models. Therefore, the study catchment is classified into different landscapes units that fulfil similar hydrological function, based on classification criteria such as the height above the nearest drainage, slope, aspect and land cover. At present, to suggested model includes four distinguishable landscapes: hillslopes, terraces/plateaus, riparian areas, and glacierized areas. Different parallel model structures are then associated with the different landscape units to describe their different dominant runoff generation mechanisms. These hydrological units are parallel and only connected by groundwater reservoir. The transferability of this landscape-based model can then be compared with the transferability of a lumped model. In this study, FLEX-Topo was developed and tested in three study sites: two cold-arid catchments in China (the upper Heihe River and the Urumqi Glacier No1 catchment), and one tropical catchment in Thailand (the upper Ping River). Stringent model tests indicate that FLEX-Topo, allowing for more process heterogeneity than lumped model formulations, exhibits higher capabilities to be spatially transferred. Furthermore, the simulated water balances, including internal fluxes, hydrograph

  10. Advanced Production Planning Models

    SciTech Connect

    JONES,DEAN A.; LAWTON,CRAIG R.; KJELDGAARD,EDWIN A.; WRIGHT,STEPHEN TROY; TURNQUIST,MARK A.; NOZICK,LINDA K.; LIST,GEORGE F.

    2000-12-01

    >This report describes the innovative modeling approach developed as a result of a 3-year Laboratory Directed Research and Development project. The overall goal of this project was to provide an effective suite of solvers for advanced production planning at facilities in the nuclear weapons complex (NWC). We focused our development activities on problems related to operations at the DOE's Pantex Plant. These types of scheduling problems appear in many contexts other than Pantex--both within the NWC (e.g., Neutron Generators) and in other commercial manufacturing settings. We successfully developed an innovative and effective solution strategy for these types of problems. We have tested this approach on actual data from Pantex, and from Org. 14000 (Neutron Generator production). This report focuses on the mathematical representation of the modeling approach and presents three representative studies using Pantex data. Results associated with the Neutron Generator facility will be published in a subsequent SAND report. The approach to task-based scheduling described here represents a significant addition to the literature for large-scale, realistic scheduling problems in a variety of production settings.

  11. Advanced Chemistry Basins Model

    SciTech Connect

    William Goddard; Mario Blanco; Lawrence Cathles; Paul Manhardt; Peter Meulbroek; Yongchun Tang

    2002-11-10

    The DOE-funded Advanced Chemistry Basin model project is intended to develop a public domain, user-friendly basin modeling software under PC or low end workstation environment that predicts hydrocarbon generation, expulsion, migration and chemistry. The main features of the software are that it will: (1) afford users the most flexible way to choose or enter kinetic parameters for different maturity indicators; (2) afford users the most flexible way to choose or enter compositional kinetic parameters to predict hydrocarbon composition (e.g., gas/oil ratio (GOR), wax content, API gravity, etc.) at different kerogen maturities; (3) calculate the chemistry, fluxes and physical properties of all hydrocarbon phases (gas, liquid and solid) along the primary and secondary migration pathways of the basin and predict the location and intensity of phase fractionation, mixing, gas washing, etc.; and (4) predict the location and intensity of de-asphaltene processes. The project has be operative for 36 months, and is on schedule for a successful completion at the end of FY 2003.

  12. Hydrological modelling in a "big data" era: a proof of concept of hydrological models as web services

    NASA Astrophysics Data System (ADS)

    Buytaert, Wouter; Vitolo, Claudia

    2013-04-01

    Dealing with the massive increase in global data availability of all sorts is increasingly being known as "big data" science. Indeed, largely leveraged by the internet, a new resource of data sets emerges that are so large and heterogeneous that they become awkward to work with. New algorithms, methods and models are needed to filter such data to find trends, test hypotheses, make predictions and quantify uncertainties. As a considerable share of the data relate to environmental processes (e.g., satellite images, distributed sensor networks), this evolution provides exciting challenges for environmental sciences, and hydrology in particular. Web-enabled models are a promising approach to process large and distributed data sets, and to provide tailored products for a variety of end-users. It will also allow hydrological models to be used as building blocks in larger earth system simulation systems. However, in order to do so we need to reconsider the ways that hydrological models are built, results are made available, and uncertainties are quantified. We present the results of an experimental proof of concept of a hydrological modelling web-service to process heterogeneous hydrological data sets. The hydrological model itself consists of a set of conceptual model routines implemented with on a common platform. This framework is linked to global and local data sets through web standards provided by the Open Geospatial Consortium, as well as to a web interface that enables an end-user to request stream flow simulations from a self-defined location. In essence, the proof-of-concept can be seen as an implementation of the "Models of Everywhere" concept introduced by Beven in 2007. Although the setup is operational and effectively simulates stream flow, we identify several bottlenecks for optimal hydrological simulation in a web-context. The major challenges we identify are related to (1) model selection; (2) uncertainty quantification, and (3) user interaction and

  13. eWaterCycle: A global operational hydrological forecasting model

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Development of an operational hyper-resolution hydrological global model is a central goal of the eWaterCycle project (www.ewatercycle.org). This operational model includes ensemble forecasts (14 days) to predict water related stress around the globe. Assimilation of near-real time satellite data is part of the intended product that will be launched at EGU 2015. The challenges come from several directions. First, there are challenges that are mainly computer science oriented but have direct practical hydrological implications. For example, we aim to make use as much as possible of existing standards and open-source software. For example, different parts of our system are coupled through the Basic Model Interface (BMI) developed in the framework of the Community Surface Dynamics Modeling System (CSDMS). The PCR-GLOBWB model, built by Utrecht University, is the basic hydrological model that is the engine of the eWaterCycle project. Re-engineering of parts of the software was needed for it to run efficiently in a High Performance Computing (HPC) environment, and to be able to interface using BMI, and run on multiple compute nodes in parallel. The final aim is to have a spatial resolution of 1km x 1km, which is currently 10 x 10km. This high resolution is computationally not too demanding but very memory intensive. The memory bottleneck becomes especially apparent for data assimilation, for which we use OpenDA. OpenDa allows for different data assimilation techniques without the need to build these from scratch. We have developed a BMI adaptor for OpenDA, allowing OpenDA to use any BMI compatible model. To circumvent memory shortages which would result from standard applications of the Ensemble Kalman Filter, we have developed a variant that does not need to keep all ensemble members in working memory. At EGU, we will present this variant and how it fits well in HPC environments. An important step in the eWaterCycle project was the coupling between the hydrological and

  14. The One-Water Hydrologic Flow Model - The next generation in fully integrated hydrologic simulation software

    NASA Astrophysics Data System (ADS)

    Boyce, S. E.; Hanson, R. T.

    2015-12-01

    The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. MF-OWHM 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 within a supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 combined with Local Grid Refinement, Streamflow Routing, Surface-water Routing Process, Seawater Intrusion, Riparian Evapotranspiration, and the Newton-Raphson solver. MF-OWHM also includes linkages for deformation-, flow-, and head-dependent flows; additional observation and parameter options for higher-order calibrations; and redesigned code for facilitation of self-updating models and faster simulation run times. The next version of MF-OWHM, currently under development, will include a new surface-water operations module that simulates dynamic reservoir operations, the conduit flow process for karst aquifers and leaky pipe networks, a new subsidence and aquifer compaction package, and additional features and enhancements to enable more integration and cross communication between traditional MODFLOW packages. By retaining and tracking the water within the hydrosphere, MF-OWHM accounts for "all of the water everywhere and all of the time." This philosophy provides more confidence in the water accounting by the scientific community and provides the public a foundation needed to address wider classes of problems such as evaluation of conjunctive-use alternatives and sustainability analysis, including potential adaptation and mitigation strategies, and best management practices. By Scott E. Boyce and Randall T. Hanson

  15. A New Wavelet Based Approach to Assess Hydrological Models

    NASA Astrophysics Data System (ADS)

    Adamowski, J. F.; Rathinasamy, M.; Khosa, R.; Nalley, D.

    2014-12-01

    In this study, a new wavelet based multi-scale performance measure (Multiscale Nash Sutcliffe Criteria, and Multiscale Normalized Root Mean Square Error) for hydrological model comparison was developed and tested. The new measure provides a quantitative measure of model performance across different timescales. Model and observed time series are decomposed using the a trous wavelet transform, and performance measures of the model are obtained at each time scale. The usefulness of the new measure was tested using real as well as synthetic case studies. The real case studies included simulation results from the Soil Water Assessment Tool (SWAT), as well as statistical models (the Coupled Wavelet-Volterra (WVC), Artificial Neural Network (ANN), and Auto Regressive Moving Average (ARMA) methods). Data from India and Canada were used. The synthetic case studies included different kinds of errors (e.g., timing error, as well as under and over prediction of high and low flows) in outputs from a hydrologic model. It was found that the proposed wavelet based performance measures (i.e., MNSC and MNRMSE) are a more reliable measure than traditional performance measures such as the Nash Sutcliffe Criteria, Root Mean Square Error, and Normalized Root Mean Square Error. It was shown that the new measure can be used to compare different hydrological models, as well as help in model calibration.

  16. Improving the transferability of hydrological model parameters under changing conditions

    NASA Astrophysics Data System (ADS)

    Huang, Yingchun; Bárdossy, András

    2014-05-01

    Hydrological models are widely utilized to describe catchment behaviors with observed hydro-meteorological data. Hydrological process may be considered as non-stationary under the changing climate and land use conditions. An applicable hydrological model should be able to capture the essential features of the target catchment and therefore be transferable to different conditions. At present, many model applications based on the stationary assumptions are not sufficient for predicting further changes or time variability. The aim of this study is to explore new model calibration methods in order to improve the transferability of model parameters. To cope with the instability of model parameters calibrated on catchments in non-stationary conditions, we investigate the idea of simultaneously calibration on streamflow records for the period with dissimilar climate characteristics. In additional, a weather based weighting function is implemented to adjust the calibration period to future trends. For regions with limited data and ungauged basins, the common calibration was applied by using information from similar catchments. Result shows the model performance and transfer quantity could be well improved via common calibration. This model calibration approach will be used to enhance regional water management and flood forecasting capabilities.

  17. Large-scale hydrological modelling by using modified PUB recommendations: the India-HYPE case

    NASA Astrophysics Data System (ADS)

    Pechlivanidis, I. G.; Arheimer, B.

    2015-11-01

    The scientific initiative Prediction in Ungauged Basins (PUB) (2003-2012 by the IAHS) put considerable effort into improving the reliability of hydrological models to predict flow response in ungauged rivers. PUB's collective experience advanced hydrologic science and defined guidelines to make predictions in catchments without observed runoff data. At present, there is a raised interest in applying catchment models to large domains and large data samples in a multi-basin manner, to explore emerging spatial patterns or learn from comparative hydrology. However, such modelling involves additional sources of uncertainties caused by the inconsistency between input data sets, i.e. particularly regional and global databases. This may lead to inaccurate model parameterisation and erroneous process understanding. In order to bridge the gap between the best practices for flow predictions in single catchments and multi-basins at the large scale, we present a further developed and slightly modified version of the recommended best practices for PUB by Takeuchi et al. (2013). By using examples from a recent HYPE (Hydrological Predictions for the Environment) hydrological model set-up across 6000 subbasins for the Indian subcontinent, named India-HYPE v1.0, we explore the PUB recommendations, identify challenges and recommend ways to overcome them. We describe the work process related to (a) errors and inconsistencies in global databases, unknown human impacts, and poor data quality; (b) robust approaches to identify model parameters using a stepwise calibration approach, remote sensing data, expert knowledge, and catchment similarities; and (c) evaluation based on flow signatures and performance metrics, using both multiple criteria and multiple variables, and independent gauges for "blind tests". The results show that despite the strong physiographical gradient over the subcontinent, a single model can describe the spatial variability in dominant hydrological processes at the

  18. Flash flood modeling with the MARINE hydrological distributed model

    NASA Astrophysics Data System (ADS)

    Estupina-Borrell, V.; Dartus, D.; Ababou, R.

    2006-11-01

    Flash floods are characterized by their violence and the rapidity of their occurrence. Because these events are rare and unpredictable, but also fast and intense, their anticipation with sufficient lead time for warning and broadcasting is a primary subject of research. Because of the heterogeneities of the rain and of the behavior of the surface, spatially distributed hydrological models can lead to a better understanding of the processes and so on they can contribute to a better forecasting of flash flood. Our main goal here is to develop an operational and robust methodology for flash flood forecasting. This methodology should provide relevant data (information) about flood evolution on short time scales, and should be applicable even in locations where direct observations are sparse (e.g. absence of historical and modern rainfalls and streamflows in small mountainous watersheds). The flash flood forecast is obtained by the physically based, space-time distributed hydrological model "MARINE'' (Model of Anticipation of Runoff and INondations for Extreme events). This model is presented and tested in this paper for a real flash flood event. The model consists in two steps, or two components: the first component is a "basin'' flood module which generates flood runoff in the upstream part of the watershed, and the second component is the "stream network'' module, which propagates the flood in the main river and its subsidiaries. The basin flash flood generation model is a rainfall-runoff model that can integrate remotely sensed data. Surface hydraulics equations are solved with enough simplifying hypotheses to allow real time exploitation. The minimum data required by the model are: (i) the Digital Elevation Model, used to calculate slopes that generate runoff, it can be issued from satellite imagery (SPOT) or from French Geographical Institute (IGN); (ii) the rainfall data from meteorological radar, observed or anticipated by the French Meteorological Service (M

  19. EVALUATION OF HYDROLOGIC MODELS IN THE DESIGN OF STABLE LANDFILL COVERS

    EPA Science Inventory

    The study evaluates the utility of two hydrologic models in designing stable landfill cover systems. The models evaluated were HELP (Hydrologic Evaluation of Landfill Performance) and CREAMS (Chemicals, Runoff, and Erosion from Agricultural Management Systems). Studies of paramet...

  20. An improved ARIMA model for hydrological simulations

    NASA Astrophysics Data System (ADS)

    Wang, H. R.; Wang, C.; Lin, X.; Kang, J.

    2014-04-01

    Auto Regressive Integrated Moving Average (ARIMA) model is often used to calculate time series data formed by inter-annual variations of monthly data. However, the influence brought about by inter-monthly variations within each year is ignored. Based on the monthly data classified by clustering analysis, the characteristics of time series data are extracted. An improved ARIMA model is developed accounting for both the inter-annual and inter-monthly variation. The correlation between characteristic quantity and monthly data within each year is constructed by regression analysis first. The model can be used for predicting characteristic quantity followed by the stationary treatment for characteristic quantity time series by difference. A case study is conducted to predict the precipitation in Lanzhou precipitation station, China, using the model, and the results show that the accuracy of the improved model is significantly higher than the seasonal model, with the mean residual achieving 9.41 mm and the forecast accuracy increasing by 21%.

  1. Vegetation Dynamics And Soil Moisture: Consequences For Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Guardiola-Claramonte, M.; Troch, P. A.

    2007-12-01

    Current global population growth and economical development accelerates land cover conversion in many parts of the world. Introducing non-native species and woody species encroachment, with different water demands, can affect the partitioning of hydrological fluxes. The impacts on the hydrologic cycle at local to regional scales are poorly understood. The present study investigates the hydrologic implications of land use conversion from native vegetation to rubber. We first compare the vegetation dynamics of rubber (Hevea brasiliensis), a non- native specie in Southeast Asia, to the other main vegetation types in the study area. The experimental catchment, Nam Ken (69km 2), is located in the Xishuangbanna Prefecture (21 °N, 100 °E), in the south of Yunnan province in South China. From 2005 to 2006, we collected continuous records of 2 m deep soil moisture profiles in four different land covers (tea, secondary forest, grassland and rubber), and measured surface radiation in tea and rubber canopies. Our observations show that root water uptake by rubber during the dry season is controlled by the change of day-length, whereas water demand of the native vegetation starts with the arrival of the first monsoon rainfall. The different root water uptake dynamics of rubber result in distinct depletion of deeper layer soil moisture. Traditional evapotranspiration and soil moisture models are unable to simulate this specific behavior, thus a different conceptual model is needed to predict hydrologic changes due to land use conversion in the area.

  2. Hydrologic modeling in dynamic catchments: A data assimilation approach

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

    The transferability of conceptual hydrologic models in time is often limited by both their structural deficiencies and adopted parameterizations. Adopting a stationary set of model parameters ignores biases introduced by the data used to derive them, as well as any future changes to catchment conditions. Although time invariance of model parameters is one of the hallmarks of a high quality hydrologic model, very few (if any) models can achieve this due to their inherent limitations. It is therefore proposed to consider parameters as potentially time varying quantities, which can evolve according to signals in hydrologic observations. In this paper, we investigate the potential for Data Assimilation (DA) to detect known temporal patterns in model parameters from streamflow observations. It is shown that the success of the DA algorithm is strongly dependent on the method used to generate background (or prior) parameter ensembles (also referred to as the parameter evolution model). A range of traditional parameter evolution techniques are considered and found to be problematic when multiple parameters with complex time variations are estimated simultaneously. Two alternative methods are proposed, the first is a Multilayer approach that uses the EnKF to estimate hyperparameters of the temporal structure, based on apriori knowledge of the form of nonstationarity. The second is a Locally Linear approach that uses local linear estimation and requires no assumptions of the form of parameter nonstationarity. Both are shown to provide superior results in a range of synthetic case studies, when compared to traditional parameter evolution techniques.

  3. A rangeland hydrology and erosion model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil loss rates on rangelands are considered one of the few quantitative indicators for assessing rangeland health and conservation practice effectiveness. An erosion model to predict soil loss specific for rangeland applications is needed because existing erosion models were developed from cropland...

  4. RECURSIVE PARAMETER ESTIMATION OF HYDROLOGIC MODELS

    EPA Science Inventory

    Proposed is a nonlinear filtering approach to recursive parameter estimation of conceptual watershed response models in state-space form. he conceptual model state is augmented by the vector of free parameters which are to be estimated from input-output data, and the extended Kal...

  5. Selection of Hydrological Model for Waterborne Release

    SciTech Connect

    Blanchard, A.

    1999-02-03

    The purpose of this report is to evaluate the two available models and determine the appropriate model for use in following waterborne release analyses. Additionally, this report will document the DB and BDB accidents to be used in the future study.

  6. Selection of Hydrological Model for Waterborne Release

    SciTech Connect

    Blanchard, A.

    1999-04-21

    This evaluation will aid in determining the potential impacts of liquid releases to downstream populations on the Savannah River. The purpose of this report is to evaluate the two available models and determine the appropriate model for use in following waterborne release analyses. Additionally, this report will document the Design Basis and Beyond Design Basis accidents to be used in the future study.

  7. Hydrological Modelling of The Guadiana Basin

    NASA Astrophysics Data System (ADS)

    Conan, C.; Bouraoui, F.; de Marsily, G.; Bidoglio, G.

    Increased anthropogenic activities such as agriculture, irrigation, industry, mining, ur- ban water supply and sewage treatment, have created significant environmental prob- lems. To ensure sustainable development of water resources, water managers need new strategies and suitable tools. In particular it is often compulsory that surface wa- ter and groundwater be managed simultaneously both in terms of quantity and quality at catchment scales. To this purpose, a model coupling SWAT (Soil and Water As- sessment Tool) and MODFLOW (Modular 3-D Flow model) was developed. SWAT is a quasi-distributed watershed model with a GIS interface that outlines the sub-basins and stream networks from a Digital Elevation Model (DEM) and calculates daily wa- ter balances from meteorological data, soil and land-use characteristics. The particular advantage of this model, compared to other fully distributed physically based mod- els, is that it requires a small amount of readily available input data. MODFLOW is a fully distributed model that calculates groundwater flow from aquifer characteris- tics. We have adapted this new coupled model SWAT-MODFLOW to a Mediterranean catchment, the Guadiana basin, and present the first results of this work. Only wa- ter quantity results are available at this stage. The validation consisted in comparing measured and predicted daily flow at the catchment and sub-catchment outlets for the period 1970-1995. The model accurately reproduced the decrease of the piezometric level, due to increased water abstraction, and the exchanges between surface water and ground-water. The sensitivity of the model to irrigation practices was evaluated. The usefulness of this model as a management tool has been illustrated through the analysis of alternative scenarios of agricultural practices and climate change.

  8. Committee of machine learning predictors of hydrological models uncertainty

    NASA Astrophysics Data System (ADS)

    Kayastha, Nagendra; Solomatine, Dimitri

    2014-05-01

    In prediction of uncertainty based on machine learning methods, the results of various sampling schemes namely, Monte Carlo sampling (MCS), generalized likelihood uncertainty estimation (GLUE), Markov chain Monte Carlo (MCMC), shuffled complex evolution metropolis algorithm (SCEMUA), differential evolution adaptive metropolis (DREAM), particle swarm optimization (PSO) and adaptive cluster covering (ACCO)[1] used to build a predictive models. These models predict the uncertainty (quantiles of pdf) of a deterministic output from hydrological model [2]. Inputs to these models are the specially identified representative variables (past events precipitation and flows). The trained machine learning models are then employed to predict the model output uncertainty which is specific for the new input data. For each sampling scheme three machine learning methods namely, artificial neural networks, model tree, locally weighted regression are applied to predict output uncertainties. The problem here is that different sampling algorithms result in different data sets used to train different machine learning models which leads to several models (21 predictive uncertainty models). There is no clear evidence which model is the best since there is no basis for comparison. A solution could be to form a committee of all models and to sue a dynamic averaging scheme to generate the final output [3]. This approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model HBV in the Nzoia catchment in Kenya. [1] N. Kayastha, D. L. Shrestha and D. P. Solomatine. Experiments with several methods of parameter uncertainty estimation in hydrological modeling. Proc. 9th Intern. Conf. on Hydroinformatics, Tianjin, China, September 2010. [2] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press

  9. Utilization of remote sensing observations in hydrologic models

    NASA Technical Reports Server (NTRS)

    Ragan, R. M.

    1977-01-01

    Most of the remote sensing related work in hydrologic modeling has centered on modifying existing models to take advantage of the capabilities of new sensor techniques. There has been enough success with this approach to insure that remote sensing is a powerful tool in modeling the watershed processes. Unfortunately, many of the models in use were designed without recognizing the growth of remote sensing technology. Thus, their parameters were selected to be map or field crew definable. It is believed that the real benefits will come through the evolution of new models having new parameters that are developed specifically to take advantage of our capabilities in remote sensing. The ability to define hydrologically active areas could have a significant impact. The ability to define soil moisture and the evolution of new techniques to estimate evoportransportation could significantly modify our approach to hydrologic modeling. Still, without a major educational effort to develop an understanding of the techniques used to extract parameter estimates from remote sensing data, the potential offered by this new technology will not be achieved.

  10. Anticipating the Role of SWOT in Hydrologic and Hydrodynamic Modeling

    NASA Astrophysics Data System (ADS)

    Pavelsky, T.; Biancamaria, S.; Andreadis, K.; Durand, M. T.; Schumann, G.

    2015-12-01

    The Surface Water and Ocean Topography (SWOT) satellite mission is a joint project of NASA and CNES, the French space agency. It aims to provide the first simultaneous, space-based measurements of inundation extent and water surface elevation in rivers, lakes, and wetlands around the world. Although the orbit repeat time is approximately 21 days, many areas of the earth will be viewed multiple times during this window. SWOT will observe rivers as narrow as 50-100 m and lakes as small as 0.01-0.06 km2, with height accuracies of ~10 cm for water bodies 1 km2 in area. Because SWOT will measure temporal variations in the height, width, and slope of rivers, several algorithms have been developed to estimate river discharge solely from SWOT measurements. Additionally, measurements of lake height and area will allow estimation of variability in lake water storage. These new hydrologic measurements will provide important sources of information both hydrologic and hydrodynamic models at regional to global scales. SWOT-derived estimates of water storage change and discharge will help to constrain simulation of the water budget in hydrologic models. Measurements of water surface elevation will provide similar constraints on hydrodynamic models of river flow. SWOT data will be useful for model calibration and validation, but perhaps the most exciting applications involve assimilation of SWOT data into models to enhance model robustness and provide denser temporal sampling than available from SWOT observations alone.

  11. Flash flood warning based on fully dynamic hydrology modelling

    NASA Astrophysics Data System (ADS)

    Pejanovic, Goran; Petkovic, Slavko; Cvetkovic, Bojan; Nickovic, Slobodan

    2016-04-01

    Numerical hydrologic modeling has achieved limited success in the past due to, inter alia, lack of adequate input data. Over the last decade, data availability has improved substantially. For modelling purposes, high-resolution data on topography, river routing, and land cover and soil features have meanwhile become available, as well as the observations such as radar precipitation information. In our study, we have implemented the HYPROM model (Hydrology Prognostic Model) to predict a flash flood event at a smaller-scale basin in Southern Serbia. HYPROM is based on the full set of governing equations for surface hydrological dynamics, in which momentum components, along with the equation of mass continuity, are used as full prognostic equations. HYPROM also includes a river routing module serving as a collector for the extra surface water. Such approach permits appropriate representation of different hydrology scales ranging from flash floods to flows of large and slow river basins. The use of full governing equations, if not appropriately parameterized, may lead to numerical instability systems when the surface water in a model is vanishing. To resolve these modelling problems, an unconditionally stable numerical scheme and a method for height redistribution avoiding shortwave height noise have been developed in HYPROM, which achieve numerical convergence of u, v and h when surface water disappears. We have applied HYPROM, driven by radar-estimated precipitation, to predict flash flooding occurred over smaller and medium-size river basins. Two torrential rainfall cases have been simulated to check the accuracy of the model: the exceptional flooding of May 2014 in Western Serbia, and the convective flash flood of January 2015 in Southern Serbia. The second episode has been successfully predicted by HYPROM in terms of timing and intensity six hours before the event occurred. Such flash flood warning system is in preparation to be operationally implemented in the

  12. Hydrological Modelling and Parameter Identification for Green Roof

    NASA Astrophysics Data System (ADS)

    Lo, W.; Tung, C.

    2012-12-01

    Green roofs, a multilayered system covered by plants, can be used to replace traditional concrete roofs as one of various measures to mitigate the increasing stormwater runoff in the urban environment. Moreover, facing the high uncertainty of the climate change, the present engineering method as adaptation may be regarded as improper measurements; reversely, green roofs are unregretful and flexible, and thus are rather important and suitable. The related technology has been developed for several years and the researches evaluating the stormwater reduction performance of green roofs are ongoing prosperously. Many European counties, cities in the U.S., and other local governments incorporate green roof into the stormwater control policy. Therefore, in terms of stormwater management, it is necessary to develop a robust hydrologic model to quantify the efficacy of green roofs over different types of designs and environmental conditions. In this research, a physical based hydrologic model is proposed to simulate water flowing process in the green roof system. In particular, the model adopts the concept of water balance, bringing a relatively simple and intuitive idea. Also, the research compares the two methods in the surface water balance calculation. One is based on Green-Ampt equation, and the other is under the SCS curve number calculation. A green roof experiment is designed to collect weather data and water discharge. Then, the proposed model is verified with these observed data; furthermore, the parameters using in the model are calibrated to find appropriate values in the green roof hydrologic simulation. This research proposes a simple physical based hydrologic model and the measures to determine parameters for the model.

  13. Application of SMOS and ASCAT soil moisture estimations to hydrological modelling in Serbia

    NASA Astrophysics Data System (ADS)

    Zlatanovic, Nikola; Ivkovic, Marija; Drobnjak, Aleksandar

    2016-04-01

    This study explores the performance of satellite-based soil moisture products from satellites SMOS (Soil Moisture and Ocean Salinity, measuring brightness temperatures in the L-Band at 1.4 GHz) and ASCAT (Advanced SCATterometer, measuring surface backscattering coefficients in the C-band at 5.255 GHz) for hydrological application. Firstly, SMOS and ASCAT Level 2 soil moisture data were compared to in situ data over Serbia at available sites. All available in situ ground-based point measurements of soil moisture, from the Republic Hydrometeorological Service of Serbia and other independent stations, were collected for the overlapping period with satellite observations and compared against remotely sensed satellite-based soil moisture products. Two approaches are presented in this study to evaluate the applicability of satellite-based SMOS and ASCAT soil moisture products to basin-scale hydrological modelling in a case study catchment in Serbia. The first approach was based on a continuous conceptual forecast-based rainfall-runoff model (using distributed HBV model), where satellite-based soil moisture data helped perform corrections to calculated model soil moisture. The second approach analysed individual event-based rainfall-runoff modelling (using HEC-HMS), where initial (pre-event) model parameters were estimated using satellite-based soil moisture data. Both approaches involved calibration of the hydrological models with and without satellite-based soil moisture data on a case study in Serbia.

  14. On the Usefulness of Hydrologic Landscapes for Hydrologic Modeling and Water Management

    EPA Science Inventory

    Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...

  15. On the Usefulness of Hydrologic Landscapes on Hydrologic Model calibration and Selection

    EPA Science Inventory

    Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...

