A Historical Perspective of the Interagency Ecological Program: Bridging Multi-Agency Studies into Ecological Understanding of the Sacramento-San Joaquin Delta and Estuary for 40 Years

Interagency Ecological Program (IEP) | February 8th, 2013

The Interagency Ecological Program (IEP) has been in existence in some form for almost 50 years. As the San Francisco Estuary evolved due to natural and man-caused pertur

The Interagency Ecological Program (IEP) has been in existence in some form for almost 50 years. As the San Francisco Estuary evolved due to natural and man-caused perturbations, the IEP has responded by creating and re-creating itself to ensure the best understanding of the Estuary as it was influenced by water project implementation. The goal of the IEP has always been to provide this understanding to managers responsible for water project implementation in the most protective and efficient manner given social, political, and environmental constraints. On the whole, IEP has done an outstanding job of providing consistently useful data and information in a highly complex environment. As new programs and constraints are developed to cope with the ever changing natural environment and demands of society, an understanding of the history of IEP is valuable, and to learn from past experience is wise. This descriptive history is meant to document in some detail the development, strengths, and weaknesses of this one-of-a-kind multi-agency consortium that has attempted to bridge the gap between water management and estuarine science in the most significant Estuary on the west coast of North America. Sources of information for this account are personal interviews with program participants, annual reports, IEP Newsletters, coordinator meeting summaries, director meeting summaries, management team meeting notes, and personal experiences of the author. This history may err on the side of excessive detail, but that has been intentional; the author believes it is important to have detailed information available in a single reference so that interested parties can readily obtain knowledge about IEP. Some individuals may not want to read the entire report, but can easily be guided to topics of interest by consulting Appendix A, which lists significant events that influenced the IEP by page number in the report.

A holistic stochastic model for precipitation events

Nature Portfolio (Springer Nature) | February 7th, 2025

In the western United States, much of the annual precipitation falls during relatively few storm events. When precipitation is measured as daily (or hourly, etc.) accumul

In the western United States, much of the annual precipitation falls during relatively few storm events. When precipitation is measured as daily (or hourly, etc.) accumulations, these events appear as sequences of various durations. We describe a trivariate probability distribution and assert that it provides a natural description for the durations, magnitudes, and maximum intensities of such events. We show that this distribution, in its most straightforward application, indeed describes precipitation events composed of daily observations at most long-term weather stations across the western United States, allowing for a flexible assessment of specific event probabilities and return periods with respect to their three defining components. This characterization opens the door to further understanding of risk associated with out-of-sample meteorological events.

A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA

Science of the Total Environment (Elsevier) | June 9th, 2017

Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater res

Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500m below ground surface. A database of 145 predictor variables representing well characteristics, historical and current field and landscape-scale nitrogen mass balances, historical and current land use, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The boosted regression tree (BRT) method was used to screen and rank variables to predict nitrate concentration at the depths of domestic and public well supplies. The novel approach included as predictor variables outputs from existing physically based models of the Central Valley. The top five most important predictor variables included two oxidation/reduction variables (probability of manganese concentration to exceed 50 ppb and probability of dissolved oxygen concentration to be below 0.5 ppm), field-scale adjusted unsaturated zone nitrogen input for the 1975 time period, average difference between precipitation and evapotranspiration during the years 1971–2000, and 1992 total landscape nitrogen input. Twenty-five variables were selected for the final model for log-transformed nitrate. In general, increasing probability of anoxic conditions and increasing precipitation relative to potential evapotranspiration had a corresponding decrease in nitrate concentration predictions. Conversely, increasing 1975 unsaturated zone nitrogen leaching flux and 1992 total landscape nitrogen input had an increasing relative impact on nitrate predictions. Three-dimensional visualization indicates that nitrate predictions depend on the probability of anoxic conditions and other factors, and that nitrate predictions generally decreased with increasing groundwater age.

