Snow Persistence and Snow Line Elevation Trends in a Snowmelt-Driven Basin in the Central Andes and Their Correlations with Hydroclimatic Variables

• Published in: Remote sensing (Basel, Switzerland) Switzerland), 2023-12, Vol.15 (23), p.5556
• Main Authors: Aranda, Felipe, Medina, Diego, Castro, Lina, Ossandón, Álvaro, Ovalle, Ramón, Flores, Raúl P., Bolaño-Ortiz, Tomás R.
• Format: Article
• Language: English
• Subjects: Anthropogenic factors; Basins; Climate change; climatic trend; Correlation; Cryosphere; Dry season; Ecosystems; El Nino; Forecasting; Fresh water; Glaciers; Global temperature changes; Human influences; Hydrology; Hydrometeorology; MODIS; Precipitation; Remote sensing; River basins; Seasonal variations; Snow; snow basin; Snow cover; snow line detection; snow persistence; Snowmelt; Spectroradiometers; Spring; Spring (season); Stream discharge; Stream flow; Streamflow; Summer; Temperature; Trends
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs15235556

The mountain cryosphere is crucial for socio-economic processes, especially during the dry seasons. However, anthropogenic climate change has had a detrimental impact on the cryosphere due to its sensitivity. Over the past two decades, there has been a decline in precipitation and a temperature rise, leading to a substantial reduction in the timing and extent of snow cover. This increase in temperature also elevates the snow line elevation (SLE), further diminishing the volume of available freshwater in the snow-driven basins of the Andes. In this study, we use 22 years (2000–2021) of 8-day snow product (MOD10A2) from the Moderate Resolution Imaging Spectroradiometer (MODIS) to analyze the annual and seasonal variability of snow cover area, SLE, and snow persistence (SP, an indicator of the duration of snow) in the Yeso River basin in Central Chile and the correlation of SP and SLE with hydrometeorological variables and climatic indices. We introduce a new approach called the Maximum Dissimilarity Method to obtain the SLE even on cloudy days. The results are as follows: (1) Snow cover area reductions of 34.0 km2 at low elevations in spring and 86.5 km2 at mid elevations in summer were found when comparing the period 2016–2021 to 2000–2004; (2) SP trends at the annual scale revealed a significant decrease in 89% of its area and an average of 3.6 fewer days of snow cover per year; (3) an upward and significant trend of 21 m‧year−1 in the annual SLE was found; and (4) annual SP and SLE were highly correlated with annual hydrometeorological variables, and spring and summer snow variables were significantly correlated with dry streamflow. This methodology can potentially serve as a valuable tool for detecting trends in snow-covered surfaces, and thereby associate these changes with climate change or other anthropogenic effects in future research.