Simulating Nitrate Leaching Profiles in a Highly Permeable Vadose Zone

An approach is developed to simulate leaching of a dissolved chemical constituent in the vadose zone of an aquifer. Specifically, nitrate loading at the water table for different water table depths, for a range of aquifer permeability values, and for different cases of heterogeneity of the aquifer, are considered. Models from the literature are first used to derive soil–water characteristic curves (water retention and hydraulic conductivity) from a grain size distribution curve for unsaturated conditions. Given infiltration from the surface, the initial conditions for the chemical concentration, and the water content profile, leaching of the chemical in the vadose zone is simulated as a function of both time and depth. The methodology is illustrated for a permeable aquifer. Simulations are undertaken using a finite element code for saturated and unsaturated flow. Different scenarios are simulated depending on the heterogeneity of the aquifer and the depth of the water table. Modeling results show that in the example case studied, nitrate concentration loading at the water table does not depend strongly on the position of the water table, but rather on the material properties of the aquifer. The contribution of this endeavor resides in the methodology which allows a prediction of nitrate leaching using only the grain size property of the aquifer. It allows practitioners to obtain a first assessment of leaching with limited data.     

STUMOD—a Tool for Predicting Fate and Transport of Nitrogen in Soil Treatment Units

A typical onsite wastewater treatment system consists of a septic tank and a soil treatment unit to treat wastewater before it is discharged through the vadose zone to an aquifer. A tool was developed for the purpose of predicting the fate and transport of nitrogen in soil treatment units (STUMOD or Soil Treatment Unit Model). STUMOD calculates nitrogen species concentrations and the fraction of total nitrogen reaching the aquifer or a specified soil depth. Input data include parameters for hydraulics and nutrient transport and transformation. An analytical solution is used to calculate the profile of pressure based on Darcy’s equation and the relationships between suction head, unsaturated hydraulic conductivity, and soil moisture. Chemical transport is based on simplification of the advection–dispersion equation. STUMOD is relatively simple to use but accounts for important processes such as ammonium sorption, nitrification, and denitrification. STUMOD accounts for the effect of soil moisture content (a surrogate for redox conditions) on nitrification and denitrification reactions. The model has provisions to handle the influence of temperature and organic carbon content on nitrogen transformation. Model outputs, generated based on input parameters obtained from extensive literature review, were compared to a numerical model and data from laboratory tests and field sites. Both measured data and STUMOD outputs show a relatively higher removal in clayey soils compared to sandy soils. Consistent with literature data for most soils, STUMOD predicted ammonium conversion to nitrate within the first foot below the trench infiltrative surface.     

Assessing the impact of irrigation treatments on thiram residual trends: Correspondence with numerical modelling and field-scale experiments

The present study was undertaken to study the trends of transport of thiram, a dithiocarbamate pesticide, at different time and depth in the fields under real field conditions for wheat crop. Numerical simulations were carried out by solving the coupled soil–water content movement and mass transport equations using HYDRUS- 1D. The supplementary data used for paramaterization of HYDRUS-1D comprise of irrigation treatments, climatic conditions, and soil characteristics. Results focus on the effects and influence of irrigation treatments on pesticide persistence and mobility. Modelling results were in good agreement with the experimentally determined thiram concentrations. Application of the model to measured field data of thiram movement indicates that the modelling approach can provide reliable and useful estimates of the mass flux of water and non-volatile pesticide in vadose zone. For policy-makers and planners, some regulation strategies are suggested for controlling inappropriate pesticide application under deficit irrigation or rain-fed conditions.     

Using electrical resistivity tomography to assess the effectiveness of managed aquifer recharge in a salinized coastal aquifer

