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The dairy industry in the San Joaquin Valley (SJV) is one of California’s largest methane (CH4) sources. Reducing dairy emissions is a priority for the state’s climate change plans. Observations of current dairy CH4 emissions are key to monitoring actions taken toward this goal. To help support this, we present new ground-based measurements of atmospheric column-averaged CH4 mixing ratio (XCH4) gradients across a group of 600 dairies in the central SJV using EM27/SUN solar spectrometers. We used measurements from the 2019 summer and 2020 winter seasons for a top-down emission inversion based on the WRF-STILT model. Our top-down estimates of the region’s dairy emissions range from 90% to 183% of the current CALGEM inventory’s emissions of 277Gg/yr. In contrast to the strong temperature dependence found by earlier dairy CH4 emission studies, we also find that our top-down emissions during the winter measurement days are comparable to the summer measurement days, possibly due to seasonal changes in dairy management practices and meteorological conditions. Furthermore, we find significant interday variability in our measurements and find that our emission estimates overlap with earlier top-down studies and bottom-up inventories in this region. Our study demonstrates how analysis of ground-based remotely sensed CH4 gradient observations can help improve our understanding of CH4 sources at scales relevant to mitigation policy. It also reflects the need for long-term monitoring of CH4 emissions in the region and at individual facilities to better understand their emissions.

Geomorphic and hydraulic processes, which form gravel bars in large lowland rivers, have distinctive characteristics that control the magnitude and spatial patterns of infiltration and exfiltration between rivers and their immediate subsurface environments. We present a bedform-infiltration relation together with a set of field measurements along two reaches of the San Joaquin River, CA to illustrate the conditions required for infiltration and exfiltration of flow between a stream and its undulating bed, and a numerical model to investigate the factors that affect paths and residence times of flow through barforms at different discharges. It is shown that asymmetry of bar morphology is a first-order control on the extent and location of infiltration, which would otherwise produce equal areas of infiltration and exfiltration under the assumption of sinusoidal bedforms. Hydraulic conductivity varies by orders of magnitude due to fine sediment accumulation and downstream coarsening related to the process of bar evolution. This systematic variability not only controls the magnitude of infiltration, but also the residence time of flow through the bed. The lowest hydraulic conductivity along the reach occurred where the difference between the topographic gradient and the water-surface gradient is at a maximum and thus where infiltration would be greatest into a homogeneous bar, indicating the importance of managing sand supply to maintain the ventilation and flow through salmon spawning riffles. Numerical simulations corroborate our interpretation that infiltration patterns and rates are controlled by distinctive features of bar morphology.

In the San Joaquin Valley, California, recent droughts starting in 2007 have increased the pumping of groundwater, leading to widespread subsidence. In the southern portion of the San Joaquin Valley, vertical subsidence as high as 85 cm has been observed between June 2007 and December 2010 using Interferometric Synthetic Aperture Radar (InSAR). This study seeks to map regions where inelastic (not recoverable) deformation occurred during the study period, resulting in permanent compaction and loss of groundwater storage. We estimated the amount of permanent compaction by incorporating multiple datasets: the total deformation derived from InSAR, estimated skeletal specific storage and hydraulic parameters, geologic information, and measured water levels during our study period. We used two approaches, one that we consider to provide an estimate of the lowest possible amount of inelastic deformation, and one that provides a more reasonable estimate. These two approaches resulted in a spatial distribution of values for the percentage of the total deformation that was inelastic, with the former estimating a spatially averaged value of 54%, and the latter a spatially averaged value of 98%. The former corresponds to the permanent loss of 4.14 × 108 m3 of groundwater storage, or roughly 5% of the volume of groundwater used over the study time period; the latter corresponds to the loss of 7.48 × 108 m3 of groundwater storage, or roughly 9% of the volume of groundwater used. This study demonstrates that a data-driven approach can be used effectively to estimate the permanent loss of groundwater storage. This article is protected by copyright. All rights reserved.

Groundwater quality is a concern in alluvial aquifers that underlie agricultural areas, such as in the San Joaquin Valley of California. Shallow domestic wells (less than 150 m deep) in agricultural areas are often contaminated by nitrate. Agricultural and rural nitrate sources include dairy manure, synthetic fertilizers, and septic waste. Knowledge of the relative proportion that each of these sources contributes to nitrate concentration in individual wells can aid future regulatory and land management decisions. We show that nitrogen and oxygen isotopes of nitrate, boron isotopes, and iodine concentrations are a useful, novel combination of groundwater tracers to differentiate between manure, fertilizers, septic waste, and natural sources of nitrate. Furthermore, in this work, we develop a new Bayesian mixing model in which these isotopic and elemental tracers were used to estimate the probability distribution of the fractional contributions of manure, fertilizers, septic waste, and natural sources to the nitrate concentration found in an individual well. The approach was applied to 56 nitrate-impacted private domestic wells located in the San Joaquin Valley. Model analysis found that some domestic wells were clearly dominated by the manure source and suggests evidence for majority contributions from either the septic or fertilizer source for other wells. But, predictions of fractional contributions for septic and fertilizer sources were often of similar magnitude, perhaps because modeled uncertainty about the fraction of each was large. For validation of the Bayesian model, fractional estimates were compared to surrounding land use and estimated source contributions were broadly consistent with nearby land use types.

Here we present 2000 year long, annually resolved records of streamflow for the Kings, Kaweah, Tule, and Kern Rivers in the southwestern Sierra Nevada of California and consequent lake-level fluctuations at Tulare Lake in the southern San Joaquin Valley. The integrated approach of using moisture-sensitive tree ring records from the Living Blended Drought Atlas to reconstruct annual discharge and then routing this discharge to an annual Tulare Lake water balance model highlights the differences between these two types of paleoclimate records, even when subject to the same forcing factors. The reconstructed streamflow in the southern Sierra responded to yearly changes in precipitation and expressed a strong periodicity in the 2–8 year range over most of the reconstruction. The storage capacity of Tulare Lake caused it to fluctuate more slowly, masking the 2–8 year streamflow periodicity and instead expressing a strong periodicity in the 32–64 year range over much of the record. Although there have been longer droughts, the 2015 water year represents the driest in the last 2015 years and the 2012–2015 drought represents the driest 4 year period in the record. Under natural conditions, simulated Tulare Lake levels would now be at about 60 m, which is not as low as what occurred multiple times over the last 2000 years. This long-term perspective of fluctuations in climate and water supply suggests that different drought scenarios that vary in terms of severity and duration can produce similar lake-level responses in closed lake basins.

