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This paper explores the application of conceptual hydrological models in optimizing the operation of hydroelectric power plants (HPPs) in steppe regions, a crucial aspect of promoting low-carbon energy solutions. The study aims to identify the most suitable conceptual hydrological model for predicting reservoir inflows from multiple catchments in a steppe region, where spring runoff dominates the annual water volume and requires careful consideration of snowfall. Two well-known conceptual models, HBV and GR6J-CemaNeige, which incorporate snow-melting processes, were evaluated. The research also investigated the best approach to preprocessing historical data to enhance model accuracy. Furthermore, the study emphasizes the importance of accurately defining low-water periods to ensure reliable HPP operation through more accurate inflow forecasting. A hypothesis was proposed to explore the relationship between atmospheric circulation and the definition of low-water periods; however, the findings did not support this hypothesis. Overall, the results suggest that combining the conceptual models under consideration can lead to more accurate forecasts, underscoring the need for integrated approaches in managing HPP reservoirs and promoting sustainable energy production.
Eroshenko et al. (Fri,) studied this question.