NASA Astrophysics Data System (ADS)
Li, Zhanjie; Yu, Jingshan; Xu, Xinyi; Sun, Wenchao; Pang, Bo; Yue, Jiajia
2018-06-01
Hydrological models are important and effective tools for detecting complex hydrological processes. Different models have different strengths when capturing the various aspects of hydrological processes. Relying on a single model usually leads to simulation uncertainties. Ensemble approaches, based on multi-model hydrological simulations, can improve application performance over single models. In this study, the upper Yalongjiang River Basin was selected for a case study. Three commonly used hydrological models (SWAT, VIC, and BTOPMC) were selected and used for independent simulations with the same input and initial values. Then, the BP neural network method was employed to combine the results from the three models. The results show that the accuracy of BP ensemble simulation is better than that of the single models.
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.
NASA Astrophysics Data System (ADS)
Ye, L.; Wu, J.; Wang, L.; Song, T.; Ji, R.
2017-12-01
Flooding in small-scale watershed in hilly area is characterized by short time periods and rapid rise and recession due to the complex underlying surfaces, various climate type and strong effect of human activities. It is almost impossible for a single hydrological model to describe the variation of flooding in both time and space accurately for all the catchments in hilly area because the hydrological characteristics can vary significantly among different catchments. In this study, we compare the performance of 5 hydrological models with varying degrees of complexity for simulation of flash flood for 14 small-scale watershed in China in order to find the relationship between the applicability of the hydrological models and the catchments characteristics. Meanwhile, given the fact that the hydrological data is sparse in hilly area, the effect of precipitation data, DEM resolution and their interference on the uncertainty of flood simulation is also illustrated. In general, the results showed that the distributed hydrological model (HEC-HMS in this study) performed better than the lumped hydrological models. Xinajiang and API models had good simulation for the humid catchments when long-term and continuous rainfall data is provided. Dahuofang model can simulate the flood peak well while the runoff generation module is relatively poor. In addition, the effect of diverse modelling data on the simulations is not simply superposed, and there is a complex interaction effect among different modelling data. Overall, both the catchment hydrological characteristics and modelling data situation should be taken into consideration in order to choose the suitable hydrological model for flood simulation for small-scale catchment in hilly area.
NASA Astrophysics Data System (ADS)
Lafontaine, J.; Hay, L.; Markstrom, S. L.
2016-12-01
The United States Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the conterminous United States (CONUS). As many stream reaches in the CONUS are either not gaged, or are substantially impacted by water use or flow regulation, ancillary information must be used to determine reasonable parameter estimations for streamflow simulations. Hydrologic models for 1,576 gaged watersheds across the CONUS were developed to test the feasibility of improving streamflow simulations linking physically-based hydrologic models with remotely-sensed data products (i.e. snow water equivalent). Initially, the physically-based models were calibrated to measured streamflow data to provide a baseline for comparison across multiple calibration strategy tests. In addition, not all ancillary datasets are appropriate for application to all parts of the CONUS (e.g. snow water equivalent in the southeastern U.S., where snow is a rarity). As it is not expected that any one data product or model simulation will be sufficient for representing hydrologic behavior across the entire CONUS, a systematic evaluation of which data products improve hydrologic simulations for various regions across the CONUS was performed. The resulting portfolio of calibration strategies can be used to guide selection of an appropriate combination of modeled and measured information for hydrologic model development and calibration. In addition, these calibration strategies have been developed to be flexible so that new data products can be assimilated. This analysis provides a foundation to understand how well models work when sufficient streamflow data are not available and could be used to further inform hydrologic model parameter development for ungaged areas.
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.
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.
Stimulation from Simulation? A Teaching Model of Hillslope Hydrology for Use on Microcomputers.
ERIC Educational Resources Information Center
Burt, Tim; Butcher, Dave
1986-01-01
The design and use of a simple computer model which simulates a hillslope hydrology is described in a teaching context. The model shows a relatively complex environmental system can be constructed on the basis of a simple but realistic theory, thus allowing students to simulate the hydrological response of real hillslopes. (Author/TRS)
Improving Hydrological Simulations by Incorporating GRACE Data for Parameter Calibration
NASA Astrophysics Data System (ADS)
Bai, P.
2017-12-01
Hydrological model parameters are commonly calibrated by observed streamflow data. This calibration strategy is questioned when the modeled hydrological variables of interest are not limited to streamflow. Well-performed streamflow simulations do not guarantee the reliable reproduction of other hydrological variables. One of the reasons is that hydrological model parameters are not reasonably identified. The Gravity Recovery and Climate Experiment (GRACE) satellite-derived total water storage change (TWSC) data provide an opportunity to constrain hydrological model parameterizations in combination with streamflow observations. We constructed a multi-objective calibration scheme based on GRACE-derived TWSC and streamflow observations, with the aim of improving the parameterizations of hydrological models. The multi-objective calibration scheme was compared with the traditional single-objective calibration scheme, which is based only on streamflow observations. Two monthly hydrological models were employed on 22 Chinese catchments with different hydroclimatic conditions. The model evaluation was performed using observed streamflows, GRACE-derived TWSC, and evapotranspiraiton (ET) estimates from flux towers and from the water balance approach. Results showed that the multi-objective calibration provided more reliable TWSC and ET simulations without significant deterioration in the accuracy of streamflow simulations than the single-objective calibration. In addition, the improvements of TWSC and ET simulations were more significant in relatively dry catchments than in relatively wet catchments. This study highlights the importance of including additional constraints besides streamflow observations in the parameter estimation to improve the performances of hydrological models.
Hydrological modelling in forested systems | Science ...
This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological processes. The focus of this chapter is on process-based models and approaches, specifically 'forest hydrology models'; that is, physically based simulation tools that quantify compartments of the forest hydrological cycle. Physically based models can be considered those that describe the conservation of mass, momentum and/or energy. The purpose of this chapter is to provide a brief overview of forest hydrology modeling approaches for answering important global research and management questions. The focus of this chapter is on process-based models and approaches, specifically “forest hydrology models”, i.e., physically-based simulation tools that quantify compartments of the forest hydrological cycle.
Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wood, Andrew W; Leung, Lai R; Sridhar, V
Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel Climate Model (PCM), and the implications of the comparison for a future (2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregationmore » (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly (at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at ½-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able to produce hydrologically plausible results. With the BCSD method, the RCM-derived hydrology was more sensitive to climate change than the PCM-derived hydrology.« less
Virtual hydrology observatory: an immersive visualization of hydrology modeling
NASA Astrophysics Data System (ADS)
Su, Simon; Cruz-Neira, Carolina; Habib, Emad; Gerndt, Andreas
2009-02-01
The Virtual Hydrology Observatory will provide students with the ability to observe the integrated hydrology simulation with an instructional interface by using a desktop based or immersive virtual reality setup. It is the goal of the virtual hydrology observatory application to facilitate the introduction of field experience and observational skills into hydrology courses through innovative virtual techniques that mimic activities during actual field visits. The simulation part of the application is developed from the integrated atmospheric forecast model: Weather Research and Forecasting (WRF), and the hydrology model: Gridded Surface/Subsurface Hydrologic Analysis (GSSHA). Both the output from WRF and GSSHA models are then used to generate the final visualization components of the Virtual Hydrology Observatory. The various visualization data processing techniques provided by VTK are 2D Delaunay triangulation and data optimization. Once all the visualization components are generated, they are integrated into the simulation data using VRFlowVis and VR Juggler software toolkit. VR Juggler is used primarily to provide the Virtual Hydrology Observatory application with fully immersive and real time 3D interaction experience; while VRFlowVis provides the integration framework for the hydrologic simulation data, graphical objects and user interaction. A six-sided CAVETM like system is used to run the Virtual Hydrology Observatory to provide the students with a fully immersive experience.
NASA Astrophysics Data System (ADS)
Jiao, Yang; Lei, Huimin; Yang, Dawen; Huang, Maoyi; Liu, Dengfeng; Yuan, Xing
2017-08-01
Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of eco-hydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965-1969) from -0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010-2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.
NASA Astrophysics Data System (ADS)
Kusangaya, Samuel; Warburton Toucher, Michele L.; van Garderen, Emma Archer
2018-02-01
Downscaled General Circulation Models (GCMs) output are used to forecast climate change and provide information used as input for hydrological modelling. Given that our understanding of climate change points towards an increasing frequency, timing and intensity of extreme hydrological events, there is therefore the need to assess the ability of downscaled GCMs to capture these extreme hydrological events. Extreme hydrological events play a significant role in regulating the structure and function of rivers and associated ecosystems. In this study, the Indicators of Hydrologic Alteration (IHA) method was adapted to assess the ability of simulated streamflow (using downscaled GCMs (dGCMs)) in capturing extreme river dynamics (high and low flows), as compared to streamflow simulated using historical climate data from 1960 to 2000. The ACRU hydrological model was used for simulating streamflow for the 13 water management units of the uMngeni Catchment, South Africa. Statistically downscaled climate models obtained from the Climate System Analysis Group at the University of Cape Town were used as input for the ACRU Model. Results indicated that, high flows and extreme high flows (one in ten year high flows/large flood events) were poorly represented both in terms of timing, frequency and magnitude. Simulated streamflow using dGCMs data also captures more low flows and extreme low flows (one in ten year lowest flows) than that captured in streamflow simulated using historical climate data. The overall conclusion was that although dGCMs output can reasonably be used to simulate overall streamflow, it performs poorly when simulating extreme high and low flows. Streamflow simulation from dGCMs must thus be used with caution in hydrological applications, particularly for design hydrology, as extreme high and low flows are still poorly represented. This, arguably calls for the further improvement of downscaling techniques in order to generate climate data more relevant and useful for hydrological applications such as in design hydrology. Nevertheless, the availability of downscaled climatic output provide the potential of exploring climate model uncertainties in different hydro climatic regions at local scales where forcing data is often less accessible but more accurate at finer spatial scales and with adequate spatial detail.
NASA Astrophysics Data System (ADS)
Huang, Pengnian; Li, Zhijia; Chen, Ji; Li, Qiaoling; Yao, Cheng
2016-11-01
To simulate the hydrological processes in semi-arid areas properly is still challenging. This study assesses the impact of different modeling strategies on simulating flood processes in semi-arid catchments. Four classic hydrological models, TOPMODEL, XINANJIANG (XAJ), SAC-SMA and TANK, were selected and applied to three semi-arid catchments in North China. Based on analysis and comparison of the simulation results of these classic models, four new flexible models were constructed and used to further investigate the suitability of various modeling strategies for semi-arid environments. Numerical experiments were also designed to examine the performances of the models. The results show that in semi-arid catchments a suitable model needs to include at least one nonlinear component to simulate the main process of surface runoff generation. If there are more than two nonlinear components in the hydrological model, they should be arranged in parallel, rather than in series. In addition, the results show that the parallel nonlinear components should be combined by multiplication rather than addition. Moreover, this study reveals that the key hydrological process over semi-arid catchments is the infiltration excess surface runoff, a non-linear component.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jiao, Yang; Lei, Huimin; Yang, Dawen
Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of ecohydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of themore » Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from 0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.« less
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.
Simulations of ecosystem hydrological processes using a unified multi-scale model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Xiaofan; Liu, Chongxuan; Fang, Yilin
2015-01-01
This paper presents a unified multi-scale model (UMSM) that we developed to simulate hydrological processes in an ecosystem containing both surface water and groundwater. The UMSM approach modifies the Navier–Stokes equation by adding a Darcy force term to formulate a single set of equations to describe fluid momentum and uses a generalized equation to describe fluid mass balance. The advantage of the approach is that the single set of the equations can describe hydrological processes in both surface water and groundwater where different models are traditionally required to simulate fluid flow. This feature of the UMSM significantly facilitates modelling ofmore » hydrological processes in ecosystems, especially at locations where soil/sediment may be frequently inundated and drained in response to precipitation, regional hydrological and climate changes. In this paper, the UMSM was benchmarked using WASH123D, a model commonly used for simulating coupled surface water and groundwater flow. Disney Wilderness Preserve (DWP) site at the Kissimmee, Florida, where active field monitoring and measurements are ongoing to understand hydrological and biogeochemical processes, was then used as an example to illustrate the UMSM modelling approach. The simulations results demonstrated that the DWP site is subject to the frequent changes in soil saturation, the geometry and volume of surface water bodies, and groundwater and surface water exchange. All the hydrological phenomena in surface water and groundwater components including inundation and draining, river bank flow, groundwater table change, soil saturation, hydrological interactions between groundwater and surface water, and the migration of surface water and groundwater interfaces can be simultaneously simulated using the UMSM. Overall, the UMSM offers a cross-scale approach that is particularly suitable to simulate coupled surface and ground water flow in ecosystems with strong surface water and groundwater interactions.« less
Advancing the Implementation of Hydrologic Models as Web-based Applications
NASA Astrophysics Data System (ADS)
Dahal, P.; Tarboton, D. G.; Castronova, A. M.
2017-12-01
Advanced computer simulations are required to understand hydrologic phenomenon such as rainfall-runoff response, groundwater hydrology, snow hydrology, etc. Building a hydrologic model instance to simulate a watershed requires investment in data (diverse geospatial datasets such as terrain, soil) and computer resources, typically demands a wide skill set from the analyst, and the workflow involved is often difficult to reproduce. This work introduces a web-based prototype infrastructure in the form of a web application that provides researchers with easy to use access to complete hydrological modeling functionality. This includes creating the necessary geospatial and forcing data, preparing input files for a model by applying complex data preprocessing, running the model for a user defined watershed, and saving the results to a web repository. The open source Tethys Platform was used to develop the web app front-end Graphical User Interface (GUI). We used HydroDS, a webservice that provides data preparation processing capability to support backend computations used by the app. Results are saved in HydroShare, a hydrologic information system that supports the sharing of hydrologic data, model and analysis tools. The TOPographic Kinematic APproximation and Integration (TOPKAPI) model served as the example for which we developed a complete hydrologic modeling service to demonstrate the approach. The final product is a complete modeling system accessible through the web to create input files, and run the TOPKAPI hydrologic model for a watershed of interest. We are investigating similar functionality for the preparation of input to Regional Hydro-Ecological Simulation System (RHESSys). Key Words: hydrologic modeling, web services, hydrologic information system, HydroShare, HydroDS, Tethys Platform
LSPC is the Loading Simulation Program in C++, a watershed modeling system that includes streamlined Hydrologic Simulation Program Fortran (HSPF) algorithms for simulating hydrology, sediment, and general water quality
Fallon, Nevada FORGE Thermal-Hydrological-Mechanical Models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Blankenship, Doug; Sonnenthal, Eric
Archive contains thermal-mechanical simulation input/output files. Included are files which fall into the following categories: ( 1 ) Spreadsheets with various input parameter calculations ( 2 ) Final Simulation Inputs ( 3 ) Native-State Thermal-Hydrological Model Input File Folders ( 4 ) Native-State Thermal-Hydrological-Mechanical Model Input Files ( 5 ) THM Model Stimulation Cases See 'File Descriptions.xlsx' resource below for additional information on individual files.
Simulated impacts of climate on hydrology can vary greatly as a function of the scale of the input data, model assumptions, and model structure. Four models are commonly used to simulate streamflow in model assumptions, and model structure. Four models are commonly used to simu...
Hostetler, S.W.; Giorgi, F.
1993-01-01
In this paper we investigate the feasibility of coupling regional climate models (RCMs) with landscape-scale hydrologic models (LSHMs) for studies of the effects of climate on hydrologic systems. The RCM used is the National Center for Atmospheric Research/Pennsylvania State University mesoscale model (MM4). Output from two year-round simulations (1983 and 1988) over the western United States is used to drive a lake model for Pyramid Lake in Nevada and a streamfiow model for Steamboat Creek in Oregon. Comparisons with observed data indicate that MM4 is able to produce meteorologic data sets that can be used to drive hydrologic models. Results from the lake model simulations indicate that the use of MM4 output produces reasonably good predictions of surface temperature and evaporation. Results from the streamflow simulations indicate that the use of MM4 output results in good simulations of the seasonal cycle of streamflow, but deficiencies in simulated wintertime precipitation resulted in underestimates of streamflow and soil moisture. Further work with climate (multiyear) simulations is necessary to achieve a complete analysis, but the results from this study indicate that coupling of LSHMs and RCMs may be a useful approach for evaluating the effects of climate change on hydrologic systems.
Markstrom, Steven L.
2012-01-01
A software program, called P2S, has been developed which couples the daily stream temperature simulation capabilities of the U.S. Geological Survey Stream Network Temperature model with the watershed hydrology simulation capabilities of the U.S. Geological Survey Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a modular, deterministic, distributed-parameter, physical-process watershed model that simulates hydrologic response to various combinations of climate and land use. Stream Network Temperature was developed to help aquatic biologists and engineers predict the effects of changes that hydrology and energy have on water temperatures. P2S will allow scientists and watershed managers to evaluate the effects of historical climate and projected climate change, landscape evolution, and resource management scenarios on watershed hydrology and in-stream water temperature.
NASA Astrophysics Data System (ADS)
Coe, M. T.; Costa, M. H.; Howard, E. A.
2006-12-01
In this paper we analyze the hydrology of the Amazon River system for the latter half of the 20th century with our recently completed model of terrestrial hydrology (Terrestrial Hydrology Model with Biogeochemistry, THMB). We evaluate the simulated hydrology of the Central Amazon basin against limited observations of river discharge, floodplain inundation, and water height and analyze the spatial and temporal variability of the hydrology for the period 1939-1998. We compare the simulated discharge and floodplain inundated area to the simulations by Coe et al., 2002 using a previous version of this model. The new model simulates the discharge and flooded area in better agreement with the observations than the previous model. The coefficient of correlation between the simulated and observed discharge for the greater than 27000 monthly observations of discharge at 120 sites throughout the Brazilian Amazon is 0.9874 compared to 0.9744 for the previous model. The coefficient of correlation between the simulated monthly flooded area and the satellite-based estimates by Sippel et al., 1998 exceeds 0.7 for 8 of the 12 mainstem reaches. The seasonal and inter-annual variability of the water height and the river slope compares favorably to the satellite altimetric measurements of height reported by Birkett et al., 2002.
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.
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.
The Use of Simulation Models in Teaching Geomorphology and Hydrology.
ERIC Educational Resources Information Center
Kirkby, Mike; Naden, Pam
1988-01-01
Learning about the physical environment from computer simulation models is discussed in terms of three stages: exploration, experimentation, and calibration. Discusses the effective use of models and presents two computer simulations written in BBC BASIC, STORFLO (for catchment hydrology) and SLOPEK (for hillslope evolution). (Author/GEA)
Findings and Challenges in Fine-Resolution Large-Scale Hydrological Modeling
NASA Astrophysics Data System (ADS)
Her, Y. G.
2017-12-01
Fine-resolution large-scale (FL) modeling can provide the overall picture of the hydrological cycle and transport while taking into account unique local conditions in the simulation. It can also help develop water resources management plans consistent across spatial scales by describing the spatial consequences of decisions and hydrological events extensively. FL modeling is expected to be common in the near future as global-scale remotely sensed data are emerging, and computing resources have been advanced rapidly. There are several spatially distributed models available for hydrological analyses. Some of them rely on numerical methods such as finite difference/element methods (FDM/FEM), which require excessive computing resources (implicit scheme) to manipulate large matrices or small simulation time intervals (explicit scheme) to maintain the stability of the solution, to describe two-dimensional overland processes. Others make unrealistic assumptions such as constant overland flow velocity to reduce the computational loads of the simulation. Thus, simulation efficiency often comes at the expense of precision and reliability in FL modeling. Here, we introduce a new FL continuous hydrological model and its application to four watersheds in different landscapes and sizes from 3.5 km2 to 2,800 km2 at the spatial resolution of 30 m on an hourly basis. The model provided acceptable accuracy statistics in reproducing hydrological observations made in the watersheds. The modeling outputs including the maps of simulated travel time, runoff depth, soil water content, and groundwater recharge, were animated, visualizing the dynamics of hydrological processes occurring in the watersheds during and between storm events. Findings and challenges were discussed in the context of modeling efficiency, accuracy, and reproducibility, which we found can be improved by employing advanced computing techniques and hydrological understandings, by using remotely sensed hydrological observations such as soil moisture and radar rainfall depth and by sharing the model and its codes in public domain, respectively.
NASA Astrophysics Data System (ADS)
Mendoza, Pablo A.; Mizukami, Naoki; Ikeda, Kyoko; Clark, Martyn P.; Gutmann, Ethan D.; Arnold, Jeffrey R.; Brekke, Levi D.; Rajagopalan, Balaji
2016-10-01
We examine the effects of regional climate model (RCM) horizontal resolution and forcing scaling (i.e., spatial aggregation of meteorological datasets) on the portrayal of climate change impacts. Specifically, we assess how the above decisions affect: (i) historical simulation of signature measures of hydrologic behavior, and (ii) projected changes in terms of annual water balance and hydrologic signature measures. To this end, we conduct our study in three catchments located in the headwaters of the Colorado River basin. Meteorological forcings for current and a future climate projection are obtained at three spatial resolutions (4-, 12- and 36-km) from dynamical downscaling with the Weather Research and Forecasting (WRF) regional climate model, and hydrologic changes are computed using four different hydrologic model structures. These projected changes are compared to those obtained from running hydrologic simulations with current and future 4-km WRF climate outputs re-scaled to 12- and 36-km. The results show that the horizontal resolution of WRF simulations heavily affects basin-averaged precipitation amounts, propagating into large differences in simulated signature measures across model structures. The implications of re-scaled forcing datasets on historical performance were primarily observed on simulated runoff seasonality. We also found that the effects of WRF grid resolution on projected changes in mean annual runoff and evapotranspiration may be larger than the effects of hydrologic model choice, which surpasses the effects from re-scaled forcings. Scaling effects on projected variations in hydrologic signature measures were found to be generally smaller than those coming from WRF resolution; however, forcing aggregation in many cases reversed the direction of projected changes in hydrologic behavior.
Development of Hydro-Informatic Modelling System and its Application
NASA Astrophysics Data System (ADS)
Wang, Z.; Liu, C.; Zheng, H.; Zhang, L.; Wu, X.
2009-12-01
The understanding of hydrological cycle is the core of hydrology and the scientific base of water resources management. Meanwhile, simulation of hydrological cycle has long been regarded as an important tool for the assessment, utilization and protection of water resources. In this paper, a new tool named Hydro-Informatic Modelling System (HIMS) has been developed and introduced with case studies in the Yellow River Basin in China and 331 catchments in Australia. The case studies showed that HIMS can be employed as an integrated platform for hydrological simulation in different regions. HIMS is a modular based framework of hydrological model designed for different utilization such as flood forecasting, water resources planning and evaluating hydrological impacts of climate change and human activities. The unique of HIMS is its flexibility in providing alternative modules in the simulation of hydrological cycle, which successfully overcome the difficulties in the availability of input data, the uncertainty of parameters, and the difference of rainfall-runoff processes. The modular based structure of HIMS makes it possible for developing new hydrological models by the users.
NASA Technical Reports Server (NTRS)
Alacron, Vladimir J.; Nigro, Joseph D.; McAnally, William H.; OHara, Charles G.; Engman, Edwin Ted; Toll, David
2011-01-01
This paper documents the use of simulated Moderate Resolution Imaging Spectroradiometer land use/land cover (MODIS-LULC), NASA-LIS generated precipitation and evapo-transpiration (ET), and Shuttle Radar Topography Mission (SRTM) datasets (in conjunction with standard land use, topographical and meteorological datasets) as input to hydrological models routinely used by the watershed hydrology modeling community. The study is focused in coastal watersheds in the Mississippi Gulf Coast although one of the test cases focuses in an inland watershed located in northeastern State of Mississippi, USA. The decision support tools (DSTs) into which the NASA datasets were assimilated were the Soil Water & Assessment Tool (SWAT) and the Hydrological Simulation Program FORTRAN (HSPF). These DSTs are endorsed by several US government agencies (EPA, FEMA, USGS) for water resources management strategies. These models use physiographic and meteorological data extensively. Precipitation gages and USGS gage stations in the region were used to calibrate several HSPF and SWAT model applications. Land use and topographical datasets were swapped to assess model output sensitivities. NASA-LIS meteorological data were introduced in the calibrated model applications for simulation of watershed hydrology for a time period in which no weather data were available (1997-2006). The performance of the NASA datasets in the context of hydrological modeling was assessed through comparison of measured and model-simulated hydrographs. Overall, NASA datasets were as useful as standard land use, topographical , and meteorological datasets. Moreover, NASA datasets were used for performing analyses that the standard datasets could not made possible, e.g., introduction of land use dynamics into hydrological simulations
A sensitivity analysis of regional and small watershed hydrologic models
NASA Technical Reports Server (NTRS)
Ambaruch, R.; Salomonson, V. V.; Simmons, J. W.
1975-01-01
Continuous simulation models of the hydrologic behavior of watersheds are important tools in several practical applications such as hydroelectric power planning, navigation, and flood control. Several recent studies have addressed the feasibility of using remote earth observations as sources of input data for hydrologic models. The objective of the study reported here was to determine how accurately remotely sensed measurements must be to provide inputs to hydrologic models of watersheds, within the tolerances needed for acceptably accurate synthesis of streamflow by the models. The study objective was achieved by performing a series of sensitivity analyses using continuous simulation models of three watersheds. The sensitivity analysis showed quantitatively how variations in each of 46 model inputs and parameters affect simulation accuracy with respect to five different performance indices.
Mizukami, Naoki; Clark, Martyn P.; Gutmann, Ethan D.; Mendoza, Pablo A.; Newman, Andrew J.; Nijssen, Bart; Livneh, Ben; Hay, Lauren E.; Arnold, Jeffrey R.; Brekke, Levi D.
2016-01-01
Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.
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.
Modeling Best Management Practices (BMPs) with HSPF
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...
Jacob LaFontaine; Lauren Hay; Stacey Archfield; William Farmer; Julie Kiang
2016-01-01
The U.S. Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the continental US. The portion of the NHM located within the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC) is...
Hydrological and water quality processes simulation by the integrated MOHID model
NASA Astrophysics Data System (ADS)
Epelde, Ane; Antiguedad, Iñaki; Brito, David; Eduardo, Jauch; Neves, Ramiro; Sauvage, Sabine; Sánchez-Pérez, José Miguel
2016-04-01
Different modelling approaches have been used in recent decades to study the water quality degradation caused by non-point source pollution. In this study, the MOHID fully distributed and physics-based model has been employed to simulate hydrological processes and nitrogen dynamics in a nitrate vulnerable zone: the Alegria River watershed (Basque Country, Northern Spain). The results of this study indicate that the MOHID code is suitable for hydrological processes simulation at the watershed scale, as the model shows satisfactory performance at simulating the discharge (with NSE: 0.74 and 0.76 during calibration and validation periods, respectively). The agronomical component of the code, allowed the simulation of agricultural practices, which lead to adequate crop yield simulation in the model. Furthermore, the nitrogen exportation also shows satisfactory performance (with NSE: 0.64 and 0.69 during calibration and validation periods, respectively). While the lack of field measurements do not allow to evaluate the nutrient cycling processes in depth, it has been observed that the MOHID model simulates the annual denitrification according to general ranges established for agricultural watersheds (in this study, 9 kg N ha-1 year-1). In addition, the model has simulated coherently the spatial distribution of the denitrification process, which is directly linked to the simulated hydrological conditions. Thus, the model has localized the highest rates nearby the discharge zone of the aquifer and also where the aquifer thickness is low. These results evidence the strength of this model to simulate watershed scale hydrological processes as well as the crop production and the agricultural activity derived water quality degradation (considering both nutrient exportation and nutrient cycling processes).
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.
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.
NASA Astrophysics Data System (ADS)
Lafontaine, J.; Hay, L.
2015-12-01
The United States Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the conterminous United States (CONUS). More than 1,700 gaged watersheds across the CONUS were modeled to test the feasibility of improving streamflow simulations in gaged and ungaged watersheds by linking statistically- and physically-based hydrologic models with remotely-sensed data products (i.e. - snow water equivalent) and estimates of uncertainty. Initially, the physically-based models were calibrated to measured streamflow data to provide a baseline for comparison. As many stream reaches in the CONUS are either not gaged, or are substantially impacted by water use or flow regulation, ancillary information must be used to determine reasonable parameter estimations for streamflow simulations. In addition, not all ancillary datasets are appropriate for application to all parts of the CONUS (e.g. - snow water equivalent in the southeastern U.S., where snow is a rarity). As it is not expected that any one data product or model simulation will be sufficient for representing hydrologic behavior across the entire CONUS, a systematic evaluation of which data products improve simulations of streamflow for various regions across the CONUS was performed. The resulting portfolio of calibration strategies can be used to guide selection of an appropriate combination of simulated and measured information for model development and calibration at a given location of interest. In addition, these calibration strategies have been developed to be flexible so that new data products or simulated information can be assimilated. This analysis provides a foundation to understand how well models work when streamflow data is either not available or is limited and could be used to further inform hydrologic model parameter development for ungaged areas.
HYDROLOGY AND SEDIMENT MODELING USING THE BASINS NON-POINT SOURCE MODEL
The Non-Point Source Model (Hydrologic Simulation Program-Fortran, or HSPF) within the EPA Office of Water's BASINS watershed modeling system was used to simulate streamflow and total suspended solids within Contentnea Creek, North Carolina, which is a tributary of the Neuse Rive...
APPLICATION OF A FULLY DISTRIBUTED WASHOFF AND TRANSPORT MODEL FOR A GULF COAST WATERSHED
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...
APPLICATION OF THE HSPF MODEL TO THE SOUTH FORK OF THE BROAD RIVER WATERSHED IN NORTHEASTERN GEORGIA
The Hydrological Simulation Program-Fortran (HSPF) is a comprehensive watershed model which simulates hydrology and water quality at user-specified temporal and spatial scales. Well-established model calibration and validation procedures are followed when adjusting model paramete...
Local control on precipitation in a fully coupled climate-hydrology model.
Larsen, Morten A D; Christensen, Jens H; Drews, Martin; Butts, Michael B; Refsgaard, Jens C
2016-03-10
The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.
Local control on precipitation in a fully coupled climate-hydrology model
Larsen, Morten A. D.; Christensen, Jens H.; Drews, Martin; Butts, Michael B.; Refsgaard, Jens C.
2016-01-01
The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies. PMID:26960564
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.
Publishing and sharing of hydrologic models through WaterHUB
NASA Astrophysics Data System (ADS)
Merwade, V.; Ruddell, B. L.; Song, C.; Zhao, L.; Kim, J.; Assi, A.
2011-12-01
Most hydrologists use hydrologic models to simulate the hydrologic processes to understand hydrologic pathways and fluxes for research, decision making and engineering design. Once these tasks are complete including publication of results, the models generally are not published or made available to the public for further use and improvement. Although publication or sharing of models is not required for journal publications, sharing of models may open doors for new collaborations, and avoids duplication of efforts if other researchers are interested in simulating a particular watershed for which a model already exists. For researchers, who are interested in sharing models, there are limited avenues to publishing their models to the wider community. Towards filling this gap, a prototype cyberinfrastructure (CI), called WaterHUB, is developed for sharing hydrologic data and modeling tools in an interactive environment. To test the utility of WaterHUB for sharing hydrologic models, a system to publish and share SWAT (Soil Water Assessment Tool) is developed. Users can utilize WaterHUB to search and download existing SWAT models, and also upload new SWAT models. Metadata such as the name of the watershed, name of the person or agency who developed the model, simulation period, time step, and list of calibrated parameters also published with individual model.
Painter, Scott L.; Coon, Ethan T.; Atchley, Adam L.; ...
2016-08-11
The need to understand potential climate impacts and feedbacks in Arctic regions has prompted recent interest in modeling of permafrost dynamics in a warming climate. A new fine-scale integrated surface/subsurface thermal hydrology modeling capability is described and demonstrated in proof-of-concept simulations. The new modeling capability combines a surface energy balance model with recently developed three-dimensional subsurface thermal hydrology models and new models for nonisothermal surface water flows and snow distribution in the microtopography. Surface water flows are modeled using the diffusion wave equation extended to include energy transport and phase change of ponded water. Variation of snow depth in themore » microtopography, physically the result of wind scour, is also modeled heuristically with a diffusion wave equation. The multiple surface and subsurface processes are implemented by leveraging highly parallel community software. Fully integrated thermal hydrology simulations on the tilted open book catchment, an important test case for integrated surface/subsurface flow modeling, are presented. Fine-scale 100-year projections of the integrated permafrost thermal hydrological system on an ice wedge polygon at Barrow Alaska in a warming climate are also presented. Finally, these simulations demonstrate the feasibility of microtopography-resolving, process-rich simulations as a tool to help understand possible future evolution of the carbon-rich Arctic tundra in a warming climate.« less
NASA Astrophysics Data System (ADS)
van Walsum, P. E. V.; Supit, I.
2012-06-01
Hydrologic climate change modelling is hampered by climate-dependent model parameterizations. To reduce this dependency, we extended the regional hydrologic modelling framework SIMGRO to host a two-way coupling between the soil moisture model MetaSWAP and the crop growth simulation model WOFOST, accounting for ecohydrologic feedbacks in terms of radiation fraction that reaches the soil, crop coefficient, interception fraction of rainfall, interception storage capacity, and root zone depth. Except for the last, these feedbacks are dependent on the leaf area index (LAI). The influence of regional groundwater on crop growth is included via a coupling to MODFLOW. Two versions of the MetaSWAP-WOFOST coupling were set up: one with exogenous vegetation parameters, the "static" model, and one with endogenous crop growth simulation, the "dynamic" model. Parameterization of the static and dynamic models ensured that for the current climate the simulated long-term averages of actual evapotranspiration are the same for both models. Simulations were made for two climate scenarios and two crops: grass and potato. In the dynamic model, higher temperatures in a warm year under the current climate resulted in accelerated crop development, and in the case of potato a shorter growing season, thus partly avoiding the late summer heat. The static model has a higher potential transpiration; depending on the available soil moisture, this translates to a higher actual transpiration. This difference between static and dynamic models is enlarged by climate change in combination with higher CO2 concentrations. Including the dynamic crop simulation gives for potato (and other annual arable land crops) systematically higher effects on the predicted recharge change due to climate change. Crop yields from soils with poor water retention capacities strongly depend on capillary rise if moisture supply from other sources is limited. Thus, including a crop simulation model in an integrated hydrologic simulation provides a valuable addition for hydrologic modelling as well as for crop modelling.
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.
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.
Physics-based simulations of the impacts forest management practices have on hydrologic response
Adrianne Carr; Keith Loague
2012-01-01
The impacts of logging on near-surface hydrologic response at the catchment and watershed scales were examined quantitatively using numerical simulation. The simulations were conducted with the Integrated Hydrology Model (InHM) for the North Fork of Caspar Creek Experimental Watershed, located near Fort Bragg, California. InHM is a comprehensive physics-based...
Hydrological Modeling of the Jiaoyi Watershed (China) Using HSPF Model
Yan, Chang-An; Zhang, Wanchang; Zhang, Zhijie
2014-01-01
A watershed hydrological model, hydrological simulation program-Fortran (HSPF), was applied to simulate the spatial and temporal variation of hydrological processes in the Jiaoyi watershed of Huaihe River Basin, the heaviest shortage of water resources and polluted area in China. The model was calibrated using the years 2001–2004 and validated with data from 2005 to 2006. Calibration and validation results showed that the model generally simulated mean monthly and daily runoff precisely due to the close matching hydrographs between simulated and observed runoff, as well as the excellent evaluation indicators such as Nash-Sutcliffe efficiency (NSE), coefficient of correlation (R 2), and the relative error (RE). The similar simulation results between calibration and validation period showed that all the calibrated parameters had a certain representation in Jiaoyi watershed. Additionally, the simulation in rainy months was more accurate than the drought months. Another result in this paper was that HSPF was also capable of estimating the water balance components reasonably and realistically in space through the whole watershed. The calibrated model can be used to explore the effects of climate change scenarios and various watershed management practices on the water resources and water environment in the basin. PMID:25013863
ENHANCING HYDROLOGICAL SIMULATION PROGRAM - FORTRAN MODEL CHANNEL HYDRAULIC REPRESENTATION
The Hydrological Simulation Program– FORTRAN (HSPF) is a comprehensive watershed model that employs depth-area - volume - flow relationships known as the hydraulic function table (FTABLE) to represent the hydraulic characteristics of stream channel cross-sections and reservoirs. ...
NASA Astrophysics Data System (ADS)
Mohammed, K.; Islam, A. S.; Khan, M. J. U.; Das, M. K.
2017-12-01
With the large number of hydrologic models presently available along with the global weather and geographic datasets, streamflows of almost any river in the world can be easily modeled. And if a reasonable amount of observed data from that river is available, then simulations of high accuracy can sometimes be performed after calibrating the model parameters against those observed data through inverse modeling. Although such calibrated models can succeed in simulating the general trend or mean of the observed flows very well, more often than not they fail to adequately simulate the extreme flows. This causes difficulty in tasks such as generating reliable projections of future changes in extreme flows due to climate change, which is obviously an important task due to floods and droughts being closely connected to people's lives and livelihoods. We propose an approach where the outputs of a physically-based hydrologic model are used as an input to a machine learning model to try and better simulate the extreme flows. To demonstrate this offline-coupling approach, the Soil and Water Assessment Tool (SWAT) was selected as the physically-based hydrologic model, the Artificial Neural Network (ANN) as the machine learning model and the Ganges-Brahmaputra-Meghna (GBM) river system as the study area. The GBM river system, located in South Asia, is the third largest in the world in terms of freshwater generated and forms the largest delta in the world. The flows of the GBM rivers were simulated separately in order to test the performance of this proposed approach in accurately simulating the extreme flows generated by different basins that vary in size, climate, hydrology and anthropogenic intervention on stream networks. Results show that by post-processing the simulated flows of the SWAT models with ANN models, simulations of extreme flows can be significantly improved. The mean absolute errors in simulating annual maximum/minimum daily flows were minimized from 4967 cusecs to 1294 cusecs for Ganges, from 5695 cusecs to 2115 cusecs for Brahmaputra and from 689 cusecs to 321 cusecs for Meghna. Using this approach, simulations of hydrologic variables other than streamflow can also be improved given that a decent amount of observed data for that variable is available.
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.
Wicklein, Shaun M.; Schiffer, Donna M.
2002-01-01
Hydrologic and water-quality data have been collected within the 177-square-mile Reedy Creek, Florida, watershed, beginning as early as 1939, but the data have not been used to evaluate relations among land use, hydrology, and water quality. A model of the Reedy Creek watershed was developed and applied to the period January 1990 to December 1995 to provide a computational foundation for evaluating the effects of future land-use changes on hydrology and water quality in the watershed. The Hydrological Simulation Program-Fortran (HSPF) model was used to simulate hydrology and water quality of runoff for pervious land areas, impervious land areas, and stream reaches. Six land-use types were used to characterize the hydrology and water quality of pervious and impervious land areas in the Reedy Creek watershed: agriculture, rangeland, forest, wetlands, rapid infiltration basins, and urban areas. Hydrologic routing and water-quality reactions were simulated to characterize hydrologic and water-quality processes and the movement of runoff and its constituents through the main stream channels and their tributaries. Because of the complexity of the stream system within the Reedy Creek Improvement District (RCID) (hydraulic structures, retention ponds) and the anticipated difficulty of modeling the system, an approach of calibrating the model parameters for a subset of the gaged watersheds and confirming the usefulness of the parameters by simulating the remainder of the gaged sites was selected for this study. Two sub-watersheds (Whittenhorse Creek and Davenport Creek) were selected for calibration because both have similar land use to watersheds within the RCID (with the exception of urban areas). Given the lack of available rainfall data, the hydrologic calibration of the Whittenhorse Creek and Davenport Creek sub-watersheds was considered acceptable (for monthly data, correlation coefficients, 0.86 and 0.88, and coefficients of model-fit efficiency, 0.72 and 0.74, respectively). The hydrologic model was tested by applying the parameter sets developed for Whittenhorse Creek and Davenport Creek to other land areas within the Reedy Creek watershed, and by comparing the simulated results to observed data sets for Reedy Creek near Vineland, Bonnet Creek near Vineland, and Reedy Creek near Loughman. The hydrologic model confirmation for Reedy Creek near Vineland (correlation coefficient, 0.91, and coefficient of model fit efficiency, 0.78, for monthly flows) was acceptable. Flows for Bonnet Creek near Vineland were substantially under simulated. Consideration of the ground-water contribution to Bonnet Creek could improve the water balance simulation for Bonnet Creek near Vineland. On longer time scales (monthly or over the 72-month simulation period), simulated discharges for Reedy Creek near Loughman agreed well with observed data (correlation coefficient, 0.88). For monthly flows the coefficient of model-fit efficiency was 0.77. On a shorter time scale (less than a month), however, storm volumes were greatly over simulated and low flows (less than 8 cubic feet per second) were greatly under simulated. A primary reason for the poor results at low flows is the diversion of an unknown amount of water from the RCID at the Bonnet Creek near Kissimmee site. Selection of water-quality constituents for simulation was based primarily on the availability of water-quality data. Dissolved oxygen, nitrogen, and phosphorus species were simulated. Representation of nutrient cycling in HSPF also required simulation of biochemical oxygen demand and phytoplankton populations. The correlation coefficient for simulated and observed daily mean dissolved oxygen concentration values at Reedy Creek near Vineland was 0.633. Simulated time series of total phosphorus, phosphate, ammonia nitrogen, and nitrate nitrogen generally agreed well with periodically observed values for the Whittenhorse Creek and Davenport Creek sites. Simulated water-quality c
USDA-ARS?s Scientific Manuscript database
Watershed simulation models are used extensively to investigate hydrologic processes, landuse and climate change impacts, pollutant load assessments and best management practices (BMPs). Developing, calibrating and validating these models require a number of critical decisions that will influence t...
NASA Astrophysics Data System (ADS)
Evenson, G. R.; Golden, H. E.; Lane, C.; Mclaughlin, D. L.; D'Amico, E.
2016-12-01
Geographically isolated wetlands (GIWs), defined as upland embedded wetlands, provide an array of ecosystem goods and services. Wetland conservation efforts aim to protect GIWs in the face of continued threats from anthropogenic activities. Given limited conservation resources, there is a critical need for methods capable of evaluating the watershed-scale hydrologic implications of alternative approaches to GIW conservation. Further, there is a need for methods that quantify the watershed-scale aggregate effects of GIWs to determine their regulatory status within the United States. We applied the Soil and Water Assessment Tool (SWAT), a popular watershed-scale hydrologic model, to represent the 1,700 km2 Pipestem Creek watershed in North Dakota, USA. We modified the model to incorporate an improved representation of GIW hydrologic processes via hydrologic response unit (HRU) redefinition and modifications to the model source code. We then used the model to evaluate the hydrologic effects of alternative approaches to GIW conservation prioritization by simulating the destruction/removal of GIWs by sub-classes defined by their relative position within the simulated fill-spill GIW network and their surface area characteristics. We evaluated the alternative conservation approaches as impacting (1) simulated streamflow at the Pipestem Creek watershed outlet; (2) simulated water-levels within the GIWs; and (3) simulated hydrologic connections between the GIWs. Our approach to modifying SWAT and evaluating alternative GIW conservation strategies may be replicated in different watersheds and physiographic regions to aid the development of GIW conservation priorities.
Hydrological Modelling using HEC-HMS for Flood Risk Assessment of Segamat Town, Malaysia
NASA Astrophysics Data System (ADS)
Romali, N. S.; Yusop, Z.; Ismail, A. Z.
2018-03-01
This paper presents an assessment of the applicability of using Hydrologic Modelling System developed by the Hydrologic Engineering Center (HEC-HMS) for hydrological modelling of Segamat River. The objective of the model application is to assist in the assessment of flood risk by providing the peak flows of 2011 Segamat flood for the generation of flood mapping of Segamat town. The capability of the model was evaluated by comparing the historical observed data with the simulation results of the selected flood events. The model calibration and validation efficiency was verified using Nash-Sutcliffe model efficiency coefficient. The results demonstrate the interest to implement the hydrological model for assessing flood risk where the simulated peak flow result is in agreement with historical observed data. The model efficiency of the calibrated and validated exercises is 0.90 and 0.76 respectively, which is acceptable.
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.
NASA Astrophysics Data System (ADS)
Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.
2014-08-01
Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.
Simulation of hydrologic influences on wetland ecosystem succession. Master's thesis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pompilio, R.A.
1994-09-01
This research focuses on the development of a simulation model to determine the affects of hydrological influences on a wetland ecosystem. The model allows perturbations to the inputs of various wetland data which in turn, influences the successional development of the ecosystem. This research consisted of converting a grassland ecosystem model to one which simulates wetland conditions. The critical factor in determining the success of wetland creation is the hydrology of the system. There are four of the areas of the original model which are affected by the hydrology. The model measures the health or success of the ecosystem throughmore » the measurement of the systems gross plant production, the respiration and the net primary production of biomass. Altering the auxiliary variables of water level and the rate of flow through the system explicitly details the affects hydrologic influences on those production rates. Ten case tests depicting exogenous perturbations of the hydrology were run to identify these affects. Although the tests dealt with the fluctuation of water through the system, any one of the auxiliary variables in the model could be changed to reflect site specific data. Productivity, Hazardous material management, Hazardous material pharmacy.« less
NASA Astrophysics Data System (ADS)
Vema, Vamsikrishna; Sudheer, K. P.; Chaubey, I.
2017-08-01
Watershed hydrological models are effective tools for simulating the hydrological processes in the watershed. Although there are a plethora of hydrological models, none of them can be directly applied to make water conservation decisions in irregularly bounded areas that do not confirm to topographically defined ridge lines. This study proposes a novel hydrological model that can be directly applied to any catchment, with or without ridge line boundaries. The model is based on the water balance concept, and a linear function concept to approximate the cross-boundary flow from upstream areas to the administrative catchment under consideration. The developed model is tested in 2 watersheds - Riesel Experimental Watershed and a sub-basin of Cedar Creek Watershed in Texas, USA. Hypothetical administrative catchments that did not confirm to the location of ridge lines were considered for verifying the efficacy of the model for hydrologic simulations. The linear function concept used to account the cross boundary flow was based on the hypothesis that the flow coming from outside the boundary to administrative area was proportional to the flow generated in the boundary grid cell. The model performance was satisfactory with an NSE and r2 of ≥0.80 and a PBIAS of <25 in all the cases. The simulated hydrographs for the administrative catchments of the watersheds were in good agreement with the observed hydrographs, indicating a satisfactory performance of the model in the administratively bounded areas.
LaFontaine, Jacob H.; Jones, L. Elliott; Painter, Jaime A.
2017-12-29
A suite of hydrologic models has been developed for the Apalachicola-Chattahoochee-Flint River Basin (ACFB) as part of the National Water Census, a U.S. Geological Survey research program that focuses on developing new water accounting tools and assessing water availability and use at the regional and national scales. Seven hydrologic models were developed using the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, process-based system that simulates the effects of precipitation, temperature, land cover, and water use on basin hydrology. A coarse-resolution PRMS model was developed for the entire ACFB, and six fine-resolution PRMS models were developed for six subbasins of the ACFB. The coarse-resolution model was loosely coupled with a groundwater model to better assess the effects of water use on streamflow in the lower ACFB, a complex geologic setting with karst features. The PRMS coarse-resolution model was used to provide inputs of recharge to the groundwater model, which in turn provide simulations of groundwater flow that were aggregated with PRMS-based simulations of surface runoff and shallow-subsurface flow. Simulations without the effects of water use were developed for each model for at least the calendar years 1982–2012 with longer periods for the Potato Creek subbasin (1942–2012) and the Spring Creek subbasin (1952–2012). Water-use-affected flows were simulated for 2008–12. Water budget simulations showed heterogeneous distributions of precipitation, actual evapotranspiration, recharge, runoff, and storage change across the ACFB. Streamflow volume differences between no-water-use and water-use simulations were largest along the main stem of the Apalachicola and Chattahoochee River Basins, with streamflow percentage differences largest in the upper Chattahoochee and Flint River Basins and Spring Creek in the lower Flint River Basin. Water-use information at a shorter time step and a fully coupled simulation in the lower ACFB may further improve water availability estimates and hydrologic simulations in the basin.
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.
How much expert knowledge is it worth to put in conceptual hydrological models?
NASA Astrophysics Data System (ADS)
Antonetti, Manuel; Zappa, Massimiliano
2017-04-01
Both modellers and experimentalists agree on using expert knowledge to improve our conceptual hydrological simulations on ungauged basins. However, they use expert knowledge differently for both hydrologically mapping the landscape and parameterising a given hydrological model. Modellers use generally very simplified (e.g. topography-based) mapping approaches and put most of the knowledge for constraining the model by defining parameter and process relational rules. In contrast, experimentalists tend to invest all their detailed and qualitative knowledge about processes to obtain a spatial distribution of areas with different dominant runoff generation processes (DRPs) as realistic as possible, and for defining plausible narrow value ranges for each model parameter. Since, most of the times, the modelling goal is exclusively to simulate runoff at a specific site, even strongly simplified hydrological classifications can lead to satisfying results due to equifinality of hydrological models, overfitting problems and the numerous uncertainty sources affecting runoff simulations. Therefore, to test to which extent expert knowledge can improve simulation results under uncertainty, we applied a typical modellers' modelling framework relying on parameter and process constraints defined based on expert knowledge to several catchments on the Swiss Plateau. To map the spatial distribution of the DRPs, mapping approaches with increasing involvement of expert knowledge were used. Simulation results highlighted the potential added value of using all the expert knowledge available on a catchment. Also, combinations of event types and landscapes, where even a simplified mapping approach can lead to satisfying results, were identified. Finally, the uncertainty originated by the different mapping approaches was compared with the one linked to meteorological input data and catchment initial conditions.
USDA-ARS?s Scientific Manuscript database
In recent years, large-scale watershed modeling has been implemented broadly in the field of water resources planning and management. Complex hydrological, sediment, and nutrient processes can be simulated by sophisticated watershed simulation models for important issues such as water resources all...
Towards an integrated model of floodplain hydrology representing feedbacks and anthropogenic effects
NASA Astrophysics Data System (ADS)
Andreadis, K.; Schumann, G.; Voisin, N.; O'Loughlin, F.; Tesfa, T. K.; Bates, P.
2017-12-01
The exchange of water between hillslopes, river channels and floodplain can be quite complex and the difficulty in capturing the mechanisms behind it is exacerbated by the impact of human activities such as irrigation and reservoir operations. Although there has been a vast body of work on modeling hydrological processes, most of the resulting models have been limited with regards to aspects of the coupled human-natural system. For example, hydrologic models that represent processes such as evapotranspiration, infiltration, interception and groundwater dynamics often neglect anthropogenic effects or do not adequately represent the inherently two-dimensional floodplain flow. We present an integrated modeling framework that is comprised of the Variable Infiltration Capacity (VIC) hydrology model, the LISFLOOD-FP hydrodynamic model, and the Water resources Management (WM) model. The VIC model solves the energy and water balance over a gridded domain and simulates a number of hydrologic features such as snow, frozen soils, lakes and wetlands, while also representing irrigation demand from cropland areas. LISFLOOD-FP solves an approximation of the Saint-Venant equations to efficiently simulate flow in river channels and the floodplain. The implementation of WM accommodates a variety of operating rules in reservoirs and withdrawals due to consumptive demands, allowing the successful simulation of regulated flow. The models are coupled so as to allow feedbacks between their corresponding processes, therefore providing the ability to test different hypotheses about the floodplain hydrology of large-scale basins. We test this integrated framework over the Zambezi River basin by simulating its hydrology from 2000-2010, and evaluate the results against remotely sensed observations. Finally, we examine the sensitivity of streamflow and water inundation to changes in reservoir operations, precipitation and temperature.
NASA Astrophysics Data System (ADS)
Dierauer, J. R.; Allen, D. M.
2016-12-01
Climate change is expected to lead to an increase in extremes, including daily maximum temperatures, heat waves, and meteorological droughts, which will likely result in shifts in the hydrological drought regime (i.e. the frequency, timing, duration, and severity of drought events). While many studies have used hydrologic models to simulate climate change impacts on water resources, only a small portion of these studies have analyzed impacts on low flows and/or hydrological drought. This study is the first to use a fully coupled groundwater-surface water (gw-sw) model to study climate change impacts on hydrological drought. Generic catchment-scale gw-sw models were created for each of the six major eco-regions in British Columbia using the MIKE-SHE/MIKE-11 modelling code. Daily precipitation and temperature time series downscaled using bias-correction spatial disaggregation for the simulated period of 1950-2100 were obtained from the Pacific Climate Institute Consortium (PCIC). Streamflow and groundwater drought events were identified from the simulated time series for each catchment model using the moving window quantile threshold. The frequency, timing, duration, and severity of drought events were compared between the reference period (1961-2000) and two future time periods (2031-2060, 2071-2100). Results show how hydrological drought regimes across the different British Columbia eco-regions will be impacted by climate change.
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.
Multi-metric calibration of hydrological model to capture overall flow regimes
NASA Astrophysics Data System (ADS)
Zhang, Yongyong; Shao, Quanxi; Zhang, Shifeng; Zhai, Xiaoyan; She, Dunxian
2016-08-01
Flow regimes (e.g., magnitude, frequency, variation, duration, timing and rating of change) play a critical role in water supply and flood control, environmental processes, as well as biodiversity and life history patterns in the aquatic ecosystem. The traditional flow magnitude-oriented calibration of hydrological model was usually inadequate to well capture all the characteristics of observed flow regimes. In this study, we simulated multiple flow regime metrics simultaneously by coupling a distributed hydrological model with an equally weighted multi-objective optimization algorithm. Two headwater watersheds in the arid Hexi Corridor were selected for the case study. Sixteen metrics were selected as optimization objectives, which could represent the major characteristics of flow regimes. Model performance was compared with that of the single objective calibration. Results showed that most metrics were better simulated by the multi-objective approach than those of the single objective calibration, especially the low and high flow magnitudes, frequency and variation, duration, maximum flow timing and rating. However, the model performance of middle flow magnitude was not significantly improved because this metric was usually well captured by single objective calibration. The timing of minimum flow was poorly predicted by both the multi-metric and single calibrations due to the uncertainties in model structure and input data. The sensitive parameter values of the hydrological model changed remarkably and the simulated hydrological processes by the multi-metric calibration became more reliable, because more flow characteristics were considered. The study is expected to provide more detailed flow information by hydrological simulation for the integrated water resources management, and to improve the simulation performances of overall flow regimes.
NASA Astrophysics Data System (ADS)
Braun, Marco; Chaumont, Diane
2013-04-01
Using climate model output to explore climate change impacts on hydrology requires several considerations, choices and methods in the post treatment of the datasets. In the effort of producing a comprehensive data base of climate change scenarios for over 300 watersheds in the Canadian province of Québec, a selection of state of the art procedures were applied to an ensemble comprising 87 climate simulations. The climate data ensemble is based on global climate simulations from the Coupled Model Intercomparison Project - Phase 3 (CMIP3) and regional climate simulations from the North American Regional Climate Change Assessment Program (NARCCAP) and operational simulations produced at Ouranos. Information on the response of hydrological systems to changing climate conditions can be derived by linking climate simulations with hydrological models. However, the direct use of raw climate model output variables as drivers for hydrological models is limited by issues such as spatial resolution and the calibration of hydro models with observations. Methods for downscaling and bias correcting the data are required to achieve seamless integration of climate simulations with hydro models. The effects on the results of four different approaches to data post processing were explored and compared. We present the lessons learned from building the largest data base yet for multiple stakeholders in the hydro power and water management sector in Québec putting an emphasis on the benefits and pitfalls in choosing simulations, extracting the data, performing bias corrections and documenting the results. A discussion of the sources and significance of uncertainties in the data will also be included. The climatological data base was subsequently used by the state owned hydro power company Hydro-Québec and the Centre d'expertise hydrique du Québec (CEHQ), the provincial water authority, to simulate future stream flows and analyse the impacts on hydrological indicators. While this submission focuses on the production of climatic scenarios for application in hydrology, the submission « The (cQ)2 project: assessing watershed scale hydrological changes for the province of Québec at the 2050 horizon, a collaborative framework » by Catherine Guay describes how Hydro-Québec and CEHQ put the data into use.
Integrated watershed-scale response to climate change for selected basins across the United States
Markstrom, Steven L.; Hay, Lauren E.; Ward-Garrison, D. Christian; Risley, John C.; Battaglin, William A.; Bjerklie, David M.; Chase, Katherine J.; Christiansen, Daniel E.; Dudley, Robert W.; Hunt, Randall J.; Koczot, Kathryn M.; Mastin, Mark C.; Regan, R. Steven; Viger, Roland J.; Vining, Kevin C.; Walker, John F.
2012-01-01
A study by the U.S. Geological Survey (USGS) evaluated the hydrologic response to different projected carbon emission scenarios of the 21st century using a hydrologic simulation model. This study involved five major steps: (1) setup, calibrate and evaluated the Precipitation Runoff Modeling System (PRMS) model in 14 basins across the United States by local USGS personnel; (2) acquire selected simulated carbon emission scenarios from the World Climate Research Programme's Coupled Model Intercomparison Project; (3) statistical downscaling of these scenarios to create PRMS input files which reflect the future climatic conditions of these scenarios; (4) generate PRMS projections for the carbon emission scenarios for the 14 basins; and (5) analyze the modeled hydrologic response. This report presents an overview of this study, details of the methodology, results from the 14 basin simulations, and interpretation of these results. A key finding is that the hydrological response of the different geographical regions of the United States to potential climate change may be different, depending on the dominant physical processes of that particular region. Also considered is the tremendous amount of uncertainty present in the carbon emission scenarios and how this uncertainty propagates through the hydrologic simulations.
Lin, Yu-Pin; Hong, Nien-Ming; Chiang, Li-Chi; Liu, Yen-Lan; Chu, Hone-Jay
2012-01-01
The adaptation of land-use patterns is an essential aspect of minimizing the inevitable impact of climate change at regional and local scales; for example, adapting watershed land-use patterns to mitigate the impact of climate change on a region’s hydrology. The objective of this study is to simulate and assess a region’s ability to adapt to hydrological changes by modifying land-use patterns in the Wu-Du watershed in northern Taiwan. A hydrological GWLF (Generalized Watershed Loading Functions) model is used to simulate three hydrological components, namely, runoff, groundwater and streamflow, based on various land-use scenarios under six global climate models. The land-use allocations are simulated by the CLUE-s model for the various development scenarios. The simulation results show that runoff and streamflow are strongly related to the precipitation levels predicted by different global climate models for the wet and dry seasons, but groundwater cycles are more related to land-use. The effects of climate change on groundwater and runoff can be mitigated by modifying current land-use patterns; and slowing the rate of urbanization would also reduce the impact of climate change on hydrological components. Thus, land-use adaptation on a local/regional scale provides an alternative way to reduce the impacts of global climate change on local hydrology. PMID:23202833
JAMS - a software platform for modular hydrological modelling
NASA Astrophysics Data System (ADS)
Kralisch, Sven; Fischer, Christian
2015-04-01
Current challenges of understanding and assessing the impacts of climate and land use changes on environmental systems demand for an ever-increasing integration of data and process knowledge in corresponding simulation models. Software frameworks that allow for a seamless creation of integrated models based on less complex components (domain models, process simulation routines) have therefore gained increasing attention during the last decade. JAMS is an Open-Source software framework that has been especially designed to cope with the challenges of eco-hydrological modelling. This is reflected by (i) its flexible approach for representing time and space, (ii) a strong separation of process simulation components from the declarative description of more complex models using domain specific XML, (iii) powerful analysis and visualization functions for spatial and temporal input and output data, and (iv) parameter optimization and uncertainty analysis functions commonly used in environmental modelling. Based on JAMS, different hydrological and nutrient-transport simulation models were implemented and successfully applied during the last years. We will present the JAMS core concepts and give an overview of models, simulation components and support tools available for that framework. Sample applications will be used to underline the advantages of component-based model designs and to show how JAMS can be used to address the challenges of integrated hydrological modelling.
Estimating hydrologic budgets for six Persian Gulf watersheds, Iran
NASA Astrophysics Data System (ADS)
Hosseini, Majid; Ghafouri, Mohammad; Tabatabaei, MahmoudReza; Goodarzi, Masoud; Mokarian, Zeinab
2017-10-01
Estimation of the major components of the hydrologic budget is important for determining the impacts on the water supply and quality of either planned or proposed land management projects, vegetative changes, groundwater withdrawals, and reservoir management practices and plans. As acquisition of field data is costly and time consuming, models have been created to test various land use practices and their concomitant effects on the hydrologic budget of watersheds. To simulate such management scenarios realistically, a model should be able to simulate the individual components of the hydrologic budget. The main objective of this study is to perform the SWAT2012 model for estimation of hydrological budget in six subbasin of Persian Gulf watershed; Golgol, Baghan, Marghab Shekastian, Tangebirim and Daragah, which are located in south and south west of Iran during 1991-2009. In order to evaluate the performance of the model, hydrological data, soil map, land use map and digital elevation model (DEM) are obtained and prepared for each catchment to run the model. SWAT-CUP with SUFI2 program was used for simulation, uncertainty and validation with 95 Percent Prediction Uncertainty. Coefficient of determination ( R 2) and Nash-Sutcliffe coefficient (NS) were used for evaluation of the model simulation results. Comparison of measured and predicted values demonstrated that each component of the model gave reasonable output and that the interaction among components was realistic. The study has produced a technique with reliable capability for annual and monthly water budget components in Persian Gulf watershed.
An Educational Model for Hands-On Hydrology Education
NASA Astrophysics Data System (ADS)
AghaKouchak, A.; Nakhjiri, N.; Habib, E. H.
2014-12-01
This presentation provides an overview of a hands-on modeling tool developed for students in civil engineering and earth science disciplines to help them learn the fundamentals of hydrologic processes, model calibration, sensitivity analysis, uncertainty assessment, and practice conceptual thinking in solving engineering problems. The toolbox includes two simplified hydrologic models, namely HBV-EDU and HBV-Ensemble, designed as a complement to theoretical hydrology lectures. The models provide an interdisciplinary application-oriented learning environment that introduces the hydrologic phenomena through the use of a simplified conceptual hydrologic model. The toolbox can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for teaching more advanced topics including uncertainty analysis, and ensemble simulation. Both models have been administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of hydrology.
Benchmarking hydrological model predictive capability for UK River flows and flood peaks.
NASA Astrophysics Data System (ADS)
Lane, Rosanna; Coxon, Gemma; Freer, Jim; Wagener, Thorsten
2017-04-01
Data and hydrological models are now available for national hydrological analyses. However, hydrological model performance varies between catchments, and lumped, conceptual models are not able to produce adequate simulations everywhere. This study aims to benchmark hydrological model performance for catchments across the United Kingdom within an uncertainty analysis framework. We have applied four hydrological models from the FUSE framework to 1128 catchments across the UK. These models are all lumped models and run at a daily timestep, but differ in the model structural architecture and process parameterisations, therefore producing different but equally plausible simulations. We apply FUSE over a 20 year period from 1988-2008, within a GLUE Monte Carlo uncertainty analyses framework. Model performance was evaluated for each catchment, model structure and parameter set using standard performance metrics. These were calculated both for the whole time series and to assess seasonal differences in model performance. The GLUE uncertainty analysis framework was then applied to produce simulated 5th and 95th percentile uncertainty bounds for the daily flow time-series and additionally the annual maximum prediction bounds for each catchment. The results show that the model performance varies significantly in space and time depending on catchment characteristics including climate, geology and human impact. We identify regions where models are systematically failing to produce good results, and present reasons why this could be the case. We also identify regions or catchment characteristics where one model performs better than others, and have explored what structural component or parameterisation enables certain models to produce better simulations in these catchments. Model predictive capability was assessed for each catchment, through looking at the ability of the models to produce discharge prediction bounds which successfully bound the observed discharge. These results improve our understanding of the predictive capability of simple conceptual hydrological models across the UK and help us to identify where further effort is needed to develop modelling approaches to better represent different catchment and climate typologies.
USDA-ARS?s Scientific Manuscript database
The literature of daily hydrologic modelling illustrates that daily simulation models are incapable of accurately representing hydrograph timing due to relationships between precipitation and watershed hydrologic response. For watersheds with a time of concentration less than 24 hrs and a late day p...
We developed and applied a spatially-explicit, eco-hydrologic model to examine how a landscape disturbance affects hydrologic processes, ecosystem cycling of C and N, and ecosystem structure. We simulated how the pattern and magnitude of tree removal in a catchment influences fo...
Jarrett, G. Lynn; Downs, Aimee C.; Grace-Jarrett, Patricia A.
1998-01-01
The Hydrological Simulation Pro-gram-FORTRAN (HSPF) was applied to an urban drainage basin in Jefferson County, Ky to integrate the large amounts of information being collected on water quantity and quality into an analytical framework that could be used as a management and planning tool. Hydrologic response units were developed using geographic data and a K-means analysis to characterize important hydrologic and physical factors in the basin. The Hydrological Simulation Program FORTRAN Expert System (HSPEXP) was used to calibrate the model parameters for the Middle Fork Beargrass Creek Basin for 3 years (June 1, 1991, to May 31, 1994) of 5-minute streamflow and precipitation time series, and 3 years of hourly pan-evaporation time series. The calibrated model parameters were applied to the South Fork Beargrass Creek Basin for confirmation. The model confirmation results indicated that the model simulated the system within acceptable tolerances. The coefficient of determination and coefficient of model-fit efficiency between simulated and observed daily flows were 0.91 and 0.82, respectively, for model calibration and 0.88 and 0.77, respectively, for model confirmation. The model is most sensitive to estimates of the area of effective impervious land in the basin; the spatial distribution of rain-fall; and the lower-zone evapotranspiration, lower-zone nominal storage, and infiltration-capacity parameters during recession and low-flow periods. The error contribution from these sources varies with season and antecedent conditions.
Estimating postfire water production in the Pacific Northwest
Donald F. Potts; David L. Peterson; Hans R. Zuuring
1989-01-01
Two hydrologic models were adapted to estimate postfire changer in water yield in Pacific Northwest watersheds. The WRENSS version of the simulation model PROSPER is used for hydrologic regimes dominated by rainfall: it calculates water available for streamflow onthe basis of seasonal precipitation and leaf area index. The WRENSS version of the simulation model WATBAL...
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.
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.
GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate pot...
