Remote sensing applications in water resources management are becoming an essential asset in all different levels of integrated water rational use. Due to remote sensing data availability and different acquisition sensors of satellite images, a wide variability of benchmarks could be conducted under the same theme. Rainwater harvesting is the branch of science where the rainwater is the main target to improve groundwater recharge, stratocumulus clouds are the main source of rain in arid regions. Cloud detection using remote sensing techniques proved to be efficient recently but the general uses of different cloud detection techniques are to precisely omit clouds from satellite images. The use of cloud detection scheme described herein is designed for the MERIS Level1B data; therefore, total set of 60 MERIS images was collected on monthly basis for 5 years started from January 2008. The use of the cloud detection algorithm is to find proper land cover suitable for rainwater harvesting mostly covered with cloud all over the year. Evaluation of land use for rainwater harvesting in terms of groundwater recharge is considered, several factors were taken into consideration and NDWI is one of the most important factors involved. Results pointed out that some regions in southern Saudi Arabia are qualified enough to be considered as potential sites for better rainwater harvesting.