Mapping of bioavailable strontium isotope ratios in France for archaeological provenance studies

Strontium isotope ratios (87Sr/86Sr) of archaeological samples (teeth and bones) can be used to track mobility and migration across geologically distinct landscapes. However, traditional interpolation algorithms and classification approaches used to generate Sr isoscapes are often limited in predicting multiscale 87Sr/86Sr patterning. Here we investigate the suitability of plant samples and soil leachates from the IRHUM database (www. irhumdatabase.com) to create a bioavailable 87Sr/86Sr map using a novel geostatistical framework. First, we generated an 87Sr/86Sr map by classifying 87Sr/86Sr values into five geologically representative isotope groups using cluster analysis. The isotope groups were then used as a covariate in kriging to integrate prior geological knowledge of Sr cycling with the information contained in the bioavailable dataset and enhance 87Sr/86Sr predictions. Our approach couples the strengths of classification and geostatistical methods to generate more accurate 87Sr/86Sr predictions (Root Mean Squared Error=0.0029) with an estimate of spatial uncertainty based on lithology and sample density. This bioavailable Sr isoscape is applicable for provenance studies in France, and the method is transferable to other areas with high sampling density. While our method is a step forward in generating accurate 87Sr/86Sr isoscapes, the remaining uncertainty also demonstrates that finemodelling of 87Sr/86Sr variability is challenging and requires more than geological maps for accurately predicting 87Sr/86Sr variations across the landscape. Future efforts should focus on increasing sampling density and developing predictive models to further quantify and predict the processes that lead to 87Sr/86Sr variability.

Geohydraulic and vulnerability assessment of tropically weathered and fractured gneissic aquifers using combined electrical resistivity and geostatistical methods

Sustainable potable groundwater supplied by aquifers depends on the protective capacity of the strata overlying the aquifer zones and their thicknesses, as well as the nature of the aquifers and the conduit systems. The poor overburden development of the Araromi area of Akungba-Akoko, in the crystalline basement of southwestern Nigeria, restricts most aquifers to shallow depths. Hence, there is a need to investigate the groundwater quality of the tropically weathered and fractured gneissic aquifers in the area. A combined electrical resistivity tomography (ERT) and Schlumberger vertical electrical sounding (VES) technique were employed to assess the groundwater-yielding potential and vulnerability of the aquifer units. The measured geoelectric parameters (i.e., resistivity and thickness values) at the respective VES surveyed stations were used to compute the geohydraulic parameters, such as aquifer resistivity (\({\rho }_{o}\)), hydraulic conductivity (K), transmissivity (T), porosity (\(\phi\)), permeability (\({\Psi }\)), hydraulic resistance (\({\text{K}}_{R}\)), and longitudinal conductance (S). In addition, regression analysis was employed to establish the correlations between the K and other geohydraulic parameters to achieve the objectives of this study. The subsurface lithostratigraphic units of the studied site were delineated as the motley topsoil, weathered layers, partially weathered/fractured bedrock units, and the fresh bedrock, based on the ERT and the A, H, AK, HA, and KQ curve models. The K model regression-assisted analysis showed that the \({\rho }_{o}\), T, \(\phi\), \({\Psi }\), and S contributed about 81.7%, 3.31%. 96.6%, 100%, and 11.63%, respectively, of the determined K values for the study area. The results, except T and S, have strong high positive correlations with the K of the aquifer units; hence, accounted for the recorded high percentages. The aquifer units in the area were classified as low to moderate groundwater-yielding potential due to the thin overburden, with an average depth of <4 m. However, the deep-weathered and fractured aquifer zones with depths ranging from about 39–55 m could supply high groundwater yield for sustainable exploitation. The estimated S values, i.e., 0.0226–0.1926 mho, for aquifer protective capacity ratings rated the aquifer units in the area as poor/weak to moderately high with extremely high to high aquifer vulnerability index, based on the estimated low Log \({\text{K}}_{R}\) of about 0.01–1.77 years. Hence, intended wells/boreholes in the study area and its environs, as well as any environments with similar geohydraulic and vulnerability characteristics, should be properly constructed to adequately prevent surface and subsurface infiltrating contaminants.