  16. Hydrological trend analysis in the Yellow River basin using a distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Cong, Zhentao; Yang, Dawen; Gao, Bing; Yang, Hanbo; Hu, Heping

    2009-07-01

    The hydrological cycle has been highly influenced by climate change and human activities, and it is significant for analyzing the hydrological trends that occurred in past decades in order to understand past changes and to predict future trends. The water crisis of the Yellow River basin has drawn much attention from around the world, especially the drying up of the main river along the lower reaches during the 1990s. By incorporating historical meteorological data and available geographic information related to the conditions of the landscape, a distributed hydrological model has been employed to simulate the natural runoff without consideration of artificial water intake. On the basis of the data observed and the results simulated by the model, the hydrological trends have been analyzed quantitatively for evaluating the impact from climate change and human activity. It is found that the simulated natural runoff follows a similar trend as the precipitation in the entire area being studied during the last half century, and this implies that changes in the natural runoff are mainly controlled by the climate change rather than land use change. Changes in actual evapotranspiration upstream of the Lanzhou gauge are controlled by changes in both precipitation and potential evaporation, while changes of actual evapotranspiration downstream of the Lanzhou gauge are controlled mainly by the changes in precipitation. The difference between the annual observed runoff and the simulated runoff indicates that there is little artificial water consumption upstream of the Lanzhou gauge, but the artificial water consumption becomes larger downstream of the Lanzhou gauge. The artificial water consumption shows a significant increasing trend during the past 50 years and is the main cause of the drying up of the Yellow River. However, in contrast to the common perception that the serious drying up downstream of the Yellow River during the 1990s is caused by the rapid increase of

  17. Climate Change Impacts to Watershed Hydrology using an Integrated Hydrologic Model (Invited)

    NASA Astrophysics Data System (ADS)

    Huntington, J. L.; Niswonger, R. G.

    2010-12-01

    Many climatologists project that increased green house gases (GHGs) will cause long term changes to the earth's climate superimposed onto historical variability of climate. As a result, climate change poses a difficult problem for water resource managers making longterm forcasts. Modeling hydrologic change associated with climate variability has historically been performed with compartmental models, where surface and groundwater interactions are decoupled. For example, in the few studies that explicitly consider the effects of the unsaturated zone on recharge, the unsaturated zone is represented as a stagnant column of soil through which water flows independently of the underlying water table. Furthermore, previous studies have not considered the coupled interactions of the streamflow components, including snowmelt, runoff, subsurfrace stormflow, and groundwater flow. The interaction of these dynamic coupled processes need to be simulated so they can change with the climate, rather than assuming stagnant conditions based on the present climate. Consequently, to fully assess how climate change might affect water resources, integrated models are likely the best tools. Snow dominated watersheds of the Sierra Nevada are of great importance to water supplies in the western U.S. To analyze how climate change might affect these watersheds, we rely on a integrated surface and groundwater model for three snow dominated watersheds of the eastern Sierra Nevada that are tributary to Lake Tahoe and Truckee Meadows hydrographic areas of California and Nevada. Streamflow was simulated over a 20 year period, and results indicate that 4 month, 6 month, 2 year, and 11 year observed perodicities are well simulated. Model predicted 11 year periodicities are the result of simulating spatial and temporal variations in groundwater recharge, groundwater storage, and groundwater discharge to streams. To assess hydrologic change, we use as direct input, bias corrected and statistically down

  18. 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.

  19. Modelling hydrological responses of Nerbioi River Basin to Climate Change

    NASA Astrophysics Data System (ADS)

    Mendizabal, Maddalen; Moncho, Roberto; Chust, Guillem; Torp, Peter

    2010-05-01

    Future climate change will affect aquatic systems on various pathways. Regarding the hydrological cycle, which is a very important pathway, changes in hydrometeorological variables (air temperature, precipitation, evapotranspiration) in first order impact discharges. The fourth report assessment of the Intergovernmental Panel for Climate Change indicates there is evidence that the recent warming of the climate system would result in more frequent extreme precipitation events, increased winter flood likelihoods, increased and widespread melting of snow and ice, longer and more widespread droughts, and rising sea level. Available research and climate model outputs indicate a range of hydrological impacts with likely to very likely probabilities (67 to 99%). For example, it is likely that up to 20% of the world population will live in areas where river flood potential could increase by the 2080s. In Spain, within the Atlantic basin, the hydrological variability will increase in the future due to the intensification of the positive phase of the North Atlantic Oscillation (NAO) index. This might cause flood frequency decreases, but its magnitude does not decrease. The generation of flood, its duration and magnitude are closely linked to changes in winter precipitation. The climatic conditions and relief of the Iberian Peninsula favour the generation of floods. In Spain, floods had historically strong socio-economic impacts, with more than 1525 victims in the past five decades. This upward trend of hydrological variability is expected to remain in the coming decades (medium uncertainty) when the intensification of the positive phase of the NAO index (MMA, 2006) is considered. In order to adapt or minimize climate change impacts in water resources, it is necessary to use climate projections as well as hydrological modelling tools. The main objective of this paper is to evaluate and assess the hydrological response to climate changes in flow conditions in Nerbioi river

  20. Modeling Soil Moisture Fields Using the Distributed Hydrologic Model MOBIDIC

    NASA Astrophysics Data System (ADS)

    Castillo, A. E.; Entekhabi, D.; Castelli, F.

    2011-12-01

    The Modello Bilancio Idrologico DIstributo e Continuo (MOBIDIC) is a fully-distributed physically-based basin hydrologic model [Castelli et al., 2009]. MOBIDIC represents watersheds using a system or reservoirs that interact through both mass and energy fluxes. The model uses a single-layered soil on a grid. For each grid element, soil moisture is conceptually partitioned into gravitational (free) and capillary-bound water. For computational parsimony, linear parameterization is used for infiltration rather than solving it using the nonlinear Richard's Equation. Previous applications of MOBIDIC assessed model performance based on streamflow which is a flux. In this study, the MOBIDIC simulated soil moisture, a state variable, is compared against observed values as well as values simulated by the legacy Simultaneous Heat and Water (SHAW) model [Flerchinger, 2000] which was chosen as the benchmark. Results of initial simulations with the original version of MOBIDIC prompted several model modifications such as changing the parameterization of evapotranspiration and adding capillary rise to make the model more robust in simulating the dynamics of soil moisture. In order to test the performance of the modified MOBIDIC, both short-term (a few weeks) and extended (multi-year) simulations were performed for 3 well-studied sites in the US: two sites are mountainous with deep groundwater table and semiarid climate, while the third site is fluvial with shallow groundwater table and temperate climate. For the multi-year simulations, both MOBIDIC and SHAW performed well in modeling the daily observed soil moisture. The simulations also illustrated the benefits of adding the capillary rise module and the other modifications introduced. Moreover, it was successfully demonstrated that MOBIDIC, with some conceptual approaches and some simplified parameterizations, can perform as good, if not better, than the more sophisticated SHAW model. References Castelli, F., G. Menduni, and B

  1. Chapman Conference on Spatial Variability in Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Woolhiser, D. A.; Morel-Seytoux, H. J.

    The AGU Chapman Conference on Spatial Variability in Hydrologic Modeling was held July 21-23, 1981, at the Colorado State University Pingree Park Campus, located in the mountains some 88.5 km (55 miles) west of Fort Collins, Colorado. The conference was attended by experimentalists and theoreticians from a wide range of disciplines, including geology, hydrology, civil engineering, watershed science, chemical engineering, geography, statistics, mathematics, meteorology, and soil science. The attendees included researchers at various levels of research experience, including a large contingent of graduate students and many senior scientists.The conference goal was to review progress and discuss research approaches to the spatial variability of catchment surface and subsurface properties in a distributed modeling context. Mathematical models of water movement dynamics within a catchment consist of linked partial differential equations that describe free surface flow and unsaturated and saturated flow in porous media. Such models are utilized extensively in attempts to understand and predict the environmental consequences of human activities such as agricultural land management, waste disposal, urbanization, etc. We are concerned with the spatial structure of the parameters in such models, the precipitation input, and the geometric complexity of the system boundaries. The emphasis of this conference was on surface and subsurface hydrological process and their interactions.

  2. Modeling of subglacial hydrological development following rapid supraglacial lake drainage

    PubMed Central

    Dow, C F; Kulessa, B; Rutt, I C; Tsai, V C; Pimentel, S; Doyle, S H; van As, D; Lindbäck, K; Pettersson, R; Jones, G A; Hubbard, A

    2015-01-01

    The rapid drainage of supraglacial lakes injects substantial volumes of water to the bed of the Greenland ice sheet over short timescales. The effect of these water pulses on the development of basal hydrological systems is largely unknown. To address this, we develop a lake drainage model incorporating both (1) a subglacial radial flux element driven by elastic hydraulic jacking and (2) downstream drainage through a linked channelized and distributed system. Here we present the model and examine whether substantial, efficient subglacial channels can form during or following lake drainage events and their effect on the water pressure in the surrounding distributed system. We force the model with field data from a lake drainage site, 70 km from the terminus of Russell Glacier in West Greenland. The model outputs suggest that efficient subglacial channels do not readily form in the vicinity of the lake during rapid drainage and instead water is evacuated primarily by a transient turbulent sheet and the distributed system. Following lake drainage, channels grow but are not large enough to reduce the water pressure in the surrounding distributed system, unless preexisting channels are present throughout the domain. Our results have implications for the analysis of subglacial hydrological systems in regions where rapid lake drainage provides the primary mechanism for surface-to-bed connections. Key Points Model for subglacial hydrological analysis of rapid lake drainage events Limited subglacial channel growth during and following rapid lake drainage Persistence of distributed drainage in inland areas where channel growth is limited PMID:26640746

  3. eWaterCycle: A high resolution global hydrological model

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    In 2013, the eWaterCycle project was started, which has the ambitious goal to run a high resolution global hydrological model. Starting point was the PCR-GLOBWB built by Utrecht University. The software behind this model will partially be re-engineered in order to enable to run it in a High Performance Computing (HPC) environment. The aim is to have a spatial resolution of 1km x 1km. The idea is also to run the model in real-time and forecasting mode, using data assimilation. An on-demand hydraulic model will be available for detailed flow and flood forecasting in support of navigation and disaster management. The project faces a set of scientific challenges. First, to enable the model to run in a HPC environment, model runs were analyzed to examine on which parts of the program most CPU time was spent. These parts were re-coded in Open MPI to allow for parallel processing. Different parallelization strategies are thinkable. In our case, it was decided to use watershed logic as a first step to distribute the analysis. There is rather limited recent experience with HPC in hydrology and there is much to be learned and adjusted, both on the hydrological modeling side and the computer science side. For example, an interesting early observation was that hydrological models are, due to their localized parameterization, much more memory intensive than models of sister-disciplines such as meteorology and oceanography. Because it would be deadly to have to swap information between CPU and hard drive, memory management becomes crucial. A standard Ensemble Kalman Filter (enKF) would, for example, have excessive memory demands. To circumvent these problems, an alternative to the enKF was developed that produces equivalent results. This presentation shows the most recent results from the model, including a 5km x 5km simulation and a proof of concept for the new data assimilation approach. Finally, some early ideas about financial sustainability of an operational global

  4. Selection of Hydrological Model for Waterborne Release

    SciTech Connect

    Blanchard, A.

    1999-04-21

    Following a request from the States of South Carolina and Georgia, downstream radiological consequences from postulated accidental aqueous releases at the three Savannah River Site nonreactor nuclear facilities will be examined. This evaluation will aid in determining the potential impacts of liquid releases to downstream populations on the Savannah River. The purpose of this report is to evaluate the two available models and determine the appropriate model for use in following waterborne release analyses. Additionally, this report will document the accidents to be used in the future study.

  5. Ecosystem services: Challenges and opportunities for hydrologic modeling to support decision making

    NASA Astrophysics Data System (ADS)

    Guswa, Andrew J.; Brauman, Kate A.; Brown, Casey; Hamel, Perrine; Keeler, Bonnie L.; Sayre, Susan Stratton

    2014-05-01

    Ecosystem characteristics and processes provide significant value to human health and well-being, and there is growing interest in quantifying those values. Of particular interest are water-related ecosystem services and the incorporation of their value into local and regional decision making. This presents multiple challenges and opportunities to the hydrologic-modeling community. To motivate advances in water-resources research, we first present three common decision contexts that draw upon an ecosystem-service framework: scenario analysis, payments for watershed services, and spatial planning. Within these contexts, we highlight the particular challenges to hydrologic modeling, and then present a set of opportunities that arise from ecosystem-service decisions. The paper concludes with a set of recommendations regarding how we can prioritize our work to support decisions based on ecosystem-service valuation.

  6. A Geospatial Fabric (GF) for National Hydrological Modeling

    NASA Astrophysics Data System (ADS)

    Viger, R.; Bock, A.

    2014-12-01

    The US Geological Survey (USGS) Geospatial Fabric (GF) supports the USGS National Hydrologic Model (NHM) by defining a minimally sufficient, nationally consistent set of geographic information needed to simulate streamflow at almost 60,000 points of interest (POIs). POIs primarily are defined based on: (a) a high quality set of USGS stream gages (Gages-II), (b) National Weather Service forecast nodes, (c) the USGS National Water Quality Assessment's modeling network, (d) at inlets and outlets of selected water bodies, and (e) at confluences. Each POI is associated with a stream segment which typically has two adjacent land surface areas, referred to as hydrologic response units (HRUs). Parameter tables, largely based on the National Land Cover Databases, the Soil Survey Geographic Database (SSURGO), and the geometry of the spatial data, have been derived for these features. Configurations of GF features and attribute tables are defined and made available through the USGS ScienceBase (https://www.sciencebase.gov/catalog/item/537b7327e4b0929ba496f66f). Data are organized into 20 ESRI file geodatabases, each covering a different region of the United States (https://www.sciencebase.gov/catalog/item/535edb4ae4b08e65d60fc837). Future releases will include additional realizations of NHM parameter tables. These will serve to assess the impact of alternate data sources and processing methodologies on simulated streamflows. Tools for dynamically subsetting geodatabases and model inputs based on custom watersheds are currently being prototyped. The GF is a versatile framework for data integration because it maintains feature-level indexing back to NHDPlus and the National Hydrography Dataset, which is used in many water resource studies. In addition, the GF will help to ensure a minimum initial quality of parameter information, reduce the time of developing hydrological modeling applications in the United States, and generally improve the accuracy and scientific impact of

  7. Multi-Objective Calibration of Hydrological Model Parameters Using MOSCEM-UA

    NASA Astrophysics Data System (ADS)

    Wang, Yuhui; Lei, Xiaohui; Jiang, Yunzhong; Wang, Hao

    2010-05-01

    In the past two decades, many evolutionary algorithms have been adopted in the auto-calibration of hydrological model such as NSGA-II, SCEM, etc., some of which has shown ideal performance. In this article, a detailed hydrological model auto-calibration algorithm Multi-objective Shuffled Complex Evolution Metropolis (MOSCEM-UA) has been introduced to carry out auto-calibration of hydrological model in order to clarify the equilibrium and the uncertainty of model parameters. The development and the implement flow chart of the advanced multi-objective algorithm (MOSCEM-UA) were interpreted in detail. Hymod, a conceptual hydrological model depending on Moore's concept, was then introduced as a lumped Rain-Runoff simulation approach with several principal parameters involved. The five important model parameters subjected to calibration includes maximum storage capacity, spatial variability of the soil moisture capacity, flow distributing factor between slow and quick reservoirs as well as slow tank and quick tank distribution factor. In this study, a test case on the up-stream area of KuanCheng hydrometric station in Haihe basin was studied to verify the performance of calibration. Two objectives including objective for high flow process and objective for low flow process are chosen in the process of calibration. The results emphasized that the interrelationship between objective functions could be described in correlation Pareto Front by using MOSCEM-UA. The Pareto Front can be draw after the iteration. Further more, post range of parameters corresponding to Pareto sets could also be drawn to identify the prediction range of the model. Then a set of balanced parameter was chosen to validate the model and the result showed an ideal prediction. Meanwhile, the correlation among parameters and their effects on the model performance could also be achieved.

  8. Fusing Unmanned Aerial Vehicle Imagery with High Resolution Hydrologic Modeling (Invited)

    NASA Astrophysics Data System (ADS)

    Vivoni, E. R.; Pierini, N.; Schreiner-McGraw, A.; Anderson, C.; Saripalli, S.; Rango, A.

    2013-12-01

    After decades of development and applications, high resolution hydrologic models are now common tools in research and increasingly used in practice. More recently, high resolution imagery from unmanned aerial vehicles (UAVs) that provide information on land surface properties have become available for civilian applications. Fusing the two approaches promises to significantly advance the state-of-the-art in terms of hydrologic modeling capabilities. This combination will also challenge assumptions on model processes, parameterizations and scale as land surface characteristics (~0.1 to 1 m) may now surpass traditional model resolutions (~10 to 100 m). Ultimately, predictions from high resolution hydrologic models need to be consistent with the observational data that can be collected from UAVs. This talk will describe our efforts to develop, utilize and test the impact of UAV-derived topographic and vegetation fields on the simulation of two small watersheds in the Sonoran and Chihuahuan Deserts at the Santa Rita Experimental Range (Green Valley, AZ) and the Jornada Experimental Range (Las Cruces, NM). High resolution digital terrain models, image orthomosaics and vegetation species classification were obtained from a fixed wing airplane and a rotary wing helicopter, and compared to coarser analyses and products, including Light Detection and Ranging (LiDAR). We focus the discussion on the relative improvements achieved with UAV-derived fields in terms of terrain-hydrologic-vegetation analyses and summer season simulations using the TIN-based Real-time Integrated Basin Simulator (tRIBS) model. Model simulations are evaluated at each site with respect to a high-resolution sensor network consisting of six rain gauges, forty soil moisture and temperature profiles, four channel runoff flumes, a cosmic-ray soil moisture sensor and an eddy covariance tower over multiple summer periods. We also discuss prospects for the fusion of high resolution models with novel

  9. Subgrid spatial variability of soil hydraulic functions for hydrological modelling

    NASA Astrophysics Data System (ADS)

    Kreye, Phillip; Meon, Günter

    2016-07-01

    State-of-the-art hydrological applications require a process-based, spatially distributed hydrological model. Runoff characteristics are demanded to be well reproduced by the model. Despite that, the model should be able to describe the processes at a subcatchment scale in a physically credible way. The objective of this study is to present a robust procedure to generate various sets of parameterisations of soil hydraulic functions for the description of soil heterogeneity on a subgrid scale. Relations between Rosetta-generated values of saturated hydraulic conductivity (Ks) and van Genuchten's parameters of soil hydraulic functions were statistically analysed. An universal function that is valid for the complete bandwidth of Ks values could not be found. After concentrating on natural texture classes, strong correlations were identified for all parameters. The obtained regression results were used to parameterise sets of hydraulic functions for each soil class. The methodology presented in this study is applicable on a wide range of spatial scales and does not need input data from field studies. The developments were implemented into a hydrological modelling system.

  10. Computationally efficient calibration of WATCLASS Hydrologic models using surrogate optimization

    NASA Astrophysics Data System (ADS)

    Kamali, M.; Ponnambalam, K.; Soulis, E. D.

    2007-07-01

    In this approach, exploration of the cost function space was performed with an inexpensive surrogate function, not the expensive original function. The Design and Analysis of Computer Experiments(DACE) surrogate function, which is one type of approximate models, which takes correlation function for error was employed. The results for Monte Carlo Sampling, Latin Hypercube Sampling and Design and Analysis of Computer Experiments(DACE) approximate model have been compared. The results show that DACE model has a good potential for predicting the trend of simulation results. The case study of this document was WATCLASS hydrologic model calibration on Smokey-River watershed.

  11. Hydrologic modeling of soil water storage in landfill cover systems

    SciTech Connect

    Barnes, F.J.; Rodgers, J.C.

    1987-01-01

    The accuracy of modeling soil water storage by two hydrologic models, CREAMS and HELP, was tested by comparing simulation results with field measurements of soil moisture in eight experimental landfill cover systems having a range of well-defined soil profiles and vegetative covers. Regression analysis showed that CREAMS generally represented soil moisture more accurately than HELP simulations. Soil profiles that more closely resembled natural agricultural soils were more accurately modeled than highly artificial layered soil profiles. Precautions for determining parameter values for model input and for interpreting simulation results are discussed.

  12. Defining prior probabilities for hydrologic model structures in UK catchments

    NASA Astrophysics Data System (ADS)

    Clements, Michiel; Pianosi, Francesca; Wagener, Thorsten; Coxon, Gemma; Freer, Jim; Booij, Martijn

    2014-05-01

    The selection of a model structure is an essential part of the hydrological modelling process. Recently flexible modeling frameworks have been proposed where hybrid model structures can be obtained by mixing together components from a suite of existing hydrological models. When sufficient and reliable data are available, this framework can be successfully utilised to identify the most appropriate structure, and associated optimal parameters, for a given catchment by maximizing the different models ability to reproduce the desired range of flow behaviour. In this study, we use a flexible modelling framework to address a rather different question: can the most appropriate model structure be inferred a priori (i.e without using flow observations) from catchment characteristics like topography, geology, land use, and climate? Furthermore and more generally, can we define priori probabilities of different model structures as a function of catchment characteristics? To address these questions we propose a two-step methodology and demonstrate it by application to a national database of meteo-hydrological data and catchment characteristics for 89 catchments across the UK. In the first step, each catchment is associated with its most appropriate model structure. We consider six possible structures obtained by combining two soil moisture accounting components widely used in the UK (Penman and PDM) and three different flow routing modules (linear, parallel, leaky). We measure the suitability of a model structure by the probability of finding behavioural parameterizations for that model structure when applied to the catchment under study. In the second step, we use regression analysis to establish a relation between selected model structures and the catchment characteristics. Specifically, we apply Classification And Regression Trees (CART) and show that three catchment characteristics, the Base Flow Index, the Runoff Coefficient and the mean Drainage Path Slope, can be used

  13. Coupled Dynamic Modeling to Assess Human Impact on Watershed Hydrology

    NASA Astrophysics Data System (ADS)

    Mohammed, I. N.; Tsai, Y.; Turnbull, S.; Bomblies, A.; Zia, A.

    2014-12-01

    Humans are intrinsic to the hydrologic system, both as agents of change and as beneficiaries of ecosystem services. This connection has been underappreciated in hydrology. We present a modeling linkage framework of an agent-based land use change model with a physical-based watershed model. The coupled model framework presented constitutes part of an integrated assessment model that is being developed to study human-ecosystem interaction in Missisquoi Bay, spanning Vermont and Québec, which is experiencing high concentrations of nutrients from the Missisquoi River watershed. The integrated assessment approach proposed is comprised of linking two simulation models: the Interactive Land-Use Transition Agent-Based Model (ILUTABM) and a physically based process model, the Regional Hydro-Ecological Simulation System (RHESSys). The ILUTABM treats both landscape and landowners as agents and simulates annual land-use patterns resulting from landowners annual land-use decisions and Best Management Practices (BMPs) adaptations to landowners utilities, land productivity and perceived impacts of floods. The Missisquoi River at Swanton watershed RHESSys model (drainage area of 2,200 km2) driven by climate data was first calibrated to daily streamflows and water quality sensor data at the watershed outlet. Simulated land-use patterns were then processed to drive the calibrated RHESSys model to obtain streamflow nutrient loading realizations. Nutrients loading realizations are then examined and routed back to the ILUTAB model to obtain public polices needed to manage the Missisquoi watershed as well as the Lake Champlain in general. We infer that the applicability of this approach can be generalized to other similar watersheds. Index Terms: 0402: Agricultural systems; 1800: Hydrology; 1803: Anthropogenic effects; 1834 Human impacts; 6344: System operation and management; 6334: Regional Planning

  14. Hydrologic modeling of reclaimed strip mine spoil

    SciTech Connect

    Edwards, K.B.; Stoertz, M.W.; Turney, D.C.

    1998-12-31

    A numerical groundwater flow model (MODFLOW) of a surface coal mine in southeast Ohio was calibrated under steady state conditions to match measured heads by varying hydraulic conductivity (K) and recharge (R). Sensitivity studies indicated that K was not largely dependent on the poorly quantified underclay elevation or on the lake boundary condition. The baseflow recharge was determined to be between 8 and 60 mm/yr (1 to 6% of annual rainfall) and K between 0.004 and 0.01 cm/s for the spoil aquifer.

  15. A Coupled Surface/Subsurface Model for Hydrological Drought Investigations

    NASA Astrophysics Data System (ADS)

    Musuuza, J. L.; Kumar, R.; Samaniego, L. E.; Fischer, T.; Kolditz, O.; Attinger, S.

    2013-12-01

    Hydrological droughts occur when storage in the ground and surface-water bodies falls below statistical average. Due to the inclusion of regional groundwater, hydrological droughts evolve relatively slowly. The atmospheric and surface components of the hydrological cycle have been widely studied, are well understood, and their prognoses are fairly accurate. In large-scale land surface models on the other hand, subsurface (groundwater) flow processes are usually assumed unidirectional and limited to the vertically-downward percolation and the horizontal runoffs. The vertical feedback from groundwater to the unsaturated zone as well as the groundwater recharge from surface waters are usually misrepresented, resulting in poor model performance during low-flow periods. The feedback is important during meteorological droughts because it replenishes soil moisture from ground- and surface water, thereby delaying the onset of agricultural droughts. If sustained for long periods however, the depletion can significantly reduce surface and subsurface storage and lead to severe hydrological droughts. We hypothesise that an explicit incorporation of the groundwater component into an existing land surface model would lead to better representation of low flows, which is critical for drought analyses. It would also improve the model performance during low-flow periods. For this purpose, we coupled the process-based mHM surface model (Samaniego et al. 2010) with MODFLOW (Harbaugh 2005) to analyse droughts in the Unstrut catchment, one of the tributaries of the Elbe. The catchment is located in one of the most drought-prone areas of Germany. We present results for stand-alone and coupled mHM simulations for the period 1970-2000. References Arlen W. Harbaugh. MODFLOW-2005, The U.S. Geological Survey Modular Ground-water Model-the Ground-water Flow Process, chapter Modelling techniques, sec. A. Ground water, pages 1:1-9:62. USGS, 2005. Luis Samaniego, Rohini Kumar, and Sabine Attinger

  16. Physically Based Mountain Hydrological Modelling using Reanalysis Data in Patagonia

    NASA Astrophysics Data System (ADS)

    Krogh, S.; Pomeroy, J. W.; McPhee, J. P.

    2013-05-01

    Remote regions in South America are often characterized by insufficient observations of meteorology for robust hydrological model operation. Yet water resources must be quantified, understood and predicted in order to develop effective water management policies. Here, we developed a physically based hydrological model for a major river in Patagonia using the modular Cold Regions Hydrological Modelling Platform (CRHM) in order to better understand hydrological processes leading to streamflow generation in this remote region. The Baker River -with the largest mean annual streamflow in Chile-, drains snowy mountains, glaciers, wet forests, peat and semi-arid pampas into a large lake. Meteorology over the basin is poorly monitored in that there are no high elevation weather stations and stations at low elevations are sparsely distributed, only measure temperature and rainfall and are poorly maintained. Streamflow in the basin is gauged at several points where there are high quality hydrometric stations. In order to quantify the impact of meteorological data scarcity on prediction, two additional data sources were used: the ERA-Interim (ECMWF Re-analyses) and CFSR (Climate Forecast System Reanalysis) atmospheric reanalyses. Precipitation temporal distribution and magnitude from the models and observations were compared and the reanalysis data was found to have about three times the number of days with precipitation than the observations did. Better synchronization between measured peak streamflows and modeled precipitation was found compared to observed precipitation. These differences are attributed to: (i) lack of any snowfall observations (so precipitation records does not consider snowfall events) and (ii) available rainfall observations are all located at low altitude (<500 m a.s.l), and miss the occurrence of high altitude precipitation events. CRHM parameterization was undertaken by using local physiographic and vegetation characteristics where available and

  17. What is the minimal geomorphology based hydrological model?

    NASA Astrophysics Data System (ADS)

    de Lavenne, Alban; Rigon, Riccardo; Formetta, Giuseppe; Cudennec, Christophe

    2013-04-01

    Hydrological modelling is a usefull tool to understand hydrological process. With knowledge increasing, models often become more complex. Drived by each researchers hypothesis, new components are added years after years. However, in many cases, the need of this complexity appears to be unnecessary or, in a context of lack of data, even unsuitable. We propose a modelling framework improvement of geomorphology-based models. By updating step by step models' structure and by checking separatly hypotheses for improving model performance, we aim to improve our understanding of catchment behaviour. We apply this framework on six catchments in Brittany, France. With catchment's area varying from 5km² to 316km², we explore heterogeneous situations to enrich the discussion about model's efficiency, robustness and facility of implementation. Simulations are performed from monthly time scale to annual time scale using 5 years of rainfall-runoff data. We compare the improvement bring by changing progressively model's structure. This is done by splitting catchment dynamics through the play of several flow velocities inside one or several width functions. We test separatly different hypothesis of model improvement, like accounting of velocity and rainfall spatio-temporal variability, as well as considering hydrodynamic dispersion. Models are parametrized using a particle swarm optimisation algorithm. With a minimum complexity level, this framework enable to choose wich model suits the objectives and how to take advantage of the available data.

  18. Integrating spatial altimetry data into the automatic calibration of hydrological models

    NASA Astrophysics Data System (ADS)

    Getirana, Augusto C. V.

