Analisis Ketidakpastian Parameterisasi Penggunaan Lahan dalam Model Invest Water Yield: Tinjauan Sistematis DAS Tropis - SARIF ROBO (Cannarium, 2026)
Land use change (LULC) and climate variability are key factors influencing water availability in watersheds, particularly in tropical regions. The InVEST water yield model has been widely applied to assess water-related ecosystem services; however, it still faces significant challenges related to LULC parameter uncertainty. This study aims to identify patterns of LULC parameterization, analyze the relationship between land use change and water yield, and evaluate sources of uncertainty in the InVEST model. A systematic literature review (SLR) was conducted on 43 peer-reviewed articles indexed in Scopus and Web of Science (Q1–Q2) published between 2015 and 2026. The analysis focused on key biophysical parameters, including crop coefficient (Kc), root depth, plant available water content (PAWC), and the Z parameter, as well as model validation practices. The results indicate that precipitation is the primary driver of water yield, while LULC acts as a spatial modifier through evapotranspiration and infiltration processes. Land use changes such as deforestation and urbanization generally increase water yield, whereas forest cover tends to reduce it due to higher evapotranspiration rates. The variation of LULC parameters across studies reveals substantial inconsistency, representing the main source of model uncertainty. This uncertainty propagates through hydrological processes and significantly affects water yield estimation. Moreover, limited model validation indicates that many results remain conceptual rather than empirically verified. This study concludes that LULC parameterization is a critical factor determining the uncertainty level of the InVEST model. Therefore, locally calibrated parameterization approaches and improved empirical validation are essential to enhance model reliability, particularly in tropical watersheds