Flash floods are highly destructive natural disasters, particularly in arid and semi-arid regions like Egypt, where data scarcity poses significant challenges for analysis. This study focuses on the Wadi Al-Barud basin in Egypt's Central Eastern Desert (CED), where a severe flash flood occurred on 26-27 October 2016. This flash flood event, characterized by moderate rainfall (16.4 mm/day) and a total volume of 8.85 x 106 m3, caused minor infrastructure damage, with 78.4% of the rainfall occurring within 6 h. A significant portion of floodwaters was stored in dam reservoirs, reducing downstream impacts. Multi-source data, including Landsat 8 OLI imagery, ALOS-PALSAR radar data, Global Precipitation Measurements-Integrated Multi-satellite Retrievals for Final Run (GPM-FR) precipitation data, geologic maps, field measurements, and Triangulated Irregular Networks (TINs), were integrated to analyze the flash flood event. The Soil Conservation Service Curve Number (SCS-CN) method integrated with several hydrologic models, including the Hydrologic Modelling System (HEC-HMS), Soil and Water Assessment Tool (SWAT), and European Hydrological System Model (MIKE-SHE), was applied to evaluate flood forecasting, watershed management, and runoff estimation, with results cross-validated using TIN-derived DEMs, field measurements, and Landsat 8 imagery. The SCS-CN method proved effective, with percentage differences of 5.4% and 11.7% for reservoirs 1 and 3, respectively. High-resolution GPM-FR rainfall data and ALOS-derived soil texture mapping were particularly valuable for flash flood analysis in data-scarce regions. The study concluded that the existing protection plan is sufficient for 25- and 50-year return periods but inadequate for 100-year events, especially under climate change. Recommendations include constructing additional reservoirs (0.25 x 106 m3 and 1 x 106 m3) along Wadi Kahlah and Al-Barud Delta, reinforcing the Safaga-Qena highway, and building protective barriers to divert floodwaters. The methodology is applicable to similar flash flood events globally, and advancements in geomatics and datasets will enhance future flood prediction and management.

This study aims to investigate the quantitative relationship between resistivity and the physical and mechanical properties of soil in different types of herbaceous slopes in the alpine arid and semi-arid loess area. The research is conducted in the self-built test area of Changlinggou Basin in Xining Basin. Five types of slopes, including Elymus nutans Griseb., Elymus sibiricus Linn., Agropyron trachycaulum Linn. Gaertn., Festuca arundinacea Schreb., and bare slopes are selected as the research objects. These slopes have been planted for 3 years. The study compares the effects of different herbaceous roots on the physical and mechanical properties of the soil by conducting tests of soil density and water content, and direct shear test on the soils with and without root systems. Based on these tests, a quantitative relationship between the physical and mechanical properties of different slope soils and resistivity data is established using 2D electrical resistivity tomography. The results show that: (1) Compared with the bare slope without planting, the maximum increase of soil moisture content in the upper layer (0-10 cm) of the Elymus sibiricus Linn. slope is 26.53%. The average soil density of the upper layer (0-10 cm) of the Festuca arundinacea Schreb. slope was 18.30% lower than that of the bare slope. The maximum added value of soil cohesion in the upper layer (0-10 cm) of the Elymus nutans Griseb. slope is 2.75 times that of the bare slope. (2) The resistivity characteristics of five types of slopes are affected by root distribution and slope position factors, and the resistivity value decreases with the increase of depth. The soil resistivity value of the four herbaceous slopes is larger than that of the bare slope at 0-20 cm, which is the approximately range of root distribution. (3) There are fitting equations between the physical and mechanical properties and resistivity data of five kinds of slope soils (with correlation coefficients R-2 ranging from 0.48 to 0.77), and the Pearson correlation analysis shows that the cohesion c value of the slope soil has the highest correlation with resistivity, with an R-2 value of 0.765. The results of this study demonstrate that 2D resistivity tomography technology can reflect the physical and mechanical properties of slope soil, as well as the distribution characteristics of plant roots. This provides a theoretical basis and practical guidance for effectively preventing and controlling soil erosion, shallow landslides, and other disasters in the study area and its surrounding areas.