Coupled Cellular automata – Snowmelt Runoff Model: A Novel Framework for Assessing Climate Change Impacts on Streamflow

Abstract Mountain snowpacks are key components of surface water resources, as snowmelt significantly contributes to streamflow and serves as an essential indicator of climate change and variability. Accurate estimation of snowmelt-induced streamflow and assessment of its potential response to climate change are therefore essential for effective water resources planning and management. This study presents a new coupled modeling framework that integrates a cellular automata model (CAM) to simulate snow cover area (SCA) with the Snowmelt Runoff Model (SRM) to simulate daily streamflow. The model was applied to assess the impacts of climate change and associated uncertainty on SCA and streamflow in a Mediterranean mountainous catchment. Four local climate scenarios were developed from an ensemble of nine downscaled Regional Climate Models (RCMs), assuming two warming levels for Spain (1.5 °C and 3.0 °C). The CAM–SRM framework was calibrated and validated using precipitation and temperature data from the AEMET 5 km gridded product for the period 2000–2020. Under future climate conditions, the model projected a substantial decrease in SCA and a two-month shorter snow season in warmer scenarios. An earlier onset of snowmelt peak flows is also expected, along with a projected decline in mean annual streamflow of 19.4–32.9%. These results indicate significant changes in the hydrological regime driven by climate change. The proposed modeling framework proves effective for reproducing snowmelt-driven streamflow dynamics in snow-dominated catchments and offers valuable insights for future water resources planning and management in mountainous regions. Graphical Abstract Graphical abstract description : This study presents a novel coupled modelling framework for assessing climate change impacts on streamflow using the Snowmelt-Runoff Model (SRM). The new framework integrates a cellular automata model with the SRM, enabling streamflow simulations under non-historical conditions even in the absence of snow cover observations, which are required as input along with climate variables (precipitation and temperature) in the SRM formulation. The cellular automata model provides daily future snow cover simulations, which are incorporated into the SRM to generate streamflow projections. We evaluated the impacts of climate change on climate variables under four climate scenarios considering two warming levels for Spain (1.5 °C and 3.0 °C). These scenarios were derived from an ensemble of nine Regional Climate Models (RCMs) and downscaled using two different approaches: bias correction and delta change. This study identified the significant impacts of climate change in a Mediterranean snow-dominated basin (Canales basin, southern Spain). The results revealed increased temperatures and reduced precipitation, which led to substantial declines in snow cover and streamflow. This framework offers a valuable tool for water resource management and the development of adaptive climate strategies in snow-dominated mountain regions.