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A low-to-no snow future and its impacts on water resources in the western United States

Nature Portfolio (Springer Nature) | October 26th, 2021

Summary

Anthropogenic climate change is decreasing seasonal snowpacks globally, with potentially catastrophic consequences on water resources, given the long-held reliance on sno

Anthropogenic climate change is decreasing seasonal snowpacks globally, with potentially catastrophic consequences on water resources, given the long-held reliance on snowpack in water management. In this Review, we examine the changes and trickle-down impacts of snow loss in the western United States (WUS). Across the WUS, snow water equivalent declines of ~25% are expected by 2050, with losses comparable with contemporary historical trends. There is less consensus on the time horizon of snow disappearance, but model projections combined with a new low-to-no snow definition suggest ~35–60 years before low-to-no snow becomes persistent if greenhouse gas emissions continue unabated. Diminished and more ephemeral snowpacks that melt earlier will alter groundwater and streamflow dynamics. The direction of these changes are difficult to constrain given competing factors such as higher evapotranspiration, altered vegetation composition and changes in wildfire behaviour in a warmer world. These changes undermine conventional WUS water management practices, but through proactive implementation of soft and hard adaptation strategies, there is potential to build resilience to extreme, episodic and, eventually, persistent low-to-no snow conditions. Federal investments offer a timely opportunity to address these vulnerabilities, but they require a concerted portfolio of activities that cross historically siloed physical and disciplinary boundaries.

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A Measure of Snow: A Report Based on Case Studies of The Snow Survey and Water Supply Forecasting Program

U.S. Department of Agriculture (USDA) | November 1st, 2008

Summary

Snow depth and snow water content data have been collected and disseminated throughout the Western United States for over 100 years. Early snow survey and water s

Snow depth and snow water content data have been collected and disseminated throughout the Western United States for over 100 years. Early snow survey and water supply data were gathered through the efforts of university scientists, beginning with the work of Dr. James E. Church. In 1935, the Soil Conservation Service (SCS), now the United States Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS), established a formal cooperative Snow Survey and Water Supply Forecasting (SS-WSF) Program. The Agency was charged with responsibility for “conducting snow survey and water supply forecasts and the forecasting of irrigation water supplies.” The new Program would also develop consistent methods for measuring snow and reliable models for accurate water supply forecasting. Administered by NRCS, the SS-WSF Program has grown into a network of more than 1,200 manually-measured snow courses and over 750 automated Snowpack Telemetry (SNOTEL) weather stations in 13 Western States, including Alaska. (See map on page 4.) The SS-WSF Program provides manual snow course data collected by NRCS conservation professionals, automated SNOTEL data, and modeled water supply/streamflow volume data as well as issues streamflow forecasts for over 740 locations in the West. The data and the related reports and forecasts, are made available—in near real time for the automated SNOTEL sites—to private industry; to Federal, State, and local government entities; and to private citizens through an extensive Internet delivery system and other distribution channels. With 50-80 percent of the water supply in the West arriving in the form of snow, data on the snowpack provides critical information to decision-makers and water managers throughout the West. The basic data become even more valuable when used in concert with partner organizations to provide water supply forecasting tailored to meet end-user needs. According to researchers from multiple U.S. and international agencies, research centers, and academia, changes in the world’s climate have resulted in a loss of predictability in weather, precipitation, and water transport and accumulation patterns. It is anticipated that the value the SS-WSF Program provides to society will increase over time as climate variability increases. Recently a study was done to see who uses SS-WSF data, how the data are used, and the value of the data. Users of the data were interviewed and specific events and activities were analyzed. This publication is based on that study.

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A western United States snow reanalysis dataset over the Landsat era from water years 1985 to 2021

Nature Portfolio (Springer Nature) | November 7th, 2022

Summary

Water stored in mountain snowpacks (i.e., snow water equivalent, SWE) represents an important but poorly characterized component of the terrestrial water cycle. The Weste