Luo, Chuan; Jiang, Kaixia; Wan, Rongrong; Li, Hengpeng
2017-01-01
The Hydrological Simulation Program–Fortran (HSPF) is a hydrological and water quality computer model that was developed by the United States Environmental Protection Agency. Comprehensive performance evaluations were carried out for hydrological and nutrient simulation using the HSPF model in the Xitiaoxi watershed in China. Streamflow simulation was calibrated from 1 January 2002 to 31 December 2007 and then validated from 1 January 2008 to 31 December 2010 using daily observed data, and nutrient simulation was calibrated and validated using monthly observed data during the period from July 2009 to July 2010. These results of model performance evaluation showed that the streamflows were well simulated over the study period. The determination coefficient (R2) was 0.87, 0.77 and 0.63, and the Nash-Sutcliffe coefficient of efficiency (Ens) was 0.82, 0.76 and 0.65 for the streamflow simulation in annual, monthly and daily time-steps, respectively. Although limited to monthly observed data, satisfactory performance was still achieved during the quantitative evaluation for nutrients. The R2 was 0.73, 0.82 and 0.92, and the Ens was 0.67, 0.74 and 0.86 for nitrate, ammonium and orthophosphate simulation, respectively. Some issues may affect the application of HSPF were also discussed, such as input data quality, parameter values, etc. Overall, the HSPF model can be successfully used to describe streamflow and nutrients transport in the mesoscale watershed located in the East Asian monsoon climate area. This study is expected to serve as a comprehensive and systematic documentation of understanding the HSPF model for wide application and avoiding possible misuses. PMID:29257117
Li, Zhaofu; Luo, Chuan; Jiang, Kaixia; Wan, Rongrong; Li, Hengpeng
2017-12-19
The Hydrological Simulation Program-Fortran (HSPF) is a hydrological and water quality computer model that was developed by the United States Environmental Protection Agency. Comprehensive performance evaluations were carried out for hydrological and nutrient simulation using the HSPF model in the Xitiaoxi watershed in China. Streamflow simulation was calibrated from 1 January 2002 to 31 December 2007 and then validated from 1 January 2008 to 31 December 2010 using daily observed data, and nutrient simulation was calibrated and validated using monthly observed data during the period from July 2009 to July 2010. These results of model performance evaluation showed that the streamflows were well simulated over the study period. The determination coefficient ( R ²) was 0.87, 0.77 and 0.63, and the Nash-Sutcliffe coefficient of efficiency (Ens) was 0.82, 0.76 and 0.65 for the streamflow simulation in annual, monthly and daily time-steps, respectively. Although limited to monthly observed data, satisfactory performance was still achieved during the quantitative evaluation for nutrients. The R ² was 0.73, 0.82 and 0.92, and the Ens was 0.67, 0.74 and 0.86 for nitrate, ammonium and orthophosphate simulation, respectively. Some issues may affect the application of HSPF were also discussed, such as input data quality, parameter values, etc. Overall, the HSPF model can be successfully used to describe streamflow and nutrients transport in the mesoscale watershed located in the East Asian monsoon climate area. This study is expected to serve as a comprehensive and systematic documentation of understanding the HSPF model for wide application and avoiding possible misuses.
airGRteaching: an R-package designed for teaching hydrology with lumped hydrological models
NASA Astrophysics Data System (ADS)
Thirel, Guillaume; Delaigue, Olivier; Coron, Laurent; Andréassian, Vazken; Brigode, Pierre
2017-04-01
Lumped hydrological models are useful and convenient tools for research, engineering and educational purposes. They propose catchment-scale representations of the precipitation-discharge relationship. Thanks to their limited data requirements, they can be easily implemented and run. With such models, it is possible to simulate a number of hydrological key processes over the catchment with limited structural and parametric complexity, typically evapotranspiration, runoff, underground losses, etc. The Hydrology Group at Irstea (Antony) has been developing a suite of rainfall-runoff models over the past 30 years. This resulted in a suite of models running at different time steps (from hourly to annual) applicable for various issues including water balance estimation, forecasting, simulation of impacts and scenario testing. Recently, Irstea has developed an easy-to-use R-package (R Core Team, 2016), called airGR (Coron et al., 2016, 2017), to make these models widely available. Although its initial target public was hydrological modellers, the package is already used for educational purposes. Indeed, simple models allow for rapidly visualising the effects of parameterizations and model components on flows hydrographs. In order to avoid the difficulties that students may have when manipulating R and datasets, we developed (Delaigue and Coron, 2016): - Three simplified functions to prepare data, calibrate a model and run a simulation - Simplified and dynamic plot functions - A shiny (Chang et al., 2016) interface that connects this R-package to a browser-based visualisation tool. On this interface, the students can use different hydrological models (including the possibility to use a snow-accounting model), manually modify their parameters and automatically calibrate their parameters with diverse objective functions. One of the visualisation tabs of the interface includes observed precipitation and temperature, simulated snowpack (if any), observed and simulated discharges, which are updated immediately (a calibration only needs a couple of seconds or less, a simulation is almost immediate). In addition, time series of internal variables, live-visualisation of internal variables evolution and performance statistics are provided. This interface allows for hands-on exercises that can include for instance the analysis by students of: - The effects of each parameter and model components on simulated discharge - The effects of objective functions based on high flows- or low flows-focused criteria on simulated discharge - The seasonality of the model components. References Winston Chang, Joe Cheng, JJ Allaire, Yihui Xie and Jonathan McPherson (2016). shiny: Web Application Framework for R. R package version 0.13.2. https://CRAN.R-project.org/package=shiny Coron L., Thirel G., Perrin C., Delaigue O., Andréassian V., airGR: a suite of lumped hydrological models in an R-package, Environmental Modelling and software, 2017, submitted. Coron, L., Perrin, C. and Michel, C. (2016). airGR: Suite of GR hydrological models for precipitation-runoff modelling. R package version 1.0.3. https://webgr.irstea.fr/airGR/?lang=en. Olivier Delaigue and Laurent Coron (2016). airGRteaching: Tools to simplify the use of the airGR hydrological package by students. R package version 0.0.1. https://webgr.irstea.fr/airGR/?lang=en R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
NASA Astrophysics Data System (ADS)
Painter, S.; Moulton, J. D.; Berndt, M.; Coon, E.; Garimella, R.; Lewis, K. C.; Manzini, G.; Mishra, P.; Travis, B. J.; Wilson, C. J.
2012-12-01
The frozen soils of the Arctic and subarctic regions contain vast amounts of stored organic carbon. This carbon is vulnerable to release to the atmosphere as temperatures warm and permafrost degrades. Understanding the response of the subsurface and surface hydrologic system to degrading permafrost is key to understanding the rate, timing, and chemical form of potential carbon releases to the atmosphere. Simulating the hydrologic system in degrading permafrost regions is challenging because of the potential for topographic evolution and associated drainage network reorganization as permafrost thaws and massive ground ice melts. The critical process models required for simulating hydrology include subsurface thermal hydrology of freezing/thawing soils, thermal processes within ice wedges, mechanical deformation processes, overland flow, and surface energy balances including snow dynamics. A new simulation tool, the Arctic Terrestrial Simulator (ATS), is being developed to simulate these coupled processes. The computational infrastructure must accommodate fully unstructured grids that track evolving topography, allow accurate solutions on distorted grids, provide robust and efficient solutions on highly parallel computer architectures, and enable flexibility in the strategies for coupling among the various processes. The ATS is based on Amanzi (Moulton et al. 2012), an object-oriented multi-process simulator written in C++ that provides much of the necessary computational infrastructure. Status and plans for the ATS including major hydrologic process models and validation strategies will be presented. Highly parallel simulations of overland flow using high-resolution digital elevation maps of polygonal patterned ground landscapes demonstrate the feasibility of the approach. Simulations coupling three-phase subsurface thermal hydrology with a simple thaw-induced subsidence model illustrate the strong feedbacks among the processes. D. Moulton, M. Berndt, M. Day, J. Meza, et al., High-Level Design of Amanzi, the Multi-Process High Performance Computing Simulator, Technical Report ASCEM-HPC-2011-03-1, DOE Environmental Management, 2012.
NASA Astrophysics Data System (ADS)
Paparrizos, Spyridon; Maris, Fotios
2017-05-01
The MIKE SHE model is able to simulate the entire stream flow which includes direct and basic flow. Many models either do not simulate or use simplistic methods to determine the basic flow. The MIKE SHE model takes into account many hydrological data. Since this study was directed towards the simulation of surface runoff and infiltration into saturated and unsaturated zone, the MIKE SHE is an appropriate model for reliable conclusions. In the current research, the MIKE SHE model was used to simulate runoff in the area of Sperchios River basin. Meteorological data from eight rainfall stations within the Sperchios River basin were used as inputs. Vegetation as well as geological data was used to perform the calibration and validation of the physical processes of the model. Additionally, ArcGIS program was used. The results indicated that the model was able to simulate the surface runoff satisfactorily, representing all the hydrological data adequately. Some minor differentiations appeared which can be eliminated with the appropriate adjustments that can be decided by the researcher's experience.
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 ...
NASA Astrophysics Data System (ADS)
Chang, Yong; Wu, Jichun; Jiang, Guanghui; Kang, Zhiqiang
2017-05-01
Conceptual models often suffer from the over-parameterization problem due to limited available data for the calibration. This leads to the problem of parameter nonuniqueness and equifinality, which may bring much uncertainty of the simulation result. How to find out the appropriate model structure supported by the available data to simulate the catchment is still a big challenge in the hydrological research. In this paper, we adopt a multi-model framework to identify the dominant hydrological process and appropriate model structure of a karst spring, located in Guilin city, China. For this catchment, the spring discharge is the only available data for the model calibration. This framework starts with a relative complex conceptual model according to the perception of the catchment and then this complex is simplified into several different models by gradually removing the model component. The multi-objective approach is used to compare the performance of these different models and the regional sensitivity analysis (RSA) is used to investigate the parameter identifiability. The results show this karst spring is mainly controlled by two different hydrological processes and one of the processes is threshold-driven which is consistent with the fieldwork investigation. However, the appropriate model structure to simulate the discharge of this spring is much simpler than the actual aquifer structure and hydrological processes understanding from the fieldwork investigation. A simple linear reservoir with two different outlets is enough to simulate this spring discharge. The detail runoff process in the catchment is not needed in the conceptual model to simulate the spring discharge. More complex model should need more other additional data to avoid serious deterioration of model predictions.
NASA Astrophysics Data System (ADS)
Norton, P. A., II
2015-12-01
The U. S. Geological Survey is developing a National Hydrologic Model (NHM) to support consistent hydrologic modeling across the conterminous United States (CONUS). The Precipitation-Runoff Modeling System (PRMS) simulates daily hydrologic and energy processes in watersheds, and is used for the NHM application. For PRMS each watershed is divided into hydrologic response units (HRUs); by default each HRU is assumed to have a uniform hydrologic response. The Geospatial Fabric (GF) is a database containing initial parameter values for input to PRMS and was created for the NHM. The parameter values in the GF were derived from datasets that characterize the physical features of the entire CONUS. The NHM application is composed of more than 100,000 HRUs from the GF. Selected parameter values commonly are adjusted by basin in PRMS using an automated calibration process based on calibration targets, such as streamflow. Providing each HRU with distinct values that captures variability within the CONUS may improve simulation performance of the NHM. During calibration of the NHM by HRU, selected parameter values are adjusted for PRMS based on calibration targets, such as streamflow, snow water equivalent (SWE) and actual evapotranspiration (AET). Simulated SWE, AET, and runoff were compared to value ranges derived from multiple sources (e.g. the Snow Data Assimilation System, the Moderate Resolution Imaging Spectroradiometer (i.e. MODIS) Global Evapotranspiration Project, the Simplified Surface Energy Balance model, and the Monthly Water Balance Model). This provides each HRU with a distinct set of parameter values that captures the variability within the CONUS, leading to improved model performance. We present simulation results from the NHM after preliminary calibration, including the results of basin-level calibration for the NHM using: 1) default initial GF parameter values, and 2) parameter values calibrated by HRU.
NASA Astrophysics Data System (ADS)
Jie, M.; Zhang, J.; Guo, B. B.
2017-12-01
As a typical distributed hydrological model, the SWAT model also has a challenge in calibrating parameters and analysis their uncertainty. This paper chooses the Chaohe River Basin China as the study area, through the establishment of the SWAT model, loading the DEM data of the Chaohe river basin, the watershed is automatically divided into several sub-basins. Analyzing the land use, soil and slope which are on the basis of the sub-basins and calculating the hydrological response unit (HRU) of the study area, after running SWAT model, the runoff simulation values in the watershed are obtained. On this basis, using weather data, known daily runoff of three hydrological stations, combined with the SWAT-CUP automatic program and the manual adjustment method are used to analyze the multi-site calibration of the model parameters. Furthermore, the GLUE algorithm is used to analyze the parameters uncertainty of the SWAT model. Through the sensitivity analysis, calibration and uncertainty study of SWAT, the results indicate that the parameterization of the hydrological characteristics of the Chaohe river is successful and feasible which can be used to simulate the Chaohe river basin.
Stochastic Simulation and Forecast of Hydrologic Time Series Based on Probabilistic Chaos Expansion
NASA Astrophysics Data System (ADS)
Li, Z.; Ghaith, M.
2017-12-01
Hydrological processes are characterized by many complex features, such as nonlinearity, dynamics and uncertainty. How to quantify and address such complexities and uncertainties has been a challenging task for water engineers and managers for decades. To support robust uncertainty analysis, an innovative approach for the stochastic simulation and forecast of hydrologic time series is developed is this study. Probabilistic Chaos Expansions (PCEs) are established through probabilistic collocation to tackle uncertainties associated with the parameters of traditional hydrological models. The uncertainties are quantified in model outputs as Hermite polynomials with regard to standard normal random variables. Sequentially, multivariate analysis techniques are used to analyze the complex nonlinear relationships between meteorological inputs (e.g., temperature, precipitation, evapotranspiration, etc.) and the coefficients of the Hermite polynomials. With the established relationships between model inputs and PCE coefficients, forecasts of hydrologic time series can be generated and the uncertainties in the future time series can be further tackled. The proposed approach is demonstrated using a case study in China and is compared to a traditional stochastic simulation technique, the Markov-Chain Monte-Carlo (MCMC) method. Results show that the proposed approach can serve as a reliable proxy to complicated hydrological models. It can provide probabilistic forecasting in a more computationally efficient manner, compared to the traditional MCMC method. This work provides technical support for addressing uncertainties associated with hydrological modeling and for enhancing the reliability of hydrological modeling results. Applications of the developed approach can be extended to many other complicated geophysical and environmental modeling systems to support the associated uncertainty quantification and risk analysis.
An intermediate-scale model for thermal hydrology in low-relief permafrost-affected landscapes
Jan, Ahmad; Coon, Ethan T.; Painter, Scott L.; ...
2017-07-10
Integrated surface/subsurface models for simulating the thermal hydrology of permafrost-affected regions in a warming climate have recently become available, but computational demands of those new process-rich simu- lation tools have thus far limited their applications to one-dimensional or small two-dimensional simulations. We present a mixed-dimensional model structure for efficiently simulating surface/subsurface thermal hydrology in low-relief permafrost regions at watershed scales. The approach replaces a full three-dimensional system with a two-dimensional overland thermal hydrology system and a family of one-dimensional vertical columns, where each column represents a fully coupled surface/subsurface thermal hydrology system without lateral flow. The system is then operatormore » split, sequentially updating the overland flow system without sources and the one-dimensional columns without lateral flows. We show that the app- roach is highly scalable, supports subcycling of different processes, and compares well with the corresponding fully three-dimensional representation at significantly less computational cost. Those advances enable recently developed representations of freezing soil physics to be coupled with thermal overland flow and surface energy balance at scales of 100s of meters. Furthermore developed and demonstrated for permafrost thermal hydrology, the mixed-dimensional model structure is applicable to integrated surface/subsurface thermal hydrology in general.« less
O'Reilly, Andrew M.
2007-01-01
The transient response of a hydrologic system can be of concern to water-resource managers, because it is often extreme relatively short-lived events, such as floods or droughts, that profoundly influence the management of the resource. The water available to a hydrologic system for stream flow and aquifer recharge is determined by the difference of precipitation and evapotranspiration (ET). As such, temporal variations in precipitation and ET determine the degree of influence each has on the transient response of the hydrologic system. Meteorological, ET, and hydrologic data collected from 1993 to 2003 and spanning 1- to 3 2/3 -year periods were used to develop a hydrologic model for each of five sites in central Florida. The sensitivities of simulated water levels and flows to simple approximations of ET were quantified and the adequacy of each ET approximation was assessed. ET was approximated by computing potential ET, using the Hargreaves and Priestley-Taylor equations, and applying vegetation coefficients to adjust the potential ET values to actual ET. The Hargreaves and Priestley-Taylor ET approximations were used in the calibrated hydrologic models while leaving all other model characteristics and parameter values unchanged. Two primary factors that influence how the temporal variability of ET affects hydrologic simulation in central Florida were identified: (1) stochastic character of precipitation and ET and (2) the ability of the local hydrologic system to attenuate variability in input stresses. Differences in the stochastic character of precipitation and ET, both the central location and spread of the data, result in substantial influence of precipitation on the quantity and timing of water available to the hydrologic system and a relatively small influence of ET. The temporal variability of ET was considerably less than that of precipitation at each site over a wide range of time scales (from daily to annual). However, when precipitation and ET are of similar magnitude, small errors in ET can produce relatively large errors in available water, and accurate estimates of actual ET are more important. Local hydrologic conditions can also be an important factor influencing the hydrologic response to ET variability. Various points along a flow path in a hydrologic system respond differently to temporal variations in ET. For example, soil moisture contents in the root zone are sensitive to daily variations in ET, whereas spring flow responds to only longer term variations in ET. Both the Hargreaves and Priestley-Taylor equations for potential ET, when applied with an annually invariant monthly vegetation coefficient derived from comparison of measured ET with computed potential ET values, can be used with a hydrologic model to produce reasonable predictions of water levels and flows. Baseline-adjusted modified coefficients of efficiency for simulated water levels ranged from 0.0, indicating that water levels were simulated equally as well with approximated ET as with actual ET values, to -0.6, indicating that water levels were simulated better with actual ET values. Simulations using the Hargreaves approximation consistently yielded larger absolute and relative errors than the Priestley-Taylor approximation. However, the differences between the Hargreaves and Priestley-Taylor simulations generally were much smaller than differences between these simulations and the simulations using actual ET. This suggests that the simpler Hargreaves equation may be an adequate substitute for the more complex Priestley-Taylor equation, depending on the level of accuracy required to satisfy the particular modeling objectives.
Snow hydrology in a general circulation model
NASA Technical Reports Server (NTRS)
Marshall, Susan; Roads, John O.; Glatzmaier, Gary
1994-01-01
A snow hydrology has been implemented in an atmospheric general circulation model (GCM). The snow hydrology consists of parameterizations of snowfall and snow cover fraction, a prognostic calculation of snow temperature, and a model of the snow mass and hydrologic budgets. Previously, only snow albedo had been included by a specified snow line. A 3-year GCM simulation with this now more complete surface hydrology is compared to a previous GCM control run with the specified snow line, as well as with observations. In particular, the authors discuss comparisons of the atmospheric and surface hydrologic budgets and the surface energy budget for U.S. and Canadian areas. The new snow hydrology changes the annual cycle of the surface moisture and energy budgets in the model. There is a noticeable shift in the runoff maximum from winter in the control run to spring in the snow hydrology run. A substantial amount of GCM winter precipitation is now stored in the seasonal snowpack. Snow cover also acts as an important insulating layer between the atmosphere and the ground. Wintertime soil temperatures are much higher in the snow hydrology experiment than in the control experiment. Seasonal snow cover is important for dampening large fluctuations in GCM continental skin temperature during the Northern Hemisphere winter. Snow depths and snow extent show good agreement with observations over North America. The geographic distribution of maximum depths is not as well simulated by the model due, in part, to the coarse resolution of the model. The patterns of runoff are qualitatively and quantitatively similar to observed patterns of streamflow averaged over the continental United States. The seasonal cycles of precipitation and evaporation are also reasonably well simulated by the model, although their magnitudes are larger than is observed. This is due, in part, to a cold bias in this model, which results in a dry model atmosphere and enhances the hydrologic cycle everywhere.
NASA Astrophysics Data System (ADS)
Shin, S.; Pokhrel, Y. N.
2016-12-01
Land surface models have been used to assess water resources sustainability under changing Earth environment and increasing human water needs. Overwhelming observational records indicate that human activities have ubiquitous and pertinent effects on the hydrologic cycle; however, they have been crudely represented in large scale land surface models. In this study, we enhance an integrated continental-scale land hydrology model named Leaf-Hydro-Flood to better represent land-water management. The model is implemented at high resolution (5km grids) over the continental US. Surface water and groundwater are withdrawn based on actual practices. Newly added irrigation, water diversion, and dam operation schemes allow better simulations of stream flows, evapotranspiration, and infiltration. Results of various hydrologic fluxes and stores from two sets of simulation (one with and the other without human activities) are compared over a range of river basin and aquifer scales. The improved simulations of land hydrology have potential to build consistent modeling framework for human-water-climate interactions.
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.
NASA Astrophysics Data System (ADS)
Hagemann, Stefan; Chen, Cui; Haerter, Jan O.; Gerten, Dieter; Heinke, Jens; Piani, Claudio
2010-05-01
Future climate model scenarios depend crucially on their adequate representation of the hydrological cycle. Within the European project "Water and Global Change" (WATCH) special care is taken to couple state-of-the-art climate model output to a suite of hydrological models. This coupling is expected to lead to a better assessment of changes in the hydrological cycle. However, due to the systematic model errors of climate models, their output is often not directly applicable as input for hydrological models. Thus, the methodology of a statistical bias correction has been developed, which can be used for correcting climate model output to produce internally consistent fields that have the same statistical intensity distribution as the observations. As observations, global re-analysed daily data of precipitation and temperature are used that are obtained in the WATCH project. We will apply the bias correction to global climate model data of precipitation and temperature from the GCMs ECHAM5/MPIOM, CNRM-CM3 and LMDZ-4, and intercompare the bias corrected data to the original GCM data and the observations. Then, the orginal and the bias corrected GCM data will be used to force two global hydrology models: (1) the hydrological model of the Max Planck Institute for Meteorology (MPI-HM) consisting of the Simplified Land surface (SL) scheme and the Hydrological Discharge (HD) model, and (2) the dynamic vegetation model LPJmL operated by the Potsdam Institute for Climate Impact Research. The impact of the bias correction on the projected simulated hydrological changes will be analysed, and the resulting behaviour of the two hydrology models will be compared.
Asare, Ernest Ohene; Tompkins, Adrian Mark; Bomblies, Arne
2016-01-01
Dynamical malaria models can relate precipitation to the availability of vector breeding sites using simple models of surface hydrology. Here, a revised scheme is developed for the VECTRI malaria model, which is evaluated alongside the default scheme using a two year simulation by HYDREMATS, a 10 metre resolution, village-scale model that explicitly simulates individual ponds. Despite the simplicity of the two VECTRI surface hydrology parametrization schemes, they can reproduce the sub-seasonal evolution of fractional water coverage. Calibration of the model parameters is required to simulate the mean pond fraction correctly. The default VECTRI model tended to overestimate water fraction in periods subject to light rainfall events and underestimate it during periods of intense rainfall. This systematic error was improved in the revised scheme by including the a parametrization for surface run-off, such that light rainfall below the initial abstraction threshold does not contribute to ponds. After calibration of the pond model, the VECTRI model was able to simulate vector densities that compared well to the detailed agent based model contained in HYDREMATS without further parameter adjustment. Substituting local rain-gauge data with satellite-retrieved precipitation gave a reasonable approximation, raising the prospects for regional malaria simulations even in data sparse regions. However, further improvements could be made if a method can be derived to calibrate the key hydrology parameters of the pond model in each grid cell location, possibly also incorporating slope and soil texture.
Asare, Ernest Ohene; Tompkins, Adrian Mark; Bomblies, Arne
2016-01-01
Dynamical malaria models can relate precipitation to the availability of vector breeding sites using simple models of surface hydrology. Here, a revised scheme is developed for the VECTRI malaria model, which is evaluated alongside the default scheme using a two year simulation by HYDREMATS, a 10 metre resolution, village-scale model that explicitly simulates individual ponds. Despite the simplicity of the two VECTRI surface hydrology parametrization schemes, they can reproduce the sub-seasonal evolution of fractional water coverage. Calibration of the model parameters is required to simulate the mean pond fraction correctly. The default VECTRI model tended to overestimate water fraction in periods subject to light rainfall events and underestimate it during periods of intense rainfall. This systematic error was improved in the revised scheme by including the a parametrization for surface run-off, such that light rainfall below the initial abstraction threshold does not contribute to ponds. After calibration of the pond model, the VECTRI model was able to simulate vector densities that compared well to the detailed agent based model contained in HYDREMATS without further parameter adjustment. Substituting local rain-gauge data with satellite-retrieved precipitation gave a reasonable approximation, raising the prospects for regional malaria simulations even in data sparse regions. However, further improvements could be made if a method can be derived to calibrate the key hydrology parameters of the pond model in each grid cell location, possibly also incorporating slope and soil texture. PMID:27003834
Nonlinear Prediction Model for Hydrologic Time Series Based on Wavelet Decomposition
NASA Astrophysics Data System (ADS)
Kwon, H.; Khalil, A.; Brown, C.; Lall, U.; Ahn, H.; Moon, Y.
2005-12-01
Traditionally forecasting and characterizations of hydrologic systems is performed utilizing many techniques. Stochastic linear methods such as AR and ARIMA and nonlinear ones such as statistical learning theory based tools have been extensively used. The common difficulty to all methods is the determination of sufficient and necessary information and predictors for a successful prediction. Relationships between hydrologic variables are often highly nonlinear and interrelated across the temporal scale. A new hybrid approach is proposed for the simulation of hydrologic time series combining both the wavelet transform and the nonlinear model. The present model employs some merits of wavelet transform and nonlinear time series model. The Wavelet Transform is adopted to decompose a hydrologic nonlinear process into a set of mono-component signals, which are simulated by nonlinear model. The hybrid methodology is formulated in a manner to improve the accuracy of a long term forecasting. The proposed hybrid model yields much better results in terms of capturing and reproducing the time-frequency properties of the system at hand. Prediction results are promising when compared to traditional univariate time series models. An application of the plausibility of the proposed methodology is provided and the results conclude that wavelet based time series model can be utilized for simulating and forecasting of hydrologic variable reasonably well. This will ultimately serve the purpose of integrated water resources planning and management.
Validation of a national hydrological model
NASA Astrophysics Data System (ADS)
McMillan, H. K.; Booker, D. J.; Cattoën, C.
2016-10-01
Nationwide predictions of flow time-series are valuable for development of policies relating to environmental flows, calculating reliability of supply to water users, or assessing risk of floods or droughts. This breadth of model utility is possible because various hydrological signatures can be derived from simulated flow time-series. However, producing national hydrological simulations can be challenging due to strong environmental diversity across catchments and a lack of data available to aid model parameterisation. A comprehensive and consistent suite of test procedures to quantify spatial and temporal patterns in performance across various parts of the hydrograph is described and applied to quantify the performance of an uncalibrated national rainfall-runoff model of New Zealand. Flow time-series observed at 485 gauging stations were used to calculate Nash-Sutcliffe efficiency and percent bias when simulating between-site differences in daily series, between-year differences in annual series, and between-site differences in hydrological signatures. The procedures were used to assess the benefit of applying a correction to the modelled flow duration curve based on an independent statistical analysis. They were used to aid understanding of climatological, hydrological and model-based causes of differences in predictive performance by assessing multiple hypotheses that describe where and when the model was expected to perform best. As the procedures produce quantitative measures of performance, they provide an objective basis for model assessment that could be applied when comparing observed daily flow series with competing simulated flow series from any region-wide or nationwide hydrological model. Model performance varied in space and time with better scores in larger and medium-wet catchments, and in catchments with smaller seasonal variations. Surprisingly, model performance was not sensitive to aquifer fraction or rain gauge density.
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
NASA Astrophysics Data System (ADS)
Yang, J.; Zammit, C.; McMillan, H. K.
2016-12-01
As in most countries worldwide, water management in lowland areas is a big concern for New Zealand due to its economic importance for water related human activities. As a result, the estimation of available water resources in these areas (e.g., for irrigation and water supply purpose) is crucial and often requires an understanding of complex hydrological processes, which are often characterized by strong interactions between surface water and groundwater (usually expressed as losing and gaining rivers). These processes are often represented and simulated using integrated physically based hydrological models. However models with physically based groundwater modules typically require large amount of non-readily available geologic and aquifer information and are computationally intensive. Instead, this paper presents a conceptual groundwater model that is fully integrated into New Zealand's national hydrological model TopNet based on TopModel concepts (Beven, 1992). Within this conceptual framework, the integrated model can simulate not only surface processes, but also groundwater processes and surface water-groundwater interaction processes (including groundwater flow, river-groundwater interaction, and groundwater interaction with external watersheds). The developed model was applied to two New Zealand catchments with different hydro-geological and climate characteristics (Pareora catchment in the Canterbury Plains and Grey catchment on the West Coast). Previous studies have documented strong interactions between the river and groundwater, based on the analysis of a large number of concurrent flow measurements and associated information along the river main stem. Application of the integrated hydrological model indicates flow simulation (compared to the original hydrological model conceptualisation) during low flow conditions are significantly improved and further insights on local river dynamics are gained. Due to its conceptual characteristics and low level of data requirement, the integrated model could be used at local and national scales to improve the simulation of hydrological processes in non-topographically driven areas (where groundwater processes are important), and to assess impact of climate change on the integrated hydrological cycle in these areas.
NASA Astrophysics Data System (ADS)
Niswonger, R. G.; Huntington, J. L.; Dettinger, M. D.; Rajagopal, S.; Gardner, M.; Morton, C. G.; Reeves, D. M.; Pohll, G. M.
2013-12-01
Water resources in the Tahoe basin are susceptible to long-term climate change and extreme events because it is a middle-altitude, snow-dominated basin that experiences large inter-annual climate variations. Lake Tahoe provides critical water supply for its basin and downstream populations, but changes in water supply are obscured by complex climatic and hydrologic gradients across the high relief, geologically complex basin. An integrated surface and groundwater model of the Lake Tahoe basin has been developed using GSFLOW to assess the effects of climate change and extreme events on surface and groundwater resources. Key hydrologic mechanisms are identified with this model that explains recent changes in water resources of the region. Critical vulnerabilities of regional water-supplies and hazards also were explored. Maintaining a balance between (a) accurate representation of spatial features (e.g., geology, streams, and topography) and hydrologic response (i.e., groundwater, stream, lake, and wetland flows and storages), and (b) computational efficiency, is a necessity for the desired model applications. Potential climatic influences on water resources are analyzed here in simulations of long-term water-availability and flood responses to selected 100-year climate-model projections. GSFLOW is also used to simulate a scenario depicting an especially extreme storm event that was constructed from a combination of two historical atmospheric-river storm events as part of the USGS MultiHazards Demonstration Project. Historical simulated groundwater levels, streamflow, wetlands, and lake levels compare well with measured values for a 30-year historical simulation period. Results are consistent for both small and large model grid cell sizes, due to the model's ability to represent water table altitude, streams, and other hydrologic features at the sub-grid scale. Simulated hydrologic responses are affected by climate change, where less groundwater resources will be available during more frequent droughts. Simulated floods for the region indicate issues related to drainage in the developed areas around Lake Tahoe, and necessary dam releases that create downstream flood risks.
Evapotranspiration Calculator Desktop Tool
The Evapotranspiration Calculator estimates evapotranspiration time series data for hydrological and water quality models for the Hydrologic Simulation Program - Fortran (HSPF) and the Stormwater Management Model (SWMM).
NASA Astrophysics Data System (ADS)
Tian, Y.; Zheng, Y.; Zheng, C.; Han, F., Sr.
2017-12-01
Physically based and fully-distributed integrated hydrological models (IHMs) can quantitatively depict hydrological processes, both surface and subsurface, with sufficient spatial and temporal details. However, the complexity involved in pre-processing data and setting up models seriously hindered the wider application of IHMs in scientific research and management practice. This study introduces our design and development of Visual HEIFLOW, hereafter referred to as VHF, a comprehensive graphical data processing and modeling system for integrated hydrological simulation. The current version of VHF has been structured to accommodate an IHM named HEIFLOW (Hydrological-Ecological Integrated watershed-scale FLOW model). HEIFLOW is a model being developed by the authors, which has all typical elements of physically based and fully-distributed IHMs. It is based on GSFLOW, a representative integrated surface water-groundwater model developed by USGS. HEIFLOW provides several ecological modules that enable to simulate growth cycle of general vegetation and special plants (maize and populus euphratica). VHF incorporates and streamlines all key steps of the integrated modeling, and accommodates all types of GIS data necessary to hydrological simulation. It provides a GIS-based data processing framework to prepare an IHM for simulations, and has functionalities to flexibly display and modify model features (e.g., model grids, streams, boundary conditions, observational sites, etc.) and their associated data. It enables visualization and various spatio-temporal analyses of all model inputs and outputs at different scales (i.e., computing unit, sub-basin, basin, or user-defined spatial extent). The above system features, as well as many others, can significantly reduce the difficulty and time cost of building and using a complex IHM. The case study in the Heihe River Basin demonstrated the applicability of VHF for large scale integrated SW-GW modeling. Visualization and spatial-temporal analysis of the modeling results by HEIFLOW greatly facilitates our understanding on the complicated hydrologic cycle and relationship among the hydrological and ecological variables in the study area, and provides insights into the regional water resources management.
NASA Astrophysics Data System (ADS)
Niroula, Sundar; Halder, Subhadeep; Ghosh, Subimal
2018-06-01
Real time hydrologic forecasting requires near accurate initial condition of soil moisture; however, continuous monitoring of soil moisture is not operational in many regions, such as, in Ganga basin, extended in Nepal, India and Bangladesh. Here, we examine the impacts of perturbation/error in the initial soil moisture conditions on simulated soil moisture and streamflow in Ganga basin and its propagation, during the summer monsoon season (June to September). This provides information regarding the required minimum duration of model simulation for attaining the model stability. We use the Variable Infiltration Capacity model for hydrological simulations after validation. Multiple hydrologic simulations are performed, each of 21 days, initialized on every 5th day of the monsoon season for deficit, surplus and normal monsoon years. Each of these simulations is performed with the initial soil moisture condition obtained from long term runs along with positive and negative perturbations. The time required for the convergence of initial errors is obtained for all the cases. We find a quick convergence for the year with high rainfall as well as for the wet spells within a season. We further find high spatial variations in the time required for convergence; the region with high precipitation such as Lower Ganga basin attains convergence at a faster rate. Furthermore, deeper soil layers need more time for convergence. Our analysis is the first attempt on understanding the sensitivity of hydrological simulations of Ganga basin on initial soil moisture conditions. The results obtained here may be useful in understanding the spin-up requirements for operational hydrologic forecasts.
NASA Astrophysics Data System (ADS)
Li, L.; Xu, C.-Y.; Engeland, K.
2012-04-01
With respect to model calibration, parameter estimation and analysis of uncertainty sources, different approaches have been used in hydrological models. Bayesian method is one of the most widely used methods for uncertainty assessment of hydrological models, which incorporates different sources of information into a single analysis through Bayesian theorem. However, none of these applications can well treat the uncertainty in extreme flows of hydrological models' simulations. This study proposes a Bayesian modularization method approach in uncertainty assessment of conceptual hydrological models by considering the extreme flows. It includes a comprehensive comparison and evaluation of uncertainty assessments by a new Bayesian modularization method approach and traditional Bayesian models using the Metropolis Hasting (MH) algorithm with the daily hydrological model WASMOD. Three likelihood functions are used in combination with traditional Bayesian: the AR (1) plus Normal and time period independent model (Model 1), the AR (1) plus Normal and time period dependent model (Model 2) and the AR (1) plus multi-normal model (Model 3). The results reveal that (1) the simulations derived from Bayesian modularization method are more accurate with the highest Nash-Sutcliffe efficiency value, and (2) the Bayesian modularization method performs best in uncertainty estimates of entire flows and in terms of the application and computational efficiency. The study thus introduces a new approach for reducing the extreme flow's effect on the discharge uncertainty assessment of hydrological models via Bayesian. Keywords: extreme flow, uncertainty assessment, Bayesian modularization, hydrological model, WASMOD
Effects of Simulated Land-Use Changes on Water Quality of Lake Maumelle, Arkansas
Hart, Rheannon M.; Westerman, Drew A.; Petersen, James C.; Green, W. Reed; De Lanois, Jeanne L.
2011-01-01
Lake Maumelle is one of two principal drinking-water supplies for the Little Rock and North Little Rock metropolitan areas. Lake Maumelle and the Maumelle River (its primary tributary) are more pristine than most other reservoirs and streams in the region. However, as the Lake Maumelle watershed becomes increasingly more urbanized and timber harvesting becomes more frequent, concerns about the sustainability of the quality of the water supply also have increased. Two models were developed to partially address these concerns. A Hydrological Simulation Program-FORTRAN model was developed using input data collected from October 2004 through 2008. A CE-QUAL-W2 model was developed to simulate reservoir hydrodynamics and selected water quality using the simulated output from the Hydrological Simulation Program-FORTRAN model from January 2005 through 2008. The Hydrological Simulation Program-FORTRAN watershed model was calibrated to five streamflow-gaging stations, and in general, these stations characterize a range of subwatershed areas with varying land-use types. Continuous streamflow data, discrete sediment concentration data, and other discrete water-quality data were used to calibrate the Lake Maumelle Hydrological Simulation Program-FORTRAN model. The CE-QUAL-W2 reservoir model was calibrated to water-quality data and reservoir pool altitude collected during January 2005 through December 2008 at three lake stations. In general, the overall simulation for the Hydrological Simulation Program-FORTRAN and CE-UAL-W2 models matched reasonably well to the measured data. In general, simulated and measured suspended-sediment concentrations during periods of base flow (streamflows not substantially influenced by runoff) agree reasonably well for Williams Junction (with differences-simulated minus measured value-generally ranging from -14 to 19 mg/L, and percent difference-relative to the measured value-ranging from -87 to 642 percent) and Wye (differences generally ranging from -2 to 14 mg/L, -62 to 251 percent); however, the Hydrological Simulation Program-FORTRAN model generally does not match the suspended-sediment concentrations for all stations during periods of stormflow (streamflow substantially influenced by runoff). Generally, this is also the case for fecal coliform bacteria numbers and total organic carbon and nutrient concentrations. In general, water temperature and dissolved-oxygen concentration simulations followed measured seasonal trends for all stations with the largest differences occurring during periods of lowest water temperatures (for temperature) or during the periods of lowest measured dissolved-oxygen concentrations (for dissolved oxygen). For the CE-QUAL-W2 model, simulated vertical distributions of temperatures and dissolved-oxygen concentrations agreed with measured distributions even for complex temperature profiles. Considering the oligotrophic-mesotrophic (low to intermediate primary productivity and associated low nutrient concentrations) condition of Lake Maumelle, simulated algae, phosphorus, and ammonia concentrations compared well with generally low measured values.
NASA Astrophysics Data System (ADS)
Watanabe, S.; Kim, H.; Utsumi, N.
2017-12-01
This study aims to develop a new approach which projects hydrology under climate change using super ensemble experiments. The use of multiple ensemble is essential for the estimation of extreme, which is a major issue in the impact assessment of climate change. Hence, the super ensemble experiments are recently conducted by some research programs. While it is necessary to use multiple ensemble, the multiple calculations of hydrological simulation for each output of ensemble simulations needs considerable calculation costs. To effectively use the super ensemble experiments, we adopt a strategy to use runoff projected by climate models directly. The general approach of hydrological projection is to conduct hydrological model simulations which include land-surface and river routing process using atmospheric boundary conditions projected by climate models as inputs. This study, on the other hand, simulates only river routing model using runoff projected by climate models. In general, the climate model output is systematically biased so that a preprocessing which corrects such bias is necessary for impact assessments. Various bias correction methods have been proposed, but, to the best of our knowledge, no method has proposed for variables other than surface meteorology. Here, we newly propose a method for utilizing the projected future runoff directly. The developed method estimates and corrects the bias based on the pseudo-observation which is a result of retrospective offline simulation. We show an application of this approach to the super ensemble experiments conducted under the program of Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI). More than 400 ensemble experiments from multiple climate models are available. The results of the validation using historical simulations by HAPPI indicates that the output of this approach can effectively reproduce retrospective runoff variability. Likewise, the bias of runoff from super ensemble climate projections is corrected, and the impact of climate change on hydrologic extremes is assessed in a cost-efficient way.
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.
User's guide for MAGIC-Meteorologic and hydrologic genscn (generate scenarios) input converter
Ortel, Terry W.; Martin, Angel
2010-01-01
Meteorologic and hydrologic data used in watershed modeling studies are collected by various agencies and organizations, and stored in various formats. Data may be in a raw, un-processed format with little or no quality control, or may be checked for validity before being made available. Flood-simulation systems require data in near real-time so that adequate flood warnings can be made. Additionally, forecasted data are needed to operate flood-control structures to potentially mitigate flood damages. Because real-time data are of a provisional nature, missing data may need to be estimated for use in floodsimulation systems. The Meteorologic and Hydrologic GenScn (Generate Scenarios) Input Converter (MAGIC) can be used to convert data from selected formats into the Hydrologic Simulation System-Fortran hourly-observations format for input to a Watershed Data Management database, for use in hydrologic modeling studies. MAGIC also can reformat the data to the Full Equations model time-series format, for use in hydraulic modeling studies. Examples of the application of MAGIC for use in the flood-simulation system for Salt Creek in northeastern Illinois are presented in this report.
Xue, Lianqing; Yang, Fan; Yang, Changbing; Wei, Guanghui; Li, Wenqian; He, Xinlin
2018-01-11
Understanding the mechanism of complicated hydrological processes is important for sustainable management of water resources in an arid area. This paper carried out the simulations of water movement for the Manas River Basin (MRB) using the improved semi-distributed Topographic hydrologic model (TOPMODEL) with a snowmelt model and topographic index algorithm. A new algorithm is proposed to calculate the curve of topographic index using internal tangent circle on a conical surface. Based on the traditional model, the improved indicator of temperature considered solar radiation is used to calculate the amount of snowmelt. The uncertainty of parameters for the TOPMODEL model was analyzed using the generalized likelihood uncertainty estimation (GLUE) method. The proposed model shows that the distribution of the topographic index is concentrated in high mountains, and the accuracy of runoff simulation has certain enhancement by considering radiation. Our results revealed that the performance of the improved TOPMODEL is acceptable and comparable to runoff simulation in the MRB. The uncertainty of the simulations resulted from the parameters and structures of model, climatic and anthropogenic factors. This study is expected to serve as a valuable complement for widely application of TOPMODEL and identify the mechanism of hydrological processes in arid area.
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.
Williamson, Tanja N.; Lant, Jeremiah G.; Claggett, Peter; Nystrom, Elizabeth A.; Milly, Paul C.D.; Nelson, Hugh L.; Hoffman, Scott A.; Colarullo, Susan J.; Fischer, Jeffrey M.
2015-11-18
The Water Availability Tool for Environmental Resources (WATER) is a decision support system for the nontidal part of the Delaware River Basin that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions. In order to quantify the uncertainty associated with these simulations, however, streamflow and the associated hydroclimatic variables of potential evapotranspiration, actual evapotranspiration, and snow accumulation and snowmelt must be simulated and compared to long-term, daily observations from sites. This report details model development and optimization, statistical evaluation of simulations for 57 basins ranging from 2 to 930 km2 and 11.0 to 99.5 percent forested cover, and how this statistical evaluation of daily streamflow relates to simulating environmental changes and management decisions that are best examined at monthly time steps normalized over multiple decades. The decision support system provides a database of historical spatial and climatic data for simulating streamflow for 2001–11, in addition to land-cover and general circulation model forecasts that focus on 2030 and 2060. WATER integrates geospatial sampling of landscape characteristics, including topographic and soil properties, with a regionally calibrated hillslope-hydrology model, an impervious-surface model, and hydroclimatic models that were parameterized by using three hydrologic response units: forested, agricultural, and developed land cover. This integration enables the regional hydrologic modeling approach used in WATER without requiring site-specific optimization or those stationary conditions inferred when using a statistical model.
Meyer, Swen; Blaschek, Michael; Duttmann, Rainer; Ludwig, Ralf
2016-02-01
According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. These changes are expected to have severe direct impacts on the management of water resources, agricultural productivity and drinking water supply. Current projections of future hydrological change, based on regional climate model results and subsequent hydrological modeling schemes, are very uncertain and poorly validated. The Rio Mannu di San Sperate Basin, located in Sardinia, Italy, is one test site of the CLIMB project. The Water Simulation Model (WaSiM) was set up to model current and future hydrological conditions. The availability of measured meteorological and hydrological data is poor as it is common for many Mediterranean catchments. In this study we conducted a soil sampling campaign in the Rio Mannu catchment. We tested different deterministic and hybrid geostatistical interpolation methods on soil textures and tested the performance of the applied models. We calculated a new soil texture map based on the best prediction method. The soil model in WaSiM was set up with the improved new soil information. The simulation results were compared to standard soil parametrization. WaSiMs was validated with spatial evapotranspiration rates using the triangle method (Jiang and Islam, 1999). WaSiM was driven with the meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. The climate change impact was assessed based on differences between reference and future time series. The simulated results show a reduction of all hydrological quantities in the future in the spring season. Furthermore simulation results reveal an earlier onset of dry conditions in the catchment. We show that a solid soil model setup based on short-term field measurements can improve long-term modeling results, which is especially important in ungauged catchments. Copyright © 2015 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Setegn, S. G.; Mahmoudi, M.; Lawrence, A.; Duque, N.
2015-12-01
The Applied Research Center at Florida International University (ARC-FIU) is supporting the soil and groundwater remediation efforts of the U.S. Department of Energy (DOE) Savannah River Site (SRS) by developing a surface water model to simulate the hydrology and the fate and transport of contaminants and sediment in the Tims Branch watershed. Hydrological models are useful tool in water and land resource development and decision-making for watershed management. Moreover, simulation of hydrological processes improves understanding of the environmental dynamics and helps to manage and protect water resources and the environment. MIKE SHE, an advanced integrated modeling system is used to simulate the hydrological processes of the Tim Branch watershed with the objective of developing an integrated modeling system to improve understanding of the physical, chemical and biological processes within the Tims Branch watershed. MIKE SHE simulates water flow in the entire land based phase of the hydrological cycle from rainfall to river flow, via various flow processes such as, overland flow, infiltration, evapotranspiration, and groundwater flow. In this study a MIKE SHE model is developed and applied to the Tim branch watershed to study the watershed response to storm events and understand the water balance of the watershed under different climatic and catchment characteristics. The preliminary result of the integrated model indicated that variation in the depth of overland flow highly depend on the amount and distribution of rainfall in the watershed. The ultimate goal of this project is to couple the MIKE SHE and MIKE 11 models to integrate the hydrological component in the land phase of hydrological cycle and stream flow process. The coupled MIKE SHE/MIKE 11 model will further be integrated with an Ecolab module to represent a range of water quality, contaminant transport, and ecological processes with respect to the stream, surface water and groundwater in the Tims Branch watershed at Savannah River Site.
NASA Astrophysics Data System (ADS)
Flores, A. N.; Pathak, C. S.; Senarath, S. U.; Bras, R. L.
2009-12-01
Robust hydrologic monitoring networks represent a critical element of decision support systems for effective water resource planning and management. Moreover, process representation within hydrologic simulation models is steadily improving, while at the same time computational costs are decreasing due to, for instance, readily available high performance computing resources. The ability to leverage these increasingly complex models together with the data from these monitoring networks to provide accurate and timely estimates of relevant hydrologic variables within a multiple-use, managed water resources system would substantially enhance the information available to resource decision makers. Numerical data assimilation techniques provide mathematical frameworks through which uncertain model predictions can be constrained to observational data to compensate for uncertainties in the model forcings and parameters. In ensemble-based data assimilation techniques such as the ensemble Kalman Filter (EnKF), information in observed variables such as canal, marsh and groundwater stages are propagated back to the model states in a manner related to: (1) the degree of certainty in the model state estimates and observations, and (2) the cross-correlation between the model states and the observable outputs of the model. However, the ultimate degree to which hydrologic conditions can be accurately predicted in an area of interest is controlled, in part, by the configuration of the monitoring network itself. In this proof-of-concept study we developed an approach by which the design of an existing hydrologic monitoring network is adapted to iteratively improve the predictions of hydrologic conditions within an area of the South Florida Water Management District (SFWMD). The objective of the network design is to minimize prediction errors of key hydrologic states and fluxes produced by the spatially distributed Regional Simulation Model (RSM), developed specifically to simulate the hydrologic conditions in several intensively managed and hydrologically complex watersheds within the SFWMD system. In a series of synthetic experiments RSM is used to generate the notionally true hydrologic state and the relevant observational data. The EnKF is then used as the mechanism to fuse RSM hydrologic estimates with data from the candidate network. The performance of the candidate network is measured by the prediction errors of the EnKF estimates of hydrologic states, relative to the notionally true scenario. The candidate network is then adapted by relocating existing observational sites to unobserved areas where predictions of local hydrologic conditions are most uncertain and the EnKF procedure repeated. Iteration of the monitoring network continues until further improvements in EnKF-based predictions of hydrologic conditions are negligible.
Healy, Richard W.; Scanlon, Bridget R.
2010-01-01
Simulation models are widely used in all types of hydrologic studies, and many of these models can be used to estimate recharge. Models can provide important insight into the functioning of hydrologic systems by identifying factors that influence recharge. The predictive capability of models can be used to evaluate how changes in climate, water use, land use, and other factors may affect recharge rates. Most hydrological simulation models, including watershed models and groundwater-flow models, are based on some form of water-budget equation, so the material in this chapter is closely linked to that in Chapter 2. Empirical models that are not based on a water-budget equation have also been used for estimating recharge; these models generally take the form of simple estimation equations that define annual recharge as a function of precipitation and possibly other climatic data or watershed characteristics.Model complexity varies greatly. Some models are simple accounting models; others attempt to accurately represent the physics of water movement through each compartment of the hydrologic system. Some models provide estimates of recharge explicitly; for example, a model based on the Richards equation can simulate water movement from the soil surface through the unsaturated zone to the water table. Recharge estimates can be obtained indirectly from other models. For example, recharge is a parameter in groundwater-flow models that solve for hydraulic head (i.e. groundwater level). Recharge estimates can be obtained through a model calibration process in which recharge and other model parameter values are adjusted so that simulated water levels agree with measured water levels. The simulation that provides the closest agreement is called the best fit, and the recharge value used in that simulation is the model-generated estimate of recharge.
On the information content of hydrological signatures and their relationship to catchment attributes
NASA Astrophysics Data System (ADS)
Addor, Nans; Clark, Martyn P.; Prieto, Cristina; Newman, Andrew J.; Mizukami, Naoki; Nearing, Grey; Le Vine, Nataliya
2017-04-01
Hydrological signatures, which are indices characterizing hydrologic behavior, are increasingly used for the evaluation, calibration and selection of hydrological models. Their key advantage is to provide more direct insights into specific hydrological processes than aggregated metrics (e.g., the Nash-Sutcliffe efficiency). A plethora of signatures now exists, which enable characterizing a variety of hydrograph features, but also makes the selection of signatures for new studies challenging. Here we propose that the selection of signatures should be based on their information content, which we estimated using several approaches, all leading to similar conclusions. To explore the relationship between hydrological signatures and the landscape, we extended a previously published data set of hydrometeorological time series for 671 catchments in the contiguous United States, by characterizing the climatic conditions, topography, soil, vegetation and stream network of each catchment. This new catchment attributes data set will soon be in open access, and we are looking forward to introducing it to the community. We used this data set in a data-learning algorithm (random forests) to explore whether hydrological signatures could be inferred from catchment attributes alone. We find that some signatures can be predicted remarkably well by random forests and, interestingly, the same signatures are well captured when simulating discharge using a conceptual hydrological model. We discuss what this result reveals about our understanding of hydrological processes shaping hydrological signatures. We also identify which catchment attributes exert the strongest control on catchment behavior, in particular during extreme hydrological events. Overall, climatic attributes have the most significant influence, and strongly condition how well hydrological signatures can be predicted by random forests and simulated by the hydrological model. In contrast, soil characteristics at the catchment scale are not found to be significant predictors by random forests, which raises questions on how to best use soil data for hydrological modeling, for instance for parameter estimation. We finally demonstrate that signatures with high spatial variability are poorly captured by random forests and model simulations, which makes their regionalization delicate. We conclude with a ranking of signatures based on their information content, and propose that the signatures with high information content are best suited for model calibration, model selection and understanding hydrologic similarity.
NASA Astrophysics Data System (ADS)
White, Jeremy; Stengel, Victoria; Rendon, Samuel; Banta, John
2017-08-01
Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral
in that they reproduce daily mean streamflow acceptably well according to Nash-Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.
White, Jeremy; Stengel, Victoria G.; Rendon, Samuel H.; Banta, John
2017-01-01
Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash–Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.
A new fit-for-purpose model testing framework: Decision Crash Tests
NASA Astrophysics Data System (ADS)
Tolson, Bryan; Craig, James
2016-04-01
Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building decisions. In one case, we show the set of model building decisions has a low probability to correctly support the upgrade decision. In the other case, we show evidence suggesting another set of model building decisions has a high probability to correctly support the decision. The proposed DCT framework focuses on what model users typically care about: the management decision in question. The DCT framework will often be very strict and will produce easy to interpret results enabling clear unsuitability determinations. In the past, hydrologic modelling progress has necessarily meant new models and model building methods. Continued progress in hydrologic modelling requires finding clear evidence to motivate researchers to disregard unproductive models and methods and the DCT framework is built to produce this kind of evidence. References: Andréassian, V., C. Perrin, L. Berthet, N. Le Moine, J. Lerat, C. Loumagne, L. Oudin, T. Mathevet, M.-H. Ramos, and A. Valéry (2009), Crash tests for a standardized evaluation of hydrological models. Hydrology and Earth System Sciences, 13, 1757-1764. Klemeš, V. (1986), Operational testing of hydrological simulation models. Hydrological Sciences Journal, 31 (1), 13-24.
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.
Chalise, D. R.; Haj, Adel E.; Fontaine, T.A.
2018-01-01
The hydrological simulation program Fortran (HSPF) [Hydrological Simulation Program Fortran version 12.2 (Computer software). USEPA, Washington, DC] and the precipitation runoff modeling system (PRMS) [Precipitation Runoff Modeling System version 4.0 (Computer software). USGS, Reston, VA] models are semidistributed, deterministic hydrological tools for simulating the impacts of precipitation, land use, and climate on basin hydrology and streamflow. Both models have been applied independently to many watersheds across the United States. This paper reports the statistical results assessing various temporal (daily, monthly, and annual) and spatial (small versus large watershed) scale biases in HSPF and PRMS simulations using two watersheds in the Black Hills, South Dakota. The Nash-Sutcliffe efficiency (NSE), Pearson correlation coefficient (r">rr), and coefficient of determination (R2">R2R2) statistics for the daily, monthly, and annual flows were used to evaluate the models’ performance. Results from the HSPF models showed that the HSPF consistently simulated the annual flows for both large and small basins better than the monthly and daily flows, and the simulated flows for the small watershed better than flows for the large watershed. In comparison, the PRMS model results show that the PRMS simulated the monthly flows for both the large and small watersheds better than the daily and annual flows, and the range of statistical error in the PRMS models was greater than that in the HSPF models. Moreover, it can be concluded that the statistical error in the HSPF and the PRMSdaily, monthly, and annual flow estimates for watersheds in the Black Hills was influenced by both temporal and spatial scale variability.
Hydrological model uncertainty due to spatial evapotranspiration estimation methods
NASA Astrophysics Data System (ADS)
Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub
2016-05-01
Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.
NASA Astrophysics Data System (ADS)
Mottes, Charles; Lesueur-Jannoyer, Magalie; Charlier, Jean-Baptiste; Carles, Céline; Guéné, Mathilde; Le Bail, Marianne; Malézieux, Eric
2015-10-01
Simulation of flows and pollutant transfers in heterogeneous media is widely recognized to be a remaining frontier in hydrology research. We present a new modeling approach to simulate agricultural pollutions in watersheds: WATPPASS, a model for Watershed Agricultural Techniques and Pesticide Practices ASSessment. It is designed to assess mean pesticide concentrations and loads that result from the use of pesticides in horticultural watersheds located on heterogeneous subsoil. WATPPASS is suited for small watershed with significant groundwater flows and complex aquifer systems. The model segments the watershed into fields with independent hydrological and pesticide transfers at the ground surface. Infiltrated water and pesticides are routed toward outlet using a conceptual reservoir model. We applied WATPPASS on a heterogeneous tropical volcanic watershed of Martinique in the French West Indies. We carried out and hydrological analysis that defined modeling constraints: (i) a spatial variability of runoff/infiltration partitioning according to land use, and (ii) a predominance of groundwater flow paths in two overlapping aquifers under permeable soils (50-60% of annual flows). We carried out simulations on a 550 days period at a daily time step for hydrology (Nashsqrt > 0.75). Weekly concentrations and loads of a persistent organic pesticide (chlordecone) were simulated for 67 weeks to evaluate the modeling approach. Pesticide simulations without specific calibration detected the mean long-term measured concentration, leading to a good quantification of the cumulative loads (5% error), but failed to represent the concentration peaks at the correct timing. Nevertheless, we succeed in adjusting the model structure to better represent the temporal dynamic of pesticide concentrations. This modification requires a proper evaluation on an independent dataset. Finally, WATPPASS is a compromise between complexity and easiness of use that makes it suited for cropping system assessment in complex pedological and geological environment.
NASA Astrophysics Data System (ADS)
Lafaysse, M.; Hingray, B.; Etchevers, P.; Martin, E.; Obled, C.
2011-06-01
SummaryThe SAFRAN-ISBA-MODCOU hydrological model ( Habets et al., 2008) presents severe limitations for alpine catchments. Here we propose possible model adaptations. For the catchment discretization, Relatively Homogeneous Hydrological Units (RHHUs) are used instead of the classical 8 km square grid. They are defined from the dilineation of hydrological subbasins, elevation bands, and aspect classes. Glacierized and non-glacierized areas are also treated separately. In addition, new modules are included in the model for the simulation of glacier melt, and retention of underground water. The improvement resulting from each model modification is analysed for the Upper Durance basin. RHHUs allow the model to better account for the high spatial variability of the hydrological processes (e.g. snow cover). The timing and the intensity of the spring snowmelt floods are significantly improved owing to the representation of water retention by aquifers. Despite the relatively small area covered by glaciers, accounting for glacier melt is necessary for simulating the late summer low flows. The modified model is robust over a long simulation period and it produces a good reproduction of the intra and interannual variability of discharge, which is a necessary condition for its application in a modified climate context.
NASA Astrophysics Data System (ADS)
Muraleedharan, B. V.; Kathirvel, K.; Narasimhan, B.; Nallasamy, N. D.
2014-12-01
Soil Water Assessment Tool (SWAT) is a basin scale, distributed hydrological model commonly used to predict the effect of management decisions on the hydrologic response of watersheds. Hydrologic response is decided by the various components of water balance. In the case of watersheds located in south India as well as in several other tropical countries around the world, paddy is one of the dominant crop controlling the hydrologic response of a watershed. Hence, the suitability of SWAT in replicating the hydrology of paddy fields needs to be verified. Rice paddy fields are subjected to flooding method of irrigation, while the irrigation subroutines in SWAT are developed to simulate crops grown under non flooding conditions. Moreover irrigation is represented well in field scale models, while it is poorly represented within watershed models like SWAT. Reliable simulation of flooding method of irrigation and hydrology of the fields will assist in effective water resources management of rice paddy fields which are one of the major consumers of surface and ground water resources. The current study attempts to modify the irrigation subroutine in SWAT so as to simulate flooded irrigation condition. A field water balance study was conducted on representative fields located within Gadana, a subbasin located in Tamil Nadu (southern part of India) and dominated by rice paddy based irrigation systems. The water balance of irrigated paddy fields simulated with SWAT was compared with the water balance derived by rice paddy based crop growth model named ORYZA. The variation in water levels along with the soil moisture variation predicted by SWAT was evaluated with respect to the estimates derived from ORYZA. The water levels were further validated with field based water balance measurements taken on a daily scale. It was observed that the modified irrigation subroutine was able to simulate irrigation of rice paddy within SWAT in a realistic way compared to the existing method.
NASA Astrophysics Data System (ADS)
Haberlandt, U.; Gerten, D.; Schaphoff, S.; Lucht, W.
Dynamic global vegetation models are developed with the main purpose to describe the spatio-temporal dynamics of vegetation at the global scale. Increasing concern about climate change impacts has put the focus of recent applications on the sim- ulation of the global carbon cycle. Water is a prime driver of biogeochemical and biophysical processes, thus an appropriate representation of the water cycle is crucial for their proper simulation. However, these models usually lack thorough validation of the water balance they produce. Here we present a hydrological validation of the current version of the LPJ (Lund- Potsdam-Jena) model, a dynamic global vegetation model operating at daily time steps. Long-term simulated runoff and evapotranspiration are compared to literature values, results from three global hydrological models, and discharge observations from various macroscale river basins. It was found that the seasonal and spatial patterns of the LPJ-simulated average values correspond well both with the measurements and the results from the stand-alone hy- drological models. However, a general underestimation of runoff occurs, which may be attributable to the low input dynamics of precipitation (equal distribution within a month), to the simulated vegetation pattern (potential vegetation without anthro- pogenic influence), and to some generalizations of the hydrological components in LPJ. Future research will focus on a better representation of the temporal variability of climate forcing, improved description of hydrological processes, and on the consider- ation of anthropogenic land use.
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).
Effects of baseline conditions on the simulated hydrologic response to projected climate change
Koczot, Kathryn M.; Markstrom, Steven L.; Hay, Lauren E.
2011-01-01
Changes in temperature and precipitation projected from five general circulation models, using one late-twentieth-century and three twenty-first-century emission scenarios, were downscaled to three different baseline conditions. Baseline conditions are periods of measured temperature and precipitation data selected to represent twentieth-century climate. The hydrologic effects of the climate projections are evaluated using the Precipitation-Runoff Modeling System (PRMS), which is a watershed hydrology simulation model. The Almanor Catchment in the North Fork of the Feather River basin, California, is used as a case study. Differences and similarities between PRMS simulations of hydrologic components (i.e., snowpack formation and melt, evapotranspiration, and streamflow) are examined, and results indicate that the selection of a specific time period used for baseline conditions has a substantial effect on some, but not all, hydrologic variables. This effect seems to be amplified in hydrologic variables, which accumulate over time, such as soil-moisture content. Results also indicate that uncertainty related to the selection of baseline conditions should be evaluated using a range of different baseline conditions. This is particularly important for studies in basins with highly variable climate, such as the Almanor Catchment.
Dettinger, M.D.; Cayan, D.R.; Meyer, M.K.; Jeton, A.
2004-01-01
Hydrologic responses of river basins in the Sierra Nevada of California to historical and future climate variations and changes are assessed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-yr period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th century until about 1975 when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st century with an attendant +2.5??C warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. The various projected trends in the business-as-usual simulations become readily visible despite realistic simulated natural climatic and hydrologic variability by about 2025. In contrast to these changes that are mostly associated with streamflow timing, long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. A control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995 yields climate and streamflow timing conditions much like the 1980s and 1990s throughout its duration. The availability of continuous climate-change projection outputs and careful design of initial conditions and control experiments, like those utilized here, promise to improve the quality and usability of future climate-change impact assessments.
NASA Astrophysics Data System (ADS)
Dettinger, M. D.; Cayan, D. R.; Cayan, D. R.; Meyer, M. K.
2001-12-01
Sensitivities of river basins in the Sierra Nevada of California to historical and future climate variations and changes are analyzed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-year period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th Century until about 1975, when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st Century with an attendant +2.5ºC warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. In contrast, a control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995, yields climate and streamflow-timing conditions much like the 1980s and 1990s throughout its duration. Long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. The various projected trends in the business-as-usual simulations become readily visible above simulated natural climatic and hydrologic variability by about 2020.
NASA Astrophysics Data System (ADS)
Elag, M.; Goodall, J. L.
2013-12-01
Hydrologic modeling often requires the re-use and integration of models from different disciplines to simulate complex environmental systems. Component-based modeling introduces a flexible approach for integrating physical-based processes across disciplinary boundaries. Several hydrologic-related modeling communities have adopted the component-based approach for simulating complex physical systems by integrating model components across disciplinary boundaries in a workflow. However, it is not always straightforward to create these interdisciplinary models due to the lack of sufficient knowledge about a hydrologic process. This shortcoming is a result of using informal methods for organizing and sharing information about a hydrologic process. A knowledge-based ontology provides such standards and is considered the ideal approach for overcoming this challenge. The aims of this research are to present the methodology used in analyzing the basic hydrologic domain in order to identify hydrologic processes, the ontology itself, and how the proposed ontology is integrated with the Water Resources Component (WRC) ontology. The proposed ontology standardizes the definitions of a hydrologic process, the relationships between hydrologic processes, and their associated scientific equations. The objective of the proposed Hydrologic Process (HP) Ontology is to advance the idea of creating a unified knowledge framework for components' metadata by introducing a domain-level ontology for hydrologic processes. The HP ontology is a step toward an explicit and robust domain knowledge framework that can be evolved through the contribution of domain users. Analysis of the hydrologic domain is accomplished using the Formal Concept Approach (FCA), in which the infiltration process, an important hydrologic process, is examined. Two infiltration methods, the Green-Ampt and Philip's methods, were used to demonstrate the implementation of information in the HP ontology. Furthermore, a SPARQL service is provided for semantic-based querying of the ontology.
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 ...
USDA-ARS?s Scientific Manuscript database
The responses of eco-hydrological systems to anthropogenic and natural disturbances have attracted much attention in recent years. The coupling and simulating feedback between hydrological and ecological components have been realized in several recently developed eco-hydrological models. However, li...
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.
Shiying Tian; Mohamed A. Youssef; R. Wayne Skaggs; Devendra M. Amatya; G.M. Chescheir
2012-01-01
We present a hybrid and stand-level forest ecosystem model, DRAINMOD-FOREST, for simulating the hydrology, carbon (C) and nitrogen (N) dynamics, and tree growth for drained forest lands under common silvicultural practices. The model was developed by linking DRAINMOD, the hydrological model, and DRAINMOD-N II, the soil C and N dynamics model, to a forest growth model,...
Guse, Björn; Kail, Jochem; Radinger, Johannes; Schröder, Maria; Kiesel, Jens; Hering, Daniel; Wolter, Christian; Fohrer, Nicola
2015-11-15
Climate and land use changes affect the hydro- and biosphere at different spatial scales. These changes alter hydrological processes at the catchment scale, which impact hydrodynamics and habitat conditions for biota at the river reach scale. In order to investigate the impact of large-scale changes on biota, a cascade of models at different scales is required. Using scenario simulations, the impact of climate and land use change can be compared along the model cascade. Such a cascade of consecutively coupled models was applied in this study. Discharge and water quality are predicted with a hydrological model at the catchment scale. The hydraulic flow conditions are predicted by hydrodynamic models. The habitat suitability under these hydraulic and water quality conditions is assessed based on habitat models for fish and macroinvertebrates. This modelling cascade was applied to predict and compare the impacts of climate- and land use changes at different scales to finally assess their effects on fish and macroinvertebrates. Model simulations revealed that magnitude and direction of change differed along the modelling cascade. Whilst the hydrological model predicted a relevant decrease of discharge due to climate change, the hydraulic conditions changed less. Generally, the habitat suitability for fish decreased but this was strongly species-specific and suitability even increased for some species. In contrast to climate change, the effect of land use change on discharge was negligible. However, land use change had a stronger impact on the modelled nitrate concentrations affecting the abundances of macroinvertebrates. The scenario simulations for the two organism groups illustrated that direction and intensity of changes in habitat suitability are highly species-dependent. Thus, a joined model analysis of different organism groups combined with the results of hydrological and hydrodynamic models is recommended to assess the impact of climate and land use changes on river ecosystems. Copyright © 2015 Elsevier B.V. All rights reserved.
Explicit modeling of groundwater-surface water interactions using a simple bucket-type model
NASA Astrophysics Data System (ADS)
Staudinger, Maria; Carlier, Claire; Brunner, Philip; Seibert, Jan
2017-04-01
Longer dry spells can become critical for water supply and groundwater dependent ecosystems. During these dry spells groundwater is often the most relevant source for streams. Hence, the hydrological behavior of a catchment is often dominated by groundwater surface water interactions, which can vary considerably in space and time. While classical hydrological approaches hardly consider this spatial dependence, quantitative, hydrogeological modeling approaches can couple surface runoff processes and groundwater processes. Hydrogeological modeling can help to gain an improved understanding of catchment processes during low flow. However, due to their complex parametrization and large computational requirements, such hydrogeological models are difficult to employ at catchment scale, particularly for a larger set of catchments. Then bucket-type hydrological models remain a practical alternative. In this study we combine the strengths of both the hydrogeological and bucket-type hydrological models to better understand low flow processes and ultimately to use this knowledge for low flow projections. Bucket-type hydrological models have traditionally not been developed with focus on the simulation of low flow. One consequence is that interactions between surface and groundwater are not explicitly considered. Water fluxes in bucket-type hydrological models are commonly simulated only in one direction, namely from the groundwater to the stream but not from the stream to the groundwater. This latter flux, however, can become more important during low flow situations. We therefore further developed the bucket-type hydrological model HBV to simulate low flow situations by allowing for exchange in both directions i.e. also from the stream to the groundwater. The additional HBV exchange box is developed by using a variety of synthetic hydrogeological models as training set that were generated using a fully coupled, physically based hydrogeological model. In this way processes that occur in different spatial settings within the catchment are translated to functional relationships and effective parameter values for the conceptual exchange box can be extracted. Here, we show the development and evaluation of the HBV exchange box. We further show a first application in real catchments and evaluate the model performance by comparing the simulations to benchmark models that do not consider groundwater surface water interaction.
NASA Astrophysics Data System (ADS)
Wi, S.; Freeman, S.; Brown, C.
2017-12-01
This study presents a general approach to developing computational models of human-hydrologic systems where human modification of hydrologic surface processes are significant or dominant. A river basin system is represented by a network of human-hydrologic response units (HHRUs) identified based on locations where river regulations happen (e.g., reservoir operation and diversions). Natural and human processes in HHRUs are simulated in a holistic framework that integrates component models representing rainfall-runoff, river routing, reservoir operation, flow diversion and water use processes. We illustrate the approach in a case study of the Cutzamala water system (CWS) in Mexico, a complex inter-basin water transfer system supplying the Mexico City Metropolitan Area (MCMA). The human-hydrologic system model for CWS (CUTZSIM) is evaluated in terms of streamflow and reservoir storages measured across the CWS and to water supplied for MCMA. The CUTZSIM improves the representation of hydrology and river-operation interaction and, in so doing, advances evaluation of system-wide water management consequences under altered climatic and demand regimes. The integrated modeling framework enables evaluation and simulation of model errors throughout the river basin, including errors in representation of the human component processes. Heretofore, model error evaluation, predictive error intervals and the resultant improved understanding have been limited to hydrologic processes. The general framework represents an initial step towards fuller understanding and prediction of the many and varied processes that determine the hydrologic fluxes and state variables in real river basins.
