scholarly journals A Subseasonal Regime Approach for Assessing Intra-annual Variability of Evapotranspiration and Application to the Upper Colorado River Basin

2022 ◽  
Vol 3 ◽  
Author(s):  
Jiancong Chen ◽  
Baptiste Dafflon ◽  
Haruko M. Wainwright ◽  
Anh Phuong Tran ◽  
Susan S. Hubbard
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Colorado River ◽  
Markov Models ◽  
Snow Accumulation ◽  
Meteorological Conditions ◽  
Colorado River Basin ◽  
Summer Drought ◽  
Annual Variability ◽  
Upper Colorado River Basin

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.

scholarly journals Causes for the Century-Long Decline in Colorado River Flow

2019 ◽  
Vol 32 (23) ◽  
pp. 8181-8203 ◽  
Author(s):  
M. Hoerling ◽  
J. Barsugli ◽  
B. Livneh ◽  
J. Eischeid ◽  
X. Quan ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
River Flow ◽  
Colorado River ◽  
Empirical Studies ◽  
Colorado River Basin ◽  
Climate Change Signal ◽  
Uncertainty Range ◽  
Percent Change ◽  
Upper Colorado River Basin

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.

scholarly journals Mesoscale Variability of the Upper Colorado River Snowpack

1996 ◽  
Vol 27 (5) ◽  
pp. 313-322 ◽  
Author(s):  
Chi-Hai Ling ◽  
Edward G. Josberger ◽  
A.S. Thorndike
Keyword(s):  
River Basin ◽  
Colorado River ◽  
Snow Water Equivalent ◽  
Statistical Technique ◽  
Snow Accumulation ◽  
Colorado River Basin ◽  
Mountainous Regions ◽  
Upper Colorado River Basin ◽  
Snow Water ◽  
Colorado Rocky Mountains

In the mountainous regions of the Upper Colorado River Basin, snow course observations give local measurements of snow water equivalent, which can be used to estimate regional averages of snow conditions. We develop a statistical technique to estimate the mesoscale average snow accumulation, using 8 years of snow course observations. For each of three major snow accumulation regions in the Upper Colorado River Basin – the Colorado Rocky Mountains, Colorado, the Uinta Mountains, Utah, and the Wind River Range, Wyoming – the snow course observations yield a correlation length scale of 38 km, 46 km, and 116 km respectively. This is the scale for which the snow course data at different sites are correlated with 70 per cent correlation. This correlation of snow accumulation over large distances allows for the estimation of the snow water equivalent on a mesoscale basis. With the snow course data binned into 1/4° latitude by 1/4° longitude pixels, an error analysis shows the following: for no snow course data in a given pixel, the uncertainty in the water equivalent estimate reaches 50 cm; that is, the climatological variability. However, as the number of snow courses in a pixel increases the uncertainty decreases, and approaches 5-10 cm when there are five snow courses in a pixel.

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

2021 ◽  
Author(s):  
Olivia L. Miller ◽  
Matthew P. Miller ◽  
Patrick C. Longley ◽  
Jay R. Alder ◽  
Lindsay A. Bearup ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Colorado River ◽  
Colorado River Basin ◽  
Upper Colorado River Basin
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