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USGS2010

Water-budget methods

A water budget is an accounting of water movement into and out of, and storage change within, some control volume. Universal and adaptable are adjectives that reflect key features of water-budget methods for estimating recharge. The universal concept of mass conservation of water implies that water-budget methods are applicable over any space and time scales (Healy et al ., 2007). The water budget of a soil column in a laboratory can be studied at scales of millimeters and seconds. A water-budget equation is also an integral component of atmospheric general circulation models used to predict global climates over periods of decades or more. Water-budget equations can be easily customized by adding or removing terms to accurately portray the peculiarities of any hydrologic system. The equations are generally not bound by assumptions on mechanisms by which water moves into, through, and out of the control volume of interest. So water-budget methods can be used to estimate both diffuse and focused recharge, and recharge estimates are unaffected by phenomena such as preferential flow paths within the unsaturated zone. Water-budget methods represent the largest class of techniques for estimating recharge. Most hydrologic models are derived from a water-budget equation and can therefore be classified as water-budget models. It is not feasible to address all water-budget methods in a single chapter. This chapter is limited to discussion of the “residual” water-budget approach, whereby all variables in a water-budget equation, except for recharge, are independently measured or estimated and recharge is set equal to the residual. This chapter is closely linked with Chapter 3, on modeling methods, because the equations presented here form the basis of many models and because models are often used to estimate individual components in water-budget studies. Water budgets for streams and other surface-water bodies are addressed in Chapter 4. The use of soil-water budgets and lysimeters for determining potential recharge and evapotranspiration from changes in water storage is discussed in Chapter 5. Aquifer water-budget methods based on the measurement of groundwater levels are described in Chapter 6.

Book chapter↗

USGS2024

Physics-based satellite-derived bathymetry (SDB) using Landsat OLI images

The estimation of depth in optically shallow waters using satellite imagery can be efficient and cost-effective. Active sensors measure the distance traveled by an emitted laser pulse propagating through the water with high precision and accuracy if the bottom peak intensity of the waveform is greater than the noise level. However, passive optical imaging of optically shallow water involves measuring the radiance after the sunlight undergoes downward attenuation on the way to the sea floor, and the reflected light is then attenuated while moving back upward to the water surface. The difficulty of satellite-derived bathymetry (SDB) arises from the fact that the measured radiance is a result of a complex association of physical elements, mainly the optical properties of the water, bottom reflectance, and depth. In this research, we attempt to apply physics-based algorithms to solve this complex problem as accurately as possible to overcome the limitation of having only a few known values from a multispectral sensor. Major analysis components are atmospheric correction, the estimation of water optical properties from optically deep water, and the optimization of bottom reflectance as well as the water depth. Specular reflection of the sky radiance from the water surface is modeled in addition to the typical atmospheric correction. The physical modeling of optically dominant components such as dissolved organic matter, phytoplankton, and suspended particulates allows the inversion of water attenuation coefficients from optically deep pixels. The atmospheric correction and water attenuation results are used in the ocean optical reflectance equation to solve for the bottom reflectance and water depth. At each stage of the solution, physics-based models and a physically valid, constrained Levenberg–Marquardt numerical optimization technique are used. The physics-based algorithm is applied to Landsat Operational Land Imager (OLI) imagery over the shallow coastal zone of Guam, Key West, and Puerto Rico. The SDB depths are compared to airborne lidar depths, and the root mean squared error (RMSE) is mostly less than 2 m over water as deep as 30 m. As the initial choice of bottom reflectance is critical, along with the bottom reflectance library, we describe a pure bottom unmixing method based on eigenvector analysis to estimate unknown site-specific bottom reflectance.

Remote Sensing↗

USGS2008

Crop area estimation using high and medium resolution satellite imagery in areas with complex topography

Reliable estimates of cropped area (CA) in developing countries with chronic food shortages are essential for emergency relief and the design of appropriate market-based food security programs. Satellite interpretation of CA is an effective alternative to extensive and costly field surveys, which fail to represent the spatial heterogeneity at the country-level. Bias-corrected, texture based classifications show little deviation from actual crop inventories, when estimates derived from aerial photographs or field measurements are used to remove systematic errors in medium resolution estimates. In this paper, we demonstrate a hybrid high-medium resolution technique for Central Ethiopia that combines spatially limited unbiased estimates from IKONOS images, with spatially extensive Landsat ETM+ interpretations, land-cover, and SRTM-based topography. Logistic regression is used to derive the probability of a location being crop. These individual points are then aggregated to produce regional estimates of CA. District-level analysis of Landsat based estimates showed CA totals which supported the estimates of the Bureau of Agriculture and Rural Development. Continued work will evaluate the technique in other parts of Africa, while segmentation algorithms will be evaluated, in order to automate classification of medium resolution imagery for routine CA estimation in the future.

