Snow water equivalent estimation through hydrology model simulation and the Copernicus Global land component product: A case study for the South Central Region of Bulgaria. Impact on triggering of geological and hydrological hazards

Abstract

Seasonal snow plays a crucial role in hydrology and soil–plant systems, and accurate estimation of snow water equivalent (SWE) is essential for sustainable water management and climate-smart agriculture. This study compares two approaches for generating monthly SWE estimates in the South Central Region (SCR) of Bulgaria for 2020: (i) process-based simulations using the Community Land Model (CLM 3), and (ii) archived SWE data from the Copernicus Global Land Component, derived from integrated in situ measurements and satellite observations. The comparison shows good agreement between the two approaches in lowland areas, while satellite-based SWE estimates are unreliable in mountainous terrain, which represents about 40% of the study area. The results obtained highlight the importance of integrating hydrological modeling with satellite data for estimating the water equivalent of snow cover in regions with limited observation capabilities and confirm the applicability of the Copernicus Global Land Component product for hydrological and hydrogeological forecasting, agricultural planning and climate change adaptation in Bulgaria. The assessment of the snow cover depth and its water equivalent during the winter months is important for predicting and managing the risk of hazardous geological and hydrological processes in the spring such as deep landslides and floods.