Search

The deviation of specific electrical conductance (EC) from conservative mixing behavior is well-established in the scientific literature. This principle is based on the observation that, as salt concentration in a water sample increases, the mobility of individual ions in the sample decreases, and thus their ability to conduct electricity decreases. Despite this fact, some commonly used models for salinity transport in the San Francisco Estuary (estuary) utilize EC as a primary simulation constituent, treating it as a conservative quantity. Such a modeling approach has likely been followed to exploit the wide availability of EC data for model calibration and validation, and to obviate the need to translate between EC and salinity in a domain characterized by multiple source waters with varying ionic make-ups. Arguably, this approach provides a reasonable trade-off between data translation error and model simulation error. In this paper, we critically evaluate this approach, employing an extensive salinity data set that includes measurements of EC and major ion concentrations in the estuary. We demonstrate and quantify EC deviation from steady-state, conservative mixing behavior; review the conservative mixing behavior of three bulk salinity measures (practical salinity, ionic strength, and limiting equivalent conductance); and evaluate their source-dependent correlations with EC in the estuary. We find limiting equivalent conductance—a value that assumes uninhibited mobility among individual ions in a water sample—to be an attractive alternative for salinity transport in the estuary. In addition to being a conservative quantity, it is consistently correlated with EC in the estuary’s dominant source waters, and thus addresses concerns related to data-translation error. We conclude this paper discussing pros and cons of adopting various salinity-transport model constituents.

Accurate estimates of freshwater flow to the San Francisco Estuary are important in successfully regulating this water body, in protecting its beneficial uses, and in accurately modeling its hydrodynamic and water-quality transport regime. For regulatory purposes, freshwater flow to the estuary is not directly measured; rather, it is estimated from a daily balance of upstream Delta inflows, exports, and in-Delta water use termed the net Delta outflow index (NDOI). Field research in the 1960s indicated that NDOI estimates are biased low in summer–fall and biased high in winter–spring as a result of conflating Delta island evapotranspiration estimates with the sum of ungauged hydrologic interactions between channels and islands referred to as net channel depletions. In this work, we employed a 50-year observed salinity record along with gauged tidal flows and an ensemble of five empirical flow-salinity (X2) models to test whether a seasonal bias in Delta outflow estimates could be inferred. We accomplished this objective by conducting statistical analyses and evaluating whether model skill could be improved through seasonal NDOI flow adjustments. Assuming that model residuals are associated with channel depletion uncertainty, our findings corroborate the 1960s research and suggest that channel depletions are biased low in winter months (i.e., NDOI is biased high) and biased high in late summer and early fall months (i.e., NDOI is biased low). The magnitude of seasonal bias, which can reach 1,000 cfs, is a small percentage of typical winter outflow but represents a significant percentage of typical summer outflow. Our findings were derived from five independently developed models, and are consistent with the physical understanding of water exchanges on the islands. This work provides motivation for improved characterization of these exchanges to improve Delta outflow estimates, particularly during drought periods when water supplies are scarce and must be carefully man

This work surveys the performance of several empirical models, all recalibrated to a common data set, that were developed over the past 25 years to relate freshwater flow and salinity in the San Francisco Estuary (estuary). The estuary’s salinity regime—broadly regulated to meet urban, agricultural, and ecosystem beneficial uses—is managed in spring and certain fall months to meet ecosystem objectives by controlling the 2 parts per thousand bottom salinity isohaline position (referred to as X2). We tested five empirical models for accuracy, mean, and transient behavior. We included a sixth model, employing a machine learning framework and variables other than outflow, in this survey to compare fitting skill, but did not subject it to the full suite of tests applied to the other five empirical models. Model performance was observed to vary with hydrology, year, and season, and in some cases exhibited unique limitations as a result of mathematical formulation. However, no single model formulation was found to be consistently superior across a wide range of tests and applications. One test revealed that the models performed equally well when recalibrated to a uniformly perturbed input time-series. Thus, while the models may be used to identify anomalies or seasonal biases (the latter being the subject of a companion paper), their use as inverse models to infer freshwater outflow to the estuary from salinity observations is not expected to improve upon the absolute accuracy of existing outflow estimates. This survey suggests that, for analyses that span a long hydrologic record, an ensemble approach—rather than the use of any individual model on its own—may be preferable to exploit the strengths of individual models.

