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This study examines seawater intrusion in the southern part of Kebumen District, focusing on the impact of various geological formations on groundwater salinity. Groundwater samples were systematically collected from 11 locations representing alluvial, volcanic, coastal sediment, and karst geological conditions. The samples were analyzed for major ions, including calcium (Ca2+), magnesium (Mg2+), chloride (Cl-), and bicarbonate (HCO3-), as well as Total Dissolved Solids (TDS). Ion ratios such as Mg2+/Ca2+, Cl-/HCO3-, and Mg2+/(Mg2++Ca2+), along with the Fraction of Seawater (fsea), were calculated to assess the extent of seawater intrusion. The study employed the Gibbs diagram method to identify the primary processes controlling groundwater chemistry, revealing that water-rock interactions are dominant in most samples, particularly in those affected by seawater intrusion. The results indicate significant seawater intrusion in alluvial and karst regions, especially at sampling points TP 2, TP 4, and TP 10, while volcanic and coastal sediment areas show minimal intrusion. These findings underscore the critical influence of geological conditions on seawater intrusion and highlight the need for targeted groundwater management strategies. Further research focusing on long-term monitoring is recommended to better understand and mitigate the impacts of seawater intrusion in this region. [ABSTRACT FROM AUTHOR]

Flood is one of the most frequent hydrometeorological disasters which leads in economic losses. The first step in flood disaster mitigation efforts is mapping vulnerable areas. Kencong District frequently affected by the annual flooding event. This study aims to assess flood hazard mapping by integrating the AHP method and Geographic Information System. This study used a descriptive quantitative approach through the correlation matrix of the AHP model for each physical environmental factor. These factors include slope, altitude, distance from the river, soil type, Topographic Wetness Index (TWI), and Curvature. Furthermore, with the Geographic Information System (GIS), the weighted overlay stage was carried out to obtain the results of flood-prone areas. Based on the AHP analysis, the most significant factors in determining flood-prone areas were the distance from rivers, slopes, and TWI. The results of flood-prone areas mapping were divided into five classes: from deficient 0.02%, low 4.26%, medium 37.11%, high 51.89%, and very high 6.72%. Validation of GIS mapping results with data in the field has an AUC value of 84%, which indicates that the prediction of the AHP-GIS model is perfect in flood-prone areas mapping in the Kencong District. The integration of AHP method and Geographic Information System in flood hazard assessment were able to produce a model to evaluate the spatial distribution of flood-prone areas. [ABSTRACT FROM AUTHOR]