B.P. Marchant

Generic Issues on Broad-Scale Soil Monitoring Schemes： A Review

Numerous scientific challenges arise when designing a soil monitoring network (SMN), especially when assessing large areas and several properties that are driven by numerous controlling factors of various origins and scales. Different broad approaches to the establishment of SMNs are distinguished. It is essential to establish an adequate sampling protocol that can be applied rigorously at each sampling location and time. We make recommendations regarding the within-site sampling of soil. Different statistical methods should be associated with the different types of sampling design. We review new statistical methods that account for different sources of uncertainty. Except for those parameters for which a consensus exists, the question of testing method harmonisation remains a very difficult issue. The establishment of benchmark sites devoted to harmonisation and inter-calibration is advocated as a technical solution. However, to our present knowledge, no study has addressed crucial scientific issues such as how many calibration sites are necessary and how to locate them.

In-situ tryptophan-like fluorescence: A real-time indicator of faecal contamination in drinking water supplies.

Enteric pathogens are typically inferred from the presence of surrogate indicator organisms such as thermotolerant (faecal) coliforms (TTCs). The analysis of TTCs requires time-consuming incubation in suitable laboratories, which can limit sampling resolution, particularly during critical pollution events. Here, we demonstrate the use of in-situ fluorimeters targeting tryptophan-like compounds as a rapid, reagentless indicator of TTCs in groundwater-derived potable water supplies in Africa. A range of other common indicators of TTCs were also determined including nitrate, turbidity, and sanitary risk survey scores. Sampling was conducted during both the dry and wet seasons to investigate seasonality. Tryptophan-like fluorescence was the most effective predictor of both presence/absence and number of TTCs during both seasons. Seasonal changes in tryptophan-like fluorescence in deeper supplies suggest it is transported more efficiently through the aquifer than TTCs. Moreover, the perennial elevated concentrations in some wells suggest it is more resilient than TTCs in groundwater. Therefore tryptophan-like fluorescence could also be a better indicator of some smaller, more easily transported, and long-lived, pathogenic enteric viruses. These sensors have the potential to be included in real-time pollution alert systems for drinking water supplies throughout the world, as well as for mapping enteric pathogen risks in developing regions.

Which persistent organic pollutants can we map in soil using a large spacing systematic soil monitoring design? A case study in Northern France.

Persistent organic pollutants (POPs) impact upon human and animal health and the wider environment. It is important to determine where POPs are found and the spatial pattern of POP variation. The concentrations of 90 molecules which are members of four families of POPs and two families of herbicides were measured within a region of Northern France as part of the French National Soil Monitoring Network (RMQS: Réseau de Mesures de la Qualité des Sols). We also gather information on five covariates (elevation, soil organic carbon content, road density, land cover and population density) which might influence POP concentrations. The study region contains 105 RMQS observation sites arranged on a regular square grid with spacing of 16 km. The observations include hot-spots at sites of POP application, smaller concentrations where POPs have been dispersed and observations less than the limit of quantification (LOQ) where the soil has not been impacted by POPs. Fifty nine of the molecules were detected at less than 50 sites and hence the data were unsuitable for spatial analyses. We represent the variation of the remaining 31 molecules by various linear mixed models which can include fixed effects (i.e. linear relationships between the molecule concentrations and covariates) and spatially correlated random effects. The best model for each molecule is selected by the Akaike Information Criterion. For nine of the molecules, spatial correlation is evident and hence they can potentially be mapped. For four of these molecules, the spatial correlation cannot be wholly explained by fixed effects. It appears that these molecules have been transported away from their application sites and are now dispersed across the study region with the largest concentrations found in a heavily populated depression. More complicated statistical models and sampling designs are required to explain the distribution of the less dispersed molecules.

Spatial distribution of Lindane concentration in topsoil across France.

Lindane [γ-hexachlorocyclohexane (γ-HCH)] is an organochlorine pesticide with toxic effects on humans. It is bioaccumulative and can remain in soils for long periods, and although its use for crop spraying was banned in France in 1998, it is possible that residues from before this time remain in the soil. The RMQS soil monitoring network consists of soil samples from 2200 sites on a 16 km regular grid across France, collected between 2002 and 2009. We use 726 measurements of the Lindane concentration in these samples to (i) investigate the main explanatory factors for its spatial distribution across France, and (ii) map this distribution. Geostatistics provides an appropriate framework to analyze our spatial dataset, though two issues regarding the data are worth special consideration: first, the harmonization of two subsets of the data (which were analyzed using different measurement processes), and second, the large proportion of data from one of these subsets that fell below a limit of quantification. We deal with these issues using recent methodological developments in geostatistics. Results demonstrate the importance of land use and rainfall for explaining part of the variability of Lindane across France: land use due to the past direct input of Lindane on cropland and its subsequent persistence in the soil, and rainfall due to the re-deposition of volatilized Lindane. Maps show the concentrations to be generally largest in the north and northwest of France, areas of more intensive agricultural land. We also compare levels to some contamination thresholds taken from the literature, and present maps showing the probability of Lindane concentrations exceeding these thresholds across France. These maps could be used as guidelines for deciding which areas require further sampling before some possible remediation strategy could be applied.

