Watershed Models (watershed + models)

Distribution by Scientific Domains

Selected Abstracts

A Semivirtual Watershed Model by Neural Networks

James C. Y. Guo
A semivirtual watershed model is presented in this study. This model places the design rainfall distribution on the input layer and the predicted runoff hydrograph on the output layer. The optimization scheme developed in this study can train the model to establish a set of weights under the guidance of the kinematic wave theory. The weights are time-dependent variables by which rainfall signals can be converted to runoff distributions by weighting procedures only. With the consideration of time dependence, the computational efficiency of virtual watershed models is greatly enhanced by eliminating unnecessary visitations between layers. The weighting procedure used in the semivirtual watershed model expands the rational method from peak runoff predictions to complete hydrograph predictions under continuous and nonuniform rainfall events. [source]

Impact of time-scale of the calibration objective function on the performance of watershed models

K. P. Sudheer
Abstract Many of the continuous watershed models perform all their computations on a daily time step, yet they are often calibrated at an annual or monthly time-scale that may not guarantee good simulation performance on a daily time step. The major objective of this paper is to evaluate the impact of the calibration time-scale on model predictive ability. This study considered the Soil and Water Assessment Tool for the analyses, and it has been calibrated at two time-scales, viz. monthly and daily for the War Eagle Creek watershed in the USA. The results demonstrate that the model's performance at the smaller time-scale (such as daily) cannot be ensured by calibrating them at a larger time-scale (such as monthly). It is observed that, even though the calibrated model possesses satisfactory ,goodness of fit' statistics, the simulation residuals failed to confirm the assumption of their homoscedasticity and independence. The results imply that evaluation of models should be conducted considering their behavior in various aspects of simulation, such as predictive uncertainty, hydrograph characteristics, ability to preserve statistical properties of the historic flow series, etc. The study enlightens the scope for improving/developing effective autocalibration procedures at the daily time step for watershed models. Copyright 2007 John Wiley & Sons, Ltd. [source]

Comparative assessment of two distributed watershed models with application to a small watershed

Latif Kalin
Abstract Distributed watershed models are beneficial tools for the assessment of management practices on runoff and water-induced erosion. This paper evaluates, by application to an experimental watershed, two promising distributed watershed-scale sediment models in detail: the Kinematic Runoff and Erosion (KINEROS-2) model and the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model. The physics behind each model are to some extent similar, though they have different watershed conceptualizations. KINEROS-2 was calibrated using three rainfall events and validated over four separate rainfall events. Parameters estimated by this calibration process were adapted to GSSHA. With these parameters, GSSHA generated larger and retarded flow hydrographs. A 30% reduction in both plane and channel roughness in GSSHA along with the assumption of Green-Ampt conductivity KG-A = Ks, where Ks is the saturated conductivity, resulted in almost identical hydrographs. Sediment parameters not common in both models were calibrated independently of KINEROS-2. A comparative discussion of simulation results is presented. Even though GSSHA's flow component slightly overperformed KINEROS-2, the latter outperformed GSSHA in simulations for sediment transport. In spite of the fact that KINEROS-2 is not geared toward continuous-time simulations, simulations performed with both models over a 1 month period generated comparable results. Copyright 2006 John Wiley & Sons, Ltd. [source]

The integration of ecological risk assessment and structured decision making into watershed management

Dan W Ohlson
Abstract Watershed management processes continue to call for more science and improved decision making that take into account the full range of stakeholder perspectives. Increasingly, the core principles of ecological risk assessment (i.e., the development and use of assessment endpoints and conceptual models, conducting exposure and effects analysis) are being incorporated and adapted in innovative ways to meet the call for more science. Similarly, innovative approaches to adapting decision analysis tools and methods for incorporating stakeholder concerns in complex natural resource management decisions are being increasingly applied. Here, we present an example of the integration of ecological risk assessment with decision analysis in the development of a watershed management plan for the Greater Vancouver Water District in British Columbia, Canada. Assessment endpoints were developed, ecological inventory data were collected, and watershed models were developed to characterize the existing and future condition of 3 watersheds in terms of the potential risks to water quality. Stressors to water quality include sedimentation processes (landslides, streambank erosion) and forest disturbance (wildfire, major insect or disease outbreak). Three landscape-level risk management alternatives were developed to reflect different degrees of management intervention. Each alternative was evaluated under different scenarios and analyzed by explicitly examining value-based trade-offs among water quality, environmental, financial, and social endpoints. The objective of this paper is to demonstrate how the integration of ecological risk assessment and decision analysis approaches can support decision makers in watershed management. [source]

Integrated Modular Modeling of Water and Nutrients From Point and Nonpoint Sources in the Patuxent River Watershed,

Zhi-Jun Liu
Abstract:, We present a simple modular landscape simulation model that is based on a watershed modeling framework in which different sets of processes occurring in a watershed can be simulated separately with different models. The model consists of three loosely coupled submodels: a rainfall-runoff model (TOPMODEL) for runoff generation in a subwatershed, a nutrient model for estimation of nutrients from nonpoint sources in a subwatershed, and a stream network model for integration of point and nonpoint sources in the routing process. The model performance was evaluated using monitoring data in the watershed of the Patuxent River, a tributary to the Chesapeake Bay in Maryland, from July 1997 through August 1999. Despite its simplicity, the landscape model predictions of streamflow, and sediment and nutrient loads were as good as or better than those of the Hydrological Simulation Program-Fortran model, one of the most widely used comprehensive watershed models. The landscape model was applied to predict discharges of water, sediment, silicate, organic carbon, nitrate, ammonium, organic nitrogen, total nitrogen, organic phosphorus, phosphate, and total phosphorus from the Patuxent watershed to its estuary. The predicted annual water discharge to the estuary was very close to the measured annual total in terms of percent errors for both years of the study period (,2%). The model predictions for loads of nutrients were also good (20-30%) or very good (<20%) with exceptions of sediment (40%), phosphate (36%), and organic carbon (53%) for Year 1. [source]