Natural radionuclide analysis in chattarpur area of southeastern coastal area of Odisha, India

The energy released in a spontaneous decay process of natural radionuclides is the main source of the total radiation dose to human beings. Natural radionuclides are widely distributed in soil, rocks, air, and groundwater. In present investigation, the analysis of terrestrial radionuclides such as ²²⁶Ra, ²³²Th, and ⁴⁰K in soil and sand of Chattarpur area of southeastern coast of Odisha has been carried out using NaI(Tl) gamma ray detector. The higher activity concentrations of naturally occurring radionuclides have been reported from the study area. The gamma radiationdose originating from the terrestrial radionuclides was found to vary from 95 to 1813 nGy/h with an average of 700 nGy/h. This study is important to generate a baseline data of radiation exposure in the area. Health hazard effects due to natural radiation exposure are discussed in details.     

Implication and hazard of radiation level in the building materials

The natural radioactivity due to radium, thorium, and potassium in building material samples contribute to the radiation dose received by human beings significantly. It is essential to evaluate the activity levels of these nuclides for the assessment of natural radiation dose. Activity concentrations of the gamma emitting primordial radionuclides ²³²Th, ²²⁶Ra, and ⁴⁰K were measured using high resolution gamma spectrometry technique with high purity germanium (HPGe) detector in building materials: sand, brick, granite, cement and rock, collected from various areas of Gulbarga and Koppal districts. The standard ASTM procedure was followed for the sample preparation. The distribution of radionuclides and variation in activity concentration depend upon the rock formation and the geological properties of the region. The activity of the three radionuclides, ²³²Th, ²²⁶Ra, and ⁴⁰K, were found to be in the range of 3.1–227.1, 1.6–111, and 23.2–1505 Bq/kg, respectively. The dose related radiological parameters were also calculated for all the samples and the observations show that the activity concentrations of the radionuclides are well within the UNSCEAR limits.     

Linking transit times to catchment sensitivity to atmospheric deposition of acidity and nitrogen in mountains of the western United States

Transit times are hypothesized to influence catchment sensitivity to atmospheric deposition of acidity and nitrogen (N) because they help determine the amount of time available for infiltrating precipitation to interact with catchment soil and biota. Transit time metrics, including fraction of young water (F_yw) and mean transit time (MTT), were calculated for 11 headwater catchments in mountains of the western United States based on differences in the amplitude of the seasonal signal of δ¹⁸O in streamflow and precipitation. Results were statistically compared with catchment characteristics to elucidate controlling mechanisms. Transit times also were compared with stream solute concentrations to test the hypothesis that transit times are a primary influence on weathering rates and biological assimilation of atmospherically deposited N. Results indicate that transit times in the study catchments are strongly related to soil, vegetation, and topographic characteristics, with barren terrain (bare rock and talus) and steep slopes linked to high F_yw and short MTT, whereas forest soil (hydrogroup B) was linked to low F_yw and greater MTT. Concentrations of silicate weathering products (Na⁺ and Si) were negatively related to F_yw and barren terrain, and positively related to MTT and forest soil, supporting the concept that weathering fluxes and buffering capacity tend to be low in alpine areas due to short transit times. Nitrate concentrations were positively related to N deposition, catchment slope, and barren terrain, and negatively related to forest, indicating that hydrologic and/or biogeochemical processes associated with steep slopes limit uptake of atmospherically deposited N by biota. Interannual and seasonal variability in transit times and source water contributions in the study catchments was substantial, reflecting the influence of strong temporal variations in snowmelt inputs in high‐elevation catchments of the western United States. Results from this study confirm that short transit times in these areas are a key reason they are highly sensitive to atmospheric pollution and climate change.     