    2010-06-01

    SummaryThe automatic calibration of hydrological models has traditionally been performed using gauged data. However, inaccessibility to remote areas and lack of financial support cause data to be lacking in large tropical basins, such as the Amazon basin. Advances in the acquisition, processing and availability of spatially distributed remotely sensed data move the evaluation of computational models easier and more practical. This paper presents the pioneering integration of spatial altimetry data into the automatic calibration of a hydrological model. The study area is the Branco River basin, located in the Northern Amazon basin. An empirical stage × discharge relation is obtained for the Negro River and transposed to the Branco River, which enables the correlation of spatial altimetry data with water discharge derived from the MGB-IPH hydrological model. Six scenarios are created combining two sets of objective functions with three different datasets. Two of them are composed of ENVISAT altimetric data, and the third one is derived from daily gauged discharges. The MOCOM-UA multi-criteria global optimization algorithm is used to optimize the model parameters. The calibration process is validated with gauged discharge at three gauge stations located along the Branco River and two tributaries. Results demonstrate that the combination of virtual stations along the river can provide reasonable parameters. Further, the considerably reduced number of observations provided by the satellite is not a restriction to the automatic calibration, deriving performance coefficients similar to those obtained with the process using daily gauged data.

  19. The efficacy of calibrating hydrologic model using remotely sensed evapotranspiration and soil moisture for streamflow prediction

    NASA Astrophysics Data System (ADS)

    Kunnath-Poovakka, A.; Ryu, D.; Renzullo, L. J.; George, B.

    2016-04-01

    Calibration of spatially distributed hydrologic models is frequently limited by the availability of ground observations. Remotely sensed (RS) hydrologic information provides an alternative source of observations to inform models and extend modelling capability beyond the limits of ground observations. This study examines the capability of RS evapotranspiration (ET) and soil moisture (SM) in calibrating a hydrologic model and its efficacy to improve streamflow predictions. SM retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and daily ET estimates from the CSIRO MODIS ReScaled potential ET (CMRSET) are used to calibrate a simplified Australian Water Resource Assessment - Landscape model (AWRA-L) for a selection of parameters. The Shuffled Complex Evolution Uncertainty Algorithm (SCE-UA) is employed for parameter estimation at eleven catchments in eastern Australia. A subset of parameters for calibration is selected based on the variance-based Sobol' sensitivity analysis. The efficacy of 15 objective functions for calibration is assessed based on streamflow predictions relative to control cases, and relative merits of each are discussed. Synthetic experiments were conducted to examine the effect of bias in RS ET observations on calibration. The objective function containing the root mean square deviation (RMSD) of ET result in best streamflow predictions and the efficacy is superior for catchments with medium to high average runoff. Synthetic experiments revealed that accurate ET product can improve the streamflow predictions in catchments with low average runoff.

  20. 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

  1. Development of a landscape unit delineation framework for ecoy-hydrologic models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A spatially distributed representation of basin hydrology and transport processes in eco-hydrological models facilitates the identification of critical source areas and the placement of management and conservation measures. Especially floodplains are critical landscape features that differ from nei...

  2. A NEW APPROACH TO HYDROLOGIC MODELING: DERIVED DISTRIBUTIONS REVISITED. (R824780)

    EPA Science Inventory

    A fractal geometric procedure to model hydrologic (geophysical) phenomena is introduced. The method consists of using derived distributions, obtained by transforming arbitrary multinomial multifractal measures via fractal interpolating functions, to represent observed hydrologic ...

  3. Toward improved simulation of river operations through integration with a hydrologic model

    USGS Publications Warehouse

    Morway, Eric; Niswonger, Richard; Triana, Enrique

    2016-01-01

    Advanced modeling tools are needed for informed water resources planning and management. Two classes of modeling tools are often used to this end–(1) distributed-parameter hydrologic models for quantifying supply and (2) river-operation models for sorting out demands under rule-based systems such as the prior-appropriation doctrine. Within each of these two broad classes of models, there are many software tools that excel at simulating the processes specific to each discipline, but have historically over-simplified, or at worse completely neglected, aspects of the other. As a result, water managers reliant on river-operation models for administering water resources need improved tools for representing spatially and temporally varying groundwater resources in conjunctive-use systems. A new tool is described that improves the representation of groundwater/surface-water (GW-SW) interaction within a river-operations modeling context and, in so doing, advances evaluation of system-wide hydrologic consequences of new or altered management regimes.

  4. Physically based modeling in catchment hydrology at 50: Survey and outlook

    NASA Astrophysics Data System (ADS)

    Paniconi, Claudio; Putti, Mario

    2015-09-01

    Integrated, process-based numerical models in hydrology are rapidly evolving, spurred by novel theories in mathematical physics, advances in computational methods, insights from laboratory and field experiments, and the need to better understand and predict the potential impacts of population, land use, and climate change on our water resources. At the catchment scale, these simulation models are commonly based on conservation principles for surface and subsurface water flow and solute transport (e.g., the Richards, shallow water, and advection-dispersion equations), and they require robust numerical techniques for their resolution. Traditional (and still open) challenges in developing reliable and efficient models are associated with heterogeneity and variability in parameters and state variables; nonlinearities and scale effects in process dynamics; and complex or poorly known boundary conditions and initial system states. As catchment modeling enters a highly interdisciplinary era, new challenges arise from the need to maintain physical and numerical consistency in the description of multiple processes that interact over a range of scales and across different compartments of an overall system. This paper first gives an historical overview (past 50 years) of some of the key developments in physically based hydrological modeling, emphasizing how the interplay between theory, experiments, and modeling has contributed to advancing the state of the art. The second part of the paper examines some outstanding problems in integrated catchment modeling from the perspective of recent developments in mathematical and computational science.

  5. Modelling floods in the Ammer catchment: limitations and challenges with a coupled meteo-hydrological model approach

    NASA Astrophysics Data System (ADS)

    Ludwig, R.; Taschner, S.; Mauser, W.

    Numerous applications of hydrological models have shown their capability to simulate hydrological processes with a reasonable degree of certainty. For flood modelling, the quality of precipitation data — the key input parameter — is very important but often remains questionable. This paper presents a critical review of experience in the EU-funded RAPHAEL project. Different meteorological data sources were evaluated to assess their applicability for flood modelling and forecasting in the Bavarian pre-alpine catchment of the Ammer river (709 km2), for which the hydrological aspects of runoff production are described as well as the complex nature of floods. Apart from conventional rain gauge data, forecasts from several Numerical Weather Prediction Models (NWP) as well as rain radar data are examined, scaled and applied within the framework of a GIS-structured and physically based hydrological model. Multi-scenario results are compared and analysed. The synergetic approach leads to promising results under certain meteorological conditions but emphasises various drawbacks. At present, NWPs are the only source of rainfall forecasts (up to 96 hours) with large spatial coverage and high temporal resolution. On the other hand, the coarse spatial resolution of NWP grids cannot yet address, adequately, the heterogeneous structures of orographic rainfields in complex convective situations; hence, a major downscaling problem for mountain catchment applications is introduced. As shown for two selected Ammer flood events, a high variability in prediction accuracy has still to be accepted at present. Sensitivity analysis of both meteo-data input and hydrological model performance in terms of process description are discussed and positive conclusions have been drawn for future applications of an advanced meteo-hydro model synergy.

  6. A strategy for using climate data for hydrological modelling

    NASA Astrophysics Data System (ADS)

    Rust, Henning W.; Ulbrich, Uwe; Vagenas, Christos; Meredith, Edmund; Agbeko Kpogo-Nuwoklo, Komlan

    2016-04-01

    Hydrological modeling is the basis for water related impact assessment and the development of management strategies. These models are driven with meteorological data such as precipitation, temperature, wind and humidity. Depending on the nature of the problem, hydrological modelers require meteorological data with a very high spatial and temporal resolution, e.g. to a few kilometers and hours. As dynamical downscaling to such a high resolution is computationally very costly, a continuous downscaling of global climate projections is not feasible for a longer time period. For BINGO, a double-tracked strategy will be implemented to cope with this problem: 1) high resolution dynamical downscaling is limited to episodes favoring hydrological extremes and 2) conditional weather generators are used to simulated large ensembles of spatio-temporal driving fields consistent with the current or projected climate. The first track requires identification of the relevant episodes from global simulations. This is realized by clustering atmospheric variables to obtain a set of circulation patterns. Episodes containing sequences of circulation patterns associated with hydrological extremes are then further downscaled and bias corrected. The second track relies on setting up a weather generator allowing to simulate all relevant variables consistent with the recent climate. We seek to establish a link between this generator and large scale atmospheric drivers to allow simulations consistent with climate projections. While dynamical downscaling is strong in simulating meteorological driving data associated with particular events, conditional weather generators simulate a broader range of events consistent with the large scale situation. The two tracks thus complement each other.

  7. Coupled geophysical-hydrological modeling of controlled NAPL spill

    NASA Astrophysics Data System (ADS)

    Kowalsky, M. B.; Majer, E.; Peterson, J. E.; Finsterle, S.; Mazzella, A.

    2006-12-01

    Past studies have shown reasonable sensitivity of geophysical data for detecting or monitoring the movement of non-aqueous phase liquids (NAPLs) in the subsurface. However, heterogeneity in subsurface properties and in NAPL distribution commonly results in non-unique data interpretation. Combining multiple geophysical data types and incorporating constraints from hydrological models will potentially decrease the non-uniqueness in data interpretation and aid in site characterization. Large-scale laboratory experiments have been conducted over several years to evaluate the use of various geophysical methods, including ground-penetrating radar (GPR), seismic, and electrical methods, for monitoring controlled spills of tetrachloroethylene (PCE), a hazardous industrial solvent that is pervasive in the subsurface. In the current study, we consider an experiment in which PCE was introduced into a large tank containing a heterogeneous distribution of sand and clay mixtures, and allowed to migrate while time-lapse geophysical data were collected. We consider two approaches for interpreting the surface GPR and crosswell seismic data. The first approach involves (a) waveform inversion of the surface GPR data using a non-gradient based optimization algorithm to estimate the dielectric constant distributions and (b) conversion of crosswell seismic travel times to acoustic velocity distributions; the dielectric constant and acoustic velocity distributions are then related to NAPL saturation using appropriate petrophysical models. The second approach takes advantage of a recently developed framework for coupled hydrological-geophysical modeling, providing a hydrological constraint on interpretation of the geophysical data and additionally resulting in quantitative estimates of the most relevant hydrological parameters that determine NAPL behavior in the system. Specifically, we simulate NAPL migration using the multiphase multicomponent flow simulator TOUGH2 with a 2-D radial

  8. Assessing climate change impact by integrated hydrological modelling

    NASA Astrophysics Data System (ADS)

    Lajer Hojberg, Anker; Jørgen Henriksen, Hans; Olsen, Martin; der Keur Peter, van; Seaby, Lauren Paige; Troldborg, Lars; Sonnenborg, Torben; Refsgaard, Jens Christian

    2013-04-01

    Future climate may have a profound effect on the freshwater cycle, which must be taken into consideration by water management for future planning. Developments in the future climate are nevertheless uncertain, thus adding to the challenge of managing an uncertain system. To support the water managers at various levels in Denmark, the national water resources model (DK-model) (Højberg et al., 2012; Stisen et al., 2012) was used to propagate future climate to hydrological response under considerations of the main sources of uncertainty. The DK-model is a physically based and fully distributed model constructed on the basis of the MIKE SHE/MIKE11 model system describing groundwater and surface water systems and the interaction between the domains. The model has been constructed for the entire 43.000 km2 land area of Denmark only excluding minor islands. Future climate from General Circulation Models (GCM) was downscaled by Regional Climate Models (RCM) by a distribution-based scaling method (Seaby et al., 2012). The same dataset was used to train all combinations of GCM-RCMs and they were found to represent the mean and variance at the seasonal basis equally well. Changes in hydrological response were computed by comparing the short term development from the period 1990 - 2010 to 2021 - 2050, which is the time span relevant for water management. To account for uncertainty in future climate predictions, hydrological response from the DK-model using nine combinations of GCMs and RCMs was analysed for two catchments representing the various hydrogeological conditions in Denmark. Three GCM-RCM combinations displaying high, mean and low future impacts were selected as representative climate models for which climate impact studies were carried out for the entire country. Parameter uncertainty was addressed by sensitivity analysis and was generally found to be of less importance compared to the uncertainty spanned by the GCM-RCM combinations. Analysis of the simulations

  9. Distributed hydrological models: comparison between TOPKAPI, a physically based model and TETIS, a conceptually based model

    NASA Astrophysics Data System (ADS)

    Ortiz, E.; Guna, V.

    2009-04-01

    The present work aims to carry out a comparison between two distributed hydrological models, the TOPKAPI (Ciarapica and Todini, 1998; Todini and Ciarapica, 2001) and TETIS (Vélez, J. J.; Vélez J. I. and Francés, F, 2002) models, obtaining the hydrological solution computed on the basis of the same storm events. The first model is physically based and the second one is conceptually based. The analysis was performed on the 21,4 km2 Goodwin Creek watershed, located in Panola County, Mississippi. This watershed extensively monitored by the Agricultural Research Service (ARS) National Sediment Laboratory (NSL) has been chosen because it offers a complete database compiling precipitation (16 rain gauges), runoff (6 discharge stations) and GIS data. Three storm events were chosen to evaluate the performance of the two models: the first one was chosen to calibrate the models, and the other two to validate them. Both models performed a satisfactory hydrological response both in calibration and validation events. While for the TOPKAPI model it wasn't a real calibration, due to its really good performance with parameters modal values derived of watershed characteristics, for the TETIS model it has been necessary to perform a previous automatic calibration. This calibration was carried out using the data provided by the observed hydrograph, in order to adjust the modeĺs 9 correction factors. Keywords: TETIS, TOPKAPI, distributed models, hydrological response, ungauged basins.

  10. Intercomparison of hydrologic processes in global climate models

    NASA Technical Reports Server (NTRS)

    Lau, W. K.-M.; Sud, Y. C.; Kim, J.-H.

    1995-01-01

    In this report, we address the intercomparison of precipitation (P), evaporation (E), and surface hydrologic forcing (P-E) for 23 Atmospheric Model Intercomparison Project (AMIP) general circulation models (GCM's) including relevant observations, over a variety of spatial and temporal scales. The intercomparison includes global and hemispheric means, latitudinal profiles, selected area means for the tropics and extratropics, ocean and land, respectively. In addition, we have computed anomaly pattern correlations among models and observations for different seasons, harmonic analysis for annual and semiannual cycles, and rain-rate frequency distribution. We also compare the joint influence of temperature and precipitation on local climate using the Koeppen climate classification scheme.

  11. Validating a spatially distributed hydrological model with soil morphology data

    NASA Astrophysics Data System (ADS)

    Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.

    2013-10-01

    Spatially distributed hydrological models are popular tools in hydrology and they are claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time-series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for the transport of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography. Around 40% of the catchment area are artificially drained. We measured weather data, discharge and groundwater levels in 11 piezometers for 1.5 yr. For broadening the spatially distributed data sets that can be used for model calibration and validation, we translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. We used redox-morphology signs for these estimates. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to the groundwater levels in the piezometers and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the accuracy of the groundwater level predictions was not high enough to be used for the prediction of saturated areas. The groundwater

  12. Integrated hydrological SVAT model for climate change studies in Denmark

    NASA Astrophysics Data System (ADS)

    Mollerup, M.; Refsgaard, J.; Sonnenborg, T. O.

    2010-12-01

    In a major Danish funded research project (www.hyacints.dk) a coupling is being established between the HIRHAM regional climate model code from Danish Meteorological Institute and the MIKE SHE distributed hydrological model code from DHI. The linkage between those two codes is a soil vegetation atmosphere transfer scheme, which is a module of MIKE SHE. The coupled model will be established for the entire country of Denmark (43,000 km2 land area) where a MIKE SHE based hydrological model already exists (Henriksen et al., 2003, 2008). The present paper presents the MIKE SHE SVAT module and the methodology used for parameterising and calibrating the MIKE SHE SVAT module for use throughout the country. As SVAT models previously typically have been tested for research field sites with comprehensive data on energy fluxes, soil and vegetation data, the major challenge lies in parameterisation of the model when only ordinary data exist. For this purpose annual variations of vegetation characteristics (Leaf Area Index (LAI), Crop height, Root depth and the surface albedo) for different combinations of soil profiles and vegetation types have been simulated by use of the soil plant atmosphere model Daisy (Hansen et al., 1990; Abrahamsen and Hansen, 2000) has been applied. The MIKE SHE SVAT using Daisy generated surface/soil properties model has been calibrated against existing data on groundwater heads and river discharges. Simulation results in form of evapotranspiration and percolation are compared to the existing MIKE SHE model and to observations. To analyse the use of the SVAT model in climate change impact assessments data from the ENSEMBLES project (http://ensembles-eu.metoffice.com/) have been analysed to assess the impacts on reference evapotranspiration (calculated by the Makkink and the Penmann-Monteith equations) as well as on the individual elements in the Penmann-Monteith equation (radiation, wind speed, humidity and temperature). The differences on the

  13. Parallelization of a hydrological model using the message passing interface

    USGS Publications Warehouse

    Wu, Yiping; Li, Tiejian; Sun, Liqun; Chen, Ji

    2013-01-01

    With the increasing knowledge about the natural processes, hydrological models such as the Soil and Water Assessment Tool (SWAT) are becoming larger and more complex with increasing computation time. Additionally, other procedures such as model calibration, which may require thousands of model iterations, can increase running time and thus further reduce rapid modeling and analysis. Using the widely-applied SWAT as an example, this study demonstrates how to parallelize a serial hydrological model in a Windows® environment using a parallel programing technology—Message Passing Interface (MPI). With a case study, we derived the optimal values for the two parameters (the number of processes and the corresponding percentage of work to be distributed to the master process) of the parallel SWAT (P-SWAT) on an ordinary personal computer and a work station. Our study indicates that model execution time can be reduced by 42%–70% (or a speedup of 1.74–3.36) using multiple processes (two to five) with a proper task-distribution scheme (between the master and slave processes). Although the computation time cost becomes lower with an increasing number of processes (from two to five), this enhancement becomes less due to the accompanied increase in demand for message passing procedures between the master and all slave processes. Our case study demonstrates that the P-SWAT with a five-process run may reach the maximum speedup, and the performance can be quite stable (fairly independent of a project size). Overall, the P-SWAT can help reduce the computation time substantially for an individual model run, manual and automatic calibration procedures, and optimization of best management practices. In particular, the parallelization method we used and the scheme for deriving the optimal parameters in this study can be valuable and easily applied to other hydrological or environmental models.

  14. Hydrological modeling of an ungauged watershed in Southern Andes

    NASA Astrophysics Data System (ADS)

    Alarcon, Vladimir J.; Alcayaga, Hernán; Álvarez, Enrique

    2015-12-01

    In this research, MODIS MCD12Q1 land cover, and SRTM topographical datasets were used for developing hydrological models for two ungauged watersheds: Clarillo river watershed, and Los Almendros watershed. Both watersheds are located in central Chile. Coarse precipitation and stream flow data for Los Almendros catchment were used for calibration of stream flow for Los Almendros River. Acceptable fit (with R2 values ranging within 0.62 to 0.67) was achieved during calibration. The hydrological parameters were then extrapolated for Clarillo river watershed. Simulated annual mean flows for Clarillo River were then compared to annual flows reported in the literature. Simulated mean annual flows were shown to be within the range of historical means with most of the simulated flows falling between the first and third quartile of the measured means.

  15. Hierarchical Modeling of Fen Hydrology across Multiple Scales

    NASA Astrophysics Data System (ADS)

    Li, S.; Abbas, H.; Liao, H.

    2010-12-01

    Significantly increased groundwater withdrawals, intensive agriculture, and urbanization have caused a loss of biodiversity in wetland habitats; especially evident in groundwater dependent wetlands. An example of this phenomenon is Michigan’s prairie fens - habitats to some of the rarest and globally unique species, including the federally listed endangered species. Efforts to conserve and restore these groundwater dependent ecosystems are, however, hampered by lack of understanding of complex fen hydrology. In this paper, we investigate 10 carefully selected fen sites, with a goal to systematically improve our understanding of the underlying fen flow regimes, landscape connections, and how local and regional groundwater flow systems interact to control fen ecology. We achieve this by applying the Michigan “hierarchical” groundwater modeling system live-linked a GIS-based, statewide hydrological and ecological database.

  16. Obtaining high resolution polarimetric radar based precipitation estimates in Skjern catchment, Denmark for hydrological modeling

    NASA Astrophysics Data System (ADS)

    He, X.; Vejen, F.; Sonnenborg, T. O.; Jensen, K. H.

    2015-12-01

    Precipitation is the main driving force for the terrestrial water cycle and therefore plays a critical role in determining the water budget at catchment scale. Traditionally, rain gauges are used to measure precipitation on the ground surface for hydrological modeling. However, the number of rain gauges in Denmark has significantly decreased in recent years, and it is no longer possible to represent the spatial heterogeneity of rainfall only by interpolating the rain gauge data given the current gauge density in Skjern catchment, Denmark. The quality of simulated hydrological patterns using such rain gauge based products is visibly decreased. Weather radar scans the atmosphere with large areal coverage and high spatial and temporal resolution, which makes it an ideal tool to overcome this problem. The Danish Meteorological Institute (DMI) operates C-band radars over the country. It has been previously attempted to use the single-polarization radar located at Rømø to estimate precipitation in Skjern catchment; however, the hydrological improvement by adding the single-polarization radar data was marginal due to many restrictions. A new radar located at Virring with upgraded dual-polarization technology opens new possibilities to further improve the precipitation estimation at Skjern catchment. New parameters retrieved from the Virring radar will be used to develop more advanced quantitative precipitation estimation algorithms which is an important supplement to the existing algorithm called ARNE. The development of the new algorithm will be based on the Open Source Library for Weather Radar Data Processing (WRadLib). The results of hydrological models using such product are expected to better close the water budget and improve the simulated hydrological pattern such as the land surface temperature.

  17. Misrepresentation and amendment of soil moisture in conceptual hydrological modelling

    NASA Astrophysics Data System (ADS)

    Zhuo, Lu; Han, Dawei

    2016-04-01

    Although many conceptual models are very effective in simulating river runoff, their soil moisture schemes are generally not realistic in comparison with the reality (i.e., getting the right answers for the wrong reasons). This study reveals two significant misrepresentations in those models through a case study using the Xinanjiang model which is representative of many well-known conceptual hydrological models. The first is the setting of the upper limit of its soil moisture at the field capacity, due to the 'holding excess runoff' concept (i.e., runoff begins on repletion of its storage to the field capacity). The second is neglect of capillary rise of water movement. A new scheme is therefore proposed to overcome those two issues. The amended model is as effective as its original form in flow modelling, but represents more logically realistic soil water processes. The purpose of the study is to enable the hydrological model to get the right answers for the right reasons. Therefore, the new model structure has a better capability in potentially assimilating soil moisture observations to enhance its real-time flood forecasting accuracy. The new scheme is evaluated in the Pontiac catchment of the USA through a comparison with satellite observed soil moisture. The correlation between the XAJ and the observed soil moisture is enhanced significantly from 0.64 to 0.70. In addition, a new soil moisture term called SMDS (Soil Moisture Deficit to Saturation) is proposed to complement the conventional SMD (Soil Moisture Deficit).

  18. Evaluation of a hydrological model based on Bidirectional Reach (BReach)

    NASA Astrophysics Data System (ADS)

    Van Eerdenbrugh, Katrien; Van Hoey, Stijn; Verhoest, Niko E. C.

    2016-04-01

    Evaluation and discrimination of model structures is crucial to ensure an appropriate use of hydrological models. When evaluating model results by aggregating their quality in (a subset of) individual observations, overall results of this analysis sometimes conceal important detailed information about model structural deficiencies. Analyzing model results within their local (time) context can uncover this detailed information. In this research, a methodology called Bidirectional Reach (BReach) is proposed to evaluate and analyze results of a hydrological model by assessing the maximum left and right reach in each observation point that is used for model evaluation. These maximum reaches express the capability of the model to describe a subset of the evaluation data both in the direction of the previous (left) and of the following data (right). This capability is evaluated on two levels. First, on the level of individual observations, the combination of a parameter set and an observation is classified as non-acceptable if the deviation between the accompanying model result and the measurement exceeds observational uncertainty. Second, the behavior in a sequence of observations is evaluated by means of a tolerance degree. This tolerance degree expresses the condition for satisfactory model behavior in a data series and is defined by the percentage of observations within this series that can have non-acceptable model results. Based on both criteria, the maximum left and right reaches of a model in an observation represent the data points in the direction of the previous respectively the following observations beyond which none of the sampled parameter sets both are satisfactory and result in an acceptable deviation. After assessing these reaches for a variety of tolerance degrees, results can be plotted in a combined BReach plot that show temporal changes in the behavior of model results. The methodology is applied on a Probability Distributed Model (PDM) of the river

  19. Simultaneous calibration of hydrological models in geographical space

    NASA Astrophysics Data System (ADS)

    Bárdossy, András; Huang, Yingchun; Wagener, Thorsten

    2016-07-01

    Hydrological models are usually calibrated for selected catchments individually using specific performance criteria. This procedure assumes that the catchments show individual behavior. As a consequence, the transfer of model parameters to other ungauged catchments is problematic. In this paper, the possibility of transferring part of the model parameters was investigated. Three different conceptual hydrological models were considered. The models were restructured by introducing a new parameter η which exclusively controls water balances. This parameter was considered as individual to each catchment. All other parameters, which mainly control the dynamics of the discharge (dynamical parameters), were considered for spatial transfer. Three hydrological models combined with three different performance measures were used in three different numerical experiments to investigate this transferability. The first numerical experiment, involving individual calibration of the models for 15 selected MOPEX catchments, showed that it is difficult to identify which catchments share common dynamical parameters. Parameters of one catchment might be good for another catchment but not the opposite. In the second numerical experiment, a common spatial calibration strategy was used. It was explicitly assumed that the catchments share common dynamical parameters. This strategy leads to parameters which perform well on all catchments. A leave-one-out common calibration showed that in this case a good parameter transfer to ungauged catchments can be achieved. In the third numerical experiment, the common calibration methodology was applied for 96 catchments. Another set of 96 catchments was used to test the transfer of common dynamical parameters. The results show that even a large number of catchments share similar dynamical parameters. The performance is worse than those obtained by individual calibration, but the transfer to ungauged catchments remains possible. The performance of the

  20. Geomorphological Approach to Glacial and Snow Modeling applied to Hydrology

    NASA Astrophysics Data System (ADS)

    Gsell, P.; Le Moine, N.; Ribstein, P.

    2012-12-01

    Hydrological modeling of mountainous watershed has specific problems due to the effect of ice and snow cover in a certain range of altitude. The representation of the snow and ice storage dyanmics is a main issue for the understanding of mountainous hydrosystems mechanisms for future and past climate. That's also an operational concern for watersheds equipped with hydroelectric dams, whose dimensioning and electric capacity evaluation rely on a good understanding of ice-snow dynamics, in particular for a lapse of several years. The objective of the study is to get ahead, at a theoretical view, in a way in between classical representation used in hydrological models (infinity of ice stock) and 3D ice tongues modeling describing explicitly viscous glacier evolution at a river basin scale. Geomorphology will be used in this approach. Noticing that glaciers, at a catchment scale, take the drainage system as a geometrical framework, an axe of our study lies on the coupling of the probabilistic description of the river network with determinist glacier models using concepts that already have been used in hydrology modeling like Geomorphological Instantaneous Unitary Hydrogram. By analogy, a simplified glacier model (Shallow Ice Approximation or Minimal Glacier Models) will be put together as a transfer function to simulate large scale ablation and ice front dynamics. In our study, we analyze the distribution of upstream area for a dataset of 78 river basins in the Southern Rocky Mountains. In a certain range of scale and under a few assumptions, we use a statistic model for river networks description that we adapt by considering relief by linking hypsometry and morphology. The model developed P(A>a,z) allow us to identify any site of the river network from a DEM analysis via elevation z and upstream area a fields with the help of 2 parameters. The 3D consideration may be relevant for hydrologic implications as production function usually increases with relief. This model

  1. Quantifying and Generalizing Hydrologic Responses to Dam Regulation using a Statistical Modeling Approach

    SciTech Connect

    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 of 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

  2. Assimilating data from remote sensing into a high-resolution global hydrological model

    NASA Astrophysics Data System (ADS)

    Lu, Yang; Sutanudjaja, Edwin; Drost, Niels; Hut, Rolf; Steele-Dunne, Susan; van de Giesen, Nick; de Jong, Kor; van Beek, Ludovicus; Bierkens, Marc

    2014-05-01

    This study is focused on the challenges of assimilating current and planned remote sensing data into the modified PCR-GLOB-WB model to yield optimal results. The development of a high-resolution (1 km or finer) global hydrological model has been put forward as 'Grand Challenge' for the hydrological community. Extensive assimilation of remote sensing data is a promising route to constrain and ensure the accuracy of such a hydrological model, but it poses a great challenge in many aspects. Over the last 30 years, advances in remote sensing techniques have triggered the exponential growth of hydrologically useful data from remote sensing. Aside from the ICT challenge of streaming and handing the sheer volume of data, and selecting an appropriate assimilation algorithm, the fundamental questions of which datasets contain the most useful information and how to use them must be addressed. The first task is to divide the candidate datasets into those that will be assimilated and those that will be used to parameterize or force the model. As the time step is reduced from daily to ~hourly, remote sensing data may play a crucial role in providing a more dynamic description of the land surface, or in downscaling the forcing data. Here, we will present a outline of the key processes in the PCR-GLOB-WB and a summary of which states and fluxes will benefit most from assimilation, and which model parameters can be modified to incorporate real-time information from remote sensing. Finally, we need to consider the gap in spatial scales. The PCR-GLOB-WB model is now running at 10 km resolution and will be modified to run at 1 km scale, while the spatial resolution of many remote sensing products is considerably coarser. We will present an overview of the downscaling approaches under consideration for key state variables. The eWaterCycle project is a collaboration between Delft University of Technology, Utrecht University and the Netherlands eScience Center. The final aim is to

  3. A modular approach to addressing model design, scale, and parameter estimation issues in distributed hydrological modelling

    NASA Astrophysics Data System (ADS)

    Leavesley, G. H.; Markstrom, S. L.; Restrepo, P. J.; Viger, R. J.

