Spatially explicit simulation of hydrologically controlled carbon and nitrogen cycles and associated feedback mechanisms in a boreal ecosystem

NASA Astrophysics Data System (ADS)

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

2009-06-01

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

The power of runoff

NASA Astrophysics Data System (ADS)

Wörman, A.; Lindström, G.; Riml, J.

2017-05-01

Although the potential energy of surface water is a small part of Earth's energy budget, this highly variable physical property is a key component in the terrestrial hydrologic cycle empowering geomorphological and hydrological processes throughout the hydrosphere. By downscaling of the daily hydrometeorological data acquired in Sweden over the last half-century this study quantifies the spatial and temporal distribution of the dominating energy components in terrestrial hydrology, including the frictional resistance in surface water and groundwater as well as hydropower. The energy consumed in groundwater circulation was found to be 34.6 TWh/y or a heat production of approximately 13% of the geothermal heat flux. Significant climate driven, periodic fluctuations in the power of runoff, stream flows and groundwater circulation were revealed that have not previously been documented. We found that the runoff power ranged from 173 to 260 TWh/y even when averaged over the entire surface of Sweden in a five-year moving window. We separated short-term fluctuations in runoff due to precipitation filtered through the watershed from longer-term seasonal and climate driven modes. Strong climate driven correlations between the power of runoff and climate indices, wind and solar intensity were found over periods of 3.6 and 8 years. The high covariance that we found between the potential energy of surface water and wind energy implies significant challenges for the combination of these renewable energy sources.

A conceptual socio-hydrological model of the co-evolution of humans and water: case study of the Tarim River basin, western China

NASA Astrophysics Data System (ADS)

Liu, D.; Tian, F.; Lin, M.; Sivapalan, M.

2015-02-01

The complex interactions and feedbacks between humans and water are critically important issues but remain poorly understood in the newly proposed discipline of socio-hydrology (Sivapalan et al., 2012). An exploratory model with the appropriate level of simplification can be valuable for improving our understanding of the co-evolution and self-organization of socio-hydrological systems driven by interactions and feedbacks operating at different scales. In this study, a simplified conceptual socio-hydrological model based on logistic growth curves is developed for the Tarim River basin in western China and is used to illustrate the explanatory power of such a co-evolutionary model. The study area is the main stream of the Tarim River, which is divided into two modeling units. The socio-hydrological system is composed of four sub-systems, i.e., the hydrological, ecological, economic, and social sub-systems. In each modeling unit, the hydrological equation focusing on water balance is coupled to the other three evolutionary equations to represent the dynamics of the social sub-system (denoted by population), the economic sub-system (denoted by irrigated crop area ratio), and the ecological sub-system (denoted by natural vegetation cover), each of which is expressed in terms of a logistic growth curve. Four feedback loops are identified to represent the complex interactions among different sub-systems and different spatial units, of which two are inner loops occurring within each separate unit and the other two are outer loops linking the two modeling units. The feedback mechanisms are incorporated into the constitutive relations for model parameters, i.e., the colonization and mortality rates in the logistic growth curves that are jointly determined by the state variables of all sub-systems. The co-evolution of the Tarim socio-hydrological system is then analyzed with this conceptual model to gain insights into the overall system dynamics and its sensitivity to the external drivers and internal system variables. The results show a costly pendulum swing between a balanced distribution of socio-economic and natural ecologic resources among the upper and lower reaches and a highly skewed distribution towards the upper reach. This evolution is principally driven by the attitudinal changes occurring within water resources management policies that reflect the evolving community awareness of society to concerns regarding the ecology and environment.

Mountain Hydrology of the Semi-Arid Western U.S.: Research Needs, Opportunities and Challenges

NASA Astrophysics Data System (ADS)

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

2004-12-01

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

Variability in physical and biological exchange among coastal wetlands and their adjacent Great Lakes

EPA Science Inventory

Hydrology is a major governor of physically-driven exchange among coastal wetlands and the adjacent Great Lake, whereas fish movement is a major governor of biologically-driven exchange. We use data describing coastal wetland morphology, hydrology, water quality, and fish tissue...

Reliable estimates of predictive uncertainty for an Alpine catchment using a non-parametric methodology

NASA Astrophysics Data System (ADS)

Matos, José P.; Schaefli, Bettina; Schleiss, Anton J.

2017-04-01

Uncertainty affects hydrological modelling efforts from the very measurements (or forecasts) that serve as inputs to the more or less inaccurate predictions that are produced. Uncertainty is truly inescapable in hydrology and yet, due to the theoretical and technical hurdles associated with its quantification, it is at times still neglected or estimated only qualitatively. In recent years the scientific community has made a significant effort towards quantifying this hydrologic prediction uncertainty. Despite this, most of the developed methodologies can be computationally demanding, are complex from a theoretical point of view, require substantial expertise to be employed, and are constrained by a number of assumptions about the model error distribution. These assumptions limit the reliability of many methods in case of errors that show particular cases of non-normality, heteroscedasticity, or autocorrelation. The present contribution builds on a non-parametric data-driven approach that was developed for uncertainty quantification in operational (real-time) forecasting settings. The approach is based on the concept of Pareto optimality and can be used as a standalone forecasting tool or as a postprocessor. By virtue of its non-parametric nature and a general operating principle, it can be applied directly and with ease to predictions of streamflow, water stage, or even accumulated runoff. Also, it is a methodology capable of coping with high heteroscedasticity and seasonal hydrological regimes (e.g. snowmelt and rainfall driven events in the same catchment). Finally, the training and operation of the model are very fast, making it a tool particularly adapted to operational use. To illustrate its practical use, the uncertainty quantification method is coupled with a process-based hydrological model to produce statistically reliable forecasts for an Alpine catchment located in Switzerland. Results are presented and discussed in terms of their reliability and resolution.

Impacts of Non-Stationarity in Climate on Flood Intensity-Duration-Frequency: Case Studies in Mountainous Areas with Snowmelt

NASA Astrophysics Data System (ADS)

Hou, Z.; Ren, H.; Sun, N.; Leung, L. R.; Liu, Y.; Coleman, A. M.; Skaggs, R.; Wigmosta, M. S.

2017-12-01

Hydrologic engineering design usually involves intensity-duration-frequency (IDF) analysis for calculating runoff from a design storm of specified precipitation frequency and duration using event-based hydrologic rainfall-runoff models. Traditionally, the procedure assumes climate stationarity and neglects snowmelt-driven runoff contribution to floods. In this study, we used high resolution climate simulations to provide inputs to the physics-based Distributed Hydrology Soil and Vegetation Model (DHSVM) to determine the spatially distributed precipitation and snowmelt available for runoff. Climate model outputs were extracted around different mountainous field sites in Colorado and California. IDF curves were generated at each numerical grid of DHSVM based on the simulated precipitation, temperature, and available water for runoff. Quantitative evaluation of trending and stationarity tests were conducted to identify (quasi-)stationary time periods for reliable IDF analysis. The impact of stationarity was evaluated by comparing the derived IDF attributes with respect to time windows of different length and level of stationarity. Spatial mapping of event return-period was performed for various design storms, and spatial mapping of event intensity was performed for given duration and return periods. IDF characteristics were systematically compared (historical vs RCP4.5 vs RCP8.5) using annual maximum series vs partial duration series data with the goal of providing reliable IDF analyses to support hydrologic engineering design.

Stream Width Dynamics in a Small Headwater Catchment

NASA Astrophysics Data System (ADS)

Barefoot, E. A.; Pavelsky, T.; Allen, G. H.; Zimmer, M. A.; McGlynn, B. L.

2016-12-01

Changing streamflow conditions cause small, ephemeral and intermittent stream networks to expand and contract, while simultaneously driving widening and narrowing of streams. The resulting dynamic surface area of ephemeral streams impacts critical hydrological and biogeochemical processes, including air-water gas exchange, solute transport, and sediment transport. Despite the importance of these dynamics, to our knowledge there exists no complete study of how stream widths vary throughout an entire catchment in response to changing streamflow conditions. Here we present the first characterization of how variable hydrologic conditions impact the distribution of stream widths in a 48 ha headwater catchment in the Stony Creek Research Watershed, NC, USA. We surveyed stream widths longitudinally every 5 m on 12 occasions over a range of stream discharge from 7 L/s to 128 L/s at the catchment outlet. We hypothesize that the shape and location of the stream width distribution are driven by the action of two interrelated mechanisms, network extension and at-a-station widening, both of which increase with discharge. We observe that during very low flow conditions, network extension more significantly influences distribution location, and during high flow conditions stream widening is the dominant driver. During moderate flows, we observe an approximately 1 cm rightward shift in the distribution peak with every additional 10 L/s of increased discharge, which we attribute to a greater impact of at-a-station widening on distribution location. Aside from this small shift, the qualitative location and shape of the stream width distribution are largely invariant with changing streamflow. We suggest that the basic characteristics of stream width distributions constitute an equilibrium between the two described mechanisms across variable hydrologic conditions.

A model for the hydrologic and climatic behavior of water on Mars

NASA Technical Reports Server (NTRS)

Clifford, Stephen M.

1993-01-01

An analysis is carried out of the hydrologic response of a water-rich Mars to climate change and to the physical and thermal evolution of its crust, with particular attention given to the potential role of the subsurface transport, assuming that the current models of insolation-driven change describe reasonably the atmospheric leg of the planet's long-term hydrologic cycle. Among the items considered are the thermal and hydrologic properties of the crust, the potential distribution of ground ice and ground water, the stability and replenishment of equatorial ground ice, basal melting and the polar mass balance, the thermal evolution of the early cryosphere, the recharge of the valley networks and outflow, and several processes that are likely to drive the large-scale vertical and horizontal transport of H2O within the crust. The results lead to the conclusion that subsurface transport has likely played an important role in the geomorphic evolution of the Martian surface and the long-term cycling of H2O between the atmosphere, polar caps, and near-surface crust.

RWater - A Novel Cyber-enabled Data-driven Educational Tool for Interpreting and Modeling Hydrologic Processes

NASA Astrophysics Data System (ADS)

Rajib, M. A.; Merwade, V.; Zhao, L.; Song, C.

2014-12-01

Explaining the complex cause-and-effect relationships in hydrologic cycle can often be challenging in a classroom with the use of traditional teaching approaches. With the availability of observed rainfall, streamflow and other hydrology data on the internet, it is possible to provide the necessary tools to students to explore these relationships and enhance their learning experience. From this perspective, a new online educational tool, called RWater, is developed using Purdue University's HUBzero technology. RWater's unique features include: (i) its accessibility including the R software from any java supported web browser; (ii) no installation of any software on user's computer; (iii) all the work and resulting data are stored in user's working directory on RWater server; and (iv) no prior programming experience with R software is necessary. In its current version, RWater can dynamically extract streamflow data from any USGS gaging station without any need for post-processing for use in the educational modules. By following data-driven modules, students can write small scripts in R and thereby create visualizations to identify the effect of rainfall distribution and watershed characteristics on runoff generation, investigate the impacts of landuse and climate change on streamflow, and explore the changes in extreme hydrologic events in actual locations. Each module contains relevant definitions, instructions on data extraction and coding, as well as conceptual questions based on the possible analyses which the students would perform. In order to assess its suitability in classroom implementation, and to evaluate users' perception over its utility, the current version of RWater has been tested with three different groups: (i) high school students, (ii) middle and high school teachers; and (iii) upper undergraduate/graduate students. The survey results from these trials suggest that the RWater has potential to improve students' understanding on various relationships in hydrologic cycle, leading towards effective dissemination of hydrology education ranging from K-12 to the graduate level. RWater is a publicly available for use at: https://mygeohub.org/tools/rwater.

Using a spatially-distributed hydrologic biogeochemistry model to study the spatial variation of carbon processes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; Davis, K. J.; He, Y.

2015-12-01

Forest carbon processes are affected by soil moisture, soil temperature and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore they can neither resolve topographically driven hill-slope soil moisture patterns, nor simulate the nonlinear effects of soil moisture on carbon processes. A spatially-distributed biogeochemistry model, Flux-PIHM-BGC, has been developed by coupling the Biome-BGC (BBGC) model with a coupled physically-based land surface hydrologic model, Flux-PIHM. Flux-PIHM incorporates a land-surface scheme (adapted from the Noah land surface model) into the Penn State Integrated Hydrologic Model (PIHM). Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. Flux-PIHM-BGC model was tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations at the SSHCZO, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, aboveground carbon stock, and soil carbon efflux, provided an ideal test bed for the coupled model. Model results show that when uniform solar radiation is used, vegetation carbon and soil carbon are positively correlated with soil moisture in space, which agrees with the observations within the watershed. When topographically-driven solar radiation is used, however, the wetter valley floor becomes radiation limited, and produces less vegetation and soil carbon than the drier hillslope due to the assumption that canopy height is uniform in the watershed. This contradicts with the observations, and suggests that a tree height model with dynamic allocation model are needed to reproduce the spatial variation of carbon processes within a watershed.

A socio-hydrologic model of coupled water-agriculture dynamics with emphasis on farm size.

NASA Astrophysics Data System (ADS)

Brugger, D. R.; Maneta, M. P.

2015-12-01

Agricultural land cover dynamics in the U.S. are dominated by two trends: 1) total agricultural land is decreasing and 2) average farm size is increasing. These trends have important implications for the future of water resources because 1) growing more food on less land is due in large part to increased groundwater withdrawal and 2) larger farms can better afford both more efficient irrigation and more groundwater access. However, these large-scale trends are due to individual farm operators responding to many factors including climate, economics, and policy. It is therefore difficult to incorporate the trends into watershed-scale hydrologic models. Traditional scenario-based approaches are valuable for many applications, but there is typically no feedback between the hydrologic model and the agricultural dynamics and so limited insight is gained into the how agriculture co-evolves with water resources. We present a socio-hydrologic model that couples simplified hydrologic and agricultural economic dynamics, accounting for many factors that depend on farm size such as irrigation efficiency and returns to scale. We introduce an "economic memory" (EM) state variable that is driven by agricultural revenue and affects whether farms are sold when land market values exceed expected returns from agriculture. The model uses a Generalized Mixture Model of Gaussians to approximate the distribution of farm sizes in a study area, effectively lumping farms into "small," "medium," and "large" groups that have independent parameterizations. We apply the model in a semi-arid watershed in the upper Columbia River Basin, calibrating to data on streamflow, total agricultural land cover, and farm size distribution. The model is used to investigate the sensitivity of the coupled system to various hydrologic and economic scenarios such as increasing market value of land, reduced surface water availability, and increased irrigation efficiency in small farms.

Macroscale hydrologic modeling of ecologically relevant flow metrics

NASA Astrophysics Data System (ADS)

Wenger, Seth J.; Luce, Charles H.; Hamlet, Alan F.; Isaak, Daniel J.; Neville, Helen M.

2010-09-01

Stream hydrology strongly affects the structure of aquatic communities. Changes to air temperature and precipitation driven by increased greenhouse gas concentrations are shifting timing and volume of streamflows potentially affecting these communities. The variable infiltration capacity (VIC) macroscale hydrologic model has been employed at regional scales to describe and forecast hydrologic changes but has been calibrated and applied mainly to large rivers. An important question is how well VIC runoff simulations serve to answer questions about hydrologic changes in smaller streams, which are important habitat for many fish species. To answer this question, we aggregated gridded VIC outputs within the drainage basins of 55 streamflow gages in the Pacific Northwest United States and compared modeled hydrographs and summary metrics to observations. For most streams, several ecologically relevant aspects of the hydrologic regime were accurately modeled, including center of flow timing, mean annual and summer flows and frequency of winter floods. Frequencies of high and low flows in the summer were not well predicted, however. Predictions were worse for sites with strong groundwater influence, and some sites showed errors that may result from limitations in the forcing climate data. Higher resolution (1/16th degree) modeling provided small improvements over lower resolution (1/8th degree). Despite some limitations, the VIC model appears capable of representing several ecologically relevant hydrologic characteristics in streams, making it a useful tool for understanding the effects of hydrology in delimiting species distributions and predicting the potential effects of climate shifts on aquatic organisms.

An interdisciplinary swat ecohydrological model to define catchment-scale hydrologic partitioning

NASA Astrophysics Data System (ADS)

Shope, C. L.; Maharjan, G. R.; Tenhunen, J.; Seo, B.; Kim, K.; Riley, J.; Arnhold, S.; Koellner, T.; Ok, Y. S.; Peiffer, S.; Kim, B.; Park, J.-H.; Huwe, B.

2013-06-01

Land use and climate change have long been implicated in modifying ecosystem services, such as water quality and water yield, biodiversity, and agricultural production. To account for future effects on ecosystem services, the integration of physical, biological, economic, and social data over several scales must be implemented to assess the effects on natural resource availability and use. Our objective is to assess the capability of the SWAT model to capture short-duration monsoonal rainfall-runoff processes in complex mountainous terrain under rapid, event-driven processes in a monsoonal environment. To accomplish this, we developed a unique quality-control gap-filling algorithm for interpolation of high frequency meteorological data. We used a novel multi-location, multi-optimization calibration technique to improve estimations of catchment-wide hydrologic partitioning. We calibrated the interdisciplinary model to a combination of statistical, hydrologic, and plant growth metrics. In addition, we used multiple locations of different drainage area, aspect, elevation, and geologic substrata distributed throughout the catchment. Results indicate scale-dependent sensitivity of hydrologic partitioning and substantial influence of engineered features. While our model accurately reproduced observed discharge variability, the addition of hydrologic and plant growth objective functions identified the importance of culverts in catchment-wide flow distribution. The results of this study provide a valuable resource to describe landscape controls and their implication on discharge, sediment transport, and nutrient loading. This study also shows the challenges of applying the SWAT model to complex terrain and extreme environments. By incorporating anthropogenic features into modeling scenarios, we can greatly enhance our understanding of the hydroecological impacts on ecosystem services.

A Bayesian Uncertainty Framework for Conceptual Snowmelt and Hydrologic Models Applied to the Tenderfoot Creek Experimental Forest

NASA Astrophysics Data System (ADS)

Smith, T.; Marshall, L.

2007-12-01

In many mountainous regions, the single most important parameter in forecasting the controls on regional water resources is snowpack (Williams et al., 1999). In an effort to bridge the gap between theoretical understanding and functional modeling of snow-driven watersheds, a flexible hydrologic modeling framework is being developed. The aim is to create a suite of models that move from parsimonious structures, concentrated on aggregated watershed response, to those focused on representing finer scale processes and distributed response. This framework will operate as a tool to investigate the link between hydrologic model predictive performance, uncertainty, model complexity, and observable hydrologic processes. Bayesian methods, and particularly Markov chain Monte Carlo (MCMC) techniques, are extremely useful in uncertainty assessment and parameter estimation of hydrologic models. However, these methods have some difficulties in implementation. In a traditional Bayesian setting, it can be difficult to reconcile multiple data types, particularly those offering different spatial and temporal coverage, depending on the model type. These difficulties are also exacerbated by sensitivity of MCMC algorithms to model initialization and complex parameter interdependencies. As a way of circumnavigating some of the computational complications, adaptive MCMC algorithms have been developed to take advantage of the information gained from each successive iteration. Two adaptive algorithms are compared is this study, the Adaptive Metropolis (AM) algorithm, developed by Haario et al (2001), and the Delayed Rejection Adaptive Metropolis (DRAM) algorithm, developed by Haario et al (2006). While neither algorithm is truly Markovian, it has been proven that each satisfies the desired ergodicity and stationarity properties of Markov chains. Both algorithms were implemented as the uncertainty and parameter estimation framework for a conceptual rainfall-runoff model based on the Probability Distributed Model (PDM), developed by Moore (1985). We implement the modeling framework in Stringer Creek watershed in the Tenderfoot Creek Experimental Forest (TCEF), Montana. The snowmelt-driven watershed offers that additional challenge of modeling snow accumulation and melt and current efforts are aimed at developing a temperature- and radiation-index snowmelt model. Auxiliary data available from within TCEF's watersheds are used to support in the understanding of information value as it relates to predictive performance. Because the model is based on lumped parameters, auxiliary data are hard to incorporate directly. However, these additional data offer benefits through the ability to inform prior distributions of the lumped, model parameters. By incorporating data offering different information into the uncertainty assessment process, a cross-validation technique is engaged to better ensure that modeled results reflect real process complexity.

Intertime jump statistics of state-dependent Poisson processes.

PubMed

Daly, Edoardo; Porporato, Amilcare

2007-01-01

A method to obtain the probability distribution of the interarrival times of jump occurrences in systems driven by state-dependent Poisson noise is proposed. Such a method uses the survivor function obtained by a modified version of the master equation associated to the stochastic process under analysis. A model for the timing of human activities shows the capability of state-dependent Poisson noise to generate power-law distributions. The application of the method to a model for neuron dynamics and to a hydrological model accounting for land-atmosphere interaction elucidates the origin of characteristic recurrence intervals and possible persistence in state-dependent Poisson models.

Cytherellid species (Ostracoda) and their significance to the Late Quaternary events in the Santos Basin, Brazil

USGS Publications Warehouse

Bergue, C.T.; Coimbra, J.C.; Cronin, T. M.

2007-01-01

Four autochthonous cytherellid species (Cytherella serratula (BRADY, 1880), C. hermargentina WHATLEY et al. 1998, C. pleistocenica sp. nov. and C. santosensis sp. nov.) have been identified from two offshore cores (44 samples) within the Santos Basin. The distribution of these ostracodes is controlled by local hydrological conditions such as the temperature and, possibly, the oxygen minimum zone (OMZ). However, these factors cannot explain completely the species occurrence in the analysed cores, and relative sea level changes and productivity variation driven by climatic changes are proposed as additional explanations for the faunal distribution pattern. ?? E. Schweizerbart'sche Verlagsbuchhandlung (Na??gele u. Obermiller), 2007.

Extreme flood estimation by the SCHADEX method in a snow-driven catchment: application to Atnasjø (Norway)

NASA Astrophysics Data System (ADS)

Paquet, Emmanuel; Lawrence, Deborah

2013-04-01

The SCHADEX method for extreme flood estimation was developed by Paquet et al. (2006, 2013), and since 2008, it is the reference method used by Electricité de France (EDF) for dam spillway design. SCHADEX is a so-called "semi-continuous" stochastic simulation method in that flood events are simulated on an event basis and are superimposed on a continuous simulation of the catchment saturation hazard usingrainfall-runoff modelling. The MORDOR hydrological model (Garçon, 1999) has thus far been used for the rainfall-runoff modelling. MORDOR is a conceptual, lumped, reservoir model with daily areal rainfall and air temperature as the driving input data. The principal hydrological processes represented are evapotranspiration, direct and indirect runoff, ground water, snow accumulation and melt, and routing. The model has been intensively used at EDF for more than 15 years, in particular for inflow forecasts for French mountainous catchments. SCHADEX has now also been applied to the Atnasjø catchment (463 km²), a well-documented inland catchment in south-central Norway, dominated by snowmelt flooding during spring/early summer. To support this application, a weather pattern classification based on extreme rainfall was first established for Norway (Fleig, 2012). This classification scheme was then used to build a Multi-Exponential Weather Pattern distribution (MEWP), as introduced by Garavaglia et al. (2010) for extreme rainfall estimation. The MORDOR model was then calibrated relative to daily discharge data for Atnasjø. Finally, a SCHADEX simulation was run to build a daily discharge distribution with a sufficient number of simulations for assessing the extreme quantiles. Detailed results are used to illustrate how SCHADEX handles the complex and interacting hydrological processes driving flood generation in this snow driven catchment. Seasonal and monthly distributions, as well as statistics for several thousand simulated events reaching a 1000 years return level value and assessment of snowmelt role in extreme floods are presented. This study illustrates the complexity of the extreme flood estimation in snow driven catchments, and the need for a good representation of snow accumulation and melting processes in simulations for design flood estimations. In particular, the SCHADEX method is able to represent a range of possible catchment conditions (representing both soil moisture and snowmelt) in which extreme flood events can occur. This study is part of a collaboration between NVE and EDF, initiated within the FloodFreq COST Action (http://www.cost-floodfreq.eu/). References: Fleig, A., Scientific Report of the Short Term Scientific Mission Anne Fleig visiting Électricité de France, FloodFreq COST action - STSM report, 2012 Garavaglia, F., Gailhard, J., Paquet, E., Lang, M., Garçon, R., and Bernardara, P., Introducing a rainfall compound distribution model based on weather patterns sub-sampling, Hydrol. Earth Syst. Sci., 14, 951-964, doi:10.5194/hess-14-951-2010, 2010 Garçon, R. Modèle global pluie-débit pour la prévision et la prédétermination des crues, La Houille Blanche, 7-8, 88-95. doi: 10.1051/lhb/1999088 Paquet, E., Gailhard, J. and Garçon, R. (2006), Evolution of the GRADEX method: improvement by atmospheric circulation classification and hydrological modeling, La Houille Blanche, 5, 80-90. doi: 10.1051/lhb/2006091 Paquet, E., Garavaglia, F., Garçon, R. and Gailhard, J. (2012), The SCHADEX method: a semi-continuous rainfall-runoff simulation for extreme food estimation, Journal of Hydrology, under revision

Simulation and analysis of conjunctive use with MODFLOW's farm process

USGS Publications Warehouse

Hanson, R.T.; Schmid, W.; Faunt, C.C.; Lockwood, B.

2010-01-01

The extension of MODFLOW onto the landscape with the Farm Process (MF-FMP) facilitates fully coupled simulation of the use and movement of water from precipitation, streamflow and runoff, groundwater flow, and consumption by natural and agricultural vegetation throughout the hydrologic system at all times. This allows for more complete analysis of conjunctive use water-resource systems than previously possible with MODFLOW by combining relevant aspects of the landscape with the groundwater and surface water components. This analysis is accomplished using distributed cell-by-cell supply-constrained and demand-driven components across the landscape within " water-balance subregions" comprised of one or more model cells that can represent a single farm, a group of farms, or other hydrologic or geopolitical entities. Simulation of micro-agriculture in the Pajaro Valley and macro-agriculture in the Central Valley are used to demonstrate the utility of MF-FMP. For Pajaro Valley, the simulation of an aquifer storage and recovery system and related coastal water distribution system to supplant coastal pumpage was analyzed subject to climate variations and additional supplemental sources such as local runoff. For the Central Valley, analysis of conjunctive use from different hydrologic settings of northern and southern subregions shows how and when precipitation, surface water, and groundwater are important to conjunctive use. The examples show that through MF-FMP's ability to simulate natural and anthropogenic components of the hydrologic cycle, the distribution and dynamics of supply and demand can be analyzed, understood, and managed. This analysis of conjunctive use would be difficult without embedding them in the simulation and are difficult to estimate a priori. Journal compilation ?? 2010 National Ground Water Association. No claim to original US government works.

Vegetation function and non-uniqueness of the hydrological response

NASA Astrophysics Data System (ADS)

Ivanov, V. Y.; Fatichi, S.; Kampf, S. K.; Caporali, E.

2012-04-01

Through local moisture uptake vegetation exerts seasonal and longer-term impacts on the watershed hydrological response. However, the role of vegetation may go beyond the conventionally implied and well-understood "sink" function in the basin soil moisture storage equation. We argue that vegetation function imposes a "homogenizing" effect on pre-event soil moisture spatial storage, decreasing the likelihood that a rainfall event will result in a topographically-driven redistribution of soil water and the consequent formation of variable source areas. In combination with vegetation temporal dynamics, this may lead to the non-uniqueness of the hydrological response with respect to the mean basin wetness. This study designs a set of relevant numerical experiments carried out with two physically-based models; one of the models, HYDRUS, resolves variably saturated subsurface flow using a fully three-dimensional formulation, while the other model, tRIBS+VEGGIE, uses a one-dimensional formulation applied in a quasi-three-dimensional framework in combination with the model of vegetation dynamics. We demonstrate that (1) vegetation function modifies spatial heterogeneity in moisture spatial storage by imposing different degrees of subsurface flow connectivity; explore mechanistically (2) how and why a basin with the same mean soil moisture can have distinctly different spatial soil moisture distributions; and demonstrate (2) how these distinct moisture distributions result in a hysteretic runoff response to precipitation. Furthermore, the study argues that near-surface soil moisture is an insufficient indicator of the initial moisture state of a catchment with the implication of its limited effect on hydrological predictability.

Exploring the Influence of Topography on Belowground C Processes Using a Coupled Hydrologic-Biogeochemical Model

NASA Astrophysics Data System (ADS)

Shi, Y.; Davis, K. J.; Eissenstat, D. M.; Kaye, J. P.; Duffy, C.; Yu, X.; He, Y.

2014-12-01

Belowground carbon processes are affected by soil moisture and soil temperature, but current biogeochemical models are 1-D and cannot resolve topographically driven hill-slope soil moisture patterns, and cannot simulate the nonlinear effects of soil moisture on carbon processes. Coupling spatially-distributed physically-based hydrologic models with biogeochemical models may yield significant improvements in the representation of topographic influence on belowground C processes. We will couple the Flux-PIHM model to the Biome-BGC (BBGC) model. Flux-PIHM is a coupled physically-based land surface hydrologic model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. The coupled Flux-PIHM-BBGC model will be tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, above ground carbon stock, and soil carbon efflux, make SSHCZO an ideal test bed for the coupled model. In the coupled model, each Flux-PIHM model grid will couple a BBGC cell. Flux-PIHM will provide BBGC with soil moisture and soil temperature information, while BBGC provides Flux-PIHM with leaf area index. Preliminary results show that when Biome- BGC is driven by PIHM simulated soil moisture pattern, the simulated soil carbon is clearly impacted by topography.

The Relationship Between the Zonal Mean ITCZ and Regional Precipitation during the mid-Holocene

NASA Astrophysics Data System (ADS)

Niezgoda, K.; Noone, D.; Konecky, B.

2017-12-01

Characteristics of the zonal mean Tropical Rain Belt (TRB, i.e. the ITCZ + the land-based monsoons) are often inferred from individual proxy records of precipitation or other hydroclimatic variables. However, these inferences can be misleading. Here, an isotope-enabled climate model simulation is used to evaluate metrics of the zonal mean ITCZ vs. regional hydrological characteristics during the mid-Holocene (MH, 6 kya). The MH provides a unique perspective on the relationship between the ITCZ and regional hydrology because of large, orbitally-driven shifts in tropical precipitation as well as a critical mass of proxy records. By using a climate model with simulated water isotopes, characteristics of atmospheric circulation and water transport processes can be inferred, and comparison with isotope proxies can be made more directly. We find that estimations of the zonal-mean ITCZ are insufficient for evaluating regional responses of hydrological cycles to forcing changes. For example, one approximation of a 1.5-degree northward shift in the zonal-mean ITCZ position during the MH corresponded well with northward shifts in maximum rainfall in tropical Africa, but did not match southward shifts in the tropical Pacific or longitudinal shifts in the Indian monsoon region. In many regions, the spatial distribution of water vapor isotopes suggests that changes in moisture source and atmospheric circulation were a greater influence on precipitation distribution, intensity, and isotope ratio than the average northward shift in ITCZ latitude. These findings reinforce the idea that using tropical hydrological proxy records to infer zonal-mean characteristics of the ITCZ may be misleading. Rather, tropical proxy records of precipitation, particularly those that record precipitation isotopes, serve as a guideline for regional hydrological changes while model simulations can put them in the context of zonal mean tropical convergence.

Newtonian nudging for a Richards equation-based distributed hydrological model

NASA Astrophysics Data System (ADS)

Paniconi, Claudio; Marrocu, Marino; Putti, Mario; Verbunt, Mark

The objective of data assimilation is to provide physically consistent estimates of spatially distributed environmental variables. In this study a relatively simple data assimilation method has been implemented in a relatively complex hydrological model. The data assimilation technique is Newtonian relaxation or nudging, in which model variables are driven towards observations by a forcing term added to the model equations. The forcing term is proportional to the difference between simulation and observation (relaxation component) and contains four-dimensional weighting functions that can incorporate prior knowledge about the spatial and temporal variability and characteristic scales of the state variable(s) being assimilated. The numerical model couples a three-dimensional finite element Richards equation solver for variably saturated porous media and a finite difference diffusion wave approximation based on digital elevation data for surface water dynamics. We describe the implementation of the data assimilation algorithm for the coupled model and report on the numerical and hydrological performance of the resulting assimilation scheme. Nudging is shown to be successful in improving the hydrological simulation results, and it introduces little computational cost, in terms of CPU and other numerical aspects of the model's behavior, in some cases even improving numerical performance compared to model runs without nudging. We also examine the sensitivity of the model to nudging term parameters including the spatio-temporal influence coefficients in the weighting functions. Overall the nudging algorithm is quite flexible, for instance in dealing with concurrent observation datasets, gridded or scattered data, and different state variables, and the implementation presented here can be readily extended to any of these features not already incorporated. Moreover the nudging code and tests can serve as a basis for implementation of more sophisticated data assimilation techniques in a Richards equation-based hydrological model.

Macroscale hydrologic modeling of ecologically relevant flow metrics

Treesearch

Seth J. Wenger; Charles H. Luce; Alan F. Hamlet; Daniel J. Isaak; Helen M. Neville

2010-01-01

Stream hydrology strongly affects the structure of aquatic communities. Changes to air temperature and precipitation driven by increased greenhouse gas concentrations are shifting timing and volume of streamflows potentially affecting these communities. The variable infiltration capacity (VIC) macroscale hydrologic model has been employed at regional scales to describe...

A simplified rainfall-runoff stochastic simulation method for an application of the SCHADEX method to ungauged catchments.

NASA Astrophysics Data System (ADS)

Penot, David; Paquet, Emmanuel; Lang, Michel

2014-05-01

SCHADEX is a probabilistic method for extreme flood estimation, developed and applied since 2006 at Electricité de France (EDF) for dam spillway design [Paquet et al., 2013]. SCHADEX is based on a semi-continuous rainfall-runoff simulation process. The method has been built around two models: a Multi-Exponential Weather Pattern (MEWP) distribution for rainfall probability estimation [Garavaglia et al., 2010] and the MORDOR hydrological model. To use SCHADEX in ungauged context, rainfall distribution and hydrological model must be regionalized. The regionalization of the MEWP rainfall distribution can be managed with SPAZM, a daily rainfall interpolator [Gottardi et al., 2012] which provides reasonable estimates of point and areal rainfall up to hight quantiles. The main issue remains to regionalize MORDOR which is heavily parametrized. A much more simple model has been considered: the SCS model. It is a well known model for event simulation [USDA SCS, 1985; Beven, 2003] and it relies on only one parameter. Then, the idea is to use the SCS model instead of MORDOR within a simplified stochastic simulation scheme to produce a distribution of flood volume from an exhaustive crossing between rainy events and catchment saturation hazards. The presentation details this process and its capacity to generate a runoff distribution based on catchment areal rainfall distribution. The simulation method depends on a unique parameter Smax, the maximum initial loss of the catchment. Then an initial loss S (between zero and Smax) can be drawn to account for the variability of catchment state (between dry and saturated). The distribution of initial loss (or conversely, of catchment saturation, as modeled by MORDOR) seems closely linked to the catchment's regime, therefore easily to regionalize. The simulation takes into account a snow contribution for snow driven catchments, and an antecedent runoff. The presentation shows the results of this stochastic procedure applied on 80 French catchments and its capacity to represent the asymptotic behaviour of the runoff distribution. References: K. J. Beven. Rainfall-Runoff modelling The Primer, British Library, 2003. F. Garavaglia, J. Gailhard, E. Paquet, M. Lang, R. Garçon, and P. Bernardara. Introducing a rainfall compound distribution model based on weather patterns sub-sampling. Hydrology and Earth System Sciences, 14(6):951-964, 2010. F. Gottardi, C. Obled, J. Gailhard, and E. Paquet. Statistical reanalysis of precipitation fields based on ground network data and weather patterns : Application over french mountains. Journal of Hydrology, 432-433:154-167, 2012. ISSN 0022-1694. E. Paquet, F. Garavaglia, R Garçon, and J. Gailhard. The schadex method : a semi-continuous rainfall-runoff simulation for extreme flood estimation. Journal of Hydrology, 2013. USDA SCS, National Engineering Handbook, Supplement A, Section 4, Chapter 10. Whashington DC, 1985.

Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations

PubMed Central

Wang, Wei; Lu, Hui; Yang, Dawen; Sothea, Khem; Jiao, Yang; Gao, Bin; Peng, Xueting; Pang, Zhiguo

2016-01-01

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998–2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002–2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability. PMID:27010692

Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations.

PubMed

Wang, Wei; Lu, Hui; Yang, Dawen; Sothea, Khem; Jiao, Yang; Gao, Bin; Peng, Xueting; Pang, Zhiguo

2016-01-01

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998-2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002-2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability.

Community-Driven Support in the Hydrologic Sciences through Data, Education and Outreach

NASA Astrophysics Data System (ADS)

Clark, E.

2015-12-01

The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) is a non-profit funded by the National Science Foundation to support water science research and education. As outlined in the CUAHSI Education and Outreach Strategy, our objectives are: 1) helping the member institutions communicate water science; 2) cross-disciplinary water education; 3) dissemination of research; 4) place-based water education using data services; and 5) broadening participation. Through the CUAHSI Water Data Center, online tools and resources are available to discover, download, and analyze multiple time-series water datasets across various parameters. CUAHSI supports novel graduate student research through the Pathfinder Fellowship program which has enhanced the interdisciplinary breadth of early-career research. Public outreach through the Let's Talk About Water film symposium and cyberseminar programs have proven effective in distributing research, leading to more recent development of virtual training workshops. By refining and building upon CUAHSI's existing programs, new training opportunities, collaborative projects, and community-building activities for the hydrologic sciences have come to fruition, such as the recent National Flood Interoperability Experiment with the NOAA's National Water Center.

Community-Driven Support in the Hydrologic Sciences through Data, Education and Outreach

NASA Astrophysics Data System (ADS)

Cox, P. R.

2014-12-01

The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) is a non-profit funded by the National Science Foundation to support water science research and education. As outlined in the CUAHSI Education and Outreach Strategy, our objectives are: 1) helping the member institutions communicate water science; 2) cross-disciplinary water education; 3) dissemination of research; 4) place-based water education using data services; and 5) broadening participation. Through the CUAHSI Water Data Center, online tools and resources are available to discover, download, and analyze multiple time-series water datasets across various parameters. CUAHSI supports novel graduate student research through the Pathfinder Fellowship program which has enhanced the interdisciplinary breadth of early-career research. Public outreach through the Let's Talk About Water film symposium and cyberseminar programs have proven effective in distributing research, leading to more recent development of virtual training workshops. By refining and building upon CUAHSI's existing programs, new training opportunities, collaborative projects, and community-building activities for the hydrologic sciences have come to fruition, such as the recent National Flood Interoperability Experiment with the NOAA's National Water Center.

CEREF: A hybrid data-driven model for forecasting annual streamflow from a socio-hydrological system

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Runoff scenarios of the Ötz catchment (Tyrol, Austria) considering climate change driven changes of the cryosphere

NASA Astrophysics Data System (ADS)

Helfricht, Kay; Schneeberger, Klaus; Welebil, Irene; Schöber, Johannes; Huss, Matthias; Formayer, Herbert; Huttenlau, Matthias; Schneider, Katrin

2014-05-01

The seasonal distribution of runoff in alpine catchments is markedly influenced by the cryospheric contribution (snow and ice). Long-term climate change will alter these reservoirs and consequently have an impact on the water balance. Glacierized catchments like the Ötztal (Tyrol, Austria) are particularly sensitive to changes in the cryosphere and the hydrological changes related to them. The Ötztal possesses an outstanding role in Austrian and international cryospheric research and reacts sensitive to changes in hydrology due to its socio-economic structure (e.g. importance of tourism, hydro-power). In this study future glacier scenarios for the runoff calculations in the Ötztal catchment are developed. In addition to climatological scenario data, glacier scenarios were established for the hydrological simulation of future runoff. Glacier outlines and glacier surface elevation changes of the Austrian Glacier Inventory were used to derive present ice thickness distribution and scenarios of glacier area distribution. Direct effects of climate change (i.e. temperature and precipitation change) and indirect effects in terms of variations in the cryosphere were considered for the analysis of the mean runoff and particularly flood frequencies. Runoff was modelled with the hydrological model HQSim, which was calibrated for the runoff gauges at Brunau, Obergurgl and Vent. For a sensitivity study, the model was driven by separate glacier scenarios. Keeping glacier area constant, variable climate input was used to separate the effect of climate sensitivity. Results of the combination of changed glacier areas and changed climate input were subsequently analysed. Glacier scenarios show first a decrease in volume, before glacier area shrinks. The applied method indicates a 50% ice volume loss by 2050 relative to today. Further, model results show a reduction in glacier volume and area to less than 20% of the current ice cover towards the end of the 21st century. The effect of reduced glacier areas can be seen in a reduction of runoff particularly in summer. Maintaining the glacier areas constant, runoff would increase in summer month caused by higher ice melt under climate change conditions. Also runoff increases in spring and fall is expected due to a shift from solid to liquid precipitation in the mountain catchments. The simulation of the combination of glacier change and climate change scenarios results in an increase in runoff in spring due to a shift in the snowline and a decrease in runoff in summer caused by reduced glacier area.

Quantifying the Hydrologic Effect of Climate Variability in the Lower Colorado Basin

NASA Astrophysics Data System (ADS)

Switanek, M.; Troch, P. A.

2007-12-01

Regional climate patterns are driven in large part by ocean states and associated atmospheric circulations, but modified through feedbacks from land surface conditions. The latter defines the climate elasticity of a river basin. Many regions that lie between semi-arid and semi-humid zones with seasonal rainfall, for instance, experience prolonged periods of wet and dry spells. Understanding the triggers that bring a river basin from one state (e.g. wet period of late 90s in the Colorado basin) abruptly to another state (multi-year drought initiated in 2001 to present) is what motivates the present study. Our research methodology investigates the causes of regional climate variability and its effect on hydrologic response. By correlating, using different monthly time lags, sea surface temperatures (SST) and sea level pressures (SLP) with basin averaged precipitation and surface temperature, we determine the most influential regions of the Pacific Ocean on lower Colorado climate variability. Using the most correlated data for each month, we derive precipitation and temperature distributions under similar conditions to that of the El Niño Southern Oscillation (ENSO). We compare the distributions of the climatic data, given ENSO constraints on SST and SLP, to the distributions considering non-ENSO years. Finally, we use observed stream flows and climatic data to determine the basin's climate elasticity. This allows us to quantitatively translate the predicted regional climate effects of ENSO on hydrologic response. Our presentation will use data for the Little Colorado as an example to demonstrate the procedure and produce preliminary results.

Hydrological patterns in warming permafrost: comparing results from a control and drained site on a floodplain tundra near Chersky, Northeast Siberia

NASA Astrophysics Data System (ADS)

Boelck, Sandra; Goeckede, Mathias; Hildebrandt, Anke; Vonk, Jorien; Heimann, Martin

2017-04-01

Permafrost areas represent a major reservoir for organic carbon. At the same time, permafrost ecosystems are very susceptible to changing climate conditions. The stability of this reservoir, i.e. changes in lateral and vertical carbon fluxes in permafrost ecosystems, largely depends on groundwater level, temperature and vegetation community. Particularly during summer when the soil thaws and a so-called active layer develops, fluctuations in carbon flux rates are often dominantly driven by water availability. Such dry soil conditions are expected to become more frequent in the future due to deepening active layers as a consequence of climate change. This could result in degradation of polygonal tundra landscape properties with channelled water transport pathways. Therefore, water table depth and the associated groundwater fluxes are crucial to understand transport patterns and to quantify the lateral export of carbon through an aquatic system. Consequently, a fundamental understanding of hydrological patterns on ecosystem structure and function is required to close the carbon balance of permafrost ecosystems. This study focuses on small-scale hydrological patterns and its influencing factors, such as topography and precipitation events. Near Chersky, Northeast Siberia, we monitored (i) a control site of floodplain tundra, and (ii) a drained site, characterised by a drainage ring which was constructed in 2004, to study the effects of water availability on the carbon cycle. This experimental disturbance simulates drainage effects following the degradation of ice-rich permafrost ecosystems under future climate change. Continuous monitoring of water table depth in drained and control areas revealed small-scale water table variations. At several key locations, we collected water samples to determine the isotopic composition (δ18O, δD) of surface water, suprapermafrost groundwater and precipitation. Furthermore, a weir at the drainage ditch was constructed to directly measure the discharge of the drained system. This hydrological sampling programme was complemented by continuous monitoring of atmospheric vertical turbulent carbon fluxes and meteorological conditions by two eddy-covariance towers on each site. Our results from the hydrological sampling campaign of summer 2016 indicate that total discharge through the drained system was mainly driven by precipitation events as well as modified evaporative loss due to temperature changes. The distributed network of groundwater gauges allows deriving lateral, local scale groundwater flow direction and its spatial variability, as well as the response to precipitation events within different parts of this ecosystem. Isotopic analysis of water samples showed the contribution of specific end member water sources, and how these vary across the season while the active layer deepens. Future research will focus on carbon fluxes, distribution and sources in relation to hydrological patterns.

Application of global datasets for hydrological modelling of a remote, snowmelt driven catchment in the Canadian Sub-Arctic

NASA Astrophysics Data System (ADS)

Casson, David; Werner, Micha; Weerts, Albrecht; Schellekens, Jaap; Solomatine, Dimitri

2017-04-01

Hydrological modelling in the Canadian Sub-Arctic is hindered by the limited spatial and temporal coverage of local meteorological data. Local watershed modelling often relies on data from a sparse network of meteorological stations with a rough density of 3 active stations per 100,000 km2. Global datasets hold great promise for application due to more comprehensive spatial and extended temporal coverage. A key objective of this study is to demonstrate the application of global datasets and data assimilation techniques for hydrological modelling of a data sparse, Sub-Arctic watershed. Application of available datasets and modelling techniques is currently limited in practice due to a lack of local capacity and understanding of available tools. Due to the importance of snow processes in the region, this study also aims to evaluate the performance of global SWE products for snowpack modelling. The Snare Watershed is a 13,300 km2 snowmelt driven sub-basin of the Mackenzie River Basin, Northwest Territories, Canada. The Snare watershed is data sparse in terms of meteorological data, but is well gauged with consistent discharge records since the late 1970s. End of winter snowpack surveys have been conducted every year from 1978-present. The application of global re-analysis datasets from the EU FP7 eartH2Observe project are investigated in this study. Precipitation data are taken from Multi-Source Weighted-Ensemble Precipitation (MSWEP) and temperature data from Watch Forcing Data applied to European Reanalysis (ERA)-Interim data (WFDEI). GlobSnow-2 is a global Snow Water Equivalent (SWE) measurement product funded by the European Space Agency (ESA) and is also evaluated over the local watershed. Downscaled precipitation, temperature and potential evaporation datasets are used as forcing data in a distributed version of the HBV model implemented in the WFLOW framework. Results demonstrate the successful application of global datasets in local watershed modelling, but that validation of actual frozen precipitation and snowpack conditions is very difficult. The distributed hydrological model shows good streamflow simulation performance based on statistical model evaluation techniques. Results are also promising for inter-annual variability, spring snowmelt onset and time to peak flows. It is expected that data assimilation of stream flow using an Ensemble Kalman Filter will further improve model performance. This study shows that global re-analysis datasets hold great potential for understanding the hydrology and snowpack dynamics of the expansive and data sparse sub-Arctic. However, global SWE products will require further validation and algorithm improvements, particularly over boreal forest and lake-rich regions.

Methodological challenges to bridge the gap between regional climate and hydrology models

NASA Astrophysics Data System (ADS)

Bozhinova, Denica; José Gómez-Navarro, Juan; Raible, Christoph; Felder, Guido

2017-04-01

The frequency and severity of floods worldwide, together with their impacts, are expected to increase under climate change scenarios. It is therefore very important to gain insight into the physical mechanisms responsible for such events in order to constrain the associated uncertainties. Model simulations of the climate and hydrological processes are important tools that can provide insight in the underlying physical processes and thus enable an accurate assessment of the risks. Coupled together, they can provide a physically consistent picture that allows to assess the phenomenon in a comprehensive way. However, climate and hydrological models work at different temporal and spatial scales, so there are a number of methodological challenges that need to be carefully addressed. An important issue pertains the presence of biases in the simulation of precipitation. Climate models in general, and Regional Climate models (RCMs) in particular, are affected by a number of systematic biases that limit their reliability. In many studies, prominently the assessment of changes due to climate change, such biases are minimised by applying the so-called delta approach, which focuses on changes disregarding absolute values that are more affected by biases. However, this approach is not suitable in this scenario, as the absolute value of precipitation, rather than the change, is fed into the hydrological model. Therefore, bias has to be previously removed, being this a complex matter where various methodologies have been proposed. In this study, we apply and discuss the advantages and caveats of two different methodologies that correct the simulated precipitation to minimise differences with respect an observational dataset: a linear fit (FIT) of the accumulated distributions and Quantile Mapping (QM). The target region is Switzerland, and therefore the observational dataset is provided by MeteoSwiss. The RCM is the Weather Research and Forecasting model (WRF), driven at the boundaries by the Community Earth System Model (CESM). The raw simulation driven by CESM exhibit prominent biases that stand out in the evolution of the annual cycle and demonstrate that the correction of biases is mandatory in this type of studies, rather than a minor correction that might be neglected. The simulation spans the period 1976 - 2005, although the application of the correction is carried out on a daily basis. Both methods lead to a corrected field of precipitation that respects the temporal evolution of the simulated precipitation, at the same time that mimics the distribution of precipitation according to the one in the observations. Due to the nature of the two methodologies, there are important differences between the products of both corrections, that lead to dataset with different properties. FIT is generally more accurate regarding the reproduction of the tails of the distribution, i.e. extreme events, whereas the nature of QM renders it a general-purpose correction whose skill is equally distributed across the full distribution of precipitation, including central values.

Data-Driven Model Uncertainty Estimation in Hydrologic Data Assimilation

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding

NASA Astrophysics Data System (ADS)

Kelleher, Christa; McGlynn, Brian; Wagener, Thorsten

2017-07-01

Distributed catchment models are widely used tools for predicting hydrologic behavior. While distributed models require many parameters to describe a system, they are expected to simulate behavior that is more consistent with observed processes. However, obtaining a single set of acceptable parameters can be problematic, as parameter equifinality often results in several behavioral sets that fit observations (typically streamflow). In this study, we investigate the extent to which equifinality impacts a typical distributed modeling application. We outline a hierarchical approach to reduce the number of behavioral sets based on regional, observation-driven, and expert-knowledge-based constraints. For our application, we explore how each of these constraint classes reduced the number of behavioral parameter sets and altered distributions of spatiotemporal simulations, simulating a well-studied headwater catchment, Stringer Creek, Montana, using the distributed hydrology-soil-vegetation model (DHSVM). As a demonstrative exercise, we investigated model performance across 10 000 parameter sets. Constraints on regional signatures, the hydrograph, and two internal measurements of snow water equivalent time series reduced the number of behavioral parameter sets but still left a small number with similar goodness of fit. This subset was ultimately further reduced by incorporating pattern expectations of groundwater table depth across the catchment. Our results suggest that utilizing a hierarchical approach based on regional datasets, observations, and expert knowledge to identify behavioral parameter sets can reduce equifinality and bolster more careful application and simulation of spatiotemporal processes via distributed modeling at the catchment scale.

Insight into runoff characteristics using hydrological modeling in the data-scarce southern Tibetan Plateau: Past, present, and future

PubMed Central

Cai, Mingyong; Yang, Shengtian; Zhao, Changsen; Zhou, Qiuwen; Hou, Lipeng

2017-01-01

Regional hydrological modeling in ungauged regions has attracted growing attention in water resources research. The southern Tibetan Plateau often suffers from data scarcity in watershed hydrological simulation and water resources assessment. This hinders further research characterizing the water cycle and solving international water resource issues in the area. In this study, a multi-spatial data based Distributed Time-Variant Gain Model (MS-DTVGM) is applied to the Yarlung Zangbo River basin, an important international river basin in the southern Tibetan Plateau with limited meteorological data. This model is driven purely by spatial data from multiple sources and is independent of traditional meteorological data. Based on the methods presented in this study, daily snow cover and potential evapotranspiration data in the Yarlung Zangbo River basin in 2050 are obtained. Future (2050) climatic data (precipitation and air temperature) from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR5) are used to study the hydrological response to climate change. The result shows that river runoff will increase due to precipitation and air temperature changes by 2050. Few differences are found between daily runoff simulations from different Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5 and RCP8.5) for 2050. Historical station observations (1960–2000) at Nuxia and model simulations for two periods (2006–2009 and 2050) are combined to study inter-annual and intra-annual runoff distribution and variability. The inter-annual runoff variation is stable and the coefficient of variation (CV) varies from 0.21 to 0.27. In contrast, the intra-annual runoff varies significantly with runoff in summer and autumn accounting for more than 80% of the total amount. Compared to the historical period (1960–2000), the present period (2006–2009) has a slightly uneven intra-annual runoff temporal distribution, and becomes more balanced in the future (2050). PMID:28486483

Insight into runoff characteristics using hydrological modeling in the data-scarce southern Tibetan Plateau: Past, present, and future.

PubMed

Cai, Mingyong; Yang, Shengtian; Zhao, Changsen; Zhou, Qiuwen; Hou, Lipeng

2017-01-01

Regional hydrological modeling in ungauged regions has attracted growing attention in water resources research. The southern Tibetan Plateau often suffers from data scarcity in watershed hydrological simulation and water resources assessment. This hinders further research characterizing the water cycle and solving international water resource issues in the area. In this study, a multi-spatial data based Distributed Time-Variant Gain Model (MS-DTVGM) is applied to the Yarlung Zangbo River basin, an important international river basin in the southern Tibetan Plateau with limited meteorological data. This model is driven purely by spatial data from multiple sources and is independent of traditional meteorological data. Based on the methods presented in this study, daily snow cover and potential evapotranspiration data in the Yarlung Zangbo River basin in 2050 are obtained. Future (2050) climatic data (precipitation and air temperature) from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR5) are used to study the hydrological response to climate change. The result shows that river runoff will increase due to precipitation and air temperature changes by 2050. Few differences are found between daily runoff simulations from different Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5 and RCP8.5) for 2050. Historical station observations (1960-2000) at Nuxia and model simulations for two periods (2006-2009 and 2050) are combined to study inter-annual and intra-annual runoff distribution and variability. The inter-annual runoff variation is stable and the coefficient of variation (CV) varies from 0.21 to 0.27. In contrast, the intra-annual runoff varies significantly with runoff in summer and autumn accounting for more than 80% of the total amount. Compared to the historical period (1960-2000), the present period (2006-2009) has a slightly uneven intra-annual runoff temporal distribution, and becomes more balanced in the future (2050).

Using a spatially-distributed hydrologic biogeochemistry model with nitrogen transport to study the spatial variation of carbon stocks and fluxes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; He, Y.; Davis, K. J.

2017-12-01

Most current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve topographically driven land surface heterogeneity (e.g., lateral water flow, soil moisture, soil temperature, solar radiation) or the spatial pattern of nutrient availability. A spatially distributed forest biogeochemical model with nitrogen transport, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM, and adding an advection dominated nitrogen transport module. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model, and is augmented by adding a topographic solar radiation module. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while nitrogen is transported among model grids via surface and subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation, while BBGC provides Flux-PIHM with spatially-distributed leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills Critical Zone Observatory. The model-predicted aboveground vegetation carbon and soil carbon distributions generally agree with the macro patterns observed within the watershed. The importance of abiotic variables (including soil moisture, soil temperature, solar radiation, and soil mineral nitrogen) in predicting aboveground carbon distribution is calculated using a random forest. The result suggests that the spatial pattern of aboveground carbon is controlled by the distribution of soil mineral nitrogen. A Flux-PIHM-BGC simulation without the nitrogen transport module is also executed. The model without nitrogen transport fails in predicting the spatial patterns of vegetation carbon, which indicates the importance of having a nitrogen transport module in spatially distributed ecohydrologic modeling.

Combining hydrological modeling and remote sensing observations to enable data-driven decision making for Devils Lake flood mitigation in a changing climate

NASA Astrophysics Data System (ADS)

Zhang, X.; Lim, Y. H.; Teng, W. L.; Kirilenko, A.

2010-12-01

The water level of Devils Lake in North Dakota has been rising since 1993, reaching record highs in each of the past three years. Nearly $1 billion have already been spent in mitigating the flooding impacts. If the current wet cycle continues, Devils Lake, a terminal lake currently at 1452 ft, will likely overflow at 1458 ft and cause extensive downstream flooding, with devastating environmental and economic impacts at local, regional, and international levels. We have implemented a distributed rainfall-runoff model, HEC-HMS, to simulate the hydro-dynamics of the lake watershed, and used NASA's remote sensing data, including the TRMM Multi-Satellite Precipitation Analysis (TMPA) and AIRS surface air temperature, to drive the model. The entire watershed with an area of about 10,000 km2 was delineated into six sub-basins using 30 m DEM, with each sub-basin having several hundred thousand hydrological cells. We generated a fine-resolution weather data set, based on a combination of ground observations and remote sensing data, to drive the hydrological simulations. Compared with a very limited number of data series available from five meteorological stations located within the watershed (none belonging to the US Historical Climate Network), NASA data offer a uniform coverage and dense distribution. The satellite and ground observations of precipitation and temperature agreed well with each other. However, if only weather station data were used, the observed runoff was underestimated by at least 30%, regardless of the value of the snow melt-rate coefficient used. The inclusion of NASA data, on the other hand, greatly improved the accuracy of runoff estimates, to within 2% of observations. Better runoff estimates will enable better predictions of water levels. The watershed hydrological model is coupled with a reservoir model, HEC-ResSim. The calibration against the observed lake elevation and monthly evaporation estimates from 2001 to 2004 showed a lake seepage varying between 500 - 1300 cfs. The coupled models can reproduce water level of the lake at sub-feet accuracy, and will be driven by the downscaled CMIP-3 projections of future climate, to provide decision support for mitigation measures in response to the potential flooding.

Rainfall and hydrological stability alter the impact of top predators on food web structure and function.

PubMed

Marino, Nicholas A C; Srivastava, Diane S; MacDonald, A Andrew M; Leal, Juliana S; Campos, Alice B A; Farjalla, Vinicius F

2017-02-01

Climate change will alter the distribution of rainfall, with potential consequences for the hydrological dynamics of aquatic habitats. Hydrological stability can be an important determinant of diversity in temporary aquatic habitats, affecting species persistence and the importance of predation on community dynamics. As such, prey are not only affected by drought-induced mortality but also the risk of predation [a non-consumptive effect (NCE)] and actual consumption by predators [a consumptive effect (CE)]. Climate-induced changes in rainfall may directly, or via altered hydrological stability, affect predator-prey interactions and their cascading effects on the food web, but this has rarely been explored, especially in natural food webs. To address this question, we performed a field experiment using tank bromeliads and their aquatic food web, composed of predatory damselfly larvae, macroinvertebrate prey and bacteria. We manipulated the presence and consumption ability of damselfly larvae under three rainfall scenarios (ambient, few large rainfall events and several small rainfall events), recorded the hydrological dynamics within bromeliads and examined the effects on macroinvertebrate colonization, nutrient cycling and bacterial biomass and turnover. Despite our large perturbations of rainfall, rainfall scenario had no effect on the hydrological dynamics of bromeliads. As a result, macroinvertebrate colonization and nutrient cycling depended on the hydrological stability of bromeliads, with no direct effect of rainfall or predation. In contrast, rainfall scenario determined the direction of the indirect effects of predators on bacteria, driven by both predator CEs and NCEs. These results suggest that rainfall and the hydrological stability of bromeliads had indirect effects on the food web through changes in the CEs and NCEs of predators. We suggest that future studies should consider the importance of the variability in hydrological dynamics among habitats as well as the biological mechanisms underlying the ecological responses to climate change. © 2016 John Wiley & Sons Ltd.

A Community Publication and Dissemination System for Hydrology Education Materials

NASA Astrophysics Data System (ADS)

Ruddell, B. L.

2015-12-01

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

Reproductive ecology of interior least tern and piping plover in relation to Platte River hydrology and sandbar dynamics.

PubMed

Farnsworth, Jason M; Baasch, David M; Smith, Chadwin B; Werbylo, Kevin L

2017-05-01

Investigations of breeding ecology of interior least tern ( Sternula antillarum athalassos ) and piping plover ( Charadrius melodus ) in the Platte River basin in Nebraska, USA, have embraced the idea that these species are physiologically adapted to begin nesting concurrent with the cessation of spring floods. Low use and productivity on contemporary Platte River sandbars have been attributed to anthropomorphically driven changes in basin hydrology and channel morphology or to unusually late annual runoff events. We examined distributions of least tern and piping plover nest initiation dates in relation to the hydrology of the historical central Platte River (CPR) and contemporary CPR and lower Platte River (LPR). We also developed an emergent sandbar habitat model to evaluate the potential for reproductive success given observed hydrology, stage-discharge relationships, and sandbar height distributions. We found the timing of the late-spring rise to be spatially and temporally consistent, typically occurring in mid-June. However, piping plover nest initiation peaks in May and least tern nest initiation peaks in early June; both of which occur before the late spring rise. In neither case does there appear to be an adaptation to begin nesting concurrent with the cessation of spring floods. As a consequence, there are many years when no successful reproduction is possible because emergent sandbar habitat is inundated after most nests have been initiated, and there is little potential for successful renesting. The frequency of nest inundation, in turn, severely limits the potential for maintenance of stable species subpopulations on Platte River sandbars. Why then did these species expand into and persist in a basin where the hydrology is not ideally suited to their reproductive ecology? We hypothesize the availability and use of alternative off-channel nesting habitats, like sandpits, may allow for the maintenance of stable species subpopulations in the Platte River basin.

Coupling of the simultaneous heat and water model with a distributed hydrological model and evaluation of the combined model in a cold region watershed

USDA-ARS?s Scientific Manuscript database

To represent the effects of frozen soil on hydrology in cold regions, a new physically based distributed hydrological model has been developed by coupling the simultaneous heat and water model (SHAW) with the geomorphology based distributed hydrological model (GBHM), under the framework of the water...

Development of a distributed biosphere hydrological model and its evaluation with the Southern Great Plains Experiments (SGP97 and SGP99)

USDA-ARS?s Scientific Manuscript database

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

The Mekong's future flows under multiple driving factors: How future climate change, hydropower developments and irrigation expansion drive hydrological changes?

NASA Astrophysics Data System (ADS)

Hoang, L. P.; van Vliet, M. T. H.; Lauri, H.; Kummu, M.; Koponen, J.; Supit, I.; Leemans, R.; Kabat, P.; Ludwig, F.

2016-12-01

The Mekong River's flows and water resources are in many ways essential for sustaining economic growths, flood security of about 70 million people and biodiversity in one of the world's most ecologically productive wetland systems. The river's hydrological cycle, however, are increasingly perturbed by climate change, large-scale hydropower developments and rapid irrigated land expansions. This study presents an integrated impact assessment to characterize and quantify future hydrological changes induced by these driving factors, both separately and combined. We have integrated a crop simulation module and a hydropower dam module into a distributed hydrological model (VMod) and simulated the Mekong's hydrology under multiple climate change and development scenarios. Our results show that the Mekong's hydrological regime will experience substantial changes caused by the considered factors. Magnitude-wise, hydropower dam developments exhibit the largest impacts on river flows, with projected higher flows (up to +35%) during the dry season and lower flows (up to -44%) during the wet season. Annual flow changes caused by the dams, however, are relatively marginal. In contrast to this, climate change is projected to increase the Mekong's annual flows (up to +16%) while irrigated land expansions result in annual flow reductions (-1% to -3%). Combining the impacts of these three drivers, we found that river flow changes, especially those at the monthly scale, largely differ from changes under the individual driving factors. This is explained by large differences in impacts' magnitudes and contrasting impacts' directions for the individual drivers. We argue that the Mekong's future flows are likely driven by multiple factors and thus advocate for integrated assessment approaches and tools that support proper considerations of these factors and their interplays.

A "total parameter estimation" method in the varification of distributed hydrological models

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Origin of the Valley Networks On Mars: A Hydrological Perspective

NASA Technical Reports Server (NTRS)

Gulick, Virginia C.

2000-01-01

The geomorphology of the Martian valley networks is examined from a hydrological perspective for their compatibility with an origin by rainfall, globally higher heat flow, and localized hydrothermal systems. Comparison of morphology and spatial distribution of valleys on geologic surfaces with terrestrial fluvial valleys suggests that most Martian valleys are probably not indicative of a rainfall origin, nor are they indicative of formation by an early global uniformly higher heat flow. In general, valleys are not uniformly distributed within geologic surface units as are terrestrial fluvial valleys. Valleys tend to form either as isolated systems or in clusters on a geologic surface unit leaving large expanses of the unit virtually untouched by erosion. With the exception of fluvial valleys on some volcanoes, most Martian valleys exhibit a sapping morphology and do not appear to have formed along with those that exhibit a runoff morphology. In contrast, terrestrial sapping valleys form from and along with runoff valleys. The isolated or clustered distribution of valleys suggests localized water sources were important in drainage development. Persistent ground-water outflow driven by localized, but vigorous hydrothermal circulation associated with magmatism, volcanism, impacts, or tectonism is, however, consistent with valley morphology and distribution. Snowfall from sublimating ice-covered lakes or seas may have provided an atmospheric water source for the formation of some valleys in regions where the surface is easily eroded and where localized geothermal/hydrothermal activity is sufficient to melt accumulated snowpacks.

A question driven socio-hydrological modeling process

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

Large-scale runoff generation - parsimonious parameterisation using high-resolution topography

NASA Astrophysics Data System (ADS)

Gong, L.; Halldin, S.; Xu, C.-Y.

2011-08-01

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting at very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TRG only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3" (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

Large-scale runoff generation - parsimonious parameterisation using high-resolution topography

NASA Astrophysics Data System (ADS)

Gong, L.; Halldin, S.; Xu, C.-Y.

2010-09-01

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting a very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TGR only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3'' (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

Aspect-related Vegetation Differences Amplify Soil Moisture Variability in Semiarid Landscapes

NASA Astrophysics Data System (ADS)

Yetemen, O.; Srivastava, A.; Kumari, N.; Saco, P. M.

2017-12-01

Soil moisture variability (SMV) in semiarid landscapes is affected by vegetation, soil texture, climate, aspect, and topography. The heterogeneity in vegetation cover that results from the effects of microclimate, terrain attributes (slope gradient, aspect, drainage area etc.), soil properties, and spatial variability in precipitation have been reported to act as the dominant factors modulating SMV in semiarid ecosystems. However, the role of hillslope aspect in SMV, though reported in many field studies, has not received the same degree of attention probably due to the lack of extensive large datasets. Numerical simulations can then be used to elucidate the contribution of aspect-driven vegetation patterns to this variability. In this work, we perform a sensitivity analysis to study on variables driving SMV using the CHILD landscape evolution model equipped with a spatially-distributed solar-radiation component that couples vegetation dynamics and surface hydrology. To explore how aspect-driven vegetation heterogeneity contributes to the SMV, CHILD was run using a range of parameters selected to reflect different scenarios (from uniform to heterogeneous vegetation cover). Throughout the simulations, the spatial distribution of soil moisture and vegetation cover are computed to estimate the corresponding coefficients of variation. Under the uniform spatial precipitation forcing and uniform soil properties, the factors affecting the spatial distribution of solar insolation are found to play a key role in the SMV through the emergence of aspect-driven vegetation patterns. Hence, factors such as catchment gradient, aspect, and latitude, define water stress and vegetation growth, and in turn affect the available soil moisture content. Interestingly, changes in soil properties (porosity, root depth, and pore-size distribution) over the domain are not as effective as the other factors. These findings show that the factors associated to aspect-related vegetation differences amplify the soil moisture variability of semi-arid landscapes.

Evaluation of Probable Maximum Precipitation and Flood under Climate Change in the 21st Century

NASA Astrophysics Data System (ADS)

Gangrade, S.; Kao, S. C.; Rastogi, D.; Ashfaq, M.; Naz, B. S.; Kabela, E.; Anantharaj, V. G.; Singh, N.; Preston, B. L.; Mei, R.

2016-12-01

Critical infrastructures are potentially vulnerable to extreme hydro-climatic events. Under a warming environment, the magnitude and frequency of extreme precipitation and flood are likely to increase enhancing the needs to more accurately quantify the risks due to climate change. In this study, we utilized an integrated modeling framework that includes the Weather Research Forecasting (WRF) model and a high resolution distributed hydrology soil vegetation model (DHSVM) to simulate probable maximum precipitation (PMP) and flood (PMF) events over Alabama-Coosa-Tallapoosa River Basin. A total of 120 storms were selected to simulate moisture maximized PMP under different meteorological forcings, including historical storms driven by Climate Forecast System Reanalysis (CFSR) and baseline (1981-2010), near term future (2021-2050) and long term future (2071-2100) storms driven by Community Climate System Model version 4 (CCSM4) under Representative Concentrations Pathway 8.5 emission scenario. We also analyzed the sensitivity of PMF to various antecedent hydrologic conditions such as initial soil moisture conditions and tested different compulsive approaches. Overall, a statistical significant increase is projected for future PMP and PMF, mainly attributed to the increase of background air temperature. The ensemble of simulated PMP and PMF along with their sensitivity allows us to better quantify the potential risks associated with hydro-climatic extreme events on critical energy-water infrastructures such as major hydropower dams and nuclear power plants.

Cyberinfrastructure to Support Collaborative and Reproducible Computational Hydrologic Modeling

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Creating Data and Modeling Enabled Hydrology Instruction Using Collaborative Approach

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Genetic Programming for Automatic Hydrological Modelling

NASA Astrophysics Data System (ADS)

Chadalawada, Jayashree; Babovic, Vladan

2017-04-01

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

Global and Regional Real-time Systems for Flood and Drought Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Hong, Y.; Gourley, J. J.; Xue, X.; Flamig, Z.

2015-12-01

A Hydrometeorological Extreme Mapping and Prediction System (HyXtreme-MaP), initially built upon the Coupled Routing and Excess STorage (CREST) distributed hydrological model, is driven by real-time quasi-global TRMM/GPM satellites and by the US Multi-Radar Multi-Sensor (MRMS) radar network with dual-polarimetric upgrade to simulate streamflow, actual ET, soil moisture and other hydrologic variables at 1/8th degree resolution quasi-globally (http://eos.ou.edu) and at 250-meter 2.5-mintue resolution over the Continental United States (CONUS: http://flash.ou.edu).­ Multifaceted and collaborative by-design, this end-to-end research framework aims to not only integrate data, models, and applications but also brings people together (i.e., NOAA, NASA, University researchers, and end-users). This presentation will review the progresses, challenges and opportunities of such HyXTREME-MaP System used to monitor global floods and droughts, and also to predict flash floods over the CONUS.

Global change effects on biogeochemical processes of Argentinian estuaries: an overview of vulnerabilities and ecohydrological adaptive outlooks.

PubMed

Kopprio, Germán A; Biancalana, Florencia; Fricke, Anna; Garzón Cardona, John E; Martínez, Ana; Lara, Rubén J

2015-02-28

The aims of this work are to provide an overview of the current stresses of estuaries in Argentina and to propose adaptation strategies from an ecohydrological approach. Several Argentinian estuaries are impacted by pollutants, derived mainly from sewage discharge and agricultural or industrial activities. Anthropogenic impacts are expected to rise with increasing human population. Climate-driven warmer temperature and hydrological changes will alter stratification, residence time, oxygen content, salinity, pollutant distribution, organism physiology and ecology, and nutrient dynamics. Good water quality is essential in enhancing estuarine ecological resilience to disturbances brought on by global change. The preservation, restoration, and creation of wetlands will help to protect the coast from erosion, increase sediment accretion rates, and improve water quality by removing excess nutrients and pollutants. The capacity of hydrologic basin ecosystems to absorb human and natural impacts can be improved through holistic management, which should consider social vulnerability in complex human-natural systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

A satellite view of aerosols in the climate system

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Tanre, Didier; Boucher, Olivier

2002-01-01

Anthropogenic aerosols are intricately linked to the climate system and to the hydrologic cycle. The net effect of aerosols is to cool the climate system by reflecting sunlight. Depending on their composition, aerosols can also absorb sunlight in the atmosphere, further cooling the surface but warming the atmosphere in the process. These effects of aerosols on the temperature profile, along with the role of aerosols as cloud condensation nuclei, impact the hydrologic cycle, through changes in cloud cover, cloud properties and precipitation. Unravelling these feedbacks is particularly difficult because aerosols take a multitude of shapes and forms, ranging from desert dust to urban pollution, and because aerosol concentrations vary strongly over time and space. To accurately study aerosol distribution and composition therefore requires continuous observations from satellites, networks of ground-based instruments and dedicated field experiments. Increases in aerosol concentration and changes in their composition, driven by industrialization and an expanding population, may adversely affect the Earth's climate and water supply.

GEOMORPHIC AND HYDROLOGIC INTERACTIONS IN THE DETERMINATION OF EQUILIBRIUM SOIL DEPTH

NASA Astrophysics Data System (ADS)

Nicotina, L.; Rinaldo, A.; Tarboton, D. G.

2009-12-01

In this work we propose numerical studies of the interactions between hydrology and geomorphology in the formation of the actual soil depth that drives ecologic and hydrologic processes. Sediment transport and geomorphic landscape evolution processes (i.e. erosion/deposition vs. soil production) strongly influence hydrology, carbon sequestration, soil formation and stream water chemistry. The process of rock conversion into soil originates a strong hydrologic control through the formation of the soil depth that participates to hydrologic processes, influence vegetation type and patterns and actively participate in the co-evolution mechanisms that shape the landscape. The description of spatial patterns in hydrology is usually constrained by the availability of field data, especially when dealing with quantities that are not easily measurable. In these circumstances it is deemed fundamental the capability of deriving hydrologic boundary conditions from physically based approaches. Here we aim, in a general framework, at the formulation of an integrated approach for the prediction of soil depth by mean of i) soil production models and ii) geomorphic transport laws. The processes that take place in the critical zone are driven by the extension of it and have foundamental importance over short time scales as well as on geologic time scales (i.e. as biota affects climate that drives hydrology and thus contributes on shaping the landscape). Our study aims at the investigation of the relationships between soil depth, topography and runoff production, we also address the mechanisms that bring to the development of actual patterns of soil depths which at the same time influence runoff. We use a schematic representation of the hydrologic processes that relies on the description of the topography (throuh a topographic wetness index) and the spatially variable soil depths. Such a model is applied in order to investigate the development of equilibrium soil depth patterns under different hydrologic regimes and under two different hypothesis for the dynamic equilibrium (local or topographic dynamic equilibrium) of soils as well as the temporal scales associated to them. The obtained results are tested against a field survey of soil depths carried out in the Dry Creek catchment located in southern Idaho, near Boise (USA). The develped approach results to be suitable for the problem at hand as the hydrologic model results to be sensitive to the soil depths distribution.