Organic aerosol mass (OM) components were investigated at Fresno in winter and at Fontana in summer by positive matrix factorization of high-resolution time-of-flight aerosol mass spectra and of Fourier Transform infrared spectra, as well as by k-means clustering of light-scattering (LS) aerosol single-particle spectra. The results were comparable for all three methods at both sites, showing different contributions of primary and secondary organic aerosol sources to PM1. At Fresno biomass burning organic aerosol contributed 27% of OM on low-fog days, and nitrate-related oxidized OA (NOOA) accounted for 47% of OM on high-fog days, whereas at Fontana very oxygenated organic aerosol (VOOA) components contributed 58–69% of OM. Amine and organosulfate fragment concentrations were between 2 and 3 times higher on high-fog days than on low-fog days at Fresno, indicating increased formation from fog-related processes. NOOA and biomass burning organic aerosol components were largely on different particles than the VOOA components in Fresno, but in Fontana both NOOA and VOOA components were distributed on most particle types, consistent with a longer time for and a larger contribution from gas-phase photochemical secondary organic aerosol formation in summer Fontana than winter Fresno. Uncommon trace organic fragments, elevated inorganic, and alcohol group submicron mass concentrations persisted at Fontana for more than 5days after 4 July fireworks. These unique aerosol chemical compositions at Fresno and Fontana show substantial and extended air-quality impacts from residential burning and fireworks.

Agricultural ammonia (NH3) emissions are highly uncertain, with high spatiotemporal variability and a lack of widespread in situ measurements. Regional NH3 emission estimates using mass balance or emission ratio approaches are uncertain due to variable NH3 sources and sinks as well as unknown plume correlations with other dairy source tracers. We characterize the spatial distributions of NH3 and methane (CH4) dairy plumes using in situ surface and airborne measurements in the Tulare dairy feedlot region of the San Joaquin Valley, California, during the NASA Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality 2013 field campaign. Surface NH3 and CH4 mixing ratios exhibit large variability with maxima localized downwind of individual dairy feedlots. The geometric mean NH3:CH4 enhancement ratio derived from surface measurements is 0.15 ± 0.03 ppmv ppmv–1. Individual dairy feedlots with spatially distinct NH3 and CH4 source pathways led to statistically significant correlations between NH3 and CH4 in 68% of the 69 downwind plumes sampled. At longer sampling distances, the NH3:CH4 enhancement ratio decreases 20–30%, suggesting the potential for NH3 deposition as a loss term for plumes within a few kilometers downwind of feedlots. Aircraft boundary layer transect measurements directly above surfacemore » mobile measurements in the dairy region show comparable gradients and geometric mean enhancement ratios within measurement uncertainties, even when including NH3 partitioning to submicron particles. Individual NH3 and CH4 plumes sampled at close proximity where losses are minimal are not necessarily correlated due to lack of mixing and distinct source pathways. As a result, our analyses have important implications for constraining NH3 sink and plume variability influences on regional NH3 emission estimates and for improving NH3 emission inventory spatial allocations.« less

Precipitation characteristics, such as intensity, frequency, duration, and event pattern, are changing due to the increases in greenhouse gases, transition of ocean oscillation phases, etc. In this paper, we evaluate the ability of 11 realizations from multiple regional climate model (RCM)/global climate model pairs in the North American Regional Climate Change Assessment Program (NARCCAP) to simulate the seasonal variability and magnitude of storm properties, including storm duration, interstorm period, and storm intensity. The results indicate that NARCCAP RCMs simulate the seasonal variability better in the Greater Sacramento and San Joaquin than in Las Vegas, which may be due to the RCMs' inability to simulate local convective precipitation associated with the North American Monsoon. We also investigate the impacts of climate change on these storm characteristics by comparing the percentage change and absolute change of storm properties determined from NARCCAP historical runs and future runs. We find that individual RCMs exhibit great uncertainty in the percentage changes in storm duration, interstorm period, and average storm intensity. The ensemble means of storm properties across 11 future NARCCAP RCM projections show different responses to climate change in different locations. Our analyses provide guidelines for selecting the appropriate RCMs for hydrologic studies related to storm properties and provide forecasters and water managers with detailed information of future changes in storm properties so that they can sustainably manage water resources. Our results may also contribute to the nonstationary precipitation scenario development by incorporating the percentage changes of storm properties caused by human-induced warming into the stochastic precipitation model.

A modified Ambient Ion Monitor-Ion Chromatograph was utilized to monitor the composition of water-soluble fine particulate matter (PM2.5) and precursor gases at the Bakersfield, CA, supersite during Research at the Nexus of Air Quality and Climate Change (CalNex) in May and June of 2010. The observations were used to investigate inorganic gas/particle partitioning, to derive an empirical relationship between ammonia emissions and temperature, and to assess the performance of the Community Multiscale Air Quality (CMAQ) model. The water-soluble PM2.5 maximized in the morning and in the evening because of gas/particle partitioning and possibly regional transport. Among the PM2.5 constituents, pNO3− was the dominant chemical species with campaign average mass loading of 0.80 µg m−3, and the mass loadings of pNH4+ and pSO42− were 0.46 µg m−3 and 0.53 µg m−3, respectively. The observed HNO3 (g) levels had an average of 0.14 ppb. Sub-ppb levels of SO2 (g) were measured, consistent with the absence of major emission sources in the region. Measured NH3 (g) had an average of 19.7 ppb over the campaign and demonstrated a strong relationship with temperature. Observations of ammonia were used to derive an empirical enthalpy for volatilization of 30.8 ± 2.1 kJ mol−1. The gas/particle partitioning of semivolatile PM2.5 composition was driven by meteorological factors and limited by total nitrate (TN) in this region. CMAQ model output exhibited significant biases in the predicted concentrations of pSO42−, NH3 (g), and TN. The largest model bias was in HNO3 (g), with an overprediction of an order of magnitude, which may be due to missing HNO3 (g) sinks such as reactive uptake on dust in the CMAQ framework.

[1] The San Emigdio Mountains are an example of an archetypical, transpressional structural system, bounded to the south by the San Andreas strike-slip fault, and to the north by the active Wheeler Ridge thrust. Apatite (U-Th)/He and apatite and zircon fission track ages were obtained along transects across the range and from wells in and to the north of the range. Apatite (U-Th)/He ages are 4–6 Ma adjacent to the San Andreas fault, and both (U-Th)/He and fission track ages grow older with distance to the north from the San Andreas. The young ages north of the San Andreas fault contrast with early Miocene (U-Th)/He ages from Mount Pinos on the south side of the fault. Restoration of sample paleodepths in the San Emigdio Mountains using a regional unconformity at the base of the Eocene Tejon Formation indicates that the San Emigdio Mountains represent a crustal fragment that has been exhumed more than 5 km along the San Andreas fault since late Miocene time. Marked differences in the timing and rate of exhumation between the northern and southern sides of the San Andreas fault are difficult to reconcile with existing structural models of the western Transverse Ranges as a thin-skinned thrust system. Instead, these results suggest that rheologic heterogeneities may play a role in localizing deformation along the Big Bend of the San Andreas fault as the San Emigdio Mountains are compressed between the crystalline basement of Mount Pinos and oceanic crust that underlies the southern San Joaquin Valley.