Coupling Cellular Automata Land Use Change with Distributed Hydrologic Models
NASA Astrophysics Data System (ADS)
Shu, L.; Duffy, C.
2017-12-01
There has been extensive research on LUC modeling with broad applications to simulating urban growth and changing demographic patterns across multiple scales. The importance of land conversion is a critical issue in watershed scale studies and is generally not treated in most watershed modeling approaches. In this study we apply spatially explicit hydrologic and landuse change models and the Conestoga Watershed in Lancaster County, Pennsylvania. The Penn State Integrated Hydrologic Model (PIHM) partitions the water balance in space and time over the urban catchment, the coupled Cellular Automata Land Use Change model (CALUC) dynamically simulates the evolution of land use classes based on physical measures associated with population change and land use demand factors. The CALUC model is based on iteratively applying discrete rules to each individual spatial cell. The essence the CA modeling involves calculation of the Transition Potential (TP) for conversion of a grid cell from one land use class to another. This potential includes five factors: random perturbation, suitability, accessibility, neighborhood effect, inertia effects and zonal factors. In spite of simplicity, this CALUC model has been shown to be very effective for simulating LUC leading to the emergence of complex spatial patterns. The components of TP are derived from present land use data for landuse reanalysis and for realistic future land use scenarios. For the CALUC we use early-settlement (circa 1790) initial land class values and final or present-day (2010) land classes to calibrate the model. CALUC- PIHM dynamically simulates the hydrologic response of conversion from pre-settlement to present landuse. The simulations highlight the capability and value of dynamic coupling of catchment hydrology with land use change over long time periods. Analysis of the simulation uses various metrics such as the distributed water balance, flow duration curves, etc. to show how deforestation, urbanization and agricultural land development interact for the period 1790- present.
Simulated discharge trends indicate robustness of hydrological models in a changing climate
NASA Astrophysics Data System (ADS)
Addor, Nans; Nikolova, Silviya; Seibert, Jan
2016-04-01
Assessing the robustness of hydrological models under contrasted climatic conditions should be part any hydrological model evaluation. Robust models are particularly important for climate impact studies, as models performing well under current conditions are not necessarily capable of correctly simulating hydrological perturbations caused by climate change. A pressing issue is the usually assumed stationarity of parameter values over time. Modeling experiments using conceptual hydrological models revealed that assuming transposability of parameters values in changing climatic conditions can lead to significant biases in discharge simulations. This raises the question whether parameter values should to be modified over time to reflect changes in hydrological processes induced by climate change. Such a question denotes a focus on the contribution of internal processes (i.e., catchment processes) to discharge generation. Here we adopt a different perspective and explore the contribution of external forcing (i.e., changes in precipitation and temperature) to changes in discharge. We argue that in a robust hydrological model, discharge variability should be induced by changes in the boundary conditions, and not by changes in parameter values. In this study, we explore how well the conceptual hydrological model HBV captures transient changes in hydrological signatures over the period 1970-2009. Our analysis focuses on research catchments in Switzerland undisturbed by human activities. The precipitation and temperature forcing are extracted from recently released 2km gridded data sets. We use a genetic algorithm to calibrate HBV for the whole 40-year period and for the eight successive 5-year periods to assess eventual trends in parameter values. Model calibration is run multiple times to account for parameter uncertainty. We find that in alpine catchments showing a significant increase of winter discharge, this trend can be captured reasonably well with constant parameter values over the whole reference period. Further, preliminary results suggest that some trends in parameter values do not reflect changes in hydrological processes, as reported by others previously, but instead might stem from a modeling artifact related to the parameterization of evapotranspiration, which is overly sensitive to temperature increase. We adopt a trading-space-for-time approach to better understand whether robust relationships between parameter values and forcing can be established, and to critically explore the rationale behind time-dependent parameter values in conceptual hydrological models.
Development of a Coupled Hydrological/Sediment Yield Model for a Watershed at Regional Level
NASA Technical Reports Server (NTRS)
Rajbhandaril, Narayan; Crosson, William; Tsegaye, Teferi; Coleman, Tommy; Liu, Yaping; Soman, Vishwas
1998-01-01
Development of a hydrologic model for the study of environmental conservation requires a comprehensive understanding of individual-storm affecting hydrologic and sedimentologic processes. The hydrologic models that we are currently coupling are the Simulator for Hydrology and Energy Exchange at the Land Surface (SHEELS) and the Distributed Runoff Model (DRUM). SHEELS runs continuously to estimate surface energy fluxes and sub-surface soil water fluxes, while DRUM operates during and following precipitation events to predict surface runoff and peak flow through channel routing. The lateral re-distribution of surface water determined by DRUM is passed to SHEELS, which then adjusts soil water contents throughout the profile. The model SHEELS is well documented in Smith et al. (1993) and Laymen and Crosson (1995). The model DRUM is well documented in Vieux et al. (1990) and Vieux and Gauer (1994). The coupled hydrologic model, SHEELS/DRUM, does not simulate sedimentologic processes. The simulation of the sedimentologic process is important for environmental conservation planning and management. Therefore, we attempted to develop a conceptual frame work for coupling a sediment yield model with SHEELS/DRUM to estimate individual-storm sediment yield from a watershed at a regional level. The sediment yield model that will be used for this study is the Universal Soil Loss Equation (USLE) with some modifications to enable the model to predict individual-storm sediment yield. The predicted sediment yield does not include wind erosion and erosion caused by irrigation and snow melt. Units used for this study are those given by Foster et al. (1981) for SI units.
NASA Astrophysics Data System (ADS)
Lafaysse, Matthieu; Hingray, Benoit
2010-05-01
The impact of global change on water resources is expected to be especially pronounced in mountainous areas. Future hydrological scenarios required for impact studies are classically simulated with hydrological models from future meteorological scenarios based on GCMs outputs. Future hydrological regimes of French rivers were estimated following this methodology by Boé et al. (2009) with the physical-based hydrological model SAFRAN-ISBA-MODCOU (SIM), developed by Météo-France. Scenarios obtained for the Alps seem however not very reliable due to the poor performance achieved by the model for the present climate over this region. This work presents possible improvements of SIM for a more relevant simulation of alpine catchments hydrological behavior. Results obtained for the upper Durance catchment (3580 km2) are given for illustration. This catchment is located in Southern French Alps. Its outlet is the Serre-Ponçon lake, a large dam operated for hydropower production, with a key role for water supply in southeastern France. With altitudes ranging from 700 to 4100 meters, the catchment presents highly seasonal flows: minimum and maximum discharges are observed in winter and spring respectively due to snow accumulation and melt, low flows are sustained by glacier melt in late summer (39 km2 are covered by glaciers), major floods can be observed in fall due to large liquid precipitation amounts. Two main limitations of SIM were identified for this catchment. First the 8km-side grid discretization gives a bad representation of the spatial variability of hydrological processes induced by elevation and orientation. Then, low flows are not well represented because the model doesn't include deep storage in aquifers nor ice melt from glaciers. We modified SIM accordingly. For the first point, we applied a discretization based on topography : we divided the catchment in 9 sub-catchments and further 300 meters elevation bands. The vertical variability of meteorological inputs and vegetation cover could be thus better accounted for. Then, each elevation band is divided in 7 exposure classes, in order to represent the influence on snow cover of the solar radiation spatial variability . This discretisation results in 539 Hydrological Units where hydrological processes are assumed to be homogeneous. For the second point, we first included the possibility for glacier melt in previous discretization. We next added a conceptual non-linear underground reservoir in order to simulate water retention by aquifers. These adaptations lead to a clear improvement of simulations for all the hydrometric stations. Daily simulated discharges fit well with measurements (Nash score = 0.8). The model has a good ability to simulate interannual variability and it is robust under a long simulation period (1959-2006). This encourages us to use it in a modified climate context. We studied the effect of each model improvement with a set of sensitivity tests. Accounting for elevation bands allows simulating more persistent snow cover at high altitudes, contributing later to river flows. Adding underground storage leads to delay the snowmelt runoff transfer in river. The exposure influence is not so sensitive for discharges simulation, but it gives a more accurate description of the spatial variability of snow cover. Although glaciered areas are very small compared to total basin area, a better simulation of summer low flows is obtained including a glacier melt module. Despite previous improvements, winter low flows are still slightly underestimated. As suggested by a simple sensitivity analysis, this could be partly due to the fact that the model doesn't correctly simulate basal snowmelt by ground heat flow.
J. X. Zhang; J. Q. Wu; K. Chang; W. J. Elliot; S. Dun
2009-01-01
The recent modification of the Water Erosion Prediction Project (WEPP) model has improved its applicability to hydrology and erosion modeling in forest watersheds. To generate reliable topographic and hydrologic inputs for the WEPP model, carefully selecting digital elevation models (DEMs) with appropriate resolution and accuracy is essential because topography is a...
Modelling hydrologic and hydrodynamic processes in basins with large semi-arid wetlands
NASA Astrophysics Data System (ADS)
Fleischmann, Ayan; Siqueira, Vinícius; Paris, Adrien; Collischonn, Walter; Paiva, Rodrigo; Pontes, Paulo; Crétaux, Jean-François; Bergé-Nguyen, Muriel; Biancamaria, Sylvain; Gosset, Marielle; Calmant, Stephane; Tanimoun, Bachir
2018-06-01
Hydrological and hydrodynamic models are core tools for simulation of large basins and complex river systems associated to wetlands. Recent studies have pointed towards the importance of online coupling strategies, representing feedbacks between floodplain inundation and vertical hydrology. Especially across semi-arid regions, soil-floodplain interactions can be strong. In this study, we included a two-way coupling scheme in a large scale hydrological-hydrodynamic model (MGB) and tested different model structures, in order to assess which processes are important to be simulated in large semi-arid wetlands and how these processes interact with water budget components. To demonstrate benefits from this coupling over a validation case, the model was applied to the Upper Niger River basin encompassing the Niger Inner Delta, a vast semi-arid wetland in the Sahel Desert. Simulation was carried out from 1999 to 2014 with daily TMPA 3B42 precipitation as forcing, using both in-situ and remotely sensed data for calibration and validation. Model outputs were in good agreement with discharge and water levels at stations both upstream and downstream of the Inner Delta (Nash-Sutcliffe Efficiency (NSE) >0.6 for most gauges), as well as for flooded areas within the Delta region (NSE = 0.6; r = 0.85). Model estimates of annual water losses across the Delta varied between 20.1 and 30.6 km3/yr, while annual evapotranspiration ranged between 760 mm/yr and 1130 mm/yr. Evaluation of model structure indicated that representation of both floodplain channels hydrodynamics (storage, bifurcations, lateral connections) and vertical hydrological processes (floodplain water infiltration into soil column; evapotranspiration from soil and vegetation and evaporation of open water) are necessary to correctly simulate flood wave attenuation and evapotranspiration along the basin. Two-way coupled models are necessary to better understand processes in large semi-arid wetlands. Finally, such coupled hydrologic and hydrodynamic modelling proves to be an important tool for integrated evaluation of hydrological processes in such poorly gauged, large scale basins. We hope that this model application provides new ways forward for large scale model development in such systems, involving semi-arid regions and complex floodplains.
NASA Astrophysics Data System (ADS)
Kao, S. C.; Shi, X.; Kumar, J.; Ricciuto, D. M.; Mao, J.; Thornton, P. E.
2017-12-01
With the concern of changing hydrologic regime, there is a crucial need to better understand how water availability may change and influence water management decisions in the projected future climate conditions. Despite that surface hydrology has long been simulated by land model within the Earth System modeling (ESM) framework, given the coarser horizontal resolution and lack of engineering-level calibration, raw runoff from ESM is generally discarded by water resource managers when conducting hydro-climate impact assessments. To identify a likely path to improve the credibility of ESM-simulated natural runoff, we conducted regional model simulation using the land component (ALM) of the Accelerated Climate Modeling for Energy (ACME) version 1 focusing on the conterminous United States (CONUS). Two very different forcing data sets, including (1) the conventional 0.5° CRUNCEP (v5, 1901-2013) and (2) the 1-km Daymet (v3, 1980-2013) aggregated to 0.5°, were used to conduct 20th century transient simulation with satellite phenology. Additional meteorologic and hydrologic observations, including PRISM precipitation and U.S. Geological Survey WaterWatch runoff, were used for model evaluation. For various CONUS hydrologic regions (such as Pacific Northwest), we found that Daymet can significantly improve the reasonableness of simulated ALM runoff even without intensive calibration. The large dry bias of CRUNCEP precipitation (evaluated by PRISM) in multiple CONUS hydrologic regions is believed to be the main reason causing runoff underestimation. The results suggest that when driving with skillful precipitation estimates, ESM has the ability to produce reasonable natural runoff estimates to support further water management studies. Nevertheless, model calibration will be required for regions (such as Upper Colorado) where ill performance is showed for multiple different forcings.
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.
Westerman, Drew A.; Clark, Brian R.
2013-01-01
The results from the precipitation-runoff hydrologic model, the one-dimensional unsteady-state hydraulic model, and a separate two-dimensional model developed as part of a coincident study, each complement the other in terms of streamflow timing, water-surface elevations, and velocities propagated by the June 11, 2010, flood event. The simulated grids for water depth and stream velocity from each model were directly compared by subtracting the one-dimensional hydraulic model grid from the two-dimensional model grid. The absolute mean difference for the simulated water depth was 0.9 foot. Additionally, the absolute mean difference for the simulated stream velocity was 1.9 feet per second.
NASA Astrophysics Data System (ADS)
Graham, L. Phil; Andersson, Lotta; Horan, Mark; Kunz, Richard; Lumsden, Trevor; Schulze, Roland; Warburton, Michele; Wilk, Julie; Yang, Wei
This study used climate change projections from different regional approaches to assess hydrological effects on the Thukela River Basin in KwaZulu-Natal, South Africa. Projecting impacts of future climate change onto hydrological systems can be undertaken in different ways and a variety of effects can be expected. Although simulation results from global climate models (GCMs) are typically used to project future climate, different outcomes from these projections may be obtained depending on the GCMs themselves and how they are applied, including different ways of downscaling from global to regional scales. Projections of climate change from different downscaling methods, different global climate models and different future emissions scenarios were used as input to simulations in a hydrological model to assess climate change impacts on hydrology. A total of 10 hydrological change simulations were made, resulting in a matrix of hydrological response results. This matrix included results from dynamically downscaled climate change projections from the same regional climate model (RCM) using an ensemble of three GCMs and three global emissions scenarios, and from statistically downscaled projections using results from five GCMs with the same emissions scenario. Although the matrix of results does not provide complete and consistent coverage of potential uncertainties from the different methods, some robust results were identified. In some regards, the results were in agreement and consistent for the different simulations. For others, particularly rainfall, the simulations showed divergence. For example, all of the statistically downscaled simulations showed an annual increase in precipitation and corresponding increase in river runoff, while the RCM downscaled simulations showed both increases and decreases in runoff. According to the two projections that best represent runoff for the observed climate, increased runoff would generally be expected for this basin in the future. Dealing with such variability in results is not atypical for assessing climate change impacts in Africa and practitioners are faced with how to interpret them. This work highlights the need for additional, well-coordinated regional climate downscaling for the region to further define the range of uncertainties involved.
Impacts of climate change and internal climate variability on french rivers streamflows
NASA Astrophysics Data System (ADS)
Dayon, Gildas; Boé, Julien; Martin, Eric
2016-04-01
The assessment of the impacts of climate change often requires to set up long chains of modeling, from the model to estimate the future concentration of greenhouse gases to the impact model. Throughout the modeling chain, sources of uncertainty accumulate making the exploitation of results for the development of adaptation strategies difficult. It is proposed here to assess the impacts of climate change on the hydrological cycle over France and the associated uncertainties. The contribution of the uncertainties from greenhouse gases emission scenario, climate models and internal variability are addressed in this work. To have a large ensemble of climate simulations, the study is based on Global Climate Models (GCM) simulations from the Coupled Model Intercomparison Phase 5 (CMIP5), including several simulations from the same GCM to properly assess uncertainties from internal climate variability. Simulations from the four Radiative Concentration Pathway (RCP) are downscaled with a statistical method developed in a previous study (Dayon et al. 2015). The hydrological system Isba-Modcou is then driven by the downscaling results on a 8 km grid over France. Isba is a land surface model that calculates the energy and water balance and Modcou a hydrogeological model that routes the surface runoff given by Isba. Based on that framework, uncertainties uncertainties from greenhouse gases emission scenario, climate models and climate internal variability are evaluated. Their relative importance is described for the next decades and the end of this century. In a last part, uncertainties due to internal climate variability on streamflows simulated with downscaled GCM and Isba-Modcou are evaluated against observations and hydrological reconstructions on the whole 20th century. Hydrological reconstructions are based on the downscaling of recent atmospheric reanalyses of the 20th century and observations of temperature and precipitation. We show that the multi-decadal variability of streamflows observed in the 20th century is generally weaker in the hydrological simulations done with the historical simulations from climate models. References: Dayon et al. (2015), Transferability in the future climate of a statistical downscaling mehtod for precipitation in France, J. Geophys. Res. Atmos., 120, 1023-1043, doi:10.1002/2014JD022236
NASA Astrophysics Data System (ADS)
Ou, G.; Nijssen, B.; Nearing, G. S.; Newman, A. J.; Mizukami, N.; Clark, M. P.
2016-12-01
The Structure for Unifying Multiple Modeling Alternatives (SUMMA) provides a unifying modeling framework for process-based hydrologic modeling by defining a general set of conservation equations for mass and energy, with the capability to incorporate multiple choices for spatial discretizations and flux parameterizations. In this study, we provide a first demonstration of large-scale hydrologic simulations using SUMMA through an application to the Columbia River Basin (CRB) in the northwestern United States and Canada for a multi-decadal simulation period. The CRB is discretized into 11,723 hydrologic response units (HRUs) according to the United States Geologic Service Geospatial Fabric. The soil parameters are derived from the Natural Resources Conservation Service Soil Survey Geographic (SSURGO) Database. The land cover parameters are based on the National Land Cover Database from the year 2001 created by the Multi-Resolution Land Characteristics (MRLC) Consortium. The forcing data, including hourly air pressure, temperature, specific humidity, wind speed, precipitation, shortwave and longwave radiations, are based on Phase 2 of the North American Land Data Assimilation System (NLDAS-2) and averaged for each HRU. The simulation results are compared to simulations with the Variable Infiltration Capacity (VIC) model and the Precipitation Runoff Modeling System (PRMS). We are particularly interested in SUMMA's capability to mimic model behaviors of the other two models through the selection of appropriate model parameterizations in SUMMA.
USDA-ARS?s Scientific Manuscript database
Rangeland managers and scientists are in need of predictive tools to accurately simulate post-fire hydrologic responses and provide hydrologic risk assessment. Rangeland hydrologic modeling has advanced in recent years; however, model advancements have largely been associated with data from gently ...
An ecohydrologic model for a shallow groundwater urban environment.
Arden, Sam; Ma, Xin Cissy; Brown, Mark
2014-01-01
The urban environment is a patchwork of natural and artificial surfaces that results in complex interactions with and impacts to natural hydrologic cycles. Evapotranspiration is a major hydrologic flow that is often altered through urbanization, although the mechanisms of change are sometimes difficult to tease out due to difficulty in effectively simulating soil-plant-atmosphere interactions. This paper introduces a simplified yet realistic model that is a combination of existing surface runoff and ecohydrology models designed to increase the quantitative understanding of complex urban hydrologic processes. Results demonstrate that the model is capable of simulating the long-term variability of major hydrologic fluxes as a function of impervious surface, temperature, water table elevation, canopy interception, soil characteristics, precipitation and complex mechanisms of plant water uptake. These understandings have potential implications for holistic urban water system management.
Strategies for Large Scale Implementation of a Multiscale, Multiprocess Integrated Hydrologic Model
NASA Astrophysics Data System (ADS)
Kumar, M.; Duffy, C.
2006-05-01
Distributed models simulate hydrologic state variables in space and time while taking into account the heterogeneities in terrain, surface, subsurface properties and meteorological forcings. Computational cost and complexity associated with these model increases with its tendency to accurately simulate the large number of interacting physical processes at fine spatio-temporal resolution in a large basin. A hydrologic model run on a coarse spatial discretization of the watershed with limited number of physical processes needs lesser computational load. But this negatively affects the accuracy of model results and restricts physical realization of the problem. So it is imperative to have an integrated modeling strategy (a) which can be universally applied at various scales in order to study the tradeoffs between computational complexity (determined by spatio- temporal resolution), accuracy and predictive uncertainty in relation to various approximations of physical processes (b) which can be applied at adaptively different spatial scales in the same domain by taking into account the local heterogeneity of topography and hydrogeologic variables c) which is flexible enough to incorporate different number and approximation of process equations depending on model purpose and computational constraint. An efficient implementation of this strategy becomes all the more important for Great Salt Lake river basin which is relatively large (~89000 sq. km) and complex in terms of hydrologic and geomorphic conditions. Also the types and the time scales of hydrologic processes which are dominant in different parts of basin are different. Part of snow melt runoff generated in the Uinta Mountains infiltrates and contributes as base flow to the Great Salt Lake over a time scale of decades to centuries. The adaptive strategy helps capture the steep topographic and climatic gradient along the Wasatch front. Here we present the aforesaid modeling strategy along with an associated hydrologic modeling framework which facilitates a seamless, computationally efficient and accurate integration of the process model with the data model. The flexibility of this framework leads to implementation of multiscale, multiresolution, adaptive refinement/de-refinement and nested modeling simulations with least computational burden. However, performing these simulations and related calibration of these models over a large basin at higher spatio- temporal resolutions is computationally intensive and requires use of increasing computing power. With the advent of parallel processing architectures, high computing performance can be achieved by parallelization of existing serial integrated-hydrologic-model code. This translates to running the same model simulation on a network of large number of processors thereby reducing the time needed to obtain solution. The paper also discusses the implementation of the integrated model on parallel processors. Also will be discussed the mapping of the problem on multi-processor environment, method to incorporate coupling between hydrologic processes using interprocessor communication models, model data structure and parallel numerical algorithms to obtain high performance.
A physically-based Distributed Hydrologic Model for Tropical Catchments
NASA Astrophysics Data System (ADS)
Abebe, N. A.; Ogden, F. L.
2010-12-01
Hydrological models are mathematical formulations intended to represent observed hydrological processes in a watershed. Simulated watersheds in turn vary in their nature based on their geographic location, altitude, climatic variables and geology and soil formation. Due to these variations, available hydrologic models vary in process formulation, spatial and temporal resolution and data demand. Many tropical watersheds are characterized by extensive and persistent biological activity and a large amount of rain. The Agua Salud catchments located within the Panama Canal Watershed, Panama, are such catchments identified by steep rolling topography, deep soils derived from weathered bedrock, and limited exposed bedrock. Tropical soils are highly affected by soil cracks, decayed tree roots and earthworm burrows forming a network of preferential flow paths that drain to a perched water table, which forms at a depth where the vertical hydraulic conductivity is significantly reduced near the bottom of the bioturbation layer. We have developed a physics-based, spatially distributed, multi-layered hydrologic model to simulate the dominant processes in these tropical watersheds. The model incorporates the major flow processes including overland flow, channel flow, matrix and non-Richards film flow infiltration, lateral downslope saturated matrix and non-Darcian pipe flow in the bioturbation layer, and deep saturated groundwater flow. Emphasis is given to the modeling of subsurface unsaturated zone soil moisture dynamics and the saturated preferential lateral flow from the network of macrospores. Preliminary results indicate that the model has the capability to simulate the complex hydrological processes in the catchment and will be a useful tool in the ongoing comprehensive ecohydrological studies in tropical catchments, and help improve our understanding of the hydrological effects of deforestation and aforestation.
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.
Step wise, multiple objective calibration of a hydrologic model for a snowmelt dominated basin
Hay, L.E.; Leavesley, G.H.; Clark, M.P.; Markstrom, S.L.; Viger, R.J.; Umemoto, M.
2006-01-01
The ability to apply a hydrologic model to large numbers of basins for forecasting purposes requires a quick and effective calibration strategy. This paper presents a step wise, multiple objective, automated procedure for hydrologic model calibration. This procedure includes the sequential calibration of a model's simulation of solar radiation (SR), potential evapotranspiration (PET), water balance, and daily runoff. The procedure uses the Shuffled Complex Evolution global search algorithm to calibrate the U.S. Geological Survey's Precipitation Runoff Modeling System in the Yampa River basin of Colorado. This process assures that intermediate states of the model (SR and PET on a monthly mean basis), as well as the water balance and components of the daily hydrograph are simulated, consistently with measured values.
Global change and terrestrial hydrology - A review
NASA Technical Reports Server (NTRS)
Dickinson, Robert E.
1991-01-01
This paper reviews the role of terrestrial hydrology in determining the coupling between the surface and atmosphere. Present experience with interactive numerical simulation is discussed and approaches to the inclusion of land hydrology in global climate models ae considered. At present, a wide range of answers as to expected changes in surface hydrology is given by nominally similar models. Studies of the effects of tropical deforestation and global warming illustrate this point.
NASA Astrophysics Data System (ADS)
Noh, S. J.; Tachikawa, Y.; Shiiba, M.; Yorozu, K.; Kim, S.
2012-04-01
Data assimilation methods have received increased attention to accomplish uncertainty assessment and enhancement of forecasting capability in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modeling software are based on a deterministic approach. In this study, we developed a hydrological modeling framework for sequential data assimilation, so called MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modeling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. Sequential data assimilation based on the particle filters is available for any hydrologic models based on MPI-OHyMoS considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process 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. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for short-term streamflow forecasting of several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and remotely-sensed rainfall data such as X-band or C-band radar is estimated and mitigated in the sequential data assimilation.
Ebel, B.A.; Mirus, B.B.; Heppner, C.S.; VanderKwaak, J.E.; Loague, K.
2009-01-01
Distributed hydrologic models capable of simulating fully-coupled surface water and groundwater flow are increasingly used to examine problems in the hydrologic sciences. Several techniques are currently available to couple the surface and subsurface; the two most frequently employed approaches are first-order exchange coefficients (a.k.a., the surface conductance method) and enforced continuity of pressure and flux at the surface-subsurface boundary condition. The effort reported here examines the parameter sensitivity of simulated hydrologic response for the first-order exchange coefficients at a well-characterized field site using the fully coupled Integrated Hydrology Model (InHM). This investigation demonstrates that the first-order exchange coefficients can be selected such that the simulated hydrologic response is insensitive to the parameter choice, while simulation time is considerably reduced. Alternatively, the ability to choose a first-order exchange coefficient that intentionally decouples the surface and subsurface facilitates concept-development simulations to examine real-world situations where the surface-subsurface exchange is impaired. While the parameters comprising the first-order exchange coefficient cannot be directly estimated or measured, the insensitivity of the simulated flow system to these parameters (when chosen appropriately) combined with the ability to mimic actual physical processes suggests that the first-order exchange coefficient approach can be consistent with a physics-based framework. Copyright ?? 2009 John Wiley & Sons, Ltd.
A generalized methodology for identification of threshold for HRU delineation in SWAT model
NASA Astrophysics Data System (ADS)
M, J.; Sudheer, K.; Chaubey, I.; Raj, C.
2016-12-01
The distributed hydrological model, Soil and Water Assessment Tool (SWAT) is a comprehensive hydrologic model widely used for making various decisions. The simulation accuracy of the distributed hydrological model differs due to the mechanism involved in the subdivision of the watershed. Soil and Water Assessment Tool (SWAT) considers sub-dividing the watershed and the sub-basins into small computing units known as 'hydrologic response units (HRU). The delineation of HRU is done based on unique combinations of land use, soil types, and slope within the sub-watersheds, which are not spatially defined. The computations in SWAT are done at HRU level and are then aggregated up to the sub-basin outlet, which is routed through the stream system. Generally, the HRUs are delineated by considering a threshold percentage of land use, soil and slope are to be given by the modeler to decrease the computation time of the model. The thresholds constrain the minimum area for constructing an HRU. In the current HRU delineation practice in SWAT, the land use, soil and slope of the watershed within a sub-basin, which is less than the predefined threshold, will be surpassed by the dominating land use, soil and slope, and introduce some level of ambiguity in the process simulations in terms of inappropriate representation of the area. But the loss of information due to variation in the threshold values depends highly on the purpose of the study. Therefore this research studies the effects of threshold values of HRU delineation on the hydrological modeling of SWAT on sediment simulations and suggests guidelines for selecting the appropriate threshold values considering the sediment simulation accuracy. The preliminary study was done on Illinois watershed by assigning different thresholds for land use and soil. A general methodology was proposed for identifying an appropriate threshold for HRU delineation in SWAT model that considered computational time and accuracy of the simulation. The methodology can be adopted for identifying an appropriate threshold for SWAT model simulation in any watershed with a single simulation of the model with a zero-zero threshold.
Representing northern peatland microtopography and hydrology within the Community Land Model
Shi, Xiaoying; Thornton, Peter E.; Ricciuto, Daniel M.; ...
2015-11-12
Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth for a vegetated wetland, independent of prescribed regional water tables. We introduce here a new configuration of the Community Land Model (CLM) which includes a fully prognostic water table calculation for a vegetated peatland. Our structural and process changes to CLM focus on modifications needed to representmore » the hydrologic cycle of bogs environment with perched water tables, as well as distinct hydrologic dynamics and vegetation communities of the raised hummock and sunken hollow microtopography characteristic of peatland bogs. The modified model was parameterized and independently evaluated against observations from an ombrotrophic raised-dome bog in northern Minnesota (S1-Bog), the site for the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE). Simulated water table levels compared well with site-level observations. The new model predicts hydrologic changes in response to planned warming at the SPRUCE site. At present, standing water is commonly observed in bog hollows after large rainfall events during the growing season, but simulations suggest a sharp decrease in water table levels due to increased evapotranspiration under the most extreme warming level, nearly eliminating the occurrence of standing water in the growing season. Simulated soil energy balance was strongly influenced by reduced winter snowpack under warming simulations, with the warming influence on soil temperature partly offset by the loss of insulating snowpack in early and late winter. Furthermore, the new model provides improved predictive capacity for seasonal hydrological dynamics in northern peatlands, and provides a useful foundation for investigation of northern peatland carbon exchange.« less
Representing northern peatland microtopography and hydrology within the Community Land Model
Shi, X.; Thornton, P. E.; Ricciuto, D. M.; ...
2015-02-20
Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth for a vegetated wetland, independent of prescribed regional water tables. We introduce here a new configuration of the Community Land Model (CLM) which includes a fully prognostic water table calculation for a vegetated peatland. Our structural and process changes to CLM focus on modifications needed to representmore » the hydrologic cycle of bogs environment with perched water tables, as well as distinct hydrologic dynamics and vegetation communities of the raised hummock and sunken hollow microtopography characteristic of peatland bogs. The modified model was parameterized and independently evaluated against observations from an ombrotrophic raised-dome bog in northern Minnesota (S1-Bog), the site for the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE). Simulated water table levels compared well with site-level observations. The new model predicts significant hydrologic changes in response to planned warming at the SPRUCE site. At present, standing water is commonly observed in bog hollows after large rainfall events during the growing season, but simulations suggest a sharp decrease in water table levels due to increased evapotranspiration under the most extreme warming level, nearly eliminating the occurrence of standing water in the growing season. Simulated soil energy balance was strongly influenced by reduced winter snowpack under warming simulations, with the warming influence on soil temperature partly offset by the loss of insulating snowpack in early and late winter. The new model provides improved predictive capacity for seasonal hydrological dynamics in northern peatlands, and provides a useful foundation for investigation of northern peatland carbon exchange.« less
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.
NASA Astrophysics Data System (ADS)
Yalew, Seleshi; van der Zaag, Pieter; Mul, Marloes; Uhlenbrook, Stefan; Teferi, Ermias; van Griensven, Ann; van der Kwast, Johannes
2013-04-01
Hydrology of a basin, alongside climate change, is well documented to impact and to be impacted by land use/land cover change processes. The need to understand the impacts of hydrology on land use change and vice- versa cannot be overstated especially in basins such as the Upper Blue Nile in Ethiopia, where the vast majority of farmers depend on rain-fed agriculture. A slight fluctuation in rainy seasons or an increase or decrease in magnitude of precipitation can easily trigger drought or flooding. On the other hand, ever growing population and emerging economic development, among others, is likely to continually alter land use/land cover change, thereby affecting hydrological processes. With the intention of identifying and analyzing interactions and future scenarios of the hydrology and land use/land cover, we carried out a case study on a meso-scale catchment, in the Upper Blue Nile basin. A land use model using SITE (SImulation of Terrestrial Environments) was built for analyzing land use trends from aerial land cover photographs of 1957 and simulate until 2009 based on socio-economic as well as biophysical factors. Major land use drivers in the catchment were identified and used as input to the land use model. Separate land use maps were produced using Landsat images of 1972, 1986, 1994 and 2009 for historical calibration of the land use model. By the same token, a hydrological model for the same catchment was built using the SWAT (Soil and Water Assessment Tool) model. After calibration of the two independent models, they were loosely coupled for analyzing the changes in either of the models and impacts on the other. Among other details, the coupled model performed better in identifying limiting factors from both the hydrology as well as from the land use perspectives. For instance, the simulation of the uncoupled land use model alone (without inputs from SWAT on the water budget of each land use parcel) continually considered a land use type such as a wet land/marsh land, simply as a wetland until the simulation period finishes. The wetland or the marsh land, which is not crop friendly in the location, does not get allocated to any other land use such as for certain crop types or settlement, because the land use model cannot tell how much water is added to or drained from each parcel every season. However, the simulation feedback from the coupled hydrological model shows that certain wetland/marsh land parcels, in fact, hold less and less water or even dry up during the simulation period, thereby putting themselves as a good candidate to be picked by the land use model in a next time step and to be allocated to other land use types. The same way, a measure in the land use aspect, which considers socio-economic as well as biophysical driving forces of in the catchment, shows changes in runoff and sedimentation levels in SWAT model outputs. The results of a future scenario considering the continuing population growth projects that about 35% of the wetland dries up and gets converted to cultivation by 2020. This study emphasizes the importance of identifying possible impacts of the future hydrology on other components of the socio-environmental systems and contrariwise during environmental decision making, especially in areas where a relatively small change may have large impacts (such flood and/or drought prone basins as the Nile). The study also demonstrates a sound methodology for assessing the impact of land use change on hydrology and vice-versa by dynamically exchanging data through feedback mechanisms (coupling socio-environmental and hydrological models) which lead to a better understanding of socio-environmental problems. Keywords: Coupling, socio-environment, Nile, land use models, hydrological models
NASA Astrophysics Data System (ADS)
Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.
2018-05-01
Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed hydrology. However, a thorough validation and a comparison with other methods are recommended before using the JBC method, since it may perform worse than the IBC method for some cases due to bias nonstationarity of climate model outputs.
[Review on HSPF model for simulation of hydrology and water quality processes].
Li, Zhao-fu; Liu, Hong-Yu; Li, Yan
2012-07-01
Hydrological Simulation Program-FORTRAN (HSPF), written in FORTRAN, is one ol the best semi-distributed hydrology and water quality models, which was first developed based on the Stanford Watershed Model. Many studies on HSPF model application were conducted. It can represent the contributions of sediment, nutrients, pesticides, conservatives and fecal coliforms from agricultural areas, continuously simulate water quantity and quality processes, as well as the effects of climate change and land use change on water quantity and quality. HSPF consists of three basic application components: PERLND (Pervious Land Segment) IMPLND (Impervious Land Segment), and RCHRES (free-flowing reach or mixed reservoirs). In general, HSPF has extensive application in the modeling of hydrology or water quality processes and the analysis of climate change and land use change. However, it has limited use in China. The main problems with HSPF include: (1) some algorithms and procedures still need to revise, (2) due to the high standard for input data, the accuracy of the model is limited by spatial and attribute data, (3) the model is only applicable for the simulation of well-mixed rivers, reservoirs and one-dimensional water bodies, it must be integrated with other models to solve more complex problems. At present, studies on HSPF model development are still undergoing, such as revision of model platform, extension of model function, method development for model calibration, and analysis of parameter sensitivity. With the accumulation of basic data and imorovement of data sharing, the HSPF model will be applied more extensively in China.
Johnson, M.S.; Coon, W.F.; Mehta, V.K.; Steenhuis, T.S.; Brooks, E.S.; Boll, J.
2003-01-01
Differences in the simulation of hydrologic processes by watershed models directly affect the accuracy of results. Surface runoff generation can be simulated as either: (1) infiltration-excess (or Hortonian) overland flow, or (2) saturation-excess overland flow. This study compared the Hydrological Simulation Program - FORTRAN (HSPF) and the Soil Moisture Routing (SMR) models, each representing one of these mechanisms. These two models were applied to a 102 km2 watershed in the upper part of the Irondequoit Creek basin in central New York State over a seven-year simulation period. The models differed in both the complexity of simulating snowmelt and baseflow processes as well as the detail in which the geographic information was preserved by each model. Despite their differences in structure and representation of hydrologic processes, the two models simulated streamflow with almost equal accuracy. Since streamflow is an integral response and depends mainly on the watershed water balance, this was not unexpected. Model efficiency values for the seven-year simulation period were 0.67 and 0.65 for SMR and HSPF, respectively. HSPF simulated winter streamflow slightly better than SMR as a result of its complex snowmelt routine, whereas SMR simulated summer flows better than HSPF as a result of its runoff and baseflow processes. An important difference between model results was the ability to predict the spatial distribution of soil moisture content. HSPF aggregates soil moisture content, which is generally related to a specific pervious land unit across the entire watershed, whereas SMR predictions of moisture content distribution are geographically specific and matched field observations reasonably well. Important is that the saturated area was predicted well by SMR and confirmed the validity of using saturation-excess mechanisms for this hillslope dominated watershed. ?? 2003 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Tang, G.; Bartlein, P. J.
2012-08-01
Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM) simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i) modify a DGVM for simulating land surface water balances; (ii) evaluate the modified model in simulating actual evapotranspiration (ET), soil moisture, and surface runoff at regional or watershed scales; and (iii) gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH) model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ) DGVM. To evaluate the model we ran LH using historical (1981-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981-2006 (R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficient > 0.52). The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences < 15%) with observed values for these rivers. Compared to a degree-day method for snowmelt computation, the addition of the solar radiation effect on snowmelt enabled LH to better simulate monthly stream flow in winter and early spring for rivers located at mid-to-high latitudes. In addition, LH-modeled monthly soil moisture for the state of Illinois (US) agreed well (R2 = 0.79, p < 0.01) with observed data for the years 1984-2001. Overall, this study justifies both the feasibility of incorporating satellite-based land covers into a DGVM and the reliability of LH to simulate land-surface water balances. To better estimate surface/river runoff at mid-to-high latitudes, we recommended that LPJ-DGVM considers the effects of solar radiation on snowmelt.
Global-Scale Hydrology: Simple Characterization of Complex Simulation
NASA Technical Reports Server (NTRS)
Koster, Randal D.
1999-01-01
Atmospheric general circulation models (AGCMS) are unique and valuable tools for the analysis of large-scale hydrology. AGCM simulations of climate provide tremendous amounts of hydrological data with a spatial and temporal coverage unmatched by observation systems. To the extent that the AGCM behaves realistically, these data can shed light on the nature of the real world's hydrological cycle. In the first part of the seminar, I will describe the hydrological cycle in a typical AGCM, with some emphasis on the validation of simulated precipitation against observations. The second part of the seminar will focus on a key goal in large-scale hydrology studies, namely the identification of simple, overarching controls on hydrological behavior hidden amidst the tremendous amounts of data produced by the highly complex AGCM parameterizations. In particular, I will show that a simple 50-year-old climatological relation (and a recent extension we made to it) successfully predicts, to first order, both the annual mean and the interannual variability of simulated evaporation and runoff fluxes. The seminar will conclude with an example of a practical application of global hydrology studies. The accurate prediction of weather statistics several months in advance would have tremendous societal benefits, and conventional wisdom today points at the use of coupled ocean-atmosphere-land models for such seasonal-to-interannual prediction. Understanding the hydrological cycle in AGCMs is critical to establishing the potential for such prediction. Our own studies show, among other things, that soil moisture retention can lead to significant precipitation predictability in many midlatitude and tropical regions.
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.
NASA Astrophysics Data System (ADS)
Troy, Tara J.; Ines, Amor V. M.; Lall, Upmanu; Robertson, Andrew W.
2013-04-01
Large-scale hydrologic models, such as the Variable Infiltration Capacity (VIC) model, are used for a variety of studies, from drought monitoring to projecting the potential impact of climate change on the hydrologic cycle decades in advance. The majority of these models simulates the natural hydrological cycle and neglects the effects of human activities such as irrigation, which can result in streamflow withdrawals and increased evapotranspiration. In some parts of the world, these activities do not significantly affect the hydrologic cycle, but this is not the case in south Asia where irrigated agriculture has a large water footprint. To address this gap, we incorporate a crop growth model and irrigation model into the VIC model in order to simulate the impacts of irrigated and rainfed agriculture on the hydrologic cycle over south Asia (Indus, Ganges, and Brahmaputra basin and peninsular India). The crop growth model responds to climate signals, including temperature and water stress, to simulate the growth of maize, wheat, rice, and millet. For the primarily rainfed maize crop, the crop growth model shows good correlation with observed All-India yields (0.7) with lower correlations for the irrigated wheat and rice crops (0.4). The difference in correlation is because irrigation provides a buffer against climate conditions, so that rainfed crop growth is more tied to climate than irrigated crop growth. The irrigation water demands induce hydrologic water stress in significant parts of the region, particularly in the Indus, with the streamflow unable to meet the irrigation demands. Although rainfall can vary significantly in south Asia, we find that water scarcity is largely chronic due to the irrigation demands rather than being intermittent due to climate variability.
A fully integrated SWAT-MODFLOW hydrologic model
USDA-ARS?s Scientific Manuscript database
The Soil and Water Assessment Tool (SWAT) and MODFLOW models are being used worldwide for managing surface and groundwater water resources. The SWAT models hydrological processes occurring at the surface including shallow aquifers, while MODFLOW simulate groundwater processes. However, neither SWAT ...
Sams, J. I.; Witt, E. C.
1995-01-01
The Hydrological Simulation Program - Fortran (HSPF) was used to simulate streamflow and sediment transport in two surface-mined basins of Fayette County, Pa. Hydrologic data from the Stony Fork Basin (0.93 square miles) was used to calibrate HSPF parameters. The calibrated parameters were applied to an HSPF model of the Poplar Run Basin (8.83 square miles) to evaluate the transfer value of model parameters. The results of this investigation provide information to the Pennsylvania Department of Environmental Resources, Bureau of Mining and Reclamation, regarding the value of the simulated hydrologic data for use in cumulative hydrologic-impact assessments of surface-mined basins. The calibration period was October 1, 1985, through September 30, 1988 (water years 1986-88). The simulated data were representative of the observed data from the Stony Fork Basin. Mean simulated streamflow was 1.64 cubic feet per second compared to measured streamflow of 1.58 cubic feet per second for the 3-year period. The difference between the observed and simulated peak stormflow ranged from 4.0 to 59.7 percent for 12 storms. The simulated sediment load for the 1987 water year was 127.14 tons (0.21 ton per acre), which compares to a measured sediment load of 147.09 tons (0.25 ton per acre). The total simulated suspended-sediment load for the 3-year period was 538.2 tons (0.30 ton per acre per year), which compares to a measured sediment load of 467.61 tons (0.26 ton per acre per year). The model was verified by comparing observed and simulated data from October 1, 1988, through September 30, 1989. The results obtained were comparable to those from the calibration period. The simulated mean daily discharge was representative of the range of data observed from the basin and of the frequency with which specific discharges were equalled or exceeded. The calibrated and verified parameters from the Stony Fork model were applied to an HSPF model of the Poplar Run Basin. The two basins are in a similar physical setting. Data from October 1, 1987, through September 30, 1989, were used to evaluate the Poplar Run model. In general, the results from the Poplar Run model were comparable to those obtained from the Stony Fork model. The difference between observed and simulated total streamflow was 1.1 percent for the 2-year period. The mean annual streamflow simulated by the Poplar Run model was 18.3 cubic feet per second. This compares to an observed streamflow of 18.15 cubic feet per second. For the 2-year period, the simulated sediment load was 2,754 tons (0.24 ton per acre per year), which compares to a measured sediment load of 3,051.2 tons (0.27 ton per acre per year) for the Poplar Run Basin. Cumulative frequency-distribution curves of the observed and simulated streamflow compared well. The comparison between observed and simulated data improved as the time span increased. Simulated annual means and totals were more representative of the observed data than hourly data used in comparing storm events. The structure and organization of the HSPF model facilitated the simulation of a wide range of hydrologic processes. The simulation results from this investigation indicate that model parameters may be transferred to ungaged basins to generate representative hydrologic data through modeling techniques.
POLYNOMIAL-BASED DISAGGREGATION OF HOURLY RAINFALL FOR CONTINUOUS HYDROLOGIC SIMULATION
Hydrologic modeling of urban watersheds for designs and analyses of stormwater conveyance facilities can be performed in either an event-based or continuous fashion. Continuous simulation requires, among other things, the use of a time series of rainfall amounts. However, for urb...
NASA Astrophysics Data System (ADS)
Rajib, A.; Evenson, G. R.; Golden, H. E.; Lane, C.
2017-12-01
Evapotranspiration (ET), a highly dynamic flux in wetland landscapes, regulates the accuracy of surface/sub-surface runoff simulation in a hydrologic model. Accordingly, considerable uncertainty in simulating ET-related processes remains, including our limited ability to incorporate realistic ground conditions, particularly those involved with complex land-atmosphere feedbacks, vegetation growth, and energy balances. Uncertainty persists despite using high resolution topography and/or detailed land use data. Thus, a good hydrologic model can produce right answers for wrong reasons. In this study, we develop an efficient approach for multi-variable assimilation of remotely sensed earth observations (EOs) into a hydrologic model and apply it in the 1700 km2 Pipestem Creek watershed in the Prairie Pothole Region of North Dakota, USA. Our goal is to employ EOs, specifically Leaf Area Index (LAI) and Potential Evapotranspiration (PET), as surrogates for the aforementioned processes without overruling the model's built-in physical/semi-empirical process conceptualizations. To do this, we modified the source code of an already-improved version of the Soil and Water Assessment Tool (SWAT) for wetland hydrology (Evenson et al. 2016 HP 30(22):4168) to directly assimilate remotely-sensed LAI and PET (obtained from the 500 m and 1 km Moderate Resolution Imaging Spectroradiometer (MODIS) gridded products, respectively) into each model Hydrologic Response Unit (HRU). Two configurations of the model, one with and one without EO assimilation, are calibrated against streamflow observations at the watershed outlet. Spatio-temporal changes in the HRU-level water balance, based on calibrated outputs, are evaluated using MODIS Actual Evapotranspiration (AET) as a reference. It is expected that the model configuration having remotely sensed LAI and PET, will simulate more realistic land-atmosphere feedbacks, vegetation growth and energy balance. As a result, this will decrease simulated water balance uncertainties compared to the default model configuration.
NASA Astrophysics Data System (ADS)
Pathiraja, S.; Anghileri, D.; Burlando, P.; Sharma, A.; Marshall, L.; Moradkhani, H.
2018-03-01
The global prevalence of rapid and extensive land use change necessitates hydrologic modelling methodologies capable of handling non-stationarity. This is particularly true in the context of Hydrologic Forecasting using Data Assimilation. Data Assimilation has been shown to dramatically improve forecast skill in hydrologic and meteorological applications, although such improvements are conditional on using bias-free observations and model simulations. A hydrologic model calibrated to a particular set of land cover conditions has the potential to produce biased simulations when the catchment is disturbed. This paper sheds new light on the impacts of bias or systematic errors in hydrologic data assimilation, in the context of forecasting in catchments with changing land surface conditions and a model calibrated to pre-change conditions. We posit that in such cases, the impact of systematic model errors on assimilation or forecast quality is dependent on the inherent prediction uncertainty that persists even in pre-change conditions. Through experiments on a range of catchments, we develop a conceptual relationship between total prediction uncertainty and the impacts of land cover changes on the hydrologic regime to demonstrate how forecast quality is affected when using state estimation Data Assimilation with no modifications to account for land cover changes. This work shows that systematic model errors as a result of changing or changed catchment conditions do not always necessitate adjustments to the modelling or assimilation methodology, for instance through re-calibration of the hydrologic model, time varying model parameters or revised offline/online bias estimation.
NASA Astrophysics Data System (ADS)
He, X.; Stisen, S.; Henriksen, H. J.
2015-12-01
Hydrological models are important tools to support decision making in water resource management in the past few decades. Nowadays, frequent occurrence of extreme hydrological events has put focus on development of real-time hydrological modeling and forecasting systems. Among the various types of hydrological models, it is only the rainfall-runoff models for surface water that are commonly used in the online real-time fashion; and there is never a tradition to use integrated hydrological models for both surface water and groundwater with large scale perspective. At the Geological Survey of Denmark and Greenland (GEUS), we have setup and calibrated an integrated hydrological model that covers the entire nation, namely the DK-model. So far, the DK-model has only been used in offline mode for historical and future scenario simulations. Therefore, challenges arise when operating the DK-model in real-time mode due to lack of technical experiences and stakeholder awareness. In the present study, we try to demonstrate the process of bringing the DK-model online while actively involving the opinions of the stakeholders. Although the system is not yet fully operational, a prototype has been finished and presented to the stakeholders which can simulate groundwater levels, streamflow and water content in the root zone with a lead time of 48 hours and refreshed every 6 hours. The active involvement of stakeholders has provided very valuable insights and feedbacks for future improvements.
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.
Global operational hydrological forecasts through eWaterCycle
NASA Astrophysics Data System (ADS)
van de Giesen, Nick; Bierkens, Marc; Donchyts, Gennadii; Drost, Niels; Hut, Rolf; Sutanudjaja, Edwin
2015-04-01
Central goal of the eWaterCycle project (www.ewatercycle.org) is the development of an operational hyper-resolution hydrological global model. This model is able to produce 14 day ensemble forecasts based on a hydrological model and operational weather data (presently NOAA's Global Ensemble Forecast System). Special attention is paid to prediction of situations in which water related issues are relevant, such as floods, droughts, navigation, hydropower generation, and irrigation stress. Near-real time satellite data will be assimilated in the hydrological simulations, which is a feature that will be presented for the first time at EGU 2015. First, we address challenges that are mainly computer science oriented but have direct practical hydrological implications. An important feature in this is the use of existing standards and open-source software to the maximum extent possible. For example, we use the Community Surface Dynamics Modeling System (CSDMS) approach to coupling models (Basic Model Interface (BMI)). The hydrological model underlying the project is PCR-GLOBWB, built by Utrecht University. This is the motor behind the predictions and state estimations. Parts of PCR-GLOBWB have been re-engineered to facilitate running it in a High Performance Computing (HPC) environment, run parallel on multiple nodes, as well as to use BMI. Hydrological models are not very CPU intensive compared to, say, atmospheric models. They are, however, memory hungry due to the localized processes and associated effective parameters. To accommodate this memory need, especially in an ensemble setting, a variation on the traditional Ensemble Kalman Filter was developed that needs much less on-chip memory. Due to the operational nature, the coupling of the hydrological model with hydraulic models is very important. The idea is not to run detailed hydraulic routing schemes over the complete globe but to have on-demand simulation prepared off-line with respect to topography and parameterizations. This allows for very detailed simulations at hectare to meter scales, where and when this is needed. At EGU 2015, the operational global eWaterCycle model will be presented for the first time, including forecasts at high resolution, the innovative data assimilation approach, and on-demand coupling with hydraulic models.
Significant uncertainty in global scale hydrological modeling from precipitation data errors
NASA Astrophysics Data System (ADS)
Sperna Weiland, Frederiek C.; Vrugt, Jasper A.; van Beek, Rens (L.) P. H.; Weerts, Albrecht H.; Bierkens, Marc F. P.
2015-10-01
In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we focus on large-scale hydrologic modeling and analyze the effect of parameter and rainfall data uncertainty on simulated discharge dynamics with the global hydrologic model PCR-GLOBWB. We use three rainfall data products; the CFSR reanalysis, the ERA-Interim reanalysis, and a combined ERA-40 reanalysis and CRU dataset. Parameter uncertainty is derived from Latin Hypercube Sampling (LHS) using monthly discharge data from five of the largest river systems in the world. Our results demonstrate that the default parameterization of PCR-GLOBWB, derived from global datasets, can be improved by calibrating the model against monthly discharge observations. Yet, it is difficult to find a single parameterization of PCR-GLOBWB that works well for all of the five river basins considered herein and shows consistent performance during both the calibration and evaluation period. Still there may be possibilities for regionalization based on catchment similarities. Our simulations illustrate that parameter uncertainty constitutes only a minor part of predictive uncertainty. Thus, the apparent dichotomy between simulations of global-scale hydrologic behavior and actual data cannot be resolved by simply increasing the model complexity of PCR-GLOBWB and resolving sub-grid processes. Instead, it would be more productive to improve the characterization of global rainfall amounts at spatial resolutions of 0.5° and smaller.
Clark, Martyn P.; Slater, Andrew G.; Rupp, David E.; Woods, Ross A.; Vrugt, Jasper A.; Gupta, Hoshin V.; Wagener, Thorsten; Hay, Lauren E.
2008-01-01
The problems of identifying the most appropriate model structure for a given problem and quantifying the uncertainty in model structure remain outstanding research challenges for the discipline of hydrology. Progress on these problems requires understanding of the nature of differences between models. This paper presents a methodology to diagnose differences in hydrological model structures: the Framework for Understanding Structural Errors (FUSE). FUSE was used to construct 79 unique model structures by combining components of 4 existing hydrological models. These new models were used to simulate streamflow in two of the basins used in the Model Parameter Estimation Experiment (MOPEX): the Guadalupe River (Texas) and the French Broad River (North Carolina). Results show that the new models produced simulations of streamflow that were at least as good as the simulations produced by the models that participated in the MOPEX experiment. Our initial application of the FUSE method for the Guadalupe River exposed relationships between model structure and model performance, suggesting that the choice of model structure is just as important as the choice of model parameters. However, further work is needed to evaluate model simulations using multiple criteria to diagnose the relative importance of model structural differences in various climate regimes and to assess the amount of independent information in each of the models. This work will be crucial to both identifying the most appropriate model structure for a given problem and quantifying the uncertainty in model structure. To facilitate research on these problems, the FORTRAN‐90 source code for FUSE is available upon request from the lead author.
NASA Astrophysics Data System (ADS)
Lafontaine, J.; Hay, L.; Archfield, S. A.; Farmer, W. H.; Kiang, J. E.
2014-12-01
The U.S. Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the continental US. The portion of the NHM located within the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC) is being used to test the feasibility of improving streamflow simulations in gaged and ungaged watersheds by linking statistically- and physically-based hydrologic models. The GCPO LCC covers part or all of 12 states and 5 sub-geographies, totaling approximately 726,000 km2, and is centered on the lower Mississippi Alluvial Valley. A total of 346 USGS streamgages in the GCPO LCC region were selected to evaluate the performance of this new calibration methodology for the period 1980 to 2013. Initially, the physically-based models are calibrated to measured streamflow data to provide a baseline for comparison. An enhanced calibration procedure then is used to calibrate the physically-based models in the gaged and ungaged areas of the GCPO LCC using statistically-based estimates of streamflow. For this application, the calibration procedure is adjusted to address the limitations of the statistically generated time series to reproduce measured streamflow in gaged basins, primarily by incorporating error and bias estimates. As part of this effort, estimates of uncertainty in the model simulations are also computed for the gaged and ungaged watersheds.
NASA Astrophysics Data System (ADS)
Carmichael, Matthew J.; Inglis, Gordon N.; Badger, Marcus P. S.; Naafs, B. David A.; Behrooz, Leila; Remmelzwaal, Serginio; Monteiro, Fanny M.; Rohrssen, Megan; Farnsworth, Alexander; Buss, Heather L.; Dickson, Alexander J.; Valdes, Paul J.; Lunt, Daniel J.; Pancost, Richard D.
2017-10-01
The Paleocene-Eocene Thermal Maximum (PETM) hyperthermal, 56 million years ago (Ma), is the most dramatic example of abrupt Cenozoic global warming. During the PETM surface temperatures increased between 5 and 9 °C and the onset likely took < 20 kyr. The PETM provides a case study of the impacts of rapid global warming on the Earth system, including both hydrological and associated biogeochemical feedbacks, and proxy data from the PETM can provide constraints on changes in warm climate hydrology simulated by general circulation models (GCMs). In this paper, we provide a critical review of biological and geochemical signatures interpreted as direct or indirect indicators of hydrological change at the PETM, explore the importance of adopting multi-proxy approaches, and present a preliminary model-data comparison. Hydrological records complement those of temperature and indicate that the climatic response at the PETM was complex, with significant regional and temporal variability. This is further illustrated by the biogeochemical consequences of inferred changes in hydrology and, in fact, changes in precipitation and the biogeochemical consequences are often conflated in geochemical signatures. There is also strong evidence in many regions for changes in the episodic and/or intra-annual distribution of precipitation that has not widely been considered when comparing proxy data to GCM output. Crucially, GCM simulations indicate that the response of the hydrological cycle to the PETM was heterogeneous - some regions are associated with increased precipitation - evaporation (P - E), whilst others are characterised by a decrease. Interestingly, the majority of proxy data come from the regions where GCMs predict an increase in PETM precipitation. We propose that comparison of hydrological proxies to GCM output can be an important test of model skill, but this will be enhanced by further data from regions of model-simulated aridity and simulation of extreme precipitation events.
Facilitating hydrological data analysis workflows in R: the RHydro package
NASA Astrophysics Data System (ADS)
Buytaert, Wouter; Moulds, Simon; Skoien, Jon; Pebesma, Edzer; Reusser, Dominik
2015-04-01
The advent of new technologies such as web-services and big data analytics holds great promise for hydrological data analysis and simulation. Driven by the need for better water management tools, it allows for the construction of much more complex workflows, that integrate more and potentially more heterogeneous data sources with longer tool chains of algorithms and models. With the scientific challenge of designing the most adequate processing workflow comes the technical challenge of implementing the workflow with a minimal risk for errors. A wide variety of new workbench technologies and other data handling systems are being developed. At the same time, the functionality of available data processing languages such as R and Python is increasing at an accelerating pace. Because of the large diversity of scientific questions and simulation needs in hydrology, it is unlikely that one single optimal method for constructing hydrological data analysis workflows will emerge. Nevertheless, languages such as R and Python are quickly gaining popularity because they combine a wide array of functionality with high flexibility and versatility. The object-oriented nature of high-level data processing languages makes them particularly suited for the handling of complex and potentially large datasets. In this paper, we explore how handling and processing of hydrological data in R can be facilitated further by designing and implementing a set of relevant classes and methods in the experimental R package RHydro. We build upon existing efforts such as the sp and raster packages for spatial data and the spacetime package for spatiotemporal data to define classes for hydrological data (HydroST). In order to handle simulation data from hydrological models conveniently, a HM class is defined. Relevant methods are implemented to allow for an optimal integration of the HM class with existing model fitting and simulation functionality in R. Lastly, we discuss some of the design challenges of the RHydro package, including integration with big data technologies, web technologies, and emerging data models in hydrology.
High resolution global flood hazard map from physically-based hydrologic and hydraulic models.
NASA Astrophysics Data System (ADS)
Begnudelli, L.; Kaheil, Y.; McCollum, J.
2017-12-01
The global flood map published online at http://www.fmglobal.com/research-and-resources/global-flood-map at 90m resolution is being used worldwide to understand flood risk exposure, exercise certain measures of mitigation, and/or transfer the residual risk financially through flood insurance programs. The modeling system is based on a physically-based hydrologic model to simulate river discharges, and 2D shallow-water hydrodynamic model to simulate inundation. The model can be applied to large-scale flood hazard mapping thanks to several solutions that maximize its efficiency and the use of parallel computing. The hydrologic component of the modeling system is the Hillslope River Routing (HRR) hydrologic model. HRR simulates hydrological processes using a Green-Ampt parameterization, and is calibrated against observed discharge data from several publicly-available datasets. For inundation mapping, we use a 2D Finite-Volume Shallow-Water model with wetting/drying. We introduce here a grid Up-Scaling Technique (UST) for hydraulic modeling to perform simulations at higher resolution at global scale with relatively short computational times. A 30m SRTM is now available worldwide along with higher accuracy and/or resolution local Digital Elevation Models (DEMs) in many countries and regions. UST consists of aggregating computational cells, thus forming a coarser grid, while retaining the topographic information from the original full-resolution mesh. The full-resolution topography is used for building relationships between volume and free surface elevation inside cells and computing inter-cell fluxes. This approach almost achieves computational speed typical of the coarse grids while preserving, to a significant extent, the accuracy offered by the much higher resolution available DEM. The simulations are carried out along each river of the network by forcing the hydraulic model with the streamflow hydrographs generated by HRR. Hydrographs are scaled so that the peak corresponds to the return period corresponding to the hazard map being produced (e.g. 100 years, 500 years). Each numerical simulation models one river reach, except for the longest reaches which are split in smaller parts. Here we show results for selected river basins worldwide.
Boyce, Scott E.; Hanson, Randall T.
2015-01-01
The MODFLOW-2005 (MF) family of hydrologic simulators has diverged into multiple versions designed for specific needs, thus limiting their use to their respective designs. The One-Water Hydrologic Flow Model (MF-OWHM v1.0) is an integrated hydrologic flow model that is an enhanced fusion of multiple MF versions. While maintaining compatibility with existing MF versions, MF-OWHM includes: linkages for coupled heads, flows, and deformation; facilitation of self-updating models, additional observation and parameter options for higher-order calibrations; and redesigned code for faster simulations. This first release of MF-OWHM incorporates MODFLOW-2005 and the Farm Process (MF-FMP2), with new features (FMP3), combined with Local Grid Refinement (MF-LGR), Streamflow Routing (SFR), Surfacewater Routing Process (SWR), Seawater Intrusion (SWI), Riparian Evapotranspiration (RIP-ET), the Newton Formulation (MF-NWT), and more. MF-OWHM represents a complete integrated hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for consumption by agriculture and natural vegetation on the landscape, and for potable and other uses. By retaining and keeping track of the water during simulation of the hydrosphere, MF-OWHM accounts for “all of the water everywhere and all of the time.” This provides the foundation needed to address integrated hydrologic problems such as evaluation of conjunctive-use alternatives and sustainability analysis, including potential adaptation and mitigation strategies, and best management practices.
NASA Astrophysics Data System (ADS)
Pilz, Tobias; Francke, Till; Bronstert, Axel
2016-04-01
Until today a large number of competing computer models has been developed to understand hydrological processes and to simulate and predict streamflow dynamics of rivers. This is primarily the result of a lack of a unified theory in catchment hydrology due to insufficient process understanding and uncertainties related to model development and application. Therefore, the goal of this study is to analyze the uncertainty structure of a process-based hydrological catchment model employing a multiple hypotheses approach. The study focuses on three major problems that have received only little attention in previous investigations. First, to estimate the impact of model structural uncertainty by employing several alternative representations for each simulated process. Second, explore the influence of landscape discretization and parameterization from multiple datasets and user decisions. Third, employ several numerical solvers for the integration of the governing ordinary differential equations to study the effect on simulation results. The generated ensemble of model hypotheses is then analyzed and the three sources of uncertainty compared against each other. To ensure consistency and comparability all model structures and numerical solvers are implemented within a single simulation environment. First results suggest that the selection of a sophisticated numerical solver for the differential equations positively affects simulation outcomes. However, already some simple and easy to implement explicit methods perform surprisingly well and need less computational efforts than more advanced but time consuming implicit techniques. There is general evidence that ambiguous and subjective user decisions form a major source of uncertainty and can greatly influence model development and application at all stages.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Foley, M.G.; Petrie, G.M.; Baldwin, A.J.
1982-06-01
This report contains the input data and computer results for the Geologic Simulation Model. This model is described in detail in the following report: Petrie, G.M., et. al. 1981. Geologic Simulation Model for a Hypothetical Site in the Columbia Plateau, Pacific Northwest Laboratory, Richland, Washington. The Geologic Simulation Model is a quasi-deterministic process-response model which simulates, for a million years into the future, the development of the geologic and hydrologic systems of the ground-water basin containing the Pasco Basin. Effects of natural processes on the ground-water hydrologic system are modeled principally by rate equations. The combined effects and synergistic interactionsmore » of different processes are approximated by linear superposition of their effects during discrete time intervals in a stepwise-integration approach.« less
NASA Astrophysics Data System (ADS)
van Walsum, P. E. V.
2011-11-01
Climate change impact modelling of hydrologic responses is hampered by climate-dependent model parameterizations. Reducing this dependency was one of the goals of extending the regional hydrologic modelling system SIMGRO with a two-way coupling to the crop growth simulation model WOFOST. The coupling includes feedbacks to the hydrologic model in terms of the root zone depth, soil cover, leaf area index, interception storage capacity, crop height and crop factor. For investigating whether such feedbacks lead to significantly different simulation results, two versions of the model coupling were set up for a test region: one with exogenous vegetation parameters, the "static" model, and one with endogenous simulation of the crop growth, the "dynamic" model WOFOST. The used parameterization methods of the static/dynamic vegetation models ensure that for the current climate the simulated long-term average of the actual evapotranspiration is the same for both models. Simulations were made for two climate scenarios. Owing to the higher temperatures in combination with a higher CO2-concentration of the atmosphere, a forward time shift of the crop development is simulated in the dynamic model; the used arable land crop, potatoes, also shows a shortening of the growing season. For this crop, a significant reduction of the potential transpiration is simulated compared to the static model, in the example by 15% in a warm, dry year. In consequence, the simulated crop water stress (the unit minus the relative transpiration) is lower when the dynamic model is used; also the simulated increase of crop water stress due to climate change is lower; in the example, the simulated increase is 15 percentage points less (of 55) than when a static model is used. The static/dynamic models also simulate different absolute values of the transpiration. The difference is most pronounced for potatoes at locations with ample moisture supply; this supply can either come from storage release of a good soil or from capillary rise. With good supply of moisture, the dynamic model simulates up to 10% less actual evapotranspiration than the static one in the example. This can lead to cases where the dynamic model predicts a slight increase of the recharge in a climate scenario, where the static model predicts a decrease. The use of a dynamic model also affects the simulated demand for surface water from external sources; especially the timing is affected. The proposed modelling approach uses postulated relationships that require validation with controlled field trials. In the Netherlands there is a lack of experimental facilities for performing such validations.
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.
Testing the ability of a semidistributed hydrological model to simulate contributing area
NASA Astrophysics Data System (ADS)
Mengistu, S. G.; Spence, C.
2016-06-01
A dry climate, the prevalence of small depressions, and the lack of a well-developed drainage network are characteristics of environments with extremely variable contributing areas to runoff. These types of regions arguably present the greatest challenge to properly understanding catchment streamflow generation processes. Previous studies have shown that contributing area dynamics are important for streamflow response, but the nature of the relationship between the two is not typically understood. Furthermore, it is not often tested how well hydrological models simulate contributing area. In this study, the ability of a semidistributed hydrological model, the PDMROF configuration of Environment Canada's MESH model, was tested to determine if it could simulate contributing area. The study focused on the St. Denis Creek watershed in central Saskatchewan, Canada, which with its considerable topographic depressions, exhibits wide variation in contributing area, making it ideal for this type of investigation. MESH-PDMROF was able to replicate contributing area derived independently from satellite imagery. Daily model simulations revealed a hysteretic relationship between contributing area and streamflow not apparent from the less frequent remote sensing observations. This exercise revealed that contributing area extent can be simulated by a semi-distributed hydrological model with a scheme that assumes storage capacity distribution can be represented with a probability function. However, further investigation is needed to determine if it can adequately represent the complex relationship between streamflow and contributing area that is such a key signature of catchment behavior.