Water stored in mountain snowpacks (i.e., snow water equivalent, SWE) represents an important but poorly characterized component of the terrestrial water cycle. The Western United States snow reanalysis (WUS–SR) dataset is novel in its combination of spatial resolution (~500 m), spatial extent (31°–49° N; 102°–125° W), and temporal continuity (daily over 1985–2021). WUS–SR is generated using a Bayesian framework with model-based snow estimates updated through the assimilation of cloud-free Landsat fractional snow-covered area observations. Over the WUS, the peak SWE verification with independent in situ measurements show correlation coefficient, mean difference (MD), and root mean squared difference (RMSD) of 0.77, −0.15 m, and 0.28 m, respectively. The effects of forest cover and Landsat image availability on peak SWE are assessed. WUS–SR peak SWE is well correlated (ranging from 0.75 to 0.91) against independent lidar-derived SWE taken near April 1st, with MD

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Adapting California’s Water Management to Climate Change

Public Policy Institute of California (PPIC) | January 12th, 2009

Summary

Among the potential impacts of climate change, accelerated sea level rise and a reduced Sierra snowpack are the most certain. Both will pose significant challenges for wa

Among the potential impacts of climate change, accelerated sea level rise and a reduced Sierra snowpack are the most certain. Both will pose significant challenges for water supply and flood management. Water utilities have already begun to plan for these changes, but flood control agencies are lagging behind and face greater regulatory constraints. State leadership is needed to resolve some threats, including the risk of catastrophic failure in the Sacramento-San Joaquin Delta. This report was prepared as part of the Preparing California for a Changing Climate project.

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Agricultural risks from changing snowmelt

Nature Portfolio (Springer Nature) | April 20th, 2020

Summary

Snowpack stores cold-season precipitation to meet warm-season water demand. Climate change threatens to disturb this balance by altering the fraction of precipita

Snowpack stores cold-season precipitation to meet warm-season water demand. Climate change threatens to disturb this balance by altering the fraction of precipitation falling as snow and the timing of snowmelt, which may have profound effects on food production in basins where irrigated agriculture relies heavily on snowmelt runoff. Here, we analyse global patterns of snowmelt and agricultural water uses to identify regions and crops that are most dependent on snowmelt water resources. We find hotspots primarily in high-mountain Asia (the Tibetan Plateau), Central Asia, western Russia, western US and the southern Andes. Using projections of sub-annual runoff under warming scenarios, we identify the basins most at risk from changing snowmelt patterns, where up to 40% of irrigation demand must be met by new alternative water supplies under a 4 °C warming scenario. Our results highlight basins and crops where adaptation of water management and agricultural systems may be especially critical in a changing climate.

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Anthropogenic warming impacts on California snowpack during drought

American Geophysical Union (AGU) | March 15th, 2017

Summary

Sierra Nevada climate and snowpack is simulated during the period of extreme drought from 2011 to 2015 and compared to an identical simulation except for the removal of t

Sierra Nevada climate and snowpack is simulated during the period of extreme drought from 2011 to 2015 and compared to an identical simulation except for the removal of the twentieth century anthropogenic warming. Anthropogenic warming reduced average snowpack levels by 25%, with middle‐to‐low elevations experiencing reductions between 26 and 43%. In terms of event frequency, return periods associated with anomalies in 4 year 1 April snow water equivalent are estimated to have doubled, and possibly quadrupled, due to past warming. We also estimate effects of future anthropogenic warmth on snowpack during a drought similar to that of 2011–2015. Further snowpack declines of 60–85% are expected, depending on emissions scenario. The return periods associated with future snowpack levels are estimated to range from millennia to much longer. Therefore, past human emissions of greenhouse gases are already negatively impacting statewide water resources during drought, and much more severe impacts are likely to be inevitable.

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Anthropogenic Warming Impacts on Today's Sierra Nevada Snowpack and Flood Risk

American Geophysical Union (AGU) | June 15th, 2018

Summary

This study investigates temperature impacts to snowpack and runoff‐driven flood risk over the Sierra Nevada during the extremely wet year of 2016–2017, which followed

