This study aims to assess hydrological degradation prone zones (HDPZs) in the semiarid Tungabhadra River (TBR) Basin through integrating geospatial data and advanced statistical techniques. The novelty of this research lies in the application of Principal Component Analysis (PCA) to combine diverse datasets, including spectral indices (NDVI, SAVI, NDWI, NDSI, BSI, WRI), geological features, geomorphology, and hydrological parameters, for a comprehensive spatial assessment. High-resolution satellite imagery, terrain data, and field-based observations derived key environmental indices. These datasets were standardized and analyzed through PCA to identify significant contributors to hydrological degradation and to map priority zones for management interventions. The results identified five distinct HDPZ categories: Highly Safe (14.67 %), Safe (28.83 %), Moderate (30.65 %), Degraded (20.70 %), and Highly Degraded (5.14 %), with spatial patterns influenced by geological, hydrological, and anthropogenic factors. The PCA analysis highlighted the dominant role of vegetation health, soil salinity, drainage density, and lineament density in driving degradation. The model's validity was confirmed through the AUC-ROC curve, yielding an AUC value of 0.841, indicating the high accuracy and reliability of the PCA-based classification. These findings offer valuable insights into the spatial prioritization of conservation efforts and sustainable water resource management in semiarid regions. This study demonstrates the potential of integrated geospatial approaches to address environmental degradation and provides a replicable methodology for similar vulnerable basins. By integrating scientific Analysis with practical applications, this research contributes to effective land, water, and environmental management, emphasizing the need for adaptive strategies in response to climatic and anthropogenic pressures.