The Effect of Rainfall-Runoff Characteristics on the Economic Loss from Flooding Using the ECLAC Method

Abstract

This study develops an integrated flood-inundation simulation using the Storm Water Management Model (SWMM), the Hydrologic Engineering Center’s River Analysis System (HEC-RAS), and ArcGIS, and estimates flood-related economic losses using the Economic Commission for Latin America and the Caribbean’s (ECLAC) Damage and Loss Assessment (DaLA) approach. The study was conducted in the Gajah Putih Watershed, Surakarta City, Central Java, Indonesia. The methodology combines rainfall-runoff modeling, hydraulic inundation mapping, GIS-based exposure analysis, and household survey data collected via questionnaires and interviews. Input data include rainfall records from the Ngemplak and PSDA B. Solo stations, LiDAR data, Sentinel-2A imagery, land-cover maps, and anonymous household survey data. The hydrological analysis shows that the Curve Number (CN) increased from 60.34 in 2016 to 65.73 in 2023, indicating a shift toward more impervious land cover. Drainage basin (DAD)-level validation against questionnaire-based observations of flood exposure yielded a mean absolute percentage error (MAPE) of 4.28%, indicating acceptable spatial agreement between the simulation and aggregated field evidence. The ECLAC/DaLA valuation indicates that the Q50 flood scenario produced total economic losses of IDR 13.04 billion, with the residential sector experiencing the greatest impact from physical asset damage and income disruption. The findings show that urbanization increases the potential for surface runoff and economic exposure. The resulting inundation and economic loss maps can support the prioritization of flood mitigation and drainage infrastructure investments in the study area.