    2002-02-01

    A modular approach to model design and construction provides a flexible framework in which to focus the multidisciplinary research and operational efforts needed to facilitate the development, selection, and application of the most robust distributed modelling methods. A variety of modular approaches have been developed, but with little consideration for compatibility among systems and concepts. Several systems are proprietary, limiting any user interaction. The US Geological Survey modular modelling system (MMS) is a modular modelling framework that uses an open source software approach to enable all members of the scientific community to address collaboratively the many complex issues associated with the design, development, and application of distributed hydrological and environmental models. Implementation of a common modular concept is not a trivial task. However, it brings the resources of a larger community to bear on the problems of distributed modelling, provides a framework in which to compare alternative modelling approaches objectively, and provides a means of sharing the latest modelling advances. The concepts and components of the MMS are described and an example application of the MMS, in a decision-support system context, is presented to demonstrate current system capabilities.

  4. A modular approach to addressing model design, scale, and parameter estimation issues in distributed hydrological modelling

    USGS Publications Warehouse

    Leavesley, G.H.; Markstrom, S.L.; Restrepo, P.J.; Viger, R.J.

    2002-01-01

    A modular approach to model design and construction provides a flexible framework in which to focus the multidisciplinary research and operational efforts needed to facilitate the development, selection, and application of the most robust distributed modelling methods. A variety of modular approaches have been developed, but with little consideration for compatibility among systems and concepts. Several systems are proprietary, limiting any user interaction. The US Geological Survey modular modelling system (MMS) is a modular modelling framework that uses an open source software approach to enable all members of the scientific community to address collaboratively the many complex issues associated with the design, development, and application of distributed hydrological and environmental models. Implementation of a common modular concept is not a trivial task. However, it brings the resources of a larger community to bear on the problems of distributed modelling, provides a framework in which to compare alternative modelling approaches objectively, and provides a means of sharing the latest modelling advances. The concepts and components of the MMS are described and an example application of the MMS, in a decision-support system context, is presented to demonstrate current system capabilities. Copyright ?? 2002 John Wiley and Sons, Ltd.

  5. A Hydrologic and Geomorphic Model of Estuary Breaching and Closure

    NASA Astrophysics Data System (ADS)

    Rich, A.; Keller, E. A.

    2012-12-01

    Many coastal estuaries are separated seasonally from the ocean by a swash-deposited beach berm. The opening of the inlet may occur by fluvial erosion of the beach berm and closure occurs when sand deposition outpaces erosion of the inlet. To better understand how the hydrology of estuaries affects breaching and closing patterns, a model is developed that incorporates an estuary hydrologic budget with a geormorphic model of the inlet system. When calibrated, the model is able to reproduce the initial seasonal breaching, seasonal closure, intermittent closures and breaches, and the low-streamflow estuary hydrology of the Carmel Lagoon, located in Central California. For two years when the estuary inlet drains directly across the beach-berm in accordance with model assumptions, the calibrated model predicts the observed 48-hour estuary stage amplitude with correlation coefficients of 0.77 and 0.65. For the calibrated model, streamflow is the predominant control on whether the estuary inlet is open or closed. In a series of sensitivity analyses, it is seen that the function of bar-built, coastal estuaries are sensitive to morphologic and hydrologic variations of the beach berm, and changes to the estuary storage itself. By varying individual components of the berm-system and estuary storage, the amount of the time the estuary is open changes -43 - 28% for the 18.2 model period. The morphology of the berm affects barrier groundwater flow, inlet hydraulics, and estuary storage. Importantly, the elevation of the berm determines the volume of water that must enter the estuary in order to breach, and it modulates the wave-overtopping flux. A high berm renders streamflow the predominant control on function and decreases the amount of time that the estuary is open by 4%, whereas a lower berm allows wave-overtopping to contribute to function and increases time open by 24%. By excavating an estuary, it will breach less frequently (-32% change in open) and store water up to 3

  6. Parameter estimation of hydrologic models using data assimilation

    NASA Astrophysics Data System (ADS)

    Kaheil, Y. H.

    2005-12-01

    The uncertainties associated with the modeling of hydrologic systems sometimes demand that data should be incorporated in an on-line fashion in order to understand the behavior of the system. This paper represents a Bayesian strategy to estimate parameters for hydrologic models in an iterative mode. The paper presents a modified technique called localized Bayesian recursive estimation (LoBaRE) that efficiently identifies the optimum parameter region, avoiding convergence to a single best parameter set. The LoBaRE methodology is tested for parameter estimation for two different types of models: a support vector machine (SVM) model for predicting soil moisture, and the Sacramento Soil Moisture Accounting (SAC-SMA) model for estimating streamflow. The SAC-SMA model has 13 parameters that must be determined. The SVM model has three parameters. Bayesian inference is used to estimate the best parameter set in an iterative fashion. This is done by narrowing the sampling space by imposing uncertainty bounds on the posterior best parameter set and/or updating the "parent" bounds based on their fitness. The new approach results in fast convergence towards the optimal parameter set using minimum training/calibration data and evaluation of fewer parameter sets. The efficacy of the localized methodology is also compared with the previously used Bayesian recursive estimation (BaRE) algorithm.

  7. Real-data Calibration Experiments On A Distributed Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Brath, A.; Montanari, A.; Toth, E.

    The increasing availability of extended information on the study watersheds does not generally overcome the need for the determination through calibration of at least a part of the parameters of distributed hydrologic models. The complexity of such models, making the computations highly intensive, has often prevented an extensive analysis of calibration issues. The purpose of this study is an evaluation of the validation results of a series of automatic calibration experiments (using the shuffled complex evolu- tion method, Duan et al., 1992) performed with a highly conceptualised, continuously simulating, distributed hydrologic model applied on the real data of a mid-sized Ital- ian watershed. Major flood events occurred in the 1990-2000 decade are simulated with the parameters obtained by the calibration of the model against discharge data observed at the closure section of the watershed and the hydrological features (overall agreement, volumes, peaks and times to peak) of the discharges obtained both in the closure and in an interior stream-gauge are analysed for validation purposes. A first set of calibrations investigates the effect of the variability of the calibration periods, using the data from several single flood events and from longer, continuous periods. Another analysis regards the influence of rainfall input and it is carried out varying the size and distribution of the raingauge network, in order to examine the relation between the spatial pattern of observed rainfall and the variability of modelled runoff. Lastly, a comparison of the hydrographs obtained for the flood events with the model parameterisation resulting when modifying the objective function to be minimised in the automatic calibration procedure is presented.

  8. Hydrologic consistency analysed through modeling at multiple time steps: does hydrological model performance benefit from finer time step information?

    NASA Astrophysics Data System (ADS)

    Ficchi, Andrea; Perrin, Charles; Andréassian, Vazken

    2015-04-01

    We investigate the operational utility of fine time step hydro-climatic information using a large catchment data set. The originality of this data set lies in the availability of precipitation data from the 6-minute rain gauges of Météo-France, and in the size of the catchment set (217 French catchments in total). The rainfall-runoff model used (GR4) has been adapted to hourly and sub-hourly time steps (up to 6-minute) from the daily time step version (Perrin et al., 2003). The model is applied at different time steps ranging from 6-minute to 1 day (6-, 12-, 30-minute, 1-, 3-, 6-, 12-hour and 1 day) and the evolution of model performance for each catchment is evaluated at the daily time step by aggregation of model outputs. Three classes of behavior are found according to the trend of model performance as the time step becomes finer: (i) catchments presenting an improvement of model performance; (ii) catchments with a model performance insensitive to the time step; (iii) catchments for which the performance even deteriorates as the time step becomes finer. The reasons behind these different trends are investigated from a hydrological point of view, by relating the model sensitivity to data at finer time step to catchment descriptors. References: Perrin, C., C. Michel and V. Andréassian (2003), "Improvement of a parsimonious model for streamflow simulation", Journal of Hydrology, 279(1-4): 275-289.

  9. Exploring Information Theory for improving Hydrologic Model Performance

    NASA Astrophysics Data System (ADS)

    Martinez Baquero, G. F.; Gupta, H. V.

    2005-12-01

    For more than 30 years, Information Theory (IT) concepts have appeared in literature and practice of hydrology in several ways. Although these concepts are implicit in many practical applications and ideas, still the language and use are not widespread among the scientific community dedicated to study hydrologic processes. At the same time, new points of view, as the shown in this session, reflect the increasing availability of data and information with finer resolution. Equally, increasing computing capabilities, the development of more complex decision-making systems, and better forecasting tools impose on hydrologists new challenges related to the optimal use of data and the information that can be extracted from it. In our understanding, one of the approaches to address these challenges is to recognize that the notion of information is inherent to the problem of dealing with hydrologic data and the evaluation of its characteristics. The goal of this poster is to evaluate how IT can be used to generate a conceptual framework for assessing the performance of models against real data, and how these assessments can help us to increase our knowledge about the physical mechanisms involved.

  10. Back to the Future: Have Remotely Sensed Digital Elevation Models Improved Hydrological Parameter Extraction?

    NASA Astrophysics Data System (ADS)

    Jarihani, B.

    2015-12-01

    Digital Elevation Models (DEMs) that accurately replicate both landscape form and processes are critical to support modeling of environmental processes. Pre-processing analysis of DEMs and extracting characteristics of the watershed (e.g., stream networks, catchment delineation, surface and subsurface flow paths) is essential for hydrological and geomorphic analysis and sediment transport. This study investigates the status of the current remotely-sensed DEMs in providing advanced morphometric information of drainage basins particularly in data sparse regions. Here we assess the accuracy of three available DEMs: (i) hydrologically corrected "H-DEM" of Geoscience Australia derived from the Shuttle Radar Topography Mission (SRTM) data; (ii) the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) version2 1-arc-second (~30 m) data; and (iii) the 9-arc-second national GEODATA DEM-9S ver3 from Geoscience Australia and the Australian National University. We used ESRI's geospatial data model, Arc Hydro and HEC-GeoHMS, designed for building hydrologic information systems to synthesize geospatial and temporal water resources data that support hydrologic modeling and analysis. A coastal catchment in northeast Australia was selected as the study site where very high resolution LiDAR data are available for parts of the area as reference data to assess the accuracy of other lower resolution datasets. This study provides morphometric information for drainage basins as part of the broad research on sediment flux from coastal basins to Great Barrier Reef, Australia. After applying geo-referencing and elevation corrections, stream and sub basins were delineated for each DEM. Then physical characteristics for streams (i.e., length, upstream and downstream elevation, and slope) and sub-basins (i.e., longest flow lengths, area, relief and slopes) were extracted and compared with reference datasets from LiDAR. Results showed that

  11. Improved understanding and prediction of the hydrologic response of highly urbanized catchments through development of the Illinois Urban Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Cantone, Joshua; Schmidt, Arthur

    2011-08-01

    What happens to the rain in highly urbanized catchments? That is the question that urban hydrologists must ask themselves when trying to integrate the hydrologic and hydraulic processes that affect the hydrologic response of urban catchments. The Illinois Urban Hydrologic Model (IUHM) has been developed to help answer this question and improve understanding and prediction of hydrologic response in highly urbanized catchments. Urban catchments are significantly different than natural watersheds, but there are similarities that allow features of the pioneering geomorphologic instantaneous unit hydrograph concept developed for natural watersheds to be adapted to the urban setting. This probabilistically based approach is a marked departure from the traditional deterministic models used to design and simulate urban sewer systems and does not have the burdensome input data requirements that detailed deterministic models possess. Application of IUHM to the CDS-51 catchment located in the village of Dolton, Illinois, highlights the model's ability to predict the hydrologic response of the catchment as well as the widely accepted SWMM model and is in accordance with observed data recorded by the United States Geological Survey. In addition, the unique structure and organization of urban sewer networks make it possible to characterize a set of ratios for urban catchments that allow IUHM to be applied when detailed input data are not available.

  12. Estimating Runoff From Roadcuts With a Distributed Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Cuhaciyan, C.; Luce, C.; Voisin, N.; Lettenmaier, D.; Black, T.

    2008-12-01

    Roads can have a substantial effect on hydrologic patterns of forested watersheds; the most noteworthy being the resurfacing of shallow groundwater at roadcuts. The influence of roads on hydrology has compelled hydrologists to include water routing and storage routines in rainfall-runoff models, such as those in the Distributed Hydrologic Soil Vegetation Model (DHSVM). We tested the ability of DHSVM to match observed runoff in roadcuts of a watershed in the Coast Range of Oregon. Eight roadcuts were instrumented using large tipping bucket gauges designed to capture only the water entering the roadside ditch from an 80-m long roadcut. The roadcuts were categorized by the topography of the upstream hillside as either swale, planar, or ridge. The simulation was run from December 2002 to December 2003 at a relatively fine spatial resolution (10-m). Average observed soil depths are 1.8-m across the watershed, below which there lies deep and highly weathered sandstone. DHSVM was designed for relatively impermeable bedrock and shallow soils; therefore it does not provide a mechanism for deep groundwater movement and storage. In the geologic setting of the study basin, however, water is routed through the sandstone allowing water to pass under roads through the parent material. For this reason a uniformly deep soil of 6.5-m with a decreased decay in conductivity with depth was used in the model to allow water to be routed beneath roadcuts that are up to 5.5-m in height. Up to three, typically shallow, soil layers can be modeled in DHSVM. We used the lowest of the three soil layers to mimic the hydraulically-well-connected sandstone exposed at deeper roadcuts. The model was calibrated against observed discharge at the outlet of the watershed. While model results closely matched the observed hydrograph at the watershed outlet, simulated runoff at an upstream gauge and the roadside ditches were varied and often higher than those observed in the field. The timing of the field

  13. Hydrologic effects of fire in sagebrush plant communities: Implications for rangeland hydrology and erosion modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Millions of dollars are spent annually in the United States mitigating fire effects on rangeland hydrology and erosion. Rangeland managers and scientists need predictive tools to simulate hydrologic processes dictating post-fire responses, assist mitigation and risk assessments, and predict post-fir...

  14. How simple can a distributed hydrological model be?

    NASA Astrophysics Data System (ADS)

    Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

    2015-04-01

    It is well known that lumped conceptual models can often reproduce catchment streamflow response with about a 'handful' of model parameters. But what is the appropriate complexity of a distributed hydrological model, in order to reproduce the distinct streamflow response of heterogeneous internal subcatchments? Is the number of identifiable parameters proportional to the number of stream gauges? Into how many pieces should the catchment be broken-up? And which model structures are best suited to represent the behavior of particular landscape units? We investigated these questions in a case study based on the Attert basin in Luxembourg, where 10 subcatchments with clean and mixed geologies and land use manifested different rainfall-runoff behavior. The hydrological response of individual subcatchments was well represented using a range of lumped models with 4-8 parameters. We then attempted to simulate the 10 streamflow time series simultaneously, using a distributed model. Existing distributed models are often perceived to be over-parameterized. In order to avoid this problem, model development followed an iterative hypothesis-testing process. We developed, calibrated and compared alternative model variants, differing in the landscape classification approach, and in the structure of components intended to represent individual landscape elements. Decisions such as how to break-up the catchment, and which structure to assign to distinct landscape elements were found to significantly influence the model's predictive performance. In the present case, we determined that a geology-based landscape classification provided the best characterization of the observed differences in streamflow responses. In addition, we found that the individual geological units could be represented by remarkably simple model structures. The overall complexity of the distributed model was of about two 'handfuls' (10) of model parameters.

  15. Input Variable Selection for Hydrologic Modeling Using Anns

    NASA Astrophysics Data System (ADS)

    Ganti, R.; Jain, A.

    2011-12-01

    The use of artificial neural network (ANN) models in water resources applications has grown considerably over the last couple of decades. In learning problems, where a connectionist network is trained with a finite sized training set, better generalization performance is often obtained when unneeded weights in the network are eliminated. One source of unneeded weights comes from the inclusion of input variables that provide little information about the output variables. Hence, in the ANN modeling methodology, one of the approaches that has received little attention, is the selection of appropriate model inputs. In the past, different methods have been used for identifying and eliminating these input variables. Normally, linear methods of Auto Correlation Function (ACF) and Partial Auto Correlation Function (PACF) have been adopted. For nonlinear physical systems e.g. hydrological systems, model inputs selected based on the linear correlation analysis among input and output variables cannot assure to capture the non-linearity in the system. In the present study, two of the non-linear methods have been explored for the Input Variable Selection (IVS). The linear method employing ACF and PACF is also used for comparison purposes. The first non-linear method utilizes a measure of the Mutual Information Criterion (MIC) to characterize the dependence between a potential model input and the output, which is a step wise input selection procedure. The second non-linear method is improvement over the first method which eliminates redundant inputs based on a partial measure of mutual information criterion (PMIC), which is also a step wise procedure. Further, the number of input variables to be considered for the development of ANN model was determined using the Principal Component Analysis (PCA), which previously used to be done by trial and error approach. The daily river flow data derived from Godavari River Basin @ Polavaram, Andhra Pradesh, India, and the daily average

  16. Can a multi-model approach improve hydrological ensemble forecasting? A study on 29 French catchments using 16 hydrological model structures

    NASA Astrophysics Data System (ADS)

    Velázquez, J. A.; Anctil, F.; Ramos, M. H.; Perrin, C.

    2011-02-01

    An operational hydrological ensemble forecasting system based on a meteorological ensemble prediction system (M-EPS) coupled with a hydrological model searches to capture the uncertainties associated with the meteorological prediction to better predict river flows. However, the structure of the hydrological model is also an important source of uncertainty that has to be taken into account. This study aims at evaluating and comparing the performance and the reliability of different types of hydrological ensemble prediction systems (H-EPS), when ensemble weather forecasts are combined with a multi-model approach. The study is based on 29 catchments in France and 16 lumped hydrological model structures, driven by the weather forecasts from the European centre for medium-range weather forecasts (ECMWF). Results show that the ensemble predictions produced by a combination of several hydrological model structures and meteorological ensembles have higher skill and reliability than ensemble predictions given either by one single hydrological model fed by weather ensemble predictions or by several hydrological models and a deterministic meteorological forecast.

  17. Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models

    NASA Astrophysics Data System (ADS)

    Mazzoleni, Maurizio; Alfonso, Leonardo; Chacon-Hurtado, Juan; Solomatine, Dimitri

    2015-09-01

    Catastrophic floods cause significant socio-economical losses. Non-structural measures, such as real-time flood forecasting, can potentially reduce flood risk. To this end, data assimilation methods have been used to improve flood forecasts by integrating static ground observations, and in some cases also remote sensing observations, within water models. Current hydrologic and hydraulic research works consider assimilation of observations coming from traditional, static sensors. At the same time, low-cost, mobile sensors and mobile communication devices are becoming also increasingly available. The main goal and innovation of this study is to demonstrate the usefulness of assimilating uncertain streamflow observations that are dynamic in space and intermittent in time in the context of two different semi-distributed hydrological model structures. The developed method is applied to the Brue basin, where the dynamic observations are imitated by the synthetic observations of discharge. The results of this study show how model structures and sensors locations affect in different ways the assimilation of streamflow observations. In addition, it proves how assimilation of such uncertain observations from dynamic sensors can provide model improvements similar to those of streamflow observations coming from a non-optimal network of static physical sensors. This can be a potential application of recent efforts to build citizen observatories of water, which can make the citizens an active part in information capturing, evaluation and communication, helping simultaneously to improvement of model-based flood forecasting.

  18. Impact of wetlands mapping on parameterization of hydrologic simulation models

    NASA Astrophysics Data System (ADS)

    Viger, R.

    2015-12-01

    Wetlands and other surface depressions can impact hydrologic response within the landscape in a number of ways, such as intercepting runoff and near-surface flows or changing the potential for evaporation and seepage into the soil. The role of these features is increasingly being integrated into hydrological simulation models, such as the USGS Precipitation-Runoff Modeling System (PRMS) and the Soil Water Assessment Tool (SWAT), and applied to landscapes where wetlands are dominating features. Because the extent of these features varies widely through time, many modeling applications rely on delineations of the maximum possible extent to define total capacity of a model's spatial response unit. This poster presents an evaluation of several wetland map delineations for the Pipestem River basin in the North Dakota Prairie-pothole region. The featured data sets include the US Fish and Wildlife Service National Wetlands Inventory (NWI), surface water bodies extracted from the US Geological Survey National Hydrography Dataset (NHD), and elevation depressions extracted from 1 meter LiDAR data for the area. In addition to characterizing differences in the quality of these datasets, the poster will assess the impact of these differences when parameters are derived from them for the spatial response units of the PRMS model.

  19. A flexible modeling package for topographically based watershed hydrology

    NASA Astrophysics Data System (ADS)

    Wang, Jun; Endreny, Theodore A.; Hassett, James M.

    2005-11-01

    An OBJect-oriented TOPographic-based (OBJTOP) hydrological model with a graphical user interface (GUI) was created using object-oriented design (OOD) methods and the objected-oriented programming (OOP) language-C++. OBJTOP presents an array of alternative TOPMODEL hydrological processes of (1) saturation excess or the mixture of infiltration/saturation excess overland flow, (2) exponential or power law decay of hydraulic conductivity with soil depth, (3) topographic index (TI) or soil topographic index (STI) weighting of run-off likelihood, and (4) simulations with or without channel routing, to explain watershed response and increase flexibility and applicability. OBJTOP utilized an object-oriented design (OOD) approach, including the 'inheritance' concept to study individual objects (or processes) at multiple levels, and the 'aggregation' concept to study the interactions of objects (or processes). Further, OOD readily provides for model extension, creating a description of hydrologic processes in a natural, direct, concise, and adaptable manner distinct from procedurally designed and implemented models. The OBJTOP GUI provides an efficient tool for data input, parameter modification, simulation scheme selection and model calibration with three objective functions, including Nash-Sutcliffe. Graphical outputs include time series plots of precipitation depth, partitioned run-off volumes, watertable depth (average or TI/STI based), and map graphics of TI, STI, and depth to watertable. Applications illustrating OBJTOP ability and flexibility include simulation of the TOPMODEL standard Slapton Wood, UK dataset, and simulation of Ward Pound Ridge, NY a small forested catchment with power function decay of hydraulic conductivity and extensive impervious surfaces.

  20. Operational use of distributed hydrological models. Experiences and challenges at a Norwegian hydropower company (Agder Energi).

    NASA Astrophysics Data System (ADS)

    Viggo Matheussen, Bernt; Andresen, Arne; Weisser, Claudia

    2014-05-01

    The Scandinavian hydropower industry has traditionally adopted the lumped conceptual hydrological model - HBV, as the tool for producing forecasts of inflows and mountain snow packs. Such forecasting systems - based on lumped conceptual models - have several drawbacks. Firstly, a lumped model does not produce spatial data, and comparisons with remote sensed snow cover data (which are now available) are complicated. Secondly, several climate parameters such as wind speed are now becoming more available and can potentially improve forecasts due to improved estimates of precipitation gauge efficiency, and more physically correct calculation of turbulent heat fluxes. At last, when the number of catchments increases, it is cumbersome and slow to run multiple hydrology models compared to running one model for all catchments. With the drawbacks of the lumped hydrology models in mind, and with inspiration from other forecasting systems using distributed models, Agder Energy decided to develop a forecasting system applying a physically based distributed model. In this paper we describe an operational inflow and snowpack forecast system developed for the Scandinavian mountain range. The system applies a modern macroscale land surface hydrology model (VIC) which in combination with historical climate data and weather predictions can be used to produce both short-term, and seasonal forecasts of inflow and mountain snowpack. Experiences with the forecast system are illustrated using results from individual subcatchments as well as aggregated regional forecasts of inflow and snowpack. Conversion of water volumes into effective energy inflow are also presented and compared to data from the Nordic hydropower system. Further on, we document several important "lessons-learned" that may be of interest to the hydrological research community. Specifically a semi-automatic data cleansing system combining spatial and temporal visualization techniques with statistical procedures are

  1. Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

    NASA Technical Reports Server (NTRS)

    Miller, L. D.; Tom, C.; Nualchawee, K.

    1977-01-01

    A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

  2. An Integrated Hydrologic Bayesian Multi-Model Combination Framework: Confronting Input, parameter and model structural uncertainty in Hydrologic Prediction

    SciTech Connect

    Ajami, N K; Duan, Q; Sorooshian, S

    2006-05-05

    This paper presents a new technique--Integrated Bayesian Uncertainty Estimator (IBUNE) to account for the major uncertainties of hydrologic rainfall-runoff predictions explicitly. The uncertainties from the input (forcing) data--mainly the precipitation observations and from the model parameters are reduced through a Monte Carlo Markov Chain (MCMC) scheme named Shuffled Complex Evolution Metropolis (SCEM) algorithm which has been extended to include a precipitation error model. Afterwards, the Bayesian Model Averaging (BMA) scheme is employed to further improve the prediction skill and uncertainty estimation using multiple model output. A series of case studies using three rainfall-runoff models to predict the streamflow in the Leaf River basin, Mississippi are used to examine the necessity and usefulness of this technique. The results suggests that ignoring either input forcings error or model structural uncertainty will lead to unrealistic model simulations and their associated uncertainty bounds which does not consistently capture and represent the real-world behavior of the watershed.

  3. Modelling the Mekong: hydrological simulation for environmental impact studies

    NASA Astrophysics Data System (ADS)

    Kite, Geoff

    2001-11-01

    The Mekong, with a basin area of almost 800,000 km 2 and a length of 4500 km, is one of the most important rivers of the world. The many lakes and wetlands along the river, including Cambodia's Tonle Sap (Grand Lac), are major sources of fish for the riparian peoples and form an important part of the regional economy. This resource may be affected by proposed developments in the basin. Using climatic, topographic and land cover data from the Internet, the semi-distributed land-use runoff process (SLURP) hydrological model was used to simulate the complete hydrological cycle of the Mekong and its tributaries. Information on dam locations and reservoir characteristics were obtained from local sources. The model was verified by comparing simulated flows with recorded daily flows for the Mekong River and by comparing simulated levels of the Tonle Sap lake with recorded daily levels. The daily computed levels of the Tonle Sap lake were then converted into flooded areas for each land cover around the lake which were then used in a fish production model to evaluate the possible impacts of basin development on the fisheries. Model outputs may also be used to investigate issues such as water allocations and the effects of land use change or climate change on water resources and the aquatic and riparian environments.

  4. Modeling Vernal Pool Hydrology and Vegetation in the Sierra Nevadas

    NASA Astrophysics Data System (ADS)

    Montrone, A. K.; Saito, L.; Weisberg, P.; Gosejohan, M.

    2012-12-01

    Vernal pools are geographic depressions with relatively impermeable substrates that are subject to four distinct seasons in mountainous regions: they fill with snow in the winter, melt into inundated pools in the spring, become unsaturated and vegetated by summer, then dry and become fully desiccated by fall. Vernal pools in California are greatly threatened. Over 90% of the pools in California have been destroyed by urbanization and other land use changes and continue to disappear with population growth. Furthermore, these pools face threats posed by climate change due to altered precipitation and temperature regimes. In the context of anthropogenic climate change, we are evaluating the direct and indirect effects of grazing management on ecohydrology and plant community structure in vernal pools Northern Sierra Nevada mountains. Hydrologic models of vernal pool basins, driven by climatic variables, are used to 1) determine if a changing climate will alter the magnitude and spatial distribution of inundation period within the pools; 2) determine how the available habitat for vernal pool vegetation specialists will change with climate change; 3) determine if increased soil compaction due to cattle grazing can help mitigate effects of climate change resulting from changes in hydraulic conductivity; and 4) determine the importance of spatial resolution in constructing the physical representation of the pools within the hydrologic models. Preliminary results from the models including calibration error metrics and hydroperiod impacts of grazing for models with varying spatial complexity will be presented.

  5. Modeling of subglacial hydrological development following rapid supraglacial lake drainage

    NASA Astrophysics Data System (ADS)

    Dow, C. F.; Kulessa, B.; Rutt, I. C.; Tsai, V. C.; Pimentel, S.; Doyle, S. H.; As, D.; Lindbäck, K.; Pettersson, R.; Jones, G. A.; Hubbard, A.

    2015-06-01

    The rapid drainage of supraglacial lakes injects substantial volumes of water to the bed of the Greenland ice sheet over short timescales. The effect of these water pulses on the development of basal hydrological systems is largely unknown. To address this, we develop a lake drainage model incorporating both (1) a subglacial radial flux element driven by elastic hydraulic jacking and (2) downstream drainage through a linked channelized and distributed system. Here we present the model and examine whether substantial, efficient subglacial channels can form during or following lake drainage events and their effect on the water pressure in the surrounding distributed system. We force the model with field data from a lake drainage site, 70 km from the terminus of Russell Glacier in West Greenland. The model outputs suggest that efficient subglacial channels do not readily form in the vicinity of the lake during rapid drainage and instead water is evacuated primarily by a transient turbulent sheet and the distributed system. Following lake drainage, channels grow but are not large enough to reduce the water pressure in the surrounding distributed system, unless preexisting channels are present throughout the domain. Our results have implications for the analysis of subglacial hydrological systems in regions where rapid lake drainage provides the primary mechanism for surface-to-bed connections.

