The construction of the Keuliling Reservoir aims to accommodate and utilise water for agricultural purposes. In this research, soil erosion modelling using the USLE method showed that the level of erosion hazard for each Keuliling Reservoir sub-watershed was classified into low-moderate. Land erosion occurred in the area around the reservoir inundation is the most significant contribution to the magnitude of erosion (38.62Mg∙ha-1y-1. Based on the point of sediment sampling in the Keuliling reservoir, the sediment volume was 1.43 Mg∙m-3. So, the volumetric sediment input from the Keuliling reservoir watershed is 20.918,32 m3∙y-1. The degradation of reservoir function due to sedimentation can affect reservoir services. The ability to estimate the rate of watershed surface erosion and sediment deposition in the reservoir is vital for reservoir sustainability. Besides the land erosion in the Keuliling Reservoir, there are also other potential sources of erosion that can reduce the capacity of the reservoir, i.e. the rate of sedimentation from a reservoir cliff landslide. The USLE estimation results show that the soil erosion analysis provides important and systematic information about nature, intensity and spatial distribution in the watershed and sediment volume in the Keuliling Reservoir. This finding allows the identification of the most vulnerable areas and the type of erosion dominant for long-term land management.
Flood with intense rainfall and inadequate drainage system leads to flood inundation in residential areas, which in turn damages the housing components and causes a loss. The different level of flood inundation at various affected locations caused varying degrees of losses. This study aimed to identify the damage conditions and analysed the physical loss of the residential building components. The physical vulnerability level is influenced by two damage qualification: the structural and architectural damages. The third-order polynomial function approach produces the best model for both qualifications, yielding the smallest average of errors (RMSE) of 0.0187 for the structural quality and 0.0672 for the architectural quality. The amount of losses related to the architectural elements of the house is smaller compared to the structural one as it is not its main component. This approach is useful as a guide in determining the post-flood handling rehabilitation cost of both structural and architectural elements that will be more appropriate for future conditions. This information is essential as effective management to design flood disaster mitigation strategies and may serve as a basis for flood risk management.
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