Identifying Hydrologic Processes in Agricultural Watersheds Using Precipitation-Runoff Models
Linard, Joshua I.; Wolock, David M.; Webb, Richard M.T.; Wieczorek, Michael
2009-01-01
Understanding the fate and transport of agricultural chemicals applied to agricultural fields will assist in designing the most effective strategies to prevent water-quality impairments. At a watershed scale, the processes controlling the fate and transport of agricultural chemicals are generally understood only conceptually. To examine the applicability of conceptual models to the processes actually occurring, two precipitation-runoff models - the Soil and Water Assessment Tool (SWAT) and the Water, Energy, and Biogeochemical Model (WEBMOD) - were applied in different agricultural settings of the contiguous United States. Each model, through different physical processes, simulated the transport of water to a stream from the surface, the unsaturated zone, and the saturated zone. Models were calibrated for watersheds in Maryland, Indiana, and Nebraska. The calibrated sets of input parameters for each model at each watershed are discussed, and the criteria used to validate the models are explained. The SWAT and WEBMOD model results at each watershed conformed to each other and to the processes identified in each watershed's conceptual hydrology. In Maryland the conceptual understanding of the hydrology indicated groundwater flow was the largest annual source of streamflow; the simulation results for the validation period confirm this. The dominant source of water to the Indiana watershed was thought to be tile drains. Although tile drains were not explicitly simulated in the SWAT model, a large component of streamflow was received from lateral flow, which could be attributed to tile drains. Being able to explicitly account for tile drains, WEBMOD indicated water from tile drains constituted most of the annual streamflow in the Indiana watershed. The Nebraska models indicated annual streamflow was composed primarily of perennial groundwater flow and infiltration-excess runoff, which conformed to the conceptual hydrology developed for that watershed. The hydrologic processes represented in the parameter sets resulting from each model were comparable at individual watersheds, but varied between watersheds. The models were unable to show, however, whether hydrologic processes other than those included in the original conceptual models were major contributors to streamflow. Supplemental simulations of agricultural chemical transport could improve the ability to assess conceptual models.
NASA Astrophysics Data System (ADS)
Zhu, Dehua; Echendu, Shirley; Xuan, Yunqing; Webster, Mike; Cluckie, Ian
2016-11-01
Impact-focused studies of extreme weather require coupling of accurate simulations of weather and climate systems and impact-measuring hydrological models which themselves demand larger computer resources. In this paper, we present a preliminary analysis of a high-performance computing (HPC)-based hydrological modelling approach, which is aimed at utilizing and maximizing HPC power resources, to support the study on extreme weather impact due to climate change. Here, four case studies are presented through implementation on the HPC Wales platform of the UK mesoscale meteorological Unified Model (UM) with high-resolution simulation suite UKV, alongside a Linux-based hydrological model, Hydrological Predictions for the Environment (HYPE). The results of this study suggest that the coupled hydro-meteorological model was still able to capture the major flood peaks, compared with the conventional gauge- or radar-driving forecast, but with the added value of much extended forecast lead time. The high-resolution rainfall estimation produced by the UKV performs similarly to that of radar rainfall products in the first 2-3 days of tested flood events, but the uncertainties particularly increased as the forecast horizon goes beyond 3 days. This study takes a step forward to identify how the online mode approach can be used, where both numerical weather prediction and the hydrological model are executed, either simultaneously or on the same hardware infrastructures, so that more effective interaction and communication can be achieved and maintained between the models. But the concluding comments are that running the entire system on a reasonably powerful HPC platform does not yet allow for real-time simulations, even without the most complex and demanding data simulation part.
Modeling the Historical Flood Events in France
NASA Astrophysics Data System (ADS)
Ali, Hani; Blaquière, Simon
2017-04-01
We will present the simulation results for different scenarios based on the flood model developed by AXA Global P&C CAT Modeling team. The model uses a Digital Elevation Model (DEM) with 75 m resolution, a hydrographic system (DB Carthage), daily rainfall data from "Météo France", water level from "HYDRO Banque" the French Hydrological Database (www.hydro.eaufrance.fr), for more than 1500 stations, hydrological model from IRSTEA and in-house hydraulic tool. In particular, the model re-simulates the most important and costly flood events that occurred during the past decade in France: we will present the re-simulated meteorological conditions since 1964 and estimate insurance loss incurred on current AXA portfolio of individual risks.
Watershed scale response to climate change--Trout Lake Basin, Wisconsin
Walker, John F.; Hunt, Randall J.; Hay, Lauren E.; Markstrom, Steven L.
2012-01-01
Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Trout River Basin at Trout Lake in northern Wisconsin.
Watershed scale response to climate change--Clear Creek Basin, Iowa
Christiansen, Daniel E.; Hay, Lauren E.; Markstrom, Steven L.
2012-01-01
Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Clear Creek Basin, near Coralville, Iowa.
Watershed scale response to climate change--Feather River Basin, California
Koczot, Kathryn M.; Markstrom, Steven L.; Hay, Lauren E.
2012-01-01
Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Feather River Basin, California.
Watershed scale response to climate change--South Fork Flathead River Basin, Montana
Chase, Katherine J.; Hay, Lauren E.; Markstrom, Steven L.
2012-01-01
Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the South Fork Flathead River Basin, Montana.
Watershed scale response to climate change--Cathance Stream Basin, Maine
Dudley, Robert W.; Hay, Lauren E.; Markstrom, Steven L.; Hodgkins, Glenn A.
2012-01-01
Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Cathance Stream Basin, Maine.
Watershed scale response to climate change--Pomperaug River Watershed, Connecticut
Bjerklie, David M.; Hay, Lauren E.; Markstrom, Steven L.
2012-01-01
Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Pomperaug River Basin at Southbury, Connecticut.
Watershed scale response to climate change--Starkweather Coulee Basin, North Dakota
Vining, Kevin C.; Hay, Lauren E.; Markstrom, Steven L.
2012-01-01
Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Starkweather Coulee Basin near Webster, North Dakota.
Watershed scale response to climate change--Sagehen Creek Basin, California
Markstrom, Steven L.; Hay, Lauren E.; Regan, R. Steven
2012-01-01
Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Sagehen Creek Basin near Truckee, California.
Watershed scale response to climate change--Sprague River Basin, Oregon
Risley, John; Hay, Lauren E.; Markstrom, Steven L.
2012-01-01
Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Sprague River Basin near Chiloquin, Oregon.
Watershed scale response to climate change--Black Earth Creek Basin, Wisconsin
Hunt, Randall J.; Walker, John F.; Westenbroek, Steven M.; Hay, Lauren E.; Markstrom, Steven L.
2012-01-01
Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Black Earth Creek Basin, Wisconsin.
Watershed scale response to climate change--East River Basin, Colorado
Battaglin, William A.; Hay, Lauren E.; Markstrom, Steven L.
2012-01-01
Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the East River Basin, Colorado.
Watershed scale response to climate change--Naches River Basin, Washington
Mastin, Mark C.; Hay, Lauren E.; Markstrom, Steven L.
2012-01-01
Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Naches River Basin below Tieton River in Washington.
Watershed scale response to climate change--Flint River Basin, Georgia
Hay, Lauren E.; Markstrom, Steven L.
2012-01-01
Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Flint River Basin at Montezuma, Georgia.
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.
Markstrom, Steven L.; Niswonger, Richard G.; Regan, R. Steven; Prudic, David E.; Barlow, Paul M.
2008-01-01
The need to assess the effects of variability in climate, biota, geology, and human activities on water availability and flow requires the development of models that couple two or more components of the hydrologic cycle. An integrated hydrologic model called GSFLOW (Ground-water and Surface-water FLOW) was developed to simulate coupled ground-water and surface-water resources. The new model is based on the integration of the U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) and the U.S. Geological Survey Modular Ground-Water Flow Model (MODFLOW). Additional model components were developed, and existing components were modified, to facilitate integration of the models. Methods were developed to route flow among the PRMS Hydrologic Response Units (HRUs) and between the HRUs and the MODFLOW finite-difference cells. This report describes the organization, concepts, design, and mathematical formulation of all GSFLOW model components. An important aspect of the integrated model design is its ability to conserve water mass and to provide comprehensive water budgets for a location of interest. This report includes descriptions of how water budgets are calculated for the integrated model and for individual model components. GSFLOW provides a robust modeling system for simulating flow through the hydrologic cycle, while allowing for future enhancements to incorporate other simulation techniques.
NASA Astrophysics Data System (ADS)
Qi, Wei; Liu, Junguo; Yang, Hong; Sweetapple, Chris
2018-03-01
Global precipitation products are very important datasets in flow simulations, especially in poorly gauged regions. Uncertainties resulting from precipitation products, hydrological models and their combinations vary with time and data magnitude, and undermine their application to flow simulations. However, previous studies have not quantified these uncertainties individually and explicitly. This study developed an ensemble-based dynamic Bayesian averaging approach (e-Bay) for deterministic discharge simulations using multiple global precipitation products and hydrological models. In this approach, the joint probability of precipitation products and hydrological models being correct is quantified based on uncertainties in maximum and mean estimation, posterior probability is quantified as functions of the magnitude and timing of discharges, and the law of total probability is implemented to calculate expected discharges. Six global fine-resolution precipitation products and two hydrological models of different complexities are included in an illustrative application. e-Bay can effectively quantify uncertainties and therefore generate better deterministic discharges than traditional approaches (weighted average methods with equal and varying weights and maximum likelihood approach). The mean Nash-Sutcliffe Efficiency values of e-Bay are up to 0.97 and 0.85 in training and validation periods respectively, which are at least 0.06 and 0.13 higher than traditional approaches. In addition, with increased training data, assessment criteria values of e-Bay show smaller fluctuations than traditional approaches and its performance becomes outstanding. The proposed e-Bay approach bridges the gap between global precipitation products and their pragmatic applications to discharge simulations, and is beneficial to water resources management in ungauged or poorly gauged regions across the world.
Better Insight Into Water Resources Management With Integrated Hydrodynamic And Water Quality Models
NASA Astrophysics Data System (ADS)
Debele, B.; Srinivasan, R.; Parlange, J.
2004-12-01
Models have long been used in water resources management to guide decision making and improve understanding of the system. Numerous models of different scales -spatial and temporal - are available. Yet, very few models manage to bridge simulations of hydrological and water quality parameters from both upland watershed and riverine system. Most water quality models, such as QUAL2E and EPD-RIV1 concentrate on the riverine system while CE-QUAL-W2 and WASP models focus on larger waterbodies, such as lakes and reservoirs. On the other hand, the original SWAT model, HSPF and other upland watershed hydrological models simulate agricultural (diffuse) pollution sources with limited number of processes incorporated to handle point source pollutions that emanate from industrial sectors. Such limitations, which are common in most hydrodynamic and water quality models undermine better understanding that otherwise could be uncovered by employing integrated hydrological and water quality models for both upland watershed and riverine system. The SWAT model is a well documented and verified hydrological and water quality model that has been developed to simulate the effects of various management scenarios on the health of the environment in terms of water quantity and quality. Recently, the SWAT model has been extended to include the simulation of hydrodynamic and water quality parameters in the river system. The extended SWAT model (ESWAT) has been further extended to run using diurnally varying (hourly) weather data and produce outputs at hourly timescales. This and other improvements in the ESWAT model have been documented in the current work. Besides, the results from two case studies in Texas will be reported.
Robustness and Uncertainty: Applications for Policy in Climate and Hydrological Modeling
NASA Astrophysics Data System (ADS)
Fields, A. L., III
2015-12-01
Policymakers must often decide how to proceed when presented with conflicting simulation data from hydrological, climatological, and geological models. While laboratory sciences often appeal to the reproducibility of results to argue for the validity of their conclusions, simulations cannot use this strategy for a number of pragmatic and methodological reasons. However, robustness of predictions and causal structures can serve the same function for simulations as reproducibility does for laboratory experiments and field observations in either adjudicating between conflicting results or showing that there is insufficient justification to externally validate the results. Additionally, an interpretation of the argument from robustness is presented that involves appealing to the convergence of many well-built and diverse models rather than the more common version which involves appealing to the probability that one of a set of models is likely to be true. This interpretation strengthens the case for taking robustness as an additional requirement for the validation of simulation results and ultimately supports the idea that computer simulations can provide information about the world that is just as trustworthy as data from more traditional laboratory studies and field observations. Understanding the importance of robust results for the validation of simulation data is especially important for policymakers making decisions on the basis of potentially conflicting models. Applications will span climate, hydrological, and hydroclimatological models.
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.
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
NASA Astrophysics Data System (ADS)
Taxak, A. K.; Ojha, C. S. P.
2017-12-01
Land use and land cover (LULC) changes within a watershed are recognised as an important factor affecting hydrological processes and water resources. LULC changes continuously not only in long term but also on the inter-annual and season level. Changes in LULC affects the interception, storage and moisture. A widely used approach in rainfall-runoff modelling through Land surface models (LSM)/ hydrological models is to keep LULC same throughout the model running period. In long term simulations where land use change take place during the run period, using a single LULC does not represent a true picture of ground conditions could result in stationarity of model responses. The present work presents a case study in which changes in LULC are incorporated by using multiple LULC layers. LULC for the study period were created using imageries from Landsat series, Sentinal, EO-1 ALI. Distributed, physically based Variable Infiltration Capacity (VIC) model was modified to allow inclusion of LULC as a time varying variable just like climate. The Narayani basin was simulated with LULC, leaf area index (LAI), albedo and climate data for 1992-2015. The results showed that the model simulation with varied parametrization approach has a large improvement over the conventional fixed parametrization approach in terms of long-term water balance. The proposed modelling approach could improve hydrological modelling for applications like land cover change studies, water budget studies etc.
Ravazzani, Giovanni; Ghilardi, Matteo; Mendlik, Thomas; Gobiet, Andreas; Corbari, Chiara; Mancini, Marco
2014-01-01
Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required beacause of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied. PMID:25285917
Ravazzani, Giovanni; Ghilardi, Matteo; Mendlik, Thomas; Gobiet, Andreas; Corbari, Chiara; Mancini, Marco
2014-01-01
Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required because of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied.
Simulated natural hydrologic regime of an intermountain playa conservation site
Sanderson, J.S.; Kotliar, N.B.; Steingraeber, D.A.; Browne, C.
2008-01-01
An intermountain playa wetland preserve in Colorado's San Luis Valley was studied to assess how its current hydrologic function compares to its natural hydrologic regime. Current hydrologic conditions were quantified, and on-site effects of off-site water use were assessed. A water-budget model was developed to simulate an unaltered (i.e., natural) hydrologic regime, and simulated natural conditions were compared to observed conditions. From 1998-2002, observed stream inflows accounted for ??? 80% of total annual water inputs. No ground water discharged to the wetland. Evapotranspiration (ET) accounted for ??? 69% of total annual water loss. Simulated natural conditions differed substantially from current altered conditions with respect to depth, variability, and frequency of flooding. During 1998-2002, observed monthly mean surface-water depth was 65% lower than under simulated natural conditions. Observed monthly variability in water depth range from 129% greater (May) to 100% less (September and October) than simulated. As observed, the wetland dried completely (i.e., was ephemeral) in all years; as simulated, the wetland was ephemeral in two of five years. For the period 1915-2002, the simulated wetland was inundated continuously for as long as 16 years and nine months. The large differences in observed and simulated surface-water dynamics resulted from differences between altered and simulated unaltered stream inflows. The maximum and minimum annual total stream inflows observed from 1998-2005 were 3.1 ?? 106 m3 and 0 m3, respectively, versus 15.5 ?? 106 m3 and 3.2 ?? 106 m3 under simulated natural conditions from 1915-2002. The maximum simulated inflow was 484% greater than observed. These data indicate that the current hydrologic regime of this intermountain playa differs significantly from its natural hydrologic regime, which has important implications for planning and assessing conservation success. ?? 2008, The Society of Wetland Scientists.
Post-processing of multi-hydrologic model simulations for improved streamflow projections
NASA Astrophysics Data System (ADS)
khajehei, sepideh; Ahmadalipour, Ali; Moradkhani, Hamid
2016-04-01
Hydrologic model outputs are prone to bias and uncertainty due to knowledge deficiency in model and data. Uncertainty in hydroclimatic projections arises due to uncertainty in hydrologic model as well as the epistemic or aleatory uncertainties in GCM parameterization and development. This study is conducted to: 1) evaluate the recently developed multi-variate post-processing method for historical simulations and 2) assess the effect of post-processing on uncertainty and reliability of future streamflow projections in both high-flow and low-flow conditions. The first objective is performed for historical period of 1970-1999. Future streamflow projections are generated for 10 statistically downscaled GCMs from two widely used downscaling methods: Bias Corrected Statistically Downscaled (BCSD) and Multivariate Adaptive Constructed Analogs (MACA), over the period of 2010-2099 for two representative concentration pathways of RCP4.5 and RCP8.5. Three semi-distributed hydrologic models were employed and calibrated at 1/16 degree latitude-longitude resolution for over 100 points across the Columbia River Basin (CRB) in the pacific northwest USA. Streamflow outputs are post-processed through a Bayesian framework based on copula functions. The post-processing approach is relying on a transfer function developed based on bivariate joint distribution between the observation and simulation in historical period. Results show that application of post-processing technique leads to considerably higher accuracy in historical simulations and also reducing model uncertainty in future streamflow projections.
NASA Astrophysics Data System (ADS)
Garousi Nejad, I.; He, S.; Tang, Q.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Tarboton, D. G.; Ohara, N.; Lin, H.
2017-12-01
Spatial scale is one of the main considerations in hydrological modeling of snowmelt in mountainous areas. The size of model elements controls the degree to which variability can be explicitly represented versus what needs to be parameterized using effective properties such as averages or other subgrid variability parameterizations that may degrade the quality of model simulations. For snowmelt modeling terrain parameters such as slope, aspect, vegetation and elevation play an important role in the timing and quantity of snowmelt that serves as an input to hydrologic runoff generation processes. In general, higher resolution enhances the accuracy of the simulation since fine meshes represent and preserve the spatial variability of atmospheric and surface characteristics better than coarse resolution. However, this increases computational cost and there may be a scale beyond which the model response does not improve due to diminishing sensitivity to variability and irreducible uncertainty associated with the spatial interpolation of inputs. This paper examines the influence of spatial resolution on the snowmelt process using simulations of and data from the Animas River watershed, an alpine mountainous area in Colorado, USA, using an unstructured distributed physically based hydrological model developed for a parallel computing environment, ADHydro. Five spatial resolutions (30 m, 100 m, 250 m, 500 m, and 1 km) were used to investigate the variations in hydrologic response. This study demonstrated the importance of choosing the appropriate spatial scale in the implementation of ADHydro to obtain a balance between representing spatial variability and the computational cost. According to the results, variation in the input variables and parameters due to using different spatial resolution resulted in changes in the obtained hydrological variables, especially snowmelt, both at the basin-scale and distributed across the model mesh.
NASA Astrophysics Data System (ADS)
Farmer, W. H.; Kiang, J. E.
2017-12-01
The development, deployment and maintenance of water resources management infrastructure and practices rely on hydrologic characterization, which requires an understanding of local hydrology. With regards to streamflow, this understanding is typically quantified with statistics derived from long-term streamgage records. However, a fundamental problem is how to characterize local hydrology without the luxury of streamgage records, a problem that complicates water resources management at ungaged locations and for long-term future projections. This problem has typically been addressed through the development of point estimators, such as regression equations, to estimate particular statistics. Physically-based precipitation-runoff models, which are capable of producing simulated hydrographs, offer an alternative to point estimators. The advantage of simulated hydrographs is that they can be used to compute any number of streamflow statistics from a single source (the simulated hydrograph) rather than relying on a diverse set of point estimators. However, the use of simulated hydrographs introduces a degree of model uncertainty that is propagated through to estimated streamflow statistics and may have drastic effects on management decisions. We compare the accuracy and precision of streamflow statistics (e.g. the mean annual streamflow, the annual maximum streamflow exceeded in 10% of years, and the minimum seven-day average streamflow exceeded in 90% of years, among others) derived from point estimators (e.g. regressions, kriging, machine learning) to that of statistics derived from simulated hydrographs across the continental United States. Initial results suggest that the error introduced through hydrograph simulation may substantially bias the resulting hydrologic characterization.
A Model-Model and Data-Model Comparison for the Early Eocene Hydrological Cycle
NASA Technical Reports Server (NTRS)
Carmichael, Matthew J.; Lunt, Daniel J.; Huber, Matthew; Heinemann, Malte; Kiehl, Jeffrey; LeGrande, Allegra; Loptson, Claire A.; Roberts, Chris D.; Sagoo, Navjit; Shields, Christine
2016-01-01
A range of proxy observations have recently provided constraints on how Earth's hydrological cycle responded to early Eocene climatic changes. However, comparisons of proxy data to general circulation model (GCM) simulated hydrology are limited and inter-model variability remains poorly characterised. In this work, we undertake an intercomparison of GCM-derived precipitation and P - E distributions within the extended EoMIP ensemble (Eocene Modelling Intercomparison Project; Lunt et al., 2012), which includes previously published early Eocene simulations performed using five GCMs differing in boundary conditions, model structure, and precipitation-relevant parameterisation schemes. We show that an intensified hydrological cycle, manifested in enhanced global precipitation and evaporation rates, is simulated for all Eocene simulations relative to the preindustrial conditions. This is primarily due to elevated atmospheric paleo-CO2, resulting in elevated temperatures, although the effects of differences in paleogeography and ice sheets are also important in some models. For a given CO2 level, globally averaged precipitation rates vary widely between models, largely arising from different simulated surface air temperatures. Models with a similar global sensitivity of precipitation rate to temperature (dP=dT ) display different regional precipitation responses for a given temperature change. Regions that are particularly sensitive to model choice include the South Pacific, tropical Africa, and the Peri-Tethys, which may represent targets for future proxy acquisition. A comparison of early and middle Eocene leaf-fossil-derived precipitation estimates with the GCM output illustrates that GCMs generally underestimate precipitation rates at high latitudes, although a possible seasonal bias of the proxies cannot be excluded. Models which warm these regions, either via elevated CO2 or by varying poorly constrained model parameter values, are most successful in simulating a match with geologic data. Further data from low-latitude regions and better constraints on early Eocene CO2 are now required to discriminate between these model simulations given the large error bars on paleoprecipitation estimates. Given the clear differences between simulated precipitation distributions within the ensemble, our results suggest that paleohydrological data offer an independent means by which to evaluate model skill for warm climates.
NASA Astrophysics Data System (ADS)
Prucha, R. H.; Dayton, C. S.; Hawley, C. M.
2002-12-01
The Rocky Flats Environmental Technology Site (RFETS) in Golden, Colorado, a former Department of Energy nuclear weapons manufacturing facility, is currently undergoing closure. The natural semi-arid interaction between surface and subsurface flow at RFETS is complex and complicated by the industrial modifications to the flow system. Using a substantial site data set, a distributed parameter, fully-integrated hydrologic model was developed to assess the hydrologic impact of different hypothetical site closure configurations on the current flow system and to better understand the integrated hydrologic behavior of the system. An integrated model with this level of detail has not been previously developed in a semi-arid area, and a unique, but comprehensive, approach was required to calibrate and validate the model. Several hypothetical scenarios were developed to simulate hydrologic effects of modifying different aspects of the site. For example, some of the simulated modifications included regrading the current land surface, changing the existing surface channel network, removing subsurface trenches and gravity drain flow systems, installing a slurry wall and geotechnical cover, changing the current vegetative cover, and converting existing buildings and pavement to permeable soil areas. The integrated flow model was developed using a rigorous physically-based code so that realistic design parameters can simulate these changes. This code also permitted evaluation of changes to complex integrated hydrologic system responses that included channelized and overland flow, pond levels, unsaturated zone storage, groundwater heads and flow directions, and integrated water balances for key areas. Results generally show that channel flow offsite decreases substantially for different scenarios, while groundwater heads generally increase within the reconfigured industrial area most of which is then discharged as evapotranspiration. These changes have significant implications to site closure and operation.
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.
NASA Astrophysics Data System (ADS)
Campo, Lorenzo; Caparrini, Francesca
2013-04-01
The need for accurate distributed hydrological modelling has constantly increased in last years for several purposes: agricultural applications, water resources management, hydrological balance at watershed scale, floods forecast. The main input for the hydrological numerical models is rainfall data that present, at the same time, a large availability of measures (in gauged regions, with respect to other micro-meteorological variables) and the most complex spatial patterns. While also in presence of densely gauged watersheds the spatial interpolation of the rainfall is a non-trivial problem, due to the spatial intermittence of the variable (especially at finer temporal scales), ungauged regions need an alternative source of rainfall data in order to perform the hydrological modelling. Such source can be constituted by the satellite-estimated rainfall fields, with reference to both geostationary and polar-orbit platforms. In this work the rainfall product obtained by the Aqua-AIRS sensor were used in order to assess the feasibility of the use of satellite-based rainfall as input for distributed hydrological modelling. The MOBIDIC (MOdello di BIlancio Distribuito e Continuo) model, developed at the Department of civil and Environmental Engineering of the University of Florence and operationally used by Tuscany Region and Umbria Region for flood prediction and management, was used for the experiments. In particular three experiments were carried on: a) hydrological simulation with the use of rain-gauges data, b) simulation with the use of satellite-only rainfall estimates, c) simulation with the combined use of the two sources of data in order to obtain an optimal estimate of the actual rainfall fields. The domain of the study was the central Italy. Several critical events occurred in the area were analyzed. A discussion of the results is provided.
NASA Astrophysics Data System (ADS)
Velasquez, N.; Ochoa, A.; Castillo, S.; Hoyos Ortiz, C. D.
2017-12-01
The skill of river discharge simulation using hydrological models strongly depends on the quality and spatio-temporal representativeness of precipitation during storm events. All precipitation measurement strategies have their own strengths and weaknesses that translate into discharge simulation uncertainties. Distributed hydrological models are based on evolving rainfall fields in the same time scale as the hydrological simulation. In general, rainfall measurements from a dense and well maintained rain gauge network provide a very good estimation of the total volume for each rainfall event, however, the spatial structure relies on interpolation strategies introducing considerable uncertainty in the simulation process. On the other hand, rainfall retrievals from radar reflectivity achieve a better spatial structure representation but with higher uncertainty in the surface precipitation intensity and volume depending on the vertical rainfall characteristics and radar scan strategy. To assess the impact of both rainfall measurement methodologies on hydrological simulations, and in particular the effects of the rainfall spatio-temporal variability, a numerical modeling experiment is proposed including the use of a novel QPE (Quantitative Precipitation Estimation) method based on disdrometer data in order to estimate surface rainfall from radar reflectivity. The experiment is based on the simulation of 84 storms, the hydrological simulations are carried out using radar QPE and two different interpolation methods (IDW and TIN), and the assessment of simulated peak flow. Results show significant rainfall differences between radar QPE and the interpolated fields, evidencing a poor representation of storms in the interpolated fields, which tend to miss the precise location of the intense precipitation cores, and to artificially generate rainfall in some areas of the catchment. Regarding streamflow modelling, the potential improvement achieved by using radar QPE depends on the density of the rain gauge network and its distribution relative to the precipitation events. The results for the 84 storms show a better model skill using radar QPE than the interpolated fields. Results using interpolated fields are highly affected by the dominant rainfall type and the basin scale.
Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)
Atchley, A. L.; Painter, S. L.; Harp, D. R.; ...
2015-04-14
Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. However, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth System Models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth System Models challenge validation and parameterization of hydrothermal models. A recently developed surface/subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurementsmore » to calibrate and identify fine scale controls of ALT in ice wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze/thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g. troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.« less
NASA Astrophysics Data System (ADS)
Mezbahuddin, M.; Grant, R. F.; Flanagan, L. B.
2016-08-01
Improved predictive capacity of hydrology and surface energy exchange is critical for conserving boreal peatland carbon sequestration under drier and warmer climates. We represented basic processes for water and O2 transport and their effects on ecosystem water, energy, carbon, and nutrient cycling in a process-based model ecosys to simulate effects of seasonal and interannual variations in hydrology on peat water content, water table depth (WTD), and surface energy exchange of a Western Canadian fen peatland. Substituting a van Genuchten model (VGM) for a modified Campbell model (MCM) in ecosys enabled a significantly better simulation of peat moisture retention as indicated by higher modeled versus measured R2 and Willmot's index (d) with VGM (R2 0.7, d 0.8) than with MCM (R2 0.25, d 0.35) for daily peat water contents from a wetter year 2004 to a drier year 2009. With the improved peat moisture simulation, ecosys modeled hourly WTD and energy fluxes reasonably well (modeled versus measured R2: WTD 0.6, net radiation 0.99, sensible heat >0.8, and latent heat >0.85). Gradually declining ratios of precipitation to evapotranspiration and of lateral recharge to discharge enabled simulation of a gradual drawdown of growing season WTD and a consequent peat drying from 2004 to 2009. When WTD fell below a threshold of 0.35 m below the hollow surface, intense drying of mosses in ecosys caused a simulated reduction in evapotranspiration and an increase in Bowen ratio during late growing season that were consistent with measurements. Hence, using appropriate water desorption curve coupled with vertical-lateral hydraulic schemes is vital to accurately simulate peatland hydrology and energy balance.
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.
Hydrological responses to dynamically and statistically downscaled climate model output
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.
Watershed scale response to climate change--Yampa River Basin, Colorado
Hay, Lauren E.; Battaglin, William A.; Markstrom, Steven L.
2012-01-01
General Circulation Model simulations of future climate through 2099 project a wide range of possible scenarios. To determine the sensitivity and potential effect of long-term climate change on the freshwater resources of the United States, the U.S. Geological Survey Global Change study, "An integrated watershed scale response to global change in selected basins across the United States" was started in 2008. The long-term goal of this national study is to provide the foundation for hydrologically based climate change studies across the nation. Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Yampa River Basin at Steamboat Springs, Colorado.
Dogrul, Emin C.; Schmid, Wolfgang; Hanson, Randall T.; Kadir, Tariq; Chung, Francis
2016-01-01
Effective modeling of conjunctive use of surface and subsurface water resources requires simulation of land use-based root zone and surface flow processes as well as groundwater flows, streamflows, and their interactions. Recently, two computer models developed for this purpose, the Integrated Water Flow Model (IWFM) from the California Department of Water Resources and the MODFLOW with Farm Process (MF-FMP) from the US Geological Survey, have been applied to complex basins such as the Central Valley of California. As both IWFM and MFFMP are publicly available for download and can be applied to other basins, there is a need to objectively compare the main approaches and features used in both models. This paper compares the concepts, as well as the method and simulation features of each hydrologic model pertaining to groundwater, surface water, and landscape processes. The comparison is focused on the integrated simulation of water demand and supply, water use, and the flow between coupled hydrologic processes. The differences in the capabilities and features of these two models could affect the outcome and types of water resource problems that can be simulated.
NASA Astrophysics Data System (ADS)
Seibert, S. P.; Skublics, D.; Ehret, U.
2014-09-01
The coordinated operation of reservoirs in large-scale river basins has great potential to improve flood mitigation. However, this requires large scale hydrological models to translate the effect of reservoir operation to downstream points of interest, in a quality sufficient for the iterative development of optimized operation strategies. And, of course, it requires reservoirs large enough to make a noticeable impact. In this paper, we present and discuss several methods dealing with these prerequisites for reservoir operation using the example of three major floods in the Bavarian Danube basin (45,000 km2) and nine reservoirs therein: We start by presenting an approach for multi-criteria evaluation of model performance during floods, including aspects of local sensitivity to simulation quality. Then we investigate the potential of joint hydrologic-2d-hydrodynamic modeling to improve model performance. Based on this, we evaluate upper limits of reservoir impact under idealized conditions (perfect knowledge of future rainfall) with two methods: Detailed simulations and statistical analysis of the reservoirs' specific retention volume. Finally, we investigate to what degree reservoir operation strategies optimized for local (downstream vicinity to the reservoir) and regional (at the Danube) points of interest are compatible. With respect to model evaluation, we found that the consideration of local sensitivities to simulation quality added valuable information not included in the other evaluation criteria (Nash-Sutcliffe efficiency and Peak timing). With respect to the second question, adding hydrodynamic models to the model chain did, contrary to our expectations, not improve simulations, despite the fact that under idealized conditions (using observed instead of simulated lateral inflow) the hydrodynamic models clearly outperformed the routing schemes of the hydrological models. Apparently, the advantages of hydrodynamic models could not be fully exploited when fed by output from hydrological models afflicted with systematic errors in volume and timing. This effect could potentially be reduced by joint calibration of the hydrological-hydrodynamic model chain. Finally, based on the combination of the simulation-based and statistical impact assessment, we identified one reservoir potentially useful for coordinated, regional flood mitigation for the Danube. While this finding is specific to our test basin, the more interesting and generally valid finding is that operation strategies optimized for local and regional flood mitigation are not necessarily mutually exclusive, sometimes they are identical, sometimes they can, due to temporal offsets, be pursued simultaneously.
Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.; ...
2017-09-14
Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.
Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less
LaFontaine, Jacob H.; Hay, Lauren E.; Viger, Roland J.; Markstrom, Steve L.; Regan, R. Steve; Elliott, Caroline M.; Jones, John W.
2013-01-01
A hydrologic model of the Apalachicola–Chattahoochee–Flint River Basin (ACFB) has been developed as part of a U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center effort to provide integrated science that helps resource managers understand the effect of climate change on a range of ecosystem responses. The hydrologic model was developed as part of the Southeast Regional Assessment Project using the Precipitation Runoff Modeling System (PRMS), a deterministic, distributed-parameter, process-based system that simulates the effects of precipitation, temperature, and land use on basin hydrology. The ACFB PRMS model simulates streamflow throughout the approximately 50,700 square-kilometer basin on a daily time step for the period 1950–99 using gridded climate forcings of air temperature and precipitation, and parameters derived from spatial data layers of altitude, land cover, soils, surficial geology, depression storage (small water bodies), and data from 56 USGS streamgages. Measured streamflow data from 35 of the 56 USGS streamgages were used to calibrate and evaluate simulated basin streamflow; the remaining gage locations were used for model delineation only. The model matched measured daily streamflow at 31 of the 35 calibration gages with Nash-Sutcliffe Model Efficiency Index (NS) greater than 0.6. Streamflow data for some calibration gages were augmented for regulation and water use effects to represent more natural flow volumes. Time-static parameters describing land cover limited the ability of the simulation to match historical runoff in the more developed subbasins. Overall, the PRMS simulation of the ACFB provides a good representation of basin hydrology on annual and monthly time steps. Calibration subbasins were analyzed by separating the 35 subbasins into five classes based on physiography, land use, and stream type (tributary or mainstem). The lowest NS values were rarely below 0.6, whereas the median NS for all five classes was within 0.74 to 0.96 for annual mean streamflow, 0.89 to 0.98 for mean monthly streamflow, and 0.82 to 0.98 for monthly mean streamflow. The median bias for all five classes was within –4.3 to 0.8 percent for annual mean streamflow, –6.3 to 0.5 percent for mean monthly streamflow, and –9.3 to 1.3 percent for monthly mean streamflow. The NS results combined with the percent bias results indicated a good to very good streamflow volume simulation for all subbasins. This simulation of the ACFB provides a foundation for future modeling and interpretive studies. Streamflow and other components of the hydrologic cycle simulated by PRMS can be used to inform other types of simulations; water-temperature, hydrodynamic, and ecosystem-dynamics simulations are three examples. In addition, possible future hydrologic conditions could be studied using this model in combination with land cover projections and downscaled general circulation model results.
NASA Astrophysics Data System (ADS)
Balin Talamba, D.; Higy, C.; Joerin, C.; Musy, A.
The paper presents an application concerning the hydrological modelling for the Haute-Mentue catchment, located in western Switzerland. A simplified version of Topmodel, developed in a Labview programming environment, was applied in the aim of modelling the hydrological processes on this catchment. Previous researches car- ried out in this region outlined the importance of the environmental tracers in studying the hydrological behaviour and an important knowledge has been accumulated dur- ing this period concerning the mechanisms responsible for runoff generation. In con- formity with the theoretical constraints, Topmodel was applied for an Haute-Mentue sub-catchment where tracing experiments showed constantly low contributions of the soil water during the flood events. The model was applied for two humid periods in 1998. First, the model calibration was done in order to provide the best estimations for the total runoff. Instead, the simulated components (groundwater and rapid flow) showed far deviations from the reality indicated by the tracing experiments. Thus, a new calibration was performed including additional information given by the environ- mental tracing. The calibration of the model was done by using simulated annealing (SA) techniques, which are easy to implement and statistically allow for converging to a global minimum. The only problem is that the method is time and computer consum- ing. To improve this, a version of SA was used which is known as very fast-simulated annealing (VFSA). The principles are the same as for the SA technique. The random search is guided by certain probability distribution and the acceptance criterion is the same as for SA but the VFSA allows for better taking into account the ranges of vari- ation of each parameter. Practice with Topmodel showed that the energy function has different sensitivities along different dimensions of the parameter space. The VFSA algorithm allows differentiated search in relation with the sensitivity of the param- eters. The environmental tracing was used in the aim of constraining the parameter space in order to better simulate the hydrological behaviour of the catchment. VFSA outlined issues for characterising the significance of Topmodel input parameters as well as their uncertainty for the hydrological modelling.
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.
Application of bayesian networks to real-time flood risk estimation
NASA Astrophysics Data System (ADS)
Garrote, L.; Molina, M.; Blasco, G.
2003-04-01
This paper presents the application of a computational paradigm taken from the field of artificial intelligence - the bayesian network - to model the behaviour of hydrologic basins during floods. The final goal of this research is to develop representation techniques for hydrologic simulation models in order to define, develop and validate a mechanism, supported by a software environment, oriented to build decision models for the prediction and management of river floods in real time. The emphasis is placed on providing decision makers with tools to incorporate their knowledge of basin behaviour, usually formulated in terms of rainfall-runoff models, in the process of real-time decision making during floods. A rainfall-runoff model is only a step in the process of decision making. If a reliable rainfall forecast is available and the rainfall-runoff model is well calibrated, decisions can be based mainly on model results. However, in most practical situations, uncertainties in rainfall forecasts or model performance have to be incorporated in the decision process. The computation paradigm adopted for the simulation of hydrologic processes is the bayesian network. A bayesian network is a directed acyclic graph that represents causal influences between linked variables. Under this representation, uncertain qualitative variables are related through causal relations quantified with conditional probabilities. The solution algorithm allows the computation of the expected probability distribution of unknown variables conditioned to the observations. An approach to represent hydrologic processes by bayesian networks with temporal and spatial extensions is presented in this paper, together with a methodology for the development of bayesian models using results produced by deterministic hydrologic simulation models
An approach for modelling snowcover ablation and snowmelt runoff in cold region environments
NASA Astrophysics Data System (ADS)
Dornes, Pablo Fernando
Reliable hydrological model simulations are the result of numerous complex interactions among hydrological inputs, landscape properties, and initial conditions. Determination of the effects of these factors is one of the main challenges in hydrological modelling. This situation becomes even more difficult in cold regions due to the ungauged nature of subarctic and arctic environments. This research work is an attempt to apply a new approach for modelling snowcover ablation and snowmelt runoff in complex subarctic environments with limited data while retaining integrity in the process representations. The modelling strategy is based on the incorporation of both detailed process understanding and inputs along with information gained from observations of basin-wide streamflow phenomenon; essentially a combination of deductive and inductive approaches. The study was conducted in the Wolf Creek Research Basin, Yukon Territory, using three models, a small-scale physically based hydrological model, a land surface scheme, and a land surface hydrological model. The spatial representation was based on previous research studies and observations, and was accomplished by incorporating landscape units, defined according to topography and vegetation, as the spatial model elements. Comparisons between distributed and aggregated modelling approaches showed that simulations incorporating distributed initial snowcover and corrected solar radiation were able to properly simulate snowcover ablation and snowmelt runoff whereas the aggregated modelling approaches were unable to represent the differential snowmelt rates and complex snowmelt runoff dynamics. Similarly, the inclusion of spatially distributed information in a land surface scheme clearly improved simulations of snowcover ablation. Application of the same modelling approach at a larger scale using the same landscape based parameterisation showed satisfactory results in simulating snowcover ablation and snowmelt runoff with minimal calibration. Verification of this approach in an arctic basin illustrated that landscape based parameters are a feasible regionalisation framework for distributed and physically based models. In summary, the proposed modelling philosophy, based on the combination of an inductive and deductive reasoning, is a suitable strategy for reliable predictions of snowcover ablation and snowmelt runoff in cold regions and complex environments.
NASA Astrophysics Data System (ADS)
Badar, Bazigha; Romshoo, Shakil A.; Khan, M. A.
2013-04-01
In this paper, we evaluate the impact of changing land use/land cover (LULC) on the hydrological processes in Dal lake catchment of Kashmir Himalayas by integrating remote sensing, simulation modelling and extensive field observations. Over the years, various anthropogenic pressures in the lake catchment have significantly altered the land system, impairing, inter-alia, sustained biotic communities and water quality of the lake. The primary objective of this paper was to help a better understanding of the LULC change, its driving forces and the overall impact on the hydrological response patterns. Multi-sensor and multi-temporal satellite data for 1992 and 2005 was used for determining the spatio-temporal dynamics of the lake catchment. Geographic Information System (GIS) based simulation model namely Generalized Watershed Loading Function (GWLF) was used to model the hydrological processes under the LULC conditions. We discuss spatio-temporal variations in LULC and identify factors contributing to these variations and analyze the corresponding impacts of the change on the hydrological processes like runoff, erosion and sedimentation. The simulated results on the hydrological responses reveal that depletion of the vegetation cover in the study area and increase in impervious and bare surface cover due to anthropogenic interventions are the primary reasons for the increased runoff, erosion and sediment discharges in the Dal lake catchment. This study concludes that LULC change in the catchment is a major concern that has disrupted the ecological stability and functioning of the Dal lake ecosystem.
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.
Comparisons of regional Hydrological Angular Momentum (HAM) of the different models
NASA Astrophysics Data System (ADS)
Nastula, J.; Kolaczek, B.; Popinski, W.
2006-10-01
In the paper hydrological excitations of the polar motion (HAM) were computed from various hydrological data series (NCEP, ECMWF, CPC water storage and LaD World Simulations of global continental water). HAM series obtained from these four models and the geodetic excitation function GEOD computed from the polar motion COMB03 data were compared in the seasonal spectral band. The results show big differences of these hydrological excitation functions as well as of their spectra in the seasonal spectra band. Seasonal oscillations of the global geophysical excitation functions (AAM + OAM + HAM) in all cases besides the NCEP/NCAR model are smaller than the geodetic excitation function. It means that these models need further improvement and perhaps not only hydrological models need improvements.
NASA Astrophysics Data System (ADS)
Li, J.
2017-12-01
Large-watershed flood simulation and forecasting is very important for a distributed hydrological model in the application. There are some challenges including the model's spatial resolution effect, model performance and accuracy and so on. To cope with the challenge of the model's spatial resolution effect, different model resolution including 1000m*1000m, 600m*600m, 500m*500m, 400m*400m, 200m*200m were used to build the distributed hydrological model—Liuxihe model respectively. The purpose is to find which one is the best resolution for Liuxihe model in Large-watershed flood simulation and forecasting. This study sets up a physically based distributed hydrological model for flood forecasting of the Liujiang River basin in south China. Terrain data digital elevation model (DEM), soil type and land use type are downloaded from the website freely. The model parameters are optimized by using an improved Particle Swarm Optimization(PSO) algorithm; And parameter optimization could reduce the parameter uncertainty that exists for physically deriving model parameters. The different model resolution (200m*200m—1000m*1000m ) are proposed for modeling the Liujiang River basin flood with the Liuxihe model in this study. The best model's spatial resolution effect for flood simulation and forecasting is 200m*200m.And with the model's spatial resolution reduction, the model performance and accuracy also become worse and worse. When the model resolution is 1000m*1000m, the flood simulation and forecasting result is the worst, also the river channel divided based on this resolution is differs from the actual one. To keep the model with an acceptable performance, minimum model spatial resolution is needed. The suggested threshold model spatial resolution for modeling the Liujiang River basin flood is a 500m*500m grid cell, but the model spatial resolution with a 200m*200m grid cell is recommended in this study to keep the model at a best performance.
NASA Astrophysics Data System (ADS)
Valentin, M. M.; Hay, L.; Van Beusekom, A. E.; Viger, R. J.; Hogue, T. S.
2016-12-01
Forecasting the hydrologic response to climate change in Alaska's glaciated watersheds remains daunting for hydrologists due to sparse field data and few modeling tools, which frustrates efforts to manage and protect critical aquatic habitat. Approximately 20% of the 64,000 square kilometer Copper River watershed is glaciated, and its glacier-fed tributaries support renowned salmon fisheries that are economically, culturally, and nutritionally invaluable to the local communities. This study adapts a simple, yet powerful, conceptual hydrologic model to simulate changes in the timing and volume of streamflow in the Copper River, Alaska as glaciers change under plausible future climate scenarios. The USGS monthly water balance model (MWBM), a hydrologic tool used for two decades to evaluate a broad range of hydrologic questions in the contiguous U.S., was enhanced to include glacier melt simulations and remotely sensed data. In this presentation we summarize the technical details behind our MWBM adaptation and demonstrate its use in the Copper River Basin to evaluate glacier and streamflow responses to climate change.
USGS Geospatial Fabric and Geo Data Portal for Continental Scale Hydrology Simulations
NASA Astrophysics Data System (ADS)
Sampson, K. M.; Newman, A. J.; Blodgett, D. L.; Viger, R.; Hay, L.; Clark, M. P.
2013-12-01
This presentation describes use of United States Geological Survey (USGS) data products and server-based resources for continental-scale hydrologic simulations. The USGS Modeling of Watershed Systems (MoWS) group provides a consistent national geospatial fabric built on NHDPlus. They have defined more than 100,000 hydrologic response units (HRUs) over the continental United States based on points of interest (POIs) and split into left and right bank based on the corresponding stream segment. Geophysical attributes are calculated for each HRU that can be used to define parameters in hydrologic and land-surface models. The Geo Data Portal (GDP) project at the USGS Center for Integrated Data Analytics (CIDA) provides access to downscaled climate datasets and processing services via web-interface and python modules for creating forcing datasets for any polygon (such as an HRU). These resources greatly reduce the labor required for creating model-ready data in-house, contributing to efficient and effective modeling applications. We will present an application of this USGS cyber-infrastructure for assessments of impacts of climate change on hydrology over the continental United States.
Detecting hydrological changes through conceptual model
NASA Astrophysics Data System (ADS)
Viola, Francesco; Caracciolo, Domenico; Pumo, Dario; Francipane, Antonio; Valerio Noto, Leonardo
2015-04-01
Natural changes and human modifications in hydrological systems coevolve and interact in a coupled and interlinked way. If, on one hand, climatic changes are stochastic, non-steady, and affect the hydrological systems, on the other hand, human-induced changes due to over-exploitation of soils and water resources modifies the natural landscape, water fluxes and its partitioning. Indeed, the traditional assumption of static systems in hydrological analysis, which has been adopted for long time, fails whenever transient climatic conditions and/or land use changes occur. Time series analysis is a way to explore environmental changes together with societal changes; unfortunately, the not distinguishability between causes restrict the scope of this method. In order to overcome this limitation, it is possible to couple time series analysis with an opportune hydrological model, such as a conceptual hydrological model, which offers a schematization of complex dynamics acting within a basin. Assuming that model parameters represent morphological basin characteristics and that calibration is a way to detect hydrological signature at a specific moment, it is possible to argue that calibrating the model over different time windows could be a method for detecting potential hydrological changes. In order to test the capabilities of a conceptual model in detecting hydrological changes, this work presents different "in silico" experiments. A synthetic-basin is forced with an ensemble of possible future scenarios generated with a stochastic weather generator able to simulate steady and non-steady climatic conditions. The experiments refer to Mediterranean climate, which is characterized by marked seasonality, and consider the outcomes of the IPCC 5th report for describing climate evolution in the next century. In particular, in order to generate future climate change scenarios, a stochastic downscaling in space and time is carried out using realizations of an ensemble of General Circulation Models (GCMs) for the future scenarios 2046-2065 and 2081-2100. Land use changes (i.e., changes in the fraction of impervious area due to increasing urbanization) are explicitly simulated, while the reference hydrological responses are assessed by the spatially distributed, process-based hydrological model tRIBS, the TIN-based Real-time Integrated Basin Simulator. Several scenarios have been created, describing hypothetical centuries with steady conditions, climate change conditions, land use change conditions and finally complex conditions involving both transient climatic modifications and gradual land use changes. A conceptual lumped model, the EHSM (EcoHydrological Streamflow Model) is calibrated for the above mentioned scenarios with regard to different time-windows. The calibrated parameters show high sensitivity to anthropic variations in land use and/or climatic variability. Land use changes are clearly visible from parameters evolution especially when steady climatic conditions are considered. When the increase in urbanization is coupled with rainfall reduction the ability to detect human interventions through the analysis of conceptual model parameters is weakened.
NASA Astrophysics Data System (ADS)
Atchley, A. L.; Linn, R.; Middleton, R. S.; Runde, I.; Coon, E.; Michaletz, S. T.
2016-12-01
Wildfire is a complex agent of change that both affects and depends on eco-hydrological systems, thereby constituting a tightly linked system of disturbances and eco-hydrological conditions. For example, structure, build-up, and moisture content of fuel are dependent on eco-hydrological regimes, which impacts fire spread and intensity. Fire behavior, on the other hand, determines the severity and extent of eco-hydrological disturbance, often resulting in a mosaic of untouched, stressed, damaged, or completely destroyed vegetation within the fire perimeter. This in turn drives new eco-hydrological system behavior. The cycles of disturbance and recovery present a complex evolving system with many unknowns especially in the face of climate change that has implications for fire risk, water supply, and forest composition. Physically-based numerical experiments that attempt to capture the complex linkages between eco-hydrological regimes that affect fire behavior and the echo-hydrological response from those fire disturbances help build the understanding required to project how fire disturbance and eco-hydrological conditions coevolve over time. Here we explore the use of FIRETEC—a physically-based 3D combustion model that solves conservation of mass, momentum, energy, and chemical species—to resolve fire spread over complex terrain and fuel structures. Uniquely, we couple a physically-based plant mortality model with FIRETEC and examine the resultant hydrologic impact. In this proof of concept demonstration we spatially distribute fuel structure and moisture content based on the eco-hydrological condition to use as input for FIRETEC. The fire behavior simulation then produces localized burn severity and heat injures which are used as input to a spatially-informed plant mortality model. Ultimately we demonstrate the applicability of physically-based models to explore integrated disturbance and eco-hydrologic response to wildfire behavior and specifically map how fire spread and intensity is affect by the antecedent eco-hydrological condition, which then affects the resulting tree mortality patterns.
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.
The End-to-end Demonstrator for improved decision making in the water sector in Europe (EDgE)
NASA Astrophysics Data System (ADS)
Wood, Eric; Wanders, Niko; Pan, Ming; Sheffield, Justin; Samaniego, Luis; Thober, Stephan; Kumar, Rohinni; Prudhomme, Christel; Houghton-Carr, Helen
2017-04-01
High-resolution simulations of water resources from hydrological models are vital to supporting important climate services. Apart from a high level of detail, both spatially and temporally, it is important to provide simulations that consistently cover a range of timescales, from historical reanalysis to seasonal forecast and future projections. In the new EDgE project commissioned by the ECMWF (C3S) we try to fulfill these requirements. EDgE is a proof-of-concept project which combines climate data and state-of-the-art hydrological modelling to demonstrate a water-oriented information system implemented through a web application. EDgE is working with key European stakeholders representative of private and public sectors to jointly develop and tailor approaches and techniques. With these tools, stakeholders are assisted in using improved climate information in decision-making, and supported in the development of climate change adaptation and mitigation policies. Here, we present the first results of the EDgE modelling chain, which is divided into three main processes: 1) pre-processing and downscaling; 2) hydrological modelling; 3) post-processing. Consistent downscaling and bias corrections for historical simulations, seasonal forecasts and climate projections ensure that the results across scales are robust. The daily temporal resolution and 5km spatial resolution ensure locally relevant simulations. With the use of four hydrological models (PCR-GLOBWB, VIC, mHM, Noah-MP), uncertainty between models is properly addressed, while consistency is guaranteed by using identical input data for static land surface parameterizations. The forecast results are communicated to stakeholders via Sectoral Climate Impact Indicators (SCIIs) that have been created in collaboration with the end-user community of the EDgE project. The final product of this project is composed of 15 years of seasonal forecast and 10 climate change projections, all combined with four hydrological models. These unique high-resolution climate information simulations in the EDgE project provide an unprecedented information system for decision-making over Europe.
Use of soft data for multi-criteria calibration and validation of APEX: Impact on model simulations
USDA-ARS?s Scientific Manuscript database
It is widely known that the use of soft data and multiple model performance criteria in model calibration and validation is critical to ensuring the model capture major hydrologic and water quality processes. The Agricultural Policy/Environmental eXtender (APEX) is a hydrologic and water quality mod...
NASA Astrophysics Data System (ADS)
Shen, Yan-Jun; Shen, Yanjun; Fink, Manfred; Kralisch, Sven; Brenning, Alexander
2018-01-01
Understanding the water balance, especially as it relates to the distribution of runoff components, is crucial for water resource management and coping with the impacts of climate change. However, hydrological processes are poorly known in mountainous regions due to data scarcity and the complex dynamics of snow and glaciers. This study aims to provide a quantitative comparison of gridded precipitation products in the Tianshan Mountains, located in Central Asia and in order to further understand the mountain hydrology and distribution of runoff components in the glacierized Kaidu Basin. We found that gridded precipitation products are affected by inconsistent biases based on a spatiotemporal comparison with the nearest weather stations and should be evaluated with caution before using them as boundary conditions in hydrological modeling. Although uncertainties remain in this data-scarce basin, driven by field survey data and bias-corrected gridded data sets (ERA-Interim and APHRODITE), the water balance and distribution of runoff components can be plausibly quantified based on the distributed hydrological model (J2000). We further examined parameter sensitivity and uncertainty with respect to both simulated streamflow and different runoff components based on an ensemble of simulations. This study demonstrated the possibility of integrating gridded products in hydrological modeling. The methodology used can be important for model applications and design in other data-scarce mountainous regions. The model-based simulation quantified the water balance and how the water resources are partitioned throughout the year in Tianshan Mountain basins, although the uncertainties present in this study result in important limitations.
Development of an Integrated Hydrologic Modeling System for Rainfall-Runoff Simulation
NASA Astrophysics Data System (ADS)
Lu, B.; Piasecki, M.
2008-12-01
This paper aims to present the development of an integrated hydrological model which involves functionalities of digital watershed processing, online data retrieval, hydrologic simulation and post-event analysis. The proposed system is intended to work as a back end to the CUAHSI HIS cyberinfrastructure developments. As a first step into developing this system, a physics-based distributed hydrologic model PIHM (Penn State Integrated Hydrologic Model) is wrapped into OpenMI(Open Modeling Interface and Environment ) environment so as to seamlessly interact with OpenMI compliant meteorological models. The graphical user interface is being developed from the openGIS application called MapWindows which permits functionality expansion through the addition of plug-ins. . Modules required to set up through the GUI workboard include those for retrieving meteorological data from existing database or meteorological prediction models, obtaining geospatial data from the output of digital watershed processing, and importing initial condition and boundary condition. They are connected to the OpenMI compliant PIHM to simulate rainfall-runoff processes and includes a module for automatically displaying output after the simulation. Online databases are accessed through the WaterOneFlow web services, and the retrieved data are either stored in an observation database(OD) following the schema of Observation Data Model(ODM) in case for time series support, or a grid based storage facility which may be a format like netCDF or a grid-based-data database schema . Specific development steps include the creation of a bridge to overcome interoperability issue between PIHM and the ODM, as well as the embedding of TauDEM (Terrain Analysis Using Digital Elevation Models) into the model. This module is responsible for developing watershed and stream network using digital elevation models. Visualizing and editing geospatial data is achieved by the usage of MapWinGIS, an ActiveX control developed by MapWindow team. After applying to the practical watershed, the performance of the model can be tested by the post-event analysis module.
NASA Astrophysics Data System (ADS)
Ercan, A.; Kavvas, M. L.; Ishida, K.; Chen, Z. Q.; Amin, M. Z. M.; Shaaban, A. J.
2017-12-01
Impacts of climate change on the hydrologic processes under future climate change conditions were assessed over various watersheds of Peninsular Malaysia by means of a coupled regional climate and physically-based hydrology model that utilized an ensemble of future climate change projections. An ensemble of 15 different future climate realizations from coarse resolution global climate models' (GCMs) projections for the 21st century were dynamically downscaled to 6 km resolution over Peninsular Malaysia by a regional numerical climate model, which was then coupled with the watershed hydrology model WEHY through the atmospheric boundary layer over the selected watersheds of Peninsular Malaysia. Hydrologic simulations were carried out at hourly increments and at hillslope-scale in order to assess the impacts of climate change on the water balances and flooding conditions at the selected watersheds during the 21st century. The coupled regional climate and hydrology model was simulated for a duration of 90 years for each of the 15 realizations. It is demonstrated that the increase in mean monthly flows due to the impact of expected climate change during 2040-2100 is statistically significant at the selected watersheds. Furthermore, the flood frequency analyses for the selected watersheds indicate an overall increasing trend in the second half of the 21st century.
VERIFICATION OF THE HYDROLOGIC EVALUATION OF LANDFILL PERFORMANCE (HELP) MODEL USING FIELD DATA
The report describes a study conducted to verify the Hydrologic Evaluation of Landfill Performance (HELP) computer model using existing field data from a total of 20 landfill cells at 7 sites in the United States. Simulations using the HELP model were run to compare the predicted...
USDA-ARS?s Scientific Manuscript database
Various computer models, ranging from simple to complex, have been developed to simulate hydrology and water quality from field to watershed scales. However, many users are uncertain about which model to choose when estimating water quantity and quality conditions in a watershed. This study compared...
NASA Astrophysics Data System (ADS)
da Silva, Felipe das Neves Roque; Alves, José Luis Drummond; Cataldi, Marcio
2018-03-01
This paper aims to validate inflow simulations concerning the present-day climate at Água Vermelha Hydroelectric Plant (AVHP—located on the Grande River Basin) based on the Soil Moisture Accounting Procedure (SMAP) hydrological model. In order to provide rainfall data to the SMAP model, the RegCM regional climate model was also used working with boundary conditions from the MIROC model. Initially, present-day climate simulation performed by RegCM model was analyzed. It was found that, in terms of rainfall, the model was able to simulate the main patterns observed over South America. A bias correction technique was also used and it was essential to reduce mistakes related to rainfall simulation. Comparison between rainfall simulations from RegCM and MIROC showed improvements when the dynamical downscaling was performed. Then, SMAP, a rainfall-runoff hydrological model, was used to simulate inflows at Água Vermelha Hydroelectric Plant. After calibration with observed rainfall, SMAP simulations were evaluated in two different periods from the one used in calibration. During calibration, SMAP captures the inflow variability observed at AVHP. During validation periods, the hydrological model obtained better results and statistics with observed rainfall. However, in spite of some discrepancies, the use of simulated rainfall without bias correction captured the interannual flow variability. However, the use of bias removal in the simulated rainfall performed by RegCM brought significant improvements to the simulation of natural inflows performed by SMAP. Not only the curve of simulated inflow became more similar to the observed inflow, but also the statistics improved their values. Improvements were also noticed in the inflow simulation when the rainfall was provided by the regional climate model compared to the global model. In general, results obtained so far prove that there was an added value in rainfall when regional climate model was compared to global climate model and that data from regional models must be bias-corrected so as to improve their results.
NASA Astrophysics Data System (ADS)
Baroni, Gabriele; Zink, Matthias; Kumar, Rohini; Samaniego, Luis; Attinger, Sabine
2017-04-01
The advances in computer science and the availability of new detailed data-sets have led to a growing number of distributed hydrological models applied to finer and finer grid resolutions for larger and larger catchment areas. It was argued, however, that this trend does not necessarily guarantee better understanding of the hydrological processes or it is even not necessary for specific modelling applications. In the present study, this topic is further discussed in relation to the soil spatial heterogeneity and its effect on simulated hydrological state and fluxes. To this end, three methods are developed and used for the characterization of the soil heterogeneity at different spatial scales. The methods are applied at the soil map of the upper Neckar catchment (Germany), as example. The different soil realizations are assessed regarding their impact on simulated state and fluxes using the distributed hydrological model mHM. The results are analysed by aggregating the model outputs at different spatial scales based on the Representative Elementary Scale concept (RES) proposed by Refsgaard et al. (2016). The analysis is further extended in the present study by aggregating the model output also at different temporal scales. The results show that small scale soil variabilities are not relevant when the integrated hydrological responses are considered e.g., simulated streamflow or average soil moisture over sub-catchments. On the contrary, these small scale soil variabilities strongly affect locally simulated states and fluxes i.e., soil moisture and evapotranspiration simulated at the grid resolution. A clear trade-off is also detected by aggregating the model output by spatial and temporal scales. Despite the scale at which the soil variabilities are (or are not) relevant is not universal, the RES concept provides a simple and effective framework to quantify the predictive capability of distributed models and to identify the need for further model improvements e.g., finer resolution input. For this reason, the integration in this analysis of all the relevant input factors (e.g., precipitation, vegetation, geology) could provide a strong support for the definition of the right scale for each specific model application. In this context, however, the main challenge for a proper model assessment will be the correct characterization of the spatio- temporal variability of each input factor. Refsgaard, J.C., Højberg, A.L., He, X., Hansen, A.L., Rasmussen, S.H., Stisen, S., 2016. Where are the limits of model predictive capabilities?: Representative Elementary Scale - RES. Hydrol. Process. doi:10.1002/hyp.11029
NASA Astrophysics Data System (ADS)
KIM, J.; Smith, M. B.; Koren, V.; Salas, F.; Cui, Z.; Johnson, D.
2017-12-01
The National Oceanic and Atmospheric Administration (NOAA)-National Weather Service (NWS) developed the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) framework as an initial step towards spatially distributed modeling at River Forecast Centers (RFCs). Recently, the NOAA/NWS worked with the National Center for Atmospheric Research (NCAR) to implement the National Water Model (NWM) for nationally-consistent water resources prediction. The NWM is based on the WRF-Hydro framework and is run at a 1km spatial resolution and 1-hour time step over the contiguous United States (CONUS) and contributing areas in Canada and Mexico. In this study, we compare streamflow simulations from HL-RDHM and WRF-Hydro to observations from 279 USGS stations. For streamflow simulations, HL-RDHM is run on 4km grids with the temporal resolution of 1 hour for a 5-year period (Water Years 2008-2012), using a priori parameters provided by NOAA-NWS. The WRF-Hydro streamflow simulations for the same time period are extracted from NCAR's 23 retrospective run of the NWM (version 1.0) over CONUS based on 1km grids. We choose 279 USGS stations which are relatively less affected by dams or reservoirs, in the domains of six different RFCs. We use the daily average values of simulations and observations for the convenience of comparison. The main purpose of this research is to evaluate how HL-RDHM and WRF-Hydro perform at USGS gauge stations. We compare daily time-series of observations and both simulations, and calculate the error values using a variety of error functions. Using these plots and error values, we evaluate the performances of HL-RDHM and WRF-Hydro models. Our results show a mix of model performance across geographic regions.
NASA Astrophysics Data System (ADS)
Regina, J. A.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Cheng, Y.; Zhu, J.
2017-12-01
Preferential flow paths (PFP) resulting from biotic and abiotic factors contribute significantly to the generation of runoff in moist lowland tropical watersheds. Flow through PFPs represents the dominant mechanism by which land use choices affect hydrological behavior. The relative influence of PFP varies depending upon land-use management practices. Assessing the possible effects of land-use and landcover change on flows, and other ecosystem services, in the humid tropics partially depends on adequate simulation of PFP across different land-uses. Currently, 5% of global trade passes through the Panama Canal, which is supplied with fresh water from the Panama Canal Watershed. A third set of locks, recently constructed, are expected to double the capacity of the Canal. We incorporated explicit simulation of PFPs in to the ADHydro HPC distributed hydrological model to simulate the effects of land-use and landcover change due to land management incentives on water resources availability in the Panama Canal Watershed. These simulations help to test hypotheses related to the effectiveness of various proposed payments for ecosystem services schemes. This presentation will focus on hydrological model formulation and performance in an HPC environment.
Ensemble Bayesian forecasting system Part I: Theory and algorithms
NASA Astrophysics Data System (ADS)
Herr, Henry D.; Krzysztofowicz, Roman
2015-05-01
The ensemble Bayesian forecasting system (EBFS), whose theory was published in 2001, is developed for the purpose of quantifying the total uncertainty about a discrete-time, continuous-state, non-stationary stochastic process such as a time series of stages, discharges, or volumes at a river gauge. The EBFS is built of three components: an input ensemble forecaster (IEF), which simulates the uncertainty associated with random inputs; a deterministic hydrologic model (of any complexity), which simulates physical processes within a river basin; and a hydrologic uncertainty processor (HUP), which simulates the hydrologic uncertainty (an aggregate of all uncertainties except input). It works as a Monte Carlo simulator: an ensemble of time series of inputs (e.g., precipitation amounts) generated by the IEF is transformed deterministically through a hydrologic model into an ensemble of time series of outputs, which is next transformed stochastically by the HUP into an ensemble of time series of predictands (e.g., river stages). Previous research indicated that in order to attain an acceptable sampling error, the ensemble size must be on the order of hundreds (for probabilistic river stage forecasts and probabilistic flood forecasts) or even thousands (for probabilistic stage transition forecasts). The computing time needed to run the hydrologic model this many times renders the straightforward simulations operationally infeasible. This motivates the development of the ensemble Bayesian forecasting system with randomization (EBFSR), which takes full advantage of the analytic meta-Gaussian HUP and generates multiple ensemble members after each run of the hydrologic model; this auxiliary randomization reduces the required size of the meteorological input ensemble and makes it operationally feasible to generate a Bayesian ensemble forecast of large size. Such a forecast quantifies the total uncertainty, is well calibrated against the prior (climatic) distribution of predictand, possesses a Bayesian coherence property, constitutes a random sample of the predictand, and has an acceptable sampling error-which makes it suitable for rational decision making under uncertainty.
Application of remote sensing to hydrology. [for the formulation of watershed behavior models
NASA Technical Reports Server (NTRS)
Ambaruch, R.; Simmons, J. W.
1973-01-01
Streamflow forecasting and hydrologic modelling are considered in a feasibility assessment of using the data produced by remote observation from space and/or aircraft to reduce the time and expense normally involved in achieving the ability to predict the hydrological behavior of an ungaged watershed. Existing watershed models are described, and both stochastic and parametric techniques are discussed towards the selection of a suitable simulation model. Technical progress and applications are reported and recommendations are made for additional research.
Banta, J. Ryan; Ockerman, Darwin J.
2014-01-01
Suspended sediment in rivers and streams can play an important role in ecological health of rivers and estuaries and consequently is an important issue for water-resource managers. To better understand suspended-sediment loads and transport in a watershed, the U.S. Geological Survey (USGS), in cooperation with the San Antonio River Authority, developed a Hydrological Simulation Program—FORTRAN model to simulate hydrologic conditions and suspended-sediment loads during 2000–12 for four watersheds, which comprise the overall study area in the San Antonio River Basin (hereinafter referred to as the “USGS–2014 model”). The study area consists of approximately 2,150 square miles encompassing parts of Bexar, Guadalupe, Wilson, Karnes, DeWitt, Goliad, Victoria, and Refugio Counties. The USGS–2014 model was calibrated for hydrology and suspended sediment for 2006–12. Overall, model-fit statistics and graphic evaluations from the calibration and testing periods provided multiple lines of evidence indicating that the USGS–2014 model simulations of hydrologic and suspended-sediment conditions were mostly “good” to “very good.” Model simulation results indicated that approximately 1,230 tons per day of suspended sediment exited the study area and were delivered to the Guadalupe River during 2006–12, of which approximately 62 percent originated upstream from the study area. Sample data and simulated model results indicate that most of the suspended-sediment load in the study area consisted of silt- and clay-sized particles (less than 0.0625 millimeters). The Cibolo Creek watershed was the largest contributor of suspended sediment from the study area. For the entire study area, open/developed land and cropland exhibited the highest simulated soil erosion rates; however, the largest contributions of sediment (by land-cover type) were pasture and forest/rangeland/shrubland, which together composed approximately 80 percent of the land cover of the study area and generated about 70 percent of the suspended-sediment load from the study area.
NASA Astrophysics Data System (ADS)
Li, W.; Su, Y.; Harmon, T. C.; Guo, Q.