  6. Approaches to handle data of low quality in hydrological modelling

    NASA Astrophysics Data System (ADS)

    Herma, Felix; Bárdossy, András; Hörning, Sebastian

    2015-04-01

    Hydrological modelling is an important tool for many applications in water resources engineering. It is widely used for designing storage reservoirs, flood protection measures or for prediction purposes. Therefore the quality of the required input data and the used hydrological model have a significant influence on the quality of the results and, consequently, on the reliability for the mentioned objectives above. Many factors affect the usefulness of data and models. In the first place, the number and spatial distribution of observation points build the base for all subsequent processes. Secondly, the quality of the input data, e.g. discharge, precipitation, has to be checked. It is known that rain gauge measurements underlie a high uncertainty, especially during periods with high rain intensities or snowfall. Last, the choice of the model according to the objective of its usage is the determining factor. Under such conditions a reliable assessment of the uncertainty is required. This contribution will focus on the described items and try to provide approaches on how to handle the presented problems. A hydrological model usually needs areal information of specific input data. The density and distribution of gauging stations lead to uncertainty if a spatial interpolation of the measures is applied. In the case of a high topographic variability within a catchment, uncertainties through the underestimation of rainfall amounts at exposed stations can occur. Drifts of rain or snow by wind are a central issue at this point. Common interpolation methods of precipitation are different forms of kriging which provide only the best estimate at the ungauged locations. However, these methods cannot correctly quantify the associated uncertainty of the estimation. Thus, this contribution applies a new method of random mixing of spatial random fields with the ability to incorporate equality and inequality constraints. Such conditions are applied to exposed gauging stations on

  7. Spatial interpolation schemes of daily precipitation for hydrologic modeling

    USGS Publications Warehouse

    Hwang, Y.; Clark, M.; Rajagopalan, B.; Leavesley, G.

    2012-01-01

    Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

  8. Considering complementary relationship of evaporation in Budyko's hydrological model

    NASA Astrophysics Data System (ADS)

    Han, Songjun; Shao, Weiwei

    2013-04-01

    In Budyko's hydrological model, actual evaporation was partitioned from precipitation as a function of the relative magnitude of precipitation and potential evaporation. In practice, both Penman equation and Priestley-Taylor equation have been used to estimate the potential evaporation with same Budyko curve, and they are not distinguished under Budyko framework. Nevertheless, according to the complementary relationship of evaporation, the definitions of Penman equation and Priestley-Taylor equation are absolutely different. When water availability is not limited, evaporation occurs at Priestley-Taylor's evaporation (Ew, referred to as wet environment evaporation). As the surface dries without changing the available energy, the actual and Penman's potential evaporation (Epen) rates depart from Ew with opposite changes in fluxes. So the question is: what is the difference of the Budyko's hydrological model with potential evaporation estimated by Penman or Priestley-Taylor equation? How to consider the complementary relationship in Budyko framework? In this study, for both long-term (multiyear) and annual values on water balances in the 29 non-humid catchments in the middle Yellow River Basin of China, the performances of Budyko's hydrological model with potential evaporation estimated by Epen and Ew were distinguished and compared. The catchments with larger value of Ep/Ew (ratio of Penman potential evaporation to Priestley-Taylor evaporation) are characterized with smaller evaporation ratios. The value of Ep/Ew can be served as another variable besides dryness index to partition actual evaporation from precipitation. With Priestley-Taylor equation as energy supply, an empirical formula for the parameter of the Budyko in terms of Ep/Ew and curve is proposed. Therefore, the complementary relationship of evaporation should be considered in the Budyko framework.

  9. Time-lapse, Distributed Microgravity Observations as a Tool to Inform Hydrological Models

    NASA Astrophysics Data System (ADS)

    Piccolroaz, S.; Majone, B.; Palmieri, F.; Cassiani, G.; Bellin, A.

    2014-12-01

    Thanks to significant advances in technology and modeling capabilities, the use of geophysical monitoring techniques in support of hydrological modeling showed a rapid growth over the last decades. However, at the catchment scale, the payoff in terms of model reliability has not always justified the increased experimental efforts needed in order to collect useful additional information. The objective of this work is to evaluate the advantage gained by coupling traditional hydrological data with unconventional geophysical information in inverse modeling of a complex hydrological system. In particular, we explored how the use of time-lapsed, spatially distributed micro-gravity measurements may improve the conceptual modeling of a complex catchment, allowing for an unambiguous identification of the more appropriate model and a general reduction of uncertainty. The study area is the Vermigliana catchment, a small alpine watershed located in the South-Eastern Alps, Italy. The morphology is relatively complex, being characterized by several minor valleys and ridges with elevation ranging from 950 m a.s.l. to 3558 m a.s.l. The catchment has been monitored by 13 micro-gravity stations (part of a network covering a larger area), where extensive micro-gravity measurements have been performed during 6 field campaign between 2009 and 2011. Sub-daily streamflow data are available at the Vermiglio stream gauging station (with a contributing area of 79 km2) for the same period. Once corrected to remove the effect of ocean tides and instrumental drift, micro-gravity measurements have been used as proxy of changes in the total water storage, including soil moisture, groundwater and snowpack. These data have been combined with streamflow measurements in a multi-objective optimization approach, coupling a semi-distributed hydrological model (GEOTRANSF) with a gravity model. The inclusion of microgravity data resulted in a better constraint of the inversion procedure and an improved

  10. An Integrated Multiscale Approach to River Flood Prediction Using a Land-Surface Hydrology Model

    NASA Astrophysics Data System (ADS)

    Mackey, B. P.; Barros, A. P.; Krishnamurti, T. N.

    2005-05-01

    This work outlines and demonstrates a comprehensive hydrometeorological flood forecasting system that is interdisciplinary in nature, multiscale in its approach, and state-of-the-art in its use of forecasting techniques. This integrated approach links both meteorological and hydrological tools in order to realize a more accurate prediction of major flood events three to six days in advance. One focus is on a new non-linear method to improve global multi-model superensemble precipitation forecasts with an emphasis on successful prediction of intense rain areas. On average, the skill from such a technique is higher and the bias lower than any of the individual member models, and the overall character of the precipitation distribution is maintained through the 5-day forecast period. In addition, global and nested regional spectral models are integrated in hindcast mode. Output from such models as well as from the superensemble is used as forcing input to a physically-based, spatially-distributed hydrology model in order to predict streamflow response during selected flood events. In this terrestrial hydrology prediction system, a dynamical water routing scheme and other physical parameterizations are used in conjunction with a 3-D hydrologic model that keeps track of surface water and energy budgets, including surface-subsurface interactions, groundwater and hydraulic river routing. Experiments are run for the Limpopo River basin in southeastern Africa, where massive flooding occurred in both years 2000 and 2001. An important intermediate step in this process is the downscaling of the precipitation forecasts from the course resolution atmospheric models to the much finer resolution (1 to 10 km) required by the hydrology model. For this purpose, we examined the space-time scaling behavior of simulated precipitation fields from the NWP models at different resolutions and devised a simple physically-based multifractal downscaling algorithm that relies on the scaling

  11. Modelling exploration of non-stationary hydrological system

    NASA Astrophysics Data System (ADS)

    Kim, Kue Bum; Kwon, Hyun-Han; Han, Dawei

    2015-04-01

    Traditional hydrological modelling assumes that the catchment does not change with time (i.e., stationary conditions) which means the model calibrated for the historical period is valid for the future period. However, in reality, due to change of climate and catchment conditions this stationarity assumption may not be valid in the future. It is a challenge to make the hydrological model adaptive to the future climate and catchment conditions that are not observable at the present time. In this study a lumped conceptual rainfall-runoff model called IHACRES was applied to a catchment in southwest England. Long observation data from 1961 to 2008 were used and seasonal calibration (in this study only summer period is further explored because it is more sensitive to climate and land cover change than the other three seasons) has been done since there are significant seasonal rainfall patterns. We expect that the model performance can be improved by calibrating the model based on individual seasons. The data is split into calibration and validation periods with the intention of using the validation period to represent the future unobserved situations. The success of the non-stationary model will depend not only on good performance during the calibration period but also the validation period. Initially, the calibration is based on changing the model parameters with time. Methodology is proposed to adapt the parameters using the step forward and backward selection schemes. However, in the validation both the forward and backward multiple parameter changing models failed. One problem is that the regression with time is not reliable since the trend may not be in a monotonic linear relationship with time. The second issue is that changing multiple parameters makes the selection process very complex which is time consuming and not effective in the validation period. As a result, two new concepts are explored. First, only one parameter is selected for adjustment while the other

  12. Advanced Chemistry Basins Model

    SciTech Connect

    Blanco, Mario; Cathles, Lawrence; Manhardt, Paul; Meulbroek, Peter; Tang, Yongchun

    2003-02-13

    The objective of this project is to: (1) Develop a database of additional and better maturity indicators for paleo-heat flow calibration; (2) Develop maturation models capable of predicting the chemical composition of hydrocarbons produced by a specific kerogen as a function of maturity, heating rate, etc.; assemble a compositional kinetic database of representative kerogens; (3) Develop a 4 phase equation of state-flash model that can define the physical properties (viscosity, density, etc.) of the products of kerogen maturation, and phase transitions that occur along secondary migration pathways; (4) Build a conventional basin model and incorporate new maturity indicators and data bases in a user-friendly way; (5) Develop an algorithm which combines the volume change and viscosities of the compositional maturation model to predict the chemistry of the hydrocarbons that will be expelled from the kerogen to the secondary migration pathways; (6) Develop an algorithm that predicts the flow of hydrocarbons along secondary migration pathways, accounts for mixing of miscible hydrocarbon components along the pathway, and calculates the phase fractionation that will occur as the hydrocarbons move upward down the geothermal and fluid pressure gradients in the basin; and (7) Integrate the above components into a functional model implemented on a PC or low cost workstation.

  13. Coupled Hydrological-Meteorological Modeling to Support Simulation of an Ozone Exceedance Episode over Texas

    NASA Astrophysics Data System (ADS)

    Barton, S.; Linder, K.; Stewart, A.; Peters-Lidard, C.; McHenry, J.; Coats, C.; Trayanov, A.

    2001-05-01

    Current meteorological modeling systems used to drive air quality models in support of State Implementation Planning are deficient. They often fail to adequately represent the three-dimensional evolution of the planetary boundary layer, the development and maintenance of low-level jets, and the formation, timing, location and extent of convective clouds. All of these factors contribute to failures in the modeling systems' simulations of critical air pollution episodes relied upon for policy-making purposes. Based on recent research, it is now understood that deficiencies in the underlying representation of the temporal and spatial variations in soil moisture lead to critical deficiencies in the ability of the current generation of meteorological models to reproduce complex flows and atmospheric states which modulate air quality, particularly in the weakly-forced environments typical of ozone exceedance events. We are improving upon these identified deficiencies by configuring an advanced, data-assimilating, high-resolution land-surface hydrology model (TOPLATS) to drive the overlying meteorological model (MM5) within the eight-county Houston Non-Attainment Area for the purpose of improving air quality predictions. Although our hypothesis is that appropriate modeling of soil moisture is critical for proper coupled modeling, we must rely on readily available streamflow data to validate the hydrologic predictions. Results for several validation watersheds-chosen by location, size, diversity of parameters, and available streamflow data-will be presented.

  14. Implications of complete watershed soil moisture measurements to hydrologic modeling

    NASA Technical Reports Server (NTRS)

    Engman, E. T.; Jackson, T. J.; Schmugge, T. J.

    1983-01-01

    A series of six microwave data collection flights for measuring soil moisture were made over a small 7.8 square kilometer watershed in southwestern Minnesota. These flights were made to provide 100 percent coverage of the basin at a 400 m resolution. In addition, three flight lines were flown at preselected areas to provide a sample of data at a higher resolution of 60 m. The low level flights provide considerably more information on soil moisture variability. The results are discussed in terms of reproducibility, spatial variability and temporal variability, and their implications for hydrologic modeling.

  15. Hydrological Ensemble Simulation in Huaihe Catchment Based on VIC Model

    NASA Astrophysics Data System (ADS)

    Sun, R.; Yuan, H.

    2013-12-01

    Huaihe catchment plays a very important role in the political, economic, and cultural development in China. However, hydrological disasters frequently occur in Huaihe catchment, and thus hydrological simulation in this area has very important significance. The Variable Infiltration Capacity(VIC)model, a macroscale distributed hydrological model is applied to the upper Huaihe Catchment, to simulate the discharge of the basin outlet Bengbu station from 1970 to 1999. The uncertainty in the calibration of VIC model parameters has been analyzed, and the best set of parameters in the training period of 1970~1993 is achieved using the Generalized Likelihood Uncertainty Estimation (GLUE) method. The study also addresses the influence of different likelihood functions for the parameter sensitivity as well as the uncertainty of discharge simulation. Results show that among the six chosen parameters, the soil thickness of the second layer (d2) is the most sensitive one, followed by the saturation capacity curve shape parameter (B). Moreover, the parameter selection is sensitive to different likelihood functions. For example, the soil thickness of the third layer (d3) is sensitive when using Nash coefficient as the likelihood function, while d3 is not sensitive when using relative error as the likelihood function. With the 95% confidence interval, the coverage rate of the simulated discharge versus the observed discharge is small (around 0.4), indicating that the uncertainty in the model is large. The coverage rate of selecting relative error as the likelihood function is bigger than that of selecting Nash coefficient. Based on the calibration and sensitivity studies, hydrological ensemble forecasts have been established using multiple parameter sets. The ensemble mean forecasts show better simulations than the control forecast (i.e. the simulation using the best set of parameters) for the long-term trend of discharge, while the control forecast is better in the simulation of

  16. Hydrological Response to Climate Change over the Blue Nile Basin Distributed hydrological modeling based on surrogate climate change scenarios

    NASA Astrophysics Data System (ADS)

    Berhane, F. G.; Anyah, R. O.

    2010-12-01

    The program Soil and Water Assessment Tool (SWAT2009) model has been applied to the Blue Nile Basin to study the hydrological response to surrogate climate changes over the Blue Nile Basin (Ethiopia) by downscaling gridded weather data. The specific objectives of the study include (i) examining the performance of the SWAT model in simulating hydrology-climate interactions and feedbacks within the entire Blue Nile Basin, and (ii) investigating the response of hydrological variables to surrogate climate changes. Monthly weather data from the Climate Research Unit (CRU) are converted to daily values as input into the SWAT using Monthly to Daily Weather Converter (MODAWEC). Using the program SUFI-2 (Sequential Uncertainty Fitting Algorithm), data from 1979 to 1983 are applied for sensitivity analysis and calibration (P-factor = 90%, R-factor =0.7, R2 =0.93 and NS=0.93) and subsequently to validate hindcasts over the period 1984-1989 (R2 =0.92 and NS=0.92). The period from 1960-2000 was used as baseline and has been used to determine the changes and the effect of the surrogate climate changes over the Blue Nile Basin. Overall, our surrogate climate change based simulations indicate the hydrology of the Blue Nile catchment is very sensitive to potential climate change with 100%, 34% and 51% increase to the surface runoff, lateral flow and water yield respectively for the A2 scenario surrogate. Key Words: SWAT, MODAWEC, Blue Nile Basin, SUFI-2, climate change, hydrological modeling, CRU

  17. Identification of hydrological model parameters for flood forecasting using data depth measures

    NASA Astrophysics Data System (ADS)

    Krauße, T.; Cullmann, J.

    2011-03-01

    The development of methods for estimating the parameters of hydrological models considering uncertainties has been of high interest in hydrological research over the last years. Besides the very popular Markov Chain Monte Carlo (MCMC) methods which estimate the uncertainty of model parameters in the settings of a Bayesian framework, the development of depth based sampling methods, also entitled robust parameter estimation (ROPE), have attracted an increasing research interest. These methods understand the estimation of model parameters as a geometric search of a set of robust performing parameter vectors by application of the concept of data depth. Recent studies showed that the parameter vectors estimated by depth based sampling perform more robust in validation. One major advantage of this kind of approach over the MCMC methods is that the formulation of a likelihood function within a Bayesian uncertainty framework gets obsolete and arbitrary purpose-oriented performance criteria defined by the user can be integrated without any further complications. In this paper we present an advanced ROPE method entitled the Advanced Robust Parameter Estimation by Monte Carlo algorithm (AROPEMC). The AROPEMC algorithm is a modified version of the original robust parameter estimation algorithm ROPEMC developed by Bárdossy and Singh (2008). AROPEMC performs by merging iterative Monte Carlo simulations, identifying well performing parameter vectors, the sampling of robust parameter vectors according to the principle of data depth and the application of a well-founded stopping criterion applied in supervised machine learning. The principals of the algorithm are illustrated by means of the Rosenbrock's and Rastrigin's function, two well known performance benchmarks for optimisation algorithms. Two case studies demonstrate the advantage of AROPEMC compared to state of the art global optimisation algorithms. A distributed process-oriented hydrological model is calibrated and

  18. Advanced Turbulence Modeling Concepts

    NASA Technical Reports Server (NTRS)

    Shih, Tsan-Hsing

    2005-01-01

    The ZCET program developed at NASA Glenn Research Center is to study hydrogen/air injection concepts for aircraft gas turbine engines that meet conventional gas turbine performance levels and provide low levels of harmful NOx emissions. A CFD study for ZCET program has been successfully carried out. It uses the most recently enhanced National combustion code (NCC) to perform CFD simulations for two configurations of hydrogen fuel injectors (GRC- and Sandia-injector). The results can be used to assist experimental studies to provide quick mixing, low emission and high performance fuel injector designs. The work started with the configuration of the single-hole injector. The computational models were taken from the experimental designs. For example, the GRC single-hole injector consists of one air tube (0.78 inches long and 0.265 inches in diameter) and two hydrogen tubes (0.3 inches long and 0.0226 inches in diameter opposed at 180 degree). The hydrogen tubes are located 0.3 inches upstream from the exit of the air element (the inlet location for the combustor). To do the simulation, the single-hole injector is connected to a combustor model (8.16 inches long and 0.5 inches in diameter). The inlet conditions for air and hydrogen elements are defined according to actual experimental designs. Two crossing jets of hydrogen/air are simulated in detail in the injector. The cold flow, reacting flow, flame temperature, combustor pressure and possible flashback phenomena are studied. Two grid resolutions of the numerical model have been adopted. The first computational grid contains 0.52 million elements, the second one contains over 1.3 million elements. The CFD results have shown only about 5% difference between the two grid resolutions. Therefore, the CFD result obtained from the model of 1.3-million grid resolution can be considered as a grid independent numerical solution. Turbulence models built in NCC are consolidated and well tested. They can handle both coarse and

  19. A conceptual data model coupling with physically-based distributed hydrological models based on catchment discretization schemas

    NASA Astrophysics Data System (ADS)

    Liu, Yuanming; Zhang, Wanchang; Zhang, Zhijie

    2015-11-01

    In hydrology, the data types, spatio-temporal scales and formats for physically-based distributed hydrological models and the distributed data or parameters may be different before significant data pre-processing or may change during hydrological simulation run time. A data model is devoted to these problems for sophisticated numerical hydrological modeling procedures. In this paper, we propose a conceptual data model to interpret the comprehensive, universal and complex water environmental entities. We also present an innovative integration methodology to couple the data model with physically-based distributed hydrological models (DHMs) based on catchment discretization schemas. The data model provides a reasonable framework for researchers of organizing and pre-processing water environmental spatio-temporal datasets. It also facilitates seamless data flow fluid and dynamic by hydrological response units (HRUs) as the core between the object-oriented databases and physically-based distributed hydrological models.

  20. Integrating water resources management in eco-hydrological modelling.

    PubMed

    Koch, H; Liersch, S; Hattermann, F F

    2013-01-01

    In this paper the integration of water resources management with regard to reservoir management in an eco-hydrological model is described. The model was designed to simulate different reservoir management options, such as optimized hydropower production, irrigation intake from the reservoir or optimized provisioning downstream. The integrated model can be used to investigate the impacts of climate variability/change on discharge or to study possible adaptation strategies in terms of reservoir management. The study area, the Upper Niger Basin located in the West African Sahel, is characterized by a monsoon-type climate. Rainfall and discharge regime are subject to strong seasonality. Measured data from a reservoir are used to show that the reservoir model and the integrated management options can be used to simulate the regulation of this reservoir. The inflow into the reservoir and the discharge downstream of the reservoir are quite distinctive, which points out the importance of the inclusion of water resources management. PMID:23552241

  1. Models and data for hydrological analyses - lessons learned from uncertainty

    NASA Astrophysics Data System (ADS)

    Balin, D.; Parent, E.; Goetzinger, J.; Musy, A.; Bardossy, A.; Rode, M.

    2009-04-01

    Modelling has become an unavoidable step in the hydrological analyses. Intensive monitoring of experimental or representative catchments in different environments allowed identifying of dominant processes that further enabled the choice of an appropriate model structure to be used for simulation, forecast or scenario analyses. Progresses have been done in building different modelling structures (conceptual and physically based, lumped and distributed) that are now being extensively used at different scales, with different amounts of input data and together with different calibration procedures. The present study will analyse the role of uncertainty, in a Bayesian context, as a tool to learn how input data (discharge, soil moisture, chemistry, rainfall) could be used to evaluate two semi and fully distributed modelling structures (TOPMODEL and WASIM-ETH) in two different catchments: a small (2km2) one in the Swiss Plateau region (the Haute-Mentue catchment) and a medium (100km2) one in low range mountain in central Germany (Weisse Elster catchment).

  2. Advances in Remote Sensing for Assessing High Altitude Glacio-Hydrology - with a Focus on High Mountain Asia

    NASA Astrophysics Data System (ADS)

    Bolch, T.

    2014-12-01

    Meltwater released by glaciers can be of high importance for the overall run-off and thus affect society and development of mountainous regions and their forelands. However, glaciers are mostly located in harsh and remote environment and detailed in-situ measurements are impossible or limited to few glaciers. This lack of measurements of glacier characteristics (e.g. area, debris cover, flow) and mass budgets hampers a correct glacio-hydrologic modelling and representation of processes in advanced simulation models. Remote sensing has been proven a powerful tool in providing essential data to fill this gap. The most basic information in this respect is the location and area of the glaciers. A global and some regional inventories exist, but the uncertainties and differences among them are high, especially with respect to the upper accumulation area and debris cover. I here present a multi-method approach to map glaciers more precisely based on remote sensing data and combining image ratioing (using visible, infrared and thermal bands), micro-wave coherence images, terrain analysis, differencing of digital elevation models (DEMs) and, if available, high resolution images. DEM differencing is used to provide region-wide mass balance assessments, but volume to mass conversion and data voids introduce uncertainties. For High Mountain Asia (HMA), a crucial region in terms of water resources and glacier changes, most studies concentrate on the period after the year 2000 with the SRTM-DEM as baseline data set. However, declassified satellite data from the 1960s and 1970s also exist and allowed to extend the data record back in time for several regions in HMA. Using an example from an ice-covered area of ~5000 km² in the Aksu-Tarim catchment in Central Tien Shan the importance of remote sensing for glacio-hydrological modelling is shown. This is especially true for debris-covered and surge-type glaciers whose reaction to climate is still not fully understood. Therefore

  3. Integrating 3D geological information with a national physically-based hydrological modelling system

    NASA Astrophysics Data System (ADS)

    Lewis, Elizabeth; Parkin, Geoff; Kessler, Holger; Whiteman, Mark

    2016-04-01

    Robust numerical models are an essential tool for informing flood and water management and policy around the world. Physically-based hydrological models have traditionally not been used for such applications due to prohibitively large data, time and computational resource requirements. Given recent advances in computing power and data availability, a robust, physically-based hydrological modelling system for Great Britain using the SHETRAN model and national datasets has been created. Such a model has several advantages over less complex systems. Firstly, compared with conceptual models, a national physically-based model is more readily applicable to ungauged catchments, in which hydrological predictions are also required. Secondly, the results of a physically-based system may be more robust under changing conditions such as climate and land cover, as physical processes and relationships are explicitly accounted for. Finally, a fully integrated surface and subsurface model such as SHETRAN offers a wider range of applications compared with simpler schemes, such as assessments of groundwater resources, sediment and nutrient transport and flooding from multiple sources. As such, SHETRAN provides a robust means of simulating numerous terrestrial system processes which will add physical realism when coupled to the JULES land surface model. 306 catchments spanning Great Britain have been modelled using this system. The standard configuration of this system performs satisfactorily (NSE > 0.5) for 72% of catchments and well (NSE > 0.7) for 48%. Many of the remaining 28% of catchments that performed relatively poorly (NSE < 0.5) are located in the chalk in the south east of England. As such, the British Geological Survey 3D geology model for Great Britain (GB3D) has been incorporated, for the first time in any hydrological model, to pave the way for improvements to be made to simulations of catchments with important groundwater regimes. This coupling has involved

  4. Simultaneous calibration of hydrological models in geographical space

    NASA Astrophysics Data System (ADS)

    Bárdossy, A.; Huang, Y.; Wagener, T.

    2015-10-01

    Hydrological models are usually calibrated for selected catchments individually using specific performance criteria. This procedure assumes that the catchments show individual behavior. As a consequence, the transfer of model parameters to other ungauged catchments is problematic. In this paper, the possibility of transferring part of the model parameters was investigated. Three different conceptual hydrological models were considered. The models were restructured by introducing a new parameter η which exclusively controls water balances. This parameter was considered as individual to each catchment. All other parameters, which mainly control the dynamics of the discharge (dynamical parameters), were considered for spatial transfer. Three hydrological models combined with three different performance measures were used in four different numerical experiments to investigate this transferability. The first numerical experiment, individual calibration of the models for 15 selected MOPEX catchments, showed that it is difficult to identify which catchments share common dynamical parameters. Parameters of one catchment might be good for another catchment but not reversed. In the second numerical experiment, a common spatial calibration strategy was used. It was explicitly assumed that the catchments share common dynamical parameters. This strategy leads to parameters which perform well on all catchments. A leave one out common calibration showed that in this case a good parameter transfer to ungauged catchments can be achieved. In the third numerical experiment, the common calibration methodology was applied for 96 catchments. Another set of 96 catchments were used to test the transfer of common dynamical parameters. The results show that even a large number of catchments share similar dynamical parameters. The performance is worse than those obtained by individual calibration, but the transfer to ungauged catchments remains possible. The performance of the common

  5. Hydrologic Analysis for Kankakee River Watershed Streamflow Accounting Model

    NASA Astrophysics Data System (ADS)

    Zhang, Z.; Knapp, H. V.

    2014-12-01

    Streamflow frequency is used for in-stream flow needs evaluation, water supply planning, water quality analysis, and stream classification, among other purposes. The Illinois Streamflow Accounting Model (ILSAM) was developed to predict the streamflow frequency for Illinois streams and has the capacity to explore anthropogenic impacts on streamflow frequency. Over the past two decades, ILSAM has been applied to ten major watersheds in Illinois. This study updates the hydrologic analysis for the Kankakee River watershed. The hydrologic analyses used to develop the model involved evaluating streamflow records from gaging stations and developing regional equations to estimate flows at ungaged sites throughout the watersheds. Impacts to flow quantity from dams, water supplies, and treated wastewater effluents are examined. The baseline flow condition is the flow record at gaged sites which includes historic anthropogenic effects. The unaltered flow condition, influenced primarily by climate, topography, hydrogeology, and land use, is determined by separating the effects of historic human impact. The effects of the various human modifications to flow in the basin have changed substantially over the history of the available streamflow records. The present flow condition is determined by assuming that current human impact extends back throughout the history of available streamflow records, and statistical estimates are computed accordingly. Flow frequency estimates for each gaging record are adjusted to account for differences in the period of record and other factors such as the hydrologic persistence of low flow. For ungaged sites, a regional regression based on unaltered flow conditions is developed to estimate flow frequency, and adjustments are made to account for human impacts to represent the present flow condition for all sites.

  6. One-Water Hydrologic Flow Model (MODFLOW-OWHM)

    USGS Publications Warehouse

    Hanson, Randall T.; Boyce, Scott E.; Schmid, Wolfgang; Hughes, Joseph D.; Mehl, Steffen W.; Leake, Stanley A.; Maddock, Thomas, III; Niswonger, Richard G.

