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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #304392
Title: Hydrologic and water quality modeling: spatial and temporal considerations

Author
item Baffaut, Claire
item Dabney, Seth
item SMOLEN, MIKE - Oklahoma State University
item YOUSEF, MOHAMED - North Carolina State University
item Bonta, James - Jim
item CHU, MARIA - Washington State University
item Guzman Jaimes, Jorge
item SHEDEKAR, VINAYAK - The Ohio State University
item JHA, MANOJ - North Carolina Agricultural And Technical State University
item Arnold, Jeffrey

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/3/2014
Publication Date: 1/13/2016
Citation: Baffaut, C., Dabney, S.M., Smolen, M., Yousef, M.A., Bonta, J.V., Chu, M.L., Guzman, J.A., Shedekar, V.S., Jha, M.K., Arnold, J.G. 2016. Hydrologic and water quality modeling: spatial and temporal considerations. Transactions of the ASABE. 58(6):1661-1680. doi: 10.13031/trans.58.10714.

Interpretive Summary: Hydrologic and water quality models are used to help manage water resources by investigating the effects of climate, land use, land management, and water management on water resources. Each water-related issue is better investigated at a specific scale, which can vary spatially from point to watershed, and temporally from seconds to centuries. Similarly, equations used in the models may place scale restrictions on their use. In 2012, ASABE published a collection of 22 papers on the setup and use of 25 hydrologic and water quality models. Each paper detailed the process to follow and the issues that could arise during setup of a specific model for a specific site. The objective of this paper is to highlight the spatial- and temporal- scale principles that should guide selecting and setting up a hydrologic model, using information provided in the 22 papers as well as other published literature. The paper describes how the scale of a model relates to the modeling objectives, the processes simulated, the setup process, available data, and results interpretation. Overall, the scale of the model should match the scale of the processes that need to be simulated given the modeling objectives, the scale of the data used during model setup should be compatible with the scale of the model and with the objectives of the study, and the model should be evaluated at the scale at which the results will be analyzed and interpreted. Guiding principles to achieve these goals are proposed and will benefit modelers as well as water resources managers and decision makers who rely on these models for scenario analysis.

Technical Abstract: Hydrologic and water quality models are used to help manage water resources by investigating the effects of climate, land use, land management, and water management on water resources. Each water-related issue is better investigated at a specific scale, which can vary spatially from point to watershed, and temporally from seconds to centuries. Similarly, assumptions implied in the formulation of the models may place scale restrictions on their use. In 2012, ASABE published a collection of 22 papers on the calibration, validation, and use of 25 hydrologic and water quality models. Each paper detailed the process to follow and the issues that could arise during calibration or application of a specific model. The objective of this paper is to highlight the spatial- and temporal- scale principles that should guide selecting, parameterizing, and calibrating a hydrologic model, using information provided in these papers as well as other published literature. The paper describes how the spatio-temporal scale of a model relates to the modeling objectives, the processes simulated, the parameterization and calibration process, data available for parameterization and calibration, and results interpretation. Overall, the intended scale of the model should match the scale of the processes that need to be simulated given the modeling objectives, the scale of input and calibration data should be compatible with the scale of the model and with the objectives of the study, and the model should be calibrated at the scale at which the results will be analyzed and interpreted. A list of guiding principles to achieve these goals is proposed.