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A simple framework for assessing the sensitivity of mountain watersheds to warming‐driven snowpack loss
Author(s) -
Tennant Christopher J.,
Crosby Benjamin T.,
Godsey Sarah E.,
VanKirk Robert W.,
Derryberry DeWayne R.
Publication year - 2015
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2015gl063413
Subject(s) - snowpack , elevation (ballistics) , snow , environmental science , watershed , drainage basin , range (aeronautics) , hydrology (agriculture) , atmospheric sciences , geology , geomorphology , geography , mathematics , geometry , cartography , geotechnical engineering , machine learning , computer science , materials science , composite material
The common observation that snowpack increases with elevation suggests that a catchment's elevation distribution should be a robust indicator of its potential to store snow and its sensitivity to snowpack loss. To capture a wide range of potential elevation‐based responses, we used Monte Carlo methods to simulate 20,000 watershed elevation distributions. We applied a simple function relating warming, elevation, and snowpack to explore snowpack losses from the simulated elevation distributions. Regression analyses demonstrate that snowpack loss is best described by three parameters that identify the central tendency, variance, and shape of each catchment's elevation distribution. Equal amounts of snowpack loss can occur even when catchments are centered within different elevation zones; this stresses the value of also measuring the variance and shape of elevation distributions. Responses of the simulated elevation distributions to warming are nonlinear and emphasize that the sensitivity of mountain forests to snowpack loss will likely be watershed dependent.