Over 40 years, the detrital aquifer of the Plana de Castellón (Spanish Mediterranean coast) has been subjected to seawater intrusion because of long dry periods combined with intensive groundwater exploitation. Against this backdrop, a managed artificial recharge (MAR) scheme was implemented to improve the groundwater quality. The large difference between the electrical conductivity (EC) of the ambient groundwater (brackish water due to marine intrusion) and the recharge water (freshwater) meant that there was a strong contrast between the resistivities of the brackish water saturated zone and the freshwater saturated zone. Electrical resistivity tomography (ERT) can be used for surveying similar settings to evaluate the effectiveness of artificial recharge schemes. By integrating geophysical data with lithological information, EC logs from boreholes, and hydrochemical data, we can interpret electrical resistivity (ER) with groundwater EC values and so identify freshwater saturated zones. Using this approach, ERT images provided a high-resolution spatial characterization and an accurate picture of the shape and extent of the recharge plume of the MAR site. After 5 months of injection, a freshwater plume with an EC of 400–600 μS/cm had formed that extended 400 m in the W-E direction, 250 m in the N-S direction, and to a depth of 40 m below piezometric level. This study also provides correlations between ER values with different lithologies and groundwater EC values that can be used to support other studies.     

Soil Gas Volatile Organic Compound Concentration Contours for Locating Vadose Zone Nonaqueous Phase Liquid Contamination

Diffusion of VOC from cylindrical vadose zone domains contaminatedwith distributed nonaqueous phase liquid is examined in the steadystate approximation. The effects of first-order biodegradation and ofan extended underlying pool of LNAPL floating on the water table belowthe cylindrical domain are explored by means of an orthogonal functionsapproach. The distribution of VOC in the vadose zone above a floatingcircular LNAPL pool of finite size is explored by a numerical method.The results provide information useful in estimating the spacing anddepth at which soil gas samples should be taken in order to detect thepresence of such source areas. Comparison of model results with soilgas VOC measurements at various depths also provides insight into theextent to which natural biodegradation of the VOCs is taking place.     

Trace metals: Inputs, sedimentation and accumulation in San Vicente Bay, Chile

The present study deals with sediment dynamics affecting sediment-associated metal distributions in an embayment system experiencing pollution from coastal industries. Sedimentary metal content may originate from diagenetic processes of foundation rock on the bottom, allochthonous minerals from natural sources, and metals from industrial effluents along the coast. The study presents experimental estimations of quantities of metals entering the bay in industrial wastewater, measurements of metal content in particulate material captured in sediment traps, and metals distribution in surface sediments. Quantitative estimations of metals entering the system in industrial effluent showed the relation Pb Zn > Cu > Cr Ni > Cd. That of metals associated with particulate material from traps was Zn > Cr Cu > Pb > Ni > Cd and the abundance of metals in sediments was Zn > Cr > Cu > Pb > Ni > Cd. Finally, rates of bottom sediment accumulation are estimated in relation to the time of residence of water in the bay. The experimental data on sedimentation and sediment abundance were consistent with field observations on distribution and accumulation at sites of major sedimentation in this bay.     

Fate and movement of atrazine, cyanazine, metolachlor and selected degradation products in water resources of the deep Loess Hills of Southwestern Iowa, USA

The environmental fate and movement of herbicides widely used for weed control in corn are assessed for a deep loess soil in southwestern Iowa. Beginning in the early 1980s, the herbicide-based weed control program emphasized the application of atrazine (ATR) or cyanazine (CYN) and metolachlor (MET) for both broadleaf and grass control. Between 1992 and 1995, concentrations of ATR, desethylatrazine (DEA), desisopropylatrazine (DIA), CYN and MET were measured in rainwater, both shallow and deep vadose zone water, and well water. Results show that the frequency of herbicide detections and the range and distribution of occurrences are dependent upon both landscape position and temporal inputs of recharge water from rainfall. Generally, DIA was observed more frequently and in higher mean concentration in well water than DEA, while DEA was observed more frequently than DIA in vadose zone groundwater. A chromatographic analogy is suggested to explain the occurrence patterns observed for both parent herbicide and degradation products within the unsaturated zone water. Analysis of rainwater samples collected during this time also revealed low concentrations of ATR, CYN and MET, with the timing of the detections indicative of non-local transport. Results show that the deep loess soil conducts both water and agricultural chemicals relatively rapidly and as such represents a production system which is vulnerable to contamination of shallow groundwater by herbicide-derived chemicals. Results also illustrate the importance of including major herbicide degradation products in water resource impact assessment studies.     

