The Cost of Bad Timing: How Phenology and Frequency Determine Agricultural Flood Risk.

Abstract

Accurate valuation of flood risk is fundamental to efficient resource allocation, insurance pricing, and public investment in agriculture. Standard economic models, which often link asset damage directly to hazard magnitude, fail to capture the unique vulnerability of agricultural capital-where the value of standing crops is contingent upon phenological stage. This study develops a capital valuation framework to deconstruct the economic burden of flooding on cropland, demonstrating that the timing of a flood is a primary determinant of financial loss, often outweighing the role of physical flood magnitude. We model agricultural flood risk as expected annual damage (EAD) to crop capital, integrating hydrologic frequency analysis for a U.S. Midwest County with a phenologically-explicit damage function. This function disaggregates risk into two components: a Flood Hazard Index (FHI), quantifying flood intensity and duration across return periods, and a Flood Susceptibility Index (FSI), representing the time-sensitive depreciation rate of crop capital at different growth stages. Probability-weighted losses are summed across all flood scenarios to derive total EAD. Results reveal that the distribution of losses is heavily skewed toward high-probability, low-severity events. The 2-year and 25-year floods collectively account for approximately 45% of total EAD, despite extreme (≥ 100-year) events generating substantially larger per-event losses. Frequent floods impose the highest economic cost not because of peak discharge, but because their high likelihood of coinciding with phenologically sensitive periods is compounded by longer inundation durations-a "double liability" where occurrence probability and capital impairment duration are simultaneously maximized. Conversely, low-probability, high-severity events tend to occur outside the growing season, leaving lower-value capital exposed. These findings invert conventional risk models and carry significant implications for crop insurance design, flood mitigation investment, and agricultural capital management under climate volatility.

Supplementary information: The online version contains supplementary material available at 10.1007/s11269-026-04801-1.