2013-12-01
Light Detection and Ranging (lidar) is an optical remote sensing technology that measures properties of scattered light to find range and/or other information of a distant object. Due to its ability to generate 3-dimensional data with high spatial resolution and accuracy, lidar technology is being increasingly used in ecology, geography, geology, geomorphology, seismology, remote sensing, and atmospheric physics. In this study we construct a 3-dimentional (3D) radiative transfer model (RTM) using lidar data to simulate the spatial distribution of solar radiation (direct and diffuse) on the surface of water and mountain forests. The model includes three sub-models: a light model simulating the light source, a sensor model simulating the camera, and a scene model simulating the landscape. We use ground-based and airborne lidar data to characterize the 3D structure of the study area, and generate a detailed 3D scene model. The interactions between light and object are simulated using the Monte Carlo Ray Tracing (MCRT) method. A large number of rays are generated from the light source. For each individual ray, the full traveling path is traced until it is absorbed or escapes from the scene boundary. By locating the sensor at different positions and directions, we can simulate the spatial distribution of solar energy at the ground, vegetation and water surfaces. These outputs can then be incorporated into meteorological drivers for hydrologic and energy balance models to improve our understanding of hydrologic processes and ecosystem functions.
Regan, R. Steve; Niswonger, Richard G.; Markstrom, Steven L.; Barlow, Paul M.
2015-10-02
The spin-up simulation should be run for a sufficient length of time necessary to establish antecedent conditions throughout a model domain. Each GSFLOW application can require different lengths of time to account for the hydrologic stresses to propagate through a coupled groundwater and surface-water system. Typically, groundwater hydrologic processes require many years to come into equilibrium with dynamic climate and other forcing (or stress) data, such as precipitation and well pumping, whereas runoff-dominated surface-water processes respond relatively quickly. Use of a spin-up simulation can substantially reduce execution-time requirements for applications where the time period of interest is small compared to the time for hydrologic memory; thus, use of the restart option can be an efficient strategy for forecast and calibration simulations that require multiple simulations starting from the same day.
NASA Astrophysics Data System (ADS)
Malek, Keyvan; Stöckle, Claudio; Chinnayakanahalli, Kiran; Nelson, Roger; Liu, Mingliang; Rajagopalan, Kirti; Barik, Muhammad; Adam, Jennifer C.
2017-08-01
Food supply is affected by a complex nexus of land, atmosphere, and human processes, including short- and long-term stressors (e.g., drought and climate change, respectively). A simulation platform that captures these complex elements can be used to inform policy and best management practices to promote sustainable agriculture. We have developed a tightly coupled framework using the macroscale variable infiltration capacity (VIC) hydrologic model and the CropSyst agricultural model. A mechanistic irrigation module was also developed for inclusion in this framework. Because VIC-CropSyst combines two widely used and mechanistic models (for crop phenology, growth, management, and macroscale hydrology), it can provide realistic and hydrologically consistent simulations of water availability, crop water requirements for irrigation, and agricultural productivity for both irrigated and dryland systems. This allows VIC-CropSyst to provide managers and decision makers with reliable information on regional water stresses and their impacts on food production. Additionally, VIC-CropSyst is being used in conjunction with socioeconomic models, river system models, and atmospheric models to simulate feedback processes between regional water availability, agricultural water management decisions, and land-atmosphere interactions. The performance of VIC-CropSyst was evaluated on both regional (over the US Pacific Northwest) and point scales. Point-scale evaluation involved using two flux tower sites located in agricultural fields in the US (Nebraska and Illinois). The agreement between recorded and simulated evapotranspiration (ET), applied irrigation water, soil moisture, leaf area index (LAI), and yield indicated that, although the model is intended to work on regional scales, it also captures field-scale processes in agricultural areas.
Simulated hydrologic response to climate change during the 21st century in New Hampshire
Bjerklie, David M.; Sturtevant, Luke P.
2018-01-24
The U.S. Geological Survey, in cooperation with the New Hampshire Department of Environmental Services and the Department of Health and Human Services, has developed a hydrologic model to assess the effects of short- and long-term climate change on hydrology in New Hampshire. This report documents the model and datasets developed by using the model to predict how climate change will affect the hydrologic cycle and provide data that can be used by State and local agencies to identify locations that are vulnerable to the effects of climate change in areas across New Hampshire. Future hydrologic projections were developed from the output of five general circulation models for two future climate scenarios. The scenarios are based on projected future greenhouse gas emissions and estimates of land-use and land-cover change within a projected global economic framework. An evaluation of the possible effect of projected future temperature on modeling of evapotranspiration is summarized to address concerns regarding the implications of the future climate on model parameters that are based on climate variables. The results of the model simulations are hydrologic projections indicating increasing streamflow across the State with large increases in streamflow during winter and early spring and general decreases during late spring and summer. Wide spatial variability in changes to groundwater recharge is projected, with general decreases in the Connecticut River Valley and at high elevations in the northern part of the State and general increases in coastal and lowland areas of the State. In general, total winter snowfall is projected to decrease across the State, but there is a possibility of increasing snow in some locations, particularly during November, February, and March. The simulated future changes in recharge and snowfall vary by watershed across the State. This means that each area of the State could experience very different changes, depending on topography or other factors. Therefore, planning for infrastructure and public safety needs to be flexible in order to address the range of possible outcomes indicated by the various model simulations. The absolute magnitude and timing of the daily streamflows, especially the larger floods, are not considered to be reliably simulated compared to changes in frequency and duration of daily streamflows and changes in accumulated monthly and seasonal streamflow volumes. Simulated current and future streamflow, groundwater recharge, and snowfall datasets include simulated data derived from the five general circulation models used in this study for a current reference time period and two future time periods. Average monthly streamflow time series datasets are provided for 27 streamgages in New Hampshire. Fourteen of the 27 streamgages associated with daily streamflow time series showed a good calibration. Average monthly groundwater recharge and snowfall time series for the same reference time period and two future time periods are also provided for each of the 467 hydrologic response units that compose the model.
NASA Astrophysics Data System (ADS)
Tobin, K. J.; Bennett, M. E.
2008-05-01
The Cimarron River Basin (3110 sq km) between Dodge and Guthrie, Oklahoma is located in northern Oklahoma and was used as a test bed to compare the hydrological model performance associated with different methods of precipitation quantification. The Soil and Water Assessment Tool (SWAT) was selected for this project, which is a comprehensive model that, besides quantifying watershed hydrology, can simulate water quality as well as nutrient and sediment loading within stream reaches. An advantage of this location is the extensive monitoring of MET parameters (precipitation, temperature, relative humidity, wind speed, solar radiation) afforded by the Oklahoma Mesonet, which has been documented to improve the performance of SWAT. The utility of TRMM 3B42 and NEXRAD Stage III data in supporting the hydrologic modeling of Cimarron River Basin is demonstrated. Minor adjustments to selected model parameters were made to make parameter values more realistic based on results from previous studies and information and to more realistically simulate base flow. Significantly, no ad hoc adjustments to major parameters such as Curve Number or Available Soil Water were made and robust simulations were obtained. TRMM and NEXRAD data are aggregated into an average daily estimate of precipitation for each TRMM grid cell (0.25 degree X 0.25 degree). Preliminary simulation of stream flow (year 2004 to 2006) in the Cimarron River Basin yields acceptable monthly results with very little adjustment of model parameters using TRMM 3B42 precipitation data (mass balance error = 3 percent; Monthly Nash-Sutcliffe efficiency coefficients (NS) = 0.77). However, both Oklahoma Mesonet rain gauge (mass balance error = 13 percent; Monthly NS = 0.91; Daily NS = 0.64) and NEXRAD Stage III data (mass balance error = -5 percent; Monthly NS = 0.95; Daily NS = 0.69) produces superior simulations even at a sub-monthly time scale; daily results are time averaged over a three day period. Note that all types of precipitation data perform better than a synthetic precipitation dataset generated using a weather simulator (mass balance error = 12 percent; Monthly NS = 0.40). Our study again documents that merged precipitation satellite products, such as TRMM 3B42, can support semi-distributed hydrologic modeling at the watershed scale. However, apparently additional work is required to improve TRMM precipitation retrievals over land to generate a product that yields more robust hydrological simulations especially at finer time scales. Additionally, ongoing work in this basin will compare TRMM results with stream flow model results generated using CMORPH precipitation estimates. Finally, in the future we plan to use simulated, semi-distributed soil moisture values determined by SWAT for comparison with gridded soil moisture estimates from TRMM-TMI that should provide further validation of our modeling efforts.
NASA Astrophysics Data System (ADS)
Devendran, A. A.; Lakshmanan, G.
2014-11-01
Data quality for GIS processing and analysis is becoming an increased concern due to the accelerated application of GIS technology for problem solving and decision making roles. Uncertainty in the geographic representation of the real world arises as these representations are incomplete. Identification of the sources of these uncertainties and the ways in which they operate in GIS based representations become crucial in any spatial data representation and geospatial analysis applied to any field of application. This paper reviews the articles on the various components of spatial data quality and various uncertainties inherent in them and special focus is paid to two fields of application such as Urban Simulation and Hydrological Modelling. Urban growth is a complicated process involving the spatio-temporal changes of all socio-economic and physical components at different scales. Cellular Automata (CA) model is one of the simulation models, which randomly selects potential cells for urbanisation and the transition rules evaluate the properties of the cell and its neighbour. Uncertainty arising from CA modelling is assessed mainly using sensitivity analysis including Monte Carlo simulation method. Likewise, the importance of hydrological uncertainty analysis has been emphasized in recent years and there is an urgent need to incorporate uncertainty estimation into water resources assessment procedures. The Soil and Water Assessment Tool (SWAT) is a continuous time watershed model to evaluate various impacts of land use management and climate on hydrology and water quality. Hydrological model uncertainties using SWAT model are dealt primarily by Generalized Likelihood Uncertainty Estimation (GLUE) method.
Modelling past hydrology of an interfluve area in the Campine region (NE Belgium)
NASA Astrophysics Data System (ADS)
Leterme, Bertrand; Beerten, Koen; Gedeon, Matej; Vandersteen, Katrijn
2015-04-01
This study aims at hydrological model verification of a small lowland interfluve area (18.6 km²) in NE Belgium, for conditions that are different than today. We compare the current state with five reference periods in the past (AD 1500, 1770, 1854, 1909 and 1961) representing important stages of landscape evolution in the study area. Historical information and proxy data are used to derive conceptual model features and boundary conditions specific to each period: topography, surface water geometry (canal, drains and lakes), land use, soils, vegetation and climate. The influence of landscape evolution on the hydrological cycle is assessed using numerical simulations of a coupled unsaturated zone - groundwater model (HYDRUS-MODFLOW). The induced hydrological changes are assessed in terms of groundwater level, recharge, evapotranspiration, and surface water discharge. HYDRUS-MODFLOW coupling allows including important processes such as the groundwater contribution to evapotranspiration. Major land use change occurred between AD 1854 and 1909, with about 41% of the study area being converted from heath to coniferous forest, together with the development of a drainage network. Results show that this led to a significant decrease of groundwater recharge and lowering of the groundwater table. A limitation of the study lies in the comparison of simulated past hydrology with appropriate palaeo-records. Examples are given as how some indicators (groundwater head, swamp zones) can be used to tend to model validation. Quantifying the relative impact of land use and climate changes requires running sensitivity simulations where the models using alternative land use are run with the climate forcing of other periods. A few examples of such sensitivity runs are presented in order to compare the influence of land use and climate change on the study area hydrology.
A two-step sensitivity analysis for hydrological signatures in Jinhua River Basin, East China
NASA Astrophysics Data System (ADS)
Pan, S.; Fu, G.; Chiang, Y. M.; Xu, Y. P.
2016-12-01
Owing to model complexity and large number of parameters, calibration and sensitivity analysis are difficult processes for distributed hydrological models. In this study, a two-step sensitivity analysis approach is proposed for analyzing the hydrological signatures in Jinhua River Basin, East China, using the Distributed Hydrology-Soil-Vegetation Model (DHSVM). A rough sensitivity analysis is firstly conducted to obtain preliminary influential parameters via Analysis of Variance. The number of parameters was greatly reduced from eighteen-three to sixteen. Afterwards, the sixteen parameters are further analyzed based on a variance-based global sensitivity analysis, i.e., Sobol's sensitivity analysis method, to achieve robust sensitivity rankings and parameter contributions. Parallel-Computing is applied to reduce computational burden in variance-based sensitivity analysis. The results reveal that only a few number of model parameters are significantly sensitive, including rain LAI multiplier, lateral conductivity, porosity, field capacity, wilting point of clay loam, understory monthly LAI, understory minimum resistance and root zone depths of croplands. Finally several hydrological signatures are used for investigating the performance of DHSVM. Results show that high value of efficiency criteria didn't indicate excellent performance of hydrological signatures. For most samples from Sobol's sensitivity analysis, water yield was simulated very well. However, lowest and maximum annual daily runoffs were underestimated. Most of seven-day minimum runoffs were overestimated. Nevertheless, good performances of the three signatures above still exist in a number of samples. Analysis of peak flow shows that small and medium floods are simulated perfectly while slight underestimations happen to large floods. The work in this study helps to further multi-objective calibration of DHSVM model and indicates where to improve the reliability and credibility of model simulation.
Effects of timber management on the hydrology of wetland forests in the Southern United States
Ge Sun; Steven G. McNulty; James P. Shepard; Devendra M. Amatya; Hans Riekerk; Nicholas B. Comerford; Wayne Skaggs; Lloyd Swift
2001-01-01
The objectives of this paper are to review the hydrologic impacts of various common forest management practices that include harvesting, site preparation, and drainage. Field hydrological data collected during the past 5±10 years from ten forested wetland sites across the southern US are synthesized using various methods including hydrologic simulation models and...
NASA Astrophysics Data System (ADS)
Braakhekke, Maarten; Rebel, Karin; Dekker, Stefan; Smith, Benjamin; Sutanudjaja, Edwin; van Beek, Rens; van Kampenhout, Leo; Wassen, Martin
2017-04-01
In up to 30% of the global land surface ecosystems are potentially influenced by the presence of a shallow groundwater table. In these regions upward water flux by capillary rise increases soil moisture availability in the root zone, which has a strong effect on evapotranspiration, vegetation dynamics, and fluxes of carbon and nitrogen. Most global hydrological models and several land surface models simulate groundwater table dynamics and their effects on land surface processes. However, these models typically have relatively simplistic representation of vegetation and do not consider changes in vegetation type and structure. Dynamic global vegetation models (DGVMs), describe land surface from an ecological perspective, combining detailed description of vegetation dynamics and structure, and biogeochemical processes and are thus more appropriate to simulate the ecological and biogeochemical effects of groundwater interactions. However, currently virtually all DGVMs ignore these effects, assuming that water tables are too deep to affect soil moisture in the root zone. We have implemented a tight coupling between the dynamic global ecosystem model LPJ-GUESS and the global hydrological model PCR-GLOBWB, which explicitly simulates groundwater dynamics. This coupled model allows us to explicitly account for groundwater effects on terrestrial ecosystem processes at global scale. Results of global simulations indicate that groundwater strongly influences fluxes of water, carbon and nitrogen, in many regions, adding up to a considerable effect at the global scale.
Aquatic Contaminant and Mercury Simulation Modules Developed for Hydrologic and Hydraulic Models
2016-07-01
through the food chain. Human health may also be affected by ingesting contaminated water or fish. As a result, the criteria for protecting human...ER D C/ EL T R- 16 -8 Environmental Quality Technology Research Program Aquatic Contaminant and Mercury Simulation Modules Developed...Quality Technology Research Program ERDC/EL TR-16-8 July 2016 Aquatic Contaminant and Mercury Simulation Modules Developed for Hydrologic and
Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)
Atchley, Adam L.; Painter, Scott L.; Harp, Dylan R.; ...
2015-09-01
Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. Thus, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth system models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth system models challenge validation and parameterization of hydrothermal models. A recently developed surface–subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurementsmore » to achieve the goals of constructing a process-rich model based on plausible parameters and to identify fine-scale controls of ALT in ice-wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze–thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g., troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.« less
NASA Astrophysics Data System (ADS)
Saber, M.; Sefelnasr, A.; Yilmaz, K. K.
2015-12-01
Flash flood is a natural hydrological phenomenon which affects many regions of the world. The behavior and effect of this phenomenon is different from one region to the other regions depending on several issues such as climatology and hydrological and topographical conditions at the target regions. Wadi assiut, Egypt as arid environment, and Gumara catchment, Lake Tana, Ethiopia, as humid conditions have been selected for application. The main target of this work is to simulate flash floods at both catchments considering the difference between them on the flash flood behaviors based on the variability of both of them. In order to simulate the flash floods, remote sensing data and a physical-based distributed hydrological model, Hydro-BEAM-WaS (Hydrological River Basin Environmental Assessment Model incorporating Wadi System) have been integrated used in this work. Based on the simulation results of flash floods in these regions, it was found that the time to reach the maximum peak is very short and consequently the warning time is very short as well. It was found that the flash floods starts from zero flow in arid environment, but on the contrary in humid arid, it starts from Base flow which is changeable based on the simulated events. Distribution maps of flash floods showing the vulnerable regions of these selected areas have been developed. Consequently, some mitigation strategies relying on this study have been introduced. The proposed methodology can be applied effectively for flash flood forecasting at different climate regions, however the paucity of observational data.
Improving Permafrost Hydrology Prediction Through Data-Model Integration
NASA Astrophysics Data System (ADS)
Wilson, C. J.; Andresen, C. G.; Atchley, A. L.; Bolton, W. R.; Busey, R.; Coon, E.; Charsley-Groffman, L.
2017-12-01
The CMIP5 Earth System Models were unable to adequately predict the fate of the 16GT of permafrost carbon in a warming climate due to poor representation of Arctic ecosystem processes. The DOE Office of Science Next Generation Ecosystem Experiment, NGEE-Arctic project aims to reduce uncertainty in the Arctic carbon cycle and its impact on the Earth's climate system by improved representation of the coupled physical, chemical and biological processes that drive how much buried carbon will be converted to CO2 and CH4, how fast this will happen, which form will dominate, and the degree to which increased plant productivity will offset increased soil carbon emissions. These processes fundamentally depend on permafrost thaw rate and its influence on surface and subsurface hydrology through thermal erosion, land subsidence and changes to groundwater flow pathways as soil, bedrock and alluvial pore ice and massive ground ice melts. LANL and its NGEE colleagues are co-developing data and models to better understand controls on permafrost degradation and improve prediction of the evolution of permafrost and its impact on Arctic hydrology. The LANL Advanced Terrestrial Simulator was built using a state of the art HPC software framework to enable the first fully coupled 3-dimensional surface-subsurface thermal-hydrology and land surface deformation simulations to simulate the evolution of the physical Arctic environment. Here we show how field data including hydrology, snow, vegetation, geochemistry and soil properties, are informing the development and application of the ATS to improve understanding of controls on permafrost stability and permafrost hydrology. The ATS is being used to inform parameterizations of complex coupled physical, ecological and biogeochemical processes for implementation in the DOE ACME land model, to better predict the role of changing Arctic hydrology on the global climate system. LA-UR-17-26566.
Fusing Unmanned Aerial Vehicle Imagery with High Resolution Hydrologic Modeling (Invited)
NASA Astrophysics Data System (ADS)
Vivoni, E. R.; Pierini, N.; Schreiner-McGraw, A.; Anderson, C.; Saripalli, S.; Rango, A.
2013-12-01
After decades of development and applications, high resolution hydrologic models are now common tools in research and increasingly used in practice. More recently, high resolution imagery from unmanned aerial vehicles (UAVs) that provide information on land surface properties have become available for civilian applications. Fusing the two approaches promises to significantly advance the state-of-the-art in terms of hydrologic modeling capabilities. This combination will also challenge assumptions on model processes, parameterizations and scale as land surface characteristics (~0.1 to 1 m) may now surpass traditional model resolutions (~10 to 100 m). Ultimately, predictions from high resolution hydrologic models need to be consistent with the observational data that can be collected from UAVs. This talk will describe our efforts to develop, utilize and test the impact of UAV-derived topographic and vegetation fields on the simulation of two small watersheds in the Sonoran and Chihuahuan Deserts at the Santa Rita Experimental Range (Green Valley, AZ) and the Jornada Experimental Range (Las Cruces, NM). High resolution digital terrain models, image orthomosaics and vegetation species classification were obtained from a fixed wing airplane and a rotary wing helicopter, and compared to coarser analyses and products, including Light Detection and Ranging (LiDAR). We focus the discussion on the relative improvements achieved with UAV-derived fields in terms of terrain-hydrologic-vegetation analyses and summer season simulations using the TIN-based Real-time Integrated Basin Simulator (tRIBS) model. Model simulations are evaluated at each site with respect to a high-resolution sensor network consisting of six rain gauges, forty soil moisture and temperature profiles, four channel runoff flumes, a cosmic-ray soil moisture sensor and an eddy covariance tower over multiple summer periods. We also discuss prospects for the fusion of high resolution models with novel observations from UAVs, including synthetic aperture radar and multispectral imagery.
Spatially Explicit Simulation of Mesotopographic Controls on Peatland Hydrology and Carbon Fluxes
NASA Astrophysics Data System (ADS)
Sonnentag, O.; Chen, J. M.; Roulet, N. T.
2006-12-01
A number of field carbon flux measurements, paleoecological records, and model simulations have acknowledged the importance of northern peatlands in terrestrial carbon cycling and methane emissions. An important parameter in peatlands that influences both net primary productivity, the net gain of carbon through photosynthesis, and decomposition under aerobic and anaerobic conditions, is the position of the water table. Biological and physical processes involved in peatland carbon dynamics and their hydrological controls operate at different spatial scales. The highly variable hydraulic characteristics of the peat profile and the overall shape of the peat body as defined by its surface topography at the mesoscale (104 m2) are of major importance for peatland water table dynamics. Common types of peatlands include bogs with a slightly domed centre. As a result of the convex profile, their water supply is restricted to atmospheric inputs, and water is mainly shed by shallow subsurface flow. From a modelling perspective the influence of mesotopographic controls on peatland hydrology and thus carbon balance requires that process-oriented models that examine the links between peatland hydrology, ecosystem functioning, and climate must incorporate some form of lateral subsurface flow consideration. Most hydrological and ecological modelling studies in complex terrain explicitly account for the topographic controls on lateral subsurface flow through digital elevation models. However, modelling studies in peatlands often employ simple empirical parameterizations of lateral subsurface flow, neglecting the influence of peatlands low relief mesoscale topography. Our objective is to explicitly simulate the mesotopographic controls on peatland hydrology and carbon fluxes using the Boreal Ecosystem Productivity Simulator (BEPS) adapted to northern peatlands. BEPS is a process-oriented ecosystem model in a remote sensing framework that takes into account peatlands multi-layer canopy through vertically stratified mapped leaf area index. Model outputs are validated against multi-year measurements taken at an eddy-covariance flux tower located within Mer Bleue bog, a typical raised bog near Ottawa, Ontario, Canada. Model results for seasonal water table dynamics and evapotranspiration at daily time steps in 2003 are in good agreement with measurements with R2=0.74 and R2=0.79, respectively, and indicate the suitability of our pursued approach.
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.
Multimodel Uncertainty Changes in Simulated River Flows Induced by Human Impact Parameterizations
NASA Technical Reports Server (NTRS)
Liu, Xingcai; Tang, Qiuhong; Cui, Huijuan; Mu, Mengfei; Gerten Dieter; Gosling, Simon; Masaki, Yoshimitsu; Satoh, Yusuke; Wada, Yoshihide
2017-01-01
Human impacts increasingly affect the global hydrological cycle and indeed dominate hydrological changes in some regions. Hydrologists have sought to identify the human-impact-induced hydrological variations via parameterizing anthropogenic water uses in global hydrological models (GHMs). The consequently increased model complexity is likely to introduce additional uncertainty among GHMs. Here, using four GHMs, between-model uncertainties are quantified in terms of the ratio of signal to noise (SNR) for average river flow during 1971-2000 simulated in two experiments, with representation of human impacts (VARSOC) and without (NOSOC). It is the first quantitative investigation of between-model uncertainty resulted from the inclusion of human impact parameterizations. Results show that the between-model uncertainties in terms of SNRs in the VARSOC annual flow are larger (about 2 for global and varied magnitude for different basins) than those in the NOSOC, which are particularly significant in most areas of Asia and northern areas to the Mediterranean Sea. The SNR differences are mostly negative (-20 to 5, indicating higher uncertainty) for basin-averaged annual flow. The VARSOC high flow shows slightly lower uncertainties than NOSOC simulations, with SNR differences mostly ranging from -20 to 20. The uncertainty differences between the two experiments are significantly related to the fraction of irrigation areas of basins. The large additional uncertainties in VARSOC simulations introduced by the inclusion of parameterizations of human impacts raise the urgent need of GHMs development regarding a better understanding of human impacts. Differences in the parameterizations of irrigation, reservoir regulation and water withdrawals are discussed towards potential directions of improvements for future GHM development. We also discuss the advantages of statistical approaches to reduce the between-model uncertainties, and the importance of calibration of GHMs for not only better performances of historical simulations but also more robust and confidential future projections of hydrological changes under a changing environment.
Niswonger, Richard G.; Allander, Kip K.; Jeton, Anne E.
2014-01-01
A terminal lake basin in west-central Nevada, Walker Lake, has undergone drastic change over the past 90 yrs due to upstream water use for agriculture. Decreased inflows to the lake have resulted in 100 km2 decrease in lake surface area and a total loss of fisheries due to salinization. The ecologic health of Walker Lake is of great concern as the lake is a stopover point on the Pacific route for migratory birds from within and outside the United States. Stakeholders, water institutions, and scientists have engaged in collaborative modeling and the development of a decision support system that is being used to develop and analyze management change options to restore the lake. Here we use an integrated management and hydrologic model that relies on state-of-the-art simulation capabilities to evaluate the benefits of using integrated hydrologic models as components of a decision support system. Nonlinear feedbacks among climate, surface-water and groundwater exchanges, and water use present challenges for simulating realistic outcomes associated with management change. Integrated management and hydrologic modeling provides a means of simulating benefits associated with management change in the Walker River basin where drastic changes in the hydrologic landscape have taken place over the last century. Through the collaborative modeling process, stakeholder support is increasing and possibly leading to management change options that result in reductions in Walker Lake salt concentrations, as simulated by the decision support system.
NASA Astrophysics Data System (ADS)
Neill, A. J.; Tetzlaff, D.; Strachan, N.; Soulsby, C.
2016-12-01
The non-linearities of runoff generation processes are strongly influenced by the connectivity of hillslopes and channel networks, particularly where overland flow is an important runoff mechanism. Despite major advances in understanding hydrological connectivity and runoff generation, the role of connectivity in the contamination of potable water supplies by faecal pathogens from grazing animals remains unclear. This is a water quality issue with serious implications for public health. Here, we sought to understand the dynamics of hydrological connectivity, flow paths and linked faecal pathogen transport in a montane catchment in Scotland with high deer populations. We firstly calibrated, within an uncertainty framework, a parsimonious tracer-aided hydrological model to daily discharge and stream isotope data. The model, developed on the basis of past empirical and tracer studies, conceptualises the catchment as three interacting hydrological source areas (dynamic saturation zone, dynamic hillslope, and groundwater) for which water fluxes, water ages and storage-based connectivity can be simulated. We next coupled several faecal indicator organism (FIO; a common indicator of faecal pathogen contamination) behaviour and transport schemes to the robust hydrological models. A further calibration was then undertaken based on the ability of each coupled model to simulate daily FIO concentrations. This gave us a final set of coupled behavioural models from which we explored how in-stream FIO dynamics could be related to the changing connectivity between the three hydrological source areas, flow paths, water ages and consequent dominant runoff generation processes. We found that high levels of FIOs were transient and episodic, and strongly correlated with periods of high connectivity through overland flow. This non-linearity in connectivity and FIO flux was successfully captured within our dynamic, tracer-aided hydrological model.
NASA Astrophysics Data System (ADS)
Pomeroy, J. W.; Fang, X.
2014-12-01
The vast effort in hydrology devoted to parameter calibration as a means to improve model performance assumes that the models concerned are not fundamentally wrong. By focussing on finding optimal parameter sets and ascribing poor model performance to parameter or data uncertainty, these efforts may fail to consider the need to improve models with more intelligent descriptions of hydrological processes. To test this hypothesis, a flexible physically based hydrological model including a full suite of snow hydrology processes as well as warm season, hillslope and groundwater hydrology was applied to Marmot Creek Research Basin, Canadian Rocky Mountains where excellent driving meteorology and basin biophysical descriptions exist. Model parameters were set from values found in the basin or from similar environments; no parameters were calibrated. The model was tested against snow surveys and streamflow observations. The model used algorithms that describe snow redistribution, sublimation and forest canopy effects on snowmelt and evaporative processes that are rarely implemented in hydrological models. To investigate the contribution of these processes to model predictive capability, the model was "falsified" by deleting parameterisations for forest canopy snow mass and energy, blowing snow, intercepted rain evaporation, and sublimation. Model falsification by ignoring forest canopy processes contributed to a large increase in SWE errors for forested portions of the research basin with RMSE increasing from 19 to 55 mm and mean bias (MB) increasing from 0.004 to 0.62. In the alpine tundra portion, removing blowing processes resulted in an increase in model SWE MB from 0.04 to 2.55 on north-facing slopes and -0.006 to -0.48 on south-facing slopes. Eliminating these algorithms degraded streamflow prediction with the Nash Sutcliffe efficiency dropping from 0.58 to 0.22 and MB increasing from 0.01 to 0.09. These results show dramatic model improvements by including snow redistribution and melt processes associated with wind transport and forest canopies. As most hydrological models do not currently include these processes, it is suggested that modellers first improve the realism of model structures before trying to optimise what are inherently inadequate simulations of hydrology.
Bales, Jerad; Fulford, Janice M.; Swain, Eric D.
1997-01-01
A study was conducted to review selected features of the Natural System Model, version 4.3 . The Natural System Model is a regional-scale model that uses recent climatic data and estimates of historic vegetation and topography to simulate pre-canal-drainage hydrologic response in south Florida. Equations used to represent the hydrologic system and the numerical solution of these equations in the model were documented and reviewed. Convergence testing was performed using 1965 input data, and selected other aspects of the model were evaluated.Some conclusions from the evaluation of the Natural System Model include the following observations . Simulations were generally insensitive to the temporal resolution used in the model. However, reduction of the computational cell size from 2-mile by 2-mile to 2/3-mile by 2/3-mile resulted in a decrease in spatial mean ponding depths for October of 0.35 foot for a 3-hour time step.Review of the computer code indicated that there is no limit on the amount of water that can be transferred from the river system to the overland flow system, on the amount of seepage from the river to the ground-water system, on evaporation from the river system, or on evapotranspiration from the overland-flow system . Oscillations of 0.2 foot or less in simulated river stage were identified and attributed to a volume limiting function which is applied in solution of the overland-flow equations. The computation of the resistance coefficient is not consistent with the computation of overland-flow velocity. Ground-water boundary conditions do not always ensure a no-flow condition at the boundary. These inconsistencies had varying degrees of effects on model simulations, and it is likely that simulations longer than 1 year are needed to fully identify effects. However, inconsistencies in model formulations should not be ignored, even if the effects of such errors on model results appear to be small or have not been clearly defined.The Natural System Model can be a very useful tool for estimating pre-drainage hydrologic response in south Florida. The model includes all of the important physical processes needed to simulate a water balance. With a few exceptions, these hydrologic processes are represented in a reasonable manner using empirical, semiempirical, and mechanistic relations . The data sets that have been assembled to represent physical features, and hydrologic and meteorological conditions are quite extensive in their scope.Some suggestions for model application were made. Simulation results from the Natural System Model need to be interpreted on a regional basis, rather than cell by cell. The available evidence suggests that simulated water levels should be interpreted with about a plus or minus 1 foot uncertainty. It is probably not appropriate to use the Natural System Model to estimate pre-drainage discharges (as opposed to hydroperiods and water levels) at a particular location or across a set of adjacent computational cells. All simulated results for computational cells within about 10 miles of the model boundaries have a higher degree of uncertainty than results for the interior of the model domain. It is most appropriate to interpret the Natural System Model simulation results in connection with other available information. Stronger linkages between hydrologic inputs to the Everglades and the ecological response of the system would enhance restoration efforts .
Modeling winter hydrological processes under differing climatic conditions: Modifying WEPP
NASA Astrophysics Data System (ADS)
Dun, Shuhui
Water erosion is a serious and continuous environmental problem worldwide. In cold regions, soil freeze and thaw has great impacts on infiltration and erosion. Rain or snowmelt on a thawing soil can cause severe water erosion. Of equal importance is snow accumulation and snowmelt, which can be the predominant hydrological process in areas of mid- to high latitudes and forested watersheds. Modelers must properly simulate winter processes to adequately represent the overall hydrological outcome and sediment and chemical transport in these areas. Modeling winter hydrology is presently lacking in water erosion models. Most of these models are based on the functional Universal Soil Loss Equation (USLE) or its revised forms, e.g., Revised USLE (RUSLE). In RUSLE a seasonally variable soil erodibility factor (K) was used to account for the effects of frozen and thawing soil. Yet the use of this factor requires observation data for calibration, and such a simplified approach cannot represent the complicated transient freeze-thaw processes and their impacts on surface runoff and erosion. The Water Erosion Prediction Project (WEPP) watershed model, a physically-based erosion prediction software developed by the USDA-ARS, has seen numerous applications within and outside the US. WEPP simulates winter processes, including snow accumulation, snowmelt, and soil freeze-thaw, using an approach based on mass and energy conservation. However, previous studies showed the inadequacy of the winter routines in the WEPP model. Therefore, the objectives of this study were: (1) To adapt a modeling approach for winter hydrology based on mass and energy conservation, and to implement this approach into a physically-oriented hydrological model, such as WEPP; and (2) To assess this modeling approach through case applications to different geographic conditions. A new winter routine was developed and its performance was evaluated by incorporating it into WEPP (v2008.9) and then applying WEPP to four study sites at different spatial scales under different climatic conditions, including experimental plots in Pullman, WA and Morris, MN, two agricultural drainages in Pendleton, OR, and a forest watershed in Mica Creek, ID. The model applications showed promising results, indicating adequacy of the mass- and energy-balance-based approach for winter hydrology simulation.
NASA Astrophysics Data System (ADS)
Khuat Duy, B.; Archambeau, P.; Dewals, B. J.; Erpicum, S.; Pirotton, M.
2009-04-01
Following recurrent inundation problems on the Berwinne catchment, in Belgium, a combined hydrologic and hydrodynamic study has been carried out in order to find adequate solutions for the floods mitigation. Thanks to detailed 2D simulations, the effectiveness of the solutions can be assessed not only in terms of discharge and height reductions in the river, but also with other aspects such as the inundated surfaces reduction and the decrease of inundated buildings and roads. The study is carried out in successive phases. First, the hydrological runoffs are generated using a physically based and spatially distributed multi-layer model solving depth-integrated equations for overland flow, subsurface flow and baseflow. Real floods events are simulated using rainfall series collected at 8 stations (over 20 years of available data). The hydrological inputs are routed through the river network (and through the sewage network if relevant) with the 1D component of the modelling system, which solves the Saint-Venant equations for both free-surface and pressurized flows in a unified way. On the main part of the river, the measured river cross-sections are included in the modelling, and existing structures along the river (such as bridges, sluices or pipes) are modelled explicitely with specific cross sections. Two gauging stations with over 15 years of continuous measurements allow the calibration of both the hydrologic and hydrodynamic models. Second, the flood mitigation solutions are tested in the simulations in the case of an extreme flooding event, and their effects are assessed using detailed 2D simulations on a few selected sensitive areas. The digital elevation model comes from an airborne laser survey with a spatial resolution of 1 point per square metre and is completed in the river bed with a bathymetry interpolated from cross-section data. The upstream discharge is extracted from the 1D simulation for the selected rainfall event. The study carried out with this methodology allowed to assess the suggested solutions with multiple effectiveness criteria and therefore constitutes a very useful support for decision makers.
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.
Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin
Shrestha, M.S.; Artan, Guleid A.; Bajracharya, S.R.; Sharma, R. R.
2008-01-01
In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.
Hydrologic modeling strategy for the Islamic Republic of Mauritania, Africa
Friedel, Michael J.
2008-01-01
The government of Mauritania is interested in how to maintain hydrologic balance to ensure a long-term stable water supply for minerals-related, domestic, and other purposes. Because of the many complicating and competing natural and anthropogenic factors, hydrologists will perform quantitative analysis with specific objectives and relevant computer models in mind. Whereas various computer models are available for studying water-resource priorities, the success of these models to provide reliable predictions largely depends on adequacy of the model-calibration process. Predictive analysis helps us evaluate the accuracy and uncertainty associated with simulated dependent variables of our calibrated model. In this report, the hydrologic modeling process is reviewed and a strategy summarized for future Mauritanian hydrologic modeling studies.
On the deterministic and stochastic use of hydrologic models
Farmer, William H.; Vogel, Richard M.
2016-01-01
Environmental simulation models, such as precipitation-runoff watershed models, are increasingly used in a deterministic manner for environmental and water resources design, planning, and management. In operational hydrology, simulated responses are now routinely used to plan, design, and manage a very wide class of water resource systems. However, all such models are calibrated to existing data sets and retain some residual error. This residual, typically unknown in practice, is often ignored, implicitly trusting simulated responses as if they are deterministic quantities. In general, ignoring the residuals will result in simulated responses with distributional properties that do not mimic those of the observed responses. This discrepancy has major implications for the operational use of environmental simulation models as is shown here. Both a simple linear model and a distributed-parameter precipitation-runoff model are used to document the expected bias in the distributional properties of simulated responses when the residuals are ignored. The systematic reintroduction of residuals into simulated responses in a manner that produces stochastic output is shown to improve the distributional properties of the simulated responses. Every effort should be made to understand the distributional behavior of simulation residuals and to use environmental simulation models in a stochastic manner.
Perkins, S.P.; Sophocleous, M.
1999-01-01
We developed a model code to simulate a watershed's hydrology and the hydraulic response of an interconnected stream-aquifer system, and applied the model code to the Lower Republican River Basin in Kansas. The model code links two well-known computer programs: MODFLOW (modular 3-D flow model), which simulates ground water flow and stream-aquifer interaction; and SWAT (soil water assessment tool), a soil water budget simulator for an agricultural watershed. SWAT represents a basin as a collection of subbasins in terms of soil, land use, and weather data, and simulates each subbasin on a daily basis to determine runoff, percolation, evaporation, irrigation, pond seepages and crop growth. Because SWAT applies a lumped hydrologic model to each subbasin, spatial heterogeneities with respect to factors such as soil type and land use are not resolved geographically, but can instead be represented statistically. For the Republican River Basin model, each combination of six soil types and three land uses, referred to as a hydrologic response unit (HRU), was simulated with a separate execution of SWAT. A spatially weighted average was then taken over these results for each hydrologic flux and time step by a separate program, SWBAVG. We wrote a package for MOD-FLOW to associate each subbasin with a subset of aquifer grid cells and stream reaches, and to distribute the hydrologic fluxes given for each subbasin by SWAT and SWBAVG over MODFLOW's stream-aquifer grid to represent tributary flow, surface and ground water diversions, ground water recharge, and evapotranspiration from ground water. The Lower Republican River Basin model was calibrated with respect to measured ground water levels, streamflow, and reported irrigation water use. The model was used to examine the relative contributions of stream yield components and the impact on stream yield and base flow of administrative measures to restrict irrigation water use during droughts. Model results indicate that tributary flow is the dominant component of stream yield and that reduction of irrigation water use produces a corresponding increase in base flow and stream yield. However, the increase in stream yield resulting from reduced water use does not appear to be of sufficient magnitude to restore minimum desirable streamflows.
Jianbo Cui; Changsheng Li; Carl Trettin
2005-01-01
A comprehensive biogeochemical model, Wetland-DNDC, was applied to analyze the carbon and hydrologic characteristics of forested wetland ecosystem at Minnesota (MN) and Florida (FL) sites. The model simulates the flows of carbon, energy, and water in forested wetlands. Modeled carbon dynamics depends on physiological plant factors, the size of plant pools,...
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...
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...
NASA Astrophysics Data System (ADS)
Stanzel, Philipp; Kling, Harald
2017-04-01
EURO-CORDEX Regional Climate Model (RCM) data are available as result of the latest initiative of the climate modelling community to provide ever improved simulations of past and future climate in Europe. The spatial resolution of the climate models increased from 25 x 25 km in the previous coordinated initiative, ENSEMBLES, to 12 x 12 km in the CORDEX EUR-11 simulations. This higher spatial resolution might yield improved representation of the historic climate, especially in complex mountainous terrain, improving applicability in impact studies. CORDEX scenario simulations are based on Representative Concentration Pathways, while ENSEMBLES applied the SRES greenhouse gas emission scenarios. The new emission scenarios might lead to different projections of future climate. In this contribution we explore these two dimensions of development from ENSEMBLES to CORDEX - representation of the past and projections for the future - in the context of a hydrological climate change impact study for the Danube River. We replicated previous hydrological simulations that used ENSEMBLES data of 21 RCM simulations under SRES A1B emission scenario as meteorological input data (Kling et al. 2012), and now applied CORDEX EUR-11 data of 16 RCM simulations under RCP4.5 and RCP8.5 emission scenarios. The climate variables precipitation and temperature were used to drive a monthly hydrological model of the upper Danube basin upstream of Vienna (100,000 km2). RCM data was bias corrected and downscaled to the scale of hydrological model units. Results with CORDEX data were compared with results with ENSEMBLES data, analysing both the driving meteorological input and the resulting discharge projections. Results with CORDEX data show no general improvement in the accuracy of representing historic climatic features, despite the increase in spatial model resolution. The tendency of ENSEMBLES scenario projections of increasing precipitation in winter and decreasing precipitation in summer is reproduced with the CORDEX RCMs, albeit with slightly higher precipitation in the CORDEX data. The distinct pattern of future change in discharge seasonality - increasing winter discharge and decreasing summer discharge - is confirmed with the new CORDEX data, with a range of projections very similar to the range projected by the ENSEMBLES RCMs. References: Kling, H., Fuchs, M., Paulin, M. 2012. Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios. Journal of Hydrology 424-425, 264-277.
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.
The validity of flow approximations when simulating catchment-integrated flash floods
NASA Astrophysics Data System (ADS)
Bout, B.; Jetten, V. G.
2018-01-01
Within hydrological models, flow approximations are commonly used to reduce computation time. The validity of these approximations is strongly determined by flow height, flow velocity and the spatial resolution of the model. In this presentation, the validity and performance of the kinematic, diffusive and dynamic flow approximations are investigated for use in a catchment-based flood model. Particularly, the validity during flood events and for varying spatial resolutions is investigated. The OpenLISEM hydrological model is extended to implement both these flow approximations and channel flooding based on dynamic flow. The flow approximations are used to recreate measured discharge in three catchments, among which is the hydrograph of the 2003 flood event in the Fella river basin. Furthermore, spatial resolutions are varied for the flood simulation in order to investigate the influence of spatial resolution on these flow approximations. Results show that the kinematic, diffusive and dynamic flow approximation provide least to highest accuracy, respectively, in recreating measured discharge. Kinematic flow, which is commonly used in hydrological modelling, substantially over-estimates hydrological connectivity in the simulations with a spatial resolution of below 30 m. Since spatial resolutions of models have strongly increased over the past decades, usage of routed kinematic flow should be reconsidered. The combination of diffusive or dynamic overland flow and dynamic channel flooding provides high accuracy in recreating the 2003 Fella river flood event. Finally, in the case of flood events, spatial modelling of kinematic flow substantially over-estimates hydrological connectivity and flow concentration since pressure forces are removed, leading to significant errors.
Impact of length of calibration period on the apex model output simulation performance
USDA-ARS?s Scientific Manuscript database
Datasets from long-term monitoring sites that can be used for calibration and validation of hydrologic and water quality models are rare due to resource constraints. As a result, hydrologic and water quality models are calibrated and, when possible, validated using short-term measured data. A previo...
Mohammad Safeeq; Guillaume S. Mauger; Gordon E. Grant; Ivan Arismendi; Alan F. Hamlet; Se-Yeun Lee
2014-01-01
Assessing uncertainties in hydrologic models can improve accuracy in predicting future streamflow. Here, simulated streamflows using the Variable Infiltration Capacity (VIC) model at coarse (1/16°) and fine (1/120°) spatial resolutions were evaluated against observed streamflows from 217 watersheds. In...
NASA Astrophysics Data System (ADS)
Chegwidden, O.; Nijssen, B.; Mao, Y.; Rupp, D. E.
2016-12-01
The Columbia River Basin (CRB) in the United States' Pacific Northwest (PNW) is highly regulated for hydropower generation, flood control, fish survival, irrigation and navigation. Historically it has had a hydrologic regime characterized by winter precipitation in the form of snow, followed by a spring peak in streamflow from snowmelt. Anthropogenic climate change is expected to significantly alter this regime, causing changes to streamflow timing and volume. While numerous hydrologic studies have been conducted across the CRB, the impact of methodological choices in hydrologic modeling has not been as heavily investigated. To better understand their impact on the spread in modeled projections of hydrological change, we ran simulations involving permutations of a variety of methodological choices. We used outputs from ten global climate models (GCMs) and two representative concentration pathways from the Intergovernmental Panel on Climate Change's Fifth Assessment Report. After downscaling the GCM output using three different techniques we forced the Variable Infiltration Capacity (VIC) model and the Precipitation Runoff Modeling System (PRMS), both implemented at 1/16th degree ( 5 km) for the period 1950-2099. For the VIC model, we used three independently-derived parameter sets. We will show results from the range of simulations, both in the form of basin-wide spatial analyses of hydrologic variables and through analyses of changes in streamflow at selected sites throughout the CRB. We will then discuss the differences in sensitivities to climate change seen among the projections, paying particular attention to differences in projections from the hydrologic models and different parameter sets.
Overview of a simple model describing variation of dissolved organic carbon in an upland catchment
Boyer, Elizabeth W.; Hornberger, George M.; Bencala, Kenneth E.; McKnight, Diane M.
1996-01-01
Hydrological mechanisms controlling the variation of dissolved organic carbon (DOC) were investigated in the Deer Creek catchment located near Montezuma, CO. Patterns of DOC in streamflow suggested that increased flows through the upper soil horizon during snowmelt are responsible for flushing this DOC-enriched interstitial water to the streams. We examined possible hydrological mechanisms to explain the observed variability of DOC in Deer Creek by first simulating the hydrological response of the catchment using TOPMODEL and then routing the predicted flows through a simple model that accounted for temporal changes in DOC. Conceptually the DOC model can be taken to represent a terrestrial (soil) reservoir in which DOC builds up during low flow periods and is flushed out when infiltrating meltwaters cause the water table to rise into this “reservoir”. Concentrations of DOC measured in the upper soil and in streamflow were compared to model simulations. The simulated DOC response provides a reasonable reproduction of the observed dynamics of DOC in the stream at Deer Creek.
NASA Astrophysics Data System (ADS)
Zhu, Honglei; Li, Ying; Huang, Yanwei; Li, Yingchen; Hou, Cuicui; Shi, Xiaoliang
2018-07-01
Satellite-based precipitation estimates with high spatial and temporal resolution and large areal coverage have provided hydrologists a potential alternative source for hydrological applications since the last few years, especially for ungauged regions. This study evaluates five satellite-based precipitation datasets, namely, Fengyun, TRMM 3B42, TRMM 3B42RT, CMORPH_BLD and CMORPH_RAW, against gauge observations for streamflow simulation with a distributed hydrological model (SWAT) over the Huifa river basin, Northeast China. Results show that, by comparing the statistical indices (MA, M5P, STDE, ME, BIAS and CC) and inter-annual precipitation, it is demonstrated that Fengyun TRMM 3B42 and CMORPH_BLD show better agreement with gauge precipitation data than CMORPH_RAW and TRMM 3B42RT. When the SWAT model for each dataset calibrated and validated individually, satisfactory model performances (defined as: NS > 0.5) are achieved at daily scale for Fengyun, TRMM 3B42 and gauge-driven model, and very good performances (defined as: NS > 0.75) are achieved at monthly scale for Fengyun and gauge-driven model, respectively. The CMORPH_BLD forced daily simulations also yield higher values of NS and R2 than CMORPH_RAW and TRMM 3B42RT at daily and monthly step. From the uncertainty results, variations of P-factor values and frequency distribution curves of NS suggest that the simulation uncertainty increase when operating the Fengyun, 3B42RT, CMORPH_BLD and CMORPH_RAW-driven model with best fitted parameters for rain gauge SWAT model. The results also indicate that the influence of parameter uncertainty on model simulation results may be greater than the effect of input data accuracy. It is noted that uncertainty analysis is necessary to evaluate the hydrological applications of satellite-based precipitation datasets.
Richard MT Webb; David L. Parkhurst
2016-01-01
The U.S. Geological Surveyâs (USGS) Water, Energy, and Biogeochemical Model (WEBMOD) was used to simulate hydrology, weathering, and isotopic fractionation in the Andrews Creek watershed in Rocky Mountain National Park, Colorado and the Icacos River watershed in the Luquillo Experimental Forest, Puerto Rico. WEBMOD includes hydrologic modules derived from the USGS...
Hydrologic Effects of Global Climate Change on a Large Drained Pine Forest
Devendra M. Amatya; Ge Sun; R. W. Skaggs; G. M Chescheir; J. E. Nettles
2006-01-01
A simulation study using a watershed scale forest hydrology model (DRAINWAT) was conducted to evaluate potential effects of climate change on the hydrology of a 3,000 ha managed pine forest in coastal North Carolina. The model was first validated with a five-year (1996-2000) data set fro111 the study site and then run with 50-years (1951-00) of historic weather data...
NASA Astrophysics Data System (ADS)
Endalamaw, A. M.; Bolton, W. R.; Young, J. M.; Morton, D.; Hinzman, L. D.
2013-12-01
The sub-arctic environment can be characterized as being located in the zone of discontinuous permafrost. Although the distribution of permafrost is site specific, it dominates many of the hydrologic and ecologic responses and functions including vegetation distribution, stream flow, soil moisture, and storage processes. In this region, the boundaries that separate the major ecosystem types (deciduous dominated and coniferous dominated ecosystems) as well as permafrost (permafrost verses non-permafrost) occur over very short spatial scales. One of the goals of this research project is to improve parameterizations of meso-scale hydrologic models in this environment. Using the Caribou-Poker Creeks Research Watershed (CPCRW) as the test area, simulations of the headwater catchments of varying permafrost and vegetation distributions were performed. CPCRW, located approximately 50 km northeast of Fairbanks, Alaska, is located within the zone of discontinuous permafrost and the boreal forest ecosystem. The Variable Infiltration Capacity (VIC) model was selected as the hydrologic model. In CPCRW, permafrost and coniferous vegetation is generally found on north facing slopes and valley bottoms. Permafrost free soils and deciduous vegetation is generally found on south facing slopes. In this study, hydrologic simulations using fine scale vegetation and soil parameterizations - based upon slope and aspect analysis at a 50 meter resolution - were conducted. Simulations were also conducted using downscaled vegetation from the Scenarios Network for Alaska and Arctic Planning (SNAP) (1 km resolution) and soil data sets from the Food and Agriculture Organization (FAO) (approximately 9 km resolution). Preliminary simulation results show that soil and vegetation parameterizations based upon fine scale slope/aspect analysis increases the R2 values (0.5 to 0.65 in the high permafrost (53%) basin; 0.43 to 0.56 in the low permafrost (2%) basin) relative to parameterization based on coarse scale data. These results suggest that using fine resolution parameterizations can be used to improve meso-scale hydrological modeling in this region.
NASA Astrophysics Data System (ADS)
Green, T. R.; Erksine, R. H.; David, O.; Ascough, J. C., II; Kipka, H.; Lloyd, W. J.; McMaster, G. S.
2015-12-01
Water movement and storage within a watershed may be simulated at different spatial resolutions of land areas or hydrological response units (HRUs). Here, effects of HRU size on simulated soil water and surface runoff are tested using the AgroEcoSystem-Watershed (AgES-W) model with three different resolutions of HRUs. We studied a 56-ha agricultural watershed in northern Colorado, USA farmed primarily under a wheat-fallow rotation. The delineation algorithm was based upon topography (surface flow paths), land use (crop management strips and native grass), and mapped soil units (three types), which produced HRUs that follow the land use and soil boundaries. AgES-W model parameters that control surface and subsurface hydrology were calibrated using simulated daily soil moisture at different landscape positions and depths where soil moisture was measured hourly and averaged up to daily values. Parameter sets were both uniform and spatially variable with depth and across the watershed (5 different calibration approaches). Although forward simulations were computationally efficient (less than 1 minute each), each calibration required thousands of model runs. Execution of such large jobs was facilitated by using the Object Modeling System with the Cloud Services Innovation Platform to manage four virtual machines on a commercial web service configured with a total of 64 computational cores and 120 GB of memory. Results show how spatially distributed and averaged soil moisture and runoff at the outlet vary with different HRU delineations. The results will help guide HRU delineation, spatial resolution and parameter estimation methods for improved hydrological simulations in this and other semi-arid agricultural watersheds.
The western arctic linkage experiment (WALE): overview and synthesis
A.D. McGuire; J. Walsh; J.S. Kimball; J.S. Clein; S.E. Euskirdhen; S. Drobot; U.C. Herzfeld; J. Maslanik; R.B. Lammers; M.A. Rawlins; C.J. Vorosmarty; T.S. Rupp; W. Wu; M. Calef
2008-01-01
The primary goal of the Western Arctic Linkage Experiment (WALE) was to better understand uncertainties of simulated hydrologic and ecosystem dynamics of the western Arctic in the context of 1) uncertainties in the data available to drive the models and 2) different approaches to simulating regional hydrology and ecosystem dynamics. Analyses of datasets on climate...
NASA Astrophysics Data System (ADS)
Brauer, Claudia; Overeem, Aart; Uijlenhoet, Remko
2015-04-01
Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of differences in rainfall estimates on discharge simulations in a lowland catchment by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in the Hupsel Brook catchment. We used two automatic rain gauges with hourly resolution, located inside the catchment (the base run) and 30 km northeast. Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. Traditionally, the precipitation research community places emphasis on quantifying spatial errors and uncertainty, but for hydrological applications, temporal errors and uncertainty should be quantified as well. Its memory makes the hydrologic system sensitive to missed or badly timed rainfall events, but also emphasizes the effect of a bias in rainfall estimates. Systematic underestimation of rainfall by the uncorrected operational radar product leads to very dry model states and an increasing underestimation of discharge. Using the rain gauge 30 km northeast of the catchment yields good results for climatological studies, but not for forecasting individual floods. Simulating discharge using the maps derived from microwave link data and the gauge-adjusted radar product yields good results for both events and climatological studies. This indicates that these products can be used in catchments without gauges in or near the catchment. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. Improving rainfall measurements can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.
Empirical tools for simulating salinity in the estuaries in Everglades National Park, Florida
NASA Astrophysics Data System (ADS)
Marshall, F. E.; Smith, D. T.; Nickerson, D. M.
2011-12-01
Salinity in a shallow estuary is affected by upland freshwater inputs (surface runoff, stream/canal flows, groundwater), atmospheric processes (precipitation, evaporation), marine connectivity, and wind patterns. In Everglades National Park (ENP) in South Florida, the unique Everglades ecosystem exists as an interconnected system of fresh, brackish, and salt water marshes, mangroves, and open water. For this effort a coastal aquifer conceptual model of the Everglades hydrologic system was used with traditional correlation and regression hydrologic techniques to create a series of multiple linear regression (MLR) salinity models from observed hydrologic, marine, and weather data. The 37 ENP MLR salinity models cover most of the estuarine areas of ENP and produce daily salinity simulations that are capable of estimating 65-80% of the daily variability in salinity depending upon the model. The Root Mean Squared Error is typically about 2-4 salinity units, and there is little bias in the predictions. However, the absolute error of a model prediction in the nearshore embayments and the mangrove zone of Florida Bay may be relatively large for a particular daily simulation during the seasonal transitions. Comparisons show that the models group regionally by similar independent variables and salinity regimes. The MLR salinity models have approximately the same expected range of simulation accuracy and error as higher spatial resolution salinity models.
Hydrologic and water quality sensitivity to climate and land ...
This page describes a current EPA ORD project. No project report or other download is available at this time. Please see the section Next Steps below for a timeline of anticipated products of this work. Background: Projected changes in climate during the next century could cause or contribute to increased flooding, drought, water quality degradation, and ecosystem impairment. The effects of climate change in different watersheds will vary due to regional differences in climate change, physiographic setting, and interaction with land-use, pollutant sources, and water management in different locations. EPA is conducting watershed modeling to develop hydrologic and water quality change scenarios for 20 relatively large U.S. watersheds. Watershed modeling will be conducted using the Hydrologic Simulation Program-FORTRAN (HSPF) and Soil Water Assessment Tool (SWAT) watershed models. Study areas range from about 10,000-15,000 square miles in size, and will cover nearly every ecoregion in the United States and a range of hydro-climatic conditions. A range of hydrologic and water quality endpoints will be determined for each watershed simulation. Endpoints will be selected to inform upon a range of stream flow, water quality, aquatic ecosystem, and EPA program management goals and targets. Model simulations will be conducted to evaluate a range of projected future (2040-2070) changes in climate and land-use. Simulations will include baseline conditions,
NASA Astrophysics Data System (ADS)
Marsh, C.; Pomeroy, J. W.; Wheater, H. S.
2017-12-01
Accurate management of water resources is necessary for social, economic, and environmental sustainability worldwide. In locations with seasonal snowcovers, the accurate prediction of these water resources is further complicated due to frozen soils, solid-phase precipitation, blowing snow transport, and snowcover-vegetation-atmosphere interactions. Complex process interactions and feedbacks are a key feature of hydrological systems and may result in emergent phenomena, i.e., the arising of novel and unexpected properties within a complex system. One example is the feedback associated with blowing snow redistribution, which can lead to drifts that cause locally-increased soil moisture, thus increasing plant growth that in turn subsequently impacts snow redistribution, creating larger drifts. Attempting to simulate these emergent behaviours is a significant challenge, however, and there is concern that process conceptualizations within current models are too incomplete to represent the needed interactions. An improved understanding of the role of emergence in hydrological systems often requires high resolution distributed numerical hydrological models that incorporate the relevant process dynamics. The Canadian Hydrological Model (CHM) provides a novel tool for examining cold region hydrological systems. Key features include efficient terrain representation, allowing simulations at various spatial scales, reduced computational overhead, and a modular process representation allowing for an alternative-hypothesis framework. Using both physics-based and conceptual process representations sourced from long term process studies and the current cold regions literature allows for comparison of process representations and importantly, their ability to produce emergent behaviours. Examining the system in a holistic, process-based manner can hopefully derive important insights and aid in development of improved process representations.
NASA Astrophysics Data System (ADS)
Hoch, J. M.; Neal, J. C.; Baart, F.; Van Beek, L. P.; Winsemius, H.; Bates, P. D.; Bierkens, M. F.
2017-12-01
Currently, many approaches to provide detailed flood hazard and risk estimates are built upon specific hydrologic or hydrodynamic model routines. By applying these routines in stand-alone mode important processes can however not accurately be described. For instance, global hydrologic models run at coarse spatial resolution, not supporting the detailed simulation of flood hazard. Hydrodynamic models excel in the computations of open water flow dynamics, but dependent on specific runoff or observed discharge as input. In most cases hydrodynamic models are forced at the boundaries and thus cannot account for water sources within the model domain, limiting the simulation of inundation dynamics to reaches fed by upstream boundaries. Recently, Hoch et al. (HESS, 2017) coupled PCR-GLOBWB (PCR) with the hydrodynamic model Delft3D Flexible Mesh (DFM). By means of the Basic Model Interface both models were connected on a cell-by-cell basis, allowing for spatially explicit coupling. Model results showed that discharge simulations can profit from model coupling compared to stand-alone runs. As model results of a coupled simulation depend on the quality of the models, it would be worthwhile to allow a suite of models to be coupled. To facilitate this, we present GLOFRIM, a globally applicable framework for integrated hydrologic-hydrodynamic inundation modelling. In the current version coupling between PCR and both DFM and LISFLOOD-FP (LFP) can be established (Hoch et al., GMDD, 2017). First results show that differences between both hydrodynamic models are present in the timing of peak discharge which is most likely due to differences in channel-floodplain interactions and bathymetry processing. Having benchmarked inundation extent, LFP and DFM agree for around half of the inundated area which is attributable to variations in grid size. Results also indicate that, despite using identical boundary conditions and forcing, the schematization itself as well as internal processes can still greatly influence results. In general, the application of GLOFRIM brings several advantages. For example, with PCR being a global model, it is possible to reduce the dependency of observation data for discharge boundaries, and benchmarking of hydrodynamic models is greatly facilitated by employing identical hydrologic forcing.
Simulated CONUS Flash Flood Climatologies from Distributed Hydrologic Models
NASA Astrophysics Data System (ADS)
Flamig, Z.; Gourley, J. J.; Vergara, H. J.; Kirstetter, P. E.; Hong, Y.
2016-12-01
This study will describe a CONUS flash flood climatology created over the period from 2002 through 2011. The MRMS reanalysis precipitation dataset was used as forcing into the Ensemble Framework For Flash Flood Forecasting (EF5). This high resolution 1-sq km 5-minute dataset is ideal for simulating flash floods with a distributed hydrologic model. EF5 features multiple water balance components including SAC-SMA, CREST, and a hydrophobic model all coupled with kinematic wave routing. The EF5/SAC-SMA and EF5/CREST water balance schemes were used for the creation of dual flash flood climatologies based on the differing water balance principles. For the period from 2002 through 2011 the daily maximum streamflow, unit streamflow, and time of peak streamflow was stored along with the minimum soil moisture. These variables are used to describe the states of the soils right before a flash flood event and the peak streamflow that was simulated during the flash flood event. The results will be shown, compared and contrasted. The resulting model simulations will be verified on basins less than 1,000-sq km with USGS gauges to ensure the distributed hydrologic models are reliable. The results will also be compared spatially to Storm Data flash flood event observations to judge the degree of agreement between the simulated climatologies and observations.
Potential effects of climate change on ground water in Lansing, Michigan
Croley, T.E.; Luukkonen, C.L.
2003-01-01
Computer simulations involving general circulation models, a hydrologic modeling system, and a ground water flow model indicate potential impacts of selected climate change projections on ground water levels in the Lansing, Michigan, area. General circulation models developed by the Canadian Climate Centre and the Hadley Centre generated meteorology estimates for 1961 through 1990 (as a reference condition) and for the 20 years centered on 2030 (as a changed climate condition). Using these meteorology estimates, the Great Lakes Environmental Research Laboratory's hydrologic modeling system produced corresponding period streamflow simulations. Ground water recharge was estimated from the streamflow simulations and from variables derived from the general circulation models. The U.S. Geological Survey developed a numerical ground water flow model of the Saginaw and glacial aquifers in the Tri-County region surrounding Lansing, Michigan. Model simulations, using the ground water recharge estimates, indicate changes in ground water levels. Within the Lansing area, simulated ground water levels in the Saginaw aquifer declined under the Canadian predictions and increased under the Hadley.
NASA Astrophysics Data System (ADS)
Hoch, Jannis M.; Neal, Jeffrey C.; Baart, Fedor; van Beek, Rens; Winsemius, Hessel C.; Bates, Paul D.; Bierkens, Marc F. P.
2017-10-01
We here present GLOFRIM, a globally applicable computational framework for integrated hydrological-hydrodynamic modelling. GLOFRIM facilitates spatially explicit coupling of hydrodynamic and hydrologic models and caters for an ensemble of models to be coupled. It currently encompasses the global hydrological model PCR-GLOBWB as well as the hydrodynamic models Delft3D Flexible Mesh (DFM; solving the full shallow-water equations and allowing for spatially flexible meshing) and LISFLOOD-FP (LFP; solving the local inertia equations and running on regular grids). The main advantages of the framework are its open and free access, its global applicability, its versatility, and its extensibility with other hydrological or hydrodynamic models. Before applying GLOFRIM to an actual test case, we benchmarked both DFM and LFP for a synthetic test case. Results show that for sub-critical flow conditions, discharge response to the same input signal is near-identical for both models, which agrees with previous studies. We subsequently applied the framework to the Amazon River basin to not only test the framework thoroughly, but also to perform a first-ever benchmark of flexible and regular grids on a large-scale. Both DFM and LFP produce comparable results in terms of simulated discharge with LFP exhibiting slightly higher accuracy as expressed by a Kling-Gupta efficiency of 0.82 compared to 0.76 for DFM. However, benchmarking inundation extent between DFM and LFP over the entire study area, a critical success index of 0.46 was obtained, indicating that the models disagree as often as they agree. Differences between models in both simulated discharge and inundation extent are to a large extent attributable to the gridding techniques employed. In fact, the results show that both the numerical scheme of the inundation model and the gridding technique can contribute to deviations in simulated inundation extent as we control for model forcing and boundary conditions. This study shows that the presented computational framework is robust and widely applicable. GLOFRIM is designed as open access and easily extendable, and thus we hope that other large-scale hydrological and hydrodynamic models will be added. Eventually, more locally relevant processes would be captured and more robust model inter-comparison, benchmarking, and ensemble simulations of flood hazard on a large scale would be allowed for.
NASA Astrophysics Data System (ADS)
Anghileri, D.; Kaelin, A.; Peleg, N.; Fatichi, S.; Molnar, P.; Roques, C.; Longuevergne, L.; Burlando, P.
2017-12-01
Hydrological modeling in poorly gauged basins can benefit from the use of remote sensing datasets although there are challenges associated with the mismatch in spatial and temporal scales between catchment scale hydrological models and remote sensing products. We model the hydrological processes and long-term water budget of the Lake Turkana catchment, a transboundary basin between Kenya and Ethiopia, by integrating several remote sensing products into a spatially distributed and physically explicit model, Topkapi-ETH. Lake Turkana is the world largest desert lake draining a catchment of 145'500 km2. It has three main contributing rivers: the Omo river, which contributes most of the annual lake inflow, the Turkwel river, and the Kerio rivers, which contribute the remaining part. The lake levels have shown great variations in the last decades due to long-term climate fluctuations and the regulation of three reservoirs, Gibe I, II, and III, which significantly alter the hydrological seasonality. Another large reservoir is planned and may be built in the next decade, generating concerns about the fate of Lake Turkana in the long run because of this additional anthropogenic pressure and increasing evaporation driven by climate change. We consider different remote sensing datasets, i.e., TRMM-V7 for precipitation, MERRA-2 for temperature, as inputs to the spatially distributed hydrological model. We validate the simulation results with other remote sensing datasets, i.e., GRACE for total water storage anomalies, GLDAS-NOAH for soil moisture, ERA-Interim/Land for surface runoff, and TOPEX/Poseidon for satellite altimetry data. Results highlight how different remote sensing products can be integrated into a hydrological modeling framework accounting for their relative uncertainties. We also carried out simulations with the artificial reservoirs planned in the north part of the catchment and without any reservoirs, to assess their impacts on the catchment hydrological regime and the Lake Turkana level variability.
Evaluating hydrological model performance using information theory-based metrics
USDA-ARS?s Scientific Manuscript database
The accuracy-based model performance metrics not necessarily reflect the qualitative correspondence between simulated and measured streamflow time series. The objective of this work was to use the information theory-based metrics to see whether they can be used as complementary tool for hydrologic m...
Information and complexity measures for hydrologic model evaluation
USDA-ARS?s Scientific Manuscript database
Hydrological models are commonly evaluated through the residual-based performance measures such as the root-mean square error or efficiency criteria. Such measures, however, do not evaluate the degree of similarity of patterns in simulated and measured time series. The objective of this study was to...
Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization
Xi, Maolong; Lu, Dan; Gui, Dongwei; ...
2016-11-27
Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less
Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization
NASA Astrophysics Data System (ADS)
Xi, Maolong; Lu, Dan; Gui, Dongwei; Qi, Zhiming; Zhang, Guannan
2017-01-01
Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so as to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.
Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xi, Maolong; Lu, Dan; Gui, Dongwei
Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less
On the Representation of Subgrid Microtopography Effects in Process-based Hydrologic Models
NASA Astrophysics Data System (ADS)
Jan, A.; Painter, S. L.; Coon, E. T.
