Use of the SmeltCam as an Efficient Fish-Sampling Alternative Within the San Francisco Estuary

University of California, Davis (UC Davis) | June 1st, 2021

Resource managers often rely on long-term monitoring surveys to detect trends in biological data. However, no survey gear is 100% efficient, and many sources of bias can

Resource managers often rely on long-term monitoring surveys to detect trends in biological data. However, no survey gear is 100% efficient, and many sources of bias can be responsible for detecting or not detecting biological trends. The SmeltCam is an imaging apparatus developed as a potential sampling alternative to long-term trawling gear surveys within the San Francisco Estuary, California, to reduce handling stress on sensitive species like the Delta Smelt (Hypomesus transpacificus). Although believed to be a reliable alternative to closed cod-end trawling surveys, no formal test of sampling efficiency has been implemented using the SmeltCam. We used a paired deployment of the SmeltCam and a conventional closed cod-end trawl within the Napa River and San Pablo Bay, a Bayesian binomial N-mixture model, and data simulations to determine the sampling efficiency of both deployed gear types to capture a Delta Smelt surrogate (Northern Anchovy, Engraulis mordax) and to test potential bias in our modeling framework. We found that retention efficiency—a component of detection efficiency that estimates the probability a fish is retained by the gear, conditional on gear contact—was slightly higher using the SmeltCam (mean = 0.58) than the conventional trawl (mean = 0.47, Probability SmeltCam retention efficiency > trawl retention efficiency = 94%). We also found turbidity did not affect the SmeltCam’s retention efficiency, although total fish density during an individual tow improved the trawl’s retention efficiency. Simulations also showed the binomial model was accurate when model assumptions were met. Collectively, our results suggest the SmeltCam to be a reliable alternative to sampling with conventional trawling gear, but future tests are needed to confirm whether the SmeltCam is as reliable when applied to taxa other than Northern Anchovy over a greater range of conditions.

User Manual for the California Central Valley Groundwater-Surface Water Simulation Model

California Department of Water Resources (DWR) | June 13th, 2013

This report describes the input and output files for the California Central Valley Groundwater-Surface Water Simulation Model (C2VSim). C2VSim is an integrated numeri

This report describes the input and output files for the California Central Valley Groundwater-Surface Water Simulation Model (C2VSim). C2VSim is an integrated numerical model simulating land surface processes and groundwater and surface water flows in the main alluvial aquifer system of California’s Central Valley (figure 1). C2VSim was developed using the Integrated Water Flow Model (IWFM) application, which couples a three-dimensional finite element groundwater simulation process with one-dimensional land surface, stream flow, lake, unsaturated zone and smallstream watershed simulation processes. The C2VSim version described in this report runs under IWFM version 3.02 and utilizes a coarse grid, and is thus referred to as version 3.02-CG. In addition, the input files for the C2VSim model are regularly updated to correct errors, incorporate improved input data or extend the simulation time period. These updates are referred to as revisions; this report describes the data in revision R374, released in June 2013. The C2VSim model inputs include monthly historical precipitation, stream inflows, surface water diversions, land use and crop acreages for the simulation period, October 1921 through September 2009. C2VSim dynamically calculates crop water demands, allocates contributions from precipitation, soil moisture and surface water diversions, and calculates the groundwater pumpage required to meet the remaining demand. The coarse grid version of the C2VSim model incorporates a finite element grid with 1392 elements, grouped into 21 water budget subregions (figure 1), which are further grouped by drainage basin into five hydrologic regions. The model subregions are based on Depletion Study Areas (DSAs), originally created by the DWR Division of Planning for estimating regional water supplies and demands. Hydrologic parameters (including hydraulic conductivities, storage parameters and recession coefficients) were calibrated to match observed values including groundwater heads, groundwater head differences between well pairs, surface water flows, and stream-groundwater flows for the period between September 1975 and October 2003. The model simulates the historical response of the Central Valley’s groundwater flow system to historical stresses, and can also be used to simulate the response to projected future stresses. Agricultural groundwater pumping is not monitored in the Central Valley, and the C2VSim model provides pumpage estimates that are considered robust because they are constrained spatially and temporally by the estimated demand and surface water supplies. The calibrated model is also being used as the basis for the groundwater flow component of CalSim 3, a water resources planning model for simulating operation of the California State Water Project (SWP) and Federal Central Valley Project (CVP).