Parallel computing method for simulating hydrological processesof large rivers under climate change

NASA Astrophysics Data System (ADS)

Wang, H.; Chen, Y.

2016-12-01

Climate change is one of the proverbial global environmental problems in the world.Climate change has altered the watershed hydrological processes in time and space distribution, especially in worldlarge rivers.Watershed hydrological process simulation based on physically based distributed hydrological model can could have better results compared with the lumped models.However, watershed hydrological process simulation includes large amount of calculations, especially in large rivers, thus needing huge computing resources that may not be steadily available for the researchers or at high expense, this seriously restricted the research and application. To solve this problem, the current parallel method are mostly parallel computing in space and time dimensions.They calculate the natural features orderly thatbased on distributed hydrological model by grid (unit, a basin) from upstream to downstream.This articleproposes ahigh-performancecomputing method of hydrological process simulation with high speedratio and parallel efficiency.It combinedthe runoff characteristics of time and space of distributed hydrological model withthe methods adopting distributed data storage, memory database, distributed computing, parallel computing based on computing power unit.The method has strong adaptability and extensibility,which means it canmake full use of the computing and storage resources under the condition of limited computing resources, and the computing efficiency can be improved linearly with the increase of computing resources .This method can satisfy the parallel computing requirements ofhydrological process simulation in small, medium and large rivers.

Vulnerability of riparian ecosystems to elevated CO2 and climate change in arid and semiarid western North America

USGS Publications Warehouse

Perry, Laura G.; Andersen, Douglas C.; Reynolds, Lindsay V.; Nelson, S. Mark; Shafroth, Patrick B.

2012-01-01

Riparian ecosystems, already greatly altered by water management, land development, and biological invasion, are being further altered by increasing atmospheric CO2 concentrations ([CO2]) and climate change, particularly in arid and semiarid (dryland) regions. In this literature review, we (1) summarize expected changes in [CO2], climate, hydrology, and water management in dryland western North America, (2) consider likely effects of those changes on riparian ecosystems, and (3) identify critical knowledge gaps. Temperatures in the region are rising and droughts are becoming more frequent and intense. Warmer temperatures in turn are altering river hydrology: advancing the timing of spring snow melt floods, altering flood magnitudes, and reducing summer and base flows. Direct effects of increased [CO2] and climate change on riparian ecosystems may be similar to effects in uplands, including increased heat and water stress, altered phenology and species geographic distributions, and disrupted trophic and symbiotic interactions. Indirect effects due to climate-driven changes in streamflow, however, may exacerbate the direct effects of warming and increase the relative importance of moisture and fluvial disturbance as drivers of riparian ecosystem response to global change. Together, climate change and climate-driven changes in streamflow are likely to reduce abundance of dominant, native, early-successional tree species, favor herbaceous species and both drought-tolerant and late-successional woody species (including many introduced species), reduce habitat quality for many riparian animals, and slow litter decomposition and nutrient cycling. Climate-driven changes in human water demand and associated water management may intensify these effects. On some regulated rivers, however, reservoir releases could be managed to protect riparian ecosystem. Immediate research priorities include determining riparian species' environmental requirements and monitoring riparian ecosystems to allow rapid detection and response to undesirable ecological change.

Watershed hydrology. Chapter 7.

Treesearch

Elons S. Verry; Kenneth N. Brooks; Dale S. Nichols; Dawn R. Ferris; Stephen D. Sebestyen

2011-01-01

Watershed hydrology is determined by the local climate, land use, and pathways of water flow. At the Marcell Experimental Forest (MEF), streamflow is dominated by spring runoff events driven by snowmelt and spring rains common to the strongly continental climate of northern Minnesota. Snowmelt and rainfall in early spring saturate both mineral and organic soils and...

Inferring changes in water cycle dynamics of intensively managed landscapes via the theory of time-variant travel time distributions

NASA Astrophysics Data System (ADS)

Danesh-Yazdi, Mohammad; Foufoula-Georgiou, Efi; Karwan, Diana L.; Botter, Gianluca

2016-10-01

Climatic trends and anthropogenic changes in land cover and land use are impacting the hydrology and water quality of streams at the field, watershed, and regional scales in complex ways. In poorly drained agricultural landscapes, subsurface drainage systems have been successful in increasing crop productivity by removing excess soil moisture. However, their hydroecological consequences are still debated in view of the observed increased concentrations of nitrate, phosphorus, and pesticides in many streams, as well as altered runoff volumes and timing. In this study, we employ the recently developed theory of time-variant travel time distributions within the StorAge Selection function framework to quantify changes in water cycle dynamics resulting from the combined climate and land use changes. Our results from analysis of a subbasin in the Minnesota River Basin indicate a significant decrease in the mean travel time of water in the shallow subsurface layer during the growing season under current conditions compared to the pre-1970s conditions. We also find highly damped year-to-year fluctuations in the mean travel time, which we attribute to the "homogenization" of the hydrologic response due to artificial drainage. The dependence of the mean travel time on the spatial heterogeneity of some soil characteristics as well as on the basin scale is further explored via numerical experiments. Simulations indicate that the mean travel time is independent of scale for spatial scales larger than approximately 200 km2, suggesting that hydrologic data from larger basins may be used to infer the average of smaller-scale-driven changes in water cycle dynamics.

Innovative Tools for Water Quality/Quantity Management: New York City's Operations Support Tool

NASA Astrophysics Data System (ADS)

Wang, L.; Schaake, J. C.; Day, G. N.; Porter, J.; Sheer, D. P.; Pyke, G.

2011-12-01

The New York City Department of Environmental Protection (DEP) manages New York City's water supply, which is comprised of over 20 reservoirs and supplies more than 1 billion gallons of water per day to over 9 million customers. Recently, DEP has initiated design of an Operations Support Tool (OST), a state-of-the-art decision support system to provide computational and predictive support for water supply operations and planning. This presentation describes the technical structure of OST, including the underlying water supply and water quality models, data sources and database management, reservoir inflow forecasts, and the functionalities required to meet the needs of a diverse group of end users. OST is a major upgrade of DEP's current water supply - water quality model, developed to evaluate alternatives for controlling turbidity in NYC's Catskill reservoirs. While the current model relies on historical hydrologic and meteorological data, OST can be driven by forecasted future conditions. It will receive a variety of near-real-time data from a number of sources. OST will support two major types of simulations: long-term, for evaluating policy or infrastructure changes over an extended period of time; and short-term "position analysis" (PA) simulations, consisting of multiple short simulations, all starting from the same initial conditions. Typically, the starting conditions for a PA run will represent those for the current day and traces of forecasted hydrology will drive the model for the duration of the simulation period. The result of these simulations will be a distribution of future system states based on system operating rules and the range of input ensemble streamflow predictions. DEP managers will analyze the output distributions and make operation decisions using risk-based metrics such as probability of refill. Currently, in the developmental stages of OST, forecasts are based on antecedent hydrologic conditions and are statistical in nature. The statistical algorithm is a relatively simple and versatile, but lacks short-term skill critical for water quality and spill management. To improve short-term skill, OST will ultimately operate with meteorologically driven hydrologic forecasts provided by the National Weather Service (NWS). OST functionalities will support a wide range of DEP uses, including short term operational projections, outage planning and emergency management, operating rule development, and water supply planning. A core use of OST will be to inform reservoir management strategies to control and mitigate turbidity events while ensuring water supply reliability. OST will also allow DEP to manage its complex reservoir system to meet multiple objectives, including ecological flows, tailwater fisheries and recreational releases, and peak flow mitigation for downstream communities.

The distribution and hydrological significance of rock glaciers in the Nepalese Himalaya

NASA Astrophysics Data System (ADS)

Jones, D. B.; Harrison, S.; Anderson, K.; Selley, H. L.; Wood, J. L.; Betts, R. A.

2018-01-01

In the Nepalese Himalaya, there is little information on the number, spatial distribution and morphometric characteristics of rock glaciers, and this information is required if their hydrological contribution is to be understood. Based on freely available fine spatial resolution satellite data accessible through Google Earth, we produced the first comprehensive Nepalese rock glacier inventory, supported through statistical validation and field survey. The inventory includes the location of over 6000 rock glaciers, with a mean specific density of 3.4%. This corresponds to an areal coverage of 1371 km2. Our approach subsampled approximately 20% of the total identified rock glacier inventory (n = 1137) and digitised their outlines so that quantitative/qualitative landform attributes could be extracted. Intact landforms (containing ice) accounted for 68% of the subsample, and the remaining were classified as relict (not containing ice). The majority (56%) were found to have a northerly aspect (NE, N, and NW), and landforms situated within north- to west-aspects reside at lower elevations than those with south- to- east aspects. In Nepal, we show that rock glaciers are situated between 3225 and 5675 m a.s.l., with the mean minimum elevation at the front estimated to be 4977 ± 280 m a.s.l. for intact landforms and 4541 ± 346 m a.s.l. for relict landforms. The hydrological significance of rock glaciers in Nepal was then established by statistically upscaling the results from the subsample to estimate that these cryospheric reserves store between 16.72 and 25.08 billion m3 of water. This study, for the first time, estimates rock glacier water volume equivalents and evaluates their relative hydrological importance in comparison to ice glaciers. Across the Nepalese Himalaya, rock glacier to ice glacier water volume equivalent is 1:9, and generally increases westwards (e.g., ratio = 1:3, West region). This inventory represents a preliminary step for understanding the spatial distribution and the geomorphic conditions necessary for rock glacier formation in the Himalaya. With continued climatically-driven ice glacier recession, the relative importance of rock glaciers in the Nepalese Himalaya will potentially increase.

Probabilistic flood inundation prediction within a coupled hydrodynamic, distributed hydrologic modeling framework

NASA Astrophysics Data System (ADS)

Adams, T. E.

2016-12-01

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

Dynamically adaptive data-driven simulation of extreme hydrological flows

NASA Astrophysics Data System (ADS)

Kumar Jain, Pushkar; Mandli, Kyle; Hoteit, Ibrahim; Knio, Omar; Dawson, Clint

2018-02-01

Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.

Scale effect challenges in urban hydrology highlighted with a distributed hydrological model

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Holocene Decadal to Multidecadal Hydrologic Variability in the Everglades: Climate and Implications for Ecosystem Management

NASA Astrophysics Data System (ADS)

Moses, C. S.; Anderson, W. T.; Saunders, C.; Rebenack, C.

2009-12-01

The Florida Everglades are a complex, unique ecosystem. Adding to the complexity, a system of canals and gates control the flow of waters from central Florida southward into the Everglades, and ultimately Florida Bay and the Gulf of Mexico. With south Florida’s distinct wet and dry seasons, the hydrology has driven ecosystem evolution over the last 4-5 kya. However, since the 1920s the water content of the Everglades has largely been anthropogenically modulated, with the exception of the natural variability of evaporation and precipitation over the large area south of the Tamiami Trail. Because of the incredibly flat nature of the Everglades, small changes in the freshwater balance have substantial impacts on the diversity and distribution of organisms. Decadal and multidecadal variability in precipitation, hurricane incidence, and sea level rise all have important effects on the ecosystem. During the instrumental record, the natural precipitation across south Florida has been strongly influenced by combinations of the Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation, and ENSO. Here we discuss evidence of natural climate variability impacts on the ecosystem beyond the anthropogenic hydrological controls. Proxy environmental data from seeds, charcoal, and trees, plus the sparse, but available, instrumental records provide evidence of changes in the ecosystem over the Holocene, and suggest considerations for future management.

Scaling, Similarity, and the Fourth Paradigm for Hydrology

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Clark, Martyn; Samaniego, Luis; Verhoest, Niko E. C.; van Emmerik, Tim; Uijlenhoet, Remko; Achieng, Kevin; Franz, Trenton E.; Woods, Ross

2017-01-01

In this synthesis paper addressing hydrologic scaling and similarity, we posit that roadblocks in the search for universal laws of hydrology are hindered by our focus on computational simulation (the third paradigm), and assert that it is time for hydrology to embrace a fourth paradigm of data-intensive science. Advances in information-based hydrologic science, coupled with an explosion of hydrologic data and advances in parameter estimation and modelling, have laid the foundation for a data-driven framework for scrutinizing hydrological scaling and similarity hypotheses. We summarize important scaling and similarity concepts (hypotheses) that require testing, describe a mutual information framework for testing these hypotheses, describe boundary condition, state flux, and parameter data requirements across scales to support testing these hypotheses, and discuss some challenges to overcome while pursuing the fourth hydrological paradigm. We call upon the hydrologic sciences community to develop a focused effort towards adopting the fourth paradigm and apply this to outstanding challenges in scaling and similarity.

Evaluating hydrologic response to land cover and climate change: An example from the Palmyra Atoll National Wildlife Refuge

NASA Astrophysics Data System (ADS)

Lane, J. W.; Briggs, M.; Kulongoski, J. T.; Pollock, A. L.

2013-12-01

The Palmyra Atoll National Wildlife Refuge is located in the central Pacific Ocean, about 1,000 miles south of the island of Oahu. Impacts on the atoll's hydrologic and ecologic systems are anticipated from two key anthropogenic drivers of change: (1) eradication of invasive coconut palms and replanting of native Pisonia grandis trees, and (2) global climate change. In the near-term, the palm eradication program is expected to modify the distribution and quality of groundwater proximal to the reforested areas. Longer term, sea level rise, changes in precipitation, and changes in storm frequency and intensity are expected to have a broader impact on the freshwater resources of the atoll. We have initiated a project to characterize current climatic and hydrologic conditions on Palmyra, and monitor changes in order to model baseline conditions and future changes in groundwater distribution. Because rain water harvest satisfies human need on Palmyra, the atoll enables study of groundwater resource change uncomplicated by groundwater pumping stress. Field trips conducted in 2008 and 2013 have included geophysical surveys, weather station upgrades, installation of monitoring wells, and geochemical sampling. Nine wells have been installed on Cooper Island (the largest island of the atoll), each instrumented with a combination of temperature, conductivity, and pressure sensors. Repeated frequency-domain electromagnetic conductivity surveys indicate a reduction in the thickness of the freshwater lens on the southern side of the Cooper Island since 2008, possibly linked to recent modification to the atoll's runway and drainage system. These results indicate that we can successfully capture future transformations induced by land cover and climate changes. The Palmyra Atoll project provides open-source information and insight about human-driven change to the vulnerable freshwater resources of low-lying islands; we hope others will take interest in, and make use of the hydrologic data now being collected on the atoll.

Climate change and stream temperature projections in the Columbia River basin: habitat implications of spatial variation in hydrologic drivers

NASA Astrophysics Data System (ADS)

Ficklin, D. L.; Barnhart, B. L.; Knouft, J. H.; Stewart, I. T.; Maurer, E. P.; Letsinger, S. L.; Whittaker, G. W.

2014-12-01

Water temperature is a primary physical factor regulating the persistence and distribution of aquatic taxa. Considering projected increases in air temperature and changes in precipitation in the coming century, accurate assessment of suitable thermal habitats in freshwater systems is critical for predicting aquatic species' responses to changes in climate and for guiding adaptation strategies. We use a hydrologic model coupled with a stream temperature model and downscaled general circulation model outputs to explore the spatially and temporally varying changes in stream temperature for the late 21st century at the subbasin and ecological province scale for the Columbia River basin (CRB). On average, stream temperatures are projected to increase 3.5 °C for the spring, 5.2 °C for the summer, 2.7 °C for the fall, and 1.6 °C for the winter. While results indicate changes in stream temperature are correlated with changes in air temperature, our results also capture the important, and often ignored, influence of hydrological processes on changes in stream temperature. Decreases in future snowcover will result in increased thermal sensitivity within regions that were previously buffered by the cooling effect of flow originating as snowmelt. Other hydrological components, such as precipitation, surface runoff, lateral soil water flow, and groundwater inflow, are negatively correlated to increases in stream temperature depending on the ecological province and season. At the ecological province scale, the largest increase in annual stream temperature was within the Mountain Snake ecological province, which is characterized by migratory coldwater fish species. Stream temperature changes varied seasonally with the largest projected stream temperature increases occurring during the spring and summer for all ecological provinces. Our results indicate that stream temperatures are driven by local processes and ultimately require a physically explicit modeling approach to accurately characterize the habitat regulating the distribution and diversity of aquatic taxa.

Climate change and stream temperature projections in the Columbia River Basin: biological implications of spatial variation in hydrologic drivers

NASA Astrophysics Data System (ADS)

Ficklin, D. L.; Barnhart, B. L.; Knouft, J. H.; Stewart, I. T.; Maurer, E. P.; Letsinger, S. L.; Whittaker, G. W.

2014-06-01

Water temperature is a primary physical factor regulating the persistence and distribution of aquatic taxa. Considering projected increases in temperature and changes in precipitation in the coming century, accurate assessment of suitable thermal habitat in freshwater systems is critical for predicting aquatic species responses to changes in climate and for guiding adaptation strategies. We use a hydrologic model coupled with a stream temperature model and downscaled General Circulation Model outputs to explore the spatially and temporally varying changes in stream temperature at the subbasin and ecological province scale for the Columbia River Basin. On average, stream temperatures are projected to increase 3.5 °C for the spring, 5.2 °C for the summer, 2.7 °C for the fall, and 1.6 °C for the winter. While results indicate changes in stream temperature are correlated with changes in air temperature, our results also capture the important, and often ignored, influence of hydrological processes on changes in stream temperature. Decreases in future snowcover will result in increased thermal sensitivity within regions that were previously buffered by the cooling effect of flow originating as snowmelt. Other hydrological components, such as precipitation, surface runoff, lateral soil flow, and groundwater, are negatively correlated to increases in stream temperature depending on the season and ecological province. At the ecological province scale, the largest increase in annual stream temperature was within the Mountain Snake ecological province, which is characterized by non-migratory coldwater fish species. Stream temperature changes varied seasonally with the largest projected stream temperature increases occurring during the spring and summer for all ecological provinces. Our results indicate that stream temperatures are driven by local processes and ultimately require a physically-explicit modeling approach to accurately characterize the habitat regulating the distribution and diversity of aquatic taxa.

Empirical Validation of Integrated Learning Performances for Hydrologic Phenomena: 3rd-Grade Students' Model-Driven Explanation-Construction

ERIC Educational Resources Information Center

Forbes, Cory T.; Zangori, Laura; Schwarz, Christina V.

2015-01-01

Water is a crucial topic that spans the K-12 science curriculum, including the elementary grades. Students should engage in the articulation, negotiation, and revision of model-based explanations about hydrologic phenomena. However, past research has shown that students, particularly early learners, often struggle to understand hydrologic…

Climate change and watershed mercury export in a Coastal Plain watershed

Treesearch

Heather Golden; Christopher D. Knightes; Paul A. Conrads; Toby D. Feaster; Gary M. Davis; Stephen T. Benedict; Paul M. Bradley

2016-01-01

Future changes in climatic conditions may affect variations in watershed processes (e.g., hydrological, biogeochemical) and surface water quality across a wide range of physiographic provinces, ecosystems, and spatial scales. How such climatic shifts will impact watershed mercury (Hg) dynamics and hydrologically-driven Hg transport is a significant concern.

Effect of climate fluctuation on long-term vegetation dynamics in Carolina bay wetlands

Treesearch

Chrissa Stroh; Diane De Steven; Glenn Guntenspergen

2008-01-01

Carolina bays and similar depression wetlands of the U. S. Southeastern Coastal Plain have hydrologic regimes that are driven primarily by rainfall. Therefore, climate fluctuations such as drought cycles have the potential to shape long-term vegetation dynamics. Models suggest two potential long-term responses to hydrologic fluctuations, either cyclic change...

Simple Kinematic Pathway Approach (KPA) to Catchment-scale Travel Time and Water Age Distributions

NASA Astrophysics Data System (ADS)

Soltani, S. S.; Cvetkovic, V.; Destouni, G.

2017-12-01

The distribution of catchment-scale water travel times is strongly influenced by morphological dispersion and is partitioned between hillslope and larger, regional scales. We explore whether hillslope travel times are predictable using a simple semi-analytical "kinematic pathway approach" (KPA) that accounts for dispersion on two levels of morphological and macro-dispersion. The study gives new insights to shallow (hillslope) and deep (regional) groundwater travel times by comparing numerical simulations of travel time distributions, referred to as "dynamic model", with corresponding KPA computations for three different real catchment case studies in Sweden. KPA uses basic structural and hydrological data to compute transient water travel time (forward mode) and age (backward mode) distributions at the catchment outlet. Longitudinal and morphological dispersion components are reflected in KPA computations by assuming an effective Peclet number and topographically driven pathway length distributions, respectively. Numerical simulations of advective travel times are obtained by means of particle tracking using the fully-integrated flow model MIKE SHE. The comparison of computed cumulative distribution functions of travel times shows significant influence of morphological dispersion and groundwater recharge rate on the compatibility of the "kinematic pathway" and "dynamic" models. Zones of high recharge rate in "dynamic" models are associated with topographically driven groundwater flow paths to adjacent discharge zones, e.g. rivers and lakes, through relatively shallow pathway compartments. These zones exhibit more compatible behavior between "dynamic" and "kinematic pathway" models than the zones of low recharge rate. Interestingly, the travel time distributions of hillslope compartments remain almost unchanged with increasing recharge rates in the "dynamic" models. This robust "dynamic" model behavior suggests that flow path lengths and travel times in shallow hillslope compartments are controlled by topography, and therefore application and further development of the simple "kinematic pathway" approach is promising for their modeling.

Newtonian Nudging For A Richards Equation-based Distributed Hydrological Model

NASA Astrophysics Data System (ADS)

Paniconi, C.; Marrocu, M.; Putti, M.; Verbunt, M.

In this study a relatively simple data assimilation method has been implemented in a relatively complex hydrological model. The data assimilation technique is Newtonian relaxation or nudging, in which model variables are driven towards observations by a forcing term added to the model equations. The forcing term is proportional to the difference between simulation and observation (relaxation component) and contains four-dimensional weighting functions that can incorporate prior knowledge about the spatial and temporal variability and characteristic scales of the state variable(s) being assimilated. The numerical model couples a three-dimensional finite element Richards equation solver for variably saturated porous media and a finite difference diffusion wave approximation based on digital elevation data for surface water dynamics. We describe the implementation of the data assimilation algorithm for the coupled model and report on the numerical and hydrological performance of the resulting assimila- tion scheme. Nudging is shown to be successful in improving the hydrological sim- ulation results, and it introduces little computational cost, in terms of CPU and other numerical aspects of the model's behavior, in some cases even improving numerical performance compared to model runs without nudging. We also examine the sensitiv- ity of the model to nudging term parameters including the spatio-temporal influence coefficients in the weighting functions. Overall the nudging algorithm is quite flexi- ble, for instance in dealing with concurrent observation datasets, gridded or scattered data, and different state variables, and the implementation presented here can be read- ily extended to any features not already incorporated. Moreover the nudging code and tests can serve as a basis for implementation of more sophisticated data assimilation techniques in a Richards equation-based hydrological model.

Socio-hydrologic modeling to understand and mediate the competition for water between agriculture development and environmental health: Murrumbidgee River Basin, Australia

NASA Astrophysics Data System (ADS)

van Emmerik, T. H. M.; Li, Z.; Sivapalan, M.; Pande, S.; Kandasamy, J.; Savenije, H. H. G.; Chanan, A.; Vigneswaran, S.

2014-03-01

Competition for water between humans and ecosystems is set to become a flash point in the coming decades in many parts of the world. An entirely new and comprehensive quantitative framework is needed to establish a holistic understanding of that competition, thereby enabling the development of effective mediation strategies. This paper presents a modeling study centered on the Murrumbidgee River Basin (MRB). The MRB has witnessed a unique system dynamics over the last 100 years as a result of interactions between patterns of water management and climate driven hydrological variability. Data analysis has revealed a pendulum swing between agricultural development and restoration of environmental health and ecosystem services over different stages of basin scale water resource development. A parsimonious, stylized, quasi-distributed coupled socio-hydrologic system model that simulates the two-way coupling between human and hydrological systems of the MRB is used to mimic dominant features of the pendulum swing. The model consists of coupled nonlinear ordinary differential equations that describe the interaction between five state variables that govern the co-evolution: reservoir storage, irrigated area, human population, ecosystem health, and a measure of environmental awareness. The model simulations track the propagation of the external climatic and socio-economic drivers through this coupled, complex system to the emergence of the pendulum swing. The model results point to a competition between human "productive" and environmental "restorative" forces that underpin the pendulum swing. Both the forces are endogenous, i.e., generated by the system dynamics in response to external drivers and mediated by humans through technology change and environmental awareness, respectively. We propose this as a generalizable modeling framework for coupled human hydrological systems that is potentially transferable to systems in different climatic and socio-economic settings.

Distributed watershed modeling of design storms to identify nonpoint source loading areas

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

Endreny, T.A.; Wood, E.F.

1999-03-01

Watershed areas that generate nonpoint source (NPS) polluted runoff need to be identified prior to the design of basin-wide water quality projects. Current watershed-scale NPS models lack a variable source area (VSA) hydrology routine, and are therefore unable to identify spatially dynamic runoff zones. The TOPLATS model used a watertable-driven VSA hydrology routine to identify runoff zones in a 17.5 km{sup 2} agricultural watershed in central Oklahoma. Runoff areas were identified in a static modeling framework as a function of prestorm watertable depth and also in a dynamic modeling framework by simulating basin response to 2, 10, and 25 yrmore » return period 6 h design storms. Variable source area expansion occurred throughout the duration of each 6 h storm and total runoff area increased with design storm intensity. Basin-average runoff rates of 1 mm h{sup {minus}1} provided little insight into runoff extremes while the spatially distributed analysis identified saturation excess zones with runoff rates equaling effective precipitation. The intersection of agricultural landcover areas with these saturation excess runoff zones targeted the priority potential NPS runoff zones that should be validated with field visits. These intersected areas, labeled as potential NPS runoff zones, were mapped within the watershed to demonstrate spatial analysis options available in TOPLATS for managing complex distributions of watershed runoff. TOPLATS concepts in spatial saturation excess runoff modelling should be incorporated into NPS management models.« less

A decade of sea level rise slowed by climate-driven hydrology.

PubMed

Reager, J T; Gardner, A S; Famiglietti, J S; Wiese, D N; Eicker, A; Lo, M-H

2016-02-12

Climate-driven changes in land water storage and their contributions to sea level rise have been absent from Intergovernmental Panel on Climate Change sea level budgets owing to observational challenges. Recent advances in satellite measurement of time-variable gravity combined with reconciled global glacier loss estimates enable a disaggregation of continental land mass changes and a quantification of this term. We found that between 2002 and 2014, climate variability resulted in an additional 3200 ± 900 gigatons of water being stored on land. This gain partially offset water losses from ice sheets, glaciers, and groundwater pumping, slowing the rate of sea level rise by 0.71 ± 0.20 millimeters per year. These findings highlight the importance of climate-driven changes in hydrology when assigning attribution to decadal changes in sea level. Copyright © 2016, American Association for the Advancement of Science.

Seamless hydrological predictions for a monsoon driven catchment in North-East India

NASA Astrophysics Data System (ADS)

Köhn, Lisei; Bürger, Gerd; Bronstert, Axel

2016-04-01

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

US GEOLOGICAL SURVEY'S NATIONAL SYSTEM FOR PROCESSING AND DISTRIBUTION OF NEAR REAL-TIME HYDROLOGICAL DATA.

USGS Publications Warehouse

Shope, William G.; ,

1987-01-01

The US Geological Survey is utilizing a national network of more than 1000 satellite data-collection stations, four satellite-relay direct-readout ground stations, and more than 50 computers linked together in a private telecommunications network to acquire, process, and distribute hydrological data in near real-time. The four Survey offices operating a satellite direct-readout ground station provide near real-time hydrological data to computers located in other Survey offices through the Survey's Distributed Information System. The computerized distribution system permits automated data processing and distribution to be carried out in a timely manner under the control and operation of the Survey office responsible for the data-collection stations and for the dissemination of hydrological information to the water-data users.

Topographically Driven Lateral Water Fluxes and Their Influence on Carbon Assimilation of a Black Spruce Ecosystem.

NASA Astrophysics Data System (ADS)

Govind, A.; Chen, J. M.; Margolis, H.; Bernier, P. Y.

2006-12-01

Current estimates of ecophysiological indicators overlook the effects of topographically-driven lateral flow of soil water. We hypothesize that topographically driven lateral water flows over the landscape have significant influence on the terrestrial carbon cycle. To this end, we simulated the hydrological controls on carbon cycle processes in a black spruce forest in central Quebec, Canada, using the Boreal Ecosystem Productivity Simulator (BEPS) at a daily time step. We accounted for lateral surface and subsurface flows in BEPS by incorporating a distributed, process-oriented hydrological procedure. The results show that modeled dynamics of ecophysiological processes such as evapotranspiration (ET) and photosynthesis (GPP) are consistent with the spatial variation of land cover, topography, soil texture, and leaf area index. Simulated ET and GPP averaged within the footprint of an eddy covariance tower in the watershed agree well with flux measurements with R2=0.77 and 0.83 for ET and GPP, respectively. For ET simulation, much of the remaining discrepancies are found in the winter when the model underestimates snow sublimation. For GPP, there is an underestimation in the fall coinciding with a mid growing season drought, showing the high sensitivity of the model to the soil water status. The key processes controlling primary production were hydraulic limitations for water transfer from soil, roots, stems and leaves through stomatal conductance. Therefore, a further understanding of soil water dynamics is warranted. Comparison with the soil water content of the footprint- averaged unsaturated zone showed that the model captured the annual trend. We also simulated the variations in the water table as well as the mid growing season drought, with a reasonable accuracy(R2=0.68). The foot print average water budget reveals that the annual precipitation of 835mm is partitioned into 282mm of ET, 541 mm of subsurface runoff, and 6 mm of storage change. To test the influence of topographically driven lateral water flow on the carbon cycle, we made three hydrological modeling scenarios viz. 1) explicit hydrological simulation including lateral water routing, 2) bucket model with implicit runoff calculations and 3) a control run, where the lateral water flow was turned off in the model. Bucket model overestimated GPP as much as 25% as opposed to explicit simulations because there was no topographical constrain on runoff. Flat areas dominated with mineral soils shows the highest overestimation because of an increase in stomatal conductance. Control simulation, on the other hand, underestimated GPP as much as 15% as opposed to explicit routing because of rapid soil saturation, which decreases stomatal conductance. These results suggest that lateral water flow does play a significant role in the terrestrial carbon cycle and should be accounted for in ecological models. For details please see http://ajit.govind.googlepages.com/agu2006

Impact of spatio-temporal scale of adjustment on variational assimilation of hydrologic and hydrometeorological data in operational distributed hydrologic models

NASA Astrophysics Data System (ADS)

Lee, H.; Seo, D.; McKee, P.; Corby, R.

2009-12-01

One of the large challenges in data assimilation (DA) into distributed hydrologic models is to reduce the large degrees of freedom involved in the inverse problem to avoid overfitting. To assess the sensitivity of the performance of DA to the dimensionality of the inverse problem, we design and carry out real-world experiments in which the control vector in variational DA (VAR) is solved at different scales in space and time, e.g., lumped, semi-distributed, and fully-distributed in space, and hourly, 6 hourly, etc., in time. The size of the control vector is related to the degrees of freedom in the inverse problem. For the assessment, we use the prototype 4-dimenational variational data assimilator (4DVAR) that assimilates streamflow, precipitation and potential evaporation data into the NWS Hydrology Laboratory’s Research Distributed Hydrologic Model (HL-RDHM). In this talk, we present the initial results for a number of basins in Oklahoma and Texas.

CNMM: a Catchment Environmental Model for Managing Water Quality and Greenhouse Gas Emissions

NASA Astrophysics Data System (ADS)

Li, Y.

2015-12-01

Mitigating agricultural diffuse pollution and greenhouse gas emissions is a complicated task due to tempo-spatial lags between the field practices and the watershed responses. Spatially-distributed modeling is essential to the implementation of cost-effective and best management practices (BMPs) to optimize land uses and nutrient applications as well as to project the impact of climate change on the watershed service functions. CNMM (the Catchment Nutrients Management Model) is a 3D spatially-distributed, grid-based and process-oriented biophysical model comprehensively developed to simulate energy balance, hydrology, plant/crop growth, biogeochemistry of life elements (e.g., C, N and P), waste treatment, waterway vegetation/purification, stream water quality and land management in agricultural watersheds as affected by land utilization strategies such as BMPs and by climate change. The CNMM is driven by a number of spatially-distributed data such as weather, topography (including DEM and shading), stream network, stream water, soil, vegetation and land management (including waste treatments), and runs at an hourly time step. It represents a catchment as a matrix of square uniformly-sized cells, where each cell is defined as a homogeneous hydrological response unit with all the hydrologically-significant parameters the same but varied at soil depths in fine intervals. Therefore, spatial variability is represented by allowing parameters to vary horizontally and vertically in space. A four-direction flux routing algorithm is applied to route water and nutrients across soils of cells governed by the gradients of either water head or elevation. A linear channel reservoir scheme is deployed to route water and nutrients in stream networks. The model is capable of computing CO2, CH4, NH3, NO, N2O and N2 emissions from soils and stream waters. The CNMM can serve as an idea modelling tool to investigate the overwhelming critical zone research at various catchment scales.

Base flow-driven shifts in tropical stream temperature regimes across a mean annual rainfall gradient

Treesearch

Ayron M. Strauch; Richard A. MacKenzie; Ralph W. Tingley

2017-01-01

Climate change is expected to affect air temperature and watershed hydrology, but the degree to which these concurrent changes affect stream temperature is not well documented in the tropics. How stream temperature varies over time under changing hydrologic conditions is difficult to isolate from seasonal changes in air temperature. Groundwater and bank storage...

Carbon dioxide exchange rates from short- and long-hydroperiod Everglades freshwater marsh

Treesearch

K. L. Jimenez; G. Starr; C. L. Staudhammer; J. L. Schedlbauer; H. W. Loescher; Sparkle L Malone; S. F. Oberbauer

2012-01-01

Everglades freshwater marshes were once carbon sinks, but human-driven hydrologic changes have led to uncertainty about the current state of their carbon dynamics. To investigate the effect of hydrology on CO2 exchange, we used eddy covariance measurements for 2 years (2008-2009) in marl (short-hydroperiod) and peat (long-hydroperiod) wetlands in Everglades National...

Water ecosystem service function assessment based on eco-hydrological process in Luanhe Basin,China

NASA Astrophysics Data System (ADS)

Zhang, C.; Hao, C.; Qin, T.; Wang, G.; Weng, B.

2012-12-01

At present, ecological water are mainly occupied by a rapid development of social economic and population explosion, which seriously threat the ecological security and water security in watershed and regional scale. Due to the lack of a unified standard of measuring the benefit of water resource, social economic and ecosystem, the water allocation can't take place in social economic and ecosystem. The function which provided by water in terrestrial, aquatic and social economic system can be addressed through water ecosystem service function research, and it can guide the water allocation in water resource management. The function which provided by water in terrestrial, aquatic and social economic system can be addressed through water ecosystem service function research, and it can guide the water allocation in water resource management. Throughout the researches of water ecosystem service, a clear identification of the connection of water ecosystem service function has not been established, and eco-economic approach can't meet the practical requirement of water allocation. Based on "nature-artificiality" dual water cycle theory and eco-hydrological process, this paper proposes a connection and indicator system of water ecosystem service function. In approach, this paper establishes an integrated assessment approach through prototype observation technology, numerical simulation, physical simulation and modern geographic information technology. The core content is to couple an eco-hydrological model, which involves the key processes of distributed hydrological model (WEP), ecological model (CLM-DGVM), in terms of eco-hydrological process. This paper systematically evaluates the eco-hydrological process and evolution of Luanhe Basin in terms of precipitation, ET, runoff, groundwater, ecosystem's scale, form and distribution. According to the results of eco-hydrological process, this paper assesses the direct and derived service function. The result indicates that the general service function of 2010 has minor increase than 2007, however the general function of two years are in common level; Compare with different region, the upstream, middle stream and downstream indicates "worse", "common" and "good" level respectively. The first three derived functions are leisure, offer products and industrial water use. In the end, this paper investigates the evolution of water ecosystem service function under rising temperatures and elevated CO2 concentration scenarios in Luanhe Basin through eco-hydrological model. The results elaborate that the water ecosystem service functions would decline when temperature rising, and warming to 1.5 degree is the mutation point of sharp drop; Increased CO2 concentration scenario will improve the direct service function in the whole Basin; under the overlying scenario, different region shows different results, the direct service function will increased in upstream and middle stream, direct service function will drop in downstream. A comprehensive analysis indicates that the rising temperature is the major driven of water ecosystem service function in Luanhe Basin.

Characterizing the utility of the TMPA real-time product for hydrologic predictions over global river basins across scales

NASA Astrophysics Data System (ADS)

Gao, H.; Zhang, S.; Nijssen, B.; Zhou, T.; Voisin, N.; Sheffield, J.; Lee, K.; Shukla, S.; Lettenmaier, D. P.

2017-12-01

Despite its errors and uncertainties, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis real-time product (TMPA-RT) has been widely used for hydrological monitoring and forecasting due to its timely availability for real-time applications. To evaluate the utility of TMPA-RT in hydrologic predictions, many studies have compared modeled streamflows driven by TMPA-RT against gauge data. However, because of the limited availability of streamflow observations in data sparse regions, there is still a lack of comprehensive comparisons for TMPA-RT based hydrologic predictions at the global scale. Furthermore, it is expected that its skill is less optimal at the subbasin scale than the basin scale. In this study, we evaluate and characterize the utility of the TMPA-RT product over selected global river basins during the period of 1998 to 2015 using the TMPA research product (TMPA-RP) as a reference. The Variable Infiltration Capacity (VIC) model, which was calibrated and validated previously, is adopted to simulate streamflows driven by TMPA-RT and TMPA-RP, respectively. The objective of this study is to analyze the spatial and temporal characteristics of the hydrologic predictions by answering the following questions: (1) How do the precipitation errors associated with the TMPA-RT product transform into streamflow errors with respect to geographical and climatological characteristics? (2) How do streamflow errors vary across scales within a basin?

A Cyber Enabled Collaborative Environment for Creating, Sharing and Using Data and Modeling Driven Curriculum Modules for Hydrology Education

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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.

On Lack of Robustness in Hydrological Model Development Due to Absence of Guidelines for Selecting Calibration and Evaluation Data: Demonstration for Data-Driven Models

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Maier, Holger R.; Wu, Wenyan; Dandy, Graeme C.; Gupta, Hoshin V.; Zhang, Tuqiao

2018-02-01

Hydrological models are used for a wide variety of engineering purposes, including streamflow forecasting and flood-risk estimation. To develop such models, it is common to allocate the available data to calibration and evaluation data subsets. Surprisingly, the issue of how this allocation can affect model evaluation performance has been largely ignored in the research literature. This paper discusses the evaluation performance bias that can arise from how available data are allocated to calibration and evaluation subsets. As a first step to assessing this issue in a statistically rigorous fashion, we present a comprehensive investigation of the influence of data allocation on the development of data-driven artificial neural network (ANN) models of streamflow. Four well-known formal data splitting methods are applied to 754 catchments from Australia and the U.S. to develop 902,483 ANN models. Results clearly show that the choice of the method used for data allocation has a significant impact on model performance, particularly for runoff data that are more highly skewed, highlighting the importance of considering the impact of data splitting when developing hydrological models. The statistical behavior of the data splitting methods investigated is discussed and guidance is offered on the selection of the most appropriate data splitting methods to achieve representative evaluation performance for streamflow data with different statistical properties. Although our results are obtained for data-driven models, they highlight the fact that this issue is likely to have a significant impact on all types of hydrological models, especially conceptual rainfall-runoff models.

The Hydrologic Cycle Distributed Active Archive Center

NASA Technical Reports Server (NTRS)

Hardin, Danny M.; Goodman, H. Michael

1995-01-01

The Marshall Space Flight Center Distributed Active Archive Center in Huntsville, Alabama supports the acquisition, production, archival and dissemination of data relevant to the study of the global hydrologic cycle. This paper describes the Hydrologic Cycle DAAC, surveys its principle data holdings, addresses future growth, and gives information for accessing the data sets.

Replacing climatological potential evapotranspiration estimates with dynamic satellite-based observations in operational hydrologic prediction models

NASA Astrophysics Data System (ADS)

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

2011-12-01

In the face of a changing climate, growing populations, and increased human habitation in hydrologically risky locations, both short- and long-range planners increasingly require robust and reliable streamflow forecast information. Current operational forecasting utilizes watershed-scale, conceptual models driven by ground-based (commonly point-scale) observations of precipitation and temperature and climatological potential evapotranspiration (PET) estimates. The PET values are derived from historic pan evaporation observations and remain static from year-to-year. The need for regional dynamic PET values is vital for improved operational forecasting. With the advent of satellite remote sensing and the adoption of a more flexible operational forecast system by the National Weather Service, incorporation of advanced data products is now more feasible than in years past. In this study, we will test a previously developed satellite-derived PET product (UCLA MODIS-PET) in the National Weather Service forecast models and compare the model results to current methods. The UCLA MODIS-PET method is based on the Priestley-Taylor formulation, is driven with MODIS satellite products, and produces a daily, 250m PET estimate. The focus area is eight headwater basins in the upper Midwest U.S. There is a need to develop improved forecasting methods for this region that are able to account for climatic and landscape changes more readily and effectively than current methods. This region is highly flood prone yet sensitive to prolonged dry periods in late summer and early fall, and is characterized by a highly managed landscape, which has drastically altered the natural hydrologic cycle. Our goal is to improve model simulations, and thereby, the initial conditions prior to the start of a forecast through the use of PET values that better reflect actual watershed conditions. The forecast models are being tested in both distributed and lumped mode.

Inferring hydraulic properties of alpine aquifers from the propagation of diurnal snowmelt signals

NASA Astrophysics Data System (ADS)

Kurylyk, Barret L.; Hayashi, Masaki

2017-05-01

Alpine watersheds source major rivers throughout the world and supply essential water for irrigation, human consumption, and hydroelectricity. Coarse depositional units in alpine watersheds can store and transmit significant volumes of groundwater and thus augment stream discharge during the dry season. These environments are typically data scarce, which has limited the application of physically based models to investigate hydrologic sensitivity to environmental change. This study focuses on a coarse alpine talus unit within the Lake O'Hara watershed in the Canadian Rockies. We investigate processes controlling the hydrologic functioning of the talus unit using field observations and a numerical groundwater flow model driven with a distributed snowmelt model. The model hydraulic parameters are adjusted to investigate how these properties influence the propagation of snowmelt-induced diurnal signals. The model results expectedly demonstrate that diurnal signals at the talus outlet are progressively damped and lagged with lower hydraulic conductivity and higher specific yield. The simulations further indicate that the lag can be primarily controlled by a higher hydraulic conductivity upper layer, whereas the damping can be strongly influenced by a lower hydraulic conductivity layer along the base of the talus. The simulations specifically suggest that the talus slope can be represented as a two layer system with a high conductivity zone (0.02 m s-1) overlying a 10 cm thick lower conductivity zone (0.002 m s-1). This study demonstrates that diurnal signals can be used to elucidate the hydrologic functioning and hydraulic properties of shallow aquifers and thus aid in the parameterization of hydrological models.

Hydrological response of the Mediterranean catchments- A review

NASA Astrophysics Data System (ADS)

Merheb, Mohammad; Moussa, Roger; Abdallah, Chadi; Colin, François; Perrin, Charles; Baghdadi, Nicolas

2015-04-01

The Mediterranean region is a water stressed environment with increasing climatic and anthropogenic pressures. This work presents a review of 120 hydrological studies carried out in the Mediterranean region. It contributes to the ongoing hydrological research initiative on "Hydrology in a changing world" launched by the IAHS in 2014. It aims to understand the characteristics of hydrological response under Mediterranean conditions, taking into account changes driven by anthropogenic and climatic factors; and to compare modeling and regionalization approaches in use. The study region is divided into three sub-regions: Northwestern Mediterranean (NWM), Eastern (EM) and Southern Mediterranean (SM). Information on catchments responses and modeling approaches at different time scales (annual, dry season and event) were extracted from published studies, and analyzed. Results indicate regional discrepancies (between NWM, EM and SM sub-regions) in the distribution of climatic and hydrological response characteristics at the annual and the event scale. The NWM catchments are the wettest, and the SM catchments are the driest, while the EM catchments are intermediate and exhibit the largest variability. The NWM sub-region shows the most extreme rainfall regime in the Mediterranean, particularly, in an arc that extends from Northeastern Spain to Northeastern Italy. Observations indicate decreasing tendency in water resources due to both anthropogenic and climatic impacts, and a more extreme rainfall regime. Moreover, Mediterranean catchments show very heterogeneous responses in time and space which make the modeling of their hydrological functioning very complicated and data demanding, with increasing model limitations and uncertainties. Nevertheless, the models in use are classical ones; very few were developed to address these regional specificities. Regionalization studies in the Mediterranean are scarce even in term of low flows and FDCs which is surprising in a water-stressed region that witnesses long low-flows periods. Predictions of runoff hydrograph give poor results. For flow duration curves and low flows regionalization, statistical and geo-statistical methods appear to outperform parametric approaches and regression respectively. Mixed results were found for regional flood analysis which appears to be the most common regionalization practice in the area. Finally, given the great heterogeneity in the hydrological responses of Mediterranean catchments and the increasing anthropogenic and climatic pressures, the region appears to be in need for more detailed observations and new modeling techniques adapted to its specificities. Keywords: hydrology, catchment, Mediterranean, modeling, regionalization, anthropogenic impact, climate change.

Decision Support System for hydrological extremes

NASA Astrophysics Data System (ADS)

Bobée, Bernard; El Adlouni, Salaheddine

2014-05-01

The study of the tail behaviour of extreme event distributions is important in several applied statistical fields such as hydrology, finance, and telecommunications. For example in hydrology, it is important to estimate adequately extreme quantiles in order to build and manage safe and effective hydraulic structures (dams, for example). Two main classes of distributions are used in hydrological frequency analysis: the class D of sub-exponential (Gamma (G2), Gumbel, Halphen type A (HA), Halphen type B (HB)…) and the class C of regularly varying distributions (Fréchet, Log-Pearson, Halphen type IB …) with a heavier tail. A Decision Support System (DSS) based on the characterization of the right tail, corresponding low probability of excedence p (high return period T=1/p, in hydrology), has been developed. The DSS allows discriminating between the class C and D and in its last version, a new prior step is added in order to test Lognormality. Indeed, the right tail of the Lognormal distribution (LN) is between the tails of distributions of the classes C and D; studies indicated difficulty with the discrimination between LN and distributions of the classes C and D. Other tools are useful to discriminate between distributions of the same class D (HA, HB and G2; see other communication). Some numerical illustrations show that, the DSS allows discriminating between Lognormal, regularly varying and sub-exponential distributions; and lead to coherent conclusions. Key words: Regularly varying distributions, subexponential distributions, Decision Support System, Heavy tailed distribution, Extreme value theory

The role of precipitation type, intensity, and spatial distribution in source water quality after wildfire

NASA Astrophysics Data System (ADS)

Murphy, Sheila F.; Writer, Jeffrey H.; Blaine McCleskey, R.; Martin, Deborah A.

2015-08-01

Storms following wildfires are known to impair drinking water supplies in the southwestern United States, yet our understanding of the role of precipitation in post-wildfire water quality is far from complete. We quantitatively assessed water-quality impacts of different hydrologic events in the Colorado Front Range and found that for a three-year period, substantial hydrologic and geochemical responses downstream of a burned area were primarily driven by convective storms with a 30 min rainfall intensity >10 mm h-1. These storms, which typically occur several times each year in July-September, are often small in area, short-lived, and highly variable in intensity and geographic distribution. Thus, a rain gage network with high temporal resolution and spatial density, together with high-resolution stream sampling, are required to adequately characterize post-wildfire responses. We measured total suspended sediment, dissolved organic carbon (DOC), nitrate, and manganese concentrations that were 10-156 times higher downstream of a burned area compared to upstream during relatively common (50% annual exceedance probability) rainstorms, and water quality was sufficiently impaired to pose water-treatment concerns. Short-term water-quality impairment was driven primarily by increased surface runoff during higher intensity convective storms that caused erosion in the burned area and transport of sediment and chemical constituents to streams. Annual sediment yields downstream of the burned area were controlled by storm events and subsequent remobilization, whereas DOC yields were closely linked to annual runoff and thus were more dependent on interannual variation in spring runoff. Nitrate yields were highest in the third year post-wildfire. Results from this study quantitatively demonstrate that water quality can be altered for several years after wildfire. Because the southwestern US is prone to wildfires and high-intensity rain storms, the role of storms in post-wildfire water-quality impacts must be considered when assessing water-quality vulnerability.

The role of precipitation type, intensity, and spatial distribution in source water quality after wildfire

USGS Publications Warehouse

Murphy, Sheila F.; Writer, Jeffrey H.; McCleskey, R. Blaine; Martin, Deborah A.

2015-01-01

Storms following wildfires are known to impair drinking water supplies in the southwestern United States, yet our understanding of the role of precipitation in post-wildfire water quality is far from complete. We quantitatively assessed water-quality impacts of different hydrologic events in the Colorado Front Range and found that for a three-year period, substantial hydrologic and geochemical responses downstream of a burned area were primarily driven by convective storms with a 30 min rainfall intensity >10 mm h−1. These storms, which typically occur several times each year in July–September, are often small in area, short-lived, and highly variable in intensity and geographic distribution. Thus, a rain gage network with high temporal resolution and spatial density, together with high-resolution stream sampling, are required to adequately characterize post-wildfire responses. We measured total suspended sediment, dissolved organic carbon (DOC), nitrate, and manganese concentrations that were 10–156 times higher downstream of a burned area compared to upstream during relatively common (50% annual exceedance probability) rainstorms, and water quality was sufficiently impaired to pose water-treatment concerns. Short-term water-quality impairment was driven primarily by increased surface runoff during higher intensity convective storms that caused erosion in the burned area and transport of sediment and chemical constituents to streams. Annual sediment yields downstream of the burned area were controlled by storm events and subsequent remobilization, whereas DOC yields were closely linked to annual runoff and thus were more dependent on interannual variation in spring runoff. Nitrate yields were highest in the third year post-wildfire. Results from this study quantitatively demonstrate that water quality can be altered for several years after wildfire. Because the southwestern US is prone to wildfires and high-intensity rain storms, the role of storms in post-wildfire water-quality impacts must be considered when assessing water-quality vulnerability.

Global Maps of Temporal Streamflow Characteristics Based on Observations from Many Small Catchments

NASA Astrophysics Data System (ADS)

Beck, H.; van Dijk, A.; de Roo, A.

2014-12-01

Streamflow (Q) estimation in ungauged catchments is one of the greatest challenges facing hydrologists. We used observed Q from approximately 7500 small catchments (<10,000 km2) around the globe to train neural network ensembles to estimate temporal Q distribution characteristics from climate and physiographic characteristics of the catchments. In total 17 Q characteristics were selected, including mean annual Q, baseflow index, and a number of flow percentiles. Training coefficients of determination for the estimation of the Q characteristics ranged from 0.56 for the baseflow recession constant to 0.93 for the Q timing. Overall, climate indices dominated among the predictors. Predictors related to soils and geology were the least important, perhaps due to data quality. The trained neural network ensembles were subsequently applied spatially over the ice-free land surface including ungauged regions, resulting in global maps of the Q characteristics (0.125° spatial resolution). These maps possess several unique features: 1) they represent purely observation-driven estimates; 2) are based on an unprecedentedly large set of catchments; and 3) have associated uncertainty estimates. The maps can be used for various hydrological applications, including the diagnosis of macro-scale hydrological models. To demonstrate this, the produced maps were compared to equivalent maps derived from the simulated daily Q of five macro-scale hydrological models, highlighting various opportunities for improvement in model Q behavior. The produced dataset is available for download.

Hydrological control on Ozone greenhouse gas effect

NASA Astrophysics Data System (ADS)

Kuai, L.; Bowman, K. W.; Worden, H. M.; Herman, R. L.; Kulawik, S. S.

2016-12-01

Our study present a new concept to use a derived observation-based quantity: instantaneous radiative kernel (IRK), to access the hydrological control on the variation of ozone greenhouse gas effect with AURA TES satellite data. We attribute the spatiotemporal variation of the TES O3 longwave radiative effect (LWRE), which is defined as the net reduction of top-of-atmosphere flux due to total tropospheric O3 absorption, to variations in relative humidity, surface temperature, and tropospheric O3 column. The maximum GHG effect for ozone, represented by LWRE, is found to be around 0.6 to 0.7 Wm-2 on zonal average in the subtropics. This maximum is related by low water vapor concentrations and suppression of clouds, which are driven by the downward branch of the Hadley cell over this region. Within the subtropics, the largest values of LWRE are over the Middle East (>1 W/m2) due to both large thermal contrast and tropospheric ozone enhancements from atmospheric circulation and pollution. Conversely, a lower ozone GHG effect (about 0.4 Wm-2 or lower) is found in the deep tropics closely following the Inter-Tropical Convergence Zone, attributable to strong water vapor absorption and clouds over deep convective regions. These results show that changes in the hydrological cycle due to climate change could impact the magnitude and distribution of ozone radiative forcing.

Moving university hydrology education forward with community-based geoinformatics, data and modeling resources

NASA Astrophysics Data System (ADS)

Merwade, V.; Ruddell, B. L.

2012-08-01

In this opinion paper, we review recent literature related to data and modeling driven instruction in hydrology, and present our findings from surveying the hydrology education community in the United States. This paper presents an argument that that data and modeling driven geoscience cybereducation (DMDGC) approaches are essential for teaching the conceptual and applied aspects of hydrology, as a part of the broader effort to improve science, technology, engineering, and mathematics (STEM) education at the university level. The authors have undertaken a series of surveys and a workshop involving university hydrology educators to determine the state of the practice of DMDGC approaches to hydrology. We identify the most common tools and approaches currently utilized, quantify the extent of the adoption of DMDGC approaches in the university hydrology classroom, and explain the community's views on the challenges and barriers preventing DMDGC approaches from wider use. DMDGC approaches are currently emphasized at the graduate level of the curriculum, and only the most basic modeling and visualization tools are in widespread use. The community identifies the greatest barriers to greater adoption as a lack of access to easily adoptable curriculum materials and a lack of time and training to learn constantly changing tools and methods. The community's current consensus is that DMDGC approaches should emphasize conceptual learning, and should be used to complement rather than replace lecture-based pedagogies. Inadequate online material publication and sharing systems, and a lack of incentives for faculty to develop and publish materials via such systems, is also identified as a challenge. Based on these findings, we suggest that a number of steps should be taken by the community to develop the potential of DMDGC in university hydrology education, including formal development and assessment of curriculum materials, integrating lecture-format and DMDGC approaches, incentivizing the publication by faculty of excellent DMDGC curriculum materials, and implementing the publication and dissemination cyberinfrastructure necessary to support the unique DMDGC digital curriculum materials.

Moving university hydrology education forward with geoinformatics, data and modeling approaches

NASA Astrophysics Data System (ADS)

Merwade, V.; Ruddell, B. L.

2012-02-01

In this opinion paper, we review recent literature related to data and modeling driven instruction in hydrology, and present our findings from surveying the hydrology education community in the United States. This paper presents an argument that that Data and Modeling Driven Geoscience Cybereducation (DMDGC) approaches are valuable for teaching the conceptual and applied aspects of hydrology, as a part of the broader effort to improve Science, Technology, Engineering, and Mathematics (STEM) education at the university level. The authors have undertaken a series of surveys and a workshop involving the community of university hydrology educators to determine the state of the practice of DMDGC approaches to hydrology. We identify the most common tools and approaches currently utilized, quantify the extent of the adoption of DMDGC approaches in the university hydrology classroom, and explain the community's views on the challenges and barriers preventing DMDGC approaches from wider use. DMDGC approaches are currently emphasized at the graduate level of the curriculum, and only the most basic modeling and visualization tools are in widespread use. The community identifies the greatest barriers to greater adoption as a lack of access to easily adoptable curriculum materials and a lack of time and training to learn constantly changing tools and methods. The community's current consensus is that DMDGC approaches should emphasize conceptual learning, and should be used to complement rather than replace lecture-based pedagogies. Inadequate online material-publication and sharing systems, and a lack of incentives for faculty to develop and publish materials via such systems, is also identified as a challenge. Based on these findings, we suggest that a number of steps should be taken by the community to develop the potential of DMDGC in university hydrology education, including formal development and assessment of curriculum materials integrating lecture-format and DMDGC approaches, incentivizing the publication by faculty of excellent DMDGC curriculum materials, and implementing the publication and dissemination cyberinfrastructure necessary to support the unique DMDGC digital curriculum materials.

Benchmarking observational uncertainties for hydrology (Invited)

NASA Astrophysics Data System (ADS)

McMillan, H. K.; Krueger, T.; Freer, J. E.; Westerberg, I.

2013-12-01

There is a pressing need for authoritative and concise information on the expected error distributions and magnitudes in hydrological data, to understand its information content. Many studies have discussed how to incorporate uncertainty information into model calibration and implementation, and shown how model results can be biased if uncertainty is not appropriately characterised. However, it is not always possible (for example due to financial or time constraints) to make detailed studies of uncertainty for every research study. Instead, we propose that the hydrological community could benefit greatly from sharing information on likely uncertainty characteristics and the main factors that control the resulting magnitude. In this presentation, we review the current knowledge of uncertainty for a number of key hydrological variables: rainfall, flow and water quality (suspended solids, nitrogen, phosphorus). We collated information on the specifics of the data measurement (data type, temporal and spatial resolution), error characteristics measured (e.g. standard error, confidence bounds) and error magnitude. Our results were primarily split by data type. Rainfall uncertainty was controlled most strongly by spatial scale, flow uncertainty was controlled by flow state (low, high) and gauging method. Water quality presented a more complex picture with many component errors. For all variables, it was easy to find examples where relative error magnitude exceeded 40%. We discuss some of the recent developments in hydrology which increase the need for guidance on typical error magnitudes, in particular when doing comparative/regionalisation and multi-objective analysis. Increased sharing of data, comparisons between multiple catchments, and storage in national/international databases can mean that data-users are far removed from data collection, but require good uncertainty information to reduce bias in comparisons or catchment regionalisation studies. Recently it has become more common for hydrologists to use multiple data types and sources within a single study. This may be driven by complex water management questions which integrate water quantity, quality and ecology; or by recognition of the value of auxiliary data to understand hydrological processes. We discuss briefly the impact of data uncertainty on the increasingly popular use of diagnostic signatures for hydrological process understanding and model development.

A new spatial snow distribution in hydrological models parameterized from observed spatial variability of precipitation.

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Weltzien, Ingunn

2016-04-01

The traditional catchment hydrological model with its many free calibration parameters is not a well suited tool for prediction under conditions for which is has not been calibrated. Important tasks for hydrological modelling such as prediction in ungauged basins and assessing hydrological effects of climate change are hence not solved satisfactory. In order to reduce the number of calibration parameters in hydrological models we have introduced a new model which uses a dynamic gamma distribution as the spatial frequency distribution of snow water equivalent (SWE). The parameters are estimated from observed spatial variability of precipitation and the magnitude of accumulation and melting events and are hence not subject to calibration. The relationship between spatial mean and variance of precipitation is found to follow a pattern where decreasing temporal correlation with increasing accumulation or duration of the event leads to a levelling off or even a decrease of the spatial variance. The new model for snow distribution is implemented in the, already parameter parsimonious, DDD (Distance Distribution Dynamics) hydrological model and was tested for 71 Norwegian catchments. We compared the new snow distribution model with the current operational snow distribution model where a fixed, calibrated coefficient of variation parameterizes a log-normal model for snow distribution. Results show that the precision of runoff simulations is equal, but that the new snow distribution model better simulates snow covered area (SCA) when compared with MODIS satellite derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" is prevented and hence spurious trends in SWE.

Hypothesis testing in hydrology: Theory and practice

NASA Astrophysics Data System (ADS)

Kirchner, James; Pfister, Laurent

2017-04-01

Well-posed hypothesis tests have spurred major advances in hydrological theory. However, a random sample of recent research papers suggests that in hydrology, as in other fields, hypothesis formulation and testing rarely correspond to the idealized model of the scientific method. Practices such as "p-hacking" or "HARKing" (Hypothesizing After the Results are Known) are major obstacles to more rigorous hypothesis testing in hydrology, along with the well-known problem of confirmation bias - the tendency to value and trust confirmations more than refutations - among both researchers and reviewers. Hypothesis testing is not the only recipe for scientific progress, however: exploratory research, driven by innovations in measurement and observation, has also underlain many key advances. Further improvements in observation and measurement will be vital to both exploratory research and hypothesis testing, and thus to advancing the science of hydrology.

Forest hydrology

Treesearch

Ge Sun; Devendra Amatya; Steve McNulty

2016-01-01

Forest hydrology studies the distribution, storage, movement, and quality of water and the hydrological processes in forest-dominated ecosystems. Forest hydrological science is regarded as the foundation of modern integrated water¬shed management. This chapter provides an overview of the history of forest hydrology and basic principles of this unique branch of...

Performance of complex snow cover descriptions in a distributed hydrological model system: A case study for the high Alpine terrain of the Berchtesgaden Alps.

PubMed

Warscher, M; Strasser, U; Kraller, G; Marke, T; Franz, H; Kunstmann, H

2013-05-01

[1] Runoff generation in Alpine regions is typically affected by snow processes. Snow accumulation, storage, redistribution, and ablation control the availability of water. In this study, several robust parameterizations describing snow processes in Alpine environments were implemented in a fully distributed, physically based hydrological model. Snow cover development is simulated using different methods from a simple temperature index approach, followed by an energy balance scheme, to additionally accounting for gravitational and wind-driven lateral snow redistribution. Test site for the study is the Berchtesgaden National Park (Bavarian Alps, Germany) which is characterized by extreme topography and climate conditions. The performance of the model system in reproducing snow cover dynamics and resulting discharge generation is analyzed and validated via measurements of snow water equivalent and snow depth, satellite-based remote sensing data, and runoff gauge data. Model efficiency (the Nash-Sutcliffe coefficient) for simulated runoff increases from 0.57 to 0.68 in a high Alpine headwater catchment and from 0.62 to 0.64 in total with increasing snow model complexity. In particular, the results show that the introduction of the energy balance scheme reproduces daily fluctuations in the snowmelt rates that trace down to the channel stream. These daily cycles measured in snowmelt and resulting runoff rates could not be reproduced by using the temperature index approach. In addition, accounting for lateral snow transport changes the seasonal distribution of modeled snowmelt amounts, which leads to a higher accuracy in modeling runoff characteristics.

Hybrid insolation forcing of Pliocene monsoon dynamics in West Africa

NASA Astrophysics Data System (ADS)

Kuechler, Rony R.; Dupont, Lydie M.; Schefuß, Enno

2018-01-01

The Pliocene is regarded as a potential analogue for future climate with conditions generally warmer-than-today and higher-than-preindustrial atmospheric CO2 levels. Here we present the first orbitally resolved records of continental hydrology and vegetation changes from West Africa for two Pliocene time intervals (5.0-4.6 Ma, 3.6-3.0 Ma), which we compare with records from the last glacial cycle (Kuechler et al., 2013). Our results indicate that changes in local insolation alone are insufficient to explain the full degree of hydrologic variations. Generally two modes of interacting insolation forcings are observed: during eccentricity maxima, when precession was strong, the West African monsoon was driven by summer insolation; during eccentricity minima, when precession-driven variations in local insolation were minimal, obliquity-driven changes in the summer latitudinal insolation gradient became dominant. This hybrid monsoonal forcing concept explains orbitally controlled tropical climate changes, incorporating the forcing mechanism of latitudinal gradients for the Pliocene, which probably increased in importance during subsequent Northern Hemisphere glaciations.

Multi-site calibration, validation, and sensitivity analysis of the MIKE SHE Model for a large watershed in northern China

Treesearch

S. Wang; Z. Zhang; G. Sun; P. Strauss; J. Guo; Y. Tang; A. Yao

2012-01-01

Model calibration is essential for hydrologic modeling of large watersheds in a heterogeneous mountain environment. Little guidance is available for model calibration protocols for distributed models that aim at capturing the spatial variability of hydrologic processes. This study used the physically-based distributed hydrologic model, MIKE SHE, to contrast a lumped...

Effect of Spatial Distribution and Connectivity of Urban Impervious Areas on Hydrologic Response

NASA Astrophysics Data System (ADS)

Khoshouei, F.; Basu, N. B.; Schnoor, J. L.

2012-12-01

Urbanization alters the hydrology of a watershed by increasing impervious areas which results in decreased infiltration and increased runoff. Total Impervious Area (TIA) has been extensively used as a metric to describe this impact. It has recently been recognized, however, that TIA is a necessary but not sufficient attribute to describe the hydrologic response of a watershed. The connectivity and spatial placement of the impervious areas play a significant role in altering streamflow distributions. While the importance of spatial metrics is well recognized, the actual magnitude of their impact has not been adequately quantified in a systematic manner. We assess the effect of the spatial distribution of impervious area on hydrologic response in six peri-urban watersheds with areas in the order of 15 sq km in Midwest. We use the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model from the Army Corp of Engineers for our exploration. GSSHA is a grid-based two-dimensional hydrologic model with 2D overland flow and 1D streamflow and infiltration. The models for the watersheds were calibrated and validated using discharge data from USGS streamflow database. The models were then used in a virtual experimentation mode to understand the variability in hydrologic response as a function of different patterns of urban expansion. A new metric, "Impervious Area Width Function- IAWF" was developed that captured the distribution of flow path lengths from impervious areas. This metric captured the difference in hydrologic response between two watersheds with the same total impervious area but different distributions. The results suggest that urban development in areas with longer travel time (far from outlet) results in higher peak flows.

Catchments as non-linear filters: evaluating data-driven approaches for spatio-temporal predictions in ungauged basins

NASA Astrophysics Data System (ADS)

Bellugi, D. G.; Tennant, C.; Larsen, L.

2016-12-01

Catchment and climate heterogeneity complicate prediction of runoff across time and space, and resulting parameter uncertainty can lead to large accumulated errors in hydrologic models, particularly in ungauged basins. Recently, data-driven modeling approaches have been shown to avoid the accumulated uncertainty associated with many physically-based models, providing an appealing alternative for hydrologic prediction. However, the effectiveness of different methods in hydrologically and geomorphically distinct catchments, and the robustness of these methods to changing climate and changing hydrologic processes remain to be tested. Here, we evaluate the use of machine learning techniques to predict daily runoff across time and space using only essential climatic forcing (e.g. precipitation, temperature, and potential evapotranspiration) time series as model input. Model training and testing was done using a high quality dataset of daily runoff and climate forcing data for 25+ years for 600+ minimally-disturbed catchments (drainage area range 5-25,000 km2, median size 336 km2) that cover a wide range of climatic and physical characteristics. Preliminary results using Support Vector Regression (SVR) suggest that in some catchments this nonlinear-based regression technique can accurately predict daily runoff, while the same approach fails in other catchments, indicating that the representation of climate inputs and/or catchment filter characteristics in the model structure need further refinement to increase performance. We bolster this analysis by using Sparse Identification of Nonlinear Dynamics (a sparse symbolic regression technique) to uncover the governing equations that describe runoff processes in catchments where SVR performed well and for ones where it performed poorly, thereby enabling inference about governing processes. This provides a robust means of examining how catchment complexity influences runoff prediction skill, and represents a contribution towards the integration of data-driven inference and physically-based models.

State transitions and feedback mechanisms control hydrology in the constructed catchment ´Chicken Creeḱ

NASA Astrophysics Data System (ADS)

Schaaf, Wolfgang; Gerwin, Werner; Hinz, Christoph; Zaplata, Markus

2016-04-01

Landscapes and ecosystems are complex systems with many feedback mechanisms acting between the various abiotic and biotic components. The knowledge about these interacting processes is mainly derived from mature ecosystems. The initial development of ecosystem complexity may involve state transitions following catastrophic shifts, disturbances or transgression of thresholds. The Chicken Creek catchment was constructed in 2005 in the mining area of Lusatia/Germany to study processes and feedback mechanisms during ecosystem evolution. The hillslope-shaped 6 ha site has defined boundary conditions and well-documented inner structures. The dominating substrate above the underlying clay layer is Pleistocene sandy material representing mainly the lower C horizon of the former landscape. Since 2005, the unrestricted, unmanaged development of the catchment was intensively monitored. During the ten years since then, we observed characteristic state transitions in catchment functioning driven by feedbacks between original substrate properties, surface structures, soil development and vegetation succession. Whereas surface runoff induced by surface crusting and infiltration dominated catchment hydrology in the first years, the impact of vegetation on hydrological pathways and groundwater levels became more and more evident during the last years. Discharge from the catchment changed from episodic events driven by precipitation and surface runoff to groundwater driven. This general picture is overlain by spatial patterns and single episodic events of external drivers. The scientific value of the Chicken Creek site with known boundary conditions and structure information could help in disentangling general feedback mechanisms between hydrologic, pedogenic, biological and geomorphological processes as well as a in gaining a more integrative view of succession and its drivers during the transition from initial, less complex systems to more mature ecosystems. Long-term time series of data are a key for a better understanding of these processes and the effects on ecosystem resilience and self-organization.

An eco-hydrological approach to predicting regional vegetation and groundwater response to ecological water convergence in dryland riparian ecosystems

USDA-ARS?s Scientific Manuscript database

To improve the management strategy of riparian restoration, better understanding of the dynamic of eco-hydrological system and its feedback between hydrological and ecological components are needed. The fully distributed eco-hydrological model coupled with a hydrology component was developed based o...

A Monthly Water-Balance Model Driven By a Graphical User Interface

USGS Publications Warehouse

McCabe, Gregory J.; Markstrom, Steven L.

2007-01-01

This report describes a monthly water-balance model driven by a graphical user interface, referred to as the Thornthwaite monthly water-balance program. Computations of monthly water-balance components of the hydrologic cycle are made for a specified location. The program can be used as a research tool, an assessment tool, and a tool for classroom instruction.

Research on the semi-distributed monthly rainfall runoff model at the Lancang River basin based on DEM

NASA Astrophysics Data System (ADS)

Liu, Gang; Zhao, Rong; Liu, Jiping; Zhang, Qingpu

2007-06-01

The Lancang River Basin is so narrow and its hydrological and meteorological information are so flexible. The Rainfall, evaporation, glacial melt water and groundwater affect the runoff whose replenishment forms changing notable with the season in different areas at the basin. Characters of different kind of distributed model and conceptual hydrological model are analyzed. A semi-distributed hydrological model of relation between monthly runoff and rainfall, temperate and soil type has been built in Changdu County based on Visual Basic and ArcObject. The way of discretization of distributed hydrological model was used in the model, and principles of conceptual model are taken into account. The sub-catchment of Changdu is divided into regular cells, and all kinds of hydrological and meteorological information and land use classes and slope extracted from 1:250000 digital elevation models are distributed in each cell. The model does not think of the rainfall-runoff hydro-physical process but use the conceptual model to simulate the whole contributes to the runoff of the area. The affection of evapotranspiration loss and underground water is taken into account at the same time. The spatial distribute characteristics of the monthly runoff in the area are simulated and analyzed with a few parameters.

Hydrologic response to multimodel climate output using a physically based model of groundwater/surface water interactions

NASA Astrophysics Data System (ADS)

Sulis, M.; Paniconi, C.; Marrocu, M.; Huard, D.; Chaumont, D.

2012-12-01

General circulation models (GCMs) are the primary instruments for obtaining projections of future global climate change. Outputs from GCMs, aided by dynamical and/or statistical downscaling techniques, have long been used to simulate changes in regional climate systems over wide spatiotemporal scales. Numerous studies have acknowledged the disagreements between the various GCMs and between the different downscaling methods designed to compensate for the mismatch between climate model output and the spatial scale at which hydrological models are applied. Very little is known, however, about the importance of these differences once they have been input or assimilated by a nonlinear hydrological model. This issue is investigated here at the catchment scale using a process-based model of integrated surface and subsurface hydrologic response driven by outputs from 12 members of a multimodel climate ensemble. The data set consists of daily values of precipitation and min/max temperatures obtained by combining four regional climate models and five GCMs. The regional scenarios were downscaled using a quantile scaling bias-correction technique. The hydrologic response was simulated for the 690 km2des Anglais catchment in southwestern Quebec, Canada. The results show that different hydrological components (river discharge, aquifer recharge, and soil moisture storage) respond differently to precipitation and temperature anomalies in the multimodel climate output, with greater variability for annual discharge compared to recharge and soil moisture storage. We also find that runoff generation and extreme event-driven peak hydrograph flows are highly sensitive to any uncertainty in climate data. Finally, the results show the significant impact of changing sequences of rainy days on groundwater recharge fluxes and the influence of longer dry spells in modifying soil moisture spatial variability.

Tilt and strain deformation induced by hydrologically active natural fractures: application to the tiltmeters installed in Sainte-Croix-aux-Mines observatory (France)

NASA Astrophysics Data System (ADS)

Longuevergne, Laurent; Florsch, Nicolas; Boudin, Frédéric; Oudin, Ludovic; Camerlynck, Christian

2009-08-01

We investigate the deformation induced by water pressure variations in hydrologically active natural fractures, and recorded by tiltmeters and strainmeters. The deformation associated with a single fracture is derived using finite-element modelling (FEM). A range in fracture geometries is explored, first to highlight the sensitivity of each geometrical parameter to the deformation, and secondly to allow transfer to observation sites. Water level variations in the fracture are then derived from a hydrological model, driven by observed rainfall, and calibrated on fracture water flow measurements. The modelling results are explicitly applied to constrain the local hydrological contribution to observations with the 100-m-long hydrostatic tiltmeter installed at Sainte-Croix-aux-Mines (France). Our study shows that well-founded physical modelling of local hydrological effect allows a substantial correction of records in observatories.