Journal of Geophysical Research D: Atmospheres↗

USGS2010

Local energy flux estimates for unstable conditions using variance data in semiarid rangelands

A network of meteorological stations was installed during the Monsoon '90 field campaign in the Walnut Gulch experimental watershed. The study area has a fairly complex surface. The vegetation cover is heterogeneous and sparse, and the terrain is mildly hilly, but dissected by ephemeral channels. Besides measurement of some of the standard weather data such as wind speed, air temperature, and solar radiation, these sites also contained instruments for estimating the local surface energy balance. The approach utilized measurements of net radiation ( R n ), soil heat flux ( G ) and Monin-Obukhov similarity theory applied to first- and second-order turbulent statistics of wind speed and temperature for determining the sensible heat flux ( H ). The latent heat flux ( LE ) was solved as a residual in the surface energy balance equation, namely, LE = −( R n + G + H ). This procedure (VAR-RESID) for estimating the energy fluxes satisfied monetary constraints and the requirement for low maintenance and continued operation through the harsh environmental conditions experienced in semiarid regions. Comparison of energy fluxes using this approach with more traditional eddy correlation techniques showed differences were within 20% under unstable conditions. Similar variability in flux estimates over the study area was present in the eddy correlation data. Hence, estimates of H and LE using the VAR-RESID approach under unstable conditions were considered satisfactory. Also, with second-order statistics of vertical velocity collected at several sites, the local momentum roughness length was estimated. This is an important parameter used in modeling the turbulent transfer of momentum and sensible heat fluxes across the surface-atmosphere interface.

Water Resources Research↗

USGS2012

Trace metal concentrations in snow from the Yukon River Basin, Alaska and Canada

We report here on metal concentrations in snow collected from the Yukon River basin. Atmospheric transport of metals and subsequent deposition is a known mechanism for introducing metals into the northern environment. Potential sources of airborne elements are locally generated terrestrial sources, locally derived anthropogenic sources, and long range atmospheric transport. Sites were distributed along the Yukon River corridor and within the southeastern, central, and western basin areas. Snow samples were taken in the spring of 2001 and 2002 when the snow pack was at its maximum. Total-depth composite samples were taken from pits using clean techniques. Mercury was analyzed using cold vapor atomic fluorescence spectrometry. All other elements were analyzed by inductively coupled plasma-mass spectrometry. In samples from remote sites, the concentration for selected metals ranged from: 0.015 - 0.34 ug/L for V, 0.01 - 0.22 ug/L for Ni, < 0.05 - 0.52 ug/L for Cu, 0.14 - 2.8 ug/L for Zn, 0.002 - 0.046 ug/L for Cd, 0.03 - 0.13 ug/L for Pb, 0.00041 - 0.0023 ug/L for filtered-Hg. Because the entire snow pack was sampled and there was no evidence of mid-season thaw, these concentrations represent the seasonal deposition. There was no significant difference in the seasonal deposition of V, Ni, Cu, Zn, Cd, and Pb at these sites between 2001 and 2002, and no north-south or east-west trend in concentrations. Samples taken from within communities, however, had significantly higher concentrations of V, Ni, Cu, Zn, and Cd in 2001, and Ni, Cu, and Pb in 2002 relative to the remote sites. Our data indicate that the atmospheric deposition of metals in the Yukon River basin is relatively uniform both spatially and temporally. However, communities have a measurable but variable effect on metal concentrations. Copyright ASCE 2005.

Conference Paper↗

USGS1982

Phase relations in the system NaCl-KCl-H2O. Part I: Differential thermal analysis of the NaCl-KCl liquidas at 1 atmosphere and 500, 1000, 1500, and 2000 bars

A simple differential thermal analysis (DTA) technique has been developed to study phase relations of various chemical systems at elevated pressures and temperatures. The DTA system has been calibrated against known melting temperatures in the system NaCl-KCl. Isobaric sections of the liquidus in the system NaCl-KCl have been determined at pressures of 1 atmosphere and 500, 1000, 1500, and 2000 bars. Using the least-squares method, the following equation was used to fit the experimental data: T(°C)= ∑ i=0 6 a i X i KCl "> T(°C)=∑i=06a i X i KCl where T is the liquidus temperature, X KCl is mole fraction of KCl, and a i (listed below) are the derived empirical constants. P (bars) a o "> ao a 1 "> a1 a 2 "> a2 a 3 "> a3 a 4 "> a4 a 5 "> a5 a 6 "> a6 1 atm. 800.1 −334.2 781.6 −6490.3 17553.1 −17638.4 6098.3 500 813.5 −354.9 743.3 −6011.7 16406.4 −16516.3 5702.8 1000 824.5 −406.7 1446.8 −8818.4 21253.5 −20343.7 6839.4 1500 838.6 −418.7 1434.7 −8819.0 21557.9 −20908.4 7123.1 2000 848.5 −381.5 1246.9 −8605.0 21785.8 −21449.1 7375.8 The liquidus temperatures estimated from these equations are within ±3°C of experimental values. The measured liquidus temperatures at 1 atmosphere agree with the best available data to within 5°C. The melting temperatures for pure end members at higher pressures agree with the values calculated from the Simon equation (Clark, 1959) to within 3°C. No previous melting data are available for the intermediate compositions at elevated pressures. Using the data in both heating and cooling scans, the minimum melting temperature at 1 atmosphere in the system was located at 658° ± 3° C where the sample has an equimolar composition.

