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At least 91 records · Page 5

Capturing soil moisture and salinity changes in flooded coastal forests using electrical resistivity and induced polarization

Geophysical methods provide high-resolution spatial measurements of physical quantities sensitive to changes in soil moisture and salinity and can be used to monitor soil hydrological responses to flooding. However, extracting quantitative hydrological information from geophysical data remains challenging. In this study, we extended existing petrophysical models to estimate soil moisture and salinity from electrical measurements to address this challenge. We manipulated two hydrologically isolated 2000 m 2 experimental plots by simultaneously inundating them with 265 m 3 of either freshwater or estuarine water. Repeated electrical resistivity and induced polarization measurements were used to image the water and solute infiltration along two transects that are 100 and 42 m in length. Petrophysical models derived from laboratory multi-salinity electrical measurements were used to estimate changes in soil moisture and fluid salinity from field measurements of real and imaginary conductivity during the ecosystem-scale flooding experiment. The real conductivity increased by ∼100% in the freshwater plot and ∼570% in the saltwater plot. The change in imaginary conductivity in the freshwater plot was <1 mS/m, whereas that of the estuarine water plot was ∼5 mS/m. Real conductivity shows dependence on soil moisture content with a coefficient of determination (R 2 ) > 0.7, while the imaginary conductivity shows a dependence on soil salinity with R 2 > 0.6. The results validate the use of electrical resistivity for estimating changes in soil moisture content in response to flooding. Combining electrical resistivity imaging with induced polarization measurements provides the possibility to account for changes in pore fluid conductivity.

Adebayo, Moses B. [Univ. of Toledo, OH (United Sta↗

Characterization of Iron and Organic Carbon Colloids in Boreal Rivers and Their Fate at High Salinity

Riverine colloids are important carriers of macronutrients, trace metals, and pollutants into marine waters. The aim of the current study was to extend the understanding of iron (Fe) and organic carbon (OC) colloids in boreal rivers and their fate at higher salinities. X-ray absorbance spectroscopy (XAS) and dynamic light scattering (DLS) were combined to explore Fe speciation and colloidal characteristics such as size and surface charge and how these are affected at increasing salinity. XAS confirmed the presence of two Fe phases in the river waters—Fe-organic matter (OM) complexes and Fe(oxy)hydroxides. From DLS measurements on filtered and unfiltered samples, three particle size distributions were identified. The smallest particles (10–40 nm) were positively charged and suggested to consist of essentially bare Fe (oxy)hydroxide nanoparticles. The largest particles (300–900 nm) were dominated by Fe(oxy)hydroxides associated with chromophoric molecular matter. An intermediate size distribution (100–200 nm) with a negative surface charge was presumably dominated by OM and containing Fe-OM complexes. Increasing the salinity resulted in a removal of the smallest distribution. Unexpectedly, both the intermediate and largest size distributions were still detected at high salinity. The collective results suggest that Fe(oxy) hydroxides and Fe-OM complexes are both found across the wide size range studied and that colloidal size does not necessarily reflect either Fe speciation or stability toward salinity-induced aggregation. The findings further demonstrate that also particles beyond the typically studied <0.45-μm size range should be considered to fully understand the riverine transport and fate of macronutrients, trace metals, and pollutants.

54 ENVIRONMENTAL SCIENCES↗

Microbial Ecology and Site Characteristics Underlie Differences in Salinity-Methane Relationships in Coastal Wetlands