System Dynamics to Climate-Driven Water Budget Analysis in the Eastern Snake Plains Aquifer

NASA Astrophysics Data System (ADS)

Ryu, J.; Contor, B.; Wylie, A.; Johnson, G.; Allen, R. G.

2010-12-01

Climate variability, weather extremes and climate change continue to threaten the sustainability of water resources in the western United States. Given current climate change projections, increasing temperature is likely to modify the timing, form, and intensity of precipitation events, which consequently affect regional and local hydrologic cycles. As a result, drought, water shortage, and subsequent water conflicts may become an increasing threat in monotone hydrologic systems in arid lands, such as the Eastern Snake Plain Aquifer (ESPA). The ESPA, in particular, is a critical asset in the state of Idaho. It is known as the economic lifeblood for more than half of Idaho’s population so that water resources availability and aquifer management due to climate change is of great interest, especially over the next few decades. In this study, we apply system dynamics as a methodology with which to address dynamically complex problems in ESPA’s water resources management. Aquifer recharge and discharge dynamics are coded in STELLA modeling system as input and output, respectively to identify long-term behavior of aquifer responses to climate-driven hydrological changes.

Potential for Remotely Sensed Soil Moisture Data in Hydrologic Modeling

NASA Technical Reports Server (NTRS)

Engman, Edwin T.

1997-01-01

Many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture and portray the spatial heterogeneity of hydrologic processes and properties that one encounters in drainage basins. The hydrologic processes that may be detected include ground water recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential ET, and information about the hydrologic properties of soils and heterogeneity of hydrologic parameters. Microwave remote sensing has the potential to detect these signatures within a basin in the form of volumetric soil moisture measurements in the top few cm. These signatures should provide information on how and where to apply soil physical parameters in distributed and lumped parameter models and how to subdivide drainage basins into hydrologically similar sub-basins.

Improving flood forecasting capability of physically based distributed hydrological model by parameter optimization

NASA Astrophysics Data System (ADS)

Chen, Y.; Li, J.; Xu, H.

2015-10-01

Physically based distributed hydrological models discrete the terrain of the whole catchment into a number of grid cells at fine resolution, and assimilate different terrain data and precipitation to different cells, and are regarded to have the potential to improve the catchment hydrological processes simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters, but unfortunately, the uncertanties associated with this model parameter deriving is very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study, the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using PSO algorithm and to test its competence and to improve its performances, the second is to explore the possibility of improving physically based distributed hydrological models capability in cathcment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improverd Particle Swarm Optimization (PSO) algorithm is developed for the parameter optimization of Liuxihe model in catchment flood forecasting, the improvements include to adopt the linear decreasing inertia weight strategy to change the inertia weight, and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for Liuxihe model parameter optimization effectively, and could improve the model capability largely in catchment flood forecasting, thus proven that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for Liuxihe model catchment flood forcasting is 20 and 30, respectively.

Reference hydrologic networks II. Using reference hydrologic networks to assess climate-driven changes in streamflow

USGS Publications Warehouse

Burn, Donald H.; Hannaford, Jamie; Hodgkins, Glenn A.; Whitfield, Paul H.; Thorne, Robin; Marsh, Terry

2012-01-01

Reference hydrologic networks (RHNs) can play an important role in monitoring for changes in the hydrological regime related to climate variation and change. Currently, the literature concerning hydrological response to climate variations is complex and confounded by the combinations of many methods of analysis, wide variations in hydrology, and the inclusion of data series that include changes in land use, storage regulation and water use in addition to those of climate. Three case studies that illustrate a variety of approaches to the analysis of data from RHNs are presented and used, together with a summary of studies from the literature, to develop approaches for the investigation of changes in the hydrological regime at a continental or global scale, particularly for international comparison. We present recommendations for an analysis framework and the next steps to advance such an initiative. There is a particular focus on the desirability of establishing standardized procedures and methodologies for both the creation of new national RHNs and the systematic analysis of data derived from a collection of RHNs.

Ensemble Analysis of Variational Assimilation of Hydrologic and Hydrometeorological Data into Distributed Hydrologic Model

NASA Astrophysics Data System (ADS)

Lee, H.; Seo, D.; Koren, V.

2008-12-01

A prototype 4DVAR (four-dimensional variational) data assimilator for gridded Sacramento soil-moisture accounting and kinematic-wave routing models in the Hydrology Laboratory's Research Distributed Hydrologic Model (HL-RDHM) has been developed. The prototype assimilates streamflow and in-situ soil moisture data and adjusts gridded precipitation and climatological potential evaporation data to reduce uncertainty in the model initial conditions for improved monitoring and prediction of streamflow and soil moisture at the outlet and interior locations within the catchment. Due to large degrees of freedom involved, data assimilation (DA) into distributed hydrologic models is complex. To understand and assess sensitivity of the performance of DA to uncertainties in the model initial conditions and in the data, two synthetic experiments have been carried out in an ensemble framework. Results from the synthetic experiments shed much light on the potential and limitations with DA into distributed models. For initial real-world assessment, the prototype DA has also been applied to the headwater basin at Eldon near the Oklahoma-Arkansas border. We present these results and describe the next steps.

Astronomically Forced Hydrology of the Late Cretaceous Sub-tropical Potosí Basin, Bolivia

NASA Astrophysics Data System (ADS)

Tasistro-Hart, A.; Maloof, A. C.; Schoene, B.; Eddy, M. P.

2017-12-01

Orbital forcings paced the ice ages of the Pleistocene, demonstrating that periodic variations in the latitudinal distribution of insolation amplified by ice-albedo feedbacks can guide global climate. How these forcings operate in the hot-houses that span most of the planet's history, however, is unknown. The lacustrine El Molino formation of the late Cretaceous-early Paleogene Potosí Basin in present-day Bolivia contains carbonate-mud parasequences that record fluctuating hydrological conditions from 73 to 63 Ma. This study presents the first cyclostratigraphic analysis using high-resolution drone-derived imagery and 3D elevation models, combined with conventional stratigraphic measurements and magnetic susceptibility data. The drone-derived data are integrated over the entire outcrop at two field areas using a novel application of stratigraphic potential field modeling that increases signal-to-noise ratios prior to spectral analysis. We demonstrate that these parasequences exhibit significant periodicities consistent with eccentricity (400 and 100 kyr), obliquity (50 kyr, 40 kyr, and 29 kyr), precession (17-23 kyr), and semi-precession (9-11 kyr). New U-Pb ID-TIMS zircon ages from intercalacted ash beds corroborate the interpreted sedimentation rates at two sites, indicating that the Potosí Basin contains evidence for hot-house astronomical forcing of sub-tropical lacustrine hydrology. Global climate simulations of late Cretaceous orbital end-member configurations demonstrate precessional-eccentricity and obliquity driven modulation of basin hydrology. In model simulations, the forcings drive long-term shifts in the location of the intertropical convergence zone, changing precipitation along the northern extent of the Potosí Basin's catchment area. This study is the first to demonstrate orbital forcing of a lacustrine system during the Maastrichtian and could ultimately contribute to a precise age for the Cretaceous-Paleogene boundary.

Influence of permafrost distribution on groundwater flow in the context of climate-driven permafrost thaw: example from Yukon Flats Basin, Alaska, United States

USGS Publications Warehouse

Walvoord, Michelle Ann; Voss, Clifford I.; Wellman, Tristan P.

2012-01-01

Understanding the role of permafrost in controlling groundwater flow paths and fluxes is central in studies aimed at assessing potential climate change impacts on vegetation, species habitat, biogeochemical cycling, and biodiversity. Recent field studies in interior Alaska show evidence of hydrologic changes hypothesized to result from permafrost degradation. This study assesses the hydrologic control exerted by permafrost, elucidates modes of regional groundwater flow for various spatial permafrost patterns, and evaluates potential hydrologic consequences of permafrost degradation. The Yukon Flats Basin (YFB), a large (118,340 km2) subbasin within the Yukon River Basin, provides the basis for this investigation. Model simulations that represent an assumed permafrost thaw sequence reveal the following trends with decreasing permafrost coverage: (1) increased groundwater discharge to rivers, consistent with historical trends in base flow observations in the Yukon River Basin, (2) potential for increased overall groundwater flux, (3) increased spatial extent of groundwater discharge in lowlands, and (4) decreased proportion of suprapermafrost (shallow) groundwater contribution to total base flow. These trends directly affect the chemical composition and residence time of riverine exports, the state of groundwater-influenced lakes and wetlands, seasonal river-ice thickness, and stream temperatures. Presently, the YFB is coarsely mapped as spanning the continuous-discontinuous permafrost transition that model analysis shows to be a critical threshold; thus, the YFB may be on the verge of major hydrologic change should the current permafrost extent decrease. This possibility underscores the need for improved characterization of permafrost and other hydrogeologic information in the region via geophysical techniques, remote sensing, and ground-based observations.

The critical role of uncertainty in projections of hydrological extremes

NASA Astrophysics Data System (ADS)

Meresa, Hadush K.; Romanowicz, Renata J.

2017-08-01

This paper aims to quantify the uncertainty in projections of future hydrological extremes in the Biala Tarnowska River at Koszyce gauging station, south Poland. The approach followed is based on several climate projections obtained from the EURO-CORDEX initiative, raw and bias-corrected realizations of catchment precipitation, and flow simulations derived using multiple hydrological model parameter sets. The projections cover the 21st century. Three sources of uncertainty are considered: one related to climate projection ensemble spread, the second related to the uncertainty in hydrological model parameters and the third related to the error in fitting theoretical distribution models to annual extreme flow series. The uncertainty of projected extreme indices related to hydrological model parameters was conditioned on flow observations from the reference period using the generalized likelihood uncertainty estimation (GLUE) approach, with separate criteria for high- and low-flow extremes. Extreme (low and high) flow quantiles were estimated using the generalized extreme value (GEV) distribution at different return periods and were based on two different lengths of the flow time series. A sensitivity analysis based on the analysis of variance (ANOVA) shows that the uncertainty introduced by the hydrological model parameters can be larger than the climate model variability and the distribution fit uncertainty for the low-flow extremes whilst for the high-flow extremes higher uncertainty is observed from climate models than from hydrological parameter and distribution fit uncertainties. This implies that ignoring one of the three uncertainty sources may cause great risk to future hydrological extreme adaptations and water resource planning and management.

The impacts of precipitation amount simulation on hydrological modeling in Nordic watersheds

NASA Astrophysics Data System (ADS)

Li, Zhi; Brissette, Fancois; Chen, Jie

2013-04-01

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

Modeling the Hydrological Cycle in the Atmosphere of Mars: Influence of a Bimodal Size Distribution of Aerosol Nucleation Particles

NASA Astrophysics Data System (ADS)

Shaposhnikov, Dmitry S.; Rodin, Alexander V.; Medvedev, Alexander S.; Fedorova, Anna A.; Kuroda, Takeshi; Hartogh, Paul

2018-02-01

We present a new implementation of the hydrological cycle scheme into a general circulation model of the Martian atmosphere. The model includes a semi-Lagrangian transport scheme for water vapor and ice and accounts for microphysics of phase transitions between them. The hydrological scheme includes processes of saturation, nucleation, particle growth, sublimation, and sedimentation under the assumption of a variable size distribution. The scheme has been implemented into the Max Planck Institute Martian general circulation model and tested assuming monomodal and bimodal lognormal distributions of ice condensation nuclei. We present a comparison of the simulated annual variations, horizontal and vertical distributions of water vapor, and ice clouds with the available observations from instruments on board Mars orbiters. The accounting for bimodality of aerosol particle distribution improves the simulations of the annual hydrological cycle, including predicted ice clouds mass, opacity, number density, and particle radii. The increased number density and lower nucleation rates bring the simulated cloud opacities closer to observations. Simulations show a weak effect of the excess of small aerosol particles on the simulated water vapor distributions.

Capacity building for hydrological change - using a blended learning approach

NASA Astrophysics Data System (ADS)

Nacken, H.

2015-04-01

Extreme hydrological events have always been a challenge to societies. There is growing evidence that hydrological extremes have already become more severe in some regions. The Middle East and North Africa (MENA) region is characterized as one of the world's most water-scarce and driest regions, with a high dependency on climate-sensitive agriculture. There is an urgent need for capacity building programmes that prepare water professionals and communities to deal with the expected hydrological changes and extremes. The most successful capacity building programmes are the country driven ones which involve a wide range of national stakeholders, have a high degree of in-country ownership and have an applicability character. The method of choice to set up such capacity building programmes will be through blended learning.

Invited perspective: Why I am an optimist

NASA Astrophysics Data System (ADS)

Burges, Stephen J.

2011-03-01

I address a range of topics that provide the sociopolitical-technological setting for my professional life. I discuss some influential features of post-World War II world geopolitics, landmark technological developments of that era, and the resulting follow-up technologies that have made it possible to approach various problems in hydrology and water resources. I next address societal needs that have driven developments in hydrology and water resources engineering and follow with a discussion of the modern foundations of our science and what I think are the principal issues in hydrology. I pose three community challenges that when accomplished should advance hydrologic science: data network needs for improving the water budgets at all scales, characterizing subsurface water flow paths, and the information archiving and mining needs from instruments that will generate substantially richer data detail than have been used for most hydrologic work to the present. I then discuss several hydrologic and water resource risk-based decision issues that matter to society to illustrate how such risks have been addressed successfully in the past. I conclude with a long-term community "grand challenge," the coupled modeling of the ocean-atmosphere-landform hydrologic cycle for the purpose of long-lead time hydrologic prediction.

Study of Parameters And Methods of LL-Ⅳ Distributed Hydrological Model in DMIP2

NASA Astrophysics Data System (ADS)

Li, L.; Wu, J.; Wang, X.; Yang, C.; Zhao, Y.; Zhou, H.

2008-05-01

: The Physics-based distributed hydrological model is considered as an important developing period from the traditional experience-hydrology to the physical hydrology. The Hydrology Laboratory of the NOAA National Weather Service proposes the first and second phase of the Distributed Model Intercomparison Project (DMIP)，that it is a great epoch-making work. LL distributed hydrological model has been developed to the fourth generation since it was established in 1997 on the Fengman-I district reservoir area (11000 km2).The LL-I distributed hydrological model was born with the applications of flood control system in the Fengman-I in China. LL-II was developed under the DMIP-I support, it is combined with GIS, RS, GPS, radar rainfall measurement.LL-III was established along with Applications of LL Distributed Model on Water Resources which was supported by the 973-projects of The Ministry of Science and Technology of the People's Republic of China. LL-Ⅳ was developed to face China's water problem. Combined with Blue River and the Baron Fork River basin of DMIP-II, the convection-diffusion equation of non-saturated and saturated seepage was derived from the soil water dynamics and continuous equation. In view of the technical characteristics of the model, the advantage of using convection-diffusion equation to compute confluence overall is longer period of predictable, saving memory space, fast budgeting, clear physical concepts, etc. The determination of parameters of hydrological model is the key, including experience coefficients and parameters of physical parameters. There are methods of experience, inversion, and the optimization to determine the model parameters, and each has advantages and disadvantages. This paper briefly introduces the LL-Ⅳ distribution hydrological model equations, and particularly introduces methods of parameters determination and simulation results on Blue River and Baron Fork River basin for DMIP-II. The soil moisture diffusion coefficient and coefficient of hydraulic conductivity are involved all through the LL-Ⅳ distribution of runoff and slope convergence model, used mainly empirical formula to determine. It's used optimization methods to calculate the two parameters of evaporation capacity (coefficient of bare land and vegetation land), two parameters of interception and wave velocity of Overland Flow, interflow and groundwater. The approach of determining wave velocity of River Network confluence and diffusion coefficient is: 1. Estimate roughness based mainly on digital information such as land use, soil texture, etc. 2.Establish the empirical formula. Another method is called convection-diffusion numerical inversion.

Curricula and Syllabi in Hydrology. A Contribution to the International Hydrological Programme. UNESCO Technical Papers in Hydrology No. 22. Second Edition.

ERIC Educational Resources Information Center

Chandra, Satish, Ed.; Mostertman, L. J., Ed.

Hydrology is the science dealing with the earth's waters, their occurrence, circulation, and distribution, their chemical and physical properties, and their reaction with the environment. As such, hydrology is an indispensible requirement for planning in the field of water resources. Objectives for, spectrum of, and topics for education in…

Algal extracellular release in river-floodplain dissolved organic matter: response of extracellular enzymatic activity during a post-flood period

PubMed Central

Sieczko, Anna; Maschek, Maria; Peduzzi, Peter

2015-01-01

River-floodplain systems are susceptible to rapid hydrological events. Changing hydrological connectivity of the floodplain generates a broad range of conditions, from lentic to lotic. This creates a mixture of allochthonously and autochthonously derived dissolved organic matter (DOM). Autochthonous DOM, including photosynthetic extracellular release (PER), is an important source supporting bacterial secondary production (BSP). Nonetheless, no details are available regarding microbial extracellular enzymatic activity (EEA) as a response to PER under variable hydrological settings in river-floodplain systems. To investigate the relationship between bacterial and phytoplankton components, we therefore used EEA as a tool to track the microbial response to non-chromophoric, but reactive and ecologically important DOM. The study was conducted in three floodplain subsystems with distinct hydrological regimes (Danube Floodplain National Park, Austria). The focus was on the post-flood period. Enhanced %PER (up to 48% of primary production) in a hydrologically isolated subsystem was strongly correlated with β-glucosidase, which was related to BSP. This shows that—in disconnected floodplain backwaters with high terrestrial input—BSP can also be driven by autochthonous carbon sources (PER). In a semi-isolated section, in the presence of fresh labile material from primary producers, enhanced activity of phenol oxidase was observed. In frequently flooded river-floodplain systems, BSP was mainly driven by enzymatic degradation of particulate primary production. Our research demonstrates that EEA measurements are an excellent tool to describe the coupling between bacteria and phytoplankton, which cannot be deciphered when focusing solely on chromophoric DOM. PMID:25741326

Numerical modelling of hydrologically-driven slope instability by means of porous media mechanics

NASA Astrophysics Data System (ADS)

Kakogiannou, Evanthia; Sanavia, Lorenzo; Lora, Marco; Schrefler, Bernhard

2015-04-01

Heavy rainfall can trigger slope failure which generally involves shallow soil deposit of different grading and origin usually in a state of partial saturation. In this case of slope instability, the behaviour of the soil slope is closely related not only to the distribution of pore-water pressure but also to the stress state during rainfall infiltration involving both mechanical and hydrological processes. In order to understand better these physical key processes, in this research work, the modelling of rainfall induced slope failure is considered as a coupled variably saturated hydro-mechanical problem. Therefore, the geometrically linear finite element code Comes-Geo for non-isothermal elasto-plastic multiphase solid porous materials is used, as developed by B.A. Schrefler and his co-workers. In this context, a detailed numerical analysis of an experimental slope stability test due to rainfall infiltration is presented. The main goals of this work are to understand the triggering mechanisms during the progressive failure, the effect of using different constitutive models of the mechanical soil behavior on the numerical results and the use of the second order work criterion on the detection of slope instability.

Recent and historic drivers of landscape change in the Everglades ridge, slough, and Tree Island mosaic

USGS Publications Warehouse

Larsen, Laurel G.; Nicholas Aumen,; Bernhardt, Christopher E.; Vic Engel,; Givnish, Thomas J.; S Hagerthey, P McCormick; Harvey, Judson; Lynn Leonard,; McCormick, P.; McVoy, Christopher; Noe, Gregory; Nungesser, Martha K.; Rutchey, K.; Sklar, Fred; Troxler, Tiffany G.; Volin, John C.; Willard, Debra A.

2011-01-01

More than half of the original Everglades extent formed a patterned peat mosaic of elevated ridges, lower and more open sloughs, and tree islands aligned parallel to the dominant flow direction. This ecologically important landscape structure remained in a dynamic equilibrium for millennia prior to rapid degradation over the past century in response to human manipulation of the hydrologic system. Restoration of the patterned landscape structure is one of the primary objectives of the Everglades restoration effort. Recent research has revealed that three main drivers regulated feedbacks that initiated and maintained landscape structure: the spatial and temporal distribution of surface water depths, surface and subsurface flow, and phosphorus supply. Causes of recent degradation include but are not limited to perturbations to these historically important controls; shifts in mineral and sulfate supply may have also contributed to degradation. Restoring predrainage hydrologic conditions will likely preserve remaining landscape pattern structure, provided a sufficient supply of surface water with low nutrient and low total dissolved solids content exists to maintain a rainfall-driven water chemistry. However, because of hysteresis in landscape evolution trajectories, restoration of areas with a fully degraded landscape could require additional human intervention.

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.

Sequential data assimilation for a distributed hydrologic model considering different time scale of internal processes

NASA Astrophysics Data System (ADS)

Noh, S.; Tachikawa, Y.; Shiiba, M.; Kim, S.

2011-12-01

Applications of the sequential data assimilation methods have been increasing in hydrology to reduce uncertainty in the model prediction. In a distributed hydrologic model, there are many types of state variables and each variable interacts with each other based on different time scales. However, the framework to deal with the delayed response, which originates from different time scale of hydrologic processes, has not been thoroughly addressed in the hydrologic data assimilation. In this study, we propose the lagged filtering scheme to consider the lagged response of internal states in a distributed hydrologic model using two filtering schemes; particle filtering (PF) and ensemble Kalman filtering (EnKF). The EnKF is one of the widely used sub-optimal filters implementing an efficient computation with limited number of ensemble members, however, still based on Gaussian approximation. PF can be an alternative in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions involved. In case of PF, advanced particle regularization scheme is implemented together to preserve the diversity of the particle system. In case of EnKF, the ensemble square root filter (EnSRF) are implemented. Each filtering method is parallelized and implemented in the high performance computing system. A distributed hydrologic model, the water and energy transfer processes (WEP) model, is applied for the Katsura River catchment, Japan to demonstrate the applicability of proposed approaches. Forecasted results via PF and EnKF are compared and analyzed in terms of the prediction accuracy and the probabilistic adequacy. Discussions are focused on the prospects and limitations of each data assimilation method.

Thermodynamic and dynamic responses of the hydrological cycle to solar dimming

NASA Astrophysics Data System (ADS)

Smyth, Jane E.; Russotto, Rick D.; Storelvmo, Trude

2017-05-01

The fundamental role of the hydrological cycle in the global climate system motivates a thorough evaluation of its responses to climate change and mitigation. The Geoengineering Model Intercomparison Project (GeoMIP) is a coordinated international effort to assess the climate impacts of solar geoengineering, a proposal to counteract global warming with a reduction in incoming solar radiation. We assess the mechanisms underlying the rainfall response to a simplified simulation of such solar dimming (G1) in the suite of GeoMIP models and identify robust features. While solar geoengineering nearly restores preindustrial temperatures, the global hydrology is altered. Tropical precipitation changes dominate the response across the model suite, and these are driven primarily by shifts of the Hadley circulation cells. We report a damping of the seasonal migration of the Intertropical Convergence Zone (ITCZ) in G1, associated with preferential cooling of the summer hemisphere, and annual mean ITCZ shifts in some models that are correlated with the warming of one hemisphere relative to the other. Dynamical changes better explain the varying tropical rainfall anomalies between models than changes in relative humidity or the Clausius-Clapeyron scaling of precipitation minus evaporation (P - E), given that the relative humidity and temperature responses are robust across the suite. Strong reductions in relative humidity over vegetated land regions are likely related to the CO2 physiological response in plants. The uncertainty in the spatial distribution of tropical P - E changes highlights the need for cautious consideration and continued study before any implementation of solar geoengineering.

Evaluating the spatial distribution of water balance in a small watershed, Pennsylvania

NASA Astrophysics Data System (ADS)

Yu, Zhongbo; Gburek, W. J.; Schwartz, F. W.

2000-04-01

A conceptual water-balance model was modified from a point application to be distributed for evaluating the spatial distribution of watershed water balance based on daily precipitation, temperature and other hydrological parameters. The model was calibrated by comparing simulated daily variation in soil moisture with field observed data and results of another model that simulates the vertical soil moisture flow by numerically solving Richards' equation. The impacts of soil and land use on the hydrological components of the water balance, such as evapotranspiration, soil moisture deficit, runoff and subsurface drainage, were evaluated with the calibrated model in this study. Given the same meteorological conditions and land use, the soil moisture deficit, evapotranspiration and surface runoff increase, and subsurface drainage decreases, as the available water capacity of soil increases. Among various land uses, alfalfa produced high soil moisture deficit and evapotranspiration and lower surface runoff and subsurface drainage, whereas soybeans produced an opposite trend. The simulated distribution of various hydrological components shows the combined effect of soil and land use. Simulated hydrological components compare well with observed data. The study demonstrated that the distributed water balance approach is efficient and has advantages over the use of single average value of hydrological variables and the application at a single point in the traditional practice.

Hydrologically driven ecosystem processes determine the distribution and persistence of ecosystem-specialist predators under climate change.

PubMed

Carroll, Matthew J; Heinemeyer, Andreas; Pearce-Higgins, James W; Dennis, Peter; West, Chris; Holden, Joseph; Wallage, Zoe E; Thomas, Chris D

2015-07-31

Climate change has the capacity to alter physical and biological ecosystem processes, jeopardizing the survival of associated species. This is a particular concern in cool, wet northern peatlands that could experience warmer, drier conditions. Here we show that climate, ecosystem processes and food chains combine to influence the population performance of species in British blanket bogs. Our peatland process model accurately predicts water-table depth, which predicts abundance of craneflies (keystone invertebrates), which in turn predicts observed abundances and population persistence of three ecosystem-specialist bird species that feed on craneflies during the breeding season. Climate change projections suggest that falling water tables could cause 56-81% declines in cranefly abundance and, hence, 15-51% reductions in the abundances of these birds by 2051-2080. We conclude that physical (precipitation, temperature and topography), biophysical (evapotranspiration and desiccation of invertebrates) and ecological (food chains) processes combine to determine the distributions and survival of ecosystem-specialist predators.

Hydrologically driven ecosystem processes determine the distribution and persistence of ecosystem-specialist predators under climate change

PubMed Central

Carroll, Matthew J.; Heinemeyer, Andreas; Pearce-Higgins, James W.; Dennis, Peter; West, Chris; Holden, Joseph; Wallage, Zoe E.; Thomas, Chris D.

2015-01-01

Climate change has the capacity to alter physical and biological ecosystem processes, jeopardizing the survival of associated species. This is a particular concern in cool, wet northern peatlands that could experience warmer, drier conditions. Here we show that climate, ecosystem processes and food chains combine to influence the population performance of species in British blanket bogs. Our peatland process model accurately predicts water-table depth, which predicts abundance of craneflies (keystone invertebrates), which in turn predicts observed abundances and population persistence of three ecosystem-specialist bird species that feed on craneflies during the breeding season. Climate change projections suggest that falling water tables could cause 56–81% declines in cranefly abundance and, hence, 15–51% reductions in the abundances of these birds by 2051–2080. We conclude that physical (precipitation, temperature and topography), biophysical (evapotranspiration and desiccation of invertebrates) and ecological (food chains) processes combine to determine the distributions and survival of ecosystem-specialist predators. PMID:26227623

Establishment of quantitative hydrological indexes for studies of hydro-biogeochemical interactions at the subsurface.

NASA Astrophysics Data System (ADS)

Alves Meira Neto, A.; Sengupta, A.; Wang, Y.; Volkmann, T.; Chorover, J.; Troch, P. A. A.

2017-12-01

Advances in the understanding of processes in the critical zone (CZ) are dependent on studies coupling the fields of hydrology, microbiology, geochemistry and soil development. At the same time, better insights are needed to integrate hydrologic information into biogeochemical analysis of subsurface environments. This study investigated potential hydrological indexes that help explaining spatiotemporal biogeochemical patterns. The miniLEO is a 2 m3, 10 degree sloping lysimeter located at Biosphere 2 - University of Arizona. The lysimeter was initially filled with pristine basaltic soil and subject to intermittent rainfall applications throughout the period of 18 months followed by its excavation, resulting in a grid-based sample collection at 324 locations. As a result, spatially distributed microbiological and geochemical patterns as well as soil physical properties were obtained. A hydrologic model was then developed in order to simulate the history of the system until the excavation. After being calibrated against sensor data to match its observed input-state-output behavior, the resulting distributed fields of flow velocities and moisture states were retrieved. These results were translated into several hydrological indexes to be used in with distributed microbiological and geochemical signatures. Our study attempts at conciliating sound hydrological modelling with an investigation of the subsurface biological signatures, thus providing a unique opportunity for understanding of fine-scale hydro-biological interactions.

Performance of two predictive uncertainty estimation approaches for conceptual Rainfall-Runoff Model: Bayesian Joint Inference and Hydrologic Uncertainty Post-processing

NASA Astrophysics Data System (ADS)

Hernández-López, Mario R.; Romero-Cuéllar, Jonathan; Camilo Múnera-Estrada, Juan; Coccia, Gabriele; Francés, Félix

2017-04-01

It is noticeably important to emphasize the role of uncertainty particularly when the model forecasts are used to support decision-making and water management. This research compares two approaches for the evaluation of the predictive uncertainty in hydrological modeling. First approach is the Bayesian Joint Inference of hydrological and error models. Second approach is carried out through the Model Conditional Processor using the Truncated Normal Distribution in the transformed space. This comparison is focused on the predictive distribution reliability. The case study is applied to two basins included in the Model Parameter Estimation Experiment (MOPEX). These two basins, which have different hydrological complexity, are the French Broad River (North Carolina) and the Guadalupe River (Texas). The results indicate that generally, both approaches are able to provide similar predictive performances. However, the differences between them can arise in basins with complex hydrology (e.g. ephemeral basins). This is because obtained results with Bayesian Joint Inference are strongly dependent on the suitability of the hypothesized error model. Similarly, the results in the case of the Model Conditional Processor are mainly influenced by the selected model of tails or even by the selected full probability distribution model of the data in the real space, and by the definition of the Truncated Normal Distribution in the transformed space. In summary, the different hypotheses that the modeler choose on each of the two approaches are the main cause of the different results. This research also explores a proper combination of both methodologies which could be useful to achieve less biased hydrological parameter estimation. For this approach, firstly the predictive distribution is obtained through the Model Conditional Processor. Secondly, this predictive distribution is used to derive the corresponding additive error model which is employed for the hydrological parameter estimation with the Bayesian Joint Inference methodology.

Identifying Martian Hydrothermal Sites: Geological Investigation Utilizing Multiple Datasets

NASA Technical Reports Server (NTRS)

Dohm, J. M.; Baker, V. R.; Anderson, R. C.; Scott, D. H.; Rice, J. W., Jr.; Hare, T. M.

2000-01-01

Comprehensive geological investigations of martian landscapes that may have been modified by magmatic-driven hydrothermal activity, utilizing multiple datasets, will yield prime target sites for future hydrological, mineralogical, and biological investigations.

Modeling the Impacts of Hydromodification (Conference paper)

EPA Science Inventory

Hydromodification is caused by anthropogenic activities driven by human population growth and resource consumption that alter watershed hydrologic responses. These activities include urbanization, channel modification, flow regulation by water impoundments, water withdrawal, and...

Shifts in distribution of herbivorous geese relative to hydrological variation in East Dongting Lake wetland, China.

PubMed

Zhang, Pingyang; Zou, Yeai; Xie, Yonghong; Zhang, Hong; Liu, Xiangkui; Gao, Dali; Yi, Feiyue

2018-04-24

Studies on distribution dynamics of waterbirds and the relation with hydrological changes are essential components of ecological researches. East Dongting Lake is a Ramsar site and especially important wintering ground for herbivorous geese along the East Asian-Australasian Flyway. In this paper, based on annual (2008/09-2016/17) waterbird census data, we investigated the spatial-temporal distributions of three herbivorous goose species (Lesser White-fronted Goose Anser erythropus, Bean Goose Anser fabalis, and Greater White-fronted Goose Anser albifrons) within East Dongting Lake, and analyzed their distribution dynamics (denoted by percentage similarity index, PSI) relative to variations in hydrological regime. The results demonstrated that the distribution of the globally vulnerable Lesser White-fronted Geese changed obviously between years, whereas that of Bean Geese was more stable. Greater White-fronted Geese suffered drastic distribution variation during the study period. The PSI of Lesser White-fronted Geese was negatively correlated with between-year difference in water recession time and mean water level in October, whereas no obvious trend was found in Bean Geese. The Normalized Difference Vegetation Index (NDVI) was applied to detect changes in food resources of the geese, and significant correlations were also found between NDVI and hydrological factors. It was inferred that the variations in hydrological regime affected the annual distribution dynamics of Lesser White-fronted Geese by changing food conditions; whereas the effect on Bean Geese were not reflected in this study. Species traits may explain the differences in distribution dynamics among the three goose species. It was speculated that Lesser White-fronted Geese might be more sensitive to habitat change, whereas Bean Geese were more resilient. We suggested that regulating hydrological regime was crucial in management works. Our study could offer scientific information for species conservation in the context of habitat changes in East Dongting Lake wetland and provide potential insights into habitat management in this area. Copyright © 2018 Elsevier B.V. All rights reserved.

Assessment of Coastal and Urban Flooding Hazards Applying Extreme Value Analysis and Multivariate Statistical Techniques: A Case Study in Elwood, Australia

NASA Astrophysics Data System (ADS)

Guimarães Nobre, Gabriela; Arnbjerg-Nielsen, Karsten; Rosbjerg, Dan; Madsen, Henrik

2016-04-01

Traditionally, flood risk assessment studies have been carried out from a univariate frequency analysis perspective. However, statistical dependence between hydrological variables, such as extreme rainfall and extreme sea surge, is plausible to exist, since both variables to some extent are driven by common meteorological conditions. Aiming to overcome this limitation, multivariate statistical techniques has the potential to combine different sources of flooding in the investigation. The aim of this study was to apply a range of statistical methodologies for analyzing combined extreme hydrological variables that can lead to coastal and urban flooding. The study area is the Elwood Catchment, which is a highly urbanized catchment located in the city of Port Phillip, Melbourne, Australia. The first part of the investigation dealt with the marginal extreme value distributions. Two approaches to extract extreme value series were applied (Annual Maximum and Partial Duration Series), and different probability distribution functions were fit to the observed sample. Results obtained by using the Generalized Pareto distribution demonstrate the ability of the Pareto family to model the extreme events. Advancing into multivariate extreme value analysis, first an investigation regarding the asymptotic properties of extremal dependence was carried out. As a weak positive asymptotic dependence between the bivariate extreme pairs was found, the Conditional method proposed by Heffernan and Tawn (2004) was chosen. This approach is suitable to model bivariate extreme values, which are relatively unlikely to occur together. The results show that the probability of an extreme sea surge occurring during a one-hour intensity extreme precipitation event (or vice versa) can be twice as great as what would occur when assuming independent events. Therefore, presuming independence between these two variables would result in severe underestimation of the flooding risk in the study area.

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}...

GIS Based Distributed Runoff Predictions in Variable Source Area Watersheds Employing the SCS-Curve Number

NASA Astrophysics Data System (ADS)

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

2003-04-01

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

A GIS Tool for evaluating and improving NEXRAD and its application in distributed hydrologic modeling

NASA Astrophysics Data System (ADS)

Zhang, X.; Srinivasan, R.

2008-12-01

In this study, a user friendly GIS tool was developed for evaluating and improving NEXRAD using raingauge data. This GIS tool can automatically read in raingauge and NEXRAD data, evaluate the accuracy of NEXRAD for each time unit, implement several geostatistical methods to improve the accuracy of NEXRAD through raingauge data, and output spatial precipitation map for distributed hydrologic model. The geostatistical methods incorporated in this tool include Simple Kriging with varying local means, Kriging with External Drift, Regression Kriging, Co-Kriging, and a new geostatistical method that was newly developed by Li et al. (2008). This tool was applied in two test watersheds at hourly and daily temporal scale. The preliminary cross-validation results show that incorporating raingauge data to calibrate NEXRAD can pronouncedly change the spatial pattern of NEXRAD and improve its accuracy. Using different geostatistical methods, the GIS tool was applied to produce long term precipitation input for a distributed hydrologic model - Soil and Water Assessment Tool (SWAT). Animated video was generated to vividly illustrate the effect of using different precipitation input data on distributed hydrologic modeling. Currently, this GIS tool is developed as an extension of SWAT, which is used as water quantity and quality modeling tool by USDA and EPA. The flexible module based design of this tool also makes it easy to be adapted for other hydrologic models for hydrological modeling and water resources management.

Improving flood forecasting capability of physically based distributed hydrological models by parameter optimization

NASA Astrophysics Data System (ADS)

Chen, Y.; Li, J.; Xu, H.

2016-01-01

Physically based distributed hydrological models (hereafter referred to as PBDHMs) divide the terrain of the whole catchment into a number of grid cells at fine resolution and assimilate different terrain data and precipitation to different cells. They are regarded to have the potential to improve the catchment hydrological process simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters. However, unfortunately the uncertainties associated with this model derivation are very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study: the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using particle swarm optimization (PSO) algorithm and to test its competence and to improve its performances; the second is to explore the possibility of improving physically based distributed hydrological model capability in catchment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with the Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improved PSO algorithm is developed for the parameter optimization of the Liuxihe model in catchment flood forecasting. The improvements include adoption of the linearly decreasing inertia weight strategy to change the inertia weight and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for the Liuxihe model parameter optimization effectively and could improve the model capability largely in catchment flood forecasting, thus proving that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological models. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for the Liuxihe model catchment flood forecasting are 20 and 30 respectively.

Improving rainfall representation for large-scale hydrological modelling of tropical mountain basins

NASA Astrophysics Data System (ADS)

Zulkafli, Zed; Buytaert, Wouter; Onof, Christian; Lavado, Waldo; Guyot, Jean-Loup

2013-04-01

Errors in the forcing data are sometimes overlooked in hydrological studies even when they could be the most important source of uncertainty. The latter particularly holds true in tropical countries with short historical records of rainfall monitoring and remote areas with sparse rain gauge network. In such instances, alternative data such as the remotely sensed precipitation from the TRMM (Tropical Rainfall Measuring Mission) satellite have been used. These provide a good spatial representation of rainfall processes but have been established in the literature to contain volumetric biases that may impair the results of hydrological modelling or worse, are compensated during model calibration. In this study, we analysed precipitation time series from the TMPA (TRMM Multiple Precipitation Algorithm, version 6) against measurements from over 300 gauges in the Andes and Amazon regions of Peru and Ecuador. We found moderately good monthly correlation between the pixel and gauge pairs but a severe underestimation of rainfall amounts and wet days. The discrepancy between the time series pairs is particularly visible over the east side of the Andes and may be attributed to localized and orographic-driven high intensity rainfall, which the satellite product may have limited skills at capturing due to technical and scale issues. This consequently results in a low bias in the simulated streamflow volumes further downstream. In comparison, with the recently released TMPA, version 7, the biases reduce. This work further explores several approaches to merge the two sources of rainfall measurements, each of a different spatial and temporal support, with the objective of improving the representation of rainfall in hydrological simulations. The methods used are (1) mean bias correction (2) data assimilation using Kalman filter Bayesian updating. The results are evaluated by means of (1) a comparison of runoff ratios (the ratio of the total runoff and the total precipitation over an extended period) in multiple basins, and (2) a comparison of the outcome of hydrological modelling using the distributed JULES (Joint-UK Land Environment Simulator) land surface model. First results indicate an improvement in the water balance that directly translates into an increased hydrological performance. The more interesting aspect of the study, however, will be the insights into the nature of satellite precipitation errors in this extreme environment and the optimal means of improving the data to generate increased confidence in hydrological predictions.

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.

Crowdsourcing to Acquire Hydrologic Data and Engage Citizen Scientists: CrowdHydrology

USGS Publications Warehouse

Fienen, Michael N.; Lowry, Chris

2013-01-01

Spatially and temporally distributed measurements of processes, such as baseflow at the watershed scale, come at substantial equipment and personnel cost. Research presented here focuses on building a crowdsourced database of inexpensive distributed stream stage measurements. Signs on staff gauges encourage citizen scientists to voluntarily send hydrologic measurements (e.g., stream stage) via text message to a server that stores and displays the data on the web. Based on the crowdsourced stream stage, we evaluate the accuracy of citizen scientist measurements and measurement approach. The results show that crowdsourced data collection is a supplemental method for collecting hydrologic data and a promising method of public engagement.

Reference hydrologic networks I. The status and potential future directions of national reference hydrologic networks for detecting trends

USGS Publications Warehouse

Whitfield, Paul H.; Burn, Donald H.; Hannaford, Jamie; Higgins, Hélène; Hodgkins, Glenn A.; Marsh, Terry; Looser, Ulrich

2012-01-01

Identifying climate-driven trends in river flows on a global basis is hampered by a lack of long, quality time series data for rivers with relatively undisturbed regimes. This is a global problem compounded by the lack of support for essential long-term monitoring. Experience demonstrates that, with clear strategic objectives, and the support of sponsoring organizations, reference hydrologic networks can constitute an exceptionally valuable data source to effectively identify, quantify and interpret hydrological change—the speed and magnitude of which is expected to a be a primary driver of water management and flood alleviation strategies through the future—and for additional applications. Reference hydrologic networks have been developed in many countries in the past few decades. These collections of streamflow gauging stations, that are maintained and operated with the intention of observing how the hydrology of watersheds responds to variations in climate, are described. The status of networks under development is summarized. We suggest a plan of actions to make more effective use of this collection of networks.

Investigating Hydrogeologic Controls on Sandhill Wetlands in Covered Karst with 2D Resistivity and Ground Penetrating Radar

NASA Astrophysics Data System (ADS)

Downs, C. M.; Nowicki, R. S.; Rains, M. C.; Kruse, S.

2015-12-01

In west-central Florida, wetland and lake distribution is strongly controlled by karst landforms. Sandhill wetlands and lakes are sand-filled upland basins whose water levels are groundwater driven. Lake dimensions only reach wetland edges during extreme precipitation events. Current wetland classification schemes are inappropriate for identifying sandhill wetlands due to their unique hydrologic regime and ecologic expression. As a result, it is difficult to determine whether or not a wetland is impacted by groundwater pumping, development, and climate change. A better understanding of subsurface structures and how they control the hydrologic regime is necessary for development of an identification and monitoring protocol. Long-term studies record vegetation diversity and distribution, shallow ground water levels and surface water levels. The overall goals are to determine the hydrologic controls (groundwater, seepage, surface water inputs). Most recently a series of geophysical surveys was conducted at select sites in Hernando and Pasco County, Florida. Electrical resistivity and ground penetrating radar were employed to image sand-filled basins and the top of the limestone bedrock and stratigraphy of wetland slopes, respectively. The deepest extent of these sand-filled basins is generally reflected in topography as shallow depressions. Resistivity along inundated wetlands suggests the pools are surface expressions of the surficial aquifer. However, possible breaches in confining clay layers beneath topographic highs between depressions are seen in resistivity profiles as conductive anomalies and in GPR as interruptions in otherwise continuous horizons. These data occur at sites where unconfined and confined water levels are in agreement, suggesting communication between shallow and deep groundwater. Wetland plants are observed outside the historic wetland boundary at many sites, GPR profiles show near-surface layers dipping towards the wetlands at a shallower angle than the slope. Wetlands plants are often found where these layers are truncated by the slope suggesting seepage of unconfined aquifer and a new wetland boundary.

Two tales of legacy effects on stream nutrient behaviour

NASA Astrophysics Data System (ADS)

Bieroza, M.; Heathwaite, A. L.

2017-12-01

Intensive agriculture has led to large-scale land use conversion, shortening of flow pathways and increased loads of nutrients in streams. This legacy results in gradual build-up of nutrients in agricultural catchments: in soil for phosphorus (biogeochemical legacy) and in the unsaturated zone for nitrate (hydrologic legacy), controlling the water quality in the long-term. Here we investigate these effects on phosphorus and nitrate stream concentrations using high-frequency (10-5 - 100 Hz) sampling with in situ wet-chemistry analysers and optical sensors. Based on our 5 year study, we observe that storm flow responses differ for both nutrients: phosphorus shows rapid increases (up to 3 orders of magnitude) in concentrations with stream flow, whereas nitrate shows both dilution and concentration effects with increasing flow. However, the range of nitrate concentrations change is narrow (up to 2 times the mean) and reflects chemostatic behaviour. We link these nutrient responses with their dominant sources and flow pathways in the catchment. Nitrate from agriculture (with the peak loading in 1983) is stored in the unsaturated zone of the Penrith Sandstone, which can reach up to 70 m depth. Thus nitrate legacy is related to a hydrologic time lag with long travel times in the unsaturated zone. Phosphorus is mainly sorbed to soil particles, therefore it is mobilised rapidly during rainfall events (biogeochemical legacy). The phosphorus stream response will however depend on how well connected is the stream to the catchment sources (driven by soil moisture distribution) and biogeochemical activity (driven by temperature), leading to both chemostatic and non-chemostatic responses, alternating on a storm-to-storm and seasonal basis. Our results also show that transient within-channel storage is playing an important role in delivery of phosphorus, providing an additional time lag component. These results show, that consistent agricultural legacy in the catchment (high historical loads of nutrients) has different effects on nutrients stream responses, depending on their dominant sources and pathways. Both types of time lags, biogeochemical for phosphorus and hydrologic for nitrate, need to be taken into account when designing and evaluating the effectiveness of the agri-environmental mitigation measures.

Effects of distributed and centralized stormwater best management practices and land cover on urban stream hydrology at the catchment scale

NASA Astrophysics Data System (ADS)

Loperfido, J. V.; Noe, Gregory B.; Jarnagin, S. Taylor; Hogan, Dianna M.

2014-11-01

Urban stormwater runoff remains an important issue that causes local and regional-scale water quantity and quality issues. Stormwater best management practices (BMPs) have been widely used to mitigate runoff issues, traditionally in a centralized manner; however, problems associated with urban hydrology have remained. An emerging trend is implementation of BMPs in a distributed manner (multi-BMP treatment trains located on the landscape and integrated with urban design), but little catchment-scale performance of these systems have been reported to date. Here, stream hydrologic data (March, 2011-September, 2012) are evaluated in four catchments located in the Chesapeake Bay watershed: one utilizing distributed stormwater BMPs, two utilizing centralized stormwater BMPs, and a forested catchment serving as a reference. Among urban catchments with similar land cover, geology and BMP design standards (i.e. 100-year event), but contrasting placement of stormwater BMPs, distributed BMPs resulted in: significantly greater estimated baseflow, a higher minimum precipitation threshold for stream response and maximum discharge increases, better maximum discharge control for small precipitation events, and reduced runoff volume during an extreme (1000-year) precipitation event compared to centralized BMPs. For all catchments, greater forest land cover and less impervious cover appeared to be more important drivers than stormwater BMP spatial pattern, and caused lower total, stormflow, and baseflow runoff volume; lower maximum discharge during typical precipitation events; and lower runoff volume during an extreme precipitation event. Analysis of hydrologic field data in this study suggests that both the spatial distribution of stormwater BMPs and land cover are important for management of urban stormwater runoff. In particular, catchment-wide application of distributed BMPs improved stream hydrology compared to centralized BMPs, but not enough to fully replicate forested catchment stream hydrology. Integrated planning of stormwater management, protected riparian buffers and forest land cover with suburban development in the distributed-BMP catchment enabled multi-purpose use of land that provided esthetic value and green-space, community gathering points, and wildlife habitat in addition to hydrologic stormwater treatment.

Effects of distributed and centralized stormwater best management practices and land cover on urban stream hydrology at the catchment scale

USGS Publications Warehouse

Loperfido, John V.; Noe, Gregory B.; Jarnagin, S. Taylor; Hogan, Dianna M.

2014-01-01

Urban stormwater runoff remains an important issue that causes local and regional-scale water quantity and quality issues. Stormwater best management practices (BMPs) have been widely used to mitigate runoff issues, traditionally in a centralized manner; however, problems associated with urban hydrology have remained. An emerging trend is implementation of BMPs in a distributed manner (multi-BMP treatment trains located on the landscape and integrated with urban design), but little catchment-scale performance of these systems have been reported to date. Here, stream hydrologic data (March, 2011–September, 2012) are evaluated in four catchments located in the Chesapeake Bay watershed: one utilizing distributed stormwater BMPs, two utilizing centralized stormwater BMPs, and a forested catchment serving as a reference. Among urban catchments with similar land cover, geology and BMP design standards (i.e. 100-year event), but contrasting placement of stormwater BMPs, distributed BMPs resulted in: significantly greater estimated baseflow, a higher minimum precipitation threshold for stream response and maximum discharge increases, better maximum discharge control for small precipitation events, and reduced runoff volume during an extreme (1000-year) precipitation event compared to centralized BMPs. For all catchments, greater forest land cover and less impervious cover appeared to be more important drivers than stormwater BMP spatial pattern, and caused lower total, stormflow, and baseflow runoff volume; lower maximum discharge during typical precipitation events; and lower runoff volume during an extreme precipitation event. Analysis of hydrologic field data in this study suggests that both the spatial distribution of stormwater BMPs and land cover are important for management of urban stormwater runoff. In particular, catchment-wide application of distributed BMPs improved stream hydrology compared to centralized BMPs, but not enough to fully replicate forested catchment stream hydrology. Integrated planning of stormwater management, protected riparian buffers and forest land cover with suburban development in the distributed-BMP catchment enabled multi-purpose use of land that provided esthetic value and green-space, community gathering points, and wildlife habitat in addition to hydrologic stormwater treatment.

Comparison of the performance and reliability of 18 lumped hydrological models driven by ECMWF rainfall ensemble forecasts: a case study on 29 French catchments

NASA Astrophysics Data System (ADS)

Velázquez, Juan Alberto; Anctil, François; Ramos, Maria-Helena; Perrin, Charles

2010-05-01

An ensemble forecasting system seeks to assess and to communicate the uncertainty of hydrological predictions by proposing, at each time step, an ensemble of forecasts from which one can estimate the probability distribution of the predictant (the probabilistic forecast), in contrast with a single estimate of the flow, for which no distribution is obtainable (the deterministic forecast). In the past years, efforts towards the development of probabilistic hydrological prediction systems were made with the adoption of ensembles of numerical weather predictions (NWPs). The additional information provided by the different available Ensemble Prediction Systems (EPS) was evaluated in a hydrological context on various case studies (see the review by Cloke and Pappenberger, 2009). For example, the European ECMWF-EPS was explored in case studies by Roulin et al. (2005), Bartholmes et al. (2005), Jaun et al. (2008), and Renner et al. (2009). The Canadian EC-EPS was also evaluated by Velázquez et al. (2009). Most of these case studies investigate the ensemble predictions of a given hydrological model, set up over a limited number of catchments. Uncertainty from weather predictions is assessed through the use of meteorological ensembles. However, uncertainty from the tested hydrological model and statistical robustness of the forecasting system when coping with different hydro-meteorological conditions are less frequently evaluated. The aim of this study is to evaluate and compare the performance and the reliability of 18 lumped hydrological models applied to a large number of catchments in an operational ensemble forecasting context. Some of these models were evaluated in a previous study (Perrin et al. 2001) for their ability to simulate streamflow. Results demonstrated that very simple models can achieve a level of performance almost as high (sometimes higher) as models with more parameters. In the present study, we focus on the ability of the hydrological models to provide reliable probabilistic forecasts of streamflow, based on ensemble weather predictions. The models were therefore adapted to run in a forecasting mode, i.e., to update initial conditions according to the last observed discharge at the time of the forecast, and to cope with ensemble weather scenarios. All models are lumped, i.e., the hydrological behavior is integrated over the spatial scale of the catchment, and run at daily time steps. The complexity of tested models varies between 3 and 13 parameters. The models are tested on 29 French catchments. Daily streamflow time series extend over 17 months, from March 2005 to July 2006. Catchment areas range between 1470 km2 and 9390 km2, and represent a variety of hydrological and meteorological conditions. The 12 UTC 10-day ECMWF rainfall ensemble (51 members) was used, which led to daily streamflow forecasts for a 9-day lead time. In order to assess the performance and reliability of the hydrological ensemble predictions, we computed the Continuous Ranked probability Score (CRPS) (Matheson and Winkler, 1976), as well as the reliability diagram (e.g. Wilks, 1995) and the rank histogram (Talagrand et al., 1999). Since the ECMWF deterministic forecasts are also available, the performance of the hydrological forecasting systems was also evaluated by comparing the deterministic score (MAE) with the probabilistic score (CRPS). The results obtained for the 18 hydrological models and the 29 studied catchments are discussed in the perspective of improving the operational use of ensemble forecasting in hydrology. References Bartholmes, J. and Todini, E.: Coupling meteorological and hydrological models for flood forecasting, Hydrol. Earth Syst. Sci., 9, 333-346, 2005. Cloke, H. and Pappenberger, F.: Ensemble Flood Forecasting: A Review. Journal of Hydrology 375 (3-4): 613-626, 2009. Jaun, S., Ahrens, B., Walser, A., Ewen, T., and Schär, C.: A probabilistic view on the August 2005 floods in the upper Rhine catchment, Nat. Hazards Earth Syst. Sci., 8, 281-291, 2008. Matheson, J. E. and Winkler, R. L.: Scoring rules for continuous probability distributions, Manage Sci., 22, 1087-1096, 1976. Perrin, C., Michel C. and Andréassian,V. Does a large number of parameters enhance model performance? Comparative assessment of common catchment model structures on 429 catchments, J. Hydrol., 242, 275-301, 2001. Renner, M., Werner, M. G. F., Rademacher, S., and Sprokkereef, E.: Verification of ensemble flow forecast for the River Rhine, J. Hydrol., 376, 463-475, 2009. Roulin, E. and Vannitsem, S.: Skill of medium-range hydrological ensemble predictions, J. Hydrometeorol., 6, 729-744, 2005. Talagrand, O., Vautard, R., and Strauss, B.: Evaluation of the probabilistic prediction systems, in: Proceedings, ECMWF Workshop on Predictability, Shinfield Park, Reading, Berkshire, ECMWF, 1-25, 1999. Velázquez, J.A., Petit, T., Lavoie, A., Boucher M.-A., Turcotte R., Fortin V., and Anctil, F. : An evaluation of the Canadian global meteorological ensemble prediction system for short-term hydrological forecasting, Hydrol. Earth Syst. Sci., 13, 2221-2231, 2009. Wilks, D. S.: Statistical Methods in the Atmospheric Sciences, Academic Press, San Diego, CA, 465 pp., 1995.

Rainy Day: A Remote Sensing-Driven Extreme Rainfall Simulation Approach for Hazard Assessment

NASA Astrophysics Data System (ADS)

Wright, Daniel; Yatheendradas, Soni; Peters-Lidard, Christa; Kirschbaum, Dalia; Ayalew, Tibebu; Mantilla, Ricardo; Krajewski, Witold

2015-04-01

Progress on the assessment of rainfall-driven hazards such as floods and landslides has been hampered by the challenge of characterizing the frequency, intensity, and structure of extreme rainfall at the watershed or hillslope scale. Conventional approaches rely on simplifying assumptions and are strongly dependent on the location, the availability of long-term rain gage measurements, and the subjectivity of the analyst. Regional and global-scale rainfall remote sensing products provide an alternative, but are limited by relatively short (~15-year) observational records. To overcome this, we have coupled these remote sensing products with a space-time resampling framework known as stochastic storm transposition (SST). SST "lengthens" the rainfall record by resampling from a catalog of observed storms from a user-defined region, effectively recreating the regional extreme rainfall hydroclimate. This coupling has been codified in Rainy Day, a Python-based platform for quickly generating large numbers of probabilistic extreme rainfall "scenarios" at any point on the globe. Rainy Day is readily compatible with any gridded rainfall dataset. The user can optionally incorporate regional rain gage or weather radar measurements for bias correction using the Precipitation Uncertainties for Satellite Hydrology (PUSH) framework. Results from Rainy Day using the CMORPH satellite precipitation product are compared with local observations in two examples. The first example is peak discharge estimation in a medium-sized (~4000 square km) watershed in the central United States performed using CUENCAS, a parsimonious physically-based distributed hydrologic model. The second example is rainfall frequency analysis for Saint Lucia, a small volcanic island in the eastern Caribbean that is prone to landslides and flash floods. The distinct rainfall hydroclimates of the two example sites illustrate the flexibility of the approach and its usefulness for hazard analysis in data-poor regions.

Data-Driven Geospatial Visual Analytics for Real-Time Urban Flooding Decision Support

NASA Astrophysics Data System (ADS)

Liu, Y.; Hill, D.; Rodriguez, A.; Marini, L.; Kooper, R.; Myers, J.; Wu, X.; Minsker, B. S.

2009-12-01

Urban flooding is responsible for the loss of life and property as well as the release of pathogens and other pollutants into the environment. Previous studies have shown that spatial distribution of intense rainfall significantly impacts the triggering and behavior of urban flooding. However, no general purpose tools yet exist for deriving rainfall data and rendering them in real-time at the resolution of hydrologic units used for analyzing urban flooding. This paper presents a new visual analytics system that derives and renders rainfall data from the NEXRAD weather radar system at the sewershed (i.e. urban hydrologic unit) scale in real-time for a Chicago stormwater management project. We introduce a lightweight Web 2.0 approach which takes advantages of scientific workflow management and publishing capabilities developed at NCSA (National Center for Supercomputing Applications), streaming data-aware semantic content management repository, web-based Google Earth/Map and time-aware KML (Keyhole Markup Language). A collection of polygon-based virtual sensors is created from the NEXRAD Level II data using spatial, temporal and thematic transformations at the sewershed level in order to produce persistent virtual rainfall data sources for the animation. Animated color-coded rainfall map in the sewershed can be played in real-time as a movie using time-aware KML inside the web browser-based Google Earth for visually analyzing the spatiotemporal patterns of the rainfall intensity in the sewershed. Such system provides valuable information for situational awareness and improved decision support during extreme storm events in an urban area. Our further work includes incorporating additional data (such as basement flooding events data) or physics-based predictive models that can be used for more integrated data-driven decision support.

Critical impact of vegetation physiology on the continental hydrologic cycle in response to increasing CO2

NASA Astrophysics Data System (ADS)

Lemordant, Léo; Gentine, Pierre; Swann, Abigail S.; Cook, Benjamin I.; Scheff, Jacob

2018-04-01

Predicting how increasing atmospheric CO2 will affect the hydrologic cycle is of utmost importance for a range of applications ranging from ecological services to human life and activities. A typical perspective is that hydrologic change is driven by precipitation and radiation changes due to climate change, and that the land surface will adjust. Using Earth system models with decoupled surface (vegetation physiology) and atmospheric (radiative) CO2 responses, we here show that the CO2 physiological response has a dominant role in evapotranspiration and evaporative fraction changes and has a major effect on long-term runoff compared with radiative or precipitation changes due to increased atmospheric CO2. This major effect is true for most hydrological stress variables over the largest fraction of the globe, except for soil moisture, which exhibits a more nonlinear response. This highlights the key role of vegetation in controlling future terrestrial hydrologic response and emphasizes that the carbon and water cycles are intimately coupled over land.

Socio-Hydrology Modelling for an Uncertain Future, with Examples from the USA and Canada (Invited)

NASA Astrophysics Data System (ADS)

White, D. D.; Gober, P.; Sampson, D. A.; Quay, R.; Kirkwood, C.

2013-12-01

Socio-hydrology brings an interest in human values, markets, social organizations and public policy to the traditional emphasis of water science on climate, hydrology, toxicology,and ecology. It also conveys a decision focus in the form of decision support tools, engagement, and new knowledge about the science-policy interface. This paper demonstrates how policy decisions and human behavior can be better integrated into climate and hydrological models to improve their usefulness for support in decision making. Examples from the Southwest USA and Western Canada highlight uncertainties, vulnerabilities, and critical tradeoffs facing water decision makers in the face of rapidly changing environmental and societal conditions. Irreducible uncertainties in downscaled climate and hydrological models limit the usefulness of climate-driven, predict-and-plan methods of water resource planning and management. Thus, it is argued that such methods should be replaced by approaches that use exploratory modelling, scenario planning, and risk assessment in which the emphasis is on managing uncertainty rather than on reducing it.

APPLICATION OF A FULLY DISTRIBUTED WASHOFF AND TRANSPORT MODEL FOR A GULF COAST WATERSHED

EPA Science Inventory

Advances in hydrologic modeling have been shown to improve the accuracy of rainfall runoff simulation and prediction. Building on the capabilities of distributed hydrologic modeling, a water quality model was developed to simulate buildup, washoff, and advective transport of a co...

Modelling Seasonally Freezing Ground Conditions

DTIC Science & Technology

1989-05-01

used as the ’snow input’ in the larger hydrological models, e.g. Pangburn (1987). The most advanced index model is Anderson’s (1973) model. This bases...source as the soils) is shown in figures 32 and 33. Table 10 shows the percentage areas of Hydrologic Soil Groups, Land Use and Slope Distribution for...C") z c~cu CYa) 65 table 10: Percentage areas of Hydrologic Soil Grouos, Land Use and Slope Distribution over W3 (?Pn!ke e: al., 1978) Parameter

Uncertainty Propagation of Non-Parametric-Derived Precipitation Estimates into Multi-Hydrologic Model Simulations

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Comprehensive Representation of Hydrologic and Geomorphic Process Coupling in Numerical Models: Internal Dynamics and Basin Evolution

NASA Astrophysics Data System (ADS)

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

2005-12-01

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

Internal Catchment Process Simulation in a Snow-Dominated Basin: Performance Evaluation with Spatiotemporally Variable Runoff Generation and Groundwater Dynamics

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

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 showed some unexpected results, where climate models predicting the largest increase in net precipitation did not result in the largest increase in groundwater heads. This was found to be the result of different initial conditions (1990 - 2010) for the various climate models. In some areas a combination of a high initial groundwater head and an increase in precipitation towards 2021 - 2050 resulted in a groundwater head raise that reached the drainage or the surface water system. This will increase the exchange from the groundwater to the surface water system, but reduce the raise in groundwater heads. An alternative climate model, with a lower initial head can thus predict a higher increase in the groundwater head, although the increase in precipitation is lower. This illustrates an extra dimension in the uncertainty assessment, namely the climate models capability of simulating the current climatic conditions in a way that can reproduce the observed hydrological response. Højberg, AL, Troldborg, L, Stisen, S, et al. (2012) Stakeholder driven update and improvement of a national water resources model - http://www.sciencedirect.com/science/article/pii/S1364815212002423 Seaby, LP, Refsgaard, JC, Sonnenborg, TO, et al. (2012) Assessment of robustness and significance of climate change signals for an ensemble of distribution-based scaled climate projections (submitted) Journal of Hydrology Stisen, S, Højberg, AL, Troldborg, L et al., (2012): On the importance of appropriate rain-gauge catch correction for hydrological modelling at mid to high latitudes - http://www.hydrol-earth-syst-sci.net/16/4157/2012/

Getting the right answers for the right reasons: Linking measurements, analyses, and models to advance the science of hydrology

NASA Astrophysics Data System (ADS)

Kirchner, James W.

2006-03-01

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

Results of Formal Evaluation of a Data and Modeling Driven Hydrology Learning Module

NASA Astrophysics Data System (ADS)

Ruddell, B. L.; Sanchez, C. A.; Schiesser, R.; Merwade, V.

2014-12-01

New hydrologists should not only develop a well-defined knowledgebase of basic hydrological concepts, but also synthesize this factual learning with more authentic 'real-world' knowledge gained from the interpretation and analysis of data from hydrological models (Merwade and Ruddell, 2012, Wagener et al., 2007). However, hydrological instruction is often implemented using a traditional teacher-centered approach (e.g., lectures) (Wagener, 2007). The emergence of rich and dynamic computer simulation techniques which allow students the opportunity for more authentic application of knowledge (Merwade & Ruddell, 2012). This study evaluates the efficacy of using such data-driven simulations to increase the understanding of the field of hydrology in the lower-division undergraduate geoscience classroom. In this study, 88 students at a local community college who were enrolled in an Introductory Earth Science class were evaluated on their learning performance in a unit on applying the Rational Method to estimate hydrographs and flooding for urban areas. Students were either presented with a data and visualization rich computer module (n=52), or with paper and pencil calculation activities (n=36). All conceptual material presented in lecture was consistent across these two conditions. Students were evaluated for not only changes in their knowledge and application of the concepts within the unit (e.g., effects of urbanization and impervious cover, discharge rates), but also for their broad "T-shaped" profile of professional knowledge and skills. While results showed significant (p<.05) increases from pre to post assessments in all learning areas for both groups, there is a significantly larger benefit for the data module group when it came to (1) understanding the effects of urbanization and impervious cover on flooding, (2) applying consistent vocabulary appropriately within context, and (3) explaining the roles and responsibilities of hydrologists and flood managers.

Calibration process of highly parameterized semi-distributed hydrological model

NASA Astrophysics Data System (ADS)

Vidmar, Andrej; Brilly, Mitja

2017-04-01

Hydrological phenomena take place in the hydrological system, which is governed by nature, and are essentially stochastic. These phenomena are unique, non-recurring, and changeable across space and time. Since any river basin with its own natural characteristics and any hydrological event therein, are unique, this is a complex process that is not researched enough. Calibration is a procedure of determining the parameters of a model that are not known well enough. Input and output variables and mathematical model expressions are known, while only some parameters are unknown, which are determined by calibrating the model. The software used for hydrological modelling nowadays is equipped with sophisticated algorithms for calibration purposes without possibility to manage process by modeler. The results are not the best. We develop procedure for expert driven process of calibration. We use HBV-light-CLI hydrological model which has command line interface and coupling it with PEST. PEST is parameter estimation tool which is used widely in ground water modeling and can be used also on surface waters. Process of calibration managed by expert directly, and proportionally to the expert knowledge, affects the outcome of the inversion procedure and achieves better results than if the procedure had been left to the selected optimization algorithm. First step is to properly define spatial characteristic and structural design of semi-distributed model including all morphological and hydrological phenomena, like karstic area, alluvial area and forest area. This step includes and requires geological, meteorological, hydraulic and hydrological knowledge of modeler. Second step is to set initial parameter values at their preferred values based on expert knowledge. In this step we also define all parameter and observation groups. Peak data are essential in process of calibration if we are mainly interested in flood events. Each Sub Catchment in the model has own observations group. Third step is to set appropriate bounds to parameters in their range of realistic values. Fourth step is to use of singular value decomposition (SVD) ensures that PEST maintains numerical stability, regardless of how ill-posed is the inverse problem Fifth step is to run PWTADJ1. This creates a new PEST control file in which weights are adjusted such that the contribution made to the total objective function by each observation group is the same. This prevents the information content of any group from being invisible to the inversion process. Sixth step is to add Tikhonov regularization to the PEST control file by running the ADDREG1 utility (Doherty, J, 2013). In adding regularization to the PEST control file ADDREG1 automatically provides a prior information equation for each parameter in which the preferred value of that parameter is equated to its initial value. Last step is to run PEST. We run BeoPEST which a parallel version of PEST and can be run on multiple computers in parallel in same time on TCP communications and this speedup process of calibrations. The case study with results of calibration and validation of the model will be presented.

The Effect of Model Grid Resolution on the Distributed Hydrologic Simulations for Forecasting Stream Flows and Reservoir Storage

NASA Astrophysics Data System (ADS)

Turnbull, S. J.

2017-12-01

Within the US Army Corps of Engineers (USACE), reservoirs are typically operated according to a rule curve that specifies target water levels based on the time of year. The rule curve is intended to maximize flood protection by specifying releases of water before the dominant rainfall period for a region. While some operating allowances are permissible, generally the rule curve elevations must be maintained. While this operational approach provides for the required flood control purpose, it may not result in optimal reservoir operations for multi-use impoundments. In the Russian River Valley of California a multi-agency research effort called Forecast-Informed Reservoir Operations (FIRO) is assessing the application of forecast weather and streamflow predictions to potentially enhance the operation of reservoirs in the watershed. The focus of the study has been on Lake Mendocino, a USACE project important for flood control, water supply, power generation and ecological flows. As part of this effort the Engineer Research and Development Center is assessing the ability of utilizing the physics based, distributed watershed model Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model to simulate stream flows, reservoir stages, and discharges while being driven by weather forecast products. A key question in this application is the effect of watershed model resolution on forecasted stream flows. To help resolve this question, GSSHA models of multiple grid resolutions, 30, 50, and 270m, were developed for the upper Russian River, which includes Lake Mendocino. The models were derived from common inputs: DEM, soils, land use, stream network, reservoir characteristics, and specified inflows and discharges. All the models were calibrated in both event and continuous simulation mode using measured precipitation gages and then driven with the West-WRF atmospheric model in prediction mode to assess the ability of the model to function in short term, less than one week, forecasting mode. In this presentation we will discuss the effect the grid resolution has model development, parameter assignment, streamflow prediction and forecasting capability utilizing the West-WRF forecast hydro-meteorology.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Simultaneous Semi-Distributed Model Calibration Guided by Hydrologic Landscapes in the Pacific Northwest, USA

EPA Science Inventory

Modelling approaches to transfer hydrologically-relevant information from locations with streamflow measurements to locations without such measurements continues to be an active field of research for hydrologists. The Pacific Northwest Hydrologic Landscapes (PNW HL) provide a sol...

Delineating floodplain and upload areas for hydrologic models: A comparison of methods

USDA-ARS?s Scientific Manuscript database

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. Floodplains are critical landscape features that differ from neighboring up...

Using StorAge Selection Functions to Improve Simulation of Groundwater Nitrate Lag Times in the SWAT Modeling Framework.

NASA Astrophysics Data System (ADS)

Wilusz, D. C.; Fuka, D.; Cho, C.; Ball, W. P.; Easton, Z. M.; Harman, C. J.

2017-12-01

Intensive agriculture and atmospheric deposition have dramatically increased the input of reactive nitrogen into many watersheds worldwide. Reactive nitrogen can leach as nitrate into groundwater, which is stored and eventually released over years to decades into surface waters, potentially degrading water quality. To simulate the fate and transport of groundwater nitrate, many researchers and practitioners use the Soil and Water Assessment Tool (SWAT) or an enhanced version of SWAT that accounts for topographically-driven variable source areas (TopoSWAT). Both SWAT and TopoSWAT effectively assume that nitrate in the groundwater reservoir is well-mixed, which is known to be a poor assumption at many sites. In this study, we describe modifications to TopoSWAT that (1) relax the assumption of groundwater well-mixedness, (2) more flexibly parameterize groundwater transport as a time-varying distribution of travel times using the recently developed theory of rank StorAge Selection (rSAS) functions, and (3) allow for groundwater age to be represented by position on the hillslope or hydrological distance from the stream. The approach conceptualizes the groundwater aquifer as a population of water parcels entering as recharge with a particular nitrate concentration, aging as they move through storage, and eventually exiting as baseflow. The rSAS function selects the distribution of parcel ages that exit as baseflow based on a parameterized probability distribution; this distribution can be adjusted to preferentially select different distributions of young and old parcels in storage so as to reproduce (in principle) any form of transport. The modified TopoSWAT model (TopoSWAT+rSAS) is tested at a small agricultural catchment in the Eastern Shore, MD with an extensive hydrologic and hydrochemical data record for calibration and evaluation. The results examine (1) the sensitivity of TopoSWAT+rSAS modeling of nitrate transport to assumptions about the distribution of travel times of the groundwater aquifer, (2) which travel times are most likely at our study site based on available data, and (3) how TopoSWAT+rSAS performs and can be applied to other catchments.

Real-Time Mapping alert system; characteristics and capabilities

USGS Publications Warehouse

Torres, L.A.; Lambert, S.C.; Liebermann, T.D.

1995-01-01

The U.S. Geological Survey has an extensive hydrologic network that records and transmits precipitation, stage, discharge, and other water-related data on a real-time basis to an automated data processing system. Data values are recorded on electronic data collection platforms at field sampling sites. These values are transmitted by means of orbiting satellites to receiving ground stations, and by way of telecommunication lines to a U.S. Geological Survey office where they are processed on a computer system. Data that exceed predefined thresholds are identified as alert values. The current alert status at monitoring sites within a state or region is of critical importance during floods, hurricanes, and other extreme hydrologic events. This report describes the characteristics and capabilities of a series of computer programs for real-time mapping of hydrologic data. The software provides interactive graphics display and query of hydrologic information from the network in a real-time, map-based, menu-driven environment.

Humans in Biogeophysical Models: Colonial Period Human-Environment Interactions in the Northeastern United States

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

The role of stochastic storms on hillslope runoff generation and connectivity in a dryland basin

NASA Astrophysics Data System (ADS)

Michaelides, K.; Singer, M. B.; Mudd, S. M.

2016-12-01

Despite low annual rainfall, dryland basins can generate significant surface runoff during certain rainstorms, which can cause flash flooding and high rates of erosion. However, it remains challenging to anticipate the nature and frequency of runoff generation in hydrological systems which are driven by spatially and temporally stochastic rainstorms. In particular, the stochasticity of rainfall presents challenges to simulating the hydrological response of dryland basins and understanding flow connectivity from hillslopes to the channel. Here we simulate hillslope runoff generation using rainfall characteristics produced by a simple stochastic rainfall generator, which is based on a rich rainfall dataset from the Walnut Gulch Experimental Watershed (WGEW) in Arizona, USA. We assess hillslope runoff generation using the hydrological model, COUP2D, driven by a subset of characteristic output from multiple ensembles of decadal monsoonal rainfall from the stochastic rainfall generator. The rainfall generator operates across WGEW by simulating storms with areas smaller than the basin and enables explicit characterization of rainfall characteristics at any location. We combine the characteristics of rainfall intensity and duration with data on rainstorm area and location to model the surface runoff properties (depth, velocity, duration, distance downslope) on a range of hillslopes within the basin derived from LiDAR analysis. We also analyze connectivity of flow from hillslopes to the channel for various combinations of hillslopes and storms. This approach provides a framework for understanding spatial and temporal dynamics of runoff generation and connectivity that is faithful to the hydrological characteristics of dryland environments.