This study investigates temperature impacts to snowpack and runoff‐driven flood risk over the Sierra Nevada during the extremely wet year of 2016–2017, which followed the extraordinary California drought of 2011–2015. By perturbing near‐surface temperatures from a 9‐km dynamically downscaled simulation, a series of offline land surface model experiments explore how Sierra Nevada hydrology has already been impacted by historical anthropogenic warming and how these impacts evolve under future warming scenarios. Results show that historical warming reduced 2016–2017 Sierra Nevada snow water equivalent by 20% while increasing early‐season runoff by 30%. An additional one third to two thirds loss of snowpack is projected by the end of the century, depending on the emission scenario, with middle elevations experiencing the most significant declines. Notably, the number of days in the future with runoff exceeding 20 mm nearly doubles under a mitigation emission scenarios and triples under a business‐as‐usual scenario. A smaller snow‐to‐rain ratio, as opposed to increased snowmelt, is found to be the primary mechanism of temperature impacts to Sierra snowpack and runoff. These findings are consequential to the prevalence of early‐season floods in the Sierra Nevada. In the Feather River Watershed, historical warming increased runoff by over one third during the period of heaviest precipitation in February 2017. This suggests that historical anthropogenic warming may have exacerbated runoff conditions underlying the Oroville Dam spillway overflow that occurred in this month. As warming continues in the future, the potential for runoff‐based flood risk may rise even higher.

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Asymmetric emergence of low-to-no snow in the midlatitudes of the American Cordillera

Nature Portfolio (Springer Nature) | November 14th, 2022

Summary

Societies and ecosystems within and downstream of mountains rely on seasonal snowmelt to satisfy their water demands. Anthropogenic climate change has reduced mountain sn

Societies and ecosystems within and downstream of mountains rely on seasonal snowmelt to satisfy their water demands. Anthropogenic climate change has reduced mountain snowpacks worldwide, altering snowmelt magnitude and timing. Here the global warming level leading to widespread and persistent mountain snowpack decline, termed low-to-no snow, is estimated for the world’s most latitudinally contiguous mountain range, the American Cordillera. We show that a combination of dynamical, thermodynamical and hypsometric factors results in an asymmetric emergence of low-to-no-snow conditions within the midlatitudes of the American Cordillera. Low-to-no-snow emergence occurs approximately 20 years earlier in the southern hemisphere, at a third of the local warming level, and coincides with runoff efficiency declines (8% average) in both dry and wet years. The prevention of a low-to-no-snow future in either hemisphere requires the level of global warming to be held to, at most, +2.5 °C.

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Attribution of declining western U.S. snowpack to human effects

American Meteorological Society (AMS) | December 1st, 2008

Summary

Observations show snowpack has declined across much of the western United States over the period 1950–99. This reduction has important social and economic impli

Observations show snowpack has declined across much of the western United States over the period 1950–99. This reduction has important social and economic implications, as water retained in the snowpack from winter storms forms an important part of the hydrological cycle and water supply in the region. A formal model-based detection and attribution (D–A) study of these reductions is performed. The detection variable is the ratio of 1 April snow water equivalent (SWE) to water-year-to-date precipitation (P), chosen to reduce the effect of P variability on the results. Estimates of natural internal climate variability are obtained from 1600 years of two control simulations performed with fully coupled ocean–atmosphere climate models. Estimates of the SWE/P response to anthropogenic greenhouse gases, ozone, and some aerosols are taken from multiple-member ensembles of perturbation experiments run with two models. The D–A shows the observations and anthropogenically forced models have greater SWE/P reductions than can be explained by natural internal climate variability alone. Model-estimated effects of changes in solar and volcanic forcing likewise do not explain the SWE/P reductions. The mean model estimate is that about half of the SWE/P reductions observed in the west from 1950 to 1999 are the result of climate changes forced by anthropogenic greenhouse gases, ozone, and aerosols.

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California Climate Science and Data for Water Resources Management

California Department of Water Resources (DWR) | July 6th, 2015

Summary

Climate change creates critical challenges for California water resources management. The vulnerability of the water sector to climate change stems from a modified hydrol

Climate change creates critical challenges for California water resources management. The vulnerability of the water sector to climate change stems from a modified hydrology that affects the frequency, magnitude, and duration of extreme events, which, in turn, affect water quantity, quality, and infrastructure. Warmer temperatures drive the snow line higher and reduce snowpack, resulting in less water storage. Intense rainfall events will continue to affect the state, possibly leading to more frequent and/or more extensive flooding. The acceleration of sea level rise will produce higher storm surges during coastal storms. Droughts are likely to become more frequent and persistent during this century. Because California contains multiple climate zones, each region of the state will experience a combination of impacts from climate change unique to that area. While significant uncertainties still remain for local precipitation and temperature changes, projections at the regional and statewide levels are already available. Water supply managers in California have multiple tools and institutional capabilities to limit vulnerability to changing conditions, which can also serve as response mechanisms to a wide range of climate changes. This brochure summarizes the observations, projections, and challenges that climate change poses for water resources management in California, and highlights climate change content developed for the California Water Plan Update 2013.