Methane (CH 4 ) is a potent greenhouse gas emitted by archaea in anaerobic environments such as wetland soils. Tidal freshwater wetlands are predicted to become increasingly saline as sea levels rise due to climate change. Previous work has shown that increases in salinity generally decrease CH 4 emissions, but with considerable variation, including instances where salinization increased CH 4 flux. We measured microbial community composition, biogeochemistry, and CH 4 flux from field samples and lab experiments from four different sites across a wide geographic range. We sought to assess how site differences and microbial ecology affect how CH 4 emissions are influenced by salinization. CH 4 flux was generally, but not always, positively correlated with CO 2 flux, soil carbon, ammonium, phosphate, and pH. Methanogen guilds were positively correlated with CH 4 flux across all sites, while methanotroph guilds were both positively and negatively correlated with CH 4 depending on site. There was mixed support for negative relationships between CH 4 fluxes and concentrations of alternative electron acceptors and abundances of taxa that reduce them. CH 4 /salinity relationships ranged from negative, to neutral, to positive and appeared to be influenced by site characteristics such as pH and plant composition, which also likely contributed to site differences in microbial communities. The activity of site-specific microbes that may respond differently to low-level salinity increases is likely an important driver of CH 4 /salinity relationships. Our results suggest several factors that make it difficult to generalize CH 4 /salinity relationships and highlight the need for paired microbial and flux measurements across a broader range of sites.

54 ENVIRONMENTAL SCIENCES↗

Irrigation scheduling, freeze warning and soil salinity detecting

The author has identified the following significant results. Correlations of multispectral scanner (MSS) digital data differences between vegetated and bare soil areas with salinity levels from the eight saline areas using MSS bands seven and ten in the infrared region were significant. Correlations were derived for Cameron County, Texas. Detection of saline soils may be possible, using either film density readings or multispectral scanner data, when the lower reflectance of vegetation on highly saline soil and the higher reflectance of vegetation on lower saline soil are considered by using film on MSS contrasts between vegetation and bare soil.

Wiegand, C. L.↗

Remote sensing of salinity

The complex dielectric constant of sea water is a function of salinity at 21 cm wavelength, and sea water salinity can be determined by a measurement of emissivity at 21 cm along with a measurement of thermodynamic temperature. Three aircraft and one helicopter experiments using two different 21 cm radiometers were conducted under different salinity and temperature conditions. Single or multiple ground truth measurements were used to calibrate the data in each experiment. It is inferred from these experiments that accuracies of 1 to 2%/OO are possible with a single surface calibration point necessary only every two hours if the following conditions are met--water temperatures above 20 C, salinities above 10%/OO, and level plane flight. More frequent calibration, constraint of the aircraft's orientation to the same as it was during calibration, and two point calibration (at a high and low salinity level) rather than single point calibration may give even better accuracies in some instances.

Thomann, G. C.↗

Testing of a technique for remotely measuring water salinity in an estuarine environment

An aircraft experiment was flown on November 7, 1973 to test a technique for remote water salinity measurement. Apparent temperatures at 21 cm and 8-14 micron wavelengths were recorded on eight runs over a line along which the salinity varied from 5 to 30%. Boat measurements were used for calibration and accuracy calculations. Overall RMS accuracy over the complete range of salinities was 3.6%. Overall RMS accuracy for salinities greater than 10%, where the technique is more sensitive, was 2.6%. Much of this error is believed to be due to inability to exactly locate boat and aircraft positions. The standard deviation over the eight runs for salinities or = 10% is 1.4%; this error contains a component due to mislocation of the aircraft also. It is believed that operational use of the technique is possible with accuracies of 1-2%.

Thomann, G. C.↗

The salinity effect in a mixed layer ocean model

A model of the thermally mixed layer in the upper ocean as developed by Kraus and Turner and extended by Denman is further extended to investigate the effects of salinity. In the tropical and subtropical Atlantic Ocean rapid increases in salinity occur at the bottom of a uniformly mixed surface layer. The most significant effects produced by the inclusion of salinity are the reduction of the deepening rate and the corresponding change in the heating characteristics of the mixed layer. If the net surface heating is positive, but small, salinity effects must be included to determine whether the mixed layer temperature will increase or decrease. Precipitation over tropical oceans leads to the development of a shallow stable layer accompanied by a decrease in the temperature and salinity at the sea surface.

