Integrating human decision-making into a hydrological model to accurately estimate the impacts of agricultural policies

Agriculture is a major contributor to nutrient pollution that drives eutrophication in aquatic ecosystems. This study integrates hydrological modeling with farmer behavioral analysis to assess the effectiveness of two agricultural conservation practices—cover crops and reduced nitrogen fertilizer application—in reducing nitrate loss from fields in the Tar-Pamlico River Basin of North Carolina. Survey responses from 279 farmers revealed widespread reluctance to adopt conservation practices, particularly strict fertilizer reductions. A hydrological model showed that applying each practice to 25 percent of agricultural land could substantially reduce nitrate export, with cover crops showing greater effectiveness than reduced fertilizer use. However, an integrated socio-hydrological model, which incorporated behavioral responses from farmers, predicted much smaller reductions in nitrate loss due to limited voluntary adoption. Specifically, nitrate reductions were overestimated by a factor of 8 for cover crops and by a factor of 25 for reduced fertilizer application when behavioral responses were excluded. This result highlights a critical limitation of traditional modeling approaches and underscores the importance of integrating human decision-making into environmental policy analysis. By linking policy incentives with both biophysical and social responses, this study offers a more realistic framework for designing cost-effective and impactful agricultural conservation strategies. Incorporating farmer behavior into watershed modeling highlights the vital role of stakeholder decision-making in policy design, revealing large discrepancies in nutrient reduction estimates between traditional hydrological and novel socio-hydrological models, according to survey results of 279 farmers in the Tar-Pamlico River Basin.