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Fenner Valley 7-002
Fish Lake Valley 6-014
Fremont Valley 6-046
Gilroy-Hollister Valley - Llagas Area 3-003.01
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Indian Wells Valley - 6-054
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Ivanpah Valley 6-030
Jacumba Valley 7-047
Johnson Valley - Soggy Lake 7-018.01
Johnson Valley - Upper Johnson Valley 7-018.02
Joshua Tree 7-062
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Kelso Valley 6-031
Lanfair Valley 7-001
Langford Valley - Irwin 6036.02
Langford Valley - Langford Well Lake 6-036.01
Langford Valley 6-036.02
Las Posas Valley 4-008
Lavic Valley 7-014
Leach Valley 6-027
Lockwood Valley 4-017
Long Valley 6-011
Los Osos Valley - Los Osos 3-008.01
Los Osos Valley - Warden Creek 3-008.02
Lost Horse Valley 7-051
Lower Kingston Valley 6-021
Lower Mojave River Valley 6-040
Lucerne Valley 7-019
Malibu Valley 4-022
Means Valley 7-017
Mesquite Valley 6-029
Middle Amargosa Valley - 6-020
Middle Mojave River Valley 6-041
Mission Valley 9-014
Modoc) 5-004
Morongo Valley 7-020
Morro Valley 3-041
Napa-Sonoma Valley - Napa-Sonoma Lowlands 2-002.03
Needles Valley 7-044
Ocotillo-Clark Valley 7-025
Ogilby Valley 7-035
Ojai Valley 4-002
Orocopia Valley - 7-031
Owens Valley - Fish Slough 6-012.02
Owens Valley 6-012.01
Owl Lake Valley 6-088
Pahrump Valley 6-028
Palo Verde Mesa 7-039
Palo Verde Valley 7-038
Pamo Valley 9-024
Panamint Valley 6-058
Peach Tree Valley 3-032
Petaluma Valley 2-001
Pilot Knob Valley 6-051
Pinto Valley 7-006
Pipes Canyon Fault Valley 7-049
Pittsburgh Plain 2-004
Piute Valley 7-045
Pleasant Valley 4-006
Potrero Valley 9-029
Poway Valley 9-013
Raymond 4-023
Red Pass Valley 6-024
Redding Area - Anderson 5-006.03
Redding Area - Bowman 5-006.01
Redding Area - Enterprise 5-006.04
Redding Area - Millville 5-006.05
Redding Area - South Battle Creek 5-006.06
Rice Valley 7-004
Riggs Valley 6-023
Russell Valley 4-020
Sacramento Valley - Antelope 5-021.54
Sacramento Valley - Bend 5-021.53
Sacramento Valley - Butte 5-021.70
Sacramento Valley - Colusa 5-021.52
Sacramento Valley - Corning 5-021.51
Sacramento Valley - Los Molinos 5-021.56
Sacramento Valley - North American (5-021.64)
Sacramento Valley - North Yuba 5-021.60
Sacramento Valley - Red Bluff 5-021.50
Sacramento Valley - Solano 5-021.66
Sacramento Valley - South American 5-021.65
Sacramento Valley - South Yuba 5-021.61
Sacramento Valley - Sutter 5-021.62
Sacramento Valley - Vina 5-021.57
Sacramento Valley - Wyandotte Creek 5-021.69
Sacramento Valley - Yolo 5021.67
Salinas Valley - 180/400 Foot Aquifer 3-004.01
Salinas Valley - Atascadero Area 3-004.11
Salinas Valley - East Side Aquifer 3-004.02
Salinas Valley - Forebay Aquifer 3-004.04
Salinas Valley - Langley Area 3-004.09
Salinas Valley - Monterey 3-004.10
Salinas Valley - Paso Robles Area 3-004.06
Salinas Valley - Upper Valley Aquifer 3-004.05
Saline Valley 6-017
Salt Wells Valley 6-053
San Antonio Creek Valley 3-014
San Dieguito Creek 9-012
San Elijo Valley 9-023
