Combined use of evolutionary algorithms and hydrological models to simulate snow cover and flow in alpine basins

Abstract

Snow cover area, which can be obtained from satellite, is a valuable information to simulate streamflow in snow-dominated mountain basins where snowmelt is a major runoff factor. However, usually satellite do not provide long completed snow cover area spatiotemporal series, which are required to calibrate and validate hydrological models. It is due to difference limitations, as presence of clouds, sensor failure, low revisit time or spatial resolution, or recent launch.Cellular automata models, which use precipitation and temperature as driving variables and some transition rules between cells through calibrated parameters, are capable of capturing the dynamics of snow cover area. Therefore, they can be used to complete and extend the information provided by satellite.In this work, we simulate long series of daily streamflow in the Canales basin (Sierra Nevada, south Spain) by combining a cellular automata model and the Snowmelt Runoff Model. The Snowmelt Runoff Model is a degree-day model that requires data of temperature, precipitation, and snow cover area and has been widely used in simulation of streamflow in snow-dominated mountainous basins around the world.The water resources in the Canales basin are regulated by a reservoir, which contributes to supply the Granada city water demand. The main resources stored in reservoir come from Sierra Nevada Mountains during the melting season. Therefore, the dynamics of snow is essential to simulate streamflow in the Canales basin.It has been also used to simulate future local climate scenarios generated for specific level of warming in peninsular Spain.Aknowledments: This research has been partially supported by the projects: STAGES-IPCC (TED2021-130744B-C21), SIGLO-PRO project (PID2021-128021OB-I00), SIERRA-CC project (PID2022-137623OA-I00) from the Spanish Ministry of Science, Innovation and Universities, and SER-PM (2908/22) from the National Park Research Program.