A new moving strategy for the sequential Monte Carlo approach in optimizing the hydrological model parameters

NASA Astrophysics Data System (ADS)

Zhu, Gaofeng; Li, Xin; Ma, Jinzhu; Wang, Yunquan; Liu, Shaomin; Huang, Chunlin; Zhang, Kun; Hu, Xiaoli

2018-04-01

Sequential Monte Carlo (SMC) samplers have become increasing popular for estimating the posterior parameter distribution with the non-linear dependency structures and multiple modes often present in hydrological models. However, the explorative capabilities and efficiency of the sampler depends strongly on the efficiency in the move step of SMC sampler. In this paper we presented a new SMC sampler entitled the Particle Evolution Metropolis Sequential Monte Carlo (PEM-SMC) algorithm, which is well suited to handle unknown static parameters of hydrologic model. The PEM-SMC sampler is inspired by the works of Liang and Wong (2001) and operates by incorporating the strengths of the genetic algorithm, differential evolution algorithm and Metropolis-Hasting algorithm into the framework of SMC. We also prove that the sampler admits the target distribution to be a stationary distribution. Two case studies including a multi-dimensional bimodal normal distribution and a conceptual rainfall-runoff hydrologic model by only considering parameter uncertainty and simultaneously considering parameter and input uncertainty show that PEM-SMC sampler is generally superior to other popular SMC algorithms in handling the high dimensional problems. The study also indicated that it may be important to account for model structural uncertainty by using multiplier different hydrological models in the SMC framework in future study.

Development of Load Duration Curve System in Data Scarce Watersheds Based on a Distributed Hydrological Model

NASA Astrophysics Data System (ADS)

WANG, J.

2017-12-01

In stream water quality control, the total maximum daily load (TMDL) program is very effective. However, the load duration curves (LDC) of TMDL are difficult to be established because no sufficient observed flow and pollutant data can be provided in data-scarce watersheds in which no hydrological stations or consecutively long-term hydrological data are available. Although the point sources or a non-point sources of pollutants can be clarified easily with the aid of LDC, where does the pollutant come from and to where it will be transported in the watershed cannot be traced by LDC. To seek out the best management practices (BMPs) of pollutants in a watershed, and to overcome the limitation of LDC, we proposed to develop LDC based on a distributed hydrological model of SWAT for the water quality management in data scarce river basins. In this study, firstly, the distributed hydrological model of SWAT was established with the scarce-hydrological data. Then, the long-term daily flows were generated with the established SWAT model and rainfall data from the adjacent weather station. Flow duration curves (FDC) was then developed with the aid of generated daily flows by SWAT model. Considering the goal of water quality management, LDC curves of different pollutants can be obtained based on the FDC. With the monitored water quality data and the LDC curves, the water quality problems caused by the point or non-point source pollutants in different seasons can be ascertained. Finally, the distributed hydrological model of SWAT was employed again to tracing the spatial distribution and the origination of the pollutants of coming from what kind of agricultural practices and/or other human activities. A case study was conducted in the Jian-jiang river, a tributary of Yangtze river, of Duyun city, Guizhou province. Results indicate that this kind of method can realize the water quality management based on TMDL and find out the suitable BMPs for reducing pollutant in a watershed.

Distributed Hydrologic Modeling of Semiarid Basins in Arizona: A Platform for Land Cover and Climate Change Assessments

NASA Astrophysics Data System (ADS)

Hawkins, G. A.; Vivoni, E. R.

2011-12-01

Watershed management is challenged by rising concerns over climate change and its potential to interact with land cover alterations to impact regional water supplies and hydrologic processes. The inability to conduct experimental manipulations that address climate and land cover change at watershed scales limits the capacity of water managers to make decisions to protect future supplies. As a result, spatially-explicit, physically-based models possess value for predicting the possible consequences on watershed hydrology. In this study, we apply a distributed watershed model, the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS), to the Beaver Creek basin in Arizona. This sub-basin of the Verde River is representative of the regional topography, land cover, soils distribution and availability of hydrologic data in forested regions of northern Arizona. As such, it can serve as a demonstration study in the broader region to illustrate the utility of distributed models for change assessment studies. Through a model application to summertime conditions, we compare the hydrologic response from three sources of meteorological input: (1) an available network of ground-based stations, (2) weather radar rainfall estimates, and (3) the North American Land Data Assimilation System (NLDAS). Comparisons focus on analysis of spatiotemporal distributions of precipitation, soil moisture, runoff generation, evapotranspiration and recharge from the root zone at high resolution for an assessment of sustainable water supplies for agricultural and domestic purposes. We also present a preliminary analysis of the impact of vegetation change arising from historical treatments in the Beaver Creek to inform the hydrologic consequences in the form of soil moisture and evapotranspiration patterns with differing degrees of proposed forest thinning. Our results are discussed in the context of improved hydrologic predictions for sustainability and decision-making under the uncertainties induced by combined climate and land cover change.

Impacts of climate change on precipitation and discharge extremes through the use of statistical downscaling approaches in a Mediterranean basin.

PubMed

Piras, Monica; Mascaro, Giuseppe; Deidda, Roberto; Vivoni, Enrique R

2016-02-01

Mediterranean region is characterized by high precipitation variability often enhanced by orography, with strong seasonality and large inter-annual fluctuations, and by high heterogeneity of terrain and land surface properties. As a consequence, catchments in this area are often prone to the occurrence of hydrometeorological extremes, including storms, floods and flash-floods. A number of climate studies focused in the Mediterranean region predict that extreme events will occur with higher intensity and frequency, thus requiring further analyses to assess their effect at the land surface, particularly in small- and medium-sized watersheds. In this study, climate and hydrologic simulations produced within the Climate Induced Changes on the Hydrology of Mediterranean Basins (CLIMB) EU FP7 research project were used to analyze how precipitation extremes propagate into discharge extremes in the Rio Mannu basin (472.5km(2)), located in Sardinia, Italy. The basin hydrologic response to climate forcings in a reference (1971-2000) and a future (2041-2070) period was simulated through the combined use of a set of global and regional climate models, statistical downscaling techniques, and a process based distributed hydrologic model. We analyzed and compared the distribution of annual maxima extracted from hourly and daily precipitation and peak discharge time series, simulated by the hydrologic model under climate forcing. For this aim, yearly maxima were fit by the Generalized Extreme Value (GEV) distribution using a regional approach. Next, we discussed commonality and contrasting behaviors of precipitation and discharge maxima distributions to better understand how hydrological transformations impact propagation of extremes. Finally, we show how rainfall statistical downscaling algorithms produce more reliable forcings for hydrological models than coarse climate model outputs. Copyright © 2015 Elsevier B.V. All rights reserved.

An Iterative Local Updating Ensemble Smoother for Estimation and Uncertainty Assessment of Hydrologic Model Parameters With Multimodal Distributions

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

A Bayesian alternative for multi-objective ecohydrological model specification

NASA Astrophysics Data System (ADS)

Tang, Yating; Marshall, Lucy; Sharma, Ashish; Ajami, Hoori

2018-01-01

Recent studies have identified the importance of vegetation processes in terrestrial hydrologic systems. Process-based ecohydrological models combine hydrological, physical, biochemical and ecological processes of the catchments, and as such are generally more complex and parametric than conceptual hydrological models. Thus, appropriate calibration objectives and model uncertainty analysis are essential for ecohydrological modeling. In recent years, Bayesian inference has become one of the most popular tools for quantifying the uncertainties in hydrological modeling with the development of Markov chain Monte Carlo (MCMC) techniques. The Bayesian approach offers an appealing alternative to traditional multi-objective hydrologic model calibrations by defining proper prior distributions that can be considered analogous to the ad-hoc weighting often prescribed in multi-objective calibration. Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological modeling framework based on a traditional Pareto-based model calibration technique. In our study, a Pareto-based multi-objective optimization and a formal Bayesian framework are implemented in a conceptual ecohydrological model that combines a hydrological model (HYMOD) and a modified Bucket Grassland Model (BGM). Simulations focused on one objective (streamflow/LAI) and multiple objectives (streamflow and LAI) with different emphasis defined via the prior distribution of the model error parameters. Results show more reliable outputs for both predicted streamflow and LAI using Bayesian multi-objective calibration with specified prior distributions for error parameters based on results from the Pareto front in the ecohydrological modeling. The methodology implemented here provides insight into the usefulness of multiobjective Bayesian calibration for ecohydrologic systems and the importance of appropriate prior distributions in such approaches.

Hydrological parameter estimations from a conservative tracer test with variable-density effects at the Boise Hydrogeophysical Research Site

NASA Astrophysics Data System (ADS)

Dafflon, B.; Barrash, W.; Cardiff, M.; Johnson, T. C.

2011-12-01

Reliable predictions of groundwater flow and solute transport require an estimation of the detailed distribution of the parameters (e.g., hydraulic conductivity, effective porosity) controlling these processes. However, such parameters are difficult to estimate because of the inaccessibility and complexity of the subsurface. In this regard, developments in parameter estimation techniques and investigations of field experiments are still challenging and necessary to improve our understanding and the prediction of hydrological processes. Here we analyze a conservative tracer test conducted at the Boise Hydrogeophysical Research Site in 2001 in a heterogeneous unconfined fluvial aquifer. Some relevant characteristics of this test include: variable-density (sinking) effects because of the injection concentration of the bromide tracer, the relatively small size of the experiment, and the availability of various sources of geophysical and hydrological information. The information contained in this experiment is evaluated through several parameter estimation approaches, including a grid-search-based strategy, stochastic simulation of hydrological property distributions, and deterministic inversion using regularization and pilot-point techniques. Doing this allows us to investigate hydraulic conductivity and effective porosity distributions and to compare the effects of assumptions from several methods and parameterizations. Our results provide new insights into the understanding of variable-density transport processes and the hydrological relevance of incorporating various sources of information in parameter estimation approaches. Among others, the variable-density effect and the effective porosity distribution, as well as their coupling with the hydraulic conductivity structure, are seen to be significant in the transport process. The results also show that assumed prior information can strongly influence the estimated distributions of hydrological properties.

A Web-based Distributed Voluntary Computing Platform for Large Scale Hydrological Computations

NASA Astrophysics Data System (ADS)

Demir, I.; Agliamzanov, R.

2014-12-01

Distributed volunteer computing can enable researchers and scientist to form large parallel computing environments to utilize the computing power of the millions of computers on the Internet, and use them towards running large scale environmental simulations and models to serve the common good of local communities and the world. Recent developments in web technologies and standards allow client-side scripting languages to run at speeds close to native application, and utilize the power of Graphics Processing Units (GPU). Using a client-side scripting language like JavaScript, we have developed an open distributed computing framework that makes it easy for researchers to write their own hydrologic models, and run them on volunteer computers. Users will easily enable their websites for visitors to volunteer sharing their computer resources to contribute running advanced hydrological models and simulations. Using a web-based system allows users to start volunteering their computational resources within seconds without installing any software. The framework distributes the model simulation to thousands of nodes in small spatial and computational sizes. A relational database system is utilized for managing data connections and queue management for the distributed computing nodes. In this paper, we present a web-based distributed volunteer computing platform to enable large scale hydrological simulations and model runs in an open and integrated environment.

Evaluating Spatial Variability in Sediment and Phosphorus Concentration-Discharge Relationships Using Bayesian Inference and Self-Organizing Maps

NASA Astrophysics Data System (ADS)

Underwood, Kristen L.; Rizzo, Donna M.; Schroth, Andrew W.; Dewoolkar, Mandar M.

2017-12-01

Given the variable biogeochemical, physical, and hydrological processes driving fluvial sediment and nutrient export, the water science and management communities need data-driven methods to identify regions prone to production and transport under variable hydrometeorological conditions. We use Bayesian analysis to segment concentration-discharge linear regression models for total suspended solids (TSS) and particulate and dissolved phosphorus (PP, DP) using 22 years of monitoring data from 18 Lake Champlain watersheds. Bayesian inference was leveraged to estimate segmented regression model parameters and identify threshold position. The identified threshold positions demonstrated a considerable range below and above the median discharge—which has been used previously as the default breakpoint in segmented regression models to discern differences between pre and post-threshold export regimes. We then applied a Self-Organizing Map (SOM), which partitioned the watersheds into clusters of TSS, PP, and DP export regimes using watershed characteristics, as well as Bayesian regression intercepts and slopes. A SOM defined two clusters of high-flux basins, one where PP flux was predominantly episodic and hydrologically driven; and another in which the sediment and nutrient sourcing and mobilization were more bimodal, resulting from both hydrologic processes at post-threshold discharges and reactive processes (e.g., nutrient cycling or lateral/vertical exchanges of fine sediment) at prethreshold discharges. A separate DP SOM defined two high-flux clusters exhibiting a bimodal concentration-discharge response, but driven by differing land use. Our novel framework shows promise as a tool with broad management application that provides insights into landscape drivers of riverine solute and sediment export.

Human impact parameterization in global hydrological models improves estimates of monthly discharges and hydrological extremes: a multi-model validation study

NASA Astrophysics Data System (ADS)

Veldkamp, Ted; Ward, Philip; de Moel, Hans; Aerts, Jeroen; Muller Schmied, Hannes; Portmann, Felix; Zhao, Fang; Gerten, Dieter; Masaki, Yoshimitsu; Pokhrel, Yadu; Satoh, Yusuke; Gosling, Simon; Zaherpour, Jamal; Wada, Yoshihide

2017-04-01

Human impacts on freshwater resources and hydrological features form the core of present-day water related hazards, like flooding, droughts, water scarcity, and water quality issues. Driven by the societal and scientific needs to correctly model such water related hazards a fair amount of resources has been invested over the past decades to represent human activities and their interactions with the hydrological cycle in global hydrological models (GHMs). Use of these GHMs - including the human dimension - is widespread, especially in water resources research. Evaluation or comparative assessments of the ability of such GHMs to represent real-world hydrological conditions are, unfortunately, however often limited to (near-)natural river basins. Such studies are, therefore, not able to test the model representation of human activities and its associated impact on estimates of freshwater resources or assessments of hydrological extremes. Studies that did perform a validation exercise - including the human dimension and looking into managed catchments - either focused only on one hydrological model, and/or incorporated only a few data points (i.e. river basins) for validation. To date, a comprehensive comparative analysis that evaluates whether and where incorporating the human dimension actually improves the performance of different GHMs with respect to their representation of real-world hydrological conditions and extremes is missing. The absence of such study limits the potential benchmarking of GHMs and their outcomes in hydrological hazard and risk assessments significantly, potentially hampering incorporation of GHMs and their modelling results in actual policy making and decision support with respect to water resources management. To address this issue, we evaluate in this study the performance of five state-of-the-art GHMs that include anthropogenic activities in their modelling scheme, with respect to their representation of monthly discharges and hydrological extremes. To this end, we compared their monthly discharge simulations under a naturalized and a time-dependent human impact simulation, with monthly GRDC river discharge observations of 2,412 stations over the period 1971-2010. Evaluation metrics that were used to assess the performance of the GHMs included the modified Kling-Gupta Efficiency index, and its individual parameters describing the linear correlation coefficient, the bias ratio, and the variability ratio, as well as indicators for hydrological extremes (Q90, Q10). Our results show that inclusion of anthropogenic activities in the modelling framework generally enhances the overall performance of the GHMs studied, mainly driven by bias-improvements, and to a lesser extent due to changes in modelled hydrological variability. Whilst the inclusion of anthropogenic activities takes mainly effect in the managed catchments, a significant share of the (near-)natural catchments is influenced as well. To get estimates of hydrological extremes right, especially when looking at low-flows, inclusion of human activities is paramount. Whilst high-flow estimates are mainly decreased, impact of human activities on low-flows is ambiguous, i.e. due to the relative importance of the timing of return flows and reservoir operations. Even with inclusion of the human dimension we find, nevertheless, a persistent overestimation of hydrological extremes across all models, which should be accounted for in future assessments.

Exploring changes in the spatial distribution of stream baseflow generation during a seasonal recession

Treesearch

R.A. Payn; M.N. Gooseff; B.L. McGlynn; K.E. Bencala; S.M. Wondzell

2012-01-01

Relating watershed structure to streamflow generation is a primary focus of hydrology. However, comparisons of longitudinal variability in stream discharge with adjacent valley structure have been rare, resulting in poor understanding of the distribution of the hydrologic mechanisms that cause variability in streamflow generation along valleys. This study explores...

Impacts of Freshets on Hyporheic Exchange Flow under Neutral Conditions

NASA Astrophysics Data System (ADS)

Singh, T.; Wu, L.; Worman, A. L. E.; Hannah, D. M.; Krause, S.; Gomez-Velez, J. D.

2016-12-01

Hyporheic zones (HZs) are characterized by the exchange of water, solutes, momentum and energy between streams and aquifers. Hyporheic exchange flow (HEF) is driven by pressure gradients along the sediment-water interface, which in turn are caused by interactions between channel flow and bed topography. With this in mind, changes in channel flow can have significant effects in the hydrodynamic and transport characteristics of HZs. While previous research has improved our understanding of the drivers and controls of HEF, little attention has been paid to the potential impacts of transient dynamic hydrologic forcing, such as freshets. In this study, we use a two-dimensional, homogeneous flow and transport model with a time-varying pressure distribution at the sediment-water interface to explore the dynamic development of HZ characteristics in response to discharge fluctuations (i.e., freshets). With this model, we explore a wide range of plausible scenarios for discharge and bed geometry. Our modelling results show that a single freshet alters the spatial extent and penetration of the HZ, though quantitatively different, when investigated using hydrological (streamlines/flow field) and geochemical (>90% of surface water in streambed) approaches of HZ. We summarize the results of a detailed sensitivity analysis where the effects of hydraulic geometry (slope, amplitude of the streambed), flood characteristics (duration, skewness and magnitude of the flood wave) and biogeochemical timescales (time-scale for oxygen consumption) on the HZ's extent, mean age, and oxic/anoxic zonation are explored. Taking into consideration these multiple morphological characteristics along with variable hydrological controls has clear potential to facilitate process understanding and upscaling.

Robust and Heterogeneous Hydrological Changes under Global Warming

NASA Astrophysics Data System (ADS)

Kumar, S.; Zwiers, F. W.; Dirmeyer, P.; Lawrence, D. M.; Shrestha, R. R.; Werner, A. T.

2015-12-01

The Intergovernmental Panel on Climate Change (IPCC) has continued to find it difficult to make clear assessments of streamflow changes [Assessment Report 5, Working Group II, Chapter 3] in large part because of the heterogeneity of observed and projected hydrological changes. While prior studies have found some evidence of human influence on precipitation changes, the detection of streamflow changes is not robust. Here, we show that the terrestrial branch of the hydrological cycle, namely the partitioning of precipitation into evapotranspiration and runoff, is an important piece of the puzzle that may explain the apparent disconnect between the detectability of precipitation and streamflow changes. We apply Budyko framework to quantify sensitivity of hydrological changes to climate driven changes in water balance regionally. We demonstrate that the hydrological sensitivity is 3 times greater in regions where the hydrological cycle is energy limited (wet regions) than water limited (dry regions), and therefore the detectability of streamflow changes is also greater by 30-40% in wet regions. Evidence from observations in western North America and an analysis of Coupled Model Intercomparison Project Phase 5 climate models at global scales indicate that use of the Budyko framework can help identify robust and spatially heterogeneous hydrological responses to external forcing on the climate system.

Spatially explicit simulation of hydrologically controlled carbon and nitrogen cycles and associated feedback mechanisms in a boreal ecosystem in Eastern Canada.

NASA Astrophysics Data System (ADS)

Govind, A.; Chen, J. M.; Margolis, H.

2007-12-01

Current estimates of terrestrial carbon overlook the effects of topographically-driven lateral flow of soil water. We hypothesize that this component, which occur at a landscape or watershed scale have significant influences on the spatial distribution of carbon, due to its large contribution to the local water balance. To this end, we further developed a spatially explicit ecohydrological model, BEPS-TerrainLab V2.0. We simulated the coupled hydrological and carbon cycle processes in a black spruce-moss ecosystem in central Quebec, Canada. The carbon stocks were initialized using a long term carbon cycling model, InTEC, under a climate change and disturbance scenario, the accuracy of which was determined with inventory plot measurements. Further, we simulated and validated several ecosystem indicators such as ET, GPP, NEP, water table, snow depth and soil temperature, using the measurements for two years, 2004 and 2005. After gaining confidence in the model's ability to simulate ecohydrological processes, we tested the influence of lateral water flow on the carbon cycle. We made three hydrological modeling scenarios 1) Explicit, were realistic lateral water routing was considered 2) Implicit where calculations were based on a bucket modeling approach 3) NoFlow, where the lateral water flow was turned off in the model. The results showed that pronounced anomalies exist among the scenarios for the simulated GPP, ET and NEP. In general, Implicit calculation overestimated GPP and underestimated NEP, as opposed to Explicit simulation. NoFlow underestimated GPP and overestimated NEP. The key processes controlling GPP were manifested through stomatal conductance which reduces under conditions of rapid soil saturation ( NoFlow ) or increases in the Implicit case, and, nitrogen availability which affects Vcmax, the maximum carboxylation rate. However, for NEP, the anomalies were attributed to differences in soil carbon pool decomposition, which determine the heterotrophic respiration and the resultant nitrogen mineralization which affects GPP and several other feedback mechanisms. These results suggest that lateral water flow does play a significant role in the terrestrial carbon distribution. Therefore, regional or global scale terrestrial carbon estimates could have significant errors if proper hydrological constrains are not considered for modeling ecological processes due to large topographic variations on the Earth's surface. For more info please visit: http://ajit.govind.googlepages.com/agu2007

Soil moisture monitoring in Candelaro basin, Southern Italy

NASA Astrophysics Data System (ADS)

Campana, C.; Gigante, V.; Iacobellis, V.

2012-04-01

The signature of the hydrologic regime can be investigated, in principle, by recognizing the main mechanisms of runoff generation that take place in the basin and affect the seasonal behavior or the rainfall-driven events. In this framework, besides the implementation of hydrological models, a crucial role should be played by direct observation of key state variables such as soil moisture at different depths and different distances from the river network. In fact, understanding hydrological systems is often limited by the frequency and spatial distribution of observations. Experimental catchments, which are field laboratories with long-term measurements of hydrological variables, are not only sources of data but also sources of knowledge. Wireless distributed sensing platforms are a key technology to address the need for overcoming field limitations such as conflicts between soil use and cable connections. A stand-alone wireless network system has been installed for continuous monitoring of soil water contents at multiple depths along a transect located in Celone basin (sub-basin of Candelaro basin in Puglia, Southern Italy). The transect consists of five verticals, each one having three soil water content sensors at multiple depths: 0,05 m, 0,6 m and 1,2 m below the ground level. The total length of the transect is 307 m and the average distance between the verticals is 77 m. The main elements of the instrumental system installed are: fifteen Decagon 10HS Soil Moisture Sensors, five Decagon Em50R Wireless Radio Data Loggers, one Rain gauge, one Decagon Data Station and one Campbell CR1000 Data Logger. Main advantages of the system as described and presented in this work are that installation of the wireless network system is fast and easy to use, data retrieval and monitoring information over large spatial scales can be obtained in (near) real-time mode and finally other type of sensors can be connected to the system, also offering wide potentials for future applications. First records of the wireless underground network system indicate the presence of interesting patterns in space-time variability of volumetric soil moisture content, that provide evidence of the combined process of vertical infiltration and lateral flow. ACKNOWLEDGEMENT The research in this work is supported by the MIRAGE FP7 project (Grant agreement n. 211732).

Soil Moisture: The Hydrologic Interface Between Surface and Ground Waters

NASA Technical Reports Server (NTRS)

Engman, Edwin T.

1997-01-01

A hypothesis is presented that many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture. The specific hydrologic processes that may be detected include groundwater recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential evapotranspiration (ET), and information about the hydrologic properties of soils. In basin and hillslope hydrology, soil moisture is the interface between surface and ground waters.

Real-world hydrologic assessment of a fully-distributed hydrological model in a parallel computing environment

NASA Astrophysics Data System (ADS)

Vivoni, Enrique R.; Mascaro, Giuseppe; Mniszewski, Susan; Fasel, Patricia; Springer, Everett P.; Ivanov, Valeriy Y.; Bras, Rafael L.

2011-10-01

SummaryA major challenge in the use of fully-distributed hydrologic models has been the lack of computational capabilities for high-resolution, long-term simulations in large river basins. In this study, we present the parallel model implementation and real-world hydrologic assessment of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS). Our parallelization approach is based on the decomposition of a complex watershed using the channel network as a directed graph. The resulting sub-basin partitioning divides effort among processors and handles hydrologic exchanges across boundaries. Through numerical experiments in a set of nested basins, we quantify parallel performance relative to serial runs for a range of processors, simulation complexities and lengths, and sub-basin partitioning methods, while accounting for inter-run variability on a parallel computing system. In contrast to serial simulations, the parallel model speed-up depends on the variability of hydrologic processes. Load balancing significantly improves parallel speed-up with proportionally faster runs as simulation complexity (domain resolution and channel network extent) increases. The best strategy for large river basins is to combine a balanced partitioning with an extended channel network, with potential savings through a lower TIN resolution. Based on these advances, a wider range of applications for fully-distributed hydrologic models are now possible. This is illustrated through a set of ensemble forecasts that account for precipitation uncertainty derived from a statistical downscaling model.

The influence of the hydrologic cycle on the extent of sea ice with climatic implications

NASA Technical Reports Server (NTRS)

Dean, Ken; Gosink, Joan

1991-01-01

The role was analyzed of the hydrologic cycle on the distribution of sea ice, and its influence on forcings and fluxes between the marine environment and the atmosphere. River discharge plays a significant role in degrading the sea ice before any melting occurs elsewhere along the coast. The influence is considered of river discharge on the albedo, thermal balance, and distribution of sea ice. Quantitative atmospheric-hydrologic models are being developed to describe these processes in the coastal zone. Input for the models will come from satellite images, hydrologic data, and field observations. The resulting analysis provides a basis for the study of the significance of the hydrologic cycle throughout the Arctic Basin and its influence on the regional climate as a result of possible climatic scenarios. The area offshore from the Mackenzie River delta was selected as the study area.

The role of the antecedent soil moisture condition on the distributed hydrologic modelling of the Toce alpine basin floods.

NASA Astrophysics Data System (ADS)

Ravazzani, G.; Montaldo, N.; Mancini, M.; Rosso, R.

2003-04-01

Event-based hydrologic models need the antecedent soil moisture condition, as critical boundary initial condition for flood simulation. Land-surface models (LSMs) have been developed to simulate mass and energy transfers, and to update the soil moisture condition through time from the solution of water and energy balance equations. They are recently used in distributed hydrologic modeling for flood prediction systems. Recent developments have made LSMs more complex by inclusion of more processes and controlling variables, increasing parameter number and uncertainty of their estimates. This also led to increasing of computational burden and parameterization of the distributed hydrologic models. In this study we investigate: 1) the role of soil moisture initial conditions in the modeling of Alpine basin floods; 2) the adequate complexity level of LSMs for the distributed hydrologic modeling of Alpine basin floods. The Toce basin is the case study; it is located in the North Piedmont (Italian Alps), and it has a total drainage area of 1534 km2 at Candoglia section. Three distributed hydrologic models of different level of complexity are developed and compared: two (TDLSM and SDLSM) are continuous models, one (FEST02) is an event model based on the simplified SCS-CN method for rainfall abstractions. In the TDLSM model a two-layer LSM computes both saturation and infiltration excess runoff, and simulates the evolution of the water table spatial distribution using the topographic index; in the SDLSM model a simplified one-layer distributed LSM only computes hortonian runoff, and doesn’t simulate the water table dynamic. All the three hydrologic models simulate the surface runoff propagation through the Muskingum-Cunge method. TDLSM and SDLSM models have been applied for the two-year (1996 and 1997) simulation period, during which two major floods occurred in the November 1996 and in the June 1997. The models have been calibrated and tested comparing simulated and observed hydrographs at Candoglia. Sensitivity analysis of the models to significant LSM parameters were also performed. The performances of the three models in the simulation of the two major floods are compared. Interestingly, the results indicate that the SDLSM model is able to sufficiently well predict the major floods of this Alpine basin; indeed, this model is a good compromise between the over-parameterized and too complex TDLSM model and the over-simplified FEST02 model.

Debates—Hypothesis testing in hydrology: Theory and practice

NASA Astrophysics Data System (ADS)

Pfister, Laurent; Kirchner, James W.

2017-03-01

The basic structure of the scientific method—at least in its idealized form—is widely championed as a recipe for scientific progress, but the day-to-day practice may be different. Here, we explore the spectrum of current practice in hypothesis formulation and testing in hydrology, based on a random sample of recent research papers. This analysis suggests that in hydrology, as in other fields, hypothesis formulation and testing rarely correspond to the idealized model of the scientific method. Practices such as "p-hacking" or "HARKing" (Hypothesizing After the Results are Known) are major obstacles to more rigorous hypothesis testing in hydrology, along with the well-known problem of confirmation bias—the tendency to value and trust confirmations more than refutations—among both researchers and reviewers. Nonetheless, as several examples illustrate, hypothesis tests have played an essential role in spurring major advances in hydrological theory. Hypothesis testing is not the only recipe for scientific progress, however. Exploratory research, driven by innovations in measurement and observation, has also underlain many key advances. Further improvements in observation and measurement will be vital to both exploratory research and hypothesis testing, and thus to advancing the science of hydrology.

CrowdHydrology: crowdsourcing hydrologic data and engaging citizen scientists.

PubMed

Lowry, Christopher S; Fienen, Michael N

2013-01-01

Spatially and temporally distributed measurements of processes, such as baseflow at the watershed scale, come at substantial equipment and personnel cost. Research presented here focuses on building a crowdsourced database of inexpensive distributed stream stage measurements. Signs on staff gauges encourage citizen scientists to voluntarily send hydrologic measurements (e.g., stream stage) via text message to a server that stores and displays the data on the web. Based on the crowdsourced stream stage, we evaluate the accuracy of citizen scientist measurements and measurement approach. The results show that crowdsourced data collection is a supplemental method for collecting hydrologic data and a promising method of public engagement. © 2012, The Author(s). Ground Water © 2012, National Ground Water Association.

An analysis of historic and projected climate scenarios in the Western United States using hydrologic landscape classification.

EPA Science Inventory

: Identifying areas of similar hydrology within the United States and its regions (hydrologic landscapes - HLs) is an active area of research. HLs are being used to construct spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, a...

An analysis of historic and projected climate scenarios in the Western united States using hydrologic landscape classification

EPA Science Inventory

Identifying areas of similar hydrology within the United States and its regions (Hydrologic landscapes - HLs) is an active area of research. HLs have been used to make spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, and the ...

Using Hydrologic Landscape Classification to Evaluate the Hydrologic Effects of Climate in the Southwestern United States

EPA Science Inventory

Hydrologic landscapes (HLs) have been an active area of research at regional and national scales in the United States. The concept has been used to make spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, and the Pacific Northwe...

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

USDA-ARS?s Scientific Manuscript database

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 ...

Propagation of model and forcing uncertainty into hydrological drought characteristics in a multi-model century-long experiment in continental river basins

NASA Astrophysics Data System (ADS)

Samaniego, L. E.; Kumar, R.; Schaefer, D.; Huang, S.; Yang, T.; Mishra, V.; Eisner, S.; Vetter, T.; Pechlivanidis, I.; Liersch, S.; Flörke, M.; Krysanova, V.

2015-12-01

Droughts are creeping hydro-meteorological events that bring societiesand natural systems to their limits and inducing considerablesocio-economic losses. Currently it is hypothesized that climate changewill exacerbate current trends leading a more severe and extendeddroughts, as well as, larger than normal recovery periods. Currentassessments, however, lack of a consistent framework to deal withcompatible initial conditions for the impact models and a set ofstandardized historical and future forcings. The ISI-MIP project provides an unique opportunity to understand thepropagation of model and forcing uncertainty into century-long timeseries of drought characteristics using an ensemble of model predictionsacross a broad range of climate scenarios and regions. In the presentstudy, we analyze this issue using the hydrologic simulations carriedout with HYPE, mHM, SWIM, VIC, and WaterGAP3 in seven large continentalriver basins: Amazon, Blue Nile, Ganges, Niger, Mississippi, Rhine,Yellow. All models are calibrated against observed streamflow duringthe period 1971-2001 using the same forcings based on the WATCH datasets. These constrained models were then forced with bias correctedoutputs of five CMIP-5 GCMs under four RCP scenarios (i.e. 2.6, 4.5,6.0, and 8.5 W/m2) for the period 1971-2099. A non-parametric kernel density approach is used to estimate thetemporal evolution of a monthly runoff index based on simulatedstreamflow. Hydrologic simulations corresponding to each GCM during thehistoric period of 1981-2010 serve as reference for the estimation ofthe basin specific monthly probability distribution functions. GCMspecific reference pdfs are then used to recast the future hydrologicmodel outputs from different RCP scenarios. Based on these results,drought severity and duration are investigated during periods: 1)2006-2035, 2) 2036-2065 and 3) 2070-2099. Two main hypothesis areinvestigated: 1) model predictive uncertainty of drought indices amongdifferent hydrologic models is negligible compared to the uncertaintyoriginated from different GCMs and 2) the projected drift of droughtcharacteristics is hydrologic model independent and it is only driven bythe GCM variability. The temporal evolution between drought severity andduration is also analyzed.

Picturing and modelling catchments by representative hillslopes

NASA Astrophysics Data System (ADS)

Loritz, Ralf; Hassler, Sibylle; Jackisch, Conrad; Zehe, Erwin

2016-04-01

Hydrological modelling studies often start with a qualitative sketch of the hydrological processes of a catchment. These so-called perceptual models are often pictured as hillslopes and are generalizations displaying only the dominant and relevant processes of a catchment or hillslope. The problem with these models is that they are prone to become too much predetermined by the designer's background and experience. Moreover it is difficult to know if that picture is correct and contains enough complexity to represent the system under study. Nevertheless, because of their qualitative form, perceptual models are easy to understand and can be an excellent tool for multidisciplinary exchange between researchers with different backgrounds, helping to identify the dominant structures and processes in a catchment. In our study we explore whether a perceptual model built upon an intensive field campaign may serve as a blueprint for setting up representative hillslopes in a hydrological model to reproduce the functioning of two distinctly different catchments. We use a physically-based 2D hillslope model which has proven capable to be driven by measured soil-hydrological parameters. A key asset of our approach is that the model structure itself remains a picture of the perceptual model, which is benchmarked against a) geo-physical images of the subsurface and b) observed dynamics of discharge, distributed state variables and fluxes (soil moisture, matric potential and sap flow). Within this approach we are able to set up two behavioral model structures which allow the simulation of the most important hydrological fluxes and state variables in good accordance with available observations within the 19.4 km2 large Colpach catchment and the 4.5 km2 large Wollefsbach catchment in Luxembourg without the necessity of calibration. This corroborates, contrary to the widespread opinion, that a) lower mesoscale catchments may be modelled by representative hillslopes and b) physically-based models can be parametrized based on comprehensive field data and a good perceptual model. Our results particularly indicate that the main challenge in understanding and modelling the seasonal water balance of a catchment is a proper representation of the phenological cycle of vegetation, not exclusively the structure of the subsurface and spatial variability of soil hydraulic parameters.

Socio-hydrologic modeling to understand and mediate the competition for water between agriculture development and environmental health: Murrumbidgee River basin, Australia

NASA Astrophysics Data System (ADS)

van Emmerik, T. H. M.; Li, Z.; Sivapalan, M.; Pande, S.; Kandasamy, J.; Savenije, H. H. G.; Chanan, A.; Vigneswaran, S.

2014-10-01

Competition for water between humans and ecosystems is set to become a flash point in the coming decades in many parts of the world. An entirely new and comprehensive quantitative framework is needed to establish a holistic understanding of that competition, thereby enabling the development of effective mediation strategies. This paper presents a modeling study centered on the Murrumbidgee River basin (MRB). The MRB has witnessed a unique system dynamics over the last 100 years as a result of interactions between patterns of water management and climate driven hydrological variability. Data analysis has revealed a pendulum swing between agricultural development and restoration of environmental health and ecosystem services over different stages of basin-scale water resource development. A parsimonious, stylized, quasi-distributed coupled socio-hydrologic system model that simulates the two-way coupling between human and hydrological systems of the MRB is used to mimic and explain dominant features of the pendulum swing. The model consists of coupled nonlinear ordinary differential equations that describe the interaction between five state variables that govern the co-evolution: reservoir storage, irrigated area, human population, ecosystem health, and environmental awareness. The model simulations track the propagation of the external climatic and socio-economic drivers through this coupled, complex system to the emergence of the pendulum swing. The model results point to a competition between human "productive" and environmental "restorative" forces that underpin the pendulum swing. Both the forces are endogenous, i.e., generated by the system dynamics in response to external drivers and mediated by humans through technology change and environmental awareness, respectively. Sensitivity analysis carried out with the model further reveals that socio-hydrologic modeling can be used as a tool to explain or gain insight into observed co-evolutionary dynamics of diverse human-water coupled systems. This paper therefore contributes to the ultimate development of a generic modeling framework that can be applied to human-water coupled systems in different climatic and socio-economic settings.

An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios

NASA Astrophysics Data System (ADS)

Addor, N.; Jaun, S.; Zappa, M.

2011-01-01

The Sihl River flows through Zurich, Switzerland's most populated city, for which it represents the largest flood threat. To anticipate extreme discharge events and provide decision support in case of flood risk, a hydrometeorological ensemble prediction system (HEPS) was launched operationally in 2008. This models chain relies on limited-area atmospheric forecasts provided by the deterministic model COSMO-7 and the probabilistic model COSMO-LEPS. These atmospheric forecasts are used to force a semi-distributed hydrological model (PREVAH), coupled to a hydraulic model (FLORIS). The resulting hydrological forecasts are eventually communicated to the stakeholders involved in the Sihl discharge management. This fully operational setting provides a real framework to compare the potential of deterministic and probabilistic discharge forecasts for flood mitigation. To study the suitability of HEPS for small-scale basins and to quantify the added-value conveyed by the probability information, a reforecast was made for the period June 2007 to December 2009 for the Sihl catchment (336 km2). Several metrics support the conclusion that the performance gain can be of up to 2 days lead time for the catchment considered. Brier skill scores show that COSMO-LEPS-based hydrological forecasts overall outperform their COSMO-7 based counterparts for all the lead times and event intensities considered. The small size of the Sihl catchment does not prevent skillful discharge forecasts, but makes them particularly dependent on correct precipitation forecasts, as shown by comparisons with a reference run driven by observed meteorological parameters. Our evaluation stresses that the capacity of the model to provide confident and reliable mid-term probability forecasts for high discharges is limited. The two most intense events of the study period are investigated utilising a novel graphical representation of probability forecasts and used to generate high discharge scenarios. They highlight challenges for making decisions on the basis of hydrological predictions, and indicate the need for a tool to be used in addition to forecasts to compare the different mitigation actions possible in the Sihl catchment.

A component-based, integrated spatially distributed hydrologic/water quality model: AgroEcoSystem-Watershed (AgES-W) overview and application

USDA-ARS?s Scientific Manuscript database

AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic/water quality simulation components. The AgES-W model was previously evaluated for streamflow and recently has been enhanced with the addition of nitrogen (N) and sediment modeling compo...

The Spatially-Distributed Agroecosystem-Watershed (Ages-W) Hydrologic/Water Quality (H/WQ) model for assessment of conservation effects

USDA-ARS?s Scientific Manuscript database

AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic/water quality (H/WQ) simulation components under the Object Modeling System (OMS3) environmental modeling framework. AgES-W has recently been enhanced with the addition of nitrogen (N) a...

Impact of microwave derived soil moisture on hydrologic simulations using a spatially distributed water balance model

NASA Technical Reports Server (NTRS)

Lin, D. S.; Wood, E. F.; Famiglietti, J. S.; Mancini, M.

1994-01-01

Spatial distributions of soil moisture over an agricultural watershed with a drainage area of 60 ha were derived from two NASA microwave remote sensors, and then used as a feedback to determine the initial condition for a distributed water balance model. Simulated hydrologic fluxes over a period of twelve days were compared with field observations and with model predictions based on a streamflow derived initial condition. The results indicated that even the low resolution remotely sensed data can improve the hydrologic model's performance in simulating the dynamics of unsaturated zone soil moisture. For the particular watershed under study, the simulated water budget was not sensitive to the resolutions of the microwave sensors.

A post-Cassini view of Titan's methane-based hydrologic cycle

NASA Astrophysics Data System (ADS)

Hayes, Alexander G.; Lorenz, Ralph D.; Lunine, Jonathan I.

2018-05-01

The methane-based hydrologic cycle on Saturn's largest moon, Titan, is an extreme analogue to Earth's water cycle. Titan is the only planetary body in the Solar System, other than Earth, that is known to have an active hydrologic cycle. With a surface pressure of 1.5 bar and temperatures of 90 to 95 K, methane and ethane condense out of a nitrogen-based atmosphere and flow as liquids on the moon's surface. Exchange processes between atmospheric, surface and subsurface reservoirs produce methane and ethane cloud systems, as well as erosional and depositional landscapes that have strikingly similar forms to their terrestrial counterparts. Over its 13-year exploration of the Saturn system, the Cassini-Huygens mission revealed that Titan's hydrocarbon-based hydrology is driven by nested methane cycles that operate over a range of timescales, including geologic, orbital (for example, Croll-Milankovitch cycles), seasonal and that of a single convective storm. In this Review Article, we describe the dominant exchange processes that operate over these timescales and present a post-Cassini view of Titan's methane-based hydrologic system.

Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS)

USGS Publications Warehouse

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

2018-01-08

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

Downscaling of RCM outputs for representative catchments in the Mediterranean region, for the 1951-2100 time-frame

NASA Astrophysics Data System (ADS)

Deidda, Roberto; Marrocu, Marino; Pusceddu, Gabriella; Langousis, Andreas; Mascaro, Giuseppe; Caroletti, Giulio

2013-04-01

Within the activities of the EU FP7 CLIMB project (www.climb-fp7.eu), we developed downscaling procedures to reliably assess climate forcing at hydrologically relevant scales, and applied them to six representative hydrological basins located in the Mediterranean region: Riu Mannu and Noce in Italy, Chiba in Tunisia, Kocaeli in Turkey, Thau in France, and Gaza in Palestine. As a first step towards this aim, we used daily precipitation and temperature data from the gridded E-OBS project (www.ecad.eu/dailydata), as reference fields, to rank 14 Regional Climate Model (RCM) outputs from the ENSEMBLES project (http://ensembles-eu.metoffice.com). The four best performing model outputs were selected, with the additional constraint of maintaining 2 outputs obtained from running different RCMs driven by the same GCM, and 2 runs from the same RCM driven by different GCMs. For these four RCM-GCM model combinations, a set of downscaling techniques were developed and applied, for the period 1951-2100, to variables used in hydrological modeling (i.e. precipitation; mean, maximum and minimum daily temperatures; direct solar radiation, relative humidity, magnitude and direction of surface winds). The quality of the final products is discussed, together with the results obtained after applying a bias reduction procedure to daily temperature and precipitation fields.

Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model

NASA Astrophysics Data System (ADS)

Laiolo, P.; Gabellani, S.; Campo, L.; Silvestro, F.; Delogu, F.; Rudari, R.; Pulvirenti, L.; Boni, G.; Fascetti, F.; Pierdicca, N.; Crapolicchio, R.; Hasenauer, S.; Puca, S.

2016-06-01

The reliable estimation of hydrological variables in space and time is of fundamental importance in operational hydrology to improve the flood predictions and hydrological cycle description. Nowadays remotely sensed data can offer a chance to improve hydrological models especially in environments with scarce ground based data. The aim of this work is to update the state variables of a physically based, distributed and continuous hydrological model using four different satellite-derived data (three soil moisture products and a land surface temperature measurement) and one soil moisture analysis to evaluate, even with a non optimal technique, the impact on the hydrological cycle. The experiments were carried out for a small catchment, in the northern part of Italy, for the period July 2012-June 2013. The products were pre-processed according to their own characteristics and then they were assimilated into the model using a simple nudging technique. The benefits on the model predictions of discharge were tested against observations. The analysis showed a general improvement of the model discharge predictions, even with a simple assimilation technique, for all the assimilation experiments; the Nash-Sutcliffe model efficiency coefficient was increased from 0.6 (relative to the model without assimilation) to 0.7, moreover, errors on discharge were reduced up to the 10%. An added value to the model was found in the rainfall season (autumn): all the assimilation experiments reduced the errors up to the 20%. This demonstrated that discharge prediction of a distributed hydrological model, which works at fine scale resolution in a small basin, can be improved with the assimilation of coarse-scale satellite-derived data.

Subglacial efficiency and storage modified by the temporal pattern of high-elevation meltwater input

NASA Astrophysics Data System (ADS)

Andrews, L. C.; Dow, C. F.; Poinar, K.; Nowicki, S.

2017-12-01

Ice flow in marginal region of the Greenland Ice Sheet dynamically responds to summer melting as surface meltwater is routed through the supraglacial hydrologic system to the bed of the ice sheet via crevasses and moulins. Given the expected increases in surface melt production and extent, and the potential for high elevation surface-to-bed connections, it is imperative to understand how meltwater delivered to the bed from different high-elevation supraglacial storage features affects the evolution of the subglacial hydrologic system and associated ice dynamics. Here, we use the two-dimensional subglacial hydrologic model, GLaDS, which includes distributed and channelized water flow, to test how the subglacial system of an idealized outlet glacier responds to cases of high-elevation firn-aquifer-type and supraglacial-lake-type englacial drainage over the course of 5 years. Model outputs driven by these high elevation drainage types are compared to steady-state model results, where the subglacial system only receives the 1980-2016 mean MERRA-2 runoff via low-elevation moulins. Across all experiments, the subglacial hydrologic system displays inter-annual memory, resulting in multiyear declines in subglacial pressure during the onset of seasonal melting and growth of subglacial channels. The gradual addition of water in firn-aquifer-type drainage scenarios resulted in small increases in subglacial water storage but limited changes in subglacial efficiency and channelization. Rapid, supraglacial-lake-type drainage resulted in short-term local increases in subglacial water pressure and storage, which gave way to spatially extensive decreases in subglacial pressure and downstream channelization. These preliminary results suggest that the character of high-elevation englacial drainage can have a strong, and possibly outsized, control on subglacial efficiency throughout the ablation zone. Therefore, understanding both how high elevation meltwater is stored supraglacially and the probability of crevassing at high elevations will play an important role in how the subglacial system, proglacial discharge and ice motion will respond to future increases in surface melt production and runoff.

Subglacial efficiency and storage modified by the temporal pattern of high-elevation meltwater input

NASA Astrophysics Data System (ADS)

Ackley, S. F.; Maksym, T.; Stammerjohn, S. E.; Gao, Y.; Weissling, B.

2016-12-01

Ice flow in marginal region of the Greenland Ice Sheet dynamically responds to summer melting as surface meltwater is routed through the supraglacial hydrologic system to the bed of the ice sheet via crevasses and moulins. Given the expected increases in surface melt production and extent, and the potential for high elevation surface-to-bed connections, it is imperative to understand how meltwater delivered to the bed from different high-elevation supraglacial storage features affects the evolution of the subglacial hydrologic system and associated ice dynamics. Here, we use the two-dimensional subglacial hydrologic model, GLaDS, which includes distributed and channelized water flow, to test how the subglacial system of an idealized outlet glacier responds to cases of high-elevation firn-aquifer-type and supraglacial-lake-type englacial drainage over the course of 5 years. Model outputs driven by these high elevation drainage types are compared to steady-state model results, where the subglacial system only receives the 1980-2016 mean MERRA-2 runoff via low-elevation moulins. Across all experiments, the subglacial hydrologic system displays inter-annual memory, resulting in multiyear declines in subglacial pressure during the onset of seasonal melting and growth of subglacial channels. The gradual addition of water in firn-aquifer-type drainage scenarios resulted in small increases in subglacial water storage but limited changes in subglacial efficiency and channelization. Rapid, supraglacial-lake-type drainage resulted in short-term local increases in subglacial water pressure and storage, which gave way to spatially extensive decreases in subglacial pressure and downstream channelization. These preliminary results suggest that the character of high-elevation englacial drainage can have a strong, and possibly outsized, control on subglacial efficiency throughout the ablation zone. Therefore, understanding both how high elevation meltwater is stored supraglacially and the probability of crevassing at high elevations will play an important role in how the subglacial system, proglacial discharge and ice motion will respond to future increases in surface melt production and runoff.

Ecohydrologic relationships of two juniper woodlands with different precipitation regimes

NASA Astrophysics Data System (ADS)

Ochoa, C. G.; Guldan, S. J.; Deboodt, T.; Fernald, A.; Ray, G.

2015-12-01

The significant expansion of juniper (Juniperus spp.) woodlands throughout the western U.S. during the last two centuries has disrupted important ecological functions and hydrologic processes. The relationships between water and vegetation distribution are highly impacted by the ongoing shift from shrub steppe and grassland to woodland-dominated landscapes. We investigated vegetation dynamics and hydrologic processes occurring in two distinct juniper landscapes with different precipitation regimes in the Intermountain West region: A winter snow-dominated (Oregon) and a summer rain-dominated with some winter precipitation (New Mexico) landscape. Results from the Oregon site showed marginal differences (1-2%) in soil moisture in treated vs untreated watersheds throughout the dry and wet seasons. In general, soil moisture was greater in the treated watershed in both seasons. Canopy cover affected soil moisture over time. Perennial grass cover was positively correlated with changes in soil moisture, whereas juniper cover was negatively correlated with changes in soil moisture. Shallow groundwater response observed in upland and valley monitoring wells indicate there are temporary hydrologic connections between upland and valley locations during the winter precipitation season. Results from the New Mexico site provided valuable information regarding timing and intensity of monsoon-driven precipitation and the rainfall threshold (5 mm/15 min) that triggers runoff. Long-term vegetation dynamics and hydrologic processes were evaluated based on pre- and post-juniper removal (70%) in three watersheds. In general, less runoff and greater forage response was observed in the treated watersheds. During rainfall events, soil moisture was less under juniper canopy compared with inter-canopy; this difference in soil moisture was intensified during high intensity, short duration rainstorms in the summer months. We found that winter snow precipitation helped recharge soil moisture prior to plant growth in the springtime, but it did not generate streamflow. Study results provide valuable information towards understanding ecohydrologic differences and similarities of woody vegetation expansion in semiarid areas on both sides of the continental divide in the Intermountain West.

Socio-hydrologic Modeling to Understand and Mediate the Competition for Water between Humans and Ecosystems: Murrumbidgee River Basin, Australia (Invited)

NASA Astrophysics Data System (ADS)

Sivapalan, M.

2013-12-01

Competition for water between humans and ecosystems is set to become a flash point in coming decades in all parts of the world. An entirely new and comprehensive quantitative framework is needed to establish a holistic understanding of that competition, thereby enabling development of effective mediation strategies. This paper presents a case study centered on the Murrumbidgee river basin in eastern Australia that illustrates the dynamics of the balance between water extraction and use for food production and efforts to mitigate and reverse consequent degradation of the riparian environment. Interactions between patterns of water management and climate driven hydrological variability within the prevailing socio-economic environment have contributed to the emergence of new whole system dynamics over the last 100 years. In particular, data analysis reveals a pendulum swing between an exclusive focus on agricultural development and food production in the initial stages of water resource development and its attendant socio-economic benefits, followed by the gradual realization of the adverse environmental impacts, efforts to mitigate these with the use of remedial measures, and ultimately concerted efforts and externally imposed solutions to restore environmental health and ecosystem services. A quasi-distributed coupled socio-hydrologic system model that explicitly includes the two-way coupling between human and hydrological systems, including evolution of human values/norms relating to water and the environment, is able to mimic broad features of this pendulum swing. The model consists of coupled nonlinear differential equations that include four state variables describing the co-evolution of storage capacity, irrigated area, human population, and ecosystem health. The model is used to generate insights into the dominant controls of the trajectory of co-evolution of the coupled human-water system, to serve as the theoretical framework for more detailed analysis of the system, and to generate organizing principles that may be transferable to other systems in different climatic and socio-economic settings.

[Advance in researches on the effect of forest on hydrological process].

PubMed

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

2003-01-01

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

Watershed Modeling Applications with the Open-Access Modular Distributed Watershed Educational Toolbox (MOD-WET) and Introductory Hydrology Textbook

NASA Astrophysics Data System (ADS)

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

2014-12-01

Traditionally, introductory hydrology courses focus on hydrologic processes as independent or semi-independent concepts that are ultimately integrated into a watershed model near the end of the term. When an "off-the-shelf" watershed model is introduced in the curriculum, this approach can result in a potential disconnect between process-based hydrology and the inherent interconnectivity of processes within the water cycle. In order to curb this and reduce the learning curve associated with applying hydrologic concepts to complex real-world problems, we developed the open-access Modular Distributed Watershed Educational Toolbox (MOD-WET). The user-friendly, MATLAB-based toolbox contains the same physical equations for hydrological processes (i.e. precipitation, snow, radiation, evaporation, unsaturated flow, infiltration, groundwater, and runoff) that are presented in the companion e-textbook (http://aqua.seas.ucla.edu/margulis_intro_to_hydro_textbook.html) and taught in the classroom. The modular toolbox functions can be used by students to study individual hydrologic processes. These functions are integrated together to form a simple spatially-distributed watershed model, which reinforces a holistic understanding of how hydrologic processes are interconnected and modeled. Therefore when watershed modeling is introduced, students are already familiar with the fundamental building blocks that have been unified in the MOD-WET model. Extensive effort has been placed on the development of a highly modular and well-documented code that can be run on a personal computer within the commonly-used MATLAB environment. MOD-WET was designed to: 1) increase the qualitative and quantitative understanding of hydrological processes at the basin-scale and demonstrate how they vary with watershed properties, 2) emphasize applications of hydrologic concepts rather than computer programming, 3) elucidate the underlying physical processes that can often be obscured with a complicated "off-the-shelf" watershed model in an introductory hydrology course, and 4) reduce the learning curve associated with analyzing meaningful real-world problems. The open-access MOD-WET and e-textbook have already been successfully incorporated within our undergraduate curriculum.

Hydrological resiliency in the Western Boreal Plains: classification of hydrological responses using wavelet analysis to assess landscape resilience

NASA Astrophysics Data System (ADS)

Probert, Samantha; Kettridge, Nicholas; Devito, Kevin; Hannah, David; Parkin, Geoff

2017-04-01

The Boreal represents a system of substantial resilience to climate change, with minimal ecological change over the past 6000 years. However, unprecedented climatic warming, coupled with catchment disturbances could exceed thresholds of hydrological function in the Western Boreal Plains. Knowledge of ecohydrological and climatic feedbacks that shape the resilience of boreal forests has advanced significantly in recent years, but this knowledge is yet to be applied and understood at landscape scales. Hydrological modelling at the landscape scale is challenging in the WBP due to diverse, non-topographically driven hydrology across the mosaic of terrestrial and aquatic ecosystems. This study functionally divides the geologic and ecological components of the landscape into Hydrologic Response Areas (HRAs) and wetland, forestland, interface and pond Hydrologic Units (HUs) to accurately characterise water storage and infer transmission at multiple spatial and temporal scales. Wavelet analysis is applied to pond and groundwater levels to describe the patterns of water storage in response to climate signals; to isolate dominant controls on hydrological responses and to assess the relative importance of physical controls between wet and dry climates. This identifies which components of the landscape exhibit greater magnitude and frequency of variability to wetting and drying trends, further to testing the hierarchical framework for hydrological storage controls of: climate, bedrock geology, surficial geology, soil, vegetation, and topography. Classifying HRA and HU hydrological function is essential to understand and predict water storage and redistribution through drought cycles and wet periods. This work recognises which landscape components are most sensitive under climate change and disturbance and also creates scope for hydrological resiliency research in Boreal systems by recognising critical landscape components and their role in landscape collapse or catastrophic shift in ecosystem function under future climatic scenarios.

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).

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

USDA-ARS?s Scientific Manuscript database

The coupling of land surface models and hydrological models potentially improves the land surface representation, benefiting both the streamflow prediction capabilities as well as providing improved estimates of water and energy fluxes into the atmosphere. In this study, the simple biosphere model 2...

A physically based catchment partitioning method for hydrological analysis

NASA Astrophysics Data System (ADS)

Menduni, Giovanni; Riboni, Vittoria

2000-07-01

We propose a partitioning method for the topographic surface, which is particularly suitable for hydrological distributed modelling and shallow-landslide distributed modelling. The model provides variable mesh size and appears to be a natural evolution of contour-based digital terrain models. The proposed method allows the drainage network to be derived from the contour lines. The single channels are calculated via a search for the steepest downslope lines. Then, for each network node, the contributing area is determined by means of a search for both steepest upslope and downslope lines. This leads to the basin being partitioned into physically based finite elements delimited by irregular polygons. In particular, the distributed computation of local geomorphological parameters (i.e. aspect, average slope and elevation, main stream length, concentration time, etc.) can be performed easily for each single element. The contributing area system, together with the information on the distribution of geomorphological parameters provide a useful tool for distributed hydrological modelling and simulation of environmental processes such as erosion, sediment transport and shallow landslides.

Watershed Scale Stable Isotope Distribution and Implications on Soil Organic Carbon Loss Monitoring under Hydrologic Uncertainty

NASA Astrophysics Data System (ADS)

Ahmed, I.; Karim, A.; Boutton, T. W.; Strom, K.; Fox, J.

2013-12-01

The thematic focus of this 3-year period multidisciplinary USDA-CBG collaborative applied research is integrated monitoring of soil organic carbon (SOC) loss from multi-use lands using state-of-the-art stable isotope science under uncertain hydrologic influences. In this study, SOC loss and water runoff are being monitored on a 150 square kilometer watershed in Houston, Texas, using natural rainfall events, and total organic carbon/nitrogen concentration (TOC/TN) and stable isotope ratio (δ13C, δ15N) measurements with different land-use types. The work presents the interdisciplinary research results to uncover statistically valid and scientifically sound ways to monitor SOC loss by (i) application of Bayesian Markov Chain Monte Carlo statistical models to assess the relationship between rainfall-runoff and SOC release during soil erosion in space and time, (ii) capturing the episodic nature of rainfall events and its role in the spatial distribution of SOC loss from water erosion, (iii) stable isotope composition guided fingerprinting (source and quantity) of SOC by considering various types of erosion processes common in a heterogeneous watershed, to be able to tell what percentage of SOC is lost from various land-use types (Fox and Papanicolaou, 2008), (iv) creating an integrated watershed scale statistical soil loss monitoring model driven by spatial and temporal correlation of flow and stable isotope composition (Ahmed et. al., 2013a,b), and (v) creation of an integrated decision support system (DSS) for sustainable management of SOC under hydrologic uncertainty to assist the end users. References: Ahmed, I., Karim, A., Boutton, T.W., and Strom, K.B. (2013a). 'Monitoring Soil Organic Carbon Loss from Erosion Using Stable Isotopes.' Proc., Soil Carbon Sequestration, International Conference, May 26-29, Reykjavik, Iceland. Ahmed, I, Bouttom, T.W., Strom, K. B., Karim, A., and Irvin-Smith, N. (2013b). 'Soil carbon distribution and loss monitoring in the urbanized Buffalo Bayou watershed, Houston, Texas.' Proc., 4th Annual All Investigators Meeting of the North American Carbon Program, February 4-7, Albuquerque, NM. Fox, J.F. and Papanicolaou, A.N. (2008). An un-mixing model to study watershed erosion processes. Advances in Water Resources, 31, 96-108. ______________________________ * Corresponding author';s e-mail: ifahmed@pvamu.edu

[Oncomelania hupensis snail distribution in working areas of Yangtze River hydrologic agencies located in middle and lower reaches of Yangtze River in 2016].

PubMed

Min, Xu; Suo-Xin, Huang; Zheng-Yuan, Zhao; Ben-Jiao, Hu; Jun, Fu; Si-Min, Dai; Li-Hong, Wen

2016-10-13

To understand the Oncomelania hupensis snail distribution in the working areas of Yangtze River hydrologic agencies located in the middle and lower reaches of the Yangtze River in 2016, so as to provide the evidence for assessing the risk of schistosome infection of hydrological workers and establishing the control strategies. The suspicious environments with O. hupensis snails in the above working areas were selected as study areas, and the snail situation was surveyed by the system sampling method combined with the environmental sampling method. The survey data were collected and analyzed statistically. Totally 19 working areas from 17 hydrological agencies were selected as the investigation sites, among which, 10 working areas from 9 agencies were found with O. hupensis snail distribution. The constituent ratio of the areas with snails reached to 38.81% of the investigation areas, the occurrence rate of frames with snails was 3.08%, and the average density of living snails was 0.07 /0.1 m 2 . By comparison, the average density of living snails and occurrence rate of frames with snails in hydrological agencies under the jurisdiction of the Middle Reaches Administrative Bureau were the most serious among three administrative bureaus of the Yangtze River Water Resources Commission. There are various degrees of O. hupensis breeding in the working areas of hydrological agencies located in the middle and lower reaches of the Yangtze River, and the hydrological workers are facing with the risk of schistosome infection.

Assessing the value of variational assimilation of streamflow data into distributed hydrologic models for improved streamflow monitoring and prediction at ungauged and gauged locations in the catchment

NASA Astrophysics Data System (ADS)

Lee, Hak Su; Seo, Dong-Jun; Liu, Yuqiong; McKee, Paul; Corby, Robert

2010-05-01

State updating of distributed hydrologic models via assimilation of streamflow data is subject to "overfitting" because large dimensionality of the state space of the model may render the assimilation problem seriously underdetermined. To examine the issue in the context of operational hydrology, we carried out a set of real-world experiments in which we assimilate streamflow data at interior and/or outlet locations into gridded SAC and kinematic-wave routing models of the U.S. National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM). We used for the experiments nine basins in the southern plains of the U.S. The experiments consist of selectively assimilating streamflow at different gauge locations, outlet and/or interior, and carrying out both dependent and independent validation. To assess the sensitivity of the quality of assimilation-aided streamflow simulation to the reduced dimensionality of the state space, we carried out data assimilation at spatially semi-distributed or lumped scale and by adjusting biases in precipitation and potential evaporation at a 6-hourly or larger scale. In this talk, we present the results and findings.

Fish utilisation of wetland nurseries with complex hydrological connectivity.

PubMed

Davis, Ben; Johnston, Ross; Baker, Ronald; Sheaves, Marcus

2012-01-01

The physical and faunal characteristics of coastal wetlands are driven by dynamics of hydrological connectivity to adjacent habitats. Wetlands on estuary floodplains are particularly dynamic, driven by a complex interplay of tidal marine connections and seasonal freshwater flooding, often with unknown consequences for fish using these habitats. To understand the patterns and subsequent processes driving fish assemblage structure in such wetlands, we examined the nature and diversity of temporal utilisation patterns at a species or genus level over three annual cycles in a tropical Australian estuarine wetland system. Four general patterns of utilisation were apparent based on CPUE and size-structure dynamics: (i) classic nursery utlisation (use by recently settled recruits for their first year) (ii) interrupted peristence (iii) delayed recruitment (iv) facultative wetland residence. Despite the small self-recruiting 'facultative wetland resident' group, wetland occupancy seems largely driven by connectivity to the subtidal estuary channel. Variable connection regimes (i.e. frequency and timing of connections) within and between different wetland units (e.g. individual pools, lagoons, swamps) will therefore interact with the diversity of species recruitment schedules to generate variable wetland assemblages in time and space. In addition, the assemblage structure is heavily modified by freshwater flow, through simultaneously curtailing persistence of the 'interrupted persistence' group, establishing connectivity for freshwater spawned members of both the 'facultative wetland resident' and 'delayed recruitment group', and apparently mediating use of intermediate nursery habitats for marine-spawned members of the 'delayed recruitment' group. The diversity of utilisation pattern and the complexity of associated drivers means assemblage compositions, and therefore ecosystem functioning, is likely to vary among years depending on variations in hydrological connectivity. Consequently, there is a need to incorporate this diversity into understandings of habitat function, conservation and management.

Fish Utilisation of Wetland Nurseries with Complex Hydrological Connectivity

PubMed Central

Davis, Ben; Johnston, Ross; Baker, Ronald; Sheaves, Marcus

2012-01-01

The physical and faunal characteristics of coastal wetlands are driven by dynamics of hydrological connectivity to adjacent habitats. Wetlands on estuary floodplains are particularly dynamic, driven by a complex interplay of tidal marine connections and seasonal freshwater flooding, often with unknown consequences for fish using these habitats. To understand the patterns and subsequent processes driving fish assemblage structure in such wetlands, we examined the nature and diversity of temporal utilisation patterns at a species or genus level over three annual cycles in a tropical Australian estuarine wetland system. Four general patterns of utilisation were apparent based on CPUE and size-structure dynamics: (i) classic nursery utlisation (use by recently settled recruits for their first year) (ii) interrupted peristence (iii) delayed recruitment (iv) facultative wetland residence. Despite the small self-recruiting ‘facultative wetland resident’ group, wetland occupancy seems largely driven by connectivity to the subtidal estuary channel. Variable connection regimes (i.e. frequency and timing of connections) within and between different wetland units (e.g. individual pools, lagoons, swamps) will therefore interact with the diversity of species recruitment schedules to generate variable wetland assemblages in time and space. In addition, the assemblage structure is heavily modified by freshwater flow, through simultaneously curtailing persistence of the ’interrupted persistence’ group, establishing connectivity for freshwater spawned members of both the ‘facultative wetland resident’ and ‘delayed recruitment group’, and apparently mediating use of intermediate nursery habitats for marine-spawned members of the ‘delayed recruitment’ group. The diversity of utilisation pattern and the complexity of associated drivers means assemblage compositions, and therefore ecosystem functioning, is likely to vary among years depending on variations in hydrological connectivity. Consequently, there is a need to incorporate this diversity into understandings of habitat function, conservation and management. PMID:23152857

Hydrological changes in the Amur river basin: two approaches for assignment of climate projections into hydrological model

NASA Astrophysics Data System (ADS)

Gelfan, Alexander; Kalugin, Andrei; Motovilov, Yury

2017-04-01

A regional hydrological model was setup to assess possible impact of climate change on the hydrological regime of the Amur drainage basin (the catchment area is 1 855 000 km2). The model is based on the ECOMAG hydrological modeling platform and describes spatially distributed processes of water cycle in this great basin with account for flow regulation by the Russian and Chinese reservoirs. Earlier, the regional hydrological model was intensively evaluated against 20-year streamflow data over the whole Amur basin and, being driven by 252-station meteorological observations as input data, demonstrated good performance. In this study, we firstly assessed the reliability of the model to reproduce the historical streamflow series when Global Climate Model (GCM) simulation data are used as input into the hydrological model. Data of nine GCMs involved in CMIP5 project was utilized and we found that ensemble mean of annual flow is close to the observed flow (error is about 14%) while data of separate GCMs may result in much larger errors. Reproduction of seasonal flow for the historical period turned out weaker; first of all because of large errors in simulated seasonal precipitation, so hydrological consequences of climate change were estimated just in terms of annual flow. We analyzed the hydrological projections from the climate change scenarios. The impacts were assessed in four 20-year periods: early- (2020-2039), mid- (2040-2059) and two end-century (2060-2079; 2080-2099) periods using an ensemble of nine GCMs and four Representative Concentration Pathways (RCP) scenarios. Mean annual runoff anomalies calculated as percentages of the future runoff (simulated under 36 GCM-RCP combinations of climate scenarios) to the historical runoff (simulated under the corresponding GCM outputs for the reference 1986-2005 period) were estimated. Hydrological model gave small negative runoff anomalies for almost all GCM-RCP combinations of climate scenarios and for all 20-year periods. The largest ensemble mean anomaly was about minus 8% by the end of XXI century under the most severe RCP8.5 scenario. We compared the mean annual runoff anomalies projected under the GCM-based data for the XXI century with the corresponding anomalies projected under a modified observed climatology using the delta-change (DC) method. Use of the modified observed records as driving forces for hydrological model-based projections can be considered as an alternative to the GCM-based scenarios if the latter are uncertain. The main advantage of the DC approach is its simplicity: in its simplest version only differences between present and future climates (i.e. between the long-term means of the climatic variables) are considered as DC-factors. In this study, the DC-factors for the reference meteorological series (1986-2005) of climate parameters were calculated from the GCM-based scenarios. The modified historical data were used as input into the hydrological models. For each of four 20-year period, runoff anomalies simulated under the delta-changed historical time series were compared with runoff anomalies simulated under the corresponding GCM-data with the same mean. We found that the compared projections are closely correlated. Thus, for the Amur basin, the modified observed climatology can be used as driving force for hydrological model-based projections and considered as an alternative to the GCM-based scenarios if only annual flow projections are of the interest.

Can Recent Global Changes Explain the Dramatic Range Contraction of an Endangered Semi-Aquatic Mammal Species in the French Pyrenees?

PubMed

Charbonnel, Anaïs; Laffaille, Pascal; Biffi, Marjorie; Blanc, Frédéric; Maire, Anthony; Némoz, Mélanie; Sanchez-Perez, José Miguel; Sauvage, Sabine; Buisson, Laëtitia

2016-01-01

Species distribution models (SDMs) are the main tool to predict global change impacts on species ranges. Climate change alone is frequently considered, but in freshwater ecosystems, hydrology is a key driver of the ecology of aquatic species. At large scale, hydrology is however rarely accounted for, owing to the lack of detailed stream flow data. In this study, we developed an integrated modelling approach to simulate stream flow using the hydrological Soil and Water Assessment Tool (SWAT). Simulated stream flow was subsequently included as an input variable in SDMs along with topographic, hydrographic, climatic and land-cover descriptors. SDMs were applied to two temporally-distinct surveys of the distribution of the endangered Pyrenean desman (Galemys pyrenaicus) in the French Pyrenees: a historical one conducted from 1985 to 1992 and a current one carried out between 2011 and 2013. The model calibrated on historical data was also forecasted onto the current period to assess its ability to describe the distributional change of the Pyrenean desman that has been modelled in the recent years. First, we found that hydrological and climatic variables were the ones influencing the most the distribution of this species for both periods, emphasizing the importance of taking into account hydrology when SDMs are applied to aquatic species. Secondly, our results highlighted a strong range contraction of the Pyrenean desman in the French Pyrenees over the last 25 years. Given that this range contraction was under-estimated when the historical model was forecasted onto current conditions, this finding suggests that other drivers may be interacting with climate, hydrology and land-use changes. Our results imply major concerns for the conservation of this endemic semi-aquatic mammal since changes in climate and hydrology are expected to become more intense in the future.

Can Recent Global Changes Explain the Dramatic Range Contraction of an Endangered Semi-Aquatic Mammal Species in the French Pyrenees?

PubMed Central

Charbonnel, Anaïs; Laffaille, Pascal; Biffi, Marjorie; Blanc, Frédéric; Maire, Anthony; Némoz, Mélanie; Sanchez-Perez, José Miguel; Sauvage, Sabine

2016-01-01

Species distribution models (SDMs) are the main tool to predict global change impacts on species ranges. Climate change alone is frequently considered, but in freshwater ecosystems, hydrology is a key driver of the ecology of aquatic species. At large scale, hydrology is however rarely accounted for, owing to the lack of detailed stream flow data. In this study, we developed an integrated modelling approach to simulate stream flow using the hydrological Soil and Water Assessment Tool (SWAT). Simulated stream flow was subsequently included as an input variable in SDMs along with topographic, hydrographic, climatic and land-cover descriptors. SDMs were applied to two temporally-distinct surveys of the distribution of the endangered Pyrenean desman (Galemys pyrenaicus) in the French Pyrenees: a historical one conducted from 1985 to 1992 and a current one carried out between 2011 and 2013. The model calibrated on historical data was also forecasted onto the current period to assess its ability to describe the distributional change of the Pyrenean desman that has been modelled in the recent years. First, we found that hydrological and climatic variables were the ones influencing the most the distribution of this species for both periods, emphasizing the importance of taking into account hydrology when SDMs are applied to aquatic species. Secondly, our results highlighted a strong range contraction of the Pyrenean desman in the French Pyrenees over the last 25 years. Given that this range contraction was under-estimated when the historical model was forecasted onto current conditions, this finding suggests that other drivers may be interacting with climate, hydrology and land-use changes. Our results imply major concerns for the conservation of this endemic semi-aquatic mammal since changes in climate and hydrology are expected to become more intense in the future. PMID:27467269

Morphological variation of freshwater crabs Zilchiopsis collastinensis and Trichodactylus borellianus (Decapoda, Trichodactylidae) among localities from the middle Paraná River basin during different hydrological periods

PubMed Central

Torres, María Victoria; Collins, Pablo Agustín; Giri, Federico

2014-01-01

Abstract Measures of hydrologic connectivity have been used extensively to describe spatial connections in riverine landscapes. Hydrologic fluctuations constitute an important macrofactor that regulates other environmental variables and can explain the distribution and abundance of organisms. We analysed morphological variations among individuals of two freshwater crab species, Zilchiopsis collastinensis and Trichodactylus borellianus, from localities of the middle Paraná River basin during two phases of the local hydrological regime. Specimens were sampled at sites (localities) of Paraná River, Saladillo Stream, Salado River and Coronda River when water levels were falling and rising. The conductivity, pH, temperature and geographical coordinates were recorded at each site. The dorsal cephalothorax of each crab was represented using 16 landmarks for Zilchiopsis collastinensis and 14 landmarks for Trichodactylus borellianus. The Canonical Variate Analyses showed differences in shape (for both species) among the crabs collected from the Paraná and Salado Rivers during the two hydrologic phases. We did not find a general distribution pattern for shape among the crab localities. During falling water, the shapes of Zilchiopsis collastinensis were not related to latitude-longitude gradient (i.e., showing greater overlap in shape), while during rising water the shapes were ordered along a distributional gradient according to geographical location. Contrary, shapes of Trichodactylus borellianus were related to latitude-longitude during falling water and were not related to distributional gradient during rising water. The cephalothorax shape showed, in general, no statistically significant covariations with environmental variables for either species. These results show that each freshwater crab species, from different localities of the middle Paraná River, remain connected; however, these connections change throughout the hydrologic regime of the floodplain system. This study was useful for delineating how the relation among shapes of crabs of localities varies during two phases of the hydrological regime and for estimating the connections and geographical patterns in the floodplain system. PMID:25561836

Development of a Sediment Transport Component for DHSVM

NASA Astrophysics Data System (ADS)

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

2003-12-01

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

Hydrological system dynamics of glaciated Karnali River Basin Nepal Himalaya using J2000 Hydrological model

NASA Astrophysics Data System (ADS)

Khatiwada, K. R.; Nepal, S.; Panthi, J., Sr.; Shrestha, M.

