<p>Watershed management has become a crucial aspect of planning in response to escalating anthropogenic activities. However, there is still a lack of comprehensive watershed prioritization in Indonesia, especially in research that combines multiple analytical techniques. The main objective of this study is to assess and categorize watershed conservation priorities. This study presents a novel clustering-based integration of geomorphometric, principal component analysis (PCA), and hypsometric analysis as an analytical framework that is infrequently used in watershed research in Indonesia. For ungauged subwatershed prioritization, the approach provides a feasible and reproducible solution by utilizing open-access spatial data (DEMNAS). Geomorphometric analysis involves 15 parameters, resulting 6 significant parameters from PCA by identifying eigenvalues &gt; 1 based on Kaiser criterion as major contributors. On the other hand, hypsometric analysis assesses the area under the curve called as hypsometric integral. Each method generates distinct prioritization outcomes because of different emphasizes. The final prioritization is achieved through K-means clustering derived from the integration of the prior three methods, suggesting that SW 1, SW 2, SW 4, and SW 7 emerge as the highest priority, whereas SW 5, SW 8, and SW 10 are identified as the lowest priority. The findings demonstrate how the entire methods identify upstream subwatersheds as being most susceptible to runoff and erosion. This morphology-based method also provides an advantageous starting point in prioritizing subwatershed conservation for ungauged watersheds where hydrological data are scarce or non-existent. For prospective watershed management initiatives, this study provides a comprehensive and reproducible prioritization strategy.</p> Graphical Abstract <p>The graphical illustrates management priorities identification by categorizing morphological aspects of subwatersheds using geomorphometric analysis, Principal Component Analysis (PCA), and hypsometric analysis. Watershed identification involves using SWAT to define 10 subwatersheds (SW 1–SW 10). Each is represented by areal, relief, and linear parameters. In this step, the basic spatial units for additional analysis are established. The indicators analysis evaluates a number of geomorphometric factors and hypsometric integral. In order to minimize dimensionality and extract important components, the ranking phase includes a number of analytical techniques, such as PCA. Geomorphometric and hypsometric analysis are also ranked for each parameter. This stage makes it possible to systematically rank subwatersheds according to their morphological characteristics. Ultimately, cluster analysis is used to organize subwatersheds into priority classes during the clustering phase. Based on the three aforementioned methods, this categorization takes cluster center distances into account. A spatial map that divides the subwatersheds into cluster membership 1 (high), 2 (medium), and 3 (low) priority classes serves as the end result and serves as the foundation for focused watershed management techniques. </p>