Anticipating Environmental and Environmental-Health Implications of Extreme Storms: ARkStorm Scenario

American Society of Civil Engineers (ASCE) | July 22nd, 2015

The ARkStorm Scenario predicts that a prolonged winter storm event across California would cause extreme precipitation, flooding, winds, physical damages, and e

The ARkStorm Scenario predicts that a prolonged winter storm event across California would cause extreme precipitation, flooding, winds, physical damages, and economic impacts. This study uses a literature review and geographic information system-based analysis of national and state databases to infer how and where ARkStorm could cause environmental damages, release contamination from diverse natural and anthropogenic sources, affect ecosystem and human health, and cause economic impacts from environmental-remediation, liability, and health care costs. Examples of plausible ARkStorm environmental and health concerns include complex mixtures of contaminants such as petroleum, mercury, asbestos, persistent organic pollutants, molds, and pathogens; adverse physical and contamination impacts on riverine and coastal marine ecosystems; and increased incidences of mold-related health concerns, some vector-borne diseases, and valley fever. Coastal cities, the San Francisco Bay area, the Sacramento-San Joaquin River Delta, parts of the Central Valley, and some mountainous areas would likely be most affected. This type of screening analysis, coupled with follow-up local assessments, can help stakeholders in California and disaster-prone areas elsewhere better plan for, mitigate, and respond to future environmental disasters.

Application of Hydrologic Simulation Program—FORTRAN (HSPF) as Part of an Integrated Hydrologic Model for the Salinas Valley, California

U.S. Geological Survey (USGS) | April 8th, 2025

The U.S. Geological Survey (USGS), in cooperation with the Monterey County Water Resources Agency, conducted studies to help evaluate the surface-water and grou

The U.S. Geological Survey (USGS), in cooperation with the Monterey County Water Resources Agency, conducted studies to help evaluate the surface-water and groundwater resources of the Salinas Valley study area, consisting of the entire Salinas River watershed and several smaller, adjacent coastal watersheds draining into Monterey Bay. The Salinas Valley study area is a highly productive agricultural region that depends on the coordinated use of surface water and groundwater to meet demand for irrigation and public water supply. To continue to meet these demands, a better understanding of the historical water balance and the effects of water-resource development on the long-term sustainability of water resources in the Salinas Valley study area is needed.

Application of Satellite Data to Model Storm Runoff Into Rosamond Dry Lake

Loyola Marymount University | October 15th, 2014

Antelope Valley is situated in Southern California and is bounded by the Tehachapi and the San Gabriel Mountains. It stretches over 2,200 mi2 and encompasses Rosamond Dry

Antelope Valley is situated in Southern California and is bounded by the Tehachapi and the San Gabriel Mountains. It stretches over 2,200 mi2 and encompasses Rosamond Dry Lake and the 1,200 mi2 watershed draining into it. The cities of Lancaster and Palmdale are the two major urban centers that lie in the watershed draining into Rosamond Dry Lake. The lake lies within the vicinity of the Edwards Air Force Base and provides an important site for aviation research and test operations in addition to ecosystem services. Hence, it is necessary to balance the need to remove water from the lake to support Edwards Air Force Base’s aircraft missions and the need to inundate the lake to protect the its surface and the ecosystem it supports. 

Application of synthetic scenarios to address water resource concerns: A management-guided case study from the Upper Colorado River Basin

Climate Services (Elsevier) | December 9th, 2017

Water managers are increasingly interested in better understanding and planning for projected resource impacts from climate change. In this management-guided study, we u

Water managers are increasingly interested in better understanding and planning for projected resource impacts from climate change. In this management-guided study, we use a very large suite of synthetic climate scenarios in a statistical modeling framework to simultaneously evaluate how (1) average temperature and precipitation changes, (2) initial basin conditions, and (3) temporal characteristics of the input climate data influence water year flow in the Upper Colorado River. The results here suggest that existing studies may underestimate the degree of uncertainty in future streamflow, particularly under moderate temperature and precipitation changes. However, we also find that the relative severity of future flow projections within a given climate scenario can be estimated with simple metrics that characterize the input climate data and basin conditions. These results suggest that simple testing, like the analyses presented in this paper, may be helpful in understanding differences between existing studies or in identifying specific conditions for physically based mechanistic modeling. Both options could reduce overall cost and improve the efficiency of conducting climate change impacts studies.

Are Atmospheric Models Too Cold in the Mountains? The State of Science and Insights from the SAIL Field Campaign

American Meteorological Society (AMS) | July 16th, 2024

Artes: An Integrated Model of Water Supply in L.A. County

University of California, Los Angeles (UCLA) | May 1st, 2017

Los Angeles faces a future with less imported water. Infrastructure and institutions will have to adapt. Understanding emerging policy and investment needs requires anal

Los Angeles faces a future with less imported water. Infrastructure and institutions will have to adapt. Understanding emerging policy and investment needs requires analysis across systems, a typically elusive goal within the diverse and disparately managed water systems of L.A. A more comprehensive analysis of water resources in Los Angeles requires an understanding of people, pipes, and plants. It could also be flexible to incorporate the fast-changing landscape of models, data, and analysis that the active agencies of the region continue to develop. With these goals in mind, we developed a water supply model for the metropolitan L.A. County region (Artes) to understand the potential for enhancing local water use across scenarios of demand and supply. The basic approach combines knowledge from engineering, hydrology, ecology, and sociology. The model is intentionally lightweight. Flexible and adaptive modeling can address many questions at multiple geographic scales, while also being able to incorporate new tools, data, and other models that are released. This model was developed to: * Determine how local groundwater, recycling and stormwater capture supplies could maximally meet water demands across L.A. County, based on current knowledge of hydrology and hydrogeology * Analyze tradeoffs in per capita water demand and available imported water supplies * Investigate system-wide effects of increased conservation * Minimize assumptions regarding data gaps * Use modeling to highlight to key gaps in scientific understanding, while creatively addressing the shortfalls in a precautionary manner. For instance, we compare modeled and historic groundwater pumping and managed aquifer recharge to assess the potential for groundwater overdraft. This manual describes important information for understanding model operations, assumptions, inputs, and outputs. The manual version (3.7) was written after development of 3 versions code for different research studies, which are in press or under review.