Miller, J. R.↗

Effects of salinity on the microwave emission of soils

Controlled plot experiments were conducted to collect L and C band passive microwave data concurrent with ground observations of salinity and soil moisture. Two dielectric mixing models were used with an emission model to predict the emissivity from a bare smooth uniform profile. The models produce nearly identical results when near zero salinity is involved and reproduce the observed data at L band extremely well. Discrepancies at C band are attributed to sampling depth problems. Comparisons of predicted emissivities at various salinities with observed values indicate that the dynamic range of the emissivities can be explained using either of the dielectric mixing models. Evaluation of the entire data set, which included four salinity levels, indicates that for general application the effects of soil salinity can be ignored in interpreting microwave data for estimating soil moisture under most agricultural conditions.

Jackson, T. J.↗

Salinity effects on the microwave emission of soils

Controlled plot experiments were conducted to collect L and C band passive microwave data concurrent with ground observations of salinity and soil moisture. Two dielectric mixing models were used with an emission model to predict the emissivity from a bare smooth uniform profile. The models produce nearly identical results when near zero salinity is involved and reproduce the observed data at L band extremely well. Discrepancies at C band are attributed to sampling depth problems. Comparisons of predicted emissivities at various salinities with observed values indicate that the dynamic range of the emissivities can be explained using either of the dielectric mixing models. Evaluation of the entire data set, which included four salinity levels, indicates that for general application the effects of soil salinity can be ignored in interpreting microwave data for estimating soil moisture under most agricultural conditions.

Jackson, Thomas J.↗

Effects of Precipitation on Ocean Mixed-Layer Temperature and Salinity as Simulated in a 2-D Coupled Ocean-Cloud Resolving Atmosphere Model

A two-dimensional coupled ocean-cloud resolving atmosphere model is used to investigate possible roles of convective scale ocean disturbances induced by atmospheric precipitation on ocean mixed-layer heat and salt budgets. The model couples a cloud resolving model with an embedded mixed layer-ocean circulation model. Five experiment are performed under imposed large-scale atmospheric forcing in terms of vertical velocity derived from the TOGA COARE observations during a selected seven-day period. The dominant variability of mixed-layer temperature and salinity are simulated by the coupled model with imposed large-scale forcing. The mixed-layer temperatures in the coupled experiments with 1-D and 2-D ocean models show similar variations when salinity effects are not included. When salinity effects are included, however, differences in the domain-mean mixed-layer salinity and temperature between coupled experiments with 1-D and 2-D ocean models could be as large as 0.3 PSU and 0.4 C respectively. Without fresh water effects, the nocturnal heat loss over ocean surface causes deep mixed layers and weak cooling rates so that the nocturnal mixed-layer temperatures tend to be horizontally-uniform. The fresh water flux, however, causes shallow mixed layers over convective areas while the nocturnal heat loss causes deep mixed layer over convection-free areas so that the mixed-layer temperatures have large horizontal fluctuations. Furthermore, fresh water flux exhibits larger spatial fluctuations than surface heat flux because heavy rainfall occurs over convective areas embedded in broad non-convective or clear areas, whereas diurnal signals over whole model areas yield high spatial correlation of surface heat flux. As a result, mixed-layer salinities contribute more to the density differences than do mixed-layer temperatures.

Li, Xiaofan↗

Effects of the Ionosphere on Passive Microwave Remote Sensing of Ocean Salinity from Space

Among the remote sensing applications currently being considered from space is the measurement of sea surface salinity. The salinity of the open ocean is important for understanding ocean circulation and for modeling energy exchange with the atmosphere. Passive microwave remote sensors operating near 1.4 GHz (L-band) could provide data needed to fill the gap in current coverage and to complement in situ arrays being planned to provide subsurface profiles in the future. However, the dynamic range of the salinity signal in the open ocean is relatively small and propagation effects along the path from surface to sensor must be taken into account. In particular, Faraday rotation and even attenuation/emission in the ionosphere can be important sources of error. The purpose or this work is to estimate the magnitude of these effects in the context of a future remote sensing system in space to measure salinity in L-band. Data will be presented as a function of time location and solar activity using IRI-95 to model the ionosphere. The ionosphere presents two potential sources of error for the measurement of salinity: Rotation of the polarization vector (Faraday rotation) and attenuation/emission. Estimates of the effect of these two phenomena on passive remote sensing over the oceans at L-band (1.4 GHz) are presented.

