Assessing spatial uncertainty in mapping soil erodibility factor using geostatistical stochastic simulation

Soil erosion is one of most widespread process of degradation. The erodibility of a soil is a measure of its susceptibility to erosion and depends on many soil properties. Soil erodibility factor varies greatly over space and is commonly estimated using the revised universal soil loss equation. Neglecting information about estimation uncertainty may lead to improper decision-making. One geostatistical approach to spatial analysis is sequential Gaussian simulation, which draws alternative, equally probable, joint realizations of a regionalised variable. Differences between the realizations provide a measure of spatial uncertainty and allow us to carry out an error analysis. The objective of this paper was to assess the model output error of soil erodibility resulting from the uncertainties in the input attributes (texture and organic matter). The study area covers about 30 km² (Calabria, southern Italy). Topsoil samples were collected at 175 locations within the study area in 2006 and the main chemical and physical soil properties were determined. As soil textural size fractions are compositional data, the additive-logratio (alr) transformation was used to remove the non-negativity and constant-sum constraints on compositional variables. A Monte Carlo analysis was performed, which consisted of drawing a large number (500) of identically distributed input attributes from the multivariable joint probability distribution function. We incorporated spatial cross-correlation information through joint sequential Gaussian simulation, because model inputs were spatially correlated. The erodibility model was then estimated for each set of the 500 joint realisations of the input variables and the ensemble of the model outputs was used to infer the erodibility probability distribution function. This approach has also allowed for delineating the areas characterised by greater uncertainty and then to suggest efficient supplementary sampling strategies for further improving the precision of K value predictions.     

A guideline for the evaluation of the soil radon potential based on geogenic and anthropogenic parameters

Following a brief review about radon (²²²Rn) in soils, this study gives a compilation and evaluation of important parameters of the soil ²²²Rn potential. Because investigations of the potential are usually limited to rural areas, anthropogenic or urban effects have not attracted much attention so far. Measurements within the densely populated Ruhr district (Germany) present some new insights into geogenic and anthropogenic parameters on the soil ²²²Rn potential. According to their importance, seven parameters were strung in aranking system, which can be applied in both rural and urban areas: made grounds, geology, relief, vegetation cover, tectonics, soil sealing, traffic vibrations. While the first four parameters control the soil ²²²Rn potential on a more regional scale, the last three can modify it locally. Furthermore, an evaluation of the potential within a ten-point-system is proposed. The advantage of the system lies in the possibility to estimate the soil ²²²Rn potential of any site on a local scale. Common classifications and rankings, based on insufficiently scaled maps, can be included in the proposed system.     

Spatial distribution mapping and radiological hazard assessment of groundwater and soil gas radon in Ekiti State,Southwest Nigeria

Groundwater constitutes the major source of utility water in Ekiti State with the majority of the population depending on groundwater for drinking and other household uses. Soil in the area is commonly used as a component of building materials, which may produce radon in the indoor environment. Excessive concentrations of radon in water and soil can cause radiological health risks to human as witnessed by the increased cases of lung cancer among non-smokers in Nigeria, which may be traceable to the ingestion and inhalation ²²²Rn in drinking water and indoor air. In the present study, comparative in situ measurements of radon in groundwater and soil gas were carried out at one hundred selected locations across the Ekiti State in southwest Nigeria, using a RAD7 radon detector to generate a radon distribution map and to estimate radiation hazards due to radon. The concentrations of radon in groundwater ranged from 0.9 to 472 Bq L^?1 with a mean of 34.7?±?4.4 Bq L^?1, while those of soil gas ranged from 0.1 to 315 kBq L^?1 with a mean of 38.9?±?1.4 kBq L^?1. The total annual effective dose due to inhalation and ingestion of radon in groundwater amounted to 94.7 µSv year^?1, which is lower than the reference dose of 100 µSv year^?1 recommended by the World Health Organization (WHO). The radon map generated for groundwater and soil gas identified three distinct areas with radon levels ranging from low to high. The results of this study show that some locations (Emure, Gbonyin, Ijero and Ikole) show mean total annual effective doses which are higher than the recommended limit. It can then be inferred that the groundwater samples pose significant radiological hazards to the population and that the noticed increase in lung cancer cases may be attributed to the consumption of groundwater in the area.     