Using GA-Ridge regression to select hydro-geological parameters influencing groundwater pollution vulnerability

For groundwater conservation and management, it is important to accurately assess groundwater pollution vulnerability. This study proposed an integrated model using ridge regression and a genetic algorithm (GA) to effectively select the major hydro-geological parameters influencing groundwater pollution vulnerability in an aquifer. The GA-Ridge regression method determined that depth to water, net recharge, topography, and the impact of vadose zone media were the hydro-geological parameters that influenced trichloroethene pollution vulnerability in a Korean aquifer. When using these selected hydro-geological parameters, the accuracy was improved for various statistical nonlinear and artificial intelligence (AI) techniques, such as multinomial logistic regression, decision trees, artificial neural networks, and case-based reasoning. These results provide a proof of concept that the GA-Ridge regression is effective at determining influential hydro-geological parameters for the pollution vulnerability of an aquifer, and in turn, improves the AI performance in assessing groundwater pollution vulnerability.     

Environmental Factors and Risk Areas of West Nile Virus in Southern California, 2007–2009

The West Nile virus (WNV) may post a significant health risk for mammals, including humans and insects. This study examines the spatial–temporal effects of environmental factors on WNV dissemination with a case study of ten counties in the southern California, where the epidemic was recently most prevalent within the USA. WNV surveillance data were obtained from the California Vectorborne Disease Surveillance System and Centers for Disease Control and Prevention. Remote sensing and Geographic Information Systems (GIS) techniques were combined to derive environmental variables. Principal component analysis was performed to select the most relevant environmental variables. Two ecological zones were identified based on the selected variables. Identification of risk areas for WNV was limited to a zone with 95% mosquitoes surveillance records. Three time windows, the epidemiological weeks?18–26, 27–35, and 36–44 in each year of 2007–2009, were examined in details with risk area mapping. It is found that the southern part of San Joaquin Valley in Kern County and Los Angeles County (especially its southern part) were the most vulnerable locations for WNV outbreak. Main factors contributing to the WNV propagation included summer mean temperature, annual mean deviation from the mean temperature, land surface temperature, elevation, landscape complexity, landscape diversity, and vegetation water content. The result of this study improves understanding of WNV ecology and provides tools for detecting, tracking, and predicting the epidemic. The holistic approach developed for this study, which integrated remotely sensed, GIS-based, and in situ-measured environmental data with landscape metrics, may be applied to studies of other vector-borne diseases.     

Polynomial Surrogates for Open-Channel Flows in Random Steady State

Assessing epistemic uncertainties is considered as a milestone for improving numerical predictions of a dynamical system. In hydrodynamics, uncertainties in input parameters translate into uncertainties in simulated water levels through the shallow water equations. We investigate the ability of generalized polynomial chaos (gPC) surrogate to evaluate the probabilistic features of water level simulated by a 1-D hydraulic model (MASCARET) with the same accuracy as a classical Monte Carlo method but at a reduced computational cost. This study highlights that the water level probability density function and covariance matrix are better estimated with the polynomial surrogate model than with a Monte Carlo approach on the forward model given a limited budget of MASCARET evaluations. The gPC-surrogate performance is first assessed on an idealized channel with uniform geometry and then applied on the more realistic case of the Garonne River (France) for which a global sensitivity analysis using sparse least-angle regression was performed to reduce the size of the stochastic problem. For both cases, Galerkin projection approximation coupled to Gaussian quadrature that involves a limited number of forward model evaluations is compared with least-square regression for computing the coefficients when the surrogate is parameterized with respect to the local friction coefficient and the upstream discharge. The results showed that a gPC-surrogate with total polynomial degree equal to 6 requiring 49 forward model evaluations is sufficient to represent the water level distribution (in the sense of the \(\ell _2\) norm), the probability density function and the water level covariance matrix for further use in the framework of data assimilation. In locations where the flow dynamics is more complex due to bathymetry, a higher polynomial degree is needed to retrieve the water level distribution. The use of a surrogate is thus a promising strategy for uncertainty quantification studies in open-channel flows and should be extended to unsteady flows. It also paves the way toward cost-effective ensemble-based data assimilation for flood forecasting and water resource management.     