LeVine, D. M.↗

Analysis of Salinity Intrusion in the San Francisco Bay-Delta using a GA- Optimized Neural Net, and Application of the Model to Prediction in the Elkhorn Slough Habitat

The San Francisco Bay Delta is a large hydrodynamic complex that incorporates the Sacramento and San Joaquin Estuaries, the Burman Marsh, and the San Francisco Bay proper. Competition exists for the use of this extensive water system both from the fisheries industry, the agricultural industry, and from the marine and estuarine animal species within the Delta. As tidal fluctuations occur, more saline water pushes upstream allowing fish to migrate beyond the Burman Marsh for breeding and habitat occupation. However, the agriculture industry does not want extensive salinity intrusion to impact water quality for human and plant consumption. The balance is regulated by pumping stations located alone the estuaries and reservoirs whereby flushing of fresh water keeps the saline intrusion at bay. The pumping schedule is driven by data collected at various locations within the Bay Delta and by numerical models that predict the salinity intrusion as part of a larger model of the system. The Interagency Ecological Program (IEP) for the San Francisco Bay/Sacramento-San Joaquin Estuary collects, monitors, and archives the data, and the Department of Water Resources provides a numerical model simulation (DSM2) from which predictions are made that drive the pumping schedule. A problem with this procedure is that the numerical simulation takes roughly 16 hours to complete a C:~ prediction. We have created a neural net, optimized with a genetic algorithm, that takes as input the archived data from multiple stations and predicts stage, salinity, and flow at the Carquinez Straits (at the downstream end of the Burman Marsh). This model seems to be robust in its predictions and operates much faster than the current numerical DSM2 model. Because the system is strongly tidal driven, we used both Principal Component Analysis and Fast Fourier Transforms to discover dominant features within the IEP data. We then filtered out the dominant tidal forcing to discover non-primary tidal effects, and used this to enhance the neural network by mapping input-output relationships in a more efficient manner. Furthermore, the neural network implicitly incorporates both the hydrodynamic and water quality models into a single predictive system. Although our model has not yet been enhanced to demonstrate improve pumping schedules, it has the possibility to support better decision-making procedures that may then be implemented by State agencies if desired. Our intention is now to use this model in the smaller Elkhorn Slough complex near Monterey Bay where no such hydrodynamic model currently exists. At the Elkhorn Slough, we are fusing the neural net model of tidally-driven flow with in situ flow data and airborne and satellite remote sensation data. These further constrain the behavior of the model in predicting the longer-term health and future of this vital estuary.

Thompson, David E.↗

Long Term Surface Salinity Measurements

Our long-term goal is to establish a reliable system for monitoring surface salinity around the global ocean. Salinity is a strong indicator of the freshwater cycle and has a great influence on upper ocean stratification. Global salinity measurements have potential to improve climate forecasts if an observation system can be developed. This project is developing a new internal field conductivity cell that can be protected from biological fouling for two years. Combined with a temperature sensor, this foul-proof cell can be deployed widely on surface drifters. A reliable in-situ network of surface salinity sensors will be an important adjunct to the salinity sensing satellite AQUARIUS to be deployed by NASA in 2009. A new internal-field conductivity cell has been developed by N Brown, along with new electronics. This sensor system has been combined with a temperature sensor to make a conductivity - temperature (UT) sensor suitable for deployment on drifters. The basic sensor concepts have been proven on a high resolution CTD. A simpler (lower cost) circuit has been built for this application. A protection mechanism for the conductivity cell that includes antifouling protection has also been designed and built. Mr. A.Walsh of our commercial partner E-Paint has designed and delivered time-release formulations of antifoulants for our application. Mr. G. Williams of partner Clearwater Instrumentation advised on power and communication issues and supplied surface drifters for testing.

