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Title: Advances in distributed watershed modeling: a review and application of the AgroEcoSystem-Watershed (AgES-W) model

Author
item Ascough Ii, James
item Green, Timothy
item DAVID, OLAF - Colorado State University
item KIPKA, HOLM - Colorad0 State University
item McMaster, Gregory
item FINK, MANFRED - Friedrick-Schiller University
item KRAUSE, PETER - Thuringian State Institute For Environment And Geology
item KRALISCH, SVEN - Friedrick-Schiller University

Submitted to: Environmental Modeling International Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 6/14/2014
Publication Date: 6/21/2014
Citation: Ascough II, J.C., Green, T.R., David, O., Kipka, H., Mcmaster, G.S., Fink, M., Krause, P., Kralisch, S. 2014. Advances in distributed watershed modeling: a review and application of the AgroEcoSystem-Watershed (AgES-W) model. Environmental Modeling International Conference Proceedings. Available: http://www.iemss.org/sites/iemss2014/papers/iemss2014_submission_351.pdf.

Interpretive Summary: This paper provides a review of current developments in distributed watershed modeling, including use of stochastic-based methods, influence of data resolution and scaling issues, and the use of environmental modeling frameworks that maintain modularity, reusability, and interoperability (or compatibility) of both customized science modules at different scales and auxiliary components for visualization, parameter estimation, and uncertainty analysis. Important findings and observed trends from this work include: 1) limitations in scale-up of hydrological/water quality processes for watershed modeling; 2) the impacts of data provisioning (availability and resolution) on watershed modeling capabilities, and 3) recommendations concerning the employment of a more holistic component-based modeling approach that is capable of examining individual processes and systems and the interconnection between them. In addition, an application of the AgroEcoSystem-Watershed (AgES-W) modular, Java-based spatially distributed model to the Walnut Creek and South Fork watersheds in Iowa, USA is presented to demonstrate many of the advances described above that are currently available for watershed management at multiple scales. Model evaluations will include statistical comparisons of AgES-W simulated flows and N concentrations/loads with monitoring data from outlets of the experimental Iowa watersheds.

Technical Abstract: Progress in the understanding of physical, chemical, and biological processes influencing water quality, coupled with advancements 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. This paper provides a review of current developments in distributed watershed modeling, including use of stochastic-based methods, influence of data resolution and scaling issues, and the use of environmental modeling frameworks that maintain modularity, reusability, and interoperability (or compatibility) of both customized science modules at different scales and auxiliary components for visualization, parameter estimation, and uncertainty analysis. Important findings and observed trends from this work include: 1) limitations in scale-up of hydrological/water quality processes for watershed modeling; 2) the impacts of data provisioning (availability and resolution) on watershed modeling capabilities, and 3) recommendations concerning the employment of a more holistic component-based modeling approach that is capable of examining individual processes and systems and the interconnection between them. In addition, an application of the AgroEcoSystem-Watershed (AgES-W) modular, Java-based spatially distributed model to the Walnut Creek and South Fork watersheds in Iowa, USA is presented to demonstrate many of the advances described above that are currently available for watershed management at multiple scales. Model evaluations will include statistical comparisons of AgES-W simulated flows and N concentrations/loads with monitoring data from outlets of the experimental Iowa watersheds.