    2014-01-01

    The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model (IHM) that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. Conjunctive use is the combined use of groundwater and surface water. MF-OWHM allows the simulation, analysis, and management of nearly all components of human and natural water movement and use in a physically-based supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 (MF-FMP2) combined with Local Grid Refinement (LGR) for embedded models to allow use of the Farm Process (FMP) and Streamflow Routing (SFR) within embedded grids. MF-OWHM also includes new features such as the Surface-water Routing Process (SWR), Seawater Intrusion (SWI), and Riparian Evapotrasnpiration (RIP-ET), and new solvers such as Newton-Raphson (NWT) and nonlinear preconditioned conjugate gradient (PCGN). This IHM also includes new connectivities to expand the linkages for deformation-, flow-, and head-dependent flows. Deformation-dependent flows are simulated through the optional linkage to simulated land subsidence with a vertically deforming mesh. Flow-dependent flows now include linkages between the new SWR with SFR and FMP, as well as connectivity with embedded models for SFR and FMP through LGR. Head-dependent flows now include a modified Hydrologic Flow Barrier Package (HFB) that allows optional transient HFB capabilities, and the flow between any two layers that are adjacent along a depositional or erosional boundary or displaced along a fault. MF-OWHM represents a complete operational hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for consumption by irrigated agriculture, but also of water used in urban areas and by natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply

  7. Modeling of thermally driven hydrological processes in partially saturated fractured rock

    SciTech Connect

    Tsang, Yvonne; Birkholzer, Jens; Mukhopadhyay, Sumit

    2009-03-15

    This paper is a review of the research that led to an in-depth understanding of flow and transport processes under strong heat stimulation in fractured, porous rock. It first describes the anticipated multiple processes that come into play in a partially saturated, fractured porous volcanic tuff geological formation, when it is subject to a heat source such as that originating from the decay of radionuclides. The rationale is then given for numerical modeling being a key element in the study of multiple processes that are coupled. The paper outlines how the conceptualization and the numerical modeling of the problem evolved, progressing from the simplified to the more realistic. Examples of numerical models are presented so as to illustrate the advancement and maturation of the research over the last two decades. The most recent model applied to in situ field thermal tests is characterized by (1) incorporation of a full set of thermal-hydrological processes into a numerical simulator, (2) realistic representation of the field test geometry, in three dimensions, and (3) use of site-specific characterization data for model inputs. Model predictions were carried out prior to initiation of data collection, and the model results were compared to diverse sets of measurements. The approach of close integration between modeling and field measurements has yielded a better understanding of how coupled thermal hydrological processes produce redistribution of moisture within the rock, which affects local permeability values and subsequently the flow of liquid and gases. The fluid flow in turn will change the temperature field. We end with a note on future research opportunities, specifically those incorporating chemical, mechanical, and microbiological factors into the study of thermal and hydrological processes.

  8. EFFICIENT HYDROLOGICAL TRACER-TEST DESIGN (EHTD) MODEL

    EPA Science Inventory

    Hydrological tracer testing is the most reliable diagnostic technique available for establishing flow trajectories and hydrologic connections and for determining basic hydraulic and geometric parameters necessary for establishing operative solute-transport processes. Tracer-test...

  9. Catchment Classification via Hydrologic Modeling: Evaluating the Relative Importance of Model Selection, Parameterization and Classification Techniques

    NASA Astrophysics Data System (ADS)

    Marshall, L. A.; Smith, T. J.; To, L.

    2015-12-01

    Classification has emerged as an important tool for evaluating the runoff generating mechanisms in catchments and for providing a basis on which to group catchments having similar characteristics. These methods are particularly important for transferring models from one catchment to another in the case of data scarce regions or paired catchment studies .In many cases, the goal of catchment classification is to be able to identify models or parameter sets that could be applied to similar catchments for predictive purposes. A potential impediment to this goal is the impact of error in both the classification technique and the hydrologic model. In this study, we examine the relationship between catchment classification, hydrologic models, and model parameterizations for the purpose of transferring models between similar catchments. Building on previous work using a data set of over 100 catchments from south-east Australia, we identify several hydrologic model structures and calibrate each model for each catchment. We use clustering to identify groups of catchments with similar hydrologic response (as characterized through the calibrated model parameters). We examine the dependency of the clustered catchment groups on the pre-selected model, the uncertainty in the calibrated model parameters, and the clustering or classification algorithm. Further, we investigate the relationship between the catchment clusters and certain catchment physical characteristics or signatures, which are more typically used for catchment classification. Overall, our work is aimed at elucidating the potential sources of uncertainty in catchment classification, and the utility of classification for improving hydrologic predictions.

  10. Large-scale hydrological modelling by using modified PUB recommendations: the India-HYPE case

    NASA Astrophysics Data System (ADS)

    Pechlivanidis, I. G.; Arheimer, B.

    2015-03-01

    The Prediction in Ungauged Basins (PUB) scientific initiative (2003-2012 by IAHS) put considerable effort into improving the reliability of hydrological models to predict flow response in ungauged rivers. PUB's collective experience advanced hydrologic science and defined guidelines to make predictions in catchments without observed runoff data. At present, there is a raised interest in applying catchment models for large domains and large data samples in a multi-basin manner. However, such modelling involves several sources of uncertainties, which may be caused by the imperfectness of input data, i.e. particularly regional and global databases. This may lead to inaccurate model parameterisation and incomplete process understanding. In order to bridge the gap between the best practices for single catchments and large-scale hydrology, we present a further developed and slightly modified version of the recommended best practices for PUB by Takeuchi et al. (2013). By using examples from a recent HYPE hydrological model set-up on the Indian subcontinent, named India-HYPE v1.0, we explore the recommendations, indicate challenges and recommend quality checks to avoid erroneous assumptions. We identify the obstacles, ways to overcome them and describe the work process related to: (a) errors and inconsistencies in global databases, unknown human impacts, poor data quality, (b) robust approaches to identify parameters using a stepwise calibration approach, remote sensing data, expert knowledge and catchment similarities; and (c) evaluation based on flow signatures and performance metrics, using both multiple criteria and multiple variables, and independent gauges for "blind tests". The results show that despite the strong hydro-climatic gradient over the subcontinent, a single model can adequately describe the spatial variability in dominant hydrological processes at the catchment scale. Eventually, during calibration of India-HYPE, the median Kling-Gupta Efficiency for

  11. Top-down methodology for rainfall-runoff modelling and evaluation of hydrological extremes

    NASA Astrophysics Data System (ADS)

    Willems, Patrick

    2014-05-01

    A top-down methodology is presented for implementation and calibration of a lumped conceptual catchment rainfall-runoff model that aims to produce high model performance (depending on the quality and availability of data) in terms of rainfall-runoff discharges for the full range from low to high discharges, including the peak and low flow extremes. The model is to be used to support water engineering applications, which most often deal with high and low flows as well as cumulative runoff volumes. With this application in mind, the paper wants to contribute to the above-mentioned problems and advancements on model evaluation, model-structure selection, the overparameterization problem and the long time the modeller needs to invest or the difficulties one encounters when building and calibrating a lumped conceptual model for a river catchment. The methodology is an empirical and step-wise technique that includes examination of the various model components step by step through a data-based analysis of response characteristics. The approach starts from a generalized lumped conceptual model structure. In this structure, only the general components of a lumped conceptual model, such as the existence of storage and routing elements, and their inter-links, are pre-defined. The detailed specifications on model equations and parameters are supported by advanced time series analysis of the empirical response between the rainfall and evapotranspiration inputs and the river flow output. Subresponses are separated and submodel components and related subsets of parameters are calibrated as independently as possible. At the same time, the model-structure identification process aims to reach parsimonious submodel-structures, and accounts for the serial dependency of runoff values, which typically is higher for low flows than for high flows. It also accounts for the heteroscedasticity and dependency of model residuals when evaluating the model performance. It is shown that this step

  12. A decade of advancement in understanding of rangeland hydrology and erosion and the effects of conservation practices

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Over the past decade the USDA-ARS Northwest Watershed Research Center (NWRC) has conducted extensive field research to quantify hydrologic and erosion effects of rangeland conservation practices and to develop and advance tools for rangeland assessment and management. Much of what was previously kn...

  13. 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.

  14. Techniques to Access Databases and Integrate Data for Hydrologic Modeling

    SciTech Connect

    Whelan, Gene; Tenney, Nathan D.; Pelton, Mitchell A.; Coleman, Andre M.; Ward, Duane L.; Droppo, James G.; Meyer, Philip D.; Dorow, Kevin E.; Taira, Randal Y.

    2009-06-17

    This document addresses techniques to access and integrate data for defining site-specific conditions and behaviors associated with ground-water and surface-water radionuclide transport applicable to U.S. Nuclear Regulatory Commission reviews. Environmental models typically require input data from multiple internal and external sources that may include, but are not limited to, stream and rainfall gage data, meteorological data, hydrogeological data, habitat data, and biological data. These data may be retrieved from a variety of organizations (e.g., federal, state, and regional) and source types (e.g., HTTP, FTP, and databases). Available data sources relevant to hydrologic analyses for reactor licensing are identified and reviewed. The data sources described can be useful to define model inputs and parameters, including site features (e.g., watershed boundaries, stream locations, reservoirs, site topography), site properties (e.g., surface conditions, subsurface hydraulic properties, water quality), and site boundary conditions, input forcings, and extreme events (e.g., stream discharge, lake levels, precipitation, recharge, flood and drought characteristics). Available software tools for accessing established databases, retrieving the data, and integrating it with models were identified and reviewed. The emphasis in this review was on existing software products with minimal required modifications to enable their use with the FRAMES modeling framework. The ability of four of these tools to access and retrieve the identified data sources was reviewed. These four software tools were the Hydrologic Data Acquisition and Processing System (HDAPS), Integrated Water Resources Modeling System (IWRMS) External Data Harvester, Data for Environmental Modeling Environmental Data Download Tool (D4EM EDDT), and the FRAMES Internet Database Tools. The IWRMS External Data Harvester and the D4EM EDDT were identified as the most promising tools based on their ability to access and

  15. 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

  16. ANNIE - INTERACTIVE PROCESSING OF DATA BASES FOR HYDROLOGIC MODELS.

    USGS Publications Warehouse

    Lumb, Alan M.; Kittle, John L.

    1985-01-01

    ANNIE is a data storage and retrieval system that was developed to reduce the time and effort required to calibrate, verify, and apply watershed models that continuously simulate water quantity and quality. Watershed models have three categories of input: parameters to describe segments of a drainage area, linkage of the segments, and time-series data. Additional goals for ANNIE include the development of software that is easily implemented on minicomputers and some microcomputers and software that has no special requirements for interactive display terminals. Another goal is for the user interaction to be based on the experience of the user so that ANNIE is helpful to the inexperienced user and yet efficient and brief for the experienced user. Finally, the code should be designed so that additional hydrologic models can easily be added to ANNIE.

  17. Observatories, think tanks, and community models in the hydrologic and environmental sciences: How does it affect me?

    NASA Astrophysics Data System (ADS)

    Torgersen, Thomas

    2006-06-01

    Multiple issues in hydrologic and environmental sciences are now squarely in the public focus and require both government and scientific study. Two facts also emerge: (1) The new approach being touted publicly for advancing the hydrologic and environmental sciences is the establishment of community-operated "big science" (observatories, think tanks, community models, and data repositories). (2) There have been important changes in the business of science over the last 20 years that make it important for the hydrologic and environmental sciences to demonstrate the "value" of public investment in hydrological and environmental science. Given that community-operated big science (observatories, think tanks, community models, and data repositories) could become operational, I argue that such big science should not mean a reduction in the importance of single-investigator science. Rather, specific linkages between the large-scale, team-built, community-operated big science and the single investigator should provide context data, observatory data, and systems models for a continuing stream of hypotheses by discipline-based, specialized research and a strong rationale for continued, single-PI ("discovery-based") research. I also argue that big science can be managed to provide a better means of demonstrating the value of public investment in the hydrologic and environmental sciences. Decisions regarding policy will still be political, but big science could provide an integration of the best scientific understanding as a guide for the best policy.

  18. A hydrologic and geomorphic model of estuary breaching and closure

    NASA Astrophysics Data System (ADS)

    Rich, Andrew; Keller, Edward A.

    2013-06-01

    To better understand how the hydrology of bar-built estuaries affects breaching and closing patterns, a model is developed that incorporates an estuary hydrologic budget with a geomorphic model of the inlet system. Erosion of the inlet is caused by inlet flow, whereas the only morphologic effect of waves is the deposition of sand into the inlet. When calibrated, the model is able to reproduce the initial seasonal breaching, seasonal closure, intermittent closures and breaches, and the low-streamflow (closed state) estuary hydrology of the Carmel Lagoon, located in Central California. Model performance was tested against three separate years of water-level observations. When open during these years, the inlet was visually observed to drain directly across the beach berm, in accordance with model assumptions. The calibrated model predicts the observed 48-h estuary stage amplitude with root mean square errors of 0.45 m, 0.39 m and 0.42 m for the three separate years. For the calibrated model, the probability that the estuary inlet is closed decreases exponentially with increasing inflow (streamflow plus wave overtopping), decreasing 10-fold in probability as mean daily inflow increases from 0.2 to 1.0 m3/s. Seasonal patterns of inlet state reflect the seasonal pattern of streamflow, though wave overtopping may become the main hydrologic flux during low streamflow conditions, infrequently causing short-lived breaches. In a series of sensitivity analyses it is seen that the status of the inlet and storage of water are sensitive to factors that control the storage, transmission, and inflow of water. By varying individual components of the berm system and estuary storage, the amount of the time the estuary is open may increase by 57%, or decrease by 44%, compared to the amount of time the estuary is open during calibrated model conditions for the 18.2-year model period. The individual components tested are: berm height, width, length, and hydraulic conductivity; estuary

  19. Can global hydrological models reproduce large scale river flood regimes?

    NASA Astrophysics Data System (ADS)

    Eisner, Stephanie; Flörke, Martina

    2013-04-01

    River flooding remains one of the most severe natural hazards. On the one hand, major flood events pose a serious threat to human well-being, causing deaths and considerable economic damage. On the other hand, the periodic occurrence of flood pulses is crucial to maintain the functioning of riverine floodplains and wetlands, and to preserve the ecosystem services the latter provide. In many regions, river floods reveal a distinct seasonality, i.e. they occur at a particular time during the year. This seasonality is related to regionally dominant flood generating processes which can be expressed in river flood types. While in data-rich regions (esp. Europe and North America) the analysis of flood regimes can be based on observed river discharge time series, this data is sparse or lacking in many other regions of the world. This gap of knowledge can be filled by global modeling approaches. However, to date most global modeling studies have focused on mean annual or monthly water availability and their change over time while simulating discharge extremes, both floods and droughts, still remains a challenge for large scale hydrological models. This study will explore the ability of the global hydrological model WaterGAP3 to simulate the large scale patterns of river flood regimes, represented by seasonal pattern and the dominant flood type. WaterGAP3 simulates the global terrestrial water balance on a 5 arc minute spatial grid (excluding Greenland and Antarctica) at a daily time step. The model accounts for human interference on river flow, i.e. water abstraction for various purposes, e.g. irrigation, and flow regulation by large dams and reservoirs. Our analysis will provide insight in the general ability of global hydrological models to reproduce river flood regimes and thus will promote the creation of a global map of river flood regimes to provide a spatially inclusive and comprehensive picture. Understanding present-day flood regimes can support both flood risk

  20. Inverse hydrological modelling of spatio-temporal rainfall patterns

    NASA Astrophysics Data System (ADS)

    Grundmann, Jens; Hörning, Sebastian; Bárdossy, András

    2016-04-01

    Distributed hydrological models are commonly used for simulating the non-linear response of a watershed to rainfall events for addressing different hydrological properties of the landscape. Such models are driven by spatial rainfall patterns for consecutive time steps, which are normally generated from point measurements using spatial interpolation methods. However, such methods fail in reproducing the true spatio-temporal rainfall patterns especially in data scarce regions with poorly gauged catchments or for highly dynamic, small scaled rainstorms which are not well recorded by existing monitoring networks. Consequently, uncertainties are associated with poorly identified spatio-temporal rainfall distribution in distributed rainfall-runoff-modelling since the amount of rainfall received by a catchment as well as the dynamics of the runoff generation of flood waves are underestimated. For addressing these challenges a novel methodology for inverse hydrological modelling is proposed using a Markov-Chain-Monte-Carlo framework. Thereby, potential candidates of spatio-temporal rainfall patterns are generated and selected according their ability to reproduce the observed surface runoff at the catchment outlet for a given transfer function in a best way. The Methodology combines the concept of random mixing of random spatial fields with a grid-based spatial distributed rainfall runoff model. The conditional target rainfall field is obtained as a linear combination of unconditional spatial random fields. The corresponding weights of the linear combination are selected such that the spatial variability of the rainfall amounts as well as the actual observed rainfall values are reproduced. The functionality of the methodology is demonstrated on a synthetic example. Thereby, the known spatio-temporal distribution of rainfall is reproduced for a given number of point observations of rainfall and the integral catchment response at the catchment outlet for a synthetic catchment

  1. European Continental Scale Hydrological Model, Limitations and Challenges

    NASA Astrophysics Data System (ADS)

    Rouholahnejad, E.; Abbaspour, K.

    2014-12-01

    The pressures on water resources due to increasing levels of societal demand, increasing conflict of interest and uncertainties with regard to freshwater availability create challenges for water managers and policymakers in many parts of Europe. At the same time, climate change adds a new level of pressure and uncertainty with regard to freshwater supplies. On the other hand, the small-scale sectoral structure of water management is now reaching its limits. The integrated management of water in basins requires a new level of consideration where water bodies are to be viewed in the context of the whole river system and managed as a unit within their basins. In this research we present the limitations and challenges of modelling the hydrology of the continent Europe. The challenges include: data availability at continental scale and the use of globally available data, streamgauge data quality and their misleading impacts on model calibration, calibration of large-scale distributed model, uncertainty quantification, and computation time. We describe how to avoid over parameterization in calibration process and introduce a parallel processing scheme to overcome high computation time. We used Soil and Water Assessment Tool (SWAT) program as an integrated hydrology and crop growth simulator to model water resources of the Europe continent. Different components of water resources are simulated and crop yield and water quality are considered at the Hydrological Response Unit (HRU) level. The water resources are quantified at subbasin level with monthly time intervals for the period of 1970-2006. The use of a large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation and provides the overall picture of water resources temporal and spatial distribution across the continent. The calibrated model and results provide information support to the European Water

  2. Does model structure limit the use of satellite data as hydrologic forcing for distributed operational models?

    NASA Astrophysics Data System (ADS)

    Bowman, A. L.; Franz, K.; Hogue, T. S.

    2015-12-01

    We are investigating the implications for use of satellite data in operational streamflow prediction. Specifically, the consequence of potential hydrologic model structure deficiencies on the ability to achieve improved forecast accuracy through the use of satellite data. We want to understand why advanced data do not lead to improved streamflow simulations by exploring how various fluxes and states differ among models of increasing complexity. In a series of prior studies, we investigated the use of a daily satellite-derived potential evapotranspiration (PET) estimate as input to the National Weather Service (NWS) streamflow forecast models for watersheds in the Upper Mississippi and Red river basins. Although the spatial PET product appears to represent the day-to-day variability in PET more realistically than current climatological methods used by the NWS, the impact of the satellite data on streamflow simulations results in slightly poorer model efficiency overall. Analysis of the model states indicates the model progresses differently between simulations with baseline PET and the satellite-derived PET input, though variation in streamflow simulations overall is negligible. For instance, the upper zone states, responsible for the high flows of a hydrograph, show a profound difference, while simulation of the peak flows tend to show little variation in the timing and magnitude. Using the spatial PET input, the lower zone states show improvement with simulating the recession limb and baseflow portion of the hydrograph. We anticipate that through a better understanding of the relationship between model structure, model states, and simulated streamflow we will be able to diagnose why simulations of discharge from the forecast model have failed to improve when provided seemingly more representative input data. Identifying model limitations are critical to demonstrating the full benefit of a satellite data for operational use.

  3. The Coupling and Modeling of Eco-hydrological Processes in the Upper Reaches of Heihe River

    NASA Astrophysics Data System (ADS)

    Yang, Dawen; Cong, Zhentao; Yang, Hanbo

    2013-04-01

    Developing new watershed models to couple the ecological, hydrological and social-economical processes for improving the understanding and regulation ability of the processes involved in water resources generation and transformation in the inland watersheds, is one important general scientific target of the NSFC Major Plan of "Integrated Research on the Eco-Hydrological Processes of Heihe Basin". With aims at this scientific target, the proposed research project will carry out a multi-scales and multi-processes study on eco-hydrology in the upper reaches of the Heihe River, identify the key eco-hydrological processes in the study region, develop a distributed eco-hydrological model for this region, and build a data assimilation and uncertainty analysis system for the developed model. Then this model will be used to assess the impacts of climate change and human activity on the runoff in the upper reaches of Heihe River. This study will improve the ability in simulating and predicting the runoff responses to environment changes in this basin, and also to promote the realization of the target of the NSFC Major Plan. This project will focus on the following three major researches: 1) the identification of key eco-hydrological processes and the overall structure designing of eco-hydrological model; 2) the development of distributed eco-hydrological watershed model; 3) the simulation and prediction of the eco-hydrological changes in the upper reaches of Heihe River. Through this study, it is expected to establish a benchmark eco-hydrological model for the mountainous watersheds with arid-cold climate and high elevation, where there are the most complex landscape, closely coupled ecological and hydrological system, and the most comprehensive hydrological processes. Also a breakthrough in the simulation of coupled eco-hydrological processes is expected.

  4. Hydrological modelling of slopes from field monitoring data

    NASA Astrophysics Data System (ADS)

    Comegna, Luca; Damiano, Emilia; Greco, Roberto; Guida, Andrea; Olivares, Lucio; Picarelli, Luciano

    2013-04-01

    A simplified hydrological model of a steep slope covered with loose granular pyroclastic deposits is presented. The slope is located in the mountains northern of Naples, and the soil cover, constituted by layers of loose volcanic ashes and pumices with a total thickness of 2.5m, lays upon a fractured limestone bedrock. At the interface between the bedrock and the soil cover, a layer of weathered ashes, with significant clay fraction, is sometimes observed. The slope has a fairly regular inclination of 40°, and is covered by chestnut woods and thick brushwood growing in late spring. The inclination of the slope is comparable with the internal friction angle of the ashes, thus the equilibrium is possible thanks to the contribution offered to the shear strength by the soil suction in unsaturated conditions. Indeed, in December 1999, a landslide was triggered by prolonged and intense precipitations. As it frequently happens with similar pyroclastic covers, the triggered slide exhibited a flow-like behavior, covering 2km in few minutes, heavily hitting the nearby town of Cervinara (AV). Since then, the slope has been constantly monitored, and during the last two years an automated station with seven TDR probes for the measurement of soil water content, eight tensiometers for the measurement of soil suction, and a rain gauge, has been operating. The data, collected every two hours, allowed getting more insight of the hydrological behavior of the slope and building up an effective hydrological model. In the model, the layered soil profile has been replaced with a single homogeneous layer, with water retention curve estimated by coupling the values of water content and suction measured at various depths. A seasonal top boundary condition has been introduced, related to the annual cycle of the vegetation: the observed precipitations quickly caused changes of soil suction at the depth of -50cm during the entire year, with the exception of the period between the end of May

  5. Modeling Climate Change Impacts on Landscape Evolution, Fire, and Hydrology

    NASA Astrophysics Data System (ADS)

    Sheppard, B. S.; O Connor, C.; Falk, D. A.; Garfin, G. M.

    2015-12-01

    Landscape disturbances such as wildfire interact with climate variability to influence hydrologic regimes. We coupled landscape, fire, and hydrologic models and forced them using projected climate to demonstrate climate change impacts anticipated at Fort Huachuca in southeastern Arizona, USA. The US Department of Defense (DoD) recognizes climate change as a trend that has implications for military installations, national security and global instability. The goal of this DoD Strategic Environmental Research and Development Program (SERDP) project (RC-2232) is to provide decision making tools for military installations in the southwestern US to help them adapt to the operational realities associated with climate change. For this study we coupled the spatially explicit fire and vegetation dynamics model FireBGCv2 with the Automated Geospatial Watershed Assessment tool (AGWA) to evaluate landscape vegetation change, fire disturbance, and surface runoff in response to projected climate forcing. A projected climate stream for the years 2005-2055 was developed from the Multivariate Adaptive Constructed Analogs (MACA) 4 km statistical downscaling of the CanESM2 GCM using Representative Concentration Pathway (RCP) 8.5. AGWA, an ArcGIS add-in tool, was used to automate the parameterization and execution of the Soil Water Assessment Tool (SWAT) and the KINematic runoff and EROSion2 (KINEROS2) models based on GIS layers. Landscape raster data generated by FireBGCv2 project an increase in fire and drought associated tree mortality and a decrease in vegetative basal area over the years of simulation. Preliminary results from SWAT modeling efforts show an increase to surface runoff during years following a fire, and for future winter rainy seasons. Initial results from KINEROS2 model runs show that peak runoff rates are expected to increase 10-100 fold as a result of intense rainfall falling on burned areas.

  6. Reduction of uncertainty of hydrological modelling using different precipitation inputs

    NASA Astrophysics Data System (ADS)

    Pluntke, T.; Pavlik, D.; Bernhofer, C.

    2012-04-01

    Precipitation is one of the main sources of uncertainty in hydrological modelling, due to its high temporal and spatial variability. A dense network of rain gauge stations or a combination with, e.g., radar data is needed to account for the - in comparison to other climatic elements - pronounced variability. The density of existing station-networks is low in many countries worldwide. Alternative approaches that use additional information should be applied to improve the estimation of areal precipitation. Within the project "International Research Alliance Saxony" (http://www.iwas-sachsen.ufz.de/), one subproject aims at a system analysis of a meso-scale catchment of the Western Bug in Ukraine. Effective and sustainable measures have to be identified to improve the water quality of the Western Bug under the premise of upcoming changes of climate, land use and socio economy. An exact quantification of the water balance is needed as a pre-requisite for a matter balance. This contribution demonstrates possibilities to reduce the uncertainties of water balance modelling of the catchment Kamianka-Buzka/ Western Bug (2560 km2) by applying and combining alternative precipitation inputs. Available precipitation data were undergone an extensive quality check and were bias corrected. The Soil and Water Assessment Tool (SWAT, http://swatmodel.tamu.edu/) was used for water balance modelling. By default, meteorological observations are incorporated into SWAT using the station that is nearest to the centroid of each sub-catchment. Two alternative precipitation inputs were applied: 1) Data of 20 stations were regionalized using kriging methods. 2) The output of the Regional Climate Model CCLM that was set up for the region was used. After a pre-calibration of the model, three models - having different precipitation inputs - were set up and calibrated independently applying the auto-calibration procedure Sequential Uncertainty Fitting (Abbaspour et al. 2004). The performance of the

  7. ADVANCED MIXING MODELS

    SciTech Connect

    Lee, S; Dimenna, R; Tamburello, D

    2011-02-14

    height from zero to 10 ft. The sludge has been characterized and modeled as micron-sized solids, typically 1 to 5 microns, at weight fractions as high as 20 to 30 wt%, specific gravities to 1.4, and viscosities up to 64 cp during motion. The sludge is suspended and mixed through the use of submersible slurry jet pumps. To suspend settled sludge, water is added to the tank as a slurry medium and stirred with the jet pump. Although there is considerable technical literature on mixing and solid suspension in agitated tanks, very little literature has been published on jet mixing in a large-scale tank. One of the main objectives in the waste processing is to provide feed of a uniform slurry composition at a certain weight percentage (e.g. typically {approx}13 wt% at SRS) over an extended period of time. In preparation of the sludge for slurrying, several important questions have been raised with regard to sludge suspension and mixing of the solid suspension in the bulk of the tank: (1) How much time is required to prepare a slurry with a uniform solid composition? (2) How long will it take to suspend and mix the sludge for uniform composition in any particular waste tank? (3) What are good mixing indicators to answer the questions concerning sludge mixing stated above in a general fashion applicable to any waste tank/slurry pump geometry and fluid/sludge combination?

  8. Impact of Temporal Data Resolution on Parameter Inference and Model Identification in Conceptual Hydrological Modeling: Insights from an Experimental Catchment

    NASA Astrophysics Data System (ADS)

    Fenicia, F.; Kavetski, D.; Clark, M.