User’s Manual for the Draper Climate-Distribution Software Suite with Data-Evaluation Tools

U.S. Geological Survey (USGS) | March 20th, 2019

Development of a time series of spatially distributed climate data is an important step in the process of developing physically based environmental models requiri

Development of a time series of spatially distributed climate data is an important step in the process of developing physically based environmental models requiring distributed inputs of climate data beyond what is available from observations collected at climate stations. To prepare inputs required for model-mapping units across the study area, climate data (temperature and precipitation) are distributed by combining data from gridded surfaces of mean-monthly climate-data values with (often) widely spaced daily pointobservations. Examples of climate-data files used to develop PRMS-formatted input files for the Merced River Basin Precipitation-Runoff Modeling System (PRMS) are includedin this manual. The Draper Climate-Distribution Software Suite (Draper Suite) consists of the Draper climate-distribution program (Draper) and several supporting pre- and post-processing applications. Draper combines spatially distributed input in the form of monthly averaged values for precipitation, maximum temperature, and minimum temperature with daily observed data from climate stations to estimate distributed climate-data values at predefined locations across a study area (typically adrainage basin) on a daily time step. Alternative methods are used when station data are limited or missing for a particular day. Draper uses a set of required and optional input andoutput files with defined formats and naming conventions. Ashell application also is available to manage multiple runs of the Draper application. Other applications in the Draper Suite include (1) a toolto find and interactively remove outliers in the input data, (2) atool to check and enforce a minimum daily temperature range, and (3) a tool to view output diagnostic information as time- series graphs. These tools can be used iteratively to evaluate and improve the results from Draper as part of a work flow involving physically-based environmental models, such as the Precipitation-Runoff Modeling System (PRMS).

USGS Science at Work in the Delta Estuary

U.S. Geological Survey (USGS) | November 19th, 2013

The San Francisco Bay and Sacramento-San Joaquin Delta form one of the largest estuaries in the United States. The “Bay-Delta” system provides water to more than 25 m

The San Francisco Bay and Sacramento-San Joaquin Delta form one of the largest estuaries in the United States. The “Bay-Delta” system provides water to more than 25 million California residents and vast farmlands, as well as key habitat for birds, fish, and other wildlife. To help ensure the health of this crucial estuary, the U.S. Geological Survey, in close cooperation with partner agencies and organizations, is providing science essential to addressing societal issues associated with water quantity and quality, sediment transportation, environmental contamination, animal health and status, habitat restoration, hazards, ground subsidence, and climate change.

USGS Science at Work in the San Francisco Bay and Sacramento-San Joaquin Delta Estuary

U.S. Geological Survey (USGS) | ?

The San Francisco Bay and Sacramento-San Joaquin Delta form one of the largest estuaries in the United States. The “Bay-Delta” system provides water to more than 25 m

The San Francisco Bay and Sacramento-San Joaquin Delta form one of the largest estuaries in the United States. The “Bay-Delta” system provides water to more than 25 million California residents and vast farmlands, as well as key habitat for birds, fish, and other wildlife. To help ensure the health of this crucial estuary, the U.S. Geological Survey, in close cooperation with partner agencies and organizations, is providing science essential to addressing societal issues associated with water quantity and quality, sediment transportation, environmental contamination, animal health and status, habitat restoration, hazards, ground subsidence, and climate change.

Using a Time-of-Travel Sampling Approach to Quantify Per- and Polyfluoroalkyl Substances (PFAS) Stream Loading and Source Inputs in a Mixed-Source, Urban Catchment

American Chemical Society (ACS) | September 16th, 2024

Using Conceptual Models and Decision-Support Tools to Guide Ecosystem Restoration Planning and Adaptive Management: An Example from the Sacramento–San Joaquin Delta, California

University of California, Davis (UC Davis) | October 1st, 2012

The Sacramento–San Joaquin Delta (the Delta) is located on the western edge of California’s Central Valley and is of critical ecological and economic importance. H

The Sacramento–San Joaquin Delta (the Delta) is located on the western edge of California’s Central Valley and is of critical ecological and economic importance. However, ecosystem alterations for human uses changed many of the Delta’s natural processes, and it is now considered in need of restoration. An approach was developed to evaluate and rank restoration actions in the Delta under the Ecosystem Restoration Program’s Delta Regional Ecosystem Restoration Implementation Plan (DRERIP). The DRERIP approach provides an explicit framework for evaluating restoration actions, using linked conceptual models, an action evaluation procedure, and a decision-support tool. Conceptual models allow scientists and managers to synthesize scientific information and make qualitative predictions about ecosystem function and restoration outcomes to guide and focus restoration efforts. The action evaluation procedure is a structured assessment of restoration actions. The procedure clearly describes actions to be evaluated, assesses the magnitude (importance and scale) and certainty of anticipated ecological outcomes, estimates degrees of worth (achieving intended outcomes) and risk (causing adverse consequences), evaluates the reversibility of the action, and identifies opportunities for learning. The values for worthiness, risk, reversibility, and learning opportunity are used in the decision- support tool to determine the fate of a proposed action. The decision-support tool is a structured decision tree that determines the disposition of an action: whether a restoration project should be discarded, revised with a different approach and re-evaluated, or implemented; and, if implemented, at what scale (targeted research, pilot project, or full implementation). The DRERIP approach provides managers with a valuable tool for restoration planning, and a foundation for integration with quantitative methods for a comprehensive ecosystem restoration plan.

Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits

National Academy of Sciences (NAS) | December 1st, 2016

Much of the United States faces chronic or episodic water shortages. It is the topic of daily news in the West, where a historic 4-year drought has caused California to

Much of the United States faces chronic or episodic water shortages. It is the topic of daily news in the West, where a historic 4-year drought has caused California to restrict the delivery of water to cities and farms. At the same time, the Midwest and Northeast have received drenching rains and heavier than normal snow. Against this backdrop—of not enough water or too much water—the National Academies of Sciences, Engineering, and Medicine’s Water Science and Technology Board initiated a study on the beneficial use of stormwater and graywater. Graywater is a year-round source of water for nonpotable use, and use of urban stormwater can augment local water supplies, reduce demand for imported water, and lessen impacts from discharge.

Using Landsat and MODIS satellite collections to examine extent, timing, and potential impacts of surface water inundation in California croplands

Remote Sensing Applications: Society and Environment (RSASE) | October 1st, 2022

The state of California, United States of America produces many crop products that are both utilized domestically and exported throughout the world. With nearly 39,000 km

The state of California, United States of America produces many crop products that are both utilized domestically and exported throughout the world. With nearly 39,000 km2 of croplands, monitoring unintentional and intentional surface water inundation is important for water resource management and flood hazard readiness. We examine inundation dynamics in California croplands from 2003 to 2020 by intersecting monthly surface water maps (n = 216 months) derived using two satellite remote sensing platforms (Landsat and Moderate Resolution Imaging Spectroradiometer [MODIS]) with a high-quality cropland map generated by the California Department of Water Resources. Surface water maps were produced using the Dynamic Surface Water Extent model, in which satellite image pixels are classified into different levels of detection confidence. Our analysis focused on calculating monthly and annual occurrence of “high confidence” water for each satellite collection across eight cropland types and 58 counties. Results indicate that 49.9% (MODIS) to 56.4% (Landsat) of croplands were inundated at least once during the 18-year timespan. Rice crops, due to their unique need of consistent surface water and dominance as a crop type in CA, had the highest proportion of and mean annual inundation area, while citrus crops had the lowest. Mean monthly inundation patterns in most croplands followed California's precipitation patterns with high inundation during the winter and spring rainy season. At the county level, croplands in the southern Central Valley typically had high occurrences of inundation in conjunction with large crop areas. Exposure and sensitivity of inundation for three crop types (citrus, deciduous, and vineyards) that are typically less associated with intentional inundation were geographically variable, but overall were generally highest in counties in the southern Central Valley, California's primary agricultural region. Flood and precipitation related crop insurance claims indicated that rice had the highest mean indemnity payout for any month with damages typically occurring in March and April. Insurance claims were also high in deciduous fruit and nut crops, which had peak damages in February. A comparison between inundation results and insurance claims suggests that the inundation mapped by our process coincides with claim activity. These data elucidate water inundation patterns across the state that can serve to inform farmers, insurers, decision makers, resource managers, and flood mitigation professionals.

Using machine learning to predict 1,2,3-trichloropropane contamination from legacy non-point source pollution of groundwater in California's Central Valley

Elsevier | May 6th, 2023

1,2,3-tricholoropropane (TCP) is an impurity common in nematicides applied to agricultural soils from the 1940s to the 1980s. Evidence from animal studies indicates t

1,2,3-tricholoropropane (TCP) is an impurity common in nematicides applied to agricultural soils from the 1940s to the 1980s. Evidence from animal studies indicates that TCP is a probable human carcinogen. TCP leaches through the soil into groundwater where it persists and contaminates thousands of wells in Asia, Europe, and North America. In California, TCP contaminates drinking water wells, with the highest levels of TCP beneath agricultural land used to grow grapevines. This study performs a mass balance and evaluates the ability of three types of tree-based machine learning models to predict TCP concentration in California's Central Valley aquifer system: classification and regression trees (CART), Random Forest (RF), and Boosted Regression Trees (BRT). To construct the models, multiple spatial explanatory variables were used, including historical agricultural land use data, irrigation levels, precipitation, soil type, groundwater age, redox state, and the presence of the co-contaminant nitrate. To estimate the amount of TCP applied to farmland in California, state historical pesticide and land use documents were used in the mass balance. Between 110,000 and 4,300,000 kg of TCP are estimated to have accumulated in the subsurface. Machine learning models indicate that the most important explanatory variables to predict TCP contamination of groundwater are precipitation, redox state, and the presence of the co-contaminant nitrate. Additionally, a 1000-m buffer area offers a slightly higher predictive performance as compared to 500-m and 1500-m buffers. Furthermore, the RF model outperforms CART and BRT for predictive performance. Finally, modeling using decision trees can predict TCP contamination levels in areas where monitoring is lacking, help target future TCP monitoring efforts, and aid in identifying areas to avoid when drilling new drinking water wells.