Geochimica et Cosmochimica Acta↗

USGS1999

Hydrologic assessment of the Upper Dorr Run Watershed, Hocking County, Ohio, 1998

The Upper Dorr Run Watershed in Hocking County, Ohio, has been mined several times for coal and clay since 1913 and is a significant source of acid mine drainage to the Hocking River. To assess the surface-water hydrology of the site, a topographic map showing the location of springs and other hydrologic features of interest was prepared using aerial photography and field surveying and mapping techniques. Discharge and water-quality measurements at six springs and one stream site were made during field investigations in June 1998. Discharge and water quality observed at a downstream weir on Upper Dorr Run represents the combined discharge from springs plus ground-water inflow. Discharges from springs to surface water were generally small (less than 0.3 cubic foot per second), but one spring constituted 56 percent of the total discharge measured at the downstream weir. The total flow at an intermediate measurement site was less than the combined discharge of the upgradient springs because of evaporation, transpiration, and ground-water flow beneath the stream channel. The total flow at the weir was greater than the combined discharge of all springs, primarily because two potential sources of water were not included in field measurements. The water quality in Upper Dorr Run is strongly affected by acid mine drainage as indicated by pH less than 4, elevated acidity, and elevated concentrations of dissolved sulfate and dissolved iron. Concentrations of chemical constituents in the water were lower at the downstream weir than at the source springs because of residence times in ponds and chemical interactions between the water and the atmosphere. Acidity loads during the sampling period were significantly higher from the Lower Kittanning (No. 5) coal (272 kilograms per day) than from the Upper Kittanning (No. 6) coal (17.7 kilograms per day). Comparison of data obtained in 1998 to data obtained in 1982 showed that quality of water of selected sampling sites had not changed appreciably in 16 years.

Water-Resources Investigations Report↗

USGS2002

Net ecosystem production: A comprehensive measure of net carbon accumulation by ecosystems

The conceptual framework used by ecologists and biogeochemists must allow for accurate and clearly defined comparisons of carbon fluxes made with disparate techniques across a spectrum of temporal and spatial scales. Consistent with usage over the past four decades, we define "net ecosystem production" (NEP) as the net carbon accumulation by ecosystems. Past use of this term has been ambiguous, because it has been used conceptually as a measure of carbon accumulation by ecosystems, but it has often been calculated considering only the balance between gross primary production (GPP) and ecosystem respiration. This calculation ignores other carbon fluxes from ecosystems (e.g., leaching of dissolved carbon and losses associated with disturbance). To avoid conceptual ambiguities, we argue that NEP be defined, as in the past, as the net carbon accumulation by ecosystems and that it explicitly incorporate all the carbon fluxes from an ecosystem, including autotrophic respiration, heterotrophic respiration, losses associated with disturbance, dissolved and particulate carbon losses, volatile organic compound emissions, and lateral transfers among ecosystems. Net biome productivity (NBP), which has been proposed to account for carbon loss during episodic disturbance, is equivalent to NEP at regional or global scales. The multi-scale conceptual framework we describe provides continuity between flux measurements made at the scale of soil profiles and chambers, forest inventories, eddy covariance towers, aircraft, and inversions of remote atmospheric flask samples, allowing a direct comparison of NEP estimates made at all temporal and spatial scales.

Ecological Applications↗

USGS2019

Quantifying the eroded and deposited mass of mercury-contaminated sediment by using terrestrial laser scanning at the confluence of Humbug Creek and the South Yuba River, Nevada County, California, 2011–13

