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Water 2018, 10(11), 1496; https://doi.org/10.3390/w10111496

Modeling Water Yield: Assessing the Role of Site and Region-Specific Attributes in Determining Model Performance of the InVEST Seasonal Water Yield Model

1
Consejo Nacional de Investigaciones Científicas y Técnicas—Instituto Argentino de Oceanografía, Florida 8000, Bahía Blanca, B8000BFW Buenos Aires, Argentina
2
Departamento de Geografía y Turismo, Universidad Nacional del Sur, 12 de Octubre and San Juan, Bahía Blanca, B8000CTD Buenos Aires, Argentina
3
Department of Biological Sciences, Queen’s University, Kingston, ON K7L 3N6, Canada
4
Departamento de Geología, Universidad Nacional del Sur, Av. Alem 1253, 2do Cuerpo, Bahía Blanca, B8000BFW Buenos Aires, Argentina
5
Departamento de Biología, Bioquímica y Farmacia, Universidad Nacional del Sur, San Juan 670, B8000DIC Bahía Blanca, Argentina
6
Dorset Environmental Science Centre, Ontario Ministry of the Environment, Conservation, and Parks, P.O. Box 39, Dorset, ON P0A 1E0, Canada
*
Author to whom correspondence should be addressed.
Received: 31 August 2018 / Revised: 13 October 2018 / Accepted: 16 October 2018 / Published: 23 October 2018
(This article belongs to the Special Issue Current and Emerging Issues Surrounding Water in the Americas)
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Abstract

Simple hydrological models, such as the Seasonal Water Yield Model developed by the Natural Capital Project (InVEST SWYM), are attractive as data requirements are relatively easy to satisfy. However, simple models may produce unrealistic results when the underlying hydrological processes are inadequately described. We used the variation in performance of the InVEST SWYM across watersheds to identify correlates of poorly modeled outcomes of InVEST SWYM. We grouped 749 watersheds from across North America into five bioclimatic regions using nine environmental variables. For each region, we compared the predicted flow patterns to actual flow conditions over a 15-year period. The correlation between the modeled and actual flows was highly dispersed and relatively poor, with 92% of r2 values less than 0.5 and 42% less than 0.1. We linked cryospheric variables to model performance in the bioclimatic region with the poorest model performance (the Low elevation Boreal Sub-humid region—LeBSh). After incorporating cryospheric conditions into the InVEST SWYM, predictions improved significantly in 30% of the LeBSh watersheds. We provide a relatively straightforward approach for identifying processes that simple hydrological models may not consider or which need further attention or refinement. View Full-Text
Keywords: hydrological models; InVEST SWYM Natural Capital Project; model processes; model fit; environmental regions hydrological models; InVEST SWYM Natural Capital Project; model processes; model fit; environmental regions
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Scordo, F.; Lavender, T.M.; Seitz, C.; Perillo, V.L.; Rusak, J.A.; Piccolo, M.C.; Perillo, G.M.E. Modeling Water Yield: Assessing the Role of Site and Region-Specific Attributes in Determining Model Performance of the InVEST Seasonal Water Yield Model. Water 2018, 10, 1496.

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