scholarly journals How will baseflow respond to climate change in the Upper Colorado River Basin?

Author(s):  
Olivia L. Miller ◽  
Matthew P. Miller ◽  
Patrick C. Longley ◽  
Jay R. Alder ◽  
Lindsay A. Bearup ◽  
...  
2019 ◽  
Vol 32 (23) ◽  
pp. 8181-8203 ◽  
Author(s):  
M. Hoerling ◽  
J. Barsugli ◽  
B. Livneh ◽  
J. Eischeid ◽  
X. Quan ◽  
...  

Abstract Upper Colorado River basin streamflow has declined by roughly 20% over the last century of the instrumental period, based on estimates of naturalized flow above Lees Ferry. Here we assess factors causing the decline and evaluate the premise that rising surface temperatures have been mostly responsible. We use an event attribution framework involving parallel sets of global model experiments with and without climate change drivers. We demonstrate that climate change forcing has acted to reduce Upper Colorado River basin streamflow during this period by about 10% (with uncertainty range of 6%–14% reductions). The magnitude of the observed flow decline is found to be inconsistent with natural variability alone, and approximately one-half of the observed flow decline is judged to have resulted from long-term climate change. Each of three different global models used herein indicates that climate change forcing during the last century has acted to increase surface temperature (~+1.2°C) and decrease precipitation (~−3%). Using large ensemble methods, we diagnose the separate effects of temperature and precipitation changes on Upper Colorado River streamflow. Precipitation change is found to be the most consequential factor owing to its amplified impact on flow resulting from precipitation elasticity (percent change in streamflow per percent change in precipitation) of ~2. We confirm that warming has also driven streamflow declines, as inferred from empirical studies, although operating as a secondary factor. Our finding of a modest −2.5% °C−1 temperature sensitivity, on the basis of our best model-derived estimate, indicates that only about one-third of the attributable climate change signal in Colorado River decline resulted from warming, whereas about two-thirds resulted from precipitation decline.


2022 ◽  
Vol 3 ◽  
Author(s):  
Jiancong Chen ◽  
Baptiste Dafflon ◽  
Haruko M. Wainwright ◽  
Anh Phuong Tran ◽  
Susan S. Hubbard

Evapotranspiration (ET) is strongly influenced by gradual climate change and fluctuations in meteorological conditions, such as earlier snowmelt and occurrence of droughts. While numerous studies have investigated how climate change influences the inter-annual variability of ET, very few studies focused on quantifying how subseasonal events control the intra-variability of ET. In this study, we developed the concept of subseasonal regimes, whose timing and duration are determined statistically using Hidden Markov Models (HMM) based on meteorological conditions. We tested the value of subseasonal regimes for quantitatively characterizing the variability of seasonal and subseasonal events, including the onset of snow accumulation, snowmelt, growing season, monsoon, and defoliation. We examined how ET varied as a function of the timing of these events within a year and across six watersheds in the region. Variability of annual ET across these six sites is much less significant than the variability in hydroclimate attributes at the sites. Subseasonal ET, defined as the total ET during a given subseasonal regime, provides a measure of intra-annual variability of ET. Our study suggests that snowmelt and monsoon timing influence regime transitions and duration, such as earlier snowmelt can increase springtime ET rapidly but can trigger long-lasting fore-summer drought conditions that lead to decrease subseasonal ET. Overall, our approach provides an enhanced statistically based framework for quantifying how the timing of subseasonal-event transitions influence ET variability. The improved understanding of subseasonal ET variability is important for predicting the future impact of climate change on water resources from the Upper Colorado River Basin regions.


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