Conclusion

This research investigates the relationship between drought indices and crop yields, focusing on corn and soybean production in Iowa from 2000 to 2022. By analyzing both conventional and satellite-based drought indices, such as the Standardized Precipitation Index (SPI), the Standardized Precipitation-Evapotranspiration Index (SPEI), the Palmer Drought Severity Index (PDSI), and the Evaporative Demand Drought Index (EDDI), this study provides a comprehensive assessment of how climatic variability impacts agricultural productivity. These indices, applied at various temporal scales (1, 3, 6, and 12 months), capture the complex interplay of precipitation, evapotranspiration, and soil moisture dynamics in crop growth stages. The findings reveal a high frequency of intense drought episodes in 2003, 2012, 2013, 2020, and 2022, which had pronounced impacts on crop yields, particularly in Iowa’s central, southern, and western regions. While drought is likely the primary driver of these yield reductions, other confounding factors, such as pest infestations, disease outbreaks, soil fertility variability, and management practices, could also have contributed to these fluctuations. Additionally, extreme weather events like heat waves during critical growth phases may have compounded the impacts of water deficiency. The detrended standardized yield residual series (SRYS) effectively isolated the effects of climatic variability, illustrating significant crop output fluctuations for corn and soybeans. These analyses identified SPI-3, SPEI-3, and PDSI as critical indices for detecting water deficiency during key growth phases, underscoring their utility in assessing drought impacts. Geographically, variations in soil moisture across Iowa’s regions indicate drought conditions can induce severe water scarcity, particularly in areas with lower soil water-holding capacity. These spatial patterns emphasize the importance of integrating localized data into drought mitigation strategies. The results also demonstrate crop-specific sensitivities: SPI-3 and SPEI-3 exhibited stronger correlations with corn yields, effectively capturing the impact of short-term precipitation deficits on corn productivity. In contrast, soybeans showed a stronger association with PDSI, which reflects prolonged moisture availability, indicating that soybeans are more sensitive to cumulative soil moisture conditions over time. Medium-term indices, such as SPI-6 and SPEI-6, were particularly effective at capturing conditions that align with soybean growth and productivity, suggesting that these indices reflect the environmental conditions influencing soybeans rather than any intrinsic association with the indices themselves. This distinction highlights the value of selecting appropriate drought metrics based on the crop and its sensitivity to specific temporal scales of moisture variability. Furthermore, the findings indicate that EDDI, which measures evaporative demand, negatively impacts corn yields, reinforcing the crop’s vulnerability to high-temperature stress during critical growth periods. These observations highlight the significance of maintaining consistent moisture levels across the growing season to enhance crop productivity. This study’s insights can inform strategies to optimize water resource management and mitigate the adverse effects of drought on agriculture. The results of this study hold practical relevance for agricultural planning and drought management. While the integration of multiple drought indices enhances our understanding of drought dynamics, it is important to recognize that these indices are models with inherent limitations. Rather than providing absolute ”truth,” they offer complementary perspectives on drought impacts, such as short-term deficits (e.g., SPI-3) or cumulative moisture conditions (e.g., PDSI). These insights can guide adaptive strategies, including selecting drought-tolerant crops, optimizing irrigation, and aligning planting schedules with moisture availability. Decision-support systems, such as drought relief programs and crop insurance frameworks, can benefit from incorporating these findings to enhance risk aversion strategies and minimize economic losses. While this study primarily models historical environmental conditions, its insights into the differential responses of corn and soybeans to short- and long-term drought indices lay the groundwork for developing forecasting tools. Such tools could help farmers anticipate drought impacts and make informed decisions about crop selection, planting schedules, and resource allocation. Although predicting drought cycles and long-term climate variability is a complex challenge, integrating these findings with climate models and real-time monitoring systems could improve agricultural resilience and guide investments in climate-adaptive practices tailored to Iowa’s regional needs. While this study provides valuable contributions, certain limitations should be acknowledged. The reliance on standardized drought indices derived from meteorological and satellite data introduces inherent uncertainties, particularly in regions with limited ground-based observations. Additionally, statewide yield averages may obscure localized variations in drought impacts, as factors like irrigation practices, soil properties, and crop management strategies can significantly influence outcomes. Future research should address these limitations by incorporating finer spatial resolutions and integrating field-level data. The findings highlight the need to examine the implications of climate change on drought-crop relationships. Rising temperatures and variable precipitation will challenge the utility of current drought indices. Real-time monitoring tools and precision agriculture can help farmers make adaptive decisions, but farming’s inherent path dependencies mean risks cannot be entirely eliminated once planting decisions are made. These tools could mitigate risks during the growing season, but systemic feedback, such as market responses and price stability, must also be addressed. Future work should explore integrating real-time tools with crop insurance and government subsidies to reduce risk and sustain profit margins under changing climate conditions.