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Hydroclimate Report Water Year 2016

California Department of Water Resources (DWR) | September 5th, 2017

Summary

Water year 2016 ended up being different than expected, from a climate standpoint. Water year 2015 marked the 4th year of drought in California, ending with record high t

Water year 2016 ended up being different than expected, from a climate standpoint. Water year 2015 marked the 4th year of drought in California, ending with record high temperatures, record low precipitation, and a record low snowpack. Forecasts were for a strong, wet El Nino during water year 2016, with the potential to rival large flood producing events of 1983 and 1998, higher than average sea levels, increased wave action and potential damage along the coast, warmer than average temperatures, and above-average precipitation producing storms. As a result of the cooling of the tropical Pacific sea surface temperatures, and the decay of El Nino, only some of the anticipated impacts were realized, above-average precipitation and greater than average snowpack did not come to pass. While statewide air temperatures averaged lower than the record setting 2015 water year they were still well above the long-term record, ranking water year 2016 warmest 117 of 121 since 1895. Precipitation was above normal in the Northern Sierra with the majority of precipitation falling in January and March. Precipitation in the Southern Sierra was on average with the long-term trend. Differences in Northern and Southern Sierra precipitation were due to the majority of Atmospheric River landfalls occurring in the north including the two strongest occurring in the first two weeks of March while only two Atmospheric Rivers made landfall south of Monterey Bay. Statewide snowpack was 15 percent below average and impacted the April-July snowmelt with streamflow on the Sacramento and San Joaquin Rivers by 32 percent and 22 percent below average respectively. Water year type was classified as “Below Normal” for the Sacramento River system and “Dry” for the San Joaquin. Overall, water year 2016 was an improvement to the previous four years of drought conditions with enough precipitation to offset some of the large deficits in water storage reservoirs.

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Hydroclimate Report Water Year 2017

California Department of Water Resources (DWR) | August 1st, 2018

Summary

Water year (WY) 2017 began with lingering impacts from a severe and prolonged drought mitigated slightly by the previous WY. Expectations were uncertain for the W

Water year (WY) 2017 began with lingering impacts from a severe and prolonged drought mitigated slightly by the previous WY. Expectations were uncertain for the WY with the potential for a weak La Nina event taking shape in the eastern tropical Pacific. Dry weather, cold storms or warm storms are all possible in this circulation pattern. No one foresaw the epic year that was about to unfold.

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Hydroclimate Variability in Snow-fed River Systems

American Meteorological Society (AMS) | June 25th, 2019

Summary

Snow-fed river system communities are highly sensitive to climate change because the majority of their water supply is derived from snow. A warmer climate shift

Snow-fed river system communities are highly sensitive to climate change because the majority of their water supply is derived from snow. A warmer climate shifts precipitation phase from snow to rain, altering snowpack dynamics, shifting peak streamflow timing, reducing groundwater recharge, and increasing winter and spring flooding. Warmer spring and summer temperatures further compound these “snow droughts” by increasing evapotranspiration rates and irrigation water demand. This presents critical challenges in managing seasonal water supply and demand engineered for stationary climate patterns.

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Increasing elevation of fire in the Sierra Nevada and implications for forest change

Ecological Society of America (ESA) | July 23rd, 2015

Summary

Fire in high‐elevation forest ecosystems can have severe impacts on forest structure, function and biodiversity. Using a 105‐year data set, we found increasing elevat

Fire in high‐elevation forest ecosystems can have severe impacts on forest structure, function and biodiversity. Using a 105‐year data set, we found increasing elevation extent of fires in the Sierra Nevada, and pose five hypotheses to explain this pattern. Beyond the recognized pattern of increasing fire frequency in the Sierra Nevada since the late 20th century, we find that the upper elevation extent of those fires has also been increasing. Factors such as fire season climate and fuel build up are recognized potential drivers of changes in fire regimes. Patterns of warming climate and increasing stand density are consistent with both the direction and magnitude of increasing elevation of wildfire. Reduction in high elevation wildfire suppression and increasing ignition frequencies may also contribute to the observed pattern. Historical biases in fire reporting are recognized, but not likely to explain the observed patterns. The four plausible mechanistic hypotheses (changes in fire management, climate, fuels, ignitions) are not mutually exclusive, and likely have synergistic interactions that may explain the observed changes. Irrespective of mechanism, the observed pattern of increasing occurrence of fire in these subalpine forests may have significant impacts on their resilience to changing climatic conditions.

