Effective groundwater management is crucial under the current climatic conditions, addressing both qualitative and quantitative aspects. An important step in delineating groundwater potential zones involves remote sensing (RS) data and geographic information systems (GISs), facilitating resource assessment, and the implementation of suitable field data management. This study introduces the delineation of potential groundwater zones using seven layers and the Multi-Criteria Decision Analysis (MCDA) method. Satty’s Analytic Hierarchy Process (AHP) was employed to rank the seven selected parameters, contributing to the advancement of groundwater research and resource assessment. All seven thematic layers (Rainfall, Geology, Land Use/Land Cover, Drainage Density, Elevation, Slope, and Soil) were prepared and analyzed to delineate groundwater potential zones. The resulting groundwater potential zone map was categorized into four classes, Very Good, Good, Moderate, and Poor, covering areas of 81.53 km² (45.1%), 56.36 km² (31.2%), 19.54 km² (10.8%), and 23.17 km² (12.8%) of the total area, respectively. The accuracy of the output was validated by comparing it with information on groundwater prospects in the area, and the overall accuracy of the method was approximately 72%. High-yield boreholes were drilled and concentrated in the Very Good groundwater potential zones, while low-yield ones were developed in the Poor areas.

Hydraulic conductivity (K) is essential for understanding groundwater movement in shallow alluvial aquifers. Upstream of the Siret–Moldova confluence, Romania, this parameter is poorly constrained, because available K values come from only 34 wells reported in existing hydrogeological documentation. This study provides the first directional geostatistical characterization of K in this shallow alluvial aquifer and evaluates the spatial reliability of the mapped zones. K values ranged from 9.96 to 171.73 m/day. Because the raw data were positively skewed, the values were log-transformed before geostatistical modelling. Spatial continuity and anisotropy were examined using omnidirectional and directional semivariograms. Three theoretical models were tested—Spherical, Gaussian and Exponential—and their performance was compared using cross-validation statistics and prediction standard-error maps. The Gaussian and Spherical models showed comparable performance; however, the Gaussian model was retained because it produced marginally lower errors and a smoother spatial pattern (ME = 0.0055, RMSE = 0.4870, RMSSE = 0.8697, R² = 0.6712). The back-transformed K map shows three main zones: lower values in the northern and eastern sectors, intermediate values in the central sector, and the highest values toward the west. This pattern is consistent with coarser Moldova River alluvial deposits in the west and more heterogeneous lithological conditions in the central area. The prediction standard-error maps indicate the areas where the interpolated hydraulic conductivity (K) is more reliably constrained. The resulting map provides a preliminary spatial representation of the main hydraulic-conductivity zones and indicates where additional K measurements are needed before detailed groundwater-flow modelling or local groundwater-resource assessment.

The paper examines groundwater from the area between the Siret and Moldova rivers. Data from 2021 and 2022 were used, taken from twelve monitoring wells. The main ions (Ca2+, Mg2+, Na+, K+, HCO3−, Cl-, SO42−, NO3−) were checked with basic statistics, boxplots and the Piper and Schoeller-Berkaloff diagrams. The ion values from the two years stay close. The higher ones appear only in a few wells, and those places have local factors that influence the water. The meq·L-1 values also fall in the same range in both years. Ca2+ and HCO3−, remain dominant in all samples. The two diagrams place the water in the Ca–HCO3 field, with no major change from one year to the next. There is no sign of a larger chemical shift in the aquifer, and the small differences stay local. The data show a stable aquifer, and these values can help when the area is checked again in the future.