This study introduces HydroWizard, an innovative framework addressing critical challenges in water resource modeling through enhanced transparency, efficiency, reproducibility, and extensibility. Integrating a YAML-based Model Specification Language with a sophisticated Execution Engine, HydroWizard enables accessible modeling of complex water systems.

Applied to the Lower Omo-Gibe River Basin in Ethiopia, the study employs Evolutionary Multi-Objective Direct Policy Search to identify 283 Pareto-optimal policies. Findings reveal nuanced trade-offs: irrigation-optimized policies eliminate demand deficits but reduce environmental flows by up to 48%, while environmentally-focused policies show opposite effects. Notably, mean power generation remains relatively consistent across policies, challenging assumptions about water resource allocation trade-offs.

HydroWizard introduces novel visualization techniques, including animated rule curves and system state graphs, enhancing strategy interpretability. Its versatility is demonstrated through application to diverse water systems, including the Zambezi River Basin.

This research marks a significant advancement in water resource modeling, offering an open-source, accessible tool for complex water system analysis. It contributes valuable insights for sustainable water management and sets a new standard for global water resource management studies, emerging as an innovative solution to intensifying water management challenges worldwide.