2015-12-01

Hydrological modelling plays an important role in understanding hydrological processes of a catchment. In the context of climate change, the understanding of hydrological characteristic of the catchment is very vital to understand how the climate change will affect the hydrological regime. This research facilitates in better understanding of the hydrological system dynamics of a himalayan mountainous catchment in western Nepal. The Karnali River, longest river flowing inside Nepal, is one of the three major basins of Nepal, having the area of 45269 sq. km. is unique. The basin has steep topography and high mountains to the northern side. The 40% of the basin is dominated by forest land while other land cover are: grass land, bare rocky land etc. About 2% of the areas in basin is covered by permanent glacier apart from that about 12% of basin has the snow and ice cover. There are 34 meteorological stations distributed across the basin. A process oriented distributed J2000 hydrologial model has been applied to understand the hydrological system dynamics. The model application provides distributed output of various hydrological components. The J2000 model applies Hydrological Response Unit (HRU) as a modelling entity. With 6861 HRU and 1010 reaches, the model was calibrated (1981-1999) and validated (2000-2004) at a daily scale using split-sample test. The model is able to capture the overall hydrological dynamics well. The rising limbs and recession limbs are simulated equally and with satisfactory ground water conditions. Based on the graphical and statistical evaluation of the model performance the model is able to simulate hydrological processes fairly well. Calibration shows that Nash Sutcliffe efficiency is 0.91, coefficient of determination is 0.92 Initial observation shows that during the pre-monsoon season(March to May) the glacial runoff is 25% of the total discharge while in the monsoon(June to September) season it is only 13%. The surface runoff contributed about 40%, 20% in subsurface while there is about 13% in the base flow. For better understanding and interpretation of the area there is still need of further coherent research and analysis for land use change and future climate change impact in the glaciered alpine catchment of Himalayan region.

Hydrology of the Bonneville Salt Flats, northwestern Utah, and simulation of ground-water flow and solute transport in the shallow-brine aquifer

USGS Publications Warehouse

Mason, James L.; Kipp, Kenneth L.

1998-01-01

This report describes the hydrologic system of the Bonneville Salt Flats with emphasis on the mechanisms of solute transport. Variable-density, three-dimensional computer simulations of the near-surface part of the ground-water system were done to quantify both the transport of salt dissolved in subsurface brine that leaves the salt-crust area and the salt dissolved and precipitated on the land surface. The study was designed to define the hydrology of the brine ground-water system and the natural and anthropogenic processes causing salt loss, and where feasible, to quantify these processes. Specific areas of study include the transport of salt in solution by ground-water flow and the transport of salt in solution by wind-driven ponds and the subsequent salt precipitation on the surface of the playa upon evaporation or seepage into the subsurface. In addition, hydraulic and chemical changes in the hydrologic system since previous studies were documented.

“Black Swans” of Hydrology: Can our Models Address the Science of Hydrologic Change?

NASA Astrophysics Data System (ADS)

Kumar, P.

2009-12-01

Coupled models of terrestrial hydrology and climate have grown in complexity leading to better understanding of the coupling between the hydrosphere, biosphere, and the climate system. During the past two decades, these models have evolved through generational changes as they have grown in sophistication in their ability to resolve spatial heterogeneity as well as vegetation dynamics and biogeochemistry. These developments have, in part, been driven by data collection efforts ranging from focused field campaigns to long-term observational networks, advances in remote sensing and other measurement technologies, along with sophisticated estimation and assimilation methods. However, the hydrologic cycle is changing leading to unexpected and unanticipated behavior through emergent dynamics and patterns that are not part of the historical milieu. Is there a new thinking that is needed to address this challenge? The goal of this talk is to draw from the modeling developments in the past two decades to foster a debate for moving forward.

Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods

NASA Astrophysics Data System (ADS)

Werner, A. T.; Cannon, A. J.

2015-06-01

Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e., correlation tests) and distributional properties (i.e., tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3 day peak flow and 7 day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational datasets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational dataset. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7 day low flow events, regardless of reanalysis or observational dataset. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event-scale spatial gradients, passed the greatest number of tests for hydrologic extremes. Non-stationarity in the observational/reanalysis datasets complicated the evaluation of downscaling performance. Comparing temporal homogeneity and trends in climate indices and hydrological model outputs calculated from downscaled reanalyses and gridded observations was useful for diagnosing the reliability of the various historical datasets. We recommend that such analyses be conducted before such data are used to construct future hydro-climatic change scenarios.

Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods

NASA Astrophysics Data System (ADS)

Werner, Arelia T.; Cannon, Alex J.

2016-04-01

Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e. correlation tests) and distributional properties (i.e. tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), the climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3-day peak flow and 7-day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational data sets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational data set. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7-day low-flow events, regardless of reanalysis or observational data set. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event-scale spatial gradients, passed the greatest number of tests for hydrologic extremes. Non-stationarity in the observational/reanalysis data sets complicated the evaluation of downscaling performance. Comparing temporal homogeneity and trends in climate indices and hydrological model outputs calculated from downscaled reanalyses and gridded observations was useful for diagnosing the reliability of the various historical data sets. We recommend that such analyses be conducted before such data are used to construct future hydro-climatic change scenarios.

A dynamic nitrogen budget model of a Pacific Northwest salt ...

EPA Pesticide Factsheets

The role of salt marshes as either nitrogen sinks or sources in relation to their adjacent estuaries has been a focus of ecosystem service research for many decades. The complex hydrology of these systems is driven by tides, upland surface runoff, precipitation, evapotranspiration, and groundwater inputs, all of which can vary significantly on timescales ranging from sub-daily to seasonal. Additionally, many of these hydrologic drivers may vary with a changing climate. Due to this temporal variation in hydrology, it is difficult to represent salt marsh nitrogen budgets as steady-state models. A dynamic nitrogen budget model that varies based on hydrologic conditions may more accurately describe the role of salt marshes in nitrogen cycling. In this study we aim to develop a hydrologic model that is coupled with a process-based nitrogen model to simulate nitrogen dynamics at multiple temporal scales. To construct and validate our model we will use hydrologic and nitrogen species data collected from 2010 to present, from a 1.8 hectare salt marsh in the Yaquina Estuary, OR, USA. Hydrologic data include water table levels at two transects, upland tributary flow, tidal channel stage and flow, and vertical hydraulic head gradients. Nitrogen pool data include concentrations of nitrate and ammonium in porewater, tidal channel water, and extracted from soil cores. Nitrogen flux data include denitrification rates, nitrogen concentrations in upland runoff, and tida

Coupling physically based and data-driven models for assessing freshwater inflow into the Small Aral Sea

NASA Astrophysics Data System (ADS)

Ayzel, Georgy; Izhitskiy, Alexander

2018-06-01

The Aral Sea desiccation and related changes in hydroclimatic conditions on a regional level is a hot topic for past decades. The key problem of scientific research projects devoted to an investigation of modern Aral Sea basin hydrological regime is its discontinuous nature - the only limited amount of papers takes into account the complex runoff formation system entirely. Addressing this challenge we have developed a continuous prediction system for assessing freshwater inflow into the Small Aral Sea based on coupling stack of hydrological and data-driven models. Results show a good prediction skill and approve the possibility to develop a valuable water assessment tool which utilizes the power of classical physically based and modern machine learning models both for territories with complex water management system and strong water-related data scarcity. The source code and data of the proposed system is available on a Github page (https://github.com/SMASHIproject/IWRM2018).

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.

Linked hydrologic and climate variations in British Columbia and Yukon.

PubMed

Whitfield, P H

2001-01-01

Climatic and hydrologic variations between the decades 1976-1985 and 1986-1995 are examined at 34 climate stations and 275 hydrology stations. The variations in climate are distributed across a broad spatial area. Temperatures were generally warmer in the most recent decade, with many stations showing significant increases during the spring and fall. No significant decreases in temperature were found. Significant increases in temperature were more frequent in the south than in the northern portions of the region. Significant changes in precipitation were also more prevalent in the south. In coastal areas, there were significant decreases in precipitation during the dry season, and significant increases during the wet season. In the BC interior, significant precipitation decreases occurred during the fall, with significant increases during the winter and spring. In the north there were few changes in precipitation. The hydrologic responses to these variations in climate follow six distinctive patterns. The spatial distribution of these patterns suggests that in different ecozones, small variations in climate, particularly temperature, elicit different hydrologic responses.

Towards Sustainability and Scalability of Educational Innovations in Hydrology:What is the Value and who is the Customer?

NASA Astrophysics Data System (ADS)

Deshotel, M.; Habib, E. H.

2016-12-01

There is an increasing desire by the water education community to use emerging research resources and technological advances in order to reform current educational practices. Recent years have witnessed some exemplary developments that tap into emerging hydrologic modeling and data sharing resources, innovative digital and visualization technologies, and field experiences. However, such attempts remain largely at the scale of individual efforts and fall short of meeting scalability and sustainability solutions. This can be attributed to number of reasons such as inadequate experience with modeling and data-based educational developments, lack of faculty time to invest in further developments, and lack of resources to further support the project. Another important but often-overlooked reason is the lack of adequate insight on the actual needs of end-users of such developments. Such insight is highly critical to inform how to scale and sustain educational innovations. In this presentation, we share with the hydrologic community experiences gathered from an ongoing experiment where the authors engaged in a hypothesis-driven, customer-discovery process to inform the scalability and sustainability of educational innovations in the field of hydrology and water resources education. The experiment is part of a program called Innovation Corps for Learning (I-Corps L). This program follows a business model approach where a value proposition is initially formulated on the educational innovation. The authors then engaged in a hypothesis-validation process through an intense series of customer interviews with different segments of potential end users, including junior/senior students, student interns, and hydrology professors. The authors also sought insight from engineering firms by interviewing junior engineers and their supervisors to gather feedback on the preparedness of graduating engineers as they enter the workforce in the area of water resources. Exploring the large landscape of potential users is critical in formulating a user-driven approach that can inform the innovation development. The presentation shares the results of this experiment and the insight gained and discusses how such information can inform the community on sustaining and scaling hydrology educational developments.

Hydrology or biology? Modeling simplistic physical constraints on lake carbon biogeochemistry to identify when and where biology is likely to matter

NASA Astrophysics Data System (ADS)

Jones, S.; Zwart, J. A.; Solomon, C.; Kelly, P. T.

2017-12-01

Current efforts to scale lake carbon biogeochemistry rely heavily on empirical observations and rarely consider physical or biological inter-lake heterogeneity that is likely to regulate terrestrial dissolved organic carbon (tDOC) decomposition in lakes. This may in part result from a traditional focus of lake ecologists on in-lake biological processes OR physical-chemical pattern across lake regions, rather than on process AND pattern across scales. To explore the relative importance of local biological processes and physical processes driven by lake hydrologic setting, we created a simple, analytical model of tDOC decomposition in lakes that focuses on the regulating roles of lake size and catchment hydrologic export. Our simplistic model can generally recreate patterns consistent with both local- and regional-scale patterns in tDOC concentration and decomposition. We also see that variation in lake hydrologic setting, including the importance of evaporation as a hydrologic export, generates significant, emergent variation in tDOC decomposition at a given hydrologic residence time, and creates patterns that have been historically attributed to variation in tDOC quality. Comparing predictions of this `biologically null model' to field observations and more biologically complex models could indicate when and where biology is likely to matter most.

An experimental test of fitness variation across a hydrologic gradient predicts willow and poplar species distributions.

PubMed

Wei, Xiaojing; Savage, Jessica A; Riggs, Charlotte E; Cavender-Bares, Jeannine

2017-05-01

Environmental filtering is an important community assembly process influencing species distributions. Contrasting species abundance patterns along environmental gradients are commonly used to provide evidence for environmental filtering. However, the same abundance patterns may result from alternative or concurrent assembly processes. Experimental tests are an important means to decipher whether species fitness varies with environment, in the absence of dispersal constraints and biotic interactions, and to draw conclusions about the importance of environmental filtering in community assembly. We performed an experimental test of environmental filtering in 14 closely related willow and poplar species (family Salicaceae) by transplanting cuttings of each species into 40 common gardens established along a natural hydrologic gradient in the field, where competition was minimized and herbivory was controlled. We analyzed species fitness responses to the hydrologic environment based on cumulative growth and survival over two years using aster fitness models. We also examined variation in nine drought and flooding tolerance traits expected to contribute to performance based on a priori understanding of plant function in relation to water availability and stress. We found substantial evidence that environmental filtering along the hydrologic gradient played a critical role in determining species distributions. Fitness variation of each species in the field experiment was used to model their water table depth optima. These optima predicted 68% of the variation in species realized hydrologic niches based on peak abundance in naturally assembled communities in the surrounding region. Multiple traits associated with water transport efficiency and water stress tolerance were correlated with species hydrologic niches, but they did not necessarily covary with each other. As a consequence, species occupying similar hydrologic niches had different combinations of trait values. Moreover, individual traits were less phylogenetically conserved than species hydrologic niches and integrated water stress tolerance as determined by multiple traits. We conclude that differential fitness among species along the hydrologic gradient was the consequence of multiple traits associated with water transport and water stress tolerance, expressed in different combinations by different species. Varying environmental tolerance, in turn, played a critical role in driving niche segregation among close relatives along the hydrologic gradient. © 2017 by the Ecological Society of America.

Centuries of human-driven change in salt marsh ecosystems.

PubMed

Gedan, K Bromberg; Silliman, B R; Bertness, M D

2009-01-01

Salt marshes are among the most abundant, fertile, and accessible coastal habitats on earth, and they provide more ecosystem services to coastal populations than any other environment. Since the Middle Ages, humans have manipulated salt marshes at a grand scale, altering species composition, distribution, and ecosystem function. Here, we review historic and contemporary human activities in marsh ecosystems--exploitation of plant products; conversion to farmland, salt works, and urban land; introduction of non-native species; alteration of coastal hydrology; and metal and nutrient pollution. Unexpectedly, diverse types of impacts can have a similar consequence, turning salt marsh food webs upside down, dramatically increasing top down control. Of the various impacts, invasive species, runaway consumer effects, and sea level rise represent the greatest threats to salt marsh ecosystems. We conclude that the best way to protect salt marshes and the services they provide is through the integrated approach of ecosystem-based management.

Chapter 1: Hydrologic exchange flows and their ecological consequences in river corridors

USGS Publications Warehouse

Harvey, Judson

2016-01-01

The actively flowing waters of streams and rivers remain in close contact with surrounding off-channel and subsurface environments. These hydrologic linkages between relatively fast flowing channel waters, with more slowly flowing waters off-channel and in the subsurface, are collectively referred to as hydrologic exchange flows (HEFs). HEFs include surface exchange with a channel’s marginal areas and subsurface flow through the streambed (hyporheic flow), as well as storm-driven bank storage and overbank flows onto floodplains. HEFs are important, not only for storing water and attenuating flood peaks, but also for their role in influencing water conservation, water quality improvement, and related outcomes for ecological values and services of aquatic ecosystems. Biogeochemical opportunities for chemical transformations are increased by HEFs as a result of the prolonged contact between flowing waters and geochemically and microbially active surfaces of sediments and vegetation. Chemical processing is intensified and water quality is often improved by removal of excess nutrients, metals, and organic contaminants from flowing waters. HEFs also are important regulators of organic matter decomposition, nutrient recycling, and stream metabolism that helps establish a balanced and resilient aquatic food web. The shallow and protected storage zones associated with HEFs support nursery and feeding areas for aquatic organisms that sustain aquatic biological diversity. Understanding of these varied roles for HEFs has been driven by the related disciplines of stream ecology, fluvial geomorphology, surface-water hydraulics, and groundwater hydrology. A current research emphasis is on the role that HEFs play in altered flow regimes, including restoration to achieve diverse goals, such as expanding aquatic habitats and managing dissolved and suspended river loads to reduce over-fertilization of coastal waters and offset wetland loss. New integrative concepts and models are emerging (eg, hydrologic connectivity) that emphasize HEF functions in river corridors over a wide range of spatial and temporal scales.

Influence of forest roads standards and networks on water yield as predicted by the distributed hydrology-soil-vegetation model

Treesearch

Salli F. Dymond; W. Michael Aust; Steven P. Prisley; Mark H. Eisenbies; James M. Vose

2013-01-01

Throughout the country, foresters are continually looking at the effects of logging and forest roads on stream discharge and overall stream health. In the Pacific Northwest, a distributed hydrology-soil-vegetation model (DHSVM) has been used to predict the effects of logging on peak discharge in mountainous regions. DHSVM uses elevation, meteorological, vegetation, and...

Intertwined electron-nuclear motion in frustrated double ionization in driven heteronuclear molecules

NASA Astrophysics Data System (ADS)

Vilà, A.; Zhu, J.; Scrinzi, A.; Emmanouilidou, A.

2018-03-01

We study frustrated double ionization (FDI) in a strongly-driven heteronuclear molecule HeH+ and compare with H2. We compute the probability distribution of the sum of the final kinetic energies of the nuclei for strongly-driven HeH+. We find that this distribution has more than one peak for strongly-driven HeH+, a feature we do not find to be present for strongly-driven H2. Moreover, we compute the probability distribution of the principal quantum number n of FDI. We find that this distribution has several peaks for strongly-driven HeH+, while the respective distribution has one main peak and a ‘shoulder’ at lower principal quantum numbers n for strongly-driven H2. Surprisingly, we find this feature to be a clear signature of the intertwined electron-nuclear motion.

Effect and relevance of the artificial drainage system when assessing the hydrologic impact of the imperviousness distribution within the watershed

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Scale effect challenges in urban hydrology highlighted with a Fully Distributed Model and High-resolution rainfall data

NASA Astrophysics Data System (ADS)

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

2017-04-01

Nowadays, there is a growing interest on small-scale rainfall information, provided by weather radars, to be used in urban water management and decision-making. Therefore, an increasing interest is in parallel devoted to the development of fully distributed and grid-based models following the increase of computation capabilities, the availability of high-resolution GIS information needed for such models implementation. However, the choice of an appropriate implementation scale to integrate the catchment heterogeneity and the whole measured rainfall variability provided by High-resolution radar technologies still issues. This work proposes a two steps investigation of scale effects in urban hydrology and its effects on modeling works. In the first step fractal tools are used to highlight the scale dependency observed within distributed data used to describe the catchment heterogeneity, both the structure of the sewer network and the distribution of impervious areas are analyzed. Then an intensive multi-scale modeling work is carried out to understand scaling effects on hydrological model performance. Investigations were conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model was implemented at 17 spatial resolutions ranging from 100 m to 5 m and modeling investigations were performed using both rain gauge rainfall information as well as high resolution X band radar data in order to assess the sensitivity of the model to small scale rainfall variability. Results coming out from this work demonstrate scale effect challenges in urban hydrology modeling. In fact, fractal concept highlights the scale dependency observed within distributed data used to implement hydrological models. Patterns of geophysical data change when we change the observation pixel size. The multi-scale modeling investigation performed with Multi-Hydro model at 17 spatial resolutions confirms scaling effect on hydrological model performance. Results were analyzed at three ranges of scales identified in the fractal analysis and confirmed in the modeling work. The sensitivity of the model to small-scale rainfall variability was discussed as well.

Diatom-inferred hydrological changes and Holocene geomorphic transitioning of Africa's largest estuarine system, Lake St Lucia

NASA Astrophysics Data System (ADS)

Gomes, M.; Humphries, M. S.; Kirsten, K. L.; Green, A. N.; Finch, J. M.; de Lecea, A. M.

2017-06-01

The diverse lagoons and coastal lakes along the east coast of South Africa occupy incised valleys that were flooded during the rise and subsequent stabilisation of relative sea-level during the Holocene. Sedimentary deposits contained within these waterbodies provide an opportunity to investigate complex hydrological and sedimentological processes, and examine sea-level controls governing system geomorphic evolution. In this paper, we combine diatom and sulfur isotope analyses from two sediment cores extracted from the northern sub-basins of Lake St Lucia, a large shallow estuarine lake that is today largely isolated from direct ocean influence behind a Holocene-Pleistocene barrier complex. Analyses allow the reconstruction of hydrological changes associated with the geomorphic development of the system over the mid-to late Holocene. The sedimentary sequences indicate that St Lucia was a shallow, partially enclosed estuary/embayment dominated by strong tidal flows prior to ∼6200 cal. BP. Infilling was initiated when sea-level rise slowed and stabilised around present day levels, resulting in the accumulation of fine-grained sediment behind an emergent proto-barrier. Diatom assemblages, dominated by marine benthic and epiphytic species, reveal a system structured by marine water influx and characterised by marsh and tidal flat habitats until ∼4550 cal. BP. A shift in the biological community at ∼4550 cal. BP is linked to the development of a back-barrier water body that supported a brackish community. Marine planktonics and enrichments in δ34S suggest recurrent, large-scale barrier inundation events during this time, coincident with a mid-Holocene sea-level highstand. Periodic marine incursions associated with episodes of enhanced storminess and overwash remained prevalent until ∼1200 cal. BP, when further barrier construction ultimately isolated the northern basins from the ocean. This study provides the first reconstruction of the palaeohydrological environment at Lake St Lucia and highlights the long-term geomorphic controls that have shaped the recent evolution and natural dynamics of the system. Unlike most coastal lake systems, this system is particularly effective as an archive of geomorphological change. Systems driven by back-barrier modifications, such as Lake St Lucia, highlight how geomorphological changes driven by sediment-supply, climate and sea level can be distributed unevenly over several isolated back-barrier basins.

A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model

NASA Astrophysics Data System (ADS)

Abbaspour, K. C.; Rouholahnejad, E.; Vaghefi, S.; Srinivasan, R.; Yang, H.; Kløve, B.

2015-05-01

A combination of driving forces are increasing pressure on local, national, and regional water supplies needed for irrigation, energy production, industrial uses, domestic purposes, and the environment. In many parts of Europe groundwater quantity, and in particular quality, have come under sever degradation and water levels have decreased resulting in negative environmental impacts. Rapid improvements in the economy of the eastern European block of countries and uncertainties with regard to freshwater availability create challenges for water managers. At the same time, climate change adds a new level of uncertainty with regard to freshwater supplies. In this research we build and calibrate an integrated hydrological model of Europe using the Soil and Water Assessment Tool (SWAT) program. 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. Leaching of nitrate into groundwater is also simulated at a finer spatial level (HRU). The use of large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation. In this article we discuss issues with data availability, calibration of large-scale distributed models, and outline procedures for model calibration and uncertainty analysis. The calibrated model and results provide information support to the European Water Framework Directive and lay the basis for further assessment of the impact of climate change on water availability and quality. The approach and methods developed are general and can be applied to any large region around the world.

The stable isotope composition of halite and sulfate of hyperarid soils and its relation to aqueous transport

NASA Astrophysics Data System (ADS)

Amundson, Ronald; Barnes, Jaime D.; Ewing, Stephanie; Heimsath, Arjun; Chong, Guillermo

2012-12-01

Halite (NaCl) and gypsum or anhydrite (CaSO4) are water-soluble minerals found in soils of the driest regions of Earth, and only modest attention has been given to the hydrological processes that distribute these salts vertically in soil profiles. The two most notable chloride and sulfate-rich deserts on earth are the Dry Valleys of Antarctica and the Atacama Desert of Chile. While each is hyperarid, they possess very different hydrological regimes. We first show, using previously published S and O isotope data for sulfate minerals, that downward migration of water and sulfate is the primary mechanism responsible for depth profiles of sulfate concentration, and S and O isotopes, in both deserts. In contrast, we found quite different soluble Cl concentration and Cl isotope profiles between the two deserts. For Antarctic soils with an ice layer near the soil surface, the Cl concentrations increase with decreasing soil depth, whereas the ratio of 37Cl/35Cl increases. Based on previous field observations by others, we found that thermally driven upward movement of brine during the winter, described by an advection/diffusion model, qualitatively mimics the observed profiles. In contrast, in the Atacama Desert where rare but relatively large rains drive Cl downward through the profiles, Cl concentrations and 37Cl/35Cl ratios increased with depth. The depth trends in Cl isotopes are more closely explained by a Rayleigh-like model of downward fluid flow. The isotope profiles, and our modeling, reveal the similarities and differences between these two very arid regions on Earth, and are relevant for constraining models of fluid flow in arid zone soil and vadose zone hydrology.

Integrating Fluvial and Oceanic Drivers in Operational Flooding Forecasts for San Francisco Bay

NASA Astrophysics Data System (ADS)

Herdman, Liv; Erikson, Li; Barnard, Patrick; Kim, Jungho; Cifelli, Rob; Johnson, Lynn

2016-04-01

The nine counties that make up the San Francisco Bay area are home to 7.5 million people and these communties are susceptible to flooding along the bay shoreline and inland creeks that drain to the bay. A forecast model that integrates fluvial and oceanic drivers is necessary for predicting flooding in this complex urban environment. The U.S. Geological Survey ( USGS) and National Weather Service (NWS) are developing a state-of-the-art flooding forecast model for the San Francisco Bay area that will predict watershed and ocean-based flooding up to 72 hours in advance of an approaching storm. The model framework for flood forecasts is based on the USGS-developed Coastal Storm Modeling System (CoSMoS) that was applied to San Francisco Bay under the Our Coast Our Future project. For this application, we utilize Delft3D-FM, a hydrodynamic model based on a flexible mesh grid, to calculate water levels that account for tidal forcing, seasonal water level anomalies, surge and in-Bay generated wind waves from the wind and pressure fields of a NWS forecast model, and tributary discharges from the Research Distributed Hydrologic Model (RDHM), developed by the NWS Office of Hydrologic Development. The flooding extent is determined by overlaying the resulting water levels onto a recently completed 2-m digital elevation model of the study area which best resolves the extensive levee and tidal marsh systems in the region. Here we present initial pilot results of hindcast winter storms in January 2010 and December 2012, where the flooding is driven by oceanic and fluvial factors respectively. We also demonstrate the feasibility of predicting flooding on an operational time scale that incorporates both atmospheric and hydrologic forcings.

A Multialgorithm Approach to Land Surface Modeling of Suspended Sediment in the Colorado Front Range

PubMed Central

Stewart, J. R.; Kasprzyk, J. R.; Rajagopalan, B.; Minear, J. T.; Raseman, W. J.

2017-01-01

Abstract A new paradigm of simulating suspended sediment load (SSL) with a Land Surface Model (LSM) is presented here. Five erosion and SSL algorithms were applied within a common LSM framework to quantify uncertainties and evaluate predictability in two steep, forested catchments (>1,000 km2). The algorithms were chosen from among widely used sediment models, including empirically based: monovariate rating curve (MRC) and the Modified Universal Soil Loss Equation (MUSLE); stochastically based: the Load Estimator (LOADEST); conceptually based: the Hydrologic Simulation Program—Fortran (HSPF); and physically based: the Distributed Hydrology Soil Vegetation Model (DHSVM). The algorithms were driven by the hydrologic fluxes and meteorological inputs generated from the Variable Infiltration Capacity (VIC) LSM. A multiobjective calibration was applied to each algorithm and optimized parameter sets were validated over an excluded period, as well as in a transfer experiment to a nearby catchment to explore parameter robustness. Algorithm performance showed consistent decreases when parameter sets were applied to periods with greatly differing SSL variability relative to the calibration period. Of interest was a joint calibration of all sediment algorithm and streamflow parameters simultaneously, from which trade‐offs between streamflow performance and partitioning of runoff and base flow to optimize SSL timing were noted, decreasing the flexibility and robustness of the streamflow to adapt to different time periods. Parameter transferability to another catchment was most successful in more process‐oriented algorithms, the HSPF and the DHSVM. This first‐of‐its‐kind multialgorithm sediment scheme offers a unique capability to portray acute episodic loading while quantifying trade‐offs and uncertainties across a range of algorithm structures. PMID:29399268

The combined effects of topography and vegetation on catchment connectivity

NASA Astrophysics Data System (ADS)

Nippgen, F.; McGlynn, B. L.; Emanuel, R. E.

2012-12-01

The deconvolution of whole catchment runoff response into its temporally dynamic source areas is a grand challenge in hydrology. The extent to which the intersection of static and dynamic catchment characteristics (e.g. topography and vegetation) influences water redistribution within a catchment and the hydrologic connectivity of hillslopes to the riparian and stream system is largely unknown. Over time, patterns of catchment storage shift and, because of threshold connectivity behavior, catchment areas become disconnected from the stream network. We developed a simple but spatially distributed modeling framework that explicitly incorporates static (topography) and dynamic (vegetation) catchment structure to document the evolution of catchment connectivity over the course of a water year. We employed directly measured eddy-covariance evapotranspiration data co-located within a highly instrumented (>150 recording groundwater wells) and gauged catchment to parse the effect of current and zero vegetation scenarios on the temporal evolution of hydrologic connectivity. In the absence of vegetation, and thus in the absence of evapotranspiration, modeled absolute connectivity was 4.5% greater during peak flow and 3.9% greater during late summer baseflow when compared to the actual vegetation scenario. The most significant differences in connected catchment area between current and zero vegetation (14.9%) occurred during the recession period in early July, when water and energy availability were at an optimum. However, the greatest relative difference in connected area occurs during the late summer baseflow period when the absence of evapotranspiration results in a connected area approximately 500% greater than when vegetation is present, while the relative increase during peak flow is just 6%. Changes in connected areas ultimately lead to propose a biologically modified geomorphic width function. This biogeomorphic width function is the result of lateral water redistribution driven by topography and water uptake by vegetation.

Emergence of new hydrologic regimes of surface water resources in the conterminous United States under future warming

NASA Astrophysics Data System (ADS)

Leng, Guoyong; Huang, Maoyi; Voisin, Nathalie; Zhang, Xuesong; Asrar, Ghassem R.; Leung, L. Ruby

2016-11-01

Despite the importance of surface water to people and ecosystems, few studies have explored detectable changes in surface water supply in a changing climate, given its large natural variability. Here we analyze runoff projections from the Variable Infiltration Capacity hydrological model driven by 97 downscaled and bias-corrected Coupled Model Intercomparison Project Phase 5 climate projections over the conterminous United States (CONUS). Our results show that more than 40% of the CONUS land area will experience significant changes in the probability distribution functions (i.e. PDFs) of summer and winter runoff by the end of the 21st century, which may pose great challenges to future surface water supply. Sub-basin mean runoff PDFs are projected to change significantly after 2040s depending on the emission scenarios, with earliest occurrence in the Pacific Northwest and northern California regions. When examining the response as a function of changes in the global mean temperature (ΔGMT), a linear relationship is revealed at the 95% confidence level. Generally, 1 °C increase of GMT leads to 11% and 17% more lands experiencing changes in summer and winter runoff PDFs, respectively. Such changes in land fraction scale with ΔGMT at the country scale independent of emission scenarios, but the same relationship does not necessarily hold at sub-basin scales, due to the larger role of atmospheric circulation changes and their uncertainties on regional precipitation. Further analyses show that the emergence of significant changes in sub-basin runoff PDFs is indicative of the emergence of new hydrology regimes and it is dominated by the changes in variability rather than shift in the mean, regardless of the emission scenarios.

Machine Learning and Deep Learning Models to Predict Runoff Water Quantity and Quality

NASA Astrophysics Data System (ADS)

Bradford, S. A.; Liang, J.; Li, W.; Murata, T.; Simunek, J.

2017-12-01

Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models, which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with physically-based models, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. In this presentation we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport (the HYDRUS-1D overland flow module). A large number of numerical simulations were carried out to develop a database containing information about the impact of various input parameters (weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices) on runoff water quantity and quality outputs. This database was used to train data-driven models. Three different methods (Neural Networks, Support Vector Machines, and Recurrence Neural Networks) were explored to prepare input- output functional relations. Results demonstrate the ability and limitations of machine learning and deep learning models to predict runoff water quantity and quality.

Enhancing the T-shaped learning profile when teaching hydrology using data, modeling, and visualization activities

NASA Astrophysics Data System (ADS)

Sanchez, Christopher A.; Ruddell, Benjamin L.; Schiesser, Roy; Merwade, Venkatesh

2016-03-01

Previous research has suggested that the use of more authentic learning activities can produce more robust and durable knowledge gains. This is consistent with calls within civil engineering education, specifically hydrology, that suggest that curricula should more often include professional perspective and data analysis skills to better develop the "T-shaped" knowledge profile of a professional hydrologist (i.e., professional breadth combined with technical depth). It was expected that the inclusion of a data-driven simulation lab exercise that was contextualized within a real-world situation and more consistent with the job duties of a professional in the field, would provide enhanced learning and appreciation of job duties beyond more conventional paper-and-pencil exercises in a lower-division undergraduate course. Results indicate that while students learned in both conditions, learning was enhanced for the data-driven simulation group in nearly every content area. This pattern of results suggests that the use of data-driven modeling and visualization activities can have a significant positive impact on instruction. This increase in learning likely facilitates the development of student perspective and conceptual mastery, enabling students to make better choices about their studies, while also better preparing them for work as a professional in the field.

Enhancing the T-shaped learning profile when teaching hydrology using data, modeling, and visualization activities

NASA Astrophysics Data System (ADS)

Sanchez, C. A.; Ruddell, B. L.; Schiesser, R.; Merwade, V.

2015-07-01

Previous research has suggested that the use of more authentic learning activities can produce more robust and durable knowledge gains. This is consistent with calls within civil engineering education, specifically hydrology, that suggest that curricula should more often include professional perspective and data analysis skills to better develop the "T-shaped" knowledge profile of a professional hydrologist (i.e., professional breadth combined with technical depth). It was expected that the inclusion of a data driven simulation lab exercise that was contextualized within a real-world situation and more consistent with the job duties of a professional in the field, would provide enhanced learning and appreciation of job duties beyond more conventional paper-and-pencil exercises in a lower division undergraduate course. Results indicate that while students learned in both conditions, learning was enhanced for the data-driven simulation group in nearly every content area. This pattern of results suggests that the use of data-driven modeling and visualization activities can have a significant positive impact on instruction. This increase in learning likely facilitates the development of student perspective and conceptual mastery, enabling students to make better choices about their studies, while also better preparing them for work as a professional in the field.

Effects of changes in climate variability and extremes on the exceedance of critical algal bloom thresholds

NASA Astrophysics Data System (ADS)

Hecht, J. S.; Zia, A.; Beckage, B.; Winter, J.; Schroth, A. W.; Bomblies, A.; Clemins, P. J.; Rizzo, D. M.

2017-12-01

Identifying critical thresholds associated with algal blooms in freshwater lakes is important for avoiding persistent eutrophic conditions and their undesirable ecological, recreational and drinking water impacts. Recent Integrated Assessment Model (IAM) and Bayesian network studies have demonstrated that future climatic changes could increase the duration and intensity of these blooms. Yet, few studies have systematically examined the sensitivity of algal blooms to projected changes in precipitation and temperature variability and extremes at storm-event to seasonal timescales. We employ an IAM, which couples downscaled Global Climate Model (GCM) output with hydrologic and water quality models, to examine the sensitivity of algal blooms in Lake Champlain's shallow Missisquoi Bay to potential future climate changes. We first identify a set of statistically downscaled GCMs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) that reproduce recent historical daily temperature and precipitation observations well in the Lake Champlain basin. Then, we identify plausible covarying changes in the (i) mean and variance of seasonal precipitation and temperature distributions and (ii) frequency and magnitude of individual storm events. We assess the response of water quality indicators (e.g. chlorophyll a concentrations, Trophic State Index) and societal impacts to sequences of daily meteorological series generated from distributions that account for these covarying changes. We also discuss strategies for examining the sensitivity of bloom impacts to different weather sequences generated from a single set of precipitation and temperature distributions with a limited number of computationally intensive IAM simulations. We then evaluate the implications of modeling these changes in climate variability and extreme precipitation events for nutrient management. Finally, we consider the generalizability of our findings for water bodies with different physical and climatic characteristics and address the extent to which climate-driven alterations to terrestrial hydrologic processes, such as evapotranspiration and soil moisture storage, mediate changes to lake water quality.

Statistical analysis of hydrological response in urbanising catchments based on adaptive sampling using inter-amount times

NASA Astrophysics Data System (ADS)

ten Veldhuis, Marie-Claire; Schleiss, Marc

2017-04-01

Urban catchments are typically characterised by a more flashy nature of the hydrological response compared to natural catchments. Predicting flow changes associated with urbanisation is not straightforward, as they are influenced by interactions between impervious cover, basin size, drainage connectivity and stormwater management infrastructure. In this study, we present an alternative approach to statistical analysis of hydrological response variability and basin flashiness, based on the distribution of inter-amount times. We analyse inter-amount time distributions of high-resolution streamflow time series for 17 (semi-)urbanised basins in North Carolina, USA, ranging from 13 to 238 km2 in size. We show that in the inter-amount-time framework, sampling frequency is tuned to the local variability of the flow pattern, resulting in a different representation and weighting of high and low flow periods in the statistical distribution. This leads to important differences in the way the distribution quantiles, mean, coefficient of variation and skewness vary across scales and results in lower mean intermittency and improved scaling. Moreover, we show that inter-amount-time distributions can be used to detect regulation effects on flow patterns, identify critical sampling scales and characterise flashiness of hydrological response. The possibility to use both the classical approach and the inter-amount-time framework to identify minimum observable scales and analyse flow data opens up interesting areas for future research.

Modelling Inland Flood Events for Hazard Maps in Taiwan

NASA Astrophysics Data System (ADS)

Ghosh, S.; Nzerem, K.; Sassi, M.; Hilberts, A.; Assteerawatt, A.; Tillmanns, S.; Mathur, P.; Mitas, C.; Rafique, F.

2015-12-01

Taiwan experiences significant inland flooding, driven by torrential rainfall from plum rain storms and typhoons during summer and fall. From last 13 to 16 years data, 3,000 buildings were damaged by such floods annually with a loss US$0.41 billion (Water Resources Agency). This long, narrow island nation with mostly hilly/mountainous topography is located at tropical-subtropical zone with annual average typhoon-hit-frequency of 3-4 (Central Weather Bureau) and annual average precipitation of 2502mm (WRA) - 2.5 times of the world's average. Spatial and temporal distributions of countrywide precipitation are uneven, with very high local extreme rainfall intensities. Annual average precipitation is 3000-5000mm in the mountainous regions, 78% of it falls in May-October, and the 1-hour to 3-day maximum rainfall are about 85 to 93% of the world records (WRA). Rivers in Taiwan are short with small upstream areas and high runoff coefficients of watersheds. These rivers have the steepest slopes, the shortest response time with rapid flows, and the largest peak flows as well as specific flood peak discharge (WRA) in the world. RMS has recently developed a countrywide inland flood model for Taiwan, producing hazard return period maps at 1arcsec grid resolution. These can be the basis for evaluating and managing flood risk, its economic impacts, and insured flood losses. The model is initiated with sub-daily historical meteorological forcings and calibrated to daily discharge observations at about 50 river gauges over the period 2003-2013. Simulations of hydrologic processes, via rainfall-runoff and routing models, are subsequently performed based on a 10000 year set of stochastic forcing. The rainfall-runoff model is physically based continuous, semi-distributed model for catchment hydrology. The 1-D wave propagation hydraulic model considers catchment runoff in routing and describes large-scale transport processes along the river. It also accounts for reservoir storage. Major historical flood events have been successfully simulated along with spatial patterns of flows. Comparison of stochastic discharge statistics w.r.t. observed ones from Hydrological Year Books of Taiwan over all recorded years are also in good agreement.

Integrated surface and groundwater modelling in the Thames Basin, UK using the Open Modelling Interface

NASA Astrophysics Data System (ADS)

Mackay, Jonathan; Abesser, Corinna; Hughes, Andrew; Jackson, Chris; Kingdon, Andrew; Mansour, Majdi; Pachocka, Magdalena; Wang, Lei; Williams, Ann

2013-04-01

The River Thames catchment is situated in the south-east of England. It covers approximately 16,000 km2 and is the most heavily populated river basin in the UK. It is also one of the driest and has experienced severe drought events in the recent past. With the onset of climate change and human exploitation of our environment, there are now serious concerns over the sustainability of water resources in this basin with 6 million m3 consumed every day for public water supply alone. Groundwater in the Thames basin is extremely important, providing 40% of water for public supply. The principal aquifer is the Chalk, a dual permeability limestone, which has been extensively studied to understand its hydraulic properties. The fractured Jurassic limestone in the upper catchment also forms an important aquifer, supporting baseflow downstream during periods of drought. These aquifers are unconnected other than through the River Thames and its tributaries, which provide two-thirds of London's drinking water. Therefore, to manage these water resources sustainably and to make robust projections into the future, surface and groundwater processes must be considered in combination. This necessitates the simulation of the feedbacks and complex interactions between different parts of the water cycle, and the development of integrated environmental models. The Open Modelling Interface (OpenMI) standard provides a method through which environmental models of varying complexity and structure can be linked, allowing them to run simultaneously and exchange data at each timestep. This architecture has allowed us to represent the surface and subsurface flow processes within the Thames basin at an appropriate level of complexity based on our understanding of particular hydrological processes and features. We have developed a hydrological model in OpenMI which integrates a process-driven, gridded finite difference groundwater model of the Chalk with a more simplistic, semi-distributed conceptual model of the Jurassic limestone. A distributed river routing model of the Thames has also been integrated to connect the surface and subsurface hydrological processes. This application demonstrates the potential benefits and issues associated with implementing this approach.

Hyporheic Zone Residence Time Distributions in Regulated River Corridors

NASA Astrophysics Data System (ADS)

Song, X.; Chen, X.; Shuai, P.; Gomez-Velez, J. D.; Ren, H.; Hammond, G. E.

2017-12-01

Regulated rivers exhibit stage fluctuations at multiple frequencies due to both natural processes (e.g., seasonal cycle) and anthropogenic activities (e.g., dam operation). The interaction between the dynamic river flow conditions and the heterogeneous aquifer properties results in complex hydrologic exchange pathways that are ubiquitous in free-flowing and regulated river corridors. The dynamic nature of the exchange flow is reflected in the residence time distribution (RTD) of river water within the groundwater system, which is a key metric that links river corridor biogeochemical processes with the hydrologic exchange. Understanding the dynamics of RTDs is critical to gain the mechanistic understanding of hydrologic exchange fluxes and propose new parsimonious models for river corridors, yet it is understudied primarily due to the high computational demands. In this study, we developed parallel particle tracking algorithms to reveal how river flow variations affect the RTD of river water in the alluvial aquifer. Particle tracking was conducted using the velocity outputs generated by three-dimensional groundwater flow simulations of PFLOTRAN in a 1600 x 800 x 20m model domain within the DOE Hanford Site. Long-term monitoring data of inland well water levels and river stage were used for eight years of flow simulation. Nearly a half million particles were continually released along the river boundary to calculate the RTDs. Spectral analysis of the river stage data revealed high-frequency (sub-daily to weekly) river stage fluctuations caused by dam operations. The higher frequencies of stage variation were progressively filtered to generate multiple sets of flow boundary conditions. A series of flow simulations were performed by using the filtered flow boundary conditions and various degrees of subsurface heterogeneity to study the relative contribution of flow dynamics and physical heterogeneity on river water RTD. Our results revealed multimodal RTDs of river water as a result of the highly variable exchange pathways driven by interactions between dynamic flow and aquifer heterogeneity. A relationship between the RTD and frequency of flow variation was built for each heterogeneity structure, which can be used to assess the potential ecological consequences of dam operations in regulated rivers.

Improved hydrological-model design by integrating nutrient and water flow

NASA Astrophysics Data System (ADS)

Arheimer, B.; Lindstrom, G.

2013-12-01

The potential of integrating hydrologic and nutrient concentration data to better understand patterns of catchment response and to better design hydrological modeling was explored using a national multi-basin model system for Sweden, called ';S-HYPE'. The model system covers more than 450 000 km2 and produce daily values of nutrient concentration and water discharge in 37 000 catchments from 1961 and onwards. It is based on the processed-based and semi-distributed HYdrological Predictions for the Environment (HYPE) code. The model is used operationally for assessments of water status or climate change impacts and for forecasts by the national warning service of floods, droughts and fire. The first model was launched in 2008, but S-HYPE is continuously improved and released in new versions every second year. Observations are available in 400 sites for daily water discharge and some 900 sites for monthly grab samples of nutrient concentrations. The latest version (2012) has an average NSE for water discharge of 0.7 and an average relative error of 5%, including both regulated and unregulated rivers with catchments from ten to several thousands of km2 and various landuse. The daily relative errors of nutrient concentrations are on average 20% for total Nitrogen and 35% for total Phosphorus. This presentation will give practical examples of how the nutrient data has been used to trace errors or inadequate parameter values in the hydrological model. Since 2008 several parts of the model structure has been reconsidered both in the source code, parameter values and input data of catchment characteristics. In this process water quality has been guiding much of the overall model design of catchment hydrological functions and routing along the river network. The model structure has thus been developed iteratively when evaluating results and checking time-series. Examples of water quality driven improvements will be given for estimation of vertical flow paths, such as separation of the hydrograph in surface flow, snow melt and baseflow, as well as horizontal flow paths in the landscape, such as mixing from various land use, impact from lakes and river channel volume. Overall, the S-HYPE model performance of water discharge increased from NSE 0.55 to 0.69 as an average for 400 gauges between the version 2010 and 2012. Most of this improvement, however, can be referred to improved regulations routines, rating curves for major lakes and parameters correcting ET and precipitation. Nevertheless, integrated water and nutrient modeling put constraints on the hydrological parameter values, which reduce equifinality for the hydrological part without reducing the model performance. The examples illustrates that the credibility of the hydrological model structure is thus improved by integrating water and nutrient flow. This lead to improved understanding of flow paths and water-nutrient process interactions in Sweden, which in turn will be very useful in further model analysis on impact of climate change or measures to reduce nutrient load from rivers to the Baltic Sea.

A dynamic nitrogen budget model of a Pacific Northwest salt marsh

EPA Science Inventory

The role of salt marshes as either nitrogen sinks or sources in relation to their adjacent estuaries has been a focus of ecosystem service research for many decades. The complex hydrology of these systems is driven by tides, upland surface runoff, precipitation, evapotranspirati...

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation.

PubMed

Qin, Changbo; Jia, Yangwen; Su, Z; Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-07-29

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems.

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation

PubMed Central

Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-01-01

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946

Projected Irrigation Requirement Under Climate Change in Korean Peninsula by Apply Global Hydrologic Model to Local Scale.

NASA Astrophysics Data System (ADS)

Yang, B.; Lee, D. K.

2016-12-01

Understanding spatial distribution of irrigation requirement is critically important for agricultural water management. However, many studies considering future agricultural water management in Korea assessed irrigation requirement on watershed or administrative district scale, but have not accounted the spatial distribution. Lumped hydrologic model has typically used in Korea for simulating watershed scale irrigation requirement, while distribution hydrologic model can simulate the spatial distribution grid by grid. To overcome this shortcoming, here we applied a grid base global hydrologic model (H08) into local scale to estimate spatial distribution under future irrigation requirement of Korean Peninsula. Korea is one of the world's most densely populated countries, with also high produce and demand of rice which requires higher soil moisture than other crops. Although, most of the precipitation concentrate in particular season and disagree with crop growth season. This precipitation character makes management of agricultural water which is approximately 60% of total water usage critical issue in Korea. Furthermore, under future climate change, the precipitation predicted to be more concentrated and necessary need change of future water management plan. In order to apply global hydrological model into local scale, we selected appropriate major crops under social and local climate condition in Korea to estimate cropping area and yield, and revised the cropping area map more accurately. As a result, future irrigation requirement estimation varies under each projection, however, slightly decreased in most case. The simulation reveals, evapotranspiration increase slightly while effective precipitation also increase to balance the irrigation requirement. This finding suggest practical guideline to decision makers for further agricultural water management plan including future development of water supply plan to resolve water scarcity.

Different modelling approaches to evaluate nitrogen transport and turnover at the watershed scale

NASA Astrophysics Data System (ADS)

Epelde, Ane Miren; Antiguedad, Iñaki; Brito, David; Jauch, Eduardo; Neves, Ramiro; Garneau, Cyril; Sauvage, Sabine; Sánchez-Pérez, José Miguel

2016-08-01

This study presents the simulation of hydrological processes and nutrient transport and turnover processes using two integrated numerical models: Soil and Water Assessment Tool (SWAT) (Arnold et al., 1998), an empirical and semi-distributed numerical model; and Modelo Hidrodinâmico (MOHID) (Neves, 1985), a physics-based and fully distributed numerical model. This work shows that both models reproduce satisfactorily water and nitrate exportation at the watershed scale at annual and daily basis, MOHID providing slightly better results. At the watershed scale, both SWAT and MOHID simulated similarly and satisfactorily the denitrification amount. However, as MOHID numerical model was the only one able to reproduce adequately the spatial variation of the soil hydrological conditions and water table level fluctuation, it proved to be the only model able of reproducing the spatial variation of the nutrient cycling processes that are dependent to the soil hydrological conditions such as the denitrification process. This evidences the strength of the fully distributed and physics-based models to simulate the spatial variability of nutrient cycling processes that are dependent to the hydrological conditions of the soils.

The Influence of Runoff and Surface Hydrology on Titan's Weather and Climate

NASA Astrophysics Data System (ADS)

Faulk, S.; Lora, J. M.; Mitchell, J.; Moon, S.

2017-12-01

Titan's surface liquid distribution has been shown by general circulation models (GCMs) to greatly influence the hydrological cycle, producing characteristic weather and seasonal climate patterns. Simulations from the Titan Atmospheric Model (TAM) with imposed polar methane "wetlands" reservoirs realistically produce observed cloud features and temperature profiles of Titan's atmosphere, whereas "aquaplanet" simulations with a global methane ocean are not as successful. In addition, wetlands simulations, unlike aquaplanet simulations, demonstrate strong correlations between extreme rainfall behavior and observed geomorphic features, indicating the influential role of precipitation in shaping Titan's surface. The wetlands configuration is, in part, motivated by Titan's large-scale topography featuring low-latitude highlands and high-latitude lowlands, with the implication being that methane may concentrate in the high-latitude lowlands by way of runoff and subsurface flow of a global or regional methane table. However, the extent to which topography controls the surface liquid distribution and thus impacts the global hydrological cycle by driving surface and subsurface flow is unclear. Here we present TAM simulations wherein the imposed wetlands reservoirs are replaced by a surface runoff scheme that allows surface liquid to self-consistently redistribute under the influence of topography. We discuss the impact of surface runoff on the surface liquid distribution over seasonal timescales and compare the resulting hydrological cycle to observed cloud and surface features, as well as to the hydrological cycles of the TAM wetlands and aquaplanet simulations. While still idealized, this more realistic representation of Titan's hydrology provides new insight into the complex interaction between Titan's atmosphere and surface, demonstrates the influence of surface runoff on Titan's global climate, and lays the groundwork for further surface hydrology developments in Titan GCMs, including infiltration and subsurface flow.

The impact of runoff and surface hydrology on Titan's climate

NASA Astrophysics Data System (ADS)

Faulk, Sean; Lora, Juan; Mitchell, Jonathan

2017-10-01

Titan’s surface liquid distribution has been shown by general circulation models (GCMs) to greatly influence the hydrological cycle. Simulations from the Titan Atmospheric Model (TAM) with imposed polar methane “wetlands” reservoirs realistically produce many observed features of Titan’s atmosphere, whereas “aquaplanet” simulations with a global methane ocean are not as successful. In addition, wetlands simulations, unlike aquaplanet simulations, demonstrate strong correlations between extreme rainfall behavior and observed geomorphic features, indicating the influential role of precipitation in shaping Titan’s surface. The wetlands configuration is, in part, motivated by Titan’s large-scale topography featuring low-latitude highlands and high-latitude lowlands, with the implication being that methane may concentrate in the high-latitude lowlands by way of runoff and subsurface flow. However, the extent to which topography controls the surface liquid distribution and thus impacts the global hydrological cycle by driving surface and subsurface flow is unclear. Here we present TAM simulations wherein the imposed wetlands reservoirs are replaced by a surface runoff scheme that allows surface liquid to self-consistently redistribute under the influence of topography. To isolate the singular impact of surface runoff on Titan’s climatology, we run simulations without parameterizations of subsurface flow and topography-atmosphere interactions. We discuss the impact of surface runoff on the surface liquid distribution over seasonal timescales and compare the resulting hydrological cycle to observed cloud and surface features, as well as to the hydrological cycles of the TAM wetlands and aquaplanet simulations. While still idealized, this more realistic representation of Titan’s hydrology provides new insight into the complex interaction between Titan’s atmosphere and surface, demonstrates the influence of surface runoff on Titan’s global climate, and lays the groundwork for further surface hydrology developments in Titan GCMs.

The Impact of Microwave-Derived Surface Soil Moisture on Watershed Hydrological Modeling

NASA Technical Reports Server (NTRS)

ONeill, P. E.; Hsu, A. Y.; Jackson, T. J.; Wood, E. F.; Zion, M.

1997-01-01

The usefulness of incorporating microwave-derived soil moisture information in a semi-distributed hydrological model was demonstrated for the Washita '92 experiment in the Little Washita River watershed in Oklahoma. Initializing the hydrological model with surface soil moisture fields from the ESTAR airborne L-band microwave radiometer on a single wet day at the start of the study period produced more accurate model predictions of soil moisture than a standard hydrological initialization with streamflow data over an eight-day soil moisture drydown.

Satellite-observed snow cover variations over the Tibetan Plateau for the period 2001-2014

NASA Astrophysics Data System (ADS)

Long, D.; Chen, X.

2016-12-01

Snow is an integral component of the global climate system. Owing to its high albedo and thermal and water storage properties, snow has important linkages and feedbacks through its influence on surface energy and moisture fluxes, clouds, precipitation, hydrology, and atmospheric circulation. As the "Roof of the World" and the "Third Pole" with the highest mountains in middle latitudes, the Tibetan Plateau (TP) is one of the most hot spots in climate change and hydrological studies, in which seasonal snow cover is a critical aspect. Unlike large-scale snow cover and regional-scale glaciers over other cryospheric regions, changes in snow cover over the TP has been largely unknown due mostly to the quality of observations. Based on improved MODIS daily snow cover products, this study aims to quantify the distribution and changes in snow cover over the TP for the period 2001 to 2014. Results show that the spatial distribution of changes in snow cover fraction (SCF) over the 14-year study period exhibited a general negative trend over the TP driven primarily by increasing land surface temperature (LST), except some areas of the upper Golden-Sanded River and upper Brahmaputra River basins. However, decreased LST and increased precipitation in the accumulation season (September to the following February) resulted in increased SCF in the accumulation season, coinciding with large-scale cold snaps and heavy snowfall events at middle latitudes. Detailed analyses of the intra-annual variability of SCF in the TP regions show an increase in SCF in the accumulation season but a decrease in SCF in the melting season (March to August), indicating that the intra-annual amplitude of SCF increased during the study period and more snow cover was released as snowmelt in the spring season.

Projected climate impacts for the amphibians of the western hemisphere

USGS Publications Warehouse

Lawler, Joshua J.; Shafer, Sarah L.; Bancroft, Betsy A.; Blaustein, Andrew R.

2010-01-01

Given their physiological requirements, limited dispersal abilities, and hydrologically sensitive habitats, amphibians are likely to be highly sensitive to future climatic changes. We used three approaches to map areas in the western hemisphere where amphibians are particularly likely to be affected by climate change. First, we used bioclimatic models to project potential climate-driven shifts in the distribution of 413 amphibian species based on 20 climate simulations for 2071–2100. We summarized these projections to produce estimates of species turnover. Second, we mapped the distribution of 1099 species with restricted geographic ranges. Finally, using the 20 future climate-change simulations, we mapped areas that were consistently projected to receive less seasonal precipitation in the coming century and thus were likely to have altered microclimates and local hydrologies. Species turnover was projected to be highest in the Andes Mountains and parts of Central America and Mexico, where, on average, turnover rates exceeded 60% under the lower of two emissions scenarios. Many of the restricted-range species not included in our range-shift analyses were concentrated in parts of the Andes and Central America and in Brazil's Atlantic Forest. Much of Central America, southwestern North America, and parts of South America were consistently projected to experience decreased precipitation by the end of the century. Combining the results of the three analyses highlighted several areas in which amphibians are likely to be significantly affected by climate change for multiple reasons. Portions of southern Central America were simultaneously projected to experience high species turnover, have many additional restricted-range species, and were consistently projected to receive less precipitation. Together, our three analyses form one potential assessment of the geographic vulnerability of amphibians to climate change and as such provide broad-scale guidance for directing conservation efforts.

Projected climate impacts for the amphibians of the Western hemisphere.

PubMed

Lawler, Joshua J; Shafer, Sarah L; Bancroft, Betsy A; Blaustein, Andrew R

2010-02-01

Given their physiological requirements, limited dispersal abilities, and hydrologically sensitive habitats, amphibians are likely to be highly sensitive to future climatic changes. We used three approaches to map areas in the western hemisphere where amphibians are particularly likely to be affected by climate change. First, we used bioclimatic models to project potential climate-driven shifts in the distribution of 413 amphibian species based on 20 climate simulations for 2071-2100. We summarized these projections to produce estimates of species turnover. Second, we mapped the distribution of 1099 species with restricted geographic ranges. Finally, using the 20 future climate-change simulations, we mapped areas that were consistently projected to receive less seasonal precipitation in the coming century and thus were likely to have altered microclimates and local hydrologies. Species turnover was projected to be highest in the Andes Mountains and parts of Central America and Mexico, where, on average, turnover rates exceeded 60% under the lower of two emissions scenarios. Many of the restricted-range species not included in our range-shift analyses were concentrated in parts of the Andes and Central America and in Brazil's Atlantic Forest. Much of Central America, southwestern North America, and parts of South America were consistently projected to experience decreased precipitation by the end of the century. Combining the results of the three analyses highlighted several areas in which amphibians are likely to be significantly affected by climate change for multiple reasons. Portions of southern Central America were simultaneously projected to experience high species turnover, have many additional restricted-range species, and were consistently projected to receive less precipitation. Together, our three analyses form one potential assessment of the geographic vulnerability of amphibians to climate change and as such provide broad-scale guidance for directing conservation efforts.

Integrating Sediment Connectivity into Water Resources Management Trough a Graph Theoretic, Stochastic Modeling Framework.

NASA Astrophysics Data System (ADS)

Schmitt, R. J. P.; Castelletti, A.; Bizzi, S.

2014-12-01

Understanding sediment transport processes at the river basin scale, their temporal spectra and spatial patterns is key to identify and minimize morphologic risks associated to channel adjustments processes. This work contributes a stochastic framework for modeling bed-load connectivity based on recent advances in the field (e.g., Bizzi & Lerner, 2013; Czubas & Foufoulas-Georgiu, 2014). It presents river managers with novel indicators from reach scale vulnerability to channel adjustment in large river networks with sparse hydrologic and sediment observations. The framework comprises three steps. First, based on a distributed hydrological model and remotely sensed information, the framework identifies a representative grain size class for each reach. Second, sediment residence time distributions are calculated for each reach in a Monte-Carlo approach applying standard sediment transport equations driven by local hydraulic conditions. Third, a network analysis defines the up- and downstream connectivity for various travel times resulting in characteristic up/downstream connectivity signatures for each reach. Channel vulnerability indicators quantify the imbalance between up/downstream connectivity for each travel time domain, representing process dependent latency of morphologic response. Last, based on the stochastic core of the model, a sensitivity analysis identifies drivers of change and major sources of uncertainty in order to target key detrimental processes and to guide effective gathering of additional data. The application, limitation and integration into a decision analytic framework is demonstrated for a major part of the Red River Basin in Northern Vietnam (179.000 km2). Here, a plethora of anthropic alterations ranging from large reservoir construction to land-use changes results in major downstream deterioration and calls for deriving concerted sediment management strategies to mitigate current and limit future morphologic alterations.

Development of a biosphere hydrological model considering vegetation dynamics and its evaluation at basin scale under climate change

NASA Astrophysics Data System (ADS)

Li, Qiaoling; Ishidaira, Hiroshi

2012-01-01

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

A comparison of MIKE SHE and DRAINMOD for modeling forested wetland hydrology in coastal South Carolina, USA

Treesearch

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

2010-01-01

Models are widely used to assess hydrologic impacts of land-management, land-use change and climate change. Two hydrologic models with different spatial scales, MIKE SHE (spatially distributed, watershed-scale) and DRAINMOD (lumped, fieldscale), were compared in terms of their performance in predicting stream flow and water table depth in a first-order forested...

Bi-criteria evaluation of the MIKE SHE model for a forested watershed on the South Carolina coastal plain

Treesearch

Z. Dai; C. Li; C. Trettin; G. Sun; D. Amatya; H. Li

2010-01-01

Hydrological models are important tools for effective management, conservation and restoration of forested wetlands. The objective of this study was to test a distributed hydrological model, MIKE SHE, by using bi-criteria (i.e., two measurable variables, streamflow and water table depth) to describe the hydrological processes in a forested watershed that is...

Improving student comprehension of the interconnectivity of the hydrologic cycle with a novel 'hydrology toolbox', integrated watershed model, and companion textbook

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Analog-Based Postprocessing of Navigation-Related Hydrological Ensemble Forecasts

NASA Astrophysics Data System (ADS)

Hemri, S.; Klein, B.

2017-11-01

Inland waterway transport benefits from probabilistic forecasts of water levels as they allow to optimize the ship load and, hence, to minimize the transport costs. Probabilistic state-of-the-art hydrologic ensemble forecasts inherit biases and dispersion errors from the atmospheric ensemble forecasts they are driven with. The use of statistical postprocessing techniques like ensemble model output statistics (EMOS) allows for a reduction of these systematic errors by fitting a statistical model based on training data. In this study, training periods for EMOS are selected based on forecast analogs, i.e., historical forecasts that are similar to the forecast to be verified. Due to the strong autocorrelation of water levels, forecast analogs have to be selected based on entire forecast hydrographs in order to guarantee similar hydrograph shapes. Custom-tailored measures of similarity for forecast hydrographs comprise hydrological series distance (SD), the hydrological matching algorithm (HMA), and dynamic time warping (DTW). Verification against observations reveals that EMOS forecasts for water level at three gauges along the river Rhine with training periods selected based on SD, HMA, and DTW compare favorably with reference EMOS forecasts, which are based on either seasonal training periods or on training periods obtained by dividing the hydrological forecast trajectories into runoff regimes.

Checklist of the continental fishes of the state of Chiapas, Mexico, and their distribution

PubMed Central

Velázquez-Veláquez, Ernesto; López-Vila, Jesús Manuel; Gómez-González, Adán Enrique; Romero-Berny, Emilio Ismael; Lievano-Trujillo, Jorge Luis; Matamoros, Wilfredo A.

2016-01-01

Abstract An updated checklist of the distribution of fishes that inhabit the continental waters of the Mexican state of Chiapas is presented. The state was compartmentalized into 12 hydrological regions for the purpose of understanding the distribution of fish fauna across a state with large physiographic variance. The ichthyofauna of Chiapas is represented by 311 species distributed in two classes, 26 orders, 73 families, and 182 genera, including 12 exotic species. The families with the highest number of species were Cichlidae, Poeciliidae, Sciaenidae, Carangidae, Ariidae, Gobiidae, and Haemulidae. This study attempts to close gaps in knowledge of the distribution of ichthyofauna in the diverse hydrological regions of Chiapas, Mexico. PMID:27920608

Understanding patterns of vegetation structure and distribution across Great Smoky Mountains National Park using LiDAR and meteorology data

NASA Astrophysics Data System (ADS)

Kumar, J.; Hargrove, W. W.; Norman, S. P.; Hoffman, F. M.

2017-12-01

Great Smoky Mountains National Park (GSMNP) in Tennessee is a biodiversity hotspot and home to a large number of plant, animal and bird species. Driven by gradients of climate (ex. temperature, precipitation regimes), topography (ex. elevation, slope, aspect), geology (ex. soil types, textures, depth), hydrology (ex. drainage, moisture availability) etc. GSMNP offers a diverse composition and distribution of vegetation which in turn supports an array of wildlife. Understanding the vegetation canopy structure is critical to understand, monitor and manage the complex forest ecosystems like the Great Smoky Mountain National Park (GSMNP). Vegetation canopies not only help understand the vegetation, but are also a critically important habitat characteristics of many threatened and endangered animal and bird species that GSMNP is home to. Using airborne Light Detection and Ranging (LiDAR) we characterize the three-dimensional structure of the vegetation. LiDAR based analysis gives detailed insight in the canopy structure (overstory and understory) and its spatial variability within and across forest types. Vegetation structure and spatial distribution show strong correlation with climate, topographic, and edaphic variables and our multivariate analysis not just mines rich and large LiDAR data but presents ecological insights and data for vegetation within the park that can be useful to forest managers in their management and conservation efforts.

Improved Lower Mekong River Basin Hydrological Decision Making Using NASA Satellite-based Earth Observation Systems

NASA Astrophysics Data System (ADS)

Bolten, J. D.; Mohammed, I. N.; Srinivasan, R.; Lakshmi, V.

2017-12-01

Better understanding of the hydrological cycle of the Lower Mekong River Basin (LMRB) and addressing the value-added information of using remote sensing data on the spatial variability of soil moisture over the Mekong Basin is the objective of this work. In this work, we present the development and assessment of the LMRB (drainage area of 495,000 km2) Soil and Water Assessment Tool (SWAT). The coupled model framework presented is part of SERVIR, a joint capacity building venture between NASA and the U.S. Agency for International Development, providing state-of-the-art, satellite-based earth monitoring, imaging and mapping data, geospatial information, predictive models, and science applications to improve environmental decision-making among multiple developing nations. The developed LMRB SWAT model enables the integration of satellite-based daily gridded precipitation, air temperature, digital elevation model, soil texture, and land cover and land use data to drive SWAT model simulations over the Lower Mekong River Basin. The LMRB SWAT model driven by remote sensing climate data was calibrated and verified with observed runoff data at the watershed outlet as well as at multiple sites along the main river course. Another LMRB SWAT model set driven by in-situ climate observations was also calibrated and verified to streamflow data. Simulated soil moisture estimates from the two models were then examined and compared to a downscaled Soil Moisture Active Passive Sensor (SMAP) 36 km radiometer products. Results from this work present a framework for improving SWAT performance by utilizing a downscaled SMAP soil moisture products used for model calibration and validation. Index Terms: 1622: Earth system modeling; 1631: Land/atmosphere interactions; 1800: Hydrology; 1836 Hydrological cycles and budgets; 1840 Hydrometeorology; 1855: Remote sensing; 1866: Soil moisture; 6334: Regional Planning

Distributed Hydrologic Modeling Apps for Decision Support in the Cloud

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Assessment of Hydrologic Response to Variable Precipitation Forcing: Russian River Case Study

NASA Astrophysics Data System (ADS)

Cifelli, R.; Hsu, C.; Johnson, L. E.

2014-12-01

NOAA Hydrometeorology Testbed (HMT) activities in California have involved deployment of advanced sensor networks to better track atmospheric river (AR) dynamics and inland penetration of high water vapor air masses. Numerical weather prediction models and decision support tools have been developed to provide forecasters a better basis for forecasting heavy precipitation and consequent flooding. The HMT also involves a joint project with California Department of Water Resources (CA-DWR) and the Scripps Institute for Oceanography (SIO) as part of CA-DWR's Enhanced Flood Response and Emergency Preparedness (EFREP) program. The HMT activities have included development and calibration of a distributed hydrologic model, the NWS Office of Hydrologic Development's (OHD) Research Distributed Hydrologic Model (RDHM), to prototype the distributed approach for flood and other water resources applications. HMT has applied RDHM to the Russian-Napa watersheds for research assessment of gap-filling weather radars for precipitation and hydrologic forecasting and for establishing a prototype to inform both the NWS Monterey Forecast Office and the California Nevada River Forecast Center (CNRFC) of RDHM capabilities. In this presentation, a variety of precipitation forcings generated with and without gap filling radar and rain gauge data are used as input to RDHM to assess the hydrologic response for selected case study events. Both the precipitation forcing and hydrologic model are run at different spatial and temporal resolution in order to examine the sensitivity of runoff to the precipitation inputs. Based on the timing of the events and the variations of spatial and temporal resolution, the parameters which dominate the hydrologic response are identified. The assessment is implemented at two USGS stations (Ukiah near Russian River and Austin Creek near Cazadero) that are minimally influenced by managed flows and objective evaluation can thus be derived. The results are assessed using statistical metrics, including daily Nash scores, Pearson Correlation, and sub daily timing errors.

Hydrologic characteristics of freshwater mussel habitat: novel insights from modeled flows

USGS Publications Warehouse

Drew, C. Ashton; Eddy, Michele; Kwak, Thomas J.; Cope, W. Gregory; Augspurger, Tom

2018-01-01

The ability to model freshwater stream habitat and species distributions is limited by the spatially sparse flow data available from long-term gauging stations. Flow data beyond the immediate vicinity of gauging stations would enhance our ability to explore and characterize hydrologic habitat suitability. The southeastern USA supports high aquatic biodiversity, but threats, such as landuse alteration, climate change, conflicting water-resource demands, and pollution, have led to the imperilment and legal protection of many species. The ability to distinguish suitable from unsuitable habitat conditions, including hydrologic suitability, is a key criterion for successful conservation and restoration of aquatic species. We used the example of the critically endangered Tar River Spinymussel (Parvaspina steinstansana) and associated species to demonstrate the value of modeled flow data (WaterFALL™) to generate novel insights into population structure and testable hypotheses regarding hydrologic suitability. With ordination models, we: 1) identified all catchments with potentially suitable hydrology, 2) identified 2 distinct hydrologic environments occupied by the Tar River Spinymussel, and 3) estimated greater hydrological habitat niche breadth of assumed surrogate species associates at the catchment scale. Our findings provide the first demonstrated application of complete, continuous, regional modeled hydrologic data to freshwater mussel distribution and management. This research highlights the utility of modeling and data-mining methods to facilitate further exploration and application of such modeled environmental conditions to inform aquatic species management. We conclude that such an approach can support landscape-scale management decisions that require spatial information at fine resolution (e.g., enhanced National Hydrology Dataset catchments) and broad extent (e.g., multiple river basins).

Hydrological-niche models predict water plant functional group distributions in diverse wetland types.

PubMed

Deane, David C; Nicol, Jason M; Gehrig, Susan L; Harding, Claire; Aldridge, Kane T; Goodman, Abigail M; Brookes, Justin D

2017-06-01

Human use of water resources threatens environmental water supplies. If resource managers are to develop policies that avoid unacceptable ecological impacts, some means to predict ecosystem response to changes in water availability is necessary. This is difficult to achieve at spatial scales relevant for water resource management because of the high natural variability in ecosystem hydrology and ecology. Water plant functional groups classify species with similar hydrological niche preferences together, allowing a qualitative means to generalize community responses to changes in hydrology. We tested the potential for functional groups in making quantitative prediction of water plant functional group distributions across diverse wetland types over a large geographical extent. We sampled wetlands covering a broad range of hydrogeomorphic and salinity conditions in South Australia, collecting both hydrological and floristic data from 687 quadrats across 28 wetland hydrological gradients. We built hydrological-niche models for eight water plant functional groups using a range of candidate models combining different surface inundation metrics. We then tested the predictive performance of top-ranked individual and averaged models for each functional group. Cross validation showed that models achieved acceptable predictive performance, with correct classification rates in the range 0.68-0.95. Model predictions can be made at any spatial scale that hydrological data are available and could be implemented in a geographical information system. We show the response of water plant functional groups to inundation is consistent enough across diverse wetland types to quantify the probability of hydrological impacts over regional spatial scales. © 2017 by the Ecological Society of America.

Full implementation of a distributed hydrological model based on check dam trapped sediment volumes

NASA Astrophysics Data System (ADS)

Bussi, Gianbattista; Francés, Félix

2014-05-01

Lack of hydrometeorological data is one of the most compelling limitations to the implementation of distributed environmental models. Mediterranean catchments, in particular, are characterised by high spatial variability of meteorological phenomena and soil characteristics, which may prevents from transferring model calibrations from a fully gauged catchment to a totally o partially ungauged one. For this reason, new sources of data are required in order to extend the use of distributed models to non-monitored or low-monitored areas. An important source of information regarding the hydrological and sediment cycle is represented by sediment deposits accumulated at the bottom of reservoirs. Since the 60s, reservoir sedimentation volumes were used as proxy data for the estimation of inter-annual total sediment yield rates, or, in more recent years, as a reference measure of the sediment transport for sediment model calibration and validation. Nevertheless, the possibility of using such data for constraining the calibration of a hydrological model has not been exhaustively investigated so far. In this study, the use of nine check dam reservoir sedimentation volumes for hydrological and sedimentological model calibration and spatio-temporal validation was examined. Check dams are common structures in Mediterranean areas, and are a potential source of spatially distributed information regarding both hydrological and sediment cycle. In this case-study, the TETIS hydrological and sediment model was implemented in a medium-size Mediterranean catchment (Rambla del Poyo, Spain) by taking advantage of sediment deposits accumulated behind the check dams located in the catchment headwaters. Reservoir trap efficiency was taken into account by coupling the TETIS model with a pond trap efficiency model. The model was calibrated by adjusting some of its parameters in order to reproduce the total sediment volume accumulated behind a check dam. Then, the model was spatially validated by obtaining the simulated sedimentation volume at the other eight check dams and comparing it to the observed sedimentation volumes. Lastly, the simulated water discharge at the catchment outlet was compared with observed water discharge records in order to check the hydrological sub-model behaviour. Model results provided highly valuable information concerning the spatial distribution of soil erosion and sediment transport. Spatial validation of the sediment sub-model provided very good results at seven check dams out of nine. This study shows that check dams can be a useful tool also for constraining hydrological model calibration, as model results agree with water discharge observations. In fact, the hydrological model validation at a downstream water flow gauge obtained a Nash-Sutcliffe efficiency of 0.8. This technique is applicable to all catchments with presence of check dams, and only requires rainfall and temperature data and soil characteristics maps.

