Paper No. 17-2
Presentation Time: 1:50 PM
MODELING UNCERTAINTY ARISING FROM CO-EVOLVING HUMAN AND HYDROLOGIC SYSTEMS
Humans impose stresses on the water cycle through various actions including land use alterations, water quality degradation, and river modification. In the Earth system, impacts are not limited to the human system affecting the water system; both systems are coupled and co-evolutionary, in which dynamic feedbacks from the water system can also directly affect behavior in the human system. The goal of this research is to improve understanding and representation of the causes of hydrologic variability and uncertainty due to humans through use of a socio-hydrologic modeling approach that simulates dynamic, coupled human-environment interactions. In this study, we build a socio-hydrological model that combines an agent-based model (ABM) with a semi-distributed hydrologic model based on the U.S. Army Corps of Engineers Hydrologic Modeling System (HEC-HMS). This model uses the curve number method to relate land cover change 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). The model is implemented for a watershed representative of the mixed agricultural/small urban area land use found in Iowa, USA. We have simulated scenarios of crop prices, conservation subsidies, and yields, along with varied farmer parameters that illustrate the effects of human system variables on peak discharges. High corn prices lead to low amounts of conservation land; consequently, peak discharges are largely unaffected and the city agent does not achieve his/her flood reduction goal. However, when corn prices are low and/or the watershed is characterized by a conservation-minded farmer population, mean peak discharge is reduced by 11%. Ultimately, this modeling framework will be used as a platform for engagement with critical stakeholders, which will allow investigation of the effects of various policy decisions on hydrologic issues and lead to more informed decision making within the watershed under future climate.