A Reliability Estimation in Modeling Watershed Runoff With Uncertainties

NASA Astrophysics Data System (ADS)

Melching, Charles S.; Yen, Ben Chie; Wenzel, Harry G., Jr.

1990-10-01

The reliability of simulation results produced by watershed runoff models is a function of uncertainties in nature, data, model parameters, and model structure. A framework is presented here for using a reliability analysis method (such as first-order second-moment techniques or Monte Carlo simulation) to evaluate the combined effect of the uncertainties on the reliability of output hydrographs from hydrologic models. For a given event the prediction reliability can be expressed in terms of the probability distribution of the estimated hydrologic variable. The peak discharge probability for a watershed in Illinois using the HEC-1 watershed model is given as an example. The study of the reliability of predictions from watershed models provides useful information on the stochastic nature of output from deterministic models subject to uncertainties and identifies the relative contribution of the various uncertainties to unreliability of model predictions.

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

NASA Astrophysics Data System (ADS)

Smith, T.; Marshall, L.

2007-12-01

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

WATGIS: A GIS-Based Lumped Parameter Water Quality Model

Treesearch

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2002-01-01

A Geographic Information System (GIS)­based, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogen­loading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...

Large-watershed flood simulation and forecasting based on different-resolution distributed hydrological model

NASA Astrophysics Data System (ADS)

Li, J.

2017-12-01

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

Assessment and Reduction of Model Parametric Uncertainties: A Case Study with A Distributed Hydrological Model

NASA Astrophysics Data System (ADS)

Gan, Y.; Liang, X. Z.; Duan, Q.; Xu, J.; Zhao, P.; Hong, Y.

2017-12-01

The uncertainties associated with the parameters of a hydrological model need to be quantified and reduced for it to be useful for operational hydrological forecasting and decision support. An uncertainty quantification framework is presented to facilitate practical assessment and reduction of model parametric uncertainties. A case study, using the distributed hydrological model CREST for daily streamflow simulation during the period 2008-2010 over ten watershed, was used to demonstrate the performance of this new framework. Model behaviors across watersheds were analyzed by a two-stage stepwise sensitivity analysis procedure, using LH-OAT method for screening out insensitive parameters, followed by MARS-based Sobol' sensitivity indices for quantifying each parameter's contribution to the response variance due to its first-order and higher-order effects. Pareto optimal sets of the influential parameters were then found by the adaptive surrogate-based multi-objective optimization procedure, using MARS model for approximating the parameter-response relationship and SCE-UA algorithm for searching the optimal parameter sets of the adaptively updated surrogate model. The final optimal parameter sets were validated against the daily streamflow simulation of the same watersheds during the period 2011-2012. The stepwise sensitivity analysis procedure efficiently reduced the number of parameters that need to be calibrated from twelve to seven, which helps to limit the dimensionality of calibration problem and serves to enhance the efficiency of parameter calibration. The adaptive MARS-based multi-objective calibration exercise provided satisfactory solutions to the reproduction of the observed streamflow for all watersheds. The final optimal solutions showed significant improvement when compared to the default solutions, with about 65-90% reduction in 1-NSE and 60-95% reduction in |RB|. The validation exercise indicated a large improvement in model performance with about 40-85% reduction in 1-NSE, and 35-90% reduction in |RB|. Overall, this uncertainty quantification framework is robust, effective and efficient for parametric uncertainty analysis, the results of which provide useful information that helps to understand the model behaviors and improve the model simulations.

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.

SCS-CN based time-distributed sediment yield model

NASA Astrophysics Data System (ADS)

Tyagi, J. V.; Mishra, S. K.; Singh, Ranvir; Singh, V. P.

2008-05-01

SummaryA sediment yield model is developed to estimate the temporal rates of sediment yield from rainfall events on natural watersheds. The model utilizes the SCS-CN based infiltration model for computation of rainfall-excess rate, and the SCS-CN-inspired proportionality concept for computation of sediment-excess. For computation of sedimentographs, the sediment-excess is routed to the watershed outlet using a single linear reservoir technique. Analytical development of the model shows the ratio of the potential maximum erosion (A) to the potential maximum retention (S) of the SCS-CN method is constant for a watershed. The model is calibrated and validated on a number of events using the data of seven watersheds from India and the USA. Representative values of the A/S ratio computed for the watersheds from calibration are used for the validation of the model. The encouraging results of the proposed simple four parameter model exhibit its potential in field application.

Numerical and machine learning simulation of parametric distributions of groundwater residence time in streams and wells

NASA Astrophysics Data System (ADS)

Starn, J. J.; Belitz, K.; Carlson, C.

2017-12-01

Groundwater residence-time distributions (RTDs) are critical for assessing susceptibility of water resources to contamination. This novel approach for estimating regional RTDs was to first simulate groundwater flow using existing regional digital data sets in 13 intermediate size watersheds (each an average of 7,000 square kilometers) that are representative of a wide range of glacial systems. RTDs were simulated with particle tracking. We refer to these models as "general models" because they are based on regional, as opposed to site-specific, digital data. Parametric RTDs were created from particle RTDs by fitting 1- and 2-component Weibull, gamma, and inverse Gaussian distributions, thus reducing a large number of particle travel times to 3 to 7 parameters (shape, location, and scale for each component plus a mixing fraction) for each modeled area. The scale parameter of these distributions is related to the mean exponential age; the shape parameter controls departure from the ideal exponential distribution and is partly a function of interaction with bedrock and with drainage density. Given the flexible shape and mathematical similarity of these distributions, any of them are potentially a good fit to particle RTDs. The 1-component gamma distribution provided a good fit to basin-wide particle RTDs. RTDs at monitoring wells and streams often have more complicated shapes than basin-wide RTDs, caused in part by heterogeneity in the model, and generally require 2-component distributions. A machine learning model was trained on the RTD parameters using features derived from regionally available watershed characteristics such as recharge rate, material thickness, and stream density. RTDs appeared to vary systematically across the landscape in relation to watershed features. This relation was used to produce maps of useful metrics with respect to risk-based thresholds, such as the time to first exceedance, time to maximum concentration, time above the threshold (exposure time), and the time until last exceedance; thus, the parameters of groundwater residence time are measures of the intrinsic susceptibility of groundwater to contamination.

The Use of a Geomorphometric Classification to Estimate Subsurface Heterogeneity in the Unconsolidated Sediments of Mountain Watersheds

NASA Astrophysics Data System (ADS)

Cairns, D.; Byrne, J. M.; Jiskoot, H.; McKenzie, J. M.; Johnson, D. L.

2013-12-01

Groundwater controls many aspects of water quantity and quality in mountain watersheds. Groundwater recharge and flow originating in mountain watersheds are often difficult to quantify due to challenges in the characterization of the local geology, as subsurface data are sparse and difficult to collect. Remote sensing data are more readily available and are beneficial for the characterization of watershed hydrodynamics. We present an automated geomorphometric model to identify the approximate spatial distribution of geomorphic features, and to segment each of these features based on relative hydrostratigraphic differences. A digital elevation model (DEM) dataset and predefined indices are used as inputs in a mountain watershed. The model uses periglacial, glacial, fluvial, slope evolution and lacustrine processes to identify regions that are subsequently delineated using morphometric principles. A 10 m cell size DEM from the headwaters of the St. Mary River watershed in Glacier National Park, Montana, was considered sufficient for this research. Morphometric parameters extracted from the DEM that were found to be useful for the calibration of the model were elevation, slope, flow direction, flow accumulation, and surface roughness. Algorithms were developed to utilize these parameters and delineate the distributions of bedrock outcrops, periglacial landscapes, alluvial channels, fans and outwash plains, glacial depositional features, talus slopes, and other mass wasted material. Theoretical differences in sedimentation and hydrofacies associated with each of the geomorphic features were used to segment the watershed into units reflecting similar hydrogeologic properties such as hydraulic conductivity and thickness. The results of the model were verified by comparing the distribution of geomorphic features with published geomorphic maps. Although agreement in semantics between datasets caused difficulties, a consensus yielded a comparison Dice Coefficient of 0.65. The results can be used to assist in groundwater model calibration, or to estimate spatial differences in near-surface groundwater behaviour. Verification of the geomorphometric model would be augmented by evaluating its success after use in the calibration of the groundwater simulation. These results may also be used directly in momentum-based equations to create a stochastic routing routine beneath the soil interface for a hydrometeorological model.

Wolf Creek Research Basin Cold REgion Process Studies - 1992-2003

NASA Astrophysics Data System (ADS)

Janowicz, R.; Hedstrom, N.; Pomeroy, J.; Granger, R.; Carey, S.

2004-12-01

The development of hydrological models in northern regions are complicated by cold region processes. Sparse vegetation influences snowpack accumulation, redistribution and melt, frozen ground effects infiltration and runoff and cold soils in the summer effect evapotranspiration rates. Situated in the upper Yukon River watershed, the 195 km2 Wolf Creek Research Basin was instrumented in 1992 to calibrate hydrologic flow models, and has since evolved into a comprehensive study of cold region processes and linkages, contributing significantly to hydrological and climate change modelling. Studies include those of precipitation distribution, snowpack accumulation and redistribution, energy balance, snowmelt infiltration, and water balance. Studies of the spatial variability of hydrometeorological data demonstrate the importance of physical parameters on their distribution and control on runoff processes. Many studies have also identified the complex interaction of several of the physical parameters, including topography, vegetation and frozen ground (seasonal or permafrost) as important. They also show that there is a fundamental, underlying spatial structure to the watershed that must be adequately represented in parameterization schemes for scaling and watershed modelling. The specific results of numerous studies are presented.

Automatic Calibration of a Semi-Distributed Hydrologic Model Using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Bekele, E. G.; Nicklow, J. W.

2005-12-01

Hydrologic simulation models need to be calibrated and validated before using them for operational predictions. Spatially-distributed hydrologic models generally have a large number of parameters to capture the various physical characteristics of a hydrologic system. Manual calibration of such models is a very tedious and daunting task, and its success depends on the subjective assessment of a particular modeler, which includes knowledge of the basic approaches and interactions in the model. In order to alleviate these shortcomings, an automatic calibration model, which employs an evolutionary optimization technique known as Particle Swarm Optimizer (PSO) for parameter estimation, is developed. PSO is a heuristic search algorithm that is inspired by social behavior of bird flocking or fish schooling. The newly-developed calibration model is integrated to the U.S. Department of Agriculture's Soil and Water Assessment Tool (SWAT). SWAT is a physically-based, semi-distributed hydrologic model that was developed to predict the long term impacts of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use, and management conditions. SWAT was calibrated for streamflow and sediment concentration. The calibration process involves parameter specification, whereby sensitive model parameters are identified, and parameter estimation. In order to reduce the number of parameters to be calibrated, parameterization was performed. The methodology is applied to a demonstration watershed known as Big Creek, which is located in southern Illinois. Application results show the effectiveness of the approach and model predictions are significantly improved.

Watershed scale response to climate change--Pomperaug River Watershed, Connecticut

USGS Publications Warehouse

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.

Simultaneous Semi-Distributed Model Calibration Guided by ...

EPA Pesticide Factsheets

Modelling approaches to transfer hydrologically-relevant information from locations with streamflow measurements to locations without such measurements continues to be an active field of research for hydrologists. The Pacific Northwest Hydrologic Landscapes (PNW HL) provide a solid conceptual classification framework based on our understanding of dominant processes. A Hydrologic Landscape code (5 letter descriptor based on physical and climatic properties) describes each assessment unit area, and these units average area 60km2. The core function of these HL codes is to relate and transfer hydrologically meaningful information between watersheds without the need for streamflow time series. We present a novel approach based on the HL framework to answer the question “How can we calibrate models across separate watersheds simultaneously, guided by our understanding of dominant processes?“. We should be able to apply the same parameterizations to assessment units of common HL codes if 1) the Hydrologic Landscapes contain hydrologic information transferable between watersheds at a sub-watershed-scale and 2) we use a conceptual hydrologic model and parameters that reflect the hydrologic behavior of a watershed. In this study, This work specifically tests the ability or inability to use HL-codes to inform and share model parameters across watersheds in the Pacific Northwest. EPA’s Western Ecology Division has published and is refining a framework for defining la

A COMPUTATIONAL FRAMEWORK FOR EVALUATION OF NPS MANAGEMENT SCENARIOS: ROLE OF PARAMETER UNCERTAINTY

EPA Science Inventory

Utility of complex distributed-parameter watershed models for evaluation of the effectiveness of non-point source sediment and nutrient abatement scenarios such as Best Management Practices (BMPs) often follows the traditional {calibrate ---> validate ---> predict} procedure. Des...

P2S--Coupled simulation with the Precipitation-Runoff Modeling System (PRMS) and the Stream Temperature Network (SNTemp) Models

USGS Publications Warehouse

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.

Predicting nonstationary flood frequencies: Evidence supports an updated stationarity thesis in the United States

NASA Astrophysics Data System (ADS)

Luke, Adam; Vrugt, Jasper A.; AghaKouchak, Amir; Matthew, Richard; Sanders, Brett F.

2017-07-01

Nonstationary extreme value analysis (NEVA) can improve the statistical representation of observed flood peak distributions compared to stationary (ST) analysis, but management of flood risk relies on predictions of out-of-sample distributions for which NEVA has not been comprehensively evaluated. In this study, we apply split-sample testing to 1250 annual maximum discharge records in the United States and compare the predictive capabilities of NEVA relative to ST extreme value analysis using a log-Pearson Type III (LPIII) distribution. The parameters of the LPIII distribution in the ST and nonstationary (NS) models are estimated from the first half of each record using Bayesian inference. The second half of each record is reserved to evaluate the predictions under the ST and NS models. The NS model is applied for prediction by (1) extrapolating the trend of the NS model parameters throughout the evaluation period and (2) using the NS model parameter values at the end of the fitting period to predict with an updated ST model (uST). Our analysis shows that the ST predictions are preferred, overall. NS model parameter extrapolation is rarely preferred. However, if fitting period discharges are influenced by physical changes in the watershed, for example from anthropogenic activity, the uST model is strongly preferred relative to ST and NS predictions. The uST model is therefore recommended for evaluation of current flood risk in watersheds that have undergone physical changes. Supporting information includes a MATLAB® program that estimates the (ST/NS/uST) LPIII parameters from annual peak discharge data through Bayesian inference.

A Coupled Approach with Stochastic Rainfall-Runoff Simulation and Hydraulic Modeling for Extreme Flood Estimation on Large Watersheds

NASA Astrophysics Data System (ADS)

Paquet, E.

2015-12-01

The SCHADEX method aims at estimating the distribution of peak and daily discharges up to extreme quantiles. It couples a precipitation probabilistic model based on weather patterns, with a stochastic rainfall-runoff simulation process using a conceptual lumped model. It allows exploring an exhaustive set of hydrological conditions and watershed responses to intense rainfall events. Since 2006, it has been widely applied in France to about one hundred watersheds for dam spillway design, and also aboard (Norway, Canada and central Europe among others). However, its application to large watersheds (above 10 000 km²) faces some significant issues: spatial heterogeneity of rainfall and hydrological processes and flood peak damping due to hydraulic effects (flood plains, natural or man-made embankment) being the more important. This led to the development of an extreme flood simulation framework for large and heterogeneous watersheds, based on the SCHADEX method. Its main features are: Division of the large (or main) watershed into several smaller sub-watersheds, where the spatial homogeneity of the hydro-meteorological processes can reasonably be assumed, and where the hydraulic effects can be neglected. Identification of pilot watersheds where discharge data are available, thus where rainfall-runoff models can be calibrated. They will be parameters donors to non-gauged watersheds. Spatially coherent stochastic simulations for all the sub-watersheds at the daily time step. Identification of a selection of simulated events for a given return period (according to the distribution of runoff volumes at the scale of the main watershed). Generation of the complete hourly hydrographs at each of the sub-watersheds outlets. Routing to the main outlet with hydraulic 1D or 2D models. The presentation will be illustrated with the case-study of the Isère watershed (9981 km), a French snow-driven watershed. The main novelties of this method will be underlined, as well as its perspectives and future improvements.

Stream Discharge and Evapotranspiration Responses to Climate Change and Their Associated Uncertainties in a Large Semi-Arid Basin

NASA Astrophysics Data System (ADS)

Bassam, S.; Ren, J.

2017-12-01

Predicting future water availability in watersheds is very important for proper water resources management, especially in semi-arid regions with scarce water resources. Hydrological models have been considered as powerful tools in predicting future hydrological conditions in watershed systems in the past two decades. Streamflow and evapotranspiration are the two important components in watershed water balance estimation as the former is the most commonly-used indicator of the overall water budget estimation, and the latter is the second biggest component of water budget (biggest outflow from the system). One of the main concerns in watershed scale hydrological modeling is the uncertainties associated with model prediction, which could arise from errors in model parameters and input meteorological data, or errors in model representation of the physics of hydrological processes. Understanding and quantifying these uncertainties are vital to water resources managers for proper decision making based on model predictions. In this study, we evaluated the impacts of different climate change scenarios on the future stream discharge and evapotranspiration, and their associated uncertainties, throughout a large semi-arid basin using a stochastically-calibrated, physically-based, semi-distributed hydrological model. The results of this study could provide valuable insights in applying hydrological models in large scale watersheds, understanding the associated sensitivity and uncertainties in model parameters, and estimating the corresponding impacts on interested hydrological process variables under different climate change scenarios.

Analysis of regional rainfall-runoff parameters for the Lake Michigan Diversion hydrological modeling

USGS Publications Warehouse

Soong, David T.; Over, Thomas M.

2015-01-01

Recalibration of the HSPF parameters to the updated inputs and land covers was completed on two representative watershed models selected from the nine by using a manual method (HSPEXP) and an automatic method (PEST). The objective of the recalibration was to develop a regional parameter set that improves the accuracy in runoff volume prediction for the nine study watersheds. Knowledge about flow and watershed characteristics plays a vital role for validating the calibration in both manual and automatic methods. The best performing parameter set was determined by the automatic calibration method on a two-watershed model. Applying this newly determined parameter set to the nine watersheds for runoff volume simulation resulted in “very good” ratings in five watersheds, an improvement as compared to “very good” ratings achieved for three watersheds by the North Branch parameter set.

EVALUATING HYDROLOGICAL RESPONSE TO ...

EPA Pesticide Factsheets

Studies of future management and policy options based on different assumptions provide a mechanism to examine possible outcomes and especially their likely benefits or consequences. Planning and assessment in land and water resource management are evolving toward complex, spatially explicit regional assessments. These problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and temporal scales. The extensive data requirements and the difficult task of building input parameter files, however, have long been an obstacle to the timely and cost-effective use of such complex models by resource managers. The U.S. EPA Landscape Ecology Branch in collaboration with the USDA-ARS Southwest Watershed Research Center has developed a geographic information system (GIS) tool to facilitate this process. A GIS provides the framework within which spatially distributed data are collected and used to prepare model input files, and model results are evaluated. The Automated Geospatial Watershed Assessment (AGWA) tool uses widely available standardized spatial datasets that can be obtained via the internet at no cost to the user. The data are used to develop input parameter files for KINEROS2 and SWAT, two watershed runoff and erosion simulation models that operate at different spatial and temporal scales. AGWA automates the process of transforming digital data into simulation model results and provides a visualization tool

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.

MODELING PHYSICAL HABITAT PARAMETERS

EPA Science Inventory

Salmonid populations can be affected by alterations in stream physical habitat. Fish productivity is determined by the stream's physical habitat structure ( channel form, substrate distribution, riparian vegetation), water quality, flow regime and inputs from the watershed (sedim...

Flood predictions using the parallel version of distributed numerical physical rainfall-runoff model TOPKAPI

NASA Astrophysics Data System (ADS)

Boyko, Oleksiy; Zheleznyak, Mark

2015-04-01

The original numerical code TOPKAPI-IMMS of the distributed rainfall-runoff model TOPKAPI ( Todini et al, 1996-2014) is developed and implemented in Ukraine. The parallel version of the code has been developed recently to be used on multiprocessors systems - multicore/processors PC and clusters. Algorithm is based on binary-tree decomposition of the watershed for the balancing of the amount of computation for all processors/cores. Message passing interface (MPI) protocol is used as a parallel computing framework. The numerical efficiency of the parallelization algorithms is demonstrated for the case studies for the flood predictions of the mountain watersheds of the Ukrainian Carpathian regions. The modeling results is compared with the predictions based on the lumped parameters models.

Model simulations of flood and debris flow timing in steep catchments after wildfire

NASA Astrophysics Data System (ADS)

Rengers, F. K.; McGuire, L. A.; Kean, J. W.; Staley, D. M.; Hobley, D. E. J.

2016-08-01

Debris flows are a typical hazard on steep slopes after wildfire, but unlike debris flows that mobilize from landslides, most postwildfire debris flows are generated from water runoff. The majority of existing debris flow modeling has focused on landslide-triggered debris flows. In this study we explore the potential for using process-based rainfall-runoff models to simulate the timing of water flow and runoff-generated debris flows in recently burned areas. Two different spatially distributed hydrologic models with differing levels of complexity were used: the full shallow water equations and the kinematic wave approximation. Model parameter values were calibrated in two different watersheds, spanning two orders of magnitude in drainage area. These watersheds were affected by the 2009 Station Fire in the San Gabriel Mountains, CA, USA. Input data for the numerical models were constrained by time series of soil moisture, flow stage, and rainfall collected at field sites, as well as high-resolution lidar-derived digital elevation models. The calibrated parameters were used to model a third watershed in the burn area, and the results show a good match with observed timing of flow peaks. The calibrated roughness parameter (Manning's n) was generally higher when using the kinematic wave approximation relative to the shallow water equations, and decreased with increasing spatial scale. The calibrated effective watershed hydraulic conductivity was low for both models, even for storms occurring several months after the fire, suggesting that wildfire-induced changes to soil-water infiltration were retained throughout that time. Overall, the two model simulations were quite similar suggesting that a kinematic wave model, which is simpler and more computationally efficient, is a suitable approach for predicting flood and debris flow timing in steep, burned watersheds.

Model simulations of flood and debris flow timing in steep catchments after wildfire

USGS Publications Warehouse

Rengers, Francis K.; McGuire, Luke; Kean, Jason W.; Staley, Dennis M.; Hobley, D.E.J

2016-01-01

Debris flows are a typical hazard on steep slopes after wildfire, but unlike debris flows that mobilize from landslides, most post-wildfire debris flows are generated from water runoff. The majority of existing debris-flow modeling has focused on landslide-triggered debris flows. In this study we explore the potential for using process-based rainfall-runoff models to simulate the timing of water flow and runoff-generated debris flows in recently burned areas. Two different spatially distributed hydrologic models with differing levels of complexity were used: the full shallow water equations and the kinematic wave approximation. Model parameter values were calibrated in two different watersheds, spanning two orders of magnitude in drainage area. These watersheds were affected by the 2009 Station Fire in the San Gabriel Mountains, CA, USA. Input data for the numerical models were constrained by time series of soil moisture, flow stage, and rainfall collected at field sites, as well as high-resolution lidar-derived digital elevation models. The calibrated parameters were used to model a third watershed in the burn area, and the results show a good match with observed timing of flow peaks. The calibrated roughness parameter (Manning's $n$) was generally higher when using the kinematic wave approximation relative to the shallow water equations, and decreased with increasing spatial scale. The calibrated effective watershed hydraulic conductivity was low for both models, even for storms occurring several months after the fire, suggesting that wildfire-induced changes to soil-water infiltration were retained throughout that time. Overall the two model simulations were quite similar suggesting that a kinematic wave model, which is simpler and more computationally efficient, is a suitable approach for predicting flood and debris flow timing in steep, burned watersheds.

Simulation of semi-arid hydrological processes at different spatial resolutions using the AgroEcoSystem-Watershed (AgES-W) model

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.

Modeling runoff and erosion risk in a~small steep cultivated watershed using different data sources: from on-site measurements to farmers' perceptions

NASA Astrophysics Data System (ADS)

Auvet, B.; Lidon, B.; Kartiwa, B.; Le Bissonnais, Y.; Poussin, J.-C.

2015-09-01

This paper presents an approach to model runoff and erosion risk in a context of data scarcity, whereas the majority of available models require large quantities of physical data that are frequently not accessible. To overcome this problem, our approach uses different sources of data, particularly on agricultural practices (tillage and land cover) and farmers' perceptions of runoff and erosion. The model was developed on a small (5 ha) cultivated watershed characterized by extreme conditions (slopes of up to 55 %, extreme rainfall events) on the Merapi volcano in Indonesia. Runoff was modelled using two versions of STREAM. First, a lumped version was used to determine the global parameters of the watershed. Second, a distributed version used three parameters for the production of runoff (slope, land cover and roughness), a precise DEM, and the position of waterways for runoff distribution. This information was derived from field observations and interviews with farmers. Both surface runoff models accurately reproduced runoff at the outlet. However, the distributed model (Nash-Sutcliffe = 0.94) was more accurate than the adjusted lumped model (N-S = 0.85), especially for the smallest and biggest runoff events, and produced accurate spatial distribution of runoff production and concentration. Different types of erosion processes (landslides, linear inter-ridge erosion, linear erosion in main waterways) were modelled as a combination of a hazard map (the spatial distribution of runoff/infiltration volume provided by the distributed model), and a susceptibility map combining slope, land cover and tillage, derived from in situ observations and interviews with farmers. Each erosion risk map gives a spatial representation of the different erosion processes including risk intensities and frequencies that were validated by the farmers and by in situ observations. Maps of erosion risk confirmed the impact of the concentration of runoff, the high susceptibility of long steep slopes, and revealed the critical role of tillage direction. Calibrating and validating models using in situ measurements, observations and farmers' perceptions made it possible to represent runoff and erosion risk despite the initial scarcity of hydrological data. Even if the models mainly provided orders of magnitude and qualitative information, they significantly improved our understanding of the watershed dynamics. In addition, the information produced by such models is easy for farmers to use to manage runoff and erosion by using appropriate agricultural practices.

Performance of a distributed semi-conceptual hydrological model under tropical watershed conditions

USDA-ARS?s Scientific Manuscript database

Many hydrologic models have been developed to help manage natural resources all over the world. Nevertheless, most models have presented a high complexity in terms of data base requirements, as well as, many calibration parameters. This has resulted in serious difficulties to application in catchmen...

Developing a calibrated CONUS-wide watershed-scale simulation platform for quantifying the influence of different sources of uncertainty on streamflow forecast skill

NASA Astrophysics Data System (ADS)

Newman, A. J.; Sampson, K. M.; Wood, A. W.; Hopson, T. M.; Brekke, L. D.; Arnold, J.; Raff, D. A.; Clark, M. P.

2013-12-01

Skill in model-based hydrologic forecasting depends on the ability to estimate a watershed's initial moisture and energy conditions, to forecast future weather and climate inputs, and on the quality of the hydrologic model's representation of watershed processes. The impact of these factors on prediction skill varies regionally, seasonally, and by model. We are investigating these influences using a watershed simulation platform that spans the continental US (CONUS), encompassing a broad range of hydroclimatic variation, and that uses the current simulation models of National Weather Service streamflow forecasting operations. The first phase of this effort centered on the implementation and calibration of the SNOW-17 and Sacramento soil moisture accounting (SAC-SMA) based hydrologic modeling system for a range of watersheds. The base configuration includes 630 basins in the United States Geological Survey's Hydro-Climatic Data Network 2009 (HCDN-2009, Lins 2012) conterminous U.S. basin subset. Retrospective model forcings were derived from Daymet (http://daymet.ornl.gov/), and where available, a priori parameter estimates were based on or compared with the operational NWS model parameters. Model calibration was accomplished by several objective, automated strategies, including the shuffled complex evolution (SCE) optimization approach developed within the NWS in the early 1990s (Duan et al. 1993). This presentation describes outcomes from this effort, including insights about measuring simulation skill, and on relationships between simulation skill and model parameters, basin characteristics (climate, topography, vegetation, soils), and the quality of forcing inputs. References: %Z Thornton, P.; Thornton, M.; Mayer, B.; Wilhelmi, N.; Wei, Y.; Devarakonda, R; Cook, R. Daymet: Daily Surface Weather on a 1 km Grid for North America. 1980-2008; Oak Ridge National Laboratory Distributed Active Archive Center: Oak Ridge, TN, USA, 2012; Volume 10.

An inexact log-normal distribution-based stochastic chance-constrained model for agricultural water quality management

NASA Astrophysics Data System (ADS)

Wang, Yu; Fan, Jie; Xu, Ye; Sun, Wei; Chen, Dong

2018-05-01

In this study, an inexact log-normal-based stochastic chance-constrained programming model was developed for solving the non-point source pollution issues caused by agricultural activities. Compared to the general stochastic chance-constrained programming model, the main advantage of the proposed model is that it allows random variables to be expressed as a log-normal distribution, rather than a general normal distribution. Possible deviations in solutions caused by irrational parameter assumptions were avoided. The agricultural system management in the Erhai Lake watershed was used as a case study, where critical system factors, including rainfall and runoff amounts, show characteristics of a log-normal distribution. Several interval solutions were obtained under different constraint-satisfaction levels, which were useful in evaluating the trade-off between system economy and reliability. The applied results show that the proposed model could help decision makers to design optimal production patterns under complex uncertainties. The successful application of this model is expected to provide a good example for agricultural management in many other watersheds.

Topographic filtering simulation model for sediment source apportionment

NASA Astrophysics Data System (ADS)

Cho, Se Jong; Wilcock, Peter; Hobbs, Benjamin

2018-05-01

We propose a Topographic Filtering simulation model (Topofilter) that can be used to identify those locations that are likely to contribute most of the sediment load delivered from a watershed. The reduced complexity model links spatially distributed estimates of annual soil erosion, high-resolution topography, and observed sediment loading to determine the distribution of sediment delivery ratio across a watershed. The model uses two simple two-parameter topographic transfer functions based on the distance and change in elevation from upland sources to the nearest stream channel and then down the stream network. The approach does not attempt to find a single best-calibrated solution of sediment delivery, but uses a model conditioning approach to develop a large number of possible solutions. For each model run, locations that contribute to 90% of the sediment loading are identified and those locations that appear in this set in most of the 10,000 model runs are identified as the sources that are most likely to contribute to most of the sediment delivered to the watershed outlet. Because the underlying model is quite simple and strongly anchored by reliable information on soil erosion, topography, and sediment load, we believe that the ensemble of simulation outputs provides a useful basis for identifying the dominant sediment sources in the watershed.

Calibration and parameterization of a semi-distributed hydrological model to support sub-daily ensemble flood forecasting; a watershed in southeast Brazil

NASA Astrophysics Data System (ADS)

de Almeida Bressiani, D.; Srinivasan, R.; Mendiondo, E. M.

2013-12-01

The use of distributed or semi-distributed models to represent the processes and dynamics of a watershed in the last few years has increased. These models are important tools to predict and forecast the hydrological responses of the watersheds, and they can subside disaster risk management and planning. However they usually have a lot of parameters, of which, due to the spatial and temporal variability of the processes, are not known, specially in developing countries; therefore a robust and sensible calibration is very important. This study conduced a sub-daily calibration and parameterization of the Soil & Water Assessment Tool (SWAT) for a 12,600 km2 watershed in southeast Brazil, and uses ensemble forecasts to evaluate if the model can be used as a tool for flood forecasting. The Piracicaba Watershed, in São Paulo State, is mainly rural, but has about 4 million of population in highly relevant urban areas, and three cities in the list of critical cities of the National Center for Natural Disasters Monitoring and Alerts. For calibration: the watershed was divided in areas with similar hydrological characteristics, for each of these areas one gauge station was chosen for calibration; this procedure was performed to evaluate the effectiveness of calibrating in fewer places, since areas with the same group of groundwater, soil, land use and slope characteristics should have similar parameters; making calibration a less time-consuming task. The sensibility analysis and calibration were performed on the software SWAT-CUP with the optimization algorithm: Sequential Uncertainly Fitting Version 2 (SUFI-2), which uses Latin hypercube sampling scheme in an iterative process. The performance of the models to evaluate the calibration and validation was done with: Nash-Sutcliffe efficiency coefficient (NSE), determination coefficient (r2), root mean square error (RMSE), and percent bias (PBIAS), with monthly average values of NSE around 0.70, r2 of 0.9, normalized RMSE of 0.01, and PBIAS of 10. Past events were analysed to evaluate the possibility of using the SWAT developed model for Piracicaba watershed as a tool for ensemble flood forecasting. For the ensemble evaluation members from the numerical model Eta were used. Eta is an atmospheric model used for research and operational purposes, with 5km resolution, and is updated twice a day (00 e 12 UTC) for a ten day horizon, with precipitation and weather estimates for each hour. The parameterized SWAT model performed overall well for ensemble flood forecasting.

Calibration and Validation of Nonpoint Source Pollution and Erosion Comparison Tool,N- SPECT, for Tropical Conditions

NASA Astrophysics Data System (ADS)

Fares, A.; Cheng, C. L.; Dogan, A.

2006-12-01

Impaired water quality caused by agriculture, urbanization, and spread of invasive species has been identified as a major factor in the degradation of coastal ecosystems in the tropics. Watershed-scale nonpoint source pollution models facilitate in evaluating effective management practices to alleviate the negative impacts of different land-use changes. The Non-Point Source Pollution and Erosion Comparison Tool (N-SPECT) is a newly released watershed model that was not previously tested under tropical conditions. The two objectives of this study were to: i) calibrate and validate N-SPECT for the Hanalei Watershed of the Hawai`ian island of Kaua`i; ii) evaluate the performance of N-SPECT under tropical conditions using the sensitivity analysis approach. Hanalei watershed has one of the wettest points on earth, Mt. Waialeale with an average annual rainfall of 11,000 mm. This rainfall decreases to 2,000 mm at the outlet of the watershed near the coast. Number of rain days is one of the major input parameters that influences N-SPECT's simulation results. This parameter was used to account for plant canopy interception losses. The watershed was divided into sub- basins to accurately distribute the number of rain days throughout the watershed. Total runoff volume predicted by the model compared well with measured data. The model underestimated measured runoff by 1% for calibration period and 5% for validation period due to higher intensity precipitation in the validation period. Sensitivity analysis revealed that the model was most sensitive to the number of rain days, followed by canopy interception, and least sensitive to the number of sub-basins. The sediment and water quality portion of the model is currently being evaluated.

Modeling post-wildfire hydrological processes with ParFlow

NASA Astrophysics Data System (ADS)

Escobar, I. S.; Lopez, S. R.; Kinoshita, A. M.

2017-12-01

Wildfires alter the natural processes within a watershed, such as surface runoff, evapotranspiration rates, and subsurface water storage. Post-fire hydrologic models are typically one-dimensional, empirically-based models or two-dimensional, conceptually-based models with lumped parameter distributions. These models are useful for modeling and predictions at the watershed outlet; however, do not provide detailed, distributed hydrologic processes at the point scale within the watershed. This research uses ParFlow, a three-dimensional, distributed hydrologic model to simulate post-fire hydrologic processes by representing the spatial and temporal variability of soil burn severity (via hydrophobicity) and vegetation recovery. Using this approach, we are able to evaluate the change in post-fire water components (surface flow, lateral flow, baseflow, and evapotranspiration). This work builds upon previous field and remote sensing analysis conducted for the 2003 Old Fire Burn in Devil Canyon, located in southern California (USA). This model is initially developed for a hillslope defined by a 500 m by 1000 m lateral extent. The subsurface reaches 12.4 m and is assigned a variable cell thickness to explicitly consider soil burn severity throughout the stages of recovery and vegetation regrowth. We consider four slope and eight hydrophobic layer configurations. Evapotranspiration is used as a proxy for vegetation regrowth and is represented by the satellite-based Simplified Surface Energy Balance (SSEBOP) product. The pre- and post-fire surface runoff, subsurface storage, and surface storage interactions are evaluated at the point scale. Results will be used as a basis for developing and fine-tuning a watershed-scale model. Long-term 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. In reference to the presenter, Isabel Escobar: Research is funded by the NASA-DIRECT STEM Program. Travel expenses for this presentation is funded by CSU-LSAMP. CSU-LSAMP is supported by the National Science Foundation under Grant # HRD-1302873 and the CSU Office of Chancellor.

Enhancing model prediction reliability through improved soil representation and constrained model auto calibration - A paired waterhsed study

USDA-ARS?s Scientific Manuscript database

Process based and distributed watershed models possess a large number of parameters that are not directly measured in field and need to be calibrated through matching modeled in-stream fluxes with monitored data. Recently, there have been waves of concern about the reliability of this common practic...

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

PRMS-IV, the precipitation-runoff modeling system, version 4

USGS Publications Warehouse

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

2015-01-01

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

Indigenous Waters: Applying the SWAT Hydrological Model to the Lumbee River Watershed

NASA Astrophysics Data System (ADS)

Painter, J.; Singh, N.; Martin, K. L.; Vose, J. M.; Wear, D. N.; Emanuel, R. E.

2016-12-01

Hydrological modeling can reveal insight about how rainfall becomes streamflow in a watershed comprising heterogeneous soils, terrain and land cover. Modeling can also help disentangle predicted impacts of climate and land use change on hydrological processes. We applied a hydrological model to the Lumbee River watershed, also known as the Lumber River Watershed, in the coastal plain of North Carolina (USA) to better understand how streamflow may be impacted by predicted climate and land use change in the mid-21st century. The Lumbee River flows through a predominantly Native American community, which may be affected by changing water resources during this period. The long-term goal of our project is to predict the effects of climate and land use change on the Lumbee River watershed and on the Native community that relies upon the river. We applied the Soil & Water Assessment Tool for ArcGIS (ArcSWAT), which was calibrated to historical climate and USGS streamflow data during the late 20th century, and we determined frequency distributions for key model parameters that best predicted streamflow during this time period. After calibrating and validating the model during the historical period, we identified land use and climate projections to represent a range of future conditions in the watershed. Specifically, we selected downscaled climate forcing data from four general circulation models running the RCP8.5 scenario. We also selected land use projections from a cornerstone scenario of the USDA Forest Service's Southern Forest Futures Project. This presentation reports on our methods for propagating parameter and climatic uncertainty through model predictions, and it reports on spatial patterns of land use change predicted by the cornerstone scenario.

Exploring the Variability of Short-term Precipitation and Hydrological Response of Small Czech Watersheds

NASA Astrophysics Data System (ADS)

Kavka, Petr; Strouhal, Ludek; Weyskrabova, Lenka; Müller, Miloslav; Kozant, Petr

2017-04-01

The short-term rainfall temporal distribution is known to have a significant effect on the small watersheds' hydrological response. In Czech Republic there are limited publicly available data on rainfall patterns of short-term precipitation. On one side there are catalogues of very short-term synthetic rainfalls used in urban drainage planning and on the other side hourly distribution of daily totals of rainfalls with long return period for larger catchments analyses. This contribution introduces the preliminary outcomes of a running three years' project, which should bridge this gap and provide such data and methodology to the community of scientists, state administration as well as design planners. Six generalized 6-hours hyetographs with 1 minute resolution were derived from 10 years of radar and gauging stations data. These hyetographs are accompanied with information concerning the region of occurrence as well as their frequency related to the rainfall amount. In the next step these hyetographs are used in a complex sensitivity analysis focused on a rainfall-runoff response of small watersheds. This analysis takes into account the uncertainty related to type of the hydrological model, watershed characteristics and main model routines parameterization. Five models with different methods and structure are considered and each model is applied on 5 characteristic watersheds selected from a classification of 7700 small Czech watersheds. For each combination of model and watershed 30, rainfall scenarios were simulated and other scenarios will be used to address the parameters uncertainty. In the last step the variability of outputs will be assessed in the context of economic impacts on design of landscape water structures or mitigation measures. The research is supported by the grant QJ1520265 of the Czech Ministry of Agriculture, rainfall data were provided by the Czech Hydrometeorological Institute.

DRAINMOD-GIS: a lumped parameter watershed scale drainage and water quality model

Treesearch

G.P. Fernandez; G.M. Chescheir; R.W. Skaggs; D.M. Amatya

2006-01-01

A watershed scale lumped parameter hydrology and water quality model that includes an uncertainty analysis component was developed and tested on a lower coastal plain watershed in North Carolina. Uncertainty analysis was used to determine the impacts of uncertainty in field and network parameters of the model on the predicted outflows and nitrate-nitrogen loads at the...

An approach to measure parameter sensitivity in watershed ...

EPA Pesticide Factsheets

Hydrologic responses vary spatially and temporally according to watershed characteristics. In this study, the hydrologic models that we developed earlier for the Little Miami River (LMR) and Las Vegas Wash (LVW) watersheds were used for detail sensitivity analyses. To compare the relative sensitivities of the hydrologic parameters of these two models, we used Normalized Root Mean Square Error (NRMSE). By combining the NRMSE index with the flow duration curve analysis, we derived an approach to measure parameter sensitivities under different flow regimes. Results show that the parameters related to groundwater are highly sensitive in the LMR watershed, whereas the LVW watershed is primarily sensitive to near surface and impervious parameters. The high and medium flows are more impacted by most of the parameters. Low flow regime was highly sensitive to groundwater related parameters. Moreover, our approach is found to be useful in facilitating model development and calibration. This journal article describes hydrological modeling of climate change and land use changes on stream hydrology, and elucidates the importance of hydrological model construction in generating valid modeling results.

Methodology and application of combined watershed and ground-water models in Kansas

USGS Publications Warehouse

Sophocleous, M.; Perkins, S.P.

2000-01-01

Increased irrigation in Kansas and other regions during the last several decades has caused serious water depletion, making the development of comprehensive strategies and tools to resolve such problems increasingly important. This paper makes the case for an intermediate complexity, quasi-distributed, comprehensive, large-watershed model, which falls between the fully distributed, physically based hydrological modeling system of the type of the SHE model and the lumped, conceptual rainfall-runoff modeling system of the type of the Stanford watershed model. This is achieved by integrating the quasi-distributed watershed model SWAT with the fully-distributed ground-water model MODFLOW. The advantage of this approach is the appreciably smaller input data requirements and the use of readily available data (compared to the fully distributed, physically based models), the statistical handling of watershed heterogeneities by employing the hydrologic-response-unit concept, and the significantly increased flexibility in handling stream-aquifer interactions, distributed well withdrawals, and multiple land uses. The mechanics of integrating the component watershed and ground-water models are outlined, and three real-world management applications of the integrated model from Kansas are briefly presented. Three different aspects of the integrated model are emphasized: (1) management applications of a Decision Support System for the integrated model (Rattlesnake Creek subbasin); (2) alternative conceptual models of spatial heterogeneity related to the presence or absence of an underlying aquifer with shallow or deep water table (Lower Republican River basin); and (3) the general nature of the integrated model linkage by employing a watershed simulator other than SWAT (Wet Walnut Creek basin). These applications demonstrate the practicality and versatility of this relatively simple and conceptually clear approach, making public acceptance of the integrated watershed modeling system much easier. This approach also enhances model calibration and thus the reliability of model results. (C) 2000 Elsevier Science B.V.Increased irrigation in Kansas and other regions during the last several decades has caused serious water depletion, making the development of comprehensive strategies and tools to resolve such problems increasingly important. This paper makes the case for an intermediate complexity, quasi-distributed, comprehensive, large-watershed model, which falls between the fully distributed, physically based hydrological modeling system of the type of the SHE model and the lumped, conceptual rainfall-runoff modeling system of the type of the Stanford watershed model. This is achieved by integrating the quasi-distributed watershed model SWAT with the fully-distributed ground-water model MODFLOW. The advantage of this approach is the appreciably smaller input data requirements and the use of readily available data (compared to the fully distributed, physically based models), the statistical handling of watershed heterogeneities by employing the hydrologic-response-unit concept, and the significantly increased flexibility in handling stream-aquifer interactions, distributed well withdrawals, and multiple land uses. The mechanics of integrating the component watershed and ground-water models are outlined, and three real-world management applications of the integrated model from Kansas are briefly presented. Three different aspects of the integrated model are emphasized: (1) management applications of a Decision Support System for the integrated model (Rattlesnake Creek subbasin); (2) alternative conceptual models of spatial heterogeneity related to the presence or absence of an underlying aquifer with shallow or deep water table (Lower Republican River basin); and (3) the general nature of the integrated model linkage by employing a watershed simulator other than SWAT (Wet Walnut Creek basin). These applications demonstrate the practicality and ve

Watershed scale response to climate change--Trout Lake Basin, Wisconsin

USGS Publications Warehouse

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

USGS Publications Warehouse

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

USGS Publications Warehouse

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

USGS Publications Warehouse

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

USGS Publications Warehouse

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--Starkweather Coulee Basin, North Dakota

USGS Publications Warehouse

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

USGS Publications Warehouse

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

USGS Publications Warehouse

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

USGS Publications Warehouse

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

USGS Publications Warehouse

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

USGS Publications Warehouse

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

USGS Publications Warehouse

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.

Influence of the Magnitude and Spatial Distribution of Water Storage in Aquifers on the Character of Baseflow Recessions

NASA Astrophysics Data System (ADS)

Nieber, J. L.; Li, W.

2017-12-01

The instantaneous groundwater discharge (Qgw) from a watershed is related to volume of drainable water stored (Sgw) within the watershed aquifer(s). The relation is hysteretic and the magnitude of the hysteresis is completely scale-dependent. In the research reported here we apply a previously calibrated (USGS) GSFLOW model to the simulation of surface and subsurface runoff for the Sagehen Creek watershed. This 29.3 km2 watershed is located in the eastern range of the Sierra Nevada Mountains, and most of the precipitation falls in the form of snow. The GSFLOW model is composed of a surface water and shallow subsurface flow hydrology model, PRMS, and a groundwater flow component based on MODFLOW. PRMS is a semi-distributed watershed model, very similar in character to the well-known SWAT model. The PRMS model is coupled with the MODFLOW model in that deep percolation generated within the PRMS model feeds into the MODFLOW model. The simulated baseflow recessions, plotted as -dQ/dt vs Q, show a strong dependence to watershed topography and plot concave downward. These plots show a somewhat weaker dependence on the hydrologic fluxes of evapotranspiration and recharge, with the concave downward shape maintained but somewhat modified by these hydrologic fluxes. As expected the Qgw vs Sgw relation is markedly hysteretic. The cause for this hysteresis is related to the magnitude of water stored, and also the spatial distribution of water stored in the watershed, with the antecedent storage in upland areas controlling the recession flow in late time, while the valley area dominates the recession flow in the early time. Both the minimum streamflow (Qmin ; the flow at the transition between early time and late time uninterrupted recession) and the intercept (intercept of the regression line fit to the recession data on a log-log scale) show a strong relationship with antecedent streamflows. The minimum streamflow, Qmin, is found to be a valid normalizing parameter for producing a unique normalized -dQ/dt vs. Q relation from data manifesting the effects of hysteresis. It is proposed that this normalized relation can be used to improve the performance of low-dimension dynamic models of watershed hydrology that would otherwise not account for hysteresis in Qgw vs Sgw.

Curve Number Application in Continuous Runoff Models: An Exercise in Futility?

NASA Astrophysics Data System (ADS)

Lamont, S. J.; Eli, R. N.

2006-12-01

The suitability of applying the NRCS (Natural Resource Conservation Service) Curve Number (CN) to continuous runoff prediction is examined by studying the dependence of CN on several hydrologic variables in the context of a complex nonlinear hydrologic model. The continuous watershed model Hydrologic Simulation Program-FORTRAN (HSPF) was employed using a simple theoretical watershed in two numerical procedures designed to investigate the influence of soil type, soil depth, storm depth, storm distribution, and initial abstraction ratio value on the calculated CN value. This study stems from a concurrent project involving the design of a hydrologic modeling system to support the Cumulative Hydrologic Impact Assessments (CHIA) of over 230 coal-mined watersheds throughout West Virginia. Because of the large number of watersheds and limited availability of data necessary for HSPF calibration, it was initially proposed that predetermined CN values be used as a surrogate for those HSPF parameters controlling direct runoff. A soil physics model was developed to relate CN values to those HSPF parameters governing soil moisture content and infiltration behavior, with the remaining HSPF parameters being adopted from previous calibrations on real watersheds. A numerical procedure was then adopted to back-calculate CN values from the theoretical watershed using antecedent moisture conditions equivalent to the NRCS Antecedent Runoff Condition (ARC) II. This procedure used the direct runoff produced from a cyclic synthetic storm event time series input to HSPF. A second numerical method of CN determination, using real time series rainfall data, was used to provide a comparison to those CN values determined using the synthetic storm event time series. It was determined that the calculated CN values resulting from both numerical methods demonstrated a nonlinear dependence on all of the computational variables listed above. It was concluded that the use of the Curve Number as a surrogate for the selected subset of HPSF parameters could not be justified. These results suggest that use of the Curve Number in other complex continuous time series hydrologic models may not be appropriate, given the limitations inherent in the definition of the NRCS CN method.

A METHODOLOGY FOR ESTIMATING UNCERTAINTY OF A DISTRIBUTED HYDROLOGIC MODEL: APPLICATION TO POCONO CREEK WATERSHED

EPA Science Inventory

Utility of distributed hydrologic and water quality models for watershed management and sustainability studies should be accompanied by rigorous model uncertainty analysis. However, the use of complex watershed models primarily follows the traditional {calibrate/validate/predict}...

Modular modeling system for building distributed hydrologic models with a user-friendly software package

NASA Astrophysics Data System (ADS)

Wi, S.; Ray, P. A.; Brown, C.

2015-12-01

A software package developed to facilitate building distributed hydrologic models in a modular modeling system is presented. The software package provides a user-friendly graphical user interface that eases its practical use in water resources-related research and practice. The modular modeling system organizes the options available to users when assembling models according to the stages of hydrological cycle, such as potential evapotranspiration, soil moisture accounting, and snow/glacier melting processes. The software is intended to be a comprehensive tool that simplifies the task of developing, calibrating, validating, and using hydrologic models through the inclusion of intelligent automation to minimize user effort, and reduce opportunities for error. Processes so far automated include the definition of system boundaries (i.e., watershed delineation), climate and geographical input generation, and parameter calibration. Built-in post-processing toolkits greatly improve the functionality of the software as a decision support tool for water resources system management and planning. Example post-processing toolkits enable streamflow simulation at ungauged sites with predefined model parameters, and perform climate change risk assessment by means of the decision scaling approach. The software is validated through application to watersheds representing a variety of hydrologic regimes.

[Nitrogen non-point source pollution identification based on ArcSWAT in Changle River].

PubMed

Deng, Ou-Ping; Sun, Si-Yang; Lü, Jun

2013-04-01

The ArcSWAT (Soil and Water Assessment Tool) model was adopted for Non-point source (NPS) nitrogen pollution modeling and nitrogen source apportionment for the Changle River watershed, a typical agricultural watershed in Southeast China. Water quality and hydrological parameters were monitored, and the watershed natural conditions (including soil, climate, land use, etc) and pollution sources information were also investigated and collected for SWAT database. The ArcSWAT model was established in the Changle River after the calibrating and validating procedures of the model parameters. Based on the validated SWAT model, the contributions of different nitrogen sources to river TN loading were quantified, and spatial-temporal distributions of NPS nitrogen export to rivers were addressed. The results showed that in the Changle River watershed, Nitrogen fertilizer, nitrogen air deposition and nitrogen soil pool were the prominent pollution sources, which contributed 35%, 32% and 25% to the river TN loading, respectively. There were spatial-temporal variations in the critical sources for NPS TN export to the river. Natural sources, such as soil nitrogen pool and atmospheric nitrogen deposition, should be targeted as the critical sources for river TN pollution during the rainy seasons. Chemical nitrogen fertilizer application should be targeted as the critical sources for river TN pollution during the crop growing season. Chemical nitrogen fertilizer application, soil nitrogen pool and atmospheric nitrogen deposition were the main sources for TN exported from the garden plot, forest and residential land, respectively. However, they were the main sources for TN exported both from the upland and paddy field. These results revealed that NPS pollution controlling rules should focus on the spatio-temporal distribution of NPS pollution sources.

The importance of diverse data types to calibrate a watershed model of the Trout Lake Basin, Northern Wisconsin, USA

USGS Publications Warehouse

Hunt, R.J.; Feinstein, D.T.; Pint, C.D.; Anderson, M.P.

2006-01-01

As part of the USGS Water, Energy, and Biogeochemical Budgets project and the NSF Long-Term Ecological Research work, a parameter estimation code was used to calibrate a deterministic groundwater flow model of the Trout Lake Basin in northern Wisconsin. Observations included traditional calibration targets (head, lake stage, and baseflow observations) as well as unconventional targets such as groundwater flows to and from lakes, depth of a lake water plume, and time of travel. The unconventional data types were important for parameter estimation convergence and allowed the development of a more detailed parameterization capable of resolving model objectives with well-constrained parameter values. Independent estimates of groundwater inflow to lakes were most important for constraining lakebed leakance and the depth of the lake water plume was important for determining hydraulic conductivity and conceptual aquifer layering. The most important target overall, however, was a conventional regional baseflow target that led to correct distribution of flow between sub-basins and the regional system during model calibration. The use of an automated parameter estimation code: (1) facilitated the calibration process by providing a quantitative assessment of the model's ability to match disparate observed data types; and (2) allowed assessment of the influence of observed targets on the calibration process. The model calibration required the use of a 'universal' parameter estimation code in order to include all types of observations in the objective function. The methods described in this paper help address issues of watershed complexity and non-uniqueness common to deterministic watershed models. ?? 2005 Elsevier B.V. All rights reserved.

A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

2015-04-01

The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Uncertainty in BMP evaluation and optimization for watershed management

NASA Astrophysics Data System (ADS)

Chaubey, I.; Cibin, R.; Sudheer, K.; Her, Y.

2012-12-01

Use of computer simulation models have increased substantially to make watershed management decisions and to develop strategies for water quality improvements. These models are often used to evaluate potential benefits of various best management practices (BMPs) for reducing losses of pollutants from sources areas into receiving waterbodies. Similarly, use of simulation models in optimizing selection and placement of best management practices under single (maximization of crop production or minimization of pollutant transport) and multiple objective functions has increased recently. One of the limitations of the currently available assessment and optimization approaches is that the BMP strategies are considered deterministic. Uncertainties in input data (e.g. precipitation, streamflow, sediment, nutrient and pesticide losses measured, land use) and model parameters may result in considerable uncertainty in watershed response under various BMP options. We have developed and evaluated options to include uncertainty in BMP evaluation and optimization for watershed management. We have also applied these methods to evaluate uncertainty in ecosystem services from mixed land use watersheds. In this presentation, we will discuss methods to to quantify uncertainties in BMP assessment and optimization solutions due to uncertainties in model inputs and parameters. We have used a watershed model (Soil and Water Assessment Tool or SWAT) to simulate the hydrology and water quality in mixed land use watershed located in Midwest USA. The SWAT model was also used to represent various BMPs in the watershed needed to improve water quality. SWAT model parameters, land use change parameters, and climate change parameters were considered uncertain. It was observed that model parameters, land use and climate changes resulted in considerable uncertainties in BMP performance in reducing P, N, and sediment loads. In addition, climate change scenarios also affected uncertainties in SWAT simulated crop yields. Considerable uncertainties in the net cost and the water quality improvements resulted due to uncertainties in land use, climate change, and model parameter values.

The role of interior watershed processes in improving parameter estimation and performance of watershed models.

PubMed

Yen, Haw; Bailey, Ryan T; Arabi, Mazdak; Ahmadi, Mehdi; White, Michael J; Arnold, Jeffrey G

2014-09-01

Watershed models typically are evaluated solely through comparison of in-stream water and nutrient fluxes with measured data using established performance criteria, whereas processes and responses within the interior of the watershed that govern these global fluxes often are neglected. Due to the large number of parameters at the disposal of these models, circumstances may arise in which excellent global results are achieved using inaccurate magnitudes of these "intra-watershed" responses. When used for scenario analysis, a given model hence may inaccurately predict the global, in-stream effect of implementing land-use practices at the interior of the watershed. In this study, data regarding internal watershed behavior are used to constrain parameter estimation to maintain realistic intra-watershed responses while also matching available in-stream monitoring data. The methodology is demonstrated for the Eagle Creek Watershed in central Indiana. Streamflow and nitrate (NO) loading are used as global in-stream comparisons, with two process responses, the annual mass of denitrification and the ratio of NO losses from subsurface and surface flow, used to constrain parameter estimation. Results show that imposing these constraints not only yields realistic internal watershed behavior but also provides good in-stream comparisons. Results further demonstrate that in the absence of incorporating intra-watershed constraints, evaluation of nutrient abatement strategies could be misleading, even though typical performance criteria are satisfied. Incorporating intra-watershed responses yields a watershed model that more accurately represents the observed behavior of the system and hence a tool that can be used with confidence in scenario evaluation. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Using Predictive Uncertainty Analysis to Assess Hydrologic Model Performance for a Watershed in Oregon

NASA Astrophysics Data System (ADS)

Brannan, K. M.; Somor, A.

2016-12-01

A variety of statistics are used to assess watershed model performance but these statistics do not directly answer the question: what is the uncertainty of my prediction. Understanding predictive uncertainty is important when using a watershed model to develop a Total Maximum Daily Load (TMDL). TMDLs are a key component of the US Clean Water Act and specify the amount of a pollutant that can enter a waterbody when the waterbody meets water quality criteria. TMDL developers use watershed models to estimate pollutant loads from nonpoint sources of pollution. We are developing a TMDL for bacteria impairments in a watershed in the Coastal Range of Oregon. We setup an HSPF model of the watershed and used the calibration software PEST to estimate HSPF hydrologic parameters and then perform predictive uncertainty analysis of stream flow. We used Monte-Carlo simulation to run the model with 1,000 different parameter sets and assess predictive uncertainty. In order to reduce the chance of specious parameter sets, we accounted for the relationships among parameter values by using mathematically-based regularization techniques and an estimate of the parameter covariance when generating random parameter sets. We used a novel approach to select flow data for predictive uncertainty analysis. We set aside flow data that occurred on days that bacteria samples were collected. We did not use these flows in the estimation of the model parameters. We calculated a percent uncertainty for each flow observation based 1,000 model runs. We also used several methods to visualize results with an emphasis on making the data accessible to both technical and general audiences. We will use the predictive uncertainty estimates in the next phase of our work, simulating bacteria fate and transport in the watershed.

Evaluating agricultural nonpoint-source pollution using integrated geographic information systems and hydrologic/water quality model

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

Tim, U.S.; Jolly, R.

1994-01-01

Considerable progress has been made in developing physically based, distributed parameter, hydrologic/water quality (HIWQ) models for planning and control of nonpoint-source pollution. The widespread use of these models is often constrained by the excessive and time-consuming input data demands and the lack of computing efficiencies necessary for iterative simulation of alternative management strategies. Recent developments in geographic information systems (GIS) provide techniques for handling large amounts of spatial data for modeling nonpoint-source pollution problems. Because a GIS can be used to combine information from several sources to form an array of model input data and to examine any combinations ofmore » spatial input/output data, it represents a highly effective tool for HiWQ modeling. This paper describes the integration of a distributed-parameter model (AGNPS) with a GIS (ARC/INFO) to examine nonpoint sources of pollution in an agricultural watershed. The ARC/INFO GIS provided the tools to generate and spatially organize the disparate data to support modeling, while the AGNPS model was used to predict several water quality variables including soil erosion and sedimentation within a watershed. The integrated system was used to evaluate the effectiveness of several alternative management strategies in reducing sediment pollution in a 417-ha watershed located in southern Iowa. The implementation of vegetative filter strips and contour buffer (grass) strips resulted in a 41 and 47% reduction in sediment yield at the watershed outlet, respectively. In addition, when the integrated system was used, the combination of the above management strategies resulted in a 71% reduction in sediment yield. In general, the study demonstrated the utility of integrating a simulation model with GIS for nonpoini-source pollution control and planning. Such techniques can help characterize the diffuse sources of pollution at the landscape level. 52 refs., 6 figs., 1 tab.« less

Hydrometeorological Analysis of Flooding Events in San Antonio, TX

NASA Astrophysics Data System (ADS)

Chintalapudi, S.; Sharif, H.; Elhassan, A.

2008-12-01

South Central Texas is particularly vulnerable to floods due to: proximity to a moist air source (the Gulf of Mexico); the Balcones Escarpment, which concentrates rainfall runoff; a tendency for synoptic scale features to become cut-off and stall over the area; and decaying tropical cyclones stalling over the area. The San Antonio Metropolitan Area is the 7th largest city in the nation, one of the most flash-flood prone regions in North America, and has experienced a number of flooding events in the last decade (1998, 2002, 2004, and 2007). Research is being conducted to characterize the meteorological conditions that lead to these events and apply the rainfall and watershed characteristics data to recreate the runoff events using a two- dimensional, physically-based, distributed-parameter hydrologic model. The physically based, distributed-parameter Gridded Surface Subsurface Hydrologic Analysis (GSSHA) hydrological model was used for simulating the watershed response to these storm events. Finally observed discharges were compared to GSSHA model discharges for these storm events. Analysis of the some of these events will be presented.

Mapping the Climate of Puerto Rico, Vieques and Culebra.

Treesearch

CHRISTOPHER DALY; E. H. HELMER; MAYA QUINONES

2003-01-01

Spatially explicit climate data contribute to watershed resource management, mapping vegetation type with satellite imagery, mapping present and hypothetical future ecological zones, and predicting species distributions. The regression based Parameter-elevation Regressions on Independent Slopes Model (PRISM) uses spatial data sets, a knowledge base and expert...

METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL

EPA Science Inventory

The use of a fitted-parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can l...

An integrated groundwater and surface water approach to quantifying the contribution of hydrological pathways to streamflow

NASA Astrophysics Data System (ADS)

O'Brien, R. J.; Deakin, J.; Misstear, B.; Gill, L.; Flynn, R. M.

2012-12-01

An appreciation of the quantity of streamflow derived from the main hydrological groundwater and surface water pathways transporting diffuse pollutants is critical when addressing a wide range of water resource management issues. The Pathways Project, funded by the Irish EPA, is developing a Catchment Management Tool (CMT) as an aid to water resource decision makers. The pollutants investigated by the CMT include phosphorus, nitrogen, sediments, pesticides and pathogens. An important first step in this process is to provide reliable estimates of the slower responding groundwater pathways in conjunction with the quicker overland and interflow pathways. Four watersheds are being investigated, with continuous rainfall, discharge, temperature and conductivity data being collected at gauging points within each of the watersheds. These datasets are being used to populate the semi-distributed, lumped flow model, NAM and also the distributed, finite difference model, MODFLOW. One of the main challenges is to achieve credible separations of the hydrograph into the main pathways in relatively small catchments (sometimes less than 5km2) with short response times. To assist the numerical modelling, physical separation techniques have been used to constrain the separations within probable limits. Physical techniques include: Master Recession Analysis; a modified Lyne and Hollick one-parameter digital separation; an approach developed in Ireland involving the application of recharge coefficients to hydrologically effective rainfall estimates; and finally using the NAM and MODFLOW models themselves as means of investigating separations. The contribution from each of the pathways, combined with an understanding of the attenuation of the contaminants along those pathways, will inform the CMT. This understanding will lay the foundation for linking the parameters of the NAM model to watershed descriptors such as slope, drainage density, watershed area, soil type, etc., in order to predict the response of a watershed to rainfall. This is an important deliverable of this research and will be fundamental for initial investigations in ungauged watersheds. This approach to quantifying hydrological pathways will therefore have wider applicability across Ireland and in hydrological settings elsewhere internationally. The research is being carried out for the Environmental Protection Agency by a consortium involving Queen's University Belfast, University College Dublin and Trinity College Dublin. Pathway separations in a karst watershed. Observed discharge (Black) with separated pathways: quick diffuse flow (Blue); slow diffuse flow (Green); interflow (Light Blue) and overland flow (Red).

Definition and sensitivity of the conceptual MORDOR rainfall-runoff model parameters using different multi-criteria calibration strategies

NASA Astrophysics Data System (ADS)

Garavaglia, F.; Seyve, E.; Gottardi, F.; Le Lay, M.; Gailhard, J.; Garçon, R.

2014-12-01

MORDOR is a conceptual hydrological model extensively used in Électricité de France (EDF, French electric utility company) operational applications: (i) hydrological forecasting, (ii) flood risk assessment, (iii) water balance and (iv) climate change studies. MORDOR is a lumped, reservoir, elevation based model with hourly or daily areal rainfall and air temperature as the driving input data. The principal hydrological processes represented are evapotranspiration, direct and indirect runoff, ground water, snow accumulation and melt and routing. The model has been intensively used at EDF for more than 20 years, in particular for modeling French mountainous watersheds. In the matter of parameters calibration we propose and test alternative multi-criteria techniques based on two specific approaches: automatic calibration using single-objective functions and a priori parameter calibration founded on hydrological watershed features. The automatic calibration approach uses single-objective functions, based on Kling-Gupta efficiency, to quantify the good agreement between the simulated and observed runoff focusing on four different runoff samples: (i) time-series sample, (I) annual hydrological regime, (iii) monthly cumulative distribution functions and (iv) recession sequences.The primary purpose of this study is to analyze the definition and sensitivity of MORDOR parameters testing different calibration techniques in order to: (i) simplify the model structure, (ii) increase the calibration-validation performance of the model and (iii) reduce the equifinality problem of calibration process. We propose an alternative calibration strategy that reaches these goals. The analysis is illustrated by calibrating MORDOR model to daily data for 50 watersheds located in French mountainous regions.

Application of Physics Based Distributed Hydrologic Models to Assess Anthropologic Land Disturbance in Watersheds

NASA Astrophysics Data System (ADS)

Downer, C. W.; Ogden, F. L.; Byrd, A. R.

2008-12-01

The Department of Defense (DoD) manages approximately 200,000 km2 of land within the United States on military installations and flood control and river improvement projects. The Watershed Systems Group (WSG) within the Coastal and Hydraulics Laboratory of the Engineer Research and Development Center (ERDC) supports the US Army and the US Army Corps of Engineers in both military and civil operations through the development, modification and application of surface and sub-surface hydrologic models. The US Army has a long history of land management and the development of analytical tools to assist with the management of US Army lands. The US Army has invested heavily in the distributed hydrologic model GSSHA and its predecessor CASC2D. These tools have been applied at numerous military and civil sites to analyze the effects of landscape alteration on hydrologic response and related consequences, changes in erosion and sediment transport, along with associated contaminants. Examples include: impacts of military training and land management activities, impact of changing land use (urbanization or environmental restoration), as well as impacts of management practices employed to abate problems, i.e. Best Management Practices (BMPs). Traditional models such as HSPF and SWAT, are largely conceptual in nature. GSSHA attempts to simulate the physical processes actually occurring in the watershed allowing the user to explicitly simulate changing parameter values in response to changes in land use, land cover, elevation, etc. Issues of scale raise questions: How do we best include fine-scale land use or management features in models of large watersheds? Do these features have to be represented explicitly through physical processes in the watershed domain? Can a point model, physical or empirical, suffice? Can these features be lumped into coarsely resolved numerical grids or sub-watersheds? In this presentation we will discuss the US Army's distributed hydrologic models in terms of how they simulate the relevant processes and present multiple applications of the models used for analyzing land management and land use change. Using these applications as a basis we will discuss issues related to the analysis of anthropogenic alterations in the landscape.

Coupling of Water and Carbon Cycles in Boreal Ecosystems at Watershed and National Scales

NASA Astrophysics Data System (ADS)

Chen, J. M.; Ju, W.; Govind, A.; Sonnentag, O.

2009-05-01

The boreal landscapes is relatively flat giving the impression of spatial homogeneity. However, glacial activities have left distinct fingerprints on the vegetation distribution on moderately rolling terrains over the boreal landscape. Upland or lowland forests types or wetlands having various degrees of hydrological connectivitiy to the surrounding terrain are typical of the boreal landscape. The nature of the terrain creates unique hydrological conditions affecting the local-scale ecophysiological and biogeochemical processes. As part of the Canadian Carbon Program, we investigated the importance of lateral water redistribution through surface and subsurface flows in the spatial distribution of the vertical fluxes of water and carbon. A spatially explicit hydroecological model (BEPS-TerrainLab) has been developed and tested in forested and wetland watersheds . Remotely sensed vegetation parameters along with other spatial datasets are used to run this model, and tower flux data are used for partial validation. It is demonstrated in both forest and wetland watersheds that ignoring the lateral water redistribution over the landscape, commonly done in 1-dimensional bucket models, can cause considerable biases in the vertical carbon and water flux estimation, in addition to the distortion of the spatial patterns of these fluxes. The biases in the carbon flux are considerably larger than those in the water flux. The significance of these findings in national carbon budget estimation is demonstrated by separate modeling of 2015 watersheds over the Canadian landmass.

Comparative analysis of model behaviour for flood prediction purposes using Self-Organizing Maps

NASA Astrophysics Data System (ADS)

Herbst, M.; Casper, M. C.; Grundmann, J.; Buchholz, O.

2009-03-01

Distributed watershed models constitute a key component in flood forecasting systems. It is widely recognized that models because of their structural differences have varying capabilities of capturing different aspects of the system behaviour equally well. Of course, this also applies to the reproduction of peak discharges by a simulation model which is of particular interest regarding the flood forecasting problem. In our study we use a Self-Organizing Map (SOM) in combination with index measures which are derived from the flow duration curve in order to examine the conditions under which three different distributed watershed models are capable of reproducing flood events present in the calibration data. These indices are specifically conceptualized to extract data on the peak discharge characteristics of model output time series which are obtained from Monte-Carlo simulations with the distributed watershed models NASIM, LARSIM and WaSIM-ETH. The SOM helps to analyze this data by producing a discretized mapping of their distribution in the index space onto a two dimensional plane such that their pattern and consequently the patterns of model behaviour can be conveyed in a comprehensive manner. It is demonstrated how the SOM provides useful information about details of model behaviour and also helps identifying the model parameters that are relevant for the reproduction of peak discharges and thus for flood prediction problems. It is further shown how the SOM can be used to identify those parameter sets from among the Monte-Carlo data that most closely approximate the peak discharges of a measured time series. The results represent the characteristics of the observed time series with partially superior accuracy than the reference simulation obtained by implementing a simple calibration strategy using the global optimization algorithm SCE-UA. The most prominent advantage of using SOM in the context of model analysis is that it allows to comparatively evaluating the data from two or more models. Our results highlight the individuality of the model realizations in terms of the index measures and shed a critical light on the use and implementation of simple and yet too rigorous calibration strategies.

Hydrologic behaviour of the Lake of Monate (Italy): a parsimonious modelling strategy

NASA Astrophysics Data System (ADS)

Tomesani, Giulia; Soligno, Irene; Castellarin, Attilio; Baratti, Emanuele; Cervi, Federico; Montanari, Alberto

2016-04-01

The Lake of Monate (province of Varese, Northern Italy), is a unique example of ecosystem in equilibrium. The lake water quality is deemed excellent notwithstanding the intensive agricultural cultivation, industrial assets and mining activities characterising the surrounding areas. The lake has a true touristic vocation and is the only swimmable water body of the province of Varese, which counts several natural lakes. Lake of Monate has no tributary and its overall watershed area is equal to c.a. 6.6 km2 including the lake surface (i.e. 2.6 km2), of which 3.3 out of c.a. 4.0 km2 belong to the topographical watershed, while the remaining 0.7 km2 belong to the underground watershed. The latter is larger than the topographical watershed due to the presence of moraine formations on top of the limestone bedrock. The local administration recently promoted an intensive environmental monitoring campaign that aims to reach a better understanding of the hydrology of the lake and the subsurface water fluxes. The monitoring campaign started in October 2013 and, as a result, several meteoclimatic and hydrologic data have been collected up to now at daily and hourly timescales. Our study focuses on a preliminary representation of the hydrological behaviour of the lake through a modified version of HyMOD, a conceptual 5-parameter lumped rainfall-runoff model based on the probability-distributed soil storage capacity. The modified model is a semi-distributed application of HyMOD that uses the same five parameters of the original version and simulates the rainfall-runoff transformation for the whole lake watershed at daily time scale in terms of: direct precipitation on, and evaporation from, the lake surface; overall lake inflow, by separating the runoff component (topographic watershed) from the groundwater component (overall watershed); lake water-level oscillation; streamflow at the lake outlet. We used the first year of hydrometeorological observations as calibration data and the second year as validation data and we compared two calibration strategies which maximize two different objective functions: (1) Nash-Sutcliffe efficiency of simulated daily water-level fluctuations, NSE, and (2) linear correlation coefficient between daily series of simulated groundwater inflow and observed water table elevation multiplied by NSE. The validation exercise seems to point out the value of incorporating groundwater measurements for improving the reliability and robustness of the conceptual model.

A Four-parameter Budyko Equation for Mean Annual Water Balance

NASA Astrophysics Data System (ADS)

Tang, Y.; Wang, D.

2016-12-01

In this study, a four-parameter Budyko equation for long-term water balance at watershed scale is derived based on the proportionality relationships of the two-stage partitioning of precipitation. The four-parameter Budyko equation provides a practical solution to balance model simplicity and representation of dominated hydrologic processes. Under the four-parameter Budyko framework, the key hydrologic processes related to the lower bound of Budyko curve are determined, that is, the lower bound is corresponding to the situation when surface runoff and initial evaporation not competing with base flow generation are zero. The derived model is applied to 166 MOPEX watersheds in United States, and the dominant controlling factors on each parameter are determined. Then, four statistical models are proposed to predict the four model parameters based on the dominant controlling factors, e.g., saturated hydraulic conductivity, fraction of sand, time period between two storms, watershed slope, and Normalized Difference Vegetation Index. This study shows a potential application of the four-parameter Budyko equation to constrain land-surface parameterizations in ungauged watersheds or general circulation models.

Simulation of streamflow in the Pleasant, Narraguagus, Sheepscot, and Royal Rivers, Maine, using watershed models

USGS Publications Warehouse

Dudley, Robert W.; Nielsen, Martha G.