Simulating hydrological processes of a typical small mountainous catchment in Tibetan Plateau

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Virus-Bacterium Coupling Driven by both Turbidity and Hydrodynamics in an Amazonian Floodplain Lake ▿ † ‡

PubMed Central

Barros, Nathan; Farjalla, Vinicius F.; Soares, Maria C.; Melo, Rossana C. N.; Roland, Fábio

2010-01-01

The importance of viruses in aquatic ecosystem functioning has been widely described. However, few studies have examined tropical aquatic ecosystems. Here, we evaluated for the first time viruses and their relationship with other planktonic communities in an Amazonian freshwater ecosystem. Coupling between viruses and bacteria was studied, focusing both on hydrologic dynamics and anthropogenic forced turbidity in the system (Lake Batata). Samples were taken during four hydrologic seasons at both natural and impacted sites to count virus-like particles (VLP) and bacteria. In parallel, virus-infected bacteria were identified and quantified by transmission electron microscopy (TEM). Viral abundance ranged from 0.5 × 107 ± 0.2 × 107 VLP ml−1 (high-water season, impacted site) to 1.7 × 107 ± 0.4 × 107 VLP ml−1 (low-water season, natural site). These data were strongly correlated with the bacterial abundance (r2 = 0.84; P < 0.05), which ranged from 1.0 × 106 ± 0.5 × 106 cells ml−1 (high water, impacted site) to 3.4 × 106 ± 0.7 × 106 cells ml−1 (low water, natural site). Moreover, the viral abundance was weakly correlated with chlorophyll a, suggesting that most viruses were bacteriophages. TEM quantitative analyses revealed that the frequency of visibly infected cells was 20%, with 10 ± 3 phages per cell section. In general, we found a low virus-bacterium ratio (<7). Both the close coupling between the viral and bacterial abundances and the low virus-bacterium ratio suggest that viral abundance tends to be driven by the reduction of hosts for viral infection. Our results demonstrate that viruses are controlled by biological substrates, whereas in addition to grazing, bacteria are regulated by physical processes caused by turbidity, which affect underwater light distribution and dissolved organic carbon availability. PMID:20833790

Performance of a coupled lagged ensemble weather and river runoff prediction model system for the Alpine Ammer River catchment

NASA Astrophysics Data System (ADS)

Smiatek, G.; Kunstmann, H.; Werhahn, J.

2012-04-01

The Ammer River catchment located in the Bavarian Ammergau Alps and alpine forelands, Germany, represents with elevations reaching 2185 m and annual mean precipitation between1100 and 2000 mm a very demanding test ground for a river runoff prediction system. Large flooding events in 1999 and 2005 motivated the development of a physically based prediction tool in this area. Such a tool is the coupled high resolution numerical weather and river runoff forecasting system AM-POE that is being studied in several configurations in various experiments starting from the year 2005. Corner stones of the coupled system are the hydrological water balance model WaSiM-ETH run at 100 m grid resolution, the numerical weather prediction model (NWP) MM5 driven at 3.5 km grid cell resolution and the Perl Object Environment (POE) framework. POE implements the input data download from various sources, the input data provision via SOAP based WEB services as well as the runs of the hydrology model both with observed and with NWP predicted meteorology input. The one way coupled system utilizes a lagged ensemble prediction system (EPS) taking into account combination of recent and previous NWP forecasts. Results obtained in the years 2005-2011 reveal that river runoff simulations depict high correlation with observed runoff when driven with monitored observations in hindcast experiments. The ability to runoff forecasts is depending on lead times in the lagged ensemble prediction and shows still limitations resulting from errors in timing and total amount of the predicted precipitation in the complex mountainous area. The presentation describes the system implementation, and demonstrates the application of the POE framework in networking, distributed computing and in the setup of various experiments as well as long term results of the system application in the years 2005 - 2011.

Virus-bacterium coupling driven by both turbidity and hydrodynamics in an Amazonian floodplain lake.

PubMed

Barros, Nathan; Farjalla, Vinicius F; Soares, Maria C; Melo, Rossana C N; Roland, Fábio

2010-11-01

The importance of viruses in aquatic ecosystem functioning has been widely described. However, few studies have examined tropical aquatic ecosystems. Here, we evaluated for the first time viruses and their relationship with other planktonic communities in an Amazonian freshwater ecosystem. Coupling between viruses and bacteria was studied, focusing both on hydrologic dynamics and anthropogenic forced turbidity in the system (Lake Batata). Samples were taken during four hydrologic seasons at both natural and impacted sites to count virus-like particles (VLP) and bacteria. In parallel, virus-infected bacteria were identified and quantified by transmission electron microscopy (TEM). Viral abundance ranged from 0.5 × 10⁷ ± 0.2 × 10⁷ VLP ml⁻¹ (high-water season, impacted site) to 1.7 × 10⁷ ± 0.4 × 10⁷ VLP ml⁻¹ (low-water season, natural site). These data were strongly correlated with the bacterial abundance (r² = 0.84; P < 0.05), which ranged from 1.0 × 10⁶ ± 0.5 × 10⁶ cells ml⁻¹ (high water, impacted site) to 3.4 × 10⁶ ± 0.7 × 10⁶ cells ml⁻¹ (low water, natural site). Moreover, the viral abundance was weakly correlated with chlorophyll a, suggesting that most viruses were bacteriophages. TEM quantitative analyses revealed that the frequency of visibly infected cells was 20%, with 10 ± 3 phages per cell section. In general, we found a low virus-bacterium ratio (<7). Both the close coupling between the viral and bacterial abundances and the low virus-bacterium ratio suggest that viral abundance tends to be driven by the reduction of hosts for viral infection. Our results demonstrate that viruses are controlled by biological substrates, whereas in addition to grazing, bacteria are regulated by physical processes caused by turbidity, which affect underwater light distribution and dissolved organic carbon availability.

The increasing importance of atmospheric demand in regulating ecosystem functioning

USDA-ARS?s Scientific Manuscript database

The profound effects of hydrologic stress on ecosystem productivity, water use, and mortality are driven by two variables – soil moisture supply and atmospheric demand for water. The impact of these two drivers on ecosystem processes has historically been difficult to disentangle, and often the rol...

Ensemble catchment hydrological modelling for climate change impact analysis

NASA Astrophysics Data System (ADS)

Vansteenkiste, Thomas; Ntegeka, Victor; Willems, Patrick

2014-05-01

It is vital to investigate how the hydrological model structure affects the climate change impact given that future changes not in the range for which the models were calibrated or validated are likely. Thus an ensemble modelling approach which involves a diversity of models with different structures such as spatial resolutions and process descriptions is crucial. The ensemble modelling approach was applied to a set of models: from the lumped conceptual models NAM, PDM and VHM, an intermediate detailed and distributed model WetSpa, to the highly detailed and fully distributed model MIKE-SHE. Explicit focus was given to the high and low flow extremes. All models were calibrated for sub flows and quick flows derived from rainfall and potential evapotranspiration (ETo) time series. In general, all models were able to produce reliable estimates of the flow regimes under the current climate for extreme peak and low flows. An intercomparison of the low and high flow changes under changed climatic conditions was made using climate scenarios tailored for extremes. Tailoring was important for two reasons. First, since the use of many scenarios was not feasible it was necessary to construct few scenarios that would reasonably represent the range of extreme impacts. Second, scenarios would be more informative as changes in high and low flows would be easily traced to changes of ETo and rainfall; the tailored scenarios are constructed using seasonal changes that are defined using different levels of magnitude (high, mean and low) for rainfall and ETo. After simulation of these climate scenarios in the five hydrological models, close agreement was found among the models. The different models predicted similar range of peak flow changes. For the low flows, however, the differences in the projected impact range by different hydrological models was larger, particularly for the drier scenarios. This suggests that the hydrological model structure is critical in low flow predictions, more than in high flow conditions. Hence, the mechanism of the slow flow component simulation requires further attention. It is concluded that a multi-model ensemble approach where different plausible model structures are applied, is extremely useful. It improves the reliability of climate change impact results and allows decision making to be based on uncertainty assessment that includes model structure related uncertainties. References: Ntegeka, V., Baguis, P., Roulin, E., Willems, P., 2014. Developing tailored climate change scenarios for hydrological impact assessments. Journal of Hydrology, 508C, 307-321 Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., Willems, P., De Smedt, F., Batelaan, O., 2013. Climate change impact on river flows and catchment hydrology: a comparison of two spatially distributed models. Hydrological Processes, 27(25), 3649-3662. Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., Van Steenbergen, N., De Smedt, F., Batelaan, O., Pereira, F., Willems, P., 2014. Intercomparison of five lumped and distributed models for catchment runoff and extreme flow simulation. Journal of Hydrology, in press. Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., De Smedt, F., Batelaan, O., Pereira, F., Willems, P., 2014. Intercomparison of climate scenario impact predictions by a lumped and distributed model ensemble. Journal of Hydrology, in revision.

A Distributed Hydrological model Forced by DIMP2 Data and the WRF Mesoscale model

NASA Astrophysics Data System (ADS)

Wayand, N. E.

2010-12-01

Forecasted warming over the next century will drastically reduce seasonal snowpack that provides 40% of the world’s drinking water. With increased climate warming, droughts may occur more frequently, which will increase society’s reliance on this same summer snowpack as a water supply. This study aims to reduce driving data errors that lead to poor simulations of snow ablation and accumulation, and streamflow. Results from the Distributed Hydrological Model Intercomparison Project Phase 2 (DMIP2) project using the Distributed Hydrology Soil and Vegetation Model (DHSVM) highlighted the critical need for accurate driving data that distributed models require. Currently, the meteorological driving data for distributed hydrological models commonly rely on interpolation techniques between a network of observational stations, as well as historical monthly means. This method is limited by two significant issues: snowpack is stored at high elevations, where interpolation techniques perform poorly due to sparse observations, and historic climatological means may be unsuitable in a changing climate. Mesoscale models may provide a physically-based approach to supplement surface observations over high-elevation terrain. Initial results have shown that while temperature lapse rates are well represented by multiple mesoscale models, significant precipitation biases are dependent on the particular model microphysics. We evaluate multiple methods of downscaling surface variables from the Weather and Research Forecasting (WRF) model that are then used to drive DHSVM over the North Fork American River basin in California. A comparison between each downscaled driving data set and paired DHSVM results to observations will determine how much improvement in simulated streamflow and snowpack are gained at the expense of each additional degree of downscaling. Our results from DMIP2 will be used as a benchmark for the best available DHSVM run using all available observational data. The findings presented here will help guide watershed managers of the requirements, advantages and limitations of using a distributed hydrological model coupled with various forms of forcing data over mountainous terrain.

Watershed and Economic Data InterOperability (WEDO) System

EPA Science Inventory

Hydrologic modeling is essential for environmental, economic, and human health decision-making. However, sharing of modeling studies is limited within the watershed modeling community. Distribution of hydrologic modeling research typically involves publishing summarized data in p...

Watershed and Economic Data InterOperability (WEDO) System (presentation)

EPA Science Inventory

Hydrologic modeling is essential for environmental, economic, and human health decision- making. However, sharing of modeling studies is limited within the watershed modeling community. Distribution of hydrologic modeling research typically involves publishing summarized data in ...

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.

Comparisons of Satellite Soil Moisture, an Energy Balance Model Driven by LST Data and Point Measurements

NASA Astrophysics Data System (ADS)

Laiolo, Paola; Gabellani, Simone; Rudari, Roberto; Boni, Giorgio; Puca, Silvia

2013-04-01

Soil moisture plays a fundamental role in the partitioning of mass and energy fluxes between land surface and atmosphere, thereby influencing climate and weather, and it is important in determining the rainfall-runoff response of catchments; moreover, in hydrological modelling and flood forecasting, a correct definition of moisture conditions is a key factor for accurate predictions. Different sources of information for the estimation of the soil moisture state are currently available: satellite data, point measurements and model predictions. All are affected by intrinsic uncertainty. Among different satellite sensors that can be used for soil moisture estimation three major groups can be distinguished: passive microwave sensors (e.g., SSMI), active sensors (e.g. SAR, Scatterometers), and optical sensors (e.g. Spectroradiometers). The last two families, mainly because of their temporal and spatial resolution seem the most suitable for hydrological applications In this work soil moisture point measurements from 10 sensors in the Italian territory are compared of with the satellite products both from the HSAF project SM-OBS-2, derived from the ASCAT scatterometer, and from ACHAB, an operative energy balance model that assimilate LST data derived from MSG and furnishes daily an evaporative fraction index related to soil moisture content for all the Italian region. Distributed comparison of the ACHAB and SM-OBS-2 on the whole Italian territory are performed too.

On the Fidelity of Semi-distributed Hydrologic Model Simulations for Large Scale Catchment Applications

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.; Lakshmi, V.

2017-12-01

Application of semi-distributed hydrologic modeling frameworks is a viable alternative to fully distributed hyper-resolution hydrologic models due to computational efficiency and resolving fine-scale spatial structure of hydrologic fluxes and states. However, fidelity of semi-distributed model simulations is impacted by (1) formulation of hydrologic response units (HRUs), and (2) aggregation of catchment properties for formulating simulation elements. Here, we evaluate the performance of a recently developed Soil Moisture and Runoff simulation Toolkit (SMART) for large catchment scale simulations. In SMART, topologically connected HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are equivalent cross sections (ECS) representative of a hillslope in first order sub-basins. Earlier investigations have shown that formulation of ECSs at the scale of a first order sub-basin reduces computational time significantly without compromising simulation accuracy. However, the implementation of this approach has not been fully explored for catchment scale simulations. To assess SMART performance, we set-up the model over the Little Washita watershed in Oklahoma. Model evaluations using in-situ soil moisture observations show satisfactory model performance. In addition, we evaluated the performance of a number of soil moisture disaggregation schemes recently developed to provide spatially explicit soil moisture outputs at fine scale resolution. Our results illustrate that the statistical disaggregation scheme performs significantly better than the methods based on topographic data. Future work is focused on assessing the performance of SMART using remotely sensed soil moisture observations using spatially based model evaluation metrics.

Interactions between hydrology and water chemistry shape bacterioplankton biogeography across boreal freshwater networks

PubMed Central

Niño-García, Juan Pablo; Ruiz-González, Clara; del Giorgio, Paul A

2016-01-01

Disentangling the mechanisms shaping bacterioplankton communities across freshwater ecosystems requires considering a hydrologic dimension that can influence both dispersal and local sorting, but how the environment and hydrology interact to shape the biogeography of freshwater bacterioplankton over large spatial scales remains unexplored. Using Illumina sequencing of the 16S ribosomal RNA gene, we investigate the large-scale spatial patterns of bacterioplankton across 386 freshwater systems from seven distinct regions in boreal Québec. We show that both hydrology and local water chemistry (mostly pH) interact to shape a sequential structuring of communities from highly diverse assemblages in headwater streams toward larger rivers and lakes dominated by fewer taxa. Increases in water residence time along the hydrologic continuum were accompanied by major losses of bacterial richness and by an increased differentiation of communities driven by local conditions (pH and other related variables). This suggests that hydrology and network position modulate the relative role of environmental sorting and mass effects on community assembly by determining both the time frame for bacterial growth and the composition of the immigrant pool. The apparent low dispersal limitation (that is, the lack of influence of geographic distance on the spatial patterns observed at the taxonomic resolution used) suggests that these boreal bacterioplankton communities derive from a shared bacterial pool that enters the networks through the smallest streams, largely dominated by mass effects, and that is increasingly subjected to local sorting of species during transit along the hydrologic continuum. PMID:26849312

Interactions between hydrology and water chemistry shape bacterioplankton biogeography across boreal freshwater networks.

PubMed

Niño-García, Juan Pablo; Ruiz-González, Clara; Del Giorgio, Paul A

2016-07-01

Disentangling the mechanisms shaping bacterioplankton communities across freshwater ecosystems requires considering a hydrologic dimension that can influence both dispersal and local sorting, but how the environment and hydrology interact to shape the biogeography of freshwater bacterioplankton over large spatial scales remains unexplored. Using Illumina sequencing of the 16S ribosomal RNA gene, we investigate the large-scale spatial patterns of bacterioplankton across 386 freshwater systems from seven distinct regions in boreal Québec. We show that both hydrology and local water chemistry (mostly pH) interact to shape a sequential structuring of communities from highly diverse assemblages in headwater streams toward larger rivers and lakes dominated by fewer taxa. Increases in water residence time along the hydrologic continuum were accompanied by major losses of bacterial richness and by an increased differentiation of communities driven by local conditions (pH and other related variables). This suggests that hydrology and network position modulate the relative role of environmental sorting and mass effects on community assembly by determining both the time frame for bacterial growth and the composition of the immigrant pool. The apparent low dispersal limitation (that is, the lack of influence of geographic distance on the spatial patterns observed at the taxonomic resolution used) suggests that these boreal bacterioplankton communities derive from a shared bacterial pool that enters the networks through the smallest streams, largely dominated by mass effects, and that is increasingly subjected to local sorting of species during transit along the hydrologic continuum.

A Large-Scale, High-Resolution Hydrological Model Parameter Data Set for Climate Change Impact Assessment for the Conterminous US

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

Oubeidillah, Abdoul A; Kao, Shih-Chieh; Ashfaq, Moetasim

2014-01-01

To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation- and data-intensive effort was conducted to organize a comprehensive hydrologic dataset with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation including meteorologic forcings, soil, land class, vegetation, and elevation were collected from multiple best-available data sources and organized for 2107 hydrologic subbasins (8-digit hydrologic units, HUC8s) in the conterminous United States at refined 1/24 (~4 km) spatial resolution. Using high-performance computing for intensive model calibration, a high-resolution parameter dataset was prepared for the macro-scale Variable Infiltration Capacity (VIC) hydrologic model. The VICmore » simulation was driven by DAYMET daily meteorological forcing and was calibrated against USGS WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter dataset may help reasonably simulate runoff at most US HUC8 subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the resources required for further model improvement across the entire conterminous United States. We anticipate that through this hydrologic parameter dataset, the repeated effort of fundamental data processing can be lessened, so that research efforts can emphasize the more challenging task of assessing climate change impacts. The pre-organized model parameter dataset will be provided to interested parties to support further hydro-climate impact assessment.« less

Using the hydrologic model mike she to assess disturbance impacts on watershed process and responses across the Southeastern U.S.

Treesearch

Ge Sun; Jianbiao Lu; Steven G. McNulty; James M. Vose; Devendra M. Amayta

2006-01-01

A clear understanding of the basic hydrologic processes is needed to restore and manage watersheds across the diverse physiologic gradients in the Southeastern U.S. We evaluated a physically based, spatially distributed watershed hydrologic model called MIKE SHE/MIKE 11 to evaluate disturbance impacts on water use and yield across the region. Long-term forest...

Modeling the climatic and subsurface stratigraphy controls on the hydrology of a Carolina bay wetland in South Carolina, USA

Treesearch

Ge Sun; Timothy J. Callahan; Jennifer E. Pyzoha; Carl C. Trettin

2006-01-01

Restoring depressional wetlands or geographically isolated wetlands such as cypress swamps and Carolina bays on the Atlantic Coastal Plains requires a clear understanding of the hydrologic processes and water balances. The objectives of this paper are to (1) test a distributed forest hydrology model, FLATWOODS, for a Carolina bay wetland system using seven years of...

Modeling the climatic and subsurface stratigraphy controls on the hydrology of a Carolina Bay wetland in South Carolina, USA

Treesearch

Ge Sun; Timothy J. Callahan; Jennifer E. Pyzoha; Carl C. Trettin

2006-01-01

Restoring depressional wetlands or geographically isolated wetlands such as cypress swamps and Carolina bays on the Atlantic Coastal Plains requires a clear understanding of the hydrologic processes and water balances. The objectives of this paper are to (1) test a distributed forest hydrology model, FLATWOODS, for a Carolina bay wetland system using seven years of...

Quantifying the distribution of tracer discharge from boreal catchments under transient flow using the kinematic pathway approach

NASA Astrophysics Data System (ADS)

Soltani, S. S.; Cvetkovic, V.

2017-07-01

This focuses on solute discharge from boreal catchments with relatively shallow groundwater table and topography-driven groundwater flow. We explore whether a simplified semianalytical approach can be used for predictive modeling of the statistical distribution of tracer discharge. The approach is referred to as the "kinematic pathways approach" (KPA). This approach uses hydrological and tracer inputs and topographical and hydrogeological information; the latter regards average aquifer depth to the less permeable bedrock. A characteristic velocity of water flow through the catchment is further obtained from the overall water balance in the catchment. For the waterborne tracer transport through the catchment, morphological dispersion is accounted for by topographical analysis of the distribution of pathway lengths to the catchment outlet. Macrodispersion is accounted for heuristically by assuming an effective Péclet number. Distribution of water travel times through the catchment reflect the dispersion on both levels and are derived in both a forward mode (transit time from input to outlet) and a backward mode (water age when arriving at outlet arrival). The forward distribution of water travel times is further used for the tracer discharge modeling by convolution. The approach is applied to modeling of a 23 year long chloride data series for a specific catchment Kringlan (Sweden), and for generic modeling to better understand the dependence of the tracer discharge distribution on different dispersion aspects. The KPA is found to provide reasonable estimates of tracer discharge distribution, and particularly of extreme values, depending on method for determining the pathway length distribution. As a possible alternative analytical model of tracer transport through a catchment, the reservoir approach generally results in large tracer dispersion. This implies that tracer discharge distributions obtained from a mixed reservoir approach and from KPA are only compatible under large dispersion conditions.

Hydrologic refugia, plants, and climate change.

PubMed

McLaughlin, Blair C; Ackerly, David D; Klos, P Zion; Natali, Jennifer; Dawson, Todd E; Thompson, Sally E

2017-08-01

Climate, physical landscapes, and biota interact to generate heterogeneous hydrologic conditions in space and over time, which are reflected in spatial patterns of species distributions. As these species distributions respond to rapid climate change, microrefugia may support local species persistence in the face of deteriorating climatic suitability. Recent focus on temperature as a determinant of microrefugia insufficiently accounts for the importance of hydrologic processes and changing water availability with changing climate. Where water scarcity is a major limitation now or under future climates, hydrologic microrefugia are likely to prove essential for species persistence, particularly for sessile species and plants. Zones of high relative water availability - mesic microenvironments - are generated by a wide array of hydrologic processes, and may be loosely coupled to climatic processes and therefore buffered from climate change. Here, we review the mechanisms that generate mesic microenvironments and their likely robustness in the face of climate change. We argue that mesic microenvironments will act as species-specific refugia only if the nature and space/time variability in water availability are compatible with the ecological requirements of a target species. We illustrate this argument with case studies drawn from California oak woodland ecosystems. We posit that identification of hydrologic refugia could form a cornerstone of climate-cognizant conservation strategies, but that this would require improved understanding of climate change effects on key hydrologic processes, including frequently cryptic processes such as groundwater flow. © 2017 John Wiley & Sons Ltd.

Investigating the relationship between a soils classification and the spatial parameters of a conceptual catchment-scale hydrological model

NASA Astrophysics Data System (ADS)

Dunn, S. M.; Lilly, A.

2001-10-01

There are now many examples of hydrological models that utilise the capabilities of Geographic Information Systems to generate spatially distributed predictions of behaviour. However, the spatial variability of hydrological parameters relating to distributions of soils and vegetation can be hard to establish. In this paper, the relationship between a soil hydrological classification Hydrology of Soil Types (HOST) and the spatial parameters of a conceptual catchment-scale model is investigated. A procedure involving inverse modelling using Monte-Carlo simulations on two catchments is developed to identify relative values for soil related parameters of the DIY model. The relative values determine the internal variability of hydrological processes as a function of the soil type. For three out of the four soil parameters studied, the variability between HOST classes was found to be consistent across two catchments when tested independently. Problems in identifying values for the fourth 'fast response distance' parameter have highlighted a potential limitation with the present structure of the model. The present assumption that this parameter can be related simply to soil type rather than topography appears to be inadequate. With the exclusion of this parameter, calibrated parameter sets from one catchment can be converted into equivalent parameter sets for the alternate catchment on the basis of their HOST distributions, to give a reasonable simulation of flow. Following further testing on different catchments, and modifications to the definition of the fast response distance parameter, the technique provides a methodology whereby it is possible to directly derive spatial soil parameters for new catchments.

Integrating a reservoir regulation scheme into a spatially distributed hydrological model

DOE PAGES

Zhao, Gang; Gao, Huili; Naz, Bibi S; ...

2016-10-14

During the past several decades, numerous reservoirs have been built across the world for a variety of purposes such as flood control, irrigation, municipal/industrial water supplies, and hydropower generation. Consequently, timing and magnitude of natural streamflows have been altered significantly by reservoir operations. In addition, the hydrological cycle can be modified by land-use/land-cover and climate changes. To understand the fine-scale feedback between hydrological processes and water management decisions, a distributed hydrological model embedded with a reservoir component is desired. In this study, a multi-purpose reservoir module with predefined complex operational rules was integrated into the Distributed Hydrology Soil Vegetation Modelmore » (DHSVM). Conditional operating rules, which are designed to reduce flood risk and enhance water supply reliability, were adopted in this module. The performance of the integrated model was tested over the upper Brazos River Basin in Texas, where two U.S. Army Corps of Engineers reservoirs, Lake Whitney and Aquilla Lake, are located. The integrated DHSVM was calibrated and validated using observed reservoir inflow, outflow, and storage data. The error statistics were summarized for both reservoirs on a daily, weekly, and monthly basis. Using the weekly reservoir storage for Lake Whitney as an example, the coefficient of determination (R 2) and the Nash-Sutcliff Efficiency (NSE) were 0.85 and 0.75, respectively. These results suggest that this reservoir module holds promise for use in sub-monthly hydrological simulations. Furthermore, with the new reservoir component, the DHSVM provides a platform to support adaptive water resources management under the impacts of evolving anthropogenic activities and substantial environmental changes.« less

Integrating a reservoir regulation scheme into a spatially distributed hydrological model

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

Zhao, Gang; Gao, Huili; Naz, Bibi S

During the past several decades, numerous reservoirs have been built across the world for a variety of purposes such as flood control, irrigation, municipal/industrial water supplies, and hydropower generation. Consequently, timing and magnitude of natural streamflows have been altered significantly by reservoir operations. In addition, the hydrological cycle can be modified by land-use/land-cover and climate changes. To understand the fine-scale feedback between hydrological processes and water management decisions, a distributed hydrological model embedded with a reservoir component is desired. In this study, a multi-purpose reservoir module with predefined complex operational rules was integrated into the Distributed Hydrology Soil Vegetation Modelmore » (DHSVM). Conditional operating rules, which are designed to reduce flood risk and enhance water supply reliability, were adopted in this module. The performance of the integrated model was tested over the upper Brazos River Basin in Texas, where two U.S. Army Corps of Engineers reservoirs, Lake Whitney and Aquilla Lake, are located. The integrated DHSVM was calibrated and validated using observed reservoir inflow, outflow, and storage data. The error statistics were summarized for both reservoirs on a daily, weekly, and monthly basis. Using the weekly reservoir storage for Lake Whitney as an example, the coefficient of determination (R 2) and the Nash-Sutcliff Efficiency (NSE) were 0.85 and 0.75, respectively. These results suggest that this reservoir module holds promise for use in sub-monthly hydrological simulations. Furthermore, with the new reservoir component, the DHSVM provides a platform to support adaptive water resources management under the impacts of evolving anthropogenic activities and substantial environmental changes.« less

Catchment Integration of Sensor Array Observations to Understand Hydrologic Connectivity

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

A New Multivariate Approach in Generating Ensemble Meteorological Forcings for Hydrological Forecasting

NASA Astrophysics Data System (ADS)

Khajehei, Sepideh; Moradkhani, Hamid

2015-04-01

Producing reliable and accurate hydrologic ensemble forecasts are subject to various sources of uncertainty, including meteorological forcing, initial conditions, model structure, and model parameters. Producing reliable and skillful precipitation ensemble forecasts is one approach to reduce the total uncertainty in hydrological applications. Currently, National Weather Prediction (NWP) models are developing ensemble forecasts for various temporal ranges. It is proven that raw products from NWP models are biased in mean and spread. Given the above state, there is a need for methods that are able to generate reliable ensemble forecasts for hydrological applications. One of the common techniques is to apply statistical procedures in order to generate ensemble forecast from NWP-generated single-value forecasts. The procedure is based on the bivariate probability distribution between the observation and single-value precipitation forecast. However, one of the assumptions of the current method is fitting Gaussian distribution to the marginal distributions of observed and modeled climate variable. Here, we have described and evaluated a Bayesian approach based on Copula functions to develop an ensemble precipitation forecast from the conditional distribution of single-value precipitation forecasts. Copula functions are known as the multivariate joint distribution of univariate marginal distributions, which are presented as an alternative procedure in capturing the uncertainties related to meteorological forcing. Copulas are capable of modeling the joint distribution of two variables with any level of correlation and dependency. This study is conducted over a sub-basin in the Columbia River Basin in USA using the monthly precipitation forecasts from Climate Forecast System (CFS) with 0.5x0.5 Deg. spatial resolution to reproduce the observations. The verification is conducted on a different period and the superiority of the procedure is compared with Ensemble Pre-Processor approach currently used by National Weather Service River Forecast Centers in USA.

Analysis on flood generation processes by means of a continuous simulation model

NASA Astrophysics Data System (ADS)

Fiorentino, M.; Gioia, A.; Iacobellis, V.; Manfreda, S.

2006-03-01

In the present research, we exploited a continuous hydrological simulation to investigate on key variables responsible of flood peak formation. With this purpose, a distributed hydrological model (DREAM) is used in cascade with a rainfall generator (IRP-Iterated Random Pulse) to simulate a large number of extreme events providing insight into the main controls of flood generation mechanisms. Investigated variables are those used in theoretically derived probability distribution of floods based on the concept of partial contributing area (e.g. Iacobellis and Fiorentino, 2000). The continuous simulation model is used to investigate on the hydrological losses occurring during extreme events, the variability of the source area contributing to the flood peak and its lag-time. Results suggest interesting simplification for the theoretical probability distribution of floods according to the different climatic and geomorfologic environments. The study is applied to two basins located in Southern Italy with different climatic characteristics.

Modeling Best Management Practices (BMPs) with HSPF

EPA Science Inventory

The Hydrological Simulation Program-Fortran (HSPF) is a semi-distributed watershed model, which simulates hydrology and water quality processes at user-specified spatial and temporal scales. Although HSPF is a comprehensive and highly flexible model, a number of investigators not...

A Bayesian Alternative for Multi-objective Ecohydrological Model Specification

NASA Astrophysics Data System (ADS)

Tang, Y.; Marshall, L. A.; Sharma, A.; Ajami, H.

2015-12-01

Process-based ecohydrological models combine the study of hydrological, physical, biogeochemical and ecological processes of the catchments, which are usually more complex and parametric than conceptual hydrological models. Thus, appropriate calibration objectives and model uncertainty analysis are essential for ecohydrological modeling. In recent years, Bayesian inference has become one of the most popular tools for quantifying the uncertainties in hydrological modeling with the development of Markov Chain Monte Carlo (MCMC) techniques. Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological framework. In our study, a formal Bayesian approach is implemented in an ecohydrological model which combines a hydrological model (HyMOD) and a dynamic vegetation model (DVM). Simulations focused on one objective likelihood (Streamflow/LAI) and multi-objective likelihoods (Streamflow and LAI) with different weights are compared. Uniform, weakly informative and strongly informative prior distributions are used in different simulations. The Kullback-leibler divergence (KLD) is used to measure the dis(similarity) between different priors and corresponding posterior distributions to examine the parameter sensitivity. Results show that different prior distributions can strongly influence posterior distributions for parameters, especially when the available data is limited or parameters are insensitive to the available data. We demonstrate differences in optimized parameters and uncertainty limits in different cases based on multi-objective likelihoods vs. single objective likelihoods. We also demonstrate the importance of appropriately defining the weights of objectives in multi-objective calibration according to different data types.

The Hydrologic Instrumentation Facility of the U.S. Geological Survey

USGS Publications Warehouse

Wagner, C.R.; Jeffers, Sharon

1984-01-01

The U.S. Geological Survey Water Resources Division has improved support to the agencies field offices by the consolidation of all instrumentation support services in a single facility. This facility known as the Hydrologic Instrumentation Facility (HIF) is located at the National Space Technology Laboratory, Mississippi, about 50 miles east of New Orleans, Louisiana. The HIF is responsible for design and development, testing, evaluation, procurement, warehousing, distribution and repair of a variety of specialized hydrologic instrumentation. The centralization has resulted in more efficient and effective support of the Survey 's hydrologic programs. (USGS)

Hydrological responses to dynamically and statistically downscaled climate model output

USGS Publications Warehouse

Wilby, R.L.; Hay, L.E.; Gutowski, W.J.; 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.

Detection of dominant runoff generation processes in flood frequency analysis

NASA Astrophysics Data System (ADS)

Iacobellis, Vito; Fiorentino, Mauro; Gioia, Andrea; Manfreda, Salvatore

2010-05-01

The investigation on hydrologic similarity represents one of the most exciting challenges faced by hydrologists in the last few years, in order to reduce uncertainty on flood prediction in ungauged basins (e.g., IAHS Decade on Predictions in Ungauged Basins (PUB) - Sivapalan et al., 2003). In perspective, the identification of dominant runoff generation mechanisms may provide a strategy for catchment classification and identification hydrologically omogeneous regions. In this context, we exploited the framework of theoretically derived flood probability distributions, in order to interpret the physical behavior of real basins. Recent developments on theoretically derived distributions have highlighted that in a given basin different runoff processes may coexistence and modify or affect the shape of flood distributions. The identification of dominant runoff generation mechanisms represents a key signatures of flood distributions providing an insight in hydrologic similarity. Iacobellis and Fiorentino (2000) introduced a novel distribution of flood peak annual maxima, the "IF" distribution, which exploited the variable source area concept, coupled with a runoff threshold having scaling properties. More recently, Gioia et al (2008) introduced the Two Component-IF (TCIF) distribution, generalizing the IF distribution, based on two different threshold mechanisms, associated respectively to ordinary and extraordinary events. Indeed, ordinary floods are mostly due to rainfall events exceeding a threshold infiltration rate in a small source area, while the so-called outlier events, often responsible of the high skewness of flood distributions, are triggered by severe rainfalls exceeding a threshold storage in a large portion of the basin. Within this scheme, we focused on the application of both models (IF and TCIF) over a considerable number of catchments belonging to different regions of Southern Italy. In particular, we stressed, as a case of strong general interest in the field of statistical hydrology, the role of procedures for parameters estimation and techniques for model selection in the case of nested distributions. References Gioia, A., V. Iacobellis, S. Manfreda, M. Fiorentino, Runoff thresholds in derived flood frequency distributions, Hydrol. Earth Syst. Sci., 12, 1295-1307, 2008. Iacobellis, V., and M. Fiorentino (2000), Derived distribution of floods based on the concept of partial area coverage with a climatic appeal, Water Resour. Res., 36(2), 469-482. Sivapalan, M., Takeuchi, K., Franks, S. W., Gupta, V. K., Karambiri, H., Lakshmi, V., Liang, X., McDonnell, J. J., Mendiondo, E. M., O'Connell, P. E., Oki, T., Pomeroy, J. W., Schertzer, D., Uhlenbrook, S. and Zehe, E.: IAHS Decade on Predictions in Ungauged Basins (PUB), 2003-2012: Shaping an exciting future for the hydrological sciences, Hydrol. Sci. J., 48(6), 857-880, 2003.

Assessment of the water balance over France using regionalized Turc-Pike formula

NASA Astrophysics Data System (ADS)

Le Lay, Matthieu; Garçon, Rémy; Gailhard, Joël; Garavaglia, Federico

2016-04-01

With extensive use of hydrological models over a wide range of hydro-climatic contexts, bias in hydro-climatic data may lead to unreliable models and thus hydrological forecasts and projections. This issue is particularly pregnant when considering mountainous areas with great uncertainties on precipitations, or when considering complex unconservative catchments (e.g. karstic systems). The Turc-Pike water balance formula, analogous to the classical Budyko formula, is a simple and efficient mathematical formulation relating long-term average streamflow to long-term average precipitation and potential evaporation. In this study, we propose to apply this framework to assess and eventually adjust the water-balance before calibrating an operational hydrologic model (MORDOR model). Considering a large set of 350 french catchments, the Turc-Pike formula is regionalized based on ecohydrologic criterions to handle various hydro-climatic contexts. This interannual regional model is then applied to assess the water-balance over numerous catchments and various conditions, such as karstic, snow-driven or glaciarized and even anthropized catchments. Results show that it is possible to obtain pretty realistic corrections of meteorological inputs (precipitations, temperature or potential evaporation) or hydrologic surface (or runoff). These corrections can often be confirmed a posteriori by exogenous information. Positive impacts on hydrologic model's calibration are also demonstrated. This methodology is now operational for hydrologic applications at EDF (Electricité de France, French electric utility company), and therefore applied on hundreds of catchments.

A hydrologic drying bias in water-resource impact analyses of anthropogenic climate change

USGS Publications Warehouse

Milly, Paul; Dunne, Krista A.

2017-01-01

For water-resource planning, sensitivity of freshwater availability to anthropogenic climate change (ACC) often is analyzed with “offline” hydrologic models that use precipitation and potential evapotranspiration (Ep) as inputs. Because Ep is not a climate-model output, an intermediary model of Ep must be introduced to connect the climate model to the hydrologic model. Several Ep methods are used. The suitability of each can be assessed by noting a credible Ep method for offline analyses should be able to reproduce climate models’ ACC-driven changes in actual evapotranspiration in regions and seasons of negligible water stress (Ew). We quantified this ability for seven commonly used Ep methods and for a simple proportionality with available energy (“energy-only” method). With the exception of the energy-only method, all methods tend to overestimate substantially the increase in Ep associated with ACC. In an offline hydrologic model, the Ep-change biases produce excessive increases in actual evapotranspiration (E), whether the system experiences water stress or not, and thence strong negative biases in runoff change, as compared to hydrologic fluxes in the driving climate models. The runoff biases are comparable in magnitude to the ACC-induced runoff changes themselves. These results suggest future hydrologic drying (wetting) trends likely are being systematically and substantially overestimated (underestimated) in many water-resource impact analyses.

[Gene method for inconsistent hydrological frequency calculation. 2: Diagnosis system of hydrological genes and method of hydrological moment genes with inconsistent characters].

PubMed

Xie, Ping; Zhao, Jiang Yan; Wu, Zi Yi; Sang, Yan Fang; Chen, Jie; Li, Bin Bin; Gu, Hai Ting

2018-04-01

The analysis of inconsistent hydrological series is one of the major problems that should be solved for engineering hydrological calculation in changing environment. In this study, the diffe-rences of non-consistency and non-stationarity were analyzed from the perspective of composition of hydrological series. The inconsistent hydrological phenomena were generalized into hydrological processes with inheritance, variability and evolution characteristics or regulations. Furthermore, the hydrological genes were identified following the theory of biological genes, while their inheritance bases and variability bases were determined based on composition of hydrological series under diffe-rent time scales. To identify and test the components of hydrological genes, we constructed a diagnosis system of hydrological genes. With the P-3 distribution as an example, we described the process of construction and expression of the moment genes to illustrate the inheritance, variability and evolution principles of hydrological genes. With the annual minimum 1-month runoff series of Yunjinghong station in Lancangjiang River basin as an example, we verified the feasibility and practicability of hydrological gene theory for the calculation of inconsistent hydrological frequency. The results showed that the method could be used to reveal the evolution of inconsistent hydrological series. Therefore, it provided a new research pathway for engineering hydrological calculation in changing environment and an essential reference for the assessment of water security.

Development of a coupled model of a distributed hydrological model and a rice growth model for optimizing irrigation schedule

NASA Astrophysics Data System (ADS)

Tsujimoto, Kumiko; Homma, Koki; Koike, Toshio; Ohta, Tetsu

2013-04-01

A coupled model of a distributed hydrological model and a rice growth model was developed in this study. The distributed hydrological model used in this study is the Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM) developed by Wang et al. (2009). This model includes a modified SiB2 (Simple Biosphere Model, Sellers et al., 1996) and the Geomorphology-Based Hydrological Model (GBHM) and thus it can physically calculate both water and energy fluxes. The rice growth model used in this study is the Simulation Model for Rice-Weather relations (SIMRIW) - rainfed developed by Homma et al. (2009). This is an updated version of the original SIMRIW (Horie et al., 1987) and can calculate rice growth by considering the yield reduction due to water stress. The purpose of the coupling is the integration of hydrology and crop science to develop a tool to support decision making 1) for determining the necessary agricultural water resources and 2) for allocating limited water resources to various sectors. The efficient water use and optimal water allocation in the agricultural sector are necessary to balance supply and demand of limited water resources. In addition, variations in available soil moisture are the main reasons of variations in rice yield. In our model, soil moisture and the Leaf Area Index (LAI) are calculated inside SIMRIW-rainfed so that these variables can be simulated dynamically and more precisely based on the rice than the more general calculations is the original WEB-DHM. At the same time by coupling SIMRIW-rainfed with WEB-DHM, lateral flow of soil water, increases in soil moisture and reduction of river discharge due to the irrigation, and its effects on the rice growth can be calculated. Agricultural information such as planting date, rice cultivar, fertilization amount are given in a fully distributed manner. The coupled model was validated using LAI and soil moisture in a small basin in western Cambodia (Sangker River Basin). This basin is mostly rainfed paddy so that irrigation scheme was firstly switched off. Several simulations with varying irrigation scheme were performed to determine the optimal irrigation schedule in this basin.

Extreme Hydrological Changes in the Western United States Drive Reductions in Water Supply by Mid Century

NASA Astrophysics Data System (ADS)

Pagan, Brianna; Ashfaq, Moetasim; Rastogi, Deeksha; Kao, Shih-Chieh; Naz, Bibi; Mei, Rui; Kendall, Donald; Pal, Jeremy

2016-04-01

The Western United States has a greater vulnerability to climate change impacts on water security due to a reliance on snowmelt driven imported water. The State of California, which is the most populous and agriculturally productive in the United States, depends on an extensive artificial water storage and conveyance system primarily for irrigated agriculture, municipal and industrial supply and hydropower generation. This study provides an integrated approach to assessing climate change impacts on the hydrologic cycle and hydrologic extremes for all water supplies to Southern California including the San-Joaquin River, Tulare Lake, Sacramento River, Owens Valley, Mono Lake, and Colorado River basins. A 10-member ensemble of coupled global climate models is dynamically downscaled forcing a regional and hydrological model resulting in a high-resolution 4-km output for the region. Greenhouse gas concentrations are prescribed according to historical values for the present-day (1965-2005) and the IPCC Representative Concentration Pathway 8.5 for the near to mid term future (2010-2050). While precipitation is projected to remain the same or slightly increase, rising temperatures result in a shift in precipitation type towards more rainfall, reducing cold season snowpack and earlier snowmelt. Associated with these hydrological changes are substantial increases in both dry and flood event frequency and intensity, which are evaluated by using the Generalized Extreme Value distribution, Standardized Precipitation Index and ratio of daily precipitation to annual precipitation. Daily annual maximum runoff and precipitation event events significantly increase in intensity and frequency. Return periods change such that extreme events in the future become much more common by mid-century. The largest changes occur in the Colorado River where the daily annual maximum runoff 100-year event, for example, becomes approximately ten times more likely and twice as likely in the other basins. Volumes for annual cumulative maximum runoff increase and in contrast decrease for annual cumulative minimum runoff. Intuitively, increased frequency of years with below historical average runoff put further strain on water supply. However, the escalating likelihood of runoff occurring earlier in the year and in significantly higher amounts poses a substantial flood control risk requiring the release of water from reservoirs, also potentially decreasing water availability. Significant reductions in snowpack and increases in extreme runoff necessitate additional multiyear storage solutions for urban and agricultural regions in the Western United States.

An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios

NASA Astrophysics Data System (ADS)

Addor, N.; Jaun, S.; Fundel, F.; Zappa, M.

2011-07-01

The Sihl River flows through Zurich, Switzerland's most populated city, for which it represents the largest flood threat. To anticipate extreme discharge events and provide decision support in case of flood risk, a hydrometeorological ensemble prediction system (HEPS) was launched operationally in 2008. This model chain relies on limited-area atmospheric forecasts provided by the deterministic model COSMO-7 and the probabilistic model COSMO-LEPS. These atmospheric forecasts are used to force a semi-distributed hydrological model (PREVAH), coupled to a hydraulic model (FLORIS). The resulting hydrological forecasts are eventually communicated to the stakeholders involved in the Sihl discharge management. This fully operational setting provides a real framework with which to compare the potential of deterministic and probabilistic discharge forecasts for flood mitigation. To study the suitability of HEPS for small-scale basins and to quantify the added-value conveyed by the probability information, a reforecast was made for the period June 2007 to December 2009 for the Sihl catchment (336 km2). Several metrics support the conclusion that the performance gain can be of up to 2 days lead time for the catchment considered. Brier skill scores show that overall COSMO-LEPS-based hydrological forecasts outperforms their COSMO-7-based counterparts for all the lead times and event intensities considered. The small size of the Sihl catchment does not prevent skillful discharge forecasts, but makes them particularly dependent on correct precipitation forecasts, as shown by comparisons with a reference run driven by observed meteorological parameters. Our evaluation stresses that the capacity of the model to provide confident and reliable mid-term probability forecasts for high discharges is limited. The two most intense events of the study period are investigated utilising a novel graphical representation of probability forecasts, and are used to generate high discharge scenarios. They highlight challenges for making decisions on the basis of hydrological predictions, and indicate the need for a tool to be used in addition to forecasts to compare the different mitigation actions possible in the Sihl catchment. No definitive conclusion on the model chain capacity to forecast flooding events endangering the city of Zurich could be drawn because of the under-sampling of extreme events. Further research on the form of the reforecasts needed to infer on floods associated to return periods of several decades, centuries, is encouraged.

The origin of high and low flows in the river Rhine: particle tracing and water quality calculations in a distributed hydrological model

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Simultaneous abrupt shifts in hydrology and fish assemblage structure in a floodplain lake in the central Amazon

PubMed Central

Röpke, Cristhiana P.; Amadio, Sidinéia; Zuanon, Jansen; Ferreira, Efrem J. G.; Deus, Cláudia Pereira de; Pires, Tiago H. S.; Winemiller, Kirk O.

2017-01-01

Combined effects of climate change and deforestation have altered precipitation patterns in the Amazon. This has led to changes in the frequency of extreme events of flood and drought in recent decades and in the magnitude of the annual flood pulse, a phenomenon that influences virtually all aspects of river-floodplain ecosystem dynamics. Analysis of long-term data revealed abrupt and synchronous changes in hydrology and fish assemblage structure of a floodplain lake near the confluence of Amazon and Negro rivers. After an intense drought in 2005, the assemblage assumed a different and fairly persistent taxonomic composition and functional structure. Declines in abundance after 2005 were more pronounced for species of all sizes having equilibrium life history strategy, large species with periodic life history strategy, and for all trophic levels except primary consumers. Our results suggest that the extreme drought triggered changes in the fish assemblage and subsequent anomalous hydrological conditions have hampered assemblage recovery. These findings stress the need to account for climatic-driven hydrological changes in conservation efforts addressing aquatic biodiversity and fishery resources in the central Amazon. PMID:28071701

Real-Time Mapping alert system; user's manual

USGS Publications Warehouse

Torres, L.A.

1996-01-01

The U.S. Geological Survey has an extensive hydrologic network that records and transmits precipitation, stage, discharge, and other water- related data on a real-time basis to an automated data processing system. Data values are recorded on electronic data collection platforms at field monitoring sites. These values are transmitted by means of orbiting satellites to receiving ground stations, and by way of telecommunication lines to a U.S. Geological Survey office where they are processed on a computer system. Data that exceed predefined thresholds are identified as alert values. These alert values can help keep water- resource specialists informed of current hydrologic conditions. The current alert status at monitoring sites is of critical importance during floods, hurricanes, and other extreme hydrologic events where quick analysis of the situation is needed. This manual provides instructions for using the Real-Time Mapping software, a series of computer programs developed by the U.S. Geological Survey for quick analysis of hydrologic conditions, and guides users through a basic interactive session. The software provides interactive graphics display and query of real-time information in a map-based, menu-driven environment.

Simultaneous abrupt shifts in hydrology and fish assemblage structure in a floodplain lake in the central Amazon.

PubMed

Röpke, Cristhiana P; Amadio, Sidinéia; Zuanon, Jansen; Ferreira, Efrem J G; Deus, Cláudia Pereira de; Pires, Tiago H S; Winemiller, Kirk O

2017-01-10

Combined effects of climate change and deforestation have altered precipitation patterns in the Amazon. This has led to changes in the frequency of extreme events of flood and drought in recent decades and in the magnitude of the annual flood pulse, a phenomenon that influences virtually all aspects of river-floodplain ecosystem dynamics. Analysis of long-term data revealed abrupt and synchronous changes in hydrology and fish assemblage structure of a floodplain lake near the confluence of Amazon and Negro rivers. After an intense drought in 2005, the assemblage assumed a different and fairly persistent taxonomic composition and functional structure. Declines in abundance after 2005 were more pronounced for species of all sizes having equilibrium life history strategy, large species with periodic life history strategy, and for all trophic levels except primary consumers. Our results suggest that the extreme drought triggered changes in the fish assemblage and subsequent anomalous hydrological conditions have hampered assemblage recovery. These findings stress the need to account for climatic-driven hydrological changes in conservation efforts addressing aquatic biodiversity and fishery resources in the central Amazon.

Developing of Watershed Radionuclide Transport Model DHSVM-R as Modification and Extension of Distributed Hydrological and Sediment Dynamics Model DHSVM

NASA Astrophysics Data System (ADS)

Zheleznyak, M.; Kivva, S.; Onda, Y.; Nanba, K.; Wakiyama, Y.; Konoplev, A.

2015-12-01

The reliable modeling tools for prediction wash - off radionuclides from watersheds are needed as for assessment the consequences of accidental and industrial releases of radionuclides, as for soil erosion studies using the radioactive tracers. The distributed model of radionuclide transport through watershed in exchangeable and nonexchangeable forms in solute and with sediments was developed and validated for small Chernobyl watersheds in 90th within EU SPARTACUS project (van der Perk et al., 1996). New tendency is coupling of radionuclide transport models and the widely validated hydrological distributed models. To develop radionuclide transport model DHSVM-R the open source Distributed Hydrology Soil Vegetation Model -DHSVM http://www.hydro.washington.edu/Lettenmaier/Models/DHSVM was modified and extended. The main changes provided in the hydrological and sediment transport modules of DHSVM are as follows: Morel-Seytoux infiltration model is added; four-directions schematization for the model's cells flows (D4) is replaced by D8 approach; the finite-difference schemes for solution of kinematic wave equations for overland water flow, stream net flow, and sediment transport are replaced by new computationally efficient scheme. New radionuclide transport module, coupled with hydrological and sediment transport modules, continues SPARTACUS's approach, - it describes radionuclide wash-off from watershed and transport via stream network in soluble phase and on suspended sediments. The hydrological module of DHSVM-R was calibrated and validated for the watersheds of Ukrainian Carpathian mountains and for the subwatersheds of Niida river flowing 137Cs in solute and with suspended sediments to Pacific Ocean at 30 km north of the Fukushima Daiichi NPP. The modules of radionuclide and sediment transport were calibrated and validated versus experimental data for USLE experimental plots in Fukushima Prefecture and versus monitoring data collected in Niida watershed. The role of sediment transport in radionuclide wash-off from mountain and lowland watersheds is analyzed in comparison of modeling results for Chernobyl and Fukushima watersheds.

Coupling a distributed hydrological model with detailed forest structural information for large-scale global change impact assessment

NASA Astrophysics Data System (ADS)

Eisner, Stephanie; Huang, Shaochun; Majasalmi, Titta; Bright, Ryan; Astrup, Rasmus; Beldring, Stein

2017-04-01

Forests are recognized for their decisive effect on landscape water balance with structural forest characteristics as stand density or species composition determining energy partitioning and dominant flow paths. However, spatial and temporal variability in forest structure is often poorly represented in hydrological modeling frameworks, in particular in regional to large scale hydrological modeling and impact analysis. As a common practice, prescribed land cover classes (including different generic forest types) are linked to parameter values derived from literature, or parameters are determined by calibration. While national forest inventory (NFI) data provide comprehensive, detailed information on hydrologically relevant forest characteristics, their potential to inform hydrological simulation over larger spatial domains is rarely exploited. In this study we present a modeling framework that couples the distributed hydrological model HBV with forest structural information derived from the Norwegian NFI and multi-source remote sensing data. The modeling framework, set up for the entire of continental Norway at 1 km spatial resolution, is explicitly designed to study the combined and isolated impacts of climate change, forest management and land use change on hydrological fluxes. We use a forest classification system based on forest structure rather than biomes which allows to implicitly account for impacts of forest management on forest structural attributes. In the hydrological model, different forest classes are represented by three parameters: leaf area index (LAI), mean tree height and surface albedo. Seasonal cycles of LAI and surface albedo are dynamically simulated to make the framework applicable under climate change conditions. Based on a hindcast for the pilot regions Nord-Trøndelag and Sør-Trøndelag, we show how forest management has affected regional hydrological fluxes during the second half of the 20th century as contrasted to climate variability.

Quantifying Direct and Indirect Impact of Future Climate on Sub-Arctic Hydrology

NASA Astrophysics Data System (ADS)

Endalamaw, A. M.; Bolton, W. R.; Young-Robertson, J. M.; Morton, D.; Hinzman, L. D.

2016-12-01

Projected future climate will have a significant impact on the hydrology of interior Alaskan sub-arctic watersheds, directly though the changes in precipitation and temperature patterns, and indirectly through the cryospheric and ecological impacts. Although the latter is the dominant factor controlling the hydrological processes in the interior Alaska sub-arctic, it is often overlooked in many climate change impact studies. In this study, we aim to quantify and compare the direct and indirect impact of the projected future climate on the hydrology of the interior Alaskan sub-arctic watersheds. The Variable Infiltration Capacity (VIC) meso-scale hydrological model will be implemented to simulate the hydrological processes, including runoff, evapotranspiration, and soil moisture dynamics in the Chena River Basin (area = 5400km2), located in the interior Alaska sub-arctic region. Permafrost and vegetation distribution will be derived from the Geophysical Institute Permafrost Lab (GIPL) model and the Lund-Potsdam-Jena Dynamic Global Model (LPJ) model, respectively. All models will be calibrated and validated using historical data. The Scenario Network for Alaskan and Arctic Planning (SNAP) 5-model average projected climate data products will be used as forcing data for each of these models. The direct impact of climate change on hydrology is estimated using surface parameterization derived from the present day permafrost and vegetation distribution, and future climate forcing from SNAP projected climate data products. Along with the projected future climate, outputs of GIPL and LPJ will be incorporated into the VIC model to estimate the indirect and overall impact of future climate on the hydrology processes in the interior Alaskan sub-arctic watersheds. Finally, we will present the potential hydrological and ecological changes by the end of the 21st century.

Integrated modeling of storm drain and natural channel networks for real-time flash flood forecasting in large urban areas

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

High spatiotemporal resolution monitoring of hydrological function across degraded peatlands in the south west UK.

NASA Astrophysics Data System (ADS)

Ashe, Josie; Luscombe, David; Grand-Clement, Emilie; Gatis, Naomi; Anderson, Karen; Brazier, Richard

2014-05-01

The Exmoor/Dartmoor Mires Project is a peatland restoration programme focused on the geoclimatically marginal blanket bogs of South West England. In order to better understand the hydrological functioning of degraded/restored peatlands and support land management decisions across these uplands, this study is providing robust spatially distributed, hydrological monitoring at a high temporal resolution and in near real time. This paper presents the conceptual framework and experimental design for three hydrological monitoring arrays situated in headwater catchments dominated by eroding and drained blanket peatland. Over 250 individual measurements are collected at a high temporal resolution (15 minute time-step) via sensors integrated within a remote telemetry system. These are sent directly to a dedicated server over VHF and GPRS mobile networks. Sensors arrays are distributed at varying spatial scales throughout the studied catchments and record multiple parameters including: water table depth, channel flow, temperature, conductivity and pH measurements. A full suite of meteorological sensors and ten spatially distributed automatic flow based water samplers are also connected to the telemetry system and controlled remotely. This paper will highlight the challenges and solutions to obtaining these data in exceptionally remote and harsh field conditions over long (multi annual) temporal scales.

Using the SWAT model to improve process descriptions and define hydrologic partitioning in South Korea

NASA Astrophysics Data System (ADS)

Shope, C. L.; Maharjan, G. R.; Tenhunen, J.; Seo, B.; Kim, K.; Riley, J.; Arnhold, S.; Koellner, T.; Ok, Y. S.; Peiffer, S.; Kim, B.; Park, J.-H.; Huwe, B.

2014-02-01

Watershed-scale modeling can be a valuable tool to aid in quantification of water quality and yield; however, several challenges remain. In many watersheds, it is difficult to adequately quantify hydrologic partitioning. Data scarcity is prevalent, accuracy of spatially distributed meteorology is difficult to quantify, forest encroachment and land use issues are common, and surface water and groundwater abstractions substantially modify watershed-based processes. Our objective is to assess the capability of the Soil and Water Assessment Tool (SWAT) model to capture event-based and long-term monsoonal rainfall-runoff processes in complex mountainous terrain. To accomplish this, we developed a unique quality-control, gap-filling algorithm for interpolation of high-frequency meteorological data. We used a novel multi-location, multi-optimization calibration technique to improve estimations of catchment-wide hydrologic partitioning. The interdisciplinary model was calibrated to a unique combination of statistical, hydrologic, and plant growth metrics. Our results indicate scale-dependent sensitivity of hydrologic partitioning and substantial influence of engineered features. The addition of hydrologic and plant growth objective functions identified the importance of culverts in catchment-wide flow distribution. While this study shows the challenges of applying the SWAT model to complex terrain and extreme environments; by incorporating anthropogenic features into modeling scenarios, we can enhance our understanding of the hydroecological impact.

Knowledge discovery from high-frequency stream nitrate concentrations: hydrology and biology contributions.

PubMed

Aubert, Alice H; Thrun, Michael C; Breuer, Lutz; Ultsch, Alfred

2016-08-30

High-frequency, in-situ monitoring provides large environmental datasets. These datasets will likely bring new insights in landscape functioning and process scale understanding. However, tailoring data analysis methods is necessary. Here, we detach our analysis from the usual temporal analysis performed in hydrology to determine if it is possible to infer general rules regarding hydrochemistry from available large datasets. We combined a 2-year in-stream nitrate concentration time series (time resolution of 15 min) with concurrent hydrological, meteorological and soil moisture data. We removed the low-frequency variations through low-pass filtering, which suppressed seasonality. We then analyzed the high-frequency variability component using Pareto Density Estimation, which to our knowledge has not been applied to hydrology. The resulting distribution of nitrate concentrations revealed three normally distributed modes: low, medium and high. Studying the environmental conditions for each mode revealed the main control of nitrate concentration: the saturation state of the riparian zone. We found low nitrate concentrations under conditions of hydrological connectivity and dominant denitrifying biological processes, and we found high nitrate concentrations under hydrological recession conditions and dominant nitrifying biological processes. These results generalize our understanding of hydro-biogeochemical nitrate flux controls and bring useful information to the development of nitrogen process-based models at the landscape scale.

Multi-objective Calibration of DHSVM Based on Hydrologic Key Elements in Jinhua River Basin, East China

NASA Astrophysics Data System (ADS)

Pan, S.; Liu, L.; Xu, Y. P.

2017-12-01

Abstract: In physically based distributed hydrological model, large number of parameters, representing spatial heterogeneity of watershed and various processes in hydrologic cycle, are involved. For lack of calibration module in Distributed Hydrology Soil Vegetation Model, this study developed a multi-objective calibration module using Epsilon-Dominance Non-Dominated Sorted Genetic Algorithm II (ɛ-NSGAII) and based on parallel computing of Linux cluster for DHSVM (ɛP-DHSVM). In this study, two hydrologic key elements (i.e., runoff and evapotranspiration) are used as objectives in multi-objective calibration of model. MODIS evapotranspiration obtained by SEBAL is adopted to fill the gap of lack of observation for evapotranspiration. The results show that good performance of runoff simulation in single objective calibration cannot ensure good simulation performance of other hydrologic key elements. Self-developed ɛP-DHSVM model can make multi-objective calibration more efficiently and effectively. The running speed can be increased by more than 20-30 times via applying ɛP-DHSVM. In addition, runoff and evapotranspiration can be simulated very well simultaneously by ɛP-DHSVM, with superior values for two efficiency coefficients (0.74 for NS of runoff and 0.79 for NS of evapotranspiration, -10.5% and -8.6% for PBIAS of runoff and evapotranspiration respectively).

Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain

NASA Astrophysics Data System (ADS)

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

2013-03-01

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

Community ecology, climate change and ecohydrology in desert grassland and shrubland

Treesearch

Mathew Daniel Petrie

2014-01-01

This dissertation explores the climate, ecology and hydrology of Chihuahuan Desert ecosystems in the context of global climate change. In coming decades, the southwestern United States is projected to experience greater temperature-driven aridity, possible small decreases in annual precipitation, and a later onset of summer monsoon rainfall. These changes may have...

Predictability and Quantification of Complex Groundwater Table Dynamics Driven by Irregular Surface Water Fluctuations

NASA Astrophysics Data System (ADS)

Xin, Pei; Wang, Shen S. J.; Shen, Chengji; Zhang, Zeyu; Lu, Chunhui; Li, Ling

2018-03-01

Shallow groundwater interacts strongly with surface water across a quarter of global land area, affecting significantly the terrestrial eco-hydrology and biogeochemistry. We examined groundwater behavior subjected to unimodal impulse and irregular surface water fluctuations, combining physical experiments, numerical simulations, and functional data analysis. Both the experiments and numerical simulations demonstrated a damped and delayed response of groundwater table to surface water fluctuations. To quantify this hysteretic shallow groundwater behavior, we developed a regression model with the Gamma distribution functions adopted to account for the dependence of groundwater behavior on antecedent surface water conditions. The regression model fits and predicts well the groundwater table oscillations resulting from propagation of irregular surface water fluctuations in both laboratory and large-scale aquifers. The coefficients of the Gamma distribution function vary spatially, reflecting the hysteresis effect associated with increased amplitude damping and delay as the fluctuation propagates. The regression model, in a relatively simple functional form, has demonstrated its capacity of reproducing high-order nonlinear effects that underpin the surface water and groundwater interactions. The finding has important implications for understanding and predicting shallow groundwater behavior and associated biogeochemical processes, and will contribute broadly to studies of groundwater-dependent ecology and biogeochemistry.

Operational Precipitation prediction in Support of Real-Time Flash Flood Prediction and Reservoir Management

NASA Astrophysics Data System (ADS)

Georgakakos, K. P.

2006-05-01

The presentation will outline the implementation and performance evaluation of a number of national and international projects pertaining to operational precipitation estimation and prediction in the context of hydrologic warning systems and reservoir management support. In all cases, uncertainty measures of the estimates and predictions are an integral part of the precipitation models. Outstanding research issues whose resolution is likely to lead to improvements in the operational environment are presented. The presentation draws from the experience of the Hydrologic Research Center (http://www.hrc-lab.org) prototype implementation projects at the Panama Canal, Central America, Northern California, and South-Central US. References: Carpenter, T.M, and K.P. Georgakakos, "Discretization Scale Dependencies of the Ensemble Flow Range versus Catchment Area Relationship in Distributed Hydrologic Modeling," Journal of Hydrology, 2006, in press. Carpenter, T.M., and K.P. Georgakakos, "Impacts of Parametric and Radar Rainfall Uncertainty on the Ensemble Streamflow Simulations of a Distributed Hydrologic Model," Journal of Hydrology, 298, 202-221, 2004. Georgakakos, K.P., Graham, N.E., Carpenter, T.M., Georgakakos, A.P., and H. Yao, "Integrating Climate- Hydrology Forecasts and Multi-Objective Reservoir Management in Northern California," EOS, 86(12), 122,127, 2005. Georgakakos, K.P., and J.A. Sperfslage, "Operational Rainfall and Flow Forecasting for the Panama Canal Watershed," in The Rio Chagres: A Multidisciplinary Profile of a Tropical Watershed, R.S. Harmon, ed., Kluwer Academic Publishers, The Netherlands, Chapter 16, 323-334, 2005. Georgakakos, K. P., "Analytical results for operational flash flood guidance," Journal of Hydrology, doi:10.1016/j.jhydrol.2005.05.009, 2005.

ENSO and hydrologic extremes in the western United States

USGS Publications Warehouse

Cayan, D.R.; Redmond, K.T.; Riddle, L.G.

1999-01-01

Frequency distributions of daily precipitation in winter and daily stream flow from late winter to early summer, at several hundred sites in the western United States, exhibit strong and systematic responses to the two phases of ENSO. Most of the stream flows considered are driven by snowmelt. The Southern Oscillation index (SOI) is used as the ENSO phase indicator. Both modest (median) and larger (90th percentile) events were considered. In years with negative SOI values (El Nino), days with high daily precipitation and stream flow are more frequent than average over the Southwest and less frequent over the Northwest. During years with positive SOI values (La Nina), a nearly opposite pattern is seen. A more pronounced increase is seen in the number of days exceeding climatological 90th percentile values than in the number exceeding climatological 50th percentile values, for both precipitation and stream flow. Stream flow responses to ENSO extremes are accentuated over precipitation responses. Evidence suggests that the mechanism for this amplification involves ENSO-phase differences in the persistence and duration of wet episodes, affecting the efficiency of the process by which precipitation is converted to runoff. The SOI leads the precipitation events by several months, and hydrologic lags (mostly through snowmelt) dealy the stream flow response by several more months. The combined 6-12 month predictive aspect of this relationship should be of significant benefit in responding to flood (or drought) risk and in improving overall water management in the western states.Frequency distributions of daily precipitation in winter and daily stream flow from late winter to early summer, at several hundred sites in the western United States, exhibit strong and systematic responses to the two phases of ENSO. Most of the stream flows considered are driven by snowmelt. The Southern Oscillation index (SOI) is used as the ENSO phase indicator. Both modest (median) and larger (90th percentile) events were considered. In years with negative SOI values (El Nino), days with high daily precipitation and stream flow are more frequent than average over the Southwest and less frequent over the Northwest. During years with positive SOI values (La Nina), a nearly opposite pattern is seen. A more pronounced increase is seen in the number of days exceeding climatological 90th percentile values than in the number exceeding climatological 50th percentile values, for both precipitation and stream flow. Stream flow responses to ENSO extremes are accentuated over precipitation responses. Evidence suggests that the mechanism for this amplification involves ENSO-phase differences in the persistence and duration of wet episodes, affecting the efficiency of the process by which precipitation is converted to runoff. The SOI leads the precipitation events by several months, and hydrologic lags (mostly through snowmelt) delay the stream flow response by several more months. The combined 6-12-month predictive aspect of this relationship should be of significant benefit in responding to flood (or drought) risk and in improving overall water management in the western states.

[Research progress on hydrological scaling].

PubMed

Liu, Jianmei; Pei, Tiefan

2003-12-01

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

Flood frequency approach in a Mediterranean Flash Flood basin. A case study in the Besòs catchment

NASA Astrophysics Data System (ADS)

Velasco, D.; Zanon, F.; Corral, C.; Sempere-Torres, D.; Borga, M.

2009-04-01

Flash floods are one of the most devastating natural disasters in the Mediterranean areas. In particular, the region of Catalonia (North-East Spain) is one of the most affected by flash floods in the Iberian Peninsula. The high rainfall intensities generating these events, the specific terrain characteristics giving rise to very fast hydrological responses and the high variability in space and time of both rain and land surface, are the main features of FF and also the main cause of their extreme complexity. Distributed hydrological models have been developed to increase the flow forecast resolution in order to implement effective operational warning systems. Some studies have shown how the distributed-models accuracy is highly sensitive to reduced computational grid scale, so, hydrological model uncertainties must be studied. In these conditions, an estimation of the modeling uncertainty (whatever the accuracy is) becomes highly valuable information to enhance our ability to predict the occurrence of flash flooding. The statistical-distributed modeling approach (Reed, 2004) is proposed in the present study to simulate floods on a small basin and account for hydrologic modeling uncertainty. The Besòs catchment (1020 km2), near Barcelona, has been selected in this study to apply the proposed flood frequency methodology. Hydrometeorological data is available for 11 rain-gauges and 6 streamflow gauges in the last 12 years, and a total of 9 flood events have been identified and analyzed in this study. The DiCHiTop hydrological model (Corral, 2004) was developed to fit operational requirements in the Besòs catchment: distributed, robust and easy to implement. It is a grid-based model that works at a given resolution (here at 1 × 1 km2, the hydrological cell), defining a simplified drainage system at this scale. A loss function is applied at the hydrological cell resolution, provided by a coupled storage model between the SCS model (Mockus, 1957) in urban areas and Topmodel (Beven & Kirkby, 1979) in rural and forested areas. The distributed hydrological model is calibrated using observed streamflow information from the available events. Simulated peak discharges are then compared to observed discharges in these gauged cells, so the relative forecast errors are estimated for all the events. Flood frequency is introduced in the analysis in order to derive probability functions for relative flow error. The next step consists in the extension of the flood frequency error patterns to the corresponding subbasins so it is possible to characterize the accuracy of the simulation in the uncalibrated cells (typically ungaged basins). As a result, the operational flood simulation at every cell in the Besos catchment can be checked and validated (in a first approach) in terms of occurrence. Thus, the distributed warning system can take advantage of the modeling uncertainties for operational tasks.

Student-Centered Modules to Support Active Learning in Hydrology: Development Experiences and Users' Perspectives

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Habib, E. H.; Deshotel, M.; Merck, M. F.; Lall, U.; Farnham, D. J.

2016-12-01

Traditional approaches to undergraduate hydrology and water resource education are textbook based, adopt unit processes and rely on idealized examples of specific applications, rather than examining the contextual relations in the processes and the dynamics connecting climate and ecosystems. The overarching goal of this project is to address the needed paradigm shift in undergraduate education of engineering hydrology and water resources education to reflect parallel advances in hydrologic research and technology, mainly in the areas of new observational settings, data and modeling resources and web-based technologies. This study presents efforts to develop a set of learning modules that are case-based, data and simulation driven and delivered via a web user interface. The modules are based on real-world case studies from three regional hydrologic settings: Coastal Louisiana, Utah Rocky Mountains and Florida Everglades. These three systems provide unique learning opportunities on topics such as: regional-scale budget analysis, hydrologic effects of human and natural changes, flashflood protection, climate-hydrology teleconnections and water resource management scenarios. The technical design and contents of the modules aim to support students' ability for transforming their learning outcomes and skills to hydrologic systems other than those used by the specific activity. To promote active learning, the modules take students through a set of highly engaging learning activities that are based on analysis of hydrologic data and model simulations. The modules include user support in the form of feedback and self-assessment mechanisms that are integrated within the online modules. Module effectiveness is assessed through an improvement-focused evaluation model using a mixed-method research approach guiding collection and analysis of evaluation data. Both qualitative and quantitative data are collected through student learning data, product analysis, and staff interviews. The presentation shares with the audience lessons learned from the development and implementation of the modules, students' feedback, guidelines on design and content attributes that support active learning in hydrology, and challenges encountered during the class implementation and evaluation of the modules.

Hydrologic Model Selection using Markov chain Monte Carlo methods

NASA Astrophysics Data System (ADS)

Marshall, L.; Sharma, A.; Nott, D.

2002-12-01

Estimation of parameter uncertainty (and in turn model uncertainty) allows assessment of the risk in likely applications of hydrological models. Bayesian statistical inference provides an ideal means of assessing parameter uncertainty whereby prior knowledge about the parameter is combined with information from the available data to produce a probability distribution (the posterior distribution) that describes uncertainty about the parameter and serves as a basis for selecting appropriate values for use in modelling applications. Widespread use of Bayesian techniques in hydrology has been hindered by difficulties in summarizing and exploring the posterior distribution. These difficulties have been largely overcome by recent advances in Markov chain Monte Carlo (MCMC) methods that involve random sampling of the posterior distribution. This study presents an adaptive MCMC sampling algorithm which has characteristics that are well suited to model parameters with a high degree of correlation and interdependence, as is often evident in hydrological models. The MCMC sampling technique is used to compare six alternative configurations of a commonly used conceptual rainfall-runoff model, the Australian Water Balance Model (AWBM), using 11 years of daily rainfall runoff data from the Bass river catchment in Australia. The alternative configurations considered fall into two classes - those that consider model errors to be independent of prior values, and those that model the errors as an autoregressive process. Each such class consists of three formulations that represent increasing levels of complexity (and parameterisation) of the original model structure. The results from this study point both to the importance of using Bayesian approaches in evaluating model performance, as well as the simplicity of the MCMC sampling framework that has the ability to bring such approaches within the reach of the applied hydrological community.

Stochastic Residual-Error Analysis For Estimating Hydrologic Model Predictive Uncertainty

EPA Science Inventory

A hybrid time series-nonparametric sampling approach, referred to herein as semiparametric, is presented for the estimation of model predictive uncertainty. The methodology is a two-step procedure whereby a distributed hydrologic model is first calibrated, then followed by brute ...

How does spatial variability of climate affect catchment streamflow predictions?

EPA Science Inventory

Spatial variability of climate can negatively affect catchment streamflow predictions if it is not explicitly accounted for in hydrologic models. In this paper, we examine the changes in streamflow predictability when a hydrologic model is run with spatially variable (distribute...

Watershed analysis of the Salmon River watershed, Washington : hydrology

USGS Publications Warehouse

Bidlake, William R.

2003-01-01

The U.S. Geological Survey analyzed selected hydrologic conditions as part of a watershed analysis of the Salmon River watershed, Washington, conducted by the Quinault Indian Nation. The selected hydrologic conditions were analyzed according to a framework of hydrologic key questions that were identified for the watershed. The key questions were posed to better understand the natural, physical, and biological features of the watershed that control hydrologic responses; to better understand current streamflow characteristics, including peak and low flows; to describe any evidence that forest harvesting and road construction have altered frequency and magnitude of peak and low flows within the watershed; to describe what is currently known about the distribution and extent of wetlands and any impacts of land management activities on wetlands; and to describe how hydrologic monitoring within the watershed might help to detect future hydrologic change, to preserve critical ecosystem functions, and to protect public and private property.

[Gene method for inconsistent hydrological frequency calculation. I: Inheritance, variability and evolution principles of hydrological genes].

