Identification of Suitable Managed Aquifer Recharge Sites Using GIS-AHP and Field-Based Evaluation of Aquifer Storage Capacity in Central Kazakhstan

Managed aquifer recharge (MAR) is increasingly being realized as an important approach to improve water security in arid and semi-arid environments where there is a low amount of surface water and high climatic variability. This paper introduces a unified approach to the process of locating appropriate MAR locations and estimating recharge potential in Central Kazakhstan through the multi-criteria analysis using GIS and hydrogeological field exploration, water balance modelling. The suitability testing was preliminarily performed in the Google Earth Engine environment as a weighted overlay test with the combination of terrain, vegetation, hydrological, and land cover parameters. According to the suitability map obtained and patterns of activity in agricultural activities, eleven candidate sites were identified out of which eight were found to be suitable after hydrochemical analysis. The Nesterov and Boldyrev techniques of field-based infiltration tests, produced a range of 0.05 to 1.42 m/day of hydraulic conductivity. Water balance analysis shows that the total amount of water that could be recharged into the suitable sites is about 40.2 million m³/year and that the effective amount of water could be recharged is about 11.0 million m³/year, which is limited by the infiltration processes. This means that about 27 percent of the available water is added into ground water recharge which is a significant boost to the original estimates. The assessment of the storage capacity of the aquifers indicates that at all locations, the pore space is much greater than the recharge volumes that have been calculated and, therefore, storage is not a limiting factor in the implementation of MAR. It is estimated that there are recharge rates of between 174 and 5,282 m³/day, with a high degree of spatial variability which is caused by local hydrogeological circumstances. The suggested method offers a powerful and generalizable site selection and measurement framework of MAR in arid areas with limited data. The findings highlight the significance of combining remote sensing, field measurements, and process-based modeling to aid sustainable groundwater management and climate adaptation strategies.