2011-01-01

The U.S. Geological Survey (USGS) began a study in 2008 to investigate anticipated changes in summer streamflows and stream temperatures in four coastal Maine river basins and the potential effects of those changes on populations of endangered Atlantic salmon. To achieve this purpose, it was necessary to characterize the quantity and timing of streamflow in these rivers by developing and evaluating a distributed-parameter watershed model for a part of each river basin by using the USGS Precipitation-Runoff Modeling System (PRMS). The GIS (geographic information system) Weasel, a USGS software application, was used to delineate the four study basins and their many subbasins, and to derive parameters for their geographic features. The models were calibrated using a four-step optimization procedure in which model output was evaluated against four datasets for calibrating solar radiation, potential evapotranspiration, annual and seasonal water balances, and daily streamflows. The calibration procedure involved thousands of model runs that used the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The calibrated watershed models performed satisfactorily, in that Nash-Sutcliffe efficiency (NSE) statistic values for the calibration periods ranged from 0.59 to 0.75 (on a scale of negative infinity to 1) and NSE statistic values for the evaluation periods ranged from 0.55 to 0.73. The calibrated watershed models simulate daily streamflow at many locations in each study basin. These models enable natural resources managers to characterize the timing and amount of streamflow in order to support a variety of water-resources efforts including water-quality calculations, assessments of water use, modeling of population dynamics and migration of Atlantic salmon, modeling and assessment of habitat, and simulation of anticipated changes to streamflow and water temperature resulting from changes forecast for air temperature and precipitation.

Parameterization and Uncertainty Analysis of SWAT model in Hydrological Simulation of Chaohe River Basin

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.

GIS model-based real-time hydrological forecasting and operation management system for the Lake Balaton and its watershed

NASA Astrophysics Data System (ADS)

Adolf Szabó, János; Zoltán Réti, Gábor; Tóth, Tünde

2017-04-01

Today, the most significant mission of the decision makers on integrated water management issues is to carry out sustainable management for sharing the resources between a variety of users and the environment under conditions of considerable uncertainty (such as climate/land-use/population/etc. change) conditions. In light of this increasing water management complexity, we consider that the most pressing needs is to develop and implement up-to-date GIS model-based real-time hydrological forecasting and operation management systems for aiding decision-making processes to improve water management. After years of researches and developments the HYDROInform Ltd. has developed an integrated, on-line IT system (DIWA-HFMS: DIstributed WAtershed - Hydrologyc Forecasting & Modelling System) which is able to support a wide-ranging of the operational tasks in water resources management such as: forecasting, operation of lakes and reservoirs, water-control and management, etc. Following a test period, the DIWA-HFMS has been implemented for the Lake Balaton and its watershed (in 500 m resolution) at Central-Transdanubian Water Directorate (KDTVIZIG). The significant pillars of the system are: - The DIWA (DIstributed WAtershed) hydrologic model, which is a 3D dynamic water-balance model that distributed both in space and its parameters, and which was developed along combined principles but its mostly based on physical foundations. The DIWA integrates 3D soil-, 2D surface-, and 1D channel-hydraulic components as well. - Lakes and reservoir-operating component; - Radar-data integration module; - fully online data collection tools; - scenario manager tool to create alternative scenarios, - interactive, intuitive, highly graphical user interface. In Vienna, the main functions, operations and results-management of the system will be presented.

Climate change impact assessment on hydrology of a small watershed using semi-distributed model

NASA Astrophysics Data System (ADS)

Pandey, Brij Kishor; Gosain, A. K.; Paul, George; Khare, Deepak

2017-07-01

This study is an attempt to quantify the impact of climate change on the hydrology of Armur watershed in Godavari river basin, India. A GIS-based semi-distributed hydrological model, soil and water assessment tool (SWAT) has been employed to estimate the water balance components on the basis of unique combinations of slope, soil and land cover classes for the base line (1961-1990) and future climate scenarios (2071-2100). Sensitivity analysis of the model has been performed to identify the most critical parameters of the watershed. Average monthly calibration (1987-1994) and validation (1995-2000) have been performed using the observed discharge data. Coefficient of determination (R2), Nash-Sutcliffe efficiency (ENS) and root mean square error (RMSE) were used to evaluate the model performance. Calibrated SWAT setup has been used to evaluate the changes in water balance components of future projection over the study area. HadRM3, a regional climatic data, have been used as input of the hydrological model for climate change impact studies. In results, it was found that changes in average annual temperature (+3.25 °C), average annual rainfall (+28 %), evapotranspiration (28 %) and water yield (49 %) increased for GHG scenarios with respect to the base line scenario.

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

NASA Astrophysics Data System (ADS)

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

2003-04-01

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

Hydrogeology and Simulated Ground-Water Flow in the Salt Pond Region of Southern Rhode Island

USGS Publications Warehouse

Masterson, John P.; Sorenson, Jason R.; Stone, Janet R.; Moran, S. Bradley; Hougham, Andrea

2007-01-01

The Salt Pond region of southern Rhode Island extends from Westerly to Narragansett Bay and forms the natural boundary between the Atlantic Ocean and the shallow, highly permeable freshwater aquifer of the South Coastal Basin. Large inputs of fresh ground water coupled with the low flushing rates to the open ocean make the salt ponds particularly susceptible to eutrophication and bacterial contamination. Ground-water discharge to the salt ponds is an important though poorly quantified source of contaminants, such as dissolved nutrients. A ground-water-flow model was developed and used to delineate the watersheds to the salt ponds, including the areas that contribute ground water directly to the ponds and the areas that contribute ground water to streams that flow into ponds. The model also was used to calculate ground-water fluxes to these coastal areas for long-term average conditions. As part of the modeling analysis, adjustments were made to model input parameters to assess potential uncertainties in model-calculated watershed delineations and in ground-water discharge to the salt ponds. The results of the simulations indicate that flow to the salt ponds is affected primarily by the ease with which water is transmitted through a glacial moraine deposit near the regional ground-water divide, and by the specified recharge rate used in the model simulations. The distribution of the total freshwater flow between direct ground-water discharge and ground-water-derived surface-water (streamflow) discharge to the salt ponds is affected primarily by simulated stream characteristics, including the streambed-aquifer connection and the stream stage. The simulated position of the ground-water divide and, therefore, the model-calculated watershed delineations for the salt ponds, were affected only by changes in the transmissivity of the glacial moraine. Selected changes in other simulated hydraulic parameters had substantial effects on total freshwater discharge and the distribution of direct ground-water discharge and ground-water-derived surface-water (streamflow) discharge to the salt ponds, but still provided a reasonable match to the hydrologic data available for model calibration. To reduce the uncertainty in predictions of watershed areas and ground-water discharge to the salt ponds, additional hydrogeologic data would be required to constrain the model input parameters that have the greatest effect on the simulation results.

R-HyMOD: an R-package for the hydrological model HyMOD

NASA Astrophysics Data System (ADS)

Baratti, Emanuele; Montanari, Alberto

2015-04-01

A software code for the implementation of the HyMOD hydrological model [1] is presented. HyMOD is a conceptual lumped rainfall-runoff model that is based on the probability-distributed soil storage capacity principle introduced by R. J. Moore 1985 [2]. The general idea behind this model is to describe the spatial variability of some process parameters as, for instance, the soil structure or the water storage capacities, through probability distribution functions. In HyMOD, the rainfall-runoff process is represented through a nonlinear tank connected with three identical linear tanks in parallel representing the surface flow and a slow-flow tank representing groundwater flow. The model requires the optimization of five parameters: Cmax (the maximum storage capacity within the watershed), β (the degree of spatial variability of the soil moisture capacity within the watershed), α (a factor for partitioning the flow between two series of tanks) and the two residence time parameters of quick-flow and slow-flow tanks, kquick and kslow respectively. Given its relatively simplicity but robustness, the model is widely used in the literature. The input data consist of precipitation and potential evapotranspiration at the given time scale. The R-HyMOD package is composed by a 'canonical' R-function of HyMOD and a fast FORTRAN implementation. The first one can be easily modified and can be used, for instance, for educational purposes; the second part combines the R user friendly interface with a fast processing unit. [1] Boyle D.P. (2000), Multicriteria calibration of hydrological models, Ph.D. dissertation, Dep. of Hydrol. and Water Resour., Univ of Arizona, Tucson. [2] Moore, R.J., (1985), The probability-distributed principle and runoff production at point and basin scale, Hydrol. Sci. J., 30(2), 273-297.

Geographic information system/watershed model interface

USGS Publications Warehouse

Fisher, Gary T.

1989-01-01

Geographic information systems allow for the interactive analysis of spatial data related to water-resources investigations. A conceptual design for an interface between a geographic information system and a watershed model includes functions for the estimation of model parameter values. Design criteria include ease of use, minimal equipment requirements, a generic data-base management system, and use of a macro language. An application is demonstrated for a 90.1-square-kilometer subbasin of the Patuxent River near Unity, Maryland, that performs automated derivation of watershed parameters for hydrologic modeling.

Probability distribution functions for unit hydrographs with optimization using genetic algorithm

NASA Astrophysics Data System (ADS)

Ghorbani, Mohammad Ali; Singh, Vijay P.; Sivakumar, Bellie; H. Kashani, Mahsa; Atre, Atul Arvind; Asadi, Hakimeh

2017-05-01

A unit hydrograph (UH) of a watershed may be viewed as the unit pulse response function of a linear system. In recent years, the use of probability distribution functions (pdfs) for determining a UH has received much attention. In this study, a nonlinear optimization model is developed to transmute a UH into a pdf. The potential of six popular pdfs, namely two-parameter gamma, two-parameter Gumbel, two-parameter log-normal, two-parameter normal, three-parameter Pearson distribution, and two-parameter Weibull is tested on data from the Lighvan catchment in Iran. The probability distribution parameters are determined using the nonlinear least squares optimization method in two ways: (1) optimization by programming in Mathematica; and (2) optimization by applying genetic algorithm. The results are compared with those obtained by the traditional linear least squares method. The results show comparable capability and performance of two nonlinear methods. The gamma and Pearson distributions are the most successful models in preserving the rising and recession limbs of the unit hydographs. The log-normal distribution has a high ability in predicting both the peak flow and time to peak of the unit hydrograph. The nonlinear optimization method does not outperform the linear least squares method in determining the UH (especially for excess rainfall of one pulse), but is comparable.

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

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

The role of interior watershed processes in improving parameter estimation and performance of watershed models

USDA-ARS?s Scientific Manuscript database

Watershed models typically are evaluated solely through comparison of in-stream water and nutrient fluxes with measured data using established performance criteria, whereas processes and responses within the interior of the watershed that govern these global fluxes often are neglected. Due to the l...

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

NASA Astrophysics Data System (ADS)

Li, Y.

2015-12-01

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

Application of the Precipitation Runoff Modeling System to measure impacts of forest fire on watershed hydrology

NASA Astrophysics Data System (ADS)

Driscoll, J. M.

2015-12-01

Precipitation in the southwestern United States falls primarily in areas of higher elevation. Drought conditions over the past five years have limited snowpack and rainfall, increasing the vulnerability to and frequency of forest fires in these montane regions. In June 2012, the Little Bear fire burned approximately 69 square miles (44,200 acres) in high-elevation forests of the Rio Hondo headwater catchments, south-central New Mexico. Burn severity was high or moderate on 53 percent of the burn area. The Precipitation Runoff Modeling System (PRMS) is a publically-available watershed model developed by the U.S. Geological Survey (USGS). PRMS data are spatially distributed using a 'Geospatial Fabric' developed at a national scale to define Hydrologic Response Units (HRUs), based on topography and points of interest (such as confluences and streamgages). The Little Bear PRMS study area is comprised of 22 HRUs over a 587 square-mile area contributing to the Rio Hondo above Chavez Canyon streamgage (USGS ID 08390020), in operation from 2008 to 2014. Model input data include spatially-distributed climate data from the National Aeronautics and Space Administration (NASA) DayMet and land cover (such as vegetation and soil properties) data from the USGS Geo Data Portal. Remote sensing of vegetation over time has provided a spatial distribution of recovery and has been applied using dynamic parameters within PRMS on the daily timestep over the study area. Investigation into the source and timing of water budget components in the Rio Hondo watershed may assist water planners and managers in determining how the surface-water and groundwater systems will react to future land use/land cover changes. Further application of PRMS in additional areas will allow for comparison of streamflow before and following wildfire conditions, and may lead to better understanding of the changes in watershed-scale hydrologic processes in the Southwest through post-fire watershed recovery.

A new hydrological model for estimating extreme floods in the Alps

NASA Astrophysics Data System (ADS)

Receanu, R. G.; Hertig, J.-A.; Fallot, J.-M.

2012-04-01

Protection against flooding is very important for a country like Switzerland with a varied topography and many rivers and lakes. Because of the potential danger caused by extreme precipitation, structural and functional safety of large dams must be guaranteed to withstand the passage of an extreme flood. We introduce a new distributed hydrological model to calculate the PMF from a PMP which is spatially and temporally distributed using clouds. This model has permitted the estimation of extreme floods based on the distributed PMP and the taking into account of the specifics of alpine catchments, in particular the small size of the basins, the complex topography, the large lakes, snowmelt and glaciers. This is an important evolution compared to other models described in the literature, as they mainly use a uniform distribution of extreme precipitation all over the watershed. This paper presents the results of calculation with the developed rainfall-runoff model, taking into account measured rainfall and comparing results to observed flood events. This model includes three parts: surface runoff, underground flow and melting snow. Two Swiss watersheds are studied, for which rainfall data and flow rates are available for a considerably long period, including several episodes of heavy rainfall with high flow events. From these events, several simulations are performed to estimate the input model parameters such as soil roughness and average width of rivers in case of surface runoff. Following the same procedure, the parameters used in the underground flow simulation are also estimated indirectly, since direct underground flow and exfiltration measurements are difficult to obtain. A sensitivity analysis of the parameters is performed at the first step to define more precisely the boundary and initial conditions. The results for the two alpine basins, validated with the Nash equation, show a good correlation between the simulated and observed flows. This good correlation shows that the model is valid and gives us the confidence that the results can be extrapolated to phenomena of extreme rainfall of PMP type.

Composite measures of watershed health from a water quality perspective.

PubMed

Mallya, Ganeshchandra; Hantush, Mohamed; Govindaraju, Rao S

2018-05-15

Water quality data at gaging stations are typically compared with established federal, state, or local water quality standards to determine if violations (concentrations of specific constituents falling outside acceptable limits) have occurred. Based on the frequency and severity of water quality violations, risk metrics such as reliability, resilience, and vulnerability (R-R-V) are computed for assessing water quality-based watershed health. In this study, a modified methodology for computing R-R-V measures is presented, and a new composite watershed health index is proposed. Risk-based assessments for different water quality parameters are carried out using identified national sampling stations within the Upper Mississippi River Basin, the Maumee River Basin, and the Ohio River Basin. The distributional properties of risk measures with respect to water quality parameters are reported. Scaling behaviors of risk measures using stream order, specifically for the watershed health (WH) index, suggest that WH values increased with stream order for suspended sediment concentration, nitrogen, and orthophosphate in the Upper Mississippi River Basin. Spatial distribution of risk measures enable identification of locations exhibiting poor watershed health with respect to the chosen numerical standard, and the role of land use characteristics within the watershed. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Regionalization Approach to select the final watershed parameter set among the Pareto solutions

NASA Astrophysics Data System (ADS)

Park, G. H.; Micheletty, P. D.; Carney, S.; Quebbeman, J.; Day, G. N.

2017-12-01

The calibration of hydrological models often results in model parameters that are inconsistent with those from neighboring basins. Considering that physical similarity exists within neighboring basins some of the physically related parameters should be consistent among them. Traditional manual calibration techniques require an iterative process to make the parameters consistent, which takes additional effort in model calibration. We developed a multi-objective optimization procedure to calibrate the National Weather Service (NWS) Research Distributed Hydrological Model (RDHM), using the Nondominant Sorting Genetic Algorithm (NSGA-II) with expert knowledge of the model parameter interrelationships one objective function. The multi-objective algorithm enables us to obtain diverse parameter sets that are equally acceptable with respect to the objective functions and to choose one from the pool of the parameter sets during a subsequent regionalization step. Although all Pareto solutions are non-inferior, we exclude some of the parameter sets that show extremely values for any of the objective functions to expedite the selection process. We use an apriori model parameter set derived from the physical properties of the watershed (Koren et al., 2000) to assess the similarity for a given parameter across basins. Each parameter is assigned a weight based on its assumed similarity, such that parameters that are similar across basins are given higher weights. The parameter weights are useful to compute a closeness measure between Pareto sets of nearby basins. The regionalization approach chooses the Pareto parameter sets that minimize the closeness measure of the basin being regionalized. The presentation will describe the results of applying the regionalization approach to a set of pilot basins in the Upper Colorado basin as part of a NASA-funded project.

Developing of Watershed Radionuclide Transport Model DHSVM-R as Modification and Extension of Distributed Hydrological and Sediment Dynamics Model DHSVM

NASA Astrophysics Data System (ADS)

Zheleznyak, M.; Kivva, S.; Onda, Y.; Nanba, K.; Wakiyama, Y.; Konoplev, A.

2015-12-01

The reliable modeling tools for prediction wash - off radionuclides from watersheds are needed as for assessment the consequences of accidental and industrial releases of radionuclides, as for soil erosion studies using the radioactive tracers. The distributed model of radionuclide transport through watershed in exchangeable and nonexchangeable forms in solute and with sediments was developed and validated for small Chernobyl watersheds in 90th within EU SPARTACUS project (van der Perk et al., 1996). New tendency is coupling of radionuclide transport models and the widely validated hydrological distributed models. To develop radionuclide transport model DHSVM-R the open source Distributed Hydrology Soil Vegetation Model -DHSVM http://www.hydro.washington.edu/Lettenmaier/Models/DHSVM was modified and extended. The main changes provided in the hydrological and sediment transport modules of DHSVM are as follows: Morel-Seytoux infiltration model is added; four-directions schematization for the model's cells flows (D4) is replaced by D8 approach; the finite-difference schemes for solution of kinematic wave equations for overland water flow, stream net flow, and sediment transport are replaced by new computationally efficient scheme. New radionuclide transport module, coupled with hydrological and sediment transport modules, continues SPARTACUS's approach, - it describes radionuclide wash-off from watershed and transport via stream network in soluble phase and on suspended sediments. The hydrological module of DHSVM-R was calibrated and validated for the watersheds of Ukrainian Carpathian mountains and for the subwatersheds of Niida river flowing 137Cs in solute and with suspended sediments to Pacific Ocean at 30 km north of the Fukushima Daiichi NPP. The modules of radionuclide and sediment transport were calibrated and validated versus experimental data for USLE experimental plots in Fukushima Prefecture and versus monitoring data collected in Niida watershed. The role of sediment transport in radionuclide wash-off from mountain and lowland watersheds is analyzed in comparison of modeling results for Chernobyl and Fukushima watersheds.

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.

Simulating nitrate response functions in watersheds: Case studies in the United States and New Zealand

NASA Astrophysics Data System (ADS)

Gusyev, Maksym; Abrams, Daniel; Morgenstern, Uwe; Stewart, Michael

2016-04-01

Non-point sources of nitrate contamination are a common concern in different parts of the world and are difficult to characterize. Due to the solubility of nitrate, it easily enters groundwater and may take years or decades to completely flush to a stream. During this time, it may undergo denitrification, in particular if dissolved oxygen levels are low, requiring a representation of spatially distributed nitrate input as well as detailed hydrogeology. In this presentation, nitrate response functions are generated with four different methodologies that are listed in the order of decreasing degrees of freedom: groundwater flow and chemical transport (MODFLOW/MT3D), groundwater flow with solute particle tracing (MODFLOW/MODPATH), cross-sectional groundwater flow model (MODFLOW), and lumped parameter models (LPMs). We tested these approaches in selected watersheds in the Eastern and Midwestern United States as well as New Zealand and found similar nitrate results in all cases despite different model complexities. It is noted that only the fully three dimensional MODFLOW models with MT3D or MODPATH could account for detailed patterns of land use and nitrate applications; the cross-sectional models and lumped parameter models could only do so approximately. Denitrification at depth could also be explicitly accounted for in all four approaches, although this was not a major factor in any of the watersheds investigated.

Travel time analysis for a subsurface drained sub-watershed in Upper Big Walnut Creek Watershed, Ohio

USDA-ARS?s Scientific Manuscript database

Runoff travel time, which is a function of watershed and storm characteristics, is an important parameter affecting the prediction accuracy of hydrologic models. Although, time of concentration (tc) is a most widely used time parameter, it has multiple conceptual and computational definitions. Most ...

Advances in Parameter and Uncertainty Quantification Using Bayesian Hierarchical Techniques with a Spatially Referenced Watershed Model (Invited)

NASA Astrophysics Data System (ADS)

Alexander, R. B.; Boyer, E. W.; Schwarz, G. E.; Smith, R. A.

2013-12-01

Estimating water and material stores and fluxes in watershed studies is frequently complicated by uncertainties in quantifying hydrological and biogeochemical effects of factors such as land use, soils, and climate. Although these process-related effects are commonly measured and modeled in separate catchments, researchers are especially challenged by their complexity across catchments and diverse environmental settings, leading to a poor understanding of how model parameters and prediction uncertainties vary spatially. To address these concerns, we illustrate the use of Bayesian hierarchical modeling techniques with a dynamic version of the spatially referenced watershed model SPARROW (SPAtially Referenced Regression On Watershed attributes). The dynamic SPARROW model is designed to predict streamflow and other water cycle components (e.g., evapotranspiration, soil and groundwater storage) for monthly varying hydrological regimes, using mechanistic functions, mass conservation constraints, and statistically estimated parameters. In this application, the model domain includes nearly 30,000 NHD (National Hydrologic Data) stream reaches and their associated catchments in the Susquehanna River Basin. We report the results of our comparisons of alternative models of varying complexity, including models with different explanatory variables as well as hierarchical models that account for spatial and temporal variability in model parameters and variance (error) components. The model errors are evaluated for changes with season and catchment size and correlations in time and space. The hierarchical models consist of a two-tiered structure in which climate forcing parameters are modeled as random variables, conditioned on watershed properties. Quantification of spatial and temporal variations in the hydrological parameters and model uncertainties in this approach leads to more efficient (lower variance) and less biased model predictions throughout the river network. Moreover, predictions of water-balance components are reported according to probabilistic metrics (e.g., percentiles, prediction intervals) that include both parameter and model uncertainties. These improvements in predictions of streamflow dynamics can inform the development of more accurate predictions of spatial and temporal variations in biogeochemical stores and fluxes (e.g., nutrients and carbon) in watersheds.

Risk assessment of watershed erosion at Naesung Stream, South Korea.

PubMed

Ji, Un; Velleux, Mark; Julien, Pierre Y; Hwang, Manha

2014-04-01

A three-tiered approach was used to assess erosion risks within the Nakdong River Basin in South Korea and included: (1) a screening based on topography and land use; (2) a lumped parameter analysis using RUSLE; and (3) a detailed analysis using TREX, a fully distributed watershed model. These tiers span a range of spatial and temporal scales, with each tier providing increasing detail and resolution. The first two tiers were applied to the entire Nakdong River Basin and the Naesung Stream watershed was identified as having the highest soil erosion risk and potential for sedimentation problems. For the third tier, the TREX watershed model simulated runoff, channel flow, soil erosion, and stream sediment transport in the Naesung Stream watershed at very high resolution. TREX was calibrated for surface flows and sediment transport, and was used to simulate conditions for a large design storm. Highly erosive areas were identified along ridgelines in several headwater areas, with the northeast area of Songriwon having a particularly high erosion potential. Design storm simulations also indicated that sediment deposition of up to 55 cm could occur. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identification of drought in Dhalai river watershed using MCDM and ANN models

NASA Astrophysics Data System (ADS)

Aher, Sainath; Shinde, Sambhaji; Guha, Shantamoy; Majumder, Mrinmoy

2017-03-01

An innovative approach for drought identification is developed using Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN) models from surveyed drought parameter data around the Dhalai river watershed in Tripura hinterlands, India. Total eight drought parameters, i.e., precipitation, soil moisture, evapotranspiration, vegetation canopy, cropping pattern, temperature, cultivated land, and groundwater level were obtained from expert, literature and cultivator survey. Then, the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) were used for weighting of parameters and Drought Index Identification (DII). Field data of weighted parameters in the meso scale Dhalai River watershed were collected and used to train the ANN model. The developed ANN model was used in the same watershed for identification of drought. Results indicate that the Limited-Memory Quasi-Newton algorithm was better than the commonly used training method. Results obtained from the ANN model shows the drought index developed from the study area ranges from 0.32 to 0.72. Overall analysis revealed that, with appropriate training, the ANN model can be used in the areas where the model is calibrated, or other areas where the range of input parameters is similar to the calibrated region for drought identification.

Development, calibration, and analysis of a hydrologic and water-quality model of the Delaware Inland Bays watershed

USGS Publications Warehouse

Gutierrez-Magness, Angelica L.; Raffensperger, Jeff P.

2003-01-01

Excessive nutrients and sediment are among the most significant environmental stressors in the Delaware Inland Bays (Rehoboth, Indian River, and Little Assawoman Bays). Sources of nutrients, sediment, and other contaminants within the Inland Bays watershed include point-source discharges from industries and wastewater-treatment plants, runoff and infiltration to ground water from agricultural fields and poultry operations, effluent from on-site wastewater disposal systems, and atmospheric deposition. To determine the most effective restoration methods for the Inland Bays, it is necessary to understand the relative distribution and contribution of each of the possible sources of nutrients, sediment, and other contaminants. A cooperative study involving the Delaware Department of Natural Resources and Environmental Control, the Delaware Geological Survey, and the U.S. Geological Survey was initiated in 2000 to develop a hydrologic and water-quality model of the Delaware Inland Bays watershed that can be used as a water-resources planning and management tool. The model code Hydrological Simulation Program - FORTRAN (HSPF) was used. The 719-square-kilometer watershed was divided into 45 model segments, and the model was calibrated using streamflow and water-quality data for January 1999 through April 2000 from six U.S. Geological Survey stream-gaging stations within the watershed. Calibration for some parameters was accomplished using PEST, a model-independent parameter estimator. Model parameters were adjusted systematically so that the discrepancies between the simulated values and the corresponding observations were minimized. Modeling results indicate that soil and aquifer permeability, ditching, dominant land-use class, and land-use practices affect the amount of runoff, the mechanism or flow path (surface flow, interflow, or base flow), and the loads of sediment and nutrients. In general, the edge-of-stream total suspended solids yields in the Inland Bays watershed are low in comparison to yields reported for the Eastern Shore from the Chesapeake Bay watershed model. The flatness of the terrain and the low annual surface runoff are important factors in determining the amount of detached sediment from the land that is delivered to streams. The highest total suspended solids yields were found in the southern part of the watershed, associated with high total streamflow and a high surface runoff component, and related to soil and aquifer permeability and land use. Nutrient yields from watershed model segments in the southern part of the Inland Bays watershed were the highest of all calibrated segments, due to high runoff and the substantial amount of available organic fertilizer (animal waste), which results in over-application of organic fertilizer to crops. Time series of simulated hourly total nitrogen concentrations and observed instantaneous values indicate a seasonal pattern, with the lowest values occurring during the summer and the highest during the winter months. Total phosphorus and total suspended solids concentrations are somewhat less seasonal. During storm events, total nitrogen concentrations tend to be diluted and total phosphorus concentrations tend to rise sharply. Nitrogen is transported mainly in the aqueous phase and primarily through ground water, whereas phosphorus is strongly associated with sediment, which washes off during precipitation events.

Hydrologic conditions and assessment of water resources in the Turkey Creek watershed, Jefferson County, Colorado, 1998-2001

USGS Publications Warehouse

Bossong, Clifford R.; Caine, Jonathan S.; Stannard, David I.; Flynn, Jennifer L.; Stevens, Michael R.; Heiny-Dash, Janet S.

2003-01-01

The 47.2-square-mile Turkey Creek watershed, in Jefferson County southwest of Denver, Colorado, is relatively steep with about 4,000 feet of relief and is in an area of fractured crystalline rocks of Precambrian age. Water needs for about 4,900 households in the watershed are served by domestic wells and individual sewage-disposal systems. Hydrologic conditions are described on the basis of contemporary hydrologic and geologic data collected in the watershed from early spring 1998 through September 2001. The water resources are assessed using discrete fracture-network modeling to estimate porosity and a physically based, distributed-parameter watershed runoff model to develop estimates of water-balance terms. A variety of climatologic and hydrologic data were collected. Direct measurements of evapotranspiration indicate that a large amount (3 calendar-year mean of 82.9 percent) of precipitation is returned to the atmosphere. Surface-water records from January 1, 1999, through September 30, 2001, indicate that about 9 percent of precipitation leaves the watershed as streamflow in a seasonal pattern, with highest streamflows generally occurring in spring related to snowmelt and precipitation. Although conditions vary considerably within the watershed, overall watershed streamflow, based on several records collected during the 1940's, 1950's, 1980', and 1990's near the downstream part of watershed, can be as high as about 200 cubic feet per second on a daily basis during spring. Streamflow typically recedes to about 1 cubic foot per second or less during rainless periods and is rarely zero. Ground-water level data indicate a seasonal pattern similar to that of surface water in which water levels are highest, rising tens of feet in some locations, in the spring and then receding during rainless periods at relatively constant rates until recharged. Synoptic measurements of water levels in 131 mostly domestic wells in fall of 2001 indicate a water-table surface that conforms to topography. Analyses of reported well-construction records indicate a median reported well yield of 4 gallons per minute and a spatial distribution for reported well yield that has relatively uniform conditions of small-scale variability. Results from quarterly samples collected in water year 1999 at about 112 wells and 22 streams indicate relatively concentrated calcium-bicarbonate to calcium-chloride type water that has a higher concentration of chloride than would be expected on the basis of chloride content in precipitation and evapotranspiration rates. Comparison of the 1999 data to similar data collected in the 1970's indicates that concentrations for many constituents appear to have increased. Reconnaissance sampling in the fall of 2000 indicates that most ground water in the watershed was recharged recently, although some ground water was recharged more than 50 years ago. Additional reconnaissance sampling in the spring and fall of 2001 identified some compounds indicative of human wastewater in ground water and surface water. Outcrop fracture measurements were used to estimate potential porosities in three rock groups (metamorphic, intrusive, and fault zone) that have distinct fracture characteristics. The characterization, assuming a uniform aperture size of 100 microns, indicates very low potential fracture porosities, on the order of hundredths of a percent for metamorphic and intrusive rocks and up to about 2 percent for fault-zone rocks. A fourth rock group, Pikes Peak Granite, was defined on the basis of weathering characteristics. Short-term continuous and synoptic measurements of streamflow were used to describe base-flow characteristics in areas of the watershed underlain by each of the four rock groups and are the basis for characterization of base flow in a physically based, distributed-parameter watershed model. The watershed model, the Precipitation-Runoff Modeling System (PRMS), was used to characterize hydrologic conditions

KINEROS2-AGWA: Model Use, Calibration, and Validation

NASA Technical Reports Server (NTRS)

Goodrich, D C.; Burns, I. S.; Unkrich, C. L.; Semmens, D. J.; Guertin, D. P.; Hernandez, M.; Yatheendradas, S.; Kennedy, J. R.; Levick, L. R..

2013-01-01

KINEROS (KINematic runoff and EROSion) originated in the 1960s as a distributed event-based model that conceptualizes a watershed as a cascade of overland flow model elements that flow into trapezoidal channel model elements. KINEROS was one of the first widely available watershed models that interactively coupled a finite difference approximation of the kinematic overland flow equations to a physically based infiltration model. Development and improvement of KINEROS continued from the 1960s on a variety of projects for a range of purposes, which has resulted in a suite of KINEROS-based modeling tools. This article focuses on KINEROS2 (K2), a spatially distributed, event-based watershed rainfall-runoff and erosion model, and the companion ArcGIS-based Automated Geospatial Watershed Assessment (AGWA) tool. AGWA automates the time-consuming tasks of watershed delineation into distributed model elements and initial parameterization of these elements using commonly available, national GIS data layers. A variety of approaches have been used to calibrate and validate K2 successfully across a relatively broad range of applications (e.g., urbanization, pre- and post-fire, hillslope erosion, erosion from roads, runoff and recharge, and manure transport). The case studies presented in this article (1) compare lumped to stepwise calibration and validation of runoff and sediment at plot, hillslope, and small watershed scales; and (2) demonstrate an uncalibrated application to address relative change in watershed response to wildfire.

KINEROS2/AGWA: Model use, calibration and validation

USGS Publications Warehouse

Goodrich, D.C.; Burns, I.S.; Unkrich, C.L.; Semmens, Darius J.; Guertin, D.P.; Hernandez, M.; Yatheendradas, S.; Kennedy, Jeffrey R.; Levick, Lainie R.

2012-01-01

KINEROS (KINematic runoff and EROSion) originated in the 1960s as a distributed event-based model that conceptualizes a watershed as a cascade of overland flow model elements that flow into trapezoidal channel model elements. KINEROS was one of the first widely available watershed models that interactively coupled a finite difference approximation of the kinematic overland flow equations to a physically based infiltration model. Development and improvement of KINEROS continued from the 1960s on a variety of projects for a range of purposes, which has resulted in a suite of KINEROS-based modeling tools. This article focuses on KINEROS2 (K2), a spatially distributed, event-based watershed rainfall-runoff and erosion model, and the companion ArcGIS-based Automated Geospatial Watershed Assessment (AGWA) tool. AGWA automates the time-consuming tasks of watershed delineation into distributed model elements and initial parameterization of these elements using commonly available, national GIS data layers. A variety of approaches have been used to calibrate and validate K2 successfully across a relatively broad range of applications (e.g., urbanization, pre- and post-fire, hillslope erosion, erosion from roads, runoff and recharge, and manure transport). The case studies presented in this article (1) compare lumped to stepwise calibration and validation of runoff and sediment at plot, hillslope, and small watershed scales; and (2) demonstrate an uncalibrated application to address relative change in watershed response to wildfire.

Frozen soil parameterization in a distributed biosphere hydrological model

NASA Astrophysics Data System (ADS)

Wang, L.; Koike, T.; Yang, K.; Jin, R.; Li, H.

2010-03-01

In this study, a frozen soil parameterization has been modified and incorporated into a distributed biosphere hydrological model (WEB-DHM). The WEB-DHM with the frozen scheme was then rigorously evaluated in a small cold area, the Binngou watershed, against the in-situ observations from the WATER (Watershed Allied Telemetry Experimental Research). First, by using the original WEB-DHM without the frozen scheme, the land surface parameters and two van Genuchten parameters were optimized using the observed surface radiation fluxes and the soil moistures at upper layers (5, 10 and 20 cm depths) at the DY station in July. Second, by using the WEB-DHM with the frozen scheme, two frozen soil parameters were calibrated using the observed soil temperature at 5 cm depth at the DY station from 21 November 2007 to 20 April 2008; while the other soil hydraulic parameters were optimized by the calibration of the discharges at the basin outlet in July and August that covers the annual largest flood peak in 2008. With these calibrated parameters, the WEB-DHM with the frozen scheme was then used for a yearlong validation from 21 November 2007 to 20 November 2008. Results showed that the WEB-DHM with the frozen scheme has given much better performance than the WEB-DHM without the frozen scheme, in the simulations of soil moisture profile at the cold regions catchment and the discharges at the basin outlet in the yearlong simulation.

Derivation of a GIS-based watershed-scale conceptual model for the St. Jones River Delaware from habitat-scale conceptual models.

PubMed

Reiter, Michael A; Saintil, Max; Yang, Ziming; Pokrajac, Dragoljub

2009-08-01

Conceptual modeling is a useful tool for identifying pathways between drivers, stressors, Valued Ecosystem Components (VECs), and services that are central to understanding how an ecosystem operates. The St. Jones River watershed, DE is a complex ecosystem, and because management decisions must include ecological, social, political, and economic considerations, a conceptual model is a good tool for accommodating the full range of inputs. In 2002, a Four-Component, Level 1 conceptual model was formed for the key habitats of the St. Jones River watershed, but since the habitat level of resolution is too fine for some important watershed-scale issues we developed a functional watershed-scale model using the existing narrowed habitat-scale models. The narrowed habitat-scale conceptual models and associated matrices developed by Reiter et al. (2006) were combined with data from the 2002 land use/land cover (LULC) GIS-based maps of Kent County in Delaware to assemble a diagrammatic and numerical watershed-scale conceptual model incorporating the calculated weight of each habitat within the watershed. The numerical component of the assembled watershed model was subsequently subjected to the same Monte Carlo narrowing methodology used for the habitat versions to refine the diagrammatic component of the watershed-scale model. The narrowed numerical representation of the model was used to generate forecasts for changes in the parameters "Agriculture" and "Forest", showing that land use changes in these habitats propagated through the results of the model by the weighting factor. Also, the narrowed watershed-scale conceptual model identified some key parameters upon which to focus research attention and management decisions at the watershed scale. The forecast and simulation results seemed to indicate that the watershed-scale conceptual model does lead to different conclusions than the habitat-scale conceptual models for some issues at the larger watershed scale.

The study of soils and vegetation transformation due fire disturbances in remote areas through scenario modelling of observed hydrological response to fire impact

NASA Astrophysics Data System (ADS)

Nesterova, Natalia; Semenova, Olga; Lebedeva, Luidmila

2015-04-01

Large territories of Siberia and Russian Far East are the subject to frequent forest fires. Often there is no information available about fire impact except its timing, areal distribution and qualitative characteristics of fire severity. Observed changes of hydrological response in burnt watersheds can be considered as indirect evidence of soil and vegetation transformation due to fire impact. In our study we used MODIS Fire products to detect spatial distribution of fires in Transbaikal and Far East regions of Russia in 2000 - 2012 period. Small and middle-size watersheds (with area up to 10000 km2) affected by extensive (burn area not less than 20 %) fires were chosen. We analyzed available hydrological data (measured discharges in watersheds outlets) for chosen basins. In several cases apparent hydrological response to fire was detected. To investigate main factors causing the change of hydrologic regime after fire several scenarios of soil and vegetation transformation were developed for each watershed under consideration. Corresponding sets of hydrological model parameters describing those transformations were elaborated based on data analysis and post-fire landscape changes as derived from a literature review. We implied different factors such as removal of organic layer, albedo changes, intensification of soil thaw (in presence of permafrost and seasonal soil freezing), reduction of infiltration rate and evapotranspiration, increase of upper subsurface flow fraction in summer flood events following the fire and others. We applied Hydrograph model (Russia) to conduct simulation experiments aiming to reveal which landscape changes scenarios were more plausible. The advantages of chosen hydrological model for this study are 1) that it takes into consideration thermal processes in soils which in case of permafrost and seasonal soil freezing presence can play leading role in runoff formation and 2) that observable vegetation and soil properties are used as its parameters allowing minimal resort to calibration. The model can use dynamic set of parameters performing preassigned abrupt and/or gradual changes of landscape characteristics. Interestingly, based on modelling results it can be concluded that depending on dominant landscape different aspects of soil and vegetation cover changes may influence runoff formation in contrasting way. The results of the study will be reported.

Distributed snow modeling suitable for use with operational data for the American River watershed.

NASA Astrophysics Data System (ADS)

Shamir, E.; Georgakakos, K. P.

2004-12-01

The mountainous terrain of the American River watershed (~4300 km2) at the Western slope of the Northern Sierra Nevada is subject to significant variability in the atmospheric forcing that controls the snow accumulation and ablations processes (i.e., precipitation, surface temperature, and radiation). For a hydrologic model that attempts to predict both short- and long-term streamflow discharges, a plausible description of the seasonal and intermittent winter snow pack accumulation and ablation is crucial. At present the NWS-CNRFC operational snow model is implemented in a semi distributed manner (modeling unit of about 100-1000 km2) and therefore lump distinct spatial variability of snow processes. In this study we attempt to account for the precipitation, temperature, and radiation spatial variability by constructing a distributed snow accumulation and melting model suitable for use with commonly available sparse data. An adaptation of the NWS-Snow17 energy and mass balance that is used operationally at the NWS River Forecast Centers is implemented at 1 km2 grid cells with distributed input and model parameters. The input to the model (i.e., precipitation and surface temperature) is interpolated from observed point data. The surface temperature was interpolated over the basin based on adiabatic lapse rates using topographic information whereas the precipitation was interpolated based on maps of climatic mean annual rainfall distribution acquired from PRISM. The model parameters that control the melting rate due to radiation were interpolated based on aspect. The study was conducted for the entire American basin for the snow seasons of 1999-2000. Validation of the Snow Water Equivalent (SWE) prediction is done by comparing to observation from 12 snow Sensors. The Snow Cover Area (SCA) prediction was evaluated by comparing to remotely sensed 500m daily snow cover derived from MODIS. The results that the distribution of snow over the area is well captured and the quantity compared to the snow gauges are well estimated in the high elevation.

Modeling the probability distribution of peak discharge for infiltrating hillslopes

NASA Astrophysics Data System (ADS)

Baiamonte, Giorgio; Singh, Vijay P.

2017-07-01

Hillslope response plays a fundamental role in the prediction of peak discharge at the basin outlet. The peak discharge for the critical duration of rainfall and its probability distribution are needed for designing urban infrastructure facilities. This study derives the probability distribution, denoted as GABS model, by coupling three models: (1) the Green-Ampt model for computing infiltration, (2) the kinematic wave model for computing discharge hydrograph from the hillslope, and (3) the intensity-duration-frequency (IDF) model for computing design rainfall intensity. The Hortonian mechanism for runoff generation is employed for computing the surface runoff hydrograph. Since the antecedent soil moisture condition (ASMC) significantly affects the rate of infiltration, its effect on the probability distribution of peak discharge is investigated. Application to a watershed in Sicily, Italy, shows that with the increase of probability, the expected effect of ASMC to increase the maximum discharge diminishes. Only for low values of probability, the critical duration of rainfall is influenced by ASMC, whereas its effect on the peak discharge seems to be less for any probability. For a set of parameters, the derived probability distribution of peak discharge seems to be fitted by the gamma distribution well. Finally, an application to a small watershed, with the aim to test the possibility to arrange in advance the rational runoff coefficient tables to be used for the rational method, and a comparison between peak discharges obtained by the GABS model with those measured in an experimental flume for a loamy-sand soil were carried out.

Simulation of the Quantity, Variability, and Timing of Streamflow in the Dennys River Basin, Maine, by Use of a Precipitation-Runoff Watershed Model

USGS Publications Warehouse

Dudley, Robert W.

2008-01-01

The U.S. Geological Survey (USGS), in cooperation with the Maine Department of Marine Resources Bureau of Sea Run Fisheries and Habitat, began a study in 2004 to characterize the quantity, variability, and timing of streamflow in the Dennys River. The study included a synoptic summary of historical streamflow data at a long-term streamflow gage, collecting data from an additional four short-term streamflow gages, and the development and evaluation of a distributed-parameter watershed model for the Dennys River Basin. The watershed model used in this investigation was the USGS Precipitation-Runoff Modeling System (PRMS). The Geographic Information System (GIS) Weasel was used to delineate the Dennys River Basin and subbasins and derive parameters for their physical geographic features. Calibration of the models used in this investigation involved a four-step procedure in which model output was evaluated against four calibration data sets using computed objective functions for solar radiation, potential evapotranspiration, annual and seasonal water budgets, and daily streamflows. The calibration procedure involved thousands of model runs and was carried out using the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The SCE method reliably produces satisfactory solutions for large, complex optimization problems. The primary calibration effort went into the Dennys main stem watershed model. Calibrated parameter values obtained for the Dennys main stem model were transferred to the Cathance Stream model, and a similar four-step SCE calibration procedure was performed; this effort was undertaken to determine the potential to transfer modeling information to a nearby basin in the same region. The calibrated Dennys main stem watershed model performed with Nash-Sutcliffe efficiency (NSE) statistic values for the calibration period and evaluation period of 0.79 and 0.76, respectively. The Cathance Stream model had an NSE value of 0.68. The Dennys River Basin models make use of limited streamflow-gaging station data and provide information to characterize subbasin hydrology. The calibrated PRMS watershed models of the Dennys River Basin provide simulated daily streamflow time series from October 1, 1985, through September 30, 2006, for nearly any location within the basin. These models enable natural-resources managers to characterize the timing and quantity of water moving through the basin to support many endeavors including geochemical calculations, water-use assessment, Atlantic salmon population dynamics and migration modeling, habitat modeling and assessment, and other resource-management scenario evaluations. Characterizing streamflow contributions from subbasins in the basin and the relative amounts of surface- and ground-water contributions to streamflow throughout the basin will lead to a better understanding of water quantity and quality in the basin. Improved water-resources information will support Atlantic salmon protection efforts.

Distributed modeling of radiocesium washoff from the experimental watershed plots of the Fukushima fallout zone

NASA Astrophysics Data System (ADS)

Kivva, Sergei; Zheleznyak, Mark; Konoplev, Alexei; Nanba, Kenji; Onda, Yuichi; Wakiyama Yoshifumi Wakiyama, Yoshifumi

2015-04-01

The distributed hydrological "rainfall- runoff" models provide possibilities of the physically based simulation of surface and subsurface flow on watersheds based on the GIS processed data. The success of such modeling approaches for the predictions of the runoff and soil erosion provides a basis for the implementation of the distributed models of the radionuclide washoff from the watersheds. The field studies provided on the Chernobyl and Fukushima catchments provides a unique data sets for the comparative testing and improvements of the modeling tools for the watersheds located in the areas of the very different geographical and hydro-meteorological condition The set of USLE experimental plots has been established by CRIED, University of Tsukuba after the Fukushima accident to study soil erosion and 137Cs wash off from the watersheds (Onda et al, 2014). The distributed watershed models of surface and subsurface flow, sediment and radionuclide transport has been used to simulate the radionuclide transport in the basin Dnieper River, Ukraine and the watersheds of Prefecture Fuksuhima. DHSVM-R is extension of the distributed hydrological model DHSVM (Lettenmayer, Wigmosta et al, 1996-2014) by the including into it the module of the watershed radionuclide transport. DHSVM is a physically based, distributed hydrology-vegetation model for complex terrain based on the numerical solution of the network of one-dimensional equations. The surface flow submodel of DHSMV has been modified: four-directions schematization for the model's cells has been replaced by the eight-directions scheme, more numerically efficient finite -differences scheme was implemented. The new module of radionuclide wash-off from catchment and transport via stream network in soluble phase and on suspended sediments including bottom-water exchange processes was developed for DHSMV-R. DHSVM-R was implemented recently within Swedish- Ukrainian ENSURE project for the modeling of 234U wash-off from the watershed of Konoplyanka river, tributary of Dnieper Rivet at the territory of the Pridneprovsky Chemical) Plant and neighboring tailings dumps. The modeling results has been used for the assessment of the watershed's "hot spots" and analyses of the ways of the diminishing of the uranium wash off from the watersheds The testing of DHSMV-R has started in 2014 for Fukushima watershed experimental plots. The major amount of 137Cs is washed out from watershed on sediments and only small fraction in solute. The reason for such phenomenon that was not observed at Chernobyl can be - steeper slopes, more intensive rains ( daily maximum in Fukushima city at 160 mm, hourly maximum 69mm) and higher Kd values due to the volcanic kind of soils. The virtual rain of the daily amount 200 mm ( as in mountains around Fukushima city) was applied for Farmland A1- slope 7.36% and imaginary watershed (case B) the same as A1 however slope as in Chernobyl plots ( Konoplev, 1996) 4%. Due to the high nonlinearity in erosion equations for the such heavy precipitations the total amount of washed out 137Cs with sediments for the steep watershed A due to the simulated rainstorm ( 11530 Bq) is at 20 times higher, than such amount for mild slope watershed B ( 690 Bq) when the watershed A is only twice steeper than B. The modeling results demonstrate that the higher intensity of the extreme rainstorm in Fukushima area than in Chernobyl area initiated even on slightly steeper slopes the much higher amount of 137Cs washed out with sediments in Fukushima than in Chernobyl area. The successful testing of the distributed model provides the background for the simulation of the watersheds of the larger scales for small, medium and large rivers. The implementation of such models is important as for the forecasting of 137Cs wash out from the watersheds and following transport in rivers for the highest extreme floods that still did not happen in Fukushima area after the accident, as also for the long term forecasting of 137Cs in watershed-river systems at Fukushima.

User's Guide for the Agricultural Non-Point Source (AGNPS) Pollution Model Data Generator

USGS Publications Warehouse

Finn, Michael P.; Scheidt, Douglas J.; Jaromack, Gregory M.

2003-01-01

BACKGROUND Throughout this user guide, we refer to datasets that we used in conjunction with developing of this software for supporting cartographic research and producing the datasets to conduct research. However, this software can be used with these datasets or with more 'generic' versions of data of the appropriate type. For example, throughout the guide, we refer to national land cover data (NLCD) and digital elevation model (DEM) data from the U.S. Geological Survey (USGS) at a 30-m resolution, but any digital terrain model or land cover data at any appropriate resolution will produce results. Another key point to keep in mind is to use a consistent data resolution for all the datasets per model run. The U.S. Department of Agriculture (USDA) developed the Agricultural Nonpoint Source (AGNPS) pollution model of watershed hydrology in response to the complex problem of managing nonpoint sources of pollution. AGNPS simulates the behavior of runoff, sediment, and nutrient transport from watersheds that have agriculture as their prime use. The model operates on a cell basis and is a distributed parameter, event-based model. The model requires 22 input parameters. Output parameters are grouped primarily by hydrology, sediment, and chemical output (Young and others, 1995.) Elevation, land cover, and soil are the base data from which to extract the 22 input parameters required by the AGNPS. For automatic parameter extraction, follow the general process described in this guide of extraction from the geospatial data through the AGNPS Data Generator to generate input parameters required by the pollution model (Finn and others, 2002.)

An approach to measure parameter sensitivity in watershed hydrological modelling

EPA Science Inventory

Hydrologic responses vary spatially and temporally according to watershed characteristics. In this study, the hydrologic models that we developed earlier for the Little Miami River (LMR) and Las Vegas Wash (LVW) watersheds were used for detail sensitivity analyses. To compare the...

Frozen soil parameterization in a distributed biosphere hydrological model

NASA Astrophysics Data System (ADS)

Wang, L.; Koike, T.; Yang, K.; Jin, R.; Li, H.

2009-11-01

In this study, a frozen soil parameterization has been modified and incorporated into a distributed biosphere hydrological model (WEB-DHM). The WEB-DHM with the frozen scheme was then rigorously evaluated in a small cold area, the Binngou watershed, against the in-situ observations from the WATER (Watershed Allied Telemetry Experimental Research). In the summer 2008, land surface parameters were optimized using the observed surface radiation fluxes and the soil temperature profile at the Dadongshu-Yakou (DY) station in July; and then soil hydraulic parameters were obtained by the calibration of the July soil moisture profile at the DY station and by the calibration of the discharges at the basin outlet in July and August that covers the annual largest flood peak of 2008. The calibrated WEB-DHM with the frozen scheme was then used for a yearlong simulation from 21 November 2007 to 20 November 2008, to check its performance in cold seasons. Results showed that the WEB-DHM with the frozen scheme has given much better performance than the WEB-DHM without the frozen scheme, in the simulations of soil moisture profile at the DY station and the discharges at the basin outlet in the yearlong simulation.

Multi-gauge Calibration for modeling the Semi-Arid Santa Cruz Watershed in Arizona-Mexico Border Area Using SWAT

USGS Publications Warehouse

Niraula, Rewati; Norman, Laura A.; Meixner, Thomas; Callegary, James B.

2012-01-01

In most watershed-modeling studies, flow is calibrated at one monitoring site, usually at the watershed outlet. Like many arid and semi-arid watersheds, the main reach of the Santa Cruz watershed, located on the Arizona-Mexico border, is discontinuous for most of the year except during large flood events, and therefore the flow characteristics at the outlet do not represent the entire watershed. Calibration is required at multiple locations along the Santa Cruz River to improve model reliability. The objective of this study was to best portray surface water flow in this semiarid watershed and evaluate the effect of multi-gage calibration on flow predictions. In this study, the Soil and Water Assessment Tool (SWAT) was calibrated at seven monitoring stations, which improved model performance and increased the reliability of flow, in the Santa Cruz watershed. The most sensitive parameters to affect flow were found to be curve number (CN2), soil evaporation and compensation coefficient (ESCO), threshold water depth in shallow aquifer for return flow to occur (GWQMN), base flow alpha factor (Alpha_Bf), and effective hydraulic conductivity of the soil layer (Ch_K2). In comparison, when the model was established with a single calibration at the watershed outlet, flow predictions at other monitoring gages were inaccurate. This study emphasizes the importance of multi-gage calibration to develop a reliable watershed model in arid and semiarid environments. The developed model, with further calibration of water quality parameters will be an integral part of the Santa Cruz Watershed Ecosystem Portfolio Model (SCWEPM), an online decision support tool, to assess the impacts of climate change and urban growth in the Santa Cruz watershed.

Watershed scale response to climate change--Yampa River Basin, Colorado

USGS Publications Warehouse

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.

Lumped Parameter Models for Predicting Nitrogen Transport in Lower Coastal Plain Watersheds

Treesearch

Devendra M. Amatya; George M. Chescheir; Glen P. Fernandez; R. Wayne Skaggs; F. Birgand; J.W. Gilliam

2003-01-01

hl recent years physically based comprehensive disfributed watershed scale hydrologic/water quality models have been developed and applied 10 evaluate cumulative effects of land arld water management practices on receiving waters, Although fhesc complex physically based models are capable of simulating the impacts ofthese changes in large watersheds, they are often...

Benefits of incorporating spatial organisation of catchments for a semi-distributed hydrological model

NASA Astrophysics Data System (ADS)

Schumann, Andreas; Oppel, Henning

2017-04-01

To represent the hydrological behaviour of catchments a model should reproduce/reflect the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject of a certain spatial organisation. Since common models are mostly based on fundamental assumptions about hydrological processes, the reduction of variance of catchment properties as well as the incorporation of the spatial organisation of the catchment is desirable. We have developed a method that combines the idea of the width-function used for determination of the geomorphologic unit hydrograph with information about soil or topography. With this method we are able to assess the spatial organisation of selected catchment characteristics. An algorithm was developed that structures a watershed into sub-basins and other spatial units to minimise its heterogeneity. The outcomes of this algorithm are used for the spatial setup of a semi-distributed model. Since the spatial organisation of a catchment is not bound to a single characteristic, we have to embed information of multiple catchment properties. For this purpose we applied a fuzzy-based method to combine the spatial setup for multiple single characteristics into a union, optimal spatial differentiation. Utilizing this method, we are able to propose a spatial structure for a semi-distributed hydrological model, comprising the definition of sub-basins and a zonal classification within each sub-basin. Besides the improved spatial structuring, the performed analysis ameliorates modelling in another way. The spatial variability of catchment characteristics, which is considered by a minimum of heterogeneity in the zones, can be considered in a parameter constrained calibration scheme in a case study both options were used to explore the benefits of incorporating the spatial organisation and derived parameter constraints for the parametrisation of a HBV-96 model. We use two benchmark model setups (lumped and semi-distributed by common approaches) to address the benefits for different time and spatial scales. Moreover, the benefits for calibration effort, model performance in validation periods and process extrapolation are shown.

A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances

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

Siqueira, Hygor Evangelista; Pissarra, Teresa Cristina Tarlé; Farias do Valle Junior, Renato

Road spills of hazardous substances are common in developing countries due to increasing industrialization and traffic accidents, and represent a serious threat to soils and water in catchments. There is abundant literature on equations describing the wash-off of pollutants from roads during a storm event and there are a number of watershed models incorporating those equations in storm water quality algorithms that route runoff and pollution yields through a drainage system towards the catchment outlet. However, methods describing catchment vulnerability to contamination by road spills based solely on biophysical parameters are scarce. These methods could be particularly attractive to managersmore » because they can operate with a limited amount of easily collectable data, while still being able to provide important insights on the areas more prone to contamination within the studied watershed. The purpose of this paper was then to contribute with a new vulnerability model. To accomplish the goal, a selection of medium properties appearing in wash-off equations and routing algorithms were assembled and processed in a parametric framework based on multi criteria analysis to define the watershed vulnerability. However, parameters had to be adapted because wash-off equations and water quality models have been developed to operate primarily in the urban environment while the vulnerability model is meant to run in rural watersheds. The selected parameters were hillside slope, ground roughness (depending on land use), soil permeability (depending on soil type), distance to water courses and stream density. The vulnerability model is a spatially distributed algorithm that was prepared to run under the IDRISI Selva software, a GIS platform capable of handling spatial and alphanumeric data and execute the necessary terrain model, hydrographic and thematic analyses. For illustrative purposes, the vulnerability model was applied to the legally protected Environmental Protection Area (APA), located in the Uberaba region, state of Minas Gerais, Brazil. In this region, the risk of accidents causing chemical spills is preoccupying because large quantities of dangerous materials are transported in two important distribution highways while the APA is fundamental for the protection of water resources, the riverine ecosystems and remnants of native vegetation. In some tested scenarios, model results show 60% of vulnerable areas within the studied area. The most sensitive parameter to vulnerability is soil type. To prevent soils from contamination, specific measures were proposed involving minimization of land use conflicts that would presumably raise the soil's organic matter and in the sequel restore the soil's structural functions. Additionally, the present study proposed the preservation and reinforcement of riparian forests as one measure to protect the quality of surface water. - Highlights: • A multi criteria analog model was developed to assess rural catchment vulnerability along roads. • Model parameters were defined by analogy with urban wash-off equations and routing algorithms. • The model mixes up various biophysical and socio-economic parameters. • Model application was based on a scenario analysis. • The study is focused on the Environmental Protection Area of Uberaba River, Brazil.« less

Using geostatistical methods to estimate snow water equivalence distribution in a mountain watershed

USGS Publications Warehouse

Balk, B.; Elder, K.; Baron, Jill S.

1998-01-01

Knowledge of the spatial distribution of snow water equivalence (SWE) is necessary to adequately forecast the volume and timing of snowmelt runoff.  In April 1997, peak accumulation snow depth and density measurements were independently taken in the Loch Vale watershed (6.6 km2), Rocky Mountain National Park, Colorado.  Geostatistics and classical statistics were used to estimate SWE distribution across the watershed.  Snow depths were spatially distributed across the watershed through kriging interpolation methods which provide unbiased estimates that have minimum variances.  Snow densities were spatially modeled through regression analysis.  Combining the modeled depth and density with snow-covered area (SCA produced an estimate of the spatial distribution of SWE.  The kriged estimates of snow depth explained 37-68% of the observed variance in the measured depths.  Steep slopes, variably strong winds, and complex energy balance in the watershed contribute to a large degree of heterogeneity in snow depth.

Application of a DRAINMOD-based watershed model to a lower coastal plain watershed

Treesearch

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2003-01-01

This is a case study for applying DRAINMOD-GIS, a DRAINMOD based lumped parameter watershed model to Chicod Creek, a 11300 ha coastal plain watershed in North Carolina which is not intensively instrumented or documented. The study utilized the current database of land-use, topography, stream network, soil, and weather data available to the State and Federal agencies....

Predicting the Effect of Changing Precipitation Extremes and Land Cover Change on Urban Water Quality

NASA Astrophysics Data System (ADS)

SUN, N.; Yearsley, J. R.; Lettenmaier, D. P.

2013-12-01

Recent research shows that precipitation extremes in many of the largest U.S. urban areas have increased over the last 60 years. These changes have important implications for stormwater runoff and water quality, which in urban areas are dominated by the most extreme precipitation events. We assess the potential implications of changes in extreme precipitation and changing land cover in urban and urbanizing watersheds at the regional scale using a combination of hydrology and water quality models. Specifically, we describe the integration of a spatially distributed hydrological model - the Distributed Hydrology Soil Vegetation Model (DHSVM), the urban water quality model in EPA's Storm Water Management Model (SWMM), the semi-Lagrangian stream temperature model RBM10, and dynamical and statistical downscaling methods applied to global climate predictions. Key output water quality parameters include total suspended solids (TSS), toal nitrogen, total phosphorous, fecal coliform bacteria and stream temperature. We have evaluated the performance of the modeling system in the highly urbanized Mercer Creek watershed in the rapidly growing Bellevue urban area in WA, USA. The results suggest that the model is able to (1) produce reasonable streamflow predictions at fine temporal and spatial scales; (2) provide spatially distributed water temperature predictions that mostly agree with observations throughout a complex stream network, and characterize impacts of climate, landscape, near-stream vegetation change on stream temperature at local and regional scales; and (3) capture plausibly the response of water quality constituents to varying magnitude of precipitation events in urban environments. Next we will extend the scope of the study from the Mercer Creek watershed to include the entire Puget Sound Basin, WA, USA.

Inferring silicate weathering rates over recent timescales (less than 100 years) in crystalline aquifers by calibrating lumped parameters models with atmospheric tracers

NASA Astrophysics Data System (ADS)

Marçais, J.; Labasque, T.; Gauvain, A.; De Dreuzy, J. R.; Aquilina, L.; Abbott, B. W.

2016-12-01

Silicate minerals (e.g. feldspars, micas and olivines) are ubiquitous in crystalline rocks such as granite and schist. Groundwater dissolves some of this silica via weathering processes as it passes through the catchment, increasing silica concentration with residence time. However, quantifying weathering rates is complicated by the fact that groundwater residence time distributions (RTD) are typically unknown. Batch experiments can characterize weathering reaction type and provide estimates of dissolution rates, but weathering timescales in the field are far greater than what can be simulated in the laboratory (White and Brantley, 2003). Here we implement a novel approach coupling chlorofluorocarbons (CFC) and dissolved silica concentrations to infer timescales of silica weathering processes at the watershed scale. We investigated 6 crystalline aquifers in Brittany with contrasting lithology. We quantified silicate weathering at the watershed scale based on individual measurements from multiple wells, assuming first-order reaction kinetics. For each well, we used a lumped parameter model to determined RTD with inverse gaussian distributions, which allow two degrees of freedom. Production rate and initial silicate concentration were then optimized at the watershed scale with the calibrated model. Weathering rates were relatively similar among watersheds, varying for most sites from 0.16 to 0.42 mg/L/yr (SD = 0.09 mg/L/yr), and estimates of weathering rates were not significantly influenced by single well measurements. This work demonstrates how atmospheric tracers can be used with dissolved silica concentration to inform both RTD and first order kinetics of weathering reactions. Together these results suggest that dissolved silica could be a robust and cheap groundwater age proxy for recent timescales (less than 100 years). ------------------ White, Art F, and Susan L Brantley. 2003. « The effect of time on the weathering of silicate minerals: why do weathering rates differ in the laboratory and field? » Chemical Geology, Controls on Chemical Weathering, 202 (3-4): 479-506. doi:10.1016/j.chemgeo.2003.03.001.

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

NASA Astrophysics Data System (ADS)

Norton, P. A., II

2015-12-01

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

Impact of Watershed Development on Sediment Transport and Seasonal Flooding in the Main Stream of the Mekong River

NASA Astrophysics Data System (ADS)

Kameyama, S.; Nohara, S.; Sato, T.; Fujii, Y.; Kudo, K.

2009-12-01

The Mekong River watershed is undergoing rapid economic progress and population growth, raising conflicts between watershed development and environmental conservation. A typical conflict is between the benefits of dam construction versus the benefits of watershed ecological services. In developed countries, this conflict is changing to a coordinated search for outcomes that are mutually acceptable to all stakeholders. In the Mekong River, however, government policy gives priority to watershed development for ensuring steady energy supplies. Since the 1990s, a series of dams called “the Mekong Cascade” have been under construction. Dam construction has multiple economic values as electric power supply, irrigation water, flood control, etc. On the other hand, the artificial flow discharge controls of dam moderate seasonal hydrologic patterns of the Asian monsoon region. Dam operations can change the sediment transport regime and river structure. Furthermore, their impacts on watershed ecosystems and traditional economic activities of fisheries and agriculture in downstream areas may be severe. We focus on dam impacts on spatio-temporal patterns of sediment transport and seasonal flood in riparian areas downstream from Mekong River dams. Our study river section is located on 100 km down stream from the Golden Triangle region of Myanmar, Laos, and Thailand. We selected a 10-km section in this main channel to simulate seasonal flooding. We modeled the river hydrology in the years 1991 and 2002, before and after the Manwan dam construction (1986-1993). For this simulation, we adapted three models (distributed runoff model, 1-D hydrological model, and 2-D flood simulation with sediment movement algorithm.) Input data on river structure, water velocity, and flow volume were acquired from field survey data in November 2007 and 2008. In the step of parameter decision, we adopted the shuffled complex evolution method. To validate hydrologic parameters, we used annual water level data observed in Chiang Sean and Luang Prabang. To calculate sediment flux volume, we employed a Load-Quantity equation using total suspended solids data from monthly water sampling and flow discharge volumes over 13 months. To evaluate the impact of dam construction and watershed development, we inputted the same year of precipitation data using two watershed conditions with different parameters. Our results from the 1-D model displayed a seasonal delay of water flooding time after summer rainy season and an increase in sediment transport volume from September to October. In the flood simulation by the 2-D model, most of the annual sediment transport was concentrated from July to October. The spatial pattern of sediment dynamics was dependent largely on river structure including river meander shape, river bottom elevation, and geometry of the riparian zone. Our study approaches and simulation results show promise for beginning a quantitative assessment approach to cross-boundary environmental issues in the Mekong River watershed.

Mathematical modeling of synthetic unit hydrograph case study: Citarum watershed

NASA Astrophysics Data System (ADS)

Islahuddin, Muhammad; Sukrainingtyas, Adiska L. A.; Kusuma, M. Syahril B.; Soewono, Edy

2015-09-01

Deriving unit hydrograph is very important in analyzing watershed's hydrologic response of a rainfall event. In most cases, hourly measures of stream flow data needed in deriving unit hydrograph are not always available. Hence, one needs to develop methods for deriving unit hydrograph for ungagged watershed. Methods that have evolved are based on theoretical or empirical formulas relating hydrograph peak discharge and timing to watershed characteristics. These are usually referred to Synthetic Unit Hydrograph. In this paper, a gamma probability density function and its variant are used as mathematical approximations of a unit hydrograph for Citarum Watershed. The model is adjusted with real field condition by translation and scaling. Optimal parameters are determined by using Particle Swarm Optimization method with weighted objective function. With these models, a synthetic unit hydrograph can be developed and hydrologic parameters can be well predicted.

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

Treesearch

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

2012-01-01

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

Using tracer-derived groundwater transit times to assess storage within a high-elevation watershed of the upper Colorado River Basin, USA

NASA Astrophysics Data System (ADS)

Georgek, Jennifer L.; Kip Solomon, D.; Heilweil, Victor M.; Miller, Matthew P.

2018-03-01

Previous watershed assessments have relied on annual baseflow to evaluate the groundwater contribution to streams. To quantify the volume of groundwater in storage, additional information such as groundwater mean transit time (MTT) is needed. This study determined the groundwater MTT in the West Fork Duchesne watershed in Utah (USA) with lumped-parameter modeling of environmental tracers (SF6, CFCs, and 3H/3He) from 21 springs. Approximately 30% of the springs exhibited an exponential transit time distribution (TTD); the remaining 70% were best characterized by a piston-flow TTD. The flow-weighted groundwater MTT for the West Fork watershed is about 40 years with approximately 20 years in the unsaturated zone. A cumulative distribution of these ages revealed that most of the groundwater is between 30 and 50 years old, suggesting that declining recharge associated with 5-10-year droughts is less likely to have a profound effect on this watershed compared with systems with shorter MTTs. The estimated annual baseflow of West Fork stream flow based on chemical hydrograph separation is 1.7 × 107 m3/year, a proxy for groundwater discharge. Using both MTT and groundwater discharge, the volume of mobile groundwater stored in the watershed was calculated to be 6.5 × 108 m3, or 20 m thickness of active groundwater storage and recharge of 0.09 m/year (assuming porosity = 15%). Future watershed-scale assessments should evaluate groundwater MTT, in addition to annual baseflow, to quantify groundwater storage and more accurately assess watershed susceptibility to drought, groundwater extraction, and land-use change.

A spatially distributed model for the dynamic prediction of sediment erosion and transport in mountainous forested watersheds

NASA Astrophysics Data System (ADS)

Doten, Colleen O.; Bowling, Laura C.; Lanini, Jordan S.; Maurer, Edwin P.; Lettenmaier, Dennis P.

2006-04-01

Erosion and sediment transport in a temperate forested watershed are predicted with a new sediment model that represents the main sources of sediment generation in forested environments (mass wasting, hillslope erosion, and road surface erosion) within the distributed hydrology-soil-vegetation model (DHSVM) environment. The model produces slope failures on the basis of a factor-of-safety analysis with the infinite slope model through use of stochastically generated soil and vegetation parameters. Failed material is routed downslope with a rule-based scheme that determines sediment delivery to streams. Sediment from hillslopes and road surfaces is also transported to the channel network. A simple channel routing scheme is implemented to predict basin sediment yield. We demonstrate through an initial application of this model to the Rainy Creek catchment, a tributary of the Wenatchee River, which drains the east slopes of the Cascade Mountains, that the model produces plausible sediment yield and ratios of landsliding and surface erosion when compared to published rates for similar catchments in the Pacific Northwest. A road removal scenario and a basin-wide fire scenario are both evaluated with the model.

Effects of snowmelt on watershed transit time distributions

NASA Astrophysics Data System (ADS)

Fang, Z.; Carroll, R. W. H.; Harman, C. J.; Wilusz, D. C.; Schumer, R.

2017-12-01

Snowmelt is the principal control of the timing and magnitude of water flow through alpine watersheds, but the streamflow generated may be displaced groundwater. To quantify this effect, we use a rank StorAge Selection (rSAS) model to estimate time-dependent travel time distributions (TTDs) for the East River Catchment (ERC, 84 km2) - a headwater basin of the Colorado River, and newly designated as the Lawrence Berkeley National Laboratory's Watershed Function Science Focus Area (SFA). Through the SFA, observational networks related to precipitation and stream fluxes have been established with a focus on environmental tracers and stable isotopes. The United Stated Geological Survey Precipitation Runoff Modeling System (PRMS) was used to estimate spatially- and temporally-variable boundary fluxes of effective precipitation (snowmelt & rain), evapotranspiration, and subsurface storage. The DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm was used to calibrate the rSAS model to observed stream isotopic concentration data and quantify uncertainty. The sensitivity of the simulated TTDs to systematic changes in the boundary fluxes was explored. Different PRMS and rSAS model parameters setup were tested to explore how they affect the relationship between input precipitation, especially snowmelt, and the estimated TTDs. Wavelet Coherence Analysis (WCA) was applied to investigate the seasonality of TTD simulations. Our ultimate goal is insight into how the Colorado River headwater catchments store and route water, and how sensitive flow paths and transit times are to climatic changes.

Predicting active-layer soil thickness using topographic variables at a small watershed scale

PubMed Central

Li, Aidi; Tan, Xing; Wu, Wei; Liu, Hongbin; Zhu, Jie

2017-01-01

Knowledge about the spatial distribution of active-layer (AL) soil thickness is indispensable for ecological modeling, precision agriculture, and land resource management. However, it is difficult to obtain the details on AL soil thickness by using conventional soil survey method. In this research, the objective is to investigate the possibility and accuracy of mapping the spatial distribution of AL soil thickness through random forest (RF) model by using terrain variables at a small watershed scale. A total of 1113 soil samples collected from the slope fields were randomly divided into calibration (770 soil samples) and validation (343 soil samples) sets. Seven terrain variables including elevation, aspect, relative slope position, valley depth, flow path length, slope height, and topographic wetness index were derived from a digital elevation map (30 m). The RF model was compared with multiple linear regression (MLR), geographically weighted regression (GWR) and support vector machines (SVM) approaches based on the validation set. Model performance was evaluated by precision criteria of mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). Comparative results showed that RF outperformed MLR, GWR and SVM models. The RF gave better values of ME (0.39 cm), MAE (7.09 cm), and RMSE (10.85 cm) and higher R2 (62%). The sensitivity analysis demonstrated that the DEM had less uncertainty than the AL soil thickness. The outcome of the RF model indicated that elevation, flow path length and valley depth were the most important factors affecting the AL soil thickness variability across the watershed. These results demonstrated the RF model is a promising method for predicting spatial distribution of AL soil thickness using terrain parameters. PMID:28877196

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

USDA-ARS?s Scientific Manuscript database

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

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

USDA-ARS?s Scientific Manuscript database

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

Development of a multiobjective optimization tool for the selection and placement of best management practices for nonpoint source pollution control

NASA Astrophysics Data System (ADS)

Maringanti, Chetan; Chaubey, Indrajeet; Popp, Jennie

2009-06-01

Best management practices (BMPs) are effective in reducing the transport of agricultural nonpoint source pollutants to receiving water bodies. However, selection of BMPs for placement in a watershed requires optimization of the available resources to obtain maximum possible pollution reduction. In this study, an optimization methodology is developed to select and place BMPs in a watershed to provide solutions that are both economically and ecologically effective. This novel approach develops and utilizes a BMP tool, a database that stores the pollution reduction and cost information of different BMPs under consideration. The BMP tool replaces the dynamic linkage of the distributed parameter watershed model during optimization and therefore reduces the computation time considerably. Total pollutant load from the watershed, and net cost increase from the baseline, were the two objective functions minimized during the optimization process. The optimization model, consisting of a multiobjective genetic algorithm (NSGA-II) in combination with a watershed simulation tool (Soil Water and Assessment Tool (SWAT)), was developed and tested for nonpoint source pollution control in the L'Anguille River watershed located in eastern Arkansas. The optimized solutions provided a trade-off between the two objective functions for sediment, phosphorus, and nitrogen reduction. The results indicated that buffer strips were very effective in controlling the nonpoint source pollutants from leaving the croplands. The optimized BMP plans resulted in potential reductions of 33%, 32%, and 13% in sediment, phosphorus, and nitrogen loads, respectively, from the watershed.

