A Dynamic Reservoir Modeling Approach to Assess Water Security under Climatic and Anthropogenic Pressures: Application to the Aburrá Valley, Colombia

Water security in Aburrá Valley, Colombia, relies heavily on the Riogrande II and La Fe reservoirs, which face increasing pressures from climate variability, land use change, and rising demand. Although SWAT+ is a powerful hydrological modeling tool, its reservoir module cannot represent dynamic changes in demand, land use, or external water inflow. To address these limitations, we developed resv_dyn, a Python algorithm that integrates: (i) annual land use changes derived from Dinamica EGO, (ii) progressive demand growth, and (iii) operation with pumped inflows from non-tributary rivers. The validation of resv_dyn was conducted using the Riogrande II Reservoir as a case study, comparing its performance with the SWAT+ reservoir module. The results show that resv_dyn effectively simulates the operational conditions of the reservoir, achieving outcomes comparable to those of SWAT+. Application to La Fe Reservoir under three climate scenarios shows that increased extreme rainfall temporarily boosts natural inflows, but these isolated peaks cannot be effectively stored due to reservoir capacity constraints. As a result, the system remains continuously dependent on pumping, and supply deficits are not substantially reduced. The proposed approach improves the representation of reservoir behaviour and provides a transferable tool for assessing reservoir resilience under combined climatic and anthropogenic pressures.