San Felipe Valley 7-027
San Fernando Valley 4-012
San Gabriel Valley 4-013
San Jacinto 8-005
San Joaquin Valley - Chowchilla 5-022.05
San Joaquin Valley - Cosumnes (5-022.16)
San Joaquin Valley - Delta-Mendota 5-022.07
San Joaquin Valley - East Contra Costa 5-022.19
San Joaquin Valley - Eastern San Joaquin 5-022.01
San Joaquin Valley - Kaweah 5-022.11
San Joaquin Valley - Kern 5-022.14
San Joaquin Valley - Kings 5-022.08
San Joaquin Valley - Madera 5-022.06
San Joaquin Valley - Merced 5-022.04
San Joaquin Valley - Modesto 5-022.02
San Joaquin Valley - Pleasant Valley 5-022.10
San Joaquin Valley - Tracy 5-022.15
San Joaquin Valley - Tulare Lake 5-022.12
San Joaquin Valley - Tule 5-022.13
San Joaquin Valley - Turlock 5-022.03
San Joaquin Valley - Westside 5-022.09
San Joaquin Valley - White Wolf 5-022.18
San Juan Valley 9-001
San Luis Obispo Valley 3-009
San Luis Rey Valley - Lower San Luis Rey Valley 9-007.02
San Luis Rey Valley - Upper San Luis Rey Valley 9-007.01
San Marcos Area 9-032
San Mateo Valley 9-002
San Onofre Valley 9-003
San Pasqual Valley 9-010
Santa Barbara 3-017
Santa Clara River Valley - Fillmore 4-004.05
Santa Clara River Valley - Mound 4-004.03
Santa Clara River Valley - Oxnard 4-004.02
Santa Clara River Valley - Piru 4-004.06
Santa Clara River Valley - Santa Clara River Valley East 4-004.07
Santa Clara River Valley - Santa Paula 4-004.04
Santa Clara Valley - East Bay Plain 2-009.04
Santa Clara Valley - Niles Cone 2-009.01
Santa Clara Valley - San Mateo Plain 2-009.03
Santa Clara Valley - Santa Clara 2-009.02
Santa Cruz Mid-County 3-001
Santa Margarita 3-027
Santa Maria River Valley - Arroyo Grande 3-012.02
Santa Maria River Valley - Santa Maria 3-012.01
Santa Maria River Valley 3-012.02
Santa Maria Valley 9-011
Santa Rosa Valley - Santa Rosa Plain 1-055.01
Santa Ynez River Valley 3-015
Scott River Valley 1-005
Searles Valley 6-052
Seven Oaks Valley 8-008
Shasta Valley 1-004
Sierra Valley 5-012.01
Silver Lake Valley 6-034
Simi Valley 4-009
Soda Lake Valley 6-033
South San Diego River Valley 9-015
Superior Valley 6-049
Temecula Valley 9-005
Terwilliger Valley 7-026
Thousand Oaks Area 4-019
Tule Lake 1-002-01
Twentynine Palms Valley 7-010
Ukiah Valley 1-052
Upper Kingston Valley 6-022
Upper Mojave River Valley 6-042
Upper Ojai Valley 4-001
Upper Santa Ana Valley - Chino 8-002.01
Upper Santa Ana Valley - Cucamonga 8-002.02
Upper Santa Ana Valley - Rialto-Colton 8-002.04
Upper Santa Ana Valley - Riverside-Arlington 8-002.03
Upper Santa Ana Valley - San Bernardino 8-002.06
Upper Santa Ana Valley - San Timoteo 8-002.08
Upper Santa Ana Valley - Temescal 8-002.09
Upper Santa Ana Valley - Yucaipa 8-002.07
Vallecito-Carrizo Valley 7-028
Ventura River Valley - Lower Ventura River 4-003.02
Ventura River Valley - Upper Ventura River 4-003.01
Vidal Valley 7-042
Ward Valley 7-003
Warren Valley 7-012
West Salton Sea
Wingate Valley 6-019
Yuma Valley 7-036

Delta Documents Primers on Cal Water Infrastructure, Water Rights and Government

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