Inverse modeling of hydrologic parameters using surface flux and runoff observations in the Community Land Model

NASA Astrophysics Data System (ADS)

Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby

2013-12-01

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.

Uncertainty based modeling of rainfall-runoff: Combined differential evolution adaptive Metropolis (DREAM) and K-means clustering

NASA Astrophysics Data System (ADS)

Zahmatkesh, Zahra; Karamouz, Mohammad; Nazif, Sara

2015-09-01

Simulation of rainfall-runoff process in urban areas is of great importance considering the consequences and damages of extreme runoff events and floods. The first issue in flood hazard analysis is rainfall simulation. Large scale climate signals have been proved to be effective in rainfall simulation and prediction. In this study, an integrated scheme is developed for rainfall-runoff modeling considering different sources of uncertainty. This scheme includes three main steps of rainfall forecasting, rainfall-runoff simulation and future runoff prediction. In the first step, data driven models are developed and used to forecast rainfall using large scale climate signals as rainfall predictors. Due to high effect of different sources of uncertainty on the output of hydrologic models, in the second step uncertainty associated with input data, model parameters and model structure is incorporated in rainfall-runoff modeling and simulation. Three rainfall-runoff simulation models are developed for consideration of model conceptual (structural) uncertainty in real time runoff forecasting. To analyze the uncertainty of the model structure, streamflows generated by alternative rainfall-runoff models are combined, through developing a weighting method based on K-means clustering. Model parameters and input uncertainty are investigated using an adaptive Markov Chain Monte Carlo method. Finally, calibrated rainfall-runoff models are driven using the forecasted rainfall to predict future runoff for the watershed. The proposed scheme is employed in the case study of the Bronx River watershed, New York City. Results of uncertainty analysis of rainfall-runoff modeling reveal that simultaneous estimation of model parameters and input uncertainty significantly changes the probability distribution of the model parameters. It is also observed that by combining the outputs of the hydrological models using the proposed clustering scheme, the accuracy of runoff simulation in the watershed is remarkably improved up to 50% in comparison to the simulations by the individual models. Results indicate that the developed methodology not only provides reliable tools for rainfall and runoff modeling, but also adequate time for incorporating required mitigation measures in dealing with potentially extreme runoff events and flood hazard. Results of this study can be used in identification of the main factors affecting flood hazard analysis.

Conditioning geostatistical simulations of a heterogeneous paleo-fluvial bedrock aquifer using lithologs and pumping tests

NASA Astrophysics Data System (ADS)

Niazi, A.; Bentley, L. R.; Hayashi, M.

2016-12-01

Geostatistical simulations are used to construct heterogeneous aquifer models. Optimally, such simulations should be conditioned with both lithologic and hydraulic data. We introduce an approach to condition lithologic geostatistical simulations of a paleo-fluvial bedrock aquifer consisting of relatively high permeable sandstone channels embedded in relatively low permeable mudstone using hydraulic data. The hydraulic data consist of two-hour single well pumping tests extracted from the public water well database for a 250-km2 watershed in Alberta, Canada. First, lithologic models of the entire watershed are simulated and conditioned with hard lithological data using transition probability - Markov chain geostatistics (TPROGS). Then, a segment of the simulation around a pumping well is used to populate a flow model (FEFLOW) with either sand or mudstone. The values of the hydraulic conductivity and specific storage of sand and mudstone are then adjusted to minimize the difference between simulated and actual pumping test data using the parameter estimation program PEST. If the simulated pumping test data do not adequately match the measured data, the lithologic model is updated by locally deforming the lithology distribution using the probability perturbation method and the model parameters are again updated with PEST. This procedure is repeated until the simulated and measured data agree within a pre-determined tolerance. The procedure is repeated for each well that has pumping test data. The method creates a local groundwater model that honors both the lithologic model and pumping test data and provides estimates of hydraulic conductivity and specific storage. Eventually, the simulations will be integrated into a watershed-scale groundwater model.

Regional groundwater characteristics and hydraulic conductivity based on geological units in Korean peninsula

NASA Astrophysics Data System (ADS)

Kim, Y.; Suk, H.

2011-12-01

In this study, about 2,000 deep observation wells, stream and/or river distribution, and river's density were analyzed to identify regional groundwater flow trend, based on the regional groundwater survey of four major river watersheds including Geum river, Han river, Youngsan-Seomjin river, and Nakdong river in Korea. Hydrogeologial data were collected to analyze regional groundwater flow characteristics according to geological units. Additionally, hydrological soil type data were collected to estimate direct runoff through SCS-CN method. Temperature and precipitation data were used to quantify infiltration rate. The temperature and precipitation data were also used to quantify evaporation by Thornthwaite method and to evaluate groundwater recharge, respectively. Understanding the regional groundwater characteristics requires the database of groundwater flow parameters, but most hydrogeological data include limited information such as groundwater level and well configuration. In this study, therefore, groundwater flow parameters such as hydraulic conductivities or transmissivities were estimated using observed groundwater level by inverse model, namely PEST (Non-linear Parameter ESTimation). Since groundwater modeling studies have some uncertainties in data collection, conceptualization, and model results, model calibration should be performed. The calibration may be manually performed by changing parameters step by step, or various parameters are simultaneously changed by automatic procedure using PEST program. In this study, both manual and automatic procedures were employed to calibrate and estimate hydraulic parameter distributions. In summary, regional groundwater survey data obtained from four major river watersheds and various data of hydrology, meteorology, geology, soil, and topography in Korea were used to estimate hydraulic conductivities using PEST program. Especially, in order to estimate hydraulic conductivity effectively, it is important to perform in such a way that areas of same or similar hydrogeological characteristics should be grouped into zones. Keywords: regional groundwater, database, hydraulic conductivity, PEST, Korean peninsular Acknowledgements: This work was supported by the Radioactive Waste Management of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Knowledge Economy (2011T100200152)

Identification of Watershed-scale Critical Source Areas Using Bayesian Maximum Entropy Spatiotemporal Analysis

NASA Astrophysics Data System (ADS)

Roostaee, M.; Deng, Z.

2017-12-01

The states' environmental agencies are required by The Clean Water Act to assess all waterbodies and evaluate potential sources of impairments. Spatial and temporal distributions of water quality parameters are critical in identifying Critical Source Areas (CSAs). However, due to limitations in monetary resources and a large number of waterbodies, available monitoring stations are typically sparse with intermittent periods of data collection. Hence, scarcity of water quality data is a major obstacle in addressing sources of pollution through management strategies. In this study spatiotemporal Bayesian Maximum Entropy method (BME) is employed to model the inherent temporal and spatial variability of measured water quality indicators such as Dissolved Oxygen (DO) concentration for Turkey Creek Watershed. Turkey Creek is located in northern Louisiana and has been listed in 303(d) list for DO impairment since 2014 in Louisiana Water Quality Inventory Reports due to agricultural practices. BME method is proved to provide more accurate estimates than the methods of purely spatial analysis by incorporating space/time distribution and uncertainty in available measured soft and hard data. This model would be used to estimate DO concentration at unmonitored locations and times and subsequently identifying CSAs. The USDA's crop-specific land cover data layers of the watershed were then used to determine those practices/changes that led to low DO concentration in identified CSAs. Primary results revealed that cultivation of corn and soybean as well as urban runoff are main contributing sources in low dissolved oxygen in Turkey Creek Watershed.

Is ET often oversimplified in hydrologic models? Using long records to elucidate unaccounted for controls on ET

NASA Astrophysics Data System (ADS)

Kelleher, Christa A.; Shaw, Stephen B.

2018-02-01

Recent research has found that hydrologic modeling over decadal time periods often requires time variant model parameters. Most prior work has focused on assessing time variance in model parameters conceptualizing watershed features and functions. In this paper, we assess whether adding a time variant scalar to potential evapotranspiration (PET) can be used in place of time variant parameters. Using the HBV hydrologic model and four different simple but common PET methods (Hamon, Priestly-Taylor, Oudin, and Hargreaves), we simulated 60+ years of daily discharge on four rivers in New York state. Allowing all ten model parameters to vary in time achieved good model fits in terms of daily NSE and long-term water balance. However, allowing single model parameters to vary in time - including a scalar on PET - achieved nearly equivalent model fits across PET methods. Overall, varying a PET scalar in time is likely more physically consistent with known biophysical controls on PET as compared to varying parameters conceptualizing innate watershed properties related to soil properties such as wilting point and field capacity. This work suggests that the seeming need for time variance in innate watershed parameters may be due to overly simple evapotranspiration formulations that do not account for all factors controlling evapotranspiration over long time periods.

ArgoEcoSystem-watershed (AgES-W) model evaluation for streamflow and nitrogen/sediment dynamics on a midwest agricultural watershed

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 under the Object Modeling System Version 3 (OMS3). The AgES-W model was previously evaluated for streamflow and recently has been enhanced with the ad...

Joint analysis of input and parametric uncertainties in watershed water quality modeling: A formal Bayesian approach

NASA Astrophysics Data System (ADS)

Han, Feng; Zheng, Yi

2018-06-01

Significant Input uncertainty is a major source of error in watershed water quality (WWQ) modeling. It remains challenging to address the input uncertainty in a rigorous Bayesian framework. This study develops the Bayesian Analysis of Input and Parametric Uncertainties (BAIPU), an approach for the joint analysis of input and parametric uncertainties through a tight coupling of Markov Chain Monte Carlo (MCMC) analysis and Bayesian Model Averaging (BMA). The formal likelihood function for this approach is derived considering a lag-1 autocorrelated, heteroscedastic, and Skew Exponential Power (SEP) distributed error model. A series of numerical experiments were performed based on a synthetic nitrate pollution case and on a real study case in the Newport Bay Watershed, California. The Soil and Water Assessment Tool (SWAT) and Differential Evolution Adaptive Metropolis (DREAM(ZS)) were used as the representative WWQ model and MCMC algorithm, respectively. The major findings include the following: (1) the BAIPU can be implemented and used to appropriately identify the uncertain parameters and characterize the predictive uncertainty; (2) the compensation effect between the input and parametric uncertainties can seriously mislead the modeling based management decisions, if the input uncertainty is not explicitly accounted for; (3) the BAIPU accounts for the interaction between the input and parametric uncertainties and therefore provides more accurate calibration and uncertainty results than a sequential analysis of the uncertainties; and (4) the BAIPU quantifies the credibility of different input assumptions on a statistical basis and can be implemented as an effective inverse modeling approach to the joint inference of parameters and inputs.

Watershed and Economic Data InterOperability (WEDO) System

EPA Science Inventory

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

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

EPA Science Inventory

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

Distributed energy-balance modeling of snow-cover evolution and melt in rugged terrain: Tobacco Root Mountains, Montana, USA

USGS Publications Warehouse

Letsinger, S.L.; Olyphant, G.A.

2007-01-01

A distributed energy-balance model was developed for simulating snowpack evolution and melt in rugged terrain. The model, which was applied to a 43-km2 watershed in the Tobacco Root Mountains, Montana, USA, used measured ambient data from nearby weather stations to drive energy-balance calculations and to constrain the model of Liston and Sturm [Liston, G.E., Sturm, M., 1998. A snow-transport model for complex terrain. Journal of Glaciology 44 (148), 498-516] for calculating the initial snowpack thickness. Simulated initial snow-water equivalent ranged between 1 cm and 385 cm w.e. (water equivalent) with high values concentrated on east-facing slopes below tall summits. An interpreted satellite image of the snowcover distribution on May 6, 1998, closely matched the simulated distribution with the greatest discrepancy occurring in the floor of the main trunk valley. Model simulations indicated that snowmelt commenced early in the melt season, but rapid meltout of snow cover did not occur until after the average energy balance of the entire watershed became positive about 45 days into the melt season. Meltout was fastest in the lower part of the watershed where warmer temperatures and tree cover enhanced the energy income of the underlying snow. An interpreted satellite image of the snowcover distribution on July 9, 1998 compared favorably with the simulated distribution, and melt curves for modeled canopy-covered cells mimicked the trends measured at nearby snow pillow stations. By the end of the simulation period (August 3), 28% of the watershed remained snow covered, most of which was concentrated in the highest parts of the watershed where initially thick accumulations had been shaded by surrounding summits. The results of this study provide further demonstration of the critical role that topography plays in the timing and magnitude of snowmelt from high mountain watersheds. ?? 2006 Elsevier B.V. All rights reserved.

Connections between residence time distributions and watershed characteristics across the continental US

NASA Astrophysics Data System (ADS)

Condon, L. E.; Maxwell, R. M.; Kollet, S. J.; Maher, K.; Haggerty, R.; Forrester, M. M.

2016-12-01

Although previous studies have demonstrated fractal residence time distributions in small watersheds, analyzing residence time scaling over large spatial areas is difficult with existing observational methods. For this study we use a fully integrated groundwater surface water simulation combined with Lagrangian particle tracking to evaluate connections between residence time distributions and watershed characteristics such as geology, topography and climate. Our simulation spans more than six million square kilometers of the continental US, encompassing a broad range of watershed sizes and physiographic settings. Simulated results demonstrate power law residence time distributions with peak age rages from 1.5 to 10.5 years. These ranges agree well with previous observational work and demonstrate the feasibility of using integrated models to simulate residence times. Comparing behavior between eight major watersheds, we show spatial variability in both the peak and the variance of the residence time distributions that can be related to model inputs. Peak age is well correlated with basin averaged hydraulic conductivity and the semi-variance corresponds to aridity. While power law age distributions have previously been attributed to fractal topography, these results illustrate the importance of subsurface characteristics and macro climate as additional controls on groundwater configuration and residence times.

RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.11)

NASA Astrophysics Data System (ADS)

Long, A. J.

2014-09-01

The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, springflow, groundwater level, solute transport, or cave drip for a measurement point in response to a system input of precipitation, recharge, or solute injection. The RRAWFLOW open-source code is written in the R language and is included in the Supplement to this article along with an example model of springflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution; i.e., the unit hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Other options include the use of user-defined IRFs and different methods to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications. RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

Numerical simulation of distributed snow processes in complex terrain utilizing triangulated irregular networks (TINs)

NASA Astrophysics Data System (ADS)

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

2005-12-01

Snow processes play a significant role in the hydrologic cycle of mountainous and high-latitude catchments in the western United States. Snowmelt runoff contributes to a large percentage of stream runoff while snow covered regions remain highly localized to small portions of the catchment area. The appropriate representation of snow dynamics at a given range of spatial and temporal scales is critical for adequately predicting runoff responses in snowmelt-dominated watersheds. In particular, the accurate depiction of snow cover patterns is important as a range of topographic, land-use and geographic parameters create zones of preferential snow accumulation or ablation that significantly affect the timing of a region's snow melt and the persistence of a snow pack. In this study, we present the development and testing of a distributed snow model designed for simulations over complex terrain. The snow model is developed within the context of the TIN-based Real-time Integrated Basin Simulator (tRIBS), a fully-distributed watershed model capable of continuous simulations of coupled hydrological processes, including unsaturated-saturated zone dynamics, land-atmosphere interactions and runoff generation via multiple mechanisms. The use of triangulated irregular networks as a domain discretization allows tRIBS to accurately represent topography with a reduced number of computational nodes, as compared to traditional grid-based models. This representation is developed using a Delauney optimization criterion that causes areas of topographic homogeneity to be represented at larger spatial scales than the original grid, while more heterogeneous areas are represented at higher resolutions. We utilize the TIN-based terrain representation to simulate microscale (10-m to 100-m) snow pack dynamics over a catchment. The model includes processes such as the snow pack energy balance, wind and bulk redistribution, and snow interception by vegetation. For this study, we present tests from a distributed one-layer energy balance model as applied to a northern New Mexico hillslope in a ponderosa pine forest using both synthetic and real meteorological forcing. We also provide tests of the model's capability to represent spatial patterns within a small watershed in the Jemez Mountain region. Finally, we discuss the interaction of the tested snow process module with existing components in the watershed model and additional applications and capabilities under development.

Expression for time travel based on diffusive wave theory: applicability and considerations

NASA Astrophysics Data System (ADS)

Aguilera, J. C.; Escauriaza, C. R.; Passalacqua, P.; Gironas, J. A.

2017-12-01

Prediction of hydrological response is of utmost importance when dealing with urban planning, risk assessment, or water resources management issues. With the advent of climate change, special care must be taken with respect to variations in rainfall and runoff due to rising temperature averages. Nowadays, while typical workstations have adequate power to run distributed routing hydrological models, it is still not enough for modeling on-the-fly, a crucial ability in a natural disaster context, where rapid decisions must be made. Semi-distributed time travel models, which compute a watershed's hydrograph without explicitly solving the full shallow water equations, appear as an attractive approach to rainfall-runoff modeling since, like fully distributed models, also superimpose a grid on the watershed, and compute runoff based on cell parameter values. These models are heavily dependent on the travel time expression for an individual cell. Many models make use of expressions based on kinematic wave theory, which is not applicable in cases where watershed storage is important, such as mild slopes. This work presents a new expression for concentration times in overland flow, based on diffusive wave theory, which considers not only the effects of storage but also the effects on upstream contribution. Setting upstream contribution equal to zero gives an expression consistent with previous work on diffusive wave theory; on the other hand, neglecting storage effects (i.e.: diffusion,) is shown to be equivalent to kinematic wave theory, currently used in many spatially distributed time travel models. The newly found expression is shown to be dependent on plane discretization, particularly when dealing with very non-kinematic cases. This is shown to be the result of upstream contribution, which gets larger downstream, versus plane length. This result also provides some light on the limits on applicability of the expression: when a certain kinematic threshold is reached, the expression is no longer valid, and one must fall back to kinematic wave theory, for lack of a better option. This expression could be used for improving currently published spatially distributed time travel models, since they would become applicable in many new cases.

Simulating soil moisture change in a semiarid rangeland watershed with a process-based water-balance model

Treesearch

Howard Evan Canfield; Vicente L. Lopes

2000-01-01

A process-based, simulation model for evaporation, soil water and streamflow (BROOK903) was used to estimate soil moisture change on a semiarid rangeland watershed in southeastern Arizona. A sensitivity analysis was performed to select parameters affecting ET and soil moisture for calibration. Automatic parameter calibration was performed using a procedure based on a...

Storm Identification and Tracking for Hydrologic Modeling Using Hourly Accumulated NEXRAD Precipitation Data

NASA Astrophysics Data System (ADS)

Olivera, F.; Choi, J.; Socolofsky, S.

2006-12-01

Watershed responses to storm events are strongly affected by the spatial and temporal patterns of rainfall; that is, the spatial distribution of the precipitation intensity and its evolution over time. Although real storms are moving entities with non-uniform intensities in both space and time, hydrological applications often synthesize these attributes by assuming storms that are uniformly distributed and have variable intensity according to a pre-defined hyetograph shape. As one considers watersheds of greater size, the non-uniformity of rainfall becomes more important, because a storm may not cover the watershed's entire area and may not stay in the watershed for its full duration. In order to incorporate parameters such as storm area, propagation velocity and direction, and intensity distribution in the definition of synthetic storms, it is necessary to determine these storm characteristics from spatially distributed precipitation data. To date, most algorithms for identifying and tracking storms have been applied to short time-step radar reflectivity data (i.e., 15 minutes or less), where storm features are captured in an effectively synoptic manner. For the entire United States, however, the most reliable distributed precipitation data are the one-hour accumulated 4 km × 4 km gridded NEXRAD data of the U.S. National Weather Service (NWS) (NWS 2005. The one-hour aggregation level of the data, though, makes it more difficult to identify and track storms than when using sequences of synoptic radar reflectivity data, because storms can traverse over a number of NEXRAD cells and change size and shape appreciably between consecutive data maps. In this paper, we present a methodology to overcome the identification and tracking difficulties and to extract the characteristics of moving storms (e.g. size, propagation velocity and direction, and intensity distribution) from one-hour accumulated distributed rainfall data. The algorithm uses Gaussian Mixture Models (GMM) for storm identification and image processing for storm tracking. The method has been successfully applied to Brazos County in Texas using the 2003 Multi-sensor Precipitation Estimator (MPE) NEXRAD rainfall data.

Quantifying groundwater’s role in delaying improvements to Chesapeake Bay water quality

USGS Publications Warehouse

Sanford, Ward E.; Pope, Jason P.

2013-01-01

A study has been undertaken to determine the time required for the effects of nitrogen-reducing best management practices (BMPs) implemented at the land surface to reach the Chesapeake Bay via groundwater transport to streams. To accomplish this, a nitrogen mass-balance regression (NMBR) model was developed and applied to seven watersheds on the Delmarva Peninsula. The model included the distribution of groundwater return times obtained from a regional groundwater-flow (GWF) model, the history of nitrogen application at the land surface over the last century, and parameters that account for denitrification. The model was (1) able to reproduce nitrate concentrations in streams and wells over time, including a recent decline in the rate at which concentrations have been increasing, and (2) used to forecast future nitrogen delivery from the Delmarva Peninsula to the Bay given different scenarios of nitrogen load reduction to the water table. The relatively deep porous aquifers of the Delmarva yield longer groundwater return times than those reported earlier for western parts of the Bay watershed. Accordingly, several decades will be required to see the full effects of current and future BMPs. The magnitude of this time lag is critical information for Chesapeake Bay watershed managers and stakeholders.

Identifying Hydrologic Processes in Agricultural Watersheds Using Precipitation-Runoff Models

USGS Publications Warehouse

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.

Comparison of Two Conceptually Different Physically-based Hydrological Models - Looking Beyond Streamflows

NASA Astrophysics Data System (ADS)

Rousseau, A. N.; Álvarez; Yu, X.; Savary, S.; Duffy, C.

2015-12-01

Most physically-based hydrological models simulate to various extents the relevant watershed processes occurring at different spatiotemporal scales. These models use different physical domain representations (e.g., hydrological response units, discretized control volumes) and numerical solution techniques (e.g., finite difference method, finite element method) as well as a variety of approximations for representing the physical processes. Despite the fact that several models have been developed so far, very few inter-comparison studies have been conducted to check beyond streamflows whether different modeling approaches could simulate in a similar fashion the other processes at the watershed scale. In this study, PIHM (Qu and Duffy, 2007), a fully coupled, distributed model, and HYDROTEL (Fortin et al., 2001; Turcotte et al., 2003, 2007), a pseudo-coupled, semi-distributed model, were compared to check whether the models could corroborate observed streamflows while equally representing other processes as well such as evapotranspiration, snow accumulation/melt or infiltration, etc. For this study, the Young Womans Creek watershed, PA, was used to compare: streamflows (channel routing), actual evapotranspiration, snow water equivalent (snow accumulation and melt), infiltration, recharge, shallow water depth above the soil surface (surface flow), lateral flow into the river (surface and subsurface flow) and height of the saturated soil column (subsurface flow). Despite a lack of observed data for contrasting most of the simulated processes, it can be said that the two models can be used as simulation tools for streamflows, actual evapotranspiration, infiltration, lateral flows into the river, and height of the saturated soil column. However, each process presents particular differences as a result of the physical parameters and the modeling approaches used by each model. Potentially, these differences should be object of further analyses to definitively confirm or reject modeling hypotheses.

Empirical models for predicting volumes of sediment deposited by debris flows and sediment-laden floods in the transverse ranges of southern California

USGS Publications Warehouse

Gartner, Joseph E.; Cannon, Susan H.; Santi, Paul M

2014-01-01

Debris flows and sediment-laden floods in the Transverse Ranges of southern California pose severe hazards to nearby communities and infrastructure. Frequent wildfires denude hillslopes and increase the likelihood of these hazardous events. Debris-retention basins protect communities and infrastructure from the impacts of debris flows and sediment-laden floods and also provide critical data for volumes of sediment deposited at watershed outlets. In this study, we supplement existing data for the volumes of sediment deposited at watershed outlets with newly acquired data to develop new empirical models for predicting volumes of sediment produced by watersheds located in the Transverse Ranges of southern California. The sediment volume data represent a broad sample of conditions found in Ventura, Los Angeles and San Bernardino Counties, California. The measured volumes of sediment, watershed morphology, distributions of burn severity within each watershed, the time since the most recent fire, triggering storm rainfall conditions, and engineering soil properties were analyzed using multiple linear regressions to develop two models. A “long-term model” was developed for predicting volumes of sediment deposited by both debris flows and floods at various times since the most recent fire from a database of volumes of sediment deposited by a combination of debris flows and sediment-laden floods with no time limit since the most recent fire (n = 344). A subset of this database was used to develop an “emergency assessment model” for predicting volumes of sediment deposited by debris flows within two years of a fire (n = 92). Prior to developing the models, 32 volumes of sediment, and related parameters for watershed morphology, burn severity and rainfall conditions were retained to independently validate the long-term model. Ten of these volumes of sediment were deposited by debris flows within two years of a fire and were used to validate the emergency assessment model. The models were validated by comparing predicted and measured volumes of sediment. These validations were also performed for previously developed models and identify that the models developed here best predict volumes of sediment for burned watersheds in comparison to previously developed models.

Environmental drivers of soil microbial community distribution at the Koiliaris Critical Zone Observatory.

PubMed

Tsiknia, Myrto; Paranychianakis, Nikolaos V; Varouchakis, Emmanouil A; Moraetis, Daniel; Nikolaidis, Nikolaos P

2014-10-01

Data on soil microbial community distribution at large scales are limited despite the important information that could be drawn with regard to their function and the influence of environmental factors on nutrient cycling and ecosystem services. This study investigates the distribution of Archaea, Bacteria and Fungi as well as the dominant bacterial phyla (Acidobacteria, Actinobacteria, Bacteroidetes, Firmicutes), and classes of Proteobacteria (Alpha- and Betaproteobacteria) across the Koiliaris watershed by qPCR and associate them with environmental variables. Predictive maps of microorganisms distribution at watershed scale were generated by co-kriging, using the most significant predictors. Our findings showed that 31-79% of the spatial variation in microbial taxa abundance could be explained by the parameters measured, with total organic carbon and pH being identified as the most important. Moreover, strong correlations were set between microbial groups and their inclusion on variance explanation improved the prediction power of the models. The spatial autocorrelation of microbial groups ranged from 309 to 2.226 m, and geographic distance, by itself, could explain a high proportion of their variation. Our findings shed light on the factors shaping microbial communities at a high taxonomic level and provide evidence for ecological coherence and syntrophic interactions at the watershed scale. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Identification of anthropogenic impact on nitrogen cycling using stable isotopes and distibuted hydrologic modeling

NASA Astrophysics Data System (ADS)

Macko, S. A.; O'Connell, M. T.; Fu, Y.

2016-12-01

The Najinhe watershed is a topographically diverse, heavily agricultural watershed in northeastern China that provides opportunities for identification of the impact of land use on nitrogen cycling. Land use, both historic and current, influences the biological processing of nitrogen in a particular area. Soil conditions, including moisture, texture, and organic content, control the capacity of a parcel for processing reactive nitrogen. Compounds derived from natural and anthropogenic sources exhibit characteristic ratios of stable isotopes of nitrogen and oxygen that serve as tracers of origin as well as integrators of biological processes. A distributed hydrologic model coupled with one focusing on reactive transport is able to help determine locations with the highest impact on the dissolved N in this system. Gaussian Markov Random Fields were used to determine the biogeochemical influence of model locations whereas δ15N measurements from NO3- and NH4+ in soil extracts were used to calibrate and validate model predictions based on measured precipitation and streamflow values. Sources were integrated using a Bayesian mixing model to determine likely fate and transport parameters for various N inputs to the watershed. The application of the coupled hydrologic and transport models to a village scale catchment suggests integration and expansion to larger watersheds on the basin scale. Identification of sensitive parcels on multiple spatial scales can direct targeted land management efforts to mitigate ecological and health effects of reactive N in surface waters.

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

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

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

1999-03-01

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

APPLICATION OF THE HSPF MODEL TO THE SOUTH FORK OF THE BROAD RIVER WATERSHED IN NORTHEASTERN GEORGIA

EPA Science Inventory

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...

Modeling precipitation-runoff relationships to determine water yield from a ponderosa pine forest watershed

Treesearch

Assefa S. Desta

2006-01-01

A stochastic precipitation-runoff modeling is used to estimate a cold and warm-seasons water yield from a ponderosa pine forested watershed in the north-central Arizona. The model consists of two parts namely, simulation of the temporal and spatial distribution of precipitation using a stochastic, event-based approach and estimation of water yield from the watershed...

Calibration and validation of the SWAT model for a forested watershed in coastal South Carolina

Treesearch

Devendra M. Amatya; Elizabeth B. Haley; Norman S. Levine; Timothy J. Callahan; Artur Radecki-Pawlik; Manoj K. Jha

2008-01-01

Modeling the hydrology of low-gradient coastal watersheds on shallow, poorly drained soils is a challenging task due to the complexities in watershed delineation, runoff generation processes and pathways, flooding, and submergence caused by tropical storms. The objective of the study is to calibrate and validate a GIS-based spatially-distributed hydrologic model, SWAT...

Predicting acidification recovery at the Hubbard Brook Experimental Forest, New Hampshire: evaluation of four models.

PubMed

Tominaga, Koji; Aherne, Julian; Watmough, Shaun A; Alveteg, Mattias; Cosby, Bernard J; Driscoll, Charles T; Posch, Maximilian; Pourmokhtarian, Afshin

2010-12-01

The performance and prediction uncertainty (owing to parameter and structural uncertainties) of four dynamic watershed acidification models (MAGIC, PnET-BGC, SAFE, and VSD) were assessed by systematically applying them to data from the Hubbard Brook Experimental Forest (HBEF), New Hampshire, where long-term records of precipitation and stream chemistry were available. In order to facilitate systematic evaluation, Monte Carlo simulation was used to randomly generate common model input data sets (n = 10,000) from parameter distributions; input data were subsequently translated among models to retain consistency. The model simulations were objectively calibrated against observed data (streamwater: 1963-2004, soil: 1983). The ensemble of calibrated models was used to assess future response of soil and stream chemistry to reduced sulfur deposition at the HBEF. Although both hindcast (1850-1962) and forecast (2005-2100) predictions were qualitatively similar across the four models, the temporal pattern of key indicators of acidification recovery (stream acid neutralizing capacity and soil base saturation) differed substantially. The range in predictions resulted from differences in model structure and their associated posterior parameter distributions. These differences can be accommodated by employing multiple models (ensemble analysis) but have implications for individual model applications.

Advances in distributed watershed modeling: a review and application of the AgroEcoSystem-Watershed (AgES-W) model

USDA-ARS?s Scientific Manuscript database

Progress in the understanding of physical, chemical, and biological processes influencing water quality, coupled with advancements in the collection and analysis of hydrologic data, provide opportunities for significant innovations in the manner and level with which watershed-scale processes may be ...

Challenges and progress in distributed watershed modeling: applications of the AgroEcoSystem-Watershed (AgES-W) model

USDA-ARS?s Scientific Manuscript database

Progress in the understanding of physical, chemical, and biological processes influencing water quality, coupled with advances in the collection and analysis of hydrologic data, provide opportunities for significant innovations in the manner and level with which watershed-scale processes may be quan...

Integrated landscape/hydrologic modeling tool for semiarid watersheds

Treesearch

Mariano Hernandez; Scott N. Miller

2000-01-01

An integrated hydrologic modeling/watershed assessment tool is being developed to aid in determining the susceptibility of semiarid landscapes to natural and human-induced changes across a range of scales. Watershed processes are by definition spatially distributed and are highly variable through time, and this approach is designed to account for their spatial and...

Mapping model behaviour using Self-Organizing Maps

NASA Astrophysics Data System (ADS)

Herbst, M.; Gupta, H. V.; Casper, M. C.

2009-03-01

Hydrological model evaluation and identification essentially involves extracting and processing information from model time series. However, the type of information extracted by statistical measures has only very limited meaning because it does not relate to the hydrological context of the data. To overcome this inadequacy we exploit the diagnostic evaluation concept of Signature Indices, in which model performance is measured using theoretically relevant characteristics of system behaviour. In our study, a Self-Organizing Map (SOM) is used to process the Signatures extracted from Monte-Carlo simulations generated by the distributed conceptual watershed model NASIM. The SOM creates a hydrologically interpretable mapping of overall model behaviour, which immediately reveals deficits and trade-offs in the ability of the model to represent the different functional behaviours of the watershed. Further, it facilitates interpretation of the hydrological functions of the model parameters and provides preliminary information regarding their sensitivities. Most notably, we use this mapping to identify the set of model realizations (among the Monte-Carlo data) that most closely approximate the observed discharge time series in terms of the hydrologically relevant characteristics, and to confine the parameter space accordingly. Our results suggest that Signature Index based SOMs could potentially serve as tools for decision makers inasmuch as model realizations with specific Signature properties can be selected according to the purpose of the model application. Moreover, given that the approach helps to represent and analyze multi-dimensional distributions, it could be used to form the basis of an optimization framework that uses SOMs to characterize the model performance response surface. As such it provides a powerful and useful way to conduct model identification and model uncertainty analyses.

Mapping model behaviour using Self-Organizing Maps

NASA Astrophysics Data System (ADS)

Herbst, M.; Gupta, H. V.; Casper, M. C.

2008-12-01

Hydrological model evaluation and identification essentially depends on the extraction of information from model time series and its processing. However, the type of information extracted by statistical measures has only very limited meaning because it does not relate to the hydrological context of the data. To overcome this inadequacy we exploit the diagnostic evaluation concept of Signature Indices, in which model performance is measured using theoretically relevant characteristics of system behaviour. In our study, a Self-Organizing Map (SOM) is used to process the Signatures extracted from Monte-Carlo simulations generated by a distributed conceptual watershed model. The SOM creates a hydrologically interpretable mapping of overall model behaviour, which immediately reveals deficits and trade-offs in the ability of the model to represent the different functional behaviours of the watershed. Further, it facilitates interpretation of the hydrological functions of the model parameters and provides preliminary information regarding their sensitivities. Most notably, we use this mapping to identify the set of model realizations (among the Monte-Carlo data) that most closely approximate the observed discharge time series in terms of the hydrologically relevant characteristics, and to confine the parameter space accordingly. Our results suggest that Signature Index based SOMs could potentially serve as tools for decision makers inasmuch as model realizations with specific Signature properties can be selected according to the purpose of the model application. Moreover, given that the approach helps to represent and analyze multi-dimensional distributions, it could be used to form the basis of an optimization framework that uses SOMs to characterize the model performance response surface. As such it provides a powerful and useful way to conduct model identification and model uncertainty analyses.

Hydrological Modeling in the Bull Run Watershed in Support of a Piloting Utility Modeling Applications (PUMA) Project

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Combining remote sensing and watershed modeling for regional-scale carbon cycling studies in disturbance-prone systems

NASA Astrophysics Data System (ADS)

Hanan, E. J.; Tague, C.; Choate, J.; Liu, M.; Adam, J. C.

2016-12-01

Disturbance is a major force regulating C dynamics in terrestrial ecosystems. Evaluating future C balance in disturbance-prone systems requires understanding the underlying mechanisms that drive ecosystem processes over multiple scales of space and time. Simulation modeling is a powerful tool for bridging these scales, however, model projections are limited by large uncertainties in the initial state of vegetation C and N stores. Watershed models typically use one of two methods to initialize these stores. Spin up involves running a model until vegetation reaches steady state based on climate. This "potential" state however assumes the vegetation across the entire watershed has reached maturity and has a homogeneous age distribution. Yet to reliably represent C and N dynamics in disturbance-prone systems, models should be initialized to reflect their non-equilibrium conditions. Alternatively, remote sensing of a single vegetation parameter (typically leaf area index; LAI) can be combined with allometric relationships to allocate C and N to model stores and can reflect non-steady-state conditions. However, allometric relationships are species and region specific and do not account for environmental variation, thus resulting in C and N stores that may be unstable. To address this problem, we developed a new approach for initializing C and N pools using the watershed-scale ecohydrologic model RHESSys. The new approach merges the mechanistic stability of spinup with the spatial fidelity of remote sensing. Unlike traditional spin up, this approach supports non-homogeneous stand ages. We tested our approach in a pine-dominated watershed in central Idaho, which partially burned in July of 2000. We used LANDSAT and MODIS data to calculate LAI across the watershed following the 2000 fire. We then ran three sets of simulations using spin up, direct measurements, and the combined approach to initialize vegetation C and N stores, and compared our results to remotely sensed LAI following the simulation period. Model estimates of C, N, and water fluxes varied depending on which approach was used. The combined approach provided the best LAI estimates after 10 years of simulation. This method shows promise for improving projections of C, N, and water fluxes in disturbance-prone watersheds.

A lagged variable model for characterizing temporally dynamic export of legacy anthropogenic nitrogen from watersheds to rivers.

PubMed

Chen, Dingjiang; Guo, Yi; Hu, Minpeng; Dahlgren, Randy A

2015-08-01

Legacy nitrogen (N) sources originating from anthropogenic N inputs (NANI) may be a major cause of increasing riverine N exports in many regions, despite a significant decline in NANI. However, little quantitative knowledge exists concerning the lag effect of NANI on riverine N export. As a result, the N leaching lag effect is not well represented in most current watershed models. This study developed a lagged variable model (LVM) to address temporally dynamic export of watershed NANI to rivers. Employing a Koyck transformation approach used in economic analyses, the LVM expresses the indefinite number of lag terms from previous years' NANI with a lag term that incorporates the previous year's riverine N flux, enabling us to inversely calibrate model parameters from measurable variables using Bayesian statistics. Applying the LVM to the upper Jiaojiang watershed in eastern China for 1980-2010 indicated that ~97% of riverine export of annual NANI occurred in the current year and succeeding 10 years (~11 years lag time) and ~72% of annual riverine N flux was derived from previous years' NANI. Existing NANI over the 1993-2010 period would have required a 22% reduction to attain the target TN level (1.0 mg N L(-1)), guiding watershed N source controls considering the lag effect. The LVM was developed with parsimony of model structure and parameters (only four parameters in this study); thus, it is easy to develop and apply in other watersheds. The LVM provides a simple and effective tool for quantifying the lag effect of anthropogenic N input on riverine export in support of efficient development and evaluation of watershed N control strategies.

Compilation of watershed models for tributaries to the Great Lakes, United States, as of 2010, and identification of watersheds for future modeling for the Great Lakes Restoration Initiative

USGS Publications Warehouse

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

2011-01-01

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

Evaluating Uncertainty of Runoff Simulation using SWAT model of the Feilaixia Watershed in China Based on the GLUE Method

NASA Astrophysics Data System (ADS)

Chen, X.; Huang, G.

2017-12-01

In recent years, distributed hydrological models have been widely used in storm water management, water resources protection and so on. Therefore, how to evaluate the uncertainty of the model reasonably and efficiently becomes a hot topic today. In this paper, the soil and water assessment tool (SWAT) model is constructed for the study area of China's Feilaixia watershed, and the uncertainty of the runoff simulation is analyzed by GLUE method deeply. Taking the initial parameter range of GLUE method as the research core, the influence of different initial parameter ranges on model uncertainty is studied. In this paper, two sets of parameter ranges are chosen as the object of study, the first one (range 1) is recommended by SWAT-CUP and the second one (range 2) is calibrated by SUFI-2. The results showed that under the same number of simulations (10,000 times), the overall uncertainty obtained by the range 2 is less than the range 1. Specifically, the "behavioral" parameter sets for the range 2 is 10000 and for the range 1 is 4448. In the calibration and the validation, the ratio of P-factor to R-factor for range 1 is 1.387 and 1.391, and for range 2 is 1.405 and 1.462 respectively. In addition, the simulation result of range 2 is better with the NS and R2 slightly higher than range 1. Therefore, it can be concluded that using the parameter range calibrated by SUFI-2 as the initial parameter range for the GLUE is a way to effectively capture and evaluate the simulation uncertainty.

Channel morphology investigations using Geographic Information Systems and field research

Treesearch

Scott N. Miller; Ann Youberg; D. Phillip Guertin; David C. Goodrich

2000-01-01

Stream channels are integral to watershed function and are affected by watershed management decisions. Given an understanding of the relationships among channel and watershed variables, they may serve as indicators of upland condition or used in distributed rainfall-runoff models. This paper presents a quantitative analysis of fluvial morphology as related to watershed...

Dealing with equality and benefit for water allocation in a lake watershed: A Gini-coefficient based stochastic optimization approach

NASA Astrophysics Data System (ADS)

Dai, C.; Qin, X. S.; Chen, Y.; Guo, H. C.

2018-06-01

A Gini-coefficient based stochastic optimization (GBSO) model was developed by integrating the hydrological model, water balance model, Gini coefficient and chance-constrained programming (CCP) into a general multi-objective optimization modeling framework for supporting water resources allocation at a watershed scale. The framework was advantageous in reflecting the conflicting equity and benefit objectives for water allocation, maintaining the water balance of watershed, and dealing with system uncertainties. GBSO was solved by the non-dominated sorting Genetic Algorithms-II (NSGA-II), after the parameter uncertainties of the hydrological model have been quantified into the probability distribution of runoff as the inputs of CCP model, and the chance constraints were converted to the corresponding deterministic versions. The proposed model was applied to identify the Pareto optimal water allocation schemes in the Lake Dianchi watershed, China. The optimal Pareto-front results reflected the tradeoff between system benefit (αSB) and Gini coefficient (αG) under different significance levels (i.e. q) and different drought scenarios, which reveals the conflicting nature of equity and efficiency in water allocation problems. A lower q generally implies a lower risk of violating the system constraints and a worse drought intensity scenario corresponds to less available water resources, both of which would lead to a decreased system benefit and a less equitable water allocation scheme. Thus, the proposed modeling framework could help obtain the Pareto optimal schemes under complexity and ensure that the proposed water allocation solutions are effective for coping with drought conditions, with a proper tradeoff between system benefit and water allocation equity.

Estimating Age Distributions of Base Flow in Watersheds Underlain by Single and Dual Porosity Formations Using Groundwater Transport Simulation and Weighted Weibull Functions

NASA Astrophysics Data System (ADS)

Sanford, W. E.

2015-12-01

Age distributions of base flow to streams are important to estimate for predicting the timing of water-quality responses to changes in distributed inputs of nutrients or pollutants at the land surface. Simple models of shallow aquifers will predict exponential age distributions, but more realistic 3-D stream-aquifer geometries will cause deviations from an exponential curve. In addition, in fractured rock terrains the dual nature of the effective and total porosity of the system complicates the age distribution further. In this study shallow groundwater flow and advective transport were simulated in two regions in the Eastern United States—the Delmarva Peninsula and the upper Potomac River basin. The former is underlain by layers of unconsolidated sediment, while the latter consists of folded and fractured sedimentary rocks. Transport of groundwater to streams was simulated using the USGS code MODPATH within 175 and 275 watersheds, respectively. For the fractured rock terrain, calculations were also performed along flow pathlines to account for exchange between mobile and immobile flow zones. Porosities at both sites were calibrated using environmental tracer data (3H, 3He, CFCs and SF6) in wells and springs, and with a 30-year tritium record from the Potomac River. Carbonate and siliciclastic rocks were calibrated to have mobile porosity values of one and six percent, and immobile porosity values of 18 and 12 percent, respectively. The age distributions were fitted to Weibull functions. Whereas an exponential function has one parameter that controls the median age of the distribution, a Weibull function has an extra parameter that controls the slope of the curve. A weighted Weibull function was also developed that potentially allows for four parameters, two that control the median age and two that control the slope, one of each weighted toward early or late arrival times. For both systems the two-parameter Weibull function nearly always produced a substantially better fit to the data than the one-parameter exponential function. For the single porosity system it was found that the use of three parameters was often optimal for accurately describing the base-flow age distribution, whereas for the dual porosity system the fourth parameter was often required to fit the more complicated response curves.

[Quantitative estimation of evapotranspiration from Tahe forest ecosystem, Northeast China].

PubMed

Qu, Di; Fan, Wen-Yi; Yang, Jin-Ming; Wang, Xu-Peng

2014-06-01

Evapotranspiration (ET) is an important parameter of agriculture, meteorology and hydrology research, and also an important part of the global hydrological cycle. This paper applied the improved DHSVM distributed hydrological model to estimate daily ET of Tahe area in 2007 using leaf area index and other surface data extracted TM remote sensing data, and slope, aspect and other topographic indices obtained by using the digital elevation model. The relationship between daily ET and daily watershed outlet flow was built by the BP neural network, and a water balance equation was established for the studied watershed, together to test the accuracy of the estimation. The results showed that the model could be applied in the study area. The annual total ET of Tahe watershed was 234.01 mm. ET had a significant seasonal variation. The ET had the highest value in summer and the average daily ET value was 1.56 mm. The average daily ET in autumn and spring were 0.30, 0.29 mm, respectively, and winter had the lowest ET value. Land cover type had a great effect on ET value, and the broadleaf forest had a higher ET ability than the mixed forest, followed by the needle leaf forest.

Towards Improved High-Resolution Land Surface Hydrologic Reanalysis Using a Physically-Based Hydrologic Model and Data Assimilation

NASA Astrophysics Data System (ADS)

Shi, Y.; Davis, K. J.; Zhang, F.; Duffy, C.; Yu, X.

2014-12-01

A coupled physically based land surface hydrologic model, Flux-PIHM, has been developed by incorporating a land surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM has been implemented and manually calibrated at the Shale Hills watershed (0.08 km2) in central Pennsylvania. Model predictions of discharge, point soil moisture, point water table depth, sensible and latent heat fluxes, and soil temperature show good agreement with observations. When calibrated only using discharge, and soil moisture and water table depth at one point, Flux-PIHM is able to resolve the observed 101 m scale soil moisture pattern at the Shale Hills watershed when an appropriate map of soil hydraulic properties is provided. A Flux-PIHM data assimilation system has been developed by incorporating EnKF for model parameter and state estimation. Both synthetic and real data assimilation experiments have been performed at the Shale Hills watershed. Synthetic experiment results show that the data assimilation system is able to simultaneously provide accurate estimates of multiple parameters. In the real data experiment, the EnKF estimated parameters and manually calibrated parameters yield similar model performances, but the EnKF method significantly decreases the time and labor required for calibration. The data requirements for accurate Flux-PIHM parameter estimation via data assimilation using synthetic observations have been tested. Results show that by assimilating only in situ outlet discharge, soil water content at one point, and the land surface temperature averaged over the whole watershed, the data assimilation system can provide an accurate representation of watershed hydrology. Observations of these key variables are available with national and even global spatial coverage (e.g., MODIS surface temperature, SMAP soil moisture, and the USGS gauging stations). National atmospheric reanalysis products, soil databases and land cover databases (e.g., NLDAS-2, SSURGO, NLCD) can provide high resolution forcing and input data. Therefore the Flux-PIHM data assimilation system could be readily expanded to other watersheds to provide regional scale land surface and hydrologic reanalysis with high spatial temporal resolution.

Sacaton riparian grasslands of the Sky Islands: Mapping distribution and ecological condition using state-and-transition models in Upper Cienega Creek Watershed

Treesearch

Ron Tiller; Melissa Hughes; Gita Bodner

2013-01-01

Riparian grasslands dominated by Sporobolus wrightii (big sacaton) were once widely distributed in the intermountain basins of the Madrean Archipelago. These alluvial grasslands are still recognized as key resources for watershed function, livestock, and wildlife. The upper Cienega Creek watershed in SE Arizona is thought to harbor some of the region’s most extensive...

Fena Valley Reservoir watershed and water-balance model updates and expansion of watershed modeling to southern Guam

USGS Publications Warehouse

Rosa, Sarah N.; Hay, Lauren E.

2017-12-01

In 2014, the U.S. Geological Survey, in cooperation with the U.S. Department of Defense’s Strategic Environmental Research and Development Program, initiated a project to evaluate the potential impacts of projected climate-change on Department of Defense installations that rely on Guam’s water resources. A major task of that project was to develop a watershed model of southern Guam and a water-balance model for the Fena Valley Reservoir. The southern Guam watershed model provides a physically based tool to estimate surface-water availability in southern Guam. The U.S. Geological Survey’s Precipitation Runoff Modeling System, PRMS-IV, was used to construct the watershed model. The PRMS-IV code simulates different parts of the hydrologic cycle based on a set of user-defined modules. The southern Guam watershed model was constructed by updating a watershed model for the Fena Valley watersheds, and expanding the modeled area to include all of southern Guam. The Fena Valley watershed model was combined with a previously developed, but recently updated and recalibrated Fena Valley Reservoir water-balance model.Two important surface-water resources for the U.S. Navy and the citizens of Guam were modeled in this study; the extended model now includes the Ugum River watershed and improves upon the previous model of the Fena Valley watersheds. Surface water from the Ugum River watershed is diverted and treated for drinking water, and the Fena Valley watersheds feed the largest surface-water reservoir on Guam. The southern Guam watershed model performed “very good,” according to the criteria of Moriasi and others (2007), in the Ugum River watershed above Talofofo Falls with monthly Nash-Sutcliffe efficiency statistic values of 0.97 for the calibration period and 0.93 for the verification period (a value of 1.0 represents perfect model fit). In the Fena Valley watershed, monthly simulated streamflow volumes from the watershed model compared reasonably well with the measured values for the gaging stations on the Almagosa, Maulap, and Imong Rivers—tributaries to the Fena Valley Reservoir—with Nash-Sutcliffe efficiency values of 0.87 or higher. The southern Guam watershed model simulated the total volume of the critical dry season (January to May) streamflow for the entire simulation period within –0.54 percent at the Almagosa River, within 6.39 percent at the Maulap River, and within 6.06 percent at the Imong River.The recalibrated water-balance model of the Fena Valley Reservoir generally simulated monthly reservoir storage volume with reasonable accuracy. For the calibration and verification periods, errors in end-of-month reservoir-storage volume ranged from 6.04 percent (284.6 acre-feet or 92.7 million gallons) to –5.70 percent (–240.8 acre-feet or –78.5 million gallons). Monthly simulation bias ranged from –0.48 percent for the calibration period to 0.87 percent for the verification period; relative error ranged from –0.60 to 0.88 percent for the calibration and verification periods, respectively. The small bias indicated that the model did not consistently overestimate or underestimate reservoir storage volume.In the entirety of southern Guam, the watershed model has a “satisfactory” to “very good” rating when simulating monthly mean streamflow for all but one of the gaged watersheds during the verification period. The southern Guam watershed model uses a more sophisticated climate-distribution scheme than the older model to make use of the sparse climate data, as well as includes updated land-cover parameters and the capability to simulate closed depression areas.The new Fena Valley Reservoir water-balance model is useful as an updated tool to forecast short-term changes in the surface-water resources of Guam. Furthermore, the now spatially complete southern Guam watershed model can be used to evaluate changes in streamflow and recharge owing to climate or land-cover changes. These are substantial improvements to the previous models of the Fena Valley watershed and Reservoir. Datasets associated with this report are available as a U.S. Geological Survey data release (Rosa and Hay, 2017; DOI:10.5066/F7HH6HV4).

Improvement and comparison of likelihood functions for model calibration and parameter uncertainty analysis within a Markov chain Monte Carlo scheme

NASA Astrophysics Data System (ADS)

Cheng, Qin-Bo; Chen, Xi; Xu, Chong-Yu; Reinhardt-Imjela, Christian; Schulte, Achim

2014-11-01

In this study, the likelihood functions for uncertainty analysis of hydrological models are compared and improved through the following steps: (1) the equivalent relationship between the Nash-Sutcliffe Efficiency coefficient (NSE) and the likelihood function with Gaussian independent and identically distributed residuals is proved; (2) a new estimation method of the Box-Cox transformation (BC) parameter is developed to improve the effective elimination of the heteroscedasticity of model residuals; and (3) three likelihood functions-NSE, Generalized Error Distribution with BC (BC-GED) and Skew Generalized Error Distribution with BC (BC-SGED)-are applied for SWAT-WB-VSA (Soil and Water Assessment Tool - Water Balance - Variable Source Area) model calibration in the Baocun watershed, Eastern China. Performances of calibrated models are compared using the observed river discharges and groundwater levels. The result shows that the minimum variance constraint can effectively estimate the BC parameter. The form of the likelihood function significantly impacts on the calibrated parameters and the simulated results of high and low flow components. SWAT-WB-VSA with the NSE approach simulates flood well, but baseflow badly owing to the assumption of Gaussian error distribution, where the probability of the large error is low, but the small error around zero approximates equiprobability. By contrast, SWAT-WB-VSA with the BC-GED or BC-SGED approach mimics baseflow well, which is proved in the groundwater level simulation. The assumption of skewness of the error distribution may be unnecessary, because all the results of the BC-SGED approach are nearly the same as those of the BC-GED approach.

Using Bayesian hierarchical models to better understand nitrate sources and sinks in agricultural watersheds.

PubMed

Xia, Yongqiu; Weller, Donald E; Williams, Meghan N; Jordan, Thomas E; Yan, Xiaoyuan

2016-11-15

Export coefficient models (ECMs) are often used to predict nutrient sources and sinks in watersheds because ECMs can flexibly incorporate processes and have minimal data requirements. However, ECMs do not quantify uncertainties in model structure, parameters, or predictions; nor do they account for spatial and temporal variability in land characteristics, weather, and management practices. We applied Bayesian hierarchical methods to address these problems in ECMs used to predict nitrate concentration in streams. We compared four model formulations, a basic ECM and three models with additional terms to represent competing hypotheses about the sources of error in ECMs and about spatial and temporal variability of coefficients: an ADditive Error Model (ADEM), a SpatioTemporal Parameter Model (STPM), and a Dynamic Parameter Model (DPM). The DPM incorporates a first-order random walk to represent spatial correlation among parameters and a dynamic linear model to accommodate temporal correlation. We tested the modeling approach in a proof of concept using watershed characteristics and nitrate export measurements from watersheds in the Coastal Plain physiographic province of the Chesapeake Bay drainage. Among the four models, the DPM was the best--it had the lowest mean error, explained the most variability (R 2  = 0.99), had the narrowest prediction intervals, and provided the most effective tradeoff between fit complexity (its deviance information criterion, DIC, was 45.6 units lower than any other model, indicating overwhelming support for the DPM). The superiority of the DPM supports its underlying hypothesis that the main source of error in ECMs is their failure to account for parameter variability rather than structural error. Analysis of the fitted DPM coefficients for cropland export and instream retention revealed some of the factors controlling nitrate concentration: cropland nitrate exports were positively related to stream flow and watershed average slope, while instream nitrate retention was positively correlated with nitrate concentration. By quantifying spatial and temporal variability in sources and sinks, the DPM provides new information to better target management actions to the most effective times and places. Given the wide use of ECMs as research and management tools, our approach can be broadly applied in other watersheds and to other materials. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Impacts of climate change on current methodologies for flood risk analysis: Watershed-scale analyses using the Soil and Water Assessment Tool (SWAT)

NASA Astrophysics Data System (ADS)

Spellman, P.; Griffis, V. W.; LaFond, K.

2013-12-01

A changing climate brings about new challenges for flood risk analysis and water resources planning and management. Current methods for estimating flood risk in the US involve fitting the Pearson Type III (P3) probability distribution to the logarithms of the annual maximum flood (AMF) series using the method of moments. These methods are employed under the premise of stationarity, which assumes that the fitted distribution is time invariant and variables affecting stream flow such as climate do not fluctuate. However, climate change would bring about shifts in meteorological forcings which can alter the summary statistics (mean, variance, skew) of flood series used for P3 parameter estimation, resulting in erroneous flood risk projections. To ascertain the degree to which future risk may be misrepresented by current techniques, we use climate scenarios generated from global climate models (GCMs) as input to a hydrological model to explore how relative changes to current climate affect flood response for watersheds in the northeastern United States. The watersheds were calibrated and run on a daily time step using the continuous, semi-distributed, process based Soil and Water Assessment Tool (SWAT). Nash Sutcliffe Efficiency (NSE), RMSE to Standard Deviation ratio (RSR) and Percent Bias (PBIAS) were all used to assess model performance. Eight climate scenarios were chosen from GCM output based on relative precipitation and temperature changes from the current climate of the watershed and then further bias-corrected. Four of the scenarios were selected to represent warm-wet, warm-dry, cool-wet and cool-dry future climates, and the other four were chosen to represent more extreme, albeit possible, changes in precipitation and temperature. We quantify changes in response by comparing the differences in total mass balance and summary statistics of the logarithms of the AMF series from historical baseline values. We then compare forecasts of flood quantiles from fitting a P3 distribution to the logs of historical AMF data to that of generated AMF series.

Multiobjective Sensitivity Analysis Of Sediment And Nitrogen Processes With A Watershed Model

EPA Science Inventory

This paper presents a computational analysis for evaluating critical non-point-source sediment and nutrient (specifically nitrogen) processes and management actions at the watershed scale. In the analysis, model parameters that bear key uncertainties were presumed to reflect the ...

[Coupling SWAT and CE-QUAL-W2 models to simulate water quantity and quality in Shanmei Reservoir watershed].

PubMed

Liu, Mei-Bing; Chen, Dong-Ping; Chen, Xing-Wei; Chen, Ying

2013-12-01

A coupled watershed-reservoir modeling approach consisting of a watershed distributed model (SWAT) and a two-dimensional laterally averaged model (CE-QUAL-W2) was adopted for simulating the impact of non-point source pollution from upland watershed on water quality of Shanmei Reservoir. Using the daily serial output from Shanmei Reservoir watershed by SWAT as the input to Shanmei Reservoir by CE-QUAL-W2, the coupled modeling was calibrated for runoff and outputs of sediment and pollutant at watershed scale and for elevation, temperature, nitrate, ammonium and total nitrogen in Shanmei Reservoir. The results indicated that the simulated values agreed fairly well with the observed data, although the calculation precision of downstream model would be affected by the accumulative errors generated from the simulation of upland model. The SWAT and CE-QUAL-W2 coupled modeling could be used to assess the hydrodynamic and water quality process in complex watershed comprised of upland watershed and downstream reservoir, and might further provide scientific basis for positioning key pollution source area and controlling the reservoir eutrophication.

Bacteria transport simulation using apex model in the toenepi watershed, New Zealand

USDA-ARS?s Scientific Manuscript database

The Agricultural Policy/Environmental eXtender (APEX) model is a distributed, continuous, daily-timestep small watershed-scale hydrologic and water quality model. In this study, the newly developed fecal-derived bacteria fate and transport subroutine was applied and validated using APEX model. The ...

Remote sensing requirements as suggested by watershed model sensitivity analyses

NASA Technical Reports Server (NTRS)

Salomonson, V. V.; Rango, A.; Ormsby, J. P.; Ambaruch, R.

1975-01-01

A continuous simulation watershed model has been used to perform sensitivity analyses that provide guidance in defining remote sensing requirements for the monitoring of watershed features and processes. The results show that out of 26 input parameters having meaningful effects on simulated runoff, 6 appear to be obtainable with existing remote sensing techniques. Of these six parameters, 3 require the measurement of the areal extent of surface features (impervious areas, water bodies, and the extent of forested area), two require the descrimination of land use that can be related to overland flow roughness coefficient or the density of vegetation so as to estimate the magnitude of precipitation interception, and one parameter requires the measurement of distance to get the length over which overland flow typically occurs. Observational goals are also suggested for monitoring such fundamental watershed processes as precipitation, soil moisture, and evapotranspiration. A case study on the Patuxent River in Maryland shows that runoff simulation is improved if recent satellite land use observations are used as model inputs as opposed to less timely topographic map information.

Delineation and Analysis of Uncertainty of Contributing Areas to Wells at the Southbury Training School, Southbury, Connecticut

USGS Publications Warehouse

Starn, J. Jeffrey; Stone, Janet Radway; Mullaney, John R.

2000-01-01

Contributing areas to public-supply wells at the Southbury Training School in Southbury, Connecticut, were mapped by simulating ground-water flow in stratified glacial deposits in the lower Transylvania Brook watershed. The simulation used nonlinear regression methods and informational statistics to estimate parameters of a ground-water flow model using drawdown data from an aquifer test. The goodness of fit of the model and the uncertainty associated with model predictions were statistically measured. A watershed-scale model, depicting large-scale ground-water flow in the Transylvania Brook watershed, was used to estimate the distribution of groundwater recharge. Estimates of recharge from 10 small basins in the watershed differed on the basis of the drainage characteristics of each basin. Small basins having well-defined stream channels contributed less ground-water recharge than basins having no defined channels because potential ground-water recharge was carried away in the stream channel. Estimates of ground-water recharge were used in an aquifer-scale parameter-estimation model. Seven variations of the ground-water-flow system were posed, each representing the ground-water-flow system in slightly different but realistic ways. The model that most closely reproduced measured hydraulic heads and flows with realistic parameter values was selected as the most representative of the ground-water-flow system and was used to delineate boundaries of the contributing areas. The model fit revealed no systematic model error, which indicates that the model is likely to represent the major characteristics of the actual system. Parameter values estimated during the simulation are as follows: horizontal hydraulic conductivity of coarse-grained deposits, 154 feet per day; vertical hydraulic conductivity of coarse-grained deposits, 0.83 feet per day; horizontal hydraulic conductivity of fine-grained deposits, 29 feet per day; specific yield, 0.007; specific storage, 1.6E-05. Average annual recharge was estimated using the watershed-scale model with no parameter estimation and was determined to be 24 inches per year in the valley areas and 9 inches per year in the upland areas. The parameter estimates produced in the model are similar to expected values, with two exceptions. The estimated specific yield of the stratified glacial deposits is lower than expected, which could be caused by the layered nature of the deposits. The recharge estimate produced by the model was also lower?about 32 percent of the average annual rate. This could be caused by the timing of the aquifer test with respect to the annual cycle of ground-water recharge, and by some of the expected recharge going to parts of the flow system that were not simulated. The data used in the calibration were collected during an aquifer test from October 30 to November 4, 1996. The model fit was very good, as indicated by the correlation coefficient (0.999) between the weighted simulated values and weighted observed values. The model also reproduced the general rise in ground-water levels caused by ground-water recharge and the cyclic fluctuations caused by pumping prior to the aquifer test. Contributing areas were delineated using a particle-tracking procedure. Hypothetical particles of water were introduced at each model cell in the top layer and were tracked to determine whether or not they reached the pumped well. A deterministic contributing area was calculated using the calibrated model, and a probabilistic contributing area was calculated using a Monte Carlo approach along with the calibrated model. The Monte Carlo simulation was done, using the parameter variance/covariance matrix generated by the regression model, to estimate probabilities associated with the contributing area to the wells. The probabilities arise from uncertainty in the estimated parameter values, which in turn arise from the adequacy of the data available to comprehensively describe the groundwater-flow sy

Using a topographic index to distribute variable source area runoff predicted with the SCS curve-number equation

NASA Astrophysics Data System (ADS)

Lyon, Steve W.; Walter, M. Todd; Gérard-Marchant, Pierre; Steenhuis, Tammo S.

2004-10-01

Because the traditional Soil Conservation Service curve-number (SCS-CN) approach continues to be used ubiquitously in water quality models, new application methods are needed that are consistent with variable source area (VSA) hydrological processes in the landscape. We developed and tested a distributed approach for applying the traditional SCS-CN equation to watersheds where VSA hydrology is a dominant process. Predicting the location of source areas is important for watershed planning because restricting potentially polluting activities from runoff source areas is fundamental to controlling non-point-source pollution. The method presented here used the traditional SCS-CN approach to predict runoff volume and spatial extent of saturated areas and a topographic index, like that used in TOPMODEL, to distribute runoff source areas through watersheds. The resulting distributed CN-VSA method was applied to two subwatersheds of the Delaware basin in the Catskill Mountains region of New York State and one watershed in south-eastern Australia to produce runoff-probability maps. Observed saturated area locations in the watersheds agreed with the distributed CN-VSA method. Results showed good agreement with those obtained from the previously validated soil moisture routing (SMR) model. When compared with the traditional SCS-CN method, the distributed CN-VSA method predicted a similar total volume of runoff, but vastly different locations of runoff generation. Thus, the distributed CN-VSA approach provides a physically based method that is simple enough to be incorporated into water quality models, and other tools that currently use the traditional SCS-CN method, while still adhering to the principles of VSA hydrology.

Use of Satellite-based Remote Sensing to inform Evapotranspiration parameters in Cropping System Models

NASA Astrophysics Data System (ADS)

Dhungel, S.; Barber, M. E.

2016-12-01

The objectives of this paper are to use an automated satellite-based remote sensing evapotranspiration (ET) model to assist in parameterization of a cropping system model (CropSyst) and to examine the variability of consumptive water use of various crops across the watershed. The remote sensing model is a modified version of the Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC™) energy balance model. We present the application of an automated python-based implementation of METRIC to estimate ET as consumptive water use for agricultural areas in three watersheds in Eastern Washington - Walla Walla, Lower Yakima and Okanogan. We used these ET maps with USDA crop data to identify the variability of crop growth and water use for the major crops in these three watersheds. Some crops, such as grapes and alfalfa, showed high variability in water use in the watershed while others, such as corn, had comparatively less variability. The results helped us to estimate the range and variability of various crop parameters that are used in CropSyst. The paper also presents a systematic approach to estimate parameters of CropSyst for a crop in a watershed using METRIC results. Our initial application of this approach was used to estimate irrigation application rate for CropSyst for a selected farm in Walla Walla and was validated by comparing crop growth (as Leaf Area Index - LAI) and consumptive water use (ET) from METRIC and CropSyst. This coupling of METRIC with CropSyst will allow for more robust parameters in CropSyst and will enable accurate predictions of changes in irrigation practices and crop rotation, which are a challenge in many cropping system models.

Comparison of contact conditions obtained by direct simulation with statistical analysis for normally distributed isotropic surfaces

NASA Astrophysics Data System (ADS)

Uchidate, M.

2018-09-01

In this study, with the aim of establishing a systematic knowledge on the impact of summit extraction methods and stochastic model selection in rough contact analysis, the contact area ratio (A r /A a ) obtained by statistical contact models with different summit extraction methods was compared with a direct simulation using the boundary element method (BEM). Fifty areal topography datasets with different autocorrelation functions in terms of the power index and correlation length were used for investigation. The non-causal 2D auto-regressive model which can generate datasets with specified parameters was employed in this research. Three summit extraction methods, Nayak’s theory, 8-point analysis and watershed segmentation, were examined. With regard to the stochastic model, Bhushan’s model and BGT (Bush-Gibson-Thomas) model were applied. The values of A r /A a from the stochastic models tended to be smaller than BEM. The discrepancy between the Bhushan’s model with the 8-point analysis and BEM was slightly smaller than Nayak’s theory. The results with the watershed segmentation was similar to those with the 8-point analysis. The impact of the Wolf pruning on the discrepancy between the stochastic analysis and BEM was not very clear. In case of the BGT model which employs surface gradients, good quantitative agreement against BEM was obtained when the Nayak’s bandwidth parameter was large.

RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15)

USGS Publications Warehouse

Long, Andrew J.

2015-01-01

The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, spring flow, groundwater level, or solute transport for a measurement point in response to a system input of precipitation, recharge, or solute injection. I introduce the first version of RRAWFLOW available for download and public use and describe additional options. The open-source code is written in the R language and is available at http://sd.water.usgs.gov/projects/RRAWFLOW/RRAWFLOW.html along with an example model of streamflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution, i.e., the unit-hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Several options are included to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications (e.g., estimating missing periods in a hydrologic record). RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

Urban stream syndrome in a small, lightly developed watershed: a statistical analysis of water chemistry parameters, land use patterns, and natural sources.

PubMed

Halstead, Judith A; Kliman, Sabrina; Berheide, Catherine White; Chaucer, Alexander; Cock-Esteb, Alicea

2014-06-01

The relationships among land use patterns, geology, soil, and major solute concentrations in stream water for eight tributaries of the Kayaderosseras Creek watershed in Saratoga County, NY, were investigated using Pearson correlation coefficients and multivariate regression analysis. Sub-watersheds corresponding to each sampling site were delineated, and land use patterns were determined for each of the eight sub-watersheds using GIS. Four land use categories (urban development, agriculture, forests, and wetlands) constituted more than 99 % of the land in the sub-watersheds. Eleven water chemistry parameters were highly and positively correlated with each other and urban development. Multivariate regression models indicated urban development was the most powerful predictor for the same eleven parameters (conductivity, TN, TP, NO[Formula: see text], Cl(-), HCO(-)3, SO9(2-)4, Na(+), K(+), Ca(2+), and Mg(2+)). Adjusted R(2) values, ranging from 19 to 91 %, indicated that these models explained an average of 64 % of the variance in these 11 parameters across the samples and 70 % when Mg(2+) was omitted. The more common R (2), ranging from 29 to 92 %, averaged 68 % for these 11 parameters and 72 % when Mg(2+) was omitted. Water quality improved most with forest coverage in stream watersheds. The strong associations between water quality variables and urban development indicated an urban source for these 11 water quality parameters at all eight sampling sites was likely, suggesting that urban stream syndrome can be detected even on a relatively small scale in a lightly developed area. Possible urban sources of Ca(2+) and HCO(-)3 are suggested.

A comparison of single- and multi-site calibration and validation: a case study of SWAT in the Miyun Reservoir watershed, China

NASA Astrophysics Data System (ADS)

Bai, Jianwen; Shen, Zhenyao; Yan, Tiezhu

2017-09-01

An essential task in evaluating global water resource and pollution problems is to obtain the optimum set of parameters in hydrological models through calibration and validation. For a large-scale watershed, single-site calibration and validation may ignore spatial heterogeneity and may not meet the needs of the entire watershed. The goal of this study is to apply a multi-site calibration and validation of the Soil andWater Assessment Tool (SWAT), using the observed flow data at three monitoring sites within the Baihe watershed of the Miyun Reservoir watershed, China. Our results indicate that the multi-site calibration parameter values are more reasonable than those obtained from single-site calibrations. These results are mainly due to significant differences in the topographic factors over the large-scale area, human activities and climate variability. The multi-site method involves the division of the large watershed into smaller watersheds, and applying the calibrated parameters of the multi-site calibration to the entire watershed. It was anticipated that this case study could provide experience of multi-site calibration in a large-scale basin, and provide a good foundation for the simulation of other pollutants in followup work in the Miyun Reservoir watershed and other similar large areas.

Uncertainty in a monthly water balance model using the generalized likelihood uncertainty estimation methodology

NASA Astrophysics Data System (ADS)

Rivera, Diego; Rivas, Yessica; Godoy, Alex

2015-02-01

Hydrological models are simplified representations of natural processes and subject to errors. Uncertainty bounds are a commonly used way to assess the impact of an input or model architecture uncertainty in model outputs. Different sets of parameters could have equally robust goodness-of-fit indicators, which is known as Equifinality. We assessed the outputs from a lumped conceptual hydrological model to an agricultural watershed in central Chile under strong interannual variability (coefficient of variability of 25%) by using the Equifinality concept and uncertainty bounds. The simulation period ran from January 1999 to December 2006. Equifinality and uncertainty bounds from GLUE methodology (Generalized Likelihood Uncertainty Estimation) were used to identify parameter sets as potential representations of the system. The aim of this paper is to exploit the use of uncertainty bounds to differentiate behavioural parameter sets in a simple hydrological model. Then, we analyze the presence of equifinality in order to improve the identification of relevant hydrological processes. The water balance model for Chillan River exhibits, at a first stage, equifinality. However, it was possible to narrow the range for the parameters and eventually identify a set of parameters representing the behaviour of the watershed (a behavioural model) in agreement with observational and soft data (calculation of areal precipitation over the watershed using an isohyetal map). The mean width of the uncertainty bound around the predicted runoff for the simulation period decreased from 50 to 20 m3s-1 after fixing the parameter controlling the areal precipitation over the watershed. This decrement is equivalent to decreasing the ratio between simulated and observed discharge from 5.2 to 2.5. Despite the criticisms against the GLUE methodology, such as the lack of statistical formality, it is identified as a useful tool assisting the modeller with the identification of critical parameters.

Bacteria transport simulation using APEX model in the Toenepi watershed, New Zealand

USDA-ARS?s Scientific Manuscript database

The Agricultural Policy/Environmental eXtender (APEX) model is a distributed, continuous, daily-time step small watershed-scale hydrologic and water quality model. In this study, the newly developed fecal-derived bacteria fate and transport subroutine was applied and evalated using APEX model. The e...

[Analysis on nitrogen and phosphorus loading of non-point sources in Shiqiao river watershed based on L-THIA model].

PubMed

Li, Kai; Zeng, Fan-Tang; Fang, Huai-Yang; Lin, Shu

2013-11-01

Based on the Long-term Hydrological Impact Assessment (L-THIA) model, the effect of land use and rainfall change on nitrogen and phosphorus loading of non-point sources in Shiqiao river watershed was analyzed. The parameters in L-THIA model were revised according to the data recorded in the scene of runoff plots, which were set up in the watershed. The results showed that the distribution of areas with high pollution load was mainly concentrated in agricultural land and urban land. Agricultural land was the biggest contributor to nitrogen and phosphorus load. From 1995 to 2010, the load of major pollutants, namely TN and TP, showed an obviously increasing trend with increase rates of 17.91% and 25.30%, respectively. With the urbanization in the watershed, urban land increased rapidly and its area proportion reached 43.94%. The contribution of urban land to nitrogen and phosphorus load was over 40% in 2010. This was the main reason why pollution load still increased obviously while the agricultural land decreased greatly in the past 15 years. The rainfall occurred in the watershed was mainly concentrated in the flood season, so the nitrogen and phosphorus load of the flood season was far higher than that of the non-flood season and the proportion accounting for the whole year was over 85%. Pearson regression analysis between pollution load and the frequency of different patterns of rainfall demonstrated that rainfall exceeding 20 mm in a day was the main rainfall type causing non-point source pollution.

Understanding controls of hydrologic processes across two headwater monolithological catchments using model-data synthesis

NASA Astrophysics Data System (ADS)

Xiao, D.; Shi, Y.; Hoagland, B.; Del Vecchio, J.; Russo, T. A.; DiBiase, R. A.; Li, L.