[1] We conducted a first-order sensitivity analysis to investigate ozone responses to precursor emissions and source contributions (local versus upwind) for California's San Joaquin Valley (SJV) under four distinct meteorology conditions of summer 2000 using a three-dimensional photochemical transport model. Ozone-limiting reagents, nitrogen oxides (NOx), or anthropogenic volatile organic compounds (VOCs) (AVOCs) and their transition regime were determined from ozone sensitivity coefficients and delineated spatially at high-ozone locations in the SJV. In general, AVOC-limited areas were located near urban centers, while NOx-limited areas were located farther downwind. However, the spatial extent of AVOC-limited areas varied with meteorology. Meteorological dependence of predominant ozone-limiting precursors was found to vary significantly among different subregions within the SJV. Specifically, weaker dependences were identified for regions of the southern SJV located farther away from emission sources, where ozone chemistry was mostly limited by NOx for the episodes considered. Stronger dependences were identified for the central and northern SJV, where ozone chemistry can be limited by NOx or AVOC depending on meteorology. Source contributions to ozone sensitivities in the SJV were also investigated. Local sources were important for the eastern side of the central SJV, while upwind sources were also important (from ~40% to more than 50% of the total ozone sensitivities) for the western side of the valley, except for the most stagnant episode. Different contributing source regions were identified for the same VOC-limited areas in the northern SJV, and these depended on the flow characteristics. The predominant ozone-limiting reagent was found to exhibit less dependence on meteorology in the central and southern SJV as the baseline NOx emissions were reduced, ultimately causing ozone formation to be limited by NOx. In contrast, the VOC-limited areas in the northern SJV continued to be influenced by meteorology for two of the episodes.

[1] Several regions within California have significant air quality issues. Transport of pollutants emitted in one region to another region may add to the impact of local emissions. In this work, Lagrangian particle dispersion model simulations show the amounts of tracers that are transported within and among four regions, Southern California, the San Francisco Bay Area, the Central Valley, and the rest of the state. The simulations cover May and June of 2010, the California Research at the Nexus of Air Quality and Climate Change experiment period. Tracers of automobile emissions and one type of agricultural emission are used. Tracer mixing ratios are compared to airborne and ground-based measurements. The age of tracers in each location is also presented. Vertical profiles and diurnal cycles help to clarify the transport process. As is well known, Southern California emissions are transported to the east and affect the desert areas, and Bay Area automobile emissions are an important source of pollutants in the San Joaquin Valley. A novel result is that the Southern California Bight is filled with a mixture of well-aged carbon monoxide tracer from Southern California and the Bay Area. Air over the Bight is also affected by the agricultural emissions represented by the agricultural tracer, dominantly from the Central Valley where its sources are largest. There is no indication of transport from Southern California to the Central Valley. Emissions from the Central Valley do make their way to Southern California, as shown by the agricultural tracer, but automobile emissions from the Valley are insignificant in Southern California.

The California Research at the Nexus of Air Quality and Climate Change (CalNex) field study was conducted throughout California in May, June, and July of 2010. The study was organized to address issues simultaneously relevant to atmospheric pollution and climate change, including (1) emission inventory assessment, (2) atmospheric transport and dispersion, (3) atmospheric chemical processing, and (4) cloud-aerosol interactions and aerosol radiative effects. Measurements from networks of ground sites, a research ship, tall towers, balloon-borne ozonesondes, multiple aircraft, and satellites provided in situ and remotely sensed data on trace pollutant and greenhouse gas concentrations, aerosol chemical composition and microphysical properties, cloud microphysics, and meteorological parameters. This overview report provides operational information for the variety of sites, platforms, and measurements, their joint deployment strategy, and summarizes findings that have resulted from the collaborative analyses of the CalNex field study. Climate-relevant findings from CalNex include that leakage from natural gas infrastructure may account for the excess of observed methane over emission estimates in Los Angeles. Air-quality relevant findings include the following: mobile fleet VOC significantly declines, and NO_x emissions continue to have an impact on ozone in the Los Angeles basin; the relative contributions of diesel and gasoline emission to secondary organic aerosol are not fully understood; and nighttime NO_3 chemistry contributes significantly to secondary organic aerosol mass in the San Joaquin Valley. Findings simultaneously relevant to climate and air quality include the following: marine vessel emissions changes due to fuel sulfur and speed controls result in a net warming effect but have substantial positive impacts on local air quality.

[1] Water year indices and drought indices are helpful for categorizing water years into similar types, allowing water managers and policymakers to quantify years, visualize variability, and guide water operations. Many water management decisions, such as environmental flow requirements and water supply allocations, are based on water year type designations. They vary by region and index, but are defined by runoff in the current water year compared to average historical runoff, with numerical thresholds categorizing year types. California's Sacramento Valley and San Joaquin Valley Indices are used as case studies to examine how climate change affects indices. Modeled streamflow for 1951–2099 from the climate-forced Variable Infiltration Capacity hydrologic model estimate potential changes in runoff and water year type frequency. We show that the frequency of water year types changes significantly with climate change and different strategies to adapt water year classification indices to climate change affect water allocations as much as the impacts from changing hydroclimatic conditions.

Seasonal methane (CH4) emissions in northern California are evaluated during this study using airborne measurement data and inverse model simulations. This research applies Alpha Jet Atmospheric eXperiment (AJAX) measurements obtained during January – February 2013, July 2014, and October – November 2014 over the San Francisco Bay Area (SFBA) and northern San Joaquin Valley (SJV) in order to constrain seasonal CH4 emissions in northern California. The California Greenhouse Gas Emissions Measurement (CALGEM) a priori emission inventory was applied in conjunction with the Weather Research and Forecasting and Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) model and inverse modeling techniques to optimize CH4 emissions. Comparing model-predicted CH4 mixing ratios with airborne measurements, we find substantial underestimates suggesting that CH4 emissions were likely larger than the year 2008 a priori CALGEM emission inventory in northern California. Using AJAX measurements to optimize a priori emissions resulted in CH4 flux estimates from the SFBA/SJV of 1.77 ± 0.41, 0.83 ± 0.31, and 1.06 ± 0.39 Tg yr-1 when using winter, summer, and fall flight data, respectively. Averaging seasonal a posteriori emission estimates (weighted by posterior uncertainties) results in SFBA/SJV annual CH4 emissions of 1.28 ± 0.38 Tg yr-1. A posteriori uncertainties are reduced more effectively in the SFBA/SJV region compared to state-wide values indicating that the airborne measurements are most sensitive to emissions in this region. A posteriori estimates during this study suggest that dairy livestock was the source with the largest increase relative to the a priori CALGEM emission inventory during all seasons.