Schmitt, Raymond W.↗

Salinity Remote Sensing and the Study of the Global Water Cycle

The SMOS and AquariusISAC-D satellite missions will begin a new era to map the global sea surface salinity (SSS) field and its variability from space within the next twothree years. They will provide critical data needed to study the interactions between the ocean circulation, global water cycle and climate. Key scientific issues to address are (1) mapping large expanses of the ocean where conventional SSS data do not yet exist, (2) understanding the seasonal and interannual SSS variations and the link to precipitation, evaporation and sea-ice patterns, (3) links between SSS and variations in the oceanic overturning circulation, (4) air-sea coupling processes in the tropics that influence El Nino, and (4) closing the marine freshwater budget. There is a growing body of oceanographic evidence in the form of salinity trends that portend significant changes in the hydrologic cycle. Over the past several decades, highlatitude oceans have become fresher while the subtropical oceans have become saltier. This change is slowly spreading into the subsurface ocean layers and may be affecting the strength of the ocean's therrnohaline overturning circulation. Salinity is directly linked to the ocean dynamics through the density distribution, and provides an important signature of the global water cycle. The distribution and variation of oceanic salinity is therefore attracting increasing scientific attention due to the relationship to the global water cycle and its influence on circulation, mixing, and climate processes. The oceans dominate the water cycle by providing 86% of global surface evaporation (E) and receiving 78% of global precipitation (P). Regional differences in E-P, land runoff, and the melting or freezing of ice affect the salinity of surface water. Direct observations of E-P over the ocean have large uncertainty, with discrepancies between the various state-of-the-art precipitation analyses of a factor of two or more in many regions. Quantifying the climatic influence of the oceanic water cycle requires more accurately resolving the net air-sea water flux. Measuring global SSS trends on seasonal to interannual timescales by satellite is fundamental to this problem because the SSS trends represent detectable time-integrated signals of the variable marine hydrological cycle. Satellite measurements, coupled with an array of in situ observations, will provide global synoptic SSS fields for the first time history. These data will provide a strong constraint on climate models and data assimilation efforts, which must properly represent the freshwater budget in terms of E-P, ocean advection and surface layer mixing in order to accurately simulate the true ocean state. The SSS fields will allow us to quantify the covariability between the SSS and the strong seasonal E-P cycle in the tropics and high latitudes. Field measurement campaigns to exploit satellite and in situ measurements to close the seasonal E-P cycle over an ocean region are being considered. Lastly the satellite systems will monitor and trace the large long-lived SSS anomalies from year to year that have the potential to influence El Nino and the large scale ocean circulation.

Lagerloef, G. S. E.↗

Assessing the Potential to Derive Air-Sea Freshwater Fluxes from Aquarius-Like Observations of Surface Salinity

A state-of-the-art numerical model is used to investigate the possibility of determining freshwater flux fields from temporal changes io sea-surface salinity (SSS), a goal of the satellite salinity-measuring mission, Aquarius/SAC-D. Because the estimated advective temporal scale is usually longer than the Aquarius/SAC-D revisit time, the possibility of producing freshwater flux estimates from temporal salinity changes is first examined by using a correlation analysis. For the mean seasonal cycle, the patterns of the correlations between the freshwater fluxes and surface salinity temporal tendencies are mainly zonally oriented, and are highest where the local precipitation is also relatively high. Nonseasonal (deviations from the monthly mean) correlations are highest along mid-latitude moon tracks and are relatively small in the tropics. The complex correlation patterns presented here suggest that a global retrieval of the difference between evaporation and precipitation (E-P) from salinity changes requires more complex techniques than a simple consideration of local balance with surface forcing.

