Precipitation shifts over western North America as a result of declining Arctic sea ice cover: The coupled system response

American Meteorological Society (AMS) | July 21st, 2009

Changes in Arctic sea ice cover have the potential to impact midlatitude climate. A previous sensitivity study utilizing the National Center for Atmospheric Resea

Changes in Arctic sea ice cover have the potential to impact midlatitude climate. A previous sensitivity study utilizing the National Center for Atmospheric Research’s (NCAR) atmospheric general circulation model [AGCM; Community Climate Model, version 3 (CCM3)] to explore climate sensitivity to declining Arctic sea ice cover suggested that, as Arctic sea ice cover is reduced, precipitation patterns over western North America will shift toward dryer conditions in southwestern North America and wetter conditions in northwestern North America. Here, three complementary lines of research validate and explore the robustness of this possible climate change impact: 1) repetition of the previous sensitivity study (specified constant Arctic sea ice cover and atmospheric CO2) with an updated version of the NCAR AGCM [third Community Atmosphere Model (CAM3)], 2) investigation of the climate response to dynamically reduced Arctic sea ice cover (driven by a quadrupling of atmospheric CO2) in the coupled NCAR Community Climate System Model.

Precipitation variability increases in a warmer climate

Nature Portfolio (Springer Nature) | December 21st, 2017

Understanding changes in precipitation variability is essential for a complete explanation of the hydrologic cycle’s response to warming and its impacts. Whil

Understanding changes in precipitation variability is essential for a complete explanation of the hydrologic cycle’s response to warming and its impacts. While changes in mean and extreme precipitation have been studied intensively, precipitation variability has received less attention, despite its theoretical and practical importance. Here, we show that precipitation variability in most climatemodels increases over a majority of global land area in response to warming (66% of land has a robust increase in variability of seasonal-mean precipitation). Comparing recent decades to RCP8.5 projections for the end of the 21st century, we find that in the global, multi-model mean, precipitation variability increases 3–4% K−1 globally, 4–5% K−1 over land and 2–4% K−1 over ocean, and is remarkably robust on a range of timescales from daily to decadal. Precipitation variability increases by at least as much as mean precipitation and less than moisture and extreme precipitation for most models, regions, and timescales. We interpret this as being related to an increase in moisture which is partially mitigated by weakening circulation. We show that changes in observed daily variability in station data are consistent with increased variability.

Predation on Fishes in the Sacramento–San Joaquin Delta: Current Knowledge and Future Directions

University of California, Davis (UC Davis) | July 1st, 2016

The Delta is a diverse, highly modified aquatic system. This paper reviews relevant predator–prey theory, describes data on predator–prey relationships of Delta fishe

The Delta is a diverse, highly modified aquatic system. This paper reviews relevant predator–prey theory, describes data on predator–prey relationships of Delta fishes, ranks predator consumption rates, and presents hypotheses for the effects of predation on native and invasive species. Thiry-two different predator categories and 41 different prey categories are identified. The analysis yielded few generalizations regarding predator–prey interactions for Delta fishes. The only evidence for predator specialization occurred in Prickly Sculpin which, when it consumed fishes, ate mostly native species. Data for reptilian, avian, and mammalian predators were sparse; however, these predators may be significant fish predators in altered habitats or when hatchery salmonids are released. The database for predators and their fish prey was not strong, and long-term dietary studies combined with prey availability and behavioral and experimental studies are needed. The behavioral effects of contaminants on prey species also warrant further examination. Although it has been suggested that a reduction in the Striped Bass population be implemented to reduce predation mortality of Chinook Salmon, the large number of salmon predators in the Delta make it unlikely that this effort will significantly affect salmon mortality.

