Comparative Analysis of SWAT and HEC-HMS Models for Efficient Watershed Management

Objective: This study aims to review and compare the effectiveness of the SWAT (Soil and Water Assessment Tool) and HEC-HMS (Hydrologic Engineering Center’s Hydrologic Modeling System) models in different watershed contexts, aiming to identify the conditions under which each model performs best for sustainable water resource management. Theoretical Framework: The research is based on concepts of sustainable watershed planning and water resource management. The SWAT and HEC-HMS models are widely recognized in the literature for their robustness and applicability in hydrological simulations, commonly used for surface runoff predictions and environmental risk assessment, particularly in heterogeneous watersheds. Method: A literature review was conducted, focusing on studies published from 2019 onward that directly compared the two models. The selection of papers followed rigorous criteria of contemporaneity, methodological quality, and application in different geographical and climatic contexts. The results of these studies were analyzed and discussed comparatively. Results and Discussion: The results indicate that SWAT excels in simulating high flows and in contexts of high hydrological variability, such as in mountainous regions and humid tropical watersheds. On the other hand, HEC-HMS showed better performance in simulating low flows, particularly in scenarios with limited data availability. The discussion addresses the implications of these results for watershed management and the challenges of selecting the ideal model. Research Implications: This research provides valuable insights for watershed management, highlighting the practical implications of each model in flow prediction and disaster mitigation, such as floods and droughts. Originality/Value: The study contributes to the literature by providing a comparative analysis of the SWAT and HEC-HMS models in various environmental contexts. It reinforces the importance of selecting the most suitable model for each hydrological context.