Linking economic and social factors to peak flows in an agricultural watershed using socio-hydrologic modeling
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2020-06-02
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Copernicus Publications
Abstract
Hydrologic modeling studies most often represent humans through predefined actions and fail to account for human responses under changing hydrologic conditions. By treating both human and hydrologic systems as co-evolving, we build a socio-hydrological model that combines an agent-based model (ABM) with a semi-distributed hydrologic model. The curve number method is used to clearly illustrate the impacts of land cover changes resulting from decisions made by two different agent types. Aiming to reduce flooding, a city agent pays farmer agents to convert land into conservation. Farmer agents decide how to allocate land between conservation and production based on factors related to profits, past land use, and willingness. The model is implemented for a watershed representative of the mixed agricultural/small urban area land use found in Iowa, USA. In this preliminary study, we simulate scenarios of crop yields, crop prices, and conservation subsidies along with varied farmer parameters that 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. However, when corn prices are low and the watershed is characterized by a conservation-minded farmer population, mean peak discharge is reduced by 3 %. Overall, changes in mean peak discharge, which is representative of farmer land use decisions, are most sensitive to changes in crop prices as opposed to yields or conservation subsidies.
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This article is published as Dziubanski, David, Kristie J. Franz, and William Gutowski. "Linking economic and social factors to peak flows in an agricultural watershed using socio-hydrologic modeling." Hydrology and Earth System Sciences 24, no. 6 (2020): 2873-2894.
DOI: 10.5194/hess-24-2873-2020.
Copyright 2020 The Author(s).
Attribution 4.0 International (CC BY 4.0).
Posted with permission.