State-level multidimensional agricultural drought susceptibility and risk assessment for agriculturally prominent areas

Abstract

Given the growing climate variability, quantifying droughts has gained significant importance, particularly in agriculturally concentrated areas such as Iowa. This study presents a novel approach for evaluating the risk of agricultural drought, which combines geospatial methods with a fuzzy logic algorithm. The approach integrates a diverse array of meteorological, physical, and social factors, yielding a more comprehensive and nuanced understanding of the impacts of drought. This study has covered the agricultural sector within the Corn Belt region of Iowa and formulated maps illustrating the vulnerability and risk of drought for the timeframe spanning from 2015 to 2021. The risk maps illustrate significant progress in drought risk analysis, fully representing the spatial and temporal dimensions of vulnerability to drought. The uniqueness of this study is ascribed to its methodological framework, which integrates a thorough assessment of prior research to inform the assignment of weights to parameters in the fuzzy logic-based index. The findings demonstrate a notable increase in the proportion of Iowa’s land area classified as at a'very high’ drought risk, rising from 0.66% in 2015 to 5.39% in 2018. This upward trend suggests an escalating susceptibility to drought conditions. Mid-Iowa and the western portion of the state exhibited increased ‘high’ and ‘extremely high’ drought threats during the period. The accuracy of our drought susceptibility maps was validated using a Kappa coefficient of 75%. The drought risk indicator has the potential to be utilized in the context of drought mitigation and program monitoring. Moreover, this methodology can be modified for implementation in diverse geographical areas across the globe.