This work surveys the performance of several empirical models, all recalibrated to a common data set, that were developed over the past 25 years to relate freshwater flow and salinity in the San Francisco Estuary (estuary). The estuary’s salinity regime—broadly regulated to meet urban, agricultural, and ecosystem beneficial uses—is managed in spring and certain fall months to meet ecosystem objectives by controlling the 2 parts per thousand bottom salinity isohaline position (referred to as X2). We tested five empirical models for accuracy, mean, and transient behavior. We included a sixth model, employing a machine learning framework and variables other than outflow, in this survey to compare fitting skill, but did not subject it to the full suite of tests applied to the other five empirical models. Model performance was observed to vary with hydrology, year, and season, and in some cases exhibited unique limitations as a result of mathematical formulation. However, no single model formulation was found to be consistently superior across a wide range of tests and applications. One test revealed that the models performed equally well when recalibrated to a uniformly perturbed input time-series. Thus, while the models may be used to identify anomalies or seasonal biases (the latter being the subject of a companion paper), their use as inverse models to infer freshwater outflow to the estuary from salinity observations is not expected to improve upon the absolute accuracy of existing outflow estimates. This survey suggests that, for analyses that span a long hydrologic record, an ensemble approach—rather than the use of any individual model on its own—may be preferable to exploit the strengths of individual models.

Accurate estimates of freshwater flow to the San Francisco Estuary are important in successfully regulating this water body, in protecting its beneficial uses, and in accurately modeling its hydrodynamic and water-quality transport regime. For regulatory purposes, freshwater flow to the estuary is not directly measured; rather, it is estimated from a daily balance of upstream Delta inflows, exports, and in-Delta water use termed the net Delta outflow index (NDOI). Field research in the 1960s indicated that NDOI estimates are biased low in summer–fall and biased high in winter–spring as a result of conflating Delta island evapotranspiration estimates with the sum of ungauged hydrologic interactions between channels and islands referred to as net channel depletions. In this work, we employed a 50-year observed salinity record along with gauged tidal flows and an ensemble of five empirical flow-salinity (X2) models to test whether a seasonal bias in Delta outflow estimates could be inferred. We accomplished this objective by conducting statistical analyses and evaluating whether model skill could be improved through seasonal NDOI flow adjustments. Assuming that model residuals are associated with channel depletion uncertainty, our findings corroborate the 1960s research and suggest that channel depletions are biased low in winter months (i.e., NDOI is biased high) and biased high in late summer and early fall months (i.e., NDOI is biased low). The magnitude of seasonal bias, which can reach 1,000 cfs, is a small percentage of typical winter outflow but represents a significant percentage of typical summer outflow. Our findings were derived from five independently developed models, and are consistent with the physical understanding of water exchanges on the islands. This work provides motivation for improved characterization of these exchanges to improve Delta outflow estimates, particularly during drought periods when water supplies are scarce and must be carefully man

We evaluated two historically important data sets to characterize the San Francisco Estuary’s salinity regime before the State of California began systematic data collection in the early 1920s. One set documents barge travel along the Sacramento and San Joaquin rivers to obtain water of adequate quality for local industry; a second set documents Delta inflow used to compute antecedent outflow. The barge travel distance reported over 2 decades (1908–1929) was well explained by flow–salinity modeling, indicating internal consistency in these measurements. However, absolute salinity intrusion estimated through the barge travel data is systematically lower than suggested by contemporaneous water-quality measurements available since 1921. Through integration of these data sets, our work showed substantial similarities between 1908–1921 and the subsequent period before construction of Shasta Dam (1922–1944). Our analysis reveals an apparent shift in the estuary’s salinity regime, with lesser salinity intrusion occurring in pre-1919 summer and fall months as a result of higher summer Delta outflow; this shift may be related to lower storage and irrigation diversions as well as a preponderance of wet years with higher summer runoff in the pre–1919 period. We found seasonal patterns of wet year salinity intrusion to be comparable over the full study period (1908–1944), indicating that the relative effect of upstream water management is minimal when flows are high, consistent with findings reported in later periods. The barge and flow data provide qualitative insights on early 20th century conditions, when limited data are available. Post–1920 hydrology and salinity data are preferable for quantitative analyses because of better documentation associated with collection and analysis, and sustained reporting over several decades. This work provides a foundation for future efforts to characterize the hydrologic and hydrodynamic changes that occurred in the system between the 185

