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.

Assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications

Nature Portfolio (Springer Nature) | January 15th, 2024

Remotely sensed evapotranspiration (ET) data offer strong potential to support data-driven approaches for sustainable water management. However, practitioners require rob

Remotely sensed evapotranspiration (ET) data offer strong potential to support data-driven approaches for sustainable water management. However, practitioners require robust and rigorous accuracy assessments of such data. The OpenET system, which includes an ensemble of six remote sensing models, was developed to increase access to field-scale (30 m) ET data for the contiguous United States. Here we compare OpenET outputs against data from 152 in situ stations, primarily eddy covariance flux towers, deployed across the contiguous United States. Mean absolute error at cropland sites for the OpenET ensemble value is 15.8 mm per month (17% of mean observed ET), mean bias error is −5.3 mm per month (6%) and r2 is 0.9. Results for shrublands and forested sites show higher inter-model variability and lower accuracy relative to croplands. High accuracy and multi-model convergence across croplands demonstrate the utility of a model ensemble approach, and enhance confidence among ET data practitioners, including the agricultural water resource management community.

Assessing the Microclimate Effects and Irrigation Water Requirements of Mesic, Oasis, and Xeric Landscapes

Hydrology (MDPI) | June 10th, 2022

Urban irrigation is an essential process in land–atmosphere interactions. It is one of the uncertain parameters of urban hydrology due to various microclimates. This s

Urban irrigation is an essential process in land–atmosphere interactions. It is one of the uncertain parameters of urban hydrology due to various microclimates. This study investigated the microclimate effects and irrigation water requirements of three landscape types in an arid region of Phoenix, AZ. The microclimate effect encompassed surface temperature, air temperature, and wind speed. The simulations of the three landscapes were conducted using ENVI-met software for the hottest day of the year (23 June 2011). The simulated model was validated using ground data. Results show that the mesic landscape induced cooling effects, both in the daytime and nighttime, by reducing surface and air temperatures. However, the mesic landscape showed highwater consumption because of a high leaf area density. The oasis landscape showed 2 degrees C more daytime cooling than the mesic landscape, but the nighttime warming (surface temperature) was comparable to the xeric landscape. The potential irrigation water requirement was 1 mm/day lower than the mesic landscape. Moreover, microclimate conditions varied spatially in each neighborhood. The xeric landscape showed lower wind speeds and air temperatures between the buildings. The wind speed variations in the three landscapes were inconclusive due to differences in building orientations and discrepancies in trees’ heights. The findings can have implications for restricting the municipal irrigation budget. In addition, they can help water managers in choosing a landscape in urban areas. Urban scientists can adapt the methodology to quantify urban ET in arid regions.

Associations between per-and polyfluoroalkyl substances (PFAS) and county-level cancer incidence between 2016 and 2021 and incident cancer burden attributable to PFAS in drinking water in the United States

Nature Portfolio (Springer Nature) | January 9th, 2025

Assumptions and Estimates for California Water Plan Update 2023 (Draft)

California Department of Water Resources (DWR) | October 14th, 2022

The draft Assumptions and Estimates for California Water Plan Update 2023 (draft A&E Report) describes key assumptions and estimates, data and data sources; improvements

The draft Assumptions and Estimates for California Water Plan Update 2023 (draft A&E Report) describes key assumptions and estimates, data and data sources; improvements to analytical tools, methods, and approaches; and the supporting documents and companion State plans being used to prepare California Water Plan Update 2023 (Update 2023), State government’s strategic plan for managing and developing water resources for sustainability and resilience. The draft A&E Report cites the statutory requirements for the California Water Plan (Water Plan), key legislative and policy drivers, assumptions, and estimates related to water data portfolios, future scenarios, water accounting, watershed resilience planning, and equity in water resource management. Also discussed are resource management strategies, the alignment of integrated watershed programs and plans, and integration and alignment of State plans.

Atlantic-Pacific influence on western U.S. hydroclimate and water resources

Nature Portfolio (Springer Nature) | September 11th, 2023