Combining multivariate statistical analysis with geographic information systems mapping: a tool for delineating groundwater contamination

Multivariate Statistical Analysis (MSA) has successfully been coupled with geographic information system (GIS) mapping tools to delineate zones of aquifer contamination potential. While delineating contaminants is key to site remediation, it is often compromised by a poor understanding of hydrogeologic conditions, and by uncertainties in contaminant observations. MSA provides improved estimates of contamination potential by augmenting observed contaminant concentrations with auxiliary information from other water-quality parameters. GIS is useful for organizing and managing water-quality information by visually communicating large amounts of information. The proposed method first establishes appropriate areal extents, GIS coverages, and scales for displaying groundwater contamination concentrations of tritium and the volatile organic contaminants trichloroethylene (TCE) and tetrachloroethylene (PCE) at the Savannah River Site, South Carolina, USA. Principal components analysis is used to group variables that are most indicative of contamination potential. Tritium contamination potential is best represented as the combination of tritium with the cations Al, Mg, Na and total dissolved solids, while PCE contamination potential is predicted using PCE and Cl. Maps of contamination potentials for 1993–1995 geochemical data compare favorably with measured contaminant concentrations during 1999. Cluster analysis of water-quality data groups geochemical and contaminant concentrations into zones of homogeneous behavior.

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Resumen El Análisis Estadístico Multivariado (AEM) se ha acoplado con éxito con herramientas cartográficas del Sistema de Información Geográfico (SIG), para delinear zonas de potencial contaminación de acuíferos. En tanto que la delimitación de contaminantes es importante para recuperación del sitio, ella está a menudo amenazada por una comprensión pobre de las condiciones hidrogeológicas, y por las incertidumbres en las observaciones del contaminante. El AEM proporciona estimaciones mejoradas de contaminación potencial al aumentar las concentraciones observadas del contaminante, con la información auxiliar de otros parámetros de calidad de agua. El SIG es útil para organizar y manejar la información de calidad de agua, a través de la comunicación visual de cantidades grandes de información. El método propuesto establece primero magnitudes de área apropiadas, el área cubierta por el SIG, y las escalas para mostrar las concentraciones de contaminación del agua subterránea, a partir de tritio y de contaminantes orgánicos volátiles como tricloroetileno (TCE) y tetracloroetileno (PCE) en el sitio del Río al Savannah, Carolina del Sur, EE.UU. El análisis de componentes principales se usa para agrupar variables que son más indicativas de contaminación potencial. El potencial de contaminación Tritio, se representa mejor como la combinación de tritio con los cationes Al, Mg, Na y los sólidos disueltos totales, mientras la contaminación potencial de PCE se predice usando PCE y Cl. Los mapas de potenciales de contaminación para los datos geoquímicos de 1993–1995 se comparan favorablemente con las concentraciones medidas del contaminante durante 1999. El análisis de racimo hecho en datos de calidad de agua, agrupa concentraciones geoquímicas y concentraciones del contaminante en las zonas de comportamiento homogéneo.

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Résumé L’Analyse Statistique Multivariée (ASM) a été couplée avec succès avec les outils cartographiques des Sytèmes d’Information Géographique (SIG), afin de délimiter les zones à potentiel de contamination des aquifères. Alors que la connaissance de l’extension des contaminants est primordiale pour la réhabilitation des sites, elle est fréquemment compromise par une compréhension limitée du contexte hydrogéologique, et par les incertitudes sur l’observation des contaminants. L’ASM fournit une meilleure estimation du potentiel de contamination, en complétant les concentrations observées en contaminants par des informations annexes issues d’autres paramètres qualitatifs. Les SIG, par leurs capacités à conjuguer visuellement de grandes quantités d’information, sont utiles pour organiser et gérer les informations sur la qualité de l’eau. La première étape de la méthode proposée consiste à définir les limites spatiales appropriées, les couvertures SIG, ainsi que les échelles de visualisation des concentrations en contaminants des eaux souterraines, soit le tritium et les composés organiques volatiles trichloroéthylène et tetrachloroéthylène, sur le site de la rivière Savannah (Californie du Sud, USA). L’analyse en composantes principales est utilisée afin de regrouper les variables caractérisant de manière optimale le potentiel de contamination. Le potentiel de contamination en tritium est représenté le plus significativement par la combinaison du tritium, des cations Al, Mg et Na, et des solides dissous totaux (TDS). Le potentiel de contamination en tétrachloroéthylène est quant à lui estimé en utilisant le tetrachloroéthylène et Cl. Les cartes des potentiels de contamination établies sur les données géochimiques de la période 1993–1995 renvoient une image comparable aux concentrations en contaminants effectivement mesurées en 1999. Une analyse de groupement des données sur la qualité de l’eau rassemble les concentrations géochimiques et en contaminants dans des zones aux comportements homogènes.