2017-12-01

How do watershed hydrologic processes differ in catchments derived from different lithology? This study compares two first order, deciduous forest watersheds in Pennsylvania, a sandstone watershed, Garner Run (GR, 1.34 km2), and a shale-derived watershed, Shale Hills (SH, 0.08 km2). Both watersheds are simulated using a combination of national datasets and field measurements, and a physics-based land surface hydrologic model, Flux-PIHM. We aim to evaluate the effects of lithology on watershed hydrology and assess if we can simulate a new watershed without intensive measurements, i.e., directly use calibration information from one watershed (SH) to reproduce hydrologic dynamics of another watershed (GR). Without any calibration, the model at GR based on national datasets and calibration inforamtion from SH cannot capture some discharge peaks or the baseflow during dry periods. The model prediction agrees well with the GR field discharge and soil moisture after calibrating the soil hydraulic parameters using the uncertainty based Hornberger-Spear-Young algorithm and the Latin Hypercube Sampling method. Agreeing with the field observation and national datasets, the difference in parameter values shows that the sandstone watershed has a larger averaged soil pore diameter, greater water storage created by porosity, lower water retention ability, and greater preferential flow. The water budget calculation shows that the riparian zone and the colluvial valley serves as buffer zones that stores water at GR. Using the same procedure, we compared Flux-PIHM simulations with and without a field measured surface boulder map at GR. When the boulder map is used, the prediction of areal averaged soil moisture is improved, without performing extra calibration. When calibrated separately, the cases with or without boulder map yield different calibration values, but their hydrologic predictions are similar, showing equifinality. The calibrated soil hydraulic parameter values in the with boulder map case is more physically plausible than the without boulder map case. We switched the topography and soil properties between GR and SH, and results indicate that the hydrologic processes are more sensitive to changes in domain topography than to changes in the soil properties.

Validation of pore network simulations of ex-situ water distributions in a gas diffusion layer of proton exchange membrane fuel cells with X-ray tomographic images

NASA Astrophysics Data System (ADS)

Agaesse, Tristan; Lamibrac, Adrien; Büchi, Felix N.; Pauchet, Joel; Prat, Marc

2016-11-01

Understanding and modeling two-phase flows in the gas diffusion layer (GDL) of proton exchange membrane fuel cells are important in order to improve fuel cells performance. They are scientifically challenging because of the peculiarities of GDLs microstructures. In the present work, simulations on a pore network model are compared to X-ray tomographic images of water distributions during an ex-situ water invasion experiment. A method based on watershed segmentation was developed to extract a pore network from the 3D segmented image of the dry GDL. Pore network modeling and a full morphology model were then used to perform two-phase simulations and compared to the experimental data. The results show good agreement between experimental and simulated microscopic water distributions. Pore network extraction parameters were also benchmarked using the experimental data and results from full morphology simulations.

Diameter of fluorescent microspheres determines their distribution throughout the cortical watershed area in mice.

PubMed

Tsukada, Naoki; Katsumata, Masahiro; Oki, Koichi; Minami, Kazushi; Abe, Takato; Takahashi, Shinichi; Itoh, Yoshiaki; Suzuki, Norihiro

2018-01-15

A hemodynamic mechanism has long been assumed to play an important role in watershed infarction. In recent years, however, clinical evidence has indicated that an embolic mechanism is involved. The mechanism by which emboli are trapped preferentially in watershed areas remains unclear. In the present study, we developed a mouse embolus model using fluorescent microspheres with different diameters and evaluated the role of the microspheres' diameters in the generation of a watershed-patterned distribution. We injected fluorescent microspheres of four different diameters (i.e., 13, 24, 40, and 69 μm) into the internal carotid artery of C57BL/6 mice either (1) without ligation of the common carotid artery (normal perfusion pressure model: NPPM) or (2) with ligation of the common carotid artery (low perfusion pressure model: LPPM). Left common carotid artery ligation induced reductions in local cerebral blood flow in both the periphery and the core area of the left middle cerebral artery. A greater reduction in the border-zone area between the left anterior cerebral artery and the middle cerebral artery was also noted. After 24 h, the brains were removed and the distribution of the microspheres in the brain was evaluated using a fluorescence microscope. The 24-μm microspheres were distributed in the watershed area more frequently than the other microsphere sizes (P < .05, ANOVA followed by Tukey's test). Meanwhile, the distribution rates were similar between the NPPM and LPPM models for all microsphere sizes. This study suggested that the distribution pattern of the microspheres was only affected by the microspheres' diameters. Copyright © 2017 Elsevier B.V. All rights reserved.

An eleven-year validation of a physically-based distributed dynamic ecohydorological model tRIBS+VEGGIE: Walnut Gulch Experimental Watershed

NASA Astrophysics Data System (ADS)

Sivandran, G.; Bisht, G.; Ivanov, V. Y.; Bras, R. L.

2008-12-01

A coupled, dynamic vegetation and hydrologic model, tRIBS+VEGGIE, was applied to the semiarid Walnut Gulch Experimental Watershed in Arizona. The physically-based, distributed nature of the coupled model allows for parameterization and simulation of watershed vegetation-water-energy dynamics on timescales varying from hourly to interannual. The model also allows for explicit spatial representation of processes that vary due to complex topography, such as lateral redistribution of moisture and partitioning of radiation with respect to aspect and slope. Model parameterization and forcing was conducted using readily available databases for topography, soil types, and land use cover as well as the data from network of meteorological stations located within the Walnut Gulch watershed. In order to test the performance of the model, three sets of simulations were conducted over an 11 year period from 1997 to 2007. Two simulations focus on heavily instrumented nested watersheds within the Walnut Gulch basin; (i) Kendall watershed, which is dominated by annual grasses; and (ii) Lucky Hills watershed, which is dominated by a mixture of deciduous and evergreen shrubs. The third set of simulations cover the entire Walnut Gulch Watershed. Model validation and performance were evaluated in relation to three broad categories; (i) energy balance components: the network of meteorological stations were used to validate the key energy fluxes; (ii) water balance components: the network of flumes, rain gauges and soil moisture stations installed within the watershed were utilized to validate the manner in which the model partitions moisture; and (iii) vegetation dynamics: remote sensing products from MODIS were used to validate spatial and temporal vegetation dynamics. Model results demonstrate satisfactory spatial and temporal agreement with observed data, giving confidence that key ecohydrological processes can be adequately represented for future applications of tRIBS+VEGGIE in regional modeling of land-atmosphere interactions.

Calibration of a Physically-Based Semi-Distributed Hydrologic Model: The Importance of Internal Justification

NASA Astrophysics Data System (ADS)

Tasdighi, A.; Arabi, M.

2014-12-01

Calibration of physically-based distributed hydrologic models has always been a challenging task and subject of controversy in the literature. This study is aimed to investigate how different physiographic characteristics of watersheds call for adaption of the methods used in order to have more robust and internally justifiable simulations. Haw Watershed (1300 sq. mi.) is located in the piedmont region of North Carolina draining into B. Everett Jordan Lake located in west of Raleigh. Major land covers in this watershed are forest (50%), urban/suburban (21%) and agriculture (25%) of which a large portion is pasture. Different hydrologic behaviors are observed in this watershed based on the land use composition and size of the sub-watersheds. Highly urbanized sub-watersheds show flashier hydrographs and near instantaneous hydrologic responses. This is also the case with smaller sub-watersheds with relatively lower percentage of urban areas. The Soil and Water Assessment Tool (SWAT) has been widely used in the literature for hydrologic simulation on daily basis using Soil Conservation Service Curve Number method (SCS CN). However, it has not been used as frequently using the sub-daily routines. In this regard there are a number of studies in the literature which have used coarse time scale (daily) precipitation with methods like SCS CN to calibrate SWAT for watersheds containing different types of land uses and soils reporting satisfying results at the outlet of the watershed. This is while for physically-based distributed models, the more important concern should be to check and analyze the internal processes leading to those results. In this study, the watershed is divided into several sub-watersheds to compare the performance of SCS CN and Green & Ampt (GA) methods on different land uses at different spatial scales. The results suggest better performance of GA compared to SCS CN for smaller and highly urbanized sub-watersheds although GA predominance is not very significant for the latter. Also, the better performance of GA in simulating the peak flows and flashy behavior of the hydrographs is notable. GA did not show a significant improvement over SCS CN in simulating the excess rainfall for larger sub-watersheds.

Improved hydrological modeling using AGWA; incorporation of different management practices in hydrological modeling.

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.

WATERSHED LEVEL RISK ASSESSMENT OF NITROGEN AND PHOSPHOROUS EXPORT

EPA Science Inventory

The distribution of different types of land cover across a watershed is a principal factor in controlling the amount of nitrogen and phosphorous exported from a watershed. A well developed literature of nutrient export coefficients by land-cover class was used to model t...

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

Treesearch

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

2006-01-01

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

MODELING UNCERTAINTY OF RUNOFF AND SEDIMENT YIELD IN TWO EXPERIMENTAL WATERSHEDS

EPA Science Inventory

Sediment loading from agriculture is adversely impacting surface water quality and ecological conditions. In this regard, the use of distributed hydrologic models has gained acceptance in management of soil erosion and sediment yield from agricultural watersheds. Soil infiltrati...

Investigation of Soil Erosion and Phosphorus Transport within an Agricultural Watershed

NASA Astrophysics Data System (ADS)

Klik, A.; Jester, W.; Muhar, A.; Peinsitt, A.; Rampazzo, N.; Mentler, A.; Staudinger, B.; Eder, M.

2003-04-01

In a 40 ha agricultural used watershed in Austria, surface runoff, soil erosion and nutrient losses are measured spatially distributed with 12 small erosion plots. Crops during growing season 2002 are canola, corn, sunflower, winter wheat, winter barley, rye, sugar beets, and pasture. Canopy height and canopy cover are observed in 14-day intervals. Four times per year soil water content, shear stress and random roughness of the surface are measured in a 25 x 25 m grid (140 points). The same raster is sampled for soil texture analyses and content of different phosphorus fractions in the 0-10 cm soil depth. Spatially distributed data are used for geostatistical analysis. Along three transects hydrologic conditions of the hillslope position (top, middle, foot) are investigated by measuring soil water content and soil matrix potential. After erosive events erosion features (rills, deposition, ...) are mapped using GPS. All measured data will be used as input parameters for the Limburg Soil Erosion Model (LISEM).

Inverse Modeling of Hydrologic Parameters Using Surface Flux and Runoff Observations in the Community Land Model

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

Sun, Yu; Hou, Zhangshuan; Huang, Maoyi

2013-12-10

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Two inversion strategies, the deterministic least-square fitting and stochastic Markov-Chain Monte-Carlo (MCMC) - Bayesian inversion approaches, are evaluated by applying them to CLM4 at selected sites. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find thatmore » using model parameters calibrated by the least-square fitting provides little improvements in the model simulations but the sampling-based stochastic inversion approaches are consistent - as more information comes in, the predictive intervals of the calibrated parameters become narrower and the misfits between the calculated and observed responses decrease. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to the different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.« less

[Sensitivity analysis of AnnAGNPS model's hydrology and water quality parameters based on the perturbation analysis method].

PubMed

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.

Precipitation and Runoff Simulations of the Carson Range and Pine Nut Mountains, and Updated Estimates of Ground-Water Inflow and the Ground-Water Budgets for Basin-Fill Aquifers of Carson Valley, Douglas County, Nevada, and Alpine County, California

USGS Publications Warehouse

Jeton, Anne E.; Maurer, Douglas K.

2007-01-01

Recent estimates of ground-water inflow to the basin-fill aquifers of Carson Valley, Nevada, and California, from the adjacent Carson Range and Pine Nut Mountains ranged from 22,000 to 40,000 acre-feet per year using water-yield and chloride-balance methods. In this study, watershed models were developed for watersheds with perennial streams and for watersheds with ephemeral streams in the Carson Range and Pine Nut Mountains to provide an independent estimate of ground-water inflow. This report documents the development and calibration of the watershed models, presents model results, compares the results with recent estimates of ground-water inflow to the basin-fill aquifers of Carson Valley, and presents updated estimates of the ground-water budget for basin-fill aquifers of Carson Valley. The model used for the study was the Precipitation-Runoff Modeling System, a physically based, distributed-parameter model designed to simulate precipitation and snowmelt runoff as well as snowpack accumulation and snowmelt processes. Geographic Information System software was used to manage spatial data, characterize model drainages, and to develop Hydrologic Response Units. Models were developed for * Two watersheds with gaged perennial streams in the Carson Range and two watersheds with gaged perennial streams in the Pine Nut Mountains using measured daily mean runoff, * Ten watersheds with ungaged perennial streams using estimated daily mean runoff, * Ten watershed with ungaged ephemeral streams in the Carson Range, and * A large area of ephemeral runoff near the Pine Nut Mountains. Models developed for the gaged watersheds were used as index models to guide the calibration of models for ungaged watersheds. Model calibration was constrained by daily mean runoff for 4 gaged watersheds and for 10 ungaged watersheds in the Carson Range estimated in a previous study. The models were further constrained by annual precipitation volumes estimated in a previous study to provide estimates of ground-water inflow using similar water input. The calibration periods were water years 1990-2002 for watersheds in the Carson Range, and water years 1981-97 for watersheds in the Pine Nut Mountains. Daily mean values for water years 1990-2002 were then simulated using the calibrated watershed models in the Pine Nut Mountains. The daily mean values of precipitation, runoff, evapotranspiration, and ground-water inflow simulated from the watershed models were summed to provide annual mean rates and volumes for each year of the simulations, and mean annual rates and volumes computed for water years 1990-2002. Mean annual bias for the period of record for models of Daggett Creek and Fredericksburg Canyon watersheds, two gaged perennial watersheds in the Carson Range, was within 4 percent and relative errors were about 6 and 12 percent, respectively. Model fit was not as satisfactory for two gaged perennial watersheds, Pine Nut and Buckeye Creeks, in the Pine Nut Mountains. The Pine Nut Creek watershed model had a large negative mean annual bias and a relative error of -11 percent, underestimated runoff for all years but the wet years in the latter part of the record, but adequately simulated the bulk of the spring runoff most of the years. The Buckeye Creek watershed model overestimated mean annual runoff with a relative error of about -5 percent when water year 1994 was removed from the analysis because it had a poor record. The bias and error of the calibrated models were within generally accepted limits for watershed models, indicating the simulated rates and volumes of runoff and ground-water inflow were reasonable. The total mean annual ground-water inflow to Carson Valley computed using estimates simulated by the watershed models was 38,000 acre-feet, including ground-water inflow from Eagle Valley, recharge from precipitation on eolian sand and gravel deposits, and ground-water recharge from precipitation on the western alluvial fans. The estimate was in close agreement with that obtained from the chloride-balance method, 40,000 acre-feet, but was considerably greater than the estimate obtained from the water-yield method, 22,000 acre-feet. The similar estimates obtained from the watershed models and chloride-balance method, two relatively independent methods, provide more confidence that they represent a reasonably accurate volume of ground-water inflow to Carson Valley. However, the two estimates are not completely independent because they use similar distributions of mean annual precipitation. Annual ground-water recharge of the basin-fill aquifers in Carson Valley ranged from 51,000 to 54,000 acre-feet computed using estimates of ground-water inflow to Carson Valley simulated from the watershed models combined with previous estimates of other ground-water budget components. Estimates of mean annual ground-water discharge range from 44,000 to 47,000 acre-feet. The low range estimate for ground-water recharge, 51,000 acre-feet per year, is most similar to the high range estimate for ground-water discharge, 47,000 acre-feet per year. Thus, an average annual volume of about 50,000 acre-feet is a reasonable estimate for mean annual ground-water recharge to and discharge from the basin-fill aquifers in Carson Valley. The results of watershed models indicate that significant interannual variability in the volumes of ground-water inflow is caused by climate variations. During multi-year drought conditions, the watershed simulations indicate that ground-water recharge could be as much as 80 percent less than the mean annual volume of 50,000 acre-feet.

CHARACTERIZING SPATIAL AND TEMPORAL DYNAMICS: DEVELOPMENT OF A GRID-BASED WATERSHED MERCURY LOADING MODEL

EPA Science Inventory

A distributed grid-based watershed mercury loading model has been developed to characterize spatial and temporal dynamics of mercury from both point and non-point sources. The model simulates flow, sediment transport, and mercury dynamics on a daily time step across a diverse lan...

Agricultural Policy Environmental eXtender simulation of three adjacent row-crop watersheds in the claypan region

USDA-ARS?s Scientific Manuscript database

The Agricultural Policy Environmental Extender (APEX) model can simulate crop yields, and pollutant loadings in whole farms or small watersheds with variety of management practices. The study objectives were to identify sensitive parameters and parameterize, calibrate and validate the APEX model fo...

Implementation of surface soil moisture data assimilation with watershed scale distributed hydrological model

USDA-ARS?s Scientific Manuscript database

This paper aims to investigate how surface soil moisture data assimilation affects each hydrologic process and how spatially varying inputs affect the potential capability of surface soil moisture assimilation at the watershed scale. The Ensemble Kalman Filter (EnKF) is coupled with a watershed scal...

DEM Based Modeling: Grid or TIN? The Answer Depends

NASA Astrophysics Data System (ADS)

Ogden, F. L.; Moreno, H. A.

2015-12-01

The availability of petascale supercomputing power has enabled process-based hydrological simulations on large watersheds and two-way coupling with mesoscale atmospheric models. Of course with increasing watershed scale come corresponding increases in watershed complexity, including wide ranging water management infrastructure and objectives, and ever increasing demands for forcing data. Simulations of large watersheds using grid-based models apply a fixed resolution over the entire watershed. In large watersheds, this means an enormous number of grids, or coarsening of the grid resolution to reduce memory requirements. One alternative to grid-based methods is the triangular irregular network (TIN) approach. TINs provide the flexibility of variable resolution, which allows optimization of computational resources by providing high resolution where necessary and low resolution elsewhere. TINs also increase required effort in model setup, parameter estimation, and coupling with forcing data which are often gridded. This presentation discusses the costs and benefits of the use of TINs compared to grid-based methods, in the context of large watershed simulations within the traditional gridded WRF-HYDRO framework and the new TIN-based ADHydro high performance computing watershed simulator.

Watershed Complexity Impacts on Rainfall-Runoff Modeling

NASA Astrophysics Data System (ADS)

Goodrich, D. C.; Grayson, R.; Willgoose, G.; Palacios-Velez, O.; Bloeschl, G.

2002-12-01

Application of distributed hydrologic watershed models fundamentally requires watershed partitioning or discretization. In addition to partitioning the watershed into modeling elements, these elements typically represent a further abstraction of the actual watershed surface and its relevant hydrologic properties. A critical issue that must be addressed by any user of these models prior to their application is definition of an acceptable level of watershed discretization or geometric model complexity. A quantitative methodology to define a level of geometric model complexity commensurate with a specified level of model performance is developed for watershed rainfall-runoff modeling. In the case where watershed contributing areas are represented by overland flow planes, equilibrium discharge storage was used to define the transition from overland to channel dominated flow response. The methodology is tested on four subcatchments which cover a range of watershed scales of over three orders of magnitude in the USDA-ARS Walnut Gulch Experimental Watershed in Southeastern Arizona. It was found that distortion of the hydraulic roughness can compensate for a lower level of discretization (fewer channels) to a point. Beyond this point, hydraulic roughness distortion cannot compensate for topographic distortion of representing the watershed by fewer elements (e.g. less complex channel network). Similarly, differences in representation of topography by different model or digital elevation model (DEM) types (e.g. Triangular Irregular Elements - TINs; contour lines; and regular grid DEMs) also result in difference in runoff routing responses that can be largely compensated for by a distortion in hydraulic roughness.

Application of the ReNuMa model in the Sha He river watershed: tools for watershed environmental management.

PubMed

Sha, Jian; Liu, Min; Wang, Dong; Swaney, Dennis P; Wang, Yuqiu

2013-07-30

Models and related analytical methods are critical tools for use in modern watershed management. A modeling approach for quantifying the source apportionment of dissolved nitrogen (DN) and associated tools for examining the sensitivity and uncertainty of the model estimates were assessed for the Sha He River (SHR) watershed in China. The Regional Nutrient Management model (ReNuMa) was used to infer the primary sources of DN in the SHR watershed. This model is based on the Generalized Watershed Loading Functions (GWLF) and the Net Anthropogenic Nutrient Input (NANI) framework, modified to improve the characterization of subsurface hydrology and septic system loads. Hydrochemical processes of the SHR watershed, including streamflow, DN load fluxes, and corresponding DN concentration responses, were simulated following calibrations against observations of streamflow and DN fluxes. Uncertainty analyses were conducted with a Monte Carlo analysis to vary model parameters for assessing the associated variations in model outputs. The model performed accurately at the watershed scale and provided estimates of monthly streamflows and nutrient loads as well as DN source apportionments. The simulations identified the dominant contribution of agricultural land use and significant monthly variations. These results provide valuable support for science-based watershed management decisions and indicate the utility of ReNuMa for such applications. Copyright © 2013 Elsevier Ltd. All rights reserved.

Development of Semi-distributed ecohydrological model in the Rio Grande De Manati River Basin, Puerto Rico

NASA Astrophysics Data System (ADS)

Setegn, S. G.; Ortiz, J.; Melendez, J.; Barreto, M.; Torres-Perez, J. L.; Guild, L. S.

2015-12-01

There are limited studies in Puerto Rico that shows the water resources availability and variability with respect to changing climates and land use. The main goal of the HICE-PR (Human Impacts to Coastal Ecosystems in Puerto Rico (HICE-PR): the Río Loco Watershed (southwest coast PR) project which was funded by NASA is to evaluate the impacts of land use/land cover changes on the quality and extent of coastal and marine ecosystems (CMEs) in two priority watersheds in Puerto Rico (Manatí and Guánica).The main objective of this study is to set up a physically based spatially distributed hydrological model, Soil and Water Assessment Tool (SWAT) for the analysis of hydrological processes in the Rio Grande de Manati river basin. SWAT (soil and water assessment tool) is a spatially distributed watershed model developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds. For efficient use of distributed models for hydrological and scenario analysis, it is important that these models pass through a careful calibration and uncertainty analysis. The model was calibrated and validated using Sequential Uncertainty Fitting (SUFI-2) calibration and uncertainty analysis algorithms. The model evaluation statistics for streamflows prediction shows that there is a good agreement between the measured and simulated flows that was verified by coefficients of determination and Nash Sutcliffe efficiency greater than 0.5. Keywords: Hydrological Modeling; SWAT; SUFI-2; Rio Grande De Manati; Puerto Rico

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.

A sediment graph model based on SCS-CN method

NASA Astrophysics Data System (ADS)

Singh, P. K.; Bhunya, P. K.; Mishra, S. K.; Chaube, U. C.

2008-01-01

SummaryThis paper proposes new conceptual sediment graph models based on coupling of popular and extensively used methods, viz., Nash model based instantaneous unit sediment graph (IUSG), soil conservation service curve number (SCS-CN) method, and Power law. These models vary in their complexity and this paper tests their performance using data of the Nagwan watershed (area = 92.46 km 2) (India). The sensitivity of total sediment yield and peak sediment flow rate computations to model parameterisation is analysed. The exponent of the Power law, β, is more sensitive than other model parameters. The models are found to have substantial potential for computing sediment graphs (temporal sediment flow rate distribution) as well as total sediment yield.

Nonstationarities in Catchment Response According to Basin and Rainfall Characteristics: Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kwon, Hyun-Han; Kim, Jin-Guk; Jung, Il-Won

2015-04-01

It must be acknowledged that application of rainfall-runoff models to simulate rainfall-runoff processes are successful in gauged watershed. However, there still remain some issues that will need to be further discussed. In particular, the quantitive representation of nonstationarity issue in basin response (e.g. concentration time, storage coefficient and roughness) along with ungauged watershed needs to be studied. In this regard, this study aims to investigate nonstationarity in basin response so as to potentially provide useful information in simulating runoff processes in ungauged watershed. For this purpose, HEC-1 rainfall-runoff model was mainly utilized. In addition, this study combined HEC-1 model with Bayesian statistical model to estimate uncertainty of the parameters which is called Bayesian HEC-1 (BHEC-1). The proposed rainfall-runofall model is applied to various catchments along with various rainfall patterns to understand nonstationarities in catchment response. Further discussion about the nonstationarity in catchment response and possible regionalization of the parameters for ungauged watershed are discussed. KEYWORDS: Nonstationary, Catchment response, Uncertainty, Bayesian Acknowledgement This research was supported by a Grant (13SCIPA01) from Smart Civil Infrastructure Research Program funded by the Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and the Korea Agency for Infrastructure Technology Advancement (KAIA).

Model‐based analysis of the influence of catchment properties on hydrologic partitioning across five mountain headwater subcatchments

PubMed Central

Wagener, Thorsten; McGlynn, Brian

2015-01-01

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

Synthetic calibration of a Rainfall-Runoff Model

USGS Publications Warehouse

Thompson, David B.; Westphal, Jerome A.; ,

1990-01-01

A method for synthetically calibrating storm-mode parameters for the U.S. Geological Survey's Precipitation-Runoff Modeling System is described. Synthetic calibration is accomplished by adjusting storm-mode parameters to minimize deviations between the pseudo-probability disributions represented by regional regression equations and actual frequency distributions fitted to model-generated peak discharge and runoff volume. Results of modeling storm hydrographs using synthetic and analytic storm-mode parameters are presented. Comparisons are made between model results from both parameter sets and between model results and observed hydrographs. Although mean storm runoff is reproducible to within about 26 percent of the observed mean storm runoff for five or six parameter sets, runoff from individual storms is subject to large disparities. Predicted storm runoff volume ranged from 2 percent to 217 percent of commensurate observed values. Furthermore, simulation of peak discharges was poor. Predicted peak discharges from individual storm events ranged from 2 percent to 229 percent of commensurate observed values. The model was incapable of satisfactorily executing storm-mode simulations for the study watersheds. This result is not considered a particular fault of the model, but instead is indicative of deficiencies in similar conceptual models.

Simulation of Runoff and Reservoir Inflow for Use in a Flood-Analysis Model for the Delaware River, Pennsylvania, New Jersey, and New York, 2004-2006

USGS Publications Warehouse

Goode, Daniel J.; Koerkle, Edward H.; Hoffman, Scott A.; Regan, R. Steve; Hay, Lauren E.; Markstrom, Steven L.

2010-01-01

A model was developed to simulate inflow to reservoirs and watershed runoff to streams during three high-flow events between September 2004 and June 2006 for the main-stem subbasin of the Delaware River draining to Trenton, N.J. The model software is a modified version of the U.S. Geological Survey (USGS) Precipitation-Runoff Modeling System (PRMS), a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The PRMS model simulates time periods associated with main-stem flooding that occurred in September 2004, April 2005, and June 2006 and uses both daily and hourly time steps. Output from the PRMS model was formatted for use as inflows to a separately documented reservoir and riverrouting model, the HEC-ResSim model, developed by the U.S. Army Corps of Engineers Hydrologic Engineering Center to evaluate flooding. The models were integrated through a graphical user interface. The study area is the 6,780 square-mile watershed of the Delaware River in the states of Pennsylvania, New Jersey, and New York that drains to Trenton, N.J. A geospatial database was created for use with a geographic information system to assist model discretization, determine land-surface characterization, and estimate model parameters. The USGS National Elevation Dataset at 100-meter resolution, a Digital Elevation Model (DEM), was used for model discretization into streams and hydrologic response units. In addition, geospatial processing was used to estimate initial model parameters from the DEM and other data layers, including land use. The model discretization represents the study area using 869 hydrologic response units and 452 stream segments. The model climate data for point stations were obtained from multiple sources. These sources included daily data for 22 National Weather Service (NWS) Cooperative Climate Station network stations, hourly data for 15 stations from the National Climatic Data Center, hourly data for 1 station from the NWS Middle Atlantic River Forecast Center records, and daily and hourly data for 7 stations operated by the New York City Department of Environmental Protection. The NWS Multisensor Precipitation Estimate data set for 2001-2007 was used for computing daily precipitation for the model and for computing hourly precipitation for storm simulation periods. Calibration of the PRMS model included regression and optimization algorithms, as well as manual adjustments of model parameters. The general goal of the calibration procedure was to minimize the difference between discharge measured at USGS streamgages and the corresponding discharge simulated by the model. Daily streamflow data from 35 USGS streamgages were used in model calibration. The streamflow data represent areas draining from 20.2 to 6,780 square miles. The PRMS model simulates reservoir inflow and watershed runoff for use as input into HECResSim for the purpose of evaluating and comparing the effects of different watershed conditions on main-stem flooding in the Delaware River watershed draining to Trenton, N.J. The PRMS model is useful as a planning tool to simulate the effects of land-use changes and different antecedent conditions on local runoff and reservoir inflow and, as input to the HEC-ResSim model, on flood flows in the main stem of the Delaware River.

Reduction of uncertainty for estimating runoff with the NRCS CN model by the adaptation to local climatic conditions

NASA Astrophysics Data System (ADS)

Durán-Barroso, Pablo; González, Javier; Valdés, Juan B.

2016-04-01

Rainfall-runoff quantification is one of the most important tasks in both engineering and watershed management as it allows to identify, forecast and explain watershed response. For that purpose, the Natural Resources Conservation Service Curve Number method (NRCS CN) is the conceptual lumped model more recognized in the field of rainfall-runoff estimation. Furthermore, there is still an ongoing discussion about the procedure to determine the portion of rainfall retained in the watershed before runoff is generated, called as initial abstractions. This concept is computed as a ratio (λ) of the soil potential maximum retention S of the watershed. Initially, this ratio was assumed to be 0.2, but later it has been proposed to be modified to 0.05. However, the actual procedures to convert NRCS CN model parameters obtained under a different hypothesis about λ do not incorporate any adaptation of climatic conditions of each watershed. By this reason, we propose a new simple method for computing model parameters which is adapted to local conditions taking into account regional patterns of climate conditions. After checking the goodness of this procedure against the actual ones in 34 different watersheds located in Ohio and Texas (United States), we concluded that this novel methodology represents the most accurate and efficient alternative to refit the initial abstraction ratio.

Understanding controls of hydrologic processes across two monolithological catchments using model-data integration

NASA Astrophysics Data System (ADS)

Xiao, D.; Shi, Y.; Li, L.

2016-12-01

Field measurements are important to understand the fluxes of water, energy, sediment, and solute in the Critical Zone however are expensive in time, money, and labor. This study aims to assess the model predictability of hydrological processes in a watershed using information from another intensively-measured watershed. We compare two watersheds of different lithology using national datasets, field measurements, and physics-based model, Flux-PIHM. We focus on two monolithological, forested watersheds under the same climate in the Shale Hills Susquehanna CZO in central Pennsylvania: the Shale-based Shale Hills (SSH, 0.08 km2) and the sandstone-based Garner Run (GR, 1.34 km2). We firstly tested the transferability of calibration coefficients from SSH to GR. We found that without any calibration the model can successfully predict seasonal average soil moisture and discharge which shows the advantage of a physics-based model, however, cannot precisely capture some peaks or the runoff in summer. The model reproduces the GR field data better after calibrating the soil hydrology parameters. In particular, the percentage of sand turns out to be a critical parameter in reproducing data. With sandstone being the dominant lithology, GR has much higher sand percentage than SSH (48.02% vs. 29.01%), leading to higher hydraulic conductivity, lower overall water storage capacity, and in general lower soil moisture. This is consistent with area averaged soil moisture observations using the cosmic-ray soil moisture observing system (COSMOS) at the two sites. This work indicates that some parameters, including evapotranspiration parameters, are transferrable due to similar climatic and land cover conditions. However, the key parameters that control soil moisture, including the sand percentage, need to be recalibrated, reflecting the key role of soil hydrological properties.

On the connection of permafrost and debris flow activity in Austria

NASA Astrophysics Data System (ADS)

Huber, Thomas; Kaitna, Roland

2016-04-01

Debris flows represent a severe hazard in alpine regions and typically result from a critical combination of relief energy, water, and sediment. Hence, besides water-related trigger conditions, the availability of abundant sediment is a major control on debris flows activity in alpine regions. Increasing temperatures due to global warming are expected to affect periglacial regions and by that the distribution of alpine permafrost and the depth of the active layer, which in turn might lead to increased debris flow activity and increased interference with human interests. In this contribution we assess the importance of permafrost on documented debris flows in the past by connecting the modeled permafrost distribution with a large database of historic debris flows in Austria. The permafrost distribution is estimated based on a published model approach and mainly depends of altitude, relief, and exposition. The database of debris flows includes more than 4000 debris flow events in around 1900 watersheds. We find that 27 % of watersheds experiencing debris flow activity have a modeled permafrost area smaller than 5 % of total area. Around 7 % of the debris flow prone watersheds have an area larger than 5 %. Interestingly, our first results indicate that watersheds without permafrost experience significantly less, but more intense debris flow events than watersheds with modeled permafrost occurrence. Our study aims to contribute to a better understanding of geomorphic activity and the impact of climate change in alpine environments.

Parameter Estimation of Computationally Expensive Watershed Models Through Efficient Multi-objective Optimization and Interactive Decision Analytics

NASA Astrophysics Data System (ADS)

Akhtar, Taimoor; Shoemaker, Christine

2016-04-01

Watershed model calibration is inherently a multi-criteria problem. Conflicting trade-offs exist between different quantifiable calibration criterions indicating the non-existence of a single optimal parameterization. Hence, many experts prefer a manual approach to calibration where the inherent multi-objective nature of the calibration problem is addressed through an interactive, subjective, time-intensive and complex decision making process. Multi-objective optimization can be used to efficiently identify multiple plausible calibration alternatives and assist calibration experts during the parameter estimation process. However, there are key challenges to the use of multi objective optimization in the parameter estimation process which include: 1) multi-objective optimization usually requires many model simulations, which is difficult for complex simulation models that are computationally expensive; and 2) selection of one from numerous calibration alternatives provided by multi-objective optimization is non-trivial. This study proposes a "Hybrid Automatic Manual Strategy" (HAMS) for watershed model calibration to specifically address the above-mentioned challenges. HAMS employs a 3-stage framework for parameter estimation. Stage 1 incorporates the use of an efficient surrogate multi-objective algorithm, GOMORS, for identification of numerous calibration alternatives within a limited simulation evaluation budget. The novelty of HAMS is embedded in Stages 2 and 3 where an interactive visual and metric based analytics framework is available as a decision support tool to choose a single calibration from the numerous alternatives identified in Stage 1. Stage 2 of HAMS provides a goodness-of-fit measure / metric based interactive framework for identification of a small subset (typically less than 10) of meaningful and diverse set of calibration alternatives from the numerous alternatives obtained in Stage 1. Stage 3 incorporates the use of an interactive visual analytics framework for decision support in selection of one parameter combination from the alternatives identified in Stage 2. HAMS is applied for calibration of flow parameters of a SWAT model, (Soil and Water Assessment Tool) designed to simulate flow in the Cannonsville watershed in upstate New York. Results from the application of HAMS to Cannonsville indicate that efficient multi-objective optimization and interactive visual and metric based analytics can bridge the gap between the effective use of both automatic and manual strategies for parameter estimation of computationally expensive watershed models.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Preliminary study of soil permeability properties using principal component analysis

NASA Astrophysics Data System (ADS)

Yulianti, M.; Sudriani, Y.; Rustini, H. A.

2018-02-01

Soil permeability measurement is undoubtedly important in carrying out soil-water research such as rainfall-runoff modelling, irrigation water distribution systems, etc. It is also known that acquiring reliable soil permeability data is rather laborious, time-consuming, and costly. Therefore, it is desirable to develop the prediction model. Several studies of empirical equations for predicting permeability have been undertaken by many researchers. These studies derived the models from areas which soil characteristics are different from Indonesian soil, which suggest a possibility that these permeability models are site-specific. The purpose of this study is to identify which soil parameters correspond strongly to soil permeability and propose a preliminary model for permeability prediction. Principal component analysis (PCA) was applied to 16 parameters analysed from 37 sites consist of 91 samples obtained from Batanghari Watershed. Findings indicated five variables that have strong correlation with soil permeability, and we recommend a preliminary permeability model, which is potential for further development.

Evaluation of flash-flood discharge forecasts in complex terrain using precipitation

USGS Publications Warehouse

Yates, D.; Warner, T.T.; Brandes, E.A.; Leavesley, G.H.; Sun, Jielun; Mueller, C.K.

2001-01-01

Operational prediction of flash floods produced by thunderstorm (convective) precipitation in mountainous areas requires accurate estimates or predictions of the precipitation distribution in space and time. The details of the spatial distribution are especially critical in complex terrain because the watersheds are generally small in size, and small position errors in the forecast or observed placement of the precipitation can distribute the rain over the wrong watershed. In addition to the need for good precipitation estimates and predictions, accurate flood prediction requires a surface-hydrologic model that is capable of predicting stream or river discharge based on the precipitation-rate input data. Different techniques for the estimation and prediction of convective precipitation will be applied to the Buffalo Creek, Colorado flash flood of July 1996, where over 75 mm of rain from a thunderstorm fell on the watershed in less than 1 h. The hydrologic impact of the precipitation was exacerbated by the fact that a significant fraction of the watershed experienced a wildfire approximately two months prior to the rain event. Precipitation estimates from the National Weather Service's operational Weather Surveillance Radar-Doppler 1988 and the National Center for Atmospheric Research S-band, research, dual-polarization radar, colocated to the east of Denver, are compared. In addition, very short range forecasts from a convection-resolving dynamic model, which is initialized variationally using the radar reflectivity and Doppler winds, are compared with forecasts from an automated-algorithmic forecast system that also employs the radar data. The radar estimates of rain rate, and the two forecasting systems that employ the radar data, have degraded accuracy by virtue of the fact that they are applied in complex terrain. Nevertheless, the radar data and forecasts from the dynamic model and the automated algorithm could be operationally useful for input to surface-hydrologic models employed for flood warning. Precipitation data provided by these various techniques at short time scales and at fine spatial resolutions are employed as detailed input to a distributed-parameter hydrologic model for flash-flood prediction and analysis. With the radar-based precipitation estimates employed as input, the simulated flood discharge was similar to that observed. The dynamic-model precipitation forecast showed the most promise in providing a significant discharge-forecast lead time. The algorithmic system's precipitation forecast did not demonstrate as much skill, but the associated discharge forecast would still have been sufficient to have provided an alert of impending flood danger.

Spreadsheet WATERSHED modeling for nonpoint-source pollution management in a Wisconsin basin

USGS Publications Warehouse

Walker, J.F.; Pickard, S.A.; Sonzogni, W.C.

1989-01-01

Although several sophisticated nonpoint pollution models exist, few are available that are easy to use, cover a variety of conditions, and integrate a wide range of information to allow managers and planners to assess different control strategies. Here, a straightforward pollutant input accounting approach is presented in the form of an existing model (WATERSHED) that has been adapted to run on modern electronic spreadsheets. As an application, WATERSHED is used to assess options to improve the quality of highly eutrophic Delavan Lake in Wisconsin. WATERSHED is flexible in that several techniques, such as the Universal Soil Loss Equation or unit-area loadings, can be used to estimate nonpoint-source inputs. Once the model parameters are determined (and calibrated, if possible), the spreadsheet features can be used to conduct a sensitivity analysis of management options. In the case of Delavan Lake, it was concluded that, although some nonpoint controls were cost-effective, the overall reduction in phosphorus would be insufficient to measurably improve water quality.A straightforward pollutant input accounting approach is presented in the form of an existing model (WATERSHED) that has been adapted to run on modern electronic spreadsheets. As an application, WATERSHED is used to assess options to improve the quality of highly eutrophic Delavan Lake in Wisconsin. WATERSHED is flexible in that several techniques, such as the Universal Soil Loss Equation or unit-area loadings, can be used to estimate nonpoint-source inputs. Once the model parameters are determined (and calibrated, if possible), the spreadsheet features can be used to conduct a sensitivity analysis of management options. In the case of Delavan Lake, it was concluded that, although some nonpoint controls were cost-effective, the overall reduction in phosphorus would be insufficient to measurably improve water quality.

Measurement of Hydrologic Streamflow Metrics and Estimation of Streamflow with Lumped Parameter Models in a Managed Lake System, Sebago Lake, Maine

NASA Astrophysics Data System (ADS)

Reeve, A. S.; Martin, D.; Smith, S. M.

2013-12-01

Surface waters within the Sebago Lake watershed (southern Maine, USA) provide a variety of economically and intrinsically valuable recreational, commercial and environmental services. Different stakeholder groups for the 118 km2 Sebago Lake and surrounding watershed advocate for different lake and watershed management strategies, focusing on the operation of a dam at the outflow from Sebago Lake. While lake level in Sebago Lake has been monitored for over a century, limited data is available on the hydrologic processes that drive lake level and therefore impact how dam operation (and other changes to the region) will influence the hydroperiod of the lake. To fill this information gap several tasks were undertaken including: 1) deploying data logging pressure transducers to continuously monitor stream stage in nine tributaries, 2) measuring stream discharge at these sites to create rating curves for the nine tributaries, and using the resulting continuous discharge records to 3) calibrate lumped parameter computer models based on the GR4J model, modified to include a degree-day snowmelt routine. These lumped parameter models have been integrated with a simple lake water-balance model to estimate lake level and its response to different scenarios including dam management strategies. To date, about three years of stream stage data have been used to estimate stream discharge in all monitored tributaries (data collection is ongoing). Baseflow separation indices (BFI) for 2010 and 2011 using the USGS software PART and the Eckhart digital filter in WHAT range from 0.80-0.86 in the Crooked River and Richmill Outlet,followed by Northwest (0.75) and Muddy (0.53-0.56) Rivers, with the lowest BFI measured in Sticky River (0.41-0.56). The BFI values indicate most streams have significant groundwater (or other storage) inputs. The lumped parameter watershed model has been calibrated for four streams (Nash-Sutcliffe = 0.4 to 0.9), with the other major tributaries containing hydraulic structures that are not included in the lumped parameter model. Calibrated watershed models tend to substantially underestimate the highest streamflows while overestimating low flows. An early June 2012 event caused extremely high flows with discharge in the Crooked River (the most significant tributary) peaking at about 85 m3/day. The lumped parameter model dramatically underestimated this important and anomalous event, but provided a reasonable prediction of flows throughout the rest of 2012. Ongoing work includes incorporating hydraulic structures in the lumped parameter model and using the available data to drive the lake water-balance model that has been prepared.

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.

Effects of temporal and spatial resolution of calibration data on integrated hydrologic water quality model identification

NASA Astrophysics Data System (ADS)

Jiang, Sanyuan; Jomaa, Seifeddine; Büttner, Olaf; Rode, Michael

2014-05-01

Hydrological water quality modeling is increasingly used for investigating runoff and nutrient transport processes as well as watershed management but it is mostly unclear how data availablity determins model identification. In this study, the HYPE (HYdrological Predictions for the Environment) model, which is a process-based, semi-distributed hydrological water quality model, was applied in two different mesoscale catchments (Selke (463 km2) and Weida (99 km2)) located in central Germany to simulate discharge and inorganic nitrogen (IN) transport. PEST and DREAM(ZS) were combined with the HYPE model to conduct parameter calibration and uncertainty analysis. Split-sample test was used for model calibration (1994-1999) and validation (1999-2004). IN concentration and daily IN load were found to be highly correlated with discharge, indicating that IN leaching is mainly controlled by runoff. Both dynamics and balances of water and IN load were well captured with NSE greater than 0.83 during validation period. Multi-objective calibration (calibrating hydrological and water quality parameters simultaneously) was found to outperform step-wise calibration in terms of model robustness. Multi-site calibration was able to improve model performance at internal sites, decrease parameter posterior uncertainty and prediction uncertainty. Nitrogen-process parameters calibrated using continuous daily averages of nitrate-N concentration observations produced better and more robust simulations of IN concentration and load, lower posterior parameter uncertainty and IN concentration prediction uncertainty compared to the calibration against uncontinuous biweekly nitrate-N concentration measurements. Both PEST and DREAM(ZS) are efficient in parameter calibration. However, DREAM(ZS) is more sound in terms of parameter identification and uncertainty analysis than PEST because of its capability to evolve parameter posterior distributions and estimate prediction uncertainty based on global search and Bayesian inference schemes.

Drainage basin control of acid loadings to two Adirondack lakes

NASA Astrophysics Data System (ADS)

Booty, W. G.; Depinto, J. V.; Scheffe, R. D.

1988-07-01

Two adjacent Adirondack Park (New York) calibrated watersheds (Woods Lake and Cranberry Pond), which receive identical atmospheric inputs, generate significantly different unit area of watershed loading rates of acidity to their respective lakes. A watershed acidification model is used to evaluate the watershed parameters which are responsible for the observed differences in acid loadings to the lakes. The greater overall mean depth of overburden on Woods Lake watershed, which supplies a greater buffer capacity as well as a longer retention time of groundwater, appears to be the major factor responsible for the differences.

Managing Watersheds as Couple Human-Natural Systems: A Review of Research Opportunities

NASA Astrophysics Data System (ADS)

Cai, X.

2011-12-01

Many watersheds around the world are impaired with severe social and environmental problems due to heavy anthropogenic stresses. Humans have transformed hydrological and biochemical processes in watersheds from a stationary to non-stationary status through direct (e.g., water withdrawals) and indirect (e.g., altering vegetation and land cover) interferences. It has been found that in many watersheds that socio-economic drivers, which have caused increasingly intensive alteration of natural processes, have even overcome natural variability to become the dominant factor affecting the behavior of watershed systems. Reversing this trend requires an understanding of the drivers of this intensification trajectory, and needs tremendous policy reform and investment. As stressed by several recent National Research Council (NRC) reports, watershed management will pose an enormous challenge in the coming decades. Correspondingly, the focus of research has started an evolution from the management of reservoir, stormwater and aquifer systems to the management of integrated watershed systems, to which policy instruments designed to make more rational economic use of water resources are likely to be applied. To provide a few examples: reservoir operation studies have moved from a local to a watershed scale in order to consider upstream best management practices in soil conservation and erosion control and downstream ecological flow requirements and water rights; watersheds have been modeled as integrated hydrologic-economic systems with multidisciplinary modeling efforts, instead of traditional isolated physical systems. Today's watershed management calls for a re-definition of watersheds from isolated natural systems to coupled human-natural systems (CHNS), which are characterized by the interactions between human activities and natural processes, crossing various spatial and temporal scales within the context of a watershed. The importance of the conceptual innovation has been evidenced by 1) institutional innovation for integrated watershed management; 2) real-world management practices involving multidisciplinary expertise; 3) growing role of economics in systems analysis; 4) enhanced research programs such as the CHNS program and Water, Sustainability and Climate (WSC) program at the US National Science Foundation (NSF). Furthermore, recent scientific and technological developments are expected to accommodate integrated watershed system analysis approaches, such as: 1) increasing availability of distributed digital datasets especially from remote sensing products (e.g. digital watersheds); 2) distributed and semi-distributed watershed hydrologic modeling; 3) enhanced hydroclimatic monitoring and forecast; 4) identified evidences of vulnerability and threshold behavior of watersheds; and 5) continuing improvements in computational and optimization algorithms. Managing watersheds as CHNS will be critical for watershed sustainability, which ensures that human societies will benefit forever from the watershed through development of harmonious relationships between human and natural systems. This presentation will provide a review of the research opportunities that take advantage of the concept of CHNS and associated scientific, technological and institutional innovations/developments.

Assessment of parameter uncertainty in hydrological model using a Markov-Chain-Monte-Carlo-based multilevel-factorial-analysis method

NASA Astrophysics Data System (ADS)

Zhang, Junlong; Li, Yongping; Huang, Guohe; Chen, Xi; Bao, Anming

2016-07-01

Without a realistic assessment of parameter uncertainty, decision makers may encounter difficulties in accurately describing hydrologic processes and assessing relationships between model parameters and watershed characteristics. In this study, a Markov-Chain-Monte-Carlo-based multilevel-factorial-analysis (MCMC-MFA) method is developed, which can not only generate samples of parameters from a well constructed Markov chain and assess parameter uncertainties with straightforward Bayesian inference, but also investigate the individual and interactive effects of multiple parameters on model output through measuring the specific variations of hydrological responses. A case study is conducted for addressing parameter uncertainties in the Kaidu watershed of northwest China. Effects of multiple parameters and their interactions are quantitatively investigated using the MCMC-MFA with a three-level factorial experiment (totally 81 runs). A variance-based sensitivity analysis method is used to validate the results of parameters' effects. Results disclose that (i) soil conservation service runoff curve number for moisture condition II (CN2) and fraction of snow volume corresponding to 50% snow cover (SNO50COV) are the most significant factors to hydrological responses, implying that infiltration-excess overland flow and snow water equivalent represent important water input to the hydrological system of the Kaidu watershed; (ii) saturate hydraulic conductivity (SOL_K) and soil evaporation compensation factor (ESCO) have obvious effects on hydrological responses; this implies that the processes of percolation and evaporation would impact hydrological process in this watershed; (iii) the interactions of ESCO and SNO50COV as well as CN2 and SNO50COV have an obvious effect, implying that snow cover can impact the generation of runoff on land surface and the extraction of soil evaporative demand in lower soil layers. These findings can help enhance the hydrological model's capability for simulating/predicting water resources.

Stepwise sensitivity analysis from qualitative to quantitative: Application to the terrestrial hydrological modeling of a Conjunctive Surface-Subsurface Process (CSSP) land surface model

NASA Astrophysics Data System (ADS)

Gan, Yanjun; Liang, Xin-Zhong; Duan, Qingyun; Choi, Hyun Il; Dai, Yongjiu; Wu, Huan

2015-06-01

An uncertainty quantification framework was employed to examine the sensitivities of 24 model parameters from a newly developed Conjunctive Surface-Subsurface Process (CSSP) land surface model (LSM). The sensitivity analysis (SA) was performed over 18 representative watersheds in the contiguous United States to examine the influence of model parameters in the simulation of terrestrial hydrological processes. Two normalized metrics, relative bias (RB) and Nash-Sutcliffe efficiency (NSE), were adopted to assess the fit between simulated and observed streamflow discharge (SD) and evapotranspiration (ET) for a 14 year period. SA was conducted using a multiobjective two-stage approach, in which the first stage was a qualitative SA using the Latin Hypercube-based One-At-a-Time (LH-OAT) screening, and the second stage was a quantitative SA using the Multivariate Adaptive Regression Splines (MARS)-based Sobol' sensitivity indices. This approach combines the merits of qualitative and quantitative global SA methods, and is effective and efficient for understanding and simplifying large, complex system models. Ten of the 24 parameters were identified as important across different watersheds. The contribution of each parameter to the total response variance was then quantified by Sobol' sensitivity indices. Generally, parameter interactions contribute the most to the response variance of the CSSP, and only 5 out of 24 parameters dominate model behavior. Four photosynthetic and respiratory parameters are shown to be influential to ET, whereas reference depth for saturated hydraulic conductivity is the most influential parameter for SD in most watersheds. Parameter sensitivity patterns mainly depend on hydroclimatic regime, as well as vegetation type and soil texture. This article was corrected on 26 JUN 2015. See the end of the full text for details.

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

NASA Astrophysics Data System (ADS)

WANG, J.

2017-12-01

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

RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15)

NASA Astrophysics Data System (ADS)

Long, A. J.

2015-03-01

The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, spring flow, groundwater level, or solute transport for a measurement point in response to a system input of precipitation, recharge, or solute injection. I introduce the first version of RRAWFLOW available for download and public use and describe additional options. The open-source code is written in the R language and is available at http://sd.water.usgs.gov/projects/RRAWFLOW/RRAWFLOW.html along with an example model of streamflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution, i.e., the unit-hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Several options are included to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications (e.g., estimating missing periods in a hydrologic record). RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

Understanding the effect of watershed characteristic on the runoff using SCS curve number

NASA Astrophysics Data System (ADS)

Damayanti, Frieta; Schneider, Karl

2015-04-01

Runoff modeling is a key component in watershed management. The temporal course and amount of runoff is a complex function of a multitude of parameters such as climate, soil, topography, land use, and water management. Against the background of the current rapid environmental change, which is due to both i) man-made changes (e.g. urban development, land use change, water management) as well as ii) changes in the natural systems (e.g. climate change), understanding and predicting the impacts of these changes upon the runoff is very important and affects the wellbeing of many people living in the watershed. A main tool for predictions is hydrologic models. Particularly process based models are the method of choice to assess the impact of land use and climate change. However, many regions which experience large changes in the watersheds can be described as rather data poor, which limits the applicability of such models. This is particularly also true for the Telomoyo Watershed (545 km2) which is located in southern part of Central Java province. The average annual rainfall of the study area reaches 2971 mm. Irrigated paddy field are the dominating land use (35%), followed by built-up area and dry land agriculture. The only available soil map is the FAO soil digital map of the world, which provides rather general soil information. A field survey accompanied by a lab analysis 65 soil samples of was carried out to provide more detailed soil texture information. The soil texture map is a key input in the SCS method to define hydrological soil groups. In the frame of our study on 'Integrated Analysis on Flood Risk of Telomoyo Watershed in Response to the Climate and Land Use Change' funded by the German Academic Exchange service (DAAD) we analyzed the sensitivity of the modeled runoff upon the choice of the method to estimate the CN values using the SCS-CN method. The goal of this study is to analyze the impact of different data sources on the curve numbers and the estimated runoff. CN values were estimated using the field measurements of soil textures for different combinations of land use and topography. To transfer the local soil texture measurements to the watershed domain a statistical analysis using the frequency distribution of the measured soil textures is applied and used to derive the effective CN value for a given land use, topography and soil texture combination. Since the curve numbers change as a function of parameter combinations, the effect of different methods to estimate the curve number upon the runoff is analyzed and compared to the straight forward method of using the data from the FAO soil map.

Legacy nutrient dynamics and patterns of catchment response under changing land use and management

NASA Astrophysics Data System (ADS)

Attinger, S.; Van, M. K.; Basu, N. B.

2017-12-01

Watersheds are complex heterogeneous systems that store, transform, and release water and nutrients under a broad distribution of both natural and anthropogenic controls. Many current watershed models, from complex numerical models to simpler reservoir-type models, are considered to be well-developed in their ability to predict fluxes of water and nutrients to streams and groundwater. They are generally less adept, however, at capturing watershed storage dynamics. In other words, many current models are run with an assumption of steady-state dynamics, and focus on nutrient flows rather than changes in nutrient stocks within watersheds. Although these commonly used modeling approaches may be able to adequately capture short-term watershed dynamics, they are unable to represent the clear nonlinearities or hysteresis responses observed in watersheds experiencing significant changes in nutrient inputs. To address such a lack, we have, in the present work, developed a parsimonious modeling approach designed to capture long-term catchment responses to spatial and temporal changes in nutrient inputs. In this approach, we conceptualize the catchment as a biogeochemical reactor that is driven by nutrient inputs, characterized internally by both biogeochemical degradation and residence or travel time distributions, resulting in a specific nutrient output. For the model simulations, we define a range of different scenarios to represent real-world changes in land use and management implemented to improve water quality. We then introduce the concept of state-space trajectories to describe system responses to these potential changes in anthropogenic forcings. We also increase model complexity, in a stepwise fashion, by dividing the catchment into multiple biogeochemical reactors, coupled in series or in parallel. Using this approach, we attempt to answer the following questions: (1) What level of model complexity is needed to capture observed system responses? (2) How can we explain different patterns of nonlinearity in watershed nutrient dynamics? And finally, how does the accumulation of nutrient legacies within watersheds impact current and future water quality?

Looking for a relevant potential evapotranspiration model at the watershed scale

NASA Astrophysics Data System (ADS)

Oudin, L.; Hervieu, F.; Michel, C.; Perrin, C.; Anctil, F.; Andréassian, V.

2003-04-01

In this paper, we try to identify the most relevant approach to calculate Potential Evapotranspiration (PET) for use in a daily watershed model, to try to bring an answer to the following question: "how can we use commonly available atmospheric parameters to represent the evaporative demand at the catchment scale?". Hydrologists generally see the Penman model as the ideal model regarding to its good adequacy with lysimeter measurements and its physically-based formulation. However, in real-world engineering situations, where meteorological stations are scarce, hydrologists are often constrained to use other PET formulae with less data requirements or/and long-term average of PET values (the rationale being that PET is an inherently conservative variable). We chose to test 28 commonly used PET models coupled with 4 different daily watershed models. For each test, we compare both PET input options: actual data and long-term average data. The comparison is made in terms of streamflow simulation efficiency, over a large sample of 308 watersheds. The watersheds are located in France, Australia and the United States of America and represent varied climates. Strikingly, we find no systematic improvements of the watershed model efficiencies when using actual PET series instead of long-term averages. This suggests either that watershed models may not conveniently use the climatic information contained in PET values or that formulae are only awkward indicators of the real PET which watershed models need.

Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake.

PubMed

Luo, Chuan; Li, Zhaofu; Li, Hengpeng; Chen, Xiaomin

2015-09-02

The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS) model to predict runoff, total nitrogen (TN) and total phosphorus (TP) loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds.

On the deterministic and stochastic use of hydrologic models

USGS Publications Warehouse

Farmer, William H.; Vogel, Richard M.

2016-01-01

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

Capturing microbial sources distributed in a mixed-use watershed within an integrated environmental modeling workflow

EPA Science Inventory

Many watershed models simulate overland and instream microbial fate and transport, but few provide loading rates on land surfaces and point sources to the waterbody network. This paper describes the underlying equations for microbial loading rates associated with 1) land-applied ...

Capturing microbial sources distributed in a mixed-use watershed within an integrated environmental modeling workflow

USDA-ARS?s Scientific Manuscript database

Many watershed models simulate overland and instream microbial fate and transport, but few provide loading rates on land surfaces and point sources to the waterbody network. This paper describes the underlying equations for microbial loading rates associated with 1) land-applied manure on undevelope...

Estimating Groundwater-Age Distributions Contributing to Streams in the Fractured-Rock Terrain of the Upper Potomac River Basin, USA (Invited)

NASA Astrophysics Data System (ADS)

Sanford, W. E.; Fleming, B.; Pope, J.

2013-12-01

Base flow to individual streams has discharging groundwater with ages that vary widely between values of days to centuries or more. This distribution of ages has important repercussions for the response time of a watershed between change in land-use practices and the discharge of contaminants, such as nitrogen, to streams or coastal waterways. Lumped parameter models are frequently used to predict such watershed responses in shallow aquifers, but these usually assume homogeneous hydraulic properties. In the Chesapeake Bay watershed, however, over half of the terrain is underlain by fractured-rock, where heterogeneous hydraulic properties do not fit standard lumped-parameter model assumptions. In order to better understand the response behavior of a regional fractured-rock terrain, we developed a seven-million node, three-dimensional groundwater model of the Upper Potomac River Basin (~24,000 sq. km) using MODFLOW that includes siliciclastic, carbonate, and metamorphic rocks. Inverse modeling was undertaken to estimate regional values of hydraulic conductivity (K) using 200 water-level measurements in wells, and effective porosity using >100 environmental tracer (CFC-113, SF6, 3H, 3He) measurements from wells, springs and the Potomac River at the basin outlet. Results indicate a very strong depth-dependence of K, with values declining by 4-6 orders of magnitude within 100 m of land surface, with the bulk of the transmissivity being focused in the upper 10 m. This depth-dependent behavior has major implications for the watershed response time, as the base flows have ages that range over four orders of magnitude, as opposed to a shallow homogenous aquifer that usually has an equivalent range of less than two orders of magnitude. A tritium record from 1961-1991 in the Potomac River at the basin outflow can be reproduced by the model using advective transport and a single regional porosity value of 2-3 percent. In addition, the fit to the data can be improved at early and late times by assuming fracture porosity (1-2%) dominates transport at shallow (<10 m depth) depths, and matrix porosity (5-20%) dominates at deeper (>10 m) depths. Histograms of base-flow ages for individual subwatersheds in the basin have mean values of decades, but median values on the order of one year. Base-flow age is also predicted to increase substantially in these subwatersheds in the downstream direction.

A simple daily soil-water balance model for estimating the spatial and temporal distribution of groundwater recharge in temperate humid areas

USGS Publications Warehouse

Dripps, W.R.; Bradbury, K.R.

2007-01-01

Quantifying the spatial and temporal distribution of natural groundwater recharge is usually a prerequisite for effective groundwater modeling and management. As flow models become increasingly utilized for management decisions, there is an increased need for simple, practical methods to delineate recharge zones and quantify recharge rates. Existing models for estimating recharge distributions are data intensive, require extensive parameterization, and take a significant investment of time in order to establish. The Wisconsin Geological and Natural History Survey (WGNHS) has developed a simple daily soil-water balance (SWB) model that uses readily available soil, land cover, topographic, and climatic data in conjunction with a geographic information system (GIS) to estimate the temporal and spatial distribution of groundwater recharge at the watershed scale for temperate humid areas. To demonstrate the methodology and the applicability and performance of the model, two case studies are presented: one for the forested Trout Lake watershed of north central Wisconsin, USA and the other for the urban-agricultural Pheasant Branch Creek watershed of south central Wisconsin, USA. Overall, the SWB model performs well and presents modelers and planners with a practical tool for providing recharge estimates for modeling and water resource planning purposes in humid areas. ?? Springer-Verlag 2007.

Wildcat5 for Windows, a rainfall-runoff hydrograph model: user manual and documentation

Treesearch

R. H. Hawkins; A. Barreto-Munoz

2016-01-01

Wildcat5 for Windows (Wildcat5) is an interactive Windows Excel-based software package designed to assist watershed specialists in analyzing rainfall runoff events to predict peak flow and runoff volumes generated by single-event rainstorms for a variety of watershed soil and vegetation conditions. Model inputs are: (1) rainstorm characteristics, (2) parameters related...

Documentation of Computer Program INFIL3.0 - A Distributed-Parameter Watershed Model to Estimate Net Infiltration Below the Root Zone

USGS Publications Warehouse

,

2008-01-01

This report documents the computer program INFIL3.0, which is a grid-based, distributed-parameter, deterministic water-balance watershed model that calculates the temporal and spatial distribution of daily net infiltration of water across the lower boundary of the root zone. The bottom of the root zone is the estimated maximum depth below ground surface affected by evapotranspiration. In many field applications, net infiltration below the bottom of the root zone can be assumed to equal net recharge to an underlying water-table aquifer. The daily water balance simulated by INFIL3.0 includes precipitation as either rain or snow; snowfall accumulation, sublimation, and snowmelt; infiltration into the root zone; evapotranspiration from the root zone; drainage and water-content redistribution within the root-zone profile; surface-water runoff from, and run-on to, adjacent grid cells; and net infiltration across the bottom of the root zone. The water-balance model uses daily climate records of precipitation and air temperature and a spatially distributed representation of drainage-basin characteristics defined by topography, geology, soils, and vegetation to simulate daily net infiltration at all locations, including stream channels with intermittent streamflow in response to runoff from rain and snowmelt. The model does not simulate streamflow originating as ground-water discharge. Drainage-basin characteristics are represented in the model by a set of spatially distributed input variables uniquely assigned to each grid cell of a model grid. The report provides a description of the conceptual model of net infiltration on which the INFIL3.0 computer code is based and a detailed discussion of the methods by which INFIL3.0 simulates the net-infiltration process. The report also includes instructions for preparing input files necessary for an INFIL3.0 simulation, a description of the output files that are created as part of an INFIL3.0 simulation, and a sample problem that illustrates application of the code to a field setting. Brief descriptions of the main program routine and of each of the modules and subroutines of the INFIL3.0 code, as well as definitions of the variables used in each subroutine, are provided in an appendix.

A pollution fate and transport model application in a semi-arid region: Is some number better than no number?

PubMed

Özcan, Zeynep; Başkan, Oğuz; Düzgün, H Şebnem; Kentel, Elçin; Alp, Emre

2017-10-01

Fate and transport models are powerful tools that aid authorities in making unbiased decisions for developing sustainable management strategies. Application of pollution fate and transport models in semi-arid regions has been challenging because of unique hydrological characteristics and limited data availability. Significant temporal and spatial variability in rainfall events, complex interactions between soil, vegetation and topography, and limited water quality and hydrological data due to insufficient monitoring network make it a difficult task to develop reliable models in semi-arid regions. The performances of these models govern the final use of the outcomes such as policy implementation, screening, economical analysis, etc. In this study, a deterministic distributed fate and transport model, SWAT, is applied in Lake Mogan Watershed, a semi-arid region dominated by dry agricultural practices, to estimate nutrient loads and to develop the water budget of the watershed. To minimize the discrepancy due to limited availability of historical water quality data extensive efforts were placed in collecting site-specific data for model inputs such as soil properties, agricultural practice information and land use. Moreover, calibration parameter ranges suggested in the literature are utilized during calibration in order to obtain more realistic representation of Lake Mogan Watershed in the model. Model performance is evaluated using comparisons of the measured data with 95%CI for the simulated data and comparison of unit pollution load estimations with those provided in the literature for similar catchments, in addition to commonly used evaluation criteria such as Nash-Sutcliffe simulation efficiency, coefficient of determination and percent bias. These evaluations demonstrated that even though the model prediction power is not high according to the commonly used model performance criteria, the calibrated model may provide useful information in the comparison of the effects of different management practices on diffuse pollution and water quality in Lake Mogan Watershed. Copyright © 2017 Elsevier B.V. All rights reserved.

Event-scale power law recession analysis: quantifying methodological uncertainty

NASA Astrophysics Data System (ADS)

Dralle, David N.; Karst, Nathaniel J.; Charalampous, Kyriakos; Veenstra, Andrew; Thompson, Sally E.

2017-01-01

The study of single streamflow recession events is receiving increasing attention following the presentation of novel theoretical explanations for the emergence of power law forms of the recession relationship, and drivers of its variability. Individually characterizing streamflow recessions often involves describing the similarities and differences between model parameters fitted to each recession time series. Significant methodological sensitivity has been identified in the fitting and parameterization of models that describe populations of many recessions, but the dependence of estimated model parameters on methodological choices has not been evaluated for event-by-event forms of analysis. Here, we use daily streamflow data from 16 catchments in northern California and southern Oregon to investigate how combinations of commonly used streamflow recession definitions and fitting techniques impact parameter estimates of a widely used power law recession model. Results are relevant to watersheds that are relatively steep, forested, and rain-dominated. The highly seasonal mediterranean climate of northern California and southern Oregon ensures study catchments explore a wide range of recession behaviors and wetness states, ideal for a sensitivity analysis. In such catchments, we show the following: (i) methodological decisions, including ones that have received little attention in the literature, can impact parameter value estimates and model goodness of fit; (ii) the central tendencies of event-scale recession parameter probability distributions are largely robust to methodological choices, in the sense that differing methods rank catchments similarly according to the medians of these distributions; (iii) recession parameter distributions are method-dependent, but roughly catchment-independent, such that changing the choices made about a particular method affects a given parameter in similar ways across most catchments; and (iv) the observed correlative relationship between the power-law recession scale parameter and catchment antecedent wetness varies depending on recession definition and fitting choices. Considering study results, we recommend a combination of four key methodological decisions to maximize the quality of fitted recession curves, and to minimize bias in the related populations of fitted recession parameters.

Data analysis and hydrological modelling of frozen ground, shallow groundwater formation and river flow co-evolution at small watersheds of Russia in continuous, discontinuous permafrost and the zone of seasonal ground freezing

NASA Astrophysics Data System (ADS)

Lebedeva, Luidmila; Semenova, Olga

2015-04-01

Frozen ground distribution and its properties control the presence of aquifuge and aquifers. Correct representation of interactions between infiltrating water, ground ice, permafrost or seasonal freezing table and river flow is challenging for hydrological modelling in cold regions. Observational data of ground water levels, thawing depths in different landscapes or topographical units and meteorological information with high temporal and spatial resolution are required to analyze seasonal and interannual evolution of groundwater in active layer and its linkage to river flow. Such data are extremely rare in vast and remote regions of Russia. There are few historical datasets inherited from former USSR containing unique collection of long-term daily observations of water fluxes, frozen ground characteristics and groundwater levels. The data from three water balance stations were employed in our study with overall goal to analyze co-evolution of thawing layer, shallow groundwater and river flow by data processing and process-based modelling. Three instrumented small watersheds are situated in continuous, discontinuous permafrost zones and at the territory with seasonally frozen ground. They present different climates, landscapes and geology. The Kolyma water-balance station is located in mountainous region of continuous permafrost in North-Eastern Russia. The watershed area of 22 km2 is covered by bare rocks, mountain tundra, sparse larch forest and wet larch forest depending on slope aspect and inclination. The Bomnak water-balance station (22 km2) is situated in discontinuous permafrost zone in upper part of the Amur River basin and characterized by unmerged permafrost. Dominant landscapes are birch forest and bogs. The Pribaltiyskaya water-balance station (40 km2) located in Latvia is characterized by seasonally frozen ground and is covered by mixed forest and arable land. Process-based Hydrograph model was employed in the study. The model was developed specifically for cold regions. It describes all essential processes of land hydrological cycle including detailed algorithm of water and heat dynamics in soil accounting for water phase change. The model parameters relate to basin characteristics and could be assessed in the field. It allows avoiding parameters calibration and transferring model parameterization schemes to ungauged basins in similar conditions. The model was applied and tested against internal states of watersheds (snow, soil thawing/freezing, etc.) and runoff. Different role of frozen ground in formation of shallow groundwater and river flow in continuous, discontinuous and non-permafrost area is highlighted by comparative analysis of observations and simulations in three studied basins. The changes of fractional input of surface and subsurface components into river flow during warm seasons were assessed for each watershed. We concluded that verified hydrological model with meaningful parameters that adequately describe river flow formation and internal hydrological processes and ground freezing/thawing in the catchment could be used in scenario simulations, future predictions and transferring the results between scales.

Stochastic Watershed Models for Risk Based Decision Making

NASA Astrophysics Data System (ADS)

Vogel, R. M.

2017-12-01

Over half a century ago, the Harvard Water Program introduced the field of operational or synthetic hydrology providing stochastic streamflow models (SSMs), which could generate ensembles of synthetic streamflow traces useful for hydrologic risk management. The application of SSMs, based on streamflow observations alone, revolutionized water resources planning activities, yet has fallen out of favor due, in part, to their inability to account for the now nearly ubiquitous anthropogenic influences on streamflow. This commentary advances the modern equivalent of SSMs, termed `stochastic watershed models' (SWMs) useful as input to nearly all modern risk based water resource decision making approaches. SWMs are deterministic watershed models implemented using stochastic meteorological series, model parameters and model errors, to generate ensembles of streamflow traces that represent the variability in possible future streamflows. SWMs combine deterministic watershed models, which are ideally suited to accounting for anthropogenic influences, with recent developments in uncertainty analysis and principles of stochastic simulation

Interpretation of heavy rainfall spatial distribution in mountain watersheds by copula functions

NASA Astrophysics Data System (ADS)

Grossi, Giovanna; Balistrocchi, Matteo

2016-04-01

The spatial distribution of heavy rainfalls can strongly influence flood dynamics in mountain watersheds, depending on their geomorphologic features, namely orography, slope, land covers and soil types. Unfortunately, the direct observation of rainfall fields by meteorological radar is very difficult in this situation, so that interpolation of rain gauge observations or downscaling of meteorological predictions must be adopted to derive spatial rainfall distributions. To do so, various stochastic and physically based approaches are already available, even though the first one is the most familiar in hydrology. Indeed, Kriging interpolation procedures represent very popular techniques to face this problem by means of a stochastic approach. A certain number of restrictive assumptions and parameter uncertainties however affects Kriging. Many alternative formulations and additional procedures were therefore developed during the last decades. More recently, copula functions (Joe, 1997; Nelsen, 2006; Salvadori et al. 2007) were suggested to provide a more straightforward solution to carry out spatial interpolations of hydrologic variables (Bardossy & Pegram; 2009). Main advantages lie in the possibility of i) assessing the dependence structure relating to rainfall variables independently of marginal distributions, ii) expressing the association degree through rank correlation coefficients, iii) implementing marginal distributions and copula functions belonging to different models to develop complex joint distribution functions, iv) verifying the model reliability by effective statistical tests (Genest et al., 2009). A suitable case study to verify these potentialities is provided by the Taro River, a right-bank tributary of the Po River (northern Italy), whose contributing area amounts to about 2˙000 km2. The mountain catchment area is divided into two similar watersheds, so that spatial distribution is crucial in extreme flood event generation. A quite well diffused hydro-meteorological network, consisting of about 30 rain gauges and 10 hydrometers, monitors this medium-size watershed. A decade of rainfall-runoff event observations are available. Severe rainfall events were identified with reference to a main raingauge station, by using an interevent time definition and a depth threshold. Rainfall depths were thus derived and the spatial variability of their association degree was represented by using the Kendall coefficient. A unique copula model based on Gumbel copula function was finally found to be suitable to represent the dependence structure relating to rainfall depths observed in distinct raingauges. Bardossy A., Pegram G. (2009), Copula based multisite model for daily precipitation simulation, Hydrol. Earth Syst. Sci., 13, 2299-2314. Genest C., Rémilland B., Beaudoin D. (2009), Goodness-of-fit tests for copulas: a review and a power study, Insur. Math. Econ., 44(2), 199-213. Joe H. (1997), Multivariate models and dependence concepts, Chapman and Hall, London. Nelsen R. B. (2006), An introduction to copulas, second ed., Springer, New York. Salvadori G., De Michele C., Kottegoda N. T., Rosso R. (2007), Extremes in nature: an approach using copulas, Springer, Dordrecht, The Nederlands.

Multi-Dimensional Shallow Landslide Stability Analysis Suitable for Application at the Watershed Scale

NASA Astrophysics Data System (ADS)

Milledge, D.; Bellugi, D.; McKean, J. A.; Dietrich, W.