San Francisco Bay is one of the most important estuaries on the west coast of the Americas. Its water quality is controlled primarily by streamflow from the Sacramento and San Joaquin rivers. In fact, freshwater inflow from the Sacramento-San Joaquin Delta explains 86% of the salinity variability at the mouth of the San Francisco Bay estuary [Peterson et al., 1989]. The massive diversion of streamflow by the California State Water Project and the Central Valley Project, part of the largest manmade water control system on Earth [Reisner, 1988], has raised salinity in the estuary on daily, seasonal, and annual timescales [Nichols et al., 1986; Peterson et al., 1989].

The GATORG-GCMM global- through urban-scale nested air pollution/weather forecast model was applied to study ozone layers aloft, ozone in national parks, and weather during the August 3-6, 1990, SARMAP field campaign in northern and central California. Predictions of meteorological variables and mixing ratios of 20 gases were compared with observations. With nesting, the normalized gross error in predicted near-surface Kelvin temperatures was 1.02% and that in near-surface ozone above 50 ppbv was 22.5%. Statistics from outer nested domains indicated that the coarser the grid spacing, the greater the underprediction of ozone. In the absence of nesting, statistics deteriorated but not a lot. The model-simulated observed nighttime ozone layers aloft and daytime ozone mixed layers in the San Joaquin Valley and San Francisco Bay Area. It also simulated observed daytime and nighttime ozone layers aloft over the San Francisco Bay near Hayward. The formation mechanism of these layers is discussed. The model was used to estimate that about 47-57% of peak daytime ozone in Sequoia and Yosemite National Parks during SARMAP was produced by anthropogenic gases, 13-3% was produced by biogenic hydrocarbons, and the rest (about 40%) was background.

The Lost Hills and Belridge oilfields are in the San Joaquin Valley, California. The major oil reservoir is high porosity and low permeability diatomite. Extraction of large volumes from shallow depths causes reduction in pore pressure and subsequent compaction, forming a surface subsidence bowl. We measure this subsidence from space using interferometric analysis of SAR (Synthetic Aperture Radar) data collected by the European Space Agency Remote Sensing Satellites (ERS-1 and ERS-2). Maximum subsidence rates are as high as 40 mm in 35 days or >400 mm/yr, measured from interferograms with time separations ranging from one day to 26 months. The 8- and 26-month interferograms contain areas where the subsidence gradient exceeds the measurement possible with ERS SAR, but shows increased detail in areas of less rapid subsidence. Synoptic mapping of subsidence distribution from satellite data powerfully complements ground-based techniques, permits measurements where access is difficult, and aids identification of underlying causes.

This paper reports the first power spectra of ozone (O3) in the surface layer for which the data quality approaches that of high-quality spectra of meteorological properties. These results are employed in a surface layer scalar similarity study involving temperature, moisture, and O3 measurements over cotton. All data were obtained during the California Ozone Deposition Experiment, in the San Joaquin Valley of California, during July and August, 1991. A detailed comparison of nondimensional scalar power spectra during unstable conditions showed that the three scalars behaved similarly, thereby providing the first completely general test of scalar similarity theory.

The occurrence of selenium in agricultural drainage water derived from the central part of the western San Joaquin Valley has focused concern on alternatives to agricultural drains for managing shallow, poor-quality groundwater. A transient, three-dimensional simulation model was developed to evaluate the response of the water table to alternatives that affect recharge to or discharge from the groundwater flow system. The modeled area is 551 mi2 (1 mi2 = 2.59 km2) and includes both the semiconfined and confined zones above and below the Corcoran Clay Member of the Tulare Formation of Pleistocene age. The simulation model was calibrated using hydrologic data from 1972 to 1988, and was extended to the year 2040 to forecast for various management alternatives, including maintenance of present practices, land retirement, reduced recharge, increased groundwater pumping, and combinations of these alternatives. Maintenance of present practices results in a worsening of the situation: the total area subject to bare-soil evaporation increases from 224 mi2 in 1990 to 344 mi2 in 2040, and drain flow increases from 25,000 ac ft/yr (1 ac ft = 1234 m3) to 28,000 ac ft/yr. Although land retirement results in elimination of bare-soil evaporation and drain flow in the areas retired, it has little to no effect in adjacent areas. In contrast, regional-scale changes in recharge and pumping are effective for regional management. The area subject to bare-soil evaporation can be reduced to 78 mi2, and drain flow to 8000 ac ft/yr if (1) recharge is reduced by 15% (26,000 ac ft/yr) in areas that currently use surface and groundwater (362 mi2); (2) recharge is reduced by 40% (28,000 ac ft/yr) in areas that currently use only surface water (137 mi2); and (3) pumping rates are uniformly incremented by 0.5 ft/yr (160,000 ac ft/yr) in both areas. If these water budget changes were to be implemented in the study area, and in adjacent areas with similiar Hydrogeologic characteristics, then approximately 400,000 ac ft/yr of surface water would be made available. Thus a shift in the hydrologic budget in the central part of the western San Joaquin Valley improves the prospects for sustaining agriculture in the area, and could provide substantial water resources for other uses.

[1] A fuel-based approach is used to estimate nitrogen oxides (NOx = NO + NO2) emissions from gasoline- and diesel-powered motor vehicles. Estimates are made at the national level for the period 1990–2010. Vehicle emissions are also estimated at the state level for California, and for the South Coast (Los Angeles) and San Joaquin Valley air basins. Fuel-based emission estimates are compared with predictions from widely used emission inventory models. Changes in diesel NOxemissions vary over time: increasing between 1990 and 1997, stable between 1997 and 2007, and decreasing since 2007. In contrast, gasoline engine-related NOxemissions have decreased steadily, by ∼65% overall between 1990 and 2010, except in the San Joaquin Valley, where reductions were not as large due to faster population growth. In the San Joaquin Valley, diesel engines were the dominant on-road NOxsource in all years considered (reaching ∼70% in 2010). In the urbanized South Coast air basin, gasoline engine emissions dominated in the past and have been comparable to on-road diesel sources since 2007 (down from ∼75% in 1990). Other major anthropogenic sources of NOxare added to compare emission trends with trends in surface pollutant observations and satellite-derived data. When all major anthropogenic NOx sources are included, the overall emission trend is downward in all cases (−45% to −60%). Future reductions in motor vehicle NOxwill depend on the effectiveness of new exhaust after-treatment controls on heavy-duty trucks, as well as further improvements todurabilityof emission control systems on light-duty vehicles.

