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An improved representation of geographically isolated wetlands in a watershed‐scale hydrologic model
Author(s) -
Evenson Grey R.,
Golden Heather E.,
Lane Charles R.,
D'Amico Ellen
Publication year - 2016
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.10930
Subject(s) - watershed , environmental science , hydrology (agriculture) , wetland , soil and water assessment tool , hydrological modelling , water balance , land use , swat model , computer science , geography , cartography , streamflow , ecology , geology , drainage basin , geotechnical engineering , climatology , machine learning , biology
Abstract Geographically isolated wetlands (GIWs), defined as wetlands surrounded by uplands, provide an array of ecosystem goods and services. Within the United States, federal regulatory protections for GIWs are contingent, in part, on the quantification of their singular or aggregate effects on the hydrological, biological, or chemical integrity of waterways regulated by the Clean Water Act (CWA). However, limited tools are available to assess the downgradient effects of GIWs. We constructed a Soil and Water Assessment Tool (SWAT) model with improved representations of GIW hydrologic processes for the approximately 1700 km 2 Pipestem Creek watershed in the Prairie Pothole Region of North Dakota, USA. We then executed a series of novel modifications on the Pipestem Creek SWAT model. We (1) redefined the model's hydrologic response unit spatial boundaries to conform to mapped GIWs and associated watershed boundaries, (2) constructed a series of new model input files to direct the simulation of GIW fill–spill hydrology and upland flows to GIWs, and (3) modified the model source code to facilitate use of the new SWAT input files and improve GIW water balance simulations. We then calibrated and verified our modified SWAT model at a daily time step from 2009 through 2013. Simulation results indicated good predictive power (the maximum Nash–Sutcliffe Efficiency statistic was 0.86) and an acceptable range of uncertainty (measured using the Sequential Uncertainty Fitting v.2 uncertainty statistics). Simulation results additionally indicated good model performance with respect to GIW water balance simulations based on literature‐based descriptions of regional GIW hydrologic behaviour. Our modified SWAT model represents a critical step in advancing scientific understandings of the watershed‐scale hydrologic effects of GIWs and provides a novel method for future assessments in different watersheds and physiographic regions. Copyright © 2016 John Wiley & Sons, Ltd.