High-resolution, terrestrial laser scanning, also known as ground-based lidar (light detection and ranging), was used to quantify the volume of mercury-contaminated sediment eroded from an outcrop of historical placer-mining debris at the confluence of Humbug Creek and the South Yuba River in the Sierra Nevada foothills, about 17 kilometers northeast of Grass Valley, California, and delivered to a zone below an observed flood stage of the South Yuba River. Substantial quantities of mercury were used and lost to the environment from historical placer gold mining activities on the western slope of the Sierra Nevada, California, and recent studies have documented continued persistence of mercury and methylmercury concentrations in water, sediment, fish, and predatory invertebrates in the Yuba River drainage basin in relation to suspected mercury sources. To identify areas that have high levels of mercury contamination as possible remediation targets in the Yuba River drainage basin and other areas in the Sierra Nevada, the U.S. Geological Survey worked in cooperation with the Bureau of Land Management on this and other detailed studies. Malakoff Diggings, one of the largest hydraulic gold mines in the Sierra Nevada, is 3.5 kilometers north of the study site in the Humbug Creek subbasin. Terrestrial laser scanning was used to produce centimeter-scale, three-dimensional maps of the complex outcrop surface, which was composed of an upper erosional area (cliff and over-steepened slope) and a lower depositional area (colluvial slope). The outcrop could not be mapped non-destructively or in sufficient detail by traditional surveying techniques. The study site, which was approximately 70 meters long, 30 meters wide and 20 meters high, was surveyed four times in 2 years (December 15, 2011; October 25, 2012; January 4, 2013; and November 22, 2013) to determine volumetric differences in the upper erosional and lower depositional areas between surveys. Measured changes in volume for the upper erosional area and lower depositional area were multiplied by the corresponding sediment density so that a mass-balance relationship, between the eroded and deposited sediment during each period, could be used to estimate the amount of mercury-contaminated sediment that was transported to below the base of the colluvial slope, where it could be mobilized by the South Yuba River during a flood having a 5-to-10-year recurrence interval. On December 2, 2012, a flood of this estimated magnitude reached the base of the colluvial slope. Between the first and second surveys (December 15, 2011–October 25, 2012), an estimated mass of 18±9.2 kilograms of sediment was transported from steeper slopes to the gently sloping river bank below the base of the colluvial slope. Between the second and third surveys (October 25, 2012–January 4, 2013), an atmospheric river caused heavy precipitation at the study site during late November and early December 2012. This short-duration, high-intensity rain resulted in a large amount of erosion and deposition at the study site and also caused high streamflow (flood stage) in the South Yuba River. From October 2012 to January 2013, 51±31 kilograms of sediment was transported to below the base of the colluvial slope, that is, below the high-water mark of December 2, 2012. Between the third and fourth surveys (January 4, 2013–November 22, 2013), an additional 10±26 kilograms of sediment was transported to below the base of the colluvial slope. During the 24 months of the study, the total mass of sediment delivered below the base of the colluvial slope and the high-water mark of December 2, 2012, was 79±66 kilograms. In any given year there is a 10–20-percent chance (5-to-10-year recurrence interval) of a flood equal to or greater than that of the December 2, 2012, flood, which could transport mercury-contaminated sediment at the study site into the South Yuba River. Hydraulically modeled estimates of the South Yuba River stage during floods having a 50- and 100-year recurrence interval (2- and 1-percent annual exceedance probability, respectively) indicated that resulting river stages could be 2.2–3.0 meters above the base of the colluvial slope, or 2.2–3.0 meters above the high-water mark of December 2, 2012. Such high river stages would be likely to inundate the lower half of the colluvial slope and mobilize a substantial volume of mercury-contaminated sediment to downstream areas.

California↗

USGS2023

A one-dimensional volcanic plume model for predicting ash aggregation

During explosive volcanic eruptions, volcanic ash is ejected into the atmosphere, impacting aircraft safety and downwind communities. These volcanic clouds tend to be dominated by fine ash (<63 μm in diameter), permitting transport over hundreds to thousands of kilometers. However, field observations show that much of this fine ash aggregates into clusters or pellets with faster settling velocities than individual particles. Models of ash transport and deposition require an understanding of aggregation processes, which depend on factors like moisture content and local particle collision rates. In this study, we develop a Plume Model for Aggregate Prediction, a one-dimensional (1D) volcanic plume model that predicts the plume rise height, concentration of water phases, and size distribution of resulting ash aggregates from a set of eruption source parameters. The plume model uses a control volume approach to solve mass, momentum, and energy equations along the direction of the plume axis. The aggregation equation is solved using a fixed pivot technique and incorporates a sticking efficiency model developed from analog laboratory experiments of particle aggregation within a novel turbulence tower. When applied to the 2009 eruption of Redoubt Volcano, Alaska, the 1D model predicts that the majority of the plume is over-saturated with water, leading to a high rate of aggregation. Although the mean grain size of the computed Redoubt aggregates is larger than the measured deposits, with a peak at 1 mm rather than 500 μm, the present results provide a quantitative estimate for the magnitude of aggregation in an eruption.