Multi-parametric approach to the analysis of soil radon gas for its validation as geoindicator in two sites of the Phlegrean Fields caldera (Italy)

Radon is considered one of the short- and immediate-term earthquake precursors by International Association of Seismology and Physics of the Earth’s Interior. For this reason, the accurate and reliable measurement of its specific activity in soil gas is mandatory. Since its presence is influenced by many environmental factors, in order to eliminate this influence on the radon activity measurement a multi-parametric and multi-site analysis is necessary. Following this approach, a continuous radon monitoring was carried out in two sites of the Phlegrean Fields caldera (Campania, Italy) using the RaMonA system, which also allows for the measurement of temperature, relative humidity and pressure. In particular, the dependence of measured radon specific activity on the meteorological conditions was studied using the multiple linear regression method. The analysis was implemented also by testing data averages on different timescales. In this paper, the results of a preliminary analysis performed on data collected throughout 2012 are presented; the outcomes obtained allow to emphasize site-specific behavior and to discriminate apparent radon “anomalies” of climatic origin from those tied to the phenomena occurring in the earth’s crust. The method employed showed its usefulness by removing the effects of meteorological conditions and thus to better identify the possible radon anomalies caused by seismo-volcanic activity. The peculiarities of the different sites and some correlations with earthquakes are discussed.     

A multisource approach for coastal mapping purposes: Limeni bay,Mani and surrounding area,southern Greece

A multipurpose engineering geological map of a natural heritage site including inland and offshore areas has been compiled to provide information on many aspects for land use optimization, sustainable development and environmental protection. The mapping approach was based on data provided by conventional onland field works, marine remote sensing survey and aerial photo interpretation. These data sources were integrated into a GIS platform allowing reliable mapping solutions. The geological formations encountered were grouped into individual geotechnical units according to uniformity in lithological character, while the seabed sub-bottom structure was also obtained through several seafloor thematic map compilation. Shoreline variability and evolution for a long time period (1945–2008) were also investigated and mapped. The synergistic use of the results deducted from those disciplinary surveys is finally presented in a single engineering geological map covering the onshore and offshore area.     

Catchment scale geostatistical simulation and uncertainty of soil erodibility using sequential Gaussian simulation

Soil erodibility (K) affects sediment delivery to streams and needs to be appropriately quantified and interpolated as a fundamental geographic variable for implementing suitable catchment management and conservation practices. The spatial distribution of K for erosion modelling at non-sampling grid locations has traditionally been estimated using interpolation algorithms such as kriging which do not adequately represent the uncertainty of estimates. These methods cause smoothing effects through overestimating the low values and underestimating the large values. In this study observed values were used to implement a sequential Gaussian simulation (SGS) procedure to evaluate the certainty of modelled data. Soil erodibility values were computed using 41 soil samples taken from the top 10 cm soil layer regularly distributed across four catchments, 367–770 ha in area, within Kangaroo River State forest, New South Wales (NSW). One hundred realisations were applied in the simulation process to provide spatial uncertainty and error estimates of soil erodibility. The results indicated that values simulated by the SGS algorithm produced similar K values for the neighbouring cells. At the pixel level, the SGS approach generated a reliable estimation of soil erodibility in most areas. Spatial variation of the K factor in this study was strongly related to soil landscape differences across the catchments; within catchments slope gradient did not have a substantial impact on the numerical values of the K factor using pixel-by-pixel comparisons of raster grid maps.     

Correlation of soil radon and uranium with indoor radon in the Albuquerque,New Mexico area

High indoor radon in approximately 30 percent of private dwellings in the Albuquerque, New Mexico area has been reported previously. The present study explains the areas of high indoor radon as a function of different soil and/or bedrock in the area. Soils were sampled during summer and winter periods using alpha track radon detectors. The values range from 40 to 890 pCi/I air at a depth of 38 cm. The gross mean average is 360 pCi/I for the area for summer readings and 200 pCi/I for winter readings; both values are well over the average U.S. soil radon values of approximately 100 pCi/I. Analyses of soil uranium show a range in values of 1–6 ppm, with a mean of 3.1 ppm. Thorium values range from 3.3 to 28.8 ppm, and Th/U ratios range from 2.9 to 4.6.These values for U, Th, and Th/U suggest that soil U and Th are close to the values reported for the Sandia granite, the source of most of the pediment on which Albuquerque is built. Soil infiltration rates range from ~6 × 10^–4 to 4.5 × 10^–3 cm/sec for the samples, and soil moisture content ranges from 1.4 to 7.2 percent. A fair correlation of summer soil radon with infiltration rate is noted. Correlation of soil radon with moisture content and/or with percent silt, silt + clay, clay size fraction material is not established by this study. Soil radon values do correlate with regions in the Albuquerque area where high indoor radon is common. A better correlation of high indoor radon values with soils developed immediately over bedrock is observed. Furthermore, all values of average soil and indoor radon increase significantly with proximity of the stations to the Sandia Mountains. Soil uranium also shows this trend. The data argue that regions of potentially high radon can thus be identified.     