[1] We present an overview and analysis of cloud condensation nuclei (CCN) sampled in California by a NOAA WP-3D aircraft during the 2010 CalNex project. Four distinct geographical regions are characterized, including the Los Angeles basin, the San Joaquin and Sacramento Valleys, and the eastern Pacific Ocean west of southern California. Median size distributions in the Central Valley were unimodal (Dg ∼ 25 nm) with a larger fraction of organic species and smaller fraction of nitrate species in the Sacramento Valley aerosol than in the San Joaquin Valley aerosol. Size distributions in the Los Angeles basin and marine outflow were bimodal (geometric mean diameter, Dg ∼ 30, 90–100 nm) with similar organic fractions and some replacement of nitrate with sulfate in the marine outflow. Both fine particle and CCN concentrations were found to decrease rapidly above the planetary boundary layer (∼2 km altitude), with CCN concentrations in the boundary layer ranging from ∼102–104 cm−3 STP, while fine particle concentrations (0.004–1 μm diameters) ranged from ∼103–105 cm−3STP. The CCN-active number fraction varied between 0–100% in the Los Angeles Basin and Marine Outflow, but was substantially lower (0–40%) in the San Joaquin and Sacramento Valleys. Values of the hygroscopicity parameter,κ, inferred from the CCN measurements varied from 0.1–0.25, with the highest values in the marine outflow and the lowest values in the Sacramento Valley. The κvalues agreed well with the predictions based on size-resolved aerosol composition, but were overpredicted by almost twofold when size-averaged composition was used. CCN closure was assessed for simplified compositional and mixing state assumptions, and it was found that assuming the aerosol to be internally mixed overpredicted CCN concentrations by 30–75% for all air mass types except within the Sacramento Valley, where good closure (overprediction < 10%) was achieved by assuming insoluble organics. Assuming an externally-mixed aerosol fraction or incorporating size-resolved composition data improved closure in the other three regions, consistent with the bimodal nature of the aerosol size distribution.

[1] Despite advances in physically based hydrologic models and prediction systems, long-standing statistical methods remain a fundamental component in most operational forecasts of seasonal streamflow. We develop a hybrid framework that employs gridded observed precipitation and model-simulated snow water equivalent (SWE) data as predictors in regression equations adapted from an operational forecasting environment. We test the modified approach using the semidistributed variable infiltration capacity hydrologic model in a case study of California's Sacramento River, San Joaquin River, and Tulare Lake hydrologic regions. The approach employs a principal components regression methodology, adapted from the Natural Resources Conservation Service, which leverages the ability of the distributed model to provide an added dimension to SWE predictors in a statistical framework. Hybrid forecasts based on data simulated at grid points acting as surrogates for ground-based observing stations are found to perform comparably to those based on their observed counterparts. When a larger selection of grid points are considered as potential predictors, hybrid forecasts achieve superior skill, with the largest benefits in watersheds that are poorly represented in terms of ground-based observations. Forecasts are also found to offer overall improvement over those officially issued by California's Department of Water Resources, although their specific performance in dry years is less consistent. The study demonstrates the utility of physically based models within an operational statistical framework, as well as the ability of the approach to identify locations with strong predictive skill for potential ground station implementation.

In highly-productive agricultural areas such as California's Central Valley, where groundwater often supplies the bulk of the water required for irrigation, quantifying rates of groundwater depletion remains a challenge owing to a lack of monitoring infrastructure and the absence of water use reporting requirements. Here we use 78 months (October, 2003–March, 2010) of data from the Gravity Recovery and Climate Experiment satellite mission to estimate water storage changes in California's Sacramento and San Joaquin River Basins. We find that the basins are losing water at a rate of 31.0 ± 2.7 mm yr−1 equivalent water height, equal to a volume of 30.9 km3 for the study period, or nearly the capacity of Lake Mead, the largest reservoir in the United States. We use additional observations and hydrological model information to determine that the majority of these losses are due to groundwater depletion in the Central Valley. Our results show that the Central Valley lost 20.4 ± 3.9 mm yr−1 of groundwater during the 78-month period, or 20.3 km3 in volume. Continued groundwater depletion at this rate may well be unsustainable, with potentially dire consequences for the economic and food security of the United States.

This paper presents a dynamic model of irrigated agriculture that accounts for drainage generation and salinity accumulation. Critical model relationships involving crop production, soil salinity, and irrigation drainage are based on newly estimated functions derived from lysimeter field tests. The model allocates land and water inputs over time based on an intertemporal profit maximization objective function and soil salinity accumulation process. The model is applied to conditions in the San Joaquin Valley of California, where environmental degradation from irrigation drainage has become a policy issue. Findings indicate that in the absence of regulation, drainage volumes increase over time before reaching a steady state as increased quantities of water are allocated to leaching soil salts. The model is used to evaluate alternative drainage abatement scenarios involving drainage quotas and taxes, water supply quotas and taxes, and irrigation technology subsidies. In our example, direct drainage policies are more cost-effective in reducing drainage than policies operating indirectly through surface water use, although differences in cost efficiency are relatively small. In some cases, efforts to control drainage may result in increased soil salinity accumulation, with implications for long-term cropland productivity. While policy adjustments may alter the direction and duration of convergence to a steady state, findings suggest that a dynamic model specification may not be necessary due to rapid convergence to a comon steady state under selected scenarios.

Experimental manipulations provide a powerful tool for understanding an ecosystem's response to environmental perturbation. We combined paired eddy covariance towers with an experimental manipulation of water availability to determine the response of marsh carbon balance to drought. We monitored the Net Ecosystem Exchange of CO2 (NEE) in two ponds from 2004 to 2009 at the San Joaquin Freshwater Marsh (SJFM), and subjected one of the ponds to a yearlong drought treatment in 2007. The two ponds experienced similar flooding and environmental regimes before and after the drought, ensuring that differences between ponds were largely attributable to the 2007 drought. Drought substantially reduced surface greenness, as measured by the Enhanced Vegetation Index (EVI) and photosynthetic carbon sequestration, primarily by inhibiting leaf area development. Respiratory carbon losses were less influenced by drought than photosynthetic carbon gains. The effect of the drought lasted several years, with delayed leaf area development and peak carbon uptake rates during the subsequent year, and reduced leaf area for a couple of years. The combined effect of the drought and legacy effects created an overall loss of carbon that was equivalent to 4 years of the maximum annual carbon sequestration observed over a decade. Our results indicate that drought can have long-term impacts on ecosystem carbon balance and that future projected drought increases in Southern California will have a negative impact on marsh carbon sequestration.