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Indicators of Climate Change in California

California Environmental Protection Agency (CalEPA) | May 16th, 2018

Summary

From record temperatures to proliferating wildfires and rising seas, climate change poses an immediate and escalating threat to California’s environment, public health,

From record temperatures to proliferating wildfires and rising seas, climate change poses an immediate and escalating threat to California’s environment, public health, and economic vitality. Recent climate-related events – such as the devastating 2017 wildfires and the record-setting 2012-16 drought – have highlighted the challenges that confront the state as its climate continues to evolve. California has been a pioneer in addressing climate change. This report helps support policy decisions and facilitates communication about climate change by providing, in a single document, indicators characterizing its multiple aspects in California. Indicators are scientifically-based measurements that track trends in various aspects of climate change. Many indicators reveal discernable evidence that climate change is occurring in California and is having significant, measurable impacts in the state. The report’s 36 indicators are grouped into four categories, as listed below. The report discusses what these indicators show, why they are important, and the factors that may be influencing them. * Human-influenced (anthropogenic) drivers of climate change, such as greenhouse gas emissions * Changes in the state’s climate * Impacts of climate change on physical systems, such as oceans, lakes and snowpack * Impacts of climate change on biological systems – humans, vegetation and wildlife

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Influence of temperature and precipitation variability on near-term snow trends

Climatic Change (Springer) | October 17th, 2014

Summary

Snow is a vital resource for a host of natural and human systems. Global warming is projected to drive widespread decreases in snow accumulation by the end of the century

Snow is a vital resource for a host of natural and human systems. Global warming is projected to drive widespread decreases in snow accumulation by the end of the century, potentially affecting water, food, and energy supplies, seasonal heat extremes, and wildfire risk. However, over the next few decades, when the planning and implementation of current adaptation responses are most relevant, the snow response is more uncertain, largely because of uncertainty in regional and local precipitation trends. We use a large (40-member) single-model ensemble climate model experiment to examine the influence of precipitation variability on the direction and magnitude of near-term Northern Hemisphere snow trends. We find that near-term uncertainty in the sign of regional precipitation change does not cascade into uncertainty in the sign of regional snow accumulation change. Rather, temperature increases drive statistically robust consistency in the sign of future near-term snow accumulation trends, with all regions exhibiting reductions in the fraction of precipitation falling as snow, along with mean decreases in late-season snow accumulation. However, internal variability does create uncertainty in the magnitude of hemispheric and regional snow changes, including uncertainty as large as 33 % of the baseline mean. In addition, within the 40-member ensemble, many mid-latitude grid points exhibit at least one realization with a statistically significant positive trend in net snow accumulation, and at least one realization with a statistically significant negative trend. These results suggest that the direction of near-term snow accumulation change is robust at the regional scale, but that internal variability can influence the magnitude and direction of snow accumulation changes at the local scale, even in areas that exhibit a high signal-to-noise ratio.

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Interactions between snow cover and evaporation lead to higher sensitivity of streamflow to temperature

Nature Portfolio (Springer Nature) | December 4th, 2020

Summary

Estimates of potential evaporation often neglect the effects of snow cover on evaporation process. Here, we present a definition of potential evaporation that explicitly

Estimates of potential evaporation often neglect the effects of snow cover on evaporation process. Here, we present a definition of potential evaporation that explicitly accounts for landscapes that are partially covered by snow. We show that, in the presence of snowpack, our evaporation estimates differ from conventional methods that assume evaporation from a free water surface. Specifically, we find that conventional methods overestimate potential evaporation as well as aridity, taken as the ratio of atmospheric water demand to supply, in landscapes where snowfall is significant. With dwindling snow-cover, actual aridity increases, which could explain the reduction in streamflow with decreasing snowfall. We suggest that streamflow, and hence water availability, is more sensitive to temperature changes in colder than in warmer regions.

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Investigating the Role of Snow Water Equivalent on Streamflow Predictability during Drought

American Meteorological Society (AMS) | October 20th, 2022

Summary

Snowpack provides the majority of predictive information for water supply forecasts (WSFs) in snow-dominated basins across the western United States. Drought conditions t

