Flooding can lower annual cash crop yields and threaten the economic prosperity of farmers. As flooding events become more intense, frequent, and long-lasting due to the effects of climate change, more consideration is needed for which crops to place in high-risk areas. Previous studies have examined the broad impacts of weather events such as flooding or drought on crop yield and farmers’ revenue using long-term averages. This work expands on previous research by taking a case study approach to examine two Pennsylvania watersheds—Beaver Branch and Halfmoon Creek—and analyzes the impact of soil properties while considering the potential effects of extreme weather events such as flooding. We predict soil property impacts on crop yields and return on investment by combining predicted crop yields with other terrain and biophysical properties and applying machine learning techniques such as LASSO, principal components analysis, and random forests. The results indicate a statistically significant negative return on investment for corn, likely due to flooding, and that soil properties such as available water storage and soil organic carbon have large impacts on return on investment. This analysis will help farmers and other stakeholders identify fields that may benefit from flood-resistant crops and perennial cropping systems like riparian buffers, thus establishing a more resilient and sustainable farming operation.
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