Predicted Water-Level and Water-Quality Effects of Artificial Recharge in the Upper Coachella Valley, California, Using a Finite-Element Digital Model

U.S. Geological Survey (USGS) | April 15th, 1978

This study was begun in mid-1973 by the U.S. Geological Survey in cooperation with the Desert Water Agency (DWA) and the Coachella Valley County Water District (CVCWD). T

This study was begun in mid-1973 by the U.S. Geological Survey in cooperation with the Desert Water Agency (DWA) and the Coachella Valley County Water District (CVCWD). The purpose of the study was to (1) analyze the present water quality conditions of the ground-water basin, (2) determine the water-level changes that will result from recharging the aquifer, and (3) determine the water-quality changes that will result from recharging the aquifer. The study included: (1) Collecting, evaluating, tabulating, and computer processing all available ground-water-quality data for the study area; (2) describing the areal distribution of water quality throughout the ground-water basin; (3) updating the pumpage and other hydrologic data compiled for the analog model of the study area (Tyley, 1974); (4) developing a digital hydraulic (flow) model utilizing the finite-element method; and (5) developing a digital solute-transport (water quality) model utilizing the finite-element method. This report presents the results of the 3-year study and the predictions of the possible effects of ground-water recharge on the water resources of the upper Coachella Valley.

Predicting Streamflow Elasticity Based on Percolation Theory and Ecological Optimality

American Geophysical Union (AGU) | July 20th, 2023

Preliminary Evaluation of the Hydrogeologic System in Owens Valley, California

U.S. Geological Survey (USGS) | January 8th, 1988

Owens Valley is a major source of water for southern California and presently (1986) provides more than 60 percent of the supply for Los Angeles. Since 1970, ground-water

Owens Valley is a major source of water for southern California and presently (1986) provides more than 60 percent of the supply for Los Angeles. Since 1970, ground-water withdrawal from Owens Valley has increased, and a decline in the health of vegetation has been reported. In 1982, a cooperative project to study the hydrogeology and plant ecology of Owens Valley was begun by Inyo County, the Los Angeles Department of Water and Power, and the U.S. Geological Survey. As part of this project, the available data and present hydrologic concepts of Owens Valley were evaluated by using a ground-waterflow model. Results of this preliminary evaluation are being used to guide data collection and the development of more sophisticated hydrologic models.

Preliminary hydrogeologic assessment near the boundary of the Antelope Valley and El Mirage Valley groundwater basins, California

U.S. Geological Survey (USGS) | July 19th, 2017

Prioritizing Candidate Green Infrastructure Sites within the City of Ukiah: A Demonstration of the Site Locator Tool of GreenPlan-IT. Report prepared for the City of Ukiah Department of Public Works under Supplemental Environmental Project # R1-018-0024

San Francisco Estuary Institute (SFEI) | April 1st, 2019

Green infrastructure (GI), also known as Low Impact Development (LID), has emerged as an integral aspect of multi-benefit, watershed approaches to address concerns about

Green infrastructure (GI), also known as Low Impact Development (LID), has emerged as an integral aspect of multi-benefit, watershed approaches to address concerns about stormwater quality and quantity in an urban environment. When carefully applied, GI installations, such as rain gardens, tree-well planters, and permeable pavement, can be cost-effective, resilient ways to manage storm water at its source with measurable, cumulative environmental and community benefits. 

Probabilistic estimates of future changes in California temperature and precipitation using statistical and dynamical downscaling

Climate Dynamics (Springer) | March 30th, 2012

Sixteen global general circulation models were used to develop probabilistic projections of temperature (T) and precipitation (P) changes over California by the 2060s.

Sixteen global general circulation models were used to develop probabilistic projections of temperature (T) and precipitation (P) changes over California by the 2060s. The global models were downscaled with two statistical techniques and three nested dynamical regional climate models, although not all global models were downscaled with all techniques. Both monthly and daily timescale changes in T and P are addressed, the latter being important for a range of applications in energy use, water management, and agriculture. The T changes tend to agree more across downscaling techniques than the P changes. Year-to-year natural internal climate variability is roughly of similar magnitude to the projected T changes. In the monthly average, July temperatures shift enough that that the hottest July found in any simulation over the historical period becomes a modestly cool July in the future period. Januarys as cold as any found in the historical period are still found in the 2060s, but the median and maximum monthly average temperatures increase notably. Annual and seasonal P changes are small compared to interannual or intermodel variability. However, the annual change is composed of seasonally varying changes that are themselves much larger, but tend to cancel in the annual mean. Winters show modestly wetter conditions in the North of the state, while spring and autumn show less precipitation. The dynamical downscaling techniques project increasing precipitation in the Southeastern part of the state, which is influenced by the North American monsoon, a feature that is not captured by the statistical downscaling.