Snowpack provides the majority of predictive information for water supply forecasts (WSFs) in snow-dominated basins across the western United States. Drought conditions typically accompany decreased snowpack and lowered runoff efficiency, negatively impacting WSFs. Here, we investigate the relationship between snow water equivalent (SWE) and April–July streamflow volume (AMJJ-V) during drought in small headwater catchments, using observations from 31 USGS streamflow gauges and 54 SNOTEL stations. A linear regression approach is used to evaluate forecast skill under different historical climatologies used for model fitting, as well as with different forecast dates. Experiments are constructed in which extreme hydrological drought years are withheld from model training, that is, years with AMJJ-V below the 15th percentile. Subsets of the remaining years are used for model fitting to understand how the climatology of different training subsets impacts forecasts of extreme drought years. We generally report overprediction in drought years. However, training the forecast model on drier years, that is, below-median years (P15, P57.5], minimizes residuals by an average of 10%in drought year forecasts, relative to a baseline case, with the highest median skill obtained in mid- to late April for colder regions. We report similar findings using a modified National Resources Conservation Service (NRCS) procedure in nine large Upper Colorado River basin (UCRB) basins, highlighting the importance of the snowpack–streamflow relationship in streamflow predictability. We propose an “adaptive sampling” approach of dynamically selecting training years based on antecedent SWE conditions, showing error reductions of up to 20% in historical drought years relative to the period of record. These alternate training protocols provide opportunities for addressing the challenges of future drought risk to water supply planning.

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Is climate change implicated in the 2013-2014 California drought? A hydrologic perspective

American Geophysical Union (AGU) | April 21st, 2015

Summary

California has experienced severe drought in 2012–2014 (which appears to be continuing into 2015), with especially low winter precipitation and mountain snowpack in wi

California has experienced severe drought in 2012–2014 (which appears to be continuing into 2015), with especially low winter precipitation and mountain snowpack in winter 2013–2014. However, the extent to which climate change is implicated in the drought, if at all, is not clear. By applying modeling and statistical approaches, we construct a historical record of California snowpack, runoff, and other hydrological variables of almost 100 years in length and use the reconstructed records to analyze climate trends in the Sierra Nevada and their impact on extreme drought events in the historic record. We confirm a general warming trend and associated decreasing trends in spring snowpack and runoff. We find that the warming may have slightly exacerbated some extreme events (including the 2013–2014 drought and the 1976–1977 drought of record), but the effect is modest; instead, these drought events are mainly the result of variability in precipitation.

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Letter to State Water Board re: Flow Criteria that use Percent of Unimpaired Flow

Delta Stewardship Council (Delta Council) | May 22nd, 2012

Summary

The proposed use of percent of unimpaired flow is a step toward improving the outlook for fish and other wildlife utilizing the San Joaquin River and its tributaries. Fal

The proposed use of percent of unimpaired flow is a step toward improving the outlook for fish and other wildlife utilizing the San Joaquin River and its tributaries. Fall-run Chinook salmon are likely to benefit from February-through-June flows that are more natural in timing and variability than current flows. Compared with the existing maze of flow standards for the San Joaquin River and its tributaries, unimpaired flow comes closer to approximating natural flow, and it does so more transparently. Caveats include: (1) flow is but one of many stressors affecting fish and wildlife; (2) the choice of flow criteria and metrics needs to serve the broader needs of ecosystems as well as individual species; (3) a chosen percentage of unimpaired flow may fall short of the minimum needed by fish and wildlife in some years; and (4) such critical years are likely to become more common as Sierra Nevada snowpacks diminish as a consequence of climate change. This qualified endorsement is based on our reading of the “Technical Report on the Scientific Basis for Alternative San Joaquin River Flow and Southern Delta Salinity Objectives” (State Water Resources Control Board, February 2012).

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Acton Valley 4-005
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Coastal Plain of Los Angeles - West Coast 4-011.03
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Coastal Plain of San Diego 9-033
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Copper Mountain Valley 7-011
Corralitos - Pajaro Valley 3-002.01
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Cuddeback Valley 6-050
Cuyama Valley 3-013
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Deadman Valley - Surprise Spring 7-013.02
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Denning Spring Valley 6-078
Downtown 2-040
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Eel River Valley 1-010
El Cajon Valley 9-016
El Mirage Valley 6-043
Elsinore - Bedfored-Coldwater 8-004.02
Elsinore - Elsinore Valley 8-004.01
Escondido Valley 9-009
Fenner Valley 7-002
Fish Lake Valley 6-014
Fremont Valley 6-046
Gilroy-Hollister Valley - Llagas Area 3-003.01
Goldstone Valley 6-048
Goleta 3-016
Harper Valley 6-047
Helendale Fault Valley 7-048
Hemet Lake Valley 8-006
Hidden Valley 4-016
Imperial Valley 7-030
Indian Wells Valley - 6-054
Iron Ridge Area 7-050
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
Kane Wash Area 6-089
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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