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Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations

Bibliographic Data

ID23324745
AuthorsD N Moriasi D N Moriasi, Daniel N Moriasi (0000-0002-3389-3277, United States Department of Agriculture), J G Arnold J G Arnold, J G Arnold (United States Department of Agriculture), M W Van Liew M W Van Liew, M W Van Liew (Montana State University), Ronald L Bingner (United States Department of Agriculture), R L Bingner R L Bingner, R D Harmel (0000-0002-5344-1286, United States Department of Agriculture), R D Harmel R D Harmel, Tamie L Veith (0000-0001-7631-0214), T L Veith T L Veith
Year2007
Volume50
Issue3
Pages885-900
Publication date2007-01-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueTransactions of the ASABE (JOURNAL)
Journal identifiersISSN: 2151-0032 • E-ISSN: 2151-0040
PublisherAmerican Society of Agricultural and Biological Engineers (ASABE) (PUBLISHER)
DOI10.13031/2013.23153
OpenAlexW2058998445
LanguageEN
Citations received146
References cited1

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.

Calibration · Data mining · Hydrology (agriculture) · Machine learning · Standard deviation · Statistic · Statistics · Streamflow · Watershed · Computer Science · Environmental Science · Geology · Groundwater flow and contamination studies · Hydrology and Watershed Management Studies · Mathematics · Soil and Water Nutrient Dynamics

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Unique citing works146
Citations per year10,43
Citation span2012 - 2026 (15)
Citation velocitycurrent
Highly citedYes
Citation typesNeutral: 123

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