    2010-12-01

    A major issue in hydrological and broader environmental modeling is the uncertainty in the observed data, in particular, the effects of sparse data sampling and averaging to temporal and spatial scales that well exceed those of many hydrological dynamics of interest. This study presents quantitative and qualitative insights into the time scale dependencies of hydrological parameters, predictions and their uncertainties, and examines the impact of the time resolution of the calibration data on the identifiable system complexity. Data from an experimental basin (Weierbach, Luxembourg) is used to analyze four conceptual models of varying complexity, over time scales of 30 min to 3 days, using several combinations of numerical implementations and inference equations. Large spurious time scale trends arise in the parameter estimates when unreliable time stepping approximations are employed, and/or when the heteroscedasticity of the model residual errors is ignored. Conversely, the use of robust numerics and more adequate (albeit still imperfect) likelihood functions markedly stabilizes the time scale dependencies and improves the identifiability of increasingly complex model structures. Parameters describing slowflow remained essentially constant over the range of sub-hourly to daily scales considered here, while parameters describing quickflow converged towards increasingly precise and stable estimates as the data resolution approached the characteristic time scale of these faster processes. These results are consistent with theoretical expectations based on numerical error analysis and data-averaging considerations. Additional diagnostics confirmed the improved ability of the more complex models to reproduce distinct signatures in the observed data. More broadly, this study provides insights into the information content of data and, through robust numerical and statistical techniques, furthers the utilization of dense-resolution data and experimental insights to

  9. ADVANCED MIXING MODELS

    SciTech Connect

    Lee, S; Richard Dimenna, R; David Tamburello, D

    2008-11-13

    The process of recovering the waste in storage tanks at the Savannah River Site (SRS) typically requires mixing the contents of the tank with one to four dual-nozzle jet mixers located within the tank. The typical criteria to establish a mixed condition in a tank are based on the number of pumps in operation and the time duration of operation. To ensure that a mixed condition is achieved, operating times are set conservatively long. This approach results in high operational costs because of the long mixing times and high maintenance and repair costs for the same reason. A significant reduction in both of these costs might be realized by reducing the required mixing time based on calculating a reliable indicator of mixing with a suitably validated computer code. The work described in this report establishes the basis for further development of the theory leading to the identified mixing indicators, the benchmark analyses demonstrating their consistency with widely accepted correlations, and the application of those indicators to SRS waste tanks to provide a better, physically based estimate of the required mixing time. Waste storage tanks at SRS contain settled sludge which varies in height from zero to 10 ft. The sludge has been characterized and modeled as micron-sized solids, typically 1 to 5 microns, at weight fractions as high as 20 to 30 wt%, specific gravities to 1.4, and viscosities up to 64 cp during motion. The sludge is suspended and mixed through the use of submersible slurry jet pumps. To suspend settled sludge, water is added to the tank as a slurry medium and stirred with the jet pump. Although there is considerable technical literature on mixing and solid suspension in agitated tanks, very little literature has been published on jet mixing in a large-scale tank. If shorter mixing times can be shown to support Defense Waste Processing Facility (DWPF) or other feed requirements, longer pump lifetimes can be achieved with associated operational cost and

  10. Testing calibration routines for LISFLOOD, a distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Pannemans, B.

    2009-04-01

    Traditionally hydrological models are considered as difficult to calibrate: their highly non-linearity results in rugged and rough response surfaces were calibration algorithms easily get stuck in local minima. For the calibration of distributed hydrological models two extra factors play an important role: on the one hand they are often costly on computation, thus restricting the feasible number of model runs; on the other hand their distributed nature smooths the response surface, thus facilitating the search for a global minimum. Lisflood is a distributed hydrological model currently used for the European Flood Alert System - EFAS (Van der Knijff et al, 2008). Its upcoming recalibration over more then 200 catchments, each with an average runtime of 2-3 minutes, proved a perfect occasion to put several existing calibration algorithms to the test. The tested routines are Downhill Simplex (DHS, Nelder and Mead, 1965), SCEUA (Duan et Al. 1993), SCEM (Vrugt et al., 2003) and AMALGAM (Vrugt et al., 2008), and they were evaluated on their capability to efficiently converge onto the global minimum and on the spread in the found solutions in repeated runs. The routines were let loose on a simple hyperbolic function, on a Lisflood catchment using model output as observation, and on two Lisflood catchments using real observations (one on the river Inn in the Alps, the other along the downstream stretch of the Elbe). On the mathematical problem and on the catchment with synthetic observations DHS proved to be the fastest and the most efficient in finding a solution. SCEUA and AMALGAM are a slower, but while SCEUA keeps converging on the exact solution, AMALGAM slows down after about 600 runs. For the Lisflood models with real-time observations AMALGAM (hybrid algorithm that combines several other algorithms, we used CMA, PSO and GA) came as fastest out of the tests, and giving comparable results in consecutive runs. However, some more work is needed to tweak the stopping

  11. Ecological Acclimation and Hydrologic Response: Problem Complexity and Modeling Challenges

    NASA Astrophysics Data System (ADS)

    Kumar, P.; Srinivasan, V.; Le, P. V. V.; Drewry, D.

    2012-04-01

    Elevated CO2 in the atmosphere leads to a number of acclimatory responses in different vegetation types. These may be characterized as structural such as vegetation height or foliage density, ecophysiological such as reduction in stomatal conductance, and biochemical such as photosynthetic down-regulation. Furthermore, the allocation of assimilated carbon to different vegetation parts such as leaves, roots, stem and seeds is also altered such that empirical allometric relations are no longer valid. The extent and nature of these acclimatory responses vary between C3 and C4 vegetation and across species. These acclimatory responses have significant impact on hydrologic fluxes both pertaining to water and energy with the possibility of large-scale hydrologic influence. Capturing the pathways of acclimatory response to provide accurate ecohydrologic response predictions requires incorporating subtle relationships that are accentuated under elevated CO2. The talk will discuss the challenges of modeling these as well as applications to soybean, maize and bioenergy crops such as switchgrass and miscanthus.

  12. Calibration by Hydrological Response Unit of a National Hydrologic Model to Improve Spatial Representation and Distribution of Parameters

    NASA Astrophysics Data System (ADS)

    Norton, P. A., II

    2015-12-01

    The U. S. Geological Survey is developing a National Hydrologic Model (NHM) to support consistent hydrologic modeling across the conterminous United States (CONUS). The Precipitation-Runoff Modeling System (PRMS) simulates daily hydrologic and energy processes in watersheds, and is used for the NHM application. For PRMS each watershed is divided into hydrologic response units (HRUs); by default each HRU is assumed to have a uniform hydrologic response. The Geospatial Fabric (GF) is a database containing initial parameter values for input to PRMS and was created for the NHM. The parameter values in the GF were derived from datasets that characterize the physical features of the entire CONUS. The NHM application is composed of more than 100,000 HRUs from the GF. Selected parameter values commonly are adjusted by basin in PRMS using an automated calibration process based on calibration targets, such as streamflow. Providing each HRU with distinct values that captures variability within the CONUS may improve simulation performance of the NHM. During calibration of the NHM by HRU, selected parameter values are adjusted for PRMS based on calibration targets, such as streamflow, snow water equivalent (SWE) and actual evapotranspiration (AET). Simulated SWE, AET, and runoff were compared to value ranges derived from multiple sources (e.g. the Snow Data Assimilation System, the Moderate Resolution Imaging Spectroradiometer (i.e. MODIS) Global Evapotranspiration Project, the Simplified Surface Energy Balance model, and the Monthly Water Balance Model). This provides each HRU with a distinct set of parameter values that captures the variability within the CONUS, leading to improved model performance. We present simulation results from the NHM after preliminary calibration, including the results of basin-level calibration for the NHM using: 1) default initial GF parameter values, and 2) parameter values calibrated by HRU.

  13. Diagnosing non-stationary behaviour in a hydrological model

    NASA Astrophysics Data System (ADS)

    Thyer, Mark; Westra, Seth; Leonard, Michael; Kavetski, Dmitri; Lambert, Martin

    2013-04-01

    The stationarity of hydrological models is increasingly being called into question, due partly to changes in land cover as well as natural and anthropogenic climate change. This issue is manifest in model parameters which change over time, creating challenges in calibration and validation (as the joint distribution of model parameters is conditional to the period used for model calibration), and in prediction when one wishes to investigate runoff properties in the future. This paper describes the incorporation of non-stationary parameters into a well established rainfall-runoff model - GR4J - using a Bayesian framework for calibration and prediction, and the use of an information theoretic approach to evaluate whether the inclusion of non-stationary parameters was justified. A subcatchment of the Onkaparinga river in South Australia was used as a case study, and it was found that GR4J parameter 'x1' varied significantly seasonally and also exhibited a longer-term increasing trend over the calibration period from 1974 to 1999. The inclusion of this non-stationary parameter in the model reduced the over-prediction in the drier validation period from 2000 to 2010 from 25% to 1.5%. Whilst including non-stationarity parameters provided substantial improvements in prediction, it is advocated that this non-stationary parameters be used as a diagnostic tool to identify model deficiencies, rather than for prediction. Techniques to reduce the non-stationarity by enhancing the model structure will to include one or more missing processes will be discussed.

  14. GIS embedded hydrological modeling: the SID&GRID project

    NASA Astrophysics Data System (ADS)

    Borsi, I.; Rossetto, R.; Schifani, C.

    2012-04-01

    The SID&GRID research project, started April 2010 and funded by Regione Toscana (Italy) under the POR FSE 2007-2013, aims to develop a Decision Support System (DSS) for water resource management and planning based on open source and public domain solutions. In order to quantitatively assess water availability in space and time and to support the planning decision processes, the SID&GRID solution consists of hydrological models (coupling 3D existing and newly developed surface- and ground-water and unsaturated zone modeling codes) embedded in a GIS interface, applications and library, where all the input and output data are managed by means of DataBase Management System (DBMS). A graphical user interface (GUI) to manage, analyze and run the SID&GRID hydrological models based on open source gvSIG GIS framework (Asociación gvSIG, 2011) and a Spatial Data Infrastructure to share and interoperate with distributed geographical data is being developed. Such a GUI is thought as a "master control panel" able to guide the user from pre-processing spatial and temporal data, running the hydrological models, and analyzing the outputs. To achieve the above-mentioned goals, the following codes have been selected and are being integrated: 1. Postgresql/PostGIS (PostGIS, 2011) for the Geo Data base Management System; 2. gvSIG with Sextante (Olaya, 2011) geo-algorithm library capabilities and Grass tools (GRASS Development Team, 2011) for the desktop GIS; 3. Geoserver and Geonetwork to share and discover spatial data on the web according to Open Geospatial Consortium; 4. new tools based on the Sextante GeoAlgorithm framework; 5. MODFLOW-2005 (Harbaugh, 2005) groundwater modeling code; 6. MODFLOW-LGR (Mehl and Hill 2005) for local grid refinement; 7. VSF (Thoms et al., 2006) for the variable saturated flow component; 8. new developed routines for overland flow; 9. new algorithms in Jython integrated in gvSIG to compute the net rainfall rate reaching the soil surface, as input for

  15. Towards realistic representation of hydrological processes in integrated WRF-urban modeling system

    NASA Astrophysics Data System (ADS)

    Yang, Jiachuan; Wang, Zhi-hua; Chen, Fei; Miao, Shiguang; Tewari, Mukul; Georgescu, Matei

    2014-05-01

    To meet the demand of the ever-increasing urbanized global population, substantial conversion of natural landscapes to urban terrains is expected in the next few decades. The landscape modification will emerge as the source of many adverse effects that challenge the environmental sustainability of cities under changing climatic patterns. To address these adverse effects and to develop corresponding adaptation/mitigation strategies, physically-based single layer urban canopy model (SLUCM) has been developed and implemented into the Weather Research and Forecasting (WRF) platform. However, due to the lack of realistic representation of urban hydrological processes, simulation of urban climatology by current coupled WRF/SLUCM is inevitably inadequate. Aiming at improving the accuracy of simulations, in this study we implement physically-based parameterization of urban hydrological processes into the model, including (1) anthropogenic latent heat, (2) urban irrigation, (3) evaporation over water-holding engineered pavements, (4) urban oasis effect, and (5) green roof. In addition, we use an advanced Monte Carlo approach to quantify the sensitivity of urban hydrological modeling to parameter uncertainties. Evaluated against field observations at four major metropolitan areas, results show that the enhanced model is significantly improved in accurately predicting turbulent fluxes arising from built surfaces, especially the latent heat flux. Case studies show that green roof is capable of reducing urban surface temperature and sensible heat flux effectively, and modifying local and regional hydroclimate. Meanwhile, it is efficient in decreasing energy loading of buildings, not only cooling demand in summers but also heating demand in winters, through the combined evaporative cooling and insulation effect. Effectiveness of green roof is found to be limited by availability of water resources and highly sensitive to surface roughness heights. The enhanced WRF/SLUCM model

  16. Spatial calibration and temporal validation of flow for regional scale hydrologic modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  17. Implications of the choice and configuration of hydrologic models on the portrayal of climate change impact

    NASA Astrophysics Data System (ADS)

    Mendoza, P. A.; Clark, M. P.; Rajagopalan, B.; Mizukami, N.; Gutmann, E. D.

    2013-12-01

    Climate change studies involve several methodological choices that impact the hydrological sensitivities obtained. Among these, hydrologic model structure selection and parameter identification are particularly relevant and usually have a strong subjective component. This subjectivity is not only limited to engineering applications, but also extends to many of our research studies, resulting in problems such as missing processes in our models, inappropriate parameterizations and compensatory effects of model parameters. The goal of this research is to identify the role of model structures and parameter values on the assessment of hydrologic sensitivity to climate change. We conduct our study in three basins located in the Colorado Headwaters Region, using four different hydrologic models (PRMS, VIC, Noah and Noah-MP). We first compare both model performance and climate sensitivities using default parameterizations and parameter values calibrated with the Shuffled Complex Evolution algorithm. Our results demonstrate that calibration doesn't necessarily improve the representation of hydrological processes or decrease inter-model differences in the change of signature measures of hydrologic behavior with respect to a future climate scenario. We found that inter-model differences in hydrologic sensitivities to climate change may be larger than the climate change signal even after models have been calibrated. Results demonstrate that both model choice (after calibration) and parameter selection have important effects in the portrayal of climate change impacts, and work is ongoing to identify more robust modeling strategies that explicitly account for the subjectivity in these choices. Location of the basins of interest Hydrological models used in this study

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

    NASA Technical Reports Server (NTRS)

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

    1976-01-01

    A hydrologic planning model is developed based on remotely sensed inputs. Data from LANDSAT 1 are used to supply the model's quantitative parameters and coefficients. The use of LANDSAT data as information input to all categories of hydrologic models requiring quantitative surface parameters for their effects functioning is also investigated.

  19. 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.

  20. Extraction Of Hydrological Parameters Using High Spatial Resolution Remote Sensing For KINEROS2 Model

    NASA Astrophysics Data System (ADS)

    Sadeh, Yuval; Blumberg, Dan G.; Cohen, Hai; Morin, Efrat; Maman, Shimrit

    2016-04-01

    Arid and semi-arid environments cover more than one-third of Earth's land surface; these environments are especially vulnerable to flash flood hazards due to the poor understanding of the phenomenon and the lack of meteorological, geomorphological, and hydrological data. For many years, catchment characteristics have been observed using point-based measurements such as rain gauges and soil sample analysis. Furthermore, flood modeling techniques are not always available in ungauged catchments or in regions where data are sparse. In comparison to point-based observations, using remote sensing technologies can provide continuous spatial hydrological parameters and variables. The advances in remote sensing technologies including weather radar-based quantitative precipitation estimation (QPE) and Earth observing satellites, provide new geo-spatial data using high spatial and temporal resolution for basin-scale geomorphological analysis and hydrological models. This study used high spatial resolution remote sensing to extract some of the main input parameters of Kinematic Runoff and Erosion Model (KINEROS2), for the arid medium size Rahaf watershed (76 km^2}), located in the Judean Desert, Israel. During the research a high resolution land cover map of Rahaf basin was created using WorldView-2 multispectral satellite imageries; surface roughness was estimated using SIR-C and COSMO-SkyMed Synthetic Aperture Radar (SAR) spaceborne sensors; and rainstorm characteristics were extracted from ground-based meteorological radar. Finally, all the remotely sensed extracted data were used as inputs for the KINEROS2 through Automated Geospatial Watershed Assessment (AGWA) tool. The model-simulated peak flow and volume were then compared to runoff measurements from the watershed's pouring point. This research demonstrates the ability of using remotely sensed extracted data as inputs for the KINEROS2 model. Using AGWA, each simulated storm was successfully calibrated, when the average

  1. Recent advances towards a theory of catchment hydrologic transport: age-ranked storage and the Ω-functions

    NASA Astrophysics Data System (ADS)

    Harman, C. J.

    2014-12-01

    Models that faithfully represent spatially-integrated hydrologic transport through the critical zone at sub-watershed scales are essential building blocks for large-scale models of land use and climate controls on non-point source contaminant delivery. A particular challenge facing these models is the need to represent the delay between inputs of soluble contaminants (such as nitrate) at the field scale, and the solute load that appears in streams. Recent advances in the theory of time-variable transit time distributions (e.g. Botter et al., GRL 38(L11403), 2011) have provided a rigorous framework for representing conservative solute transport and its coupling to hydrologic variability and partitioning. Here I will present a reformulation of this framework that offers several distinct advantages over existing formulations: 1) the derivation of the governing conservation equation is simple and intuitive, 2) the closure relations are expressed in a convenient and physically meaningful way as probability distributions Ω(ST)Omega(S_T) over the storage ranked by age STS_T, and 3) changes in transport behavior determined by storage-dependent dilution and flow-path dynamics (as distinct from those due only to changes in the rates and partitioning of water flux) are completely encapsulated by these probability distributions. The framework has been implemented to model to the rich dataset of long-term stream and precipitation chloride from the Plynlimon watershed in Wales, UK. With suitable choices for the functional form of the closure relationships, only a small number of free parameters are required to reproduce the observed chloride dynamics as well as previous models with many more parameters, including reproducing the observed fractal 1/f filtering of the streamflow chloride variability. The modeled transport dynamics are sensitive to the input precipitation variability and water balance partitioning to evapotranspiration. Apparent storage-dependent age

  2. Holistic versus monomeric strategies for hydrological modelling of modified hydrosystems

    NASA Astrophysics Data System (ADS)

    Nalbantis, I.; Efstratiadis, A.; Rozos, E.; Kopsiafti, M.; Koutsoyiannis, D.

    2010-10-01

    The modelling of modified basins that are inadequately measured constitutes a challenge for hydrological science. Often, models for such systems are detailed and hydraulics-based for only one part of the system while for other parts oversimplified models or rough assumptions are used. This is typically a bottom-up approach, which seeks to exploit knowledge of hydrological processes at the micro-scale at some components of the system. Also, it is a monomeric approach in two ways: first, essential interactions among system components may be poorly represented or even omitted; second, differences in the level of detail of process representation can lead to uncontrolled errors. Additionally, the calibration procedure merely accounts for the reproduction of the observed responses using typical fitting criteria. The paper aims to raise some critical issues, regarding the entire modelling approach for such hydrosystems. For this, two alternative modelling strategies are examined that reflect two modelling approaches or philosophies: a dominant bottom-up approach, which is also monomeric and very often, based on output information and a top-down and holistic approach based on generalized information. Critical options are examined, which codify the differences between the two strategies: the representation of surface, groundwater and water management processes, the schematization and parameterization concepts and the parameter estimation methodology. The first strategy is based on stand-alone models for surface and groundwater processes and for water management, which are employed sequentially. For each model, a different (detailed or coarse) parameterization is used, which is dictated by the hydrosystem schematization. The second strategy involves model integration for all processes, parsimonious parameterization and hybrid manual-automatic parameter optimization based on multiple objectives. A test case is examined in a hydrosystem in Greece with high complexities, such

  3. Bayesian analysis of input uncertainty in hydrological modeling: 2. Application

    NASA Astrophysics Data System (ADS)

    Kavetski, Dmitri; Kuczera, George; Franks, Stewart W.

    2006-03-01

    The Bayesian total error analysis (BATEA) methodology directly addresses both input and output errors in hydrological modeling, requiring the modeler to make explicit, rather than implicit, assumptions about the likely extent of data uncertainty. This study considers a BATEA assessment of two North American catchments: (1) French Broad River and (2) Potomac basins. It assesses the performance of the conceptual Variable Infiltration Capacity (VIC) model with and without accounting for input (precipitation) uncertainty. The results show the considerable effects of precipitation errors on the predicted hydrographs (especially the prediction limits) and on the calibrated parameters. In addition, the performance of BATEA in the presence of severe model errors is analyzed. While BATEA allows a very direct treatment of input uncertainty and yields some limited insight into model errors, it requires the specification of valid error models, which are currently poorly understood and require further work. Moreover, it leads to computationally challenging highly dimensional problems. For some types of models, including the VIC implemented using robust numerical methods, the computational cost of BATEA can be reduced using Newton-type methods.

  4. Multiobjective sensitivity analysis and optimization of distributed hydrologic model MOBIDIC

    NASA Astrophysics Data System (ADS)

    Yang, J.; Castelli, F.; Chen, Y.

    2014-10-01

    Calibration of distributed hydrologic models usually involves how to deal with the large number of distributed parameters and optimization problems with multiple but often conflicting objectives that arise in a natural fashion. This study presents a multiobjective sensitivity and optimization approach to handle these problems for the MOBIDIC (MOdello di Bilancio Idrologico DIstribuito e Continuo) distributed hydrologic model, which combines two sensitivity analysis techniques (the Morris method and the state-dependent parameter (SDP) method) with multiobjective optimization (MOO) approach ɛ-NSGAII (Non-dominated Sorting Genetic Algorithm-II). This approach was implemented to calibrate MOBIDIC with its application to the Davidson watershed, North Carolina, with three objective functions, i.e., the standardized root mean square error (SRMSE) of logarithmic transformed discharge, the water balance index, and the mean absolute error of the logarithmic transformed flow duration curve, and its results were compared with those of a single objective optimization (SOO) with the traditional Nelder-Mead simplex algorithm used in MOBIDIC by taking the objective function as the Euclidean norm of these three objectives. Results show that (1) the two sensitivity analysis techniques are effective and efficient for determining the sensitive processes and insensitive parameters: surface runoff and evaporation are very sensitive processes to all three objective functions, while groundwater recession and soil hydraulic conductivity are not sensitive and were excluded in the optimization. (2) Both MOO and SOO lead to acceptable simulations; e.g., for MOO, the average Nash-Sutcliffe value is 0.75 in the calibration period and 0.70 in the validation period. (3) Evaporation and surface runoff show similar importance for watershed water balance, while the contribution of baseflow can be ignored. (4) Compared to SOO, which was dependent on the initial starting location, MOO provides more

  5. Limits and failures in hydrology: examples and lessons learned from three decades of process oriented hydrological modelling

    NASA Astrophysics Data System (ADS)

    Bronstert, Axel

    2016-04-01

    In hydrological sciences there have been rather many attempts to develop new mathematical analysis and modelling tools. Some (or even many?) of them failed or were at least only partially successful. Unfortunately, such nun-successful attempts are hardly reported on, because our common academic recognition is based on reports about success only. With all due respect to successful attempts, the scientific community could benefit a lot from reports of unsuccessful attempts or unexpected results. Therefore, in this contribution, the author presents examples of modelling failures from his own experiences during the last three decades. Emphasis is given on results obtained from process-oriented hydrological models, where the "right answer" was obtained "for the wrong reasons". Such example comprise, for instance, modelling infiltration experiments at the plot scale, modelling runoff generation from hillslope scale and in experimental catchments and modelling runoff from glaciated catchments It is explained how the "wrong reasons" could be identified and what was learned from such failures. It is argued that failures, which causes can be identified by the modeller or anybody else, could significantly contribute to a progress in hydrological system understanding or - at least - to the identification of research needs. Identification of causes of failure may even contribute more to scientific progress then brute force modelling of parameter sensitivity and uncertainty.

  6. Connectivity as a spatial performance metric to validate simulated spatial patterns of continuous hydrological states and fluxes in distributed hydrological modelling.

    NASA Astrophysics Data System (ADS)

    Koch, Julian; Stisen, Simon

    2015-04-01

    Distributed hydrological models are traditionally evaluated against single spatially aggregated catchment scale observations, e.g. river discharge or hydraulic head data with the conviction that they are suitable measures for the simulation of spatially explicit hydrological processes within a catchment. Recent studies have shown that this is disputable and often a false conclusion and raise the demand for a model evaluation framework that focuses on distributed instead of aggregated variables, such as remotely sensed data. However no single spatial performance metric has been identified yet that proved suitable for a robust comparison of observed and simulated spatial patterns of hydrological variables, nor there exists an agreed procedure to do so. This study promotes a novel spatial performance metric which is based on a connectivity analysis. The connectivity of a continuous variable is best analyzed through a decomposition of the maps into a series of binary sets, which are based on threshold values. The probability of connection of all clusters in a specific binary set is used as a metric to describe the spatial pattern of the variable and reflects if the clusters are rather disperse or centralized. The applicability, robustness and sensitivity of the new metric are assessed by comparing simulated and observed land-surface temperature (LST) patterns. The applied model is MIKE She, a coupled, physically based and fully distributed hydrological model and the observed LST maps are derived from the MODIS sensor; 33 LST maps with full coverage are available for a 6 year simulation period of the Skjern river, the HOBE hydrological observatory in western Jutland (DK). Considering an increasing and decreasing threshold value for the decomposition of the LST maps allows to investigate the connectivity of the warm and the cold clusters individually. The evolution of the metric along an increasing and decreasing threshold value is unique for each LST map and thus allows

  7. 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

  8. Plug-and-Play Hydrologic Modeling: Is That Really Possible?

    NASA Astrophysics Data System (ADS)

    Peckham, S. D.

    2012-12-01

    The vision of a community of modelers that shares reusable and well-tested process components that can easily be linked together to create new models is very appealing. In this vision, trying a new method for modeling a physical process, comparing two methods from different groups or coupling two models together to do something new is painless and straightforward. Scientists get to spend more time on understanding the natural world, making predictions and analyzing model results. Students quickly learn how different approaches differ and how sensitive models are to various input parameters. They begin to understand how the whole system works instead of just one part of it. Believe it or not, this vision is on the verge of becoming a reality but we aren't quite there yet. In order for the hydrologic modeling community to achieve this vision and work together in this way it isn't necessary for us to drastically change the way we do things. However, we do need to agree on some minimum set of standards and these have mostly to do with providing standardized metadata decriptions of our models and our data sets. We already have great software tools for accommodating differences between models that allow them to be coupled and work together. These include tools for spatial regridding, time interpolation, unit conversion, format conversion and even computer language interoperability. But in order to write software that automatically invokes these tools when needed, we need standardized machine and human-readable metadata descriptions of our models and data sets. The purpose of this talk is to review some of the technical problems that have already been solved, including the tools mentioned above, and then explain why we need standardized metadata in order to achieve the vision of seamless model integration. A new standard called the CSDMS Standard Names that is being developed for the Community Surface Dynamics Modeling System (CSDMS) project to address this problem will

  9. An eco-hydrologic model of malaria outbreaks

    NASA Astrophysics Data System (ADS)

    Montosi, E.; Manzoni, S.; Porporato, A.; Montanari, A.

    2012-03-01

    Malaria is a geographically widespread infectious disease that is well known to be affected by climate variability at both seasonal and interannual timescales. In an effort to identify climatic factors that impact malaria dynamics, there has been considerable research focused on the development of appropriate disease models for malaria transmission and their consideration alongside climatic datasets. These analyses have focused largely on variation in temperature and rainfall as direct climatic drivers of malaria dynamics. Here, we further these efforts by considering additionally the role that soil water content may play in driving malaria incidence. Specifically, we hypothesize that hydro-climatic variability should be an important factor in controlling the availability of mosquito habitats, thereby governing mosquito growth rates. To test this hypothesis, we reduce a nonlinear eco-hydrologic model to a simple linear model through a series of consecutive assumptions and apply this model to malaria incidence data from three South African provinces. Despite the assumptions made in the reduction of the model, we show that soil water content can account for a significant portion of malaria's case variability beyond its seasonal patterns, whereas neither temperature nor rainfall alone can do so. Future work should therefore consider soil water content as a simple and computable variable for incorporation into climate-driven disease models of malaria and other vector-borne infectious diseases.

  10. A coupled energy transport and hydrological model for urban canopies

    NASA Astrophysics Data System (ADS)

    Wang, Z.; Bou-Zeid, E.; Smith, J. A.

    2011-12-01

    Urban land-atmosphere interaction has been attracting more research efforts in order to understand the complex physics of flow and mass and heat transport in urban surfaces and the lower urban atmosphere. In this work, we developed and implemented a new physically-based single-layer urban canopy model, coupling the surface exchange of energy and the subsurface transport of water/soil moisture. The new model incorporates sub-facet heterogeneity for each urban surface (roof, wall or ground). This better simulates the energy transport in urban canopy layers, especially over low-intensity built (suburban type) terrains that include a significant fraction of vegetated surfaces. We implemented detailed urban hydrological models for both natural terrains (bare soil and vegetation) and porous engineered materials with water-holding capacity (concrete, gravel, etc). The skill of the new scheme was tested against experimental data collected through a wireless sensor network deployed over the campus of Princeton University. The model performance was found to be robust and insensitive to changes in weather conditions or seasonal variability. Predictions of the volumetric soil water content were also in good agreement with field measurements, highlighting the model capability of capturing subsurface water transport for urban lawns. The new model was also applied to a case study assessing different strategies, i.e. white versus green roofs, in the mitigation of urban heat island effect.

  11. MODIS-derived Potential Evapotranspiration Estimates for Operational Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Kim, J.; Hogue, T.

    2005-12-01

    The current SACramento Soil Moisture Accounting Model (SAC-SMA), used by the National Weather Service, is the primarily model for hydrologic forecasting across the United States. Potential evapotranspiration (PET), one of the required inputs, remains rather simplistic. The model traditionally uses a regional pan evaporation estimate due to the difficulty in acquiring more sophisticated measurements. This study explores an alternative methodology using only remote sensing information to capture the monthly mean distribution of potential evapotranspiration (PET) for the SAC-SMA model. We apply a simple scheme proposed by Jiang and Islam (2005) to estimate the net radiation and estimate PET within the context of the Priestley-Taylor equation using data gathered from the MODIS Terra platform. PET estimates from the MODIS data are compared with those derived from Oklahoma Mesonet ground-based measurements and traditional pan evaporation estimates. Preliminary results will be presented for the Illinois River basin at Watts (OK) identified as part of the National Weather Service's Distributed Modeling Intercomparison Project (DMIP). The resultant streamflow simulations will illustrate the sensitivity of the SAC-SMA model to potential evaporation inputs from different sources and the possibility of the application of a stand-alone PET method for un-gauged basins.