We evaluated two historically important data sets to characterize the San Francisco Estuary’s salinity regime before the State of California began systematic data collection in the early 1920s. One set documents barge travel along the Sacramento and San Joaquin rivers to obtain water of adequate quality for local industry; a second set documents Delta inflow used to compute antecedent outflow. The barge travel distance reported over 2 decades (1908–1929) was well explained by flow–salinity modeling, indicating internal consistency in these measurements. However, absolute salinity intrusion estimated through the barge travel data is systematically lower than suggested by contemporaneous water-quality measurements available since 1921. Through integration of these data sets, our work showed substantial similarities between 1908–1921 and the subsequent period before construction of Shasta Dam (1922–1944). Our analysis reveals an apparent shift in the estuary’s salinity regime, with lesser salinity intrusion occurring in pre-1919 summer and fall months as a result of higher summer Delta outflow; this shift may be related to lower storage and irrigation diversions as well as a preponderance of wet years with higher summer runoff in the pre–1919 period. We found seasonal patterns of wet year salinity intrusion to be comparable over the full study period (1908–1944), indicating that the relative effect of upstream water management is minimal when flows are high, consistent with findings reported in later periods. The barge and flow data provide qualitative insights on early 20th century conditions, when limited data are available. Post–1920 hydrology and salinity data are preferable for quantitative analyses because of better documentation associated with collection and analysis, and sustained reporting over several decades. This work provides a foundation for future efforts to characterize the hydrologic and hydrodynamic changes that occurred in the system between the 185

Chronic groundwater overdraft threatens agricultural sustainability in California's Central Valley. Diverting flood flows onto farmland for groundwater recharge offers an opportunity to help address this challenge. We studied the infiltration rate of floodwater diverted from the Kings River at a turnout upstream of the James Weir onto adjoining cropland; and calculated how much land would be necessary to capture the available floodwater, how much recharge of groundwater might be achieved, and the costs. The 1,000-acre pilot study included fields growing tomatoes, wine grapes, alfalfa and pistachios. Flood flows diverted onto vineyards infiltrated at an average rate of 2.5 inches per day under sustained flooding. At that relatively high infiltration rate, 10 acres are needed to capture one CFS of diverted flood flow. We considered these findings in the context of regional expansion. Based upon a 30-year record of Kings Basin surplus flood flows, we estimate 30,000 acres operated for on-farm flood recharge would have had the capacity to capture 80% of available flood flows and potentially offset overdraft rates in the Kings Basin. Costs of on-farm flood capture for this study were estimated at $36 per acre-foot, less than the cost for surface water storage and dedicated recharge basins.

Chronic groundwater overdraft threatens agricultural sustainability in California's Central Valley. Diverting flood flows onto farmland for groundwater recharge offers an opportunity to help address this challenge. We studied the infiltration rate of floodwater diverted from the Kings River at a turnout upstream of the James Weir onto adjoining cropland; and calculated how much land would be necessary to capture the available floodwater, how much recharge of groundwater might be achieved, and the costs. The 1,000-acre pilot study included fields growing tomatoes, wine grapes, alfalfa and pistachios. Flood flows diverted onto vineyards infiltrated at an average rate of 2.5 inches per day under sustained flooding. At that relatively high infiltration rate, 10 acres are needed to capture one CFS of diverted flood flow. We considered these findings in the context of regional expansion. Based upon a 30-year record of Kings Basin surplus flood flows, we estimate 30,000 acres operated for on-farm flood recharge would have had the capacity to capture 80% of available flood flows and potentially offset overdraft rates in the Kings Basin. Costs of on-farm flood capture for this study were estimated at $36 per acre-foot, less than the cost for surface water storage and dedicated recharge basins.

Packed-tower, counter-current air stripping is a treatment process that can be employed for removal of volatile organic compounds (VOCs) from water and wastewater. The design of an air stripper is performed using a well- developed mathematical model of the process. However, the number of variables involved exceeds the number of constraining equations by two, with the result that a number of alternative air stripper designs exist for a particular water treatment goal. In selecting the optimum design among the various alternatives, it is important to consider the capital and operating costs associated with each alternative. This report describes an interactive, microcomputer-based program - the Air Stripper Design and Costing (ASDC) program - that enables rapid evaluation of alternative air stripper designs and approximate costs associated with these designs for user-specified treatment scenarios. The various components of the program are described in detail, a guide to program operation is provided along with example applications, and results of some verification tests are presented. Air Stripping, Computer design, Water Treatment, Volatile organic compound, Also included with AD-M000 308. Revision of report dated Dec 91.

Packed-tower, counter-current air stripping is a treatment process that can be employed for removal of volatile organic compounds (VOCS) from water and wastewater. The design of an air stripper is performed using a well- developed mathematical model of the process. However, the number of variables involved exceeds the number of constraining equations by two, with the result that a number of alternative air stripper designs exist for a particular water treatment goal. In selecting the optimum design among the various alternatives, it is important to consider the capital and operating costs associated with each alternative. This report describes an interactive, microcomputer-based program - the Air Stripper Design and Costing (ASDC) program - that enables rapid evaluation of alternative air stripper designs and approximate costs associated with these designs for user-specified treatment scenarios. The various components of the program are described in detail, a guide to program operation is provided along with example applications, and results of some verification tests are presented.