Application of fuzzy logic for water supply forecasting in three Andean catchments of central Chile

Understanding the availability and distribution of water resources is crucial for efficient management. Chilean basins in the northern and central regions typically exhibit characteristics of a snow or mixed regime, with snowmelt runoff being the primary source of supply. Industries such as mining, agriculture and hydroelectric power generation experience peak demand during the snowmelt period. Determining the average and monthly distribution of runoff during this period is essential for effective planning.

Currently, both public and private institutions perform forecasts to provide valuable information to diverse users, including farmers and hydroelectric companies. This research aims to enhance the snowmelt forecast in snow-dominated or mixed basins integrating hydrometeorological forecasts and system states into a fuzzy model. The study focuses on the Choapa en Cuncumén, Maipo en el Manzano and Tinguiririca Bajo los Briones rivers.

The methodology establishes relationships between system inputs, such as precipitation, snow cover and temperature, and the output variable of snowmelt runoff. Using membership functions and fuzzy rules, the model is developed based on observations collected over fifteen-year period. The performance of each model is evaluated with the commonly employed metrics, through sensitivity analysis and cross- validation. A subsequent comparison with existing models allows us to draw conclusions about the effectiveness of fuzzy models in predicting snowmelt runoff.

The simulation yield Kling-Gupta Efficiency (KGE) values exceeding 0.5 in the first two basins and close to 0.4 in the last one, indicating an acceptable forecast relative to those produced by other institutions. This underscores varying model performance across the three basins, contingent on specific conditions and dependencies on model inputs. While a successful calibration is achieved, a detailed examination of water rights and streamflow naturalization, particularly in basins where this value holds significance, is essential.