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Abstract
Of concern to Colorado River management, as operating guidelines post-2026 are being considered, is whether water resource recovery from low flows during 2000–2020 is possible.  Here we analyze new simulations from the sixth generation of the Coupled Model Intercomparison Project (CMIP6) to determine plausible climate impacts on Colorado River flows for 2026–2050 when revised guidelines would operate. We constrain projected flows for Lee Ferry, the gauge through which 85% of the river flow passes, using its estimated sensitivity to meteorological variability together with CMIP6 projected precipitation and temperature changes. The critical importance of precipitation, especially its natural variability, is emphasized. Model projections indicate increased precipitation in the Upper Colorado River basin due to climate change, which alone increases river flows 5%–7% (relative to a 2000–2020 climatology). Depending on the river’s temperature sensitivity, this wet signal compensates some, if not all, of the depleting effects from basin warming. Considerable internal decadal precipitation variability (~5% of the climatological mean) is demonstrated, driving a greater range of plausible Colorado River flow changes for 2026–2050 than previously surmised from treatment of temperature impacts alone: the overall precipitation-induced Lee Ferry flow changes span -25% to +40% contrasting with a -30% to -5% range from expected warming effects only. Consequently, extreme low and high flows are more likely. Lee Ferry flow projections, conditioned on initial drought states akin to 2000–2020, reveal substantial recovery odds for water resources, albeit with elevated risks of even further flow declines than in recent decades.
 

During this one-hour session of the Boase water seminar series,  Associate Professor Aditi Bhaskar welcomed new civil engineering graduate students and provided an overview of the Hydrology, Water Resources, and Environmental Fluid Mechanics graduate program.  Also, Professor Michael Gooseff provided an overview of the campus-wide .
 

Wildfires can significantly impact water quality and supply, presenting challenges for water treatment plants and freshwater systems. However, high variability and data scarcity in post-wildfire in situ water quality data have hindered previous analyses. Here, I present a unique multi-scale analysis of post-burn hydrologic and water quality effects, observing small-scale driving mechanisms as well as broad, large-scale responses across watersheds. Custom-designed laboratory-scale wildfire and rainfall simulation experiment apparati were first tested on 154 ~300 cm² soil samples. Burn effects were observed in the context of other key drivers—rainfall intensity and terrain slope—to simulate variable conditions in natural settings. A synthesis of previous wildfire simulation methods was also completed, discussing benefits and limitations of different techniques. Next, broad changes in constituent responses in post-fire years were assessed for 241 forested watersheds across the U.S. West using machine learning and statistical techniques. Inter-basin variability in post-fire responses was also attributed to physiographic watershed variables and wildfire characteristics. By bridging multiple scales, this study strives to provide a holistic understanding of wildfires’ impacts on watersheds in the U.S. West.
 

Western-U.S. water managers facing changing climate and growing populations are seeking new tools to guide their planning and operational decision making. This presentation highlights two key tools that emerged from a five-year collaboration between university researchers and Salt Lake City Department of Public Utilities. Using a century-length, ten-catchment streamflow dataset we found that interannual variability in groundwater storage, inferred from winter baseflow, is a primary control on canyon runoff efficiency. Adding antecedent groundwater storage to a linear model with precipitation and melt dynamics reduces uncertainty in annual runoff from approximately 40% to 5%. Investigating the climate drivers of groundwater storage, we found an important role for an Atlantic Quadpole Mode (AQM) of sea surface temperature variability that modulates the winter precipitation patterns associated with the El Nino Southern Oscillation (ENSO). The connection between the AQM and western-U.S. hydroclimate generates precipitation anomalies as large as 30%, and is robust in observations and a 10,000-year global climate model simulation with perpetually fixed modern greenhouse gas concentrations.