Changes in hydrology and streamflow as predicted by a modelling experiment forced with climate models Manoj K. Jha 1 * and Philip W. Gassman 2 1 Civil, Architectural and Environmental Engineering, North Carolina A&T State University, 1601 E. Market St., Greensboro, NC, 27410, USA 2 Center for Agricultural and Rural Development, Iowa State University, 560 Heady Hall, Ames, IA, 50010, USA Abstract: Changes in precipitation and temperature have direct effects on crop water use, water stress, crop yield, evapotranspiration, water nutrient dynamics and other indicators. This study, built on a modelling framework with the Soil and Watershed Assessment Tool (SWAT) model for the Raccoon River Watershed in central Iowa, a typical US Midwestern agricultural watershed, examines the watershed response to changes in meteorological inputs from an ensemble of ten global climate models under the A1B scenario. Changes in climate were directly applied to observations (the delta change method) assuming that the estimates of climate change are reliable even if the simulated current climate may be biased. The ensemble average for the mid-century (1946–1965) predicted 0.7% increase in daily precipitation (monthly variation from 11.3% to +19.5%) and 2.78  C increase in average temperature over the entire watershed. These predictions were translated through a well-calibrated SWAT modelling setup into 22% decrease in snowfall, 16% decrease in surface runoff, 18% decrease in baseflow, 8% increase in evapotranspiration and 17% decrease in total water yield. The spatial impact at the subwatershed level revealed a wide variation (but no defined trend) with decrease in water yield that ranged from 10% to 23%. Flow near the watershed outlet (Van Meter, Iowa) is expected to decline by 17% on an average annual basis with the highest impact occurring during summer months with a maximum 39% reduction in August. Changes in climate were found to have a clear and significant impact signal of decreasing streamflow at the watershed outlet with far-reaching implication for drinking water supplies for the central Iowa communities. Copyright © 2013 John Wiley & Sons, Ltd. KEY WORDS climate variability; hydrological response; climate change; SWAT; GCM Received 7 November 2012; Accepted 14 March 2013 INTRODUCTION Agricultural watersheds are well known for non-point source water quality problems that vary depending upon the adopted cropping and land management practices in a given watershed. Spatial variation in topography, land use, soil types and climatic conditions impacts water, sediment and nutrient movement. Whereas topography and soil types, and to some extent land use, are a fixed set of conditions, climate offers significant variation both spatially and temporally. Changes in precipitation and temperature have direct effects on crop water use, water stress, crop yield, evapotranspiration (ET), water, nutrient dynamics and other indicators. Future change in climate is uncertain, but sophisticated climate models have been developed, which predict potential changes in climate due to increases in anthropogenic greenhouse gases. Many global circulation model (GCM) experiments predict a rise in global mean temperature of between 1.5 and 4.5  C, followed by a doubling of equivalent carbon dioxide (CO 2 ) concentrations, and considerable spatial variability in temperature and other climatic changes (IPCC, 2007). Whereas the prediction of increase in temperature is consistent, changes in predicted precipita- tion are more uncertain. But these changes will have significant implications on water storage and dynamics of corresponding nutrient movement. Information on chang- ing watershed conditions for potential changes in future climate will be critical for efficient adaptation of optimal land management practices for both land productivity and water quality. Climate change impact assessment studies usually consist of forcing hydrologic models with GCM pro- jections. Many previous studies have examined the impact of future climate change projections using GCMs and downscaled (dynamic, statistical and delta change) RCMs (Regional Climate Models) (e.g. Jha et al., 2004, 2006, 2013; Takle et al., 2005; Kang and Ramirez, 2007; Driessen et al., 2010; Forbs et al., 2010; Jin and Sridhar, 2012). These studies revealed multiple sources of uncertainties due to several factors including the number and types of GCMs that were used, specific climate *Correspondence to: Manoj K. Jha, Civil, Architectural and Environmental Engineering, North Carolina A&T State University, 1601 E. Market St, Greensboro, NC 27410, USA E-mail: mkjha@ncat.edu HYDROLOGICAL PROCESSES Hydrol. Process. 28, 2772–2781 (2014) Published online 30 April 2013 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/hyp.9836 Copyright © 2013 John Wiley & Sons, Ltd.