Groundwater storage is influenced by many geo-environmental factors. Most of these factors are prepared in the form categorical data. The present study utilized raster satellite data instead and a Random Forest machine learning model to identify groundwater potential zones at downstream parts Wadi Yalamlam, western Saudi Arabia. Eighteen groundwater-influenced variables continuous format from A...

The eastern region of Morocco is characterized by an arid to semi-arid climate. It often confronted with heavy rainfall episodes that can generate floods cause adverse human and property damage. This work studies hydrological risk in the SidiBoulenouar area (Oujda province) model map areas. method used determine watersheds their watercourses, then calculate flows mathematical formulas. Topograp...

In this work, we tested different combinations of sampling strategies, random and conditioned Latin Hypercube (cLHS)] sample ratios (10% = 147 25% 368) to predict soil phosphorus potassium contents, previously estimated using standard laboratory protocols. Other environmental covariates, used as input data for prediction, were obtained from sources (multispectral Landsat-OLI 8 image, WorldClim ...

a r t i c l e i n f o The rapid expansion of high-spatial resolution optical sensors and imagery over the last decade presents exceptional opportunities for quantifying visible attributes of geomorphic systems. In this study, we detail a simple, robust methodology (ChanGeom) to extract continuous channel width and centerline datasets for single-thread channels using freely available high-spatia...