2017-12-01
Increased availability of high-resolution digital elevation are enabling process-based hydrologic modeling on finer and finer scales. However, spatial variability in surface elevation (microtopography) exists below the scale of a typical hyper-resolution grid cell and has the potential to play a significant role in water retention, runoff, and surface/subsurface interactions. Though the concept of microtopographic features (depressions, obstructions) and the associated implications on flow and discharge are well established, representing those effects in watershed-scale integrated surface/subsurface hydrology models remains a challenge. Using the complex and coupled hydrologic environment of the Arctic polygonal tundra as an example, we study the effects of submeter topography and present a subgrid model parameterized by small-scale spatial heterogeneities for use in hyper-resolution models with polygons at a scale of 15-20 meters forming the surface cells. The subgrid model alters the flow and storage terms in the diffusion wave equation for surface flow. We compare our results against sub-meter scale simulations (acts as a benchmark for our simulations) and hyper-resolution models without the subgrid representation. The initiation of runoff in the fine-scale simulations is delayed and the recession curve is slowed relative to simulated runoff using the hyper-resolution model with no subgrid representation. Our subgrid modeling approach improves the representation of runoff and water retention relative to models that ignore subgrid topography. We evaluate different strategies for parameterizing subgrid model and present a classification-based method to efficiently move forward to larger landscapes. This work was supported by the Interoperable Design of Extreme-scale Application Software (IDEAS) project and the Next-Generation Ecosystem Experiments-Arctic (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the DOE Office of Science.
NASA Astrophysics Data System (ADS)
Lecourt, Grégoire; Revuelto, Jesús; Morin, Samuel; Zin, Isabella; Lafaysse, Matthieu; Condom, Thomas; Six, Delphine; Vionnet, Vincent; Charrois, Luc; Dumont, Marie; Gottardi, Frédéric; Laarman, Olivier; Coulaud, Catherine; Esteves, Michel; Lebel, Thierry; Vincent, Christian
2016-04-01
In Alpine catchments, the hydrological response to meteorological events is highly influenced by the precipitation phase (liquid or solid) and by snow and ice melt. It is thus necessary to simulate accurately the snowpack evolution and its spatial distribution to perform relevant hydrological simulations. This work is focused on the upper Arve Valley (Western Alps). This 205 km2 catchment has large glaciated areas (roughly 32% of the study area) and covers a large range of elevations (1000-4500 m a.s.l.). Snow presence is significant year-round. The area is also characterized by steep terrain and strong vegetation heterogeneity. Modelling hydrological processes in such a complex catchment is therefore challenging. The detailed ISBA land surface model (including the Crocus snowpack scheme) has been applied to the study area using a topography based discretization (classifying terrain by aspect, elevation, slope and presence of glacier). The meteorological forcing used to run the simulations is the reanalysis issued from the SAFRAN model which assimilates meteorological observations from the Meteo-France networks. Conceptual reservoirs with calibrated values of emptying parameters are used to represent the underground water storage. This approach has been tested to simulate the discharge on the Arve catchment and three sub-catchments over 1990-2015. The simulations were evaluated with respect to observed water discharges for several headwaters with varying glaciated areas. They allow to quantify the relative contribution of rainfall, snow and ice melt to the hydrological regime of the basin. Additionally, we present a detailed analysis of several particular flood events. For these events, the ability of the model to correctly represent the catchment behaviour is investigated, looking particularly to the relevance of the simulated snowpack. Particularly, its spatial distribution is evaluated using MODIS snow cover maps, punctual snowpack observations and summer glacier mass balance estimations.
Martin, Gary R.; Zarriello, Phillip J.; Shipp, Allison A.
2001-01-01
Rainfall, streamflow, and water-quality data collected in the Chenoweth Run Basin during February 1996?January 1998, in combination with the available historical sampling data, were used to characterize hydrologic conditions and to develop and calibrate a Hydrological Simulation Program?Fortran (HSPF) model for continuous simulation of rainfall, streamflow, suspended-sediment, and total-orthophosphate (TPO4) transport relations. Study results provide an improved understanding of basin hydrology and a hydrologic-modeling framework with analytical tools for use in comprehensive waterresource planning and management. Chenoweth Run Basin, encompassing 16.5 mi2 in suburban eastern Jefferson County, Kentucky, contains expanding urban development, particularly in the upper third of the basin. Historical water-quality problems have interfered with designated aquatic-life and recreation uses in the stream main channel (approximately 9 mi in length) and have been attributed to organic enrichment, nutrients, metals, and pathogens in urban runoff and wastewater inflows. Hydrologic conditions in Jefferson County are highly varied. In the Chenoweth Run Basin, as in much of the eastern third of the county, relief is moderately sloping to steep. Also, internal drainage in pervious areas is impeded by the shallow, fine-textured subsoils that contain abundant silts and clays. Thus, much of the precipitation here tends to move rapidly as overland flow and (or) shallow subsurface flow (interflow) to the stream channels. Data were collected at two streamflowgaging stations, one rain gage, and four waterquality- sampling sites in the basin. Precipitation, streamflow, and, consequently, constituent loads were above normal during the data-collection period of this study. Nonpoint sources contributed the largest portion of the sediment loads. However, the three wastewatertreatment plants (WWTP?s) were the source of the majority of estimated total phosphorus (TP) and TPO4 transport downstream from the WWTP?s. HSPF, a hydrologic model capable of simulating mixed-land-use basins, includes land surface, subsurface, and instream waterquantity- and water-quality-modeling components. The HSPF model was used to represent several important hydrologic features of the Chenoweth Run Basin including (1) numerous small lakes and ponds, through which approximately 25 percent of the basin drains; (2) potential seasonal ground-waterseepage losses in stream channels; (3) contributions from WWTP effluents and bypass flows; and (4) the transport and transformations of sediments and nutrients. The HSPF model was calibrated and verified for flow simulation on the basis of measured total, annual, seasonal, monthly, daily, hourly, and 5-minute-interval storm discharge data. The occurrence of numerous storms during the study period permitted a splitsample procedure to be used for a model verification on the basis of storm volumes and peaks. Total simulated and observed discharge during the model calibration period differed by approximately -5.4 percent at the upper gaging station and 3.1 percent at the lower station. The model results for the total and annual water balances were classified as very good on the basis of the calibration criteria reported in other modeling studies. The model had correlation coefficients ranging from 0.89 to 0.98 for hourly to monthly mean flows, respectively. The coefficients of model-fit efficiency for daily and monthly discharge simulations were near the excellent range (exceeding 0.97). However, the model was calibrated for a comparatively short 24-month period during which flows were above normal. Increased model error might be expected during an extended period of nearnormal flows. The model was calibrated for simulation of sediment and TPO4 transport. The simulated mean-annual load (over 24 months) ranged from -33 to -28 percent of the estimated sediment load and within +/- 1 percent of the estimated TPO4 load at the two streamflow-gaging s
Simulation of streamflow in the McTier Creek watershed, South Carolina
Feaster, Toby D.; Golden, Heather E.; Odom, Kenneth R.; Lowery, Mark A.; Conrads, Paul; Bradley, Paul M.
2010-01-01
The McTier Creek watershed is located in the Sand Hills ecoregion of South Carolina and is a small catchment within the Edisto River Basin. Two watershed hydrology models were applied to the McTier Creek watershed as part of a larger scientific investigation to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River Basin. The two models are the topography-based hydrological model (TOPMODEL) and the grid-based mercury model (GBMM). TOPMODEL uses the variable-source area concept for simulating streamflow, and GBMM uses a spatially explicit modified curve-number approach for simulating streamflow. The hydrologic output from TOPMODEL can be used explicitly to simulate the transport of mercury in separate applications, whereas the hydrology output from GBMM is used implicitly in the simulation of mercury fate and transport in GBMM. The modeling efforts were a collaboration between the U.S. Geological Survey and the U.S. Environmental Protection Agency, National Exposure Research Laboratory. Calibrations of TOPMODEL and GBMM were done independently while using the same meteorological data and the same period of record of observed data. Two U.S. Geological Survey streamflow-gaging stations were available for comparison of observed daily mean flow with simulated daily mean flow-station 02172300, McTier Creek near Monetta, South Carolina, and station 02172305, McTier Creek near New Holland, South Carolina. The period of record at the Monetta gage covers a broad range of hydrologic conditions, including a drought and a significant wet period. Calibrating the models under these extreme conditions along with the normal flow conditions included in the record enhances the robustness of the two models. Several quantitative assessments of the goodness of fit between model simulations and the observed daily mean flows were done. These included the Nash-Sutcliffe coefficient of model-fit efficiency index, Pearson's correlation coefficient, the root mean square error, the bias, and the mean absolute error. In addition, a number of graphical tools were used to assess how well the models captured the characteristics of the observed data at the Monetta and New Holland streamflow-gaging stations. The graphical tools included temporal plots of simulated and observed daily mean flows, flow-duration curves, single-mass curves, and various residual plots. The results indicated that TOPMODEL and GBMM generally produced simulations that reasonably capture the quantity, variability, and timing of the observed streamflow. For the periods modeled, the total volume of simulated daily mean flows as compared to the total volume of the observed daily mean flow from TOPMODEL was within 1 to 5 percent, and the total volume from GBMM was within 1 to 10 percent. A noticeable characteristic of the simulated hydrographs from both models is the complexity of balancing groundwater recession and flow at the streamgage when flows peak and recede rapidly. However, GBMM results indicate that groundwater recession, which affects the receding limb of the hydrograph, was more difficult to estimate with the spatially explicit curve number approach. Although the purpose of this report is not to directly compare both models, given the characteristics of the McTier Creek watershed and the fact that GBMM uses the spatially explicit curve number approach as compared to the variable-source-area concept in TOPMODEL, GBMM was able to capture the flow characteristics reasonably well.
NASA Astrophysics Data System (ADS)
Trettin, C.; Dai, Z.; Amatya, D. M.
2014-12-01
Long-term climatic and hydrologic observations on the Santee Experimental Forest in the lower coastal plain of South Carolina were used to estimate long-term changes in hydrology and forest carbon dynamics for a pair of first-order watersheds. Over 70 years of climate data indicated that warming in this forest area in the last decades was faster than the global mean; 35+ years of hydrologic records showed that forest ecosystem succession three years following Hurricane Hugo caused a substantial change in the ratio of runoff to precipitation. The change in this relationship between the paired watersheds was attributed to altered evapotranspiration processes caused by greater abundance of pine in the treatment watershed and regeneration of the mixed hardwood-pine forest on the reference watershed. The long-term records and anomalous observations are highly valuable for reliable calibration and validation of hydrological and biogeochemical models capturing the effects of climate variability. We applied the hydrological model MIKESHE that showed that runoff and water table level are sensitive to global warming, and that the sustained warming trends can be expected to decrease stream discharge and lower the mean water table depth. The spatially-explicit biogeochemical model Forest-DNDC, validated using biomass measurements from the watersheds, was used to assess carbon dynamics in response to high resolution hydrologic observation data and simulation results. The simulations showed that the long-term spatiotemporal carbon dynamics, including biomass and fluxes of soil carbon dioxide and methane were highly regulated by disturbance regimes, climatic conditions and water table depth. The utility of linked-modeling framework demonstrated here to assess biogeochemical responses at the watershed scale suggests applications for assessing the consequences of climate change within an urbanizing forested landscape. The approach may also be applicable for validating large-scale models.
NASA Technical Reports Server (NTRS)
Bosilovich, Michael G.; Yang, Runhua; Houser, Paul R.
1998-01-01
Land surface hydrology for the Off-line Land-surface GEOS Analysis (OLGA) system and Goddard Earth Observing System (GEOS-1) Data Assimilation System (DAS) has been examined using a river routing model. The GEOS-1 DAS land-surface parameterization is very simple, using an energy balance prediction of surface temperature and prescribed soil water. OLGA uses near-surface atmospheric data from the GEOS-1 DAS to drive a more comprehensive parameterization of the land-surface physics. The two global systems are evaluated using a global river routing model. The river routing model uses climatologic surface runoff from each system to simulate the river discharge from global river basins, which can be compared to climatologic river discharge. Due to the soil hydrology, the OLGA system shows a general improvement in the simulation of river discharge compared to the GEOS-1 DAS. Snowmelt processes included in OLGA also have a positive effect on the annual cycle of river discharge and source runoff. Preliminary tests of a coupled land-atmosphere model indicate improvements to the hydrologic cycle compared to the uncoupled system. The river routing model has provided a useful tool in the evaluation of the GCM hydrologic cycle, and has helped quantify the influence of the more advanced land surface 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.
Hay, L.E.; Clark, M.P.
2003-01-01
This paper examines the hydrologic model performance in three snowmelt-dominated basins in the western United States to dynamically- and statistically downscaled output from the National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP). Runoff produced using a distributed hydrologic model is compared using daily precipitation and maximum and minimum temperature timeseries derived from the following sources: (1) NCEP output (horizontal grid spacing of approximately 210 km); (2) dynamically downscaled (DDS) NCEP output using a Regional Climate Model (RegCM2, horizontal grid spacing of approximately 52 km); (3) statistically downscaled (SDS) NCEP output; (4) spatially averaged measured data used to calibrate the hydrologic model (Best-Sta) and (5) spatially averaged measured data derived from stations located within the area of the RegCM2 model output used for each basin, but excluding Best-Sta set (All-Sta). In all three basins the SDS-based simulations of daily runoff were as good as runoff produced using the Best-Sta timeseries. The NCEP, DDS, and All-Sta timeseries were able to capture the gross aspects of the seasonal cycles of precipitation and temperature. However, in all three basins, the NCEP-, DDS-, and All-Sta-based simulations of runoff showed little skill on a daily basis. When the precipitation and temperature biases were corrected in the NCEP, DDS, and All-Sta timeseries, the accuracy of the daily runoff simulations improved dramatically, but, with the exception of the bias-corrected All-Sta data set, these simulations were never as accurate as the SDS-based simulations. This need for a bias correction may be somewhat troubling, but in the case of the large station-timeseries (All-Sta), the bias correction did indeed 'correct' for the change in scale. It is unknown if bias corrections to model output will be valid in a future climate. Future work is warranted to identify the causes for (and removal of) systematic biases in DDS simulations, and improve DDS simulations of daily variability in local climate. Until then, SDS based simulations of runoff appear to be the safer downscaling choice.
Li, Zhaofu; Liu, Hongyu; Luo, Chuan; Li, Yan; Li, Hengpeng; Pan, Jianjun; Jiang, Xiaosan; Zhou, Quansuo; Xiong, Zhengqin
2015-05-01
The Hydrological Simulation Program-Fortran (HSPF), which is a hydrological and water-quality computer model that was developed by the United States Environmental Protection Agency, was employed to simulate runoff and nutrient export from a typical small watershed in a hilly eastern monsoon region of China. First, a parameter sensitivity analysis was performed to assess how changes in the model parameters affect runoff and nutrient export. Next, the model was calibrated and validated using measured runoff and nutrient concentration data. The Nash-Sutcliffe efficiency (E NS ) values of the yearly runoff were 0.87 and 0.69 for the calibration and validation periods, respectively. For storms runoff events, the E NS values were 0.93 for the calibration period and 0.47 for the validation period. Antecedent precipitation and soil moisture conditions can affect the simulation accuracy of storm event flow. The E NS values for the total nitrogen (TN) export were 0.58 for the calibration period and 0.51 for the validation period. In addition, the correlation coefficients between the observed and simulated TN concentrations were 0.84 for the calibration period and 0.74 for the validation period. For phosphorus export, the E NS values were 0.89 for the calibration period and 0.88 for the validation period. In addition, the correlation coefficients between the observed and simulated orthophosphate concentrations were 0.96 and 0.94 for the calibration and validation periods, respectively. The nutrient simulation results are generally satisfactory even though the parameter-lumped HSPF model cannot represent the effects of the spatial pattern of land cover on nutrient export. The model parameters obtained in this study could serve as reference values for applying the model to similar regions. In addition, HSPF can properly describe the characteristics of water quantity and quality processes in this area. After adjustment, calibration, and validation of the parameters, the HSPF model is suitable for hydrological and water-quality simulations in watershed planning and management and for designing best management practices.
Developing a Hydrologic Assessment Tool for Designing Bioretention in a watershed
NASA Astrophysics Data System (ADS)
Baek, Sangsoo; Ligaray, Mayzonee; Park, Jeong-Pyo; Kwon, Yongsung; Cho, Kyung Hwa
2017-04-01
Continuous urbanization has negatively impacted the ecological and hydrological environments at the global, regional, and local scales. This issue was addressed by developing Low Impact Development (LID) practices to deliver better hydrologic function and improve the environmental, economic, social and cultural outcomes. This study developed a modeling software to simulate and optimize bioretentions among LID in a given watershed. The model calculated a detailed soil infiltration process in bioretention with hydrological conditions and hydraulic facilities (e.g. riser and underdrain) and also generated an optimized plan using Flow Duration Curve (FDC). The optimization result from the simulation demonstrated that the location and size of bioretention, as well as the soil texture, are important elements for an efficient bioretention. We hope that the developed software in this study could be useful for establishing an appropriate scheme of LID installment
NASA Astrophysics Data System (ADS)
Camporese, M.; Bertoldi, G.; Bortoli, E.; Wohlfahrt, G.
2017-12-01
Integrated hydrologic surface-subsurface models (IHSSMs) are increasingly used as prediction tools to solve simultaneously states and fluxes in and between multiple terrestrial compartments (e.g., snow cover, surface water, groundwater), in an attempt to tackle environmental problems in a holistic approach. Two such models, CATHY and GEOtop, are used in this study to investigate their capabilities to reproduce hydrological processes in alpine grasslands. The two models differ significantly in the complexity of the representation of the surface energy balance and the solution of Richards equation for water flow in the variably saturated subsurface. The main goal of this research is to show how these differences in process representation can lead to different predictions of hydrologic states and fluxes, in the simulation of an experimental site located in the Venosta Valley (South Tyrol, Italy). Here, a large set of relevant hydrological data (e.g., evapotranspiration, soil moisture) has been collected, with ground and remote sensing observations. The area of interest is part of a Long-Term Ecological Research (LTER) site, a mountain steep, heterogeneous slope, where the predominant land use types are meadow, pasture, and forest. The comparison between data and model predictions, as well as between simulations with the two IHSSMs, contributes to advance our understanding of the tradeoffs between different complexities in modeĺs process representation, model accuracy, and the ability to explain observed hydrological dynamics in alpine environments.
Historical and Future Projected Hydrologic Extremes over the Midwest and Great Lakes Region
NASA Astrophysics Data System (ADS)
Byun, K.; Hamlet, A. F.; Chiu, C. M.
2016-12-01
There is an increasing body of evidence from observed data that climate variability combined with regional climate change has had a significant impact on hydrologic cycles, including both seasonal patterns of runoff and altered hydrologic extremes (e.g. floods and extreme stormwater events). To better understand changing patterns of extreme high flows in Midwest and Great Lakes region, we analyzed long-term historical observations of peak streamflow at different gaging stations. We also conducted hydrologic model experiments using the Variable Infiltration Capacity (VIC) at 1/16 degree resolution in order to explore sensitivity of annual peak streamflow, both historically and under temperature and precipitation changes for several future periods. For future projections, the Hybrid Delta statistical downscaling approach applied to the Coupled Model Inter-comparison, Phase5 (CMIP5) Global Climate Model (GCM) scenarios was used to produce driving data for the VIC hydrologic model. Preliminary results for several test basins in the Midwest support the hypothesis that there are consistent and statistically significant changes in the mean annual flood starting before and after about 1975. Future projections using hydrologic model simulations support the hypothesis of higher peak flows due to warming and increasing precipitation projected for the 21st century. We will extend this preliminary analysis using observed data and simulations from 40 river basins in the Midwest to further test these hypotheses.
Modelling hydrological conditions in the maritime forest region of south-western Nova Scotia
NASA Astrophysics Data System (ADS)
Yanni, Shelagh; Keys, Kevin; Meng, Fan-Rui; Yin, Xiwei; Clair, Tom; Arp, Paul A.
2000-02-01
Hydrological processes and conditions were quantified for the Mersey River Basin (two basins: one exiting below Mill Falls, and one exiting below George Lake), the Roger's Brook Basin, Moosepit Brook, and for other selected locations at and near Kejimkujik National Park in Nova Scotia, Canada, from 1967 to 1990. Addressed variables included precipitation (rain, snow, fog), air temperature, stream discharge, snowpack accumulations, throughfall, soil and subsoil moisture, soil temperature and soil frost, at a monthly resolution. It was found that monthly per hectare stream discharge was essentially independent of catchment area from <20 km2 to more than 1000 km2. The forest hydrology model ForHyM2 was used to simulate monthly rates of stream discharge, throughfall and snowpack water equivalents for mature forest conditions. These simulations were in good agreement with the historical records once the contributions of fog and mist to the area-wide water budget were taken into account, each on a monthly basis. The resulting simulations establish a hydrologically consistent, continuous, comprehensive and partially verified record for basin-wide outcomes for all major hydrological processes and conditions, be these related to stream discharge, soil moisture, soil temperature, snowpack accumulations, soil frost, throughfall, interception and soil percolation.
Modeling the Hydrologic Response to Changes in Groundcover Conditions Caused by Fire Disturbances
NASA Astrophysics Data System (ADS)
Kikinzon, E.; Atchley, A. L.; Coon, E.; Middleton, R. S.
2016-12-01
Climate change and fire suppression increase wildfire activity, which alters ecosystem functions and can significantly impact hydrological response. Both wildfire and prescribed burns reduce groundcover, affect top layers of subsurface, and change the structure of overland flow pathways. To understand respective effects on surface and subsurface hydrology, it is imperative to accurately represent surface-subsurface interface pre and post-fire, and to model physical processes in groundcover components. We show mechanistic models used to describe physics in two key types of groundcover, litter and duff, in Advanced Terrestrial Simulator (ATS). Litter is considered to be a part of vegetative canopy covering the surface. It has associated water storage capacity, which allows simulating interception and drainage, and its thickness is used to evaluate surface roughness with potential effect of slowing overland flow compared to bare soil. Duff on the other hand is incorporated into the subsurface, thus requiring meshing and discretization capability to support complex geometries including pinchouts, which is necessary both for achieving desired mesh resolution and portraying bare soil patches without adversely affecting the time scale. As part of the subsurface, duff has its own hydrologic and water retention properties used to resolve infiltration and saturation limited runoff generation, run on, and infiltration processes. This enables the use of ATS for fine scale modeling of integrated hydrology with adequate representation of groundcover influence. To isolate the impact of changing groundcover, we consider a simple hill slope and study the hydrological response to varying amount and geometries of groundcover. To cover landscape characteristics produced by a wide variety of fire conditions, from high intensity to low intensity fire impacts, we simulate hydrologic response to precipitation events over a number of typical geometries and with fine control over amounts of two described types of groundcover. We then analyze hydrological sensitivity to presence or absence of particular groundcover types, their respective patchiness, and possible changes in overland flow pathways.
Hydrology of malaria: Model development and application to a Sahelian village
NASA Astrophysics Data System (ADS)
Bomblies, Arne; Duchemin, Jean-Bernard; Eltahir, Elfatih A. B.
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 semiarid, desert fringe environments. The model is applied to the Sahel village of Banizoumbou, Niger, to predict interannual variability in malaria vector mosquito populations that 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. Through a dependence of aquatic-stage mosquito development and adult emergence on pool persistence, we model small-scale hydrology as a dominant control of mosquito abundance. 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. A 16% increase in rainfall between the two years was accompanied by a 132% increase in mosquito abundance between 2005 and 2006. The model reproduces mosquito population variability at seasonal and interannual timescales and highlights individual pool persistence as a dominant control. Future developments of 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.
Conceptualizing Peatlands in a Physically-Based Spatially Distributed Hydrologic Model
NASA Astrophysics Data System (ADS)
Downer, Charles; Wahl, Mark
2017-04-01
In as part of a research effort focused on climate change effects on permafrost near Fairbanks, Alaska, it became apparent that peat soils, overlain by thick sphagnum moss, had a considerable effect on the overall hydrology. Peatlands represent a confounding mixture of vegetation, soils, and water that present challenges for conceptualizing and parametrizing hydrologic models. We employed the Gridded Surface Subsurface Hydrologic Analysis Model (GSSHA) in our analysis of the Caribou Poker Creek Experimental Watershed (CPCRW). GSSHA is a physically-based, spatially distributed, watershed model developed by the U.S. Army to simulate important streamflow-generating processes (Downer and Ogden, 2004). The model enables simulation of surface water and groundwater interactions, as well as soil temperature and frozen ground effects on subsurface water movement. The test site is a 104 km2 basin located in the Yukon-Tanana Uplands of the Northern Plateaus Physiographic Province centered on 65˚10' N latitude and 147˚30' W longitude. The area lies above the Chattanika River floodplain and is characterized by rounded hilltops with gentle slopes and alluvium-floored valleys having minimal relief (Wahrhaftig, 1965) underlain by a mica shist of the Birch Creek formation (Rieger et al., 1972). The region has a cold continental climate characterized by short warm summers and long cold winters. Observed stream flows indicated significant groundwater contribution with sustained base flows even during dry periods. A site visit exposed the presence of surface water flows indicating a mixed basin that would require both surface and subsurface simulation capability to properly capture the response. Soils in the watershed are predominately silt loam underlain by shallow fractured bedrock. Throughout much of the basin, a thick layer of live sphagnum moss and fine peat covers the ground surface. A restrictive layer of permafrost is found on north facing slopes. The combination of thick moss and peat soils presented a conundrum in terms of conceptualizing the hydrology and identifying reasonable parameter ranges for physical properties. Various combinations of overland roughness, surface retention, and subsurface flow were used to represent the peatlands. The process resulted in some interesting results that may shed light on the dominant hydrologic processes associated with peatland, as well as what hydrologic conceptualizations, simulation tools, and approaches are applicable in modeling peatland hydrology. Downer, C.W., Ogden, F.L., 2004. GSSHA: Model to simulate diverse stream flow producing processes. J. Hydrol. Eng. 161-174. Rieger, S., Furbush, C.E., Schoephorster, D.B., Summerfield Jr., H., Geiger, L.C., 1972. Soils of the Caribou-Poker Creeks Research Watershed, Interior Alaska. Hanover, New Hampshire. Wahrhaftig, C., 1965. Physiographic Divisions of Alaska. Washington, DC.
Wu, Yiping; Chen, Ji
2013-01-01
Hydrological models have been increasingly used by hydrologists and water resource managers to understand natural processes and human activities that affect watersheds. In this study, we use the physically based model, Soil and Water Assessment Tool (SWAT), to investigate the hydrological processes in the East River Basin in South China, a coastal area dominated by monsoonal climate. The SWAT model was calibrated using 8-year (1973–1980) record of the daily streamflow at the basin outlet (Boluo station), and then validated using data collected during the subsequent 8 years (1981–1988). Statistical evaluation shows that SWAT can consistently simulate the streamflow of the East River with monthly Nash–Sutcliffe efficiencies of 0.93 for calibration and 0.90 for validation at the Boluo station. We analyzed the model simulations with calibrated parameters, presented the spatiotemporal distribution of the key hydrological components, and quantified their responses to different land uses. Watershed managers can use the results of this study to understand hydrological features and evaluate water resources of the East River in terms of sustainable development and effective management.
Evaluating Satellite-based Rainfall Estimates for Basin-scale Hydrologic Modeling
NASA Astrophysics Data System (ADS)
Yilmaz, K. K.; Hogue, T. S.; Hsu, K.; Gupta, H. V.; Mahani, S. E.; Sorooshian, S.
2003-12-01
The reliability of any hydrologic simulation and basin outflow prediction effort depends primarily on the rainfall estimates. The problem of estimating rainfall becomes more obvious in basins with scarce or no rain gauges. We present an evaluation of satellite-based rainfall estimates for basin-scale hydrologic modeling with particular interest in ungauged basins. The initial phase of this study focuses on comparison of mean areal rainfall estimates from ground-based rain gauge network, NEXRAD radar Stage-III, and satellite-based PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) and their influence on hydrologic model simulations over several basins in the U.S. Six-hourly accumulations of the above competing mean areal rainfall estimates are used as input to the Sacramento Soil Moisture Accounting Model. Preliminary experiments for the Leaf River Basin in Mississippi, for the period of March 2000 - June 2002, reveals that seasonality plays an important role in the comparison. There is an overestimation during the summer and underestimation during the winter in satellite-based rainfall with respect to the competing rainfall estimates. The consequence of this result on the hydrologic model is that simulated discharge underestimates the major observed peak discharges during early spring for the basin under study. Future research will entail developing correction procedures, which depend on different factors such as seasonality, geographic location and basin size, for satellite-based rainfall estimates over basins with dense rain gauge network and/or radar coverage. Extension of these correction procedures to satellite-based rainfall estimates over ungauged basins with similar characteristics has the potential for reducing the input uncertainty in ungauged basin modeling efforts.
Hydroclimatic Change in the Congo River Basin: Past, Present and Future169
NASA Astrophysics Data System (ADS)
Aloysius, N. R.
2016-12-01
Tropical regions provide habitat for the world's most diverse fauna and flora, sequester more atmospheric carbon and provide livelihood for millions of people. The hydrological cycle provides vital linkages for maintaining these ecosystem functions, yet, the understanding of its spatiotemporal variability is limited. Research on the hydrological cycle of the Congo River Basin (CRB), which encompasses the second largest rainforests, has been largely ignored. Global Climate Models (GCM) show limited skills in simulating CRB's climate and their future projections vary widely. Yet, GCMs provide the most plausible scenarios of future climate, based upon which changes in hydrologic fluxes can be predicted with the aid hydrological models. In order to address the gaps in knowledge and to highlight the research needs, we i) developed a spatially explicit hydrological model suitable for describing key hydrological processes, ii) evaluated the performance of GCMs in simulating precipitation and temperature in the region, iii) developed a set of climate change scenarios for the CRB and iv) developed a simplified modeling framework to quantify water management options for rain-fed agriculture with the objective of achieving the triple goals of sustainable development: food security, poverty alleviation and ecosystem conservation. The hydrology model, which was validated with observed stream flows at 50 locations, satisfactorily characterizes spatiotemporal variability of key fluxes. Our evaluation of 25 GCM outputs reveal that many GCMs poorly simulate regional precipitation. We implemented a statistical bias-correction method to develop precipitation and temperature projections for two future greenhouse gas emission scenarios. These climate forcings were, then, used to drive the hydrology model. Our results show that the near-term projections are not affected by emission scenarios. However, towards the mid-21st century, projections are emission scenario dependent. Available freshwater resources are projected to increase in the CRB, except in the semiarid southeast. Our findings have wider implications for climate change assessment and water resource management, because the region, with high population growth and limited capacity to adapt, are primary targets of land and water grabs. 155
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.
Simulating the hydrologic impacts of land-cover and climate changes in a semi-arid watershed
Changes in climate and land cover are principal variables affecting watershed hydrology. This paper uses a cell-based model to examine the hydrologic impacts of climate and land cover changes in the semi-arid Lower Virgin River (LVR) watershed located upstream of Lake Mead, Nevad...
Three-dimensional numerical model of ground-water flow in northern Utah Valley, Utah County, Utah
Gardner, Philip M.
2009-01-01
A three-dimensional, finite-difference, numerical model was developed to simulate ground-water flow in northern Utah Valley, Utah. The model includes expanded areal boundaries as compared to a previous ground-water flow model of the valley and incorporates more than 20 years of additional hydrologic data. The model boundary was generally expanded to include the bedrock in the surrounding mountain block as far as the surface-water divide. New wells have been drilled in basin-fill deposits near the consolidated-rock boundary. Simulating the hydrologic conditions within the bedrock allows for improved simulation of the effect of withdrawal from these wells. The inclusion of bedrock also allowed for the use of a recharge model that provided an alternative method for spatially distributing areal recharge over the mountains.The model was calibrated to steady- and transient-state conditions. The steady-state simulation was developed and calibrated by using hydrologic data that represented average conditions for 1947. The transient-state simulation was developed and calibrated by using hydrologic data collected from 1947 to 2004. Areally, the model grid is 79 rows by 70 columns, with variable cell size. Cells throughout most of the model domain represent 0.3 mile on each side. The largest cells are rectangular with dimensions of about 0.3 by 0.6 mile. The largest cells represent the mountain block on the eastern edge of the model domain where the least hydrologic data are available. Vertically, the aquifer system is divided into 4 layers which incorporate 11 hydrogeologic units. The model simulates recharge to the ground-water flow system as (1) infiltration of precipitation over the mountain block, (2) infiltration of precipitation over the valley floor, (3) infiltration of unconsumed irrigation water from fields, lawns, and gardens, (4) seepage from streams and canals, and (5) subsurface inflow from Cedar Valley. Discharge of ground water is simulated by the model to (1) flowing and pumping wells, (2) drains and springs, (3) evapotranspiration, (4) Utah Lake, (5) the Jordan River and mountain streams, and (6) Salt Lake Valley by subsurface outflow through the Jordan Narrows.During steady-state calibration, variables were adjusted within probable ranges to minimize differences between model-computed and measured water levels as well as between model-computed and independently estimated flows that include: recharge by seepage from individual streams and canals, discharge by seepage to individual streams and the Jordan River, discharge to Utah Lake, discharge to drains and springs, discharge by evapotranspiration, and subsurface flows into and out of northern Utah Valley from Cedar Valley and to Salt Lake Valley, respectively. The transient-state simulation was calibrated to measured water levels and water-level changes with consideration given to annual changes in the flows listed above.
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.
Sensitivity analysis of a ground-water-flow model
Torak, Lynn J.; ,
1991-01-01
A sensitivity analysis was performed on 18 hydrological factors affecting steady-state groundwater flow in the Upper Floridan aquifer near Albany, southwestern Georgia. Computations were based on a calibrated, two-dimensional, finite-element digital model of the stream-aquifer system and the corresponding data inputs. Flow-system sensitivity was analyzed by computing water-level residuals obtained from simulations involving individual changes to each hydrological factor. Hydrological factors to which computed water levels were most sensitive were those that produced the largest change in the sum-of-squares of residuals for the smallest change in factor value. Plots of the sum-of-squares of residuals against multiplier or additive values that effect change in the hydrological factors are used to evaluate the influence of each factor on the simulated flow system. The shapes of these 'sensitivity curves' indicate the importance of each hydrological factor to the flow system. Because the sensitivity analysis can be performed during the preliminary phase of a water-resource investigation, it can be used to identify the types of hydrological data required to accurately characterize the flow system prior to collecting additional data or making management decisions.
Water, Energy, and Biogeochemical Model (WEBMOD), user’s manual, version 1
Webb, Richard M.T.; Parkhurst, David L.
2017-02-08
The Water, Energy, and Biogeochemical Model (WEBMOD) uses the framework of the U.S. Geological Survey (USGS) Modular Modeling System to simulate fluxes of water and solutes through watersheds. WEBMOD divides watersheds into model response units (MRU) where fluxes and reactions are simulated for the following eight hillslope reservoir types: canopy; snowpack; ponding on impervious surfaces; O-horizon; two reservoirs in the unsaturated zone, which represent preferential flow and matrix flow; and two reservoirs in the saturated zone, which also represent preferential flow and matrix flow. The reservoir representing ponding on impervious surfaces, currently not functional (2016), will be implemented once the model is applied to urban areas. MRUs discharge to one or more stream reservoirs that flow to the outlet of the watershed. Hydrologic fluxes in the watershed are simulated by modules derived from the USGS Precipitation Runoff Modeling System; the National Weather Service Hydro-17 snow model; and a topography-driven hydrologic model (TOPMODEL). Modifications to the standard TOPMODEL include the addition of heterogeneous vertical infiltration rates; irrigation; lateral and vertical preferential flows through the unsaturated zone; pipe flow draining the saturated zone; gains and losses to regional aquifer systems; and the option to simulate baseflow discharge by using an exponential, parabolic, or linear decrease in transmissivity. PHREEQC, an aqueous geochemical model, is incorporated to simulate chemical reactions as waters evaporate, mix, and react within the various reservoirs of the model. The reactions that can be specified for a reservoir include equilibrium reactions among water; minerals; surfaces; exchangers; and kinetic reactions such as kinetic mineral dissolution or precipitation, biologically mediated reactions, and radioactive decay. WEBMOD also simulates variations in the concentrations of the stable isotopes deuterium and oxygen-18 as a result of varying inputs, mixing, and evaporation. This manual describes the WEBMOD input and output files, along with the algorithms and procedures used to simulate the hydrology and water quality in a watershed. Examples are presented that demonstrate hydrologic processes, weathering reactions, and isotopic evolution in an alpine watershed and the effect of irrigation on water flows and salinity in an intensively farmed agricultural area.
Bangash, Rubab F; Passuello, Ana; Hammond, Michael; Schuhmacher, Marta
2012-12-01
River Francolí is a small river in Catalonia (northeastern Spain) with an average annual low flow (~2 m(3)/s). The purpose of the River Francolí watershed assessments is to support and inform region-wide planning efforts from the perspective of water protection, climate change and water allocation. In this study, a hydrological model of the Francolí River watershed was developed for use as a tool for watershed planning, water resource assessment, and ultimately, water allocation purposes using hydrological data from 2002 to 2006 inclusive. The modeling package selected for this application is DHI's MIKE BASIN. This model is a strategic scale water resource management simulation model, which includes modeling of both land surface and subsurface hydrological processes. Topographic, land use, hydrological, rainfall, and meteorological data were used to develop the model segmentation and input. Due to the unavailability of required catchment runoff data, the NAM rainfall-runoff model was used to calculate runoff of all the sub-watersheds. The results reveal a potential pressure on the availability of groundwater and surface water in the lower part of River Francolí as was expected by the IPCC for Mediterranean river basins. The study also revealed that due to the complex hydrological regime existing in the study area and data scarcity, a comprehensive physically based method was required to better represent the interaction between groundwater and surface water. The combined ArcGIS/MIKE BASIN models appear as a useful tool to assess the hydrological cycle and to better understand water allocation to different sectors in the Francolí River watershed. Copyright © 2012 Elsevier B.V. All rights reserved.
Impact of rescaling anomaly and seasonal components of soil moisture on hydrologic data assimilation
USDA-ARS?s Scientific Manuscript database
In hydrological sciences many observations and model simulations have moderate linear association due to the noise in the datasets and/or the systematic differences between their seasonality components. This degrades the performance of model-observation integration algorithms, such as the Kalman Fil...
USDA-ARS?s Scientific Manuscript database
For more than three decades, researchers have utilized the Snowmelt Runoff Model (SRM) to test the impacts of climate change on streamflow of snow-fed systems. In this study, the hydrological effects of climate change are modeled over three sequential years using SRM with both typical and recommende...
Joseph K. O. Amoah; Devendra M. Amatya; Soronnadi Nnaji
2012-01-01
Hydrologic models often require correct estimates of surface macro-depressional storage to accurately simulate rainfallârunoff processes. Traditionally, depression storage is determined through model calibration or lumped with soil storage components or on an ad hoc basis. This paper investigates a holistic approach for estimating surface depressional storage capacity...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lei, Huimin; Huang, Maoyi; Leung, Lai-Yung R.
2014-09-01
The terrestrial water and carbon cycles interact strongly at various spatio-temporal scales. To elucidate how hydrologic processes may influence carbon cycle processes, differences in terrestrial carbon cycle simulations induced by structural differences in two runoff generation schemes were investigated using the Community Land Model 4 (CLM4). Simulations were performed with runoff generation using the default TOPMODEL-based and the Variable Infiltration Capacity (VIC) model approaches under the same experimental protocol. The comparisons showed that differences in the simulated gross primary production (GPP) are mainly attributed to differences in the simulated leaf area index (LAI) rather than soil moisture availability. More specifically,more » differences in runoff simulations can influence LAI through changes in soil moisture, soil temperature, and their seasonality that affect the onset of the growing season and the subsequent dynamic feedbacks between terrestrial water, energy, and carbon cycles. As a result of a relative difference of 36% in global mean total runoff between the two models and subsequent changes in soil moisture, soil temperature, and LAI, the simulated global mean GPP differs by 20.4%. However, the relative difference in the global mean net ecosystem exchange between the two models is small (2.1%) due to competing effects on total mean ecosystem respiration and other fluxes, although large regional differences can still be found. Our study highlights the significant interactions among the water, energy, and carbon cycles and the need for reducing uncertainty in the hydrologic parameterization of land surface models to better constrain carbon cycle modeling.« less
Revising Hydrology of a Land Surface Model
NASA Astrophysics Data System (ADS)
Le Vine, Nataliya; Butler, Adrian; McIntyre, Neil; Jackson, Christopher
2015-04-01
Land Surface Models (LSMs) are key elements in guiding adaptation to the changing water cycle and the starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, before this potential is realised, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. An important limitation is the simplistic or non-existent representation of the deep subsurface in LSMs; and another is the lack of connection of LSM parameterisations to relevant hydrological information. In this context, the paper uses a case study of the JULES (Joint UK Land Environmental Simulator) LSM applied to the Kennet region in Southern England. The paper explores the assumptions behind JULES hydrology, adapts the model structure and optimises the coupling with the ZOOMQ3D regional groundwater model. The analysis illustrates how three types of information can be used to improve the model's hydrology: a) observations, b) regionalized information, and c) information from an independent physics-based model. It is found that: 1) coupling to the groundwater model allows realistic simulation of streamflows; 2) a simple dynamic lower boundary improves upon JULES' stationary unit gradient condition; 3) a 1D vertical flow in the unsaturated zone is sufficient; however there is benefit in introducing a simple dual soil moisture retention curve; 4) regionalized information can be used to describe soil spatial heterogeneity. It is concluded that relatively simple refinements to the hydrology of JULES and its parameterisation method can provide a substantial step forward in realising its potential as a high-resolution multi-purpose model.
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.
NASA Astrophysics Data System (ADS)
Karssenberg, D.; Wanders, N.; de Roo, A.; de Jong, S.; Bierkens, M. F.
2013-12-01
Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system that is not directly linked to discharge, in particular the unsaturated zone, remains uncalibrated, or might be modified unrealistically. Soil moisture observations from satellites have the potential to fill this gap, as these provide the closest thing to a direct measurement of the state of the unsaturated zone, and thus are potentially useful in calibrating unsaturated zone model parameters. This is expected to result in a better identification of the complete hydrological system, potentially leading to improved forecasts of the hydrograph as well. Here we evaluate this added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: 1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? 2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to approaches that calibrate only with discharge, such that this leads to improved forecasts of soil moisture content and discharge as well? To answer these questions we use a dual state and parameter ensemble Kalman filter to calibrate the hydrological model LISFLOOD for the Upper Danube area. Calibration is done with discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS and ASCAT. Four scenarios are studied: no calibration (expert knowledge), calibration on discharge, calibration on remote sensing data (three satellites) and calibration on both discharge and remote sensing data. Using a split-sample approach, the model is calibrated for a period of 2 years and validated for the calibrated model parameters on a validation period of 10 years. Results show that calibration with discharge data improves the estimation of groundwater parameters (e.g., groundwater reservoir constant) and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate calibration of parameters related to land surface process (e.g., the saturated conductivity of the soil), which is not possible when calibrating on discharge alone. For the upstream area up to 40000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30 % in the RMSE for discharge simulations, compared to calibration on discharge alone. For discharge in the downstream area, the model performance due to assimilation of remotely sensed soil moisture is not increased or slightly decreased, most probably due to the longer relative importance of the routing and contribution of groundwater in downstream areas. When microwave soil moisture is used for calibration the RMSE of soil moisture simulations decreases from 0.072 m3m-3 to 0.062 m3m-3. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models leading to a better simulation of soil moisture content throughout and a better simulation of discharge in upstream areas, particularly if discharge observations are sparse.
NASA Astrophysics Data System (ADS)
Paiewonsky, Pablo; Elison Timm, Oliver
2018-03-01
In this paper, we present a simple dynamic global vegetation model whose primary intended use is auxiliary to the land-atmosphere coupling scheme of a climate model, particularly one of intermediate complexity. The model simulates and provides important ecological-only variables but also some hydrological and surface energy variables that are typically either simulated by land surface schemes or else used as boundary data input for these schemes. The model formulations and their derivations are presented here, in detail. The model includes some realistic and useful features for its level of complexity, including a photosynthetic dependency on light, full coupling of photosynthesis and transpiration through an interactive canopy resistance, and a soil organic carbon dependence for bare-soil albedo. We evaluate the model's performance by running it as part of a simple land surface scheme that is driven by reanalysis data. The evaluation against observational data includes net primary productivity, leaf area index, surface albedo, and diagnosed variables relevant for the closure of the hydrological cycle. In this setup, we find that the model gives an adequate to good simulation of basic large-scale ecological and hydrological variables. Of the variables analyzed in this paper, gross primary productivity is particularly well simulated. The results also reveal the current limitations of the model. The most significant deficiency is the excessive simulation of evapotranspiration in mid- to high northern latitudes during their winter to spring transition. The model has a relative advantage in situations that require some combination of computational efficiency, model transparency and tractability, and the simulation of the large-scale vegetation and land surface characteristics under non-present-day conditions.
Improving the Amazonian Hydrologic Cycle in a Coupled Land-Atmosphere, Single Column Model
NASA Astrophysics Data System (ADS)
Harper, A. B.; Denning, S.; Baker, I.; Prihodko, L.; Branson, M.
2006-12-01
We have coupled a land-surface model, the Simple Biosphere Model (SiB3), to a single column of the Colorado State University General Circulation Model (CSU-GCM) in the Amazon River Basin. This is a preliminary step in the broader goal of improved simulation of Basin-wide hydrology. A previous version of the coupled model (SiB2) showed drought and catastrophic dieback of the Amazon rain forest. SiB3 includes updated soil hydrology and root physiology. Our test area for the coupled single column model is near Santarem, Brazil, where measurements from the km 83 flux tower in the Tapajos National Forest can be used to evaluate model output. The model was run for 2001 using NCEP2 Reanalysis as driver data. Preliminary results show that the updated biosphere model coupled to the GCM produces improved simulations of the seasonal cycle of surface water balance and precipitation. Comparisons of the diurnal and seasonal cycles of surface fluxes are also being made.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hinzman, Larry D.; Bolton, William Robert; Young-Robertson, Jessica
This project improves meso-scale hydrologic modeling in the boreal forest by: (1) demonstrating the importance of capturing the heterogeneity of the landscape using small scale datasets for parameterization for both small and large basins; (2) demonstrating that in drier parts of the landscape and as the boreal forest dries with climate change, modeling approaches must consider the sensitivity of simulations to soil hydraulic parameters - such as residual water content - that are usually held constant. Thus, variability / flexibility in residual water content must be considered for accurate simulation of hydrologic processes in the boreal forest; (3) demonstrating thatmore » assessing climate change impacts on boreal forest hydrology through multiple model integration must account for direct effects of climate change (temperature and precipitation), and indirect effects from climate impacts on landscape characteristics (permafrost and vegetation distribution). Simulations demonstrated that climate change will increase runoff, but will increase ET to a greater extent and result in a drying of the landscape; and (4) vegetation plays a significant role in boreal hydrologic processes in permafrost free areas that have deciduous trees. This landscape type results in a decoupling of ET and precipitation, a tight coupling of ET and temperature, low runoff, and overall soil drying.« less
NASA Astrophysics Data System (ADS)
Mujumdar, Pradeep P.
2014-05-01
Climate change results in regional hydrologic change. The three prominent signals of global climate change, viz., increase in global average temperatures, rise in sea levels and change in precipitation patterns convert into signals of regional hydrologic change in terms of modifications in water availability, evaporative water demand, hydrologic extremes of floods and droughts, water quality, salinity intrusion in coastal aquifers, groundwater recharge and other related phenomena. A major research focus in hydrologic sciences in recent years has been assessment of impacts of climate change at regional scales. An important research issue addressed in this context deals with responses of water fluxes on a catchment scale to the global climatic change. A commonly adopted methodology for assessing the regional hydrologic impacts of climate change is to use the climate projections provided by the General Circulation Models (GCMs) for specified emission scenarios in conjunction with the process-based hydrologic models to generate the corresponding hydrologic projections. The scaling problem arising because of the large spatial scales at which the GCMs operate compared to those required in distributed hydrologic models, and their inability to satisfactorily simulate the variables of interest to hydrology are addressed by downscaling the GCM simulations to hydrologic scales. Projections obtained with this procedure are burdened with a large uncertainty introduced by the choice of GCMs and emission scenarios, small samples of historical data against which the models are calibrated, downscaling methods used and other sources. Development of methodologies to quantify and reduce such uncertainties is a current area of research in hydrology. In this presentation, an overview of recent research carried out by the author's group on assessment of hydrologic impacts of climate change addressing scale issues and quantification of uncertainties is provided. Methodologies developed with conditional random fields, Dempster-Shafer theory, possibility theory, imprecise probabilities and non-stationary extreme value theory are discussed. Specific applications on uncertainty quantification in impacts on streamflows, evaporative water demands, river water quality and urban flooding are presented. A brief discussion on detection and attribution of hydrologic change at river basin scales, contribution of landuse change and likely alterations in return levels of hydrologic extremes is also provided.
Assessing the Added Value of Dynamical Downscaling in the Context of Hydrologic Implication
NASA Astrophysics Data System (ADS)
Lu, M.; IM, E. S.; Lee, M. H.
2017-12-01
There is a scientific consensus that high-resolution climate simulations downscaled by Regional Climate Models (RCMs) can provide valuable refined information over the target region. However, a significant body of hydrologic impact assessment has been performing using the climate information provided by Global Climate Models (GCMs) in spite of a fundamental spatial scale gap. It is probably based on the assumption that the substantial biases and spatial scale gap from GCMs raw data can be simply removed by applying the statistical bias correction and spatial disaggregation. Indeed, many previous studies argue that the benefit of dynamical downscaling using RCMs is minimal when linking climate data with the hydrological model, from the comparison of the impact between bias-corrected GCMs and bias-corrected RCMs on hydrologic simulations. It may be true for long-term averaged climatological pattern, but it is not necessarily the case when looking into variability across various temporal spectrum. In this study, we investigate the added value of dynamical downscaling focusing on the performance in capturing climate variability. For doing this, we evaluate the performance of the distributed hydrological model over the Korean river basin using the raw output from GCM and RCM, and bias-corrected output from GCM and RCM. The impacts of climate input data on streamflow simulation are comprehensively analyzed. [Acknowledgements]This research is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 17AWMP-B083066-04).
Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections
NASA Astrophysics Data System (ADS)
Aryal, Anil; Shrestha, Sangam; Babel, Mukand S.
2018-01-01
The objective of this paper is to quantify the various sources of uncertainty in the assessment of climate change impact on hydrology in the Tamakoshi River Basin, located in the north-eastern part of Nepal. Multiple climate and hydrological models were used to simulate future climate conditions and discharge in the basin. The simulated results of future climate and river discharge were analysed for the quantification of sources of uncertainty using two-way and three-way ANOVA. The results showed that temperature and precipitation in the study area are projected to change in near- (2010-2039), mid- (2040-2069) and far-future (2070-2099) periods. Maximum temperature is likely to rise by 1.75 °C under Representative Concentration Pathway (RCP) 4.5 and by 3.52 °C under RCP 8.5. Similarly, the minimum temperature is expected to rise by 2.10 °C under RCP 4.5 and by 3.73 °C under RCP 8.5 by the end of the twenty-first century. Similarly, the precipitation in the study area is expected to change by - 2.15% under RCP 4.5 and - 2.44% under RCP 8.5 scenarios. The future discharge in the study area was projected using two hydrological models, viz. Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center's Hydrologic Modelling System (HEC-HMS). The SWAT model projected discharge is expected to change by small amount, whereas HEC-HMS model projected considerably lower discharge in future compared to the baseline period. The results also show that future climate variables and river hydrology contain uncertainty due to the choice of climate models, RCP scenarios, bias correction methods and hydrological models. During wet days, more uncertainty is observed due to the use of different climate models, whereas during dry days, the use of different hydrological models has a greater effect on uncertainty. Inter-comparison of the impacts of different climate models reveals that the REMO climate model shows higher uncertainty in the prediction of precipitation and, consequently, in the prediction of future discharge and maximum probable flood.
NASA Astrophysics Data System (ADS)
Wu, Qiusheng; Lane, Charles R.
2017-07-01
In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling-spilling-merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow simulation and hydrologic connectivity analysis.
NASA Astrophysics Data System (ADS)
Habib, E. H.; Tarboton, D. G.; Lall, U.; Bodin, M.; Rahill-Marier, B.; Chimmula, S.; Meselhe, E. A.; Ali, A.; Williams, D.; Ma, Y.
2013-12-01
The hydrologic community has long recognized the need for broad reform in hydrologic education. A paradigm shift is critically sought in undergraduate hydrology and water resource education by adopting context-rich, student-centered, and active learning strategies. Hydrologists currently deal with intricate issues rooted in complex natural ecosystems containing a multitude of interconnected processes. Advances in the multi-disciplinary field include observational settings such as Critical Zone and Water, Sustainability and Climate Observatories, Hydrologic Information Systems, instrumentation and modeling methods. These research advances theory and practices call for similar efforts and improvements in hydrologic education. The typical, text-book based approach in hydrologic education has focused on specific applications and/or unit processes associated with the hydrologic cycle with idealizations, rather than the contextual relations in the physical processes and the spatial and temporal dynamics connecting climate and ecosystems. An appreciation of the natural variability of these processes will lead to graduates with the ability to develop independent learning skills and understanding. This appreciation cannot be gained in curricula where field components such as observational and experimental data are deficient. These types of data are also critical when using simulation models to create environments that support this type of learning. Additional sources of observations in conjunction with models and field data are key to students understanding of the challenges associated with using models to represent such complex systems. Recent advances in scientific visualization and web-based technologies provide new opportunities for the development of active learning techniques utilizing ongoing research. The overall goal of the current study is to develop visual, case-based, data and simulation driven learning experiences to instructors and students through a web server-based system. Open source web technologies and community-based tools are used to facilitate wide dissemination and adaptation by diverse, independent institutions. The new hydrologic learning modules are based on recent developments in hydrologic modeling, data, and resources. The modules are embedded in three regional-scale ecosystems, Coastal Louisiana, Florida Everglades, and Utah Great Salt Lake Basin. These sites provide a wealth of hydrologic concepts and scenarios that can be used in most water resource and hydrology curricula. The study develops several learning modules based on the three hydro-systems covering subjects such as: water-budget analysis, effects of human and natural changes, climate-hydrology teleconnections, and water-resource management scenarios. The new developments include an instructional interface to give critical guidance and support to the learner and an instructor's guide containing adaptation and implementation procedures to assist instructors in adopting and integrating the material into courses and provide a consistent experience. The design of the new hydrologic education developments will be transferable to independent institutions and adaptable both instructionally and technically through a server system capable of supporting additional developments by the educational community.
BOREAS RSS-8 BIOME-BGC Model Simulations at Tower Flux Sites in 1994
NASA Technical Reports Server (NTRS)
Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Kimball, John
2000-01-01
BIOME-BGC is a general ecosystem process model designed to simulate biogeochemical and hydrologic processes across multiple scales (Running and Hunt, 1993). In this investigation, BIOME-BGC was used to estimate daily water and carbon budgets for the BOREAS tower flux sites for 1994. Carbon variables estimated by the model include gross primary production (i.e., net photosynthesis), maintenance and heterotrophic respiration, net primary production, and net ecosystem carbon exchange. Hydrologic variables estimated by the model include snowcover, evaporation, transpiration, evapotranspiration, soil moisture, and outflow. The information provided by the investigation includes input initialization and model output files for various sites in tabular ASCII format.
NASA Astrophysics Data System (ADS)
Rössler, Ole; Hänggi, Pascal; Köplin, Nina; Meyer, Rapahel; Schädler, Bruno; Weingartner, Rolf
2013-04-01
The potential effect of climate change on hydrology is the acceleration of the hydrological cycle that in turn will likely cause changes in the discharge regime. As a result, socio-economic systems (e.g., tourism, hydropower industry) may be drastically affected. In this study, we comprehensively analyzed the effect of climate change on different hydrological components like mean and low-flow levels, and drought stress in mesoscale catchments of Switzerland. In terms of mean flows approx. 200 catchments in Switzerland were simulated for the reference period 1984-2005 using the hydrological model PREVAH and projection for near (2025-2046) and far future (2074-2095) are based on delta-change values of 10 ENSEMBLES regional climate models assuming A1B emission scenario (CH2011 climate scenario data sets). We found seven distinct response types of catchments, each exhibiting a characteristic annual cycle of hydrologic change. A general pattern observed for all catchments, is the clearly decreasing summer runoff. Hence, within a second analysis of future discharge a special focus was set on summer low flow in a selection of 29 catchments in the Swiss Midlands. Low flows are critical as they have great implications on water usage and biodiversity. We re-calibrated the hydrological model PREVAH with a focus on base-flow and gauged discharge and used the aforementioned climate data sets and simulation time periods. We found low flow situations to be very likely to increase in both, magnitude and duration, especially in central and western Switzerland plateau. At third, the drought stress potential was analyzed by simulating the soil moisture level under climate change conditions in a high mountain catchment. We used the distributed hydrological model WaSiM-ETH for this aspect as soil characteristics are much better represented in this model. Soil moisture in forests below 2000 m a.s.l. were found to be affected at most, which might have implication to their function as avalanche protection forests. However, we found high uncertainties related to the downscaling method applied. Finally, we analyzed the effect of changed discharge characteristics on the hydropower production by coupling the hydrological model BERNHYDRO with a hydropower management model. For the near future (until 2050), the results indicate that losses in the hydropower production during the summer can be compensated by benefit during winter. These different aspects of climate change impacts on the hydrosphere reveal a differentiated picture involving potentially threatened and widely unaffected catchments, hydrologic parameters and hydrologic constraints to the society.
NASA Astrophysics Data System (ADS)
Boyce, S. E.; Hanson, R. T.
2015-12-01
The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. MF-OWHM fully links the movement and use of groundwater, surface water, and imported water for consumption by agriculture and natural vegetation on the landscape, and for potable and other uses within a supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 combined with Local Grid Refinement, Streamflow Routing, Surface-water Routing Process, Seawater Intrusion, Riparian Evapotranspiration, and the Newton-Raphson solver. MF-OWHM also includes linkages for deformation-, flow-, and head-dependent flows; additional observation and parameter options for higher-order calibrations; and redesigned code for facilitation of self-updating models and faster simulation run times. The next version of MF-OWHM, currently under development, will include a new surface-water operations module that simulates dynamic reservoir operations, the conduit flow process for karst aquifers and leaky pipe networks, a new subsidence and aquifer compaction package, and additional features and enhancements to enable more integration and cross communication between traditional MODFLOW packages. By retaining and tracking the water within the hydrosphere, MF-OWHM accounts for "all of the water everywhere and all of the time." This philosophy provides more confidence in the water accounting by the scientific community and provides the public a foundation needed to address wider classes of problems such as evaluation of conjunctive-use alternatives and sustainability analysis, including potential adaptation and mitigation strategies, and best management practices. By Scott E. Boyce and Randall T. Hanson
The PCR-GLOBWB global hydrological reanalysis product
NASA Astrophysics Data System (ADS)
Bierkens, M. F.; Wanders, N.; Sutanudjaja, E.; Van Beek, L. P.
2013-12-01
Accurate and long time series of hydrological data are important for understanding land surface water and energy budgets in many parts of the world, as well as for improving real-time hydrological monitoring and climate change anticipation. The ultimate goal of the present work is to produce a multi-decadal land surface hydrological reanalysis with retrospective and updated hydrological states and fluxes that are constrained to available in-situ river discharge measurements. Here we used PCR-GLOBWB (van Beek et al., 2011), which is a large-scale hydrological model intended for global to regional studies. PCR-GLOBWB provides a grid-based representation of terrestrial hydrology with a typical spatial resolution of approximately 50×50 km (currently 0.5° globally) on a daily basis. For each grid cell, PCR-GLOBWB is basically a leaky bucket type of water balance model with a process-based simulation of moisture storage in two vertically stacked soil layers as well as the water exchange between the soil and the atmosphere and the underlying groundwater reservoir. Exchange to the atmosphere comprises precipitation, evaporation and transpiration, as well as snow accumulation and melt, which are all simulated by considering vegetation phenology and sub-grid distributions of elevation, land cover and soil saturation distribution. The model thus includes detailed schemes for runoff-infiltration partitioning, interflow, groundwater recharge and baseflow, as well as river routing of discharge. . By embedding the PCR-GLOBWB model in an Ensemble Kalman Filter framework, we calibrated the model parameters based on the discharge observations from the Global Runoff Data Centre. The parameters calibrated are related to snow module, runoff-infiltration partitioning, groundwater recharge, channel discharge and baseflow processes, as well as pre-factors to correct forcing precipitation fields due to local topographic and orographic effects. Results show that the model parameters can be calibrated and forcing precipitation fields were successfully corrected. The calibrated model output was compared to the reference run of PCR-GLOBWB before calibration. Here we found significant improvement in simulation of the global terrestrial water cycle, specifically discharge simulation for major river basins in the world. The main outcome of this work is a 1960-2010 global reanalysis dataset that includes extensive daily hydrological components, such as precipitation, evaporation and transpiration, snow, soil moisture, groundwater storage and discharge. This reanalysis product may be used for understanding land surface memory processes, initializing regional studies and operational forecasts, as well as evaluating and improving our understanding of spatio-temporal variation of meteorological and hydrological processes. Moreover, The PCR-GLOBWB data assimilation framework developed in this work can also be extended by including more observational data, including remotely sensed data reflecting the distribution of energy and water (e.g., heat fluxes and soil moisture storage).
NASA Astrophysics Data System (ADS)
Chegwidden, O.; Nijssen, B.; Rupp, D. E.; Kao, S. C.; Clark, M. P.
2017-12-01
We describe results from a large hydrologic climate change dataset developed across the Pacific Northwestern United States and discuss how the analysis of those results can be seen as a framework for other large hydrologic ensemble investigations. This investigation will better inform future modeling efforts and large ensemble analyses across domains within and beyond the Pacific Northwest. Using outputs from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we provide projections of hydrologic change for the domain through the end of the 21st century. The dataset is based upon permutations of four methodological choices: (1) ten global climate models (2) two representative concentration pathways (3) three meteorological downscaling methods and (4) four unique hydrologic model set-ups (three of which entail the same hydrologic model using independently calibrated parameter sets). All simulations were conducted across the Columbia River Basin and Pacific coastal drainages at a 1/16th ( 6 km) resolution and at a daily timestep. In total, the 172 distinct simulations offer an updated, comprehensive view of climate change projections through the end of the 21st century. The results consist of routed streamflow at 400 sites throughout the domain as well as distributed spatial fields of relevant hydrologic variables like snow water equivalent and soil moisture. In this presentation, we discuss the level of agreement with previous hydrologic projections for the study area and how these projections differ with specific methodological choices. By controlling for some methodological choices we can show how each choice affects key climatic change metrics. We discuss how the spread in results varies across hydroclimatic regimes. We will use this large dataset as a case study for distilling a wide range of hydroclimatological projections into useful climate change assessments.
Open source data assimilation framework for hydrological modeling
NASA Astrophysics Data System (ADS)
Ridler, Marc; Hummel, Stef; van Velzen, Nils; Katrine Falk, Anne; Madsen, Henrik
2013-04-01
An open-source data assimilation framework is proposed for hydrological modeling. Data assimilation (DA) in hydrodynamic and hydrological forecasting systems has great potential to improve predictions and improve model result. The basic principle is to incorporate measurement information into a model with the aim to improve model results by error minimization. Great strides have been made to assimilate traditional in-situ measurements such as discharge, soil moisture, hydraulic head and snowpack into hydrologic models. More recently, remotely sensed data retrievals of soil moisture, snow water equivalent or snow cover area, surface water elevation, terrestrial water storage and land surface temperature have been successfully assimilated in hydrological models. The assimilation algorithms have become increasingly sophisticated to manage measurement and model bias, non-linear systems, data sparsity (time & space) and undetermined system uncertainty. It is therefore useful to use a pre-existing DA toolbox such as OpenDA. OpenDA is an open interface standard for (and free implementation of) a set of tools to quickly implement DA and calibration for arbitrary numerical models. The basic design philosophy of OpenDA is to breakdown DA into a set of building blocks programmed in object oriented languages. To implement DA, a model must interact with OpenDA to create model instances, propagate the model, get/set variables (or parameters) and free the model once DA is completed. An open-source interface for hydrological models exists capable of all these tasks: OpenMI. OpenMI is an open source standard interface already adopted by key hydrological model providers. It defines a universal approach to interact with hydrological models during simulation to exchange data during runtime, thus facilitating the interactions between models and data sources. The interface is flexible enough so that models can interact even if the model is coded in a different language, represent processes from a different domain or have different spatial and temporal resolutions. An open source framework that bridges OpenMI and OpenDA is presented. The framework provides a generic and easy means for any OpenMI compliant model to assimilate observation measurements. An example test case will be presented using MikeSHE, and OpenMI compliant fully coupled integrated hydrological model that can accurately simulate the feedback dynamics of overland flow, unsaturated zone and saturated zone.
System Dynamics Modeling of Transboundary Systems: The Bear River Basin Model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gerald Sehlke; Jake Jacobson
2005-09-01
System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and groundwater data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or groundwater modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less
System Dynamics Modeling of Transboundary Systems: the Bear River Basin Model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gerald Sehlke; Jacob J. Jacobson
2005-09-01
System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and ground water data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or ground water modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less
Hanson, R.T.; Flint, L.E.; Flint, A.L.; Dettinger, M.D.; Faunt, C.C.; Cayan, D.; Schmid, W.
2012-01-01
Potential climate change effects on aspects of conjunctive management of water resources can be evaluated by linking climate models with fully integrated groundwater-surface water models. The objective of this study is to develop a modeling system that links global climate models with regional hydrologic models, using the California Central Valley as a case study. The new method is a supply and demand modeling framework that can be used to simulate and analyze potential climate change and conjunctive use. Supply-constrained and demand-driven linkages in the water system in the Central Valley are represented with the linked climate models, precipitation-runoff models, agricultural and native vegetation water use, and hydrologic flow models to demonstrate the feasibility of this method. Simulated precipitation and temperature were used from the GFDL-A2 climate change scenario through the 21st century to drive a regional water balance mountain hydrologic watershed model (MHWM) for the surrounding watersheds in combination with a regional integrated hydrologic model of the Central Valley (CVHM). Application of this method demonstrates the potential transition from predominantly surface water to groundwater supply for agriculture with secondary effects that may limit this transition of conjunctive use. The particular scenario considered includes intermittent climatic droughts in the first half of the 21st century followed by severe persistent droughts in the second half of the 21st century. These climatic droughts do not yield a valley-wide operational drought but do cause reduced surface water deliveries and increased groundwater abstractions that may cause additional land subsidence, reduced water for riparian habitat, or changes in flows at the Sacramento-San Joaquin River Delta. The method developed here can be used to explore conjunctive use adaptation options and hydrologic risk assessments in regional hydrologic systems throughout the world.
Development and Application of a Simple Hydrogeomorphic Model for Headwater Catchments
We developed a catchment model based on a hydrogeomorphic concept that simulates discharge from channel-riparian complexes, zero-order basins (ZOB, basins ZB and FA), and hillslopes. Multitank models simulate ZOB and hillslope hydrological response, while kinematic wave models pr...
Toward improved simulation of river operations through integration with a hydrologic model
Morway, Eric D.; Niswonger, Richard G.; Triana, Enrique
2016-01-01
Advanced modeling tools are needed for informed water resources planning and management. Two classes of modeling tools are often used to this end–(1) distributed-parameter hydrologic models for quantifying supply and (2) river-operation models for sorting out demands under rule-based systems such as the prior-appropriation doctrine. Within each of these two broad classes of models, there are many software tools that excel at simulating the processes specific to each discipline, but have historically over-simplified, or at worse completely neglected, aspects of the other. As a result, water managers reliant on river-operation models for administering water resources need improved tools for representing spatially and temporally varying groundwater resources in conjunctive-use systems. A new tool is described that improves the representation of groundwater/surface-water (GW-SW) interaction within a river-operations modeling context and, in so doing, advances evaluation of system-wide hydrologic consequences of new or altered management regimes.
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.
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
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.
NASA Astrophysics Data System (ADS)
Park, C.; Lee, J.; Koo, M.
2011-12-01
Climate is the most critical driving force of the hydrologic system of the Earth. Since the industrial revolution, the impacts of anthropogenic activities to the Earth environment have been expanded and accelerated. Especially, the global emission of carbon dioxide into the atmosphere is known to have significantly increased temperature and affected the hydrologic system. Many hydrologists have contributed to the studies regarding the climate change on the hydrologic system since the Intergovernmental Panel on Climate Change (IPCC) was created in 1988. Among many components in the hydrologic system groundwater and its response to the climate change and anthropogenic activities are not fully understood due to the complexity of subsurface conditions between the surface and the groundwater table. A new spatio-temporal hydrologic model has been developed to estimate the impacts of climate change and land use dynamics on the groundwater. The model consists of two sub-models: a surface model and a subsurface model. The surface model involves three surface processes: interception, runoff, and evapotranspiration, and the subsurface model does also three subsurface processes: soil moisture balance, recharge, and groundwater flow. The surface model requires various input data including land use, soil types, vegetation types, topographical elevations, and meteorological data. The surface model simulates daily hydrological processes for rainfall interception, surface runoff varied by land use change and crop growth, and evapotranspiration controlled by soil moisture balance. The daily soil moisture balance is a key element to link two sub-models as it calculates infiltration and groundwater recharge by considering a time delay routing through a vadose zone down to the groundwater table. MODFLOW is adopted to simulate groundwater flow and interaction with surface water components as well. The model is technically flexible to add new model or modify existing model as it is developed with an object-oriented language - Python. The model also can easily be localized by simple modification of soil and crop properties. The actual application of the model after calibration was successful and results showed reliable water balance and interaction between the surface and subsurface hydrologic systems.