     

Determination of denitrification in the Chesapeake Bay from measurements of N2 accumulation in bottom water

This study demonstrates the feasibility of using direct N₂ measurements in an estuary for determination of denitrification. High precision measurements of dinitrogen: argon ratios (N₂∶Ar) were made by membrane inlet mass spectrometry on water samples taken along the length of the Chesapeake Bay in July and October 2004. The N₂∶Ar ratio in low salinity surface water was elevated relative to air saturation by 0.3–0.5% with no systematic change along the length of the Bay. N₂∶Ar in high salinity bottom water exhibited a linear increase in the landward direction along a 144-km longitudinal section. In this section of the Bay covering 20% of the main stem, the bottom water salinity was statistically uniform and the increase in N₂∶Ar was in the direction of net residual current flow. The system was analyzed as a capped river with the assumption that N₂ entered the water from the underlying sediment where denitrification is known to take place. The rate of denitrification needed to support the measured increase in N₂ was calculated using an average residual current velocity and water column depth. The increase in N₂ with distance (0.046μmol N l⁻¹ km⁻¹) equated to an average denitrification flux of 73 μmol N m⁻² h⁻¹. N₂ fluxes determined on sediment cores taken from the source and terminus regions of the delineated water mass were 45±23 and 83±39 μmol N m⁻² hr⁻¹, respectively, which were not statistically different from the whole system estimate. The measured change in oxygen concentration within the bottom water was used to estimate nitrogen remineralization and the efficiency of denitrification. Denitrification efficiency (nitrogen denitrified/nitrogen remineralized) was estimated to be in the range of 22–28% for the bottom water sediment system and 30–37% considering the sediment zone alone.     

Optimal linear combinations of triple frequency carrier phase data from future global navigation satellite systems

With the introduction of a third frequency on GPS Block IIF satellites and the implementation of Galileo, there will be three freely available carrier phase measurements transmitted from each system. This change in satellite navigation infrastructure will enable the use of linear combinations of the original measurements that are not currently available. As a result, it is conceivable that there may be an optimal choice of combination coefficients for a given positioning campaign. This article outlines some of the motivations of using linear combinations of Global Navigation Satellite System (GNSS) data. For example, linear combinations can be used to eliminate or mitigate individual sources of error, they can be used to alleviate excessive computational burdens, and they can be used to reduce the necessary bandwidth in communication systems. Upon establishing the motivations for using linear combinations of data, the mathematical theory involved in creating linear combinations is given. The variance of the combined signal is shown to be a weighted sum of the variances of the error sources in the untransformed signals. The weights depend on the choice of combination coefficients and the nominal frequencies of the carrier signals. As a result, there are certain choices of combination coefficients that eliminate or mitigate individual sources of error. Three categories of combinations are developed: those that eliminate the ionospheric effect, those that mitigate the effects of thermal noise and multipath, and those that mitigate the tropospheric effects. The relationships between these various categories of linear combinations are shown geometrically and the concept of optimal linear combinations of data is discussed. Finally, experimental results using optimal linear combinations of data are shown. The results are obtained using a commercially available software simulator and a GNSS processing engine from the Mobile Multi-Sensor Research Group in the Geomatics Engineering Department of the University of Calgary. It is shown that there indeed exist combinations that produce approximately the same ambiguity estimation accuracy as the pure L1 (or E1) signals, but that deliver far better baseline precision results. However, like the pure L1 (or E1) signals, instantaneously resolving integer ambiguities with these combinations will be impossible for baselines longer than about 15 km depending on the existing ionospheric conditions.     

