Date of Award
Doctor of Philosophy
Civil, Construction, and Environmental Engineering
Civil Engineering; Geology
Kristie J. Franz
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 for fully understanding hydrologic variability and uncertainty, and for future flood and drought planning. The main objective of this study was to analyze the impacts of human decision-making and changing climate on streamflow for the U.S. Midwest Corn Belt under future climate scenarios through use of a social-hydrologic modeling system.
The first part of this study focused on building and conducting a sensitivity analysis of a socio-hydrological model that combines an agent-based model (ABM) of human decision-making with a semi-distributed hydrologic model. The hydrologic model uses the curve number (CN) method to relate land cover to hydrologic response. Agents (based on two 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. Farmer agents decide how much land to convert to conservation based on factors related to profits, past land use and conservation-mindedness (willingness to convert land to conservation). In order to accurately represent a conservation practice within the hydrologic model, CNs were derived using precipitation and runoff data for 14 small watersheds in Iowa which were planted with varying amounts of native prairie vegetation (NPV) located in different watershed positions. The social-hydrologic model was implemented for a watershed representative of the mixed agricultural/small urban area land use found in Iowa, USA (Squaw Creek watershed). Scenarios of crop yield trend, crop prices, and conservation subsidies along with varied farmer parameters were simulated to illustrate the effects of human system variables on peak discharges. High corn prices lead to a decrease in conservation land from historical levels; consequently, mean peak discharge increases by 6%, creating greater potential for downstream flooding within the watershed. Overall, results indicated that changes in mean peak discharge are mostly driven by changes in crop prices as opposed to yields or conservation subsidies.
In the second part of this study, the watershed was simulated into the future under two different climate scenarios. The agent-based model was upgraded to include a social network and a “pothole module” to capture the effect of neighbor influence and on-farm flooding on decision-making. Under the RCP 4.5 (greenhouse gas concentrations peak around 2040) and RCP 8.5 (greenhouse gas concentrations continuously rise through 2100) scenarios, conservation land increases by approximately 20-60% and 40-60%, respectively. This results in a 5% and 6% 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 46% if conservation land is kept constant at the historical mean.
Dziubanski, David, "Investigating the impacts of human decision-making and climate change on hydrologic response in an agricultural watershed" (2018). Graduate Theses and Dissertations. 16574.