Relationship between radon concentrations in indoor air and in soil gas

In the Ljubljana region, 53 schools were selected for measurements of radon concentrations in soil gas close to a school building, and indoor radon concentrations in one of the ground-floor classrooms of each building. The aim was to establish a relationship between radon concentrations in indoor air and in soil gas from the ground on which the building is situated. Soil gas radon concentrations between 2 and 14 kBqm^-3 were found. Indoor radon concentrations ranged from 20 to 1,440 Bqm^-3, with seven values exceeding 200 Bqm^-3. It is concluded that good quality of the construction elements ensure low indoor radon concentration, regardless of high soil gas radon level.     

Helium in soil and overburden gas as an exploration pathfinder — an assessment

Orientation surveys were conducted over five deposits to test the potential of determining helium in overburden gas as a pathfinder for uranium mineralization and other deposits containing uranium or thorium. Samples were collected via fixed tubes emplaced at depths of 6 m in backfilled holes drilled for this purpose. Compared to the atmospheric background value of 5.24 ppm v/v He, a variable weak anomaly (maximum 5.45–5.65 ppm He) was found over part of the Angela uranium deposit, N.T., in an arid area where mineralization is mostly at a depth of 60–90 m, at or below the water-table. Helium contents were mostly at background levels over a uranium deposit in the Officer Basin, W.A., where mineralization is at the water-table at 30–35 m, although radon gave a marked anomaly. Neither helium nor radon indicated the Manyingee deposit, W.A., which has uranium mineralization in a confined aquifer at 60–110 m. Similarly, no helium anomalies were found over the uranium- and thorium-rich Mt. Weld carbonatite or mineral sands at Eneabba.There appeared to be no correlation between helium distributions shown by groundwater and overburden-gas sampling at Manyingee or Mt. Weld. At Mt. Weld, groundwaters contained 0.06 to 13.60 μ/l He and overburden gases 5.24–5.47 ppm He, with the higher gas concentrations over country rock, where waters had background helium contents. It is presumed that equilibration between overburden gas and the atmosphere is far more rapid than that between overburden gas and groundwater, so that any helium released from the water is quickly dispersed.Overburden-gas helium concentrations were found to vary according to overburden type, being 5.24–5.32 ppm where sandy and porous and 5.30–5.50 ppm where clay-rich and less permeable. These background variations, which are greater than the total background-anomaly contrasts reported in the literature for shallow soil gases, have not been accounted for in most trial surveys, nor has the possibility of similar variations being due to analytical error. From the data obtained, there is little evidence that helium can be considered an effective pathfinder for blind or concealed deposits using soil gas or overburden gas as sample media. Previous work on the use of soil and soil-gas helium determinations in uranium exploration is reviewed in the light of these findings and the concept and techniques assessed.     

基于土壤氡气测量识别甘肃北山南缘隐伏断裂

我国高放废物地质处置库首选预选区位于甘肃北山南缘，区内分布有多条大型非活动断裂构造，这些断裂很可能成为未来放射性核素迁移的主要通道。断裂在向地表延伸过程中，受第四系覆盖等因素影响，造成关键构造部位隐伏地下而难以识别。本文以北山地区新场地段南部红旗山和前红泉断裂为研究对象，采用土壤中氡气测量方法，探讨了大型断裂构造中隐伏段落的识别及其指示的水文地质意义。结果表明：土壤中氡气测量对于识别北山南缘隐伏断裂具有很好的指示意义，是传统地质调查方法的一种重要补充；红旗山和前红泉断裂裂隙系统整体开启性均较差，裂隙系统不发育，影响范围较小，不具备形成较大规模储水空间的可能性。不同断裂带土壤氡浓度背景值差异较大，可根据土壤氡浓度累积频率分布图确定背景值；土壤氡浓度等值线分布图对判断隐伏断裂位置具有一定的指示作用。对于压剪性断裂而言，主断裂多沿氡气高异常与低异常边界分布或表现为氡气中等异常，而两侧的次级断裂表现为氡气高异常。     

Modeling spatial uncertainty of heavy metal content in soil by conditional Latin hypercube sampling and geostatistical simulation

