Due to the difficulty of measuring forage yields, U.S. crop insurance and disaster programs targeted toward forage producers’ base payments on an index hoped to correlate with forage yields. This study explores using NASA’s soil moisture data, Famine Early Warning Systems Network Land Data Assimilation System (FLDAS), as a more accurate index for drought insurance and disaster programs compared to traditional indices like the United States Drought Monitor (USDM) and rainfall data as well as in-situ soil moisture data from the Oklahoma Mesonet.

Correlation analysis revealed varying degrees of correlation between NASA’s volumetric water content (VWC) and Mesonet’s VWC and rainfall anomalies across different depths and regions. High correlations at 5 cm and 25cm depth were scattered around Oklahoma's central and western parts. Lower correlations were scattered in the eastern part of the state, urban areas, and vast irrigated regions. NASA’s VWC at 25 cm consistently showed the highest correlation with hay yield anomalies, particularly in June and July. Similarly, all variables showed their highest correlations during these critical months.

Linear regression models reveal that NASA Fractional Available Water (FAW) (R² = 0.42), Mesonet FAW (R² = 0.41), NASA VWC at 5cm (R² = 0.44), NASA VWC at 25cm (R² = 0.45), USDM (R² = 0.29), and rainfall (R² = 0.31) soil moisture data are significant predictors of hay yield anomalies. Quadratic models explained up to 49% of the variance in yield anomalies. Mixed-effect models underscored the significance of NASA and Mesonet anomalies on hay yield, revealing strong relationships even when controlling for local environmental characteristics and annual weather patterns. Segmented regression models identified breakpoints in the soil moisture-yield relationship, highlighting the importance of non-linear effects in agricultural data analysis. Among all models, NASA FLDAS VWC at 25cm was consistently the best predictor.

Incorporating NASA’s soil moisture data into crop insurance and disaster protection programs could improve financial support accuracy for farmers. Future research should validate these findings across diverse regions and assess the economic impacts of implementing this approach in insurance programs.