JGR Solid Earth↗

USGS2005

NOAA-USGS Debris-Flow Warning System - Final Report

Landslides and debris flows cause loss of life and millions of dollars in property damage annually in the United States (National Research Council, 2004). In an effort to reduce loss of life by debris flows, the National Oceanic and Atmospheric Administration's (NOAA) National Weather Service (NWS) and the U.S. Geological Survey (USGS) operated an experimental debris-flow prediction and warning system in the San Francisco Bay area from 1986 to 1995 that relied on forecasts and measurements of precipitation linked to empirical precipitation thresholds to predict the onset of rainfall-triggered debris flows. Since 1995, there have been substantial improvements in quantifying precipitation estimates and forecasts, development of better models for delineating landslide hazards, and advancements in geographic information technology that allow stronger spatial and temporal linkage between precipitation forecasts and hazard models. Unfortunately, there have also been several debris flows that have caused loss of life and property across the United States. Establishment of debris-flow warning systems in areas where linkages between rainfall amounts and debris-flow occurrence have been identified can help mitigate the hazards posed by these types of landslides. Development of a national warning system can help support the NOAA-USGS goal of issuing timely Warnings of potential debris flows to the affected populace and civil authorities on a broader scale. This document presents the findings and recommendations of a joint NOAA-USGS Task Force that assessed the current state-of-the-art in precipitation forecasting and debris-flow hazard-assessment techniques. This report includes an assessment of the science and resources needed to establish a demonstration debris-flow warning project in recently burned areas of southern California and the necessary scientific advancements and resources associated with expanding such a warning system to unburned areas and, possibly, to a national scope.

Circular↗

USGS2014

Tracking changes in volcanic systems with seismic Interferometry

The detection and evaluation of time-dependent changes at volcanoes form the foundation upon which successful volcano monitoring is built. Temporal changes at volcanoes occur over all time scales and may be obvious (e.g., earthquake swarms) or subtle (e.g., a slow, steady increase in the level of tremor). Some of the most challenging types of time-dependent change to detect are subtle variations in material properties beneath active volcanoes. Although difﬁcult to measure, such changes carry important information about stresses and ﬂuids present within hydrothermal and magmatic systems. These changes are imprinted on seismic waves that propagate through volcanoes. In recent years, there has been a quantum leap in the ability to detect subtle structural changes systematically at volcanoes with seismic waves. The new methodology is based on the idea that useful seismic signals can be generated “at will” from seismic noise. This means signals can be measured any time, in contrast to the often irregular and unpredictable times of earthquakes. With seismic noise in the frequency band 0.1–1 Hz arising from the interaction of the ocean with the solid Earth known as microseisms, researchers have demonstrated that cross-correlations of passive seismic recordings between pairs of seismometers yield coherent signals (Campillo and Paul 2003; Shapiro and Campillo 2004). Based on this principle, coherent signals have been reconstructed from noise recordings in such diverse ﬁelds as helioseismology (Rickett and Claerbout 2000), ultrasound (Weaver and Lobkis 2001), ocean acoustic waves (Roux and Kuperman 2004), regional (Shapiro et al. 2005; Sabra et al. 2005; Bensen et al. 2007) and exploration (Draganov et al. 2007) seismology, atmospheric infrasound (Haney 2009), and studies of the cryosphere (Marsan et al. 2012). Initial applications of ambient seismic noise were to regional surface wave tomography (Shapiro et al. 2005). Brenguier et al. (2007) were the ﬁrst to use ambient noise tomography (ANT) to map the 3D structure of a volcanic interior (at Piton de la Fournaise). Subsequent studies have imaged volcanoes with ANT at Okmok (Masterlark et al. 2010), Toba (Stankiewicz et al. 2010), Katmai (Thurber et al. 2012), Asama (Nagaoka et al. 2012), Uturuncu (Jay et al. 2012), and Kilauea (Ballmer et al. 2013b). In addition, Ma et al. (2013) have imaged a scatterer in the volcanic region of southern Peru by applying array techniques to ambient noise correlations. Prior to and in tandem with the development of ANT, researchers discovered that repeating earthquakes, which often occur at volcanoes, could be used to monitor subtle time-dependent changes with a technique known as the doublet method or coda wave interferometry (CWI) (Poupinet et al. 1984; Roberts et al. 1992; Ratdomopurbo and Poupinet 1995; Snieder et al. 2002; Pandolﬁ et al. 2006; Wegler et al. 2006; Martini et al. 2009; Haney et al. 2009; De Angelis 2009; Nagaoka et al. 2010; Battaglia et al. 2012; Erdem and Waite 2005; Hotovec-Ellis et al. 2014). Chaput et al. (2012) have also used scattered waves from Strombolian eruption coda at Erebus volcano to image the reﬂectivity of the volcanic interior with body wave interferometry. However, CWI in its original form was limited in that repeating earthquakes, or doublets, were not always guaranteed to occur. With the widespread use of noise correlations in seismology following the groundbreaking work by Campillo and Paul (2003) and Shapiro et al. (2005), it became evident that the nature of the ambient seismic ﬁeld, due to its oceanic origin, enabled the continuous monitoring of subtle, time-dependent changes at both fault zones (Wegler and Sens-Schönfelder 2007; Brenguier et al. 2008b; Wegler et al. 2009; Sawazaki et al. 2009; Tatagi et al. 2012) and volcanoes (Sens-Schönfelder and Wegler 2006; Brenguier et al. 2008a) without the need for repeating earthquakes. Seismic precursors to eruptions based on ambient noise we