Predicting soil water content at − 33 kPa by pedotransfer functions in stoniness 1 soils in northeast Venezuela

Soil water content is a key property in the study of water available for plants, infiltration, drainage, hydraulic conductivity, irrigation, plant water stress and solute movement. However, its measurement consumes time and, in the case of stony soils, the presence of stones difficult to determinate the water content. An alternative is the use of pedotransfer functions (PTFs), as models to predict these properties from readily available data. The present work shows a comparison of different widely used PTFs to estimate water content at-33 kPa (WR_-33kPa) in high stoniness soils. The work was carried out in the Caramacate River, an area of high interest because the frequent landslides worsen the quality of drinking water. The performance of all evaluated PTFs was compared with a PTF generated for the study area. Results showed that the Urach’s PTF presented the best performance in relation to the others and could be used to estimate WR_-33kPa in soils of Caramacate River basin. The calculated PTFs had a R² of 0.65. This was slightly higher than the R² of the Urach’s PTF. The inclusion of the rock fragment volume could have the better results. The weak performance of the other PTFs could be related to the fact that the mountain soils of the basin are rich in 2:1 clay and high stoniness, which were not used as independent variables for PTFs to estimate the WR_-33kPa.     

Slurry wall containment performance: monitoring and modeling of unsaturated and saturated flow

A specific 2-year program to monitor and test both the vadose zone and the saturated zone, coupled with a numerical analysis, was performed to evaluate the overall performance of slurry wall systems for containment of contaminated areas. Despite local physical confinement (slurry walls keyed into an average 2-m-thick aquitard), for at least two decades, high concentrations of chlorinated solvents (up to 110 mg l^− 1) have been observed in aquifers that supply drinking water close to the city of Milan (Italy). Results of monitoring and in situ tests have been used to perform an unsaturated-saturated numerical model. These results yielded the necessary quantitative information to be used both for the determination of the hydraulic properties of the different media in the area and for the calibration and validation of the numerical model. Backfill material in the shallower part of the investigated aquifer dramatically affects the natural recharge of the encapsulated area. A transient simulation from wet to drought periods highlights a change in the ratio between leakages from lateral barriers that support a specific scenario of water loss through the containment system. The combination of monitoring and modelling allows a reliable estimate of the overall performance of the physical confinement to be made without using any invasive techniques on slurry wall.     

Conjunctive Vadose and Saturated Zone Monitoring for Subsurface Contamination

A comprehensive subsurface monitoring program should include contaminant detectors in both the vadose and saturated zones. Vadose zone detectors can provide an early warning of an impending groundwater contamination problem, and also yield information relevant to placing groundwater monitoring wells. Moisture probes, gas monitoring wells, and pore-liquid samplers deployed in the vadose zone complement groundwater detection wells. The objective(s) of a monitoring program, spatial-scales, and hydrogeology are important considerations for designing subsurface monitoring networks. Often, these networks are used to detect potential releases or characterize existing contamination beneath land-based waste storage facilities. A case study in Santa Barbara, California, U.S.A., illustrates the utility of vadose zone monitoring in characterizing a gasoline contamination problem and guiding the placement of groundwater monitoring wells.     

Groundwater vulnerability assessment using DRASTIC and Pesticide DRASTIC models in intense agriculture area of the Gangetic plains,India

Delineating areas susceptible to contamination from anthropogenic sources form an important component of sustainable management of groundwater resources. The present research aims at estimating vulnerability of groundwater by application of DRASTIC and Pesticide DRASTIC models in the southern part of the Gangetic plains in the state of Bihar. The DRASTIC and Pesticide DRASTIC models have considered seven parameters viz. depth to water level, net recharge, aquifer material, soil material, topography, impact of vadose zone and hydraulic conductivity. A third model, Pesticide DRASTIC LU has been adopted by adding land use as an additional parameter, to assess its impact on vulnerability zonation. The DRASTIC model indicated two vulnerable categories, moderate and high, while the Pesticide DRASTIC model revealed moderate, high and very high vulnerable categories. Out of the parameters used, depth to water level affected the vulnerability most. The parameter caused least impact was topography in DRASTIC, while in case of Pesticide DRASTIC and Pesticide DRASTIC LU models, the parameter was hydraulic conductivity. A linear regression between groundwater NO₃ concentrations and the vulnerability zonation revealed better correlation for Pesticide DRASTIC model, emphasising the effectiveness of the model in assessing groundwater vulnerability in the study region. Considering all three models, the most vulnerable areas were found to be concentrated mainly in two zones, (i) in the south-western part along Ekangarsarai-Islampur patch and (ii) around Biharsharif-Nagarnausa area in the central part. Both zones were characterised by intensive vegetable cultivation with urban areas in between.     