A hydrological simulation dataset of the Upper Colorado River Basin from 1983 to 2019

Nature Portfolio (Springer Nature) | January 20th, 2022

The Upper Colorado River Basin (UCRB) is one of the most over-allocated basins in the world. It provides water for 40 million people in Colorado and downstream states of

The Upper Colorado River Basin (UCRB) is one of the most over-allocated basins in the world. It provides water for 40 million people in Colorado and downstream states of Arizona, California, Nevada, and Utah. However, the UCRB water capacity is decreasing as a combined result of climate change and anthropogenic activities. Understanding the dynamic of the UCRB water cycle is crucial for long-term and short-term water resources management.

A joint Gaussian process model of geochemistry, geophysics, and temperature for groundwater TDS in the San Ardo Oil Field, California, USA

Journal of Hydrology (Elsevier) | May 27th, 2025

A Legal Guide to the Public's Rights to Access and Use of California's Navigable Waters

California State Lands Commission (SLC) | November 20th, 2017

In California, members of the public have rights to access and use navigable waters for many beneficial uses, including, but not limited to navigation, fishing, and

In California, members of the public have rights to access and use navigable waters for many beneficial uses, including, but not limited to navigation, fishing, and recreation. These public rights are expressed in federal law, California’s Act of Admission, the California Constitution, court opinions, and state statutes. However, the public’s rights to access and use the state’s navigable waters are sometimes misunderstood. California public officials are periodically called on to address disputes about the public’s rights to access and use the state’s navigable waters. These disputes may arise between recreational water users, such as boaters, fishermen, hunters, shoreline and beach users, and adjacent private property owners. In this guide, the California State Lands Commission seeks to inform and clarify, for the public, government officials, and private property owners, the public’s rights to access and use the state’s navigable waters by summarizing the relevant legal principles.

A Literature Review and Hypsometric Analysis to Support Decisions on Trout Management Flows on the Colorado River Downstream from Glen Canyon Dam

U.S. Geological Survey (USGS) | August 7th, 2024

Fish stranding has been studied in select rivers worldwide, often with the purpose of determining how to mitigate adverse effects of dam operations on highly valued salmo

Fish stranding has been studied in select rivers worldwide, often with the purpose of determining how to mitigate adverse effects of dam operations on highly valued salmon and trout populations. However, where a reduction in trout population size is desired by resource managers, as is the case downstream of the Glen Canyon Dam on the Colorado River, flow manipulations termed trout management flows (TMFs) may be used to optimize fish stranding and mortality. To inform the design and implementation of potential future TMFs, we reviewed relevant literature to identify key factors that influence fish stranding. We found that key factors were highly interdependent and site-specific, but general trends suggest that down-ramping (decreasing flow) at rapid rates in daytime during the late spring to summer emergence period would lead to stranding of age-0 rainbow trout in shallow shoreline habitat. A hypsometric analysis was then used to predict stranding risk for age-0 rainbow trout in Glen Canyon for a range of TMFs, which incorporated existing bathymetric data and flow and habitat suitability models. Our results indicate that a TMF with a steady high flow ranging from 12,000 to 16,000 cubic feet per second (ft3/s) combined with a minimum flow ranging from 3,000 to 5,000 ft3/s may effectively strand age-0 fish while also minimizing risk to water storage in Lake Powell and other resources. This strategy implemented under normal hydropeaking operations was predicted to lead to a substantive stranding risk when paired with low flows of 5,000 ft3/s, and especially 3,000 ft3/s. However, there remains uncertainty associated with elements of implementing an effective TMF downstream from Glen Canyon Dam. The main uncertainties include (1) the down-ramp rate that maximizes stranding of age-0 trout, (2) the duration of drawdown to maximize stranding mortality while minimizing impact to downstream resources, (3) duration of high flows required for age-0 fish to colonize newly created shoreline habitat (this is only for certain TMF hydrographs), (4) number of repetitions of TMF cycles to minimize compensatory survival response, and (5) recruitment threshold of both rainbow and brown trout populations to trigger TMF implementation.

