SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Hydrological processes and model representation: Impact of soft data on calibration 
Authors:Arnold, J.G., M.A. Youssef, H. Yen, M.J. White, A.Y. Sheshukov, A.M. Sadeghi, D.N. Moriasi, J.L. Steiner, D.M. Amatya, R.W. Skaggs, E.B. Haney, J. Jeong, M. Arabi and P.H. Gowda 
Journal:Transactions of the ASABE 
Volume (Issue):58(6) 
Article ID: 
URL (non-DOI journals): 
Broad Application Category:review/history 
Primary Application Category:calibration, sensitivity, and/or uncertainty analysis 
Secondary Application Category:model and/or data comparison 
Watershed Description:None 
Calibration Summary: 
Validation Summary: 
General Comments:This study is part of a set of 10 articles published as a special issue in Transactions ASABE, issue 58(6). The overall special issue is focused on a broad range of ecohydrological model calibration and validation topics. The articles are not necessarily focused on SWAT but the topics are extremely relevant for the SWAT user community so all 10 articles have been included in the SWAT Literature Database. 
Abstract:Hydrologic and water quality models (HWQMs) are increasingly used to support decisions on various environmental issues and policy directions for present and future scenarios, at scales varying from watershed to continental levels. Uncertainty associated with such models may affect the ability of the models to accurately evaluate the response of complex systems, leading to misguided assessments and risk management decisions. Current well-known HWQMs contain numerous input parameters, many of which are not known with certainty, and in other cases model users can hardly recognize the genesis of uncertainty. Uncertainty in data, model structure, and model parameters can propagate throughout model runs, causing the model output to substantially deviate from the expected response of the natural system. Various uncertainty assessment methods have been used with different HWQMs, creating concerns about an adequate approach for handling uncertainty in these models and how such an approach can be implemented across various discretization complexities and scales. In this article, our primary intention is to review uncertainty in the currently used HWQMs and to provide guidance and useful information for researchers and investigators. In this regard, we explore the genesis of uncertainty in hydrologic and water quality modeling (i.e., spatiotemporal scales, model representation, model discretization, model parameterization) and provide strategies for assessing uncertainty in hydrologic and water quality modeling on local and global scales when interpreting the model output. 
Keywords:Hydrologic modeling, Model calibration, Model validation, Spatiotemporal, Uncertainty.