Zhen, Li↗

Bulk Moisture and Salinity Sensor

Measurement and feedback control of nutrient solutions in plant root zones is critical to the development of healthy plants in both terrestrial and reduced-gravity environments. In addition to the water content, the amount of fertilizer in the nutrient solution is important to plant health. This typically requires a separate set of sensors to accomplish. A combination bulk moisture and salinity sensor has been designed, built, and tested with different nutrient solutions in several substrates. The substrates include glass beads, a clay-like substrate, and a nutrient-enriched substrate with the presence of plant roots. By measuring two key parameters, the sensor is able to monitor both the volumetric water content and salinity of the nutrient solution in bulk media. Many commercially available moisture sensors are point sensors, making localized measurements over a small volume at the point of insertion. Consequently, they are more prone to suffer from interferences with air bubbles, contact area of media, and root growth. This makes it difficult to get an accurate representation of true moisture content and distribution in the bulk media. Additionally, a network of point sensors is required, increasing the cabling, data acquisition, and calibration requirements. measure the dielectric properties of a material in the annular space of the vessel. Because the pore water in the media often has high salinity, a method to measure the media moisture content and salinity simultaneously was devised. Characterization of the frequency response for capacitance and conductance across the electrodes was completed for 2-mm glass bead media, 1- to 2-mm Turface (a clay like media), and 1- to 2-mm fertilized Turface with the presence of root mass. These measurements were then used to find empirical relationships among capacitance (C), the dissipation factor (D), the volumetric water content, and the pore water salinity.

Nurge, Mark↗

High salinity seawater boiling point elevation: Experimental verification

Boiling point elevation (BPE) for high salinity solutions is a crucial parameter that significantly affects the overall thermal efficiency of desalination, water treatment, and many other industrial processing systems, especially when minimum or zero liquid discharge is a key requirement. This paper addresses the discrepancies among the empirical correlations reported in the literature that were commonly used to determine BPE for seawater solutions. An evaluation of the experimental data with low solution concentration reveals that the data cannot be extrapolated to determine the BPE at high concentration (X > 140 ppt or g/kg). Besides, disparities are established within different equations used to determine the BPE for high salinity seawater. As a result of the minimal availability of experimental data of BPE for X > 140 ppt and the need to eliminate the discrepancies, an experimental setup was built, which can produce reliable and repeatable BPE data for any solution concentration. Boiling points were obtained experimentally for seawater solutions with a wide range of salinity (X between 20 and 280 ppt) and brine solution temperature (t b between 20 and 80°C). The experimental results of boiling point elevations for seawater are further compared with the experimental data and analytical results reported in the literature. The newly obtained experimental results show that the minimum and maximum BPE values for the brine solutions tested are 0.175°C at t b = 80°C and X = 20 ppt, and 11.6°C at t b = 80°C and X = 280 ppt, respectively. Furthermore, the measured BPE data for seawater concentration over 80 ppt are fitted and presented using an appropriate fitting model. The new correlation can accurately predict the BPE for high salinity seawater brines and thus should be very helpful in the design of high-energy-efficient evaporation systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Data-driven offshore CO 2 saline storage assessment methodology

The world produces approximately 50 billion tonnes of greenhouse gases annually. This is measured in CO 2 -equivalents, and geologic CO 2 storage has the potential to advance decarbonization and mitigate greenhouse gas emissions. New technologies to assess offshore carbon storage are needed to address resource, regulatory, and commercial needs. Although most efforts to assess storage resources focus on onshore criteria, offshore reservoirs offer significant storage potential and distinct development challenges. Potential advantages of offshore carbon storage include being further from human population centers and less potential to interact with groundwater. The U.S. Department of Energy's method for evaluating storage capacity in non-oil-bearing saline reservoirs has been enhanced to support assessments for offshore environments in the Offshore CO 2 Saline Storage methodology (OCSS). This methodology applies data-driven capabilities to estimate saline storage capacity while accounting for features specific to offshore reservoirs. Features include changes in CO 2 density and sedimentary differences that impact estimates of permanence and capacity. The Offshore CO 2 Saline Storage Calculator mechanizes OCSS to estimate storage capacity. This paper presents the methodology and estimates for 18 geologic domains in the Gulf of Mexico. Potential storage distributions, sensitivity analyses, and the incorporation of spatial data and tools to support safe site selection are also discussed.

58 GEOSCIENCES↗