Maplaria: a user friendly web-application for spatio-temporal malaria prevalence mapping

Background Model-based geostatistical (MBG) methods have been extensively used to map malaria risk using community survey data in low-resource settings where disease registries are incomplete or non-existent. However, the wider adoption of MBG methods by national control programmes to inform health policy decisions is hindered by the lack of advanced statistical expertise and suitable computational equipment. Here, Maplaria, an interactive, user-friendly web-application that allows users to upload their own malaria prevalence data and carry out geostatistical prediction of annual malaria prevalence at any desired spatial scale, is introduced. Methods In the design of the Maplaria web application, two main criteria were considered: the application should be able to classify subnational divisions into the most likely endemicity levels; the web application should allow only minimal input from the user in the set-up of the geostatistical inference process. To achieve this, the process of fitting and validating the geostatistical models is carried out by statistical experts using publicly available malaria survey data from the Harvard database. The stage of geostatistical prediction is entirely user-driven and allows the user to upload malaria data, as well as vector data that define the administrative boundaries for the generation of spatially aggregated inferences. Results The process of data uploading and processing is split into a series of steps spread across screens through the progressive disclosure technique that prevents the user being immediately overwhelmed by the length of the form. Each of these is illustrated using a data set from the Malaria Indicator carried out in Tanzania in 2017 as an example. Conclusions Maplaria application provides a user-friendly solution to the problem making geostatistical methods more accessible to users that have not undertaken formal training in statistics. The application is a useful tool that can be used to foster ownership, among policy makers, of disease risk maps and promote better use of data for decision-making in low resource settings.

Geohydraulic and vulnerability assessment of tropically weathered and fractured gneissic aquifers using combined electrical resistivity and geostatistical methods

Sustainable potable groundwater supplied by aquifers depends on the protective capacity of the strata overlying the aquifer zones and their thicknesses, as well as the nature of the aquifers and the conduit systems. The poor overburden development of the Araromi area of Akungba-Akoko, in the crystalline basement of southwestern Nigeria, restricts most aquifers to shallow depths. Hence, there is a need to investigate the groundwater quality of the tropically weathered and fractured gneissic aquifers in the area. A combined electrical resistivity tomography (ERT) and Schlumberger vertical electrical sounding (VES) technique were employed to assess the groundwater-yielding potential and vulnerability of the aquifer units. The measured geoelectric parameters (i.e., resistivity and thickness values) at the respective VES surveyed stations were used to compute the geohydraulic parameters, such as aquifer resistivity (\({\rho }_{o}\)), hydraulic conductivity (K), transmissivity (T), porosity (\(\phi\)), permeability (\({\Psi }\)), hydraulic resistance (\({\text{K}}_{R}\)), and longitudinal conductance (S). In addition, regression analysis was employed to establish the correlations between the K and other geohydraulic parameters to achieve the objectives of this study. The subsurface lithostratigraphic units of the studied site were delineated as the motley topsoil, weathered layers, partially weathered/fractured bedrock units, and the fresh bedrock, based on the ERT and the A, H, AK, HA, and KQ curve models. The K model regression-assisted analysis showed that the \({\rho }_{o}\), T, \(\phi\), \({\Psi }\), and S contributed about 81.7%, 3.31%. 96.6%, 100%, and 11.63%, respectively, of the determined K values for the study area. The results, except T and S, have strong high positive correlations with the K of the aquifer units; hence, accounted for the recorded high percentages. The aquifer units in the area were classified as low to moderate groundwater-yielding potential due to the thin overburden, with an average depth of <4 m. However, the deep-weathered and fractured aquifer zones with depths ranging from about 39–55 m could supply high groundwater yield for sustainable exploitation. The estimated S values, i.e., 0.0226–0.1926 mho, for aquifer protective capacity ratings rated the aquifer units in the area as poor/weak to moderately high with extremely high to high aquifer vulnerability index, based on the estimated low Log \({\text{K}}_{R}\) of about 0.01–1.77 years. Hence, intended wells/boreholes in the study area and its environs, as well as any environments with similar geohydraulic and vulnerability characteristics, should be properly constructed to adequately prevent surface and subsurface infiltrating contaminants.

The Application of Semi Variogram and Ordinary Kriging in Determining the Cohesion and Clay Percentage Distribution in Hilly Area of Sabah, Malaysia

Ordinary Kriging (OK) is one of the geostatistical methods, which were used in the variation types of mapping, which related to the soil. Compliment by semi variogram models, OK has become one of the most sought out method for the digital mapping, which applied Geographical Information System (GIS) as a main approach. Four semi variogram models, which are spherical, exponential, circular and gaussian would be applied to determine the best model for the mapping purposes, with Root-Mean-Squared-Error (RMSE) as a performance indicator. The value of the cohesion and clay percentage will be based according to the related depth. Each semi variogram model will be applied to determine the best model for each depth, whether it is cohesion or clay percentage, and producing a map, as a result. This mapping would be an alternative to the geological mapping, whereby it would show the range of the cohesion and clay percentage values rather than soil types.