The availability of hydrogeologic data associated with areas identified by the US Geological Survey as experiencing potentially induced seismicity resulting from subsurface injection

A critical need exists for site-specific hydrogeologic data in order to determine potential hazards of induced seismicity and to manage risk. By 2015, the United States Geological Survey (USGS) had identified 17 locations in the USA that are experiencing an increase in seismicity, which may be potentially induced through industrial subsurface injection. These locations span across seven states, which vary in geological setting, industrial exposure and seismic history. Comparing the research across the 17 locations revealed patterns for addressing induced seismicity concerns, despite the differences between geographical locations. Most induced seismicity studies evaluate geologic structure and seismic data from areas experiencing changes in seismic activity levels, but the inherent triggering mechanism is the transmission of hydraulic pressure pulses. This research conducted a systematic review of whether data are available in these locations to generate accurate hydrogeologic predictions, which could aid in managing seismicity. After analyzing peer-reviewed research within the 17 locations, this research confirms a lack of site-specific hydrogeologic data availability for at-risk areas. Commonly, formation geology data are available for these sites, but hydraulic parameters for the seismically active injection and basement zones are not available to researchers conducting peer-reviewed research. Obtaining hydrogeologic data would lead to better risk management for injection areas and provide additional scientific evidential support for determining a potentially induced seismic area.     

Blooms of Dinoflagellate Mixotrophs in a Lower Chesapeake Bay Tributary: Carbon and Nitrogen Uptake over Diurnal,Seasonal, and Interannual Timescales

A multi-year study was conducted in the eutrophic Lafayette River, a sub-tributary of the lower Chesapeake Bay during which uptake of inorganic and organic nitrogen (N) and C compounds was measured during multiple seasons and years when different dinoflagellate species were dominant. Seasonal dinoflagellate blooms included a variety of mixotrophic dinoflagellates including Heterocapsa triquetra in the late winter, Prorocentrum minimum in the spring, Akashiwo sanguinea in the early summer, and Scrippsiella trochoidea and Cochlodinium polykrikoides in late summer and fall. Results showed that no single N source fueled algal growth, rather rates of N and C uptake varied on seasonal and diurnal timescales, and within blooms as they initiated and developed. Rates of photosynthetic C uptake were low yielding low assimilation numbers during much of the study period and the ability to assimilate dissolved organic carbon augmented photosynthetic C uptake during bloom and non-bloom periods. The ability to use dissolved organic C during the day and night may allow mixotrophic bloom organisms a competitive advantage over co-occurring phytoplankton that are restricted to photoautotrophic growth, obtaining N and C during the day and in well-lit surface waters.     

Rainfall-derived growing season characteristics for agricultural impact assessments in South Africa

Precipitation variability imposes significant pressure in areas where agricultural practice is dominated by smallholder farmers who are dependent on subsistence farming. Advances in the understanding of this variability, in both time and space, have an important role to play in increasing the resilience of agricultural systems. The need is particularly pressing in regions of the world such as the African continent, which is already affected by multiple stresses including poverty and economic and political instability. In this paper, we explore the use of generalised linear models (GLMs) for this purpose, via a case study from north-east South Africa. A GLM is used to link the local rainfall variability to large-scale climate drivers identified from previous subcontinental-scale analyses, and the ability of the resulting model to simulate precipitation features that are relevant in agricultural applications is evaluated. We focus in particular on a set of growing season indices, proposed for the investigation of intraseasonal characteristics relevant for maize production in the region. Seven indices were computed from spatially averaged daily rainfall series from nine stations in the study area. As a first attempt to use GLMs for this type of application, the results are encouraging and suggest that the models are able to reproduce a range of agriculture-relevant indices. However, further research into spatial correlation structure is recommended to improve the multisite generation of the rainfall-derived characteristics.     