Hydrology and digital simulation of the regional aquifer system, eastern Snake River Plain, Idaho
Garabedian, S.P.
1992-01-01
The transient model was used to simulate aquifer changes from 1981 to 2010 in response to three hypothetical development alternatives: (1) Continuation of 1980 hydrologic conditions, (2) increased pumpage, and (3) increased recharge. Simulation of continued 1980 hydrologic conditions for 30 years indicated that head declines of 2 to 8 feet might be expected in the central part of the plain. The magnitude of simulated head declines was con- sistent with head declines measured during the 1980 water year. Larger declines were calculated along model boundaries, but these changes may have resulted from underestimation of tribu- tary drainage-basin underflow and inadequate aquifer definition. Simulation of increased ground-water pumpage (an additional 2,400 cubic feet per second) for 30 years indicated head declines of 10 to 50 feet in the central part of the plain. These relatively large head declines were accompanied by increased simulated river leakage of 50 percent and decreased spring discharge of 20 percent. The effect of increased recharge (800 cubic feet per sec- ond) for 30 years was a rise in simulated heads of 0 to 5 feet in the central part of the plain.
Feaster, Toby D.; Benedict, Stephen T.; Clark, Jimmy M.; Bradley, Paul M.; Conrads, Paul
2014-01-01
As part of an ongoing effort by the U.S. Geological Survey to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River Basin, analyses and simulations of the hydrology of the Edisto River Basin were made using the topography-based hydrological model (TOPMODEL). A primary focus of the investigation was to assess the potential for scaling up a previous application of TOPMODEL for the McTier Creek watershed, which is a small headwater catchment to the Edisto River Basin. Scaling up was done in a step-wise manner, beginning with applying the calibration parameters, meteorological data, and topographic-wetness-index data from the McTier Creek TOPMODEL to the Edisto River TOPMODEL. Additional changes were made for subsequent simulations, culminating in the best simulation, which included meteorological and topographic wetness index data from the Edisto River Basin and updated calibration parameters for some of the TOPMODEL calibration parameters. The scaling-up process resulted in nine simulations being made. Simulation 7 best matched the streamflows at station 02175000, Edisto River near Givhans, SC, which was the downstream limit for the TOPMODEL setup, and was obtained by adjusting the scaling factor, including streamflow routing, and using NEXRAD precipitation data for the Edisto River Basin. The Nash-Sutcliffe coefficient of model-fit efficiency and Pearson’s correlation coefficient for simulation 7 were 0.78 and 0.89, respectively. Comparison of goodness-of-fit statistics between measured and simulated daily mean streamflow for the McTier Creek and Edisto River models showed that with calibration, the Edisto River TOPMODEL produced slightly better results than the McTier Creek model, despite the substantial difference in the drainage-area size at the outlet locations for the two models (30.7 and 2,725 square miles, respectively). Along with the TOPMODEL hydrologic simulations, a visualization tool (the Edisto River Data Viewer) was developed to help assess trends and influencing variable in the stream ecosystem. Incorporated into the visualization tool were the water-quality load models TOPLOAD, TOPLOAD–H, and LOADEST. Because the focus of this investigation was on scaling up the models from McTier Creek, water-quality concentrations that were previously collected in the McTier Creek Basin were used in the water-quality load models.
NASA Astrophysics Data System (ADS)
Zhang, Y. Y.; Shao, Q. X.; Ye, A. Z.; Xing, H. T.; Xia, J.
2016-02-01
Integrated water system modeling is a feasible approach to understanding severe water crises in the world and promoting the implementation of integrated river basin management. In this study, a classic hydrological model (the time variant gain model: TVGM) was extended to an integrated water system model by coupling multiple water-related processes in hydrology, biogeochemistry, water quality, and ecology, and considering the interference of human activities. A parameter analysis tool, which included sensitivity analysis, autocalibration and model performance evaluation, was developed to improve modeling efficiency. To demonstrate the model performances, the Shaying River catchment, which is the largest highly regulated and heavily polluted tributary of the Huai River basin in China, was selected as the case study area. The model performances were evaluated on the key water-related components including runoff, water quality, diffuse pollution load (or nonpoint sources) and crop yield. Results showed that our proposed model simulated most components reasonably well. The simulated daily runoff at most regulated and less-regulated stations matched well with the observations. The average correlation coefficient and Nash-Sutcliffe efficiency were 0.85 and 0.70, respectively. Both the simulated low and high flows at most stations were improved when the dam regulation was considered. The daily ammonium-nitrogen (NH4-N) concentration was also well captured with the average correlation coefficient of 0.67. Furthermore, the diffuse source load of NH4-N and the corn yield were reasonably simulated at the administrative region scale. This integrated water system model is expected to improve the simulation performances with extension to more model functionalities, and to provide a scientific basis for the implementation in integrated river basin managements.
NASA Technical Reports Server (NTRS)
Johnson, Donald R.
2001-01-01
This research was directed to the development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. An additional objective was to investigate the accuracy and theoretical limits of global climate predictability which are imposed by the inherent limitations of simulating trace constituent transport and the hydrologic processes of condensation, precipitation and cloud life cycles.
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.
The PCR-GLOBWB global hydrological reanalysis product
NASA Astrophysics Data System (ADS)
Wanders, Niko; Bierkens, Marc; Sutanudjaja, Edwin; van Beek, Rens
2014-05-01
Accurate and long time series of hydrological data are important for understanding land surface water and energy budgets in many parts of the world, as well as for improving real-time hydrological monitoring and climate change anticipation. The ultimate goal of the present work is to produce a multi-decadal "land surface hydrological reanalysis" dataset with retrospective and updated hydrological states and fluxes that are constrained to available in-situ river discharge measurements. Here we use PCR-GLOBWB (van Beek et al., 2011), which is a large-scale hydrological model intended for global to regional studies. PCR-GLOBWB provides a grid-based representation of terrestrial hydrology with a typical spatial resolution of approximately 50×50 km (currently 0.5° globally) on a daily basis. For each grid cell, PCR-GLOBWB simulates moisture storage in two vertically stacked soil layers as well as the water exchange between the soil and the atmosphere and the underlying groundwater reservoir. Exchange to the atmosphere comprises precipitation, evaporation and transpiration, as well as snow accumulation and melt, which are all simulated by considering vegetation phenology and sub-grid variations of elevation, land cover and soil saturation distribution. The model includes improved schemes for runoff-infiltration partitioning, interflow, groundwater recharge and baseflow, as well as river routing of discharge. It also dynamically simulates water storage in reservoirs, water demand and the withdrawal, allocation and consumptive use of surface water and groundwater resources. By embedding the PCR-GLOBWB model in an Ensemble Kalman Filter framework, we calibrate the model parameters based on the discharge observations from the Global Runoff Data Centre. The parameters calibrated are related to snow accumulation and melt, runoff-infiltration partitioning, groundwater recharge, channel discharge and baseflow processes, as well as pre-factors to correct forcing precipitation fields with consideration of local topographic and orographic effects. Results show that the model parameters can be successfully calibrated, while corrections to the forcing precipitation fields are substantial. Topography has the largest impact on the corrected precipitation and globally the precipitation is reduced by 3%. The calibrated model output is compared to the reference run of PCR-GLOBWB before calibration showing significant improvement in simulation of the global terrestrial water cycle. The RMSE is reduced by 10% on average, leading to improved discharge simulations, especially under base flow situations. The main outcome of this work is a 1960-2010 global reanalysis dataset that includes extensive daily hydrological components, such as precipitation, evaporation and transpiration, snow, soil moisture, groundwater storage and discharge. This reanalysis product may be used for understanding land surface memory processes, initializing regional studies and operational forecasts, as well as evaluating and improving our understanding of spatio-temporal variation of meteorological and hydrological processes. Moreover, The PCR-GLOBWB data assimilation framework developed in this work can also be extended by including more observational data, including remotely sensed data reflecting the distribution of energy and water (e.g., heat fluxes and soil moisture storage).
Hydrologic modeling of Guinale River Basin using HEC-HMS and synthetic aperture radar
NASA Astrophysics Data System (ADS)
Bien, Ferdinand E.; Plopenio, Joanaviva C.
2017-09-01
This paper presents the methods and results of hydrologic modeling of Guinale river basin through the use of HEC-HMS software and Synthetic Aperture Radar Digital Elevation Model (SAR DEM). Guinale River Basin is located in the province of Albay, Philippines which is one of the river basins covered by the Ateneo de Naga University (ADNU) Phil-LiDAR 1. This research project was funded by the Department of Science and Technology (DOST) through the Philippine Council for Industry, Energy and Emerging Technology Research and Development (PCIEERD). Its objectives are to simulate the hydrologic model of Guinale River basin using HEC-HMS software and SAR DEM. Its basin covers an area of 165.395 sq.km. and the hydrologic model was calibrated using the storm event typhoon Nona (international name Melor). Its parameter had undergone a series of optimization processes of HEC-HMS software in order to produce an acceptable level of model efficiency. The Nash-Sutcliffe (E), Percent Bias and Standard Deviation Ratio were used to measure the model efficiency, giving values of 0.880, 0.260 and 0.346 respectively which resulted to a "very good" performance rating of the model. The flood inundation model was simulated using Legazpi Rainfall Intensity Duration Frequency Curves (RIDF) and HEC-RAS software developed by the US Army corps of Engineers (USACE). This hydrologic model will provide the Municipal Disaster Risk Reduction Management Office (MDRRMO), Local Government units (LGUs) and the community a tool for the prediction of runoff in the area.
Chen, J.; Wu, Y.
2012-01-01
This paper presents a study of the integration of the Soil and Water Assessment Tool (SWAT) model and the TOPographic MODEL (TOPMODEL) features for enhancing the physical representation of hydrologic processes. In SWAT, four hydrologic processes, which are surface runoff, baseflow, groundwater re-evaporation and deep aquifer percolation, are modeled by using a group of empirical equations. The empirical equations usually constrain the simulation capability of relevant processes. To replace these equations and to model the influences of topography and water table variation on streamflow generation, the TOPMODEL features are integrated into SWAT, and a new model, the so-called SWAT-TOP, is developed. In the new model, the process of deep aquifer percolation is removed, the concept of groundwater re-evaporation is refined, and the processes of surface runoff and baseflow are remodeled. Consequently, three parameters in SWAT are discarded, and two new parameters to reflect the TOPMODEL features are introduced. SWAT-TOP and SWAT are applied to the East River basin in South China, and the results reveal that, compared with SWAT, the new model can provide a more reasonable simulation of the hydrologic processes of surface runoff, groundwater re-evaporation, and baseflow. This study evidences that an established hydrologic model can be further improved by integrating the features of another model, which is a possible way to enhance our understanding of the workings of catchments.
NASA Astrophysics Data System (ADS)
Yamana, Teresa K.; Eltahir, Elfatih A. B.
2011-02-01
This paper describes the use of satellite-based estimates of rainfall to force the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS), a hydrology-based mechanistic model of malaria transmission. We first examined the temporal resolution of rainfall input required by HYDREMATS. Simulations conducted over Banizoumbou village in Niger showed that for reasonably accurate simulation of mosquito populations, the model requires rainfall data with at least 1 h resolution. We then investigated whether HYDREMATS could be effectively forced by satellite-based estimates of rainfall instead of ground-based observations. The Climate Prediction Center morphing technique (CMORPH) precipitation estimates distributed by the National Oceanic and Atmospheric Administration are available at a 30 min temporal resolution and 8 km spatial resolution. We compared mosquito populations simulated by HYDREMATS when the model is forced by adjusted CMORPH estimates and by ground observations. The results demonstrate that adjusted rainfall estimates from satellites can be used with a mechanistic model to accurately simulate the dynamics of mosquito populations.
VELMA (Visualizing Ecosystem Land Management Assessments) is an eco-hydrological model that produces visual simulations of many hydrologic and ecological processes over time periods from hours to days to years. The purpose thus far has been used for predicting effectiveness of g...
A Model for Wetland Hydrology: Description and Validation
R.S. Mansell; S.A. Bloom; Ge Sun
2000-01-01
WETLANDS, a multidimensional model describing water flow in variably saturated soil and evapotranspiration, was used to simulate successfully 3-years of local hydrology for a cypress pond located within a relatively flat Coastal Plain pine forest landscape. Assumptions included negligible net regional groundwater flow and radially symmetric local flow impinging on a...
Rapid methods for radionuclide contaminant transport in nuclear fuel cycle simulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Huff, Kathryn
Here, nuclear fuel cycle and nuclear waste disposal decisions are technologically coupled. However, current nuclear fuel cycle simulators lack dynamic repository performance analysis due to the computational burden of high-fidelity hydrolgic contaminant transport models. The Cyder disposal environment and repository module was developed to fill this gap. It implements medium-fidelity hydrologic radionuclide transport models to support assessment appropriate for fuel cycle simulation in the Cyclus fuel cycle simulator. Rapid modeling of hundreds of discrete waste packages in a geologic environment is enabled within this module by a suite of four closed form models for advective, dispersive, coupled, and idealized con-more » taminant transport: a Degradation Rate model, a Mixed Cell model, a Lumped Parameter model, and a 1-D Permeable Porous Medium model. A summary of the Cyder module, its timestepping algorithm, and the mathematical models implemented within it are presented. Additionally, parametric demonstrations simulations performed with Cyder are presented and shown to demonstrate functional agreement with parametric simulations conducted in a standalone hydrologic transport model, the Clay Generic Disposal System Model developed by the Used Fuel Disposition Campaign Department of Energy Office of Nuclear Energy.« less
Rapid methods for radionuclide contaminant transport in nuclear fuel cycle simulation
Huff, Kathryn
2017-08-01
Here, nuclear fuel cycle and nuclear waste disposal decisions are technologically coupled. However, current nuclear fuel cycle simulators lack dynamic repository performance analysis due to the computational burden of high-fidelity hydrolgic contaminant transport models. The Cyder disposal environment and repository module was developed to fill this gap. It implements medium-fidelity hydrologic radionuclide transport models to support assessment appropriate for fuel cycle simulation in the Cyclus fuel cycle simulator. Rapid modeling of hundreds of discrete waste packages in a geologic environment is enabled within this module by a suite of four closed form models for advective, dispersive, coupled, and idealized con-more » taminant transport: a Degradation Rate model, a Mixed Cell model, a Lumped Parameter model, and a 1-D Permeable Porous Medium model. A summary of the Cyder module, its timestepping algorithm, and the mathematical models implemented within it are presented. Additionally, parametric demonstrations simulations performed with Cyder are presented and shown to demonstrate functional agreement with parametric simulations conducted in a standalone hydrologic transport model, the Clay Generic Disposal System Model developed by the Used Fuel Disposition Campaign Department of Energy Office of Nuclear Energy.« less
NASA Astrophysics Data System (ADS)
Hakala, Kirsti; Addor, Nans; Seibert, Jan
2017-04-01
Streamflow stemming from Switzerland's mountainous landscape will be influenced by climate change, which will pose significant challenges to the water management and policy sector. In climate change impact research, the determination of future streamflow is impeded by different sources of uncertainty, which propagate through the model chain. In this research, we explicitly considered the following sources of uncertainty: (1) climate models, (2) downscaling of the climate projections to the catchment scale, (3) bias correction method and (4) parameterization of the hydrological model. We utilize climate projections at the 0.11 degree 12.5 km resolution from the EURO-CORDEX project, which are the most recent climate projections for the European domain. EURO-CORDEX is comprised of regional climate model (RCM) simulations, which have been downscaled from global climate models (GCMs) from the CMIP5 archive, using both dynamical and statistical techniques. Uncertainties are explored by applying a modeling chain involving 14 GCM-RCMs to ten Swiss catchments. We utilize the rainfall-runoff model HBV Light, which has been widely used in operational hydrological forecasting. The Lindström measure, a combination of model efficiency and volume error, was used as an objective function to calibrate HBV Light. Ten best sets of parameters are then achieved by calibrating using the genetic algorithm and Powell optimization (GAP) method. The GAP optimization method is based on the evolution of parameter sets, which works by selecting and recombining high performing parameter sets with each other. Once HBV is calibrated, we then perform a quantitative comparison of the influence of biases inherited from climate model simulations to the biases stemming from the hydrological model. The evaluation is conducted over two time periods: i) 1980-2009 to characterize the simulation realism under the current climate and ii) 2070-2099 to identify the magnitude of the projected change of streamflow under the climate scenarios RCP4.5 and RCP8.5. We utilize two techniques for correcting biases in the climate model output: quantile mapping and a new method, frequency bias correction. The FBC method matches the frequencies between observed and GCM-RCM data. In this way, it can be used to correct for all time scales, which is a known limitation of quantile mapping. A novel approach for the evaluation of the climate simulations and bias correction methods was then applied. Streamflow can be thought of as the "great integrator" of uncertainties. The ability, or the lack thereof, to correctly simulate streamflow is a way to assess the realism of the bias-corrected climate simulations. Long-term monthly mean as well as high and low flow metrics are used to evaluate the realism of the simulations under current climate and to gauge the impacts of climate change on streamflow. Preliminary results show that under present climate, calibration of the hydrological model comprises of a much smaller band of uncertainty in the modeling chain as compared to the bias correction of the GCM-RCMs. Therefore, for future time periods, we expect the bias correction of climate model data to have a greater influence on projected changes in streamflow than the calibration of the hydrological model.
An integrated model of soil, hydrology, and vegetation for carbon dynamics in wetland ecosystems
Yu Zhang; Changsheng Li; Carl C. Trettin; Harbin Li; Ge Sun
2002-01-01
Wetland ecosystems are an important component in global carbon (C) cycles and may exert a large influence on global clinlate change. Predictions of C dynamics require us to consider interactions among many critical factors of soil, hydrology, and vegetation. However, few such integrated C models exist for wetland ecosystems. In this paper, we report a simulation model...
Climate change and northern prairie wetlands: Simulations of long-term dynamics
Poiani, Karen A.; Johnson, W. Carter; Swanson, George A.; Winter, Thomas C.
1996-01-01
A mathematical model (WETSIM 2.0) was used to simulate wetland hydrology and vegetation dynamics over a 32-yr period (1961–1992) in a North Dakota prairie wetland. A hydrology component of the model calculated changes in water storage based on precipitation, evapotranspiration, snowpack, surface runoff, and subsurface inflow. A spatially explicit vegetation component in the model calculated changes in distribution of vegetative cover and open water, depending on water depth, seasonality, and existing type of vegetation.The model reproduced four known dry periods and one extremely wet period during the three decades. One simulated dry period in the early 1980s did not actually occur. Simulated water levels compared favorably with continuous observed water levels outside the calibration period (1990–1992). Changes in vegetative cover were realistic except for years when simulated water levels were significantly different than actual levels. These generally positive results support the use of the model for exploring the effects of possible climate changes on wetland resources.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hanham, R.; Vogt, W.G.; Mickle, M.H.
1986-01-01
This book presents the papers given at a conference on computerized simulation. Topics considered at the conference included expert systems, modeling in electric power systems, power systems operating strategies, energy analysis, a linear programming approach to optimum load shedding in transmission systems, econometrics, simulation in natural gas engineering, solar energy studies, artificial intelligence, vision systems, hydrology, multiprocessors, and flow models.
High-resolution downscaling for hydrological management
NASA Astrophysics Data System (ADS)
Ulbrich, Uwe; Rust, Henning; Meredith, Edmund; Kpogo-Nuwoklo, Komlan; Vagenas, Christos
2017-04-01
Hydrological modellers and water managers require high-resolution climate data to model regional hydrologies and how these may respond to future changes in the large-scale climate. The ability to successfully model such changes and, by extension, critical infrastructure planning is often impeded by a lack of suitable climate data. This typically takes the form of too-coarse data from climate models, which are not sufficiently detailed in either space or time to be able to support water management decisions and hydrological research. BINGO (Bringing INnovation in onGOing water management;
Modelling surface-water depression storage in a Prairie Pothole Region
Hay, Lauren E.; Norton, Parker A.; Viger, Roland; Markstrom, Steven; Regan, R. Steven; Vanderhoof, Melanie
2018-01-01
In this study, the Precipitation-Runoff Modelling System (PRMS) was used to simulate changes in surface-water depression storage in the 1,126-km2 Upper Pipestem Creek basin located within the Prairie Pothole Region of North Dakota, USA. The Prairie Pothole Region is characterized by millions of small water bodies (or surface-water depressions) that provide numerous ecosystem services and are considered an important contribution to the hydrologic cycle. The Upper Pipestem PRMS model was extracted from the U.S. Geological Survey's (USGS) National Hydrologic Model (NHM), developed to support consistent hydrologic modelling across the conterminous United States. The Geospatial Fabric database, created for the USGS NHM, contains hydrologic model parameter values derived from datasets that characterize the physical features of the entire conterminous United States for 109,951 hydrologic response units. Each hydrologic response unit in the Geospatial Fabric was parameterized using aggregated surface-water depression area derived from the National Hydrography Dataset Plus, an integrated suite of application-ready geospatial datasets. This paper presents a calibration strategy for the Upper Pipestem PRMS model that uses normalized lake elevation measurements to calibrate the parameters influencing simulated fractional surface-water depression storage. Results indicate that inclusion of measurements that give an indication of the change in surface-water depression storage in the calibration procedure resulted in accurate changes in surface-water depression storage in the water balance. Regionalized parameterization of the USGS NHM will require a proxy for change in surface-storage to accurately parameterize surface-water depression storage within the USGS NHM.
NASA Astrophysics Data System (ADS)
Macedo, M.; Panday, P. K.; Coe, M. T.; Lefebvre, P.; Castello, L.
2015-12-01
The Amazonian floodplains and wetlands cover one fifth of the basin and are highly productive promoting diverse biological communities and sustaining human populations with fisheries. Seasonal inundation of the floodplains fluctuates in response to drought or extreme rainfall as observed in the recent droughts of 2005 and 2010 where river levels dropped to among the lowest recorded. We model and evaluate the historical (1940-2010) and projected future (2010-2100) impacts of droughts and floods on the floodplain hydrology and inundation dynamics in the central Amazon using the Integrated Biosphere Simulator (IBIS) and the Terrestrial Hydrology Model and Biogeochemistry (THMB). Simulated discharge correlates well with observed discharges for tributaries originating in Brazil but underestimates basins draining regions in the non-Brazilian Amazon (Solimões, Japuŕa, Madeira, and Negro) by greater than 30%. A volume bias-correction from the simulated and observed runoff was used to correct the input precipitation across the major tributaries of the Amazon basin that drain the Andes. Simulated hydrological parameters (discharge, inundated area and river height) using corrected precipitation has a strong correlation with field measured discharge at gauging stations, surface water extent data (Global Inundation Extent from Multi-Satellites (GIEMS) and NASA Earth System Data Records (ESDRs) for inundation), and satellite radar altimetry (TOPEX/POSEIDON altimeter data for 1992-1998 and ENVISAT data for 2002-2010). We also used an ensemble of model outputs participating in the IPCC AR5 to drive two sets of simulations with and without carbon dioxide fertilization for the 2006-2100 period, and evaluated the potential scale and variability of future changes in discharge and inundation dynamics due to the influences of climate change and vegetation response to carbon dioxide fertilization. Preliminary modeled results for future scenarios using Representative Concentration Pathways (RCP) 4.5 indicate decreases in projected discharge and extent of inundated area on the mainstem Amazon by the late 21st century owing to influences of future climate change only.
NASA Astrophysics Data System (ADS)
House, A. R.; Thompson, J. R.; Acreman, M. C.
2016-03-01
Projected changes in climate are likely to substantially impact wetland hydrological conditions that will in turn have implications for wetland ecology. Assessing ecohydrological impacts of climate change requires models that can accurately simulate water levels at the fine-scale resolution to which species and communities respond. Hydrological conditions within the Lambourn Observatory at Boxford, Berkshire, UK were simulated using the physically based, distributed model MIKE SHE, calibrated to contemporary surface and groundwater levels. The site is a 10 ha lowland riparian wetland where complex geological conditions and channel management exert strong influences on the hydrological regime. Projected changes in precipitation, potential evapotranspiration, channel discharge and groundwater level were derived from the UK Climate Projections 2009 ensemble of climate models for the 2080s under different scenarios. Hydrological impacts of climate change differ through the wetland over short distances depending on the degree of groundwater/surface-water interaction. Discrete areas of groundwater upwelling are associated with an exaggerated response of water levels to climate change compared to non-upwelling areas. These are coincident with regions where a weathered chalk layer, which otherwise separates two main aquifers, is absent. Simulated water levels were linked to requirements of the MG8 plant community and Desmoulin's whorl snail (Vertigo moulinsiana) for which the site is designated. Impacts on each are shown to differ spatially and in line with hydrological impacts. Differences in water level requirements for this vegetation community and single species highlight the need for separate management strategies in distinct areas of the wetland.
Model modifications for simulation of flow through stratified rocks in eastern Ohio
Helgesen, J.O.; Razem, A.C.; Larson, S.P.
1982-01-01
A quasi three-dimensional groundwater flow model is being used as part of a study to determine impacts of coal-strip mining on local hydrologic systems. Modifications to the model were necessary to simulate local hydrologic conditions properly. Perched water tables required that the method of calculating vertical flow rate be changed. A head-dependent spring-discharge function and a head-dependent stream aquifer-interchange function were added to the program. Modifications were also made to allow recharge from precipitation to any layer. The modified program, data deck instructions, and sample input and output are presented. (USGS)
NASA Astrophysics Data System (ADS)
Wagener, Thorsten
2017-04-01
We increasingly build and apply hydrologic models that simulate systems beyond the catchment scale. Such models run at regional, national or even continental scales. They therefore offer opportunities for new scientific insights, for example by enabling comparative hydrology or connectivity studies, and for water management, where we might better understand changes to water resources from larger scale activities like agriculture or from hazards such as droughts. However, these models also require us to rethink how we build and evaluate them given that some of the unsolved problems from the catchment scale have not gone away. So what role should such models play in scientific advancement in hydrology? What problems do we still have to resolve before they can fulfill their role? What opportunities for solving these problems are there, but have not yet been utilized? I will provide some thoughts on these issues in the context of the IAHS Panta Rhei initiative and the scientific challenges it has set out for hydrology (Montanari et al., 2013, Hydrological Sciences Journal; McMillan et al., 2016, Hydrological Sciences Journal).
Xi, Qing; Li, Zhao-Fu; Luo, Chuan
2014-05-01
Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.
Amin, M Z M; Shaaban, A J; Ercan, A; Ishida, K; Kavvas, M L; Chen, Z Q; Jang, S
2017-01-01
Impacts of climate change on the hydrologic processes under future climate change conditions were assessed over Muda and Dungun watersheds of Peninsular Malaysia by means of a coupled regional climate and physically-based hydrology model utilizing an ensemble of future climate change projections. An ensemble of 15 different future climate realizations from coarse resolution global climate models' (GCMs) projections for the 21st century was dynamically downscaled to 6km resolution over Peninsular Malaysia by a regional climate model, which was then coupled with the watershed hydrology model WEHY through the atmospheric boundary layer over Muda and Dungun watersheds. Hydrologic simulations were carried out at hourly increments and at hillslope-scale in order to assess the impacts of climate change on the water balances and flooding conditions in the 21st century. The coupled regional climate and hydrology model was simulated for a duration of 90years for each of the 15 realizations. It is demonstrated that the increase in mean monthly flows due to the impact of expected climate change during 2040-2100 is statistically significant from April to May and from July to October at Muda watershed. Also, the increase in mean monthly flows is shown to be significant in November during 2030-2070 and from November to December during 2070-2100 at Dungun watershed. In other words, the impact of the expected climate change will be significant during the northeast and southwest monsoon seasons at Muda watershed and during the northeast monsoon season at Dungun watershed. Furthermore, the flood frequency analyses for both watersheds indicated an overall increasing trend in the second half of the 21st century. Copyright © 2016 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Haris, H.; Chow, M. F.; Usman, F.; Sidek, L. M.; Roseli, Z. A.; Norlida, M. D.
2016-03-01
Urbanization is growing rapidly in Malaysia. Rapid urbanization has known to have several negative impacts towards hydrological cycle due to decreasing of pervious area and deterioration of water quality in stormwater runoff. One of the negative impacts of urbanization is the congestion of the stormwater drainage system and this situation leading to flash flood problem and water quality degradation. There are many urban stormwater management softwares available in the market such as Storm Water Drainage System design and analysis program (DRAINS), Urban Drainage and Sewer Model (MOUSE), InfoWorks River Simulation (InfoWork RS), Hydrological Simulation Program-Fortran (HSPF), Distributed Routing Rainfall-Runoff Model (DR3M), Storm Water Management Model (SWMM), XP Storm Water Management Model (XPSWMM), MIKE-SWMM, Quality-Quantity Simulators (QQS), Storage, Treatment, Overflow, Runoff Model (STORM), and Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS). In this paper, we are going to discuss briefly about several softwares and their functionality, accessibility, characteristics and components in the quantity analysis of the hydrological design software and compare it with MSMA Design Aid and Database. Green Infrastructure (GI) is one of the main topics that has widely been discussed all over the world. Every development in the urban area is related to GI. GI can be defined as green area build in the develop area such as forest, park, wetland or floodway. The role of GI is to improve life standard such as water filtration or flood control. Among the twenty models that have been compared to MSMA SME, ten models were selected to conduct a comprehensive review for this study. These are known to be widely accepted by water resource researchers. These ten tools are further classified into three major categories as models that address the stormwater management ability of GI in terms of quantity and quality, models that have the capability of conducting the economic analysis of GI and models that can address both stormwater management and economic aspects together.
Middle Rio Grande Cooperative Water Model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tidwell, Vince; Passell, Howard
2005-11-01
This is computer simulation model built in a commercial modeling product Called Studio Expert, developed by Powersim, Inc. The simulation model is built in a system dynamics environment, allowing the simulation of the interaction among multiple systems that are all changing over time. The model focuses on hydrology, ecology, demography, and economy of the Middle Rio Grande, with Water as the unifying feature.
Using Unsupervised Learning to Unlock the Potential of Hydrologic Similarity
NASA Astrophysics Data System (ADS)
Chaney, N.; Newman, A. J.
2017-12-01
By clustering environmental data into representative hydrologic response units (HRUs), hydrologic similarity aims to harness the covariance between a system's physical environment and its hydrologic response to create reduced-order models. This is the primary approach through which sub-grid hydrologic processes are represented in large-scale models (e.g., Earth System Models). Although the possibilities of hydrologic similarity are extensive, its practical implementations have been limited to 1-d bins of oversimplistic metrics of hydrologic response (e.g., topographic index)—this is a missed opportunity. In this presentation we will show how unsupervised learning is unlocking the potential of hydrologic similarity; clustering methods enable generalized frameworks to effectively and efficiently harness the petabytes of global environmental data to robustly characterize sub-grid heterogeneity in large-scale models. To illustrate the potential that unsupervised learning has towards advancing hydrologic similarity, we introduce a hierarchical clustering algorithm (HCA) that clusters very high resolution (30-100 meters) elevation, soil, climate, and land cover data to assemble a domain's representative HRUs. These HRUs are then used to parameterize the sub-grid heterogeneity in land surface models; for this study we use the GFDL LM4 model—the land component of the GFDL Earth System Model. To explore HCA and its impacts on the hydrologic system we use a ¼ grid cell in southeastern California as a test site. HCA is used to construct an ensemble of 9 different HRU configurations—each configuration has a different number of HRUs; for each ensemble member LM4 is run between 2002 and 2014 with a 26 year spinup. The analysis of the ensemble of model simulations show that: 1) clustering the high-dimensional environmental data space leads to a robust representation of the role of the physical environment in the coupled water, energy, and carbon cycles at a relatively low number of HRUs; 2) the reduced-order model with around 300 HRUs effectively reproduces the fully distributed model simulation (30 meters) with less than 1/1000 of computational expense; 3) assigning each grid cell of the fully distributed grid to an HRU via HCA enables novel visualization methods for large-scale models—this has significant implications for how these models are applied and evaluated. We will conclude by outlining the potential that this work has within operational prediction systems including numerical weather prediction, Earth System models, and Early Warning systems.
NASA Astrophysics Data System (ADS)
Troselj, Josko; Sayama, Takahiro; Varlamov, Sergey M.; Sasaki, Toshiharu; Racault, Marie-Fanny; Takara, Kaoru; Miyazawa, Yasumasa; Kuroki, Ryusuke; Yamagata, Toshio; Yamashiki, Yosuke
2017-12-01
This study demonstrates the importance of accurate extreme discharge input in hydrological and oceanographic combined modeling by introducing two extreme typhoon events. We investigated the effects of extreme freshwater outflow events from river mouths on sea surface salinity distribution (SSS) in the coastal zone of the north-eastern Japan. Previous studies have used observed discharge at the river mouth, as well as seasonally averaged inter-annual, annual, monthly or daily simulated data. Here, we reproduced the hourly peak discharge during two typhoon events for a targeted set of nine rivers and compared their impact on SSS in the coastal zone based on observed, climatological and simulated freshwater outflows in conjunction with verification of the results using satellite remote-sensing data. We created a set of hourly simulated freshwater outflow data from nine first-class Japanese river basins flowing to the western Pacific Ocean for the two targeted typhoon events (Chataan and Roke) and used it with the integrated hydrological (CDRMV3.1.1) and oceanographic (JCOPE-T) model, to compare the case using climatological mean monthly discharges as freshwater input from rivers with the case using our hydrological model simulated discharges. By using the CDRMV model optimized with the SCE-UA method, we successfully reproduced hindcasts for peak discharges of extreme typhoon events at the river mouths and could consider multiple river basin locations. Modeled SSS results were verified by comparison with Chlorophyll-a distribution, observed by satellite remote sensing. The projection of SSS in the coastal zone became more realistic than without including extreme freshwater outflow. These results suggest that our hydrological models with optimized model parameters calibrated to the Typhoon Roke and Chataan cases can be successfully used to predict runoff values from other extreme precipitation events with similar physical characteristics. Proper simulation of extreme typhoon events provides more realistic coastal SSS and may allow a different scenario analysis with various precipitation inputs for developing a nowcasting analysis in the future.
NASA Astrophysics Data System (ADS)
Ferrant, S.; Le Page, M.; Kerr, Y. H.; Selles, A.; Mermoz, S.; Al-Bitar, A.; Muddu, S.; Gascoin, S.; Marechal, J. C.; Durand, P.; Salmon-Monviola, J.; Ceschia, E.; Bustillo, V.
2016-12-01
Nitrogen transfers at agricultural catchment level are intricately linked to water transfers. Agro-hydrological modeling approaches aim at integrating spatial heterogeneity of catchment physical properties together with agricultural practices to spatially estimate the water and nitrogen cycles. As in hydrology, the calibration schemes are designed to optimize the performance of the temporal dynamics and biases in model simulations, while ignoring the simulated spatial pattern. Yet, crop uses, i.e. transpiration and nitrogen exported by harvest, are the main fluxes at the catchment scale, highly variable in space and time. Geo-information time-series of vegetation and water index with multi-spectral optical detection S2 together with surface roughness time series with C-band radar detection S1 are used to reset soil water holding capacity parameters (depth, porosity) and agricultural practices (sowing date, irrigated area extent) of a crop model coupled with a hydrological model. This study takes two agro-hydrological contexts as demonstrators: 1-spatial nitrogen excess estimation in south-west of France, and 2-groundwater extraction for rice irrigation in south-India. Spatio-temporal patterns are involved in respectively surface water contamination due to over-fertilization and local groundwater shortages due to over-pumping for above rice inundation. Optimized Leaf Area Index profiles are simulated at the satellite images pixel level using an agro-hydrological model to reproduce spatial and temporal crop growth dynamics in south-west of France, improving the in-stream nitrogen fluxes by 12%. Accurate detection of irrigated area extents are obtained with the thresholding method based on optical indices, with a kappa of 0.81 for the dry season 2016. The actual monsoon season is monitored and will be presented. These extents drive the groundwater pumping and are highly variable in time (from 2 to 8% of the total area).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Huang, Maoyi; Hou, Zhangshuan; Leung, Lai-Yung R.
2013-12-01
With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning amore » wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.« less
High resolution modeling of reservoir storage and extent dynamics at the continental scale
NASA Astrophysics Data System (ADS)
Shin, S.; Pokhrel, Y. N.
2017-12-01
Over the past decade, significant progress has been made in developing reservoir schemes in large scale hydrological models to better simulate hydrological fluxes and storages in highly managed river basins. These schemes have been successfully used to study the impact of reservoir operation on global river basins. However, improvements in the existing schemes are needed for hydrological fluxes and storages, especially at the spatial resolution to be used in hyper-resolution hydrological modeling. In this study, we developed a reservoir routing scheme with explicit representation of reservoir storage and extent at the grid scale of 5km or less. Instead of setting reservoir area to a fixed value or diagnosing it using the area-storage equation, which is a commonly used approach in the existing reservoir schemes, we explicitly simulate the inundated storage and area for all grid cells that are within the reservoir extent. This approach enables a better simulation of river-floodplain-reservoir storage by considering both the natural flood and man-made reservoir storage. Results of the seasonal dynamics of reservoir storage, river discharge at the downstream of dams, and the reservoir inundation extent are evaluated with various datasets from ground-observations and satellite measurements. The new model captures the dynamics of these variables with a good accuracy for most of the large reservoirs in the western United States. It is expected that the incorporation of the newly developed reservoir scheme in large-scale land surface models (LSMs) will lead to improved simulation of river flow and terrestrial water storage in highly managed river basins.
NASA Astrophysics Data System (ADS)
Liu, Yaoze; Engel, Bernard A.; Flanagan, Dennis C.; Gitau, Margaret W.; McMillan, Sara K.; Chaubey, Indrajeet; Singh, Shweta
2018-05-01
Best management practices (BMPs) are popular approaches used to improve hydrology and water quality. Uncertainties in BMP effectiveness over time may result in overestimating long-term efficiency in watershed planning strategies. To represent varying long-term BMP effectiveness in hydrologic/water quality models, a high level and forward-looking modeling framework was developed. The components in the framework consist of establishment period efficiency, starting efficiency, efficiency for each storm event, efficiency between maintenance, and efficiency over the life cycle. Combined, they represent long-term efficiency for a specific type of practice and specific environmental concern (runoff/pollutant). An approach for possible implementation of the framework was discussed. The long-term impacts of grass buffer strips (agricultural BMP) and bioretention systems (urban BMP) in reducing total phosphorus were simulated to demonstrate the framework. Data gaps were captured in estimating the long-term performance of the BMPs. A Bayesian method was used to match the simulated distribution of long-term BMP efficiencies with the observed distribution with the assumption that the observed data represented long-term BMP efficiencies. The simulated distribution matched the observed distribution well with only small total predictive uncertainties. With additional data, the same method can be used to further improve the simulation results. The modeling framework and results of this study, which can be adopted in hydrologic/water quality models to better represent long-term BMP effectiveness, can help improve decision support systems for creating long-term stormwater management strategies for watershed management projects.
PRMS-IV, the precipitation-runoff modeling system, version 4
Markstrom, Steven L.; Regan, R. Steve; Hay, Lauren E.; Viger, Roland J.; Webb, Richard M.; Payn, Robert A.; LaFontaine, Jacob H.
2015-01-01
Computer models that simulate the hydrologic cycle at a watershed scale facilitate assessment of variability in climate, biota, geology, and human activities on water availability and flow. This report describes an updated version of the Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of various combinations of climate and land use on streamflow and general watershed hydrology. Several new model components were developed, and all existing components were updated, to enhance performance and supportability. This report describes the history, application, concepts, organization, and mathematical formulation of the Precipitation-Runoff Modeling System and its model components. This updated version provides improvements in (1) system flexibility for integrated science, (2) verification of conservation of water during simulation, (3) methods for spatial distribution of climate boundary conditions, and (4) methods for simulation of soil-water flow and storage.
NASA Astrophysics Data System (ADS)
Santos, Léonard; Thirel, Guillaume; Perrin, Charles
2017-04-01
Errors made by hydrological models may come from a problem in parameter estimation, uncertainty on observed measurements, numerical problems and from the model conceptualization that simplifies the reality. Here we focus on this last issue of hydrological modeling. One of the solutions to reduce structural uncertainty is to use a multimodel method, taking advantage of the great number and the variability of existing hydrological models. In particular, because different models are not similarly good in all situations, using multimodel approaches can improve the robustness of modeled outputs. Traditionally, in hydrology, multimodel methods are based on the output of the model (the simulated flow series). The aim of this poster is to introduce a different approach based on the internal variables of the models. The method is inspired by the SUper MOdel (SUMO, van den Berge et al., 2011) developed for climatology. The idea of the SUMO method is to correct the internal variables of a model taking into account the values of the internal variables of (an)other model(s). This correction is made bilaterally between the different models. The ensemble of the different models constitutes a super model in which all the models exchange information on their internal variables with each other at each time step. Due to this continuity in the exchanges, this multimodel algorithm is more dynamic than traditional multimodel methods. The method will be first tested using two GR4J models (in a state-space representation) with different parameterizations. The results will be presented and compared to traditional multimodel methods that will serve as benchmarks. In the future, other rainfall-runoff models will be used in the super model. References van den Berge, L. A., Selten, F. M., Wiegerinck, W., and Duane, G. S. (2011). A multi-model ensemble method that combines imperfect models through learning. Earth System Dynamics, 2(1) :161-177.
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.
NASA Astrophysics Data System (ADS)
Le Vine, N.; Butler, A.; McIntyre, N.; Jackson, C.
2015-08-01
Land Surface Models (LSMs) are prospective starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. A diagnostic approach to model evaluation is taken here that exploits hydrological expert knowledge to detect LSM inadequacies through consideration of the major behavioural functions of a hydrological system: overall water balance, vertical water redistribution in the unsaturated zone, temporal water redistribution and spatial water redistribution over the catchment's groundwater and surface water systems. Three types of information are utilised to improve the model's hydrology: (a) observations, (b) information about expected response from regionalised data, and (c) information from an independent physics-based model. The study considers the JULES (Joint UK Land Environmental Simulator) LSM applied to a deep-groundwater chalk catchment in the UK. The diagnosed hydrological limitations and the proposed ways to address them are indicative of the challenges faced while transitioning to a global high resolution model of the water cycle.
NASA Astrophysics Data System (ADS)
Le Vine, N.; Butler, A.; McIntyre, N.; Jackson, C.
2016-01-01
Land surface models (LSMs) are prospective starting points to develop a global hyper-resolution model of the terrestrial water, energy, and biogeochemical cycles. However, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. A diagnostic approach to model evaluation and improvement is taken here that exploits hydrological expert knowledge to detect LSM inadequacies through consideration of the major behavioural functions of a hydrological system: overall water balance, vertical water redistribution in the unsaturated zone, temporal water redistribution, and spatial water redistribution over the catchment's groundwater and surface-water systems. Three types of information are utilized to improve the model's hydrology: (a) observations, (b) information about expected response from regionalized data, and (c) information from an independent physics-based model. The study considers the JULES (Joint UK Land Environmental Simulator) LSM applied to a deep-groundwater chalk catchment in the UK. The diagnosed hydrological limitations and the proposed ways to address them are indicative of the challenges faced while transitioning to a global high resolution model of the water cycle.
NASA Astrophysics Data System (ADS)
Maxwell, R. M.; Condon, L. E.; Atchley, A. L.; Hector, B.
2017-12-01
Quantifying the available freshwater for human use and ecological function depends on fluxes and stores that are hard to observe. Evapotranspiration (ET) is the largest terrestrial flux of water behind precipitation but is observed with low spatial density. Likewise, groundwater is the largest freshwater store, yet is equally uncertain. The ability to upscale observations of these variables is an additional complication; point measurements are made at scales orders of magnitude smaller than remote sensing data products. Integrated hydrologic models that simulate continental extents at fine spatial resolution are now becoming an additional tool to constrain fluxes and address interconnections. For example, recent work has shown connections between water table depth and transpiration partitioning, and demonstrated the ability to reconcile point observations and large-scale inferences. Here we explore the dynamics of large hydrologic systems experiencing change and stress across continental North America using integrated model simulations, observations and data products. Simulations of aquifer depletion due to pervasive groundwater pumping diagnose both stream depletion and changes in ET. Simulations of systematic increases in temperature are used to understand the relationship between snowpack dynamics, surface and groundwater flow, ET and a changing climate. Remotely sensed products including the GRACE estimates of total storage change are downscaled using model simulations to better understand human impacts to the hydrologic cycle. These example applications motivate a path forward to better use simulations to understand water availability.
Developing of operational hydro-meteorological simulating and displaying system
NASA Astrophysics Data System (ADS)
Wang, Y.; Shih, D.; Chen, C.
2010-12-01
Hydrological hazards, which often occur in conjunction with extreme precipitation events, are the most frequent type of natural disaster in Taiwan. Hence, the researchers at the Taiwan Typhoon and Flood Research Institute (TTFRI) are devoted to analyzing and gaining a better understanding of the causes and effects of natural disasters, and in particular, typhoons and floods. The long-term goal of the TTFRI is to develop a unified weather-hydrological-oceanic model suitable for simulations with local parameterizations in Taiwan. The development of a fully coupled weather-hydrology interaction model is not yet completed but some operational hydro-meteorological simulations are presented as a step in the direction of completing a full model. The predicted rainfall data from Weather Research Forecasting (WRF) are used as our meteorological forcing on watershed modeling. The hydrology and hydraulic modeling are conducted by WASH123D numerical model. And the WRF/WASH123D coupled system is applied to simulate floods during the typhoon landfall periods. The daily operational runs start at 04UTC, 10UTC, 16UTC and 22UTC, about 4 hours after data downloaded from NCEP GFS. This system will execute 72-hr weather forecasts. The simulation of WASH123D will sequentially trigger after receiving WRF rainfall data. This study presents the preliminary framework of establishing this system, and our goal is to build this earlier warning system to alert the public form dangerous. The simulation results are further display by a 3D GIS web service system. This system is established following the Open Geospatial Consortium (OGC) standardization process for GIS web service, such as Web Map Service (WMS) and Web Feature Service (WFS). The traditional 2D GIS data, such as high resolution aerial photomaps and satellite images are integrated into 3D landscape model. The simulated flooding and inundation area can be dynamically mapped on Wed 3D world. The final goal of this system is to real-time forecast flood and the results can be visually displayed on the virtual catchment. The policymaker can easily and real-time gain visual information for decision making at any site through internet.
SIMULATION MODEL FOR WATERSHED MANAGEMENT PLANNING. VOLUME 2. MODEL USER MANUAL
This report provides a user manual for the hydrologic, nonpoint source pollution simulation of the generalized planning model for evaluating forest and farming management alternatives. The manual contains an explanation of application of specific code and indicates changes that s...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kleidon, Alex; Kravitz, Benjamin S.; Renner, Maik
2015-01-16
We derive analytic expressions of the transient response of the hydrological cycle to surface warming from an extremely simple energy balance model in which turbulent heat fluxes are constrained by the thermodynamic limit of maximum power. For a given magnitude of steady-state temperature change, this approach predicts the transient response as well as the steady-state change in surface energy partitioning and the hydrologic cycle. We show that the transient behavior of the simple model as well as the steady state hydrological sensitivities to greenhouse warming and solar geoengineering are comparable to results from simulations using highly complex models. Many ofmore » the global-scale hydrological cycle changes can be understood from a surface energy balance perspective, and our thermodynamically-constrained approach provides a physically robust way of estimating global hydrological changes in response to altered radiative forcing.« less
Mohammed, Ibrahim Nourein; Bolten, John D; Srinivasan, Raghavan; Lakshmi, Venkat
2018-06-01
Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region's hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling.
Mohammed, Ibrahim Nourein; Bolten, John D.; Srinivasan, Raghavan; Lakshmi, Venkat
2018-01-01
Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region’s hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling. PMID:29938116
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dai, Heng; Ye, Ming; Walker, Anthony P.
Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averagingmore » methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less
Hydrology and phosphorus transport simulation in a lowland polder by a coupled modeling system.
Yan, Renhua; Huang, Jiacong; Li, Lingling; Gao, Junfeng
2017-08-01
Modeling the rain-runoff processes and phosphorus transport processes in lowland polders is critical in finding reasonable measures to alleviate the eutrophication problem of downstream rivers and lakes. This study develops a lowland Polder Hydrology and Phosphorus modeling System (PHPS) by coupling the WALRUS-paddy model and an improved phosphorus module of a Phosphorus Dynamic model for lowland Polder systems (PDP). It considers some important hydrological characteristics, such as groundwater-unsaturated zone coupling, groundwater-surface water feedback, human-controlled irrigation and discharge, and detailed physical and biochemical cycles of phosphorus in surface water. The application of the model in the Jianwei polder shows that the simulated phosphorus matches well with the measured values. The high precision of this model combined with its low input data requirement and efficient computation make it practical and easy to the water resources management of Chinese polders. Parameter sensitivity analysis demonstrates that K uptake , c Q2 , c W1 , and c Q1 exert a significant effect on the modeled results, whereas K resuspensionMax , K settling , and K mineralization have little effect on the modeled total phosphorus. Among the three types of uncertainties (i.e., parameter, initial condition, and forcing uncertainties), forcing uncertainty produces the strongest effect on the simulated phosphorus. Based on the analysis result of annual phosphorus balance when considering the high import from irrigation and fertilization, lowland polder is capable of retaining phosphorus and reducing phosphorus export to surrounding aquatic ecosystems because of their special hydrological regulation regime. Copyright © 2016 Elsevier Ltd. All rights reserved.
Evaluation TRMM Rainfall Data In Hydrological Modeling For An Ungaged In Lhasa River Basin
NASA Astrophysics Data System (ADS)
Ji, H. J.; Liu, J.
2017-12-01
Evaluation TRMM Rainfall Data In Hydrological Modeling For An Ungaged In Lhasa River BasinHaijuan Ji1* Jintao Liu1,2 Shanshan Xu1___________________ 1College of Hydrology and Water Resources, Hohai University, Nanjing 210098, People's Republic of China 2State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, People's Republic of China ___________________ * Corresponding author. Tel.: +86-025-83786973; Fax: +86-025-83786606. E-mail address: Hhu201510@163.com (H.J. Ji). Abstract: The Tibetan Plateau plays an important role in regulating the regional hydrological processes due to its high elevations and being the headwaters of many major Asian river basins. If familiar with the distribution of hydrological characteristics, will help us improve the level of development and utilization the water resources. However, there exist glaciers and snow with few sites. It is significance for us to understand the glacier and snow hydrological process in order to recognize the evolution of water resources in the Tibetan. This manuscript takes Lhasa River as the study area, taking use of ground, remote sensing and assimilation data, taking advantage of high precision TRMM precipitation data and MODIS snow cover data, first, according to the data from ground station evaluation of TRMM data in the application of the accuracy of the Lhasa River, and based on MODIS data fusion of multi source microwave snow making cloudless snow products, which are used for discriminant and analysis glacier and snow regulation mechanism on day scale, add snow and glacier unit into xinanjing model, this model can simulate the study region's runoff evolution, parameter sensitivity even spatial variation of hydrological characteristics the next ten years on region grid scale. The results of hydrological model in Lhasa River can simulate the glacier and snow runoff variation in high cold region better, to enhance the predictive ability of the spring snow disaster.
Accelerating advances in continental domain hydrologic modeling
Archfield, Stacey A.; Clark, Martyn; Arheimer, Berit; Hay, Lauren E.; McMillan, Hilary; Kiang, Julie E.; Seibert, Jan; Hakala, Kirsti; Bock, Andrew R.; Wagener, Thorsten; Farmer, William H.; Andreassian, Vazken; Attinger, Sabine; Viglione, Alberto; Knight, Rodney; Markstrom, Steven; Over, Thomas M.
2015-01-01
In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.
NASA Astrophysics Data System (ADS)
Leirião, Sílvia; He, Xin; Christiansen, Lars; Andersen, Ole B.; Bauer-Gottwein, Peter
2009-02-01
SummaryTotal water storage change in the subsurface is a key component of the global, regional and local water balances. It is partly responsible for temporal variations of the earth's gravity field in the micro-Gal (1 μGal = 10 -8 m s -2) range. Measurements of temporal gravity variations can thus be used to determine the water storage change in the hydrological system. A numerical method for the calculation of temporal gravity changes from the output of hydrological models is developed. Gravity changes due to incremental prismatic mass storage in the hydrological model cells are determined to give an accurate 3D gravity effect. The method is implemented in MATLAB and can be used jointly with any hydrological simulation tool. The method is composed of three components: the prism formula, the MacMillan formula and the point-mass approximation. With increasing normalized distance between the storage prism and the measurement location the algorithm switches first from the prism equation to the MacMillan formula and finally to the simple point-mass approximation. The method was used to calculate the gravity signal produced by an aquifer pump test. Results are in excellent agreement with the direct numerical integration of the Theis well solution and the semi-analytical results presented in [Damiata, B.N., and Lee, T.-C., 2006. Simulated gravitational response to hydraulic testing of unconfined aquifers. Journal of Hydrology 318, 348-359]. However, the presented method can be used to forward calculate hydrology-induced temporal variations in gravity from any hydrological model, provided earth curvature effects can be neglected. The method allows for the routine assimilation of ground-based gravity data into hydrological models.
NASA Astrophysics Data System (ADS)
Vithanage, J.; Miller, S. N.; Paige, G. B.; Liu, T.
2017-12-01
We present a novel way to simulate the effects of rangeland management decisions in a GIS-based hydrologic modeling toolkit. We have implemented updates to the Automated Geospatial Watershed Assessment tool (AGWA) in which a landscape can be broken into management units (e.g., high intensity grazing, low intensity grazing, fire management, and unmanaged), each of which is assigned a different hydraulic conductivity (Ks) parameter in KINEmatic Runoff and EROSion model (KINEROS2). These updates are designed to provide modeling support to land managers tasked with rangeland watershed management planning and/or monitoring, and evaluation of water resources management. Changes to hydrologic processes and resulting hydrographs and sedigraphs are simulated within the AGWA framework. Case studies are presented in which a user selects various management scenarios and design storms, and the model identifies areas that become susceptible to change as a consequence of management decisions. The baseline (unmanaged) scenario is built using commonly available GIS data, after which the watershed is subdivided into management units. We used an array of design storms with various return periods and frequencies to evaluate the impact of management practices while changing the scale of watershed. Watershed parameters governing interception, infiltration, and surface runoff were determined with the aid of literature published on research studies carried out in the Walnut Gulch Experimental Watershed in southeast Arizona. We observed varied, but significant changes in hydrological responses (runoff) with different management practices as well with varied scales of watersheds. Results show that the toolkit can be used to quantify potential hydrologic change as a result of unitized land use decision-making.
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.
Leavesley, G.; Hay, L.
1998-01-01
Coupled atmospheric and hydrological models provide an opportunity for the improved management of water resources in headwater basins. Issues currently limiting full implementation of coupled-model methodologies include (a) the degree of uncertainty in the accuracy of precipitation and other meteorological variables simulated by atmospheric models, and (b) the problem of discordant scales between atmospheric and bydrological models. Alternative methodologies being developed to address these issues are reviewed.
NASA Astrophysics Data System (ADS)
Baroni, G.; Gräff, T.; Reinstorf, F.; Oswald, S. E.
2012-04-01
Nowadays uncertainty and sensitivity analysis are considered basic tools for the assessment of hydrological models and the evaluation of the most important sources of uncertainty. In this context, in the last decades several methods have been developed and applied in different hydrological conditions. However, in most of the cases, the studies have been done by investigating mainly the influence of the parameter uncertainty on the simulated outputs and few approaches tried to consider also other sources of uncertainty i.e. input and model structure. Moreover, several constrains arise when spatially distributed parameters are involved. To overcome these limitations a general probabilistic framework based on Monte Carlo simulations and the Sobol method has been proposed. In this study, the general probabilistic framework was applied at field scale using a 1D physical-based hydrological model (SWAP). Furthermore, the framework was extended at catchment scale in combination with a spatially distributed hydrological model (SHETRAN). The models are applied in two different experimental sites in Germany: a relatively flat cropped field close to Potsdam (Brandenburg) and a small mountainous catchment with agricultural land use (Schaefertal, Harz Mountains). For both cases, input and parameters are considered as major sources of uncertainty. Evaluation of the models was based on soil moisture detected at plot scale in different depths and, for the catchment site, also with daily discharge values. The study shows how the framework can take into account all the various sources of uncertainty i.e. input data, parameters (either in scalar or spatially distributed form) and model structures. The framework can be used in a loop in order to optimize further monitoring activities used to improve the performance of the model. In the particular applications, the results show how the sources of uncertainty are specific for each process considered. The influence of the input data as well as the presence of compensating errors become clear by the different processes simulated.
Hydrological characterization of Guadalquivir River Basin for the period 1980-2010 using VIC model
NASA Astrophysics Data System (ADS)
García-Valdecasas-Ojeda, Matilde; de Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María
2017-04-01
This study analyzes the changes of soil moisture and real evapotranspiration (ETR), during the last 30 years, in the Guadalquivir River Basin, located in the south of the Iberian Peninsula. Soil moisture content is related with the different components of the real evaporation, it is a relevant factor when analyzing the intensity of droughts and heat waves, and particularly, for the impact study of the climate change. The soil moisture and real evapotranspiration data consist of simulations obtained by using the Variable Infiltration Capacity (VIC) hydrological model. This is a large-scale hydrologic model and allows the estimations of different variables in the hydrological system of a basin. Land surface is modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), while water influx is local, only depending from the interaction between grid cell and local atmosphere environment. Observational data of temperature and precipitation from Spain02 dataset have been used as input variables for VIC model. Additionally, estimates of actual evapotranspiration and soil moisture are also analyzed using temperature, precipitation, wind, humidity and radiation as input variables for VIC. These variables are obtained from a dynamical downscaling from ERA-Interim data by the Weather Research and Forecasting (WRF) model. The simulations have a spatial resolution about 9 km and the analysis is done on a seasonal time-scale. Preliminary results show that ETR presents very low values for autumn from WRF simulations compared with VIC simulations. Only significant positive trends are found during autumn for the western part of the basin for the ETR obtained with VIC model, meanwhile no significant trends are found for the ETR WRF simulations. Keywords: Soil moisture, Real evapotranspiration, Guadalquivir Basin, trends, VIC, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).
USDA-ARS?s Scientific Manuscript database
In this paper we proposed: (1) an algorithm of glacier melt, sublimation/evaporation, accumulation, mass balance and retreat; (2) a dynamic Hydrological Response Unit approach for incorporating the algorithm into the Soil and Water Assessment Tool (SWAT) model; and (3) simulated the transient glacie...
Modelling hydrology of a single bioretention system with HYDRUS-1D.
Meng, Yingying; Wang, Huixiao; Chen, Jiangang; Zhang, Shuhan
2014-01-01
A study was carried out on the effectiveness of bioretention systems to abate stormwater using computer simulation. The hydrologic performance was simulated for two bioretention cells using HYDRUS-1D, and the simulation results were verified by field data of nearly four years. Using the validated model, the optimization of design parameters of rainfall return period, filter media depth and type, and surface area was discussed. And the annual hydrologic performance of bioretention systems was further analyzed under the optimized parameters. The study reveals that bioretention systems with underdrains and impervious boundaries do have some detention capability, while their total water retention capability is extremely limited. Better detention capability is noted for smaller rainfall events, deeper filter media, and design storms with a return period smaller than 2 years, and a cost-effective filter media depth is recommended in bioretention design. Better hydrologic effectiveness is achieved with a higher hydraulic conductivity and ratio of the bioretention surface area to the catchment area, and filter media whose conductivity is between the conductivity of loamy sand and sandy loam, and a surface area of 10% of the catchment area is recommended. In the long-term simulation, both infiltration volume and evapotranspiration are critical for the total rainfall treatment in bioretention systems.
Nustad, Rochelle A.; Wood, Tamara M.; Bales, Jerad D.
2011-01-01
The U.S. Geological Survey in cooperation with the North Dakota Department of Transportation, North Dakota State Water Commission, and U.S. Army Corps of Engineers, developed a two-dimensional hydrodynamic model of Devils Lake and Stump Lake, North Dakota to be used as a hydrologic tool for evaluating the effects of different inflow scenarios on water levels, circulation, and the transport of dissolved solids through the lake. The numerical model, UnTRIM, and data primarily collected during 2006 were used to develop and calibrate the Devils Lake model. Performance of the Devils Lake model was tested using 2009 data. The Devils Lake model was applied to evaluate the effects of an extreme flooding event on water levels and hydrological modifications within the lake on the transport of dissolved solids through Devils Lake and Stump Lake. For the 2006 calibration, simulated water levels in Devils Lake compared well with measured water levels. The maximum simulated water level at site 1 was within 0.13 feet of the maximum measured water level in the calibration, which gives reasonable confidence that the Devils Lake model is able to accurately simulate the maximum water level at site 1 for the extreme flooding scenario. The timing and direction of winddriven fluctuations in water levels on a short time scale (a few hours to a day) were reproduced well by the Devils Lake model. For this application, the Devils Lake model was not optimized for simulation of the current speed through bridge openings. In future applications, simulation of current speed through bridge openings could be improved by more accurate definition of the bathymetry and geometry of select areas in the model grid. As a test of the performance of the Devils Lake model, a simulation of 2009 conditions from April 1 through September 30, 2009 was performed. Overall, errors in inflow estimates affected the results for the 2009 simulation; however, for the rising phase of the lakes, the Devils Lake model accurately simulated the faster rate of rise in Devils Lake than in Stump Lake, and timing and direction of wind-driven fluctuations in water levels on a short time scale were reproduced well. To help the U.S. Army Corps of Engineers determine the elevation to which the protective embankment for the city of Devils Lake should be raised, an extreme flooding scenario based on an inflow of one-half the probable maximum flood was simulated. Under the conditions and assumptions of the extreme flooding scenario, the water level for both lakes reached a maximum water level around 1,461.9 feet above the National Geodetic Vertical Datum of 1929. One factor limiting the extent of pumping from the Devils Lake State Outlet is sulfate concentrations in West Bay. If sulfate concentrations can be reduced in West Bay, pumping from the Devils Lake State Outlet potentially can increase. The Devils Lake model was used to simulate the transport of dissolved solids using specific conductance data as a surrogate for sulfate. Because the transport of dissolved solids was not calibrated, results from the simulations were not actual expected concentrations. However, the effects of hydrological modifications on the transport of dissolved solids could be evaluated by comparing the effects of hydrological modifications relative to a baseline scenario in which no hydrological modifications were made. Four scenarios were simulated: (1) baseline condition (no hydrological modification), (2) diversion of Channel A, (3) reduction of the area of water exchange between Main Bay and East Bay, and (4) combination of scenarios 2 and 3. Relative to scenario 1, mean concentrations in West Bay for scenarios 2 and 4 were reduced by approximately 9 percent. Given that there is no change in concentration for scenario 3, but about a 9-percent reduction in concentration for scenario 4, the diversion of Channel A was the only hydrologic modification that appeared to have the potential to reduce sulfate c
Water and Solute Flux Simulation Using Hydropedology Survey Data in South African Catchments
NASA Astrophysics Data System (ADS)
Lorentz, Simon; van Tol, Johan; le Roux, Pieter
2017-04-01
Hydropedology surveys include linking soil profile information in hillslope transects in order to define dominant subsurface flow mechanisms and pathways. This information is useful for deriving hillslope response functions, which aid storage and travel time estimates of water and solute movement in the sub-surface. In this way, the "soft" data of the hydropedological survey can be included in simple hydrological models, where detailed modelling of processes and pathways is prohibitive. Hydropedology surveys were conducted in two catchments and the information used to improve the prediction of water and solute responses. Typical hillslope response functions are then derived using a 2-D finite element model of the hydropedological features. Similar response types are mapped. These mapped response units are invoked in a simple SCS based, hydrological and solute transport model to yield water and solute fluxes at the catchment outlets. The first catchment (1.6 km2) comprises commercial forestry in a sedimentary geology of sandstone and mudstone formation while the second catchment (6.1 km2) includes mine waste impoundments in a granitic geology. In this paper, we demonstrate the method of combining hydropedological interpretation with catchment hydrology and solute transport simulation. The forested catchment, with three dominant hillslope response types, have solute response times in excess of 90 days, whereas the granitic responses occur within 10 days. The use of the hydropedological data improves the solute distribution response and storage simulation, compared to simulations without the hydropedology interpretation. The hydrological responses are similar, with and without the use of the hydropedology data, but the simulated distribution of water in the catchment is improved using the techniques demonstrated.
NASA Technical Reports Server (NTRS)
Johnson, Kevin D.; Entekhabi, Dara; Eagleson, Peter S.
1991-01-01
Landsurface hydrological parameterizations are implemented in the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: (1) runoff and evapotranspiration functions that include the effects of subgrid scale spatial variability and use physically based equations of hydrologic flux at the soil surface, and (2) a realistic soil moisture diffusion scheme for the movement of water in the soil column. A one dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three dimensional GCM. Results of the final simulation with the GISS GCM and the new landsurface hydrology indicate that the runoff rate, especially in the tropics is significantly improved. As a result, the remaining components of the heat and moisture balance show comparable improvements when compared to observations. The validation of model results is carried from the large global (ocean and landsurface) scale, to the zonal, continental, and finally the finer river basin scales.
Rapp, Jennifer L.; Reilly, Pamela A.
2017-11-14
BackgroundThe U.S. Geological Survey (USGS), in cooperation with the Virginia Department of Environmental Quality (DEQ), reviewed a previously compiled set of linear regression models to assess their utility in defining the response of the aquatic biological community to streamflow depletion.As part of the 2012 Virginia Healthy Watersheds Initiative (HWI) study conducted by Tetra Tech, Inc., for the U.S. Environmental Protection Agency (EPA) and Virginia DEQ, a database with computed values of 72 hydrologic metrics, or indicators of hydrologic alteration (IHA), 37 fish metrics, and 64 benthic invertebrate metrics was compiled and quality assured. Hydrologic alteration was represented by simulation of streamflow record for a pre-water-withdrawal condition (baseline) without dams or developed land, compared to the simulated recent-flow condition (2008 withdrawal simulation) including dams and altered landscape to calculate a percent alteration of flow. Biological samples representing the existing populations represent a range of alteration in the biological community today.For this study, all 72 IHA metrics, which included more than 7,272 linear regression models, were considered. This extensive dataset provided the opportunity for hypothesis testing and prioritization of flow-ecology relations that have the potential to explain the effect(s) of hydrologic alteration on biological metrics in Virginia streams.
Hart, Rheannon M.; Green, W. Reed; Westerman, Drew A.; Petersen, James C.; DeLanois, Jeanne L.