This study proposes the method of simulating spatial patterns and quantifying the uncertainty in multivariate distribution of heavy metals (Cr, Cu, Ni, and Zn) by sequential indicator simulation (SIS) combined with conditional Latin hypercube sampling (cLHS) in Changhua County, Taiwan. The cLHS is used for a sampling then for SIS mapping and assessing uncertainties of heavy metal concentrations. The indicator variogram results indicate that the 700 cLHS samples replicate statistical multivariate distribution and spatial structure of the 1,082 samples. Moreover, the SIS realizations based on 700 cLHS samples are more conservative and reliable than those based on 1,082 samples for delineating soil contamination by all heavy metals with the exception of Zn. Given adequate sampling, soil contamination simulation provides sufficient information for delineating contaminated areas and planning environmental management.     

Analysis of seismic hazard in landslide-prone regions: criteria and example for an area of Daunia (southern Italy)

In relation to the assessment of earthquake-induced landslide hazard, this paper discusses general principles and describes implementation criteria for seismic hazard estimates in landslide-prone regions. These criteria were worked out during the preparation of a hazard map belonging to the official Italian geological cartography and they are proposed as guidelines for future compilation of similar maps. In the presented case study, we used a procedure for the assessment of seismic hazard impact on slope stability adopting Arias intensity Ia as seismic shaking parameter and critical acceleration a _c as parameter representing slope strength to failures induced by seismic shaking. According to this procedure, after a preliminary comparison of estimated historical maximum values of Ia with values proposed in literature as landslide-triggering thresholds, a probabilistic approach, based on the Newmark’s model, is adopted: it allows to estimate the minimum critical acceleration a _c required for a slope to keep under a prefixed value, the probability of failures induced by seismic shakings expected in a given time interval. In this way, one can prepare seismic hazard maps where seismic shaking is expressed in an indirect way through a parameter (the critical acceleration) representing the “strength” that seismic shakings mobilise in slope materials (strength demand) with a prefixed exceedance probability. This approach was applied to an area of Daunia (Apulia—southern Italy) affected by frequent landslide phenomena. The obtained results indicate that shakings with a significant slope destabilisation potential can be expected particularly in the north-western part of the area, which is exposed to the seismic activity of Apennine tectonic structures.     

Quality of land facets as soil mapping units in an area of Northern Nigeria

This study examines the quality of land facets as soil mapping units in agricultural soil surveys. This involves sampling the textural and chemical properties of the first two horizons of the land facets in two land systems in a sparsely populated area of northern Nigeria, and assessing whether or not the variances in soil properties between the land facets are significantly greater than the variances that can be observed within each land facet. The size of the variances between the land facets in relation to the variances within the facets (the intraclass correlation), provides the basis for assessing whether or not land facets are homogeneous enough for making predictions about soil and land use potentials. For the top horizons, sand and exchangeable sodium are significantly different between land facets, while clay, pH, exchangeable sodium, potassium and magnesium and cation exchange capacity, total nitrogen and organic carbon have moderate to large intraclass correlations. Only pH and exchangeable magnesium are significantly different between land facets for the second horizons and, except for silt and pH, significantly less than half of the second horizon properties are due to differences between land facets. This suggests that land facets may be useful in evaluating the broad chemical potentials of this sparsely populated environment. Some implications of the results are discussed for soil surveys and agricultural land use planning.     

Groundwater electrical conductivity and soil radon gas monitoring for earthquake precursory studies in Koyna, India

Hourly monitoring of electrical conductivity (EC) of groundwater along with groundwater levels in the 210 m deep boreholes (specially drilled for pore pressure/earthquake studies) and soil Rn gas at 60 cm below ground level in real time, in the Koyna-Warna region (characterized by basaltic rocks, >1500 m thick, and dotted with several sets of fault systems), western India, provided strong precursory signatures in response to two earthquakes (M 4.7 on 14/11/09, and M 5.1 on 12/12/09) that occurred in the study region. The EC measured in Govare well water showed precursory perturbations about 40 h prior to the M 5.1 earthquake and continued further for about 20 h after the earthquake. In response to the M 4.7 earthquake, there were EC perturbations 8 days after the earthquake. In another well (Koyna) which is located 4 km north of Govare well, no precursory signatures were found for the M 4.7 earthquake, while for M 5.1 earthquake, post-seismic precursors were found 18 days after the earthquake. Increased porosity and reduced pressure head accompanied by mixing of a freshwater component from the top zone due to earthquakes are the suggested mechanisms responsible for the observed anomalies in EC. Another parameter, soil Rn gas showed relatively proportional strength signals corresponding to these two earthquakes. In both the cases, the pre-seismic increase in Rn concentration started about 20 days in advance. The co-seismic drop in Rn levels was less by 30% from its peak value for the M 4.7 earthquake and 50% for the M 5.1 earthquake. The Rn anomalies are attributed to the opening and closing of micro-fractures before and during the earthquake. On line monitoring of these two parameters may be useful to check the entire chemistry change due to earthquake which may help to forecast impending earthquakes.     

