Groundwater depletion is one of the most critical concerns for users and policymakers. Identifying groundwater potential (low to high) helps properly plan the available groundwater resource. This study has used the possibilities of a geographical information system (GIS), remote sensing and, of course, field data to delineate the groundwater potential zones in the Chennai River Basin (CRB). Thematic layers generated for eleven controlling factors, such as geology, water level, drainage, soil, lineament, rainfall, land use, slope, aspect, geomorphology, and depth to bedrock, were brought into the GIS environment. Then, appropriate weightage was given to each layer using a multi-criteria decision-making technique, namely, the analytic hierarchical process (AHP). A groundwater potential map is generated using weighted overlay analysis, with the following five classes: very poor, poor, moderate, good, and very good. The results were comparable to the actual specific yield data from the field and accuracy was 78.43%. Thus, AHP-aided GIS–RS mapping is a useful tool in groundwater prospecting in this region of the world.

Groundwater recharge estimation is essential for sustainable water management and water supply schemes. In this paper, we review groundwater recharge estimation techniques and identify the appropriate methods by considering India’s hydrological and climatic conditions. Significant components of recharge, factors affecting groundwater recharge, aquifer systems of India, and historical groundwater recharge estimation practices are reviewed. Currently used recharge estimation methods are assessed based on case studies. The most popular estimation methods are studied and compared based on their application in various regions. It is observed that the accuracy of the recharge estimates is largely influenced by false assumptions, the possibility of erroneous measurements, a potential lack of reliable data, and a variety of problems associated with parameter estimation. The suitability of different methods for a region is found to depend on time and space considerations, the objective of the study, hydrogeological condition, and availability of data. In Indian conditions, it is suggested to use water table fluctuation and water balance methods for the recharge estimation, provided that accurate water level measurements are assured.

A flash flood is one of the hazardous phenomena, especially in dry regions. In Saudi Arabia, Jazan Province experiences data scarcity especially historical hydrological data and a lack of studies related to flash flood analysis and the rainfall and runoff interrelationship. Thus, this research aims to study the rainfall-runoff inter-relation, predict flash floods, and to map the risk areas in Jazan Province by the geological, geomorphological, and hydrogeological characteristics along with digital elevation model (DEM), watershed modeling system (WMS) and HEC-HMS models. Jazan Province encompasses 25 drainage basins, receiving a considerable amount of rainfall (ranging from 100 to 500 mm) (August, October-November, March) which intermittently cause strong and destructive flash floods. The DEM was used for delineating the catchment (drainage basins) parameters. Physiographic parameters of the catchments have been analyzed for mapping the hazard degree of the flash flood strength. Further, basins with high hazard degrees of flash floods were selected to assess rainfall-runoff inter-relation using the HEC-HMS models, GIS, and morphometric parameters. Forty %, 8%, 52% of the study area are high, medium, and low hazard degrees of flash floods, respectively. The groundwater recharge in the study area was calculated through the integration of satellite image analysis, SWAT and GIS techniques and it ranges from 0.002 mm/km²/year to 8 mm/km²/year with an average of 2.5 mm/km²/year. Rainfall-runoff inter-relation of study basins, assessed based on the integration of WMS and HEC-HMS models, indicates that the resulting runoff volume ranges from 18.5 × 10⁶ m³ to 473.1 × 10⁶ m³ at a recurrence period of 5 and 100 years at rainfall events of 65 mm and 116.8 mm, respectively.

Accurate estimation of water balance components of groundwater-fed lakes, including subsurface inflow and actual evaporation from lakes, is a complex task for hydrologists employing hydrological models. In this study, an approach that integrates isotope analysis and hydrological modeling is used to improve the representation of groundwater–surface water interactions. While based on 1 year of sampling, this method provides direct observational data to complement hydrological models and serves as a validation tool for water balance estimates. The approach, based on measurements of stable isotopes (oxygen-18: ¹⁸O; deuterium: ²H), enables quantitative estimation of the individual water flux and evapotranspiration rates. An isotope-mass-balance model was used to quantify lake water balances over a 1-year sampling period. The approach is based on the global relationship between the δ¹⁸O and δ²H values in the precipitation and kinetic isotopic fractionation in the lake water during evaporation. Assuming that the lake is hydraulically connected to the groundwater, the isotope mass-balance model accounts for the quantification of the evaporation rate considering the groundwater inflow compensating for the evaporation loss. The study addresses the model-based quantification of groundwater inflow and evaporation losses of a young glacial groundwater lake (Lake Groß Glienicke (GGS), southwest of Berlin in the Havel catchment) over the period from 2015 to 2023 with the integrated HydroGeoSphere (HGS) hydrological model. Utilizing the isotopic mass balance model, HydroCalculator, under steady-state hydrological regime conditions, the evaporation-to-inflow ($E/I$ ) ratio is determined for the period of 1 year from August 2022 to September 2023. Employing the fully integrated hydrological model, calibrated and validated under monthly normal transient flow conditions from 2008 to 2023 for the lake catchment, subsurface and groundwater inflows to the lake are calculated and compared to the calculated $E/I$ ratios based on the isotopic measurement of the lake water. Isotopic signatures confirm the lake's flow-through conditions. The calculated $E/I$ ratio for GGS is around 40 %. The calculated evaporation for the years 2022 and 2023, within the isotopic mass balance model framework, aligns well with the evaporation from the lake calculated by the HGS model. The change in $E/I$ leads to a significantly improved estimation of evaporation rates after correction for temperature fluctuations and inflow data from previous years (2015–2021). With a correlation coefficient of 0.81, these revised values show a high degree of agreement with the evaporation rates predicted by the HGS model for the corresponding years. Despite the uncertainties associated with the analysis of the water isotope signature, its integration into the hydrological model serves as a validation of the hydrological model calculations of the water balance components.