Estimating change in soil organic carbon using legacy data as the baseline: issues, approaches and lessons to learn

The importance of soil organic carbon (SOC) in maintaining soil health is well understood. However, there is growing interest in studying SOC with an emphasis on quantifying its changes in space and time. This is because of the potential for soil to be used to sequester atmospheric C. There are many issues which make this difficult, for example shortcomings in sampling designs, and differences in vertical and lateral sampling supports between surveys, particularly if legacy data are used as the baseline survey. In this study, we systematically work through these issues and show how a protocol can be developed using design-based and model-based statistical approaches to estimate changes in SOC in space and time at different spatial supports. We demonstrate this protocol in a small subcatchment in the upper Namoi valley for estimating the change in SOC over time, whereby the baseline dataset was collected during 1999–2001 and is compared with a dataset from November 2010. The results from both design-based and model-based approaches revealed a drop in SOC across the catchment between the two survey periods. A 0.26% drop in SOC was reported globally across the catchment. Nevertheless, the change in SOC reported for both approaches was not statistically significant.

Exploring the spatial variation in the fertilizer-nitrogen requirement of wheat within fields

The fertilizer-nitrogen (N) requirement for wheat grown in the UK varies from field to field. Differences in the soil type, climate and cropping history result in differences in (i) the crops’ demands for N, (ii) the supply of N from the soil (SNS) and (iii) the recovery of the fertilizer by the crops. These three components generally form the basis of systems for N recommendation. Three field experiments were set out to investigate the variation of the N requirement for wheat within fields and to explore the importance of variation in the crops’ demands for N, SNS and fertilizer recovery in explaining the differences in the economic optima for N. The N optima were found to vary by >100 kg N/ha at two of the sites. At the other site, the yield response to N was small. Yields at the optimum rate of N varied spatially by c. 4 t/ha at each site. Soil N supply, which was estimated by the unfertilized crops’ harvested N, varied spatially by 120, 75 and 60 kg/ha in the three experiments. Fertilizer recovery varied spatially from 30% to >100% at each of the sites. There were clear relationships between the SNS and the N optima at all the three sites. The expected relationship between the crops demand for N and N optima was evident at only one of the three sites. There was no consistent relationship between the N recovery and the N optima. A consistent relationship emerged, however, between the optimal yield and SNS; areas with a greater yield potential tending to also supply more N from the soil. This moderated the expected effect of the SNS and the crops demand for N on the N optima.

A survey of topsoil arsenic and mercury concentrations across France

Even at low concentrations, the presence of arsenic and mercury in soils can lead to ecological and health impacts. The recent European-wide LUCAS Topsoil Survey found that the arsenic concentration of a large proportion of French soils exceeded a threshold which indicated that further investigation was required. A much smaller proportion of soils exceeded the corresponding threshold for mercury but the impacts of mining and industrial activities on mercury concentrations are not well understood. We use samples from the French national soil monitoring network (RMQS: Réseau de Mesures de la Qualité des Sols) to explore the variation of topsoil arsenic and mercury concentrations across mainland France at a finer spatial resolution than was reported by LUCAS Topsoil. We use geostatistical methods to map the expected concentrations of these elements in the topsoil and the probabilities that the legislative thresholds are exceeded. We find that, with the exception of some areas where the geogenic concentrations and soil adsorption capacities are very low, arsenic concentrations are generally larger than the threshold which indicates that further assessment of the area is required. The lower of two other guideline values indicating risks to ecology or health is exceeded in fewer than 5% of RMQS samples. These exceedances occur in localised hot-spots primarily associated with mining and mineralization. The probabilities of mercury concentrations exceeding the further assessment threshold value are everywhere less than 0.01 and none of the RMQS samples exceed either of the ecological and health risk thresholds. However, there are some regions with elevated concentrations which can be related to volcanic material, natural mineralizations and industrial contamination. These regions are more diffuse than the hot-spots of arsenic reflecting the greater volatility of mercury and therefore the greater ease with which it can be transported and redeposited. The maps provide a baseline against which future phases of the RMQS can be compared and highlight regions where the threat of soil contamination and its impacts should be more closely monitored.