Book chapter↗

USGS2016

Stable isotope analyses of oxygen (18O:17O:16O) and chlorine (37Cl:35Cl) in perchlorate: reference materials, calibrations, methods, and interferences

Rationale Perchlorate (ClO 4 − ) is a common trace constituent of water, soils, and plants; it has both natural and synthetic sources and is subject to biodegradation. The stable isotope ratios of Cl and O provide three independent quantities for ClO 4 − source attribution and natural attenuation studies: δ 37 Cl, δ 18 O, and δ 17 O (or Δ 17 O or 17 Δ) values. Documented reference materials, calibration schemes, methods, and interferences will improve the reliability of such studies. Methods Three large batches of KClO 4 with contrasting isotopic compositions were synthesized and analyzed against VSMOW-SLAP, atmospheric O 2 , and international nitrate and chloride reference materials. Three analytical methods were tested for O isotopes: conversion of ClO 4 − to CO for continuous-flow IRMS (CO-CFIRMS), decomposition to O 2 for dual-inlet IRMS (O2-DIIRMS), and decomposition to O 2 with molecular-sieve trap (O2-DIIRMS+T). For Cl isotopes, KCl produced by thermal decomposition of KClO 4 was reprecipitated as AgCl and converted into CH 3 Cl for DIIRMS. Results KClO 4 isotopic reference materials (USGS37, USGS38, USGS39) represent a wide range of Cl and O isotopic compositions, including non-mass-dependent O isotopic variation. Isotopic fractionation and exchange can affect O isotope analyses of ClO 4 − depending on the decomposition method. Routine analyses can be adjusted for such effects by normalization, using reference materials prepared and analyzed as samples. Analytical errors caused by SO 4 2 − , NO 3 − , ReO 4 2 − , and C-bearing contaminants include isotope mixing and fractionation effects on CO and O 2 , plus direct interference from CO 2 in the mass spectrometer. The results highlight the importance of effective purification of ClO 4 − from environmental samples. Conclusions KClO 4 reference materials are available for testing methods and calibrating isotopic data for ClO 4 − and other substances with widely varying Cl or O isotopic compositions. Current ClO 4 − extraction, purification, and analysis techniques provide relative isotope-ratio measurements with uncertainties much smaller than the range of values in environmental ClO 4 − , permitting isotopic evaluation of environmental ClO 4 − sources and natural attenuation.

Rapid Communications in Mass Spectrometry↗

USGS2006

Determination of the δ 15 N of total nitrogen in solids; RSIL lab code 2893

The purpose of the Reston Stable Isotope Laboratory (RSIL) lab code 2893 is to determine the δ( 15 N/ 14 N), abbreviated as δ 15 N , of total nitrogen in solid samples. A Carlo Erba NC 2500 elemental analyzer (EA) is used to convert total nitrogen in a solid sample into N 2 gas. The EA is connected to a continuous flow isotope-ratio mass spectrometer (CF-IRMS), which determines relative difference in the isotope-amount ratios of stable nitrogen isotopes ( 15 N/ 14 N)of the product N 2 gas. The combustion is quantitative; no isotopic fractionation is involved. Samples are placed in a tin capsule and loaded into the Costech Zero Blank Autosampler of the EA. Under computer control, samples are dropped into a heated reaction tube that contains an oxidant, where the combustion takes place in a helium atmosphere containing an excess of oxygen gas. Combustion products are transported by a helium carrier through a reduction tube to remove excess oxygen and convert all nitrous oxides into N 2 and through a drying tube to remove water. The gas-phase products, mainly CO 2 and N 2 , are separated by a gas chromatograph. The gas is then introduced into the isotope-ratio mass spectrometer (IRMS) through a Finnigan MAT (now Thermo Scientific) ConFlo II interface, which also is used to inject N 2 reference gas and helium for sample dilution. The IRMS is a Thermo Scientific Delta V Plus CF-IRMS. It has a universal triple collector, two wide cups with a narrow cup in the middle, capable of measuring mass/charge ( m/z ) 28, 29, 30, simultaneously. The ion beams from N 2 are as follows: m/z 28 = N 2 = 14 N 14 N; m/z 29 = N 2 = 14 N 15 N primarily; m/z 30 = NO = 14 N 16 O primarily, which is a sign of contamination or incomplete reduction.