This study presents detailed evaluation of the seasonal and episodic performance of the Community Multiscale Air Quality (CMAQ) modeling system applied to simulate air quality at a fine grid spacing (4 km horizontal resolution) in central California, where ozone air pollution problems are severe. A rich aerometric database collected during the summer 2000 Central California Ozone Study (CCOS) is used to prepare model inputs and to evaluate meteorological simulations and chemical outputs. We examine both temporal and spatial behaviors of ozone predictions. We highlight synoptically driven high-ozone events (exemplified by the four intensive operating periods (IOPs)) for evaluating both meteorological inputs and chemical outputs (ozone and its precursors) and compare them to the summer average. For most of the summer days, cross-domain normalized gross errors are less than 25% for modeled hourly ozone, and normalized biases are between {+-}15% for both hourly and peak (1 h and 8 h) ozone. The domain-wide aggregated metrics indicate similar performance between the IOPs and the whole summer with respect to predicted ozone and its precursors. Episode-to-episode differences in ozone predictions are more pronounced at a subregional level. The model performs consistently better in the San Joaquin Valley than other air basins, and episodicmore » ozone predictions there are similar to the summer average. Poorer model performance (normalized peak ozone biases 15%) is found in the Sacramento Valley and the Bay Area and is most noticeable in episodes that are subject to the largest uncertainties in meteorological fields (wind directions in the Sacramento Valley and timing and strength of onshore flow in the Bay Area) within the boundary layer.« less

The recreational benefits from providing increased quantities of water to wildlife and fisheries habitats is estimated using linked multinomial logit site selection models and count data trip frequency models. The study encompasses waterfowl hunting, fishing and wildlife viewing at 14 recreational resources in the San Joaquin Valley, including the National Wildlife Refuges, the State Wildlife Management Areas, and six river destinations. The economic benefits of increasing water supplies to wildlife refuges were also examined by using the estimated models to predict changing patterns of site selection and overall participation due to increases in water allocations. Estimates of the dollar value per acre foot of water are calculated for increases in water to refuges. The resulting model is a flexible and useful tool for estimating the economic benefits of alternative water allocation policies for wildlife habitat and rivers.

[1] Lignin phenols have proven to be powerful biomarkers in environmental studies; however, the complexity of lignin analysis limits the number of samples and thus spatial and temporal resolution in any given study. In contrast, spectrophotometric characterization of dissolved organic matter (DOM) is rapid, noninvasive, relatively inexpensive, requires small sample volumes, and can even be measured in situ to capture fine-scale temporal and spatial detail of DOM cycling. Here we present a series of cross-validated Partial Least Squares models that use fluorescence properties of DOM to explain up to 91% of lignin compositional and concentration variability in samples collected seasonally over 2 years in the Sacramento River/San Joaquin River Delta in California, United States. These models were subsequently used to predict lignin composition and concentration from fluorescence measurements collected during a diurnal study in the San Joaquin River. While modeled lignin composition remained largely unchanged over the diurnal cycle, changes in modeled lignin concentrations were much greater than expected and indicate that the sensitivity of fluorescence-based proxies for lignin may prove invaluable as a tool for selecting the most informative samples for detailed lignin characterization. With adequate calibration, similar models could be used to significantly expand our ability to study sources and processing of DOM in complex surface water systems.

Groundwater flow modeling was used to quantitatively assess the hydrologic processes affecting ground water and solute movement to drain laterals. Modeling results were used to calculate the depth distribution of groundwater flowing into drain laterals at 1.8 m (drain lateral 1) and 2.7 m (drain lateral 2) below land surface. The simulations indicated that under nonirrigated conditions about 89% of the flow in drain lateral 2 was from groundwater originating from depths greater than 6 m below land surface. The deep groundwater has higher selenium concentrations than shallow groundwater. Simulation of irrigated conditions indicates that as recharge (deep percolation) increases, the proportional contribution of deep groundwater to drain lateral flow decreases. Groundwater flow paths and travel times estimated from the simulation results indicate that groundwater containing high concentrations of selenium (greater than 780 μg L−1) probably will continue to enter drain lateral 2 for decades.

A study was undertaken to quantitatively evaluate the hydrologic processes affecting the chemical and isotopic composition of drain lateral water in a drained agricultural field in the western San Joaquin Valley, California. The results elucidate the process of mixing of deep and shallow groundwater (below and within 6 m from land surface) entering the drain laterals. The deep groundwater was subject to evapoconcentration prior to drainage system installation and has been displaced downward (to depths greater than 6 m) in the groundwater system. The proportions of deep and shallow groundwater entering the drain laterals was calculated from the end-member oxygen 18 compositions determined in groundwater samples. The percentage of total drain lateral flow which is deep groundwater flow is about 30% for the shallow drain lateral (1.8 m below land surface) (drain lateral 1)) and 60% for the deep drain lateral (2.7 m below land surface (drain lateral 2)). During irrigation, the percentages of deep groundwater flow decrease to 0 and 30% for the shallow and deep drain laterals, respectively. Selenium concentrations in drain lateral waters decrease during irrigation but selenium loads increase. Total estimated annual loads were 1.1 and 5.4 kg of selenium for drain laterals 1 and 2, respectively. Substantial percentages of the annual load occurred during 8 days of irrigation, 23 and 9% for drain laterals 1 and 2, respectively.