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 California Water-Year Types Using Seasonal Climate Forecasts

American Meteorological Society (AMS) | August 1st, 2025

Predicting flood damage probability across the conterminous United States

Environmental Research Letters (IOP) | February 21st, 2022

Floods are the leading cause of natural disaster damages in the United States, with billions of dollars incurred every year in the form of government payouts, property da

Floods are the leading cause of natural disaster damages in the United States, with billions of dollars incurred every year in the form of government payouts, property damages, and agricultural losses. The Federal Emergency Management Agency oversees the delineation of floodplains to mitigate damages, but disparities exist between locations designated as high risk and where flood damages occur due to land use and climate changes and incomplete floodplain mapping. We harnessed publicly available geospatial datasets and random forest algorithms to analyze the spatial distribution and underlying drivers of flood damage probability (FDP) caused by excessive rainfall and overflowing water bodies across the conterminous United States. From this, we produced the first spatially complete map of FDP for the nation, along with spatially explicit standard errors for four selected cities. We trained models using the locations of historical reported flood damage events (n = 71 434) and a suite of geospatial predictors (e.g. flood severity, climate, socio-economic exposure, topographic variables, soil properties, and hydrologic characteristics). We developed independent models for each hydrologic unit code level 2 watershed and generated a FDP for each 100 m pixel. Our model classified damage or no damage with an average area under the curve accuracy of 0.75; however, model performance varied by environmental conditions, with certain land cover classes (e.g. forest) resulting in higher error rates than others (e.g. wetlands). Our results identified FDP hotspots across multiple spatial and regional scales, with high probabilities common in both inland and coastal regions. The highest flood damage probabilities tended to be in areas of low elevation, in close proximity to streams, with extreme precipitation, and with high urban road density. Given rapid environmental changes, our study demonstrates an efficient approach for updating FDP estimates across the nation.

Predicting Redox Conditions in Groundwater at a National Scale Using Random Forest Classification

American Chemical Society (ACS) | March 7th, 2024

Predicting Sediment Bulk Density for San Francisco Estuary

University of California, Davis (UC Davis) | December 19th, 2025

Sediment bulk density (ρ-dry) and particle size are two important parameters for predicting sediment bed erosion. ρ-dry, however, is difficult to measure accurately. Th

Sediment bulk density (ρ-dry) and particle size are two important parameters for predicting sediment bed erosion. ρ-dry, however, is difficult to measure accurately. The units of ρdry have not been consistently reported in the literature, leading to confusion, particularly in the calculation of sediment budgets that typically require integrating mass-based and volumetric components. Relationships between ρdry and sediment composition have been developed for multiple regions and differ between systems. Developing a system-specific predictive model for ρdry can help fill data gaps and improve sediment budgets, model accuracy, and estimates of quantities of sediment needed for restoration. In this study, we investigate whether ρdry in San Francisco Estuary can be predicted from organic carbon content or percent of fines, which are more easily or frequently measured than ρdry. We compiled sediment properties from samples collected over the past decade throughout the intertidal and subtidal regions of San Francisco Bay and the Sacramento–San Joaquin Delta to examine this relationship. Sample composition ranged from 2.18 to 99.97% fines (particles < 0.0625 mm), ρ-dry ranged from 0.22 to 1.60 g cm-3, and organic carbon ranged from 0.06 to 7.98%. Regression analysis indicates that the percent of fines explains 93% of the variation of ρ-dry (p-value < 0.05, N = 81). The coefficient of determination decreased by ~1% when organic carbon was incorporated in the regression analysis. Comparison of this predictive ρ-dry model to four published models based on samples from other regions supports previous findings that the relationship between ρdry and grain size may vary by system. We also examined additional factors that may affect sediment erodibility, such as hydrographic and oceanographic conditions. Classification of sample sites as intertidal vs. subtidal or wavy vs. non-wavy each significantly explained the residuals from the ρdry model, and both intertidal and wavy conditions were associated with higher ρ-dry values.

Predicting Streamflow Elasticity Based on Percolation Theory and Ecological Optimality

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

Predictions of groundwater PFAS occurrence at drinking water supply depths in the United States

American Association for the Advancement of Science (AAAS) | October 24th, 2024