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Spatial and temporal variability of snow cover in the Andes Mountains and its influence on streamflow in snow dominant rivers

Date

2016

Authors

Pimentel, Freddy Alejandro Saavedra, author
Kampf, Stephanie, advisor
Sibold, Jason, advisor
Fassnacht, Steven, committee member
Niemann, Jeffrey, committee member

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Abstract

The climate is changing, and snowmelt-dominated river basins are particularly sensitive to climate warming. In the Andes Mountains in South America climate measurements are sparse and unevenly distributed in snow-covered areas. Thus, remote sensing offers opportunities to improve understanding of the spatial and temporal snow patterns in this region and explore how these patterns relate to climate and hydrologic response. This study uses snow cover data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to (1) identify snow climate regions across the Andes, (2) document trends in snow persistence and their relation to precipitation and temperature, and (3) develop statistical streamflow prediction models. The first chapter of the study identified five snow climate regions: two tropical and three mid-latitude regions. In the tropical regions, snow cover was present only over 5000m on both sides of the Andes. In the mid-latitude regions the elevation of the snow line varied with latitude, dropping from 4000m to 1000m from 23 to 36°S. In the mid-latitudes, particularly where mountain peaks are highest, snow cover accumulates at lower elevations on the west side than on the east side of the Andes. The second chapter quantifies trends in annual snow persistence (SP) from 2000-2014. In the northern part of the study region, limited snow cover is present, and few trends in snow persistence were detected. A large area (70,515 km2) south of 29°S is affected by a significant loss of snow cover (2-5 day less day of snow per year). In this latitude range, most of the land surface area with snow loss (62%) is on the east side of the Andes. The trends of snow persistence relate to both precipitation and temperature, but the relative importance of each parameter changes across elevation and latitude. Precipitation has greater relative importance at lower elevations, whereas temperature has greater relative importance at higher elevations. The final chapter explores the relationship between snow cover patterns and streamflow in snow-dominated rivers in the Chilean Andes (29-36° S). Snow covered area is correlated with water yield in snowmelt-dominated watersheds, but it is not as useful for water yield forecasts in watersheds with more limited snowmelt contributions. The snow cover information was combined with climatic variables (temperature and precipitation), and physiographic variables to develop statistical models of water yield (WY) and peak flow (PF). The final statistical model developed can forecast water year WY and PF in August using precipitation, snow cover, and area of watershed as predictors, with r2 values of 0.8 and 0.7 respectively. The approaches developed for applying snow cover information from remote sensing have led to important new findings about snow patterns in a large latitude range across the Andes Mountains. New tools developed for incorporating snow cover information into water yield and peak flow forecasts can aid water management under changing climate conditions.

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