2012-12-01

The infinite slope model is the basis for almost all watershed scale slope stability models. However, it assumes that a potential landslide is infinitely long and wide. As a result, it cannot represent resistance at the margins of a potential landslide (e.g. from lateral roots), and is unable to predict the size of a potential landslide. Existing three-dimensional models generally require computationally expensive numerical solutions and have previously been applied only at the hillslope scale. Here we derive an alternative analytical treatment that accounts for lateral resistance by representing the forces acting on each margin of an unstable block. We apply 'at rest' earth pressure on the lateral sides, and 'active' and 'passive' pressure using a log-spiral method on the upslope and downslope margins. We represent root reinforcement on each margin assuming that root cohesion is an exponential function of soil depth. We benchmark this treatment against other more complete approaches (Finite Element (FE) and closed form solutions) and find that our model: 1) converges on the infinite slope predictions as length / depth and width / depth ratios become large; 2) agrees with the predictions from state-of-the-art FE models to within +/- 30% error, for the specific cases in which these can be applied. We then test our model's ability to predict failure of an actual (mapped) landslide where the relevant parameters are relatively well constrained. We find that our model predicts failure at the observed location with a nearly identical shape and predicts that larger or smaller shapes conformal to the observed shape are indeed more stable. Finally, we perform a sensitivity analysis using our model to show that lateral reinforcement sets a minimum landslide size, while the additional strength at the downslope boundary means that the optimum shape for a given size is longer in a downslope direction. However, reinforcement effects cannot fully explain the size or shape distributions of observed landslides, highlighting the importance of spatial patterns of key parameters (e.g. pore water pressure) and motivating the model's watershed scale application. This watershed scale application requires an efficient method to find the least stable shapes among an almost infinite set. However, when applied in this context, it allows a more complete examination of the controls on landslide size, shape and location.

Spatial discretization of large watersheds and its influence on the estimation of hillslope sediment yield

USDA-ARS?s Scientific Manuscript database

The combined use of water erosion models and geographic information systems (GIS) has facilitated soil loss estimation at the watershed scale. Tools such as the Geo-spatial interface for the Water Erosion Prediction Project (GeoWEPP) model provide a convenient spatially distributed soil loss estimat...

Optimal land use management for soil erosion control by using an interval-parameter fuzzy two-stage stochastic programming approach.

PubMed

Han, Jing-Cheng; Huang, Guo-He; Zhang, Hua; Li, Zhong

2013-09-01

Soil erosion is one of the most serious environmental and public health problems, and such land degradation can be effectively mitigated through performing land use transitions across a watershed. Optimal land use management can thus provide a way to reduce soil erosion while achieving the maximum net benefit. However, optimized land use allocation schemes are not always successful since uncertainties pertaining to soil erosion control are not well presented. This study applied an interval-parameter fuzzy two-stage stochastic programming approach to generate optimal land use planning strategies for soil erosion control based on an inexact optimization framework, in which various uncertainties were reflected. The modeling approach can incorporate predefined soil erosion control policies, and address inherent system uncertainties expressed as discrete intervals, fuzzy sets, and probability distributions. The developed model was demonstrated through a case study in the Xiangxi River watershed, China's Three Gorges Reservoir region. Land use transformations were employed as decision variables, and based on these, the land use change dynamics were yielded for a 15-year planning horizon. Finally, the maximum net economic benefit with an interval value of [1.197, 6.311] × 10(9) $ was obtained as well as corresponding land use allocations in the three planning periods. Also, the resulting soil erosion amount was found to be decreased and controlled at a tolerable level over the watershed. Thus, results confirm that the developed model is a useful tool for implementing land use management as not only does it allow local decision makers to optimize land use allocation, but can also help to answer how to accomplish land use changes.

Optimal Land Use Management for Soil Erosion Control by Using an Interval-Parameter Fuzzy Two-Stage Stochastic Programming Approach

NASA Astrophysics Data System (ADS)

Han, Jing-Cheng; Huang, Guo-He; Zhang, Hua; Li, Zhong

2013-09-01

Soil erosion is one of the most serious environmental and public health problems, and such land degradation can be effectively mitigated through performing land use transitions across a watershed. Optimal land use management can thus provide a way to reduce soil erosion while achieving the maximum net benefit. However, optimized land use allocation schemes are not always successful since uncertainties pertaining to soil erosion control are not well presented. This study applied an interval-parameter fuzzy two-stage stochastic programming approach to generate optimal land use planning strategies for soil erosion control based on an inexact optimization framework, in which various uncertainties were reflected. The modeling approach can incorporate predefined soil erosion control policies, and address inherent system uncertainties expressed as discrete intervals, fuzzy sets, and probability distributions. The developed model was demonstrated through a case study in the Xiangxi River watershed, China's Three Gorges Reservoir region. Land use transformations were employed as decision variables, and based on these, the land use change dynamics were yielded for a 15-year planning horizon. Finally, the maximum net economic benefit with an interval value of [1.197, 6.311] × 109 was obtained as well as corresponding land use allocations in the three planning periods. Also, the resulting soil erosion amount was found to be decreased and controlled at a tolerable level over the watershed. Thus, results confirm that the developed model is a useful tool for implementing land use management as not only does it allow local decision makers to optimize land use allocation, but can also help to answer how to accomplish land use changes.

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

Treesearch

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

2010-01-01

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

Modeled effects of climate change and plant invasion on watershed function across a steep tropical rainfall gradient

Treesearch

Ayron M. Strauch; Christian P. Giardina; Richard A. MacKenzie; Chris Heider; Tom W. Giambelluca; Ed Salminen; Gregory L. Bruland

2017-01-01

Climate change is anticipated to affect freshwater resources, but baseline data on the functioning of tropical watersheds is lacking, limiting efforts that seek to predict how watershed processes, water supply, and streamflow respond to anticipated changes in climate and vegetation change, and to management. To address this data gap, we applied the distributed...

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

NASA Astrophysics Data System (ADS)

Harman, C. J.

2014-12-01

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

A coupled modeling framework for sustainable watershed management in transboundary river basins

NASA Astrophysics Data System (ADS)

Furqan Khan, Hassaan; Yang, Y. C. Ethan; Xie, Hua; Ringler, Claudia

2017-12-01

There is a growing recognition among water resource managers that sustainable watershed management needs to not only account for the diverse ways humans benefit from the environment, but also incorporate the impact of human actions on the natural system. Coupled natural-human system modeling through explicit modeling of both natural and human behavior can help reveal the reciprocal interactions and co-evolution of the natural and human systems. This study develops a spatially scalable, generalized agent-based modeling (ABM) framework consisting of a process-based semi-distributed hydrologic model (SWAT) and a decentralized water system model to simulate the impacts of water resource management decisions that affect the food-water-energy-environment (FWEE) nexus at a watershed scale. Agents within a river basin are geographically delineated based on both political and watershed boundaries and represent key stakeholders of ecosystem services. Agents decide about the priority across three primary water uses: food production, hydropower generation and ecosystem health within their geographical domains. Agents interact with the environment (streamflow) through the SWAT model and interact with other agents through a parameter representing willingness to cooperate. The innovative two-way coupling between the water system model and SWAT enables this framework to fully explore the feedback of human decisions on the environmental dynamics and vice versa. To support non-technical stakeholder interactions, a web-based user interface has been developed that allows for role-play and participatory modeling. The generalized ABM framework is also tested in two key transboundary river basins, the Mekong River basin in Southeast Asia and the Niger River basin in West Africa, where water uses for ecosystem health compete with growing human demands on food and energy resources. We present modeling results for crop production, energy generation and violation of eco-hydrological indicators at both the agent and basin-wide levels to shed light on holistic FWEE management policies in these two basins.

Diagnostic evaluation of distributed physically based model at the REW scale (THREW) using rainfall-runoff event analysis

NASA Astrophysics Data System (ADS)

Tian, F.; Sivapalan, M.; Li, H.; Hu, H.

2007-12-01

The importance of diagnostic analysis of hydrological models is increasingly recognized by the scientific community (M. Sivapalan, et al., 2003; H. V. Gupta, et al., 2007). Model diagnosis refers to model structures and parameters being identified not only by statistical comparison of system state variables and outputs but also by process understanding in a specific watershed. Process understanding can be gained by the analysis of observational data and model results at the specific watershed as well as through regionalization. Although remote sensing technology can provide valuable data about the inputs, state variables, and outputs of the hydrological system, observational rainfall-runoff data still constitute the most accurate, reliable, direct, and thus a basic component of hydrology related database. One critical question in model diagnostic analysis is, therefore, what signature characteristic can we extract from rainfall and runoff data. To this date only a few studies have focused on this question, such as Merz et al. (2006) and Lana-Renault et al. (2007), still none of these studies related event analysis with model diagnosis in an explicit, rigorous, and systematic manner. Our work focuses on the identification of the dominant runoff generation mechanisms from event analysis of rainfall-runoff data, including correlation analysis and analysis of timing pattern. The correlation analysis involves the identification of the complex relationship among rainfall depth, intensity, runoff coefficient, and antecedent conditions, and the timing pattern analysis aims to identify the clustering pattern of runoff events in relation to the patterns of rainfall events. Our diagnostic analysis illustrates the changing pattern of runoff generation mechanisms in the DMIP2 test watersheds located in Oklahoma region, which is also well recognized by numerical simulations based on TsingHua Representative Elementary Watershed (THREW) model. The result suggests the usefulness of rainfall-runoff event analysis for model development as well as model diagnostics.

The effect of catchment discretization on rainfall-runoff model predictions

NASA Astrophysics Data System (ADS)

Goodrich, D.; Grayson, R.; Willgoose, G.; Palacios-Valez, O.; Bloschl, G.

2003-04-01

Application of distributed hydrologic watershed models fundamentally requires watershed partitioning or discretization. In addition to partitioning the watershed into modelling elements, these elements typically represent a further abstraction of the actual watershed surface and its relevant hydrologic properties. A critical issue that must be addressed by any user of these models prior to their application is definition of an acceptable level and type of watershed discretization or geometric model complexity. A quantitative methodology to define a level of geometric model complexity commensurate with a specified level of model performance is developed for watershed rainfall-runoff modelling. The methodology is tested on four subcatchments which cover a range of watershed scales of over three orders of magnitude in the USDA-ARS Walnut Gulch Experimental Watershed in Southeastern Arizona. It was found that distortion of the hydraulic roughness can compensate for a lower level of discretization (fewer channels) to a point. Beyond this point, hydraulic roughness distortion cannot compensate for the topographic distortion of representing the watershed by fewer elements (e.g. less complex channel network). Similarly, differences in representation of topography by different model or digital elevation model (DEM) types (e.g. Triangular Irregular Elements - TINs; contour lines; and regular grid DEMs) also result in difference in runoff routing responses that can be largely compensated for by a distortion in hydraulic roughness or path length. To put the effect of these discretization models in context it will be shown that relatively small non-compliance with Peclet number restrictions on timestep size can overwhelm the relatively modest differences resulting from the type of representation of topography.

Watershed erosion modeling using the probability of sediment connectivity in a gently rolling system

NASA Astrophysics Data System (ADS)

Mahoney, David Tyler; Fox, James Forrest; Al Aamery, Nabil

2018-06-01

Sediment connectivity has been shown in recent years to explain how the watershed configuration controls sediment transport. However, we find no studies develop a watershed erosion modeling framework based on sediment connectivity, and few, if any, studies have quantified sediment connectivity for gently rolling systems. We develop a new predictive sediment connectivity model that relies on the intersecting probabilities for sediment supply, detachment, transport, and buffers to sediment transport, which is integrated in a watershed erosion model framework. The model predicts sediment flux temporally and spatially across a watershed using field reconnaissance results, a high-resolution digital elevation models, a hydrologic model, and shear-based erosion formulae. Model results validate the capability of the model to predict erosion pathways causing sediment connectivity. More notably, disconnectivity dominates the gently rolling watershed across all morphologic levels of the uplands, including, microtopography from low energy undulating surfaces across the landscape, swales and gullies only active in the highest events, karst sinkholes that disconnect drainage areas, and floodplains that de-couple the hillslopes from the stream corridor. Results show that sediment connectivity is predicted for about 2% or more the watershed's area 37 days of the year, with the remaining days showing very little or no connectivity. Only 12.8 ± 0.7% of the gently rolling watershed shows sediment connectivity on the wettest day of the study year. Results also highlight the importance of urban/suburban sediment pathways in gently rolling watersheds, and dynamic and longitudinal distributions of sediment connectivity might be further investigated in future work. We suggest the method herein provides the modeler with an added tool to account for sediment transport criteria and has the potential to reduce computational costs in watershed erosion modeling.

Potential climate-induced runoff changes and associated uncertainty in four Pacific Northwest estuaries

USGS Publications Warehouse

Steele, Madeline O.; Chang, Heejun; Reusser, Deborah A.; Brown, Cheryl A.; Jung, Il-Won

2012-01-01

As part of a larger investigation into potential effects of climate change on estuarine habitats in the Pacific Northwest, we estimated changes in freshwater inputs into four estuaries: Coquille River estuary, South Slough of Coos Bay, and Yaquina Bay in Oregon, and Willapa Bay in Washington. We used the U.S. Geological Survey's Precipitation Runoff Modeling System (PRMS) to model watershed hydrological processes under current and future climatic conditions. This model allowed us to explore possible shifts in coastal hydrologic regimes at a range of spatial scales. All modeled watersheds are located in rainfall-dominated coastal areas with relatively insignificant base flow inputs, and their areas vary from 74.3 to 2,747.6 square kilometers. The watersheds also vary in mean elevation, ranging from 147 meters in the Willapa to 1,179 meters in the Coquille. The latitudes of watershed centroids range from 43.037 degrees north latitude in the Coquille River estuary to 46.629 degrees north latitude in Willapa Bay. We calibrated model parameters using historical climate grid data downscaled to one-sixteenth of a degree by the Climate Impacts Group, and historical runoff from sub-watersheds or neighboring watersheds. Nash Sutcliffe efficiency values for daily flows in calibration sub-watersheds ranged from 0.71 to 0.89. After calibration, we forced the PRMS models with four North American Regional Climate Change Assessment Program climate models: Canadian Regional Climate Model-(National Center for Atmospheric Research) Community Climate System Model version 3, Canadian Regional Climate Model-Canadian Global Climate Model version 3, Hadley Regional Model version 3-Hadley Centre Climate Model version 3, and Regional Climate Model-Canadian Global Climate Model version 3. These are global climate models (GCMs) downscaled with regional climate models that are embedded within the GCMs, and all use the A2 carbon emission scenario developed by the Intergovernmental Panel on Climate Change. With these climate-forcing outputs, we derived the mean change in flow from the period encompassing the 1980s (1971-1995) to the period encompassing the 2050s (2041-2065). Specifically, we calculated percent change in mean monthly flow rate, coefficient of variation, top 5 percent of flow, and 7-day low flow. The trends with the most agreement among climate models and among watersheds were increases in autumn mean monthly flows, especially in October and November, decreases in summer monthly mean flow, and increases in the top 5 percent of flow. We also estimated variance in PRMS outputs owing to parameter uncertainty and the selection of climate model using Latin hypercube sampling. This analysis showed that PRMS low-flow simulations are more uncertain than medium or high flow simulations, and that variation among climate models was a larger source of uncertainty than the hydrological model parameters. These results improve our understanding of how climate change may affect the saltwater-freshwater balance in Pacific Northwest estuaries, with implications for their sensitive ecosystems.

Analysis of Artificial Neural Network in Erosion Modeling: A Case Study of Serang Watershed

NASA Astrophysics Data System (ADS)

Arif, N.; Danoedoro, P.; Hartono

2017-12-01

Erosion modeling is an important measuring tool for both land users and decision makers to evaluate land cultivation and thus it is necessary to have a model to represent the actual reality. Erosion models are a complex model because of uncertainty data with different sources and processing procedures. Artificial neural networks can be relied on for complex and non-linear data processing such as erosion data. The main difficulty in artificial neural network training is the determination of the value of each network input parameters, i.e. hidden layer, momentum, learning rate, momentum, and RMS. This study tested the capability of artificial neural network application in the prediction of erosion risk with some input parameters through multiple simulations to get good classification results. The model was implemented in Serang Watershed, Kulonprogo, Yogyakarta which is one of the critical potential watersheds in Indonesia. The simulation results showed the number of iterations that gave a significant effect on the accuracy compared to other parameters. A small number of iterations can produce good accuracy if the combination of other parameters was right. In this case, one hidden layer was sufficient to produce good accuracy. The highest training accuracy achieved in this study was 99.32%, occurred in ANN 14 simulation with combination of network input parameters of 1 HL; LR 0.01; M 0.5; RMS 0.0001, and the number of iterations of 15000. The ANN training accuracy was not influenced by the number of channels, namely input dataset (erosion factors) as well as data dimensions, rather it was determined by changes in network parameters.

Users manual for an expert system (HSPEXP) for calibration of the hydrological simulation program; Fortran

USGS Publications Warehouse

Lumb, A.M.; McCammon, R.B.; Kittle, J.L.

1994-01-01

Expert system software was developed to assist less experienced modelers with calibration of a watershed model and to facilitate the interaction between the modeler and the modeling process not provided by mathematical optimization. A prototype was developed with artificial intelligence software tools, a knowledge engineer, and two domain experts. The manual procedures used by the domain experts were identified and the prototype was then coded by the knowledge engineer. The expert system consists of a set of hierarchical rules designed to guide the calibration of the model through a systematic evaluation of model parameters. When the prototype was completed and tested, it was rewritten for portability and operational use and was named HSPEXP. The watershed model Hydrological Simulation Program--Fortran (HSPF) is used in the expert system. This report is the users manual for HSPEXP and contains a discussion of the concepts and detailed steps and examples for using the software. The system has been tested on watersheds in the States of Washington and Maryland, and the system correctly identified the model parameters to be adjusted and the adjustments led to improved calibration.

An Integrated Risk Management Model for Source Water Protection Areas

PubMed Central

Chiueh, Pei-Te; Shang, Wei-Ting; Lo, Shang-Lien

2012-01-01

Watersheds are recognized as the most effective management unit for the protection of water resources. For surface water supplies that use water from upstream watersheds, evaluating threats to water quality and implementing a watershed management plan are crucial for the maintenance of drinking water safe for humans. The aim of this article is to establish a risk assessment model that provides basic information for identifying critical pollutants and areas at high risk for degraded water quality. In this study, a quantitative risk model that uses hazard quotients for each water quality parameter was combined with a qualitative risk model that uses the relative risk level of potential pollution events in order to characterize the current condition and potential risk of watersheds providing drinking water. In a case study of Taipei Source Water Area in northern Taiwan, total coliforms and total phosphorus were the top two pollutants of concern. Intensive tea-growing and recreational activities around the riparian zone may contribute the greatest pollution to the watershed. Our risk assessment tool may be enhanced by developing, recording, and updating information on pollution sources in the water supply watersheds. Moreover, management authorities could use the resultant information to create watershed risk management plans. PMID:23202770

Spatial Distribution of Hydrologic Ecosystem Service Estimates: Comparing Two Models

NASA Astrophysics Data System (ADS)

Dennedy-Frank, P. J.; Ghile, Y.; Gorelick, S.; Logsdon, R. A.; Chaubey, I.; Ziv, G.

2014-12-01

We compare estimates of the spatial distribution of water quantity provided (annual water yield) from two ecohydrologic models: the widely-used Soil and Water Assessment Tool (SWAT) and the much simpler water models from the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) toolbox. These two models differ significantly in terms of complexity, timescale of operation, effort, and data required for calibration, and so are often used in different management contexts. We compare two study sites in the US: the Wildcat Creek Watershed (2083 km2) in Indiana, a largely agricultural watershed in a cold aseasonal climate, and the Upper Upatoi Creek Watershed (876 km2) in Georgia, a mostly forested watershed in a temperate aseasonal climate. We evaluate (1) quantitative estimates of water yield to explore how well each model represents this process, and (2) ranked estimates of water yield to indicate how useful the models are for management purposes where other social and financial factors may play significant roles. The SWAT and InVEST models provide very similar estimates of the water yield of individual subbasins in the Wildcat Creek Watershed (Pearson r = 0.92, slope = 0.89), and a similar ranking of the relative water yield of those subbasins (Spearman r = 0.86). However, the two models provide relatively different estimates of the water yield of individual subbasins in the Upper Upatoi Watershed (Pearson r = 0.25, slope = 0.14), and very different ranking of the relative water yield of those subbasins (Spearman r = -0.10). The Upper Upatoi watershed has a significant baseflow contribution due to its sandy, well-drained soils. InVEST's simple seasonality terms, which assume no change in storage over the time of the model run, may not accurately estimate water yield processes when baseflow provides such a strong contribution. Our results suggest that InVEST users take care in situations where storage changes are significant.

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

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

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

PubMed Central

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

2014-01-01

A watershed hydrological model, hydrological simulation program-Fortran (HSPF), was applied to simulate the spatial and temporal variation of hydrological processes in the Jiaoyi watershed of Huaihe River Basin, the heaviest shortage of water resources and polluted area in China. The model was calibrated using the years 2001–2004 and validated with data from 2005 to 2006. Calibration and validation results showed that the model generally simulated mean monthly and daily runoff precisely due to the close matching hydrographs between simulated and observed runoff, as well as the excellent evaluation indicators such as Nash-Sutcliffe efficiency (NSE), coefficient of correlation (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

Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake

PubMed Central

Luo, Chuan; Li, Zhaofu; Li, Hengpeng; Chen, Xiaomin

2015-01-01

The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS) model to predict runoff, total nitrogen (TN) and total phosphorus (TP) loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds. PMID:26364642

Representation of regional urban development conditions using a watershed-based gradient study design

USGS Publications Warehouse

Terziotti, Silvia; McMahon, Gerard; Bell, Amanda H.

2012-01-01

As part of the U.S. Geological Survey National Water-Quality Assessment Program, the effects of urbanization on stream ecosystems (EUSE) have been intensively investigated in nine metropolitan areas in the United States, including Boston, Massachusetts; Atlanta, Georgia; Birmingham, Alabama; Raleigh, North Carolina; Salt Lake City, Utah; Denver, Colorado; Dallas–Fort Worth, Texas; Portland, Oregon; and Milwaukee–Green Bay, Wisconsin. Each of the EUSE study area watersheds was associated with one ecological region of the United States. This report evaluates whether each metropolitan area can be generalized across the ecological regions (ecoregions) within which the EUSE study watersheds are located. Seven characteristics of the EUSE watersheds that affect stream ecosystems were examined to determine the similarities in the same seven characteristics of the watersheds in the entire ecoregion. Land cover (percentage developed, forest and shrubland, and herbaceous and cultivated classes), average annual temperature, average annual precipitation, average surface elevation, and average percentage slope were selected as human-influenced, climate, and topography characteristics. Three findings emerged from this comparison that have implications for the use of EUSE data in models used to predict stream ecosystem condition. One is that the predominant or "background" land-cover type (either forested or agricultural land) in each ecoregion also is the predominant land-cover type within the associated EUSE study watersheds. The second finding is that in all EUSE study areas, the watersheds account for the range of developed land conditions that exist in the corresponding ecoregion watersheds. However, six of the nine EUSE study area watersheds have significantly different distributions of developed land from the ecoregion watersheds. Finally, in seven of the nine EUSE/ecoregion comparisons, the distributions of the values of climate variables in the EUSE watersheds are different from the distributions for watersheds in the corresponding ecoregions.

The Rangeland Hydrology and Erosion Model

NASA Astrophysics Data System (ADS)

Nearing, M. A.

2016-12-01

The Rangeland Hydrology and Erosion Model (RHEM) is a process-based model that was designed to address rangelands conditions. RHEM is designed for government agencies, land managers and conservationists who need sound, science-based technology to model, assess, and predict runoff and erosion rates on rangelands and to assist in evaluating rangeland conservation practices effects. RHEM is an event-based model that estimates runoff, erosion, and sediment delivery rates and volumes at the spatial scale of the hillslope and the temporal scale of as single rainfall event. It represents erosion processes under normal and fire-impacted rangeland conditions. Moreover, it adopts a new splash erosion and thin sheet-flow transport equation developed from rangeland data, and it links the model hydrologic and erosion parameters with rangeland plant community by providing a new system of parameter estimation equations based on 204 plots at 49 rangeland sites distributed across 15 western U.S. states. A dynamic partial differential sediment continuity equation is used to model the total detachment rate of concentrated flow and rain splash and sheet flow. RHEM is also designed to be used as a calculator, or "engine", within other watershed scale models. From the research perspective RHEM acts as a vehicle for incorporating new scientific findings from rangeland infiltration, runoff, and erosion studies. Current applications of the model include: 1) a web site for general use (conservation planning, research, etc.), 2) National Resource Inventory reports to Congress, 3) as a computational engine within watershed scale models (e.g., KINEROS, HEC), 4) Ecological Site & State and Transition Descriptions, 5) proposed in 2015 to become part of the NRCS Desktop applications for field offices.

Spatially-Distributed Cost–Effectiveness Analysis Framework to Control Phosphorus from Agricultural Diffuse Pollution

PubMed Central

Geng, Runzhe; Wang, Xiaoyan; Sharpley, Andrew N.; Meng, Fande

2015-01-01

Best management practices (BMPs) for agricultural diffuse pollution control are implemented at the field or small-watershed scale. However, the benefits of BMP implementation on receiving water quality at multiple spatial is an ongoing challenge. In this paper, we introduce an integrated approach that combines risk assessment (i.e., Phosphorus (P) index), model simulation techniques (Hydrological Simulation Program–FORTRAN), and a BMP placement tool at various scales to identify the optimal location for implementing multiple BMPs and estimate BMP effectiveness after implementation. A statistically significant decrease in nutrient discharge from watersheds is proposed to evaluate the effectiveness of BMPs, strategically targeted within watersheds. Specifically, we estimate two types of cost-effectiveness curves (total pollution reduction and proportion of watersheds improved) for four allocation approaches. Selection of a ‘‘best approach” depends on the relative importance of the two types of effectiveness, which involves a value judgment based on the random/aggregated degree of BMP distribution among and within sub-watersheds. A statistical optimization framework is developed and evaluated in Chaohe River Watershed located in the northern mountain area of Beijing. Results show that BMP implementation significantly (p >0.001) decrease P loss from the watershed. Remedial strategies where BMPs were targeted to areas of high risk of P loss, deceased P loads compared with strategies where BMPs were randomly located across watersheds. Sensitivity analysis indicated that aggregated BMP placement in particular watershed is the most cost-effective scenario to decrease P loss. The optimization approach outlined in this paper is a spatially hierarchical method for targeting nonpoint source controls across a range of scales from field to farm, to watersheds, to regions. Further, model estimates showed targeting at multiple scales is necessary to optimize program efficiency. The integrated model approach described that selects and places BMPs at varying levels of implementation, provides a new theoretical basis and technical guidance for diffuse pollution management in agricultural watersheds. PMID:26313561

Spatially-Distributed Cost-Effectiveness Analysis Framework to Control Phosphorus from Agricultural Diffuse Pollution.

PubMed

Geng, Runzhe; Wang, Xiaoyan; Sharpley, Andrew N; Meng, Fande

2015-01-01

Best management practices (BMPs) for agricultural diffuse pollution control are implemented at the field or small-watershed scale. However, the benefits of BMP implementation on receiving water quality at multiple spatial is an ongoing challenge. In this paper, we introduce an integrated approach that combines risk assessment (i.e., Phosphorus (P) index), model simulation techniques (Hydrological Simulation Program-FORTRAN), and a BMP placement tool at various scales to identify the optimal location for implementing multiple BMPs and estimate BMP effectiveness after implementation. A statistically significant decrease in nutrient discharge from watersheds is proposed to evaluate the effectiveness of BMPs, strategically targeted within watersheds. Specifically, we estimate two types of cost-effectiveness curves (total pollution reduction and proportion of watersheds improved) for four allocation approaches. Selection of a ''best approach" depends on the relative importance of the two types of effectiveness, which involves a value judgment based on the random/aggregated degree of BMP distribution among and within sub-watersheds. A statistical optimization framework is developed and evaluated in Chaohe River Watershed located in the northern mountain area of Beijing. Results show that BMP implementation significantly (p >0.001) decrease P loss from the watershed. Remedial strategies where BMPs were targeted to areas of high risk of P loss, deceased P loads compared with strategies where BMPs were randomly located across watersheds. Sensitivity analysis indicated that aggregated BMP placement in particular watershed is the most cost-effective scenario to decrease P loss. The optimization approach outlined in this paper is a spatially hierarchical method for targeting nonpoint source controls across a range of scales from field to farm, to watersheds, to regions. Further, model estimates showed targeting at multiple scales is necessary to optimize program efficiency. The integrated model approach described that selects and places BMPs at varying levels of implementation, provides a new theoretical basis and technical guidance for diffuse pollution management in agricultural watersheds.

Precipitation and runoff simulations of select perennial and ephemeral watersheds in the middle Carson River basin, Eagle, Dayton, and Churchill Valleys, west-central Nevada

USGS Publications Warehouse

Jeton, Anne E.; Maurer, Douglas K.

2011-01-01

The effect that land use may have on streamflow in the Carson River, and ultimately its impact on downstream users can be evaluated by simulating precipitation-runoff processes and estimating groundwater inflow in the middle Carson River in west-central Nevada. To address these concerns, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, began a study in 2008 to evaluate groundwater flow in the Carson River basin extending from Eagle Valley to Churchill Valley, called the middle Carson River basin in this report. This report documents the development and calibration of 12 watershed models and presents model results and the estimated mean annual water budgets for the modeled watersheds. This part of the larger middle Carson River study will provide estimates of runoff tributary to the Carson River and the potential for groundwater inflow (defined here as that component of recharge derived from percolation of excess water from the soil zone to the groundwater reservoir). The model used for the study was the U.S. Geological Survey's Precipitation-Runoff Modeling System, a physically based, distributed-parameter model designed to simulate precipitation and snowmelt runoff as well as snowpack accumulation and snowmelt processes. Models were developed for 2 perennial watersheds in Eagle Valley having gaged daily mean runoff, Ash Canyon Creek and Clear Creek, and for 10 ephemeral watersheds in the Dayton Valley and Churchill Valley hydrologic areas. Model calibration was constrained by daily mean runoff for the 2 perennial watersheds and for the 10 ephemeral watersheds by limited indirect runoff estimates and by mean annual runoff estimates derived from empirical methods. The models were further constrained by limited climate data adjusted for altitude differences using annual precipitation volumes estimated in a previous study. The calibration periods were water years 1980-2007 for Ash Canyon Creek, and water years 1991-2007 for Clear Creek. To allow for water budget comparisons to the ephemeral models, the two perennial models were then run from 1980 to 2007, the time period constrained somewhat by the later record for the high-altitude climate station used in the simulation. The daily mean values of precipitation, runoff, evapotranspiration, and groundwater inflow simulated from the watershed models were summed to provide mean annual rates and volumes derived from each year of the simulation. Mean annual bias for the calibration period for Ash Canyon Creek and Clear Creek watersheds was within 6 and 3 percent, and relative errors were about 18 and -2 percent, respectively. For the 1980-2007 period of record, mean recharge efficiency and runoff efficiency (percentage of precipitation as groundwater inflow and runoff) averaged 7 and 39 percent, respectively, for Ash Canyon Creek, and 8 and 31 percent, respectively, for Clear Creek. For this same period, groundwater inflow volumes averaged about 500 acre-feet for Ash Canyon and 1,200 acre-feet for Clear Creek. The simulation period for the ephemeral watersheds ranged from water years 1978 to 2007. Mean annual simulated precipitation ranged from 6 to 11 inches. Estimates of recharge efficiency for the ephemeral watersheds ranged from 3 percent for Eureka Canyon to 7 percent for Eldorado Canyon. Runoff efficiency ranged from 7 percent for Eureka Canyon and 15 percent at Brunswick Canyon. For the 1978-2007 period, mean annual groundwater inflow volumes ranged from about 40 acre-feet for Eureka Canyon to just under 5,000 acre-feet for Churchill Canyon watershed. Watershed model results indicate significant interannual variability in the volumes of groundwater inflow caused by climate variations. For most of the modeled watersheds, little to no groundwater inflow was simulated for years with less than 8 inches of precipitation, unless those years were preceded by abnormally high precipitation years with significant subsurface storage carryover.

Ranking streamflow model performance based on Information theory metrics

NASA Astrophysics Data System (ADS)

Martinez, Gonzalo; Pachepsky, Yakov; Pan, Feng; Wagener, Thorsten; Nicholson, Thomas

2016-04-01

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 model evaluation and selection. We simulated 10-year streamflow time series in five watersheds located in Texas, North Carolina, Mississippi, and West Virginia. Eight model of different complexity were applied. The information-theory based metrics were obtained after representing the time series as strings of symbols where different symbols corresponded to different quantiles of the probability distribution of streamflow. The symbol alphabet was used. Three metrics were computed for those strings - mean information gain that measures the randomness of the signal, effective measure complexity that characterizes predictability and fluctuation complexity that characterizes the presence of a pattern in the signal. The observed streamflow time series has smaller information content and larger complexity metrics than the precipitation time series. Watersheds served as information filters and and streamflow time series were less random and more complex than the ones of precipitation. This is reflected the fact that the watershed acts as the information filter in the hydrologic conversion process from precipitation to streamflow. The Nash Sutcliffe efficiency metric increased as the complexity of models increased, but in many cases several model had this efficiency values not statistically significant from each other. In such cases, ranking models by the closeness of the information-theory based parameters in simulated and measured streamflow time series can provide an additional criterion for the evaluation of hydrologic model performance.

A priori discretization quality metrics for distributed hydrologic modeling applications

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Estimating Watershed-Averaged Precipitation and Evapotranspiration Fluxes using Streamflow Measurements in a Semi-Arid, High Altitude Montane Catchment

NASA Astrophysics Data System (ADS)

Herrington, C.; Gonzalez-Pinzon, R.

2014-12-01

Streamflow through the Middle Rio Grande Valley is largely driven by snowmelt pulses and monsoonal precipitation events originating in the mountain highlands of New Mexico (NM) and Colorado. Water managers rely on results from storage/runoff models to distribute this resource statewide and to allocate compact deliveries to Texas under the Rio Grande Compact agreement. Prevalent drought conditions and the added uncertainty of climate change effects in the American southwest have led to a greater call for accuracy in storage model parameter inputs. While precipitation and evapotranspiration measurements are subject to scaling and representativeness errors, streamflow readings remain relatively dependable and allow watershed-average water budget estimates. Our study seeks to show that by "Doing Hydrology Backwards" we can effectively estimate watershed-average precipitation and evapotranspiration fluxes in semi-arid landscapes of NM using fluctuations in streamflow data alone. We tested this method in the Valles Caldera National Preserve (VCNP) in the Jemez Mountains of central NM. This method will be further verified by using existing weather stations and eddy-covariance towers within the VCNP to obtain measured values to compare against our model results. This study contributes to further validate this technique as being successful in humid and semi-arid catchments as the method has already been verified as effective in the former setting.

Factors affecting the occurrence of saugers in small, high-elevation rivers near the western edge of the species' natural distribution

USGS Publications Warehouse

Amadio, C.J.; Hubert, W.A.; Johnson, Kevin; Oberlie, D.; Dufek, D.

2005-01-01

Factors affecting the occurrence of saugers Sander canadensis were studied throughout the Wind River basin, a high-elevation watershed (> 1,440 m above mean sea level) on the western periphery of the species' natural distribution in central Wyoming. Adult saugers appeared to have a contiguous distribution over 170 km of streams among four rivers in the watershed. The upstream boundaries of sauger distribution were influenced by summer water temperatures and channel slopes in two rivers and by water diversion dams that created barriers to upstream movement in the other two rivers. Models that included summer water temperature, maximum water depth, habitat type (pool or run), dominant substrate, and alkalinity accounted for the variation in sauger occurrence across the watershed within the areas of sauger distribution. Water temperature was the most important basin-scale habitat feature associated with sauger occurrence, and maximum depth was the most important site-specific habitat feature. Saugers were found in a larger proportion of pools than runs in all segments of the watershed and occurred almost exclusively in pools in upstream segments of the watershed. Suitable summer water temperatures and deep, low-velocity habitat were available to support saugers over a large portion of the Wind River watershed. Future management of saugers in the Wind River watershed, as well as in other small river systems within the species' native range, should involve (1) preserving natural fluvial processes to maintain the summer water temperatures and physical habitat features needed by saugers and (2) assuring that barriers to movement do not reduce upstream boundaries of populations.

Climate Sensitivity of Water Yield for a Small Boreal Headwater Watershed in North-Central Minnesota

NASA Astrophysics Data System (ADS)

Nieber, J. L.; Hess, J.; Sebestyen, S. D.

2017-12-01

We calibrated the Hydrologic Simulation Program Fortran (HSPF) model to a 9.7 ha forested watershed, designated S2, located at the Marcell experimental forest in north-central Minnesota. The S2 watershed, like the other five experimental watersheds at the same location have been monitored since 1955. The watershed is composed of forested upland hillslopes that connect to a 3.2 ha raised bog area. Streamflow is measured at a v-notch weir at the outlet of the bog area. The HSPF model was calibrated to outflow for water years 1991 to 1995 (NSEdaily=0.80), and validated for water years 1996 to 2000 (NSEdaily=0.71). Watershed sensitivity to climate and water budget reaction to climate change scenarios were evaluated using, first, a simple empirical elasticity measure between runoff and precipitation utilizing the long-term monitoring records. Elasticity between these two variables in the S2 watershed was e(q) = 2.05, meaning for each 1% change in precipitation, there is a 2.05% change in runoff. A two parameter elasticity measure using precipitation and temperature was also used to predict how climate shifts in temperature and precipitation will impact runoff in the watershed. Annual estimated water budget was plotted with temperature and precipitation deviation from average to produce a 3-D map depicting the watershed two parameter elasticity. Watershed sensitivity was also evaluated using the HSPF model with climate inputs derived from an ensemble of 22 downscaled climate models reflecting the least and most extreme carbon emission scenarios. For the HSPF model inputs, observed daily temperature and precipitation data were adjusted using monthly shifts in average precipitation and temperature derived from the climate models to arrive at daily weather time series for the periods 2020-2050 and 2070-2100. For the HSPF outputs, the least and most extreme carbon emission scenarios showed a decrease in water yield of 9% and 11%, respectively in the 2020-2050 period and 9% and 43% respectively in the 2070-2100 period. The reduction in water yield is explained by increasing ET rates, even though precipitation increases and groundwater recharge decreases. All scenarios and time periods show an increase in flows for December through March and a decrease for May through October.

Watershed Conservation, Groundwater Management, and Adaptation to Climate Change

NASA Astrophysics Data System (ADS)

Roumasset, J.; Burnett, K.; Wada, C.

2009-12-01

Sustainability science is transdisciplinary, organizing research to deliver meaningful and practical contributions to critical issues of resource management. As yet, however, sustainability science has not been integrated with the policy sciences. We provide a step towards integration by providing an integrated model of optimal groundwater management and investment in watershed conservation. The joint optimization problem is solved under alternative forecasts of the changing rainfall distribution for the Koolau Watershed in Oahu, Hawaii. Optimal groundwater management is solved using a simplified one-dimensional model of the groundwater aquifer for analytical tractability. For a constant aquifer recharge, the model solves for the optimal trajectories of water extraction up to the desalination steady state and an incentive compatible pricing scheme. The Koolau Watershed is currently being degraded, however, by invasive plants such as Miconia calvescens and feral animals, especially wild pigs. Runoff and erosion have increased and groundwater recharge is at risk. The Koolau Partnership, a coalition of private owners, the State Department of Land and Natural Resources have proposed a $5 million (present value) conservation plan that promises to halt further losses of recharge. We compare this to the enhanced present value of the aquifer, showing the benefits are an order of magnitude greater than the costs. If conservation is done in the absence of efficient groundwater management, however, more than 40% of the potential benefits would be wasted by under-pricing and overconsumption. We require an estimate of the rainfall-generating distribution and how that distribution is changing over time. We obtain these from statistical downsizing of IPCC climate models. Despite the finding that global warming will increase precipitation for most of the world, the opposite is forecast for Hawaii. A University of Hawaii study finds that the most likely precipitation scenario is a 5-10% reduction in wet season mean precipitation and a 5% increase during the dry season by the end of the 21st century. These trends will be used to condition the time series analysis through Bayesian updating. The resulting distributions, conditioned for seasonality and long-run climate change, will be used to recursively simulate daily rainfalls, thereby allowing for serial correlation and forming a basis for the watershed model to recursively determine components of the water balance equation. The methodology will allow us to generate different sequences of rainfall from the estimated distribution and the corresponding recharge functions. These in turn are used as the basis of optimizing groundwater management under both the watershed conservation program and no conservation. We calculate how much adaptation via joint optimization of watershed conservation and groundwater management decreases the damages from declining precipitation. Inasmuch as groundwater scarcity increases with the forecasted climate change, even under optimal groundwater management, the value of watershed conservation also increases.

Quality assurance report - Loch Vale Watershed, 1999-2002

USGS Publications Warehouse

Botte, Jorin A.; Baron, Jill S.

2004-01-01

The National Park Service initiated the Loch Vale Watershed (LVWS) project in 1980 with funding from the Aquatic Effects Research Program of the National Acid Precipitation Assessment Program. Long-term ecological research and monitoring address watershed-scale ecosystem processes, particularly as they respond to atmospheric deposition and climate variability. Monitoring of meteorological, hydrologic, precipitation chemistry, and surface water quality parameters enable us to use long-term trends to distinguish natural from human-caused disturbances. Research into snow distribution, hydrologic flowpaths, vegetation responses to N deposition, isotopic transformations of N by forest and soil processes, trace metals, and aquatic ecological responses to disturbance enable us to understand processes that influence high elevation ecosystems.

Regional rainfall-runoff relations for simulation of streamflow for watersheds in Du Page County, Illinois

USGS Publications Warehouse

Duncker, James J.; Melching, Charles S.

1998-01-01

Rainfall and streamflow data collected from July 1986 through September 1993 were utilized to calibrate and verify a continuous-simulation rainfall-runoff model for three watersheds (11.8--18.0 square miles in area) in Du Page County. Classification of land cover into three categories of pervious (grassland, forest/wetland, and agricultural land) and one category of impervious subareas was sufficient to accurately simulate the rainfall-runoff relations for the three watersheds. Regional parameter sets were obtained by calibrating jointly all parameters except fraction of ground-water inflow that goes to inactive ground water (DEEPFR), interflow recession constant (IRC), and infiltration (INFILT) for runoff from all three watersheds. DEEPFR and IRC varied among the watersheds because of physical differences among the watersheds. Two values of INFILT were obtained: one representing the rainfall-runoff process on the silty and clayey soils on the uplands and lake plains that characterize Sawmill Creek, St. Joseph Creek, and eastern Du Page County; and one representing the rainfall-runoff process on the silty soils on uplands that characterize Kress Creek and parts of western Du Page County. Regional rainfall-runoff relations, defined through joint calibration of the rainfall-runoff model and verified for independent periods, presented in this report, allow estimation of runoff for watersheds in Du Page County with an error in the total water balance less than 4.0 percent; an average absolute error in the annual-flow estimates of 17.1 percent with the error rarely exceeding 25 percent for annual flows; and correlation coefficients and coefficients of model-fit efficiency for monthly flows of at least 87 and 76 percent, respectively. Close reproduction of the runoff-volume duration curves was obtained. A frequency analysis of storm-runoff volume indicates a tendency of the model to undersimulate large storms, which may result from underestimation of the amount of impervious land cover in the watershed and errors in measuring rainfall for convective storms. Overall, the results of regional calibration and verification of the rainfall-runoff model indicate the simulated rainfall-runoff relations are adequate for stormwater-management planning and design for watersheds in Du Page County.

Describing Ecosystem Complexity through Integrated Catchment Modeling

NASA Astrophysics Data System (ADS)

Shope, C. L.; Tenhunen, J. D.; Peiffer, S.

2011-12-01

Land use and climate change have been implicated in reduced ecosystem services (ie: high quality water yield, biodiversity, and agricultural yield. The prediction of ecosystem services expected under future land use decisions and changing climate conditions has become increasingly important. Complex policy and management decisions require the integration of physical, economic, and social data over several scales to assess effects on water resources and ecology. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. A variety of models are being used to simulate plot and field scale experiments within the catchment. Results from each of the local-scale models provide identification of sensitive, local-scale parameters which are then used as inputs into a large-scale watershed model. We used the spatially distributed SWAT model to synthesize the experimental field data throughout the catchment. The approach of our study was that the range in local-scale model parameter results can be used to define the sensitivity and uncertainty in the large-scale watershed model. Further, this example shows how research can be structured for scientific results describing complex ecosystems and landscapes where cross-disciplinary linkages benefit the end result. The field-based and modeling framework described is being used to develop scenarios to examine spatial and temporal changes in land use practices and climatic effects on water quantity, water quality, and sediment transport. Development of accurate modeling scenarios requires understanding the social relationship between individual and policy driven land management practices and the value of sustainable resources to all shareholders.

Comparison of WEPP and APEX runoff and erosion prediction at field scale in Goodwater Creek Experimental Watershed

USDA-ARS?s Scientific Manuscript database

The Water Erosion Prediction Project (WEPP) and the Agricultural Policy/Environmental eXtender (APEX) are process-based models that can predict spatial and temporal distributions of erosion for hillslopes and watersheds. This study applies the WEPP model to predict runoff and erosion for a 35-ha fie...

Modeling pesticide loadings from the San Joaquin watershed into the Sacramento-San Joaquin Delta using SWAT

NASA Astrophysics Data System (ADS)

Chen, H.; Zhang, M.

2016-12-01

The Sacramento-San Joaquin Delta is an ecologically rich, hydrologically complex area that serves as the hub of California's water supply. However, pesticides have been routinely detected in the Delta waterways, with concentrations exceeding the benchmark for the protection of aquatic life. Pesticide loadings into the Delta are partially attributed to the San Joaquin watershed, a highly productive agricultural watershed located upstream. Therefore, this study aims to simulate pesticide loadings to the Delta by applying the Soil and Water Assessment Tool (SWAT) model to the San Joaquin watershed, under the support of the USDA-ARS Delta Area-Wide Pest Management Program. Pesticide use patterns in the San Joaquin watershed were characterized by combining the California Pesticide Use Reporting (PUR) database and GIS analysis. Sensitivity/uncertainty analyses and multi-site calibration were performed in the simulation of stream flow, sediment, and pesticide loads along the San Joaquin River. Model performance was evaluated using a combination of graphic and quantitative measures. Preliminary results indicated that stream flow was satisfactorily simulated along the San Joaquin River and the major eastern tributaries, whereas stream flow was less accurately simulated in the western tributaries, which are ephemeral small streams that peak during winter storm events and are mainly fed by irrigation return flow during the growing season. The most sensitive parameters to stream flow were CN2, SOL_AWC, HRU_SLP, SLSUBBSN, SLSOIL, GWQMN and GW_REVAP. Regionalization of parameters is important as the sensitivity of parameters vary significantly spatially. In terms of evaluation metric, NSE tended to overrate model performance when compared to PBIAS. Anticipated results will include (1) pesticide use pattern analysis, (2) calibration and validation of stream flow, sediment, and pesticide loads, and (3) characterization of spatial patterns and temporal trends of pesticide yield.

Watershed model calibration framework developed using an influence coefficient algorithm and a genetic algorithm and analysis of pollutant discharge characteristics and load reduction in a TMDL planning area.

PubMed

Cho, Jae Heon; Lee, Jong Ho

2015-11-01

Manual calibration is common in rainfall-runoff model applications. However, rainfall-runoff models include several complicated parameters; thus, significant time and effort are required to manually calibrate the parameters individually and repeatedly. Automatic calibration has relative merit regarding time efficiency and objectivity but shortcomings regarding understanding indigenous processes in the basin. In this study, a watershed model calibration framework was developed using an influence coefficient algorithm and genetic algorithm (WMCIG) to automatically calibrate the distributed models. The optimization problem used to minimize the sum of squares of the normalized residuals of the observed and predicted values was solved using a genetic algorithm (GA). The final model parameters were determined from the iteration with the smallest sum of squares of the normalized residuals of all iterations. The WMCIG was applied to a Gomakwoncheon watershed located in an area that presents a total maximum daily load (TMDL) in Korea. The proportion of urbanized area in this watershed is low, and the diffuse pollution loads of nutrients such as phosphorus are greater than the point-source pollution loads because of the concentration of rainfall that occurs during the summer. The pollution discharges from the watershed were estimated for each land-use type, and the seasonal variations of the pollution loads were analyzed. Consecutive flow measurement gauges have not been installed in this area, and it is difficult to survey the flow and water quality in this area during the frequent heavy rainfall that occurs during the wet season. The Hydrological Simulation Program-Fortran (HSPF) model was used to calculate the runoff flow and water quality in this basin. Using the water quality results, a load duration curve was constructed for the basin, the exceedance frequency of the water quality standard was calculated for each hydrologic condition class, and the percent reduction required to achieve the water quality standard was estimated. The R(2) value for the calibrated BOD5 was 0.60, which is a moderate result, and the R(2) value for the TP was 0.86, which is a good result. The percent differences obtained for the calibrated BOD5 and TP were very good; therefore, the calibration results using WMCIG were satisfactory. From the load duration curve analysis, the WQS exceedance frequencies of the BOD5 under dry conditions and low-flow conditions were 75.7% and 65%, respectively, and the exceedance frequencies under moist and mid-range conditions were higher than under other conditions. The exceedance frequencies of the TP for the high-flow, moist and mid-range conditions were high and the exceedance rate for the high-flow condition was particularly high. Most of the data from the high-flow conditions exceeded the WQSs. Thus, nonpoint-source pollutants from storm-water runoff substantially affected the TP concentration in the Gomakwoncheon. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Shale Hills Critical Zone Observatory for Embedded Sensing and Simulation

NASA Astrophysics Data System (ADS)

Duffy, C.; Davis, K.; Kane, T.; Boyer, E.

2009-04-01

The future of environmental observing systems will utilize embedded sensor networks with continuous real-time measurement of hydrologic, atmospheric, biogeochemical, and ecological variables across diverse terrestrial environments. Embedded environmental sensors, benefitting from advances in information sciences, networking technology, materials science, computing capacity, and data synthesis methods, are undergoing revolutionary change. It is now possible to field spatially-distributed, multi-node sensor networks that provide density and spatial coverage previously accessible only via numerical simulation. At the same time, computational tools are advancing rapidly to the point where it is now possible to simulate the physical processes controlling individual parcels of water and solutes through the complete terrestrial water cycle. Our goal for the Penn State Critical Zone Observatory is to apply environmental sensor arrays, integrated hydrologic models deployed and coordinated at a testbed within the Penn State Experimental Forest. The NSF-funded CZO is designed to observe the detailed space and time complexities of the water and energy cycle for a watershed and ultimately the river basin for all physical states and fluxes (groundwater, soil moisture, temperature, streamflow, latent heat, snowmelt, chemistry, isotopes etc.). Presently fully-coupled physical models are being developed that link the atmosphere-land-vegetation-subsurface system into a fully-coupled distributed system. During the last 5 years the Penn State Integrated Hydrologic Modeling System has been under development as an open-source community modeling project funded by NSF EAR/GEO and NSF CBET/ENG. PIHM represents a strategy for the formulation and solution of fully-coupled process equations at the watershed and river basin scales, and includes a tightly coupled GIS tool for data handling, domain decomposition, optimal unstructured grid generation, and model parameterization. (PIHM; http://sourceforge.net/projects/pihmmodel/; http://sourceforge.net/projects/pihmgis/ ) The CZO sensor and simulation system is being developed to have the following elements: 1) extensive, spatially-distributed smart sensor networks to gather intensive soil, geologic, hydrologic, geochemical and isotopic data; 2) spatially-explicit multiphysics models/solutions of the land-subsurface-vegetation-atmosphere system; and 3) parallel/distributed, adaptive algorithms for rapidly simulating the states of the watershed at high resolution, and 4) signal processing tools for data mining and parameter estimation. The prototype proposed sensor array and simulation system proposed is demonstrated with preliminary results from our first year.

Hydrologic Modeling and Parameter Estimation under Data Scarcity for Java Island, Indonesia

NASA Astrophysics Data System (ADS)

Yanto, M.; Livneh, B.; Rajagopalan, B.; Kasprzyk, J. R.

2015-12-01

The Indonesian island of Java is routinely subjected to intense flooding, drought and related natural hazards, resulting in severe social and economic impacts. Although an improved understanding of the island's hydrology would help mitigate these risks, data scarcity issues make the modeling challenging. To this end, we developed a hydrological representation of Java using the Variable Infiltration Capacity (VIC) model, to simulate the hydrologic processes of several watersheds across the island. We measured the model performance using Nash-Sutcliffe Efficiency (NSE) at monthly time step. Data scarcity and quality issues for precipitation and streamflow warranted the application of a quality control procedure to data ensure consistency among watersheds resulting in 7 watersheds. To optimize the model performance, the calibration parameters were estimated using Borg Multi Objective Evolutionary Algorithm (Borg MOEA), which offers efficient searching of the parameter space, adaptive population sizing and local optima escape facility. The result shows that calibration performance is best (NSE ~ 0.6 - 0.9) in the eastern part of the domain and moderate (NSE ~ 0.3 - 0.5) in the western part of the island. The validation results are lower (NSE ~ 0.1 - 0.5) and (NSE ~ 0.1 - 0.4) in the east and west, respectively. We surmise that the presence of outliers and stark differences in the climate between calibration and validation periods in the western watersheds are responsible for low NSE in this region. In addition, we found that approximately 70% of total errors were contributed by less than 20% of total data. The spatial variability of model performance suggests the influence of both topographical and hydroclimatic controls on the hydrological processes. Most watersheds in eastern part perform better in wet season and vice versa for the western part. This modeling framework is one of the first attempts at comprehensively simulating the hydrology in this maritime, tropical continent and, offers insights for skillful hydrologic projections crucial for natural hazard mitigation.

Modelisation numerique de l'hydrologie pour l'aide a la gestion des bassins versants, par l'utilisation conjointe des systemes d'information geographique et de la methode des elements finis un nouvel outil pour le developpement durable SAGESS

NASA Astrophysics Data System (ADS)

Bel Hadj Kacem, Mohamed Salah

All hydrological processes are affected by the spatial variability of the physical parameters of the watershed, and also by human intervention on the landscape. The water outflow from a watershed strictly depends on the spatial and temporal variabilities of the physical parameters of the watershed. It is now apparent that the integration of mathematical models into GIS's can benefit both GIS and three-dimension environmental models: a true modeling capability can help the modeling community bridge the gap between planners, scientists, decision-makers and end-users. The main goal of this research is to design a practical tool to simulate run-off water surface using Geographic design a practical tool to simulate run-off water surface using Geographic Information Systems and the simulation of the hydrological behavior by the Finite Element Method.

Spatially-Distributed Stream Flow and Nutrient Dynamics Simulations Using the Component-Based AgroEcoSystem-Watershed (AgES-W) Model

NASA Astrophysics Data System (ADS)

Ascough, J. C.; David, O.; Heathman, G. C.; Smith, D. R.; Green, T. R.; Krause, P.; Kipka, H.; Fink, M.

2010-12-01

The Object Modeling System 3 (OMS3), currently being developed by the USDA-ARS Agricultural Systems Research Unit and Colorado State University (Fort Collins, CO), provides a component-based environmental modeling framework which allows the implementation of single- or multi-process modules that can be developed and applied as custom-tailored model configurations. OMS3 as a “lightweight” modeling framework contains four primary foundations: modeling resources (e.g., components) annotated with modeling metadata; domain specific knowledge bases and ontologies; tools for calibration, sensitivity analysis, and model optimization; and methods for model integration and performance scalability. The core is able to manage modeling resources and development tools for model and simulation creation, execution, evaluation, and documentation. OMS3 is based on the Java platform but is highly interoperable with C, C++, and FORTRAN on all major operating systems and architectures. The ARS Conservation Effects Assessment Project (CEAP) Watershed Assessment Study (WAS) Project Plan provides detailed descriptions of ongoing research studies at 14 benchmark watersheds in the United States. In order to satisfy the requirements of CEAP WAS Objective 5 (“develop and verify regional watershed models that quantify environmental outcomes of conservation practices in major agricultural regions”), a new watershed model development approach was initiated to take advantage of OMS3 modeling framework capabilities. Specific objectives of this study were to: 1) disaggregate and refactor various agroecosystem models (e.g., J2K-S, SWAT, WEPP) and implement hydrological, N dynamics, and crop growth science components under OMS3, 2) assemble a new modular watershed scale model for fully-distributed transfer of water and N loading between land units and stream channels, and 3) evaluate the accuracy and applicability of the modular watershed model for estimating stream flow and N dynamics. The Cedar Creek watershed (CCW) in northeastern Indiana, USA was selected for application of the OMS3-based AgroEcoSystem-Watershed (AgES-W) model. AgES-W performance for stream flow and N loading was assessed using Nash-Sutcliffe model efficiency (ENS) and percent bias (PBIAS) model evaluation statistics. Comparisons of daily and average monthly simulated and observed stream flow and N loads for the 1997-2005 simulation period resulted in PBIAS and ENS values that were similar or better than those reported in the literature for SWAT stream flow and N loading predictions at a similar scale. The results show that the AgES-W model was able to reproduce the hydrological and N dynamics of the CCW with sufficient quality, and should serve as a foundation upon which to better quantify additional water quality indicators (e.g., sediment transport and P dynamics) at the watershed scale.

Construction of a hydrologic model for estimating Wadi runoff and ground water recharge in the Eastern Desert, Egypt.

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

Gheith, H.; Sultan, M.; Environmental Research

2002-06-10

We constructed a hydrologic model to estimate the groundwater recharge rate for alluvial aquifers of the Eastern Desert from sporadic precipitation over the Red Sea hills. To estimate initial losses over sub-basins, transmission losses through channel routing, and downstream runoff, we developed an integrated model combining spatial rainfall distribution, an appropriate basin unit hydrograph, and appropriate infiltration parameters. Watersheds and stream networks identified from digital terrain elevation data were verified by comparison with co-registered Landsat thematic mapper scenes and geologic maps. Records of a November 1994 storm event acquired from rain gauges along the Nile River and the Red Seamore » shore were used to generate a spatial precipitation distribution for the study area. A 2 hour design hyetograph was adopted from rain gauge data for the 1994 flood event. The model was tested against records from the November 1994 flood event at the outlets of the Tarfa and Hammamat watersheds. Groundwater recharge rates were estimated for the alluvial aquifers within the major watersheds of the north Eastern Desert. We estimated that during the 1994 flood event, the ground water recharge through transmission losses ranged from 21 to 31% (Tarfa: 15.8 x 10{sup 6} m{sup 3}; Asyuti: 20 x 10{sup 6} m{sup 3}, Qena: 49 x 10{sup 6} m{sup 3}, Hammamat: 59 x10{sup 6} m{sup 3}) of the precipitated volume. The initial losses ranged from 65 to 77%. Only 3-7% of the precipitation reached the watershed outlets. Archival data show that rainfall events of the size of the November 1994 storm or larger occur every 40 months; thus, the annual recharge rates for the Tarfa, Asyuti, Qena, and Hammamat alluvial aquifers are estimated at 4.7 x 10{sup 6} m{sup 3}, 6 x 10{sup 6} m{sup 3}, 14.7 x 10{sup 6} m{sup 3}, and 17.7 x10{sup 6} m{sup 3}, respectively. Implications for the use of these renewable ground waters and similar water resources in other arid areas of Egypt and in neighboring countries are clear.« less

Development of genetic algorithm-based optimization module in WHAT system for hydrograph analysis and model application

NASA Astrophysics Data System (ADS)

Lim, Kyoung Jae; Park, Youn Shik; Kim, Jonggun; Shin, Yong-Chul; Kim, Nam Won; Kim, Seong Joon; Jeon, Ji-Hong; Engel, Bernard A.

2010-07-01

Many hydrologic and water quality computer models have been developed and applied to assess hydrologic and water quality impacts of land use changes. These models are typically calibrated and validated prior to their application. The Long-Term Hydrologic Impact Assessment (L-THIA) model was applied to the Little Eagle Creek (LEC) watershed and compared with the filtered direct runoff using BFLOW and the Eckhardt digital filter (with a default BFI max value of 0.80 and filter parameter value of 0.98), both available in the Web GIS-based Hydrograph Analysis Tool, called WHAT. The R2 value and the Nash-Sutcliffe coefficient values were 0.68 and 0.64 with BFLOW, and 0.66 and 0.63 with the Eckhardt digital filter. Although these results indicate that the L-THIA model estimates direct runoff reasonably well, the filtered direct runoff values using BFLOW and Eckhardt digital filter with the default BFI max and filter parameter values do not reflect hydrological and hydrogeological situations in the LEC watershed. Thus, a BFI max GA-Analyzer module (BFI max Genetic Algorithm-Analyzer module) was developed and integrated into the WHAT system for determination of the optimum BFI max parameter and filter parameter of the Eckhardt digital filter. With the automated recession curve analysis method and BFI max GA-Analyzer module of the WHAT system, the optimum BFI max value of 0.491 and filter parameter value of 0.987 were determined for the LEC watershed. The comparison of L-THIA estimates with filtered direct runoff using an optimized BFI max and filter parameter resulted in an R2 value of 0.66 and the Nash-Sutcliffe coefficient value of 0.63. However, L-THIA estimates calibrated with the optimized BFI max and filter parameter increased by 33% and estimated NPS pollutant loadings increased by more than 20%. This indicates L-THIA model direct runoff estimates can be incorrect by 33% and NPS pollutant loading estimation by more than 20%, if the accuracy of the baseflow separation method is not validated for the study watershed prior to model comparison. This study shows the importance of baseflow separation in hydrologic and water quality modeling using the L-THIA model.

Development of a "Hydrologic Equivalent Wetland" Concept for Modeling Cumulative Effects of Wetlands on Watershed Hydrology

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

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.

Detecting seasonal variations of soil parameters via field measurements and stochastic simulations in the hillslope

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; An, Hyunuk; Kim, Sanghyun

2015-04-01

Soil moisture, a critical factor in hydrologic systems, plays a key role in synthesizing interactions among soil, climate, hydrological response, solute transport and ecosystem dynamics. The spatial and temporal distribution of soil moisture at a hillslope scale is essential for understanding hillslope runoff generation processes. In this study, we implement Monte Carlo simulations in the hillslope scale using a three-dimensional surface-subsurface integrated model (3D model). Numerical simulations are compared with multiple soil moistures which had been measured using TDR(Mini_TRASE) for 22 locations in 2 or 3 depths during a whole year at a hillslope (area: 2100 square meters) located in Bongsunsa Watershed, South Korea. In stochastic simulations via Monte Carlo, uncertainty of the soil parameters and input forcing are considered and model ensembles showing good performance are selected separately for several seasonal periods. The presentation will be focused on the characterization of seasonal variations of model parameters based on simulations with field measurements. In addition, structural limitations of the contemporary modeling method will be discussed.

Impact of Yangtze River Water Transfer on the Water Quality of the Lixia River Watershed, China

PubMed Central

Ma, Xiaoxue; Wang, Lachun; Wu, Hao; Li, Na; Ma, Lei; Zeng, Chunfen; Zhou, Yi; Yang, Jun

2015-01-01

To improve water quality and reduce the negative impacts of sudden inputs of water pollution in the Lixia River watershed, China, a series of experimental water transfers from the Yangtze River to the Lixia River were conducted from 2 December 2006 to 7 January 2007. Water samples were collected every six days at 55 monitoring sites during this period. Eight water parameters (water temperature, pH, dissolved oxygen (DO), chemical oxygen demand (COD), potassium permanganate index (CODMn), ammonia nitrogen (NH4 +-N), electrical conductivity (EC), and water transparency (WT)) were analyzed to determine changes in nutrient concentrations during water transfers. The comprehensive pollution index (Pi) and single-factor (Si) evaluation methods were applied to evaluate spatio-temporal patterns of water quality during water transfers. Water quality parameters displayed different spatial and temporal distribution patterns within the watershed. Water quality was improved significantly by the water transfers, especially for sites closer to water intake points. The degree of improvement is positively related to rates of transfer inflow and drainage outflow. The effects differed for different water quality parameters at each site and at different water transfer times. There were notable decreases in NH4 +-N, DO, COD, and CODMn across the entire watershed. However, positive effects on EC and pH were not observed. It is concluded that freshwater transfers from the Yangtze River can be used as an emergency measure to flush pollutants from the Lixia River watershed. Improved understanding of the effects of water transfers on water quality can help the development and implementation of effective strategies to improve water quality within this watershed. PMID:25835525

Parameter interdependence and uncertainty induced by lumping in a hydrologic model

NASA Astrophysics Data System (ADS)

Gallagher, Mark R.; Doherty, John

2007-05-01

Throughout the world, watershed modeling is undertaken using lumped parameter hydrologic models that represent real-world processes in a manner that is at once abstract, but nevertheless relies on algorithms that reflect real-world processes and parameters that reflect real-world hydraulic properties. In most cases, values are assigned to the parameters of such models through calibration against flows at watershed outlets. One criterion by which the utility of the model and the success of the calibration process are judged is that realistic values are assigned to parameters through this process. This study employs regularization theory to examine the relationship between lumped parameters and corresponding real-world hydraulic properties. It demonstrates that any kind of parameter lumping or averaging can induce a substantial amount of "structural noise," which devices such as Box-Cox transformation of flows and autoregressive moving average (ARMA) modeling of residuals are unlikely to render homoscedastic and uncorrelated. Furthermore, values estimated for lumped parameters are unlikely to represent average values of the hydraulic properties after which they are named and are often contaminated to a greater or lesser degree by the values of hydraulic properties which they do not purport to represent at all. As a result, the question of how rigidly they should be bounded during the parameter estimation process is still an open one.

Fingerprinting Sources of Suspended Sediment in a Canadian Agricultural Watershed Using the MixSIAR Bayesian Unmixing Model

NASA Astrophysics Data System (ADS)

Smith, J. P.; Owens, P. N.; Gaspar, L.; Lobb, D. A.; Petticrew, E. L.

2015-12-01

An understanding of sediment redistribution processes and the main sediment sources within a watershed is needed to support watershed management strategies. The fingerprinting technique is increasingly being recognized as a method for establishing the source of the sediment transported within watersheds. However, the different behaviour of the various fingerprinting properties has been recognized as a major limitation of the technique, and the uncertainty associated with tracer selection needs to be addressed. There are also questions associated with which modelling approach (frequentist or Bayesian) is the best to unmix complex environmental mixtures, such as river sediment. This study aims to compare and evaluate the differences between fingerprinting predictions provided by a Bayesian unmixing model (MixSIAR) using different groups of tracer properties for use in sediment source identification. We used fallout radionuclides (e.g. 137Cs) and geochemical elements (e.g. As) as conventional fingerprinting properties, and colour parameters as emerging properties; both alone and in combination. These fingerprinting properties are being used (i.e. Koiter et al., 2013; Barthod et al., 2015) to determine the proportional contributions of fine sediment in the South Tobacco Creek Watershed, an agricultural watershed located in Manitoba, Canada. We show that the unmixing model using a combination of fallout radionuclides and geochemical tracers gave similar results to the model based on colour parameters. Furthermore, we show that a model that combines all tracers (i.e. radionuclide/geochemical and colour) gave similar results, showing that sediment sources change from predominantly topsoil in the upper reaches of the watershed to channel bank and bedrock outcrop material in the lower reaches. Barthod LRM et al. (2015). Selecting color-based tracers and classifying sediment sources in the assessment of sediment dynamics using sediment source fingerprinting. J Environ Qual. Doi:10.2134/jeq2015.01.0043 Koiter AJ et al. (2013). Investigating the role of connectivity and scale in assessing the sources of sediment in an agricultural watershed in the Canadian prairies using sediment source fingerprinting. J Soils Sediments, 13, 1676-1691.

Where Does Road Salt Go - a Static Salt Model

NASA Astrophysics Data System (ADS)

Yu, C. W.; Liu, F.; Moriarty, V. W.

2017-12-01

Each winter, more than 15 million tons of road salt is applied in the United States for the de-icing purpose. Considerable amount of chloride in road salt flows into streams/drainage systems with the snow melt runoff and spring storms, and eventually goes into ecologically sensitive low-lying areas in the watershed, such as ponds and lakes. In many watersheds in the northern part of US, the chloride level in the water body has increased significantly in the past decades, and continues an upward trend. The environmental and ecological impact of the elevated chloride level can no longer be ignored. However although there are many studies on the biological impact of elevated chloride levels, there are few investigations on how the spatially distributed road salt application affects various parts of the watershed. In this presentation, we propose a static road salt model as a first-order metric to address spacial distribution of salt loading. Derived from the Topological Wetness Index (TWI) in many hydrological models, this static salt model provides a spatial impact as- sessment of road salt applications. To demonstrate the effectiveness of the static model, National Elevation Dataset (NED) of ten-meter resolution of Lake George watershed in New York State is used to generate the TWI, which is used to compute a spatially dis- tributed "salt-loading coefficient" of the whole watershed. Spatially varying salt applica- tion rate is then aggregated, using the salt-loading coefficients as weights, to provide salt loading assessments of streams in the watershed. Time-aggregated data from five CTD (conductivity-temperature-depth) sensors in selected streams are used for calibration. The model outputs and the sensor data demonstrate a strong linear correlation, with the R value of 0.97. The investigation shows that the static modeling approach may provide an effective method for the understanding the input and transport of road salt to within watersheds.

A spatially distributed model for the assessment of land use impacts on stream temperature in small urban watersheds

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

Sun, Ning; Yearsley, John; Voisin, Nathalie

2015-05-15

Stream temperatures in urban watersheds are influenced to a high degree by anthropogenic impacts related to changes in landscape, stream channel morphology, and climate. These impacts can occur at small time and length scales, hence require analytical tools that consider the influence of the hydrologic regime, energy fluxes, topography, channel morphology, and near-stream vegetation distribution. Here we describe a modeling system that integrates the Distributed Hydrologic Soil Vegetation Model, DHSVM, with the semi-Lagrangian stream temperature model RBM, which has the capability to simulate the hydrology and water temperature of urban streams at high time and space resolutions, as well asmore » a representation of the effects of riparian shading on stream energetics. We demonstrate the modeling system through application to the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The results suggest that the model is able both to produce realistic streamflow predictions at fine temporal and spatial scales, and to provide spatially distributed water temperature predictions that are consistent with observations throughout a complex stream network. We use the modeling construct to characterize impacts of land use change and near-stream vegetation change on stream temperature throughout the Mercer Creek system. We then explore the sensitivity of stream temperature to land use changes and modifications in vegetation along the riparian corridor.« less

Model analysis of check dam impacts on long-term sediment and water budgets in southeast Arizona, USA

USGS Publications Warehouse

Norman, Laura M.; Niraula, Rewati

2016-01-01

The objective of this study was to evaluate the effect of check dam infrastructure on soil and water conservation at the catchment scale using the Soil and Water Assessment Tool (SWAT). This paired watershed study includes a watershed treated with over 2000 check dams and a Control watershed which has none, in the West Turkey Creek watershed, Southeast Arizona, USA. SWAT was calibrated for streamflow using discharge documented during the summer of 2013 at the Control site. Model results depict the necessity to eliminate lateral flow from SWAT models of aridland environments, the urgency to standardize geospatial soils data, and the care for which modelers must document altering parameters when presenting findings. Performance was assessed using the percent bias (PBIAS), with values of ±2.34%. The calibrated model was then used to examine the impacts of check dams at the Treated watershed. Approximately 630 tons of sediment is estimated to be stored behind check dams in the Treated watershed over the 3-year simulation, increasing water quality for fish habitat. A minimum precipitation event of 15 mm was necessary to instigate the detachment of soil, sediments, or rock from the study area, which occurred 2% of the time. The resulting watershed model is useful as a predictive framework and decision-support tool to consider long-term impacts of restoration and potential for future restoration.

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

USDA-ARS?s Scientific Manuscript database

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

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

NASA Astrophysics Data System (ADS)

Kurylyk, Barret L.; Hayashi, Masaki

2017-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

[Effects of sub-watershed landscape patterns at the upper reaches of Minjiang River on soil erosion].

PubMed

Yang, Meng; Li, Xiu-zhen; Yang, Zhao-ping; Hu, Yuan-man; Wen, Qing-chun

2007-11-01

Based on GIS, the spatial distribution of soil loss and sediment yield in Heishui and Zhenjiangguan sub-watersheds at the upper reaches of Minjiang River was simulated by using sediment delivery-distribution (SEDD) model, and the effects of land use/cover types on soil erosion and sediment yield were discussed, based on the simulated results and related land use maps. A landscape index named location-weighted landscape contrast index (LCI) was calculated to evaluate the effects of landscape components' spatial distribution, weight, and structure of land use/cover on soil erosion. The results showed the soil erosion modulus varied with land use pattern, and decreased in the order of bare rock > urban/village > rangeland > farmland > shrub > forest. There were no significant differences in sediment yield modules among different land use/covers. In the two sub-watersheds, the spatial distribution of land use/covers on slope tended to decrease the final sediment load at watershed outlet, hut as related to relative elevation, relative distance, and flow length, the spatial distribution tended to increase sediment yield. The two sub-watersheds had different advantages as related to landscape components' spatial distribution, but, when the land use/cover weight was considered, the advantages of Zhenjiangguan sub-watershed increased. If the land use/cover structure was considered in addition, the landscape pattern of Zhenjiangguan subwatershed was better. Therefore, only the three elements, i.e., landscape components' spatial distribution, land use/cover weight, and land use/cover structure, were considered comprehensively, can we get an overall evaluation on the effects of landscape pattern on soil erosion. The calculation of LCI related to slope suggested that this index couldn' t accurately reflect the effects of land use/cover weight and structure on soil erosion, and thus, needed to be modified.

