Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 15, 2007
Publication Date: March 15, 2007
Citation: Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Bingner, R.L., Harmel, R.D., Veith, T.L. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE. 50(3):885-900. Interpretive Summary: Computer-based watershed models can save time and money by providing the ability to quickly and efficiently evaluate and quantify water quality, water quantity and soil quality over lengthy periods. These models also provide the ability to simulate the effects of various conservation programs to aid in design of policies. In order to use model simulation outputs for tasks ranging from regulatory purposes to research, simulation outputs should be defensible. This requires that most suitable criteria and their respective range of values used to quantify the simulation outputs from watershed models be developed. Current published literature does not include watershed model performance criteria that have been developed recently. In addition, none of these papers recommends general guideline values for the criteria they have recommended for watershed simulations. This study gives recommendations on suitable watershed model validation criteria and guidelines on their respective range of values based on a comprehensive up-to-date literature review. These guidelines will aid modelers and model users determine reasonable range of values to use to quantify watershed model simulations performance accuracy.
Technical Abstract: This study makes recommendations for watershed model validation criteria for streamflow, sediment, and nutrients based on up-to-date model performance criteria review and a review of papers which recommend model validation criteria for hydrologic models and important considerations in selecting model validation criteria. In addition, the study recommends general suitable guideline value ranges for the selected criteria based on reported model validation guidelines for the selected quantitative criteria, reported values for recommended quantitative criteria for validation of selected models, and important considerations [especially measured data uncertainty] in selecting suitable model validation guidelines. Factors are discussed that can be used to justify making the guidelines more or less strict.