Validation of Satellite-Based Rainfall Estimates and Environmental Variables for Developing a Flood Vulnerability Index in Surakarta, Indonesia

This research focuses on the verification of rainfall estimation data from satellites CHIRPS and TRMM in relation to mapping flood-prone areas in Surakarta City, Indonesia. Validation was conducted by evaluating satellite data with rainfall records from monitoring stations and calculating their Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Correlation Coefficient (CC). The findings suggest that CHIRPS exhibited more accurate results than TRMM, as evidenced by the higher correlation values obtained and the lower error rates. Flood-prone areas were defined through spatial analysis making use of GIS, including all relevant criteria such as annual rainfall, altitude, land use, soil classification, and river distance. A weighted overlay analysis was performed whereby each region was classified according to susceptibility to flooding into one of the following grades of low, moderate, high, and very high. The flood vulnerability map was subsequently validated against historical flood event data whereby 97% of recorded flood events occurred within areas rated vulnerable by the model, thereby validating the credibility and robustness of the model. Information thus generated is pertinent for risk-sensitive urban planning policies and infrastructure development within the context of Surakarta City and for the optimization of disaster risk reduction actions.