The hydrologic system has increasingly been experiencing change due to a combination of human and natural factors. Human decision making within the landscape impacts the characteristics of various hydrologic processes, namely runoff, through changes in land use. Equally important, shifting climate is changing precipitation patterns, particularly precipitation intensity, which is changing the quantity of surface water flows. Quantifying the relative impacts of these two dominant components is necessary to fully understanding future hydrologic variability. In this study, the impact of climate and human decision-making on streamflow, specifically focusing on changes in conservation land, is quantified for the U.S. Midwest Corn Belt under future climate scenarios through use of a social-hydrologic modeling system. This modeling system combines an agent-based model (ABM) with a simple semi-distributed hydrologic model. The hydrologic model uses the curve number method to relate land cover to hydrologic response. Agents (based on two primary types) make decisions that affect land use within the watershed. A city agent aims to reduce flooding in a downstream urban area by paying farmer agents a subsidy for allocating land towards conservation practices that reduce runoff, similar to the U.S. Conservation Reserve Program. Farmer agents decide how much land to convert to conservation based on factors related to profits, past land use, neighbor influence (social ties), and conservation-mindedness (willingness to convert land to conservation). The model is implemented for a watershed representative of the mixed agricultural/small urban area land use found in Iowa, USA. In the first part of this study, a sensitivity analysis of the model is conducted based on changes in crop yield trend, crop prices, and conservation subsidies along with varied farmer parameters. In the second part of this study, we simulate the watershed under two future climate scenarios of temperature and precipitation and quantify the changes to peak streamflow. Under the RCP 4.5 and RCP 8.5 scenarios, conservation land increases by approximately 20-60% and 40-60%, respectively. This results in a 4% and 7% decrease in mean 95th percentile discharge relative to scenarios where conservation land is treated as constant at the historical mean. If farmers are allowed to modify their behavior through time, a 10% and 16% decrease in mean 95th percentile discharge is seen under the RCP 4.5 and 8.5 scenarios. However, overall changes to peak discharge are dominated by future changes in precipitation, with climate scenarios depicting mean 95th percentile discharge to increase by 49% for the second half of the century if conservation land is kept constant at the historical mean.
David Dziubanski recently joined Dr. Thomas Meixner’s hydrology group as a postdoctoral scientist. He will be investigating the interconnections between the social and hydrologic systems, with a specific focus on Green Infrastructure implementation in the semi-arid urban setting. David Dziubanski received his B.S in Meteorology from Iowa State University in the fall of 2011. He went on to complete his M.S in Geology in the fall of 2013 at Iowa State University under the guidance of Dr. Kristie Franz, where he earned a Research Excellence Award. His M.S work focused on assimilation of remote sensing snow data into current hydrologic forecasting models used by the National Weather Service (NWS). Following his Master’s degree, David was given the opportunity of continuing research at Iowa State under the Water and Climate Change (WACC) group. In the summer of 2018, he completed his Ph.D. in Civil Engineering. The focus of his doctoral work was examining the effects of changing climate and human-decision making on hydrologic outcomes in the Midwest Cornbelt through a coupled agent-based modeling system. In the future, he would like to continue research in the field of social-hydrology with a strong emphasis on how decisions and climate change will affect future hydrologic processes and water resources.