Selecting best mapping strategies for storm runoff modeling in a mountainous semi‐arid area

Accurate runoff and soil erosion modeling is constrained by data availability, particularly for physically based models such as OpenLISEM that are data demanding, as the processes are calculated on a cell‐by‐cell basis. The first decision when using such models is to select mapping units that best reflect the spatial variability of the soil and hydraulic properties in the catchment. In environments with limited data, available maps are usually generic, with large units that may lump together the values of the soil properties, affecting the spatial patterns of the predictions and output values in the outlet. Conversely, the output results may be equally acceptable, following the principle of equifinality. To studyhow the mapping method selected affects the model outputs, four types of input maps with different degrees of complexity were created: average values allocated to general soil map units (ASG1), average values allocated to detailed map units (ASG2), values interpolated by ordinary kriging (OK) and interpolated by kriging with external drift (KED). The study area was Ribeira Seca, a 90 km² catchment located in Santiago Island, Cape Verde (West Africa), a semi‐arid country subject to scarce but extreme rainfall during the short tropical summer monsoon. To evaluate the influence of rainfall on runoff and erosion, two storm events with different intensity and duration were considered. OK and KED inputs produced similar results, with the latter being closer to the observed hydrographs. The highest soil losses were obtained with KED (43 ton ha^{? 1} for the strongest event). To improve the results of soil loss predictions, higher accurate spatial information on the processes is needed; however, spatial information of input soil properties alone is not enough in complex landscapes. The results demonstrate the importance of selecting the appropriate mapping strategy to obtain reliable runoff and erosion estimates. Copyright © 2013 John Wiley & Sons, Ltd.     

Assessment of the prediction error in a large-scale application of a dynamic soil acidification model

 The prediction error of a relatively simple soil acidification model (SMART2) was assessed before and after calibration, focussing on the Al and NO₃ concentrations on a block scale. Although SMART2 is especially developed for application on a national to European scale, it still runs at a point support. A 5×5 km² grid was used for application on the European scale. Block characteristic values were obtained simply by taking the median value of the point support values within the corresponding grid cell. In order to increase confidence in model predictions on large spatial scales, the model was calibrated and validated for the Netherlands, using a resolution that is feasible for Europe as a whole. Because observations are available only at the point support, it was necessary to transfer them to the block support of the model results. For this purpose, about 250 point observations of soil solution concentrations in forest soils were upscaled to a 5×5 km² grid map, using multiple linear regression analysis combined with block kriging. The resulting map with upscaled observations was used for both validation and calibration. A comparison of the map with model predictions using nominal parameter values and the map with the upscaled observations showed that the model overestimated the predicted Al and NO₃ concentrations. The nominal model results were still in the 95% confidence interval of the upscaled observations, but calibration improved the model predictions and strongly reduced the model error. However, the model error after calibration remains rather large.     

UAV RGB,thermal infrared and multispectral imagery used to investigate the control of terrain on the spatial distribution of dryland biocrust

Biocrusts (topsoil communities formed by mosses, lichens, bacteria, fungi, algae, and cyanobacteria) are a key biotic component of dryland ecosystems. Whilst climate patterns control the distribution of biocrusts in drylands worldwide, terrain and soil attributes can influence biocrust distribution at landscape scale. Multi-source unmanned aerial vehicle (UAV) imagery was used to map and study biocrust ecology in a typical dryland ecosystem in central Spain. Red, green and blue (RGB) imagery was processed using structure-from-motion techniques to map terrain attributes related to microclimate and terrain stability. Multispectral imagery was used to produce accurate maps (accuracy > 80%) of dryland ecosystem components (vegetation, bare soil and biocrust composition). Finally, thermal infrared (TIR) and multispectral imagery was used to calculate the apparent thermal inertia (ATI) of soil and to evaluate how ATI was related to soil moisture (r² = 0.83). The relationship between soil properties and UAV-derived variables was first evaluated at the field plot level. Then, the maps obtained were used to explore the relationship between biocrusts and terrain attributes at ecosystem level through a redundancy analysis. The most significant variables that explain biocrust distribution are: ATI (34.4% of variance, F = 130.75; p < 0.001), Elevation (25.8%, F = 97.6; p < 0.001), and potential solar incoming radiation (PSIR) (52.9%, F = 200.1; p < 0.001). Differences were found between areas dominated by lichens and mosses. Lichen-dominated biocrusts were associated with areas with high slopes and low values of ATI, with soil characterized by a higher amount of soluble salts, and lower amount of organic carbon, total phosphorus (P_tot) and total nitrogen (N_tot). Biocrust-forming mosses dominated lower and moister areas, characterized by gentler slopes and higher values of ATI with soils with higher contents of organic carbon, P_tot and N_tot. This study shows the potential to use UAVs to improve our understanding of drylands and to evaluate the control that the terrain has on biocrust distribution.     

