This paper investigates the performance of stochastic precipitation modeling approaches in simulating critical hydrological behaviors for effective mine water management.
By evaluating these models across multiple temporal scales and focusing on their ability to capture extreme precipitation events, the study challenges conventional tools and highlights their limitations in accurately predicting variability.
The findings emphasize the importance of selecting models that align with site-specific conditions and underscore the need for robust evaluation against observed data to enhance risk assessment and operational planning in mining contexts.
