Soil moisture content is a crucial factor in hydrological studies as it helps to determine the rainfall and runoff response in the catchment. Land use, particularly cropping, can have a significant effect on soil moisture content. Hilly topography with karst features is more prone to flooding and soil erosion due to its low water holding capacity. Remote sensing technology has recently been applied to agriculture and disaster management. The aim of this research is to identify soil moisture characteristics in karst formations for runoff estimation using remotely sensed imagery from Sentinel-1. Soil moisture is calculated using the Topp model equation based on the soil dielectric value obtained from the Dubois model. By using different types of land use and soil moisture data from Sentinel-1, CN values can be generated and then used to estimate runoff. The results of the study show that extracting soil moisture information from Sentinel-1A with VV polarisation for karst areas is still challenging due to the high bias. The Sentinel-1 satellite soil moisture products could provide a real-time CN value that can be integrated with the rainfall runoff model. This research highlights the importance of monitoring soil moisture to determine CN values for flood mitigation.