Identifying large‐scale erosion and deposition processes from airborne gamma radiometrics and digital elevation models in a weathered landscape

Patterns of erosion and deposition are difficult to identify and measure at catchment and regional scale but it may be possible to infer their distribution from remote sensing using easily measured surrogate variables. Airborne geophysical surveys provide data on gamma ray emissions from surface and near‐surface material and allow estimation of K, Th and U content. Gamma ray signatures are largely determined by lithology but also change with weathering and with erosion and deposition, and may be used as a partial surrogate for those processes. Comparison of gamma ray signatures with topographic characteristics closely related to sediment transport capacity, downstream sorting of sediments, and the extent of erosion and deposition shows strong linkages. Studies in four small catchments in southeastern Australia indicate that K consistently increases as slopes become steeper while Th and U may either increase or decrease. This suggests the presence of fresh rock rather than weathered material and implies removal of material by erosion, although some patterns may result from systematic changes in lithology across catchments. Analysis by lithology confirms the increase in K with slope in granites, metamorphosed sediments and basalt, and also shows a tendency for U to decrease with slope in the granites and basalt. Gamma ray emissions vary only slightly with catchment area (a surrogate measure of water discharge) suggesting that water erosion is limited or that discharge is not closely related to area. Gamma radiometric profiles down hillslopes, averaged across the full range of gradients, show that, in most cases, radioelements initially decrease, probably reflecting increased weathering, but then increase close to valley floors because of accumulation of fine sediments. Analysis by lithology confirms the increase in radioelements close to valley floors in granites and metamorphosed sediments but the trend is less clear in basalt. Gamma ray profiles down floodplains are variable and indicate the amount of deposition and accumulation of weathered material in valley openings and exposure of bedrock in valley constrictions. Simple erosion and deposition models, based on the conservation of mass equation, and applied to the four catchments, show that all radioelements increase as the potential for deposition increases. They reach a low point in zones of no net erosion or deposition and subsequently increase as erosion becomes more intense and weathered material is lost from slopes. Analysis by lithology largely confirms this pattern. The usefulness of airborne geophysical survey data is limited by flight line spacing with most data being flown at a 200–400 m spacing in Australia. However, general trends in erosion and deposition can still be distinguished and there is capacity for calibrating long‐term erosion and deposition models once better approaches to interpretation of gamma ray data have been developed. Copyright © 2000 John Wiley & Sons, Ltd.     

Effect of basin physical characteristics on solute fluxes in nine alpine/subalpine basins,Colorado, USA

Alpine/subalpine basins may exhibit substantial variability in solute fluxes despite many apparent similarities in basin characteristics. An evaluation of controls on spatial patterns in solute fluxes may allow development of predictive tools for assessing basin sensitivity to outside perturbations such as climate change or deposition of atmospheric pollutants. Relationships between basin physical characteristics, determined from geographical information system (GIS) tools, and solute fluxes and mineral weathering rates were explored for nine alpine/subalpine basins in Rocky Mountain National Park, Colorado, using correlation analyses for 1993 and 1994 data. Stream‐water nitrate fluxes were correlated positively with basin characteristics associated with the talus environment; i.e., the fractional amounts of steep slopes (≥ 30°), unvegetated terrain and young debris (primarily Holocene till) in the basins, and were correlated negatively with fractional amounts of subalpine meadow terrain. Correlations with nitrate indicate the importance of the talus environment in promoting nitrate flux and the mitigating effect of areas with established vegetation, such as subalpine meadows. Total mineral weathering rates for the basins ranged from about 300 to 600 mol ha^?1 year^?1. Oligoclase weathering accounted for 30 to 73% of the total mineral weathering flux, and was positively correlated with the amount of old debris (primarily Pleistocene glacial till) in the basins. Although calcite is found in trace amounts in bedrock, calcite weathering accounted for up to 44% of the total mineral weathering flux. Calcite was strongly correlated with steep slope, unvegetated terrain, and young debris—probably because physical weathering in steep‐gradient areas exposes fresh mineral surfaces that contain calcite for chemical weathering. Oligoclase and calcite weathering are the dominant sources of alkalinity in the basins. However, atmospherically deposited acids consume much of the alkalinity generated by weathering of calcite and other minerals in the talus environment. Published in 2001 by John Wiley & Sons, Ltd.     