2012-01-01
Lake Maumelle, located in central Arkansas northwest of the cities of Little Rock and North Little Rock, is one of two principal drinking-water supplies for the Little Rock, and North Little Rock, Arkansas, metropolitan areas. Lake Maumelle and the Maumelle River (its primary tributary) are more pristine than most other reservoirs and streams in the region with 80 percent of the land area in the entire watershed being forested. However, as the Lake Maumelle watershed becomes increasingly more urbanized and timber harvesting becomes more extensive, concerns about the sustainability of the quality of the water supply also have increased. Two hydrodynamic and water-quality models were developed to examine the hydrology and water quality in the Lake Maumelle watershed and changes that might occur as the watershed becomes more urbanized and timber harvesting becomes more extensive. A Hydrologic Simulation Program–FORTRAN watershed model was developed using continuous streamflow and discreet suspended-sediment and water-quality data collected from January 2004 through 2010. A CE–QUAL–W2 model was developed to simulate reservoir hydrodynamics and selected water-quality characteristics using the simulated output from the Hydrologic Simulation Program–FORTRAN model from January 2004 through 2010. The calibrated Hydrologic Simulation Program–FORTRAN model and the calibrated CE–QUAL–W2 model were developed to simulate three land-use scenarios and to examine the potential effects of these land-use changes, as defined in the model, on the water quality of Lake Maumelle during the 2004 through 2010 simulation period. These scenarios included a scenario that simulated conversion of most land in the watershed to forest (scenario 1), a scenario that simulated conversion of potentially developable land to low-intensity urban land use in part of the watershed (scenario 2), and a scenario that simulated timber harvest in part of the watershed (scenario 3). Simulated land-use changes for scenarios 1 and 3 resulted in little (generally less than 10 percent) overall effect on the simulated water quality in the Hydrologic Simulation Program–FORTRAN model. The land-use change of scenario 2 affected subwatersheds that include Bringle, Reece, and Yount Creek tributaries and most other subwatersheds that drain into the northern side of Lake Maumelle; large percent increases in loading rates (generally between 10 and 25 percent) included dissolved nitrite plus nitrate nitrogen, dissolved orthophosphate, total phosphorus, suspended sediment, dissolved ammonia nitrogen, total organic carbon, and fecal coliform bacteria. For scenario 1, the simulated changes in nutrient, suspended sediment, and total organic carbon loads from the Hydrologic Simulation Program–FORTRAN model resulted in very slight (generally less than 10 percent) changes in simulated water quality for Lake Maumelle, relative to the baseline condition. Following lake mixing in the falls of 2006 and 2007, phosphorus and nitrogen concentrations were higher than the baseline condition and chlorophyll a responded accordingly. The increased nutrient and chlorophyll a concentrations in late October and into 2007 were enough to increase concentrations, on average, for the entire simulation period (2004–10). For scenario 2, the simulated changes in nutrient, suspended sediment, total organic carbon, and fecal coliform bacteria loads from the Lake Maumelle watershed resulted in slight changes in simulated water quality for Lake Maumelle, relative to the baseline condition (total nitrogen decreased by 0.01 milligram per liter; dissolved orthophosphate increased by 0.001 milligram per liter; chlorophyll a decreased by 0.1 microgram per liter). The differences in these concentrations are approximately an order of magnitude less than the error between measured and simulated concentrations in the baseline model. During the driest summer in the simulation period (2006), phosphorus and nitrogen concentrations were lower than the baseline condition and chlorophyll a concentrations decreased during the same summer season. The decrease in nitrogen and chlorophyll a concentrations during the dry summer in 2006 was enough to decrease concentrations of these constituents very slightly, on average, for the entire simulation period (2004–10). For scenario 3, the changes in simulated nutrient, suspended sediment, total organic carbon, and fecal coliform bacteria loads from Lake Maumelle watershed resulted in very slight changes in simulated water quality within Lake Maumelle, relative to the baseline condition, for most of the reservoir. Among the implications of the results of the modeling described in this report are those related to scale in both space and time. Spatial scales include limited size and location of land-use changes, their effects on loading rates, and resultant effects on water quality of Lake Maumelle. Temporally, the magnitude of the water-quality changes simulated by the land-use change scenarios over the 7-year period (2004–10) are not necessarily indicative of the changes that could be expected to occur with similar land-use changes persisting over a 20-, 30-, or 40- year period, for example. These implications should be tempered by realization of the described model limitations. The Hydrologic Simulation Program–FORTRAN watershed model was calibrated to streamflow and water-quality data from five streamflow-gaging stations, and in general, these stations characterize a range of subwatershed areas with varying land-use types. The CE–QUAL–W2 reservoir model was calibrated to water-quality data collected during January 2004 through December 2010 at three reservoir stations, representing the upper, middle, and lower sections of the reservoir. In general, the baseline simulation for the Hydrologic Simulation Program–FORTRAN and the CE–QUAL–W2 models matched reasonably well to the measured data. Simulated and measured suspended-sediment concentrations during periods of base flow (streamflows not substantially influenced by runoff) agree reasonably well for Maumelle River at Williams Junction, the station representing the upper end of the watershed (with differences—simulated minus measured value—generally ranging from -15 to 41 milligrams per liter, and percent difference—relative to the measured value—ranging from -99 to 182 percent) and Maumelle River near Wye, the station just above the reservoir at the lower end (differences generally ranging from -20 to 22 milligrams per liter, and percent difference ranging from -100 to 194 percent). In general, water temperature and dissolved-oxygen concentration simulations followed measured seasonal trends for all stations with the largest differences occurring during periods of lowest temperatures or during the periods of lowest measured dissolved-oxygen concentrations. For the CE–QUAL–W2 model, simulated vertical distributions of water temperatures and dissolved-oxygen concentrations agreed with measured vertical distributions over time, even for the most complex water-temperature profiles. Considering the oligotrophic-mesotrophic (low to intermediate primary productivity and associated low nutrient concentrations) condition of Lake Maumelle, simulated algae, phosphorus, and nitrogen concentrations compared well with generally low measured concentrations.
Conceptual Modeling Framework for E-Area PA HELP Infiltration Model Simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dyer, J. A.
A conceptual modeling framework based on the proposed E-Area Low-Level Waste Facility (LLWF) closure cap design is presented for conducting Hydrologic Evaluation of Landfill Performance (HELP) model simulations of intact and subsided cap infiltration scenarios for the next E-Area Performance Assessment (PA).
USDA-ARS?s Scientific Manuscript database
Watershed models are calibrated to simulate stream discharge as accurately as possible. Modelers will often calculate model validation statistics on aggregate (often monthly) time periods, rather than the daily step at which models typically operate. This is because daily hydrologic data exhibit lar...
MODELING CONCEPTS FOR BMP/LID SIMULATION
Enhancement of simulation options for stormwater best management practices (BMPs) and hydrologic source control is discussed in the context of the EPA Storm Water Management Model (SWMM). Options for improvement of various BMP representations are presented, with emphasis on inco...
Tradeoffs among watershed model calibration targets for parameter estimation
Hydrologic models are commonly calibrated by optimizing a single objective function target to compare simulated and observed flows, although individual targets are influenced by specific flow modes. Nash-Sutcliffe efficiency (NSE) emphasizes flood peaks in evaluating simulation f...
NASA Astrophysics Data System (ADS)
Guo, B.
2017-12-01
Mountain watershed in Western China is prone to flash floods. The Wenchuan earthquake on May 12, 2008 led to the destruction of surface, and frequent landslides and debris flow, which further exacerbated the flash flood hazards. Two giant torrent and debris flows occurred due to heavy rainfall after the earthquake, one was on August 13 2010, and the other on August 18 2010. Flash floods reduction and risk assessment are the key issues in post-disaster reconstruction. Hydrological prediction models are important and cost-efficient mitigation tools being widely applied. In this paper, hydrological observations and simulation using remote sensing data and the WMS model are carried out in the typical flood-hit area, Longxihe watershed, Dujiangyan City, Sichuan Province, China. The hydrological response of rainfall runoff is discussed. The results show that: the WMS HEC-1 model can well simulate the runoff process of small watershed in mountainous area. This methodology can be used in other earthquake-affected areas for risk assessment and to predict the magnitude of flash floods. Key Words: Rainfall-runoff modeling. Remote Sensing. Earthquake. WMS.
NASA Astrophysics Data System (ADS)
Chiu, C. M.; Hamlet, A. F.
2014-12-01
Climate change is likely to impact the Great Lakes region and Midwest region via changes in Great Lakes water levels, agricultural impacts, river flooding, urban stormwater impacts, drought, water temperature, and impacts to terrestrial and aquatic ecosystems. Self-consistent and temporally homogeneous long-term data sets of precipitation and temperature over the entire Great Lakes region and Midwest regions are needed to provide inputs to hydrologic models, assess historical trends in hydroclimatic variables, and downscale global and regional-scale climate models. To support these needs a new hybrid gridded meteorological forcing dataset at 1/16 degree resolution based on data from co-op station records, the U. S Historical Climatology Network (HCN) , the Historical Canadian Climate Database (HCCD), and Precipitation Regression on Independent Slopes Method (PRISM) has been assembled over the Great Lakes and Midwest region from 1915-2012 at daily time step. These data were then used as inputs to the macro-scale Variable Infiltration Capacity (VIC) hydrology model, implemented over the Midwest and Great Lakes region at 1/16 degree resolution, to produce simulated hydrologic variables that are amenable to long-term trend analysis. Trends in precipitation and temperature from the new meteorological driving data sets, as well as simulated hydrometeorological variables such as snowpack, soil moisture, runoff, and evaporation over the 20th century are presented and discussed.
NASA Astrophysics Data System (ADS)
Ryu, Young; Lim, Yoon-Jin; Ji, Hee-Sook; Park, Hyun-Hee; Chang, Eun-Chul; Kim, Baek-Jo
2017-11-01
In flash flood forecasting, it is necessary to consider not only traditional meteorological variables such as precipitation, evapotranspiration, and soil moisture, but also hydrological components such as streamflow. To address this challenge, the application of high resolution coupled atmospheric-hydrological models is emerging as a promising alternative. This study demonstrates the feasibility of linking a coupled atmospheric-hydrological model (WRF/WRFHydro) with 150-m horizontal grid spacing for flash flood forecasting in Korea. The study area is the Namgang Dam basin in Southern Korea, a mountainous area located downstream of Jiri Mountain (1915 m in height). Under flash flood conditions, the simulated precipitation over the entire basin is comparable to the domain-averaged precipitation, but discharge data from WRF-Hydro shows some differences in the total available water and the temporal distribution of streamflow (given by the timing of the streamflow peak following precipitation), compared to observations. On the basis of sensitivity tests, the parameters controlling the infiltration of excess precipitation and channel roughness depending on stream order are refined and their influence on temporal distribution of streamflow is addressed with intent to apply WRF-Hydro to flash flood forecasting in the Namgang Dam basin. The simulation results from the WRF-Hydro model with optimized parameters demonstrate the potential utility of a coupled atmospheric-hydrological model for forecasting heavy rain-induced flash flooding over the Korean Peninsula.
Scaling up watershed model parameters--Flow and load simulations of the Edisto River Basin
Feaster, Toby D.; Benedict, Stephen T.; Clark, Jimmy M.; Bradley, Paul M.; Conrads, Paul
2014-01-01
The Edisto River is the longest and largest river system completely contained in South Carolina and is one of the longest free flowing blackwater rivers in the United States. The Edisto River basin also has fish-tissue mercury concentrations that are some of the highest recorded in the United States. As part of an effort by the U.S. Geological Survey to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River basin, analyses and simulations of the hydrology of the Edisto River basin were made with the topography-based hydrological model (TOPMODEL). The potential for scaling up a previous application of TOPMODEL for the McTier Creek watershed, which is a small headwater catchment to the Edisto River basin, was assessed. Scaling up was done in a step-wise process beginning with applying the calibration parameters, meteorological data, and topographic wetness index data from the McTier Creek TOPMODEL to the Edisto River TOPMODEL. Additional changes were made with subsequent simulations culminating in the best simulation, which included meteorological and topographic wetness index data from the Edisto River basin and updated calibration parameters for some of the TOPMODEL calibration parameters. Comparison of goodness-of-fit statistics between measured and simulated daily mean streamflow for the two models showed that with calibration, the Edisto River TOPMODEL produced slightly better results than the McTier Creek model, despite the significant difference in the drainage-area size at the outlet locations for the two models (30.7 and 2,725 square miles, respectively). Along with the TOPMODEL hydrologic simulations, a visualization tool (the Edisto River Data Viewer) was developed to help assess trends and influencing variables in the stream ecosystem. Incorporated into the visualization tool were the water-quality load models TOPLOAD, TOPLOAD-H, and LOADEST. Because the focus of this investigation was on scaling up the models from McTier Creek, water-quality concentrations that were previously collected in the McTier Creek basin were used in the water-quality load models.
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.
NASA Astrophysics Data System (ADS)
Jiao, Y.; Yuan, X.; Yang, D.
2017-12-01
During the past five decades, significant decreasing trends in streamflow records were observed at many hydrological gauges within the middle reaches of the Yellow River basin, China, leading to an intensified water resource shortage and a rising hydrological drought risk. This phenomenon is generally considered as a consequence of climate changes and human interventions, such as greenhouse gas emissions, regional land use/cover changes, dam and reservoir constructions and direct water withdrawals. There are many studies on the attribution of streamflow decline and hydrological drought change in this region, while a consolidated conclusion is missing.In this study, we focus on historical and future hydrological drought characteristics over a semi-arid watershed located in the middle reaches of the Yellow River basin. Daily climate simulations from several IPCC CMIP5 models were collected to drive a newly developed eco-hydrological model CLM-GBHM with detailed description of river network and sub-basin topological relationship, to simulate streamflow series under different forcings and scenarios. The standard streamflow index was calculated and used to figure out the characteristics (e.g., frequency, duration and severity) of both historical and future hydrological droughts. The causes and contributions in terms of natural and anthropogenic influences will be investigated based on an optimal fingerprinting method, and the relative importance of internal variability, model and scenario uncertainties for future projections will also be estimated using a separation method. This study will facilitate the implementation of adaptation strategies for hydrological drought over the semi-arid watershed in a changing environment.
Water-Balance Model to Simulate Historical Lake Levels for Lake Merced, California
NASA Astrophysics Data System (ADS)
Maley, M. P.; Onsoy, S.; Debroux, J.; Eagon, B.
2009-12-01
Lake Merced is a freshwater lake located in southwestern San Francisco, California. In the late 1980s and early 1990s, an extended, severe drought impacted the area that resulted in significant declines in Lake Merced lake levels that raised concerns about the long-term health of the lake. In response to these concerns, the Lake Merced Water Level Restoration Project was developed to evaluate an engineered solution to increase and maintain Lake Merced lake levels. The Lake Merced Lake-Level Model was developed to support the conceptual engineering design to restore lake levels. It is a spreadsheet-based water-balance model that performs monthly water-balance calculations based on the hydrological conceptual model. The model independently calculates each water-balance component based on available climate and hydrological data. The model objective was to develop a practical, rule-based approach for the water balance and to calibrate the model results to measured lake levels. The advantage of a rule-based approach is that once the rules are defined, they enhance the ability to then adapt the model for use in future-case simulations. The model was calibrated to historical lake levels over a 70-year period from 1939 to 2009. Calibrating the model over this long historical range tested the model over a variety of hydrological conditions including wet, normal and dry precipitation years, flood events, and periods of high and low lake levels. The historical lake level range was over 16 feet. The model calibration of historical to simulated lake levels had a residual mean of 0.02 feet and an absolute residual mean of 0.42 feet. More importantly, the model demonstrated the ability to simulate both long-term and short-term trends with a strong correlation of the magnitude for both annual and seasonal fluctuations in lake levels. The calibration results demonstrate an improved conceptual understanding of the key hydrological factors that control lake levels, reduce uncertainty in the hydrological conceptual model, and increase confidence in the model’s ability to forecast future lake conditions. The Lake Merced Lake-Level Model will help decision-makers with a straightforward, practical analysis of the major contributions to lake-level declines that can be used to support engineering, environmental and other decisions.
Jung, Kwang-Wook; Yoon, Choon-G; Jang, Jae-Ho; Kong, Dong-Soo
2008-01-01
Effective watershed management often demands qualitative and quantitative predictions of the effect of future management activities as arguments for policy makers and administration. The BASINS geographic information system was developed to compute total maximum daily loads, which are helpful to establish hydrological process and water quality modeling system. In this paper the BASINS toolkit HSPF model is applied in 20,271 km(2) large watershed of the Han River Basin is used for applicability of HSPF and BMPs scenarios. For proper evaluation of watershed and stream water quality, comprehensive estimation methods are necessary to assess large amounts of point source and nonpoint-source (NPS) pollution based on the total watershed area. In this study, The Hydrological Simulation Program-FORTRAN (HSPF) was estimated to simulate watershed pollutant loads containing dam operation and applied BMPs scenarios for control NPS pollution. The 8-day monitoring data (about three years) were used in the calibration and verification processes. Model performance was in the range of "very good" and "good" based on percent difference. The water-quality simulation results were encouraging for this large sizable watershed with dam operation practice and mixed land uses; HSPF proved adequate, and its application is recommended to simulate watershed processes and BMPs evaluation. IWA Publishing 2008.
NASA Astrophysics Data System (ADS)
Hazenberg, P.; Broxton, P. D.; Brunke, M.; Gochis, D.; Niu, G. Y.; Pelletier, J. D.; Troch, P. A. A.; Zeng, X.
2015-12-01
The terrestrial hydrological system, including surface and subsurface water, is an essential component of the Earth's climate system. Over the past few decades, land surface modelers have built one-dimensional (1D) models resolving the vertical flow of water through the soil column for use in Earth system models (ESMs). These models generally have a relatively coarse model grid size (~25-100 km) and only account for sub-grid lateral hydrological variations using simple parameterization schemes. At the same time, hydrologists have developed detailed high-resolution (~0.1-10 km grid size) three dimensional (3D) models and showed the importance of accounting for the vertical and lateral redistribution of surface and subsurface water on soil moisture, the surface energy balance and ecosystem dynamics on these smaller scales. However, computational constraints have limited the implementation of the high-resolution models for continental and global scale applications. The current work presents a hybrid-3D hydrological approach is presented, where the 1D vertical soil column model (available in many ESMs) is coupled with a high-resolution lateral flow model (h2D) to simulate subsurface flow and overland flow. H2D accounts for both local-scale hillslope and regional-scale unconfined aquifer responses (i.e. riparian zone and wetlands). This approach was shown to give comparable results as those obtained by an explicit 3D Richards model for the subsurface, but improves runtime efficiency considerably. The h3D approach is implemented for the Delaware river basin, where Noah-MP land surface model (LSM) is used to calculated vertical energy and water exchanges with the atmosphere using a 10km grid resolution. Noah-MP was coupled within the WRF-Hydro infrastructure with the lateral 1km grid resolution h2D model, for which the average depth-to-bedrock, hillslope width function and soil parameters were estimated from digital datasets. The ability of this h3D approach to simulate the hydrological dynamics of the Delaware River basin will be assessed by comparing the model results (both hydrological performance and numerical efficiency) with the standard setup of the NOAH-MP model and a high-resolution (1km) version of NOAH-MP, which also explicitly accounts for lateral subsurface and overland flow.
Web-Based Model Visualization Tools to Aid in Model Optimization and Uncertainty Analysis
NASA Astrophysics Data System (ADS)
Alder, J.; van Griensven, A.; Meixner, T.
2003-12-01
Individuals applying hydrologic models have a need for a quick easy to use visualization tools to permit them to assess and understand model performance. We present here the Interactive Hydrologic Modeling (IHM) visualization toolbox. The IHM utilizes high-speed Internet access, the portability of the web and the increasing power of modern computers to provide an online toolbox for quick and easy model result visualization. This visualization interface allows for the interpretation and analysis of Monte-Carlo and batch model simulation results. Often times a given project will generate several thousands or even hundreds of thousands simulations. This large number of simulations creates a challenge for post-simulation analysis. IHM's goal is to try to solve this problem by loading all of the data into a database with a web interface that can dynamically generate graphs for the user according to their needs. IHM currently supports: a global samples statistics table (e.g. sum of squares error, sum of absolute differences etc.), top ten simulations table and graphs, graphs of an individual simulation using time step data, objective based dotty plots, threshold based parameter cumulative density function graphs (as used in the regional sensitivity analysis of Spear and Hornberger) and 2D error surface graphs of the parameter space. IHM is ideal for the simplest bucket model to the largest set of Monte-Carlo model simulations with a multi-dimensional parameter and model output space. By using a web interface, IHM offers the user complete flexibility in the sense that they can be anywhere in the world using any operating system. IHM can be a time saving and money saving alternative to spending time producing graphs or conducting analysis that may not be informative or being forced to purchase or use expensive and proprietary software. IHM is a simple, free, method of interpreting and analyzing batch model results, and is suitable for novice to expert hydrologic modelers.
Modelling water use in global hydrological models: review, challenges and directions
NASA Astrophysics Data System (ADS)
Bierkens, M. F.; de Graaf, I.; Wada, Y.; Wanders, N.; Van Beek, L. P.
2017-12-01
During the late 1980s and early 1990s, awareness of the shortage of global water resources lead to the first detailed global water resources assessments using regional statistics of water use and observations of meteorological and hydrological variables. Shortly thereafter, the first macroscale hydrological models (MHM) appeared. In these models, blue water (i.e., surface water and renewable groundwater) availability was calculated by accumulating runoff over a stream network and comparing it with population densities or with estimated water demand for agriculture, industry and households. In this talk we review the evolution of human impact modelling in global land models with a focus on global water resources, touching upon developments of the last 15 years: i.e. calculating human water scarcity; estimating groundwater depletion; adding dams and reservoirs; fully integrating water use (demand, withdrawal, consumption, return flow) in the hydrology; simulating the effects of land use change. We show example studies for each of these steps. We identify We identify major challenges that hamper the further development of integrated water resources modelling. Examples of these are: 1) simulating reservoir operations; 2) including local infrastructure and redistribution; 3) using the correct allocations rules; 4) projecting future water demand and water use. For each of these challenges we signify promising directions for further research.
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.
A Flexible Framework Hydrological Informatic Modeling System - HIMS
NASA Astrophysics Data System (ADS)
WANG, L.; Wang, Z.; Changming, L.; Li, J.; Bai, P.
2017-12-01
Simulating water cycling process temporally and spatially fitting for the characteristics of the study area was important for floods prediction and streamflow simulation with high accuracy, as soil properties, land scape, climate, and land managements were the critical factors influencing the non-linear relationship of rainfall-runoff at watershed scales. Most existing hydrological models cannot simulate water cycle process at different places with customized mechanisms with fixed single structure and mode. This study develops Hydro-Informatic Modeling System (HIMS) model with modular of each critical hydrological process with multiple choices for various scenarios to solve this problem. HIMS has the structure accounting for two runoff generation mechanisms of infiltration excess and saturation excess and estimated runoff with different methods including Time Variance Gain Model (TVGM), LCM which has good performance at ungauged areas, besides the widely used Soil Conservation Service-Curve Number (SCS-CN) method. Channel routing model contains the most widely used Muskingum, and kinematic wave equation with new solving method. HIMS model performance with its symbolic runoff generation model LCM was evaluated through comparison with the observed streamflow datasets of Lasha river watershed at hourly, daily, and monthly time steps. Comparisons between simulational and obervational streamflows were found with NSE higher than 0.87 and WE within ±20%. Water balance analysis about precipitation, streamflow, actual evapotranspiration (ET), and soil moisture change was conducted temporally at annual time step and it has been proved that HIMS model performance was reliable through comparison with literature results at the Lhasa River watershed.
NASA Astrophysics Data System (ADS)
Ruiz Pérez, Guiomar; Latron, Jérôme; Llorens, Pilar; Gallart, Francesc; Francés, Félix
2017-04-01
Selecting an adequate hydrological model is the first step to carry out a rainfall-runoff modelling exercise. A hydrological model is a hypothesis of catchment functioning, encompassing a description of dominant hydrological processes and predicting how these processes interact to produce the catchment's response to external forcing. Current research lines emphasize the importance of multiple working hypotheses for hydrological modelling instead of only using a single model. In line with this philosophy, here different hypotheses were considered and analysed to simulate the nonlinear response of a small Mediterranean catchment and to progress in the analysis of its hydrological behaviour. In particular, three hydrological models were considered representing different potential hypotheses: two lumped models called LU3 and LU4, and one distributed model called TETIS. To determine how well each specific model performed and to assess whether a model was more adequate than another, we raised three complementary tests: one based on the analysis of residual errors series, another based on a sensitivity analysis and the last one based on using multiple evaluation criteria associated to the concept of Pareto frontier. This modelling approach, based on multiple working hypotheses, helped to improve our perceptual model of the catchment behaviour and, furthermore, could be used as a guidance to improve the performance of other environmental models.
Zhang, Dan; Zhang, Qi; Qiu, Jiaming; Bai, Peng; Liang, Kang; Li, Xianghu
2018-10-01
Hydrological extremes are changing under the impacts of environmental change, i.e., climate variation and human activity, which can substantially influence ecosystems and the living environment of humans in affected region. This study investigates the impacts of environmental change on hydrological drought in the middle reaches of the Yangtze River in China based on hydrological modelling. Change points for streamflow into two major lakes and a reservoir in the study area were detected in the late 1980s using the Mann-Kendall test. Streamflow simulation by a water balance model was performed, and the resulting Kling-Gupta efficiency value was >0.90. Hydrological drought events were identified based on the simulated streamflow under different scenarios. The results show that the hydrological drought occurrence was increased by precipitation, whereas the drought peak value was increased by potential evapotranspiration. The impacts of precipitation and potential evapotranspiration on drought severity and duration varied in the study area. However, hydrological drought was intensified by the influence of human activity, which increased the severity, duration and peak value of droughts. The dominant factor for hydrological drought severity is precipitation, followed by potential evapotranspiration and human activity. The impacts of climate variation and human activity on drought severity are larger than on drought duration. In addition, environmental change is shown to have an "accumulation effect" on hydrological drought, demonstrating that the indirect impacts of environmental change on hydrological drought are much larger than the direct impacts on streamflow. This study improves our understanding of the responses of hydrological extremes to environmental change, which is useful for the management of water resources and the prediction of hydrological disasters. Copyright © 2018 Elsevier B.V. All rights reserved.
An evaluation of Dynamic TOPMODEL in natural and human-impacted catchments for low flow simulation
NASA Astrophysics Data System (ADS)
Coxon, Gemma; Freer, Jim; Lane, Rosanna; Musuuza, Jude; Woods, Ross; Wagener, Thorsten; Howden, Nicholas
2017-04-01
Models of catchment hydrology are essential tools for drought risk management, often providing input to water resource system models, aiding our understanding of low flow processes within catchments and providing low flow simulations and predictions. However, simulating low flows is challenging as hydrological systems often demonstrate threshold effects in connectivity, non-linear groundwater contributions and a greater influence of anthropogenic modifications such as surface and ground water abstractions during low flow periods. These processes are typically not well represented in commonly used hydrological models due to knowledge, data and model limitations. Hence, a better understanding of the natural and human processes that occur during low flows, how these are represented within models and how they could be improved is required to be able to provide robust and reliable predictions of future drought events. The aim of this study is to assess the skill of dynamic TOPMODEL during low flows for both natural and human-impacted catchments. Dynamic TOPMODEL was chosen for this study as it is able to explicitly characterise connectivity and fluxes across landscapes using hydrological response units (HRU's) while still maintaining flexibility in how spatially complex the model is configured and what specific functions (i.e. abstractions or groundwater stores) are represented. We apply dynamic TOPMODEL across the River Thames catchment using daily time series of observed rainfall and potential evapotranspiration data for the period 1999 - 2014, covering two major droughts in the Thames catchment. Significantly, to assess the impact of abstractions on low flows across the Thames catchment, we incorporate functions to characterise over 3,500 monthly surface water and ground water abstractions covering the simulation period into dynamic TOPMODEL. We evaluate dynamic TOPMODEL at over 90 gauging stations across the Thames catchment against multiple signatures of catchment low-flow behaviour in a 'limits of acceptability' GLUE framework. We investigate differences in model performance between signatures, different low flow periods and for natural and human impacted catchments to better understand the ability of dynamic TOPMODEL to represent low flows in space and time. Finally, we discuss future developments of dynamic TOPMODEL to improve low flow simulation and the implications of these results for modelling hydrological extremes in natural and human impacted catchments across the UK and the world.
NASA Astrophysics Data System (ADS)
Robles-Morua, A.; Vivoni, E.; Rivera-Fernandez, E. R.; Dominguez, F.; Meixner, T.
2013-05-01
Hydrologic modeling using high spatiotemporal resolution satellite precipitation products in the southwestern United States and northwest Mexico is important given the sparse nature of available rain gauges. In addition, the bimodal distribution of annual precipitation also presents a challenge as differential climate impacts during the winter and summer seasons are not currently well understood. In this work, we focus on hydrological comparisons using rainfall forcing from a satellite-based product, downscaled GCM precipitation estimates and available ground observations. The simulations are being conducted in the Santa Cruz and San Pedro river basins along the Arizona-Sonora border at high spatiotemporal resolutions (~100 m and ~1 hour). We use a distributed hydrologic model, known as the TIN-based Real-time Integrated Basin Simulator (tRIBS), to generate simulated hydrological fields under historical (1991-2000) and climate change (2031-2040) scenarios obtained from an application of the Weather Research and Forecast (WRF) model. Using the distributed model, we transform the meteorological scenarios at 10-km, hourly resolution into predictions of the annual water budget, seasonal land surface fluxes and individual hydrographs of flood and recharge events. We compare the model outputs and rainfall fields of the WRF products against the forcing from the North American Land Data Assimilation System (NLDAS) and available ground observations from the National Climatic Data Center (NCDC) and Arizona Meteorological Network (AZMET). For this contribution, we selected two full years in the historical period and in the future scenario that represent wet and dry conditions for each decade. Given the size of the two basins, we rely on a high performance computing platform and a parallel domain discretization with higher resolutions maintained at experimental catchments in each river basin. Model simulations utilize best-available data across the Arizona-Sonora border on topography, land cover and soils obtained from analysis of remotely-sensed imagery and government databases. In addition, for the historical period, we build confidence in the model simulations through comparisons with streamflow estimates in the region. The model comparisons during the historical and future periods will yield a first-of-its-kind assessment on the impacts of climate change on the hydrology of two large semiarid river basins of the southwestern United States
NASA Technical Reports Server (NTRS)
Robock, Alan; Vinnikov, Konstantin YA.; Schlosser, C. Adam; Speranskaya, Nina A.; Xue, Yongkang
1995-01-01
Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMs) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earth's surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSiB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six stations. The model calculations of soil moisture are compared to observations of soil moisture, literally 'ground truth,' snow cover, surface albedo, and net radiation, and with each other. For three of the stations, the SSiB and 15-cm bucket models produce good simulations of seasonal cycles and interannual variations of soil moisture. For the other three stations, there are large errors in the simulations by both models. Inconsistencies in specification of field capacity may be partly responsible. There is no evidence that the SSiB simulations are superior in simulating soil moisture variations. In fact, the models are quite similar since SSiB implicitly has a bucket embedded in it. One of the main differences between the models is in the treatment of runoff due to melting snow in the spring -- SSiB incorrectly puts all the snowmelt into runoff. While producing similar soil moisture simulations, the models produce very different surface latent and sensible heat fluxes, which would have large effects on GCM simulations.
Gleason, Robert A.; Tangen, Brian A.; Laubhan, Murray K.; Kermes, Kevin E.; Euliss, Ned H.
2007-01-01
Executive Summary Concern over flooding along rivers in the Prairie Pothole Region has stimulated interest in developing spatially distributed hydrologic models to simulate the effects of wetland water storage on peak river flows. Such models require spatial data on the storage volume and interception area of existing and restorable wetlands in the watershed of interest. In most cases, information on these model inputs is lacking because resolution of existing topographic maps is inadequate to estimate volume and areas of existing and restorable wetlands. Consequently, most studies have relied on wetland area to volume or interception area relationships to estimate wetland basin storage characteristics by using available surface area data obtained as a product from remotely sensed data (e.g., National Wetlands Inventory). Though application of areal input data to estimate volume and interception areas is widely used, a drawback is that there is little information available to provide guidance regarding the application, limitations, and biases associated with such approaches. Another limitation of previous modeling efforts is that water stored by wetlands within a watershed is treated as a simple lump storage component that is filled prior to routing overflow to a pour point or gaging station. This approach does not account for dynamic wetland processes that influence water stored in prairie wetlands. Further, most models have not considered the influence of human-induced hydrologic changes, such as land use, that greatly influence quantity of surface water inputs and, ultimately, the rate that a wetland basin fills and spills. The goals of this study were to (1) develop and improve methodologies for estimating and spatially depicting wetland storage volumes and interceptions areas and (2) develop models and approaches for estimating/simulating the water storage capacity of potentially restorable and existing wetlands under various restoration, land use, and climatic scenarios. To address these goals, we developed models and approaches to spatially represent storage volumes and interception areas of existing and potentially restorable wetlands in the upper Mustinka subbasin within Grant County, Minn. We then developed and applied a model to simulate wetland water storage increases that would result from restoring 25 and 50 percent of the farmed and drained wetlands in the upper Mustinka subbasin. The model simulations were performed during the growing season (May-October) for relatively wet (1993; 0.79 m of precipitation) and dry (1987; 0.40 m of precipitation) years. Results from the simulations indicated that the 25 percent restoration scenario would increase water storage by 21-24 percent and that a 50 percent scenario would increase storage by 34-38 percent. Additionally, we estimated that wetlands in the subbasin have potential to store 11.57-20.98 percent of the total precipitation that fell over the entire subbasin area (52,758 ha). Our simulation results indicated that there is considerable potential to enhance water storage in the subbasin; however, evaluation and calibration of the model is necessary before simulation results can be applied to management and planning decisions. In this report we present guidance for the development and application of models (e.g., surface area-volume predictive models, hydrology simulation model) to simulate wetland water storage to provide a basis from which to understand and predict the effects of natural or human-induced hydrologic alterations. In developing these approaches, we tried to use simple and widely available input data to simulate wetland hydrology and predict wetland water storage for a specific precipitation event or a series of events. Further, the hydrology simulation model accounted for land use and soil type, which influence surface water inputs to wetlands. Although information presented in this report is specific to the Mustinka subbasin, the approaches
Dam failure analysis for the Lago El Guineo Dam, Orocovis, Puerto Rico
Gómez-Fragoso, Julieta; Heriberto Torres-Sierra,
2016-08-09
The U.S. Geological Survey, in cooperation with the Puerto Rico Electric Power Authority, completed hydrologic and hydraulic analyses to assess the potential hazard to human life and property associated with the hypothetical failure of the Lago El Guineo Dam. The Lago El Guineo Dam is within the headwaters of the Río Grande de Manatí and impounds a drainage area of about 4.25 square kilometers.The hydrologic assessment was designed to determine the outflow hydrographs and peak discharges for Lago El Guineo and other subbasins in the Río Grande de Manatí hydrographic basin for three extreme rainfall events: (1) a 6-hour probable maximum precipitation event, (2) a 24-hour probable maximum precipitation event, and (3) a 24-hour, 100-year recurrence rainfall event. The hydraulic study simulated a dam failure of Lago El Guineo Dam using flood hydrographs generated from the hydrologic study. The simulated dam failure generated a hydrograph that was routed downstream from Lago El Guineo Dam through the lower reaches of the Río Toro Negro and the Río Grande de Manatí to determine water-surface profiles developed from the event-based hydrologic scenarios and “sunny day” conditions. The Hydrologic Engineering Center’s Hydrologic Modeling System (HEC–HMS) and Hydrologic Engineering Center’s River Analysis System (HEC–RAS) computer programs, developed by the U.S. Army Corps of Engineers, were used for the hydrologic and hydraulic modeling, respectively. The flow routing in the hydraulic analyses was completed using the unsteady flow module available in the HEC–RAS model.Above the Lago El Guineo Dam, the simulated inflow peak discharges from HEC–HMS resulted in about 550 and 414 cubic meters per second for the 6- and 24-hour probable maximum precipitation events, respectively. The 24-hour, 100-year recurrence storm simulation resulted in a peak discharge of about 216 cubic meters per second. For the hydrologic analysis, no dam failure conditions are considered within the model. The results of the hydrologic simulations indicated that for all hydrologic conditions scenarios, the Lago El Guineo Dam would not experience overtopping. For the dam breach hydraulic analysis, failure by piping was the selected hypothetical failure mode for the Lago El Guineo Dam.Results from the simulated dam failure of the Lago El Guineo Dam using the HEC–RAS model for the 6- and 24-hour probable maximum precipitation events indicated peak discharges below the dam of 1,342.43 and 1,434.69 cubic meters per second, respectively. Dam failure during the 24-hour, 100-year recurrence rainfall event resulted in a peak discharge directly downstream from Lago El Guineo Dam of 1,183.12 cubic meters per second. Dam failure during sunny-day conditions (no precipitation) produced a peak discharge at Lago El Guineo Dam of 1,015.31 cubic meters per second assuming the initial water-surface elevation was at the morning-glory spillway invert elevation.The results of the hydraulic analysis indicate that the flood would extend to many inhabited areas along the stream banks from the Lago El Guineo Dam to the mouth of the Río Grande as a result of the simulated failure of the Lago El Guineo Dam. Low-lying regions in the vicinity of Ciales, Manatí, and Barceloneta, Puerto Rico, are among the regions that would be most affected by failure of the Lago El Guineo Dam. Effects of the flood control (levee) structure constructed in 2000 to provide protection to the low-lying populated areas of Barceloneta, Puerto Rico, were considered in the hydraulic analysis of dam failure. The results indicate that overtopping can be expected in the aforementioned levee during 6- and 24-hour probable maximum precipitation events. The levee was not overtopped during dam failure scenarios under the 24-hour, 100-year recurrence rainfall event or sunny-day conditions.
NASA Astrophysics Data System (ADS)
Klug, P.; Bach, H.; Migdall, S.
2013-12-01
In arid regions the infiltration of sparse rainfalls and resulting ground water recharge is a critical quantity for the water cycle. With the PROMET model the infiltration process can be simulated in detail, since 4 soil layers together with the hourly calculation time step allow simulating the vertical water transport. Wet soils are darker than dry soils. Using the SLC reflectance model this effect can be simulated and compared to temporal high resolution time series of measured reflectances from Meteosat in order to monitor the drying process. This study demonstrates how MSG can be used to better parameterize the simulation of the infiltration process and reduce uncertainties in ground water recharge estimation. The study is carried out in the frame of the EU FP7 project CLIMB (Climate Induced Changes on the Hydrology of Mediterranean Basins). According to climate projections, Mediterranean countries are at risk of changes in the hydrological budget, the agricultural productivity and drinking water supply in the future. The CLIMB FP-7 project coordinated by the University of Munich (LMU) aims at employing integrated hydrological modelling in a new framework to reduce existing uncertainties in climate change impact analysis of the Mediterranean region [1, 2].
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.
Surface-water hydrology and runoff simulations for three basins in Pierce County, Washington
Mastin, M.C.
1996-01-01
The surface-water hydrology in Clear, Clarks, and Clover Creek Basins in central Pierce County, Washington, is described with a conceptual model of the runoff processes and then simulated with the Hydrological Simulation Program-FORTRAN (HSPF), a continuous, deterministic hydrologic model. The study area is currently undergoing a rapid conversion of rural, undeveloped land to urban and suburban land that often changes the flow characteristics of the streams that drain these lands. The complex interactions of land cover, climate, soils, topography, channel characteristics, and ground- water flow patterns determine the surface-water hydrology of the study area and require a complex numerical model to assess the impact of urbanization on streamflows. The U.S. Geological Survey completed this investigation in cooperation with the Storm Drainage and Surface Water Management Utility within the Pierce County Department of Public Works to describe the important rainfall-runoff processes within the study area and to develop a simulation model to be used as a tool to predict changes in runoff characteristics resulting from changes in land use. The conceptual model, a qualitative representation of the study basins, links the physical characteristics to the runoff process of the study basins. The model incorporates 11 generalizations identified by the investigation, eight of which describe runoff from hillslopes, and three that account for the effects of channel characteristics and ground-water flow patterns on runoff. Stream discharge was measured at 28 sites and precipitation was measured at six sites for 3 years in two overlapping phases during the period of October 1989 through September 1992 to calibrate and validate the simulation model. Comparison of rainfall data from October 1989 through September 1992 shows the data-collection period beginning with 2 wet water years followed by the relatively dry 1992 water year. Runoff was simulated with two basin models-the Clover Creek Basin model and the Clear-Clarks Basin model-by incorporating the generalizations of the conceptual model into the construction of two HSPF numerical models. Initially, the process-related parameters for runoff from glacial-till hillslopes were calibrated with numerical models for three catchment sites and one headwater basin where streamflows were continuously measured and little or no influence from ground water, channel storage, or channel losses affected runoff. At one of the catchments soil moisture was monitored and compared with simulated soil moisture. The values for these parameters were used in the basin models. Basin models were calibrated to the first year of observed streamflow data by adjusting other parameters in the numerical model that simulated channel losses, simulated channel storage in a few of the reaches in the headwaters and in the floodplain of the main stem of Clover Creek, and simulated volume and outflow of the ground-water reservoir representing the regional ground-water aquifers. The models were run for a second year without any adjustments, and simulated results were compared with observed results as a measure of validation of the models. The investigation showed the importance of defining the ground-water flow boundaries and demonstrated a simple method of simulating the influence of the regional ground-water aquifer on streamflows. In the Clover Creek Basin model, ground-water flow boundaries were used to define subbasins containing mostly glacial outwash soils and not containing any surface drainage channels. In the Clear-Clarks Basin model, ground-water flow boundaries outlined a recharge area outside the surface-water boundaries of the basin that was incorporated into the model in order to provide sufficient water to balance simulated ground-water outflows to the creeks. A simulated ground-water reservoir used to represent regional ground-water flow processes successfully provided the proper water balance of inflows and outfl
A high-resolution physically-based global flood hazard map
NASA Astrophysics Data System (ADS)
Kaheil, Y.; Begnudelli, L.; McCollum, J.
2016-12-01
We present the results from a physically-based global flood hazard model. The model uses a physically-based hydrologic model to simulate river discharges, and 2D hydrodynamic model to simulate inundation. The model is set up such that it allows the application of large-scale flood hazard through efficient use of parallel computing. For hydrology, we use the Hillslope River Routing (HRR) model. HRR accounts for surface hydrology using Green-Ampt parameterization. The model is calibrated against observed discharge data from the Global Runoff Data Centre (GRDC) network, among other publicly-available datasets. The parallel-computing framework takes advantage of the river network structure to minimize cross-processor messages, and thus significantly increases computational efficiency. For inundation, we implemented a computationally-efficient 2D finite-volume model with wetting/drying. The approach consists of simulating flood along the river network by forcing the hydraulic model with the streamflow hydrographs simulated by HRR, and scaled up to certain return levels, e.g. 100 years. The model is distributed such that each available processor takes the next simulation. Given an approximate criterion, the simulations are ordered from most-demanding to least-demanding to ensure that all processors finalize almost simultaneously. Upon completing all simulations, the maximum envelope of flood depth is taken to generate the final map. The model is applied globally, with selected results shown from different continents and regions. The maps shown depict flood depth and extent at different return periods. These maps, which are currently available at 3 arc-sec resolution ( 90m) can be made available at higher resolutions where high resolution DEMs are available. The maps can be utilized by flood risk managers at the national, regional, and even local levels to further understand their flood risk exposure, exercise certain measures of mitigation, and/or transfer the residual risk financially through flood insurance programs.
NASA Astrophysics Data System (ADS)
Rowe, H. D.; Dunbar, R. B.
2004-09-01
A basin-scale hydrologic-energy balance model that integrates modern climatological, hydrological, and hypsographic observations was developed for the modern Lake Titicaca watershed (northern Altiplano, South America) and operated under variable conditions to understand controls on post-glacial changes in lake level. The model simulates changes in five environmental variables (air temperature, cloud fraction, precipitation, relative humidity, and land surface albedo). Relatively small changes in three meteorological variables (mean annual precipitation, temperature, and/or cloud fraction) explain the large mid-Holocene lake-level decrease (˜85 m) inferred from seismic reflection profiling and supported by sediment-based paleoproxies from lake sediments. Climatic controls that shape the present-day Altiplano and the sediment-based record of Holocene lake-level change are combined to interpret model-derived lake-level simulations in terms of changes in the mean state of ENSO and its impact on moisture transport to the Altiplano.
NASA Astrophysics Data System (ADS)
Vibhava, F.; Graham, W. D.; De Rooij, R.; Maxwell, R. M.; Martin, J. B.; Cohen, M. J.
2011-12-01
The Santa Fe River Basin (SFRB) consists of three linked hydrologic units: the upper confined region (UCR), semi-confined transitional region (Cody Escarpment, CE) and lower unconfined region (LUR). Contrasting geological characteristics among these units affect streamflow generation processes. In the UCR, surface runoff and surficial stores dominate whereas in the LCR minimal surface runoff occurs and flow is dominated by groundwater sources and sinks. In the CE region the Santa Fe River (SFR) is captured entirely by a sinkhole into the Floridan aquifer, emerging as a first magnitude spring 6 km to the south. In light of these contrasting hydrological settings, developing a predictive, basin scale, physically-based hydrologic simulation model remains a research challenge. This ongoing study aims to assess the ability of a fully-coupled, physically-based three-dimensional hydrologic model (PARFLOW-CLM), to predict hydrologic conditions in the SFRB. The assessment will include testing the model's ability to adequately represent surface and subsurface flow sources, flow paths, and travel times within the basin as well as the surface-groundwater exchanges throughout the basin. In addition to simulating water fluxes, we also are collecting high resolution specific conductivity data at 10 locations throughout the river. Our objective is to exploit hypothesized strong end-member separation between riverine source water geochemistry to further refine the PARFLOW-CLM representation of riverine mixing and delivery dynamics.
Application of a water quality model in the White Cart water catchment, Glasgow, UK.
Liu, S; Tucker, P; Mansell, M; Hursthouse, A
2003-03-01
Water quality models of urban systems have previously focused on point source (sewerage system) inputs. Little attention has been given to diffuse inputs and research into diffuse pollution has been largely confined to agriculture sources. This paper reports on new research that is aimed at integrating diffuse inputs into an urban water quality model. An integrated model is introduced that is made up of four modules: hydrology, contaminant point sources, nutrient cycling and leaching. The hydrology module, T&T consists of a TOPMODEL (a TOPography-based hydrological MODEL), which simulates runoff from pervious areas and a two-tank model, which simulates runoff from impervious urban areas. Linked into the two-tank model, the contaminant point source module simulates the overflow from the sewerage system in heavy rain. The widely known SOILN (SOIL Nitrate model) is the basis of nitrogen cycle module. Finally, the leaching module consists of two functions: the production function and the transfer function. The production function is based on SLIM (Solute Leaching Intermediate Model) while the transfer function is based on the 'flushing hypothesis' which postulates a relationship between contaminant concentrations in the receiving water course and the extent to which the catchment is saturated. This paper outlines the modelling methodology and the model structures that have been developed. An application of this model in the White Cart catchment (Glasgow) is also included.
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.
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.
NASA Astrophysics Data System (ADS)
Meyer, Swen; Ludwig, Ralf
2013-04-01
According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. While there is scientific consensus that climate induced changes on the hydrology of Mediterranean regions are presently occurring and are projected to amplify in the future, very little knowledge is available about the quantification of these changes, which is hampered by a lack of suitable and cost effective hydrological monitoring and modeling systems. The European FP7-project CLIMB is aiming to analyze climate induced changes on the hydrology of the Mediterranean Basins by investigating 7 test sites located in the countries Italy, France, Turkey, Tunisia, Gaza and Egypt. CLIMB employs a combination of novel geophysical field monitoring concepts, remote sensing techniques and integrated hydrologic modeling to improve process descriptions and understanding and to quantify existing uncertainties in climate change impact analysis. The Rio Mannu Basin, located in Sardinia; Italy, is one test site of the CLIMB project. The catchment has a size of 472.5 km2, it ranges from 62 to 946 meters in elevation, at mean annual temperatures of 16°C and precipitation of about 700 mm, the annual runoff volume is about 200 mm. The physically based Water Simulation Model WaSiM Vers. 2 (Schulla & Jasper (1999)) was setup to model current and projected future hydrological conditions. The availability of measured meteorological and hydrological data is poor as common to many Mediterranean catchments. The lack of available measured input data hampers the calibration of the model setup and the validation of model outputs. State of the art remote sensing techniques and field measuring techniques were applied to improve the quality of hydrological input parameters. In a field campaign about 250 soil samples were collected and lab-analyzed. Different geostatistical regionalization methods were tested to improve the model setup. The soil parameterization of the model was tested against publically available soil data. Results show a significant improvement of modeled soil moisture outputs. To validate WaSiMs evapotranspiration (ETact) outputs, Landsat TM images were used to calculate the actual monthly mean ETact rates using the triangle method (Jiang and Islam, 1999). Simulated spatial ETact patterns and those derived from remote sensing show a good fit especially for the growing season. WaSiM was driven with the meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. Output results were analyzed for climate induced changes on selected hydrological variables. While the climate projections reveal increased precipitation rates in the spring season, first simulation results show an earlier onset and an increased duration of the dry season, imposing an increased irrigation demand and higher vulnerability of agricultural productivity.
Spatial interpolation schemes of daily precipitation for hydrologic modeling
Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.
2012-01-01
Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.
NASA Technical Reports Server (NTRS)
Johnson, Donald R.
1998-01-01
The goal of this research is the continued development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. This work involves a combination of modeling and analysis efforts involving 4DDA datasets and simulations from the University of Wisconsin (UW) hybrid isentropic-sigma (theta-sigma) coordinate model and the GEOS GCM.
Evaluation of Potential Evapotranspiration from a Hydrologic Model on a National Scale
NASA Astrophysics Data System (ADS)
Hakala, K. A.; Hay, L.; Markstrom, S. L.
2014-12-01
The US Geological Survey has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development and facilitate the application of simulations on the scale of the continental US. The NHM has a consistent geospatial fabric for modeling, consisting of over 100,000 hydrologic response units (HRUs). Each HRU requires accurate parameter estimates, some of which are attained from automated calibration. However, improved calibration can be achieved by initially utilizing as many parameters as possible from national data sets. This presentation investigates the effectiveness of calculating potential evapotranspiration (PET) parameters based on mean monthly values from the NOAA PET Atlas. Additional PET products are then used to evaluate the PET parameters. Effectively utilizing existing national-scale data sets can simplify the effort in establishing a robust NHM.
NASA Astrophysics Data System (ADS)
Hevesi, J. A.; Woolfenden, L. R.; Nishikawa, T.
2014-12-01
Communities in the Santa Rosa Plain watershed (SRPW), Sonoma County, CA, USA are experiencing increasing demand for limited water resources. Streamflow in the SRPW is runoff dominated; however, groundwater also is an important resource in the basin. The watershed has an area of 262 mi2 that includes natural, agricultural, and urban land uses. To evaluate the hydrologic system, an integrated hydrologic model was developed using the U.S. Geological Survey coupled groundwater and surface-water flow model, GSFLOW. The model uses a daily time step and a grid-based discretization of the SRPW consisting of 16,741 10-acre cells for 8 model layers to simulate all water budget components of the surface and subsurface hydrologic system. Simulation results indicate significant impacts on streamflow and recharge in response to the below average precipitation during the dry periods. The recharge and streamflow distributions simulated for historic dry periods were compared to future dry periods projected from 4 GCM realizations (two different GCMs and two different CO2 forcing scenarios) for the 21st century, with the dry periods defined as 3 consecutive years of below average precipitation. For many of the projected dry periods, the decreases in recharge and streamflow were greater than for the historic dry periods due to a combination of lower precipitation and increases in simulated evapotranspiration for the warmer 21st century projected by the GCM realizations. The greatest impact on streamflow for both historic and projected future dry periods is the diminished baseflow from late spring to early fall, with an increase in the percentage of intermittent and dry stream reaches. The results indicate that the coupled model is a useful tool for water managers to better understand the potential effects of future dry periods on spatially and temporally distributed streamflow and recharge, as well as other components of the water budget.
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.
Swain, Eric D.; Wolfert, Melinda A.; Bales, Jerad D.; Goodwin, Carl R.
2004-01-01
Successful restoration of the southern Florida ecosystem requires extensive knowledge of the physical characteristics and hydrologic processes controlling water flow and transport of constituents through extremely low-gradient freshwater marshes, shallow mangrove-fringed coastal creeks and tidal embayments, and near-shore marine waters. A sound, physically based numerical model can provide simulations of the differing hydrologic conditions that might result from various ecosystem restoration scenarios. Because hydrology and ecology are closely linked in southern Florida, hydrologic model results also can be used by ecologists to evaluate the degree of ecosystem restoration that could be achieved for various hydrologic conditions. A robust proven model, SWIFT2D, (Surface-Water Integrated Flow and Transport in Two Dimensions), was modified to simulate Southern Inland and Coastal Systems (SICS) hydrodynamics and transport conditions. Modifications include improvements to evapotranspiration and rainfall calculation and to the algorithms that describe flow through coastal creeks. Techniques used in this model should be applicable to other similar low-gradient marsh settings in southern Florida and elsewhere. Numerous investigations were conducted within the SICS area of southeastern Everglades National Park and northeastern Florida Bay to provide data and parameter values for model development and testing. The U.S. Geological Survey and the National Park Service supported investigations for quantification of evapotranspiration, vegetative resistance to flow, wind-induced flow, land elevations, vegetation classifications, salinity conditions, exchange of ground and surface waters, and flow and transport in coastal creeks and embayments. The good agreement that was achieved between measured and simulated water levels, flows, and salinities through minimal adjustment of empirical coefficients indicates that hydrologic processes within the SICS area are represented properly in the SWIFT2D model, and that the spatial and temporal resolution of these processes in the model is adequate. Sensitivity analyses were conducted to determine the effect of changes in boundary conditions and parameter values on simulation results, which aided in identifying areas of greatest uncertainty in the model. The parameter having the most uncertainty (most in need of further field study) was the flow coefficient for coastal creeks. Smaller uncertainties existed for wetlands frictional resistance and wind. Evapotranspiration and boundary inflows indicated the least uncertainty as determined by varying parameters used in their formulation and definition. Model results indicated that wind was important in reversing coastal creek flows. At Trout Creek (the major tributary connecting Taylor Slough wetlands with Florida Bay), flow in the landward direction was not simulated properly unless wind forcing was included in the simulation. Simulations also provided insight into the major influence that wind has on salinity mixing along the coast, the varying distribution of wetland flows at differing water levels, and the importance of topography in controlling flows to the coast. Slight topographic variations were shown to highly influence the routing of water. A multiple regression analysis was performed to relate inflows at the northern boundary of Taylor Slough bridge to a major pump station (S-332) north of the SICS model area. This analysis allows Taylor Slough bridge boundary conditions to be defined for the model from operating scenarios at S-332, which should facilitate use of the SICS model as an operational tool.
NASA Astrophysics Data System (ADS)
Vergara, H. J.; Kirstetter, P.; Gourley, J. J.; Flamig, Z.; Hong, Y.
2015-12-01
The macro scale patterns of simulated streamflow errors are studied in order to characterize uncertainty in a hydrologic modeling system forced with the Multi-Radar/Multi-Sensor (MRMS; http://mrms.ou.edu) quantitative precipitation estimates for flood forecasting over the Conterminous United States (CONUS). The hydrologic model is centerpiece of the Flooded Locations And Simulated Hydrograph (FLASH; http://flash.ou.edu) real-time system. The hydrologic model is implemented at 1-km/5-min resolution to generate estimates of streamflow. Data from the CONUS-wide stream gauge network of the United States' Geological Survey (USGS) were used as a reference to evaluate the discrepancies with the hydrological model predictions. Streamflow errors were studied at the event scale with particular focus on the peak flow magnitude and timing. A total of 2,680 catchments over CONUS and 75,496 events from a 10-year period are used for the simulation diagnostic analysis. Associations between streamflow errors and geophysical factors were explored and modeled. It is found that hydro-climatic factors and radar coverage could explain significant underestimation of peak flow in regions of complex terrain. Furthermore, the statistical modeling of peak flow errors shows that other geophysical factors such as basin geomorphometry, pedology, and land cover/use could also provide explanatory information. Results from this research demonstrate the utility of uncertainty characterization in providing guidance to improve model adequacy, parameter estimates, and input quality control. Likewise, the characterization of uncertainty enables probabilistic flood forecasting that can be extended to ungauged locations.
NASA Astrophysics Data System (ADS)
Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L.
2014-12-01
The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units.
The impact of hydrologic segmentation on the Critical Zone water fluxes of headwater catchments
NASA Astrophysics Data System (ADS)
Gutierrez-Jurado, H. A.; Dominguez, M.; Guan, H.
2017-12-01
Headwater catchments are usually located on areas with complex terrain, where variability in aspect and microclimate give rise to contrasting vegetation cover and soil properties. This fine-scale variability in land surface conditions within a catchment is usually overlooked in hydrologic models, and the resulting differences in hydrologic dynamics across the slopes neglected. In this work we evaluate the impact of the differential hydrologic response, or as we define it here, "hydrologic segmentation" on the partition of water fluxes of contrasting slopes within a series of headwater catchments across a latitudinal gradient. Our aim is to investigate the effect of hydrologically segmenting the slopes of headwater catchments as a function of their unique aspect-vegetation-soils associations, on the water fluxes of the catchments and their potential consequences on the water balance at a regional scale. Using a distributed hydrologic model and data from a series of catchments with varying land cover and climatic conditions, we run a set of simulations with and without hydrologic segmentation to assess the effect of changing the architecture of the top part of the critical zone on the evaporation, transpiration, infiltration and runoff fluxes of each catchment slope. We calibrate and compare the simulation results with observations from a network of hydrologic sensors and independent field estimates of the various water fluxes. Our results suggest that hydrologic segmentation will significantly affect both the timing and partition of evapotranspiration fluxes with direct impacts on soil moisture residence times and the potential for deep infiltration and aquifer recharge.
NASA Astrophysics Data System (ADS)
Wever, Nander; Comola, Francesco; Bavay, Mathias; Lehning, Michael
2017-08-01
The assessment of flood risks in alpine, snow-covered catchments requires an understanding of the linkage between the snow cover, soil and discharge in the stream network. Here, we apply the comprehensive, distributed model Alpine3D to investigate the role of soil moisture in the predisposition of the Dischma catchment in Switzerland to high flows from rainfall and snowmelt. The recently updated soil module of the physics-based multilayer snow cover model SNOWPACK, which solves the surface energy and mass balance in Alpine3D, is verified against soil moisture measurements at seven sites and various depths inside and in close proximity to the Dischma catchment. Measurements and simulations in such terrain are difficult and consequently, soil moisture was simulated with varying degrees of success. Differences between simulated and measured soil moisture mainly arise from an overestimation of soil freezing and an absence of a groundwater description in the Alpine3D model. Both were found to have an influence in the soil moisture measurements. Using the Alpine3D simulation as the surface scheme for a spatially explicit hydrologic response model using a travel time distribution approach for interflow and baseflow, streamflow simulations were performed for the discharge from the catchment. The streamflow simulations provided a closer agreement with observed streamflow when driving the hydrologic response model with soil water fluxes at 30 cm depth in the Alpine3D model. Performance decreased when using the 2 cm soil water flux, thereby mostly ignoring soil processes. This illustrates that the role of soil moisture is important to take into account when understanding the relationship between both snowpack runoff and rainfall and catchment discharge in high alpine terrain. However, using the soil water flux at 60 cm depth to drive the hydrologic response model also decreased its performance, indicating that an optimal soil depth to include in surface simulations exists and that the runoff dynamics are controlled by only a shallow soil layer. Runoff coefficients (i.e. ratio of rainfall over discharge) based on measurements for high rainfall and snowmelt events were found to be dependent on the simulated initial soil moisture state at the onset of an event, further illustrating the important role of soil moisture for the hydrological processes in the catchment. The runoff coefficients using simulated discharge were found to reproduce this dependency, which shows that the Alpine3D model framework can be successfully applied to assess the predisposition of the catchment to flood risks from both snowmelt and rainfall events.
NASA Astrophysics Data System (ADS)
Matt, Felix; Burkhart, John F.
2017-04-01
Light absorbing impurities in snow and ice (LAISI) originating from atmospheric deposition enhance snow melt by increasing the absorption of short wave radiation. The consequences are a shortening of the snow cover duration due to increased snow melt and, with respect to hydrologic processes, a temporal shift in the discharge generation. However, the magnitude of these effects as simulated in numerical models have large uncertainties, originating mainly from uncertainties in the wet and dry deposition of light absorbing aerosols, limitations in the model representation of the snowpack, and the lack of observable variables required to estimate model parameters and evaluate the simulated variables connected with the representation of LAISI. This leads to high uncertainties in the additional energy absorbed by the snow due to the presence of LAISI, a key variable in understanding snowpack energy-balance dynamics. In this study, we assess the effect of LAISI on snow melt and discharge generation and the involved uncertainties in a high mountain catchment located in the western Himalayas by using a distributed hydrological catchment model with focus on the representation of the seasonal snow pack. The snow albedo is hereby calculated from a radiative transfer model for snow, taking the increased absorption of short wave radiation by LAISI into account. Meteorological forcing data is generated from an assimilation of observations and high resolution WRF simulations, and LAISI mixing ratios from deposition rates of Black Carbon simulated with the FLEXPART model. To asses the quality of our simulations and the related uncertainties, we compare the simulated additional energy absorbed by the snow due to the presence of LAISI to the MODIS Dust Radiative Forcing in Snow (MODDRFS) algorithm satellite product.
Zhang, Wei; Li, Yong; Zhu, Bo; Zheng, Xunhua; Liu, Chunyan; Tang, Jialiang; Su, Fang; Zhang, Chong; Ju, Xiaotang; Deng, Jia
2018-03-01
Quantification of nitrogen losses and net greenhouse gas (GHG) emissions from catchments is essential for evaluating the sustainability of ecosystems. However, the hydrologic processes without lateral flows hinder the application of biogeochemical models to this challenging task. To solve this issue, we developed a coupled hydrological and biogeochemical model, Catchment Nutrients Management Model - DeNitrification-DeComposition Model (CNMM-DNDC), to include both vertical and lateral mass flows. By incorporating the core biogeochemical processes (including decomposition, nitrification, denitrification and fermentation) of the DNDC into the spatially distributed hydrologic framework of the CNMM, the simulation of lateral water flows and their influences on nitrogen transportation can be realized. The CNMM-DNDC was then calibrated and validated in a small subtropical catchment belonged to Yanting station with comprehensive field observations. Except for the calibration of water flows (surface runoff and leaching water) in 2005, stream discharges of water and nitrate in 2007, the model validations of soil temperature, soil moisture, crop yield, water flows in 2006 and associated nitrate loss, fluxes of methane, ammonia, nitric oxide and nitrous oxide, and stream discharges of water and nitrate in 2008 were statistically in good agreement with the observations. Meanwhile, our initial simulation of the catchment showed scientific predictions. For instance, it revealed the following: (i) dominant ammonia volatilization among the losses of nitrogenous gases (accounting for 11-21% of the applied annual fertilizer nitrogen in croplands); (ii) hotspots of nitrate leaching near the main stream; and (iii) a net GHG sink function of the catchment. These results implicate the model's promising capability of predicting ecosystem productivity, hydrologic nitrogen loads, losses of gaseous nitrogen and emissions of GHGs, which could be used to provide strategies for establishing sustainable catchments. In addition, the model's capability would be further proved by applying in other catchments with different backgrounds. Copyright © 2017. Published by Elsevier B.V.
An interactive modelling tool for understanding hydrological processes in lowland catchments
NASA Astrophysics Data System (ADS)
Brauer, Claudia; Torfs, Paul; Uijlenhoet, Remko
2016-04-01
Recently, we developed the Wageningen Lowland Runoff Simulator (WALRUS), a rainfall-runoff model for catchments with shallow groundwater (Brauer et al., 2014ab). WALRUS explicitly simulates processes which are important in lowland catchments, such as feedbacks between saturated and unsaturated zone and between groundwater and surface water. WALRUS has a simple model structure and few parameters with physical connotations. Some default functions (which can be changed easily for research purposes) are implemented to facilitate application by practitioners and students. The effect of water management on hydrological variables can be simulated explicitly. The model description and applications are published in open access journals (Brauer et al, 2014). The open source code (provided as R package) and manual can be downloaded freely (www.github.com/ClaudiaBrauer/WALRUS). We organised a short course for Dutch water managers and consultants to become acquainted with WALRUS. We are now adapting this course as a stand-alone tutorial suitable for a varied, international audience. In addition, simple models can aid teachers to explain hydrological principles effectively. We used WALRUS to generate examples for simple interactive tools, which we will present at the EGU General Assembly. C.C. Brauer, A.J. Teuling, P.J.J.F. Torfs, R. Uijlenhoet (2014a): The Wageningen Lowland Runoff Simulator (WALRUS): a lumped rainfall-runoff model for catchments with shallow groundwater, Geosci. Model Dev., 7, 2313-2332. C.C. Brauer, P.J.J.F. Torfs, A.J. Teuling, R. Uijlenhoet (2014b): The Wageningen Lowland Runoff Simulator (WALRUS): application to the Hupsel Brook catchment and Cabauw polder, Hydrol. Earth Syst. Sci., 18, 4007-4028.
Feedback loops and temporal misalignment in component-based hydrologic modeling
NASA Astrophysics Data System (ADS)
Elag, Mostafa M.; Goodall, Jonathan L.; Castronova, Anthony M.
2011-12-01
In component-based modeling, a complex system is represented as a series of loosely integrated components with defined interfaces and data exchanges that allow the components to be coupled together through shared boundary conditions. Although the component-based paradigm is commonly used in software engineering, it has only recently been applied for modeling hydrologic and earth systems. As a result, research is needed to test and verify the applicability of the approach for modeling hydrologic systems. The objective of this work was therefore to investigate two aspects of using component-based software architecture for hydrologic modeling: (1) simulation of feedback loops between components that share a boundary condition and (2) data transfers between temporally misaligned model components. We investigated these topics using a simple case study where diffusion of mass is modeled across a water-sediment interface. We simulated the multimedia system using two model components, one for the water and one for the sediment, coupled using the Open Modeling Interface (OpenMI) standard. The results were compared with a more conventional numerical approach for solving the system where the domain is represented by a single multidimensional array. Results showed that the component-based approach was able to produce the same results obtained with the more conventional numerical approach. When the two components were temporally misaligned, we explored the use of different interpolation schemes to minimize mass balance error within the coupled system. The outcome of this work provides evidence that component-based modeling can be used to simulate complicated feedback loops between systems and guidance as to how different interpolation schemes minimize mass balance error introduced when components are temporally misaligned.
Modeling Modern Methane Emissions from Natural Wetlands. 1; Model Description and Results
NASA Technical Reports Server (NTRS)
Walter, Bernadette P.; Heimann, Martin; Matthews, Elaine
2001-01-01
Methane is an important greenhouse gas which contributes about 22 percent to the present greenhouse effect. Natural wetlands currently constitute the biggest methane source and were the major source in preindustrial times. Wetland emissions depend highly on the climate, i.e., on soil temperature and water table. To investigate the response of methane emissions from natural wetlands to climate variations, a process-based model that derives methane emissions from natural wetlands as a function of soil temperature, water table, and net primary productivity is used. For its application on the global scale, global data sets for all model parameters are generated. In addition, a simple hydrologic model is developed in order to simulate the position of the water table in wetlands. The hydrologic model is tested against data from different wetland sites, and the sensitivity of the hydrologic model to changes in precipitation is examined. The global methane hydrology model constitutes a tool to study temporal and spatial variations in methane emissions from natural wetlands. The model is applied using high-frequency atmospheric forcing fields from European Center for Medium-range Weather Forecasts (ECMWF) re-analyses of the period from 1982 to 1993. We calculate global annual methane emissions from wetlands to be 260 teragrams per year. Twenty-five percent of these methane emissions originate from wetlands north of 30 degrees North Latitude. Only 60 percent of the produced methane is emitted, while the rest is re-oxidized. A comparison of zonal integrals of simulated global wetland emissions and results obtained by an inverse modeling approach shows good agreement. In a test with data from two wetlands the seasonality of simulated and observed methane emissions agrees well.
NASA Technical Reports Server (NTRS)
Stephens, Graeme L.; Randall, David A.; Wittmeyer, Ian L.; Dazlich, Donald A.; Tjemkes, Stephen
1993-01-01
The ability of the Colorado State University general circulation model (GCM) to simulate interactions between the hydrological cycle and the radiative processes on earth was examined by comparing various sensitivity relationships established by the model with those observed on earth, and the observed and calculated seasonal cycles of the greenhouse effect and cloud radiative forcing. Results showed that, although the GCM model used was able to simulate well some aspects of the observed sensitivities, there were many serious quantitative differences, including problems in the simulation of the column vapor in the tropics and an excessively strong clear-sky greenhouse effect in the mid-latitudes. These differences led to an underestimation by the model of the sensitivity of the clear-sky greenhouse to changes in sea surface temperature.
What is the effect of LiDAR-derived DEM resolution on large-scale watershed model results?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ping Yang; Daniel B. Ames; Andre Fonseca
This paper examines the effect of raster cell size on hydrographic feature extraction and hydrological modeling using LiDAR derived DEMs. LiDAR datasets for three experimental watersheds were converted to DEMs at various cell sizes. Watershed boundaries and stream networks were delineated from each DEM and were compared to reference data. Hydrological simulations were conducted and the outputs were compared. Smaller cell size DEMs consistently resulted in less difference between DEM-delineated features and reference data. However, minor differences been found between streamflow simulations resulted for a lumped watershed model run at daily simulations aggregated at an annual average. These findings indicatemore » that while higher resolution DEM grids may result in more accurate representation of terrain characteristics, such variations do not necessarily improve watershed scale simulation modeling. Hence the additional expense of generating high resolution DEM's for the purpose of watershed modeling at daily or longer time steps may not be warranted.« less