[1] The statistical relationship between the daily 1-hour maximum ozone (O3) concentrations and the daily maximum upper air temperature was explored for California's two most heavily polluted air basins: the South Coast Air Basin (SoCAB) and the San Joaquin Valley Air Basin (SJVAB). A coarse-scale analysis of the temperature at an elevation of 850-mbar pressure (T850) for the period 1980–2004 was obtained from the National Center for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) Reanalysis data set for grid points near Upland (SoCAB) and Parlier (SJVAB). Daily 1-hour maximum ozone concentrations were obtained from the California Air Resources Board (CARB) for these locations over the same time period. The ozone concentrations measured at any given value of the Reanalysis T850 were approximately normally distributed. The 25%, 50%, and 75% quartile ozone concentrations increased linearly with T850, reflecting the effect of temperature on emissions and chemical reaction rates. A 2D Lagrangian (trajectory) form of the UCD/CIT photochemical air quality model was used in a perturbation study to explain the variability of the ozone concentrations at each value of T850. Wind speed, wind direction, temperature, relative humidity, mixing height, initial concentrations for VOC concentrations, background ozone concentrations, time of year, and overall emissions were perturbed in a realistic fashion during this study. A total of 62 model simulations were performed, and the results were analyzed to show that long-term changes to emissions inventories were the largest sources of ozone variability at a fixed value of T850. Projections of future T850 values in California were obtained from the Geophysical Fluid Dynamics Laboratory (GFDL) model under the Intergovernmental Panel on Climate Change (IPCC) A2 and B1 emissions scenarios for the years 2001 to 2100. The future temperature trends combined with the historical statistical relationships suggest that an additional 22–30 days year−1 in California would experience O3 ≥90 ppb under the A2 global emissions scenario, and an additional 6–13 days year−1 would experience O3 ≥ 90 ppb under the B1 global emissions scenario by the year 2050 (assuming the NOx and VOC emissions remained at 1990–2004 levels). These calculations help to quantify the climate “penalty” that must be overcome to improve air quality in California.

A computer model is used to simulate floods and associated annual and present value costs for California's Sacramento-San Joaquin Delta. Empirical probability distributions of stability failure and overtopping floods for 46 islands and tracts, conditioned on water levels, are used to simulate floods. When an island floods, damage and reclamation costs are determined. The cost of levee maintenance in nonflood years is also a random variable. Multiple simulations over 50-year periods provide means and variances of annual costs of policies of reclaiming all flooded islands or reclaiming only some of them. When discounted, the resulting present value of a future stream of these costs may be compared to costs of alternative flood prevention programs (e.g., new levees). Results show that the present value of costs over 50 years for reclaiming all islands differs little from the comparable cost of reclaiming only 13 islands and leaving other islands flooded. Under both policies the present value of costs is less than the first cost of levee projects presented by the Corps of Engineers in the early 1980s.

The hydrologic sensitivities of four medium-sized mountainous catchments in the Sacramento and San Joaquin River basins to long-term global warming were analyzed. The hydrologic response of these catchments, all of which are dominated by spring snowmelt runoff, were simulated by the coupling of the snowmelt and the soil moisture accounting models of the U.S. National Weather Service River Forecast System. In all four catchments the global warming pattern, which was indexed to CO{sub 2} doubling scenarios simulated by three (global) general circulation models, produced a major seasonal shift in the snow accumulation pattern. Under the alternative climate scenarios more winter precipitation fell as rain instead of snow, and winter runoff increased while spring snowmelt runoff decreased. In addition, large increases in the annual flood maxima were simulated, primarily due to an increase in rain-on-snow events, with the time of occurrence of many large floods shifting from spring to winter.

Seasonal applied water measurements were obtained for 1710 irrigated fields in the southern San Joaquin Valley of California. Most of the fields were planted to one of five major crops: citrus, almonds, grapes, cotton, and small grains. These crops were irrigated with a wide array of irrigation technologies, including drip, sprinkler, furrows with tailwater reuse facilities, conventional furrows, and border irrigation systems. The data were analyzed within an accounting framework to standardize for a variety of climatic and cultural variations. Analyses of the mean depths of applied water by crop and irrigation technology and of the standardized results reveal that drip irrigation systems were associated with the lowest levels of applied water on permanent crops and that the levels of water applied with sprinklers did not differ significantly from those applied with surface systems on either permanent or annual crops.

[1] We define the subsurface geometry, kinematics, and seismotectonics of the Coalinga anticline in the San Joaquin basin, central California. Using seismic reflection data and quantitative fault-related folding techniques, we present a model of the Coalinga anticline that demonstrates that the structure is composed of a stack of imbricated structural wedges, related to two major fault ramps at depth, the deepest of which ruptured during the 1983 Coalinga (Mw = 6.5) earthquake. Because of the lack of basinward deformation and the observed fold shapes, these ramps are interpreted to sole to a common upper detachment, which acts as a back thrust, forming a structural wedge. This back-thrust system generates the surface expression of the Coalinga anticline and extends to the surface as the Waltham Canyon fault and a series of related east dipping thrusts. This structural analysis helps reconcile the longstanding conflict between the southwest dipping preferred nodal plane of the 1983 main shock and the western vergence of the surface anticline. Furthermore, the seismic reflection data and our model suggest that two potentially seismogenic ramps and a major back thrust underlie the fold, rather than the single fault which has been inferred in previous studies. Using a relocated earthquake catalog, we document the three-dimensional distribution of earthquakes over a 22 year period relative to both the main fault which ruptured in the 1983 event and within the structural wedge. This analysis indicates that the majority of moment release following the 1983 event occurred within the wedge itself, compatible with a model of wedge emplacement.

[1] The 14-month-long (December 1999 to February 2001) Central California Regional PM10/PM2.5 Air Quality Study (CRPAQS) consisted of acquiring speciated PM2.5 measurements at 38 sites representing urban, rural, and boundary environments in the San Joaquin Valley air basin. The study's goal was to understand the development of widespread pollution episodes by examining the spatial variability of PM2.5, ammonium nitrate (NH4NO3), and carbonaceous material on annual, seasonal, and episodic timescales. It was found that PM2.5 and NH4NO3 concentrations decrease rapidly as altitude increases, confirming that topography influences the ventilation and transport of pollutants. High PM2.5 levels from November 2000 to January 2001 contributed to 50–75% of annual average concentrations. Contributions from organic matter differed substantially between urban and rural areas. Winter meteorology and intensive residential wood combustion are likely key factors for the winter-nonwinter and urban-rural contrasts that were observed. Short-duration measurements during the intensive operating periods confirm the role of upper air currents on valley-wide transport of NH4NO3. Zones of representation for PM2.5 varied from 5 to 10 km for the urban Fresno and Bakersfield sites, and increased to 15–20 km for the boundary and rural sites. Secondary NH4NO3 occurred region-wide during winter, spreading over a much wider geographical zone than carbonaceous aerosol.

