Title
Modelling snowmelt runoff from tropical andean glaciers under climate change scenarios in the santa river sub-basin (Peru)
Date Issued
01 December 2021
Access level
open access
Resource Type
journal article
Publisher(s)
MDPI
Abstract
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.
Volume
13
Issue
24
Language
English
OCDE Knowledge area
Investigación climática
Scopus EID
2-s2.0-85121440173
Source
Water (Switzerland)
ISSN of the container
20734441
Sponsor(s)
This research was funded by Universidad Nacional Agraria La Molina (UNALM), Universidad Nacional del Altiplano de Puno (UNAP) and Instituto Nacional de Innovación Agraria (INIA). Acknowledgments: The main author thanks his father Benigno Gregorio Calizaya Ticona who passed away on 26 January 2020, because I owe many of my achievements to you. Thank you for having shaped me as the person I am. The authors thank Blair Fitzharris and Pascal Sirguey for providing the temporally interpolated MODIS snow cover product. The authors acknowledge and appreciate the support of the Universidad Nacional Agraria La Molina (UNALM), Research Institute for Sustainable Development in Highland Forests (INDES-CES) of the National University Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Instituto Nacional de Innovación Agraria (INIA), Servicio Nacional de Meteorología e Hidrología del Perú (SENAMHI) and Autoridad Nacional del Agua (ANA). Finally, the authors express their gratitude for the thorough work of the tree anonymous reviewers, who greatly improved the quality of this manuscript. Funding: This research was funded by Universidad Nacional Agraria La Molina (UNALM), Univer-sidad Nacional del Altiplano de Puno (UNAP) and Instituto Nacional de Innovación Agraria (INIA).
Sources of information: Directorio de Producción Científica Scopus