Estimation of radon as an earthquake precursor: A neural network approach

An artificial neural networks (ANN) approach combined with Fourier Transform based selection of time period in the time series Radon Emission Data has been presented and shown to improve event prediction rates and reduce false alarms in Earthquake Event Identification over the traditional multiple linear regression techniques. The paper presents a neural networks system using radial basis function (RBF) network as an alternative to traditional statistical regression technique in isolating Radon Emission Anomaly caused by seismic activities. The RBF model has been developed to accept and predict earthquakes events based on a known data set of Radon Emanation, Metrological parameters and actual earthquake events. Subsequently, the model was tested and evaluated on a future data set and a prediction rate of 87.8%, if a reduced false alarm was achieved, the results obtained are better than the traditional techniques.     

Characterising soil property in an area with limited measurement: a Bayesian approach

The Bayesian approach has been proved useful to geotechnical engineering especially when project-specific data/measurements are very limited. In this paper, we introduced a new Bayesian algorithm to estimate soil properties at each location of a study area, with very limited project-specific data. In addition to the proposed methodology and algorithms, we also conducted a model application to estimate soil permeability for each of the 64 locations within a 4-by-4 m² area, based on very limited project-specific data, that is, one measurement from each location.     

Critical parameter investigation for earthquake hazard assessment in the Sannio-Matese area of Southern Italy

Probabilistic methods have been applied for the assessment of seismic hazard in a selected region of Southern Italy (Sannio-Matese). This method is mainly suitable for engineering and planning purposes and was first introduced in 1968 by Cornell and efficiently codified into a FORTRAN computer program by McGuire. Special attention is paid in this paper to the specific input parameters, i.e. completeness of data catalogues, time variability of seismic activity, different forms of frequency distributions, and regional attenuation characteristics.     

Soil erosion susceptibility assessment and validation using a geostatistical multivariate approach: a test in Southern Sicily

A certain number of studies have been carried out in recent years that aim at developing and applying a model capable of assessing water erosion of soil. Some of these have tried to quantitatively evaluate the volumes of soil loss, while others have focused their efforts on the recognition of the areas most prone to water erosion processes. This article presents the results of a research whose objective was that of evaluating water erosion susceptibility in a Sicilian watershed: the Naro river basin. A geomorphological study was carried out to recognize the water erosion landforms and define a set of parameters expressing both the intensity of hydraulic forces and the resistance of rocks/soils. The landforms were mapped and classified according to the dominant process in landsurfaces affected by diffuse or linear water erosion. A GIS layer was obtained by combining six determining factors (bedrock lithology, land use, soil texture, plan curvature, stream power index and slope-length factor) in unique conditions units. A geostatistical multivariate approach was applied by analysing the relationships between the spatial distributions of the erosion landforms and the unique condition units. Particularly, the density of eroded area for each combination of determining factors has been calculated: such function corresponds, in fact, to the conditional probability of erosion landforms to develop, under the same geoenvironmental conditions. In light of the obtained results, a general geomorphologic model for water erosion in the Naro river basin can be depicted: cultivated areas in clayey slopes, having fine-medium soil texture, are the most prone to be eroded; linear or diffuse water erosion processes dominate where the topography is favourable to a convergent or divergent runoff, respectively. For each of the two erosion process types, a susceptibility map was produced and submitted to a validation procedure based on a spatial random partition strategy. Both the success of the validation procedure of the susceptibility models and the geomorphological coherence of the relationships between factors and process that such models suggest, confirm the reliability of the method and the goodness of the predictions.     

A geostatistical approach to predicting the washability characteristics of coal in situ

The washability characteristics of coal are dependent on two basic relations: the ash assay vs. relative density curve, and the distribution by weight of the relative densities of coal particles. Armstrong and Whitmore (1980) demonstrated that the ash content and the yield of coal floating at a particular density can be predicted with reasonable accuracy using a simple inverse proportionality relation for the ash assay vs. density curve and a lognormal model for the distribution. In this paper, geostatistical techniques are used in conjunction with the two models to predict the washability characteristics of coal in situ.