[1] Groundwater is being depleted in California's Central Valley at a rapid rate, according to data from the Gravity Recovery and Climate Experiment (GRACE) satellite. Famiglietti et al. analyzed 78 months of GRACE data covering October 2003 to March 2010 to estimate water storage changes in California's Sacramento and San Joaquin river basins. They found that the basins are losing water at a rate of about 30 millimeters per year equivalent water height, or a total of about 30 cubic kilometers over the 78-month period. Furthermore, they found that two thirds of this loss, or a total of 20 cubic kilometers for the study period, came from groundwater depletion in the Central Valley. Quantifying groundwater depletion can be challenging in many areas because of a lack of monitoring infrastructure and reporting requirements; the study shows that satellite-based monitoring can be a useful way to track groundwater volumes. The authors warn that the current rate of groundwater depletion in the Central Valley may be unsustainable and could have “potentially dire consequences for the economic and food security of the United States.” (Geophysical Research Letters, doi:10.1029/2010GL046442, 2011)

[1] California's primary hydrologic system, the San Francisco estuary and its upstream watershed, is vulnerable to the regional hydrologic consequences of projected global climate change. Projected temperature anomalies from a global climate model are used to drive a combined model of watershed hydrology and estuarine dynamics. By 2090, a projected temperature increase of 2.1°C results in a loss of about half of the average April snowpack storage, with greatest losses in the northern headwaters. Consequently, spring runoff is reduced by 5.6 km3 (∼20% of historical annual runoff), with associated increases in winter flood peaks. The smaller spring flows yield spring/summer salinity increases of up to 9 psu, with larger increases in wet years.

[1] Attempts to characterize ozone formation as sensitive to either volatile organic compounds (VOC) or NOx within a region oversimplify a problem that shows spatial and temporal variation. California's Central Valley has some of the highest ozone levels in the country and a rapidly growing population, and air quality problems in this region can be influenced by interbasin transport of ozone and its precursors. An Eulerian photochemical airshed model is applied to the region for the period 3–6 August 1990. This episode spans a weekend, and the emission inventory incorporates revised motor vehicle emissions with day-specific activity patterns. Compared with the baseline inventory, the revised inventory contains higher VOC and lower NOx emissions from motor vehicles and different temporal patterns of these emissions. Revised estimates of biogenic emissions are greatly reduced. The baseline emission inventory used in previous modeling efforts appears to contain compensating errors, with high biogenic emissions making up for low motor vehicle emissions of VOC. Results suggest that heavily urbanized areas around and downwind of the San Francisco Bay and Sacramento are VOC-sensitive, while the more rural areas are NOx-sensitive. Ozone formation in the San Joaquin Valley, where progress in reducing ambient ozone concentrations has been slow, exhibits sensitivity to emissions of both VOC and NOx, and is influenced by emissions from the San Francisco Bay Area during this modeling episode.

[1] Photochemical air pollution problems have proved difficult to understand and control in central California. A major source of uncertainty is the rate of precursor volatile organic compounds and NOx emissions, especially from motor vehicles. We develop alternative emissions estimates for on-road motor vehicles in 1990, using fuel sales data, emission factors measured in on-road studies, and ambient pollutant ratios, for a region that includes the San Francisco Bay and San Joaquin Valley air basins and Sacramento County. Fuel-based emissions estimates are compared with predictions of California's most recent motor vehicle emission factor model (EMFAC) and with an inventory that has been used in previous regional-scale photochemical modeling studies. The fuel-based inventory contains 10–50% less CO, 40–100% more nonmethane organic compounds, and 10–20% less NOx than estimated both by EMFAC and the photochemical modeling inventory. We also describe new temporal distributions of vehicle emissions by hour and day of week. Diesel trucks, a major source of NOx, have a broad midday peak in emissions on weekdays, in contrast to passenger vehicles, which show morning and afternoon commuter peaks. While passenger vehicle travel is similar on weekdays and weekends, diesel truck activity and emissions decrease by 70–80% on weekends. Vehicle emission rates and their temporal patterns are linked to a regional photochemical air pollution episode that spans a weekend in August 1990.

Plants and soils act as major sinks for the destruction of tropospheric ozone, especially during daylight hours when plant stomata open and are thought to provide the dominant pathway for the uptake of ozone. The present study, part of the California Ozone Deposition Experiment, compares predictions of the regional acid deposition model ozone surface conductance module with surface conductance data derived from eddy covariance measurements of ozone flux taken at a grape, a cotton, and a grassland site in the San Joaquin Valley of California during the summer of 1991. Results indicate that the model (which was developed to provide long-term large-area estimates for the eastern United States) significantly overpredicts the surface conductance at all times of the day for at least two important types of plant cover of the San Joaquin Valley and that it incorrectly partitions the ozone flux between transpiring and nontranspiring components of the surface at the third site. Consequently, the model either overpredicts or inaccurately represents the observed deposition velocities. Other results indicate that the presence of dew does not reduce the rate of ozone deposition, contradicting to model assumptions, and that model assumptions involving the dependency of stomata upon environmental temperature are unnecessary. The effects of measurement errors and biases, arising from the presence of the roughness sublayer and possible photochemical reactions, are also discussed. A simpler model for ozone surface deposition (at least for the San Joaquin Valley) is proposed and evaluated.

Analyses of fogwater collected by inertial impaction in the Los Angeles basin and the San Joaquin Valley indicated unusually high concentrations of major and minor ions. The dominant ions measured were NO_3^−, SO_4^(2−), NH_4^+, and H^+. Nitrate exceeded sulfate on an equivalent basis by a factor of 2.5 in the central and coastal regions of the Los Angeles basin but was approximately equal in the eastern Los Angeles basin and the San Joaquin Valley. Maximum observed values for NH_4^+, NO_3^−, and SO_4^(2−) were 10.0, 12.0, and 5.0, meq 1^(−1), while the lowest p;H observed was 2.2. Iron and lead concentrations of over 0.1 mM and 0.01 mM, respectively, were observed. High concentrations of chemical components in fog appeared to correlate well with the occurrence of smog events. Concentrations in fogwater were also affected by the physical processes of condensation and evaporation. Light, dissipating fogs routinely showed the highest concentrations.

Borehole breakouts are caused by unequal stress concentrations around a borehole resulting in shear failure of the borehole wall and creating hole elongation perpendicular to the maximum horizontal in situ stress. Breakouts in Tertiary sedimentary rocks were identified in 10 holes in the West Coalinga, Cantua Creek, and West Haven oil fields in the western San Joaquin Valley. The deeper and more reliable (1.5 to 3.7 km) breakouts were oriented northwest, indicating northeast compressive stress, perpendicular to the major fold axes in the San Joaquin Valley and at a 70°–90° angle to the major strike-slip faults in the Coast Ranges. This stress direction is consistent with a reverse slip component on northwest-trending faults in the region and with the focal mechanisms reported for the May 1983 Coalinga earthquake. The existing literature on stress measurements in central and southern California indicates that on a regional scale, the stress regime is transitional between thrust and strike-slip faulting. A hydraulic fracture test in the Kettleman Hills oil field at 3 km depth indicates that this stress regime exists in the upper crust near Coalinga as well.