Techniques and Methods↗

USGS2006

Determination of the δ 34 S of Total Sulfur in Solids: RSIL Lab Code 1800

The purpose of Reston Stable Isotope Laboratory Lab (RSIL) Code 1800 is to determine the δ( 34 S/ 32 S), abbreviated as δ 34 S, of total sulfur in a solid sample. A Carlo Erba NC 2500 elemental analyzer (EA) is used to convert total sulfur in a solid sample into SO 2 gas. The EA is connected to a continuous flow isotope-ratio mass spectrometer (CF-IRMS), which determines the relative difference in stable sulfur isotope-amount ratio ( 34 S/ 32 S) of the product SO 2 gas. The combustion is quantitative; no isotopic fractionation is involved. Samples are placed in tin capsules and loaded into a Costech Zero-Blank Autosampler on the EA. Under computer control, samples are dropped into a heated tube reaction tube that combines both the oxidation and the reduction reactions. The combustion takes place in a He atmosphere that contains an excess of oxygen gas at the oxidation zone at the top of the reaction tube. Combustion products are transported by a He carrier through the reduction zone at the bottom of the reaction tube to remove excess oxygen and through a separate drying tube to remove any water. The gas-phase products, mainly CO 2 , N 2 , and SO 2 , are separated by a gas chromatograph (GC). The gas is then introduced into the isotope-ratio mass spectrometer (IRMS) through a Thermo-Finnigan ConFlo II interface, which also is used to inject SO 2 reference gas and He for sample dilution. The IRMS is a Thermo-Finnigan DeltaPlus CF-IRMS. It has a universal triple collector with two wide cups and a narrow cup in the middle. It is capable of measuring mass/charge ( m/z ) 64 and 66 simultaneously. The ion beams from SO 2 are as follows: m/z 64 = SO 2 = 32 S 16 O 16 O; and m/z 66 = SO 2 = 34 S 16 O 16 O primarily.

Techniques and Methods↗

USGS2006

Determination of the δ 34 S of sulfate in water; RSIL lab code 1951

The purpose of the Reston Stable Isotope Laboratory (RSIL) lab code 1951 is to determine the δ( 34 S/ 32 S), abbreviated as δ 34 S, of dissolved sulfate. Dissolved sulfate is collected in the field and precipitated with BaCl 2 at pH 3 to 4 as BaSO 4 in the laboratory. However, the dissolved organic sulfur (DOS) is oxidized to SO 2 , and the carbonate is acidified to CO 2 . Both are degassed from the water sample before the sulfate is precipitated. The precipitated BaSO 4 is filtered and dried before introduction into an elemental analyzer (EA) Carlo Erba NC 2500. The EA is used to convert sulfur in a BaSO 4 solid sample into SO 2 gas, and the EA is connected to a continuous flow isotope-ratio mass spectrometer (CF-IRMS), which determines the differences in the isotope-amount ratios of stable sulfur isotopes ( 34 S/ 32 S) of the product SO 2 gas. The combustion is quantitative; no isotopic fractionation is involved. Samples are placed in a tin capsule and loaded into the Costech Zero Blank Autosampler of the EA. Under computer control, samples are dropped into a heated tube reaction tube that combines the oxidation and reduction reactions. The combustion takes place in a helium atmosphere containing an excess of oxygen gas at the oxidation zone at the top of the reaction tube. Combustion products are transported by a helium carrier through the reduction zone at the bottom of the reaction tube to remove excess oxygen and through a separate drying tube to remove any water. The gas-phase products, mainly CO 2 , N 2 , and SO 2 , are separated by a gas chromatograph. The gas is then introduced into the isotope-ratio mass spectrometer (IRMS) through a Finnigan MAT (now Thermo Scientific) ConFlo II interface, which also is used to inject SO 2 reference gas and helium for sample dilution. The IRMS is a Thermo Scientific Delta V Plus CF-IRMS. It has a universal triple collector with two wide cups and a narrow cup in the middle. It is capable of measuring mass/charge ( m/z ) 64 and 66 simultaneously. The ion beams from SO 2 are as follows: m/z 64 = SO 2 = 32 S 16 O 16 O; m/z 66 = SO 2 = 34 S 16 O 16 O primarily.

