Impact of historical and future climate change scenarios on meteorological and snow cover droughts in semi-arid and humid snow-dominated catchments

Drought is a temporary precipitation anomaly that affects other hydrological variables and can impact large areas, causing devastating effects on agriculture, environment, and water supplies. Climate change is increasing the frequency of droughts, and their intensity is expected to rise in the future.
In snow-dominated catchments, monitoring and analyzing meteorological (precipitation) and hydrological droughts (associated with snow cover area) is crucial due to their importance in water resources. These regions are particularly sensitive to climate change and serve as excellent observatories for both current and past climate change effects.
In this study, we compare historical droughts related to precipitation and snow cover area in three semi-arid and three humid catchments. We also assess the impact of future climate change scenarios on droughts in these systems. The semi-arid catchments are located in the Sierra Nevada (Spain), the Southern Rocky Mountains (Colorado), and the Andes (Chile), while the humid catchments are located in the Alps (Italy), the Caucasus Mountains (Georgia), and the Himalayas (Nepal).
Historical climate variables were obtained from the ERA5-Land reanalysis dataset, and snow cover area was modeled using these climate data along with snow cover area data from the MODIS satellite. Gap filling, extension of the historical period, and simulation of future snow cover area under climate change scenarios were achieved using an improved cellular automata algorithm, which utilizes precipitation, temperature, and elevation as driving variables. Future local climate change scenarios were generated using the stochastic weather generator LARS-WG, which incorporates climate projections from the CMIP6 ensemble, as used in the latest IPCC Sixth Assessment Report. Drought analysis was conducted in terms of frequency, duration, intensity, and magnitude of drought periods using runs theory and various thresholds of the corresponding standardized drought index for precipitation and snow cover area.

This research has been partially supported by the project SIERRA-CC (PID2022-137623OA-I00 funded by MICIU/AEI/10.13039/501100011033 and by FEDER, UE); the project SIGLO-PRO (PID2021-128021OB-I00/ AEI/10.13039/501100011033/ FEDER, UE), the project STAGES-IPCC (TED2021-130744B-C21/AEI/10.13039/501100011033/ Unión Europea NextGenerationEU/PRTR).