PubMed

Xie, Ping; Wu, Zi Yi; Zhao, Jiang Yan; Sang, Yan Fang; Chen, Jie

2018-04-01

A stochastic hydrological process is influenced by both stochastic and deterministic factors. A hydrological time series contains not only pure random components reflecting its inheri-tance characteristics, but also deterministic components reflecting variability characteristics, such as jump, trend, period, and stochastic dependence. As a result, the stochastic hydrological process presents complicated evolution phenomena and rules. To better understand these complicated phenomena and rules, this study described the inheritance and variability characteristics of an inconsistent hydrological series from two aspects: stochastic process simulation and time series analysis. In addition, several frequency analysis approaches for inconsistent time series were compared to reveal the main problems in inconsistency study. Then, we proposed a new concept of hydrological genes origined from biological genes to describe the inconsistent hydrolocal processes. The hydrologi-cal genes were constructed using moments methods, such as general moments, weight function moments, probability weight moments and L-moments. Meanwhile, the five components, including jump, trend, periodic, dependence and pure random components, of a stochastic hydrological process were defined as five hydrological bases. With this method, the inheritance and variability of inconsistent hydrological time series were synthetically considered and the inheritance, variability and evolution principles were fully described. Our study would contribute to reveal the inheritance, variability and evolution principles in probability distribution of hydrological elements.

Toward Global Real Time Hydrologic Modeling - An "Open" View From the Trenches

NASA Astrophysics Data System (ADS)

Nelson, J.

2015-12-01

Big Data has become a popular term to describe the exponential growth of data and related cyber infrastructure to process it so that better analysis can be performed and lead to improved decision-making. How are we doing in the hydrologic sciences? As part of a significant collaborative effort that brought together scientists from public, private, and academic organizations a new transformative hydrologic forecasting modeling infrastructure has been developed. How was it possible to go from deterministic hydrologic forecasts largely driven through manual interactions at 3600 stations to automated 15-day ensemble forecasts at 2.67 million stations? Earth observations of precipitation, temperature, moisture, and other atmospheric and land surface conditions form the foundation of global hydrologic forecasts, but this project demonstrates a critical component to harness these resources can be summed up in one word: OPEN. Whether it is open data sources, open software solutions with open standards, or just being open to collaborations and building teams across institutions, disciplines, and international boundaries, time and time again through my involvement in the development of a high-resolution real time global hydrologic forecasting model I have discovered that in every aspect the sum has always been greater than the parts. While much has been accomplished, much more remains to be done, but the most important lesson learned has been to the degree that we can remain open and work together, the greater our ability will be to use big data hydrologic modeling resources to solve the world's most vexing water related challenges. This presentation will demonstrate a transformational global real time hydrologic forecasting application based on downscaled ECMWF ensemble forecasts, RAPID routing, and Tethys Platform for cloud computing and visualization with discussions of the human and cyber infrastructure connections that make it successful and needs moving forward.

Determining hydrological changes in a small Arctic treeline basin using cold regions hydrological modelling and a pseudo-global warming approach

NASA Astrophysics Data System (ADS)

Krogh, S. A.; Pomeroy, J. W.

2017-12-01

Increasing temperatures are producing higher rainfall ratios, shorter snow-covered periods, permafrost thaw, more shrub coverage, more northerly treelines and greater interaction between groundwater and surface flow in Arctic basins. How these changes will impact the hydrology of the Arctic treeline environment represents a great challenge. To diagnose the future hydrology along the current Arctic treeline, a physically based cold regions model was used to simulate the hydrology of a small basin near Inuvik, Northwest Territories, Canada. The hydrological model includes hydrological processes such as snow redistribution and sublimation by wind, canopy interception of snow/rain and sublimation/evaporation, snowmelt energy balance, active layer freeze/thaw, infiltration into frozen and unfrozen soils, evapotranspiration, horizontal flow through organic terrain and snowpack, subsurface flow and streamflow routing. The model was driven with weather simulated by a high-resolution (4 km) numerical weather prediction model under two scenarios: (1) control run, using ERA-Interim boundary conditions (2001-2013) and (2) future, using a Pseudo-Global Warming (PGW) approach based on the RCP8.5 projections perturbing the control run. Transient changes in vegetation based on recent observations and ecological expectations were then used to re-parameterise the model. Historical hydrological simulations were validated against daily streamflow, snow water equivalent and active layer thickness records, showing the model's suitability in this environment. Strong annual warming ( 6 °C) and more precipitation ( 20%) were simulated by the PGW scenario, with winter precipitation and fall temperature showing the largest seasonal increase. The joint impact of climate and transient vegetation changes on snow accumulation and redistribution, evapotranspiration, active layer development, runoff generation and hydrograph characteristics are analyzed and discussed.

Hydrologic response of Pacific Northwest river to climate change

NASA Astrophysics Data System (ADS)

Su, F.; Cuo, L.; Wu, H.; Mantua, N.; Lettenmaier, D. P.

2009-12-01

The climate of the Pacific Northwest (PNW - which we define as the Columbia River basin and watersheds draining to the Oregon and Washington coasts) is expected to warm by approximately 0.3°C per decade in the next 100 years based on the IPCC the Fourth Assessment Report (AR4) results. PNW hydrology is particularly sensitive to a warming climate because of the dominant role of snowmelt in seasonal streamflow. Timing shifts in seasonality of flows, peak discharge, and base flows will impact water resource management, regional electrical energy production, and freshwater ecosystems. In this work we update previous studies of implications of climate change on PNW hydrology using a macroscale hydrology model driven by simulations of temperature and precipitation downscaled from runs of 20 General Circulation Models (GCMs) under two emissions scenarios (lower B1 and mid-high A1B) in the 21st century. The hydrology model is implemented at 1/16th degree spatial resolution over the entire PNW. A (statistical) bias-correction and spatial disaggregation downscaling approach is used for translating the transient monthly climate model output into continuous daily forcings for the hydrologic analysis. We evaluate projected changes in snow water equivalent, seasonal streamflow, and frequency of peak low flows over a set of case study watersheds in the region. We also compare these hydrologic projections with previous analysis based on delta downscaling method over the PNW. This research is part of a project investigating climate change impacts on the future of wild Pacific salmon, and is a pilot effort to investigate the hydrologic sensitivity of salmon bearing watersheds around the entire North Pacific Rim.

Artificial Intelligence Methods: Choice of algorithms, their complexity, and appropriateness within the context of hydrology and water resources. (Invited)

NASA Astrophysics Data System (ADS)

Bastidas, L. A.; Pande, S.

2009-12-01

Pattern analysis deals with the automatic detection of patterns in the data and there are a variety of algorithms available for the purpose. These algorithms are commonly called Artificial Intelligence (AI) or data driven algorithms, and have been applied lately to a variety of problems in hydrology and are becoming extremely popular. When confronting such a range of algorithms, the question of which one is the “best” arises. Some algorithms may be preferred because of the lower computational complexity; others take into account prior knowledge of the form and the amount of the data; others are chosen based on a version of the Occam’s razor principle that a simple classifier performs better. Popper has argued, however, that Occam’s razor is without operational value because there is no clear measure or criterion for simplicity. An example of measures that can be used for this purpose are: the so called algorithmic complexity - also known as Kolmogorov complexity or Kolmogorov (algorithmic) entropy; the Bayesian information criterion; or the Vapnik-Chervonenkis dimension. On the other hand, the No Free Lunch Theorem states that there is no best general algorithm, and that specific algorithms are superior only for specific problems. It should be noted also that the appropriate algorithm and the appropriate complexity are constrained by the finiteness of the available data and the uncertainties associated with it. Thus, there is compromise between the complexity of the algorithm, the data properties, and the robustness of the predictions. We discuss the above topics; briefly review the historical development of applications with particular emphasis on statistical learning theory (SLT), also known as machine learning (ML) of which support vector machines and relevant vector machines are the most commonly known algorithms. We present some applications of such algorithms for distributed hydrologic modeling; and introduce an example of how the complexity measure can be applied for appropriate model choice within the context of applications in hydrologic modeling intended for use in studies about water resources and water resources management and their direct relation to extreme conditions or natural hazards.

The Effect of Firn-Aquifer Drainage on the Greenland Subglacial System or Subglacial Efficiency and Storage Modified by the Temporal Pattern of High-Elevation Meltwater Input

NASA Technical Reports Server (NTRS)

Andrews, Lauren C.; Poinar, Kristin; Dow, Christine F.; Nowicki, Sophie M.

2017-01-01

Ice flow in marginal region of the Greenland Ice Sheet dynamically responds to summer melting as surface meltwater is routed through the supraglacial hydrologic system to the bed of the ice sheet via crevasses and moulins. Given the expected increases in surface melt production and extent, and the potential for high elevation surface-to-bed connections, it is imperative to understand how meltwater delivered to the bed from different high-elevation supraglacial storage features affects the evolution of the subglacial hydrologic system and associated ice dynamics. Here, we use the two-dimensional subglacial hydrologic model, GLaDS, which includes distributed and channelized water flow, to test how the subglacial system of an idealized outlet glacier responds to cases of high-elevation firn-aquifer-type and supraglacial-lake-type englacial drainage over the course of 5 years. Model outputs driven by these high elevation drainage types are compared to steady-state model results, where the subglacial system only receives the 1980- 2016 mean MERRA-2 runoff via low-elevation moulins. Across all experiments, the subglacial hydrologic system displays inter-annual memory, resulting in multiyear declines in subglacial pressure during the onset of seasonal melting and growth of subglacial channels. The gradual addition of water in firn-aquifer-type drainage scenarios resulted in small increases in subglacial water storage but limited changes in subglacial efficiency and channelization. Rapid, supraglacial- lake-type drainage resulted in short-term local increases in subglacial water pressure and storage, which gave way to spatially extensive decreases in subglacial pressure and downstream channelization. These preliminary results suggest that the character of high-elevation englacial drainage can have a strong, and possibly outsized, control on subglacial efficiency throughout the ablation zone. Therefore, understanding both how high elevation meltwater is stored supraglacially and the probability of crevassing at high elevations will play an important role in how the subglacial system, proglacial discharge and ice motion will respond to future increases in surface melt production and runoff.

Socio-hydrologic Modeling to Understand and Mediate the Competition for Water between Humans and Ecosystems: Murrumbidgee River Basin, Australia

NASA Astrophysics Data System (ADS)

van Emmerik, Tim; Sivapalan, Murugesu; Li, Zheng; Pande, Saket; Savenije, Hubert

2014-05-01

Around the world the demand for water resources is growing in order to satisfy rapidly increasing human populations, leading to competition for water between humans and ecosystems. An entirely new and comprehensive quantitative framework is needed to establish a holistic understanding of that competition, thereby enabling development and evaluation of effective mediation strategies. We present a case study centered on the Murrumbidgee river basin in eastern Australia that illustrates the dynamics of the balance between water extraction and use for food production and efforts to mitigate and reverse consequent degradation of the riparian environment. Interactions between patterns of water resources management and climate driven hydrological variability within the prevailing socio-economic environment have contributed to the emergence of new whole system dynamics over the last 100 years. In particular, data analysis reveals a pendulum swing between an exclusive focus on agricultural development and food production in the initial stages of water resources development and its attendant socio-economic benefits, followed by the gradual realization of the adverse environmental impacts, efforts to mitigate these with the use of remedial measures, and ultimately concerted efforts and externally imposed solutions to restore environmental health and ecosystem services. A quasi-distributed coupled socio-hydrologic system model that explicitly includes the two-way coupling between human and hydrological systems, including evolution of human values/norms relating to water and the environment, is able to mimic broad features of this pendulum swing. The model consists of coupled nonlinear differential equations that include four state variables describing the co-evolution of storage capacity, irrigated area, human population, and ecosystem health, which are all connected by feedback mechanisms. The model is used to generate insights into the dominant controls of the trajectory of co-evolution of the coupled human-water system, to serve as the theoretical framework for more detailed analysis of the system, and to generate organizing principles that may be transferable to other systems in different climatic and socio-economic settings.

Evaluating a Local Ensemble Transform Kalman Filter snow cover data assimilation method to estimate SWE within a high-resolution hydrologic modeling framework across Western US mountainous regions

NASA Astrophysics Data System (ADS)

Oaida, C. M.; Andreadis, K.; Reager, J. T., II; Famiglietti, J. S.; Levoe, S.

2017-12-01

Accurately estimating how much snow water equivalent (SWE) is stored in mountainous regions characterized by complex terrain and snowmelt-driven hydrologic cycles is not only greatly desirable, but also a big challenge. Mountain snowpack exhibits high spatial variability across a broad range of spatial and temporal scales due to a multitude of physical and climatic factors, making it difficult to observe or estimate in its entirety. Combing remotely sensed data and high resolution hydrologic modeling through data assimilation (DA) has the potential to provide a spatially and temporally continuous SWE dataset at horizontal scales that capture sub-grid snow spatial variability and are also relevant to stakeholders such as water resource managers. Here, we present the evaluation of a new snow DA approach that uses a Local Ensemble Transform Kalman Filter (LETKF) in tandem with the Variable Infiltration Capacity macro-scale hydrologic model across the Western United States, at a daily temporal resolution, and a horizontal resolution of 1.75 km x 1.75 km. The LETKF is chosen for its relative simplicity, ease of implementation, and computational efficiency and scalability. The modeling/DA system assimilates daily MODIS Snow Covered Area and Grain Size (MODSCAG) fractional snow cover over, and has been developed to efficiently calculate SWE estimates over extended periods of time and covering large regional-scale areas at relatively high spatial resolution, ultimately producing a snow reanalysis-type dataset. Here we focus on the assessment of SWE produced by the DA scheme over several basins in California's Sierra Nevada Mountain range where Airborne Snow Observatory data is available, during the last five water years (2013-2017), which include both one of the driest and one of the wettest years. Comparison against such a spatially distributed SWE observational product provides a greater understanding of the model's ability to estimate SWE and SWE spatial variability, and highlights under which conditions snow cover DA can add value in estimating SWE.

How important are the descriptions of vegetation in distributed hydrologic models?

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Thober, Stephan; Zink, Matthias; Rakovec, Oldrich; Samaniego, Luis

2016-04-01

The land surface transforms incoming, absorbed radiation into other energy forms and radiation with longer wavelengths. The land surface emits long-wave radiation, stores energy in the soil, the biomass and the air in the boundary layer, and exchanges sensible and latent heat with the atmosphere. The latter, latent heat consists of evaporation from the soil and canopy and transpiration by plants. Plants enhance in this picture the absorption of incoming radiation and decrease the resistance for evaporation of deeper soil water. Transpiration by plants is therefore either energy-limited by low incoming radiation or water-limited by small soil moisture. In the extreme cases, all available energy will be used for evapotranspiration in cold regions and all available water will be used for evapotranspiration in arid regions. Very simple formulations of latent heat, which include plant processes only very indirectly, work well in hydrologic models for these limiting cases. These simple formulations seem to work also surprisingly well in temperate regions. Hydrologic models have, however, considerable problems in semi-arid regions where the vegetation influence on latent heat should be largest. But the models have to deal with much more problems in these regions. For example data scarcity in the Mediterranean leads to very large model uncertainty due to the forcing data. Water supply is also often very regulated in semi-arid regions. Variability in river discharge can hence be largely driven by the anthropogenic influence rather than natural meteorological variations in these regions. Here we will show for Europe the areas and times when the descriptions of plant processes are important for hydrologic models. We will compare differences in model uncertainties that come from 1. different formulations of evapotranspiration, 2. different descriptions of soil-plant interactions, and 3. uncertainty in the model's input data. It can be seen that model uncertainty stemming from uncertain input data is similar or larger in magnitude than the uncertainty coming from the descriptions of the vegetation in the models. Acquisition of better input data should thus go hand in hand with more sophisticated descriptions of the land surface.

Science-Based, Community-Driven Approach to Reducing Glacier Lake Outburst Flood Risks in the Nepal Himalaya

NASA Astrophysics Data System (ADS)

Rounce, D.; McKinney, D. C.; Byers, A. C.; Shrestha, M. K.; Cuellar, A. D.; Sherpa, S. F.

2016-12-01

Over the past several decades, hundreds of lower altitude Himalayan glaciers have been melting, leaving behind new glacier lakes, holding millions of cubic meters of water. Usually contained by dams of loose boulders and soil, these lakes present a risk of glacial lake outburst floods (GLOFs). These glacial-dominated areas pose unique challenges to downstream communities in adapting to global climate change, particularly in terms of increasing threats of GLOFs. This interdisciplinary research captures unique knowledge of the Himalayan region and contributes to the development of a new generation of scientists in the area of coupled natural and human systems of glacier-dominated mountain systems. The goals of the research are to: (1) Understand natural system dynamics through an analysis of the impacts of climate change on glacial lakes, (2) Understand the human system dynamics through the strengthening of community resiliency to glacial lake hazards by developing community-driven glacial lake risk reduction systems, (3) Understand how the natural system affects the human system through the assessment of local ecological knowledge and understanding of hydrological resources and the vulnerability of the social-ecological system to GLOF hazard, and (4) Understand how the human system affects the natural system through the design and modeling of community-driven solutions to analyze the reduction of flood risk and the evolution of glacial lakes. The project integrates in situ physical and societal observations with geospatial analyses, intensive glacial hydrology and outburst flood modeling, key respondents' interviews, and community level mappings and focus groups. The Imja glacial lake in the Khumbu region of Nepal is the field research site. The project is assessing outburst flood-related processes that include glacier hydrology, river flow, hydraulics, and sediment/debris transport models. These natural system impacts are being integrated with the human science aspects to evaluate socio-economic impacts of potential outburst flood events on communities, households, and ecotourism.

Improving Long-term Post-wildfire hydrologic simulations using ParFlow

NASA Astrophysics Data System (ADS)

Lopez, S. R.; Kinoshita, A. M.

2015-12-01

Wildfires alter the natural hydrologic processes within a watershed. After vegetation is burned, the combustion of organic material and debris settles into the soil creating a hydrophobic layer beneath the soil surface with varying degree of thickness and depth. Vegetation regrowth rates vary as a function of radiative exposure, burn severity, and precipitation patterns. Hydrologic models used by the Burned Area Emergency Response (BAER) teams use input data and model calibration constraints that are generally either one-dimensional, empirically-based models, or two-dimensional, conceptually-based models with lumped parameter distributions. These models estimate runoff measurements at the watershed outlet; however, do not provide a distributed hydrologic simulation at each point within the watershed. This work uses ParFlow, a three-dimensional, distributed hydrologic model to (1) correlate burn severity with hydrophobicity, (2) evaluate vegetation recovery rate on water components, and (3) improve flood prediction for managers to help with resource allocation and management operations in burned watersheds. ParFlow is applied to Devil Canyon (43 km2) in San Bernardino, California, which was 97% burned in the 2003 Old Fire. The model set-up uses a 30m-cell size resolution over a 6.7 km by 6.4 km lateral extent. The subsurface reaches 30 m and is assigned a variable cell thickness. Variable subsurface thickness allows users to explicitly consider the degree of recovery throughout the stages of regrowth. Burn severity maps from remotely sensed imagery are used to assign initial hydrophobic layer parameters and thickness. Vegetation regrowth is represented with satellite an Enhanced Vegetation Index. Pre and post-fire hydrologic response is evaluated using runoff measurements at the watershed outlet, and using water component (overland flow, lateral flow, baseflow) measurements.

Evaluating post-wildfire hydrologic recovery using ParFlow in southern California

NASA Astrophysics Data System (ADS)

Lopez, S. R.; Kinoshita, A. M.; Atchley, A. L.

2016-12-01

Wildfires are naturally occurring hazards that can have catastrophic impacts. They can alter the natural processes within a watershed, such as surface runoff and subsurface water storage. Generally, post-fire hydrologic models are either one-dimensional, empirically-based models, or two-dimensional, conceptually-based models with lumped parameter distributions. These models are useful in providing runoff measurements at the watershed outlet; however, do not provide distributed hydrologic simulation at each point within the watershed. This research demonstrates how ParFlow, a three-dimensional, distributed hydrologic model can simulate post-fire hydrologic processes by representing soil burn severity (via hydrophobicity) and vegetation recovery as they vary both spatially and temporally. Using this approach, we are able to evaluate the change in post-fire water components (surface flow, lateral flow, baseflow, and evapotranspiration). This model is initially developed for a hillslope in Devil Canyon, burned in 2003 by the Old Fire in southern California (USA). The domain uses a 2m-cell size resolution over a 25 m by 25 m lateral extent. The subsurface reaches 2 m and is assigned a variable cell thickness, allowing an explicit consideration of the soil burn severity throughout the stages of recovery and vegetation regrowth. Vegetation regrowth is incorporated represented by satellite-based Enhanced Vegetation Index (EVI) products. The pre- and post-fire surface runoff, subsurface storage, and surface storage interactions are evaluated and will be used as a basis for developing a watershed-scale model. Long-term continuous simulations will advance our understanding of post-fire hydrological partitioning between water balance components and the spatial variability of watershed processes, providing improved guidance for post-fire watershed management.

A spatiotemporal analysis of hydrological patterns based on a wireless sensor network system

NASA Astrophysics Data System (ADS)

Plaza, F.; Slater, T. A.; Zhong, X.; Li, Y.; Liang, Y.; Liang, X.

2017-12-01

Understanding complicated spatiotemporal patterns of eco-hydrological variables at a small scale plays a profound role in improving predictability of high resolution distributed hydrological models. However, accurate and continuous monitoring of these complex patterns has become one of the main challenges in the environmental sciences. Wireless sensor networks (WSNs) have emerged as one of the most widespread potential solutions to achieve this. This study presents a spatiotemporal analysis of hydrological patterns (e.g., soil moisture, soil water potential, soil temperature and transpiration) based on observational data collected from a dense multi-hop wireless sensor network (WSN) in a steep-forested testbed located in Southwestern Pennsylvania, USA. At this WSN testbed with an approximate area of 3000 m2, environmental variables are collected from over 240 sensors that are connected to more than 100 heterogeneous motes. The sensors include the soil moisture of EC-5, soil temperature and soil water potential of MPS-1 and MPS-2, and sap flow sensors constructed in house. The motes consist of MICAz, IRIS and TelosB. In addition, several data loggers have been installed along the site to provide a comparative reference to the WSN measurements for the purpose of checking the WSN data quality. The edaphic properties monitored by the WSN sensors show strong agreement with the data logger measurements. Moreover, sap flow measurements, scaled to tree stand transpiration, are found to be reasonable. This study also investigates the feasibility and roles that these sensor measurements play in improving the performance of high-resolution distributed hydrological models. In particular, we explore this using a modified version of the Distributed Hydrological Soil Vegetation Model (DHSVM).

Episodic Endogenetic-driven Atmospheric and Hydrologic Cycles and Their Influence on the Geologic Records of the Northern and Southern Hemispheres, Mars

NASA Technical Reports Server (NTRS)

Dohm, J. M.; Fairen, A. G.; Baker, V. R.; Ferris, J. C.; Anderson, R. C.; Uceda, E. R.

2003-01-01

Diverse evidence shows a direct correlation between episodic endogenetic events of the Tharsis magmatic complex (TMC)/Superplume, flood inundations in the northern plains, and glacial/ lacustrine/ice sheet activity in the south polar region, which includes Hellas and Argyre impact basins, corroborating the MEGAOUTFLO hypothesis. The TMC encompasses a total surface area of approximately 2 x 10(exp 7) sq km, which is slightly larger than the estimated size of the Southern Pacific Superplume. These hydrologic events include: (1) a Noachian to possibly Early Hesperian oceanic epoch and related atmospheric and environmental change (a water body covering about 1/3 of the planet s surface area) related to the incipient development of Tharsis Superplume and the northwestern sloping valleys (NSVs) and possibly early circum-Chryse development, the northwest and northeast watersheds of Tharsis, respectively, (2) a smaller ocean inset within the former larger ocean related to extensive Late Hesperian to Early Amazonian effusive volcanism at Tharsis and Elysium and incisement of the circum-Chryse outflow system. During this time, magmatic/plume-driven tectonic activity transitioned into more centralized volcanism. This Late Hesperian water body may have simply diminished into smaller seas and/or lakes during the Amazonian Period, or renewed activity at Tharsis and Elysium resulted in brief perturbations from the prevailing cold and dry climatic conditions to later form minor seas or lakes. All of the hydrologic phases transitioned into extensive periods of quiescence.

Distributed HUC-based modeling with SUMMA for ensemble streamflow forecasting over large regional domains.

NASA Astrophysics Data System (ADS)

Saharia, M.; Wood, A.; Clark, M. P.; Bennett, A.; Nijssen, B.; Clark, E.; Newman, A. J.

2017-12-01

Most operational streamflow forecasting systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow require an experienced human forecaster. But this approach faces challenges surrounding process reproducibility, hindcasting capability, and extension to large domains. The operational hydrologic community is increasingly moving towards `over-the-loop' (completely automated) large-domain simulations yet recent developments indicate a widespread lack of community knowledge about the strengths and weaknesses of such systems for forecasting. A realistic representation of land surface hydrologic processes is a critical element for improving forecasts, but often comes at the substantial cost of forecast system agility and efficiency. While popular grid-based models support the distributed representation of land surface processes, intermediate-scale Hydrologic Unit Code (HUC)-based modeling could provide a more efficient and process-aligned spatial discretization, reducing the need for tradeoffs between model complexity and critical forecasting requirements such as ensemble methods and comprehensive model calibration. The National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the USACE to implement, assess, and demonstrate real-time, over-the-loop distributed streamflow forecasting for several large western US river basins and regions. In this presentation, we present early results from short to medium range hydrologic and streamflow forecasts for the Pacific Northwest (PNW). We employ a real-time 1/16th degree daily ensemble model forcings as well as downscaled Global Ensemble Forecasting System (GEFS) meteorological forecasts. These datasets drive an intermediate-scale configuration of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model, which represents the PNW using over 11,700 HUCs. The system produces not only streamflow forecasts (using the MizuRoute channel routing tool) but also distributed model states such as soil moisture and snow water equivalent. We also describe challenges in distributed model-based forecasting, including the application and early results of real-time hydrologic data assimilation.

Reducing calibration parameters to increase insight in catchment organization and similarity

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Onof, Christian

2013-04-01

Ideally, hydrological models should be built from equations parameterised from observed catchment characteristics and data. This state of affairs may never be reached, but a governing principle in hydrological modelling should be to keep the number of calibration parameters to a minimum. A reduced number of parameters to be calibrated, while maintaining the accuracy and detail required by modern hydrological models, will reduce parameter and model structure uncertainty and improve model diagnostics. The dynamics of runoff for small catchments are derived from the distribution of distances from points in the catchments to the nearest stream in a catchment. This distribution is unique for each catchment and can be determined from a geographical information system (GIS). The distribution of distances, will, when a celerity of (subsurface) flow is introduced, provide a distribution of travel times, or a unit hydrograph (UH). For spatially varying levels of saturation deficit we have different celerities and, hence, different UHs. Runoff is derived from the super-positioning of the different UHs. This study shows how celerities can be estimated if we assume that recession events represent the superpositioned UH for different levels of saturation deficit. The performance of the DDD (Distance Distribution Dynamics) model is compared to that of the Swedish HBV model and is found to perform equally well for eight Norwegian catchments although the number of parameters to be calibrated in the module concerning soil moisture and runoff dynamics is reduced from 7 in the HBV model to 1 in the DDD model. It is also shown that the DDD model has a more realistic representation of the subsurface hydrology. The transparency of the DDD model makes model diagnostics more easy and experience with DDD shows that differences in model performance may be related to differences in catchment characteristics. More specifically, it appears that the hydrological dynamics of bogs have to be taken especially into account when modelling Norwegian catchments.

Benefits of incorporating spatial organisation of catchments for a semi-distributed hydrological model

NASA Astrophysics Data System (ADS)

Schumann, Andreas; Oppel, Henning

2017-04-01

To represent the hydrological behaviour of catchments a model should reproduce/reflect the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject of a certain spatial organisation. Since common models are mostly based on fundamental assumptions about hydrological processes, the reduction of variance of catchment properties as well as the incorporation of the spatial organisation of the catchment is desirable. We have developed a method that combines the idea of the width-function used for determination of the geomorphologic unit hydrograph with information about soil or topography. With this method we are able to assess the spatial organisation of selected catchment characteristics. An algorithm was developed that structures a watershed into sub-basins and other spatial units to minimise its heterogeneity. The outcomes of this algorithm are used for the spatial setup of a semi-distributed model. Since the spatial organisation of a catchment is not bound to a single characteristic, we have to embed information of multiple catchment properties. For this purpose we applied a fuzzy-based method to combine the spatial setup for multiple single characteristics into a union, optimal spatial differentiation. Utilizing this method, we are able to propose a spatial structure for a semi-distributed hydrological model, comprising the definition of sub-basins and a zonal classification within each sub-basin. Besides the improved spatial structuring, the performed analysis ameliorates modelling in another way. The spatial variability of catchment characteristics, which is considered by a minimum of heterogeneity in the zones, can be considered in a parameter constrained calibration scheme in a case study both options were used to explore the benefits of incorporating the spatial organisation and derived parameter constraints for the parametrisation of a HBV-96 model. We use two benchmark model setups (lumped and semi-distributed by common approaches) to address the benefits for different time and spatial scales. Moreover, the benefits for calibration effort, model performance in validation periods and process extrapolation are shown.

Impact of climate change and climate anomalies on hydrologic and biogeochemical processes in an agricultural catchment of the Chesapeake Bay watershed, USA.

PubMed

Wagena, Moges B; Collick, Amy S; Ross, Andrew C; Najjar, Raymond G; Rau, Benjamin; Sommerlot, Andrew R; Fuka, Daniel R; Kleinman, Peter J A; Easton, Zachary M

2018-05-16

Nutrient export from agricultural landscapes is a water quality concern and the cause of mitigation activities worldwide. Climate change impacts hydrology and nutrient cycling by changing soil moisture, stoichiometric nutrient ratios, and soil temperature, potentially complicating mitigation measures. This research quantifies the impact of climate change and climate anomalies on hydrology, nutrient cycling, and greenhouse gas emissions in an agricultural catchment of the Chesapeake Bay watershed. We force a calibrated model with seven downscaled and bias-corrected regional climate models and derived climate anomalies to assess their impact on hydrology and the export of nitrate (NO 3 -), phosphorus (P), and sediment, and emissions of nitrous oxide (N 2 O) and di-nitrogen (N 2 ). Model-average (±standard deviation) results indicate that climate change, through an increase in precipitation and temperature, will result in substantial increases in winter/spring flow (10.6 ± 12.3%), NO 3 - (17.3 ± 6.4%), dissolved P (32.3 ± 18.4%), total P (24.8 ± 16.9%), and sediment (25.2 ± 16.6%) export, and a slight increases in N 2 O (0.3 ± 4.8%) and N 2 (0.2 ± 11.8%) emissions. Conversely, decreases in summer flow (-29.1 ± 24.6%) and the export of dissolved P (-15.5 ± 26.4%), total P (-16.3 ± 20.7%), sediment (-20.7 ± 18.3%), and NO 3 - (-29.1 ± 27.8%) are driven by greater evapotranspiration from increasing summer temperatures. Decreases in N 2 O (-26.9 ± 15.7%) and N 2 (-36.6 ± 22.9%) are predicted in the summer and driven by drier soils. While the changes in flow are related directly to changes in precipitation and temperature, the changes in nutrient and sediment export are, to some extent, driven by changes in agricultural management that climate change induces, such as earlier spring tillage and altered nutrient application timing and by alterations to nutrient cycling in the soil. Copyright © 2018 Elsevier B.V. All rights reserved.

Parallelization of a Fully-Distributed Hydrologic Model using Sub-basin Partitioning

NASA Astrophysics Data System (ADS)

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

2005-12-01

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

Impact of model structure on flow simulation and hydrological realism: from a lumped to a semi-distributed approach

NASA Astrophysics Data System (ADS)

Garavaglia, Federico; Le Lay, Matthieu; Gottardi, Fréderic; Garçon, Rémy; Gailhard, Joël; Paquet, Emmanuel; Mathevet, Thibault

2017-08-01

Model intercomparison experiments are widely used to investigate and improve hydrological model performance. However, a study based only on runoff simulation is not sufficient to discriminate between different model structures. Hence, there is a need to improve hydrological models for specific streamflow signatures (e.g., low and high flow) and multi-variable predictions (e.g., soil moisture, snow and groundwater). This study assesses the impact of model structure on flow simulation and hydrological realism using three versions of a hydrological model called MORDOR: the historical lumped structure and a revisited formulation available in both lumped and semi-distributed structures. In particular, the main goal of this paper is to investigate the relative impact of model equations and spatial discretization on flow simulation, snowpack representation and evapotranspiration estimation. Comparison of the models is based on an extensive dataset composed of 50 catchments located in French mountainous regions. The evaluation framework is founded on a multi-criterion split-sample strategy. All models were calibrated using an automatic optimization method based on an efficient genetic algorithm. The evaluation framework is enriched by the assessment of snow and evapotranspiration modeling against in situ and satellite data. The results showed that the new model formulations perform significantly better than the initial one in terms of the various streamflow signatures, snow and evapotranspiration predictions. The semi-distributed approach provides better calibration-validation performance for the snow cover area, snow water equivalent and runoff simulation, especially for nival catchments.

Automatic Calibration of a Semi-Distributed Hydrologic Model Using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Bekele, E. G.; Nicklow, J. W.

2005-12-01

Hydrologic simulation models need to be calibrated and validated before using them for operational predictions. Spatially-distributed hydrologic models generally have a large number of parameters to capture the various physical characteristics of a hydrologic system. Manual calibration of such models is a very tedious and daunting task, and its success depends on the subjective assessment of a particular modeler, which includes knowledge of the basic approaches and interactions in the model. In order to alleviate these shortcomings, an automatic calibration model, which employs an evolutionary optimization technique known as Particle Swarm Optimizer (PSO) for parameter estimation, is developed. PSO is a heuristic search algorithm that is inspired by social behavior of bird flocking or fish schooling. The newly-developed calibration model is integrated to the U.S. Department of Agriculture's Soil and Water Assessment Tool (SWAT). SWAT is a physically-based, semi-distributed hydrologic model that was developed to predict the long term impacts of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use, and management conditions. SWAT was calibrated for streamflow and sediment concentration. The calibration process involves parameter specification, whereby sensitive model parameters are identified, and parameter estimation. In order to reduce the number of parameters to be calibrated, parameterization was performed. The methodology is applied to a demonstration watershed known as Big Creek, which is located in southern Illinois. Application results show the effectiveness of the approach and model predictions are significantly improved.

Interaction of hydrological regime and vegetation in a seasonally flooded lake wetland (Poyang Lake) in China

NASA Astrophysics Data System (ADS)

Zhang, Qi

2017-04-01

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

Modeling Pre- and Post- Wildfire Hydrologic Response to Vegetation Change in the Valles Caldera National Preserve, NM

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Land-use change may exacerbate climate change impacts on water resources in the Ganges basin

NASA Astrophysics Data System (ADS)

Tsarouchi, Gina; Buytaert, Wouter

2018-02-01

Quantifying how land-use change and climate change affect water resources is a challenge in hydrological science. This work aims to quantify how future projections of land-use and climate change might affect the hydrological response of the Upper Ganges river basin in northern India, which experiences monsoon flooding almost every year. Three different sets of modelling experiments were run using the Joint UK Land Environment Simulator (JULES) land surface model (LSM) and covering the period 2000-2035: in the first set, only climate change is taken into account, and JULES was driven by the CMIP5 (Coupled Model Intercomparison Project Phase 5) outputs of 21 models, under two representative concentration pathways (RCP4.5 and RCP8.5), whilst land use was held fixed at the year 2010. In the second set, only land-use change is taken into account, and JULES was driven by a time series of 15 future land-use pathways, based on Landsat satellite imagery and the Markov chain simulation, whilst the meteorological boundary conditions were held fixed at years 2000-2005. In the third set, both climate change and land-use change were taken into consideration, as the CMIP5 model outputs were used in conjunction with the 15 future land-use pathways to force JULES. Variations in hydrological variables (stream flow, evapotranspiration and soil moisture) are calculated during the simulation period. Significant changes in the near-future (years 2030-2035) hydrologic fluxes arise under future land-cover and climate change scenarios pointing towards a severe increase in high extremes of flow: the multi-model mean of the 95th percentile of streamflow (Q5) is projected to increase by 63 % under the combined land-use and climate change high emissions scenario (RCP8.5). The changes in all examined hydrological components are greater in the combined land-use and climate change experiment. Results are further presented in a water resources context, aiming to address potential implications of climate change and land-use change from a water demand perspective. We conclude that future water demands in the Upper Ganges region for winter months may not be met.

Mountain-Scale Coupled Processes (TH/THC/THM)

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

P. Dixon

The purpose of this Model Report is to document the development of the Mountain-Scale Thermal-Hydrological (TH), Thermal-Hydrological-Chemical (THC), and Thermal-Hydrological-Mechanical (THM) Models and evaluate the effects of coupled TH/THC/THM processes on mountain-scale UZ flow at Yucca Mountain, Nevada. This Model Report was planned in ''Technical Work Plan (TWP) for: Performance Assessment Unsaturated Zone'' (BSC 2002 [160819], Section 1.12.7), and was developed in accordance with AP-SIII.10Q, Models. In this Model Report, any reference to ''repository'' means the nuclear waste repository at Yucca Mountain, and any reference to ''drifts'' means the emplacement drifts at the repository horizon. This Model Report provides themore » necessary framework to test conceptual hypotheses for analyzing mountain-scale hydrological/chemical/mechanical changes and predict flow behavior in response to heat release by radioactive decay from the nuclear waste repository at the Yucca Mountain site. The mountain-scale coupled TH/THC/THM processes models numerically simulate the impact of nuclear waste heat release on the natural hydrogeological system, including a representation of heat-driven processes occurring in the far field. The TH simulations provide predictions for thermally affected liquid saturation, gas- and liquid-phase fluxes, and water and rock temperature (together called the flow fields). The main focus of the TH Model is to predict the changes in water flux driven by evaporation/condensation processes, and drainage between drifts. The TH Model captures mountain-scale three dimensional (3-D) flow effects, including lateral diversion at the PTn/TSw interface and mountain-scale flow patterns. The Mountain-Scale THC Model evaluates TH effects on water and gas chemistry, mineral dissolution/precipitation, and the resulting impact to UZ hydrological properties, flow and transport. The THM Model addresses changes in permeability due to mechanical and thermal disturbances in stratigraphic units above and below the repository host rock. The Mountain-Scale THM Model focuses on evaluating the changes in 3-D UZ flow fields arising out of thermal stress and rock deformation during and after the thermal periods.« less

Relevance of the land use changes related to a megacity development in a Colombian river basin

NASA Astrophysics Data System (ADS)

García-Arias, Alicia; Romero Hernández, Claudia Patricia; Francés, Félix

2017-04-01

A megacity development is a main driving force for land uses changes. Population in these megacities usually rise depending on some or all of the natural resources related to the occupied area and, among them, water is a pivotal requirement. On the other hand, land use changes determine the catchment hydrology and, in consequence, its management. The better knowledge on land uses cover distribution and characteristics, the higher capabilities to increase the accuracy of hydrological predictions and the efficiency of water management. This study aims to describe the land uses changes occurred during the recent expansion of the megacity of Bogotá (Colombia) and to understand the expected changes. In addition, we propose the base for the consideration of this land use changes in the TETIS distributed hydrological modelling approach. The discussion focus on the necessity of considering this kind of scenarios in hydrological modelling for a responsible management of the water resources.

Distributed information system (water fact sheet)

USGS Publications Warehouse

Harbaugh, A.W.

1986-01-01

During 1982-85, the Water Resources Division (WRD) of the U.S. Geological Survey (USGS) installed over 70 large minicomputers in offices across the country to support its mission in the science of hydrology. These computers are connected by a communications network that allows information to be shared among computers in each office. The computers and network together are known as the Distributed Information System (DIS). The computers are accessed through the use of more than 1500 terminals and minicomputers. The WRD has three fundamentally different needs for computing: data management; hydrologic analysis; and administration. Data management accounts for 50% of the computational workload of WRD because hydrologic data are collected in all 50 states, Puerto Rico, and the Pacific trust territories. Hydrologic analysis consists of 40% of the computational workload of WRD. Cost accounting, payroll, personnel records, and planning for WRD programs occupies an estimated 10% of the computer workload. The DIS communications network is shown on a map. (Lantz-PTT)

An overview of current applications, challenges, and future trends in distributed process-based models in hydrology

USGS Publications Warehouse

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

2016-01-01

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

Modular modeling system for building distributed hydrologic models with a user-friendly software package

NASA Astrophysics Data System (ADS)

Wi, S.; Ray, P. A.; Brown, C.

2015-12-01

A software package developed to facilitate building distributed hydrologic models in a modular modeling system is presented. The software package provides a user-friendly graphical user interface that eases its practical use in water resources-related research and practice. The modular modeling system organizes the options available to users when assembling models according to the stages of hydrological cycle, such as potential evapotranspiration, soil moisture accounting, and snow/glacier melting processes. The software is intended to be a comprehensive tool that simplifies the task of developing, calibrating, validating, and using hydrologic models through the inclusion of intelligent automation to minimize user effort, and reduce opportunities for error. Processes so far automated include the definition of system boundaries (i.e., watershed delineation), climate and geographical input generation, and parameter calibration. Built-in post-processing toolkits greatly improve the functionality of the software as a decision support tool for water resources system management and planning. Example post-processing toolkits enable streamflow simulation at ungauged sites with predefined model parameters, and perform climate change risk assessment by means of the decision scaling approach. The software is validated through application to watersheds representing a variety of hydrologic regimes.

Estimation of Snow Parameters Based on Passive Microwave Remote Sensing and Meteorological Information

NASA Technical Reports Server (NTRS)

Tsang, Leung; Hwang, Jenq-Neng

1996-01-01

A method to incorporate passive microwave remote sensing measurements within a spatially distributed snow hydrology model to provide estimates of the spatial distribution of Snow Water Equivalent (SWE) as a function of time is implemented. The passive microwave remote sensing measurements are at 25 km resolution. However, in mountain regions the spatial variability of SWE over a 25 km footprint is large due to topographic influences. On the other hand, the snow hydrology model has built-in topographic information and the capability to estimate SWE at a 1 km resolution. In our work, the snow hydrology SWE estimates are updated and corrected using SSM/I passive microwave remote sensing measurements. The method is applied to the Upper Rio Grande River Basin in the mountains of Colorado. The change in prediction of SWE from hydrology modeling with and without updating is compared with measurements from two SNOTEL sites in and near the basin. The results indicate that the method incorporating the remote sensing measurements into the hydrology model is able to more closely estimate the temporal evolution of the measured values of SWE as a function of time.

On how to avoid input and structural uncertainties corrupt the inference of hydrological parameters using a Bayesian framework

NASA Astrophysics Data System (ADS)

Hernández, Mario R.; Francés, Félix

2015-04-01

One phase of the hydrological models implementation process, significantly contributing to the hydrological predictions uncertainty, is the calibration phase in which values of the unknown model parameters are tuned by optimizing an objective function. An unsuitable error model (e.g. Standard Least Squares or SLS) introduces noise into the estimation of the parameters. The main sources of this noise are the input errors and the hydrological model structural deficiencies. Thus, the biased calibrated parameters cause the divergence model phenomenon, where the errors variance of the (spatially and temporally) forecasted flows far exceeds the errors variance in the fitting period, and provoke the loss of part or all of the physical meaning of the modeled processes. In other words, yielding a calibrated hydrological model which works well, but not for the right reasons. Besides, an unsuitable error model yields a non-reliable predictive uncertainty assessment. Hence, with the aim of prevent all these undesirable effects, this research focuses on the Bayesian joint inference (BJI) of both the hydrological and error model parameters, considering a general additive (GA) error model that allows for correlation, non-stationarity (in variance and bias) and non-normality of model residuals. As hydrological model, it has been used a conceptual distributed model called TETIS, with a particular split structure of the effective model parameters. Bayesian inference has been performed with the aid of a Markov Chain Monte Carlo (MCMC) algorithm called Dream-ZS. MCMC algorithm quantifies the uncertainty of the hydrological and error model parameters by getting the joint posterior probability distribution, conditioned on the observed flows. The BJI methodology is a very powerful and reliable tool, but it must be used correctly this is, if non-stationarity in errors variance and bias is modeled, the Total Laws must be taken into account. The results of this research show that the application of BJI with a GA error model outperforms the hydrological parameters robustness (diminishing the divergence model phenomenon) and improves the reliability of the streamflow predictive distribution, in respect of the results of a bad error model as SLS. Finally, the most likely prediction in a validation period, for both BJI+GA and SLS error models shows a similar performance.

Evaluation of a distributed catchment scale water balance model

NASA Technical Reports Server (NTRS)

Troch, Peter A.; Mancini, Marco; Paniconi, Claudio; Wood, Eric F.

1993-01-01

The validity of some of the simplifying assumptions in a conceptual water balance model is investigated by comparing simulation results from the conceptual model with simulation results from a three-dimensional physically based numerical model and with field observations. We examine, in particular, assumptions and simplifications related to water table dynamics, vertical soil moisture and pressure head distributions, and subsurface flow contributions to stream discharge. The conceptual model relies on a topographic index to predict saturation excess runoff and on Philip's infiltration equation to predict infiltration excess runoff. The numerical model solves the three-dimensional Richards equation describing flow in variably saturated porous media, and handles seepage face boundaries, infiltration excess and saturation excess runoff production, and soil driven and atmosphere driven surface fluxes. The study catchments (a 7.2 sq km catchment and a 0.64 sq km subcatchment) are located in the North Appalachian ridge and valley region of eastern Pennsylvania. Hydrologic data collected during the MACHYDRO 90 field experiment are used to calibrate the models and to evaluate simulation results. It is found that water table dynamics as predicted by the conceptual model are close to the observations in a shallow water well and therefore, that a linear relationship between a topographic index and the local water table depth is found to be a reasonable assumption for catchment scale modeling. However, the hydraulic equilibrium assumption is not valid for the upper 100 cm layer of the unsaturated zone and a conceptual model that incorporates a root zone is suggested. Furthermore, theoretical subsurface flow characteristics from the conceptual model are found to be different from field observations, numerical simulation results, and theoretical baseflow recession characteristics based on Boussinesq's groundwater equation.

Using SERC for creating and publishing student generated hydrology instruction materials

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Riparian plant composition along hydrologic gradients in a dryland river basin and implications for a warming climate

USGS Publications Warehouse

Reynolds, Lindsay; Shafroth, Patrick B.

2017-01-01

Droughts in dryland regions on all continents are expected to increase in severity and duration under future climate projections. In dryland regions, it is likely that minimum streamflow will decrease with some perennial streams shifting to intermittent flow under climate-driven changes in precipitation and runoff and increases in temperature. Decreasing base flow and shifting flow regimes from perennial to intermittent could have significant implications for stream-dependent biota, including riparian vegetation. In this study, we asked, how do riparian plant communities vary along wet-to-dry hydrologic gradients on small (first–third order) streams? We collected data on geomorphic, hydrologic, and plant community characteristics on 54 stream sites ranging in hydrology from intermittent to perennial flow across the Upper Colorado River Basin (284,898 km2). We found that plant communities varied along hydrologic gradients from high to low elevation between streams, and perennial to intermittent flow. We identified indicator species associated with different hydrologic conditions and suggest how plant communities may shift under warmer, drier conditions. Our results indicate that species richness and cover of total, perennial, wetland, and native plant groups will decrease while annual plants will increase under drying conditions. Understanding how plant communities respond to regional drivers such as hydroclimate requires broad-scale approaches such as sampling across whole river basins. With increasingly arid conditions in many regions of the globe, understanding plant community shifts is key to understanding the future of riparian ecosystems.

Building hydrologic information systems to promote climate resilience in the Blue Nile/Abay higlands

USDA-ARS?s Scientific Manuscript database

Climate adaptation requires information about climate and land-surface conditions – spatially distributed, and at scales of human influence (the field scale). This article describes a project aimed at combining meteorological data, satellite remote sensing, hydrologic modeling, and downscaled clima...

Spatially Distributed Assimilation of Remotely Sensed Leaf Area Index and Potential Evapotranspiration for Hydrologic Modeling in Wetland Landscapes

EPA Science Inventory

Evapotranspiration (ET), a highly dynamic flux in wetland landscapes, regulates the accuracy of surface/sub-surface runoff simulation in a hydrologic model. However, considerable uncertainty in simulating ET-related processes remains, including our limited ability to incorporate ...

Stream Hydrology and Water Quality Impacts of Contrasting Urban Stormwater Mitigation Strategies: Centralized Versus Distributed

EPA Science Inventory

Urban land cover is commonly associated with degraded stream habitat including flashier hydrology, increased pollutant export, and lower ecological health , collectively termed “urban stream syndrome.” Pollutant export from urban areas can also contribute to water quality issues...

Ecohydrological index, native fish, and climate trends and relationships in the Kansas River basin

EPA Science Inventory

This study sought to quantify climatological and hydrological trends and their relationship to presence and distribution of two native aquatic species in the Kansas River Basin over the past half century. Trend analyses were applied to indicators of hydrologic alteration (IHAs) ...

A method for coupling a parameterization of the planetary boundary layer with a hydrologic model

NASA Technical Reports Server (NTRS)

Lin, J. D.; Sun, Shu Fen

1986-01-01

Deardorff's parameterization of the planetary boundary layer is adapted to drive a hydrologic model. The method converts the atmospheric conditions measured at the anemometer height at one site to the mean values in the planetary boundary layer; it then uses the planetary boundary layer parameterization and the hydrologic variables to calculate the fluxes of momentum, heat and moisture at the atmosphere-land interface for a different site. A simplified hydrologic model is used for a simulation study of soil moisture and ground temperature on three different land surface covers. The results indicate that this method can be used to drive a spatially distributed hydrologic model by using observed data available at a meteorological station located on or nearby the site.

Sensitivity of effective rainfall amount to land use description using GIS tool. Case of a small mediterranean catchment

NASA Astrophysics Data System (ADS)

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

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

Enhancing water cycle measurements for future hydrologic research

USGS Publications Warehouse

Loescher, H.W.; Jacobs, J.M.; Wendroth, O.; Robinson, D.A.; Poulos, G.S.; McGuire, K.; Reed, P.; Mohanty, B.P.; Shanley, J.B.; Krajewski, W.

2007-01-01

The Consortium of Universities for the Advancement of Hydrologic Sciences, Inc., established the Hydrologic Measurement Facility to transform watershed-scale hydrologic research by facilitating access to advanced instrumentation and expertise that would not otherwise be available to individual investigators. We outline a committee-based process that determined which suites of instrumentation best fit the needs of the hydrological science community and a proposed mechanism for the governance and distribution of these sensors. Here, we also focus on how these proposed suites of instrumentation can be used to address key scientific challenges, including scaling water cycle science in time and space, broadening the scope of individual subdisciplines of water cycle science, and developing mechanistic linkages among these subdisciplines and spatio-temporal scales. ?? 2007 American Meteorological Society.

Scenario-based and scenario-neutral assessment of climate change impacts on operational performance of a multipurpose reservoir

Treesearch

Allison G. Danner; Mohammad Safeeq; Gordon E. Grant; Charlotte Wickham; Desirée Tullos; Mary V. Santelmann

2017-01-01

Scenario-based and scenario-neutral impacts assessment approaches provide complementary information about how climate change-driven effects on streamflow may change the operational performance of multipurpose dams. Examining a case study of Cougar Dam in Oregon, United States, we simulated current reservoir operations under scenarios of plausible future hydrology....

Pursuing realistic hydrologic model under SUPERFLEX framework in a semi-humid catchment in China

NASA Astrophysics Data System (ADS)

Wei, Lingna; Savenije, Hubert H. G.; Gao, Hongkai; Chen, Xi

2016-04-01

Model realism is pursued perpetually by hydrologists for flood and drought prediction, integrated water resources management and decision support of water security. "Physical-based" distributed hydrologic models are speedily developed but they also encounter unneglectable challenges, for instance, computational time with low efficiency and parameters uncertainty. This study step-wisely tested four conceptual hydrologic models under the framework of SUPERFLEX in a small semi-humid catchment in southern Huai River basin of China. The original lumped FLEXL has hypothesized model structure of four reservoirs to represent canopy interception, unsaturated zone, subsurface flow of fast and slow components and base flow storage. Considering the uneven rainfall in space, the second model (FLEXD) is developed with same parameter set for different rain gauge controlling units. To reveal the effect of topography, terrain descriptor of height above the nearest drainage (HAND) combined with slope is applied to classify the experimental catchment into two landscapes. Then the third one (FLEXTOPO) builds different model blocks in consideration of the dominant hydrologic process corresponding to the topographical condition. The fourth one named FLEXTOPOD integrating the parallel framework of FLEXTOPO in four controlled units is designed to interpret spatial variability of rainfall patterns and topographic features. Through pairwise comparison, our results suggest that: (1) semi-distributed models (FLEXD and FLEXTOPOD) taking precipitation spatial heterogeneity into account has improved model performance with parsimonious parameter set, and (2) hydrologic model architecture with flexibility to reflect perceived dominant hydrologic processes can include the local terrain circumstances for each landscape. Hence, the modeling actions are coincided with the catchment behaviour and close to the "reality". The presented methodology is regarding hydrologic model as a tool to test our hypothesis and deepen our understanding of hydrologic processes, which will be helpful to improve modeling realism.

The long-term hydrological effect of forest stands on the stability of slopes

NASA Astrophysics Data System (ADS)

Bogaard, T. A.; Meng, W.; van Beek, L. P. H.

2012-04-01

Forest is widely known to improve slope stability as a result of mechanical and hydrological effects. While the mechanics underlying the stabilizing process of root reinforcement are well understood and quantified, the influence of forest on the occurrence of critical hydrological conditions in terms of suction or pore pressure remains uncertain. Due to seasonal and inter-annual fluctuations, the stabilizing influence of evaporation and transpiration is difficult to isolate from the overall noise of the hydrological signal. More long-term effects of forest stands on soil development are highly variable and thus difficult to observe and quantify. Often these effects are ambivalent, having potentially a stabilizing or destabilizing influence on a slope under particular conditions (e.g., more structured soils leading to both rapid infiltration and drainage). Consequently, it can be postulated that forests will hydrologically influence the magnitude-frequency distribution of landsliding, not only at the stand level but also on a regional scale through the groundwater system. The overall aim of this research is to understand and quantify the stabilizing hydrological effect of forests on potentially unstable slopes. To this end, we focus on the changes in the magnitude-frequency distribution of landsliding that arise as a result of variations in evapotranspiration losses over the life cycle of stands. Temporal variations in evapotranspiration comprise first of all the interception that can account for an important amount of evaporation from a forest, and that changes with seasonal and annual variations in the interception capacity of the canopy and forest floor. Transpiration also represents an important loss that varies over the various growth stages of a forest stand. Based on a literature review of water consumption by tree species and water balance studies of forested catchments we defined the potential transpiration for different growth stages. This information we used in a spatially distributed, physical-based, dynamical model to simulate the hydrology and resulting stability for a catchment on a daily scale. The results can be used to identify end members of the hydrological influence of forests on slope stability and the typical variations in stability associated with the various growth stages. They indicate that the influence of forest stand age on the water consumption can be significant and has clear consequences for the antecedent soil moisture condition within a slope and thus on the potential for slope destabilization. The outcome should help to understand the long-term impact of vegetation on slope hydrology and define sustainable and reliable management strategies at the scale of forest stands. Keywords: slope stability, hydrology, vegetation, long-tem effect

Characteristics and Impact of Imperviousness From a GIS-based Hydrological Perspective

NASA Astrophysics Data System (ADS)

Moglen, G. E.; Kim, S.

2005-12-01

With the concern that imperviousness can be differently quantified depending on data sources and methods, this study assessed imperviousness estimates using two different data sources: land use and land cover. Year 2000 land use developed by the Maryland Department of Planning was utilized to estimate imperviousness by assigning imperviousness coefficients to unique land use categories. These estimates were compared with imperviousness estimates based on satellite-derived land cover from the 2001 National Land Cover Dataset. Our study developed the relationships between these two estimates in the form of regression equations to convert imperviousness derived from one data source to the other. The regression equations are considered reliable, based on goodness-of-fit measures. Furthermore, this study examined how quantitatively different imperviousness estimates affect the prediction of hydrological response both in the flow regime and in the thermal regime. We assessed the relationships between indicators of hydrological response and imperviousness-descriptors. As indicators of flow variability, coefficient of variance, lag-one autocorrelation, and mean daily flow change were calculated based on measured mean daily stream flow from the water year 1997 to 2003. For thermal variability, indicators such as percent-days of surge, degree-day, and mean daily temperature difference were calculated base on measured stream temperature over several basins in Maryland. To describe imperviousness through the hydrological process, GIS-based spatially distributed hydrological models were developed based on a water-balance method and the SCS-CN method. Imperviousness estimates from land use and land cover were used as predictors in these models to examine the effect of imperviousness using different data sources on the prediction of hydrological response. Indicators of hydrological response were also regressed on aggregate imperviousness. This allowed for identifying if hydrological response is more sensitive to spatially distributed imperviousness or aggregate (lumped) imperviousness. The regressions between indicators of hydrological response and imperviousness-descriptors were evaluated by examining goodness-of-fit measures such as explained variance or relative standard error. The results show that imperviousness estimates using land use are better predictors of flow variability and thermal variability than imperviousness estimates using land cover. Also, this study reveals that flow variability is more sensitive to spatially distributed models than lumped models, while thermal variability is equally responsive to both models. The findings from this study can be further examined from a policy perspective with regard to policies that are based on a threshold concept for imperviousness impacts on the ecological and hydrological system.

Response of the European ecosystems to climate change: a modelling approach for the 21st century.

NASA Astrophysics Data System (ADS)

Dury, Marie; Warnant, Pierre; François, Louis; Henrot, Alexandra; Favre, Eric; Hambuckers, Alain

2010-05-01

According to projections, over the 21st century, significant climatic changes appear and will be strengthened all over the world with the continuing increase of the atmospheric CO2 level. Climate will be generally warmer with notably changes in the seasonality and in the precipitation regime. These changes will have major impacts on the environment and on the biodiversity of natural ecosystems. Geographic distribution of ecosystems may be modified since species will be driven to migrate towards more suitable areas (e. g., shifting of the arctic tree lines). The CARAIB dynamic vegetation model (Carbon Assimilation in the Biosphere) forced with 21st century climate scenarios of the IPCC (ARPEGE-Climat model) is used to illustrate and analyse the potential impacts of climate change on tree species distribution and productivity over Europe. Changes in hydrological budget (e. g., runoff) and fire effects on forests will also be shown. Transient runs (1975-2100) with a new dynamic module introduced in CARAIB are performed to follow the future evolutions. In the new module, the processes of species establishment, competition and mortality due to stresses and disturbances have been improved. Among others, increased atmospheric CO2 and warmer climate increase tree productivity while drier conditions decrease it. Regions with more severe droughts will also be affected by an increase of wildfire frequency, which may have large impacts on vegetation density and distribution.

Distributed simulation of long-term hydrological processes in a medium-sized periurban catchment under changing land use and rainwater management.

NASA Astrophysics Data System (ADS)

Labbas, Mériem; Braud, Isabelle; Branger, Flora; Kralisch, Sven

2013-04-01

Growing urbanization and related anthropogenic processes have a high potential to influence hydrological process dynamics. Typical consequences are an increase of surface imperviousness and modifications of water flow paths due to artificial channels and barriers (combined and separated system, sewer overflow device, roads, ditches, etc.). Periurban catchments, at the edge of large cities, are especially affected by fast anthropogenic modifications. They usually consist of a combination of natural areas, rural areas with dispersed settlements and urban areas mostly covered by built zones and spots of natural surfaces. In the context of the European Water Framework Directive (2000) and the Floods Directive (2007), integrated and sustainable solutions are needed to reduce flooding risks and river pollution at the scale of urban conglomerations or whole catchments. Their thorough management requires models able to assess the vulnerability of the territory and to compare the impact of different rainwater management options and planning issues. To address this question, we propose a methodology based on a multi-scale distributed hydrological modelling approach. It aims at quantifying the impact of ongoing urbanization and stormwater management on the long-term hydrological cycle in medium-sized periurban watershed. This method focuses on the understanding and formalization of dominant periurban hydrological processes from small scales (few ha to few km2) to larger scales (few hundred km2). The main objectives are to 1) simulate both urban and rural hydrological processes and 2) test the effects of different long-term land use and water management scenarios. The method relies on several tools and data: a distributed hydrological model adapted to the characteristics of periurban areas, land use and land cover maps from different dates (past, present, future) and information about rainwater management collected from local authorities. For the application of the method, the medium-scaled catchment of Yzeron (France) is chosen. It is subjected to a fast progression of urbanization since the eighties and has been monitored for a long time period. The fully-distributed hydrological model J2000, available through the JAMS modelling framework, was found appropriate to simulate the water balance of the Yzeron catchment at a daily time step. However, it was not designed especially for periurban areas, so its structure and parameters are under adaptation. Firstly, as hydrological responses in urban areas are quicker than in rural areas, a sub-daily time step is necessary to improve the simulation of periurban hydrological processes. Therefore, J2000 was adapted to be run at a hourly time step. Secondly, in order to better take into account rainwater management, an explicit representation of sewer networks is implemented in the J2000 model whose periurban version is called J2000P. It receives urban rainwater coming from impervious surfaces connected to a combined sewer system and delivers this water to the treatment plant or directly to the river in case of sewer overflow device outflows. We will present the impact of these modifications on the simulated hydrological regime.

Development of Semi-distributed ecohydrological model in the Rio Grande De Manati River Basin, Puerto Rico

NASA Astrophysics Data System (ADS)

Setegn, S. G.; Ortiz, J.; Melendez, J.; Barreto, M.; Torres-Perez, J. L.; Guild, L. S.

2015-12-01

There are limited studies in Puerto Rico that shows the water resources availability and variability with respect to changing climates and land use. The main goal of the HICE-PR (Human Impacts to Coastal Ecosystems in Puerto Rico (HICE-PR): the Río Loco Watershed (southwest coast PR) project which was funded by NASA is to evaluate the impacts of land use/land cover changes on the quality and extent of coastal and marine ecosystems (CMEs) in two priority watersheds in Puerto Rico (Manatí and Guánica).The main objective of this study is to set up a physically based spatially distributed hydrological model, Soil and Water Assessment Tool (SWAT) for the analysis of hydrological processes in the Rio Grande de Manati river basin. SWAT (soil and water assessment tool) is a spatially distributed watershed model developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds. For efficient use of distributed models for hydrological and scenario analysis, it is important that these models pass through a careful calibration and uncertainty analysis. The model was calibrated and validated using Sequential Uncertainty Fitting (SUFI-2) calibration and uncertainty analysis algorithms. The model evaluation statistics for streamflows prediction shows that there is a good agreement between the measured and simulated flows that was verified by coefficients of determination and Nash Sutcliffe efficiency greater than 0.5. Keywords: Hydrological Modeling; SWAT; SUFI-2; Rio Grande De Manati; Puerto Rico

Power-law scaling in daily rainfall patterns and consequences in urban stream discharges

NASA Astrophysics Data System (ADS)

Park, Jeryang; Krueger, Elisabeth H.; Kim, Dongkyun; Rao, Suresh C.

2016-04-01

Poissonian rainfall has been frequently used for modelling stream discharge in a catchment at the daily scale. Generally, it is assumed that the daily rainfall depth is described by memoryless exponential distribution which is transformed to stream discharge, resulting in an analytical pdf for discharge [Gamma distribution]. While it is true that catchment hydrological filtering processes (censored by constant rate ET losses, and first-order recession) increases "memory", reflected in 1/f noise in discharge time series. Here, we show that for urban watersheds in South Korea: (1) the observation of daily rainfall depths follow power-law pdfs, and spectral slopes range between 0.2 ~ 0.4; and (2) the stream discharge pdfs have power-law tails. These observation results suggest that multiple hydro-climatic factors (e.g., non-stationarity of rainfall patterns) and hydrologic filtering (increasing impervious area; more complex urban drainage networks) influence the catchment hydrologic responses. We test the role of such factors using a parsimonious model, using different types of daily rainfall patterns (e.g., power-law distributed rainfall depth with Poisson distribution in its frequency) and urban settings to reproduce patterns similar to those observed in empirical records. Our results indicate that fractality in temporally up-scaled rainfall, and the consequences of large extreme events are preserved as high discharge events in urbanizing catchments. Implications of these results to modeling urban hydrologic responses and impacts on receiving waters are discussed.

Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

Upscaling from research watersheds: an essential stage of trustworthy general-purpose hydrologic model building

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Extreme multi-basin flooding linked with extra-tropical cyclones

NASA Astrophysics Data System (ADS)

De Luca, Paolo; Hillier, John K.; Wilby, Robert L.; Quinn, Nevil W.; Harrigan, Shaun

2017-11-01

Fluvial floods are typically investigated as ‘events’ at the single basin-scale, hence flood management authorities may underestimate the threat of flooding across multiple basins driven by large-scale and nearly concurrent atmospheric event(s). We pilot a national-scale statistical analysis of the spatio-temporal characteristics of extreme multi-basin flooding (MBF) episodes, using peak river flow data for 260 basins in Great Britain (1975-2014), a sentinel region for storms impacting northwest and central Europe. During the most widespread MBF episode, 108 basins (~46% of the study area) recorded annual maximum (AMAX) discharge within a 16 day window. Such episodes are associated with persistent cyclonic and westerly atmospheric circulations, atmospheric rivers, and precipitation falling onto previously saturated ground, leading to hydrological response times <40 h and documented flood impacts. Furthermore, peak flows tend to occur after 0-13 days of very severe gales causing combined and spatially-distributed, yet differentially time-lagged, wind and flood damages. These findings have implications for emergency responders, insurers and contingency planners worldwide.

A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data

USGS Publications Warehouse

Velpuri, N.M.; Senay, G.B.; Asante, K.O.

2012-01-01

Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of interand intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellitedriven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE) of 0.80 during the validation period (2004-2009). Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1-2m. The lake level fluctuated in the range up to 4m between the years 1998-2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated satellite-driven water balance model for (i) quantitative assessment of the impact of basin developmental activities on lake levels and for (ii) forecasting lake level changes and their impact on fisheries. From this study, we suggest that globally available satellite altimetry data provide a unique opportunity for calibration and validation of hydrologic models in ungauged basins. ?? Author(s) 2012.

CREST v2.1 Refined by a Distributed Linear Reservoir Routing Scheme

NASA Astrophysics Data System (ADS)

Shen, X.; Hong, Y.; Zhang, K.; Hao, Z.; Wang, D.

2014-12-01

Hydrologic modeling is important in water resources management, and flooding disaster warning and management. Routing scheme is among the most important components of a hydrologic model. In this study, we replace the lumped LRR (linear reservoir routing) scheme used in previous versions of the distributed hydrological model, CREST (coupled routing and excess storage) by a newly proposed distributed LRR method, which is theoretically more suitable for distributed hydrological models. Consequently, we have effectively solved the problems of: 1) low values of channel flow in daily simulation, 2) discontinuous flow value along the river network during flood events and 3) irrational model parameters. The CREST model equipped with both the routing schemes have been tested in the Gan River basin. The distributed LRR scheme has been confirmed to outperform the lumped counterpart by two comparisons, hydrograph validation and visual speculation of the continuity of stream flow along the river: 1) The CREST v2.1 (version 2.1) with the implementation of the distributed LRR achieved excellent result of [NSCE(Nash coefficient), CC (correlation coefficient), bias] =[0.897, 0.947 -1.57%] while the original CREST v2.0 produced only negative NSCE, close to zero CC and large bias. 2) CREST v2.1 produced more naturally smooth river flow pattern along the river network while v2.0 simulated bumping and discontinuous discharge along the mainstream. Moreover, we further observe that by using the distributed LRR method, 1) all model parameters fell within their reasonable region after an automatic optimization; 2) CREST forced by satellite-based precipitation and PET products produces a reasonably well result, i.e., (NSCE, CC, bias) = (0.756, 0.871, -0.669%) in the case study, although there is still room to improve regarding their low spatial resolution and underestimation of the heavy rainfall events in the satellite products.

Robust Hydrological Forecasting for High-resolution Distributed Models Using a Unified Data Assimilation Approach

NASA Astrophysics Data System (ADS)

Hernandez, F.; Liang, X.

2017-12-01

Reliable real-time hydrological forecasting, to predict important phenomena such as floods, is invaluable to the society. However, modern high-resolution distributed models have faced challenges when dealing with uncertainties that are caused by the large number of parameters and initial state estimations involved. Therefore, to rely on these high-resolution models for critical real-time forecast applications, considerable improvements on the parameter and initial state estimation techniques must be made. In this work we present a unified data assimilation algorithm called Optimized PareTo Inverse Modeling through Inverse STochastic Search (OPTIMISTS) to deal with the challenge of having robust flood forecasting for high-resolution distributed models. This new algorithm combines the advantages of particle filters and variational methods in a unique way to overcome their individual weaknesses. The analysis of candidate particles compares model results with observations in a flexible time frame, and a multi-objective approach is proposed which attempts to simultaneously minimize differences with the observations and departures from the background states by using both Bayesian sampling and non-convex evolutionary optimization. Moreover, the resulting Pareto front is given a probabilistic interpretation through kernel density estimation to create a non-Gaussian distribution of the states. OPTIMISTS was tested on a low-resolution distributed land surface model using VIC (Variable Infiltration Capacity) and on a high-resolution distributed hydrological model using the DHSVM (Distributed Hydrology Soil Vegetation Model). In the tests streamflow observations are assimilated. OPTIMISTS was also compared with a traditional particle filter and a variational method. Results show that our method can reliably produce adequate forecasts and that it is able to outperform those resulting from assimilating the observations using a particle filter or an evolutionary 4D variational method alone. In addition, our method is shown to be efficient in tackling high-resolution applications with robust results.

Performance of a distributed semi-conceptual hydrological model under tropical watershed conditions

USDA-ARS?s Scientific Manuscript database

Many hydrologic models have been developed to help manage natural resources all over the world. Nevertheless, most models have presented a high complexity in terms of data base requirements, as well as, many calibration parameters. This has resulted in serious difficulties to application in catchmen...

Implementation of surface soil moisture data assimilation with watershed scale distributed hydrological model

USDA-ARS?s Scientific Manuscript database

This paper aims to investigate how surface soil moisture data assimilation affects each hydrologic process and how spatially varying inputs affect the potential capability of surface soil moisture assimilation at the watershed scale. The Ensemble Kalman Filter (EnKF) is coupled with a watershed scal...

SWAT ungauged: Hydrological budget and crop yield predictions in the Upper Mississippi River Basin

USDA-ARS?s Scientific Manuscript database

Physically based, distributed hydrologic models are increasingly used in assessments of water resources, best management practices, and climate and land use changes. Model performance evaluation in ungauged basins is an important research topic. In this study, we propose a framework for developing S...

Managing Saginaw Bay nutrient loading by surrounding watersheds through near real time hydrologic resource sheds

EPA Science Inventory

We can quantify source areas contributing material to a location during various time periods as resource sheds. Various kinds of resource sheds and their source material distributions are defined. For watershed hydrology, we compute resource sheds and their source material distri...

Evaluating the aggregate effect of geographical isolated wetlands and associated spatial and size distributions on downstream hydrologic flows

EPA Science Inventory

Geographically isolated wetlands (GIW), defined as depressional wetlands completely surrounded by uplands, support an array of ecological processes. A solid scientific understanding of the hydrologic effects of GIWs upon downstream waterways is important for legal and policy-mak...

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

Li, Hongyi; Sivapalan, Murugesu; Tian, Fuqiang

Inspired by the Dunne diagram, the climatic and landscape controls on the partitioning of annual runoff into its various components (Hortonian and Dunne overland flow and subsurface stormflow) are assessed quantitatively, from a purely theoretical perspective. A simple distributed hydrologic model has been built sufficient to simulate the effects of different combinations of climate, soil, and topography on the runoff generation processes. The model is driven by a sequence of simple hypothetical precipitation events, for a large combination of climate and landscape properties, and hydrologic responses at the catchment scale are obtained through aggregation of grid-scale responses. It is found,more » first, that the water balance responses, including relative contributions of different runoff generation mechanisms, could be related to a small set of dimensionless similarity parameters. These capture the competition between the wetting, drying, storage, and drainage functions underlying the catchment responses, and in this way, provide a quantitative approximation of the conceptual Dunne diagram. Second, only a subset of all hypothetical catchment/climate combinations is found to be ‘‘behavioral,’’ in terms of falling sufficiently close to the Budyko curve, describing mean annual runoff as a function of climate aridity. Furthermore, these behavioral combinations are mostly consistent with the qualitative picture presented in the Dunne diagram, indicating clearly the commonality between the Budyko curve and the Dunne diagram. These analyses also suggest clear interrelationships amongst the ‘‘behavioral’’ climate, soil, and topography parameter combinations, implying these catchment properties may be constrained to be codependent in order to satisfy the Budyko curve.« less

Monitoring groundwater-surface water interaction using time-series and time-frequency analysis of transient three-dimensional electrical resistivity changes

USGS Publications Warehouse

Johnson, Timothy C.; Slater, Lee D.; Ntarlagiannis, Dimitris; Day-Lewis, Frederick D.; Elwaseif, Mehrez

2012-01-01

Time-lapse resistivity imaging is increasingly used to monitor hydrologic processes. Compared to conventional hydrologic measurements, surface time-lapse resistivity provides superior spatial coverage in two or three dimensions, potentially high-resolution information in time, and information in the absence of wells. However, interpretation of time-lapse electrical tomograms is complicated by the ever-increasing size and complexity of long-term, three-dimensional (3-D) time series conductivity data sets. Here we use 3-D surface time-lapse electrical imaging to monitor subsurface electrical conductivity variations associated with stage-driven groundwater-surface water interactions along a stretch of the Columbia River adjacent to the Hanford 300 near Richland, Washington, USA. We reduce the resulting 3-D conductivity time series using both time-series and time-frequency analyses to isolate a paleochannel causing enhanced groundwater-surface water interactions. Correlation analysis on the time-lapse imaging results concisely represents enhanced groundwater-surface water interactions within the paleochannel, and provides information concerning groundwater flow velocities. Time-frequency analysis using the Stockwell (S) transform provides additional information by identifying the stage periodicities driving groundwater-surface water interactions due to upstream dam operations, and identifying segments in time-frequency space when these interactions are most active. These results provide new insight into the distribution and timing of river water intrusion into the Hanford 300 Area, which has a governing influence on the behavior of a uranium plume left over from historical nuclear fuel processing operations.