Reducing fertilizer-nitrogen losses from rowcrop landscapes: Insights and implications from a spatially explicit watershed model

USGS Publications Warehouse

McLellan, Eileen; Schilling, Keith; Robertson, Dale M.

2015-01-01

We present conceptual and quantitative models that predict changes in fertilizer-derived nitrogen delivery from rowcrop landscapes caused by agricultural conservation efforts implemented to reduce nutrient inputs and transport and increase nutrient retention in the landscape. To evaluate the relative importance of changes in the sources, transport, and sinks of fertilizer-derived nitrogen across a region, we use the spatially explicit SPAtially Referenced Regression On Watershed attributes watershed model to map the distribution, at the small watershed scale within the Upper Mississippi-Ohio River Basin (UMORB), of: (1) fertilizer inputs; (2) nutrient attenuation during delivery of those inputs to the UMORB outlet; and (3) nitrogen export from the UMORB outlet. Comparing these spatial distributions suggests that the amount of fertilizer input and degree of nutrient attenuation are both important in determining the extent of nitrogen export. From a management perspective, this means that agricultural conservation efforts to reduce nitrogen export would benefit by: (1) expanding their focus to include activities that restore and enhance nutrient processing in these highly altered landscapes; and (2) targeting specific types of best management practices to watersheds where they will be most valuable. Doing so successfully may result in a shift in current approaches to conservation planning, outreach, and funding.

Analyzing the water budget and hydrological characteristics and responses to land use in a monsoonal climate river basin in South China

USGS Publications Warehouse

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.

Spatial analysis of land use and shallow groundwater vulnerability in the watershed adjacent to Assateague Island National Seashore, Maryland and Virginia, USA

USGS Publications Warehouse

LaMotte, A.E.; Greene, E.A.

2007-01-01

Spatial relations between land use and groundwater quality in the watershed adjacent to Assateague Island National Seashore, Maryland and Virginia, USA were analyzed by the use of two spatial models. One model used a logit analysis and the other was based on geostatistics. The models were developed and compared on the basis of existing concentrations of nitrate as nitrogen in samples from 529 domestic wells. The models were applied to produce spatial probability maps that show areas in the watershed where concentrations of nitrate in groundwater are likely to exceed a predetermined management threshold value. Maps of the watershed generated by logistic regression and probability kriging analysis showing where the probability of nitrate concentrations would exceed 3 mg/L (>0.50) compared favorably. Logistic regression was less dependent on the spatial distribution of sampled wells, and identified an additional high probability area within the watershed that was missed by probability kriging. The spatial probability maps could be used to determine the natural or anthropogenic factors that best explain the occurrence and distribution of elevated concentrations of nitrate (or other constituents) in shallow groundwater. This information can be used by local land-use planners, ecologists, and managers to protect water supplies and identify land-use planning solutions and monitoring programs in vulnerable areas. ?? 2006 Springer-Verlag.

Comparison of estimated and observed stormwater runoff for fifteen watersheds in west-central Florida, using five common design techniques

USGS Publications Warehouse

Trommer, J.T.; Loper, J.E.; Hammett, K.M.; Bowman, Georgia

1996-01-01

Hydrologists use several traditional techniques for estimating peak discharges and runoff volumes from ungaged watersheds. However, applying these techniques to watersheds in west-central Florida requires that empirical relationships be extrapolated beyond tested ranges. As a result there is some uncertainty as to their accuracy. Sixty-six storms in 15 west-central Florida watersheds were modeled using (1) the rational method, (2) the U.S. Geological Survey regional regression equations, (3) the Natural Resources Conservation Service (formerly the Soil Conservation Service) TR-20 model, (4) the Army Corps of Engineers HEC-1 model, and (5) the Environmental Protection Agency SWMM model. The watersheds ranged between fully developed urban and undeveloped natural watersheds. Peak discharges and runoff volumes were estimated using standard or recommended methods for determining input parameters. All model runs were uncalibrated and the selection of input parameters was not influenced by observed data. The rational method, only used to calculate peak discharges, overestimated 45 storms, underestimated 20 storms and estimated the same discharge for 1 storm. The mean estimation error for all storms indicates the method overestimates the peak discharges. Estimation errors were generally smaller in the urban watersheds and larger in the natural watersheds. The U.S. Geological Survey regression equations provide peak discharges for storms of specific recurrence intervals. Therefore, direct comparison with observed data was limited to sixteen observed storms that had precipitation equivalent to specific recurrence intervals. The mean estimation error for all storms indicates the method overestimates both peak discharges and runoff volumes. Estimation errors were smallest for the larger natural watersheds in Sarasota County, and largest for the small watersheds located in the eastern part of the study area. The Natural Resources Conservation Service TR-20 model, overestimated peak discharges for 45 storms and underestimated 21 storms, and overestimated runoff volumes for 44 storms and underestimated 22 storms. The mean estimation error for all storms modeled indicates that the model overestimates peak discharges and runoff volumes. The smaller estimation errors in both peak discharges and runoff volumes were for storms occurring in the urban watersheds, and the larger errors were for storms occurring in the natural watersheds. The HEC-1 model overestimated peak discharge rates for 55 storms and underestimated 11 storms. Runoff volumes were overestimated for 44 storms and underestimated for 22 storms using the Army Corps of Engineers HEC-1 model. The mean estimation error for all the storms modeled indicates that the model overestimates peak discharge rates and runoff volumes. Generally, the smaller estimation errors in peak discharges were for storms occurring in the urban watersheds, and the larger errors were for storms occurring in the natural watersheds. Estimation errors in runoff volumes; however, were smallest for the 3 natural watersheds located in the southernmost part of Sarasota County. The Environmental Protection Agency Storm Water Management model produced similar peak discharges and runoff volumes when using both the Green-Ampt and Horton infiltration methods. Estimated peak discharge and runoff volume data calculated with the Horton method was only slightly higher than those calculated with the Green-Ampt method. The mean estimation error for all the storms modeled indicates the model using the Green-Ampt infiltration method overestimates peak discharges and slightly underestimates runoff volumes. Using the Horton infiltration method, the model overestimates both peak discharges and runoff volumes. The smaller estimation errors in both peak discharges and runoff volumes were for storms occurring in the five natural watersheds in Sarasota County with the least amount of impervious cover and the lowest slopes. The largest er

Assessment of soil erosion risk in Komering watershed, South Sumatera, using SWAT model

NASA Astrophysics Data System (ADS)

Salsabilla, A.; Kusratmoko, E.

2017-07-01

Changes in land use watershed led to environmental degradation. Estimated loss of soil erosion is often difficult due to some factors such as topography, land use, climate and human activities. This study aims to predict soil erosion hazard and sediment yield using the Soil and Water Assessment Tools (SWAT) hydrological model. The SWAT was chosen because it can simulate the model with limited data. The study area is Komering watershed (806,001 Ha) in South Sumatera Province. There are two factors land management intervention: 1) land with agriculture, and 2) land with cultivation. These factors selected in accordance with the regulations of spatial plan area. Application of the SWAT demonstrated that the model can predict surface runoff, soil erosion loss and sediment yield. The erosion risk for each watershed can be classified and predicted its changes based on the scenarios which arranged. In this paper, we also discussed the relationship between the distribution of erosion risk and watershed's characteristics in a spatial perspective.

Comparing Models and Methods for the Delineation of Stream Baseflow Contribution Areas

NASA Astrophysics Data System (ADS)

Chow, R.; Frind, M.; Frind, E. O.; Jones, J. P.; Sousa, M.; Rudolph, D. L.; Nowak, W.

2016-12-01

This study addresses the delineation of areas that contribute baseflow to a stream reach, also known as stream capture zones. Such areas can be delineated using standard well capture zone delineation methods, with three important differences: (1) natural gradients are smaller compared to those produced by supply wells and are therefore subject to greater numerical errors, (2) stream discharge varies seasonally, and (3) stream discharge varies spatially. This study focuses on model-related uncertainties due to parameter non-uniqueness, discretization schemes, and particle tracking algorithms. The methodology is applied to the Alder Creek watershed in southwestern Ontario. Four different model codes are compared: HydroGeoSphere, WATFLOW, MODFLOW, and FEFLOW. In addition, two delineation methods are compared: reverse particle tracking and reverse transport, where the latter considers local-scale parameter uncertainty by using a macrodispersion term to produce a capture probability plume. The results from this study indicate that different models can calibrate acceptably well to the same data and produce very similar distributions of hydraulic head, but can produce different capture zones. The stream capture zone is found to be highly sensitive to the particle tracking algorithm. It was also found that particle tracking by itself, if applied to complex systems such as the Alder Creek watershed, would require considerable subjective judgement in the delineation of stream capture zones. Reverse transport is an alternate approach that provides probability intervals for the baseflow contribution areas. In situations where the two approaches agree, the confidence in the delineation is reinforced.

Integrated Modeling System for Analysis of Watershed Water Balance: A Case Study in the Tims Branch Watershed, South Carolina

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.

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

EPA Science Inventory

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

A method for estimating peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area

USGS Publications Warehouse

Asquith, William H.; Cleveland, Theodore G.; Roussel, Meghan C.

2011-01-01

Estimates of peak and time of peak streamflow for small watersheds (less than about 640 acres) in a suburban to urban, low-slope setting are needed for drainage design that is cost-effective and risk-mitigated. During 2007-10, the U.S. Geological Survey (USGS), in cooperation with the Harris County Flood Control District and the Texas Department of Transportation, developed a method to estimate peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area. To develop the method, 24 watersheds in the study area with drainage areas less than about 3.5 square miles (2,240 acres) and with concomitant rainfall and runoff data were selected. The method is based on conjunctive analysis of rainfall and runoff data in the context of the unit hydrograph method and the rational method. For the unit hydrograph analysis, a gamma distribution model of unit hydrograph shape (a gamma unit hydrograph) was chosen and parameters estimated through matching of modeled peak and time of peak streamflow to observed values on a storm-by-storm basis. Watershed mean or watershed-specific values of peak and time to peak ("time to peak" is a parameter of the gamma unit hydrograph and is distinct from "time of peak") of the gamma unit hydrograph were computed. Two regression equations to estimate peak and time to peak of the gamma unit hydrograph that are based on watershed characteristics of drainage area and basin-development factor (BDF) were developed. For the rational method analysis, a lag time (time-R), volumetric runoff coefficient, and runoff coefficient were computed on a storm-by-storm basis. Watershed-specific values of these three metrics were computed. A regression equation to estimate time-R based on drainage area and BDF was developed. Overall arithmetic means of volumetric runoff coefficient (0.41 dimensionless) and runoff coefficient (0.25 dimensionless) for the 24 watersheds were used to express the rational method in terms of excess rainfall (the excess rational method). Both the unit hydrograph method and excess rational method are shown to provide similar estimates of peak and time of peak streamflow. The results from the two methods can be combined by using arithmetic means. A nomograph is provided that shows the respective relations between the arithmetic-mean peak and time of peak streamflow to drainage areas ranging from 10 to 640 acres. The nomograph also shows the respective relations for selected BDF ranging from undeveloped to fully developed conditions. The nomograph represents the peak streamflow for 1 inch of excess rainfall based on drainage area and BDF; the peak streamflow for design storms from the nomograph can be multiplied by the excess rainfall to estimate peak streamflow. Time of peak streamflow is readily obtained from the nomograph. Therefore, given excess rainfall values derived from watershed-loss models, which are beyond the scope of this report, the nomograph represents a method for estimating peak and time of peak streamflow for applicable watersheds in the Houston metropolitan area. Lastly, analysis of the relative influence of BDF on peak streamflow is provided, and the results indicate a 0:04log10 cubic feet per second change of peak streamflow per positive unit of change in BDF. This relative change can be used to adjust peak streamflow from the method or other hydrologic methods for a given BDF to other BDF values; example computations are provided.

Pathogen transport and fate modeling in the Upper Salem River Watershed using SWAT model.

PubMed

Niazi, Mehran; Obropta, Christopher; Miskewitz, Robert

2015-03-15

Simulation of the fate and transport of pathogen contamination was conducted with SWAT for the Upper Salem River Watershed, located in Salem County, New Jersey. This watershed is 37 km(2) and land uses are predominantly agricultural. The watershed drains to a 32 km stretch of the Salem River upstream of the head of tide. This strech is identified on the 303(d) list as impaired for pathogens. The overall goal of this research was to use SWAT as a tool to help to better understand how two pathogen indicators (Escherichia coli and fecal coliform) are transported throughout the watershed, by determining the model parameters that control the fate and transport of these two indicator species. This effort was the first watershed modeling attempt with SWAT to successfully simulate E. coli and fecal coliform simultaneously. Sensitivity analysis has been performed for flow as well as fecal coliform and E. coli. Hydrologic calibration at six sampling locations indicate that the model provides a "good" prediction of watershed outlet flow (E = 0.69) while at certain upstream calibration locations predictions are less representative (0.32 < E < 0.70). Monthly calibration and validation of the pathogen transport and fate model was conducted for both fecal coliform (0.07 < E < 0.47 and -0.94 < E < 0.33) and E. coli (0.03 < E < 0.39 and -0.81 < E < 0.31) for the six sampling points. The fit of the model compared favorably with many similar pathogen modeling efforts. The research contributes new knowledge in E. coli and fecal coliform modeling and will help increase the understanding of sensitivity analysis and pathogen modeling with SWAT at the watershed scale. Copyright © 2014 Elsevier Ltd. All rights reserved.

Conceptual model of sediment processes in the upper Yuba River watershed, Sierra Nevada, CA

USGS Publications Warehouse

Curtis, J.A.; Flint, L.E.; Alpers, Charles N.; Yarnell, S.M.

2005-01-01

This study examines the development of a conceptual model of sediment processes in the upper Yuba River watershed; and we hypothesize how components of the conceptual model may be spatially distributed using a geographical information system (GIS). The conceptual model illustrates key processes controlling sediment dynamics in the upper Yuba River watershed and was tested and revised using field measurements, aerial photography, and low elevation videography. Field reconnaissance included mass wasting and channel storage inventories, assessment of annual channel change in upland tributaries, and evaluation of the relative importance of sediment sources and transport processes. Hillslope erosion rates throughout the study area are relatively low when compared to more rapidly eroding landscapes such as the Pacific Northwest and notable hillslope sediment sources include highly erodible andesitic mudflows, serpentinized ultramafics, and unvegetated hydraulic mine pits. Mass wasting dominates surface erosion on the hillslopes; however, erosion of stored channel sediment is the primary contributor to annual sediment yield. We used GIS to spatially distribute the components of the conceptual model and created hillslope erosion potential and channel storage models. The GIS models exemplify the conceptual model in that landscapes with low potential evapotranspiration, sparse vegetation, steep slopes, erodible geology and soils, and high road densities display the greatest hillslope erosion potential and channel storage increases with increasing stream order. In-channel storage in upland tributaries impacted by hydraulic mining is an exception. Reworking of stored hydraulic mining sediment in low-order tributaries continues to elevate upper Yuba River sediment yields. Finally, we propose that spatially distributing the components of a conceptual model in a GIS framework provides a guide for developing more detailed sediment budgets or numerical models making it an inexpensive way to develop a roadmap for understanding sediment dynamics at a watershed scale.

Rainfall-Runoff and Water-Balance Models for Management of the Fena Valley Reservoir, Guam

USGS Publications Warehouse

Yeung, Chiu W.

2005-01-01

The U.S. Geological Survey's Precipitation-Runoff Modeling System (PRMS) and a generalized water-balance model were calibrated and verified for use in estimating future availability of water in the Fena Valley Reservoir in response to various combinations of water withdrawal rates and rainfall conditions. Application of PRMS provides a physically based method for estimating runoff from the Fena Valley Watershed during the annual dry season, which extends from January through May. Runoff estimates from the PRMS are used as input to the water-balance model to estimate change in water levels and storage in the reservoir. A previously published model was calibrated for the Maulap and Imong River watersheds using rainfall data collected outside of the watershed. That model was applied to the Almagosa River watershed by transferring calibrated parameters and coefficients because information on daily diversions at the Almagosa Springs upstream of the gaging station was not available at the time. Runoff from the ungaged land area was not modeled. For this study, the availability of Almagosa Springs diversion data allowed the calibration of PRMS for the Almagosa River watershed. Rainfall data collected at the Almagosa rain gage since 1992 also provided better estimates of rainfall distribution in the watershed. In addition, the discontinuation of pan-evaporation data collection in 1998 required a change in the evapotranspiration estimation method used in the PRMS model. These reasons prompted the update of the PRMS for the Fena Valley Watershed. Simulated runoff volume from the PRMS compared reasonably with measured values for gaging stations on Maulap, Almagosa, and Imong Rivers, tributaries to the Fena Valley Reservoir. On the basis of monthly runoff simulation for the dry seasons included in the entire simulation period (1992-2001), the total volume of runoff can be predicted within -3.66 percent at Maulap River, within 5.37 percent at Almagosa River, and within 10.74 percent at Imong River. Month-end reservoir volumes simulated by the reservoir water-balance model for both calibration and verification periods compared closely with measured reservoir volumes. Errors for the calibration periods ranged from 4.51 percent [208.7 acre-feet (acre-ft) or 68.0 million gallons (Mgal)] to -5.90 percent (-317.8 acre-ft or -103.6 Mgal). For the verification periods, errors ranged from 1.69 percent (103.5 acre-ft or 33.7 Mgal) to -4.60 percent (-178.7 acre-ft or -58.2 Mgal). Monthly simulation bias ranged from -0.19 percent for the calibration period to -0.98 percent for the verification period; relative error ranged from -0.37 to -1.12 percent, respectively. Relatively small bias indicated that the model did not consistently overestimate or underestimate reservoir volume.

Evaluation of a non-point source pollution model, AnnAGNPS, in a tropical watershed

USGS Publications Warehouse

Polyakov, V.; Fares, A.; Kubo, D.; Jacobi, J.; Smith, C.

2007-01-01

Impaired water quality caused by human activity and the spread of invasive plant and animal species has been identified as a major factor of degradation of coastal ecosystems in the tropics. The main goal of this study was to evaluate the performance of AnnAGNPS (Annualized Non-Point Source Pollution Model), in simulating runoff and soil erosion in a 48 km2 watershed located on the Island of Kauai, Hawaii. The model was calibrated and validated using 2 years of observed stream flow and sediment load data. Alternative scenarios of spatial rainfall distribution and canopy interception were evaluated. Monthly runoff volumes predicted by AnnAGNPS compared well with the measured data (R2 = 0.90, P < 0.05); however, up to 60% difference between the actual and simulated runoff were observed during the driest months (May and July). Prediction of daily runoff was less accurate (R2 = 0.55, P < 0.05). Predicted and observed sediment yield on a daily basis was poorly correlated (R2 = 0.5, P < 0.05). For the events of small magnitude, the model generally overestimated sediment yield, while the opposite was true for larger events. Total monthly sediment yield varied within 50% of the observed values, except for May 2004. Among the input parameters the model was most sensitive to the values of ground residue cover and canopy cover. It was found that approximately one third of the watershed area had low sediment yield (0-1 t ha-1 y-1), and presented limited erosion threat. However, 5% of the area had sediment yields in excess of 5 t ha-1 y-1. Overall, the model performed reasonably well, and it can be used as a management tool on tropical watersheds to estimate and compare sediment loads, and identify "hot spots" on the landscape. ?? 2007 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Turnbull, S. J.

2017-12-01

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

Predicting watershed acidification under alternate rainfall conditions

USGS Publications Warehouse

Huntington, T.G.

1996-01-01

The effect of alternate rainfall scenarios on acidification of a forested watershed subjected to chronic acidic deposition was assessed using the model of acidification of groundwater in catchments (MAGIC). The model was calibrated at the Panola Mountain Research Watershed, near Atlanta, Georgia, U.S.A. using measured soil properties, wet and dry deposition, and modeled hydrologic routing. Model forecast simulations were evaluated to compare alternate temporal averaging of rainfall inputs and variations in rainfall amount and seasonal distribution. Soil water alkalinity was predicted to decrease to substantially lower concentrations under lower rainfall compared with current or higher rainfall conditions. Soil water alkalinity was also predicted to decrease to lower levels when the majority of rainfall occurred during the growing season compared with other rainfall distributions. Changes in rainfall distribution that result in decreases in net soil water flux will temporarily delay acidification. Ultimately, however, decreased soil water flux will result in larger increases in soil- adsorbed sulfur and soil-water sulfate concentrations and decreases in alkalinity when compared to higher water flux conditions. Potential climate change resulting in significant changes in rainfall amounts, seasonal distribution of rainfall, or evapotranspiration will change net soil water flux and, consequently, will affect the dynamics of the acidification response to continued sulfate loading.

Assessing the seasonality and uncertainty in evapotranspiration partitioning using a tracer-aided model

NASA Astrophysics Data System (ADS)

Smith, A. A.; Welch, C.; Stadnyk, T. A.

2018-05-01

Evapotranspiration (ET) partitioning is a growing field of research in hydrology due to the significant fraction of watershed water loss it represents. The use of tracer-aided models has improved understanding of watershed processes, and has significant potential for identifying time-variable partitioning of evaporation (E) from ET. A tracer-aided model was used to establish a time-series of E/ET using differences in riverine δ18O and δ2H in four northern Canadian watersheds (lower Nelson River, Manitoba, Canada). On average E/ET follows a parabolic trend ranging from 0.7 in the spring and autumn to 0.15 (three watersheds) and 0.5 (fourth watershed) during the summer growing season. In the fourth watershed wetlands and shrubs dominate land cover. During the summer, E/ET ratios are highest in wetlands for three watersheds (10% higher than unsaturated soil storage), while lowest for the fourth watershed (20% lower than unsaturated soil storage). Uncertainty of the ET partition parameters is strongly influenced by storage volumes, with large storage volumes increasing partition uncertainty. In addition, higher simulated soil moisture increases estimated E/ET. Although unsaturated soil storage accounts for larger surface areas in these watersheds than wetlands, riverine isotopic composition is more strongly affected by E from wetlands. Comparisons of E/ET to measurement-intensive studies in similar ecoregions indicate that the methodology proposed here adequately partitions ET.

Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models

NASA Astrophysics Data System (ADS)

Zhu, Hongchun; Zhao, Yipeng; Liu, Haiying

2018-04-01

Scale is the basic attribute for expressing and describing spatial entity and phenomena. It offers theoretical significance in the study of gully structure information, variable characteristics of watershed morphology, and development evolution at different scales. This research selected five different areas in China's Loess Plateau as the experimental region and used DEM data at different scales as the experimental data. First, the change rule of the characteristic parameters of the data at different scales was analyzed. The watershed structure information did not change along with a change in the data scale. This condition was proven by selecting indices of gully bifurcation ratio and fractal dimension as characteristic parameters of watershed structure information. Then, the change rule of the characteristic parameters of gully structure with different analysis scales was analyzed by setting the scale sequence of analysis at the extraction gully. The gully structure of the watershed changed with variations in the analysis scale, and the change rule was obvious when the gully level changed. Finally, the change rule of the characteristic parameters of the gully structure at different areas was analyzed. The gully fractal dimension showed a significant numerical difference in different areas, whereas the variation of the gully branch ratio was small. The change rule indicated that the development degree of the gully obviously varied in different regions, but the morphological structure was basically similar.

Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models

NASA Astrophysics Data System (ADS)

Zhu, Hongchun; Zhao, Yipeng; Liu, Haiying

2018-06-01

Scale is the basic attribute for expressing and describing spatial entity and phenomena. It offers theoretical significance in the study of gully structure information, variable characteristics of watershed morphology, and development evolution at different scales. This research selected five different areas in China's Loess Plateau as the experimental region and used DEM data at different scales as the experimental data. First, the change rule of the characteristic parameters of the data at different scales was analyzed. The watershed structure information did not change along with a change in the data scale. This condition was proven by selecting indices of gully bifurcation ratio and fractal dimension as characteristic parameters of watershed structure information. Then, the change rule of the characteristic parameters of gully structure with different analysis scales was analyzed by setting the scale sequence of analysis at the extraction gully. The gully structure of the watershed changed with variations in the analysis scale, and the change rule was obvious when the gully level changed. Finally, the change rule of the characteristic parameters of the gully structure at different areas was analyzed. The gully fractal dimension showed a significant numerical difference in different areas, whereas the variation of the gully branch ratio was small. The change rule indicated that the development degree of the gully obviously varied in different regions, but the morphological structure was basically similar.

Application of SWAT and CAST model on Damma Glacier CZO

NASA Astrophysics Data System (ADS)

Andrianaki, Maria; Bernasconi, Stefano; Kobierska, Florian; Nikolaidis, Nikolaos

2014-05-01

Damma Glacier is one of the Critical Zone Observatories, located at the central Swiss Alps, Switzerland and is characterized by a 150-year soil chronosequence. In this study, we used the Soil and Water Assessment Tool (SWAT) to simulate the hydrology of the watershed of Damma glacier, Switzerland and of the extended area that feeds Goescheneralpsee and includes Damma watershed. SWAT was calibrated for the watershed of Damma glacier with the stream flow data collected between 2009 and 2011. Subsequently and in order to study the up-scalling effect, SWAT was run for the greater area using the same parameters. Carbon accumulation and aggregate formation along Damma soil chronosequence was modelled using ROTH-C and CAST models.

Agricultural Policy Environmental eXtender Simulation of Three Adjacent Row-Crop Watersheds in the Claypan Region.

PubMed

Anomaa Senaviratne, G M M M; Udawatta, Ranjith P; Baffaut, Claire; Anderson, Stephen H

2013-01-01

The Agricultural Policy Environmental Extender (APEX) model is used to evaluate best management practices on pollutant loading in whole farms or small watersheds. The objectives of this study were to conduct a sensitivity analysis to determine the effect of model parameters on APEX output and use the parameterized, calibrated, and validated model to evaluate long-term benefits of grass waterways. The APEX model was used to model three (East, Center, and West) adjacent field-size watersheds with claypan soils under a no-till corn ( L.)/soybean [ (L.) Merr.] rotation. Twenty-seven parameters were sensitive for crop yield, runoff, sediment, nitrogen (dissolved and total), and phosphorous (dissolved and total) simulations. The model was calibrated using measured event-based data from the Center watershed from 1993 to 1997 and validated with data from the West and East watersheds. Simulated crop yields were within ±13% of the measured yield. The model performance for event-based runoff was excellent, with calibration and validation > 0.9 and Nash-Sutcliffe coefficients (NSC) > 0.8, respectively. Sediment and total nitrogen calibration results were satisfactory for larger rainfall events (>50 mm), with > 0.5 and NSC > 0.4, but validation results remained poor, with NSC between 0.18 and 0.3. Total phosphorous was well calibrated and validated, with > 0.8 and NSC > 0.7, respectively. The presence of grass waterways reduced annual total phosphorus loadings by 13 to 25%. The replicated study indicates that APEX provides a convenient and efficient tool to evaluate long-term benefits of conservation practices. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Effectiveness of SWAT in characterizing the watershed hydrology in the snowy-mountainous Lower Bear Malad River (LBMR) watershed in Box Elder County, Utah

NASA Astrophysics Data System (ADS)

Salha, A. A.; Stevens, D. K.

2015-12-01

Distributed watershed models are essential for quantifying sediment and nutrient loads that originate from point and nonpoint sources. Such models are primary means towards generating pollutant estimates in ungaged watersheds and respond well at watershed scales by capturing the variability in soils, climatic conditions, land uses/covers and management conditions over extended periods of time. This effort evaluates the performance of the Soil and Water Assessment Tool (SWAT) model as a watershed level tool to investigate, manage, and characterize the transport and fate of nutrients in Lower Bear Malad River (LBMR) watershed (Subbasin HUC 16010204) in Utah. Water quality concerns have been documented and are primarily attributed to high phosphorus and total suspended sediment concentrations caused by agricultural and farming practices along with identified point sources (WWTPs). Input data such as Digital Elevation Model (DEM), land use/Land cover (LULC), soils, and climate data for 10 years (2000-2010) is utilized to quantify the LBMR streamflow. Such modeling is useful in developing the required water quality regulations such as Total Maximum Daily Loads (TMDL). Measured concentrations of nutrients were closely captured by simulated monthly nutrient concentrations based on the R2 and Nash- Sutcliffe fitness criteria. The model is expected to be able to identify contaminant non-point sources, identify areas of high pollution risk, locate optimal monitoring sites, and evaluate best management practices to cost-effectively reduce pollution and improve water quality as required by the LBMR watershed's TMDL.

Distributed Soil Moisture Estimation in a Mountainous Semiarid Basin: Constraining Soil Parameter Uncertainty through Field Studies

NASA Astrophysics Data System (ADS)

Yatheendradas, S.; Vivoni, E.

2007-12-01

A common practice in distributed hydrological modeling is to assign soil hydraulic properties based on coarse textural datasets. For semiarid regions with poor soil information, the performance of a model can be severely constrained due to the high model sensitivity to near-surface soil characteristics. Neglecting the uncertainty in soil hydraulic properties, their spatial variation and their naturally-occurring horizonation can potentially affect the modeled hydrological response. In this study, we investigate such effects using the TIN-based Real-time Integrated Basin Simulator (tRIBS) applied to the mid-sized (100 km2) Sierra Los Locos watershed in northern Sonora, Mexico. The Sierra Los Locos basin is characterized by complex mountainous terrain leading to topographic organization of soil characteristics and ecosystem distributions. We focus on simulations during the 2004 North American Monsoon Experiment (NAME) when intensive soil moisture measurements and aircraft- based soil moisture retrievals are available in the basin. Our experiments focus on soil moisture comparisons at the point, topographic transect and basin scales using a range of different soil characterizations. We compare the distributed soil moisture estimates obtained using (1) a deterministic simulation based on soil texture from coarse soil maps, (2) a set of ensemble simulations that capture soil parameter uncertainty and their spatial distribution, and (3) a set of simulations that conditions the ensemble on recent soil profile measurements. Uncertainties considered in near-surface soil characterization provide insights into their influence on the modeled uncertainty, into the value of soil profile observations, and into effective use of on-going field observations for constraining the soil moisture response uncertainty.

Soil-Water Balance (SWB) model estimates of soil-moisture variability and groundwater recharge in the South Platte watershed, Colorado

NASA Astrophysics Data System (ADS)

Anderson, A. M.; Walker, E. L.; Hogue, T. S.; Ruybal, C. J.

2015-12-01

Unconventional energy production in semi-arid regions places additional stress on already over-allocated water systems. Production of shale gas and oil resources in northern Colorado has rapidly increased since 2010, and is expected to continue growing due to advances in horizontal drilling and hydraulic fracturing. This unconventional energy production has implications for the availability of water in the South Platte watershed, where water demand for hydraulic fracturing of unconventional shale resources reached ~16,000 acre-feet in 2014. Groundwater resources are often exploited to meet water demands for unconventional energy production in regions like the South Platte basin, where surface water supply is limited and allocated across multiple uses. Since groundwater is often a supplement to surface water in times of drought and peak demand, variability in modeled recharge estimates can significantly impact projected availability. In the current work we used the Soil-Water Balance Model (SWB) to assess the variability in model estimates of actual evapotranspiration (ET) and soil-moisture conditions utilized to derive estimates of groundwater recharge. Using both point source and spatially distributed data, we compared modeled actual ET and soil-moisture derived from several potential ET methods, such as Thornthwaite-Mather, Jense-Haise, Turc, and Hargreaves-Samani, to historic soil moisture conditions obtained through sources including the Gravity Recovery and Climate Experiment (GRACE). In addition to a basin-scale analysis, we divided the South Platte watershed into sub-basins according to land cover to evaluate model capabilities of estimating soil-moisture parameters with variations in land cover and topography. Results ultimately allow improved prediction of groundwater recharge under future scenarios of climate and land cover change. This work also contributes to complementary subsurface groundwater modeling and decision support modeling in the South Platte.

Application of two hydrologic models with different runoff mechanisms to a hillslope dominated watershed in the northeastern US: A comparison of HSPF and SMR

USGS Publications Warehouse

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.

Sensitivity of stream flow and water table depth to potential climatic variability in a coastal forested watershed

Treesearch

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

2010-01-01

A physically based distributed hydrological model, MIKE SHE, was used to evaluate the effects of altered temperature and precipitation regimes on the streamflow and water table in a forested watershed on the southeastern Atlantic coastal plain. The model calibration and validation against both streamflow and water table depth showed that the MIKE SHE was applicable for...

Watershed and Economic Data InterOperability (WEDO) ...

EPA Pesticide Factsheets

Watershed and Economic Data InterOperability (WEDO) is a system of information technologies designed to publish watershed modeling studies for reuse. WEDO facilitates three aspects of interoperability: discovery, evaluation and integration of data. This increased level of interoperability goes beyond the current practice of publishing modeling studies as reports or journal articles. Rather than summarized results, modeling studies can be published with their full complement of input data, calibration parameters and output with associated metadata for easy duplication by others. Reproducible science is possible only if researchers can find, evaluate and use complete modeling studies performed by other modelers. WEDO greatly increases transparency by making detailed data available to the scientific community.WEDO is a next generation technology, a Web Service linked to the EPA’s EnviroAtlas for discovery of modeling studies nationwide. Streams and rivers are identified using the National Hydrography Dataset network and stream IDs. Streams with modeling studies available are color coded in the EnviroAtlas. One can select streams within a watershed of interest to readily find data available via WEDO. The WEDO website is linked from the EnviroAtlas to provide a thorough review of each modeling study. WEDO currently provides modeled flow and water quality time series, designed for a broad range of watershed and economic models for nutrient trading market analysis. M

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT ...

EPA Pesticide Factsheets

The Automated Geospatial Watershed Assessment tool (AGWA) is a GIS interface jointly developed by the USDA Agricultural Research Service, the U.S. Environmental Protection Agency, the University of Arizona, and the University of Wyoming to automate the parameterization and execution of the Soil Water Assessment Tool (SWAT) and KINEmatic Runoff and EROSion (KINEROS2) hydrologic models. The application of these two models allows AGWA to conduct hydrologic modeling and watershed assessments at multiple temporal and spatial scales. AGWA’s current outputs are runoff (volumes and peaks) and sediment yield, plus nitrogen and phosphorus with the SWAT model. AGWA uses commonly available GIS data layers to fully parameterize, execute, and visualize results from both models. Through an intuitive interface the user selects an outlet from which AGWA delineates and discretizes the watershed using a Digital Elevation Model (DEM) based on the individual model requirements. The watershed model elements are then intersected with soils and land cover data layers to derive the requisite model input parameters. The chosen model is then executed, and the results are imported back into AGWA for visualization. This allows managers to identify potential problem areas where additional monitoring can be undertaken or mitigation activities can be focused. AGWA also has tools to apply an array of best management practices. There are currently two versions of AGWA available; AGWA 1.5 for

Watershed modeling of dissolved oxygen and biochemical oxygen demand using a hydrological simulation Fortran program.

PubMed

Liu, Zhijun; Kieffer, Janna M; Kingery, William L; Huddleston, David H; Hossain, Faisal

2007-11-01

Several inland water bodies in the St. Louis Bay watershed have been identified as being potentially impaired due to low level of dissolved oxygen (DO). In order to calculate the total maximum daily loads (TMDL), a standard watershed model supported by U.S. Environmental Protection Agency, Hydrological Simulation Program Fortran (HSPF), was used to simulate water temperature, DO, and bio-chemical oxygen demand (BOD). Both point and non-point sources of BOD were included in watershed modeling. The developed model was calibrated at two time periods: 1978 to 1986 and 2000 to 2001 with simulated DO closely matched the observed data and captured the seasonal variations. The model represented the general trend and average condition of observed BOD. Water temperature and BOD decay are the major factors that affect DO simulation, whereas nutrient processes, including nitrification, denitrification, and phytoplankton cycle, have slight impacts. The calibrated water quality model provides a representative linkage between the sources of BOD and in-stream DO\\BOD concentrations. The developed input parameters in this research could be extended to similar coastal watersheds for TMDL determination and Best Management Practice (BMP) evaluation.

Modelling runoff in the northern boreal forest using SLURP with snow ripening and frozen ground

NASA Astrophysics Data System (ADS)

St. Laurent, M. E.; Valeo, C.

2003-04-01

Northern Manitoba is rich in water resources and the management of this water resource is affected by the hydrological processes taking place in the primarily Boreal forested, flat landscape of the region. This work provides insight into large-scale hydrological modelling in this area using the SLURP hydrological model while incorporating the effects of ripening snow and frozen ground. SLURP was applied to two large watersheds in northern Manitoba. The Taylor River watershed (800 square-km) and the Burntwood River watershed (7000 square-km) were used as study boundaries for the calibration and validation of the original SLURP model (version 12.2) and a modified version that incorporated frozen ground and ripening snow. Digital Elevation Models were derived with ARC/INFO's TOPOGRID function, and in conjunction with digital land cover data, ASAs and their associated physiographic data were derived using SLURPView. A thorough literature review of boreal forest hydrology provided initial parameter estimates. Daily data from 1984 to 1998 were used to calibrate and verify the original model under a variety of meteorological conditions. Calibration on the Taylor River watershed produced respectable results, and model verification efficiencies over the 15 year period were quite good. Verification performance of the Taylor parameter set on the Burntwood River watershed was not acceptable, but only modifications to the evapotranspiration parameters were required to bring model performance up to acceptable levels. Comparisons between observed and computed hydrographs identified problems with spring snowmelt timing, peak and volume prediction. This may be attributed to a lack of consideration for frozen ground in the model, and the use of the temperature index method for snowmelt. Simulations that incorporated a widely used frozen ground infiltration model into SLURP did not improve model performance. However, when SLURP's snowmelt routine was modified to consider the effects of snow ripening in the snowmelt process, model predictions of spring freshet volume and timing were greatly improved. The modified SLURP model depleted the snowpack over shorter periods of time and thus, significantly raised model efficiencies in the snowmelt period for 12 of the 15 years. Snowmelt accumulation curves developed for the original and modified model were found to be landcover dependent. The Muskeg and Coniferous landcovers were found to have the smallest changes in snow depletion periods between the original and modified SLURP models.

75 FR 48989 - Federal Interagency Steering Committee on Multimedia Environmental Modeling

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-12

..., ISCMEM Chair, U.S. Geological Survey, National Research Program, Branch of Regional Research, Eastern..., optimization modeling, reactive transport modeling, and watershed and distributed water quality modeling...

Equations for estimating synthetic unit-hydrograph parameter values for small watersheds in Lake County, Illinois

USGS Publications Warehouse

Melching, C.S.; Marquardt, J.S.

1997-01-01

Design hydrographs computed from design storms, simple models of abstractions (interception, depression storage, and infiltration), and synthetic unit hydrographs provide vital information for stormwater, flood-plain, and water-resources management throughout the United States. Rainfall and runoff data for small watersheds in Lake County collected between 1990 and 1995 were studied to develop equations for estimation of synthetic unit-hydrograph parameters on the basis of watershed and storm characteristics. The synthetic unit-hydrograph parameters of interest were the time of concentration (TC) and watershed-storage coefficient (R) for the Clark unit-hydrograph method, the unit-graph lag (UL) for the Soil Conservation Service (now known as the Natural Resources Conservation Service) dimensionless unit hydrograph, and the hydrograph-time lag (TL) for the linear-reservoir method for unit-hydrograph estimation. Data from 66 storms with effective-precipitation depths greater than 0.4 inches on 9 small watersheds (areas between 0.06 and 37 square miles (mi2)) were utilized to develop the estimation equations, and data from 11 storms on 8 of these watersheds were utilized to verify (test) the estimation equations. The synthetic unit-hydrograph parameters were determined by calibration using the U.S. Army Corps of Engineers Flood Hydrograph Package HEC-1 (TC, R, and UL) or by manual analysis of the rainfall and run-off data (TL). The relation between synthetic unit-hydrograph parameters, and watershed and storm characteristics was determined by multiple linear regression of the logarithms of the parameters and characteristics. Separate sets of equations were developed with watershed area and main channel length as the starting parameters. Percentage of impervious cover, main channel slope, and depth of effective precipitation also were identified as important characteristics for estimation of synthetic unit-hydrograph parameters. The estimation equations utilizing area had multiple correlation coefficients of 0.873, 0.961, 0.968, and 0.963 for TC, R, UL, and TL, respectively, and the estimation equations utilizing main channel length had multiple correlation coefficients of 0.845, 0.957, 0.961, and 0.963 for TC, R, UL, and TL, respectively. Simulation of the measured hydrographs for the verification storms utilizing TC and R obtained from the estimation equations yielded good results without calibration. The peak discharge for 8 of the 11 storms was estimated within 25 percent and the time-to-peak discharge for 10 of the 11 storms was estimated within 20 percent. Thus, application of the estimation equations to determine synthetic unit-hydrograph parameters for design-storm simulation may result in reliable design hydrographs; as long as the physical characteristics of the watersheds under consideration are within the range of those for the watersheds in this study (area: 0.06-37 mi2, main channel length: 0.33-16.6 miles, main channel slope: 3.13-55.3 feet per mile, and percentage of impervious cover: 7.32-40.6 percent). The estimation equations are most reliable when applied to watersheds with areas less than 25 mi2.

Stream chemistry modeling of two watersheds in the Front Range, Colorado

USGS Publications Warehouse

Meixner, Thomas; Bales, Roger C.; Williams, Mark W.; Campbell, Donald H.; Baron, Jill S.

2000-01-01

We investigated the hydrologic, geochemical, and biogeochemical controls on stream chemical composition on the Green Lakes Valley and Andrews Creek watersheds using the alpine hydrochemical model (AHM). Both sites had comparable data sets from 1994 and 1996, including high‐resolution spatial data and high‐frequency time series of hydrology, geochemistry, and meteorology. The model of each watershed consisted of three terrestrial subunits (soil, talus, and rock), with the routing between the subunits determined by spatial land cover data. Using 1994 data for model calibration and 1996 data for evaluation, AHM captured the dominant processes and successfully simulated daily stream chemical composition on both watersheds. These results confirm our procedure of using spatial and site‐specific field and laboratory data to generate an initial catchment model and then calibrating the model to calculate effective parameters for unmeasured processes. A net source of nitrogen was identified in the Andrews Creek watershed during the spring snowmelt period, whereas nitrogen was immobilized in the Green Lakes Valley. This difference was most likely due to the larger and more dominant area of talus in the Andrews Creek watershed. Our results also indicate that routing of snowmelt through either soil or talus material is sufficient for retention of H+ and release of base cations but that N retention is more important on areas mapped as soil. Owing to the larger ionic pulse and larger fraction of surface runoff the Green Lakes Valley was more sensitive to a doubling of wet deposition chemistry than the Andrews Creek watershed.

Incorporating uncertainty into the ranking of SPARROW model nutrient yields from Mississippi/Atchafalaya River basin watersheds

USGS Publications Warehouse

Robertson, Dale M.; Schwarz, Gregory E.; Saad, David A.; Alexander, Richard B.

2009-01-01

Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying “high priority” areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient-reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight-digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.

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

NASA Technical Reports Server (NTRS)

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

1997-01-01

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

Mercury concentrations in lentic fish populations related to ecosystem and watershed characteristics

Treesearch

Andrew L. Rypel

2010-01-01

Predicting mercury (Hg) concentrations of fishes at large spatial scales is a fundamental environmental challenge with the potential to improve human health. In this study, mercury concentrations were examined for five species across 161 lakes and ecosystem, and watershed parameters were investigated as explanatory variables in statistical models. For all species, Hg...

Remote sensing characterization of the Animas River watershed, southwestern Colorado, by AVIRIS imaging spectroscopy

USGS Publications Warehouse

Dalton, J.B.; Bove, D.J.; Mladinich, C.S.

2005-01-01

Visible-wavelength and near-infrared image cubes of the Animas River watershed in southwestern Colorado have been acquired by the Jet Propulsion Laboratory's Airborne Visible and InfraRed Imaging Spectrometer (AVIRIS) instrument and processed using the U.S. Geological Survey Tetracorder v3.6a2 implementation. The Tetracorder expert system utilizes a spectral reference library containing more than 400 laboratory and field spectra of end-member minerals, mineral mixtures, vegetation, manmade materials, atmospheric gases, and additional substances to generate maps of mineralogy, vegetation, snow, and other material distributions. Major iron-bearing, clay, mica, carbonate, sulfate, and other minerals were identified, among which are several minerals associated with acid rock drainage, including pyrite, jarosite, alunite, and goethite. Distributions of minerals such as calcite and chlorite indicate a relationship between acid-neutralizing assemblages and stream geochemistry within the watershed. Images denoting material distributions throughout the watershed have been orthorectified against digital terrain models to produce georeferenced image files suitable for inclusion in Geographic Information System databases. Results of this study are of use to land managers, stakeholders, and researchers interested in understanding a number of characteristics of the Animas River watershed.

Evidence of nonextensive statistical physics behavior in the watershed distribution in active tectonic areas: examples from Greece

NASA Astrophysics Data System (ADS)

Vallianatos, Filippos; Kouli, Maria

2013-08-01

The Digital Elevation Model (DEM) for the Crete Island with a resolution of approximately 20 meters was used in order to delineate watersheds by computing the flow direction and using it in the Watershed function. The Watershed function uses a raster of flow direction to determine contributing area. The Geographic Information Systems routine procedure was applied and the watersheds as well as the streams network (using a threshold of 2000 cells, i.e. the minimum number of cells that constitute a stream) were extracted from the hydrologically corrected (free of sinks) DEM. A number of a few thousand watersheds were delineated, and their areal extent was calculated. From these watersheds a number of 300 was finally selected for further analysis as the watersheds of extremely small area were excluded in order to avoid possible artifacts. Our analysis approach is based on the basic principles of Complexity theory and Tsallis Entropy introduces in the frame of non-extensive statistical physics. This concept has been successfully used for the analysis of a variety of complex dynamic systems including natural hazards, where fractality and long-range interactions are important. The analysis indicates that the statistical distribution of watersheds can be successfully described with the theoretical estimations of non-extensive statistical physics implying the complexity that characterizes the occurrences of them.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

The Rangeland Hydrology and Erosion Model: A Dynamic Approach for Predicting Soil Loss on Rangelands

NASA Astrophysics Data System (ADS)

Hernandez, Mariano; Nearing, Mark A.; Al-Hamdan, Osama Z.; Pierson, Frederick B.; Armendariz, Gerardo; Weltz, Mark A.; Spaeth, Kenneth E.; Williams, C. Jason; Nouwakpo, Sayjro K.; Goodrich, David C.; Unkrich, Carl L.; Nichols, Mary H.; Holifield Collins, Chandra D.

2017-11-01

In this study, we present the improved Rangeland Hydrology and Erosion Model (RHEM V2.3), a process-based erosion prediction tool specific for rangeland application. The article provides the mathematical formulation of the model and parameter estimation equations. Model performance is assessed against data collected from 23 runoff and sediment events in a shrub-dominated semiarid watershed in Arizona, USA. To evaluate the model, two sets of primary model parameters were determined using the RHEM V2.3 and RHEM V1.0 parameter estimation equations. Testing of the parameters indicated that RHEM V2.3 parameter estimation equations provided a 76% improvement over RHEM V1.0 parameter estimation equations. Second, the RHEM V2.3 model was calibrated to measurements from the watershed. The parameters estimated by the new equations were within the lowest and highest values of the calibrated parameter set. These results suggest that the new parameter estimation equations can be applied for this environment to predict sediment yield at the hillslope scale. Furthermore, we also applied the RHEM V2.3 to demonstrate the response of the model as a function of foliar cover and ground cover for 124 data points across Arizona and New Mexico. The dependence of average sediment yield on surface ground cover was moderately stronger than that on foliar cover. These results demonstrate that RHEM V2.3 predicts runoff volume, peak runoff, and sediment yield with sufficient accuracy for broad application to assess and manage rangeland systems.

Real-time implementations of image segmentation algorithms on shared memory multicore architecture: a survey (Conference Presentation)

NASA Astrophysics Data System (ADS)

Akil, Mohamed

2017-05-01

The real-time processing is getting more and more important in many image processing applications. Image segmentation is one of the most fundamental tasks image analysis. As a consequence, many different approaches for image segmentation have been proposed. The watershed transform is a well-known image segmentation tool. The watershed transform is a very data intensive task. To achieve acceleration and obtain real-time processing of watershed algorithms, parallel architectures and programming models for multicore computing have been developed. This paper focuses on the survey of the approaches for parallel implementation of sequential watershed algorithms on multicore general purpose CPUs: homogeneous multicore processor with shared memory. To achieve an efficient parallel implementation, it's necessary to explore different strategies (parallelization/distribution/distributed scheduling) combined with different acceleration and optimization techniques to enhance parallelism. In this paper, we give a comparison of various parallelization of sequential watershed algorithms on shared memory multicore architecture. We analyze the performance measurements of each parallel implementation and the impact of the different sources of overhead on the performance of the parallel implementations. In this comparison study, we also discuss the advantages and disadvantages of the parallel programming models. Thus, we compare the OpenMP (an application programming interface for multi-Processing) with Ptheads (POSIX Threads) to illustrate the impact of each parallel programming model on the performance of the parallel implementations.

Estimates of nitrate loads and yields from groundwater to streams in the Chesapeake Bay watershed based on land use and geology

USGS Publications Warehouse

Terziotti, Silvia; Capel, Paul D.; Tesoriero, Anthony J.; Hopple, Jessica A.; Kronholm, Scott C.

2018-03-07

The water quality of the Chesapeake Bay may be adversely affected by dissolved nitrate carried in groundwater discharge to streams. To estimate the concentrations, loads, and yields of nitrate from groundwater to streams for the Chesapeake Bay watershed, a regression model was developed based on measured nitrate concentrations from 156 small streams with watersheds less than 500 square miles (mi2 ) at baseflow. The regression model has three predictive variables: geologic unit, percent developed land, and percent agricultural land. Comparisons of estimated and actual values within geologic units were closely matched. The coefficient of determination (R2 ) for the model was 0.6906. The model was used to calculate baseflow nitrate concentrations at over 83,000 National Hydrography Dataset Plus Version 2 catchments and aggregated to 1,966 total 12-digit hydrologic units in the Chesapeake Bay watershed. The modeled output geospatial data layers provided estimated annual loads and yields of nitrate from groundwater into streams. The spatial distribution of annual nitrate yields from groundwater estimated by this method was compared to the total watershed yields of all sources estimated from a Chesapeake Bay SPAtially Referenced Regressions On Watershed attributes (SPARROW) water-quality model. The comparison showed similar spatial patterns. The regression model for groundwater contribution had similar but lower yields, suggesting that groundwater is an important source of nitrogen for streams in the Chesapeake Bay watershed.

Use of a stochastic approach for description of water balance and runoff production dynamics

NASA Astrophysics Data System (ADS)

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

2009-04-01

The present study exploits an analytical model (Manfreda, NHESS [2008]) for the description of the probability density function of soil water balance and runoff generation over a set of river basins belonging to Southern Italy. The model is based on a stochastic differential equation where the rainfall forcing is interpreted as an additive noise in the soil water balance; the watershed heterogeneity is described exploiting the conceptual lumped watershed Xinanjiang model (widely used in China) that uses a parabolic curve for the distribution of the soil water storage capacity (Zhao et al. [1980]). The model, characterized by parameters that depend on soil, vegetation and basin morphology, allowed to derive the probability density function of the relative saturation and the surface runoff of a basin accounting for the spatial heterogeneity in soil water storage. Its application on some river basins belonging to regions of Southern Italy, gives interesting insights for the investigation of the role played by the dynamical interaction between climate, soil, and vegetation in soil moisture and runoff production dynamics. Manfreda, S., Runoff Generation Dynamics within a Humid River Basin, Natural Hazard and Earth System Sciences, 8, 1349-1357, 2008. Zhao, R. -J., Zhang, Y. L., and Fang, L. R.: The Xinanjiang model, Hydrological Forecasting Proceedings Oxford Symposium, IAHS Pub. 129, 351-356, 1980.

Estimation of surface soil moisture and roughness from multi-angular ASAR imagery in the Watershed Allied Telemetry Experimental Research (WATER)

NASA Astrophysics Data System (ADS)

Wang, S. G.; Li, X.; Han, X. J.; Jin, R.

2010-06-01

Radar remote sensing has demonstrated its applicability to the retrieval of basin-scale soil moisture. The mechanism of radar backscattering from soils is complicated and strongly influenced by surface roughness. Furthermore, retrieval of soil moisture using AIEM-like models is a classic example of the underdetermined problem due to a lack of credible known soil roughness distributions at a regional scale. Characterization of this roughness is therefore crucial for an accurate derivation of soil moisture based on backscattering models. This study aims to directly obtain surface roughness information along with soil moisture from multi-angular ASAR images. The method first used a semi-empirical relationship that connects the roughness slope (Zs) and the difference in backscattering coefficient (Δσ) from ASAR data in different incidence angles, in combination with an optimal calibration form consisting of two roughness parameters (the standard deviation of surface height and the correlation length), to estimate the roughness parameters. The deduced surface roughness was then used in the AIEM model for the retrieval of soil moisture. An evaluation of the proposed method was performed in a grassland site in the middle stream of the Heihe River Basin, where the Watershed Allied Telemetry Experimental Research (WATER) was taken place. It has demonstrated that the method is feasible to achieve reliable estimation of soil water content. The key challenge to surface soil moisture retrieval is the presence of vegetation cover, which significantly impacts the estimates of surface roughness and soil moisture.

Sensitivity and Uncertainty Analysis for Streamflow Prediction Using Different Objective Functions and Optimization Algorithms: San Joaquin California

NASA Astrophysics Data System (ADS)

Paul, M.; Negahban-Azar, M.

2017-12-01

The hydrologic models usually need to be calibrated against observed streamflow at the outlet of a particular drainage area through a careful model calibration. However, a large number of parameters are required to fit in the model due to their unavailability of the field measurement. Therefore, it is difficult to calibrate the model for a large number of potential uncertain model parameters. This even becomes more challenging if the model is for a large watershed with multiple land uses and various geophysical characteristics. Sensitivity analysis (SA) can be used as a tool to identify most sensitive model parameters which affect the calibrated model performance. There are many different calibration and uncertainty analysis algorithms which can be performed with different objective functions. By incorporating sensitive parameters in streamflow simulation, effects of the suitable algorithm in improving model performance can be demonstrated by the Soil and Water Assessment Tool (SWAT) modeling. In this study, the SWAT was applied in the San Joaquin Watershed in California covering 19704 km2 to calibrate the daily streamflow. Recently, sever water stress escalating due to intensified climate variability, prolonged drought and depleting groundwater for agricultural irrigation in this watershed. Therefore it is important to perform a proper uncertainty analysis given the uncertainties inherent in hydrologic modeling to predict the spatial and temporal variation of the hydrologic process to evaluate the impacts of different hydrologic variables. The purpose of this study was to evaluate the sensitivity and uncertainty of the calibrated parameters for predicting streamflow. To evaluate the sensitivity of the calibrated parameters three different optimization algorithms (Sequential Uncertainty Fitting- SUFI-2, Generalized Likelihood Uncertainty Estimation- GLUE and Parameter Solution- ParaSol) were used with four different objective functions (coefficient of determination- r2, Nash-Sutcliffe efficiency- NSE, percent bias- PBIAS, and Kling-Gupta efficiency- KGE). The preliminary results showed that using the SUFI-2 algorithm with the objective function NSE and KGE has improved significantly the calibration (e.g. R2 and NSE is found 0.52 and 0.47 respectively for daily streamflow calibration).

ASSESSMENT OF LAND USE CHANGE IMPACTS ON FLOW CHARACTERISTICS IN AN EASTERN PENNSYLVANIA WATERSHED

EPA Science Inventory

The impacts of changes in land use/cover due to urbanization on the hydrologic regime of the watershed have long been recognized and have been the subject of many studies. Distributed hydrologic models are one means of assessing such impacts. In this study we evaluated the potent...

Upper Washita River experimental watersheds: Multiyear stability of soil water content profiles

USDA-ARS?s Scientific Manuscript database

Scaling in situ soil water content time series data to a large spatial domain is a key element of watershed environmental monitoring and modeling. The primary method of estimating and monitoring large-scale soil water content distributions is via in situ networks. It is critical to establish the s...

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.

Evaluating spatial interaction of soil property with non-point source pollution at watershed scale: the phosphorus indicator in Northeast China.

PubMed

Ouyang, Wei; Huang, Haobo; Hao, Fanghua; Shan, Yushu; Guo, Bobo

2012-08-15

To better understand the spatial dynamics of non-point source (NPS) phosphorus loading with soil property at watershed scale, integrated modeling and soil chemistry is crucial to ensure that the indicator is functioning properly and expressing the spatial interaction at two depths. Developments in distributed modeling have greatly enriched the availability of geospatial data analysis and assess the NPS pollution loading response to soil property over larger area. The 1.5 km-grid soil sampling at two depths was analyzed with eight parameters, which provided detailed spatial and vertical soil data under four main types of landuses. The impacts of landuse conversion and agricultural practice on soil property were firstly identified. Except for the slightly bigger total of potassium (TK) and cadmium (Cr), the other six parameters had larger content in 20-40 cm surface than the top 20 cm surface. The Soil and Water Assessment Tool was employed to simulate the loading of NPS phosphorus. Overlaying with the landuse distribution, it was found that the NPS phosphorus mainly comes from the subbasins dominated with upland and paddy rice. The linear correlations of eight soil parameters at two depths with NPS phosphorus loading in the subbasins of upland and paddy rice were compared, respectively. The correlations of available phosphorus (AP), total phosphorus (TP), total nitrogen (TN) and TK varied in two depths, and also can assess the loading. The soil with lower soil organic carbon (SOC) presented a significant higher risk for NPS phosphorus loading, especially in agricultural area. The Principal Component Analysis showed that the TP and zinc (Zn) in top soil and copper (Cu) and Cr in subsurface can work as indicators. The analysis suggested that the application of soil property indicators is useful for assessing NPS phosphorus loss, which is promising for water safety in agricultural area. Copyright © 2012 Elsevier B.V. All rights reserved.

Assessing the impacts of land use on downstream water quality using a hydrologically sensitive area concept.

PubMed

Giri, Subhasis; Qiu, Zeyuan; Zhang, Zhen

2018-05-01

Understanding the relationship between land use and water quality is essential to improve water quality through carefully managing landscape change. This study applies a linear mixed model at both watershed and hydrologically sensitive areas (HSAs) scales to assess such a relationship in 28 northcentral New Jersey watersheds located in a rapidly urbanizing region in the United States. Two models differ in terms of the geographic scope used to derive land use matrices that quantify land use conditions. The land use matrices at the watershed and HSAs scales represent the land use conditions in these watersheds and their HSAs, respectively. HSAs are the hydrological "hotspots" in a watershed that are prone to runoff generation during storm events. HSAs are derived using a soil topographic index (STI) that predicts hydrological sensitivity of a landscape based on a variable source area hydrology concept. The water quality indicators in these models are total nitrogen (TN), total phosphorus (TP) and total suspended solids (TSS) concentrations in streams observed at the watershed outlets. The modeling results suggest that presence of low density urban land, agricultural land and wetlands elevate while forest decreases TN, TP and/or TSS concentrations in streams. The watershed scale model tends to emphasize the role of agricultural lands in water quality degradation while the HSA scale model highlights the role of forest in water quality improvement. This study supports the hypothesis that even though HSAs are relatively smaller area compared to watershed, still the land uses within HSAs have similar impacts on downstream water quality as the land uses in entire watersheds, since both models have negligible differences in model evaluation parameters. Inclusion of HSAs brings an interesting perspective to understand the dynamic relationships between land use and water quality. Copyright © 2018 Elsevier Ltd. All rights reserved.

Daily Streamflow Predictions in an Ungauged Watershed in Northern California Using the Precipitation-Runoff Modeling System (PRMS): Calibration Challenges when nearby Gauged Watersheds are Hydrologically Dissimilar

NASA Astrophysics Data System (ADS)

Dhakal, A. S.; Adera, S.

2017-12-01

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

Multi-Dimensional Shallow Landslide Stability Analysis Suitable for Application at the Watershed Scale

NASA Astrophysics Data System (ADS)

Milledge, David; Bellugi, Dino; McKean, Jim; Dietrich, William E.

2013-04-01

Current practice in regional-scale shallow landslide hazard assessment is to adopt a one-dimensional slope stability representation. Such a representation cannot produce discrete landslides and thus cannot make predictions on landslide size. Furthermore, one-dimensional approaches cannot include lateral effects, which are known to be important in defining instability. Here we derive an alternative model that accounts for lateral resistance by representing the forces acting on each margin of an unstable block of soil. We model boundary frictional resistances using 'at rest' earth pressure on the lateral sides, and 'active' and 'passive' pressure, using the log-spiral method, on the upslope and downslope margins. We represent root reinforcement on each margin assuming that root cohesion declines exponentially with soil depth. We test our model's ability to predict failure of an observed landslide where the relevant parameters are relatively well constrained and find that our model predicts failure at the observed location and predicts that larger or smaller failures conformal to the observed shape are indeed more stable. We use a sensitivity analysis of the model to show that lateral reinforcement sets a minimum landslide size, and that the additional strength at the downslope boundary results in optimal shapes that are longer in the downslope direction. However, reinforcement effects alone cannot fully explain the size or shape distributions of observed landslides, highlighting the importance of the spatial pattern of key parameters (e.g. pore water pressure and soil depth) at the watershed scale. The application of the model at this scale requires an efficient method to find unstable shapes among an exponential number of candidates. In this context, the model allows a more extensive examination of the controls on landslide size, shape and location.

Comparison of SWAT Hydrological Model Results from TRMM 3B42, NEXRAD Stage III, and Oklahoma Mesonet Data

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.

Estimation of surface soil moisture and roughness from multi-angular ASAR imagery in the Watershed Allied Telemetry Experimental Research (WATER)

NASA Astrophysics Data System (ADS)

Wang, S. G.; Li, X.; Han, X. J.; Jin, R.

2011-05-01

Radar remote sensing has demonstrated its applicability to the retrieval of basin-scale soil moisture. The mechanism of radar backscattering from soils is complicated and strongly influenced by surface roughness. Additionally, retrieval of soil moisture using AIEM (advanced integrated equation model)-like models is a classic example of underdetermined problem due to a lack of credible known soil roughness distributions at a regional scale. Characterization of this roughness is therefore crucial for an accurate derivation of soil moisture based on backscattering models. This study aims to simultaneously obtain surface roughness parameters (standard deviation of surface height σ and correlation length cl) along with soil moisture from multi-angular ASAR images by using a two-step retrieval scheme based on the AIEM. The method firstly used a semi-empirical relationship that relates the roughness slope, Zs (Zs = σ2/cl) and the difference in backscattering coefficient (Δσ) from two ASAR images acquired with different incidence angles. Meanwhile, by using an experimental statistical relationship between σ and cl, both these parameters can be estimated. Then, the deduced roughness parameters were used for the retrieval of soil moisture in association with the AIEM. An evaluation of the proposed method was performed in an experimental area in the middle stream of the Heihe River Basin, where the Watershed Allied Telemetry Experimental Research (WATER) was taken place. It is demonstrated that the proposed method is feasible to achieve reliable estimation of soil water content. The key challenge is the presence of vegetation cover, which significantly impacts the estimates of surface roughness and soil moisture.

Estimating macroporosity in a forest watershed by use of a tension infiltrometer

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

Watson, K.W.; Luxmoore, R.J.

The ability to obtain sufficient field hydrologic data at reasonable cost can be an important limiting factor in applying transport models. A procedure is described for using ponded-flow- and tension-infiltration measurements to calculate transport parameters in a forest watershed. Thirty infiltration measurements were taken under ponded-flow conditions and at 3, 6, and 15 cm (H/sub 2/O) tension. It was assumed from capillarity theory that pores > 0.1-, 0.05-, and 0.02-cm diam, respectively, were excluded from the transport process during the tension infiltration measurements. Under ponded flow, 73% of the flux was conducted through macropores (i.e., pores > 0.1-cm diam.). Anmore » estimated 96% of the water flux was transmitted through only 0.32% of the soil volume. In general the larger the total water flux the larger the macropore contribution to total water flux. The Shapiro-Wilk normality test indicated that water flux through both matrix pore space and macropores was log-normally distributed in space.« less

Development of an analytical solution for the Budyko watershed parameter in terms of catchment physical features

NASA Astrophysics Data System (ADS)

Reaver, N.; Kaplan, D. A.; Jawitz, J. W.

2017-12-01

The Budyko hypothesis states that a catchment's long-term water and energy balances are dependent on two relatively easy to measure quantities: rainfall depth and potential evaporation. This hypothesis is expressed as a simple function, the Budyko equation, which allows for the prediction of a catchment's actual evapotranspiration and discharge from measured rainfall depth and potential evaporation, data which are widely available. However, the two main analytically derived forms of the Budyko equation contain a single unknown watershed parameter, whose value varies across catchments; variation in this parameter has been used to explain the hydrological behavior of different catchments. The watershed parameter is generally thought of as a lumped quantity that represents the influence of all catchment biophysical features (e.g. soil type and depth, vegetation type, timing of rainfall, etc). Previous work has shown that the parameter is statistically correlated with catchment properties, but an explicit expression has been elusive. While the watershed parameter can be determined empirically by fitting the Budyko equation to measured data in gauged catchments where actual evapotranspiration can be estimated, this limits the utility of the framework for predicting impacts to catchment hydrology due to changing climate and land use. In this study, we developed an analytical solution for the lumped catchment parameter for both forms of the Budyko equation. We combined these solutions with a statistical soil moisture model to obtain analytical solutions for the Budyko equation parameter as a function of measurable catchment physical features, including rooting depth, soil porosity, and soil wilting point. We tested the predictive power of these solutions using the U.S. catchments in the MOPEX database. We also compared the Budyko equation parameter estimates generated from our analytical solutions (i.e. predicted parameters) with those obtained through the calibration of the Budyko equation to discharge data (i.e. empirical parameters), and found good agreement. These results suggest that it is possible to predict the Budyko equation watershed parameter directly from physical features, even for ungauged catchments.

Modeling hydrology, groundwater recharge and non-point nitrate loadings in the Himalayan Upper Yamuna basin.

PubMed

Narula, Kapil K; Gosain, A K

2013-12-01

The mountainous Himalayan watersheds are important hydrologic systems responsible for much of the water supply in the Indian sub-continent. These watersheds are increasingly facing anthropogenic and climate-related pressures that impact spatial and temporal distribution of water availability. This study evaluates temporal and spatial distribution of water availability including groundwater recharge and quality (non-point nitrate loadings) for a Himalayan watershed, namely, the Upper Yamuna watershed (part of the Ganga River basin). The watershed has an area of 11,600 km(2) with elevation ranging from 6300 to 600 m above mean sea level. Soil and Water Assessment Tool (SWAT), a physically-based, time-continuous model, has been used to simulate the land phase of the hydrological cycle, to obtain streamflows, groundwater recharge, and nitrate (NO3) load distributions in various components of runoff. The hydrological SWAT model is integrated with the MODular finite difference groundwater FLOW model (MODFLOW), and Modular 3-Dimensional Multi-Species Transport model (MT3DMS), to obtain groundwater flow and NO3 transport. Validation of various modules of this integrated model has been done for sub-basins of the Upper Yamuna watershed. Results on surface runoff and groundwater levels obtained as outputs from simulation show a good comparison with the observed streamflows and groundwater levels (Nash-Sutcliffe and R(2) correlations greater than +0.7). Nitrate loading obtained after nitrification, denitrification, and NO3 removal from unsaturated and shallow aquifer zones is combined with groundwater recharge. Results for nitrate modeling in groundwater aquifers are compared with observed NO3 concentration and are found to be in good agreement. The study further evaluates the sensitivity of water availability to climate change. Simulations have been made with the weather inputs of climate change scenarios of A2, B2, and A1B for end of the century. Water yield estimates under climate change scenarios have been made and implications on groundwater and groundwater quality have been assessed. The delicate groundwater resource balance that connects livelihoods of millions of people seems to be under tremendously increasing pressure due to the dynamic conditions of the natural environment of the region and the future climate changes. Copyright © 2013 Elsevier B.V. All rights reserved.

Characterization and evaluation of controls on post-fire streamflow response across western US watersheds

NASA Astrophysics Data System (ADS)

Saxe, Samuel; Hogue, Terri S.; Hay, Lauren

2018-02-01

This research investigates the impact of wildfires on watershed flow regimes, specifically focusing on evaluation of fire events within specified hydroclimatic regions in the western United States, and evaluating the impact of climate and geophysical variables on response. Eighty-two watersheds were identified with at least 10 years of continuous pre-fire daily streamflow records and 5 years of continuous post-fire daily flow records. Percent change in annual runoff ratio, low flows, high flows, peak flows, number of zero flow days, baseflow index, and Richards-Baker flashiness index were calculated for each watershed using pre- and post-fire periods. Independent variables were identified for each watershed and fire event, including topographic, vegetation, climate, burn severity, percent area burned, and soils data. Results show that low flows, high flows, and peak flows increase in the first 2 years following a wildfire and decrease over time. Relative response was used to scale response variables with the respective percent area of watershed burned in order to compare regional differences in watershed response. To account for variability in precipitation events, runoff ratio was used to compare runoff directly to PRISM precipitation estimates. To account for regional differences in climate patterns, watersheds were divided into nine regions, or clusters, through k-means clustering using climate data, and regression models were produced for watersheds grouped by total area burned. Watersheds in Cluster 9 (eastern California, western Nevada, Oregon) demonstrate a small negative response to observed flow regimes after fire. Cluster 8 watersheds (coastal California) display the greatest flow responses, typically within the first year following wildfire. Most other watersheds show a positive mean relative response. In addition, simple regression models show low correlation between percent watershed burned and streamflow response, implying that other watershed factors strongly influence response. Spearman correlation identified NDVI, aridity index, percent of a watershed's precipitation that falls as rain, and slope as being positively correlated with post-fire streamflow response. This metric also suggested a negative correlation between response and the soil erodibility factor, watershed area, and percent low burn severity. Regression models identified only moderate burn severity and watershed area as being consistently positively/negatively correlated, respectively, with response. The random forest model identified only slope and percent area burned as significant watershed parameters controlling response. Results will help inform post-fire runoff management decisions by helping to identify expected changes to flow regimes, as well as facilitate parameterization for model application in burned watersheds.

Mid-Holocene hydrologic model of the Shingobee watershed, Minnesota

USGS Publications Warehouse

Filby, S.K.; Locke, Sharon M.; Person, M.A.; Winter, T.C.; Rosenberry, D.O.; Nieber, J.L.; Gutowski, W.J.; Ito, E.

2002-01-01

A hydrologifc model of the Shingobee Watershed in north-central Minnesota was developed to reconstruct mid-Holocene paleo-lake levels for Williams Lake, a surface-water body located in the southern portion of the watershed. Hydrologic parameters for the model were first estimated in a calibration exercise using a 9-yr historical record (1990-1998) of climatic and hydrologic stresses. The model reproduced observed temporal and spatial trends in surface/groundwater levels across the watershed. Mid-Holocene aquifer and lake levels were then reconstructed using two paleoclimatic data sets: CCM1 atmospheric general circulation model output and pollen-transfer functions using sediment core data from Williams Lake. Calculated paleo-lake levels based on pollen-derived paleoclimatic reconstructions indicated a 3.5-m drop in simulated lake levels and were in good agreement with the position of mid-Holocene beach sands observed in a Williams Lake sediment core transect. However, calculated paleolake levels based on CCM1 climate forcing produced only a 0.05-m drop in lake levels. We found that decreases in winter precipitation rather than temperature increases had the largest effect on simulated mid-Holocene lake levels. The study illustrates how watershed models can be used to critically evaluate paleoclimatic reconstructions by integrating geologic, climatic, limnologic, and hydrogeologic data sets. ?? 2002 University of Washington.

Multivariate Statistical Models for Predicting Sediment Yields from Southern California Watersheds

USGS Publications Warehouse

Gartner, Joseph E.; Cannon, Susan H.; Helsel, Dennis R.; Bandurraga, Mark

2009-01-01

Debris-retention basins in Southern California are frequently used to protect communities and infrastructure from the hazards of flooding and debris flow. Empirical models that predict sediment yields are used to determine the size of the basins. Such models have been developed using analyses of records of the amount of material removed from debris retention basins, associated rainfall amounts, measures of watershed characteristics, and wildfire extent and history. In this study we used multiple linear regression methods to develop two updated empirical models to predict sediment yields for watersheds located in Southern California. The models are based on both new and existing measures of volume of sediment removed from debris retention basins, measures of watershed morphology, and characterization of burn severity distributions for watersheds located in Ventura, Los Angeles, and San Bernardino Counties. The first model presented reflects conditions in watersheds located throughout the Transverse Ranges of Southern California and is based on volumes of sediment measured following single storm events with known rainfall conditions. The second model presented is specific to conditions in Ventura County watersheds and was developed using volumes of sediment measured following multiple storm events. To relate sediment volumes to triggering storm rainfall, a rainfall threshold was developed to identify storms likely to have caused sediment deposition. A measured volume of sediment deposited by numerous storms was parsed among the threshold-exceeding storms based on relative storm rainfall totals. The predictive strength of the two models developed here, and of previously-published models, was evaluated using a test dataset consisting of 65 volumes of sediment yields measured in Southern California. The evaluation indicated that the model developed using information from single storm events in the Transverse Ranges best predicted sediment yields for watersheds in San Bernardino, Los Angeles, and Ventura Counties. This model predicts sediment yield as a function of the peak 1-hour rainfall, the watershed area burned by the most recent fire (at all severities), the time since the most recent fire, watershed area, average gradient, and relief ratio. The model that reflects conditions specific to Ventura County watersheds consistently under-predicted sediment yields and is not recommended for application. Some previously-published models performed reasonably well, while others either under-predicted sediment yields or had a larger range of errors in the predicted sediment yields.

