The water scarcity problem can be generated, in many cases, as a result of undesirable intensity and distribution of rainfall patterns. Water scarcity is a common dilemma that faces arid and semi-arid regions (ASARs). In most ASARs around the world, farmers, especially those who rely on rainfed agriculture for their livelihood, are suffering from unstable climatic conditions. For instance, timing and distribution of rainfall, especially during dry periods. The noticeable increase in population coupled with decreased and erratic rains made it challenging to reduce the poverty rate in Sub-Saharan Africa. Furthermore, inefficient water management is considered to be one of the main reasons for the constancy of food insecurity in this area. This highlights the necessity to work on enhancing water availability levels and managing water resources more sustainably. Rainwater harvesting (RWH) is considered to be a potential option to increase water availability and improve food security. In many ASARs and water shortage areas, RWH is found to be an efficient approach to increase crop productivity, and guarantee agricultural sustainability. Moreover, it can help in mitigating the undesirable and negative impacts of change in rainfall patterns, spatially and temporally, which can result in forms of floods, drought, and landslides. Identifying suitable sites for RWH potentiality and proper RWH structures is crucial for the successful application of RWH. The Suitable RWH sites are determined by many biophysical and socio-economic criteria based on the targeted goals of the application. The lack of reliable ground data in developing countries is one of the main challenges for the successful implementation of RWH applications. Advanced technologies, such as Remote Sensing (RS) and satellite images (SI) offer an opportunity for a new data source to be used for RWH. Especially that data generated from these technologies offer many advantages such as good spatial coverage and diverse temporal resolutions. In addition, many of these datasets are easily and freely accessible. The integration of RS data, Geographic Information System (GIS), and other examples of open-access programs to apply and enhance the RWH system successfully and efficiently for different aspects focusing on the Blue Nile Basin (BNB) is addressed in the current research. This research aimed to study the RWH potentiality and identify suitable RWH sites in the BNB. The Multi-Criteria Analysis (MCA) approach was used to define potential sites for RWH. Furthermore, the Curve Number method (SCS-CN) was utilized to estimate the potential runoff in the BNB. This method is confirmed to be an efficient approach for easier handling of multiple data for large catchment areas and an approach that can help in saving the time required for detailed investigations. Considering the BNB as a research study area, the currentreˇ search focuses on multiple spatial scales, starting from a large scale, i.e., river basin, to a small scale i.e., Hafier located in Blue Nile State in Southern Sudan as an example of RWH applications. Results of this study emphasize the usefulness of RS and GIS using the MCA approach in defining suitable sites for RWH in large areas with the advantages of saving time and costs. This research has provided key knowledge regarding the application of open-access data and public domain products in RWH studies. Moreover, the research highlights the importance of ground data for result validation.weiterlesen