## 6 Concluding Remarks
The inconsistencies between the satellite-derived products and the in-situ measurements underline the necessity for improving future versions of IMERG algorithms, by taking into account variations in meteorology and geography, especially in semi-arid areas of the globe. The need is for more efficient physically-based algorithms, based on a comparison with surface observations across all major precipitating synoptic conditions. Most of the arid regions feature a very limited number of rain gauges, thus, reducing the reliability of the results produced. The study for the upgrade of the existing network, which is under preparation will put forward a series of steps for overcoming the issue of data scarcity. Once resolved, this could then promote the greatly needed hydrological studies on topics, such as the spatiotemporal distribution of rainfall, the mitigation of flash floods hazards, and the minimization of soil erosion. The study site contains only five rain gauges. This small number of in-situ instrumentation is an obstacle to the optimum understanding of the rainfall frequency and rain rates as well as the possible recharge options. Therefore, the second part of the study will suggest the most suitable sites for 31 new rain gauges. These new stations will provide the most efficient and appropriate coverage. In the upcoming study for a proposed, upgraded network of stations, a Digital Elevation Model and IMERG data will be used to identify the most suitable locations. These two datasets will be clustered using a k-means clustering to produce an elbow graph whose elbow-shaped region offers several possible options for the number of optimum clusters at the test site. Three different cluster sizes (namely, 3, 6, and 9) will be used to calculate the possible centroids for each size. These centroids will be tested using the Empirical Cumulative Distribution Function (ECDF), once the sum of the IMERG scenes, the scene limits, and the elevation map limits are determined. At this stage, the optimal size established is nine. Nine centroids are, therefore, taken, along with the existing five gauges, as a basis for standard error kriging. This allows a gradual minimization of the error via looping. The proposed rain gauge sites will be tested with an ECDF. The complete spectrum of rainfall and elevation is efficiently covered by 31 new rain gauge locations, and the five existing gauges. Lastly, the present study lays the foundations for further meteorological and hydrological studies at the test site. The results statistically affirm the superior performance of the IMERG dataset compared to the TMPA data typically used at the test site. Therefore, IMERG data is recommended for the optimization of a new, expanded rain gauge network with additional gauges steered by the local topography of the site. Taken together, this can promote the transformation of the study site from a dormant to a commercially active state. **Author Contributions:** All authors contributed to the paper, as follows. Conceptualization: M.M. and P.D. Methodology, investigation and analysis: M.M. Resources: M.M. and Y.S. Writing, review, and editing: M.M. and S.M. Visualization: M.M., F.D., T.S., E.B., Y.S., and S.M. Supervision: P.D. and T.S. Project administration: P.D. and T.S. All authors have read and agreed to the published version of the manuscript. **Funding:** This research received no external funding. **Acknowledgments:** This work was supported by the Helmholtz Center for Environmental Research in Leipzig, Germany, the Tubingen University, Germany, and the Suez Canal University, Egypt. The authors wish to acknowledge that the provision of the TMPA and IMERG data by the NASA/Goddard Space Flight Center's Mesoscale Atmospheric Processes Laboratory and Precipitation Processing Center, which developed and computed them as a contribution to TRMM and GPM, respectively.