The Socio-Economic Asymmetry Index (SEA): A Framework for Identifying Vulnerability–Exposure Mismatch in Flood-Prone Agricultural Landscapes

Flood risk studies in Southeast Asia often treat physical exposure and socio-economic vulnerability as separate issues. That approach misses something important: in many places, socio-economic factors matter more than physical exposure in deciding who gets hit hardest. This study introduces the Socio-Economic Asymmetry Index (SEA), a ratio-based tool designed to measure how much socio-economic vulnerability outweighs physical exposure. The framework was tested across 63,010 sampling points in the Upper Chi River Basin, northeastern Thailand. Six composite indices were built from satellite and land-use data: the Net Economic Loss Index (NELI), Income Loss Sensitivity Index (ILSI), Adaptation Cost Index (ACI), Community Economic Resilience Index (CERI), Maladaptive Development Risk Index (MDRI), and Composite Risk Index (CRI). Random Forest and SHAP analyses were then used to see how each component shaped flood outcomes. Results show that about 25% of the study area falls into High or Very High Asymmetry, with SEA values above 0.478. ACI had the strongest positive correlation with SEA (r = 0.808), followed by NELI (r = 0.788) and flood frequency (r = 0.786), while CERI showed a strong negative correlation (r = −0.707). This suggests that community resilience does help buffer socio-economic asymmetry. Using flood frequency as an external target, an SEA greater than 0.608 emerged as the best cutoff point (AUC = 0.988, sensitivity = 0.972, specificity = 0.962). K-means clustering identified four community types: High Asymmetry (9.5%), Moderate Asymmetry (37.4%), Low Asymmetry (16.2%), and Resilient (36.8%). Each type needs its own management strategy. The SEA framework offers a practical way to direct socio-economic interventions in flood-prone areas, supporting SDGs 11, 13, and 15.