A low-to-no snow future and its impacts on water resources in the western United States

Nature Portfolio (Springer Nature) | October 26th, 2021

Anthropogenic climate change is decreasing seasonal snowpacks globally, with potentially catastrophic consequences on water resources, given the long-held reliance on sno

Anthropogenic climate change is decreasing seasonal snowpacks globally, with potentially catastrophic consequences on water resources, given the long-held reliance on snowpack in water management. In this Review, we examine the changes and trickle-down impacts of snow loss in the western United States (WUS). Across the WUS, snow water equivalent declines of ~25% are expected by 2050, with losses comparable with contemporary historical trends. There is less consensus on the time horizon of snow disappearance, but model projections combined with a new low-to-no snow definition suggest ~35–60 years before low-to-no snow becomes persistent if greenhouse gas emissions continue unabated. Diminished and more ephemeral snowpacks that melt earlier will alter groundwater and streamflow dynamics. The direction of these changes are difficult to constrain given competing factors such as higher evapotranspiration, altered vegetation composition and changes in wildfire behaviour in a warmer world. These changes undermine conventional WUS water management practices, but through proactive implementation of soft and hard adaptation strategies, there is potential to build resilience to extreme, episodic and, eventually, persistent low-to-no snow conditions. Federal investments offer a timely opportunity to address these vulnerabilities, but they require a concerted portfolio of activities that cross historically siloed physical and disciplinary boundaries.

A Machine Learning Approach to Predict Groundwater Levels in California Reveals Ecosystems at Risk

Frontiers in Earth Science (Frontiers) | December 17th, 2021

Groundwater dependent ecosystems (GDEs) are increasingly threatened worldwide, but the shallow groundwater resources that they are reliant upon are seldom monitored. In t

Groundwater dependent ecosystems (GDEs) are increasingly threatened worldwide, but the shallow groundwater resources that they are reliant upon are seldom monitored. In this study, we used satellite-based remote sensing to predict groundwater levels under groundwater dependent ecosystems across California, USA. Depth to groundwater was modelled for a 35-years period (1985–2019) within all groundwater dependent ecosystems across the state (n = 95,135). Our model was developed within Google Earth Engine using Landsat satellite imagery, climate data, and field-based groundwater data [n = 627 shallow (< 30 m) monitoring wells] as predictors in a Random Forest model. Our findings show that 1) 44% of groundwater dependent ecosystems have experienced a significant long-term (1985–2019) decline in groundwater levels compared to 28% with a significant increase; 2) groundwater level declines have intensified during the most recent two decades, with 39% of groundwater dependent ecosystems experiencing declines in the 2003–2019 period compared to 27% in the 1985–2002 period; and 3) groundwater declines are most prevalent within GDEs existing in areas of the state where sustainable groundwater management is absent. Our results indicate that declining shallow groundwater levels may be adversely impacting California’s groundwater dependent ecosystems. Particularly where groundwater levels have fallen beneath plant roots or streams thereby affecting key life processes, such as forest recruitment/succession, or hydrological processes, such as streamflow that affects aquatic habitat. In the absence of groundwater monitoring well data, our model and findings can be used to help state and local water agencies fill in data gaps of shallow groundwater conditions, evaluate potential effects on GDEs, and improve sustainable groundwater management policy in California.

A Machine Learning Tool for Design of Behavioral Fish Barriers in the Sacramento-San Joaquin River Delta

U.S. Geological Survey (USGS) | January 16th, 2024

Survival of out-migrating juvenile salmonids (Oncorhynchus spp.) through the Sacramento-San Joaquin River Delta averages less than 33 percent, depending on water flow thr

Survival of out-migrating juvenile salmonids (Oncorhynchus spp.) through the Sacramento-San Joaquin River Delta averages less than 33 percent, depending on water flow through the delta, and is partially governed by the distribution of fish among three Sacramento River distributaries: Sutter, Steamboat, and Georgiana sloughs. Behavioral altering structures in the junctions of the distributaries can effectively increase entrainment into favorable routes, thereby increasing through-delta (Verona to Chips Island, California) survival. The effectiveness of these structures, hence forth called “behavioral barriers,” are dependent on shape, length, location, barrier type, and water velocity, which is governed by Sacramento River discharge (hereinafter referred to as “flow”).