Parameterizing GPFARM-Range model to simulate climate change impacts on hydrologic cycle in a subsurface drained pastureland

Abstract

In the United States' Corn Belt, conversion of tile-drained fields under a corn (Zea mays L.)–soybean (Glycine max [L.] Merr.) rotation to pastureland or prairie has significantly improved environmental quality, but may have altered the local hydrologic cycle. A recently developed rangeland management tool, the Great Plains Framework for Agricultural Resource Management in Rangelands (GPFARM-Range) model was calibrated with measured data (2006 to 2009) to simulate the hydrologic cycle of subsurface drained pastureland and thereafter predict the potential impacts of climate change on the hydrologic cycle. Soil water content and tile drainage flow data were collected (2006 to 2009) from subsurface drained pastureland plots near Gilmore City, Iowa, which had been converted from a corn–soybean rotation in 2005. The model does not have a tile drainage module, therefore, simulated water seepage below the root zone was compared with measured tile flow. Based on the percentage of bias (PBIAS), Nash-Sutcliffe model efficiency (NSE), and index of agreement (IoA), the GPFARM-Range model was found to be accurate in simulating both annual subsurface drainage (PBIAS = 1.2%, NSE = 0.76, and IoA = 0.91) and soil water storage (PBIAS = 0.54%, NSE = 0.74, and IoA = 0.91). Due to the lack of a formal tile drainage module, the timing of drainage on a monthly basis was not well simulated. Compared to the hydrologic cycle under historical climate, the simulation demonstrated 13.9% increase in subsurface drainage and 1.9% increase in evapotranspiration (ET) under a climate change regime (from 2045 to 2064). This study suggests that, after parameterization, the GPFARM-Range model can be used to estimate water balance on a yearly basis for a tile-drained pastureland, but that a tile drainage module is needed to improve the model performance in predicting tile flow in a timely manner.