Journal ArticleDOI
Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations
Daniel N. Moriasi,Jeffrey G. Arnold,M. W. Van Liew,Ronald L. Bingner,R. D. Harmel,Tamie L. Veith +5 more
TLDR
In this paper, the authors present guidelines for watershed model evaluation based on the review results and project-specific considerations, including single-event simulation, quality and quantity of measured data, model calibration procedure, evaluation time step, and project scope and magnitude.Abstract:
Watershed models are powerful tools for simulating the effect of watershed processes and management on soil and water resources. However, no comprehensive guidance is available to facilitate model evaluation in terms of the accuracy of simulated data compared to measured flow and constituent values. Thus, the objectives of this research were to: (1) determine recommended model evaluation techniques (statistical and graphical), (2) review reported ranges of values and corresponding performance ratings for the recommended statistics, and (3) establish guidelines for model evaluation based on the review results and project-specific considerations; all of these objectives focus on simulation of streamflow and transport of sediment and nutrients. These objectives were achieved with a thorough review of relevant literature on model application and recommended model evaluation methods. Based on this analysis, we recommend that three quantitative statistics, Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), and ratio of the root mean square error to the standard deviation of measured data (RSR), in addition to the graphical techniques, be used in model evaluation. The following model evaluation performance ratings were established for each recommended statistic. In general, model simulation can be judged as satisfactory if NSE > 0.50 and RSR < 0.70, and if PBIAS + 25% for streamflow, PBIAS + 55% for sediment, and PBIAS + 70% for N and P. For PBIAS, constituent-specific performance ratings were determined based on uncertainty of measured data. Additional considerations related to model evaluation guidelines are also discussed. These considerations include: single-event simulation, quality and quantity of measured data, model calibration procedure, evaluation time step, and project scope and magnitude. A case study illustrating the application of the model evaluation guidelines is also provided.read more
Citations
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Journal ArticleDOI
The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions
TL;DR: The Soil and Water Assessment Tool (SWAT) model is a continuation of nearly 30 years of modeling efforts conducted by the USDA Agricultural Research Service (ARS) and has gained international acceptance as a robust interdisciplinary watershed modeling tool.
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Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions, The
TL;DR: The Soil and Water Assessment Tool (SWAT) model is a continuation of nearly 30 years of modeling efforts conducted by the U.S. Department of Agriculture (USDA), Agricultural Research Service.
Journal ArticleDOI
SWAT: Model Use, Calibration, and Validation
Jeffrey G. Arnold,Daniel N. Moriasi,Philip W. Gassman,Karim C. Abbaspour,Michael J. White,Raghavan Srinivasan,C. Santhi,R. D. Harmel,A. van Griensven,M. W. Van Liew,Narayanan Kannan,Manoj Jha +11 more
TL;DR: The SWAT-CUP tool as discussed by the authors is a semi-distributed river basin model that requires a large number of input parameters, which complicates model parameterization and calibration, and is used to provide statistics for goodness-of-fit.
Journal ArticleDOI
Hydrologic and Water Quality Models: Performance Measures and Evaluation Criteria
TL;DR: In this paper, a meta-analysis of performance data reported in recent peer-reviewed literature for three widely published watershed-scale models (SWAT, HSPF, WARMF), and one field-scale model (ADAPT) is performed.
Journal ArticleDOI
Position paper: Characterising performance of environmental models
Neil D. Bennett,Barry Croke,Giorgio Guariso,Joseph H. A. Guillaume,Serena H. Hamilton,Anthony Jakeman,Stefano Marsili-Libelli,Lachlan Newham,John Norton,Charles Perrin,Suzanne A. Pierce,Barbara J. Robson,Ralf Seppelt,Alexey Voinov,Brian D. Fath,Vazken Andréassian +15 more
TL;DR: General classes of direct value comparison, coupling real and modelled values, preserving data patterns, indirect metrics based on parameter values, and data transformations are discussed.
References
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Journal ArticleDOI
River flow forecasting through conceptual models part I — A discussion of principles☆
J.E. Nash,J.V. Sutcliffe +1 more
TL;DR: In this article, the principles governing the application of the conceptual model technique to river flow forecasting are discussed and the necessity for a systematic approach to the development and testing of the model is explained and some preliminary ideas suggested.
Journal ArticleDOI
Large Area Hydrologic Modeling and Assessment Part i: Model Development
TL;DR: A conceptual, continuous time model called SWAT (Soil and Water Assessment Tool) was developed to assist water resource managers in assessing the impact of management on water supplies and nonpoint source pollution in watersheds and large river basins as discussed by the authors.
Journal ArticleDOI
Evaluating the use of “goodness-of-fit” Measures in hydrologic and hydroclimatic model validation
TL;DR: In this paper, the goodness-of-fit or relative error measures (including the coefficient of efficiency and the index of agreement) that overcome many of the limitations of correlation-based measures are discussed.
Journal ArticleDOI
On the validation of models
TL;DR: In this paper, it is suggested that the correlation coefficieness between observed and simulated variates is not as good as observed variates, and that correlation can be improved.
Journal ArticleDOI
Status of Automatic Calibration for Hydrologic Models: Comparison with Multilevel Expert Calibration
TL;DR: The capability of the shuffled complex evolution automatic procedure is compared with the interactive multilevel calibration multistage semiautomated method developed for calibration of the Sacramento soil moisture accounting streamflow forecasting model of the U.S. National Weather Service and suggests that the state of the art in automatic calibration now can be expounded.
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