A small subsurface ion mobility spectrometer sensor for detecting environmental soil-gas contaminants

A small subsurface ion mobility spectrometer (SS-IMS) was constructed and tested with several environmental contaminants to determine its potential for monitoring gaseous volatile organic compounds in the vadose zone. Trichloroethylene (TCE) and tetrachloroethylene (PCE) were detected and separated in IMS for the first time. Detection limits as low as 1 part per billion volume-to-volume (ppb(v)) were observed. Reduced mobility (K(0)) values were reported for 11 environmental contaminants. These data demonstrated the potential of ion mobility spectrometry as a viable technology for detecting and separating environmental soil-gas contaminants in the field, which may lead to a practical and simple approach for long-term monitoring of contaminated soils.     

Comparison of Noniterative Algorithms Based on Different Forms of Richards’ Equation

Through linearizing an implicit differencing scheme, several noniterative numerical solutions of Richards’ equation in different forms are derived here. Paniconi et al. (Water Resources Research, 27(6), 1147–1163, 1991) have developed a first-order accurate linearization of the head-based Richards’ equation (RE) and a second-order accurate linearization of the implicit-factored head-based RE. Considering other forms of RE, we propose a second-order accurate linearization of the moisture-based RE and a second-order accurate linearization of the mixed form RE combined with the primary variable switching technique. Extensive comparisons between the noniterative solutions are conducted through three numerical experiments. Their accuracies, efficiencies, and mass balance behaviors are analyzed. The results indicate that the first-order accurate scheme is not efficient compared to iterative models. The noniterative schemes of head-based RE suffer from the mass imbalance problem without iteration. The linearized moisture-based RE can obtain mass conservative, accurate results effectively, while it may confront numerical problems when the soil approaches saturation. Among these noniterative schemes, the linearized mixed form RE combined with the primary variable switching technique is superior in terms of accuracy, mass balance, and efficiency compared to traditional iterative methods.     

The contribution of drinking water to exposure to toxic substances in Canada

Factors influencing the contribution made by drinking water to an individual's exposure to chemical contaminants are reviewed. Deficiencies inherent in simple computational procedures (such as those which rely on the impact of average values to estimate the relative importance of air, food and water and other vehicles by which man is exposed to contaminants) are examined. An alternative approach is described in which a mathematical model incorporating a probabilistic approach is used to predict the distribution of the total exposure of a population. Values of the means and standard deviations for various quantities including contaminant concentrations and food and drinking water intake are used as inputs to the model. The model enables estimations to be made of the proportion of individuals whose exposure exceeds a certain critical value and the relative contribution each exposure pathway makes to the overall distribution of exposure; its versatility is illustrated utilizing data available for lead. The paper also includes a critical assessment of the value of various techniques employed for monitoring drinking water supplies in providing data suitable for exposure assessment and summarizes conclusions from a recent survey of Canadian drinking water consumption habits.     

Nonlinear Growth Models for Modelling Time Series of Groundwater Nitrate Concentrations

In this paper, a novel approach of modelling time series of nitrate concentrations in drinking water by nonlinear growth functions is proposed. An almost constant increase in the average values of nitrate concentrations occurred at the Vinokov??ak wellfield in the county of Vara?din, Croatia, in the period between 1998 and 2013. Our hypothesis was that the time series would be well adjusted to the nonlinear growth function with asymptotic properties after smoothing performed by the moving average method. We used a general growth model which does not have asymptotic properties and the logistic, Gompertz and Richards functions which do have asymptotic properties. Last three growth functions were modified based on the knowledge of a constant presence of basic nitrate concentrations in the drinking water before growth. The fit of growth curves to experimental data was assessed using R ² and Aikake’s information criterion. The modified growth functions gave the best fit to the smoothed time series of nitrate concentrations with R ² ranging from 0.9960 to 0.9986.