Techniques and Methods↗

USGS2006

Determination of the δ 34 S of low-concentration sulfate in water; RSIL lab code 1949

The purpose of the Reston Stable Isotope Laboratory (RSIL) lab code 1949 is to determine the δ( 34 S/ 32 S), abbreviated as δ 34 S, of dissolved sulfate having a concentration less than 20 milligrams per liter. Dissolved sulfate is collected on an anion-exchange resin in the field, eluted in the laboratory with 3 M KCl, and precipitated with BaCl 2 at pH 3 to 4 as BaSO 4 . The precipitated BaSO 4 is filtered and dried before introduction into an elemental analyzer (EA) Carlo Erba NC 2500. The EA is used to convert sulfur in a BaSO 4 solid sample into SO 2 gas, and the EA is connected to a continuous flow isotope-ratio mass spectrometer (CF-IRMS), which determines differences in the isotope-amount ratios of stable sulfur isotopes ( 34 S/ 32 S) of the product SO 2 gas. The combustion is quantitative; no isotopic fractionation is involved. Samples are placed in a tin capsule and loaded into the Costech Zero Blank Autosampler of the EA. Under computer control, samples are dropped into a heated reaction tube that combines the oxidation and reduction reactions. The combustion takes place in a helium atmosphere containing an excess of oxygen gas at the oxidation zone at the top of the reaction tube. Combustion products are transported by a helium carrier through the reduction zone at the bottom of the reaction tube to remove excess oxygen and through a separate drying tube to remove any water. The gas-phase products, mainly CO 2 , N 2 , and SO 2 , are separated by a gas chromatograph. The gas is then introduced into the isotope-ratio mass spectrometer (IRMS) through a Finnigan MAT (now Thermo Scientific) ConFlo II interface, which is also used to inject SO 2 reference gas and helium for sample dilution. The IRMS is a Thermo Scientific Delta V Plus CF-IRMS. It has a universal triple collector with two wide cups and a narrow cup in the middle. It is capable of measuring mass/charge ( m/z ) 64 and 66 simultaneously. The ion beams from SO 2 are as follows: m/z 64 = SO 2 = 32 S 16 O 16 O; m/z 66 = SO 2 = 34 S 16 O 16 O primarily.

Techniques and Methods↗

USGS2022

Section 5: Remote sensing of vegetation in the riparian corridor of the Colorado River’s delta 2013-2018

This remote sensing section is based on Nagler et al. (in preparation for the journal Hydrological Processes) and is a summary of the USGS preliminary findings to date. This report documents the changes in green foliage density (greenness) as measured by satellite vegetation index (VI) data and corresponding evapotranspiration (ET) in the riparian corridor of the Colorado River delta associated with the Minutes 319 and 323 environmental water deliveries using time-series data from 2013 through 2018. The report focuses on what happened only within the riparian corridor’s seven reaches since the 2014 flows, and despite being a continuation of measuring greenness and ET after the 2017 end of Minute 319, this study continued the tracking of these two variables, greenness and ET, in these original riparian corridor focal areas. Two spatial scales are used here: (1) Landsat satellite imagery at 30 m pixels and (2) the EOS-1 satellite sensor the Moderate Resolution Imaging Spectrometer (MODIS) with a resolution of 250 m pixels. The focal period includes 2013 (prepulse flow) and the years 2014-2018, with a focus on imagery collected from the Summer growing seasons 2014 through 2018 (one-year, pre-pulse and several post-pulse years, respectively). This report re-creates the 2013-2017 Landsat-based results from Jarchow et al. (2017a, b) by using the same region of interest (ROI). The report now provides revised and re-created results using all new imagery acquisition and processing techniques, as well as extraction code, created by the Vegetation Index and Phenology (VIP) Lab of the Biosystems Engineering Department of the University of Arizona (UofA). In 2018, methods employed by the VIP lab (and not ArcGIS) were used. ArcGIS was only used in the newly processed data to display the final difference maps. The entire spatial tile data from NASA was downloaded and processed at the VIP Lab using satellite imagery at two resolutions: 250 m MODIS and 30 m Landsat using three sensors, Landsat 5, Landsat 7 ETM+ and Landsat 8 Operational Land Imager (OLI), with added scenes for each year based on new clear atmosphere requirements. The VIP lab clipped the river boundary and seven riparian reaches from the previously existing ROI used in Jarchow et al. (2017 a, b) for the analyses done under Minute 319. The NASA image datasets for this riparian corridor ROI in seven reaches were re-processed to produce additional vegetation index (VI) information for years 2013 to 2018 for this report. At the same time, the report acquired and processed imagery from 2000- 2018 (data outside the scope of this report and data not shown here). The additional VIs (NDVI, scaled NDVI, EVI, EVI2) were analyzed so that new assessments of greenness and ET could be produced from the imagery datasets following methods in Nagler et al. (2013). These VI choices were based on previous performance comparisons between biophysical ground-based data and radiometric satellite-based data collected from this riparian ecosystem (Nagler et al., 2001) as well as performance related to ET estimation (Nagler et al., 2005a, b) and current advancements in VIs such as EVI2.

Colorado River Delta↗