Advances in the spatially distributed ages-w model: parallel computation, java connection framework (JCF) integration, and streamflow/nitrogen dynamics assessment

USDA-ARS?s Scientific Manuscript database

AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic and water quality (H/WQ) simulation components under the Java Connection Framework (JCF) and the Object Modeling System (OMS) environmental modeling framework. AgES-W is implicitly scala...

Advancement in Watershed Modelling Using Dynamic Lateral and Longitudinal Sediment (Dis)connectivity Prediction

NASA Astrophysics Data System (ADS)

Mahoney, D. T.; al Aamery, N. M. H.; Fox, J.

2017-12-01

The authors find that sediment (dis)connectivity has seldom taken precedence within watershed models, and the present study advances this modeling framework and applies the modeling within a bedrock-controlled system. Sediment (dis)connectivity, defined as the detachment and transport of sediment from source to sink between geomorphic zones, is a major control on sediment transport. Given the availability of high resolution geospatial data, coupling sediment connectivity concepts within sediment prediction models offers an approach to simulate sediment sources and pathways within a watershed's sediment cascade. Bedrock controlled catchments are potentially unique due to the presence of rock outcrops causing longitudinal impedance to sediment transport pathways in turn impacting the longitudinal distribution of the energy gradient responsible for conveying sediment. Therefore, the authors were motivated by the need to formulate a sediment transport model that couples sediment (dis)connectivity knowledge to predict sediment flux for bedrock controlled catchments. A watershed-scale sediment transport model was formulated that incorporates sediment (dis)connectivity knowledge collected via field reconnaissance and predicts sediment flux through coupling with the Partheniades equation and sediment continuity model. Sediment (dis)connectivity was formulated by coupling probabilistic upland lateral connectivity prediction with instream longitudinal connectivity assessments via discretization of fluid and sediment pathways. Flux predictions from the upland lateral connectivity model served as an input to the instream longitudinal connectivity model. Disconnectivity in the instream model was simulated via the discretization of stream reaches due to barriers such as bedrock outcroppings and man-made check dams. The model was tested for a bedrock controlled catchment in Kentucky, USA for which extensive historic water and sediment flux data was available. Predicted sediment flux was validated via sediment flux measurements collected by the authors. Watershed configuration and the distribution of lateral and longitudinal impedances to sediment transport were found to have significant influence on sediment connectivity and thus sediment flux.

Targeting land-use change for nitratenitrogen load reductions in an agricultural watershed

USGS Publications Warehouse

Jha, M.K.; Schilling, K.E.; Gassman, Philip W.; Wolter, C.F.

2010-01-01

The research was conducted as part of the USDA's Conservation Effects Assessment Project. The objective of the project was to evaluate the environmental effects of land-use changes, with a focus on understanding how the spatial distribution throughout a watershed influences their effectiveness.The Soil and Water AssessmentTool (SWAT) water quality model was applied to the Squaw Creek watershed, which covers 4,730 ha (11,683 ac) of prime agriculture land in southern Iowa. The model was calibrated (2000 to 2004) and validated (1996 to 1999) for overall watershed hydrology and for streamflow and nitrate loadings at the watershed outlet on an annual and monthly basis. Four scenarios for land-use change were evaluated including one scenario consistent with recent land-use changes and three scenarios focused on land-use change on highly erodible land areas, upper basin areas, and floodplain areas. Results for the Squaw Creek watershed suggested that nitrate losses were sensitive to land-use change. If land-use patterns were restored to 1990 conditions, nitrate loads may be reduced 7% to 47% in the watershed and subbasins, whereas converting row crops to grass in highly erodible land, upper basin, and floodplain areas would reduce nitrate loads by 47%, 16%, and 8%, respectively. These SWAT model simulations can provide guidance on how to begin targeting land-use change for nitrate load reductions in agricultural watersheds.

Simulating Daily and Sub-daily Water Flow in Large, Semi-arid Watershed Using SWAT: A Case Study of Nueces River Basin, Texas

NASA Astrophysics Data System (ADS)

Bassam, S.; Ren, J.

2015-12-01

Runoff generated during heavy rainfall imposes quick, but often intense, changes in the flow of streams, which increase the chance of flash floods in the vicinity of the streams. Understanding the temporal response of streams to heavy rainfall requires a hydrological model that considers meteorological, hydrological, and geological components of the streams and their watersheds. SWAT is a physically-based, semi-distributed model that is capable of simulating water flow within watersheds with both long-term, i.e. annually and monthly, and short-term (daily and sub-daily) time scales. However, the capability of SWAT in sub-daily water flow modeling within large watersheds has not been studied much, compare to long-term and daily time scales. In this study we are investigating the water flow in a large, semi-arid watershed, Nueces River Basin (NRB) with the drainage area of 16950 mi2 located in South Texas, with daily and sub-daily time scales. The objectives of this study are: (1) simulating the response of streams to heavy, and often quick, rainfall, (2) evaluating SWAT performance in sub-daily modeling of water flow within a large watershed, and (3) examining means for model performance improvement during model calibration and verification based on results of sensitivity and uncertainty analysis. The results of this study can provide important information for water resources planning during flood seasons.

An auto-adaptive optimization approach for targeting nonpoint source pollution control practices.

PubMed

Chen, Lei; Wei, Guoyuan; Shen, Zhenyao

2015-10-21

To solve computationally intensive and technically complex control of nonpoint source pollution, the traditional genetic algorithm was modified into an auto-adaptive pattern, and a new framework was proposed by integrating this new algorithm with a watershed model and an economic module. Although conceptually simple and comprehensive, the proposed algorithm would search automatically for those Pareto-optimality solutions without a complex calibration of optimization parameters. The model was applied in a case study in a typical watershed of the Three Gorges Reservoir area, China. The results indicated that the evolutionary process of optimization was improved due to the incorporation of auto-adaptive parameters. In addition, the proposed algorithm outperformed the state-of-the-art existing algorithms in terms of convergence ability and computational efficiency. At the same cost level, solutions with greater pollutant reductions could be identified. From a scientific viewpoint, the proposed algorithm could be extended to other watersheds to provide cost-effective configurations of BMPs.

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.

Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

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.

Effect of formal and informal likelihood functions on uncertainty assessment in a single event rainfall-runoff model

NASA Astrophysics Data System (ADS)

Nourali, Mahrouz; Ghahraman, Bijan; Pourreza-Bilondi, Mohsen; Davary, Kamran

2016-09-01

In the present study, DREAM(ZS), Differential Evolution Adaptive Metropolis combined with both formal and informal likelihood functions, is used to investigate uncertainty of parameters of the HEC-HMS model in Tamar watershed, Golestan province, Iran. In order to assess the uncertainty of 24 parameters used in HMS, three flood events were used to calibrate and one flood event was used to validate the posterior distributions. Moreover, performance of seven different likelihood functions (L1-L7) was assessed by means of DREAM(ZS)approach. Four likelihood functions, L1-L4, Nash-Sutcliffe (NS) efficiency, Normalized absolute error (NAE), Index of agreement (IOA), and Chiew-McMahon efficiency (CM), is considered as informal, whereas remaining (L5-L7) is represented in formal category. L5 focuses on the relationship between the traditional least squares fitting and the Bayesian inference, and L6, is a hetereoscedastic maximum likelihood error (HMLE) estimator. Finally, in likelihood function L7, serial dependence of residual errors is accounted using a first-order autoregressive (AR) model of the residuals. According to the results, sensitivities of the parameters strongly depend on the likelihood function, and vary for different likelihood functions. Most of the parameters were better defined by formal likelihood functions L5 and L7 and showed a high sensitivity to model performance. Posterior cumulative distributions corresponding to the informal likelihood functions L1, L2, L3, L4 and the formal likelihood function L6 are approximately the same for most of the sub-basins, and these likelihood functions depict almost a similar effect on sensitivity of parameters. 95% total prediction uncertainty bounds bracketed most of the observed data. Considering all the statistical indicators and criteria of uncertainty assessment, including RMSE, KGE, NS, P-factor and R-factor, results showed that DREAM(ZS) algorithm performed better under formal likelihood functions L5 and L7, but likelihood function L5 may result in biased and unreliable estimation of parameters due to violation of the residualerror assumptions. Thus, likelihood function L7 provides posterior distribution of model parameters credibly and therefore can be employed for further applications.

a Bayesian Synthesis of Predictions from Different Models for Setting Water Quality Criteria

NASA Astrophysics Data System (ADS)

Arhonditsis, G. B.; Ecological Modelling Laboratory

2011-12-01

Skeptical views of the scientific value of modelling argue that there is no true model of an ecological system, but rather several adequate descriptions of different conceptual basis and structure. In this regard, rather than picking the single "best-fit" model to predict future system responses, we can use Bayesian model averaging to synthesize the forecasts from different models. Hence, by acknowledging that models from different areas of the complexity spectrum have different strengths and weaknesses, the Bayesian model averaging is an appealing approach to improve the predictive capacity and to overcome the ambiguity surrounding the model selection or the risk of basing ecological forecasts on a single model. Our study addresses this question using a complex ecological model, developed by Ramin et al. (2011; Environ Modell Softw 26, 337-353) to guide the water quality criteria setting process in the Hamilton Harbour (Ontario, Canada), along with a simpler plankton model that considers the interplay among phosphate, detritus, and generic phytoplankton and zooplankton state variables. This simple approach is more easily subjected to detailed sensitivity analysis and also has the advantage of fewer unconstrained parameters. Using Markov Chain Monte Carlo simulations, we calculate the relative mean standard error to assess the posterior support of the two models from the existing data. Predictions from the two models are then combined using the respective standard error estimates as weights in a weighted model average. The model averaging approach is used to examine the robustness of predictive statements made from our earlier work regarding the response of Hamilton Harbour to the different nutrient loading reduction strategies. The two eutrophication models are then used in conjunction with the SPAtially Referenced Regressions On Watershed attributes (SPARROW) watershed model. The Bayesian nature of our work is used: (i) to alleviate problems of spatiotemporal resolution mismatch between watershed and receiving waterbody models; and (ii) to overcome the conceptual or scale misalignment between processes of interest and supporting information. The proposed Bayesian approach provides an effective means of empirically estimating the relation between in-stream measurements of nutrient fluxes and the sources/sinks of nutrients within the watershed, while explicitly accounting for the uncertainty associated with the existing knowledge from the system along with the different types of spatial correlation typically underlying the parameter estimation of watershed models. Our modelling exercise offers the first estimates of the export coefficients and the delivery rates from the different subcatchments and thus generates testable hypotheses regarding the nutrient export "hot spots" in the studied watershed. Finally, we conduct modeling experiments that evaluate the potential improvement of the model parameter estimates and the decrease of the predictive uncertainty, if the uncertainty associated with the contemporary nutrient loading estimates is reduced. The lessons learned from this study will contribute towards the development of integrated modelling frameworks.

Effect of forest harvesting best management practices on coarse woody debris distribution in stream and riparian zones in three Appalachian watersheds

Treesearch

J. M. McClure; R. K. Kolka; A. White

2004-01-01

The distribution of coarse woody debris (CWD) was analyzed in three Appalachian watersheds in eastern Kentucky, eighteen years after harvest. The three watersheds included an unharvested control (Control), a second watershed with best management practices (BMPs) applied that included a 15.2 m unharvested zone near the stream (BMP watershed), and a third watershed that...

Simulation of net infiltration and potential recharge using a distributed-parameter watershed model of the Death Valley region, Nevada and California

USGS Publications Warehouse

Hevesi, Joseph A.; Flint, Alan L.; Flint, Lorraine E.

2003-01-01

This report presents the development and application of the distributed-parameter watershed model, INFILv3, for estimating the temporal and spatial distribution of net infiltration and potential recharge in the Death Valley region, Nevada and California. The estimates of net infiltration quantify the downward drainage of water across the lower boundary of the root zone and are used to indicate potential recharge under variable climate conditions and drainage basin characteristics. Spatial variability in recharge in the Death Valley region likely is high owing to large differences in precipitation, potential evapotranspiration, bedrock permeability, soil thickness, vegetation characteristics, and contributions to recharge along active stream channels. The quantity and spatial distribution of recharge representing the effects of variable climatic conditions and drainage basin characteristics on recharge are needed to reduce uncertainty in modeling ground-water flow. The U.S. Geological Survey, in cooperation with the Department of Energy, developed a regional saturated-zone ground-water flow model of the Death Valley regional ground-water flow system to help evaluate the current hydrogeologic system and the potential effects of natural or human-induced changes. Although previous estimates of recharge have been made for most areas of the Death Valley region, including the area defined by the boundary of the Death Valley regional ground-water flow system, the uncertainty of these estimates is high, and the spatial and temporal variability of the recharge in these basins has not been quantified. To estimate the magnitude and distribution of potential recharge in response to variable climate and spatially varying drainage basin characteristics, the INFILv3 model uses a daily water-balance model of the root zone with a primarily deterministic representation of the processes controlling net infiltration and potential recharge. The daily water balance includes precipitation (as either rain or snow), snow accumulation, sublimation, snowmelt, infiltration into the root zone, evapotranspiration, drainage, water content change throughout the root-zone profile (represented as a 6-layered system), runoff (defined as excess rainfall and snowmelt) and surface water run-on (defined as runoff that is routed downstream), and net infiltration (simulated as drainage from the bottom root-zone layer). Potential evapotranspiration is simulated using an hourly solar radiation model to simulate daily net radiation, and daily evapotranspiration is simulated as an empirical function of root zone water content and potential evapotranspiration. The model uses daily climate records of precipitation and air temperature from a regionally distributed network of 132 climate stations and a spatially distributed representation of drainage basin characteristics defined by topography, geology, soils, and vegetation to simulate daily net infiltration at all locations, including stream channels with intermittent streamflow in response to runoff from rain and snowmelt. The temporal distribution of daily, monthly, and annual net infiltration can be used to evaluate the potential effect of future climatic conditions on potential recharge. The INFILv3 model inputs representing drainage basin characteristics were developed using a geographic information system (GIS) to define a set of spatially distributed input parameters uniquely assigned to each grid cell of the INFILv3 model grid. The model grid, which was defined by a digital elevation model (DEM) of the Death Valley region, consists of 1,252,418 model grid cells with a uniform grid cell dimension of 278.5 meters in the north-south and east-west directions. The elevation values from the DEM were used with monthly regression models developed from the daily climate data to estimate the spatial distribution of daily precipitation and air temperature. The elevation values were also used to simulate atmosp

AQUATOX Frequently Asked Questions

EPA Pesticide Factsheets

Capabilities, Installation, Source Code, Example Study Files, Biotic State Variables, Initial Conditions, Loadings, Volume, Sediments, Parameters, Libraries, Ecotoxicology, Waterbodies, Link to Watershed Models, Output, Metals, Troubleshooting

Comparing two tools for ecosystem service assessments regarding water resources decisions.

PubMed

Dennedy-Frank, P James; Muenich, Rebecca Logsdon; Chaubey, Indrajeet; Ziv, Guy

2016-07-15

We present a comparison of two ecohydrologic models commonly used for planning land management to assess the production of hydrologic ecosystem services: the Soil and Water Assessment Tool (SWAT) and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) annual water yield model. We compare these two models at two distinct sites in the US: the Wildcat Creek Watershed in Indiana and the Upper Upatoi Creek Watershed in Georgia. The InVEST and SWAT models provide similar estimates of the spatial distribution of water yield in Wildcat Creek, but very different estimates of the spatial distribution of water yield in Upper Upatoi Creek. The InVEST model may do a poor job estimating the spatial distribution of water yield in the Upper Upatoi Creek Watershed because baseflow provides a significant portion of the site's total water yield, which means that storage dynamics which are not modeled by InVEST may be important. We also compare the ability of these two models, as well as one newly developed set of ecosystem service indices, to deliver useful guidance for land management decisions focused on providing hydrologic ecosystem services in three particular decision contexts: environmental flow ecosystem services, ecosystem services for potable water supply, and ecosystem services for rainfed irrigation. We present a simple framework for selecting models or indices to evaluate hydrologic ecosystem services as a way to formalize where models deliver useful guidance. Copyright © 2016 Elsevier Ltd. All rights reserved.

A watershed scale spatially-distributed model for streambank erosion rate driven by channel curvature

NASA Astrophysics Data System (ADS)

McMillan, Mitchell; Hu, Zhiyong

2017-10-01

Streambank erosion is a major source of fluvial sediment, but few large-scale, spatially distributed models exist to quantify streambank erosion rates. We introduce a spatially distributed model for streambank erosion applicable to sinuous, single-thread channels. We argue that such a model can adequately characterize streambank erosion rates, measured at the outsides of bends over a 2-year time period, throughout a large region. The model is based on the widely-used excess-velocity equation and comprised three components: a physics-based hydrodynamic model, a large-scale 1-dimensional model of average monthly discharge, and an empirical bank erodibility parameterization. The hydrodynamic submodel requires inputs of channel centerline, slope, width, depth, friction factor, and a scour factor A; the large-scale watershed submodel utilizes watershed-averaged monthly outputs of the Noah-2.8 land surface model; bank erodibility is based on tree cover and bank height as proxies for root density. The model was calibrated with erosion rates measured in sand-bed streams throughout the northern Gulf of Mexico coastal plain. The calibrated model outperforms a purely empirical model, as well as a model based only on excess velocity, illustrating the utility of combining a physics-based hydrodynamic model with an empirical bank erodibility relationship. The model could be improved by incorporating spatial variability in channel roughness and the hydrodynamic scour factor, which are here assumed constant. A reach-scale application of the model is illustrated on ∼1 km of a medium-sized, mixed forest-pasture stream, where the model identifies streambank erosion hotspots on forested and non-forested bends.

Establish Effective Lower Bounds of Watershed Slope for Traditional Hydrologic Methods

DOT National Transportation Integrated Search

2012-06-01

Equations to estimate timing parameters for a watershed contain watershed slope as a principal parameter and : estimates are usually inversely proportional to topographic slope. Hence as slope vanishes, the estimates approach : infinity. The research...

Analysis of shifts in the spatial distribution of vegetation due to climate change

NASA Astrophysics Data System (ADS)

del Jesus, Manuel; Díez-Sierra, Javier; Rinaldo, Andrea; Rodríguez-Iturbe, Ignacio

2017-04-01

Climate change will modify the statistical regime of most climatological variables, inducing changes on average values and in the natural variability of environmental variables. These environmental variables may be used to explain the spatial distribution of functional types of vegetation in arid and semiarid watersheds through the use of plant optimization theories. Therefore, plant optimization theories may be used to approximate the response of the spatial distribution of vegetation to a changing climate. Predicting changes in these spatial distributions is important to understand how climate change may affect vegetated ecosystems, but it is also important for hydrological engineering applications where climate change effects on water availability are assessed. In this work, Maximum Entropy Production (MEP) is used as the plant optimization theory that describes the spatial distribution of functional types of vegetation. Current climatological conditions are obtained from direct observations from meteorological stations. Climate change effects are evaluated for different temporal horizons and different climate change scenarios using numerical model outputs from the CMIP5. Rainfall estimates are downscaled by means of a stochastic point process used to model rainfall. The study is carried out for the Rio Salado watershed, located within the Sevilleta LTER site, in New Mexico (USA). Results show the expected changes in the spatial distribution of vegetation and allow to evaluate the expected variability of the changes. The updated spatial distributions allow to evaluate the vegetated ecosystem health and its updated resilience. These results can then be used to inform the hydrological modeling part of climate change assessments analyzing water availability in arid and semiarid watersheds.

Application of SAC88 to estimating hydrologic effects of fire on a watersheds

Treesearch

R. Larry Ferral

1989-01-01

SAC88 is a major revision of the Sacramento Model, which was developed in 1969 with minor revisions through 1973. Two of many 1988 changes make it possible to estimate hydrologic effects of a fire in a watershed where pre-fire parameters can be calibrated or estimated: (1) Evapotranspiration, treated as extracted from six root-zone layers under pre-fire conditions, may...

Ground water flow modeling with sensitivity analyses to guide field data collection in a mountain watershed

USGS Publications Warehouse

Johnson, Raymond H.

2007-01-01

In mountain watersheds, the increased demand for clean water resources has led to an increased need for an understanding of ground water flow in alpine settings. In Prospect Gulch, located in southwestern Colorado, understanding the ground water flow system is an important first step in addressing metal loads from acid-mine drainage and acid-rock drainage in an area with historical mining. Ground water flow modeling with sensitivity analyses are presented as a general tool to guide future field data collection, which is applicable to any ground water study, including mountain watersheds. For a series of conceptual models, the observation and sensitivity capabilities of MODFLOW-2000 are used to determine composite scaled sensitivities, dimensionless scaled sensitivities, and 1% scaled sensitivity maps of hydraulic head. These sensitivities determine the most important input parameter(s) along with the location of observation data that are most useful for future model calibration. The results are generally independent of the conceptual model and indicate recharge in a high-elevation recharge zone as the most important parameter, followed by the hydraulic conductivities in all layers and recharge in the next lower-elevation zone. The most important observation data in determining these parameters are hydraulic heads at high elevations, with a depth of less than 100 m being adequate. Evaluation of a possible geologic structure with a different hydraulic conductivity than the surrounding bedrock indicates that ground water discharge to individual stream reaches has the potential to identify some of these structures. Results of these sensitivity analyses can be used to prioritize data collection in an effort to reduce time and money spend by collecting the most relevant model calibration data.

A study of remote sensing as applied to regional and small watersheds. Volume 2: Supporting technical details. [using computerized simulation models

NASA Technical Reports Server (NTRS)

1974-01-01

The Stanford Watershed Model, the Kentucky Watershed Model and OPSET program, and the NASA-IBM system for simulation and analysis of watersheds are described in terms of their applications to the study of remote sensing of water resources. Specific calibration processes and input and output parameters that are instrumental in the simulations are explained for the following kinds of data: (1) hourly precipitation data; (2) daily discharge data; (3) flood hydrographs; (4) temperature and evaporation data; and (5) snowmelt data arrays. The Sensitivity Analysis Task, which provides a method for evaluation of any of the separate simulation runs in the form of performance indices, is also reported. The method is defined and a summary of results is given which indicates the values obtained in the simulation runs performed for Town Creek, Alabama; Alamosa Creek, Colorado; and Pearl River, Louisiana. The results are shown in tabular and plot graph form. For Vol. 1, see N74-27813.

Evaluation of the ADAPT model for simulating nitrogen dynamics in a tile-drained agricultural watershed in central Illinois.

PubMed

Sogbedji, Jean M; McIsaac, Gregory F

2006-01-01

Assessing the accuracy of agronomic and water quality simulation models in different soils, land-use systems, and environments provides a basis for using and improving these models. We evaluated the performance of the ADAPT model for simulating riverine nitrate-nitrogen (NO3-N) export from a 1500-km2 watershed in central Illinois, where approximately 85% of the land is used for maize-soybean production and tile drainage is common. Soil chemical properties, crop nitrogen (N) uptake coefficient, dry matter ratio, and a denitrification reduction coefficient were used as calibration parameters to optimize the fit between measured and simulated NO3-N load from the watershed for the 1989 to 1993 period. The applicability of the calibrated parameter values was tested by using these values for simulating the 1994 to 1997 period on the same watershed. Willmott's index of agreement ranged from 0.91 to 0.97 for daily, weekly, monthly, and annual comparisons of riverine nitrate N loads. Simulation accuracy generally decreased as the time interval decreased. Willmott's index for simulated crop yields ranged from 0.91 to 0.99; however, observed crop yields were used as input to the model. The partial N budget results suggested that 52 to 72 kg N ha(-1) yr(-1) accumulated in the soil, but simulated biological N fixation associated with soybeans was considerably greater than literature values for the region. Improvement of the N fixation algorithms and incorporation of mechanisms that describe soybean yield in response to environmental conditions appear to be needed to improve the performance of the model.

Simulation of Nitrogen and Phosphorus Load Runoff by a GIS-based Distributed Model for Chikugo River Watershed

NASA Astrophysics Data System (ADS)

Iseri, Haruka; Hiramatsu, Kazuaki; Harada, Masayoshi

A distributed model was developed in order to simulate the process of nitrogen and phosphorus load runoff in the semi-urban watershed of the Chikugo River, Japan. A grid of cells 1km in size was laid over the study area, and several input variables for each cell area including DEM, land use and statistical data were extracted by GIS. In the process of water runoff, hydrograph calculated at Chikugo Barrage was in close agreement with the observed one, which achieved Nash-Sutcliffe coefficient of 0.90. In addition, the model simulated reasonably well the movement of TN and TP at each station. The model was also used to analyze three scenarios based on the watershed management: (1) reduction of nutrient loads from livestock farm, (2) improvement of septic tanks' wastewater treatment system and (3) application of purification function of paddy fields. As a result, effectiveness of management strategy in each scenario depended on land use patterns. The reduction rates of nutrient load effluent in scenarios (1) and (3) were higher than that in scenario (2). The present result suggests that an appropriate management of livestock farm together with the effective use of paddy environment would have significant effects on the reduction of nutrient loads. A suitable management strategy should be planned based on the land use pattern in the watershed.

Binational digital soils map of the Ambos Nogales watershed, southern Arizona and northern Sonora, Mexico

USGS Publications Warehouse

Norman, Laura

2004-01-01

We have prepared a digital map of soil parameters for the international Ambos Nogales watershed to use as input for selected soils-erosion models. The Ambos Nogales watershed in southern Arizona and northern Sonora, Mexico, contains the Nogales wash, a tributary of the Upper Santa Cruz River. The watershed covers an area of 235 km2, just under half of which is in Mexico. Preliminary investigations of potential erosion revealed a discrepancy in soils data and mapping across the United States-Mexican border due to issues including different mapping resolutions, incompatible formatting, and varying nomenclature and classification systems. To prepare a digital soils map appropriate for input to a soils-erosion model, the historical analog soils maps for Nogales, Ariz., were scanned and merged with the larger-scale digital soils data available for Nogales, Sonora, Mexico using a geographic information system.

Calculation and analysis of the non-point source pollution in the upstream watershed of the Panjiakou Reservoir, People's Republic of China

NASA Astrophysics Data System (ADS)

Zhang, S.; Tang, L.

2007-05-01

Panjiakou Reservoir is an important drinking water resource in Haihe River Basin, Hebei Province, People's Republic of China. The upstream watershed area is about 35,000 square kilometers. Recently, the water pollution in the reservoir is becoming more serious owing to the non-point pollution as well as point source pollution on the upstream watershed. To effectively manage the reservoir and watershed and develop a plan to reduce pollutant loads, the loading of non-point and point pollution and their distribution on the upstream watershed must be understood fully. The SWAT model is used to simulate the production and transportation of the non-point source pollutants in the upstream watershed of the Panjiakou Reservoir. The loadings of non-point source pollutants are calculated for different hydrologic years and the spatial and temporal characteristics of non-point source pollution are studied. The stream network and topographic characteristics of the stream network and sub-basins are all derived from the DEM by ArcGIS software. The soil and land use data are reclassified and the soil physical properties database file is created for the model. The SWAT model was calibrated with observed data of several hydrologic monitoring stations in the study area. The results of the calibration show that the model performs fairly well. Then the calibrated model was used to calculate the loadings of non-point source pollutants for a wet year, a normal year and a dry year respectively. The time and space distribution of flow, sediment and non-point source pollution were analyzed depending on the simulated results. The comparison of different hydrologic years on calculation results is dramatic. The loading of non-point source pollution in the wet year is relatively larger but smaller in the dry year since the non-point source pollutants are mainly transported through the runoff. The pollution loading within a year is mainly produced in the flood season. Because SWAT is a distributed model, it is possible to view model output as it varies across the basin, so the critical areas and reaches can be found in the study area. According to the simulation results, it is found that different land uses can yield different results and fertilization in rainy season has an important impact on the non- point source pollution. The limitations of the SWAT model are also discussed and the measures of the control and prevention of non- point source pollution for Panjiakou Reservoir are presented according to the analysis of model calculation results.

Sustainability analysis of bioenergy based land use change under climate change and variability

NASA Astrophysics Data System (ADS)

Raj, C.; Chaubey, I.; Brouder, S. M.; Bowling, L. C.; Cherkauer, K. A.; Frankenberger, J.; Goforth, R. R.; Gramig, B. M.; Volenec, J. J.

2014-12-01

Sustainability analyses of futuristic plausible land use and climate change scenarios are critical in making watershed-scale decisions for simultaneous improvement of food, energy and water management. Bioenergy production targets for the US are anticipated to impact farming practices through the introduction of fast growing and high yielding perennial grasses/trees, and use of crop residues as bioenergy feedstocks. These land use/land management changes raise concern over potential environmental impacts of bioenergy crop production scenarios, both in terms of water availability and water quality; impacts that may be exacerbated by climate variability and change. The objective of the study was to assess environmental, economic and biodiversity sustainability of plausible bioenergy scenarios for two watersheds in Midwest US under changing climate scenarios. The study considers fourteen sustainability indicators under nine climate change scenarios from World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3). The distributed hydrological model SWAT (Soil and Water Assessment Tool) was used to simulate perennial bioenergy crops such as Miscanthus and switchgrass, and corn stover removal at various removal rates and their impacts on hydrology and water quality. Species Distribution Models (SDMs) developed to evaluate stream fish response to hydrology and water quality changes associated with land use change were used to quantify biodiversity sustainability of various bioenergy scenarios. The watershed-scale sustainability analysis was done in the St. Joseph River watershed located in Indiana, Michigan, and Ohio; and the Wildcat Creek watershed, located in Indiana. The results indicate streamflow reduction at watershed outlet with increased evapotranspiration demands for high-yielding perennial grasses. Bioenergy crops in general improved in-stream water quality compared to conventional cropping systems (maize-soybean). Water quality benefits due to land use change were generally greater than the effects of climate change variability.

Predicting Phosphorus Dynamics Across Physiographic Regions Using a Mixed Hortonian Non-Hortonian Hydrology Model

NASA Astrophysics Data System (ADS)

Collick, A.; Easton, Z. M.; Auerbach, D.; Buchanan, B.; Kleinman, P. J. A.; Fuka, D.

2017-12-01

Predicting phosphorus (P) loss from agricultural watersheds depends on accurate representation of the hydrological and chemical processes governing P mobility and transport. In complex landscapes, P predictions are complicated by a broad range of soils with and without restrictive layers, a wide variety of agricultural management, and variable hydrological drivers. The Soil and Water Assessment Tool (SWAT) is a watershed model commonly used to predict runoff and non-point source pollution transport, but is commonly only used with Hortonian (traditional SWAT) or non-Hortonian (SWAT-VSA) initializations. Many shallow soils underlain by a restricting layer commonly generate saturation excess runoff from variable source areas (VSA), which is well represented in a re-conceptualized version, SWAT-VSA. However, many watersheds exhibit traits of both infiltration excess and saturation excess hydrology internally, based on the hydrologic distance from the stream, distribution of soils across the landscape, and characteristics of restricting layers. The objective of this research is to provide an initial look at integrating distributed predictive capabilities that consider both Hortonian and Non-Hortonian solutions simultaneously within a single SWAT-VSA initialization. We compare results from all three conceptual watershed initializations against measured surface runoff and stream P loads and to highlight the model's ability to drive sub-field management of P. All three initializations predict discharge similarly well (daily Nash-Sutcliffe Efficiencies above 0.5), but the new conceptual SWAT-VSA initialization performed best in predicting P export from the watershed, while also identifying critical source areas - those areas generating large runoff and P losses at the sub field level. These results support the use of mixed Hortonian non-Hortonian SWAT-VSA initializations in predicting watershed-scale P losses and identifying critical source areas of P loss in landscapes with VSA hydrology.

Integrated systems optimization model for biofuel development: The influence of environmental constraints

NASA Astrophysics Data System (ADS)

Housh, M.; Ng, T.; Cai, X.

2012-12-01

The environmental impact is one of the major concerns of biofuel development. While many other studies have examined the impact of biofuel expansion on stream flow and water quality, this study examines the problem from the other side - will and how a biofuel production target be affected by given environmental constraints. For this purpose, an integrated model comprises of different sub-systems of biofuel refineries, transportation, agriculture, water resources and crops/ethanol market has been developed. The sub-systems are integrated into one large-scale model to guide the optimal development plan considering the interdependency between the subsystems. The optimal development plan includes biofuel refineries location and capacity, refinery operation, land allocation between biofuel and food crops, and the corresponding stream flow and nitrate load in the watershed. The watershed is modeled as a network flow, in which the nodes represent sub-watersheds and the arcs are defined as the linkage between the sub-watersheds. The runoff contribution of each sub-watershed is determined based on the land cover and the water uses in that sub-watershed. Thus, decisions of other sub-systems such as the land allocation in the land use sub-system and the water use in the refinery sub-system define the sources and the sinks of the network. Environmental policies will be addressed in the integrated model by imposing stream flow and nitrate load constraints. These constraints can be specified by location and time in the watershed to reflect the spatial and temporal variation of the regulations. Preliminary results show that imposing monthly water flow constraints and yearly nitrate load constraints will change the biofuel development plan dramatically. Sensitivity analysis is performed to examine how the environmental constraints and their spatial and the temporal distribution influence the overall biofuel development plan and the performance of each of the sub-systems. Additional scenarios are analyzed to show the synergies of crop pattern choice (first versus second generation of biofuel crops), refinery technology adaptation (particularly on water use), refinery plant distribution, and economic incentives in terms of balanced environmental protection and bioenergy development objectives.

Accuracy of topographic index models at identifying ephemeral gully trajectories on agricultural fields

NASA Astrophysics Data System (ADS)

Sheshukov, Aleksey Y.; Sekaluvu, Lawrence; Hutchinson, Stacy L.

2018-04-01

Topographic index (TI) models have been widely used to predict trajectories and initiation points of ephemeral gullies (EGs) in agricultural landscapes. Prediction of EGs strongly relies on the selected value of critical TI threshold, and the accuracy depends on topographic features, agricultural management, and datasets of observed EGs. This study statistically evaluated the predictions by TI models in two paired watersheds in Central Kansas that had different levels of structural disturbances due to implemented conservation practices. Four TI models with sole dependency on topographic factors of slope, contributing area, and planform curvature were used in this study. The observed EGs were obtained by field reconnaissance and through the process of hydrological reconditioning of digital elevation models (DEMs). The Kernel Density Estimation analysis was used to evaluate TI distribution within a 10-m buffer of the observed EG trajectories. The EG occurrence within catchments was analyzed using kappa statistics of the error matrix approach, while the lengths of predicted EGs were compared with the observed dataset using the Nash-Sutcliffe Efficiency (NSE) statistics. The TI frequency analysis produced bi-modal distribution of topographic indexes with the pixels within the EG trajectory having a higher peak. The graphs of kappa and NSE versus critical TI threshold showed similar profile for all four TI models and both watersheds with the maximum value representing the best comparison with the observed data. The Compound Topographic Index (CTI) model presented the overall best accuracy with NSE of 0.55 and kappa of 0.32. The statistics for the disturbed watershed showed higher best critical TI threshold values than for the undisturbed watershed. Structural conservation practices implemented in the disturbed watershed reduced ephemeral channels in headwater catchments, thus producing less variability in catchments with EGs. The variation in critical thresholds for all TI models suggested that TI models tend to predict EG occurrence and length over a range of thresholds rather than find a single best value.

A simple metric to predict stream water quality from storm runoff in an urban watershed.

PubMed

Easton, Zachary M; Sullivan, Patrick J; Walter, M Todd; Fuka, Daniel R; Petrovic, A Martin; Steenhuis, Tammo S

2010-01-01

The contribution of runoff from various land uses to stream channels in a watershed is often speculated and used to underpin many model predictions. However, these contributions, often based on little or no measurements in the watershed, fail to appropriately consider the influence of the hydrologic location of a particular landscape unit in relation to the stream network. A simple model was developed to predict storm runoff and the phosphorus (P) status of a perennial stream in an urban watershed in New York State using the covariance structure of runoff from different landscape units in the watershed to predict runoff in time. One hundred and twenty-seven storm events were divided into parameterization (n = 85) and forecasting (n = 42) data sets. Runoff, dissolved P (DP), and total P (TP) were measured at nine sites distributed among three land uses (high maintenance, unmaintained, wooded), three positions in the watershed (near the outlet, midwatershed, upper watershed), and in the stream at the watershed outlet. The autocorrelation among runoff and P concentrations from the watershed landscape units (n = 9) and the covariance between measurements from the landscape units and measurements from the stream were calculated and used to predict the stream response. Models, validated using leave-one-out cross-validation and a forecasting method, were able to correctly capture temporal trends in streamflow and stream P chemistry (Nash-Sutcliffe efficiencies, 0.49-0.88). The analysis suggests that the covariance structure was consistent for all models, indicating that the physical processes governing runoff and P loss from these landscape units were stationary in time and that landscapes located in hydraulically active areas have a direct hydraulic link to the stream. This methodology provides insight into the impact of various urban landscape units on stream water quantity and quality.

Participatory Modeling Processes to Build Community Knowledge Using Shared Model and Data Resources and in a Transboundary Pacific Northwest Watershed (Nooksack River Basin, Washington, USA)

NASA Astrophysics Data System (ADS)

Bandaragoda, C.; Dumas, M.

2014-12-01

As with many western US watersheds, the Nooksack River Basin faces strong pressures associated with climate variability and change, rapid population growth, and deep-rooted water law. This transboundary basin includes contributing areas in British Columbia, Canada, and has a long history of joint data collection, model development, and facilitated communication between governmental (federal, tribal, state, local), environmental, timber, agricultural, and recreational user groups. However, each entity in the watershed responds to unique data coordination, information sharing, and adaptive management regimes and thresholds, further increasing the complexity of watershed management. Over the past four years, participatory methods were used to compile and review scientific data and models, including fish habitat (endangered salmonid species), channel hydraulics, climate data, agricultural, municipal and industrial water use, and integrated watershed scale distributed hydrologic models from over 15 years of projects (from jointly funded to independent shared work by individual companies, agencies, and universities). A specific outcome of the work includes participatory design of a collective problem statement used for guidance on future investment of shared resources and development of a data-generation process where modeling results are communicated in a three-tiers for 1) public/decision-making, 2) technical, and 3) research audiences. We establish features for successful participation using tools that are iteratively developed, tested for usability through incremental knowledge building, and designed to provide rigor in modeling. A general outcome of the work is ongoing support by tribal, state, and local governments, as well as the agricultural community, to continue the generation of shared watershed data using models in a dynamic legal and regulatory setting, where two federally recognized tribes have requested federal court resolution of federal treaty rights. Our participatory modeling process aims to integrate disciplines and watershed processes over time and space, while building capacity for more holistic watershed-scale thinking, or community knowledge, by research, governmental and public interests.

Spatially distributed storm runoff modeling using remote sensing and geographic information systems

NASA Astrophysics Data System (ADS)

Melesse, Assefa Mekonnen

Advances in scientific knowledge and new techniques of remote sensing permit a better understanding of the physical land features governing hydrologic processes, and make possible efficient, large-scale hydrologic modeling. The need for land-cover and hydrologic response change detection at a larger scale and at times of the year when hydrologic studies are critical makes satellite imagery the most cost effective, efficient and reliable source of data. The use of a Geographic Information System (GIS) to store, manipulate and visualize these data, and ultimately to estimate runoff from watersheds, has gained increasing attention in recent years. In this work, remotely-sensed data and GIS tools were used to estimate the changes in land-cover, and to estimate runoff response, for three watersheds (Etonia, Econlockhatchee, and S-65A sub-basins) in Florida. Land-use information from Digital Orthophoto Quarter Quadrangles (DOQQ), Landsat Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) were analyzed for the years 1973, 1984, 1990, 1995, and 2000. Spatial distribution of land-cover was assessed over time. The corresponding infiltration excess runoff response of the study areas due to these changes was estimated using the United States Department of Agriculture, Natural Resources Conservation Service Curve Number (USDA-NRCS-CN) method. A Digital Elevation Model (DEM)-GIS technique was developed to predict stream response to runoff events based on the travel time from each grid cell to the watershed outlet. The method was tested on a representative watershed (Simms Creek) in the Etonia sub-basin. Simulated and observed runoff volume and hydrographs were compared for 17 storm events. Isolated storms, with volumes of not less than 12.75 mm (0.5 inch) were selected. This is the minimum amount of rainfall volume recommended for the NRCS-CN method. Results show that the model predicts the runoff response of the study area with an average efficiency of 57%. Comparison of the runoff prediction to Snyder's synthetic Unit hydrograph method and TOPMODEL shows the spatially distributed infiltration excess travel time model performs better than both the Snyder's method and TOPMODEL. The model is applicable to ungaged watersheds and useful for predicting runoff hydrographs resulting from changes in the land-cover.

Metal and Nutrient Distribution and Fractionation in Managed Urban Watersheds Across the US Southwest

NASA Astrophysics Data System (ADS)

Papelis, C.; Williams, A. C.; Boettcher, T. M.

2008-12-01

Metals, metalloids, and nutrients are common contaminants of concern in arid and semi-arid watersheds in the Southwestern U.S. Because of the dramatic population growth in this part of the U.S., the potential for contamination of urban watersheds has also increased over the last few decades. Streams in urban watersheds receive storm water, urban runoff, shallow groundwater, and treated wastewater, among other sources. In addition, urban watersheds are often heavily managed to mitigate flood events and sediment- related impacts. Sediment transport can have a profound effect on the water quality of affected bodies of water. However, differences in geology, hydrogeology, and land use may have dramatic effects on the distribution of nutrients and metals in different urban watersheds. To test these effects, aqueous and sediment samples were collected above and below erosion control and other structures along two heavily managed urban watersheds, namely the Las Vegas Wash in the Las Vegas Valley Watershed, Nevada, and the Rio Salado (Salt River) in the Phoenix Metropolitan Area, Arizona. The construction of such control structures has the potential to alter the distribution of metals and metalloids in bodies of water used by wildlife. In this study, all sediments were characterized by particle size distribution, specific surface area, mineralogical composition, and scanning electron microscopy. The results of total arsenic, boron, and phosphorus extractions will be discussed, as a function of sediment characteristics. Significant differences exist between the two U.S. Southwest watersheds studied, including land use, water sources, sediment characteristics, nutrient and metal distribution, and overall system complexity. These differences lead to significant variations in metalloid and nutrient distributions in the two watersheds. Differences and similarities in the two systems will be explained as a function of sediment characteristics and watershed properties.

Uncertainty analysis of hydrological modeling in a tropical area using different algorithms

NASA Astrophysics Data System (ADS)

Rafiei Emam, Ammar; Kappas, Martin; Fassnacht, Steven; Linh, Nguyen Hoang Khanh

2018-01-01

Hydrological modeling outputs are subject to uncertainty resulting from different sources of errors (e.g., error in input data, model structure, and model parameters), making quantification of uncertainty in hydrological modeling imperative and meant to improve reliability of modeling results. The uncertainty analysis must solve difficulties in calibration of hydrological models, which further increase in areas with data scarcity. The purpose of this study is to apply four uncertainty analysis algorithms to a semi-distributed hydrological model, quantifying different source of uncertainties (especially parameter uncertainty) and evaluate their performance. In this study, the Soil and Water Assessment Tools (SWAT) eco-hydrological model was implemented for the watershed in the center of Vietnam. The sensitivity of parameters was analyzed, and the model was calibrated. The uncertainty analysis for the hydrological model was conducted based on four algorithms: Generalized Likelihood Uncertainty Estimation (GLUE), Sequential Uncertainty Fitting (SUFI), Parameter Solution method (ParaSol) and Particle Swarm Optimization (PSO). The performance of the algorithms was compared using P-factor and Rfactor, coefficient of determination (R 2), the Nash Sutcliffe coefficient of efficiency (NSE) and Percent Bias (PBIAS). The results showed the high performance of SUFI and PSO with P-factor>0.83, R-factor <0.56 and R 2>0.91, NSE>0.89, and 0.18

A fractional factorial probabilistic collocation method for uncertainty propagation of hydrologic model parameters in a reduced dimensional space

NASA Astrophysics Data System (ADS)

Wang, S.; Huang, G. H.; Huang, W.; Fan, Y. R.; Li, Z.

2015-10-01

In this study, a fractional factorial probabilistic collocation method is proposed to reveal statistical significance of hydrologic model parameters and their multi-level interactions affecting model outputs, facilitating uncertainty propagation in a reduced dimensional space. The proposed methodology is applied to the Xiangxi River watershed in China to demonstrate its validity and applicability, as well as its capability of revealing complex and dynamic parameter interactions. A set of reduced polynomial chaos expansions (PCEs) only with statistically significant terms can be obtained based on the results of factorial analysis of variance (ANOVA), achieving a reduction of uncertainty in hydrologic predictions. The predictive performance of reduced PCEs is verified by comparing against standard PCEs and the Monte Carlo with Latin hypercube sampling (MC-LHS) method in terms of reliability, sharpness, and Nash-Sutcliffe efficiency (NSE). Results reveal that the reduced PCEs are able to capture hydrologic behaviors of the Xiangxi River watershed, and they are efficient functional representations for propagating uncertainties in hydrologic predictions.

Unifying distance-based goodness-of-fit indicators for hydrologic model assessment

NASA Astrophysics Data System (ADS)

Cheng, Qinbo; Reinhardt-Imjela, Christian; Chen, Xi; Schulte, Achim

2014-05-01

The goodness-of-fit indicator, i.e. efficiency criterion, is very important for model calibration. However, recently the knowledge about the goodness-of-fit indicators is all empirical and lacks a theoretical support. Based on the likelihood theory, a unified distance-based goodness-of-fit indicator termed BC-GED model is proposed, which uses the Box-Cox (BC) transformation to remove the heteroscedasticity of model errors and the generalized error distribution (GED) with zero-mean to fit the distribution of model errors after BC. The BC-GED model can unify all recent distance-based goodness-of-fit indicators, and reveals the mean square error (MSE) and the mean absolute error (MAE) that are widely used goodness-of-fit indicators imply statistic assumptions that the model errors follow the Gaussian distribution and the Laplace distribution with zero-mean, respectively. The empirical knowledge about goodness-of-fit indicators can be also easily interpreted by BC-GED model, e.g. the sensitivity to high flow of the goodness-of-fit indicators with large power of model errors results from the low probability of large model error in the assumed distribution of these indicators. In order to assess the effect of the parameters (i.e. the BC transformation parameter λ and the GED kurtosis coefficient β also termed the power of model errors) of BC-GED model on hydrologic model calibration, six cases of BC-GED model were applied in Baocun watershed (East China) with SWAT-WB-VSA model. Comparison of the inferred model parameters and model simulation results among the six indicators demonstrates these indicators can be clearly separated two classes by the GED kurtosis β: β >1 and β ≤ 1. SWAT-WB-VSA calibrated by the class β >1 of distance-based goodness-of-fit indicators captures high flow very well and mimics the baseflow very badly, but it calibrated by the class β ≤ 1 mimics the baseflow very well, because first the larger value of β, the greater emphasis is put on high flow and second the derivative of GED probability density function at zero is zero as β >1, but discontinuous as β ≤ 1, and even infinity as β < 1 with which the maximum likelihood estimation can guarantee the model errors approach zero as well as possible. The BC-GED that estimates the parameters (i.e. λ and β) of BC-GED model as well as hydrologic model parameters is the best distance-based goodness-of-fit indicator because not only the model validation using groundwater levels is very good, but also the model errors fulfill the statistic assumption best. However, in some cases of model calibration with a few observations e.g. calibration of single-event model, for avoiding estimation of the parameters of BC-GED model the MAE i.e. the boundary indicator (β = 1) of the two classes, can replace the BC-GED, because the model validation of MAE is best.

Identification of land use and other anthropogenic impacts on nitrogen cycling using stable isotopes and distributed hydrologic modeling

NASA Astrophysics Data System (ADS)

O'Connell, M. T.; Macko, S. A.

2017-12-01

Reactive modeling of sources and processes affecting the concentration of NO3- and NH4+ in natural and anthropogenically influenced surface water can reveal unexpected characteristics of the systems. A distributed hydrologic model, TREX, is presented that provides opportunities to study multiscale effects of nitrogen inputs, outputs, and changes. The model is adapted to run on parallel computing architecture and includes the geochemical reaction module PhreeqcRM, which enables calculation of δ15N and δ18O from biologically mediated transformation reactions in addition to mixing and equilibration. Management practices intended to attenuate nitrate in surface and subsurface waters, in particular the establishment of riparian buffer zones, are variably effective due to spatial heterogeneity of soils and preferential flow through buffers. Accounting for this heterogeneity in a fully distributed biogeochemical model allows for more efficient planning and management practices. Highly sensitive areas within a watershed can be identified based on a number of spatially variable parameters, and by varying those parameters systematically to determine conditions under which those areas are under more or less critical stress. Responses can be predicted at various scales to stimuli ranging from local changes in cropping regimes to global shifts in climate. This work presents simulations of conditions showing low antecedent nitrogen retention versus significant contribution of old nitrate. Nitrogen sources are partitioned using dual isotope ratios and temporally varying concentrations. In these two scenarios, we can evaluate the efficiency of source identification based on spatially explicit information, and model effects of increasing urban land use on N biogeochemical cycling.

Regional regression models of watershed suspended-sediment discharge for the eastern United States

NASA Astrophysics Data System (ADS)

Roman, David C.; Vogel, Richard M.; Schwarz, Gregory E.

2012-11-01

SummaryEstimates of mean annual watershed sediment discharge, derived from long-term measurements of suspended-sediment concentration and streamflow, often are not available at locations of interest. The goal of this study was to develop multivariate regression models to enable prediction of mean annual suspended-sediment discharge from available basin characteristics useful for most ungaged river locations in the eastern United States. The models are based on long-term mean sediment discharge estimates and explanatory variables obtained from a combined dataset of 1201 US Geological Survey (USGS) stations derived from a SPAtially Referenced Regression on Watershed attributes (SPARROW) study and the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES) database. The resulting regional regression models summarized for major US water resources regions 1-8, exhibited prediction R2 values ranging from 76.9% to 92.7% and corresponding average model prediction errors ranging from 56.5% to 124.3%. Results from cross-validation experiments suggest that a majority of the models will perform similarly to calibration runs. The 36-parameter regional regression models also outperformed a 16-parameter national SPARROW model of suspended-sediment discharge and indicate that mean annual sediment loads in the eastern United States generally correlates with a combination of basin area, land use patterns, seasonal precipitation, soil composition, hydrologic modification, and to a lesser extent, topography.

Regional regression models of watershed suspended-sediment discharge for the eastern United States

USGS Publications Warehouse

Roman, David C.; Vogel, Richard M.; Schwarz, Gregory E.

2012-01-01

Estimates of mean annual watershed sediment discharge, derived from long-term measurements of suspended-sediment concentration and streamflow, often are not available at locations of interest. The goal of this study was to develop multivariate regression models to enable prediction of mean annual suspended-sediment discharge from available basin characteristics useful for most ungaged river locations in the eastern United States. The models are based on long-term mean sediment discharge estimates and explanatory variables obtained from a combined dataset of 1201 US Geological Survey (USGS) stations derived from a SPAtially Referenced Regression on Watershed attributes (SPARROW) study and the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES) database. The resulting regional regression models summarized for major US water resources regions 1–8, exhibited prediction R2 values ranging from 76.9% to 92.7% and corresponding average model prediction errors ranging from 56.5% to 124.3%. Results from cross-validation experiments suggest that a majority of the models will perform similarly to calibration runs. The 36-parameter regional regression models also outperformed a 16-parameter national SPARROW model of suspended-sediment discharge and indicate that mean annual sediment loads in the eastern United States generally correlates with a combination of basin area, land use patterns, seasonal precipitation, soil composition, hydrologic modification, and to a lesser extent, topography.

Hydrograph separation for karst watersheds using a two-domain rainfall-discharge model

USGS Publications Warehouse

Long, Andrew J.

2009-01-01

Highly parameterized, physically based models may be no more effective at simulating the relations between rainfall and outflow from karst watersheds than are simpler models. Here an antecedent rainfall and convolution model was used to separate a karst watershed hydrograph into two outflow components: one originating from focused recharge in conduits and one originating from slow flow in a porous annex system. In convolution, parameters of a complex system are lumped together in the impulse-response function (IRF), which describes the response of the system to an impulse of effective precipitation. Two parametric functions in superposition approximate the two-domain IRF. The outflow hydrograph can be separated into flow components by forward modeling with isolated IRF components, which provides an objective criterion for separation. As an example, the model was applied to a karst watershed in the Madison aquifer, South Dakota, USA. Simulation results indicate that this watershed is characterized by a flashy response to storms, with a peak response time of 1 day, but that 89% of the flow results from the slow-flow domain, with a peak response time of more than 1 year. This long response time may be the result of perched areas that store water above the main water table. Simulation results indicated that some aspects of the system are stationary but that nonlinearities also exist.

Development, sensitivity and uncertainty analysis of LASH model

USDA-ARS?s Scientific Manuscript database

Many hydrologic models have been developed to help manage natural resources all over the world. Nevertheless, most models have presented a high complexity regarding data base requirements, as well as, many calibration parameters. This has brought serious difficulties for applying them in watersheds ...

Evaluation and modification of five techniques for estimating stormwater runoff for watersheds in west-central Florida

USGS Publications Warehouse

Trommer, J.T.; Loper, J.E.; Hammett, K.M.

1996-01-01

Several traditional techniques have been used for estimating stormwater runoff from ungaged watersheds. Applying these techniques to water- sheds in west-central Florida requires that some of the empirical relationships be extrapolated beyond tested ranges. As a result, there is uncertainty as to the accuracy of these estimates. Sixty-six storms occurring in 15 west-central Florida watersheds were initially modeled using the Rational Method, the U.S. Geological Survey Regional Regression Equations, the Natural Resources Conservation Service TR-20 model, the U.S. Army Corps of Engineers Hydrologic Engineering Center-1 model, and the Environmental Protection Agency Storm Water Management Model. The techniques were applied according to the guidelines specified in the user manuals or standard engineering textbooks as though no field data were available and the selection of input parameters was not influenced by observed data. Computed estimates were compared with observed runoff to evaluate the accuracy of the techniques. One watershed was eliminated from further evaluation when it was determined that the area contributing runoff to the stream varies with the amount and intensity of rainfall. Therefore, further evaluation and modification of the input parameters were made for only 62 storms in 14 watersheds. Runoff ranged from 1.4 to 99.3 percent percent of rainfall. The average runoff for all watersheds included in this study was about 36 percent of rainfall. The average runoff for the urban, natural, and mixed land-use watersheds was about 41, 27, and 29 percent, respectively. Initial estimates of peak discharge using the rational method produced average watershed errors that ranged from an underestimation of 50.4 percent to an overestimation of 767 percent. The coefficient of runoff ranged from 0.20 to 0.60. Calibration of the technique produced average errors that ranged from an underestimation of 3.3 percent to an overestimation of 1.5 percent. The average calibrated coefficient of runoff for each watershed ranged from 0.02 to 0.72. The average values of the coefficient of runoff necessary to calibrate the urban, natural, and mixed land-use watersheds were 0.39, 0.16, and 0.08, respectively. The U.S. Geological Survey regional regression equations for determining peak discharge produced errors that ranged from an underestimation of 87.3 percent to an over- estimation of 1,140 percent. The regression equations for determining runoff volume produced errors that ranged from an underestimation of 95.6 percent to an overestimation of 324 percent. Regression equations developed from data used for this study produced errors that ranged between an underestimation of 82.8 percent and an over- estimation of 328 percent for peak discharge, and from an underestimation of 71.2 percent to an overestimation of 241 percent for runoff volume. Use of the equations developed for west-central Florida streams produced average errors for each type of watershed that were lower than errors associated with use of the U.S. Geological Survey equations. Initial estimates of peak discharges and runoff volumes using the Natural Resources Conservation Service TR-20 model, produced average errors of 44.6 and 42.7 percent respectively, for all the watersheds. Curve numbers and times of concentration were adjusted to match estimated and observed peak discharges and runoff volumes. The average change in the curve number for all the watersheds was a decrease of 2.8 percent. The average change in the time of concentration was an increase of 59.2 percent. The shape of the input dimensionless unit hydrograph also had to be adjusted to match the shape and peak time of the estimated and observed flood hydrographs. Peak rate factors for the modified input dimensionless unit hydrographs ranged from 162 to 454. The mean errors for peak discharges and runoff volumes were reduced to 18.9 and 19.5 percent, respectively, using the average calibrated input parameters for ea

Karst medium characterization and simulation of groundwater flow in Lijiang Riversed, China

NASA Astrophysics Data System (ADS)

Hu, B. X.

2015-12-01

It is important to study water and carbon cycle processes for water resource management, pollution prevention and global warming influence on southwest karst region of China. Lijiang river basin is selected as our study region. Interdisciplinary field and laboratory experiments with various technologies are conducted to characterize the karst aquifers in detail. Key processes in the karst water cycle and carbon cycle are determined. Based on the MODFLOW-CFP model, new watershed flow and carbon cycle models are developed coupled subsurface and surface water flow models, flow and chemical/biological models. Our study is focused on the karst springshed in Mao village. The mechanisms coupling carbon cycle and water cycle are explored. Parallel computing technology is used to construct the numerical model for the carbon cycle and water cycle in the small scale watershed, which are calibrated and verified by field observations. The developed coupling model for the small scale watershed is extended to a large scale watershed considering the scale effect of model parameters and proper model structure simplification. The large scale watershed model is used to study water cycle and carbon cycle in Lijiang rivershed, and to calculate the carbon flux and carbon sinks in the Lijiang river basin. The study results provide scientific methods for water resources management and environmental protection in southwest karst region corresponding to global climate change. This study could provide basic theory and simulation method for geological carbon sequestration in China karst region.

Simulation of groundwater flow and evaluation of carbon sink in Lijiang Rivershed, China

NASA Astrophysics Data System (ADS)

Hu, Bill X.; Cao, Jianhua; Tong, Juxiu; Gao, Bing

2016-04-01

It is important to study water and carbon cycle processes for water resource management, pollution prevention and global warming influence on southwest karst region of China. Lijiang river basin is selected as our study region. Interdisciplinary field and laboratory experiments with various technologies are conducted to characterize the karst aquifers in detail. Key processes in the karst water cycle and carbon cycle are determined. Based on the MODFLOW-CFP model, new watershed flow and carbon cycle models are developed coupled subsurface and surface water flow models, flow and chemical/biological models. Our study is focused on the karst springshed in Mao village. The mechanisms coupling carbon cycle and water cycle are explored. Parallel computing technology is used to construct the numerical model for the carbon cycle and water cycle in the small scale watershed, which are calibrated and verified by field observations. The developed coupling model for the small scale watershed is extended to a large scale watershed considering the scale effect of model parameters and proper model structure simplification. The large scale watershed model is used to study water cycle and carbon cycle in Lijiang rivershed, and to calculate the carbon flux and carbon sinks in the Lijiang river basin. The study results provide scientific methods for water resources management and environmental protection in southwest karst region corresponding to global climate change. This study could provide basic theory and simulation method for geological carbon sequestration in China karst region.

Northwest Forest Plan—the first 10 years (1994–2003): preliminary assessment of the condition of watersheds.

Treesearch

Kirsten Gallo; Steven H. Lanigan; Peter Eldred; Sean N. Gordon; Chris Moyer

2005-01-01

We aggregated road, vegetation, and inchannel data to assess the condition of sixth-field watersheds and describe the distribution of the condition of watersheds in the Northwest Forest Plan (the Plan) area. The assessment is based on 250 watersheds selected at random within the Plan area. The distributions of conditions are presented for watersheds and for many of the...

Topographic Metric Predictions of Soil redistribution and Organic Carbon Distribution in Croplands

NASA Astrophysics Data System (ADS)

Mccarty, G.; Li, X.

2017-12-01

Landscape topography is a key factor controlling soil redistribution and soil organic carbon (SOC) distribution in Iowa croplands (USA). In this study, we adopted a combined approach based on carbon () and cesium (137Cs) isotope tracers, and digital terrain analysis to understand patterns of SOC redistribution and carbon sequestration dynamics as influenced by landscape topography in tilled cropland under long term corn/soybean management. The fallout radionuclide 137Cs was used to estimate soil redistribution rates and a Lidar-derived DEM was used to obtain a set of topographic metrics for digital terrain analysis. Soil redistribution rates and patterns of SOC distribution were examined across 560 sampling locations at two field sites as well as at larger scale within the watershed. We used δ13C content in SOC to partition C3 and C4 plant derived C density at 127 locations in one of the two field sites with corn being the primary source of C4 C. Topography-based models were developed to simulate SOC distribution and soil redistribution using stepwise ordinary least square regression (SOLSR) and stepwise principal component regression (SPCR). All topography-based models developed through SPCR and SOLSR demonstrated good simulation performance, explaining more than 62% variability in SOC density and soil redistribution rates across two field sites with intensive samplings. However, the SOLSR models showed lower reliability than the SPCR models in predicting SOC density at the watershed scale. Spatial patterns of C3-derived SOC density were highly related to those of SOC density. Topographic metrics exerted substantial influence on C3-derived SOC density with the SPCR model accounting for 76.5% of the spatial variance. In contrast C4 derived SOC density had poor spatial structure likely reflecting the substantial contribution of corn vegetation to recently sequestered SOC density. Results of this study highlighted the utility of topographic SPCR models for scaling field measurements of SOC density and soil redistribution rates to watershed scale which will allow watershed model to better predict fate of ecosystem C on agricultural landscapes.

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.

Drainage area characterization for evaluating green infrastructure using the Storm Water Management Model

NASA Astrophysics Data System (ADS)

Lee, Joong Gwang; Nietch, Christopher T.; Panguluri, Srinivas

2018-05-01

Urban stormwater runoff quantity and quality are strongly dependent upon catchment properties. Models are used to simulate the runoff characteristics, but the output from a stormwater management model is dependent on how the catchment area is subdivided and represented as spatial elements. For green infrastructure modeling, we suggest a discretization method that distinguishes directly connected impervious area (DCIA) from the total impervious area (TIA). Pervious buffers, which receive runoff from upgradient impervious areas should also be identified as a separate subset of the entire pervious area (PA). This separation provides an improved model representation of the runoff process. With these criteria in mind, an approach to spatial discretization for projects using the US Environmental Protection Agency's Storm Water Management Model (SWMM) is demonstrated for the Shayler Crossing watershed (SHC), a well-monitored, residential suburban area occupying 100 ha, east of Cincinnati, Ohio. The model relies on a highly resolved spatial database of urban land cover, stormwater drainage features, and topography. To verify the spatial discretization approach, a hypothetical analysis was conducted. Six different representations of a common urbanscape that discharges runoff to a single storm inlet were evaluated with eight 24 h synthetic storms. This analysis allowed us to select a discretization scheme that balances complexity in model setup with presumed accuracy of the output with respect to the most complex discretization option considered. The balanced approach delineates directly and indirectly connected impervious areas (ICIA), buffering pervious area (BPA) receiving impervious runoff, and the other pervious area within a SWMM subcatchment. It performed well at the watershed scale with minimal calibration effort (Nash-Sutcliffe coefficient = 0.852; R2 = 0.871). The approach accommodates the distribution of runoff contributions from different spatial components and flow pathways that would impact green infrastructure performance. A developed SWMM model using the discretization approach is calibrated by adjusting parameters per land cover component, instead of per subcatchment and, therefore, can be applied to relatively large watersheds if the land cover components are relatively homogeneous and/or categorized appropriately in the GIS that supports the model parameterization. Finally, with a few model adjustments, we show how the simulated stream hydrograph can be separated into the relative contributions from different land cover types and subsurface sources, adding insight to the potential effectiveness of planned green infrastructure scenarios at the watershed scale.

Stream Flow Prediction by Remote Sensing and Genetic Programming

NASA Technical Reports Server (NTRS)

Chang, Ni-Bin

2009-01-01

A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

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

Vrugt, Jasper A; Robinson, Bruce A; Ter Braak, Cajo J F

In recent years, a strong debate has emerged in the hydrologic literature regarding what constitutes an appropriate framework for uncertainty estimation. Particularly, there is strong disagreement whether an uncertainty framework should have its roots within a proper statistical (Bayesian) context, or whether such a framework should be based on a different philosophy and implement informal measures and weaker inference to summarize parameter and predictive distributions. In this paper, we compare a formal Bayesian approach using Markov Chain Monte Carlo (MCMC) with generalized likelihood uncertainty estimation (GLUE) for assessing uncertainty in conceptual watershed modeling. Our formal Bayesian approach is implemented usingmore » the recently developed differential evolution adaptive metropolis (DREAM) MCMC scheme with a likelihood function that explicitly considers model structural, input and parameter uncertainty. Our results demonstrate that DREAM and GLUE can generate very similar estimates of total streamflow uncertainty. This suggests that formal and informal Bayesian approaches have more common ground than the hydrologic literature and ongoing debate might suggest. The main advantage of formal approaches is, however, that they attempt to disentangle the effect of forcing, parameter and model structural error on total predictive uncertainty. This is key to improving hydrologic theory and to better understand and predict the flow of water through catchments.« less

Analyzing dynamics of snow distribution and melt runoff in a meso-scaled watershed using the AgroEcoSystem-Watershed (AgES-W) model

NASA Astrophysics Data System (ADS)

Kunz, A.; Helmschrot, J.; Green, T. R.

2013-12-01

The seasonal snow cover in the western mountain regions of the United States functions as the primary supply and storage of water. Water management in these areas is often based on empirical relationships between point measurements of snow water equivalent (SWE) at selected sites and associated stream discharge. With a climate shifting towards more rain and less snow, due to the global warming, the patterns of snow deposition, and consequently the timing of melt, soil water content and the flow in streams and rivers will most likely alter. As a consequence, the established relationships between measured SWE and runoff will become unstable and unreliable, and consequently impacting the water resource management in this area. To better assess and understand the spatial and temporal dimension of altered snow cover on runoff generation in the intermountain region of the western United States, we set up the distributed hydrological AgroEcoSystem-Watershed (AgES-W) model for the Reynolds Creek Experimental Watershed (239 km2) in the Owyhee Mountains of Idaho. The study area with elevations ranging from 1101 to 2241 m is dominated by granitic and volcanic rocks and lake sediments. Deep moist soils allowing for mountain big sagebrush aspen and subalpine fir are found at higher elevations, whereas shallow, arid soils supporting sagebrush-grassland communities are common at lower elevations. Precipitation in the region varies from 230 mm at the lower elevations in the north up to 1100 mm in the higher regions at the southern margin south. The mean annual streamflow at the outlet is 0.56 m3/s. Since the Reynolds Creek Experimental Watershed (RCEW) was selected as a test basin in 1959, a comprehensive hydro-climatological network provides long-term records of daily snow, precipitation, temperature and streamflow measurements. Thus, we used a 30-year data record to calibrate and validate the AgES-W model to three nested sub-basins within the test site. First results show declining discharge volumes for RCEW, while volumes remain fairly constant for the 0.4 km2 Reynolds Mountain East (RME) headwater basin. Comparing simulated snow cover with snow-depth records measured across RME, the model was initially tested regarding its reliability to estimate spatio-temporal snow cover. AgES-W was able to simulate snow-depth dynamics quite well (>0.7 Nash-Sutcliffe Efficiency) for single measurement points, which were cross-validated using additional measurement points as well as stream discharge. The obtained parameter set was then used to model snow distribution for the entire RME basin for a period of 12 years. Applying the calibrated model to all catchments, we analyzed temporal shifts of seasonal runoff within and between the three nested subwatersheds to identify possible changes in the spatio-temporal pattern of snow accumulation and snowmelt. The model results were further used to analyze and map simulated snow water equivalents along a topographic gradient to identify spatial shifts of the snowline during the last 30 years. First results for RME indicate a decline of snow-covered area based on the course of monthly averages, with the largest declines in January and February.

Is site-specific APEX calibration necessary for field scale BMP assessment?

USDA-ARS?s Scientific Manuscript database

The possibility of extending parameter sets obtained at one site to sites with similar characteristics is appealing. This study was undertaken to test model performance and compare the effectiveness of best management practices (BMPs) using three parameters sets obtained from three watersheds when a...

Tradeoffs among watershed model calibration targets for parameter estimation

EPA Science Inventory

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...

Probability modeling of high flow extremes in Yingluoxia watershed, the upper reaches of Heihe River basin

NASA Astrophysics Data System (ADS)

Li, Zhanling; Li, Zhanjie; Li, Chengcheng

2014-05-01

Probability modeling of hydrological extremes is one of the major research areas in hydrological science. Most basins in humid and semi-humid south and east of China are concerned for probability modeling analysis of high flow extremes. While, for the inland river basin which occupies about 35% of the country area, there is a limited presence of such studies partly due to the limited data availability and a relatively low mean annual flow. The objective of this study is to carry out probability modeling of high flow extremes in the upper reach of Heihe River basin, the second largest inland river basin in China, by using the peak over threshold (POT) method and Generalized Pareto Distribution (GPD), in which the selection of threshold and inherent assumptions for POT series are elaborated in details. For comparison, other widely used probability distributions including generalized extreme value (GEV), Lognormal, Log-logistic and Gamma are employed as well. Maximum likelihood estimate is used for parameter estimations. Daily flow data at Yingluoxia station from 1978 to 2008 are used. Results show that, synthesizing the approaches of mean excess plot, stability features of model parameters, return level plot and the inherent independence assumption of POT series, an optimum threshold of 340m3/s is finally determined for high flow extremes in Yingluoxia watershed. The resulting POT series is proved to be stationary and independent based on Mann-Kendall test, Pettitt test and autocorrelation test. In terms of Kolmogorov-Smirnov test, Anderson-Darling test and several graphical diagnostics such as quantile and cumulative density function plots, GPD provides the best fit to high flow extremes in the study area. The estimated high flows for long return periods demonstrate that, as the return period increasing, the return level estimates are probably more uncertain. The frequency of high flow extremes exhibits a very slight but not significant decreasing trend from 1978 to 2008, while the intensity of such flow extremes is comparatively increasing especially for the higher return levels.

Simulation of runoff and water quality for 1990 and 2008 land use conditions in the Reedy Creek watershed, East-Central Florida

USGS Publications Warehouse

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

Grouping like catchments: A novel means to compare 40+ watersheds in the Northeastern U.S.

NASA Astrophysics Data System (ADS)

Shaw, S. B.; Walter, M.; Marjerison, R. D.

2008-12-01

One difficulty in understanding the effect of multi-scale patterns in watersheds comes from finding a concise way to identify and compare features across many basins. Comparing raw data (i.e. discharge time series) requires one to account for highly variable climate drivers while extracting meaningful metrics from the data series. Comparing model parameters imposes model assumptions that may obscure fundamental differences, potentially making it an exercise in comparing calibration factors. As a possible middle ground, we have found that the probability of a given basin-wide runoff response can be predicted by combining rainfall frequency with 1. a curve establishing a relationship between basin storage and base flow and 2. the baseflow flow-duration curve. In addition to providing a means to predict runoff, these curves succinctly present empirical runoff-response information, allowing ready graphical comparison of multiple watersheds. From 40+ watersheds throughout the Northeastern U.S., we demonstrate the potential to group watersheds and identify critical hydrologic features, providing particular insight into the influence of land use patterns as well as basin scale.

Modeling Best Management Practices (BMPs) with HSPF

EPA Science Inventory

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

Using Hybrid Techniques for Generating Watershed-scale Flood Models in an Integrated Modeling Framework

NASA Astrophysics Data System (ADS)

Saksena, S.; Merwade, V.; Singhofen, P.

2017-12-01

There is an increasing global trend towards developing large scale flood models that account for spatial heterogeneity at watershed scales to drive the future flood risk planning. Integrated surface water-groundwater modeling procedures can elucidate all the hydrologic processes taking part during a flood event to provide accurate flood outputs. Even though the advantages of using integrated modeling are widely acknowledged, the complexity of integrated process representation, computation time and number of input parameters required have deterred its application to flood inundation mapping, especially for large watersheds. This study presents a faster approach for creating watershed scale flood models using a hybrid design that breaks down the watershed into multiple regions of variable spatial resolution by prioritizing higher order streams. The methodology involves creating a hybrid model for the Upper Wabash River Basin in Indiana using Interconnected Channel and Pond Routing (ICPR) and comparing the performance with a fully-integrated 2D hydrodynamic model. The hybrid approach involves simplification procedures such as 1D channel-2D floodplain coupling; hydrologic basin (HUC-12) integration with 2D groundwater for rainfall-runoff routing; and varying spatial resolution of 2D overland flow based on stream order. The results for a 50-year return period storm event show that hybrid model (NSE=0.87) performance is similar to the 2D integrated model (NSE=0.88) but the computational time is reduced to half. The results suggest that significant computational efficiency can be obtained while maintaining model accuracy for large-scale flood models by using hybrid approaches for model creation.

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).

Distributed Modeling Reveals the Ecohydrological Dynamics Linked with Woody Plant Encroachment in the Sonoran Desert

NASA Astrophysics Data System (ADS)

Pierini, N. A.; Vivoni, E. R.; Anderson, C.; Saripalli, S.; Robles-Morua, A.