Fluid geochemistry of Yucca Mountain and vicinity

USGS Publications Warehouse

Marshall, Brian D.; Moscati, Richard J.; Patterson, Gary L.; Stuckless, John S.

2012-01-01

Yucca Mountain, a site in southwest Nevada, has been proposed for a deep underground radioactive waste repository. An extensive database of geochemical and isotopic characteristics has been established for pore waters and gases from the unsaturated zone, perched water, and saturated zone waters in the Yucca Mountain area. The development of this database has been driven by diverse needs of the Yucca Mountain Project, especially those aspects of the project involving process modeling and performance assessment. Water and gas chemistries influence the sorption behavior of radionuclides and the solubility of the radionuclide compounds that form. The chemistry of waters that may infiltrate the proposed repository will be determined in part by that of water present in the unsaturated zone above the proposed repository horizon, whereas pore-water compositions beneath the repository horizon will influence the sorption behavior of the radionuclides transported toward the water table. However, more relevant to the discussion in this chapter, development and testing of conceptual flow and transport models for the Yucca Mountain hydrologic system are strengthened through the incorporation of natural environmental tracer data into the process. Chemical and isotopic data are used to establish bounds on key hydrologic parameters and to provide corroborative evidence for model assumptions and predictions. Examples of specific issues addressed by these data include spatial and temporal variability in net fluxes, the role of faults in controlling flow paths, fracture-matrix interactions, the age and origin of perched water, and the distribution of water traveltimes.

Flow processes on the catchment scale - modeling of initial structural states and hydrological behavior in an artificial exemplary catchment

NASA Astrophysics Data System (ADS)

Maurer, Thomas; Caviedes-Voullième, Daniel; Hinz, Christoph; Gerke, Horst H.

2017-04-01

Landscapes that are heavily disturbed or newly formed by either natural processes or human activity are in a state of disequilibrium. Their initial development is thus characterized by highly dynamic processes under all climatic conditions. The primary distribution and structure of the solid phase (i.e. mineral particles forming the pore space) is one of the decisive factors for the development of hydrological behavior of the eco-hydrological system and therefore (co-) determining for its - more or less - stable final state. The artificially constructed ‚Hühnerwasser' catchment (a 6 ha area located in the open-cast lignite mine Welzow-Süd, southern Brandenburg, Germany) is a landscape laboratory where the initial eco-hydrological development is observed since 2005. The specific formation (or construction) processes generated characteristic sediment structures and distributions, resulting in a spatially heterogeneous initial state of the catchment. We developed a structure generator that simulates the characteristic distribution of the solid phase for such constructed landscapes. The program is able to generate quasi-realistic structures and sediment compositions on multiple spatial levels (1 cm up to 100 m scale). The generated structures can be i) conditioned to actual measurement values (e.g., soil texture and bulk distribution); ii) stochastically generated, and iii) calculated deterministically according to the geology and technical processes at the excavation site. Results are visualized using the GOCAD software package and the free software Paraview. Based on the 3D-spatial sediment distributions, effective hydraulic van-Genuchten parameters are calculated using pedotransfer functions. The hydraulic behavior of different sediment distribution (i.e. versions or variations of the catchment's porous body) is calculated using a numerical model developed by one of us (Caviedes-Voullième). Observation data are available from catchment monitoring are available for i) determining the boundary conditions (e.g., precipitation), and ii) the calibration / validation of the model (catchment discharge, ground water). The analysis of multiple sediment distribution scenarios should allow to approximately determine the influx of starting conditions on initial development of hydrological behavior. We present first flow modeling results for a reference (conditioned) catchment model and variations thereof. We will also give an outlook on further methodical development of our approach.

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 model that takes advantage of radial symmetry in the experimental setup. The flow model is coupled to forward models for simulating the GPR and seismic measurements, and joint inversion of the multiple data types results in images of time-varying NAPL saturation distributions. Comparison of the two approaches with results of the post-experiment excavation indicate that combining geophysical data types and incorporating hydrological constraints improves estimates of NAPL saturation relative to the conventional interpretation of the geophysical data sets. Notice: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect the official Agency policy. Mention of trade names or commercial products does not constitute endorsement or recommendation by EPA for use. This work was supported, in part, by the U.S. Dept. of Energy under Contract No. DE-AC02- 05CH11231.

The Canadian Hydrological Model (CHM): A multi-scale, variable-complexity hydrological model for cold regions

NASA Astrophysics Data System (ADS)

Marsh, C.; Pomeroy, J. W.; Wheater, H. S.

2016-12-01

There is a need for hydrological land surface schemes that can link to atmospheric models, provide hydrological prediction at multiple scales and guide the development of multiple objective water predictive systems. Distributed raster-based models suffer from an overrepresentation of topography, leading to wasted computational effort that increases uncertainty due to greater numbers of parameters and initial conditions. The Canadian Hydrological Model (CHM) is a modular, multiphysics, spatially distributed modelling framework designed for representing hydrological processes, including those that operate in cold-regions. Unstructured meshes permit variable spatial resolution, allowing coarse resolutions at low spatial variability and fine resolutions as required. Model uncertainty is reduced by lessening the necessary computational elements relative to high-resolution rasters. CHM uses a novel multi-objective approach for unstructured triangular mesh generation that fulfills hydrologically important constraints (e.g., basin boundaries, water bodies, soil classification, land cover, elevation, and slope/aspect). This provides an efficient spatial representation of parameters and initial conditions, as well as well-formed and well-graded triangles that are suitable for numerical discretization. CHM uses high-quality open source libraries and high performance computing paradigms to provide a framework that allows for integrating current state-of-the-art process algorithms. The impact of changes to model structure, including individual algorithms, parameters, initial conditions, driving meteorology, and spatial/temporal discretization can be easily tested. Initial testing of CHM compared spatial scales and model complexity for a spring melt period at a sub-arctic mountain basin. The meshing algorithm reduced the total number of computational elements and preserved the spatial heterogeneity of predictions.

A priori discretization quality metrics for distributed hydrologic modeling applications

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Natural and anthropogenic land cover change and its impact on the regional climate and hydrological extremes over Sanjiangyuan region

NASA Astrophysics Data System (ADS)

Ji, P.; Yuan, X.

2017-12-01

Located in the northern Tibetan Plateau, Sanjiangyuan is the headwater region of the Yellow River, Yangtze River and Mekong River. Besides climate change, natural and human-induced land cover change (e.g., Graze for Grass Project) is also influencing the regional hydro-climate and hydrological extremes significantly. To quantify their impacts, a land surface model (LSM) with consideration of soil moisture-lateral surface flow interaction and quasi-three-dimensional subsurface flow, is used to conduct long-term high resolution simulations driven by China Meteorological Administration Land Data Assimilation System forcing data and different land cover scenarios. In particular, the role of surface and subsurface lateral flows is also analyzed by comparing with typical one-dimensional models. Lateral flows help to simulate soil moisture variability caused by topography at hyper-resolution (e.g., 100m), which is also essential for simulating hydrological extremes including soil moisture dryness/wetness and high/low flows. The LSM will also be coupled with a regional climate model to simulate the effect of natural and anthropogenic land cover change on regional climate, with particular focus on the land-atmosphere coupling at different resolutions with different configurations in modeling land surface hydrology.

Next-Generation Intensity-Duration-Frequency Curves for Hydrologic Design in Snow-Dominated Environments

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

Yan, Hongxiang; Sun, Ning; Wigmosta, Mark

Precipitation-based intensity-duration-frequency (PREC-IDF) curves are a standard tool used to derive design floods for hydraulic infrastructure worldwide. In snow-dominated regions where a large percentage of flood events are caused by snowmelt and rain-on-snow events, the PREC-IDF design approach can lead to substantial underestimation/overestimation of design floods and associated infrastructure. In this study, next-generation IDF (NG-IDF) curves, which characterize the actual water reaching the land surface, are introduced into the design process to improve hydrologic design. The authors compared peak design flood estimates from the National Resource Conservation Service TR-55 hydrologic model driven by NG-IDF and PREC-IDF curves at 399 Snowpackmore » Telemetry (SNOTEL) stations across the western United States, all of which had at least 30 years of high-quality records. They found that about 72% of the stations in the western United States showed the potential for underdesign, for which the PREC-IDF curves underestimated peak design floods by as much as 324%. These results demonstrated the need to update the use of PREC-IDF curves to the use of NG-IDF curves for hydrologic design in snow-dominated regions.« less

Next-Generation Intensity‐Duration‐Frequency Curves for Hydrologic Design in Snow-Dominated Environments

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

Yan, Hongxiang; Sun, Ning; Wigmosta, Mark S.

Precipitation-based intensity-duration-frequency (PREC-IDF) curves are a standard tool used to derive design floods for hydraulic infrastructure worldwide. In snow-dominated regions where a large percentage of flood events are caused by snowmelt and rain-on-snow events, the PREC-IDF design approach can lead to substantial underestimation/overestimation of design floods and associated infrastructure. In this study, next-generation IDF (NG-IDF) curves, which characterize the actual water reaching the land surface, are introduced into the design process to improve hydrologic design. The authors compared peak design flood estimates from the National Resource Conservation Service TR-55 hydrologic model driven by NG-IDF and PREC-IDF curves at 399 Snowpackmore » Telemetry (SNOTEL) stations across the western United States, all of which had at least 30 years of high-quality records. They found that about 72% of the stations in the western United States showed the potential for underdesign, for which the PREC-IDF curves underestimated peak design floods by as much as 324%. These results demonstrated the need to update the use of PREC-IDF curves to the use of NG-IDF curves for hydrologic design in snow-dominated regions.« less

State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy

NASA Astrophysics Data System (ADS)

Rakovec, O.; Weerts, A. H.; Hazenberg, P.; Torfs, P. J. J. F.; Uijlenhoet, R.

2012-09-01

This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model. The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property). Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a relatively quickly responding catchment in the Belgian Ardennes. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty.

A New Approach in Generating Meteorological Forecasts for Ensemble Streamflow Forecasting using Multivariate Functions

NASA Astrophysics Data System (ADS)

Khajehei, S.; Madadgar, S.; Moradkhani, H.

2014-12-01

The reliability and accuracy of hydrological predictions are subject to various sources of uncertainty, including meteorological forcing, initial conditions, model parameters and model structure. To reduce the total uncertainty in hydrological applications, one approach is to reduce the uncertainty in meteorological forcing by using the statistical methods based on the conditional probability density functions (pdf). However, one of the requirements for current methods is to assume the Gaussian distribution for the marginal distribution of the observed and modeled meteorology. Here we propose a Bayesian approach based on Copula functions to develop the conditional distribution of precipitation forecast needed in deriving a hydrologic model for a sub-basin in the Columbia River Basin. Copula functions are introduced as an alternative approach in capturing the uncertainties related to meteorological forcing. Copulas are multivariate joint distribution of univariate marginal distributions, which are capable to model the joint behavior of variables with any level of correlation and dependency. The method is applied to the monthly forecast of CPC with 0.25x0.25 degree resolution to reproduce the PRISM dataset over 1970-2000. Results are compared with Ensemble Pre-Processor approach as a common procedure used by National Weather Service River forecast centers in reproducing observed climatology during a ten-year verification period (2000-2010).

Construction of a Distributed-network Digital Watershed Management System with B/S Techniques

NASA Astrophysics Data System (ADS)

Zhang, W. C.; Liu, Y. M.; Fang, J.

2017-07-01

Integrated watershed assessment tools for supporting land management and hydrologic research are becoming established tools in both basic and applied research. The core of these tools are mainly spatially distributed hydrologic models as they can provide a mechanism for investigating interactions among climate, topography, vegetation, and soil. However, the extensive data requirements and the difficult task of building input parameter files for driving these distributed models, have long been an obstacle to the timely and cost-effective use of such complex models by watershed managers and policy-makers. Recently, a web based geographic information system (GIS) tool to facilitate this process has been developed for a large watersheds of Jinghe and Weihe catchments located in the loess plateau of the Huanghe River basin in north-western China. A web-based GIS provides the framework within which spatially distributed data are collected and used to prepare model input files of these two watersheds and evaluate model results as well as to provide the various clients for watershed information inquiring, visualizing and assessment analysis. This Web-based Automated Geospatial Watershed Assessment GIS (WAGWA-GIS) tool uses widely available standardized spatial datasets that can be obtained via the internet oracle databank designed with association of Map Guide platform to develop input parameter files for online simulation at different spatial and temporal scales with Xing’anjiang and TOPMODEL that integrated with web-based digital watershed. WAGWA-GIS automates the process of transforming both digital data including remote sensing data, DEM, Land use/cover, soil digital maps and meteorological and hydrological station geo-location digital maps and text files containing meteorological and hydrological data obtained from stations of the watershed into hydrological models for online simulation and geo-spatial analysis and provides a visualization tool to help the user interpret results. The utility of WAGWA-GIS in jointing hydrologic and ecological investigations has been demonstrated on such diverse landscapes as Jinhe and Weihe watersheds, and will be extended to be utilized in the other watersheds in China step by step in coming years

How does precipitation become runoff? Comparison of hydrologic thresholds across hillslope and catchment scales

NASA Astrophysics Data System (ADS)

Ross, C.; Ali, G.; Oswald, C. J.; McMillan, H. K.; Walter, K.

2017-12-01

A hydrologic threshold is a critical point in time when runoff behavior rapidly changes, often in response to the activation of specific storage-driven or intensity-driven processes. Hydrologic thresholds can be viewed as characteristic signatures of hydrosystems, which makes them useful for site comparison as long as their presence (or lack thereof) can be evaluated in a standard manner across a range of environments. While several previous studies have successfully identified thresholds at a variety of individual sites, only a limited number have compared dynamics prevailing at the hillslope versus catchment scale, or distinguished the role of storage versus intensity thresholds. The objective of this study was therefore to examine precipitation input thresholds as well as "precipitation minus evapotranspiration" thresholds in environments with contrasted climatic and geographic characteristics. Historical climate and hydrometric datasets were consolidated for one hillslope site located at the Panola Mountain Research Watershed (Southeastern USA) and catchments located in the HJ Andrew's Experimental Forest (Northwestern USA), the Catfish Creek Watershed (Canadian prairies), the Experimental Lakes Area (Canadian boreal ecozone), the Tarrawarra catchment (Australia) and the Mahurangi catchment (New Zealand). Individual precipitation-runoff events were delineated using the newly introduced software HydRun to derive event-specific hydrograph parameters as well surrogate measures of antecedent moisture conditions and evapotranspiration in an automated and consistent manner. Various hydrograph parameters were then plotted against those surrogate measures to detect and evaluate site-specific threshold dynamics. Preliminary results show that a range of threshold shapes (e.g., "hockey stick", heaviside and dirac) were observed across sites. The influence of antecedent precipitation on threshold magnitude and shape also appeared stronger at sites with lower topographic relief and drier climate. Future analyses will focus on the interaction between storage and intensity thresholds in order to evaluate the importance of considering both for comparative hydrological studies.

Entropy of hydrological systems under small samples: Uncertainty and variability

NASA Astrophysics Data System (ADS)

Liu, Dengfeng; Wang, Dong; Wang, Yuankun; Wu, Jichun; Singh, Vijay P.; Zeng, Xiankui; Wang, Lachun; Chen, Yuanfang; Chen, Xi; Zhang, Liyuan; Gu, Shenghua

2016-01-01

Entropy theory has been increasingly applied in hydrology in both descriptive and inferential ways. However, little attention has been given to the small-sample condition widespread in hydrological practice, where either hydrological measurements are limited or are even nonexistent. Accordingly, entropy estimated under this condition may incur considerable bias. In this study, small-sample condition is considered and two innovative entropy estimators, the Chao-Shen (CS) estimator and the James-Stein-type shrinkage (JSS) estimator, are introduced. Simulation tests are conducted with common distributions in hydrology, that lead to the best-performing JSS estimator. Then, multi-scale moving entropy-based hydrological analyses (MM-EHA) are applied to indicate the changing patterns of uncertainty of streamflow data collected from the Yangtze River and the Yellow River, China. For further investigation into the intrinsic property of entropy applied in hydrological uncertainty analyses, correlations of entropy and other statistics at different time-scales are also calculated, which show connections between the concept of uncertainty and variability.

A Participatory Modeling Application of a Distributed Hydrologic Model in Nuevo Leon, Mexico for the 2010 Hurricane Alex Flood Event

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Geographical ecology of the palms (Arecaceae): determinants of diversity and distributions across spatial scales

PubMed Central

Eiserhardt, Wolf L.; Svenning, Jens-Christian; Kissling, W. Daniel; Balslev, Henrik

2011-01-01

Background The palm family occurs in all tropical and sub-tropical regions of the world. Palms are of high ecological and economical importance, and display complex spatial patterns of species distributions and diversity. Scope This review summarizes empirical evidence for factors that determine palm species distributions, community composition and species richness such as the abiotic environment (climate, soil chemistry, hydrology and topography), the biotic environment (vegetation structure and species interactions) and dispersal. The importance of contemporary vs. historical impacts of these factors and the scale at which they function is discussed. Finally a hierarchical scale framework is developed to guide predictor selection for future studies. Conclusions Determinants of palm distributions, composition and richness vary with spatial scale. For species distributions, climate appears to be important at landscape and broader scales, soil, topography and vegetation at landscape and local scales, hydrology at local scales, and dispersal at all scales. For community composition, soil appears important at regional and finer scales, hydrology, topography and vegetation at landscape and local scales, and dispersal again at all scales. For species richness, climate and dispersal appear to be important at continental to global scales, soil at landscape and broader scales, and topography at landscape and finer scales. Some scale–predictor combinations have not been studied or deserve further attention, e.g. climate on regional to finer scales, and hydrology and topography on landscape and broader scales. The importance of biotic interactions – apart from general vegetation structure effects – for the geographic ecology of palms is generally underexplored. Future studies should target scale–predictor combinations and geographic domains not studied yet. To avoid biased inference, one should ideally include at least all predictors previously found important at the spatial scale of investigation. PMID:21712297

A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1)

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Dorigo, Wouter; Lasslop, Gitta; Teubner, Irene; Chuvieco, Emilio; Thonicke, Kirsten

2017-12-01

Vegetation fires affect human infrastructures, ecosystems, global vegetation distribution, and atmospheric composition. However, the climatic, environmental, and socioeconomic factors that control global fire activity in vegetation are only poorly understood, and in various complexities and formulations are represented in global process-oriented vegetation-fire models. Data-driven model approaches such as machine learning algorithms have successfully been used to identify and better understand controlling factors for fire activity. However, such machine learning models cannot be easily adapted or even implemented within process-oriented global vegetation-fire models. To overcome this gap between machine learning-based approaches and process-oriented global fire models, we introduce a new flexible data-driven fire modelling approach here (Satellite Observations to predict FIre Activity, SOFIA approach version 1). SOFIA models can use several predictor variables and functional relationships to estimate burned area that can be easily adapted with more complex process-oriented vegetation-fire models. We created an ensemble of SOFIA models to test the importance of several predictor variables. SOFIA models result in the highest performance in predicting burned area if they account for a direct restriction of fire activity under wet conditions and if they include a land cover-dependent restriction or allowance of fire activity by vegetation density and biomass. The use of vegetation optical depth data from microwave satellite observations, a proxy for vegetation biomass and water content, reaches higher model performance than commonly used vegetation variables from optical sensors. We further analyse spatial patterns of the sensitivity between anthropogenic, climate, and vegetation predictor variables and burned area. We finally discuss how multiple observational datasets on climate, hydrological, vegetation, and socioeconomic variables together with data-driven modelling and model-data integration approaches can guide the future development of global process-oriented vegetation-fire models.

Fusing enhanced radar precipitation, in-situ hydrometeorological measurements and airborne LIDAR snowpack estimates in a hyper-resolution hydrologic model to improve seasonal water supply forecasts

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Busto, J.; Howard, K.; Mickey, J.; Deems, J. S.; Painter, T. H.; Richardson, M.; Dugger, A. L.; Karsten, L. R.; Tang, L.

2015-12-01

Scarcity of spatially- and temporally-continuous observations of precipitation and snowpack conditions in remote mountain watersheds results in fundamental limitations in water supply forecasting. These limitationsin observational capabilities can result in strong biases in total snowmelt-driven runoff amount, the elevational distribution of runoff, river basin tributary contributions to total basin runoff and, equally important for water management, the timing of runoff. The Upper Rio Grande River basin in Colorado and New Mexico is one basin where observational deficiencies are hypothesized to have significant adverse impacts on estimates of snowpack melt-out rates and on water supply forecasts. We present findings from a coordinated observational-modeling study within Upper Rio Grande River basin whose aim was to quanitfy the impact enhanced precipitation, meteorological and snowpack measurements on the simulation and prediction of snowmelt driven streamflow. The Rio Grande SNOwpack and streamFLOW (RIO-SNO-FLOW) Prediction Project conducted enhanced observing activities during the 2014-2015 water year. Measurements from a gap-filling, polarimetric radar (NOXP) and in-situ meteorological and snowpack measurement stations were assimilated into the WRF-Hydro modeling framework to provide continuous analyses of snowpack and streamflow conditions. Airborne lidar estimates of snowpack conditions from the NASA Airborne Snow Observatory during mid-April and mid-May were used as additional independent validations against the various model simulations and forecasts of snowpack conditions during the melt-out season. Uncalibrated WRF-Hydro model performance from simulations and forecasts driven by enhanced observational analyses were compared against results driven by currently operational data inputs. Precipitation estimates from the NOXP research radar validate significantly better against independent in situ observations of precipitation and snow-pack increases. Correcting the operational NLDAS2 forcing data with the experimental observations led to significant improvements in the seasonal accumulation and ablation of mountain snowpack and ultimately led to marked improvement in model simulated streamflow as compared with streamflow observations.

Landscape factors and hydrology influence mercury concentrations in wading birds breeding in the Florida Everglades, USA.

PubMed

Herring, Garth; Eagles-Smith, Collin A; Ackerman, Joshua T; Gawlik, Dale E; Beerens, James M

2013-08-01

The hydrology of wetland ecosystems is a key driver of both mercury (Hg) methylation and waterbird foraging ecology, and hence may play a fundamental role in waterbird exposure and risk to Hg contamination. However, few studies have investigated hydrological factors that influence waterbird Hg exposure. We examined how several landscape-level hydrological variables influenced Hg concentrations in great egret and white ibis adults and chicks in the Florida Everglades. The great egret is a visual "exploiter" species that tolerates lower prey densities and is less sensitive to hydrological conditions than is the white ibis, which is a tactile "searcher" species that pursues higher prey densities in shallow water. Mercury concentrations in adult great egrets were most influenced by the spatial region that they occupied in the Everglades (higher in the southern region); whereas the number of days a site was dry during the previous dry season was the most important factor influencing Hg concentrations in adult ibis (Hg concentrations increased with the number of days dry). In contrast, Hg concentrations in egret chicks were most influenced by calendar date (increasing with date), whereas Hg concentrations in ibis chicks were most influenced by chick age, region, and water recession rate (Hg concentrations decreased with age, were higher in the southern regions, and increased with positive water recession rates). Our results indicate that both recent (preceding two weeks) hydrological conditions, and those of the prior year, influence Hg concentrations in wading birds. Further, these results suggest that Hg exposure in wading birds is driven by complex relationships between wading bird behavior and life stage, landscape hydrologic patterns, and biogeochemical processes. Published by Elsevier B.V.

Landscape factors and hydrology influence mercury concentrations in wading birds breeding in the Florida Everglades, USA

USGS Publications Warehouse

Herring, Garth; Eagles-Smith, Collin A.; Ackerman, Joshua T.; Gawlik, Dale E.; Beerens, James M.

2013-01-01

The hydrology of wetland ecosystems is a key driver of both mercury (Hg) methylation and waterbird foraging ecology, and hence may play a fundamental role in waterbird exposure and risk to Hg contamination. However, few studies have investigated hydrological factors that influence waterbird Hg exposure. We examined how several landscape-level hydrological variables influenced Hg concentrations in great egret and white ibis adults and chicks in the Florida Everglades. The great egret is a visual “exploiter” species that tolerates lower prey densities and is less sensitive to hydrological conditions than is the white ibis, which is a tactile “searcher” species that pursues higher prey densities in shallow water. Mercury concentrations in adult great egrets were most influenced by the spatial region that they occupied in the Everglades (higher in the southern region); whereas the number of days a site was dry during the previous dry season was the most important factor influencing Hg concentrations in adult ibis (Hg concentrations increased with the number of days dry). In contrast, Hg concentrations in egret chicks were most influenced by calendar date (increasing with date), whereas Hg concentrations in ibis chicks were most influenced by chick age, region, and water recession rate (Hg concentrations decreased with age, were higher in the southern regions, and increased with positive water recession rates). Our results indicate that both recent (preceding two weeks) hydrological conditions, and those of the prior year, influence Hg concentrations in wading birds. Further, these results suggest that Hg exposure in wading birds is driven by complex relationships between wading bird behavior and life stage, landscape hydrologic patterns, and biogeochemical processes.

The Hydrological Evolution of Mars as Recorded at Gale Crater

NASA Astrophysics Data System (ADS)

Andrews-Hanna, J. C.; Horvath, D. G.

2017-12-01

The sedimentary deposits making up the Aeolis Mons sedimentary mound within Gale Crater preserve a record of the evolving hydrology and climate of Mars during the Late Noachian and Hesperian epochs. Aqueous sedimentary deposits including mudstones, deltaic deposits, and sulfate-cemented sediments indicate the past presence of liquid water on the surface. However, these observations alone do not strictly constrain the nature of the hydrology and climate at the time of deposition. We use models of the subsurface and surface hydrology to shed light on the conditions required to reproduce the observed deposits. Changes in the nature and composition of the deposits reflect changes in the balance between the surface and subsurface components of the hydrological cycle, driven by climate changes. Mudstones observed by the MSL rover at the base of the crater reflect lacustrine deposition under semi-arid conditions, with substantial fluid supply from both the surface (overland flow and direct precipitation) and subsurface. A transition at higher stratigraphic levels to sulfate-cemented sandstones required a change to a more arid climate, with the hydrology dominated by long-distance subsurface transport. Near the top of the mound, unaltered deposits indicate deposition under dry conditions, though this transition coincides with the natural limit on the rise of the water table imposed by the surrounding topography and does not require a change in climate. Erosion of the crater-filling sedimentary deposits to their present mound shape required a dramatic drop in the water table under hyper-arid conditions. Evidence for later lake stands in the Hesperian indicates transient returns to semi-arid conditions similar to those that prevailed during the Late Noachian. By coupling surface and orbital observations with hydrological modeling, we are able to make more specific constraints on the evolving climate and aridity of early Mars.

Large-scale degradation of Amazonian freshwater ecosystems

NASA Astrophysics Data System (ADS)

Castello, L.; Macedo, M.

2016-12-01

The integrity of freshwater ecosystems depends on their hydrological connectivity with land, water, and climate systems. Hydrological connectivity regulates the structure and function of Amazonian freshwater ecosystems and the provisioning of services that sustain local populations. However, the hydrological connectivity of Amazonian freshwater ecosystems is increasingly disrupted by construction of dams, mining, land-cover changes, and global climate change. This review analyzes these drivers of degradation; evaluates their impacts on hydrological connectivity; and identifies policy deficiencies that hinder freshwater ecosystem protection. There are 155 large hydroelectric dams in operation, 21 dams under construction, and there will be only three free-flowing tributaries if all 277 planned dams for the Basin are built. Land-cover changes driven by mining, dam and road construction, and agriculture and cattle ranching have already affected 20% of the Basin and up to 50% of riparian forests in some regions. Global climate change will likely exacerbate these impacts by creating warmer and dryer conditions, with less predictable rainfall and more extreme events (e.g. droughts and floods). The resulting hydrological alterations are rapidly degrading freshwater ecosystems both independently and via complex feedbacks and synergistic interactions. The ecosystem impacts include biodiversity loss, warmer stream temperatures, stronger and more frequent floodplain fires, and changes to biogeochemical cycles, transport of organic and inorganic materials, and freshwater community structure and function. The impacts also include reductions in water quality, fish yields, and availability of water for navigation, power generation, and human use. This degradation of Amazonian freshwater ecosystems cannot be curbed presently because existing policies are inconsistent across the Basin, ignore cumulative effects, and do not consider the hydrological connectivity of freshwater ecosystems. Maintaining the integrity of these freshwater ecosystems requires a basin-wide research and policy framework to understand and manage hydrological connectivity across multiple spatial scales and jurisdictional boundaries.

Probabilistic graphs as a conceptual and computational tool in hydrology and water management

NASA Astrophysics Data System (ADS)

Schoups, Gerrit

2014-05-01

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

Hydrologically-driven crustal stresses and seismicity in the New Madrid Seismic Zone.

PubMed

Craig, Timothy J; Chanard, Kristel; Calais, Eric

2017-12-15

The degree to which short-term non-tectonic processes, either natural and anthropogenic, influence the occurrence of earthquakes in active tectonic settings or 'stable' plate interiors, remains a subject of debate. Recent work in plate-boundary regions demonstrates the capacity for long-wavelength changes in continental water storage to produce observable surface deformation, induce crustal stresses and modulate seismicity rates. Here we show that a significant variation in the rate of microearthquakes in the intraplate New Madrid Seismic Zone at annual and multi-annual timescales coincides with hydrological loading in the upper Mississippi embayment. We demonstrate that this loading, which results in geodetically observed surface deformation, induces stresses within the lithosphere that, although of small amplitude, modulate the ongoing seismicity of the New Madrid region. Correspondence between surface deformation, hydrological loading and seismicity rates at both annual and multi-annual timescales indicates that seismicity variations are the direct result of elastic stresses induced by the water load.

Decadal oscillation of lakes and aquifers in the upper Great Lakes region of North America: hydroclimatic implications

USGS Publications Warehouse

Watras, C.J.; Read, J.S.; Holman, K.D.; Liu, Z.; Song, Y.-Y.; Watras, A.J.; Morgan, S.; Stanley, E.H.

2014-01-01

We report a unique hydrologic time-series which indicates that water levels in lakes and aquifers across the upper Great Lakes region of North America have been dominated by a climatically-driven, near-decadal oscillation for at least 70 years. The historical oscillation (~13y) is remarkably consistent among small seepage lakes, groundwater tables and the two largest Laurentian Great Lakes despite substantial differences in hydrology. Hydrologic analyses indicate that the oscillation has been governed primarily by changes in the net atmospheric flux of water (P-E) and stage-dependent outflow. The oscillation is hypothetically connected to large-scale atmospheric circulation patterns originating in the mid-latitude North Pacific that support the flux of moisture into the region from the Gulf of Mexico. Recent data indicate an apparent change in the historical oscillation characterized by a ~12y downward trend beginning in 1998. Record low water levels region-wide may mark the onset of a new hydroclimatic regime.

Transpiration Driven Hydrologic Transport in vegetated shallow water environments: Implications on Diel and Seasonal Soil Biogeochemical Processes and System Management

NASA Astrophysics Data System (ADS)

Bachand, P.; Bachand, S. M.; Fleck, J.; Anderson, F.

2011-12-01

Hydrology arguably plays the most important role in biogeochemical cycling of mercury in wetlands and other shallow aquatic systems. CFSTR, PFR and non-ideal reactor models are oftentimes currently used to hydrologically assess these systems and to account for the fate, transport and cycling of constituents of concern (COC) with systems assumed to be non-leaky and with diffusion dominating soil transport. Yet a number of results in the literature imply transpiration drives soil transport: transpiration into the root zone is in the range of 50 - 75% of ET seasonally; gaseous emissions from aquatic systems show a diel pattern that tracks diel ET patterns; in long detention time aquatic systems ET is the largest sink for applied surface waters; and non-reactive tracers when applied to surface waters can find themselves in the root zone and within plants. All these findings strongly suggest transpiration driven infiltration into the root zone, is a significant hydrologic pathway for constituents and is an important transport mechanism. This paper examines the annual water budget for four shallow aquatic land uses in the Yolo Bypass, California: rice, wild rice, fallowed fields and wetlands. Results indicate that differences in hydrology between the fields, particularly the temporal nature of transpiration, play a significant role in mercury transformations and transport. During the irrigation period, fallowed fields discharged 6 cm of surface water (15% applied water), rice fields 31 - 43 cm (27 - 31% applied water), and wild rice fields 16 - 39 cm (15 - 31% applied water). Evapotranspiration rates were in the range of 120 - 130 cm/y for all land uses (i.e. rice, wild rice, fallowed fields and seasonal wetlands) except for the permanent wetland which was about 1/3 higher at about 170 cm/y. During the summer, approximately 50% of the applied surface water was drawn into the root zone to meet transpiration demands. Based upon results from our water budget and utilizing modified Peclet No. calculations, we quantified the relative importance of upward diffusion from the sediments and downward advection from transpiration as hydrologic transport mechanisms in the root zone. Transpiration driven infiltration moves water past the diffusive zone within 1 - 2 days in this system during the summer months. With the waning seasons, evapotranspiration diminishes until by winter diffusion dominates throughout the entire root zone. This model has great implications on the analyses of soil biogeochemical process in the root zone of shallow aquatic systems. Downward advection is a major transport mechanism into the root zone of shallow flooded aquatic systems and provides an important physical mechanism that drives variability in the seasonal and diel storage; release and cycling of COCs; and the creation of both a physical and chemical barrierd to upward diffusion of soil-borne COCs into the water column. Models that do not account for root zone interactions may not be able to capture diel and seasonal differences. Moreover, these interactions may lead to unanticipated environmental consequences as a result of cultural practices.

Situating Green Infrastructure in Context: A Framework for Adaptive Socio-Hydrology in Cities.

PubMed

Schifman, L A; Herrmann, D L; Shuster, W D; Ossola, A; Garmestani, A; Hopton, M E

2017-12-01

Management of urban hydrologic processes using green infrastructure (GI) has largely focused on stormwater management. Thus, design and implementation of GI usually rely on physical site characteristics and local rainfall patterns, and do not typically account for human or social dimensions. This traditional approach leads to highly centralized stormwater management in a disconnected urban landscape, and can deemphasize additional benefits that GI offers, such as increased property value, greenspace aesthetics, heat island amelioration, carbon sequestration, and habitat for biodiversity. We propose a Framework for Adaptive Socio-Hydrology (FrASH) in which GI planning and implementation moves from a purely hydrology-driven perspective to an integrated socio-hydrological approach. This allows for an iterative, multifaceted decision-making process that would enable a network of stakeholders to collaboratively set a dynamic, context-guided project plan for the installation of GI, rather than a 'one-size-fits-all' installation. We explain how different sectors (e.g., governance, non-governmental organizations, academia, and industry) can create a connected network of organizations that work towards a common goal. Through a graphical Chambered Nautilus model, FrASH is experimentally applied to contrasting GI case studies and shows that this multi-stakeholder, connected, de-centralized network with a co-evolving decision-making project plan results in enhanced multi-functionality, potentially allowing for the management of resilience in urban systems at multiple scales.

One multi-media environmental system with linkage between meteorology/ hydrology/ air quality models and water quality model

NASA Astrophysics Data System (ADS)

Tang, C.; Lynch, J. A.; Dennis, R. L.

2016-12-01

The biogeochemical processing of nitrogen and associated pollutants is driven by meteorological and hydrological processes in conjunction with pollutant loading. There are feedbacks between meteorology and hydrology that will be affected by land-use change and climate change. Changes in meteorology will affect pollutant deposition. It is important to account for those feedbacks and produce internally consistent simulations of meteorology, hydrology, and pollutant loading to drive the (watershed/water quality) biogeochemical models. In this study, the ecological response to emission reductions in streams in the Potomac watershed was evaluated. Firstly, we simulated the deposition by using the fully coupled Weather Research & Forecasting (WRF) model and the Community Multiscale Air Quality (CAMQ) model; secondly, we created the hydrological data by the offline linked Variable Infiltration Capacity (VIC) model and the WRF model. Lastly, we investigated the water quality by one comprehensive/environment model, namely the linkage of CMAQ, WRF, VIC and the Model of Acidification of Groundwater In Catchment (MAGIC) model from 2002 to 2010.The simulated results (such as NO3, SO4, and SBC) fit well to the observed values. The linkage provides a generally accurate, well-tested tool for evaluating sensitivities to varying meteorology and environmental changes on acidification and other biogeochemical processes, with capability to comprehensively explore strategic policy and management design.

A community initiative for developing data and modeling driven curriculum modules for hydrology education

NASA Astrophysics Data System (ADS)

Ruddell, B. L.; Merwade, V.

2010-12-01

Hydrology and geoscience education at the undergraduate and graduate levels may benefit greatly from a structured approach to pedagogy that utilizes modeling, authentic data, and simulation exercises to engage students in practice-like activities. Extensive evidence in the educational literature suggests that students retain more of their instruction, and attain higher levels of mastery over content, when interactive and practice-like activities are used to contextualize traditional lecture-based and theory-based instruction. However, it is also important that these activities carefully link the use of data and modeling to abstract theory, to promote transfer of knowledge to other contexts. While this type of data-based activity has been practiced in the hydrology classroom for decades, the hydrology community still lacks a set of standards and a mechanism for community-based development, publication, and review of this type of curriculum material. A community-based initiative is underway to develop a set curriculum materials to teach hydrology in the engineering and geoscience university classroom using outcomes-based, pedagogically rigorous modules that use authentic data and modeling experiences to complement traditional lecture-based instruction. A preliminary design for a community cyberinfrastructure for shared module development and publication, and for module topics and outcomes and ametadata and module interoperability standards, will be presented, along with the results of a series of community surveys and workshops informing this design.

Historical trends and the long-term changes of the hydrological cycle components in a Mediterranean river basin.

PubMed

Mentzafou, A; Wagner, S; Dimitriou, E

2018-04-29

Identifying the historical hydrometeorological trends in a river basin is necessary for understanding the dominant interactions between climate, human activities and local hydromorphological conditions. Estimating the hydrological reference conditions in a river is also crucial for estimating accurately the impacts from human water related activities and design appropriate water management schemes. In this effort, the output of a regional past climate model was used, covering the period from 1660 to 1990, in combination with a dynamic, spatially distributed, hydrologic model to estimate the past and recent trends in the main hydrologic parameters such as overland flow, water storages and evapotranspiration, in a Mediterranean river basin. The simulated past hydrologic conditions (1660-1960) were compared with the current hydrologic regime (1960-1990), to assess the magnitude of human and natural impacts on the identified hydrologic trends. The hydrological components of the recent period of 2008-2016 were also examined in relation to the impact of human activities. The estimated long-term trends of the hydrologic parameters were partially assigned to varying atmospheric forcing due to volcanic activity combined with spontaneous meteorological fluctuations. Copyright © 2018. Published by Elsevier B.V.

Streamflow estimation in ungauged basins using remote sensed hydrological data

NASA Astrophysics Data System (ADS)

Vasquez, Nicolas; Vargas, Ximena

2017-04-01

In several parts of the world the scarcity of streamflow gauging stations produces an important deficit of information, and calibrating these basins remains a challenge for hydrologists. Improvements in remote sensing have provided significant information about hydrological cycle, which can be used to calibrate a hydrological model when streamflow information is not available. Several satellite products related to snow, evapotranspiration, soil moisture, among other variables provide essential information about hydrological processes, and can be used to calibrate physically based hydrological models. Despite this useful information, other aspects are unknown like aquifers dimensions or precipitation heterogeneity. We calibrated three snow driven basins in the Coquimbo Region in Northern Chile, using fSCA from MODIS (MOD10 and MYD10) and NDSI from Landsat. We also considered the MOD16 product to estimate evapotranspiration. Soil Moisture from AMSR-E was considered but it was not useful due to the spatial resolution of the product and the high heterogeneity of the terrain. The Cold Regional Hydrological Modal (CHRM) was selected to represent the hydrological processes due to the importance of snow processes which are, by far, the most important in this area, where precipitation falls as snow principally in winter (June to August) and the melting period begins in spring (September) and ends in the beginning of summer (December and January). The inputs used in the model are precipitation, temperature, short wave radiation, wind speed and relative humidity. The meteorological information was obtained from stations available in the area, and distributed spatially using orographic gradients for wind and precipitation and lapse rates for air temperature and dew point temperature. Short wave radiation was computed and corrected by cloud cover data from MODIS. Streamflow data was available but it was not used in the calibration process. The three basins are Cochiguaz river at Peñón (676 km2), Derecho river at Alcohuaz (338 km2) and Toro river in confluence with La Laguna river (468 km2). These sub-basins are part of the Elqui river basins and are located in the Andes Cordillera, Chile. The mean altitude are 3508 (m.a.s.l), 3543 (m.a.s.l) and 3625 (m.a.s.l) respectively. For the calibration period (2002 to 2014), the NSE of the fSCA are 0.85 and 0.87 for Cochiguaz and Derecho rivers. The Toro river was separated in two rivers: Vacas Heladas and Malo. NSE for these two last basins are 0.77 and 0.78. For ET, the analysis relies on the number of pixels inside each basin, but annually, the R2 are 0.62, 0.43, 0.46 and 0.58 for the four sub-basins. Some biases are noticed when ET is analyzed. For streamflow, the NSE were 0.64, 0.34 and 0.08 for Cochiguaz, Derecho and Toro river in the calibration period. Additionally, due to the uncertainty about the aquifers dimensions, a sensitivity analysis was performed.

Using Isomap to differentiate between anthropogenic and natural effects on groundwater dynamics in a complex geological setting

NASA Astrophysics Data System (ADS)

Boettcher, Steven; Merz, Christoph; Lischeid, Gunnar

2015-04-01

The water budget of many catchments has vastly changed throughout the last decades. Intensified land use and increased water withdrawal for drinking water production and irrigation are likely to intensify pressure on water resources. According to model predictions, changing rainfall intensity, duration and spatial distribution in conjunction with increasing temperatures will worsen the situation in the future. The current water resources management has to adapt to these negative developments and to account for competing demands and threats. Essential for successful management applications is the identification and the quantification of the cause-and-effect chains driving the hydrological behavior of a catchment on the scale of management. It needs to check direction and magnitude of intended effects of measures taken as well as to identify unintended side effects that interact with natural effects in heterogeneous environments (Wood et al., 1988; Bloschl and Sivapalan, 1995). Therefore, these tools have to be able to distinguish between natural and anthropogenic driven impacts, even in complex geological settings like the Pleistocene landscape of North-East Germany. This study presents an approach that utilizes monitoring data to detect and quantitatively describe the predominant processes or factors of an observed hydrological system. The multivariate data analysis involves a non-linear dimension reduction method called Isometric Feature Mapping (Isomap, Tenenbaum et al., 2000) to extract information about the causes for the observed dynamics. Ordination methods like Isomap are used to derive a meaningful low-dimensional representation of a complex, high-dimensional data set. The approach is based on the hypothesis, that the number of processes which explain the variance of the data is relative low although the intensity of the processes varies in time and space. Therefore, the results can be interpreted in reference to the effective hydrological processes which control the system. The method was applied on a data set of groundwater head and lake water level. Two factors explaining more than 95 percent of the observed spatial variations were identified: (1) the anthropogenic impact of a waterworks in the study area and (2) natural groundwater recharge dynamics of different degrees of dampening at the respective sites of observation. The spatial variation of the identified processes revealed previously unknown hydraulic connections between two aquifers and between surface water bodies and groundwater. The obtained information can be used to reduce model structure uncertainty and a more efficient process-based modeling of hydraulic system behavior. Thus, the approach provides essential information to evaluate and adapt strategies for an integrated water resources management in complex landscapes. Bloschl, G., Sivapalan, M., 1995. Scale Issues in Hydrological Modeling - a Review. Hydrological Processes, 9(3-4): 251-290. Tenenbaum, J.B., de Silva, V., Langford, J.C., 2000. A global geometric framework for nonlinear dimensionality reduction. Science, 290: 2319-2323. Wood, E.F., Sivapalan, M., Beven, K., Band, L., 1988. Effects of Spatial Variability and Scale with Implications to Hydrologic Modeling. Journal of Hydrology, 102(1-4): 29-47.

Assessing the Ability of Vegetation Indices to Identify Shallow Subsurface Water Flow Pathways from Hyperspectral Imagery Using Machine Learning: Methodology

NASA Astrophysics Data System (ADS)

Byers, J. M.; Doctor, K.

2017-12-01

A common application of the satellite and airborne acquired hyperspectral imagery in the visible and NIR spectrum is the assessment of vegetation. Various absorption features of plants related to both water and chlorophyll content can be used to measure the vigor and access to underlying water sources of the vegetation. The typical strategy is to form hand-crafted features from the hyperspectral data cube by selecting two wavelengths to form difference or ratio images in the pixel space. The new image attempts to provide greater contrast for some feature of the vegetation. The Normalized Difference Vegetation Index (NDVI) is a widely used example formed from the ratio of differences and sums at two different wavelengths. There are dozens of these indices that are ostensibly formed using insights about the underlying physics of the spectral absorption with claims to efficacy in representing various properties of vegetation. In the language of machine learning these vegetation indices are features that can be used as a useful data representation within an algorithm. In this work we use a powerful approach from machine learning, probabilistic graphical models (PGM), to balance the competing needs of using existing hydrological classifications of terrain while finding statistically reliable features within hyperspectral data for identifying the generative process of the data. The algorithm in its simplest form is called a Naïve Bayes (NB) classifier and can be constructed in a data-driven estimation procedure of the conditional probability distributions that form the PGM. The Naïve Bayes model assumes that all vegetation indices (VI) are independent of one another given the hydrological class label. We seek to test its validity in a pilot study of detecting subsurface water flow pathways from VI. A more sophisticated PGM will also be explored called a tree-augmented NB that accounts for the probabilistic dependence between VI features. This methodology provides a general approach for classifying hydrological structures from hyperspectral data.

Late Glacial and Holocene avulsions of the Rio Pastaza Megafan (Ecuador-Peru): frequency and controlling factors

NASA Astrophysics Data System (ADS)

Bernal, Carolina; Christophoul, Frédéric; Darrozes, José; Soula, Jean-Claude; Baby, Patrice; Burgos, José

2011-10-01

The geomorphological study by means of remote sensing imagery of the Rio Pastaza Megafan (Ecuador and northern Peru) reveals the traces of numerous avulsions. One hundred and eight avulsion sites have been defined. The location of these sites, the available radiocarbon ages as well as historical maps of the seventeenth century, enable us to propose an evolution history of the migration and avulsions of the Rio Pastaza since the Last Glacial Maximum. The first avulsions of the Río Pastaza occurred after the LGM in a zone close to and roughly parallel to the sudandean front, where the developed avulsion gave a distributive pattern to the ancient stream of the Río Pastaza in an area located between the modern Río Morona and Pastaza, where they caused the Rio Pastaza to develop a fan-like distributary pattern. This is interpreted as a response to thrust-related forelimb tilt, progressively shifting eastward the Rio Pastaza and the apex of the megafan. This sequence of events ended with the Great Diversion of the Rio Pastaza towards the modern Rios Corrientes and Tigre. Avulsions occurred in the Tigre-Corrientes Area between 9200 and 8,500 years Cal BP. Afterwards, the Río Pastaza was diverted to its present-day north-south course. This last significant avulsion occurred before AD 1691. In the area located between the modern Río Morona and Pastaza, avulsion frequency—probably overestimated—ranges between 100 and 200 years. In the Ríos Tigre and Corrientes area, avulsion frequency—probably underestimated—ranges from 300 to 400 years. Regional tectonics is likely to have triggered most of the avulsions in the Morona Pastaza area but its influence is restricted to this area. The factors controlling the avulsions in the Tigre-Corrientes area are less clear because the frequently described "hydrologic"-driven avulsion as observed in areas characterized by contrasted hydrologic cycles are inconsistent with the characteristics of the hydrologic cycles of the Rio Pastaza.

A simple topography-driven, calibration-free runoff generation model

NASA Astrophysics Data System (ADS)

Gao, H.; Birkel, C.; Hrachowitz, M.; Tetzlaff, D.; Soulsby, C.; Savenije, H. H. G.

2017-12-01

Determining the amount of runoff generation from rainfall occupies a central place in rainfall-runoff modelling. Moreover, reading landscapes and developing calibration-free runoff generation models that adequately reflect land surface heterogeneities remains the focus of much hydrological research. In this study, we created a new method to estimate runoff generation - HAND-based Storage Capacity curve (HSC) which uses a topographic index (HAND, Height Above the Nearest Drainage) to identify hydrological similarity and partially the saturated areas of catchments. We then coupled the HSC model with the Mass Curve Technique (MCT) method to estimate root zone storage capacity (SuMax), and obtained the calibration-free runoff generation model HSC-MCT. Both the two models (HSC and HSC-MCT) allow us to estimate runoff generation and simultaneously visualize the spatial dynamic of saturated area. We tested the two models in the data-rich Bruntland Burn (BB) experimental catchment in Scotland with an unusual time series of the field-mapped saturation area extent. The models were subsequently tested in 323 MOPEX (Model Parameter Estimation Experiment) catchments in the United States. HBV and TOPMODEL were used as benchmarks. We found that the HSC performed better in reproducing the spatio-temporal pattern of the observed saturated areas in the BB catchment compared with TOPMODEL which is based on the topographic wetness index (TWI). The HSC also outperformed HBV and TOPMODEL in the MOPEX catchments for both calibration and validation. Despite having no calibrated parameters, the HSC-MCT model also performed comparably well with the calibrated HBV and TOPMODEL, highlighting the robustness of the HSC model to both describe the spatial distribution of the root zone storage capacity and the efficiency of the MCT method to estimate the SuMax. Moreover, the HSC-MCT model facilitated effective visualization of the saturated area, which has the potential to be used for broader geoscience studies beyond hydrology.

A Seamless Framework for Global Water Cycle Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Sheffield, J.; Wood, E. F.; Chaney, N.; Fisher, C. K.; Caylor, K. K.

2013-12-01

The Global Earth Observation System of Systems (GEOSS) Water Strategy ('From Observations to Decisions') recognizes that 'water is essential for ensuring food and energy security, for facilitating poverty reduction and health security, and for the maintenance of ecosystems and biodiversity', and that water cycle data and observations are critical for improved water management and water security - especially in less developed regions. The GEOSS Water Strategy has articulated a number of goals for improved water management, including flood and drought preparedness, that include: (i) facilitating the use of Earth Observations for water cycle observations; (ii) facilitating the acquisition, processing, and distribution of data products needed for effective management; (iii) providing expertise, information systems, and datasets to the global, regional, and national water communities. There are several challenges that must be met to advance our capability to provide near real-time water cycle monitoring, early warning of hydrological hazards (floods and droughts) and risk assessment under climate change, regionally and globally. Current approaches to monitoring and predicting hydrological hazards are limited in many parts of the world, and especially in developing countries where national capacity is limited and monitoring networks are inadequate. This presentation describes the development of a seamless monitoring and prediction framework at all time scales that allows for consistent assessment of water variability from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental, global water cycle monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict current hydrological conditions, flood potential and the state of drought. Seasonal climate model forecasts are downscaled and bias-corrected to drive the land surface model to provide hydrological forecasts and drought products out 6-9 months. The system relies on historic reconstructions of water variability over the 20th century, which forms the background climatology to which current conditions can be assessed. Future changes in water availability and drought risk are quantified based on bias-corrected and downscaled climate model projections that are used to drive the land surface models. For regions with lack of on-the-ground data we are field-testing low-cost environmental sensors and along with new satellite products for terrestrial hydrology and vegetation, integrating these into the system for improved monitoring and prediction. We provide an overview of the system and some examples of real-world applications to flood and drought events, with a focus on Africa.

CLEANER-Hydrologic Observatory Joint Science Plan

NASA Astrophysics Data System (ADS)

Welty, C.; Dressler, K.; Hooper, R.

2005-12-01

The CLEANER-Hydrologic Observatory* initiative is a distributed network for research on complex environmental systems that focuses on the intersecting water-related issues of both the CUAHSI and CLEANER communities. It emphasizes research on the nation's water resources related to human-dominated natural and built environments. The network will be comprised of: interacting field sites with an integrated cyberinfrastructure; a centralized technical resource staff and management infrastructure to support interdisciplinary research through data collection from advanced sensor systems, data mining and aggregation from multiple sources and databases; cyber-tools for analysis, visualization, and predictive multi-scale modeling that is dynamically driven. As such, the network will transform 21st century workforce development in the water-related intersection of environmental science and engineering, as well as enable substantial educational and engagement opportunities for all age levels. The scientific goal and strategic intent of the CLEANER-Hydrologic Observatory Network is to transform our understanding of the earth's water cycle and associated biogeochemical cycles across spatial and temporal scales-enabling quantitative forecasts of critical water-related processes, especially those that affect and are affected by human activities. This strategy will develop scientific and engineering tools that will enable more effective adaptive approaches for resource management. The need for the network is based on three critical deficiencies in current abilities to understand large-scale environmental processes and thereby develop more effective management strategies. First we lack basic data and the infrastructure to collect them at the needed resolution. Second, we lack the means to integrate data across scales from different media (paper records, electronic worksheets, web-based) and sources (observations, experiments, simulations). Third, we lack sufficiently accurate modeling and decision-support tools to predict the underlying processes or subsequently forecast the effects of different management strategies. Water is a critical driver for the functioning of all ecosystems and development of human society, and it is a key ingredient for the success of industry, agriculture and, national economy. CLEANER-Hydrologic Observatories will foster cutting-edge science and engineering research that addresses major national needs (public and governmental) related to water and include, for example: (i) water resource problems, such as impaired surface waters, contaminated ground water, water availability for human use and ecosystem needs, floods and floodplain management, urban storm water, agricultural runoff, and coastal hypoxia; (ii) understanding environmental impacts on public health; (iii) achieving a balance of economic and environmental sustainability; (iv) reversing environmental degradation; and (v) protecting against chemical and biological threats. CLEANER (Collaborative Large-scale Engineering Analysis Network for Environmental Research) is an ENG initiative; the Hydrologic Observatory Network is GEO initiative through CUAHSI (Consortium of Universities for the Advancement of Hydrologic Science, Inc.). The two initiatives were merged into a joint, bi-directorate program in December 2004.

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

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

Simulating the hydrologic cycle in coal mining subsidence areas with a distributed hydrologic model

PubMed Central

Wang, Jianhua; Lu, Chuiyu; Sun, Qingyan; Xiao, Weihua; Cao, Guoliang; Li, Hui; Yan, Lingjia; Zhang, Bo

2017-01-01

Large-scale ground subsidence caused by coal mining and subsequent water-filling leads to serious environmental problems and economic losses, especially in plains with a high phreatic water level. Clarifying the hydrologic cycle in subsidence areas has important practical value for environmental remediation, and provides a scientific basis for water resource development and utilisation of the subsidence areas. Here we present a simulation approach to describe interactions between subsidence area water (SW) and several hydrologic factors from the River-Subsidence-Groundwater Model (RSGM), which is developed based on the distributed hydrologic model. Analysis of water balance shows that the recharge of SW from groundwater only accounts for a small fraction of the total water source, due to weak groundwater flow in the plain. The interaction between SW and groundwater has an obvious annual cycle. The SW basically performs as a net source of groundwater in the wet season, and a net sink for groundwater in the dry season. The results show there is an average 905.34 million m3 per year of water available through the Huainan coal mining subsidence areas (HCMSs). If these subsidence areas can be integrated into water resource planning, the increasingly precarious water supply infrastructure will be strengthened. PMID:28106048

Gsflow-py: An integrated hydrologic model development tool

NASA Astrophysics Data System (ADS)

Gardner, M.; Niswonger, R. G.; Morton, C.; Henson, W.; Huntington, J. L.

2017-12-01

Integrated hydrologic modeling encompasses a vast number of processes and specifications, variable in time and space, and development of model datasets can be arduous. Model input construction techniques have not been formalized or made easily reproducible. Creating the input files for integrated hydrologic models (IHM) requires complex GIS processing of raster and vector datasets from various sources. Developing stream network topology that is consistent with the model resolution digital elevation model is important for robust simulation of surface water and groundwater exchanges. Distribution of meteorologic parameters over the model domain is difficult in complex terrain at the model resolution scale, but is necessary to drive realistic simulations. Historically, development of input data for IHM models has required extensive GIS and computer programming expertise which has restricted the use of IHMs to research groups with available financial, human, and technical resources. Here we present a series of Python scripts that provide a formalized technique for the parameterization and development of integrated hydrologic model inputs for GSFLOW. With some modifications, this process could be applied to any regular grid hydrologic model. This Python toolkit automates many of the necessary and laborious processes of parameterization, including stream network development and cascade routing, land coverages, and meteorological distribution over the model domain.

Transport of fluorobenzoate tracers in a vegetated hydrologic control volume: 2. Theoretical inferences and modeling

NASA Astrophysics Data System (ADS)

Queloz, Pierre; Carraro, Luca; Benettin, Paolo; Botter, Gianluca; Rinaldo, Andrea; Bertuzzo, Enrico

2015-04-01

A theoretical analysis of transport in a controlled hydrologic volume, inclusive of two willow trees and forced by erratic water inputs, is carried out contrasting the experimental data described in a companion paper. The data refer to the hydrologic transport in a large lysimeter of different fluorobenzoic acids seen as tracers. Export of solute is modeled through a recently developed framework which accounts for nonstationary travel time distributions where we parameterize how output fluxes (namely, discharge and evapotranspiration) sample the available water ages in storage. The relevance of this work lies in the study of hydrologic drivers of the nonstationary character of residence and travel time distributions, whose definition and computation shape this theoretical transport study. Our results show that a large fraction of the different behaviors exhibited by the tracers may be charged to the variability of the hydrologic forcings experienced after the injection. Moreover, the results highlight the crucial, and often overlooked, role of evapotranspiration and plant uptake in determining the transport of water and solutes. This application also suggests that the ways evapotranspiration selects water with different ages in storage can be inferred through model calibration contrasting only tracer concentrations in the discharge. A view on upscaled transport volumes like hillslopes or catchments is maintained throughout the paper.

A micro-hydrology computation ordering algorithm

NASA Astrophysics Data System (ADS)

Croley, Thomas E.

1980-11-01

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

The Hydrology of Malaria: Model Development and Application to a Sahelian Village

NASA Astrophysics Data System (ADS)

Bomblies, A.; Duchemin, J.; Eltahir, E. A.

2008-12-01

We present a coupled hydrology and entomology model for the mechanistic simulation of local-scale response of malaria transmission to hydrological and climatological determinants in semi-arid, desert fringe environments. The model is applied to the Sahel village of Banizoumbou, Niger, to predict interannual variability in malaria vector mosquito populations which lead to variations in malaria transmission. Using a high-resolution, small-scale distributed hydrology model that incorporates remotely-sensed data for land cover and topography, we simulate the formation and persistence of the pools constituting the primary breeding habitat of Anopheles gambiae s.l. mosquitoes, the principal regional malaria vector mosquitoes. An agent-based mosquito population model is coupled to the distributed hydrology model, with aquatic stage and adult stage components. For each individual adult mosquito, the model tracks attributes relevant to population dynamics and malaria transmission, which are updated as mosquitoes interact with their environment, humans, and animals. Weekly field observations were made in 2005 and 2006. The model reproduces mosquito population variability at seasonal and interannual time scales, and highlights individual pool persistence as a dominant control. Future developments to the presented model can be used in the evaluation of impacts of climate change on malaria, as well as the a priori evaluation of environmental management-based interventions.

Climate driven changes to rainfall and streamflow patterns in a model tropical island hydrological system

Treesearch

Ayron M. Strauch; Richard A. MacKenzie; Christian P. Giardina; Gregory L. Bruland

2015-01-01

Rising atmospheric CO2 and resulting warming are expected to impact freshwater resources in the tropics, but few studies have documented how natural stream flow regimes in tropical watersheds will respond to changing rainfall patterns. To address this data gap, we utilized a space-for-time substitution across a naturally occurring and highly...

Modeling soil heating and moisture transport under extreme conditions: Forest fires and slash pile burns

Treesearch

W. J. Massman

2012-01-01

Heating any soil during a sufficiently intense wildfire or prescribed burn can alter it irreversibly, causing many significant, long-term biological, chemical, and hydrological effects. Given the climate-change-driven increasing probability of wildfires and the increasing use of prescribed burns by land managers, it is important to better understand the dynamics of the...

Comparison of threshold hydrologic response across northern catchments

Treesearch

Genevieve Ali; Doerthe Tetzlaff; Jeffrey J. McDonnell; Chris Soulsby; Sean Carey; Hjalmar Laudon; Kevin McGuire; Jim Buttle; Jan Seibert; Jamie Shanley

2015-01-01

Nine mid-latitude to high-latitude headwater catchments – part of the Northern Watershed Ecosystem Response to Climate Change (North-Watch) programme – were used to analyze threshold response to rainfall and snowmelt-driven events and link the different responses to the catchment characteristics of the nine sites. The North-Watch data include daily time-series of...

Minimal groundwater leakage restricts salinity in a hydrologically terminal basin of northwest Australia

NASA Astrophysics Data System (ADS)

Skrzypek, Grzegorz; Dogramaci, Shawan; Rouillard, Alexandra; Grierson, Pauline

2016-04-01

The Fortescue Marsh (FM) is one of the largest wetlands of arid northwest Australia (~1200 km2) and is thought to act as a terminal basin for the Upper Fortescue River catchment. Unlike the playa lake systems that predominate in most arid regions, where salinity is driven by inflow and evaporation of groundwater, the hydrological regime of the FM is driven by inundation from irregular cyclonic events [1]. Surface water of the FM is fresh to brackish and the salinity of the deepest groundwater (80 m b.g.l.) does not exceed 160 g/L; salt efflorescences are rarely present on the surface [2]. In this study, we tested the hypothesis that persistent but low rates of groundwater outflow have restricted the accumulation of salt in the FM over time. Using hydrological, hydrochemical data and dimensionless time evaporation modelling along with the water and salt budget, we calculated the time and the annual groundwater discharge volume that would be required to achieve and maintain the range of salinity levels observed in the Marsh. Groundwater outflow from alluvial and colluvial aquifers to the Lower Fortescue catchment is limited by an extremely low hydraulic gradient of 0.001 and is restricted to a relatively small 'alluvial window' of 0.35 km2 because of the elevation of the basement bedrock at the Marsh outflow. We show that if the Marsh was 100% "leakage free" i.e., a true terminal basin for the Upper Fortescue Catchment, the basin water would have achieved salt saturation after ~45 ka. This is not the case and only a very small outflow of saline groundwater of <2 GL/yr (<0.03% of the FM water volume) is needed to maintain the current salinity conditions. The minimum time required to develop the current hydrochemical composition of the water in the Marsh and the steady-state conditions for salt concentration is between 58 and 164 ka. This is a minimum age of the Marsh but it can be much older as nearly steady-state conditions could be maintained infinitely. Our approach using a combined water and salt mass balance allows a more robust assessment of the hydrological budget of such a large-scale basin. The dimensionless time versus inflow over outflow ratio model is also more accurate than the classical water budget calculations. [1] Rouillard A., Skrzypek G, Dogramaci S, Turney C, Grierson PF, 2015. Impacts of high inter-annual variability of rainfall on a century of extreme hydrological regime of northwest Australia. Hydrology and Earth System Sciences 19: 2057-2078. [2] Skrzypek G., Dogramaci S., Grierson P.F., 2013, Geochemical and hydrological processes controlling groundwater salinity of a large inland wetland of northwest Australia. Chemical Geology 357: 164-177.

RELATING WEIGHT AND COUNT DISTRIBUTIONS OF STREAM BED GRAVEL

EPA Science Inventory

The size distribution of particles in a stream bed reflects the stream hydrology as well as its physical and chemical water quality characteristics. In environmental assessments, gravel distribution determines habitat quality for aquatic insects and stream suitability for spawnin...

ASSESSMENT OF LAND USE CHANGE IMPACTS ON FLOW CHARACTERISTICS IN AN EASTERN PENNSYLVANIA WATERSHED

EPA Science Inventory

The impacts of changes in land use/cover due to urbanization on the hydrologic regime of the watershed have long been recognized and have been the subject of many studies. Distributed hydrologic models are one means of assessing such impacts. In this study we evaluated the potent...

Integrated landscape/hydrologic modeling tool for semiarid watersheds

Treesearch

Mariano Hernandez; Scott N. Miller

2000-01-01

An integrated hydrologic modeling/watershed assessment tool is being developed to aid in determining the susceptibility of semiarid landscapes to natural and human-induced changes across a range of scales. Watershed processes are by definition spatially distributed and are highly variable through time, and this approach is designed to account for their spatial and...

Making it Easy to Construct Accurate Hydrological Models that Exploit High Performance Computers (Invited)

NASA Astrophysics Data System (ADS)

Kees, C. E.; Farthing, M. W.; Terrel, A.; Certik, O.; Seljebotn, D.

2013-12-01

This presentation will focus on two barriers to progress in the hydrological modeling community, and research and development conducted to lessen or eliminate them. The first is a barrier to sharing hydrological models among specialized scientists that is caused by intertwining the implementation of numerical methods with the implementation of abstract numerical modeling information. In the Proteus toolkit for computational methods and simulation, we have decoupled these two important parts of computational model through separate "physics" and "numerics" interfaces. More recently we have begun developing the Strong Form Language for easy and direct representation of the mathematical model formulation in a domain specific language embedded in Python. The second major barrier is sharing ANY scientific software tools that have complex library or module dependencies, as most parallel, multi-physics hydrological models must have. In this setting, users and developer are dependent on an entire distribution, possibly depending on multiple compilers and special instructions depending on the environment of the target machine. To solve these problem we have developed, hashdist, a stateless package management tool and a resulting portable, open source scientific software distribution.

Terrestrial water storage variations and surface vertical deformation derived from GPS and GRACE observations in Nepal and Himalayas

NASA Astrophysics Data System (ADS)

Pan, Y.; Shen, W.; Hwang, C.

2015-12-01

As an elastic Earth, the surface vertical deformation is in response to hydrological mass change on or near Earth's surface. The continuous GPS (CGPS) records show surface vertical deformations which are significant information to estimate the variation of terrestrial water storage. We compute the loading deformations at GPS stations based on synthetic models of seasonal water load distribution and then invert the synthetic GPS data for surface mass distribution. We use GRACE gravity observations and hydrology models to evaluate seasonal water storage variability in Nepal and Himalayas. The coherence among GPS inversion results, GRACE and hydrology models indicate that GPS can provide quantitative estimates of terrestrial water storage variations by inverting the surface deformation observations. The annual peak-to-peak surface mass change derived from GPS and GRACE results reveal seasonal loads oscillations of water, snow and ice. Meanwhile, the present uplifting of Nepal and Himalayas indicates the hydrology mass loss. This study is supported by National 973 Project China (grant Nos. 2013CB733302 and 2013CB733305), NSFC (grant Nos. 41174011, 41429401, 41210006, 41128003, 41021061).

Critical zone evolution and the origins of organised complexity in watersheds

NASA Astrophysics Data System (ADS)

Harman, C.; Troch, P. A.; Pelletier, J.; Rasmussen, C.; Chorover, J.

2012-04-01

The capacity of the landscape to store and transmit water is the result of a historical trajectory of landscape, soil and vegetation development, much of which is driven by hydrology itself. Progress in geomorphology and pedology has produced models of surface and sub-surface evolution in soil-mantled uplands. These dissected, denuding modeled landscapes are emblematic of the kinds of dissipative self-organized flow structures whose hydrologic organization may also be understood by low-dimensional hydrologic models. They offer an exciting starting-point for examining the mapping between the long-term controls on landscape evolution and the high-frequency hydrologic dynamics. Here we build on recent theoretical developments in geomorphology and pedology to try to understand how the relative rates of erosion, sediment transport and soil development in a landscape determine catchment storage capacity and the relative dominance of runoff process, flow pathways and storage-discharge relationships. We do so by using a combination of landscape evolution models, hydrologic process models and data from a variety of sources, including the University of Arizona Critical Zone Observatory. A challenge to linking the landscape evolution and hydrologic model representations is the vast differences in the timescales implicit in the process representations. Furthermore the vast array of processes involved makes parameterization of such models an enormous challenge. The best data-constrained geomorphic transport and soil development laws only represent hydrologic processes implicitly, through the transport and weathering rate parameters. In this work we propose to avoid this problem by identifying the relationship between the landscape and soil evolution parameters and macroscopic climate and geological controls. These macroscopic controls (such as the aridity index) have two roles: 1) they express the water and energy constraints on the long-term evolution of the landscape system, and 2) they bound the range of plausible short-term hydroclimatic regimes that may drive a particular landscape's hydrologic dynamics. To ensure that the hydrologic dynamics implicit in the evolutionary parameters are compatible with the dynamics observed in the hydrologic modeling, a set of consistency checks based on flow process dominance are developed.

Hydrologic impacts of thawing permafrost—A review

USGS Publications Warehouse

Walvoord, Michelle Ann; Kurylyk, Barret L.

2016-01-01

Where present, permafrost exerts a primary control on water fluxes, flowpaths, and distribution. Climate warming and related drivers of soil thermal change are expected to modify the distribution of permafrost, leading to changing hydrologic conditions, including alterations in soil moisture, connectivity of inland waters, streamflow seasonality, and the partitioning of water stored above and below ground. The field of permafrost hydrology is undergoing rapid advancement with respect to multiscale observations, subsurface characterization, modeling, and integration with other disciplines. However, gaining predictive capability of the many interrelated consequences of climate change is a persistent challenge due to several factors. Observations of hydrologic change have been causally linked to permafrost thaw, but applications of process-based models needed to support and enhance the transferability of empirical linkages have often been restricted to generalized representations. Limitations stem from inadequate baseline permafrost and unfrozen hydrogeologic characterization, lack of historical data, and simplifications in structure and process representation needed to counter the high computational demands of cryohydrogeologic simulations. Further, due in part to the large degree of subsurface heterogeneity of permafrost landscapes and the nonuniformity in thaw patterns and rates, associations between various modes of permafrost thaw and hydrologic change are not readily scalable; even trajectories of change can differ. This review highlights promising advances in characterization and modeling of permafrost regions and presents ongoing research challenges toward projecting hydrologic and ecologic consequences of permafrost thaw at time and spatial scales that are useful to managers and researchers.

Characterizing Satellite Rainfall Errors based on Land Use and Land Cover and Tracing Error Source in Hydrologic Model Simulation

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Evaluation of two typical distributed energy systems

NASA Astrophysics Data System (ADS)

Han, Miaomiao; Tan, Xiu

2018-03-01

According to the two-natural gas distributed energy system driven by gas engine driven and gas turbine, in this paper, the first and second laws of thermodynamics are used to measure the distributed energy system from the two parties of “quantity” and “quality”. The calculation results show that the internal combustion engine driven distributed energy station has a higher energy efficiency, but the energy efficiency is low; the gas turbine driven distributed energy station energy efficiency is high, but the primary energy utilization rate is relatively low. When configuring the system, we should determine the applicable natural gas distributed energy system technology plan and unit configuration plan according to the actual load factors of the project and the actual factors such as the location, background and environmental requirements of the project. “quality” measure, the utilization of waste heat energy efficiency index is proposed.

Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment

PubMed Central

Prudhomme, Christel; Giuntoli, Ignazio; Robinson, Emma L.; Clark, Douglas B.; Arnell, Nigel W.; Dankers, Rutger; Fekete, Balázs M.; Franssen, Wietse; Gerten, Dieter; Gosling, Simon N.; Hagemann, Stefan; Hannah, David M.; Kim, Hyungjun; Masaki, Yoshimitsu; Satoh, Yusuke; Stacke, Tobias; Wada, Yoshihide; Wisser, Dominik

2014-01-01

Increasing concentrations of greenhouse gases in the atmosphere are expected to modify the global water cycle with significant consequences for terrestrial hydrology. We assess the impact of climate change on hydrological droughts in a multimodel experiment including seven global impact models (GIMs) driven by bias-corrected climate from five global climate models under four representative concentration pathways (RCPs). Drought severity is defined as the fraction of land under drought conditions. Results show a likely increase in the global severity of hydrological drought at the end of the 21st century, with systematically greater increases for RCPs describing stronger radiative forcings. Under RCP8.5, droughts exceeding 40% of analyzed land area are projected by nearly half of the simulations. This increase in drought severity has a strong signal-to-noise ratio at the global scale, and Southern Europe, the Middle East, the Southeast United States, Chile, and South West Australia are identified as possible hotspots for future water security issues. The uncertainty due to GIMs is greater than that from global climate models, particularly if including a GIM that accounts for the dynamic response of plants to CO2 and climate, as this model simulates little or no increase in drought frequency. Our study demonstrates that different representations of terrestrial water-cycle processes in GIMs are responsible for a much larger uncertainty in the response of hydrological drought to climate change than previously thought. When assessing the impact of climate change on hydrology, it is therefore critical to consider a diverse range of GIMs to better capture the uncertainty. PMID:24344266

Monitoring and forecasting the 2009-2010 severe drought in Southwest China

NASA Astrophysics Data System (ADS)

Zhang, X.; Tang, Q.; Liu, X.; Leng, G.; Li, Z.; Cui, H.

2015-12-01

From the fall of 2009 to the spring of 2010, an unprecedented drought swept across southwest China (SW) and led to a severe shortage in drinking water and a huge loss to regional economy. Monitoring and predicting the severe drought with several months in advance is of critical importance for such hydrological disaster assessment, preparation and mitigation. In this study, we attempted to carry out a model-based hydrological monitoring and seasonal forecasting framework, and assessed its skill in capturing the evolution of the SW drought in 2009-2010. Using the satellite-based meteorological forcings and the Variable Infiltration Capacity (VIC) hydrologic model, the drought conditions were assessed in a near-real-time manner based on a 62-year (1952-2013) retrospective simulation, wherein the satellite data was adjusted by a gauge-based forcing to remove systematic biases. Bias-corrected seasonal forecasting outputs from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2) was tentatively applied for a seasonal hydrologic prediction and its predictive skill was overall evaluated relative to a traditional Ensemble Streamflow Prediction (ESP) method with lead time varying from 1 to 6 months. The results show that the climate model-driven hydrologic predictability is generally limited to 1-month lead time and exhibits negligible skill improvement relative to ESP during this drought event, suggesting the initial hydrologic conditions (IHCs) play a dominant role in forecasting performance. The research highlights the value of the framework in providing accurate IHCs in a real-time manner which will greatly benefit drought early-warning.