This research addresses the critical need to assess surface water dynamics in semi-arid regions of Andhra Pradesh, India, by using advanced Spectral Indices for hydrological applications and methodologies. It aims to answer how remote sensing data from Landsat 8 OLI/TIRS can be effectively used to monitor and classify surface water bodies. The study applies indices such as Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Normalized Difference Thermal Index (NDTI), and Water Ratio Index (WRI). Additionally, the Weighted Composite Index (WCI) and Normalized Composite Index (NCI) are integrated with Principal Component Analysis (PCA) for multi-criteria decision making. The HYDROSAM model successfully classifies and maps various categories of surface water bodies, including non-water features (53.62%), urban water zones (37.89%), seasonal water bodies (4.32%), transitional zones (2.17%), permanent water bodies (1.05%), and river bodies (0.95%). The resultant map was validated using the AUC-ROC curve, achieving an AUC of 0.820, indicating a high level of accuracy. This methodology provides a nuanced understanding of water resource distribution and availability in the region. The findings demonstrate the robustness and reliability of the HYDROSAM model in accurately assessing surface water characteristics, thereby providing critical insights for informed water resource management, strategic land-use planning, and effective ecological conservation. This innovative methodology not only fosters sustainable water resource management in semi-arid regions but also sets a precedent for advancing research in similar ecosystems globally.