Modelling Snowmelt Runoff from Tropical Andean Glaciers under Climate Change Scenarios in the Santa River Sub-Basin (Peru)

• Autores: Calizaya, Elmer, Mejía, Abel, Barboza Castillo, Elgar, Calizaya, Fredy, Corroto, Fernando, Salas López, Rolando, Vásquez Pérez, Héctor Vladimir, Turpo Cayo, Efrain
• Formato: artículo
• Fecha de Publicación: 2021
• Institución: Instituto Nacional de Innovación Agraria
• Repositorio: INIA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:null:20.500.12955/1628
• Enlace del recurso: https://hdl.handle.net/20.500.12955/1628; https://doi.org/10.3390/w13243535
• Nivel de acceso: acceso abierto
• Materia: Cordillera Blanca (CB); Glaciers; Climate change; Water; Google earth engine (GEE; Snowmelt runoff model (SRM); https://purl.org/pe-repo/ocde/ford#4.05.00

Effects of climate change have led to a reduction in precipitation and an increase in temperature across several areas of the world. This has resulted in a sharp decline of glaciers and an increase in surface runoff in watersheds due to snowmelt. This situation requires a better understanding to improve the management of water resources in settled areas downstream of glaciers. In this study, the snowmelt runoff model (SRM) was applied in combination with snow-covered area information (SCA), precipitation, and temperature climatic data to model snowmelt runoff in the Santa River sub-basin (Peru). The procedure consisted of calibrating and validating the SRM model for 2005–2009 using the SRTM digital elevation model (DEM), observed temperature, precipitation and SAC data. Then, the SRM was applied to project future runoff in the sub-basin under the climate change scenarios RCP 4.5 and RCP 8.5. SRM patterns show consistent results; runoff decreases in the summer months and increases the rest of the year. The runoff projection under climate change scenarios shows a substantial increase from January to May, reporting the highest increases in March and April, and the lowest records from June to August. The SRM demonstrated consistent projections for the simulation of historical flows in tropical Andean glaciers.