On Soil Carbon Monitoring Networks

The design of a Soil Monitoring Network (SMN) poses numerous scientific challenges, especially for the assessment of national or continental areas. The task is particularly challenging because soil carbon content and stocks are driven by controlling factors of disparate origins and scales. Various approaches to the establishment of SMNs are reviewed here. Frameworks for soil monitoring exist in numerous countries, especially in Europe. Although some countries work using standard monitoring methodologies and coverage, there is considerable variation in approaches to the monitoring of soil carbon even within a country. In addition to achieving harmonization, there are generic issues which must be addressed when SMNs are established and operated: the SMN should be effective for different soils, and it must enable the detection of change in soil carbon at relevant spatial and temporal scales with adequate precision and statistical power. We present examples which address these issues and summarize previous reviews on this topic. It is essential to establish an adequate sampling protocol which can be applied at each sampling location and time. The design must address the questions that the user of data has and provide information with accuracy and precision at the spatial and temporal scales that match the users’ needs. Furthermore, the design must match the methods of analysis so that statistical assumptions can be justified. At the global scale, the question of harmonizing sampling and analytical methods is difficult. Here, we propose the establishment of benchmark sites devoted to harmonization and inter-calibration. We present a case study from France which addresses scientific issues such as how many calibration sites are necessary and how they should be selected.

Analyzing the spatial distribution of PCB concentrations in soils using below-quantification limit data

Polychlorinated biphenyls (PCBs) are highly toxic environmental pollutants that can accumulate in soils. We consider the problem of explaining and mapping the spatial distribution of PCBs using a spatial data set of 105 PCB-187 measurements from a region in the north of France. A large proportion of our data (35%) fell below a quantification limit (QL), meaning that their concentrations could not be determined to a sufficient degree of precision. Where a measurement fell below this QL, the inequality information was all that we were presented with. In this work, we demonstrate a full geostatistical analysis-bringing together the various components, including model selection, cross-validation, and mapping-using censored data to represent the uncertainty that results from below-QL observations. We implement a Monte Carlo maximum likelihood approach to estimate the geostatistical model parameters. To select the best set of explanatory variables for explaining and mapping the spatial distribution of PCB-187 concentrations, we apply the Akaike Information Criterion (AIC). The AIC provides a trade-off between the goodness-of-fit of a model and its complexity (i.e., the number of covariates). We then use the best set of explanatory variables to help interpolate the measurements via a Bayesian approach, and produce maps of the predictions. We calculate predictions of the probability of exceeding a concentration threshold, above which the land could be considered as contaminated. The work demonstrates some differences between approaches based on censored data and on imputed data (in which the below-QL data are replaced by a value of half of the QL). Cross-validation results demonstrate better predictions based on the censored data approach, and we should therefore have confidence in the information provided by predictions from this method.

Improved understanding of spatiotemporal controls on regional scale groundwater flooding using hydrograph analysis and impulse response functions

Controls on the spatiotemporal extent of groundwater flooding are poorly understood, despite the long duration of groundwater flood events and distinct social and economic impacts. We developed a novel approach using statistical analysis of groundwater level hydrographs and impulse response functions (IRFs) and applied it to the 2013/14 Chalk groundwater flooding in the English Lowlands. We proposed a standardised index of groundwater flooding which we calculated for monthly groundwater levels for 26 boreholes in the Chalk. We grouped these standardised series using k-means cluster analysis and cross-correlated the cluster centroids with the Standardised Precipitation Index (SPI) accumulated over time intervals between 1 and 60 months. This analysis reveals two spatially coherent groups of standardised hydrographs which responded to precipitation over different timescales. We estimated IRF models of the groundwater level response to effective precipitation for three boreholes in each group. The IRF models corroborate the SPI analysis showing different response functions between the groups. We applied identical effective precipitation inputs to each of the IRF models and observed differences between the hydrographs from each group. It is suggested this is due to the hydrogeological properties of the Chalk and of overlying relatively low permeability superficial deposits (recent unconsolidated sediments overlying the bedrock, such as clays and tills), which are extensive over one of the groups. The overarching controls on groundwater flood response are concluded to be a complex combination of antecedent conditions, rainfall and catchment hydrogeological properties. These controls should be taken into consideration when anticipating and managing future groundwater flood events. The approach presented is generic and parsimonious and can be easily applied where sufficient groundwater level and rainfall data are available.