Probabilistic Subsidence Forecast Model for the California Aqueduct Subsidence Program, San Joaquin Valley, California: Revision 1 Design Report

California Department of Water Resources (DWR) | October 4th, 2024

This report documents the development of a probabilistic subsidence forecast model for simulating a plausible range of future land-surface altitude conditions along the C

This report documents the development of a probabilistic subsidence forecast model for simulating a plausible range of future land-surface altitude conditions along the California Aqueduct (Aqueduct) and San Luis Canal in the San Joaquin Valley (SJV), with an emphasis on areas of localized subsidence (i.e., “subsidence bowls”). The model forecasts will be used to inform long-term planning and on-going analyses of potential investments needed to provide a suitable level of performance for the Aqueduct. The forecast model is primarily based on an empirical relationship between historical subsidence rates and annual water deliveries from the Central Valley Project (CVP) and State Water Project (SWP). A key assumption of the model is that the rate of groundwater overdraft, which contributes to loss of aquifer storage and permanent land subsidence, is correlated with CVP and SWP deliveries, and specifically with higher groundwater storage loss during severe drought years. Another key assumption is that the same rates of subsidence will continue even after groundwater levels decline and extraction may be coming from deeper parts of the aquifer system. If the geology and/or aquifer properties change dramatically in response, then these new conditions may have an unmodeled impact on future rates. 

Projected 21st Century Coastal Flooding in the Southern California Bight. Part 1: Development of the Third Generation CoSMoSModel

Journal of Marine Science and Engineering (MDPI) | May 24th, 2018

Due to the effects of climate change over the course of the next century, the combination of rising sea levels, severe storms, and coastal change will threaten the susta

Due to the effects of climate change over the course of the next century, the combination of rising sea levels, severe storms, and coastal change will threaten the sustainability of coastal communities, development, and ecosystems as we know them today. To clearly identify coastal vulnerabilities and develop appropriate adaptation strategies due to projected increased levels of coastal flooding and erosion, coastal managers need local-scale hazards projections using the best available climate and coastal science. In collaboration with leading scientists world-wide, the USGS designed the Coastal Storm Modeling System (CoSMoS) to assess the coastal impacts of climate change for the California coast, including the combination of sea-level rise, storms, and coastal change. In this project, we directly address the needs of coastal resource managers in Southern California by integrating a vast range of global climate change projections in a thorough and comprehensive numerical modeling framework. In Part 1 of a two-part submission on CoSMoS, methods and the latest improvements are discussed, and an example of hazard projections is presented. Click here for Part 2.

Projected 21st Century Coastal Flooding in the Southern California Bight. Part 2: Tools for Assessing Climate Change-Driven Coastal Hazards and Socio-Economic Impacts

Journal of Marine Science and Engineering (MDPI) | July 2nd, 2018

This paper is the second of two that describes the Coastal Storm Modeling System (CoSMoS) approach for quantifying physical hazards and socio-economic hazard exposure in

This paper is the second of two that describes the Coastal Storm Modeling System (CoSMoS) approach for quantifying physical hazards and socio-economic hazard exposure in coastal zones affected by sea-level rise and changing coastal storms. The modelling approach, presented in Part 1, downscales atmospheric global-scale projections to local scale coastal flood impacts by deterministically computing the combined hazards of sea-level rise, waves, storm surges, astronomic tides, fluvial discharges, and changes in shoreline positions. The method is demonstrated through an application to Southern California, United States, where the shoreline is a mix of bluffs, beaches, highly managed coastal communities, and infrastructure of high economic value. Results show that inclusion of 100-year projected coastal storms will increase flooding by 9–350% (an additional average 53.0 16.0 km2) in addition to a 25–500 cm sea-level rise. The greater flooding extents translate to a 55–110% increase in residential impact and a 40–90% increase in building replacement costs. To communicate hazards and ranges in socio-economic exposures to these hazards, a set of tools were collaboratively designed and tested with stakeholders and policy-makers; these tools consist of two web-based mapping and analytic applications as well as virtual reality visualizations. To reach a larger audience and enhance usability of the data, outreach and engagement included workshop-style trainings for targeted end-users and innovative applications of the virtual reality visualizations.

Projected Changes in California’s Precipitation Intensity-Duration-Frequency Curves

California Public Utilities Commission (CPUC) | August 15th, 2018

Traditionally, infrastructure design and rainfall-triggered landslide models rely on the notion of stationarity, which assumes that the statistics of hydroclimati

Traditionally, infrastructure design and rainfall-triggered landslide models rely on the notion of stationarity, which assumes that the statistics of hydroclimatic extremes (e.g., rainfall, streamflow, etc.) do not change significantly over time. However, during the last century, we have observed a warming climate with more intense precipitation extremes in some regions, likely due to increases in the water holding capacity of the atmosphere. Consequently, infrastructure and natural slopes will likely face more severe climatic conditions, with potential human and socioeconomic consequences. Here, we outline a framework for quantifying climate change impacts on natural and man-made infrastructure using bias-corrected multi-model simulations of historical and projected precipitation extremes. The approach evaluates changes in rainfall intensity-duration- frequency (IDF) curves and their uncertainty bounds using a non-stationary model based on Bayesian inference. We show that highly populated areas across California may experience extreme precipitation that is more intense and twice as frequent, relative to historical records, despite the expectation of unchanged annual mean precipitation. Since IDF curves are widely used for infrastructure design and risk assessment, the proposed framework offers an avenue for assessing infrastructure resilience and landslide hazard in a warming climate.