  12. Dissection of trained neural network hydrologic models for knowledge extraction

    NASA Astrophysics Data System (ADS)

    Jain, Ashu; Kumar, Sumant

    2009-07-01

    Artificial neural networks (ANNs) are powerful tools for the modeling and forecasting of complex engineering systems and have been exploited by researchers to solve a variety of problems over the last couple of decades. In spite of their proven ability to provide superior model performance compared to traditional modeling approaches, they have not become popular among decision makers for operational use. It is probably because of their perceived black box nature that does not explain or consider the underlying physical processes involved. This paper presents the results of a study aimed at a systematic dissection of the massively parallel architectures of trained ANN hydrologic models to determine if they learn the underlying physical subprocesses during training. This has been achieved using simple qualitative and quantitative techniques. The data derived from three contrasting catchments at two different time scales were employed to develop ANN models and test the methodologies employed for knowledge extraction. The results obtained in this study indicate that the number of hidden neurons determined during training for a particular data set correspond to certain subprocesses of the overall physical process being modeled. It has been found that the time scale of the data employed has an effect on optimum ANN architecture and knowledge extracted.

  13. Hydrologic modeling of two glaciated watersheds in Northeast Pennsylvania

    USGS Publications Warehouse

    Srinivasan, M.S.; Hamlett, J.M.; Day, R.L.; Sams, J.I.; Petersen, G.W.

    1998-01-01

    A hydrologic modeling study, using the Hydrologic Simulation Program - FORTRAN (HSPF), was conducted in two glaciated watersheds, Purdy Creek and Ariel Creek in northeastern Pennsylvania. Both watersheds have wetlands and poorly drained soils due to low hydraulic conductivity and presence of fragipans. The HSPF model was calibrated in the Purdy Creek watershed and verified in the Ariel Creek watershed for June 1992 to December 1993 period. In Purdy Creek, the total volume of observed streamflow during the entire simulation period was 13.36 x 106 m3 and the simulated streamflow volume was 13.82 x 106 m3 (5 percent difference). For the verification simulation in Ariel Creek, the difference between the total observed and simulated flow volumes was 17 percent. Simulated peak flow discharges were within two hours of the observed for 30 of 46 peak flow events (discharge greater than 0.1 m3/sec) in Purdy Creek and 27 of 53 events in Ariel Creek. For 22 of the 46 events in Purdy Creek and 24 of 53 in Ariel Creek, the differences between the observed and simulated peak discharge rates were less than 30 percent. These 22 events accounted for 63 percent of total volume of streamflow observed during the selected 46 peak flow events in Purdy Creek. In Ariel Creek, these 24 peak flow events accounted for 62 percent of the total flow observed during all peak flow events. Differences in observed and simulated peak flow rates and volumes (on a percent basis) were greater during the snowmelt runoff events and summer periods than for other times.A hydrologic modeling study, using the Hydrologic Simulation Program - FORTRAN (HSPF), was conducted in two glaciated watersheds, Purdy Creek and Ariel Creek in northeastern Pennsylvania. Both watersheds have wetlands and poorly drained soils due to low hydraulic conductivity and presence of fragipans. The HSPF model was calibrated in the Purdy Creek watershed and verified in the Ariel Creek watershed for June 1992 to December 1993 period. In

  14. Test of Landsat-based urban hydrologic modeling

    NASA Technical Reports Server (NTRS)

    Jackson, T. J.; Ragan, R. M.; Fitch, W. N.

    1977-01-01

    A description is presented of the Fourmile Run Study which has been conducted to evaluate Landsat remote sensing as a method of defining input parameters required by urban hydrologic planning models. The evaluation was a part of water resource planning investigations concerning the Fourmile Run Watershed. The investigations involved an examination of the relationship between urban development and flooding for the Fourmile Run Basin. The study indicates that Landsat data provide a suitable source of land cover data for investigations conducted at the planning level. An estimation of the percentage of impervious area on the basis of Landsat data is less expensive than a use of aerial photos in planning studies. Only limited success could be achieved when Landsat data were used for smaller areal units.

  15. Changes in catchment hydrology in relation to vegetation recovery: a comparative modelling experiment

    NASA Astrophysics Data System (ADS)

    Lana-Renault, Noemí; Karssenberg, Derek; Latron, Jérôme; Serrano, Mā Pilar; Regüés, David; Bierkens, Marc F. P.

    2010-05-01

    experiment aims at separating the effect of land cover from other differences (e.g. catchment area, morphology) between the two catchments. This approach allows us to make general statements on effects of land cover, required for future predictions for larger areas. In our modelling experiment, a process-based distributed hydrological model is used for the two catchments. First, we calibrate the model using data from the two catchments until a single set of parameters valid for both is found. With this set of parameters and considering a given meteorological driver (due to their proximity, it can be considered the same for both catchments), runoff at the outlet of each catchment is simulated. Land cover is then swapped between catchments and a new runoff simulation is performed for each "swapped" catchment, using the same set of parameters and the same meteorological driver. The effects of the land cover change are determined by analysing the differences between the first and the "swapped" simulations. This study is based on an analysis of the hydrological differences of two catchments with different history of land use, and a comparative modelling experiment applied to them. Following this approach, we attempt to advance our understanding of the effects of land-use/land-cover changes in catchment hydrology and, ultimately, anticipate their hydrological consequences under a future re-vegetation scenario.

  16. An attempt of ensemble modelling of future hydrological regime for selected river basin.

    NASA Astrophysics Data System (ADS)

    Valainis, A.; Timuhin, A.; Bethers, U.

    2009-04-01

    Ensemble modelling of hydrological regime may refer to usage of different Regional Climate Models (RCMs) coupled with one hydrological model, or usage of one RCM coupled with multiple hydrological models. Our goal was to examine future flow regimes based on different hydrological models. We conducted a river basin study based on one particular subbasin (Berze) of the river Lielupe basin. Lielupe is a lowland river with basin area of 17000 sq.km, situated in Latvia and Lithuania. Area of chosen subbasin is approximately 1000 sq.km. Ensemble of hydrological models consisted of MIKE SHE, and MIKE BASIN by DHI, the runoff model embedded in RCM, and in-house FiBasin model. MIKE SHE is grid based distributed hydrological model coupled with MIKE 11 flow routing model. MIKE Basin has embedded, conceptual catchment based NAM model. FiBasin is spatially distributed, finite volume based hydrological model with hydraulic routing network. The RCM and climate change scenarios are provided by Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects (PRUDENCE) project. Time period for climate change scenarios is 2071-2100. The different responses from climate change, using different calibration sets where evaluated. The uncertainty related to choice of hydrological models is evaluated. It is found that the choice of hydrological model can lead to uncertainty witch is comparable with the even to difference between the climate scenarios, or the climate change itself. This conclusion is valid for the area of study in which the expected change of the hydrological regime is rather small.

  17. Physically based modelling of alpine snow hydrology in the Canadian Rockies (Invited)

    NASA Astrophysics Data System (ADS)

    Pomeroy, J. W.; Debeer, C.; MacDonald, M. K.; Fang, X.; Hopkinson, C.

    2010-12-01

    Field, remote sensing and modelling studies at Marmot Creek Research Basin in the Canadian Rocky Mountain have been directed to advance the understanding of snow processes and to improve hydrological models of snow and streamflow. Physically based approaches are used due to the ungauged nature of most basins in the region. Physically based models can take advantage of remote sensing information for parameter selection, reducing the need for calibration of parameters from streamflow observations. Modelling studies of blowing snow over alpine terrain show that the spatial distributions of snow water equivalent in complex environments can be predicted with reasonable accuracy. An important new feature is the application of the model to aggregated landscape units (Hydrological Response Units or HRU) having common physiographic and aerodynamic characteristics; these landscape units require much less physiographic information than do fully spatially distributed blowing snow models and are suitable to application in remote alpine regions with sparse data. Alpine HRU can be easily distinguished using remote sensing information such as LiDAR estimated snow depths, or snow covered area during melt from visible spectrum high resolution imagery. Snow ablation studies have focussed on application of the energy balance to estimate snowmelt over landscape units with consideration of sub-unit depletion of snow covered area. In this case, HRU are segregated based on both snow accumulation characteristics and applied melt energy fluxes. Some indication of the spatial variability of snow accumulation is needed to estimate snow ablation and snow covered area depletion. Again, LiDAR estimated snow depths can be used to estimate the variability of snow accumulation and this parameter can then be used in calculating the shape of snowcovered area depletion curves. The calculated melt rates agree well with observations from snow surveys. Improved algorithms resulting from this application

  18. Hydrological excitation of polar motion by different variables from the GLDAS model

    NASA Astrophysics Data System (ADS)

    Wińska, Małgorzata; Nastula, Jolanta; Salstein, David

    2015-04-01

    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) model of the land-based hydrosphere. The main aim of this study is to show the influence of variables from different hydrological processes, including for example: total evapotranspiration, runoff, snowmelt, soil moisture to polar motion excitations in seasonal timescale. Hydrological excitation functions of polar motion, both global and regional, are determined by using selected variables of these GLDAS realizations. First we compare the 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 as a residual by subtracting the atmospheric - AAM (pressure + wind) and oceanic - OAM (bottom pressure + currents) contributions. Finally, the hydrological excitations are compared to these hydrological signal from the observed polar motion excitation series residuals. The results help us understand the relative importance for polar motion excitation of the individual variables from different hydrological processes, based on hydrological modeling. This method can allows us to estimate how well the polar motion excitation budget in the seasonal spectral ranges can be closed.

  19. Urban Hydrology and Water Quality Modeling - Resolution Modeling Comparison for Water Quantity and Quality

    NASA Astrophysics Data System (ADS)

    Fry, T. J.; Maxwell, R. M.

    2014-12-01

    Urbanization presents challenging water resource problems for communities worldwide. The hydromodifications associated with urbanization results in increased runoff rates and volumes and increased peak flows. These hydrologic changes can lead to increased erosion and stream destabilization, decreased evapotranspiration, decreased ground water recharge, increases in pollutant loading, and localized anthropogenic climate change or Urban Heat Islands. Stormwater represents a complex and dynamic component of the urban water cycle that requires careful mitigation. With the implementation of Phase II rules under the CWA, stormwater management is shifting from a drainage-efficiency focus to a natural systems focus. The natural system focus, referred to as Low Impact Development (LID), or Green Infrastructure, uses best management practices (BMPs) to reduce the impacts caused by urbanization hydromodification. Large-scale patterns of stormwater runoff from urban environments are complex and it is unclear what the large-scale impacts of green infrastructure are on the water cycle. High resolution physically based hydrologic models can be used to more accurately simulate the urban hydrologic cycle. These types of models tend to be more dynamic and allow for greater flexibility in evaluating and accounting for various hydrologic processes in the urban environment that may be lost with lower resolution conceptual models. We propose to evaluate the effectiveness of high resolution models to accurately represent and determine the urban hydrologic cycle with the overall goal of being able to accurately assess the impacts of LID BMPs in urban environments. We propose to complete a rigorous model intercomparison between ParFlow and FLO-2D. Both of these models can be scaled to higher resolutions, allow for rainfall to be spatially and temporally input, and solve the shallow water equations. Each model is different in the way it accounts for infiltration, initial abstraction losses

  20. Bring the catchment hydrology and carbon science together: a simple ecosystem water use efficiency model

    NASA Astrophysics Data System (ADS)

    Cheng, Lei; Zhang, Lu; Wang, Ying-Ping; Chiew, Francis; Canadell, Josep

    2016-04-01

    Water use efficiency (WUE) defined as carbon uptake per unit of water loss by plants or ecosystems is one of most important functional properties in plant sciences. While theory of WUE is quite advanced at leaf-scale, but quite limited at ecosystem scale because of the complexity of interactions among vegetation, soil and climate. In this study, we developed one simple equation for estimating ecosystem WUE with 2 parameters and 5 variables. Using this simple model, we can explain why ecosystem WUE peaks at about 60N, 20N and tropical region globally. Estimated global ecosystem WUE agrees very well with other independent estimates in both magnitude and spatial variability. We also demonstrated that this model can be used to predict quite accurately the global gross primary production (GPP) when estimates of ecosystem water use are available. We estimated global mean annual GPP as 120.7±10.1 Pg(C) year‑1 based on 7 independent estimates of global evapotranspiration. Further analysis shows both global ecosystem WUE and GPP have increased over the last three decades. About 90% of the increased trend in WUE is attributed to increased atmosphere CO2. Increases in GPP is largely driven by increasing WUE. Therefore this simple model provide an important link of catchment hydrology with carbon science community and as an independent approach for estimating ecosystem photosynthetic carbon production from traditional catchment hydrological measurements.

  1. Operational hydrological ensemble forecasts in France. Recent development of the French Hydropower Company (EDF), taking into account rainfall and hydrological model uncertainties.

    NASA Astrophysics Data System (ADS)

    Mathevet, T.; Garavaglia, F.; Garçon, R.; Gailhard, J.; Paquet, E.

    2009-04-01

    In operational conditions, the actual quality of meteorological and hydrological forecasts do not allow decision-making in a certain future. In this context, meteorological and hydrological ensemble forecasts allow a better representation of forecasts uncertainties. Compared to classical deterministic forecasts, ensemble forecasts improve the human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. In this paper, we present a hydrological ensemble forecasting system under development at EDF (French Hydropower Company). This forecasting system both takes into account rainfall forecasts uncertainties and hydrological model forecasts uncertainties. Hydrological forecasts were generated using the MORDOR model (Andreassian et al., 2006), developed at EDF and used on a daily basis in operational conditions on a hundred of watersheds. Two sources of rainfall forecasts were used : one is based on ECMWF forecasts, another is based on an analogues approach (Obled et al., 2002). Two methods of hydrological model forecasts uncertainty estimation were used : one is based on the use of equifinal parameter sets (Beven & Binley, 1992), the other is based on the statistical modelisation of the hydrological forecast empirical uncertainty (Montanari et al., 2004 ; Schaefli et al., 2007). Daily operational hydrological 7-day ensemble forecasts during 2 years in 3 alpine watersheds were evaluated. Finally, we present a way to combine rainfall and hydrological model forecast uncertainties to achieve a good probabilistic calibration. Our results show that the combination of ECMWF and analogues-based rainfall forecasts allow a good probabilistic calibration of rainfall forecasts. They show also that the statistical modeling of the hydrological forecast empirical uncertainty has a better probabilistic calibration, than the equifinal parameter set approach

  2. High-speed limnology: using advanced sensors to investigate spatial variability in biogeochemistry and hydrology.

    PubMed

    Crawford, John T; Loken, Luke C; Casson, Nora J; Smith, Colin; Stone, Amanda G; Winslow, Luke A

    2015-01-01

    Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h(-1)) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial-aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data. PMID:25406073

  3. 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...

  4. Stimulation from Simulation? A Teaching Model of Hillslope Hydrology for Use on Microcomputers.

    ERIC Educational Resources Information Center

    Burt, Tim; Butcher, Dave

    1986-01-01

    The design and use of a simple computer model which simulates a hillslope hydrology is described in a teaching context. The model shows a relatively complex environmental system can be constructed on the basis of a simple but realistic theory, thus allowing students to simulate the hydrological response of real hillslopes. (Author/TRS)

  5. HYDROLOGIC EVALUATION OF LANDFILL PERFORMANCE (HELP) MODEL: USER'S GUIDE FOR VERSION 3

    EPA Science Inventory

    The Hydrologic Evaluation of Landfill Performance (HELP) computer program is a quasi-two-dimensional hydrologic model of water movement across, into, through and out of landfills. he model accepts weather, soil and design data. andfill systems including various combinations of ve...

  6. Robust quantitative parameter estimation by advanced CMP measurements for vadose zone hydrological studies

    NASA Astrophysics Data System (ADS)

    Koyama, C.; Wang, H.; Khuut, T.; Kawai, T.; Sato, M.

    2015-12-01

    Soil moisture plays a crucial role in the understanding of processes in the vadose zone hydrology. In the last two decades ground penetrating radar (GPR) has been widely discussed has nondestructive measurement technique for soil moisture data. Especially the common mid-point (CMP) technique, which has been used in both seismic and GPR surveys to investigate the vertical velocity profiles, has a very high potential for quantitaive obervsations from the root zone to the ground water aquifer. However, the use is still rather limited today and algorithms for robust quantitative paramter estimation are lacking. In this study we develop an advanced processing scheme for operational soil moisture reetrieval at various depth. Using improved signal processing, together with a semblance - non-normalized cross-correlation sum combined stacking approach and the Dix formula, the interval velocities for multiple soil layers are obtained from the RMS velocities allowing for more accurate estimation of the permittivity at the reflecting point. Where the presence of a water saturated layer, like a groundwater aquifer, can be easily identified by its RMS velocity due to the high contrast compared to the unsaturated zone. By using a new semi-automated measurement technique the acquisition time for a full CMP gather with 1 cm intervals along a 10 m profile can be reduced significantly to under 2 minutes. The method is tested and validated under laboratory conditions in a sand-pit as well as on agricultural fields and beach sand in the Sendai city area. Comparison between CMP estimates and TDR measurements yield a very good agreement with RMSE of 1.5 Vol.-%. The accuracy of depth estimation is validated with errors smaller than 2%. Finally, we demonstrate application of the method in a test site in semi-arid Mongolia, namely the Orkhon River catchment in Bulgan, using commercial 100 MHz and 500 MHz RAMAC GPR antennas. The results demonstrate the suitability of the proposed method for

  7. An Integrated Model for Channel, Overland and Subsurface Hydrology (IMCOSH)

    NASA Astrophysics Data System (ADS)

    Qu, Y.; Duffy, C. J.

    2004-05-01

    Processes within the terrestrial hydrological cycle operate over a wide range of time scales, with interactions among them ranging from uncoupled to strongly coupled. The multiple scales involved make it necessary to couple processes in an efficient way. Given the fact that governing equations for various processes are usually either partial differential equation (PDE) or ordinary differential equation (ODE), a model strategy based on reduction of PDE's to ODE's, using a semi-discrete finite volume method (SD_FVM) over a triangular irregular network (TIN), is introduced in this paper. In other words, the system of integrated PDE describing some processes is first discretized spatially to form a local system of ODE representing each control volume. By combining with those ODE's describing other processes over the domain, an integrated ODE system is built and can be further solved by ODE solver. In this approach, spatial domain decomposition uses an unstructured grid (triangular irregular network, TIN, at this stage) with constraints, e.g. river network and critical terrain points, delineated from geographic information system (GIS) terrain analysis tools. The paper will also address the issues of multiple temporal and spatial scales of processes in complex hydrologic systems. This model is design to capture "dynamics" within multiple processes of various time scales without losing the big picture. For example, the problem of estimating dynamic recharge to groundwater and runoff in streams, or partitioning of water budgets in the channel, on the surface and within subsurface. By turning on or off particular processes or modifying constitutive relationship inside the kernel, this model can be extend to multiple spatial scales application. Preliminary results show this integrated model can capture the wide range of time scales associated with: 1) land-surface soil moisture and water table coupling, 2) gaining or losing stream channels from or to aquifers, and 3) soil

  8. A METHODOLOGY FOR ESTIMATING UNCERTAINTY OF A DISTRIBUTED HYDROLOGIC MODEL: APPLICATION TO POCONO CREEK WATERSHED

    EPA Science Inventory

    Utility of distributed hydrologic and water quality models for watershed management and sustainability studies should be accompanied by rigorous model uncertainty analysis. However, the use of complex watershed models primarily follows the traditional {calibrate/validate/predict}...

  9. Predicting hydrological signatures in ungauged catchments using spatial interpolation, index model, and rainfall-runoff modelling

    NASA Astrophysics Data System (ADS)

    Zhang, Yongqiang; Vaze, Jai; Chiew, Francis H. S.; Teng, Jin; Li, Ming

    2014-09-01

    Understanding a catchment's behaviours in terms of its underlying hydrological signatures is a fundamental task in surface water hydrology. It can help in water resource management, catchment classification, and prediction of runoff time series. This study investigated three approaches for predicting six hydrological signatures in southeastern Australia. These approaches were (1) spatial interpolation with three weighting schemes, (2) index model that estimates hydrological signatures using catchment characteristics, and (3) classical rainfall-runoff modelling. The six hydrological signatures fell into two categories: (1) long-term aggregated signatures - annual runoff coefficient, mean of log-transformed daily runoff, and zero flow ratio, and (2) signatures obtained from daily flow metrics - concavity index, seasonality ratio of runoff, and standard deviation of log-transformed daily flow. A total of 228 unregulated catchments were selected, with half the catchments randomly selected as gauged (or donors) for model building and the rest considered as ungauged (or receivers) to evaluate performance of the three approaches. The results showed that for two long-term aggregated signatures - the log-transformed daily runoff and runoff coefficient, the index model and rainfall-runoff modelling performed similarly, and were better than the spatial interpolation methods. For the zero flow ratio, the index model was best and the rainfall-runoff modelling performed worst. The other three signatures, derived from daily flow metrics and considered to be salient flow characteristics, were best predicted by the spatial interpolation methods of inverse distance weighting (IDW) and kriging. Comparison of flow duration curves predicted by the three approaches showed that the IDW method was best. The results found here provide guidelines for choosing the most appropriate approach for predicting hydrological behaviours at large scales.

  10. 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

  11. Understanding, management and modelling of urban hydrology and its consequences for receiving waters: A state of the art

    NASA Astrophysics Data System (ADS)

    Fletcher, T. D.; Andrieu, H.; Hamel, P.

    2013-01-01

    Urban hydrology has evolved to improve the way urban runoff is managed for flood protection, public health and environmental protection. There have been significant recent advances in the measurement and prediction of urban rainfall, with technologies such as radar and microwave networks showing promise. The ability to predict urban hydrology has also evolved, to deliver models suited to the small temporal and spatial scales typical of urban and peri-urban applications. Urban stormwater management increasingly consider the needs of receiving environments as well as those of humans. There is a clear trend towards approaches that attempt to restore pre-development flow-regimes and water quality, with an increasing recognition that restoring a more natural water balance benefits not only the environment, but enhances the liveability of the urban landscape. Once regarded only as a nuisance, stormwater is now increasingly regarded as a resource. Despite the advances, many important challenges in urban hydrology remain. Further research into the spatio-temporal dynamics of urban rainfall is required to improve short-term rainfall prediction. The performance of stormwater technologies in restoring the water balance and in removing emerging priority pollutants remain poorly quantified. All of these challenges are overlaid by the uncertainty of climate change, which imposes a requirement to ensure that stormwater management systems are adaptable and resilient to changes. Urban hydrology will play a critical role in addressing these challenges.

  12. Hydrological model calibration for enhancing global flood forecast skill

    NASA Astrophysics Data System (ADS)

    Hirpa, Feyera A.; Beck, Hylke E.; Salamon, Peter; Thielen-del Pozo, Jutta

    2016-04-01

    Early warning systems play a key role in flood risk reduction, and their effectiveness is directly linked to streamflow forecast skill. The skill of a streamflow forecast is affected by several factors; among them are (i) model errors due to incomplete representation of physical processes and inaccurate parameterization, (ii) uncertainty in the model initial conditions, and (iii) errors in the meteorological forcing. In macro scale (continental or global) modeling, it is a common practice to use a priori parameter estimates over large river basins or wider regions, resulting in suboptimal streamflow estimations. The aim of this work is to improve flood forecast skill of the Global Flood Awareness System (GloFAS; www.globalfloods.eu), a grid-based forecasting system that produces flood forecast unto 30 days lead, through calibration of the distributed hydrological model parameters. We use a combination of in-situ and satellite-based streamflow data for automatic calibration using a multi-objective genetic algorithm. We will present the calibrated global parameter maps and report the forecast skill improvements achieved. Furthermore, we discuss current challenges and future opportunities with regard to global-scale early flood warning systems.

  13. Quality assessment of Digital Elevation Model (DEM) in view of the Altiplano hydrological modeling

    NASA Astrophysics Data System (ADS)

    Satgé, F.; Arsen, A.; Bonnet, M.; Timouk, F.; Calmant, S.; Pilco, R.; Molina, J.; Lavado, W.; Crétaux, J.; HASM

    2013-05-01

    Topography is crucial data input for hydrological modeling but in many regions of the world, the only way to characterize topography is the use of satellite-based Digital Elevation Models (DEM). In some regions, the quality of these DEMs remains poor and induces modeling errors that may or not be compensated by model parameters tuning. In such regions, the evaluation of these data uncertainties is an important step in the modeling procedure. In this study, which focuses on the Altiplano region, we present the evaluation of the two freely available DEM. The shuttle radar topographic mission (SRTM), a product of the National Aeronautics and Space Administration (NASA) and the Advanced Space Born Thermal Emission and Reflection Global Digital Elevation Map (ASTER GDEM), data provided by the Ministry of Economy, Trade and Industry of Japan (MESI) in collaboration with the NASA, are widely used. While the first represents a resolution of 3 arc seconds (90m) the latter is 1 arc second (30m). In order to select the most reliable DEM, we compared the DEM elevation with high qualities control points elevation. Because of its large spatial coverture (track spaced of 30 km with a measure of each 172 m) and its high vertical accuracy which is less than 15 cm in good weather conditions, the Geoscience Laser Altimeter System (GLAS) on board on the Ice, Cloud and Land elevation Satellite of NASA (ICESat) represent the better solution to establish a high quality elevation database. After a quality check, more than 150 000 ICESat/GLAS measurements are suitable in terms of accuracy for the Altiplano watershed. This data base has been used to evaluate the vertical accuracy for each DEM. Regarding to the full spatial coverture; the comparison has been done for both, all kind of land coverture, range altitude and mean slope.

  14. Soil hydrologic characterization for modeling large scale soil remediation protocols

    NASA Astrophysics Data System (ADS)

    Romano, Nunzio; Palladino, Mario; Di Fiore, Paola; Sica, Benedetto; Speranza, Giuseppe

    2014-05-01

    In Campania Region (Italy), the Ministry of Environment identified a National Interest Priority Sites (NIPS) with a surface of about 200,000 ha, characterized by different levels and sources of pollution. This area, called Litorale Domitio-Agro Aversano includes some polluted agricultural land, belonging to more than 61 municipalities in the Naples and Caserta provinces. In this area, a high level spotted soil contamination is moreover due to the legal and outlaw industrial and municipal wastes dumping, with hazardous consequences also on the quality of the water table. The EU-Life+ project ECOREMED (Implementation of eco-compatible protocols for agricultural soil remediation in Litorale Domizio-Agro Aversano NIPS) has the major aim of defining an operating protocol for agriculture-based bioremediation of contaminated agricultural soils, also including the use of crops extracting pollutants to be used as biomasses for renewable energy production. In the framework of this project, soil hydrologic characterization plays a key role and modeling water flow and solute transport has two main challenging points on which we focus on. A first question is related to the fate of contaminants infiltrated from stormwater runoff and the potential for groundwater contamination. Another question is the quantification of fluxes and spatial extent of root water uptake by the plant species employed to extract pollutants in the uppermost soil horizons. Given the high variability of spatial distribution of pollutants, we use soil characterization at different scales, from field scale when facing root water uptake process, to regional scale when simulating interaction between soil hydrology and groundwater fluxes.

  15. HYDROLOGY AND SEDIMENT MODELING USING THE BASINS NON-POINT SOURCE MODEL

    EPA Science Inventory

    The Non-Point Source Model (Hydrologic Simulation Program-Fortran, or HSPF) within the EPA Office of Water's BASINS watershed modeling system was used to simulate streamflow and total suspended solids within Contentnea Creek, North Carolina, which is a tributary of the Neuse Rive...

  16. 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

  17. A comparison of alternative multiobjective calibration strategies for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Fenicia, Fabrizio; Savenije, Hubert H. G.; Matgen, Patrick; Pfister, Laurent

    2007-03-01

    A conceptual hydrological model structure contains several parameters that have to be estimated through matching observed and modeled watershed behavior in a calibration process. The requirement that a model simulation matches different aspects of system response at the same time has led the calibration problem toward a multiobjective approach. In this work we compare two multiobjective calibration approaches, each of which represents a different calibration philosophy. The first calibration approach is based on the concept of Pareto optimality and consists of calibrating all parameters with respect to a common set of objectives in one calibration stage. This approach results in a set of Pareto-optimal solutions representing the trade-offs between the selected calibration objectives. The second is a stepped calibration approach (SCA), which implies a stepwise calibration of sets of parameters that are associated with specific aspects of the system response. This approach replicates the steps followed by a hydrologist in manual calibration and develops a single solution. The comparison is performed considering the same set of objectives for the two approaches and two model structures of a different level of complexity. The difference in the two approaches, their reciprocal utility, and the practical implications involved in their application are analyzed and discussed using the Hesperange catchment case, an experimental basin in the Alzette River basin in Luxembourg. We show that the two approaches are not necessarily conflicting but can be complementary. The first approach provides useful information about the deficiencies of a model structure and therefore helps the model development, while the second attempts at determining a solution that is consistent with the data available. We also show that with increasing model complexity it becomes possible to reproduce the observations more accurately. As a result, the solutions for the different calibration objectives

  18. Disinformative data in large-scale hydrological modelling

    NASA Astrophysics Data System (ADS)

    Kauffeldt, Anna; Halldin, Sven; Rodhe, Allan; Xu, Chong-Yu; Westerberg, Ida

    2013-04-01

    Lar