Optimizing performance assessment of multi-reservoir operations for sustainable water management in a semi-arid region

Abstract

Global challenges, such as population growth, rapid urbanization, and the impacts of climate change, are creating unprecedented demands on water resources in semi-arid regions. Meeting the surging needs for irrigation and water supply requires a departure from the limitations of single reservoir systems. Instead, the construction of multi-reservoir systems within semi-arid river basins is imperative. The research employs an integrated reservoir operation approach that facilitates the controlled release of surplus water from upstream reservoirs to downstream ones. The novel Teaching-Learning-Based Optimization (TLBO) model is utilized to determine optimal irrigation releases, subsequently forming the basis for evaluating reservoir operation performance through the lenses of reliability, resilience, and vulnerability. The findings of this study shed light on the performance of these reservoirs under different models. Notably, the Aji-2 reservoir operation exhibits higher levels of reliability and resilience when the TLBO model is employed, surpassing the outcomes of the Linear Programming (LP) model. Conversely, the vulnerability of the Aji-3 reservoir operation is more pronounced with the TLBO model, albeit reduced when compared to actual release years 2005, 2009, and 2013. This study adds to the development of reservoir operation policies that favor reduced vulnerability and increased reliability.