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Title: Challenges and progress in distributed watershed modeling: applications of the AgroEcoSystem-Watershed (AgES-W) model

Author
item Ascough Ii, James
item Tomer, Mark
item Green, Timothy
item DAVID, OLAF - Colorad0 State University
item Cole, Kevin
item KIPKA, HOLM - Colorad0 State University
item Porter, Sarah

Submitted to: Meeting Abstract
Publication Type: Proceedings
Publication Acceptance Date: 11/17/2014
Publication Date: 12/1/2014
Citation: J.C. Ascough II, Tomer, M.D., Green, T.R., David, O., Cole. K.J., Kipka, H., and Porter, S.A. 2014. Challenges and progress in distributed watershed modeling: Applications of the AgroEcoSystem-Watershed (AgES-W) model. Procs. Third 21st Century Watershed Technology Conference and Workshop: Improving Water Quality and Environment, Paper No. 14-002, pgs. 1-8. DOI: 10.13031/wtcw.2014-002.DOI: 10.13031/wtcw.2014-002.

Interpretive Summary: Watershed-scale hydrologic/water quality (H/WQ) modeling has emerged as an important scientific research and management tool, particularly in efforts to understand and control water pollution. Developments in computer technology have revolutionized the study of hydrologic systems and the subsequent development of distributed parameter watershed models which theoretically involve a more accurate representation of the hydrologic system by considering the spatial variability of model parameters and inputs. Distributed parameter watershed models generally subdivide the watershed into smaller hydrologic response units (HRUs) and require data on model inputs such as soil and land use for each of the spatial units. Although this can result in a better representation of the natural hydrologic system, data assembly and development of input files for such models can require considerable effort and time on the part of the modeler. This paper discusses current challenges and advances for distributed parameter H/WQ modeling and presents a recent application of the AgroEcoSystem-Watershed (AgES-W) modular, Java-based spatially distributed model to the Upper Cedar Creek Watershed (CCW), Indiana, USA to demonstrate advances in watershed management at multiple scales. AgES-W model evaluation for the CCW includes statistical comparisons of simulated flows and nitrogen loads using monitoring data from the watershed outlet. Finally, an ongoing AgES-W model application to the South Fork Watershed, Iowa, USA for assessing spatially targeted agricultural conservation effects on water quantity and quality is described.

Technical Abstract: Progress in the understanding of physical, chemical, and biological processes influencing water quality, coupled with advances in the collection and analysis of hydrologic data, provide opportunities for significant innovations in the manner and level with which watershed-scale processes may be quantified and modeled. Watershed-scale hydrologic/water quality (H/WQ) modeling has emerged as an important scientific research and management tool, particularly in efforts to understand and control water pollution. Developments in computer technology have revolutionized the study of hydrologic systems and the subsequent development of distributed parameter watershed models which theoretically involve a more accurate representation of the hydrologic system by considering the spatial variability of model parameters and inputs. Distributed parameter watershed models generally subdivide the watershed into smaller hydrologic response units (HRUs) and require data on model inputs such as soil and land use for each of the spatial units. Although this can result in a better representation of the natural hydrologic system, data assembly and development of input files for such models can require considerable effort and time on the part of the modeler. This paper first briefly discusses current challenges and advances for distributed parameter H/WQ modeling. Next, a recent application of the AgroEcoSystem-Watershed (AgES-W) modular, Java-based spatially distributed model to the Upper Cedar Creek Watershed (CCW), Indiana, USA is presented to demonstrate many of the advances available for watershed management at multiple scales. AgES-W model evaluation for the CCW includes statistical comparisons of simulated flows and nitrogen loads using monitoring data from the watershed outlet. Finally, an ongoing AgES-W model application to the South Fork Watershed, Iowa, USA for assessing spatially targeted agricultural conservation effects on water quantity and quality is described.