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Snow Cover Temporal Dynamic Using MODIS Product, and Its Relationship with Precipitation and Temperature in the Tropical Andean Glaciers in the Alto Santa Sub-Basin (Peru)

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  • Elmer Calizaya

    (Escuela Profesional de Ingeniería Topográfica y Agrimensura, Facultad de Ciencias Agrarias, Universidad Nacional del Altiplano, Puno 21001, Peru
    Programa de Doctorado en Recursos Hídricos (PDRH), Universidad Nacional Agraria La Molina, Av. La Molina, S.N., Lima 15012, Peru)

  • Wilber Laqui

    (Programa de Doctorado en Recursos Hídricos (PDRH), Universidad Nacional Agraria La Molina, Av. La Molina, S.N., Lima 15012, Peru
    Escuela Profesional de Ingeniería Agrícola, Facultad de Ingeniería Agrícola, Universidad Nacional del Altiplano, Puno 21001, Peru)

  • Saul Sardón

    (Escuela Profesional de Ingeniería Topográfica y Agrimensura, Facultad de Ciencias Agrarias, Universidad Nacional del Altiplano, Puno 21001, Peru)

  • Fredy Calizaya

    (Escuela Profesional de Ingeniería Agronómica, Facultad de Ciencias Agrarias, Universidad Nacional del Altiplano, Puno 21001, Peru)

  • Osmar Cuentas

    (Escuela Profesional de Ingeniería Civil, Grupo en Investigación en Ingeniería Civil, Universidad Nacional de Moquegua, Moquegua 18001, Peru)

  • José Cahuana

    (Servicio Nacional de Sanidad Agraria—SENASA, Av. La Molina Este Nº 1915, Lima 15026, Peru)

  • Carmen Mindani

    (Facultad de Industrias Alimentarias, Universidad Nacional Agraria La Molina, Av. La Molina s/n, Ap. 12-056, Lima 15012, Peru)

  • Walquer Huacani

    (Carrera Profesional de Ingeniería de Minas, Universidad Nacional Micaela Bastidas de Apurímac, Abancay 03001, Peru)

Abstract

The retreats of the planet’s tropical glaciers are natural indicators of the variation of precipitation, temperature, and other variables. The glaciers of the Alto Santa sub-basin are sources of freshwater storage for consumptive and non-consumptive use for different sectors. As a result of climatic variations, it is essential to analyze the dynamics of the snow cover area (SCA). The methodology consisted of processing 6578 MODIS Snow Cover MOD10A1 product images and generating 18-year time series using the Platform Google Earth Engine (GEE). Normalized Difference Snow Index (NDSI) was used to estimate the extent of snow cover, and to validate the MODIS snow cover product, we used the same overlapping date of Landsat 5 and 8 Surface Reflectance Tier 1, to examine the relationships between daily precipitation and temperature. The standardized correlation results gave good results with stations over 4500 m.a.s.l., such as Artesonraju AP2 (4828 m.a.s.l.) of −0.84 and −0.74, precipitation, and temperature. These results show coherent behaviors of the retreat due to the variation of the climatological variables. In some years, there were anomalies in the conduct of the three variables, but these originated from events of natural weather phenomena. Regarding the dynamics of the SCA in 18 years, it decreased from 649 km 2 to 311.6. km 2 between 2000 and 2017, representing a retreat of 41%; we can conclude and confirm that the glacier retreat is imminent due to the consequences of climate change, which would affect the security of freshwater from the tropical glaciers of the Peruvian Andes.

Suggested Citation

  • Elmer Calizaya & Wilber Laqui & Saul Sardón & Fredy Calizaya & Osmar Cuentas & José Cahuana & Carmen Mindani & Walquer Huacani, 2023. "Snow Cover Temporal Dynamic Using MODIS Product, and Its Relationship with Precipitation and Temperature in the Tropical Andean Glaciers in the Alto Santa Sub-Basin (Peru)," Sustainability, MDPI, vol. 15(9), pages 1-20, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7610-:d:1140240
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    References listed on IDEAS

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    1. Vishakha Sood & Reet Kamal Tiwari & Sartajvir Singh & Ravneet Kaur & Bikash Ranjan Parida, 2022. "Glacier Boundary Mapping Using Deep Learning Classification over Bara Shigri Glacier in Western Himalayas," Sustainability, MDPI, vol. 14(20), pages 1-13, October.
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    3. Zebende, G.F., 2011. "DCCA cross-correlation coefficient: Quantifying level of cross-correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 614-618.
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