Water Scarcity: Moving Beyond Indexes to Innovative Institutions

Water scarcity is a media darling often times described as a trigger of conflict in arid regions, a by‐product of human influences ranging from desertification to climate change, or a combination of natural‐ and human‐induced changes in the water cycle. A multitude of indexes have been developed over the past 20 years to define water scarcity to map the “problem” and guide international donor investment. Few indexes include groundwater within the metrics of “scarcity.” Institutional communication contributes to the recognition of local or regional water scarcity. However, evaluations that neglect groundwater resources may incorrectly define conditions as scarce. In cases where there is a perception of scarcity, the incorporation of groundwater and related storage in aquifers, political willpower, new policy tools, and niche diplomacy often results in a revised status, either reducing or even eliminating the moniker locally. Imaginative conceptualization and innovative uses of aquifers are increasingly used to overcome water scarcity.     

Timing and distribution of alluvial fan sedimentation in response to strengthening of late Holocene ENSO variability in the Sonoran Desert,southwestern Arizona,USA

The integration of geomorphic mapping, soil stratigraphy, and radiocarbon dating of alluvial deposits offers insight to the timing, magnitude, and paleoclimatic context of Holocene fan sedimentation near Yuma, Arizona. Mapping of 3400 km² indicates about 10% of the area aggraded in the late Holocene and formed regionally extensive alluvial fan and alluvial plain cut-and-fill terraces. Fan deposits have weakly developed gravelly soils and yielded a date of 3200–2950 cal yr BP from carbonized wood. Alluvial plain deposits have weakly developed buried sandy soils and provided a date of 2460–2300 cal yr BP from a terrestrial snail shell. Precipitation records were analyzed to form historical analogues to the late Holocene aggradation and to consider the role of climatic variability and extreme hydrologic events as drivers of the sedimentation. The historical precipitation record indicates numerous above-average events correlated to the Southern Oscillation Index (SOI) in the region, but lacks any significant reactivation of alluvial fan surfaces. The timing of aggradation from 3200 to 2300 cal yr BP correlates well with other paleoclimatic proxy records in the southwestern U.S. and eastern Pacific region, which indicate an intensification of the El Niño-Southern Oscillation (ENSO) climatic pattern and rapid climate change during this period.     

International viewpoint and news

The Daliao river system in China has been seriously affected by long-term intensive industrial, urban and agricultural activities. The objectives of this study were to determine the total phosphorus (TP) content and forms of phosphate in the sediments and investigate geochemical relationships between P forms and sediment mineral phases. Twenty-seven samples of surface sediments were collected and analyzed for P and major elements. Chemical forms of phosphate in the sediments were measured by sequential selective extraction method. Results indicate that TP in the sediments of the Daliao river system averaged 703 mg kg⁻¹, in the range from 206 to 1,342 mg kg⁻¹. The sediments in the tributaries and near cities contained high TP, due to discharge of municipal and industrial effluents. The distribution of phosphate in the various mineral phases followed the order: Ca-P > RES-P > RS-P > Fe-P > Al-P > S/L-P for the Hun river and Taizi river, and Ca-P > Fe-P > RES-P > RS-P > Al-P > S/L-P for the Daliao river. Fe and Ca contents in the sediments were positively correlated to Fe associated P (Fe-P and RS-P) and Ca-P, respectively. In addition, sediment organic matter, Fe and Ca contents were positively correlated to TP in the sediments. However, Al content was not correlated to Al-P or TP in the sediments. Generally, the sediments contaminated by effluents and in tidal zone contained more bioavailable P. Possible release of P from these sediments to overlying water might pose potential risk on estuarine eutrophication.