Discharges and water levels are essential components of river hydrodynamics. In unreachable terrains and ungauged locations, it is quite difficult to measure these parameters due to rugged topography. In the present study an artificial neural network model has been developed for the Ramganga River catchment of the Ganga Basin. The modelled network is trained, validated and tested using daily water flow and level data pertaining to 4 years (2010–2013). The network has been optimized using an enumeration technique and a network topology of 4-10-2 with a learning rate set at 0.06, which was found optimum for predicting discharge and water-level values for the considered river. The mean square error values obtained for discharge and water level for the tested data were found to be 0.046 and 0.012, respectively. Thus, monsoon flow patterns can be estimated with an accuracy of about 93.42%.

There is an urgent need to explore and analyze new aquifer recharge potential zones (ARPZ) in arid regions exposed mainlyto hard rock local aquifers, whether fractured or non-fractured, for investment and fulfillment of the Saudi Vision 2030. Over-pumping, seawater intrusion, climatological changes, population growth, lack of traditional water supplies, expensive desalinized water, and excessive evaporation have characterized the Duba region of Tabuk province of Saudi Arabia (SA). Aquifer productivity and potentiality are affected by surface geology, rainfall, lineament density, drainage density, slope, elevation, soil, and normalized difference vegetation index (NDVI). This study aims to demarcate the ARPZ using integrated remote sensing and geographic information system (GIS) and (RS) approaches. The relative importance of each parameter was determined based on its impact on the aquifer’s potential through the analytical hierarchical process (AHP). The ARPZ zones are categorized into five classes starting from very low to very high potentiality. Southern, western, and northern areas have high to very high aquifer potentiality and recharge. They made up roughly 43% of the area that was examined. About 41.8% of the research area is comprised of low to very low groundwater potentiality, and this potentiality is dispersed over the western and central regions of the region. The medium aquifer potentiality level reflects about 15.2%. The high to very high aquifer potentiality areas coincide with low concentrations of total dissolved solids (TDS), electrical conductivity (EC), and nitrate (NO₃). The outcomes emphasized the decisiveness of the entire study and its applicability to any place with similar groundwater aspirations and management.