2012-12-01

Woody plant encroachment is an important issue facing semiarid ecosystems in the southwestern United States that is associated with grazing pressures, fire suppression, and the invasion of shrub species into historical grasslands. In this study, we present observational and distributed modeling activities conducted in two small rangeland watersheds of the Santa Rita Experimental Range, Arizona. This Sonoran Desert landscape is representative of the vegetation shift from grasslands to a woody savanna due to the encroachment of velvet mesquite (Prosopis velutina). The paired basins are similar in size and in close proximity, leading to equivalent meteorological and soil conditions. Nevertheless, they vary substantially in mesquite cover, with one basin having undergone a removal treatment several decades ago, while the other watershed represents the regional encroachment process. This distinction presents an excellent case study for analyzing the effects of mesquite encroachment on dryland ecohydrological dynamics. Observational datasets are obtained from a high-resolution environmental sensor network consisting of six rain gauges, twenty-one soil moisture and temperature profiles, five channel runoff flumes and an eddy covariance tower with a complete set of radiation, energy, carbon and water fluxes. In addition, high-resolution digital terrain models and image orthomosaics were obtained from a piloted aircraft with Light Detection and Ranging (LiDAR) measurements and an Unmanned Aerial Vehicle (UAV) with a digital camera. These two remote sensing platforms allowed characterizing the topography, stream network and plant species distributions at a high resolution (<1 m) in both basins. Using the sensor network, we present comparative analyses of watershed rainfall-runoff transformation in the paired basins, illustrating the role that mesquite trees have in runoff generation at the two outlet flumes. We further explore the impact of mesquite trees on the soil moisture and temperature distributions through comparisons of canopy and intercanopy sites. The field and remote sensing observations are then used in simulations using the TIN-based Real-time Integrated Basin Simulator (tRIBS) at high spatiotemporal resolutions over the two study years (2011-2012). Numerical experiments are designed to reveal the influence of the mesquite encroachment patterns on the watershed dynamics. Through the spatiotemporal analysis of model outputs, we identify how and when mesquite trees affect the spatial patterns of energy and water fluxes and their linkage to runoff production. As a result, the distributed model application provides a more complete understanding of the impact of woody encroachment on watershed-scale hydrologic patterns.

The impact of watershed management on coastal morphology: A case study using an integrated approach and numerical modeling

NASA Astrophysics Data System (ADS)

Samaras, Achilleas G.; Koutitas, Christopher G.

2014-04-01

Coastal morphology evolves as the combined result of both natural- and human- induced factors that cover a wide range of spatial and temporal scales of effect. Areas in the vicinity of natural stream mouths are of special interest, as the direct connection with the upstream watershed extends the search for drivers of morphological evolution from the coastal area to the inland as well. Although the impact of changes in watersheds on the coastal sediment budget is well established, references that study concurrently the two fields and the quantification of their connection are scarce. In the present work, the impact of land-use changes in a watershed on coastal erosion is studied for a selected site in North Greece. Applications are based on an integrated approach to quantify the impact of watershed management on coastal morphology through numerical modeling. The watershed model SWAT and a shoreline evolution model developed by the authors (PELNCON-M) are used, evaluating with the latter the performance of the three longshore sediment transport rate formulae included in the model formulation. Results document the impact of crop abandonment on coastal erosion (agricultural land decrease from 23.3% to 5.1% is accompanied by the retreat of ~ 35 m in the vicinity of the stream mouth) and show the effect of sediment transport formula selection on the evolution of coastal morphology. Analysis denotes the relative importance of the parameters involved in the dynamics of watershed-coast systems, and - through the detailed description of a case study - is deemed to provide useful insights for researchers and policy-makers involved in their study.

Effect of Temporal and Spatial Rainfall Resolution on HSPF Predictive Performance and Parameter Estimation

EPA Science Inventory

Watershed scale rainfall‐runoff models are used for environmental management and regulatory modeling applications, but their effectiveness are limited by predictive uncertainties associated with model input data. This study evaluated the effect of temporal and spatial rainfall re...

Integrated Approach to Inform the New York City Water Supply System Coupling SAR Remote Sensing Observations and the SWAT Watershed Model

NASA Astrophysics Data System (ADS)

Tesser, D.; Hoang, L.; McDonald, K. C.

2017-12-01

Efforts to improve municipal water supply systems increasingly rely on an ability to elucidate variables that drive hydrologic dynamics within large watersheds. However, fundamental model variables such as precipitation, soil moisture, evapotranspiration, and soil freeze/thaw state remain difficult to measure empirically across large, heterogeneous watersheds. Satellite remote sensing presents a method to validate these spatially and temporally dynamic variables as well as better inform the watershed models that monitor the water supply for many of the planet's most populous urban centers. PALSAR 2 L-band, Sentinel 1 C-band, and SMAP L-band scenes covering the Cannonsville branch of the New York City (NYC) water supply watershed were obtained for the period of March 2015 - October 2017. The SAR data provides information on soil moisture, free/thaw state, seasonal surface inundation, and variable source areas within the study site. Integrating the remote sensing products with watershed model outputs and ground survey data improves the representation of related processes in the Soil and Water Assessment Tool (SWAT) utilized to monitor the NYC water supply. PALSAR 2 supports accurate mapping of the extent of variable source areas while Sentinel 1 presents a method to model the timing and magnitude of snowmelt runoff events. SMAP Active Radar soil moisture product directly validates SWAT outputs at the subbasin level. This blended approach verifies the distribution of soil wetness classes within the watershed that delineate Hydrologic Response Units (HRUs) in the modified SWAT-Hillslope. The research expands the ability to model the NYC water supply source beyond a subset of the watershed while also providing high resolution information across a larger spatial scale. The global availability of these remote sensing products provides a method to capture fundamental hydrology variables in regions where current modeling efforts and in situ data remain limited.

Using the SWAT model to improve process descriptions and define hydrologic partitioning in South Korea

NASA Astrophysics Data System (ADS)

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

2014-02-01

Watershed-scale modeling can be a valuable tool to aid in quantification of water quality and yield; however, several challenges remain. In many watersheds, it is difficult to adequately quantify hydrologic partitioning. Data scarcity is prevalent, accuracy of spatially distributed meteorology is difficult to quantify, forest encroachment and land use issues are common, and surface water and groundwater abstractions substantially modify watershed-based processes. Our objective is to assess the capability of the Soil and Water Assessment Tool (SWAT) model to capture event-based and long-term monsoonal rainfall-runoff processes in complex mountainous terrain. To accomplish this, we developed a unique quality-control, gap-filling algorithm for interpolation of high-frequency meteorological data. We used a novel multi-location, multi-optimization calibration technique to improve estimations of catchment-wide hydrologic partitioning. The interdisciplinary model was calibrated to a unique combination of statistical, hydrologic, and plant growth metrics. Our results indicate scale-dependent sensitivity of hydrologic partitioning and substantial influence of engineered features. The addition of hydrologic and plant growth objective functions identified the importance of culverts in catchment-wide flow distribution. While this study shows the challenges of applying the SWAT model to complex terrain and extreme environments; by incorporating anthropogenic features into modeling scenarios, we can enhance our understanding of the hydroecological impact.

A Bayesian Hierarchical Modeling Approach to Predicting Flow in Ungauged Basins

NASA Astrophysics Data System (ADS)

Gronewold, A.; Alameddine, I.; Anderson, R. M.

2009-12-01

Recent innovative approaches to identifying and applying regression-based relationships between land use patterns (such as increasing impervious surface area and decreasing vegetative cover) and rainfall-runoff model parameters represent novel and promising improvements to predicting flow from ungauged basins. In particular, these approaches allow for predicting flows under uncertain and potentially variable future conditions due to rapid land cover changes, variable climate conditions, and other factors. Despite the broad range of literature on estimating rainfall-runoff model parameters, however, the absence of a robust set of modeling tools for identifying and quantifying uncertainties in (and correlation between) rainfall-runoff model parameters represents a significant gap in current hydrological modeling research. Here, we build upon a series of recent publications promoting novel Bayesian and probabilistic modeling strategies for quantifying rainfall-runoff model parameter estimation uncertainty. Our approach applies alternative measures of rainfall-runoff model parameter joint likelihood (including Nash-Sutcliffe efficiency, among others) to simulate samples from the joint parameter posterior probability density function. We then use these correlated samples as response variables in a Bayesian hierarchical model with land use coverage data as predictor variables in order to develop a robust land use-based tool for forecasting flow in ungauged basins while accounting for, and explicitly acknowledging, parameter estimation uncertainty. We apply this modeling strategy to low-relief coastal watersheds of Eastern North Carolina, an area representative of coastal resource waters throughout the world because of its sensitive embayments and because of the abundant (but currently threatened) natural resources it hosts. Consequently, this area is the subject of several ongoing studies and large-scale planning initiatives, including those conducted through the United States Environmental Protection Agency (USEPA) total maximum daily load (TMDL) program, as well as those addressing coastal population dynamics and sea level rise. Our approach has several advantages, including the propagation of parameter uncertainty through a nonparametric probability distribution which avoids common pitfalls of fitting parameters and model error structure to a predetermined parametric distribution function. In addition, by explicitly acknowledging correlation between model parameters (and reflecting those correlations in our predictive model) our model yields relatively efficient prediction intervals (unlike those in the current literature which are often unnecessarily large, and may lead to overly-conservative management actions). Finally, our model helps improve understanding of the rainfall-runoff process by identifying model parameters (and associated catchment attributes) which are most sensitive to current and future land use change patterns. Disclaimer: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.

Regression equations for estimation of annual peak-streamflow frequency for undeveloped watersheds in Texas using an L-moment-based, PRESS-minimized, residual-adjusted approach

USGS Publications Warehouse

Asquith, William H.; Roussel, Meghan C.

2009-01-01

Annual peak-streamflow frequency estimates are needed for flood-plain management; for objective assessment of flood risk; for cost-effective design of dams, levees, and other flood-control structures; and for design of roads, bridges, and culverts. Annual peak-streamflow frequency represents the peak streamflow for nine recurrence intervals of 2, 5, 10, 25, 50, 100, 200, 250, and 500 years. Common methods for estimation of peak-streamflow frequency for ungaged or unmonitored watersheds are regression equations for each recurrence interval developed for one or more regions; such regional equations are the subject of this report. The method is based on analysis of annual peak-streamflow data from U.S. Geological Survey streamflow-gaging stations (stations). Beginning in 2007, the U.S. Geological Survey, in cooperation with the Texas Department of Transportation and in partnership with Texas Tech University, began a 3-year investigation concerning the development of regional equations to estimate annual peak-streamflow frequency for undeveloped watersheds in Texas. The investigation focuses primarily on 638 stations with 8 or more years of data from undeveloped watersheds and other criteria. The general approach is explicitly limited to the use of L-moment statistics, which are used in conjunction with a technique of multi-linear regression referred to as PRESS minimization. The approach used to develop the regional equations, which was refined during the investigation, is referred to as the 'L-moment-based, PRESS-minimized, residual-adjusted approach'. For the approach, seven unique distributions are fit to the sample L-moments of the data for each of 638 stations and trimmed means of the seven results of the distributions for each recurrence interval are used to define the station specific, peak-streamflow frequency. As a first iteration of regression, nine weighted-least-squares, PRESS-minimized, multi-linear regression equations are computed using the watershed characteristics of drainage area, dimensionless main-channel slope, and mean annual precipitation. The residuals of the nine equations are spatially mapped, and residuals for the 10-year recurrence interval are selected for generalization to 1-degree latitude and longitude quadrangles. The generalized residual is referred to as the OmegaEM parameter and represents a generalized terrain and climate index that expresses peak-streamflow potential not otherwise represented in the three watershed characteristics. The OmegaEM parameter was assigned to each station, and using OmegaEM, nine additional regression equations are computed. Because of favorable diagnostics, the OmegaEM equations are expected to be generally reliable estimators of peak-streamflow frequency for undeveloped and ungaged stream locations in Texas. The mean residual standard error, adjusted R-squared, and percentage reduction of PRESS by use of OmegaEM are 0.30log10, 0.86, and -21 percent, respectively. Inclusion of the OmegaEM parameter provides a substantial reduction in the PRESS statistic of the regression equations and removes considerable spatial dependency in regression residuals. Although the OmegaEM parameter requires interpretation on the part of analysts and the potential exists that different analysts could estimate different values for a given watershed, the authors suggest that typical uncertainty in the OmegaEM estimate might be about +or-0.1010. Finally, given the two ensembles of equations reported herein and those in previous reports, hydrologic design engineers and other analysts have several different methods, which represent different analytical tracks, to make comparisons of peak-streamflow frequency estimates for ungaged watersheds in the study area.

Rainfall prediction of Cimanuk watershed regions with canonical correlation analysis (CCA)

NASA Astrophysics Data System (ADS)

Rustiana, Shailla; Nurani Ruchjana, Budi; Setiawan Abdullah, Atje; Hermawan, Eddy; Berliana Sipayung, Sinta; Gede Nyoman Mindra Jaya, I.; Krismianto

2017-10-01

Rainfall prediction in Indonesia is very influential on various development sectors, such as agriculture, fisheries, water resources, industry, and other sectors. The inaccurate predictions can lead to negative effects. Cimanuk watershed is one of the main pillar of water resources in West Java. This watersheds divided into three parts, which is a headwater of Cimanuk sub-watershed, Middle of Cimanuk sub-watershed and downstream of Cimanuk sub- watershed. The flow of this watershed will flow through the Jatigede reservoir and will supply water to the north-coast area in the next few years. So, the reliable model of rainfall prediction is very needed in this watershed. Rainfall prediction conducted with Canonical Correlation Analysis (CCA) method using Climate Predictability Tool (CPT) software. The prediction is every 3months on 2016 (after January) based on Climate Hazards group Infrared Precipitation with Stations (CHIRPS) data over West Java. Predictors used in CPT were the monthly data index of Nino3.4, Dipole Mode (DMI), and Monsoon Index (AUSMI-ISMI-WNPMI-WYMI) with initial condition January. The initial condition is chosen by the last data update. While, the predictant were monthly rainfall data CHIRPS region of West Java. The results of prediction rainfall showed by skill map from Pearson Correlation. High correlation of skill map are on MAM (Mar-Apr-May), AMJ (Apr-May-Jun), and JJA (Jun-Jul-Aug) which means the model is reliable to forecast rainfall distribution over Cimanuk watersheds region (over West Java) on those seasons. CCA score over those season prediction mostly over 0.7. The accuracy of the model CPT also indicated by the Relative Operating Characteristic (ROC) curve of the results of Pearson correlation 3 representative point of sub-watershed (Sumedang, Majalengka, and Cirebon), were mostly located in the top line of non-skill, and evidenced by the same of rainfall patterns between observation and forecast. So, the model of CPT with CCA method is reliable to use.

Modeling runoff and microbial overland transport with KINEROS2/STWIR model: Accuracy and uncertainty as affected by source of infiltration parameters

EPA Science Inventory

Infiltration is important to modeling the overland transport of microorganisms in environmental waters. In watershed- and hillslope scale-models, infiltration is commonly described by simple equations relating infiltration rate to soil saturated conductivity and by empirical para...

Evaluation, Calibration and Comparison of the Precipitation-Runoff Modeling System (PRMS) National Hydrologic Model (NHM) Using Moderate Resolution Imaging Spectroradiometer (MODIS) and Snow Data Assimilation System (SNODAS) Gridded Datasets

NASA Astrophysics Data System (ADS)

Norton, P. A., II; Haj, A. E., Jr.

2014-12-01

The United States Geological Survey is currently developing a National Hydrologic Model (NHM) to support and facilitate coordinated and consistent hydrologic modeling efforts at the scale of the continental United States. As part of this effort, the Geospatial Fabric (GF) for the NHM was created. The GF is a database that contains parameters derived from datasets that characterize the physical features of watersheds. The GF was used to aggregate catchments and flowlines defined in the National Hydrography Dataset Plus dataset for more than 100,000 hydrologic response units (HRUs), and to establish initial parameter values for input to the Precipitation-Runoff Modeling System (PRMS). Many parameter values are adjusted in PRMS using an automated calibration process. Using these adjusted parameter values, the PRMS model estimated variables such as evapotranspiration (ET), potential evapotranspiration (PET), snow-covered area (SCA), and snow water equivalent (SWE). In order to evaluate the effectiveness of parameter calibration, and model performance in general, several satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) and Snow Data Assimilation System (SNODAS) gridded datasets including ET, PET, SCA, and SWE were compared to PRMS-simulated values. The MODIS and SNODAS data were spatially averaged for each HRU, and compared to PRMS-simulated ET, PET, SCA, and SWE values for each HRU in the Upper Missouri River watershed. Default initial GF parameter values and PRMS calibration ranges were evaluated. Evaluation results, and the use of MODIS and SNODAS datasets to update GF parameter values and PRMS calibration ranges, are presented and discussed.

Changes in Water Quality of Grand Lake St. Marys Watershed Following Implementation of a Distressed Watershed Rules Package.

PubMed

Jacquemin, Stephen J; Johnson, Laura T; Dirksen, Theresa A; McGlinch, Greg

2018-01-01

Grand Lake St. Marys watershed has drawn attention over the past decade as water quality issues resulting from nutrient loading have come to the forefront of public opinion, political concern, and scientific study. The objective of this study was to assess long-term changes in water quality (nutrient and sediment concentrations) following the distressed watershed rules package instituted in 2011. Since that time, a variety of rules (e.g., winter manure ban) and best management practices (cover crops, manure storage or transfers, buffers, etc.) have been implemented. We used a general linear model to assess variation in total suspended solids, particulate phosphorus, soluble reactive phosphorus (SRP), nitrate N, and total Kjeldahl nitrogen concentrations from daily Chickasaw Creek (drains ∼25% of watershed) samples spanning 2008 to 2016. Parameters were related to flow (higher values during high flows), timing (lower values during winter months), and the implementation of the distressed watershed rules package (lower values following implementation). Overall, reductions following the distressed designation for all parameters ranged from 5 to 35% during medium and high flow periods (with exception of SRP). Reductions were even more pronounced during winter months covered by the manure ban, where all parameters (including SRP) exhibited decreases at medium and high flows between 20 and 60%. While the reductions seen in this study are significant, concentrations are still highly elevated and continue to be a problem. We are optimistic that this study will serve to inform future management in the region and elsewhere. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Hydrologic Forecasting in the 21st Century: Challenges and Directions of Research

NASA Astrophysics Data System (ADS)

Restrepo, P.; Schaake, J.

2009-04-01

Traditionally, the role of the Hydrology program of the National Weather Service has been centered around forecasting floods, in order to minimize loss of lives and damage to property as a result of floods as well as water levels for navigable rivers, and water supply in some areas of the country. A number of factors, including shifting population patterns, widespread drought and concerns about climate change have made it imperative to widen the focus to cover forecasting flows ranging from drought to floods and anything in between. Because of these concerns, it is imperative to develop models that rely more on the physical characteristics of the watershed for parameterization and less on historical observations. Furthermore, it is also critical to consider explicitly the sources of uncertainty in the forecasting process, including parameter values, model structure, forcings (both observations and forecasts), initial conditions, and streamflow observations. A consequence of more widespread occurrence of low flows as a result either of the already evident earlier snowmelt in the Western United States, or of the predicted changes in precipitation patterns, is the issue of water quality: lower flows will have higher concentrations of certain pollutants. This paper describes the current projects and future directions of research for hydrologic forecasting in the United States. Ongoing projects on quantitative precipitation and temperature estimates and forecasts, uncertainty modeling by the use of ensembles, data assimilation, verification, distributed conceptual modeling will be reviewed. Broad goals of the research directions are: 1) reliable modeling of the different sources of uncertainty. 2) a more expeditious and cost-effective approach by reducing the effort required in model calibration; 3) improvements in forecast lead-time and accuracy; 4) an approach for rapid adjustment of model parameters to account for changes in the watershed, both rapid as the result from forest fires or levee breaches, and slow, as the result of watershed reforestation, reforestation or urban development; 5) an expanded suite of products, including soil moisture and temperature forecasts, and water quality constituents; and 6) a comprehensive verification system to assess the effectiveness of the other 5 goals. To this end, the research plan places an emphasis on research of models with parameters that can be derived from physical watershed characteristics. Purely physically based models may be unattainable or impractical, and, therefore, models resulting from a combination of physically and conceptually approached processes may be required With respect to the hydrometeorological forcings the research plan emphasizes the development of improved precipitation estimation techniques through the synthesis of radar, rain gauge, satellite, and numerical weather prediction model output, particularly in those areas where ground-based sensors are inadequate to detect spatial variability in precipitation. Better estimation and forecasting of precipitation are most likely to be achieved by statistical merging of remote-sensor observations and forecasts from high-resolution numerical prediction models. Enhancements to the satellite-based precipitation products will include use of TRMM precipitation data in preparation for information to be supplied by the Global Precipitation Mission satellites not yet deployed. Because of a growing need for services in water resources, including low-flow forecasts for water supply customers, we will be directing research into coupled surface-groundwater models that will eventually replace the groundwater component of the existing models, and will be part of the new generation of models. Finally, the research plan covers the directions of research for probabilistic forecasting using ensembles, data assimilation and the verification and validation of both deterministic and probabilistic forecasts.

Effects of spatial variability and scale on areal -average evapotranspiration

NASA Technical Reports Server (NTRS)

Famiglietti, J. S.; Wood, Eric F.

1993-01-01

This paper explores the effect of spatial variability and scale on areally-averaged evapotranspiration. A spatially-distributed water and energy balance model is employed to determine the effect of explicit patterns of model parameters and atmospheric forcing on modeled areally-averaged evapotranspiration over a range of increasing spatial scales. The analysis is performed from the local scale to the catchment scale. The study area is King's Creek catchment, an 11.7 sq km watershed located on the native tallgrass prairie of Kansas. The dominant controls on the scaling behavior of catchment-average evapotranspiration are investigated by simulation, as is the existence of a threshold scale for evapotranspiration modeling, with implications for explicit versus statistical representation of important process controls. It appears that some of our findings are fairly general, and will therefore provide a framework for understanding the scaling behavior of areally-averaged evapotranspiration at the catchment and larger scales.

Nitrogen Flux in Watersheds: The Role of Soil Distributions and Climate in Nitrogen Flux to the Coastal Ecosystems

NASA Astrophysics Data System (ADS)

Showers, W. J.; Reyes, M. M.; Genna, B. J.

2009-12-01

Quantifying the flux of nitrate from different landscape sources in watersheds is important to understand the increased flux of nitrogen to coastal ecosystems. Recent technological advances in chemical sensor networks has demonstrated that chemical variability in aquatic environments are chronically under-sampled, and that many nutrient monitoring programs with monthly or daily sampling rates are inadequate to characterize the dominate seasonal, daily or semi-diurnal fluxes in watersheds. The RiverNet program has measured the nitrate flux in the Neuse River Basin, NC on a 15 minute interval over the past eight years. Significant diurnal variation has been observed in nitrate concentrations during high and low flow periods associated with waste water treatment plants in urban watersheds that are not present in agricultural watersheds. Discharge and N flux in the basin also has significant inter-annual variations associated with El Nino oscillations modified by the North Atlantic oscillation. Positive JMA and NAO indexes are associated with increased groundwater levels, nutrient fluxes, and estuary fish kills. To understand how climate oscillation affect discharge and nutrient fluxes, we have monitored runoff/drainages and groundwater inputs adjacent to a large waste application field over the past 4 years, and used the nitrate inputs as a tracer. Surface water run off is well correlated to precipitation patterns and is the largest nutrient flux into the river. Groundwater inputs are variable spatially and temporally, and are controlled by geology and groundwater levels. Hydric soil spatial distributions are an excellent predictor of nutrient transport across landscapes, and is related to the distribution of biogeochemical “hotspots” The isotopic composition of oxygen and nitrogen in dissolved nitrate indicate that sources change with discharge state, and that atmospherically deposited nitrogen is only important to river fluxes in forested and urban watersheds. These results also indicate that the contribution of wastewater treatment plants from urban watersheds has been greatly under-estimated in current models. Prediction of future changes in discharge and nutrient flux by the modeling of climate oscillations has important implications for water resources policy and drought management for public policy and utility managers.

The Role of Frozen Soil in Groundwater Discharge Predictions for Warming Alpine Watersheds

NASA Astrophysics Data System (ADS)

Evans, Sarah G.; Ge, Shemin; Voss, Clifford I.; Molotch, Noah P.

2018-03-01

Climate warming may alter the quantity and timing of groundwater discharge to streams in high alpine watersheds due to changes in the timing of the duration of seasonal freezing in the subsurface and snowmelt recharge. It is imperative to understand the effects of seasonal freezing and recharge on groundwater discharge to streams in warming alpine watersheds as streamflow originating from these watersheds is a critical water resource for downstream users. This study evaluates how climate warming may alter groundwater discharge due to changes in seasonally frozen ground and snowmelt using a 2-D coupled flow and heat transport model with freeze and thaw capabilities for variably saturated media. The model is applied to a representative snowmelt-dominated watershed in the Rocky Mountains of central Colorado, USA, with snowmelt time series reconstructed from a 12 year data set of hydrometeorological records and satellite-derived snow covered area. Model analyses indicate that the duration of seasonal freezing in the subsurface controls groundwater discharge to streams, while snowmelt timing controls groundwater discharge to hillslope faces. Climate warming causes changes to subsurface ice content and duration, rerouting groundwater flow paths but not altering the total magnitude of future groundwater discharge outside of the bounds of hydrologic parameter uncertainties. These findings suggest that frozen soil routines play an important role for predicting the future location of groundwater discharge in watersheds underlain by seasonally frozen ground.

The role of frozen soil in groundwater discharge predictions for warming alpine watersheds

USGS Publications Warehouse

Evans, Sarah G.; Ge, Shemin; Voss, Clifford I.; Molotch, Noah P.

2018-01-01

Climate warming may alter the quantity and timing of groundwater discharge to streams in high alpine watersheds due to changes in the timing of the duration of seasonal freezing in the subsurface and snowmelt recharge. It is imperative to understand the effects of seasonal freezing and recharge on groundwater discharge to streams in warming alpine watersheds as streamflow originating from these watersheds is a critical water resource for downstream users. This study evaluates how climate warming may alter groundwater discharge due to changes in seasonally frozen ground and snowmelt using a 2‐D coupled flow and heat transport model with freeze and thaw capabilities for variably saturated media. The model is applied to a representative snowmelt‐dominated watershed in the Rocky Mountains of central Colorado, USA, with snowmelt time series reconstructed from a 12 year data set of hydrometeorological records and satellite‐derived snow covered area. Model analyses indicate that the duration of seasonal freezing in the subsurface controls groundwater discharge to streams, while snowmelt timing controls groundwater discharge to hillslope faces. Climate warming causes changes to subsurface ice content and duration, rerouting groundwater flow paths but not altering the total magnitude of future groundwater discharge outside of the bounds of hydrologic parameter uncertainties. These findings suggest that frozen soil routines play an important role for predicting the future location of groundwater discharge in watersheds underlain by seasonally frozen ground.

Modeling stream fish distributions using interval-censored detection times.

PubMed

Ferreira, Mário; Filipe, Ana Filipa; Bardos, David C; Magalhães, Maria Filomena; Beja, Pedro

2016-08-01

Controlling for imperfect detection is important for developing species distribution models (SDMs). Occupancy-detection models based on the time needed to detect a species can be used to address this problem, but this is hindered when times to detection are not known precisely. Here, we extend the time-to-detection model to deal with detections recorded in time intervals and illustrate the method using a case study on stream fish distribution modeling. We collected electrofishing samples of six fish species across a Mediterranean watershed in Northeast Portugal. Based on a Bayesian hierarchical framework, we modeled the probability of water presence in stream channels, and the probability of species occupancy conditional on water presence, in relation to environmental and spatial variables. We also modeled time-to-first detection conditional on occupancy in relation to local factors, using modified interval-censored exponential survival models. Posterior distributions of occupancy probabilities derived from the models were used to produce species distribution maps. Simulations indicated that the modified time-to-detection model provided unbiased parameter estimates despite interval-censoring. There was a tendency for spatial variation in detection rates to be primarily influenced by depth and, to a lesser extent, stream width. Species occupancies were consistently affected by stream order, elevation, and annual precipitation. Bayesian P-values and AUCs indicated that all models had adequate fit and high discrimination ability, respectively. Mapping of predicted occupancy probabilities showed widespread distribution by most species, but uncertainty was generally higher in tributaries and upper reaches. The interval-censored time-to-detection model provides a practical solution to model occupancy-detection when detections are recorded in time intervals. This modeling framework is useful for developing SDMs while controlling for variation in detection rates, as it uses simple data that can be readily collected by field ecologists.

An Integrated Watershed and Receiving Water Model for Fecal Coliform Fate and Transport in Sinclair and Dyes Inlets, Puget Sound, WA

DTIC Science & Technology

2009-12-01

xix USLE Universal Soil Loss Equation UV Ultraviolet UZSN Upper Zone Nominal Storage WA-DOE Washington State Department of Ecology WA-DOH...Effective Impervious Area IMPLND Impervious Land Cover INFILT Interflow Inflow Parameter (related to infiltration capacity of the soil ) INSUR...within Watershed (#/Km) SCCWRP Southern California Coastal Water Research Project SCS Soil Conservation Service SGA Shellfish Growing Area SPAWAR

Combining binary decision tree and geostatistical methods to estimate snow distribution in a mountain watershed

USGS Publications Warehouse

Balk, Benjamin; Elder, Kelly

2000-01-01

We model the spatial distribution of snow across a mountain basin using an approach that combines binary decision tree and geostatistical techniques. In April 1997 and 1998, intensive snow surveys were conducted in the 6.9‐km2 Loch Vale watershed (LVWS), Rocky Mountain National Park, Colorado. Binary decision trees were used to model the large‐scale variations in snow depth, while the small‐scale variations were modeled through kriging interpolation methods. Binary decision trees related depth to the physically based independent variables of net solar radiation, elevation, slope, and vegetation cover type. These decision tree models explained 54–65% of the observed variance in the depth measurements. The tree‐based modeled depths were then subtracted from the measured depths, and the resulting residuals were spatially distributed across LVWS through kriging techniques. The kriged estimates of the residuals were added to the tree‐based modeled depths to produce a combined depth model. The combined depth estimates explained 60–85% of the variance in the measured depths. Snow densities were mapped across LVWS using regression analysis. Snow‐covered area was determined from high‐resolution aerial photographs. Combining the modeled depths and densities with a snow cover map produced estimates of the spatial distribution of snow water equivalence (SWE). This modeling approach offers improvement over previous methods of estimating SWE distribution in mountain basins.

Watershed-scale response to climate change through the twenty-first century for selected basins across the United States

USGS Publications Warehouse

Hay, Lauren E.; Markstrom, Steven; Ward-Garrison, Christian D.

2011-01-01

The hydrologic response of different climate-change emission scenarios for the twenty-first century were evaluated in 14 basins from different hydroclimatic regions across the United States using the Precipitation-Runoff Modeling System (PRMS), a process-based, distributed-parameter watershed model. This study involves four major steps: 1) setup and calibration of the PRMS model in 14 basins across the United States by local U.S. Geological Survey personnel; 2) statistical downscaling of the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3 climate-change emission scenarios to create PRMS input files that reflect these emission scenarios; 3) run PRMS for the climate-change emission scenarios for the 14 basins; and 4) evaluation of the PRMS output.This paper presents an overview of this project, 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 very different, depending on the dominant physical processes of that particular region. Also considered is the tremendous amount of uncertainty present in the climate emission scenarios and how this uncertainty propagates through the hydrologic simulations. This paper concludes with a discussion of the lessons learned and potential for future work.

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

DOE PAGES

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

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

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

Improved daily precipitation nitrate and ammonium concentration models for the Chesapeake Bay Watershed.

PubMed

Grimm, J W; Lynch, J A

2005-06-01

Daily precipitation nitrate and ammonium concentration models were developed for the Chesapeake Bay Watershed (USA) using a linear least-squares regression approach and precipitation chemistry data from 29 National Atmospheric Deposition Program/National Trends Network (NADP/NTN) sites. Only weekly samples that comprised a single precipitation event were used in model development. The most significant variables in both ammonium and nitrate models included: precipitation volume, the number of days since the last event, a measure of seasonality, latitude, and the proportion of land within 8km covered by forest or devoted to industry and transportation. Additional variables included in the nitrate model were the proportion of land within 0.8km covered by water and/or forest. Local and regional ammonia and nitrogen oxide emissions were not as well correlated as land cover. Modeled concentrations compared very well with event chemistry data collected at six NADP/AirMoN sites within the Chesapeake Bay Watershed. Wet deposition estimates were also consistent with observed deposition at selected sites. Accurately describing the spatial distribution of precipitation volume throughout the watershed is important in providing critical estimates of wet-fall deposition of ammonium and nitrate.

Water quality assessment and meta model development in Melen watershed - Turkey.

PubMed

Erturk, Ali; Gurel, Melike; Ekdal, Alpaslan; Tavsan, Cigdem; Ugurluoglu, Aysegul; Seker, Dursun Zafer; Tanik, Aysegul; Ozturk, Izzet

2010-07-01

Istanbul, being one of the highly populated metropolitan areas of the world, has been facing water scarcity since the past decade. Water transfer from Melen Watershed was considered as the most feasible option to supply water to Istanbul due to its high water potential and relatively less degraded water quality. This study consists of two parts. In the first part, water quality data covering 26 parameters from 5 monitoring stations were analyzed and assessed due to the requirements of the "Quality Required of Surface Water Intended for the Abstraction of Drinking Water" regulation. In the second part, a one-dimensional stream water quality model with simple water quality kinetics was developed. It formed a basic design for more advanced water quality models for the watershed. The reason for assessing the water quality data and developing a model was to provide information for decision making on preliminary actions to prevent any further deterioration of existing water quality. According to the water quality assessment at the water abstraction point, Melen River has relatively poor water quality with regard to NH(4)(+), BOD(5), faecal streptococcus, manganese and phenol parameters, and is unsuitable for drinking water abstraction in terms of COD, PO(4)(3-), total coliform, total suspended solids, mercury and total chromium parameters. The results derived from the model were found to be consistent with the water quality assessment. It also showed that relatively high inorganic nitrogen and phosphorus concentrations along the streams are related to diffuse nutrient loads that should be managed together with municipal and industrial wastewaters. Copyright 2010 Elsevier Ltd. All rights reserved.

Development of a Model of Nitrogen Cycling in Stormwater Control Measures and Application of the Model at the Watershed Scale

NASA Astrophysics Data System (ADS)

Bell, C.; Tague, C.; McMillan, S. K.

2016-12-01

Stormwater control measures (SCMs) create ecosystems in urban watersheds that store water and promote nitrogen (N) retention and removal. This work used computer modeling at two spatial scales (the individual SCM and watershed scale) to quantify how SCMs affect runoff and nitrogen export in urban watersheds. First, routines that simulate the dynamic hydrologic and water quality processes of an individual wet pond SCM were developed and applied to quantify N processing under different environmental and design scenarios. Results showed that deeper SCMs have greater inorganic N removal efficiencies because they have more stored volume of relatively N-deplete water, and therefore have a greater capacity to dilute relatively N-rich inflow. N removal by the SCM was more sensitive to this design parameter than it was to variations in air temperature, inflow N concentrations, and inflow volume. Next, these SCM model routines were used to simulate processes of a suburban watershed in Charlotte, NC with 16 SCMs. The watershed configuration was varied to simulate runoff under different scenarios of impervious surface connectivity to SCMs with the goal of developing a simple predictive relationship between watershed condition and N loads. We used unmitigated imperviousness (UI), percent of the impervious area that is unmitigated by SCMs, to quantify watershed condition. Results showed that as SCM mitigation decreased, or as UI increased from 3% to 15%, runoff ratios and loads of nitrite and total dissolved N increased by 26% (21-32%), 14% (3-26%) and 13% (2-25%), respectively. The shape of the relationship between these response variables and UI was linear, which indicates that mitigation of any impervious surfaces will result in proportional reductions. However, the range of UI included in this study is on the low end of urban watersheds and future work will assess the behavior of this relationship at higher TI and UI levels.

A simple temperature-based method to estimate heterogeneous frozen ground within a distributed watershed model

NASA Astrophysics Data System (ADS)

Follum, Michael L.; Niemann, Jeffrey D.; Parno, Julie T.; Downer, Charles W.

2018-05-01

Frozen ground can be important to flood production and is often heterogeneous within a watershed due to spatial variations in the available energy, insulation by snowpack and ground cover, and the thermal and moisture properties of the soil. The widely used continuous frozen ground index (CFGI) model is a degree-day approach and identifies frozen ground using a simple frost index, which varies mainly with elevation through an elevation-temperature relationship. Similarly, snow depth and its insulating effect are also estimated based on elevation. The objective of this paper is to develop a model for frozen ground that (1) captures the spatial variations of frozen ground within a watershed, (2) allows the frozen ground model to be incorporated into a variety of watershed models, and (3) allows application in data sparse environments. To do this, we modify the existing CFGI method within the gridded surface subsurface hydrologic analysis watershed model. Among the modifications, the snowpack and frost indices are simulated by replacing air temperature (a surrogate for the available energy) with a radiation-derived temperature that aims to better represent spatial variations in available energy. Ground cover is also included as an additional insulator of the soil. Furthermore, the modified Berggren equation, which accounts for soil thermal conductivity and soil moisture, is used to convert the frost index into frost depth. The modified CFGI model is tested by application at six test sites within the Sleepers River experimental watershed in Vermont. Compared to the CFGI model, the modified CFGI model more accurately captures the variations in frozen ground between the sites, inter-annual variations in frozen ground depths at a given site, and the occurrence of frozen ground.

Effects of Subbasin Size on Topographic Characteristics and Simulated Flow Paths in Sleepers River Watershed, Vermont

NASA Astrophysics Data System (ADS)

Wolock, David M.

1995-08-01

The effects of subbasin size on topographic characteristics and simulated flow paths were determined for the 111.5-km2 Sleepers River Research Watershed in Vermont using the watershed model TOPMODEL. Topography is parameterized in TOPMODEL as the spatial and statistical distribution of the index ln (a/tan B), where In is the Napierian logarithm, a is the upslope area per unit contour length, and tan B is the slope gradient. The mean, variance, and skew of the ln (a/tan B) distribution were computed for several sets of nested subbasins (0.05 to 111.5 km2)) along streams in the watershed and used as input to TOPMODEL. In general, the statistics of the ln (a/tan B) distribution and the simulated percentage of overland flow in total streamflow increased rapidly for some nested subbasins and decreased rapidly for others as subbasin size increased from 0.05 to 1 km2, generally increased up to a subbasin size of 5 km2, and remained relatively constant at a subbasin size greater than 5 km2. Differences in simulated flow paths among subbasins of all sizes (0.05 to 111.5 km2) were caused by differences in the statistics of the ln (a/tan B) distribution, not by differences in the explicit spatial arrangement of ln (a/tan B) values within the subbasins. Analysis of streamflow chemistry data from the Neversink River watershed in southeastern New York supports the hypothesis that subbasin size affects flow-path characteristics.

Calibration of Watershed Lag Time Equation for Philippine Hydrology using RADARSAT Digital Elevation Models

NASA Astrophysics Data System (ADS)

Cipriano, F. R.; Lagmay, A. M. A.; Horritt, M.; Mendoza, J.; Sabio, G.; Punay, K. N.; Taniza, H. J.; Uichanco, C.

2015-12-01

Widespread flooding is a major problem in the Philippines. The country experiences heavy amount of rainfall throughout the year and several areas are prone to flood hazards because of its unique topography. Human casualties and destruction of infrastructure are just some of the damages caused by flooding and the Philippine government has undertaken various efforts to mitigate these hazards. One of the solutions was to create flood hazard maps of different floodplains and use them to predict the possible catastrophic results of different rain scenarios. To produce these maps with accurate output, different input parameters were needed and one of those is calculating hydrological components from topographical data. This paper presents how a calibrated lag time (TL) equation was obtained using measurable catchment parameters. Lag time is an essential input in flood mapping and is defined as the duration between the peak rainfall and peak discharge of the watershed. The lag time equation involves three measurable parameters, namely, watershed length (L), maximum potential retention (S) derived from the curve number, and watershed slope (Y), all of which were available from RADARSAT Digital Elevation Models (DEM). This approach was based on a similar method developed by CH2M Hill and Horritt for Taiwan, which has a similar set of meteorological and hydrological parameters with the Philippines. Rainfall data from fourteen water level sensors covering 67 storms from all the regions in the country were used to estimate the actual lag time. These sensors were chosen by using a screening process that considers the distance of the sensors from the sea, the availability of recorded data, and the catchment size. The actual lag time values were plotted against the values obtained from the Natural Resource Conservation Management handbook lag time equation. Regression analysis was used to obtain the final calibrated equation that would be used to calculate the lag time specifically for rivers in the Philippine setting. The calculated lag time values could then be used as a parameter for modeling different flood scenarios in the country.

Application of Coupled Human-Natural Systems Model for Assessing Trade-Offs Between Watershed Ecosystem Services in Veracruz, Mexico

NASA Astrophysics Data System (ADS)

Mayer, A. S.; Jones, K.; Berry, Z. C.; Congalton, R.; Kolka, R. K.; López-Ramírez, S.; Manson, R.; Muñoz Villers, L.; Saenz, L.; Salcone, J.; Von Thaden Ugalde, J.; Asbjornsen, H.

2016-12-01

Trade-offs between ecosystem services (ES) occur due to management choices that impact the type, magnitude, and relative mix of services provided by ecosystems. Trade-offs arise when the provision of one ES is reduced as a consequence of increased use of another ES. Here, we assess ES tradeoffs with a coupled human-natural systems (CHNS) model, in response to payments for watershed services (PWS) programs in two watersheds in Veracruz, Mexico. An econometric component of the CHNS model is used to determine the effect of the PWS programs on a given land use-land cover (LULC). Eight LULC categories, corresponding to 95% of the watershed area, are used to force LULC feedbacks within the CHNS model. The LULC can transition from the present category to another, given the outcome of landowner participation in the PWS programs. Biophysical sub-models of watershed discharge and water quality, carbon storage, and biodiversity conservation are used to estimate values of ES indicators at the watershed scale. These biophysical models are derived from qualitative and quantitative observations in the study watersheds. Using these models, we gain first-approximation insights into ES tradeoffs and the sensitivity of estimated tradeoffs to model structure—serving as a critical platform for informing hypotheses about PWS program design and ES tradeoffs. With a CHNS model in place, and data collected collected from our field experiments, we explore first, baseline implications for ES of existing PWS programs in Xalapa, Veracruz; and second, we develop scenarios of potential PWS program pathways, with or without climate change projection forcings in order to improve our understanding of changes in ES distribution, magnitude and biophysical tradeoffs. Finally, the econometric component is parameterized with economic variables and indicators identified with local stakeholders in order to asses economic implications of ES tradeoffs. Outputs from the model provide important information to the local and national agencies involved in PWS program design in the study watersheds. This first tier model will be used to inform development of a more integrated process-based model using primary watershed socioeconomic and ecohydrological data, as well as household level data on participation in the PWS programs and spillover effects of PWS.

Evaluation of a spatially-distributed Thornthwaite water-balance model

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

Lough, J.A.

1993-03-01

A small watershed of low relief in coastal New Hampshire was divided into hydrologic sub-areas in a geographic information system on the basis of soils, sub-basins and remotely-sensed landcover. Three variables were spatially modeled for input to 49 individual water-balances: available water content of the root zone, water input and potential evapotranspiration (PET). The individual balances were weight-summed to generate the aggregate watershed-balance, which saw 9% (48--50 mm) less annual actual-evapotranspiration (AET) compared to a lumped approach. Analysis of streamflow coefficients suggests that the spatially-distributed approach is more representative of the basin dynamics. Variation of PET by landcover accounted formore » the majority of the 9% AET reduction. Variation of soils played a near-negligible role. As a consequence of the above points, estimates of landcover proportions and annual PET by landcover are sufficient to correct a lumped water-balance in the Northeast. If remote sensing is used to estimate the landcover area, a sensor with a high spatial resolution is required. Finally, while the lower Thornthwaite model has conceptual limitations for distributed application, the upper Thornthwaite model is highly adaptable to distributed problems and may prove useful in many earth-system models.« less

Estimates of long-term mean-annual nutrient loads considered for use in SPARROW models of the Midcontinental region of Canada and the United States, 2002 base year

USGS Publications Warehouse

Saad, David A.; Benoy, Glenn A.; Robertson, Dale M.

2018-05-11

Streamflow and nutrient concentration data needed to compute nitrogen and phosphorus loads were compiled from Federal, State, Provincial, and local agency databases and also from selected university databases. The nitrogen and phosphorus loads are necessary inputs to Spatially Referenced Regressions on Watershed Attributes (SPARROW) models. SPARROW models are a way to estimate the distribution, sources, and transport of nutrients in streams throughout the Midcontinental region of Canada and the United States. After screening the data, approximately 1,500 sites sampled by 34 agencies were identified as having suitable data for calculating the long-term mean-annual nutrient loads required for SPARROW model calibration. These final sites represent a wide range in watershed sizes, types of nutrient sources, and land-use and watershed characteristics in the Midcontinental region of Canada and the United States.

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.

Hydrologic Model Development and Calibration: Contrasting a Single- and Multi-Objective Approach for Comparing Model Performance

NASA Astrophysics Data System (ADS)

Asadzadeh, M.; Maclean, A.; Tolson, B. A.; Burn, D. H.

2009-05-01

Hydrologic model calibration aims to find a set of parameters that adequately simulates observations of watershed behavior, such as streamflow, or a state variable, such as snow water equivalent (SWE). There are different metrics for evaluating calibration effectiveness that involve quantifying prediction errors, such as the Nash-Sutcliffe (NS) coefficient and bias evaluated for the entire calibration period, on a seasonal basis, for low flows, or for high flows. Many of these metrics are conflicting such that the set of parameters that maximizes the high flow NS differs from the set of parameters that maximizes the low flow NS. Conflicting objectives are very likely when different calibration objectives are based on different fluxes and/or state variables (e.g., NS based on streamflow versus SWE). One of the most popular ways to balance different metrics is to aggregate them based on their importance and find the set of parameters that optimizes a weighted sum of the efficiency metrics. Comparing alternative hydrologic models (e.g., assessing model improvement when a process or more detail is added to the model) based on the aggregated objective might be misleading since it represents one point on the tradeoff of desired error metrics. To derive a more comprehensive model comparison, we solved a bi-objective calibration problem to estimate the tradeoff between two error metrics for each model. Although this approach is computationally more expensive than the aggregation approach, it results in a better understanding of the effectiveness of selected models at each level of every error metric and therefore provides a better rationale for judging relative model quality. The two alternative models used in this study are two MESH hydrologic models (version 1.2) of the Wolf Creek Research basin that differ in their watershed spatial discretization (a single Grouped Response Unit, GRU, versus multiple GRUs). The MESH model, currently under development by Environment Canada, is a coupled land-surface and hydrologic model. Results will demonstrate the conclusions a modeller might make regarding the value of additional watershed spatial discretization under both an aggregated (single-objective) and multi-objective model comparison framework.

SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds. The two-CN system approach

NASA Astrophysics Data System (ADS)

Soulis, K. X.; Valiantzas, J. D.

2011-10-01

The Soil Conservation Service Curve Number (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN values can be estimated by being selected from tables. However, it is more accurate to estimate the CN value from measured rainfall-runoff data (assumed available) in a watershed. Previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. They suggested the determination of a single asymptotic CN value observed for very high rainfall depths to characterize the watersheds' runoff response. In this paper, the novel hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of the inevitable presence of soil-cover complex spatial variability along watersheds is being tested. Based on this hypothesis, the simplified concept of a two-CN heterogeneous system is introduced to model the observed CN-rainfall variation by reducing the CN spatial variability into two classes. The behavior of the CN-rainfall function produced by the proposed two-CN system concept is approached theoretically, it is analyzed systematically, and it is found to be similar to the variation observed in natural watersheds. Synthetic data tests, natural watersheds examples, and detailed study of two natural experimental watersheds with known spatial heterogeneity characteristics were used to evaluate the method. The results indicate that the determination of CN values from rainfall runoff data using the proposed two-CN system approach provides reasonable accuracy and it over performs the previous original method based on the determination of a single asymptotic CN value. Although the suggested method increases the number of unknown parameters to three (instead of one), a clear physical reasoning for them is presented.

A Hydrological Modeling Framework for Flood Risk Assessment for Japan

NASA Astrophysics Data System (ADS)

Ashouri, H.; Chinnayakanahalli, K.; Chowdhary, H.; Sen Gupta, A.

2016-12-01

Flooding has been the most frequent natural disaster that claims lives and imposes significant economic losses to human societies worldwide. Japan, with an annual rainfall of up to approximately 4000 mm is extremely vulnerable to flooding. The focus of this research is to develop a macroscale hydrologic model for simulating flooding toward an improved understanding and assessment of flood risk across Japan. The framework employs a conceptual hydrological model, known as the Probability Distributed Model (PDM), as well as the Muskingum-Cunge flood routing procedure for simulating streamflow. In addition, a Temperature-Index model is incorporated to account for snowmelt and its contribution to streamflow. For an efficient calibration of the model, in terms of computational timing and convergence of the parameters, a set of A Priori parameters is obtained based on the relationships between the model parameters and the physical properties of watersheds. In this regard, we have implemented a particle tracking algorithm and a statistical model which use high resolution Digital Terrain Models to estimate different time related parameters of the model such as time to peak of the unit hydrograph. In addition, global soil moisture and depth data are used to generate A Priori estimation of maximum soil moisture capacity, an important parameter of the PDM model. Once the model is calibrated, its performance is examined during the Typhoon Nabi which struck Japan in September 2005 and caused severe flooding throughout the country. The model is also validated for the extreme precipitation event in 2012 which affected Kyushu. In both cases, quantitative measures show that simulated streamflow depicts good agreement with gauge-based observations. The model is employed to simulate thousands of possible flood events for the entire Japan which makes a basis for a comprehensive flood risk assessment and loss estimation for the flood insurance industry.

A Stochastic Multi-Media Model of Microbial Transport in Watersheds

NASA Astrophysics Data System (ADS)

Yeghiazarian, L.; Safwat, A.; Whiteaker, T.; Teklitz, A.; Nietch, C.; Maidment, D. R.; Best, E. P.

2012-12-01

Fecal contamination is the leading cause of surface-water impairment in the US, and fecal pathogens are capable of triggering massive outbreaks of gastrointestinal disease. The difficulty in prediction of water contamination has its roots in the stochastic variability of fecal pathogens in the environment, and in the complexity of microbial dynamics and interactions on the soil surface and in water. To address these challenges, we have developed a stochastic model whereby the transport of microorganisms in watersheds is considered in two broad categories: microorganisms that are attached to mineral or organic substrates in suspended sediment; and unattached microorganisms suspended in overland flow. The interactions of microorganisms with soil particles on the soil surface and in the overland flow lead to transitions of microorganisms between solid and aqueous media. The strength of attachment of microorganisms to soil particles is determined by the chemical characteristics of soils which are highly correlated with the particle size. The particle size class distribution in the suspended sediment is predicted by the Water Erosion Prediction Project (WEPP). The model is integrated with ArcGIS, resulting in a general transport-modeling framework applicable to a variety of biological and chemical surface water contaminants. Simulations are carried out for a case study of contaminant transport in the East Fork Little Miami River Watershed in Ohio. Model results include the spatial probability distribution of microbes in the watershed and can be used for assessment of (1) mechanisms dominating microbial transport, and (2) time and location of highest likelihood of microbial occurrence, thus yielding information on best water sampling strategies.

Beyond the SCS-CN method: A theoretical framework for spatially lumped rainfall-runoff response

NASA Astrophysics Data System (ADS)

Bartlett, M. S.; Parolari, A. J.; McDonnell, J. J.; Porporato, A.

2016-06-01

Since its introduction in 1954, the Soil Conservation Service curve number (SCS-CN) method has become the standard tool, in practice, for estimating an event-based rainfall-runoff response. However, because of its empirical origins, the SCS-CN method is restricted to certain geographic regions and land use types. Moreover, it does not describe the spatial variability of runoff. To move beyond these limitations, we present a new theoretical framework for spatially lumped, event-based rainfall-runoff modeling. In this framework, we describe the spatially lumped runoff model as a point description of runoff that is upscaled to a watershed area based on probability distributions that are representative of watershed heterogeneities. The framework accommodates different runoff concepts and distributions of heterogeneities, and in doing so, it provides an implicit spatial description of runoff variability. Heterogeneity in storage capacity and soil moisture are the basis for upscaling a point runoff response and linking ecohydrological processes to runoff modeling. For the framework, we consider two different runoff responses for fractions of the watershed area: "prethreshold" and "threshold-excess" runoff. These occur before and after infiltration exceeds a storage capacity threshold. Our application of the framework results in a new model (called SCS-CNx) that extends the SCS-CN method with the prethreshold and threshold-excess runoff mechanisms and an implicit spatial description of runoff. We show proof of concept in four forested watersheds and further that the resulting model may better represent geographic regions and site types that previously have been beyond the scope of the traditional SCS-CN method.

Stream chemistry responses to four range management strategies in eastern Oregon.

Treesearch

A.R. Tiedemann; D.A. Higgins; T.M. Quigley; H.R. Sanderson

1989-01-01

Responses of stream chemistry parameters, nitrate-N (NO3-N), phosphate (PO4), calcium (Ca), magnesium (Mg), potassium (K), sodium (Na), and hydrogen ion activity (pH) were measured on 13 wildland watersheds managed at four different grazing strategies. Range management strategies tested were (A) no grazing, (B) grazing without control of livestock distribution (8.2 ha/...

An experimental investigation to characterise soil macroporosity under different land use and land covers of northeast India

NASA Astrophysics Data System (ADS)

Shougrakpam, Sangeeta; Sarkar, Rupak; Dutta, Subashisa

2010-10-01

Saturated macropore flow is the dominant hydrological process in tropical and subtropical hilly watersheds of northeast India. The process of infiltration into saturated macroporous soils is primarily controlled by size, network, density, connectivity, saturation of surrounding soil matrix, and depthwise distribution of macropores. To understand the effects of local land use, land cover and management practices on soil macroporosity, colour dye infiltration experiments were conducted with ten soil columns (25 × 25 × 50 cm) collected from different watersheds of the region under similar soil and agro-climatic zones. The sampling sites included two undisturbed forested hillslopes, two conventionally cultivated paddy fields, two forest lands abandoned after Jhum cultivation, and two paddy fields, one pineapple plot and one banana plot presently under active cultivation stage of the Jhum cycle. Digital image analyses of the obtained dye patterns showed that the infiltration patterns differed significantly for different sites with varying land use, land cover, and cultivation practices. Undisturbed forest soils showed high degree of soil macroporosity throughout the soil profile, paddy fields revealed sealing of macropores at the topsoil due to hard pan formation, and Jhum cultivated plots showed disconnected subsoil macropores. The important parameters related to soil macropores such as maximum and average size of macropores, number of active macropores, and depthwise distribution of macropores were estimated to characterise the soil macroporosity for the sites. These experimentally derived quantitative data of soil macroporosity can have wide range of applications in the region such as water quality monitoring and groundwater pollution assessment due to preferential leaching of solutes and pesticides, study of soil structural properties and infiltration behaviour of soils, investigation of flash floods in rivers, and hydrological modelling of the watersheds.

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.

Modeling uncertainty and correlation in soil properties using Restricted Pairing and implications for ensemble-based hillslope-scale soil moisture and temperature estimation

NASA Astrophysics Data System (ADS)

Flores, A. N.; Entekhabi, D.; Bras, R. L.

2007-12-01

Soil hydraulic and thermal properties (SHTPs) affect both the rate of moisture redistribution in the soil column and the volumetric soil water capacity. Adequately constraining these properties through field and lab analysis to parameterize spatially-distributed hydrology models is often prohibitively expensive. Because SHTPs vary significantly at small spatial scales individual soil samples are also only reliably indicative of local conditions, and these properties remain a significant source of uncertainty in soil moisture and temperature estimation. In ensemble-based soil moisture data assimilation, uncertainty in the model-produced prior estimate due to associated uncertainty in SHTPs must be taken into account to avoid under-dispersive ensembles. To treat SHTP uncertainty for purposes of supplying inputs to a distributed watershed model we use the restricted pairing (RP) algorithm, an extension of Latin Hypercube (LH) sampling. The RP algorithm generates an arbitrary number of SHTP combinations by sampling the appropriate marginal distributions of the individual soil properties using the LH approach, while imposing a target rank correlation among the properties. A previously-published meta- database of 1309 soils representing 12 textural classes is used to fit appropriate marginal distributions to the properties and compute the target rank correlation structure, conditioned on soil texture. Given categorical soil textures, our implementation of the RP algorithm generates an arbitrarily-sized ensemble of realizations of the SHTPs required as input to the TIN-based Realtime Integrated Basin Simulator with vegetation dynamics (tRIBS+VEGGIE) distributed parameter ecohydrology model. Soil moisture ensembles simulated with RP- generated SHTPs exhibit less variance than ensembles simulated with SHTPs generated by a scheme that neglects correlation among properties. Neglecting correlation among SHTPs can lead to physically unrealistic combinations of parameters that exhibit implausible hydrologic behavior when input to the tRIBS+VEGGIE model.

Spatial characterization of riparian buffer effects on sediment loads from watershed systems.

PubMed

Momm, Henrique G; Bingner, Ronald L; Yuan, Yongping; Locke, Martin A; Wells, Robert R

2014-09-01

Understanding all watershed systems and their interactions is a complex, but critical, undertaking when developing practices designed to reduce topsoil loss and chemical/nutrient transport from agricultural fields. The presence of riparian buffer vegetation in agricultural landscapes can modify the characteristics of overland flow, promoting sediment deposition and nutrient filtering. Watershed simulation tools, such as the USDA-Annualized Agricultural Non-Point Source (AnnAGNPS) pollution model, typically require detailed information for each riparian buffer zone throughout the watershed describing the location, width, vegetation type, topography, and possible presence of concentrated flow paths through the riparian buffer zone. Research was conducted to develop GIS-based technology designed to spatially characterize riparian buffers and to estimate buffer efficiency in reducing sediment loads in a semiautomated fashion at watershed scale. The methodology combines modeling technology at different scales, at individual concentrated flow paths passing through the riparian zone, and at watershed scales. At the concentrated flow path scale, vegetative filter strip models are applied to estimate the sediment-trapping efficiency for each individual flow path, which are aggregated based on the watershed subdivision and used in the determination of the overall impact of the riparian vegetation at the watershed scale. This GIS-based technology is combined with AnnAGNPS to demonstrate the effect of riparian vegetation on sediment loadings from sheet and rill and ephemeral gully sources. The effects of variability in basic input parameters used to characterize riparian buffers, onto generated outputs at field scale (sediment trapping efficiency) and at watershed scale (sediment loadings from different sources) were evaluated and quantified. The AnnAGNPS riparian buffer component represents an important step in understanding and accounting for the effect of riparian vegetation, existing and/or managed, in reducing sediment loads at the watershed scale. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

SIMULATING SUB-DECADAL CHANNEL MORPHOLOGIC CHANGE IN EPHEMERAL STREAM NETWORKS

EPA Science Inventory

A distributed watershed model was modified to simulate cumulative channel morphologic
change from multiple runoff events in ephemeral stream networks. The model incorporates the general design of the event-based Kinematic Runoff and" Erosion Model (KINEROS), which describes t...

Simulating climate change impact on soil erosion using RUSLE model - A case study in a watershed of mid-Himalayan landscape

NASA Astrophysics Data System (ADS)

Gupta, Surya; Kumar, Suresh

2017-06-01

Climate change, particularly due to the changed precipitation trend, can have a severe impact on soil erosion. The effect is more pronounced on the higher slopes of the Himalayan region. The goal of this study was to estimate the impact of climate change on soil erosion in a watershed of the Himalayan region using RUSLE model. The GCM (general circulation model) derived emission scenarios (HadCM3 A2a and B2a SRES) were used for climate projection. The statistical downscaling model (SDSM) was used to downscale the precipitation for three future periods, 2011-2040, 2041-2070, and 2071-2099, at large scale. Rainfall erosivity ( R) was calculated for future periods using the SDSM downscaled precipitation data. ASTER digital elevation model (DEM) and Indian Remote Sensing data - IRS LISS IV satellite data were used to generate the spatial input parameters required by RUSLE model. A digital soil-landscape map was prepared to generate spatially distributed soil erodibility ( K) factor map of the watershed. Topographic factors, slope length ( L) and steepness ( S) were derived from DEM. Normalised difference vegetation index (NDVI) derived from the satellite data was used to represent spatial variation vegetation density and condition under various land use/land cover. This variation was used to represent spatial vegetation cover factor. Analysis revealed that the average annual soil loss may increase by 28.38, 25.64 and 20.33% in the 2020s, 2050s and 2080s, respectively under A2 scenario, while under B2 scenario, it may increase by 27.06, 25.31 and 23.38% in the 2020s, 2050s and 2080s, respectively, from the base period (1985-2013). The study provides a comprehensive understanding of the possible future scenario of soil erosion in the mid-Himalaya for scientists and policy makers.

Assessing the spatial and temporal variations of water quality in lowland areas, Northern Germany

NASA Astrophysics Data System (ADS)

Lam, Q. D.; Schmalz, B.; Fohrer, N.

2012-05-01

SummaryThe pollution of rivers and streams with agro-chemical contaminants has become one of the most crucial environmental problems in the world. The assessment of spatial and temporal variations of water quality influenced by point and diffuse source pollution is necessary to manage the environment sustainably in various watershed scales. The overall objectives of this study were to assess the transferability of parameter sets between lowland catchments on different scales using the ecohydrological model SWAT (Soil and Water Assessment Tool) and to evaluate the temporal and spatial patterns of water quality in the whole catchments before and after implementation of best management practices (BMPs). The study area Kielstau catchment is located in Northern Germany as typical example of lowland - flood plain landscape. Sandy, loamy and peat soils are characteristic for this area. Land use is dominated by arable land and pasture. In this study we examined two catchment areas including Kielstau catchment 50 km2 and its subcatchment, namely Moorau, with the area of 7.6 km2. The water quality of these catchments is not only influenced by diffuse sources from agricultural areas but also by point sources from municipal wastewater treatment plants (WWTPs). Diffuse sources as well as punctual entries from the WWTPs are considered in the model set-up. For this study, the calibration and validation of the model were carried out in a daily time step for flow and nutrients. The results indicate that the parameter sets could be transferred in lowland catchments with similar environmental conditions. Shallow groundwater is the major contributor to total nitrate load in the stream accounting for about 93% of the total nitrate load, while only about 7% originates in surface runoff and lateral flow. The study also indicates that applying a spatially distributed modeling approach was an appropriate method to generate source maps showing the spatial distribution of TN load from hydrologic response units (HRUs) as well as from subbasins and to identify the crucial pollution areas within a watershed whose management practices can be improved to control more effectively nitrogen loading to water bodies.

Indirect estimation of the Convective Lognormal Transfer function model parameters for describing solute transport in unsaturated and undisturbed soil.

PubMed

Mohammadi, Mohammad Hossein; Vanclooster, Marnik

2012-05-01

Solute transport in partially saturated soils is largely affected by fluid velocity distribution and pore size distribution within the solute transport domain. Hence, it is possible to describe the solute transport process in terms of the pore size distribution of the soil, and indirectly in terms of the soil hydraulic properties. In this paper, we present a conceptual approach that allows predicting the parameters of the Convective Lognormal Transfer model from knowledge of soil moisture and the Soil Moisture Characteristic (SMC), parameterized by means of the closed-form model of Kosugi (1996). It is assumed that in partially saturated conditions, the air filled pore volume act as an inert solid phase, allowing the use of the Arya et al. (1999) pragmatic approach to estimate solute travel time statistics from the saturation degree and SMC parameters. The approach is evaluated using a set of partially saturated transport experiments as presented by Mohammadi and Vanclooster (2011). Experimental results showed that the mean solute travel time, μ(t), increases proportionally with the depth (travel distance) and decreases with flow rate. The variance of solute travel time σ²(t) first decreases with flow rate up to 0.4-0.6 Ks and subsequently increases. For all tested BTCs predicted solute transport with μ(t) estimated from the conceptual model performed much better as compared to predictions with μ(t) and σ²(t) estimated from calibration of solute transport at shallow soil depths. The use of μ(t) estimated from the conceptual model therefore increases the robustness of the CLT model in predicting solute transport in heterogeneous soils at larger depths. In view of the fact that reasonable indirect estimates of the SMC can be made from basic soil properties using pedotransfer functions, the presented approach may be useful for predicting solute transport at field or watershed scales. Copyright © 2012 Elsevier B.V. All rights reserved.

Indirect estimation of the Convective Lognormal Transfer function model parameters for describing solute transport in unsaturated and undisturbed soil

NASA Astrophysics Data System (ADS)

Mohammadi, Mohammad Hossein; Vanclooster, Marnik

2012-05-01

Solute transport in partially saturated soils is largely affected by fluid velocity distribution and pore size distribution within the solute transport domain. Hence, it is possible to describe the solute transport process in terms of the pore size distribution of the soil, and indirectly in terms of the soil hydraulic properties. In this paper, we present a conceptual approach that allows predicting the parameters of the Convective Lognormal Transfer model from knowledge of soil moisture and the Soil Moisture Characteristic (SMC), parameterized by means of the closed-form model of Kosugi (1996). It is assumed that in partially saturated conditions, the air filled pore volume act as an inert solid phase, allowing the use of the Arya et al. (1999) pragmatic approach to estimate solute travel time statistics from the saturation degree and SMC parameters. The approach is evaluated using a set of partially saturated transport experiments as presented by Mohammadi and Vanclooster (2011). Experimental results showed that the mean solute travel time, μt, increases proportionally with the depth (travel distance) and decreases with flow rate. The variance of solute travel time σ2t first decreases with flow rate up to 0.4-0.6 Ks and subsequently increases. For all tested BTCs predicted solute transport with μt estimated from the conceptual model performed much better as compared to predictions with μt and σ2t estimated from calibration of solute transport at shallow soil depths. The use of μt estimated from the conceptual model therefore increases the robustness of the CLT model in predicting solute transport in heterogeneous soils at larger depths. In view of the fact that reasonable indirect estimates of the SMC can be made from basic soil properties using pedotransfer functions, the presented approach may be useful for predicting solute transport at field or watershed scales.

Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales.

PubMed

Pratt, Bethany; Chang, Heejun

2012-03-30

The relationship among land cover, topography, built structure and stream water quality in the Portland Metro region of Oregon and Clark County, Washington areas, USA, is analyzed using ordinary least squares (OLS) and geographically weighted (GWR) multiple regression models. Two scales of analysis, a sectional watershed and a buffer, offered a local and a global investigation of the sources of stream pollutants. Model accuracy, measured by R(2) values, fluctuated according to the scale, season, and regression method used. While most wet season water quality parameters are associated with urban land covers, most dry season water quality parameters are related topographic features such as elevation and slope. GWR models, which take into consideration local relations of spatial autocorrelation, had stronger results than OLS regression models. In the multiple regression models, sectioned watershed results were consistently better than the sectioned buffer results, except for dry season pH and stream temperature parameters. This suggests that while riparian land cover does have an effect on water quality, a wider contributing area needs to be included in order to account for distant sources of pollutants. Copyright © 2012 Elsevier B.V. All rights reserved.

Theory, development, and applicability of the surface water hydrologic model CASC2D

NASA Astrophysics Data System (ADS)

Downer, Charles W.; Ogden, Fred L.; Martin, William D.; Harmon, Russell S.

2002-02-01

Numerical tests indicate that Hortonian runoff mechanisms benefit from scaling effects that non-Hortonian runoff mechanisms do not share. This potentially makes Hortonian watersheds more amenable to physically based modelling provided that the physically based model employed properly accounts for rainfall distribution and initial soil moisture conditions, to which these types of model are highly sensitive. The distributed Hortonian runoff model CASC2D has been developed and tested for the US Army over the past decade. The purpose of the model is to provide the Army with superior predictions of runoff and stream-flow compared with the standard lumped parameter model HEC-1. The model is also to be used to help minimize negative effects on the landscape caused by US armed forces training activities. Development of the CASC2D model is complete and the model has been tested and applied at several locations. These applications indicate that the model can realistically reproduce hydrographs when properly applied. These applications also indicate that there may be many situations where the model is inadequate. Because of this, the Army is pursuing development of a new model, GSSHA, that will provide improved numerical stability and incorporate additional stream-flow-producing mechanisms and improved hydraulics.

Potential Stream Density in Mid-Atlantic U.S. Watersheds

PubMed Central

Elmore, Andrew J.; Julian, Jason P.; Guinn, Steven M.; Fitzpatrick, Matthew C.

2013-01-01

Stream network density exerts a strong influence on ecohydrologic processes in watersheds, yet existing stream maps fail to capture most headwater streams and therefore underestimate stream density. Furthermore, discrepancies between mapped and actual stream length vary between watersheds, confounding efforts to understand the impacts of land use on stream ecosystems. Here we report on research that predicts stream presence from coupled field observations of headwater stream channels and terrain variables that were calculated both locally and as an average across the watershed upstream of any location on the landscape. Our approach used maximum entropy modeling (MaxEnt), a robust method commonly implemented to model species distributions that requires information only on the presence of the entity of interest. In validation, the method correctly predicts the presence of 86% of all 10-m stream segments and errors are low (<1%) for catchments larger than 10 ha. We apply this model to the entire Potomac River watershed (37,800 km2) and several adjacent watersheds to map stream density and compare our results with the National Hydrography Dataset (NHD). We find that NHD underestimates stream density by up to 250%, with errors being greatest in the densely urbanized cities of Washington, DC and Baltimore, MD and in regions where the NHD has never been updated from its original, coarse-grain mapping. This work is the most ambitious attempt yet to map stream networks over a large region and will have lasting implications for modeling and conservation efforts. PMID:24023704

Spatial distribution and source apportionment of water pollution in different administrative zones of Wen-Rui-Tang (WRT) river watershed, China.

PubMed

Yang, Liping; Mei, Kun; Liu, Xingmei; Wu, Laosheng; Zhang, Minghua; Xu, Jianming; Wang, Fan

2013-08-01

Water quality degradation in river systems has caused great concerns all over the world. Identifying the spatial distribution and sources of water pollutants is the very first step for efficient water quality management. A set of water samples collected bimonthly at 12 monitoring sites in 2009 and 2010 were analyzed to determine the spatial distribution of critical parameters and to apportion the sources of pollutants in Wen-Rui-Tang (WRT) river watershed, near the East China Sea. The 12 monitoring sites were divided into three administrative zones of urban, suburban, and rural zones considering differences in land use and population density. Multivariate statistical methods [one-way analysis of variance, principal component analysis (PCA), and absolute principal component score-multiple linear regression (APCS-MLR) methods] were used to investigate the spatial distribution of water quality and to apportion the pollution sources. Results showed that most water quality parameters had no significant difference between the urban and suburban zones, whereas these two zones showed worse water quality than the rural zone. Based on PCA and APCS-MLR analysis, urban domestic sewage and commercial/service pollution, suburban domestic sewage along with fluorine point source pollution, and agricultural nonpoint source pollution with rural domestic sewage pollution were identified to the main pollution sources in urban, suburban, and rural zones, respectively. Understanding the water pollution characteristics of different administrative zones could put insights into effective water management policy-making especially in the area across various administrative zones.

Controls on the variability of net infiltration to desert sandstone

USGS Publications Warehouse

Heilweil, Victor M.; McKinney, Tim S.; Zhdanov, Michael S.; Watt, Dennis E.

2007-01-01

As populations grow in arid climates and desert bedrock aquifers are increasingly targeted for future development, understanding and quantifying the spatial variability of net infiltration becomes critically important for accurately inventorying water resources and mapping contamination vulnerability. This paper presents a conceptual model of net infiltration to desert sandstone and then develops an empirical equation for its spatial quantification at the watershed scale using linear least squares inversion methods for evaluating controlling parameters (independent variables) based on estimated net infiltration rates (dependent variables). Net infiltration rates used for this regression analysis were calculated from environmental tracers in boreholes and more than 3000 linear meters of vadose zone excavations in an upland basin in southwestern Utah underlain by Navajo sandstone. Soil coarseness, distance to upgradient outcrop, and topographic slope were shown to be the primary physical parameters controlling the spatial variability of net infiltration. Although the method should be transferable to other desert sandstone settings for determining the relative spatial distribution of net infiltration, further study is needed to evaluate the effects of other potential parameters such as slope aspect, outcrop parameters, and climate on absolute net infiltration rates.

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds

PubMed Central

Vaughn, Nicholas R.; Asner, Gregory P.; Smit, Izak P. J.; Riddel, Edward S.

2015-01-01

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50–450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques. PMID:26660502

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds.

PubMed

Vaughn, Nicholas R; Asner, Gregory P; Smit, Izak P J; Riddel, Edward S

2015-01-01

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50-450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques.

Application of four watershed acidification models to Batchawana Watershed, Canada.

PubMed

Booty, W G; Bobba, A G; Lam, D C; Jeffries, D S

1992-01-01

Four watershed acidification models (TMWAM, ETD, ILWAS, and RAINS) are reviewed and a comparison of model performance is presented for a common watershed. The models have been used to simulate the dynamics of water quantity and quality at Batchawana Watershed, Canada, a sub-basin of the Turkey Lakes Watershed. The computed results are compared with observed data for a four-year period (Jan. 1981-Dec. 1984). The models exhibit a significant range in the ability to simulate the daily, monthly and seasonal changes present in the observed data. Monthly watershed outflows and lake chemistry predictions are compared to observed data. pH and ANC are the only two chemical parameters common to all four models. Coefficient of efficiency (E), linear (r) and rank (R) correlation coefficients, and regression slope (s) are used to compare the goodness of fit of the simulated with the observed data. The ILWAS, TMWAM and RAINS models performed very well in predicting the monthly flows, with values of r and R of approximately 0.98. The ETD model also showed strong correlations with linear (r) and rank (R) correlation coefficients of 0.896 and 0.892, respectively. The results of the analyses showed that TMWAM provided the best simulation of pH (E=0.264, r=0.648), which is slightly better than ETD (E=0.240, r=0.549), and much better than ILWAS (E=-2.965, r=0.293), and RAINS (E=-4.004, r=0.473). ETD was found to be superior in predicting ANC (E=0.608, r=0.781) as compared to TMWAM (E=0.340, r=0.598), ILWAS (E=0.275, r=0.442), and RAINS (E=-1.048, r=0.356). The TMWAM model adequately simulated SO4 over the four-year period (E=0.423, r=0.682) but the ETD (E=-0.904, r=0.274), ILWAS (E=-4.314, r=0.488), and RAINS (E=-6.479, r=0.126) models all performed poorer than the benchmark model (mean observed value).