ARTMIP-early start comparison of atmospheric river detection tools: how many atmospheric rivers hit northern California’s Russian River watershed?

Climate Dynamics (Springer) | September 10th, 2018

Many atmospheric river detection tools (ARDTs) have now been developed. However, their relative performance is not well documented. This paper compares a diverse set of A

Many atmospheric river detection tools (ARDTs) have now been developed. However, their relative performance is not well documented. This paper compares a diverse set of ARDTs by applying them to a single location where a unique 12-year-long time-series from an atmospheric river observatory at Bodega Bay, California is available. The study quantifies the sensitivity of the diagnosed number, duration, and intensity of ARs at this location to the choice of ARDT, and to the choice of reanalysis data set. The ARDTs compared here represent a range of methods that vary in their use of different variables, fixed vs. percentile-based thresholds, geometric shape requirements, Eulerian vs. Lagrangian approaches, and reanalyses. The ARDTs were evaluated first using the datasets documented in their initial publication, which found an average annual count of 19 ± 7. Applying the ARDTs to the same reanalysis dataset yields an average annual count of 19 ± 4. Applying a single ARDT to three reanalyses of varying grid sizes (0.5°, 1.0°–2.5°) showed little sensitivity to the choice of reanalysis. While the annual average AR event count varied by about a factor of two (10–25 per year) depending on the ARDT, average AR duration and maximum intensity varied by less than ± 10%, i.e., 24 ± 2 h duration; 458 ± 44 kg m− 1 s− 1maximum IVT. ARDTs that use a much higher threshold for integrated vapor transport were compared separately, and yielded just 1–2 ARs annually on average. Generally, ARDTs that include either more stringent geometric criteria or higher thresholds identified the fewest AR events.

Assessing and communicating the impacts of climate change on the Southern California coast

California Natural Resources Agency (CNRA) | August 27th, 2018

 Over the course of this and the next century, the combination of rising sea levels, severe storms, and coastal erosion will threaten the sustainability of coastal commu

 Over the course of this and the next century, the combination of rising sea levels, severe storms, and coastal erosion will threaten the sustainability of coastal communities, development, and ecosystems as we currently know them. To clearly identify coastal vulnerabilities and develop appropriate adaptation strategies for projected increased levels of coastal flooding and erosion, coastal managers need user-friendly planning tools based on the best available climate and coastal science. In anticipation of these climate change impacts, many communities are in the early stages of climate change adaptation planning but lack the scientific information and tools to adequately address the potential impacts. In collaboration with leading scientists worldwide, 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 and translate that information using sophisticated physical process models into planning-scale physical, ecological, and economic exposure, shoreline change, and impact assessments, all delivered in two simple, user-friendly, online tools. Our results show that by the end of the 21st century, over 250,000 residents and nearly $40 billion in building value across Southern California could be exposed to coastal flooding from storms, sea level rise, and coastal change. Results for the other major population center in California (the greater San Francisco Bay Area) are also available but not explicitly discussed in this report. Together, CoSMoS has now assessed the exposure of 95% of the 26 million coastal residents of the State (17 million in Southern California) 

Assessing potential effects of changes in water use with a numerical groundwater-flow model of Carson Valley, Douglas County, Nevada, and Alpine County, California

U.S. Geological Survey (USGS) | July 1st, 2012

Assessing risk of groundwater pollution exposure from sea level rise in California

Publisher not available | June 12th, 2025

Sea level rise (SLR) will cause a groundwater table rise in coastal aquifers, and this can trigger exposure to toxic chemicals via direct contact with contaminated water

Sea level rise (SLR) will cause a groundwater table rise in coastal aquifers, and this can trigger exposure to toxic chemicals via direct contact with contaminated water or through vapor intrusion. This study presents deep learning- and explainable artificial intelligence (XAI) models to assess risk of polluted groundwater exposure due to SLR in California. Our method quantifies risk based on (1) SLR-related groundwater rise projections and (2) a prioritization of 2296 hazardous sites according to a geochemical indexing algorithm applied to groundwater data from the California State Water Resources Control Board. Our results indicate that nearly half a million people in California may be potentially exposed to marginal or poor groundwater by the end of the century. We show that feature collinearity renders numerous indicators on socioeconomics, demography, health and environment as dependent- and thus insignificant risk predictors. Our XAI models furthermore indicate that features on total population and features related to demographics (households of color and low income) and pollution source (proximity to wastewater dischargers) exert strongest controls on risk. However performance differences between randomly- and spatially cross-validated models highlight generalization challenges due to spatial autocorrelation. While the former model yields better results for California-specific analysis, only the latter model should be applied for unbiased risk assessments in other coastal regions.