Weathering,erosion and sediment composition in a high‐gradient river,Calabria, Italy

Source rock lithology and immediate modifying processes, such as chemical weathering and mechanical erosion, are primary controls on fluvial sediment supply. Sand composition and Chemical Index of Alteration (CIA) of parent rocks, soil and fluvial sand of the Savuto River watershed, Calabria (Italy), were used to evaluate the modifications of source rocks through different sections of the basin, characterized by different geomorphic processes, in a sub‐humid Mediterranean climate. The headwaters, with gentle topography, produce a coarse‐grained sediment load derived from deeply weathered gneiss, having sand of quartzofeldspathic composition, compositionally very different from in situ degraded bedrock. Maximum estimated CIA values suggest that source rock has been affected significantly by weathering, and it testifies to a climatic threshold on the destruction of the bedrock. The mid‐course has steeper slopes and a deeply incised valley; bedrock consists of mica‐schist and phyllite with a very thin regolith, which provides large cobble to very coarse sand sediments to the main channel. Slope instability, with an areal incidence of over 40 per cent, largely supplies detritus to the main channel. Sand‐sized detritus of soil and fluvial sand is lithic. Estimated CIA value testifies to a significant weathering of the bedrock too, even if in this part of the drainage basin steeper slopes allow erosion to exceed chemical weathering. The lower course has a braided pattern and sediment load is coarse to medium–fine grained. The river cuts across Palaeozoic crystalline rocks and Miocene siliciclastic deposits. Sand‐sized detritus, contributed from these rocks and homogenized by transport processes, has been found in the quartzolithic distal samples. Field and laboratory evidence indicates that landscape development was the result of extensive weathering during the last postglacial temperature maximum in the headwaters, and of mass‐failure and fluvial erosional processes in the mid‐ and low course. Copyright © 2000 John Wiley & Sons, Ltd.     

BME prediction of continuous geographical properties using auxiliary variables

Using auxiliary information to improve the prediction accuracy of soil properties in a physically meaningful and technically efficient manner has been widely recognized in pedometrics. In this paper, we explored a novel technique to effectively integrate sampling data and auxiliary environmental information, including continuous and categorical variables, within the framework of the Bayesian maximum entropy (BME) theory. Soil samples and observed auxiliary variables were combined to generate probability distributions of the predicted soil variable at unsampled points. These probability distributions served as soft data of the BME theory at the unsampled locations, and, together with the hard data (sample points) were used in spatial BME prediction. To gain practical insight, the proposed approach was implemented in a real-world case study involving a dataset of soil total nitrogen (TN) contents in the Shayang County of the Hubei Province (China). Five terrain indices, soil types, and soil texture were used as auxiliary variables to generate soft data. Spatial distribution of soil total nitrogen was predicted by BME, regression kriging (RK) with auxiliary variables, and ordinary kriging (OK). The results of the prediction techniques were compared in terms of the Pearson correlation coefficient (r), mean error (ME), and root mean squared error (RMSE). These results showed that the BME predictions were less biased and more accurate than those of the kriging techniques. In sum, the present work extended the BME approach to implement certain kinds of auxiliary information in a rigorous and efficient manner. Our findings showed that the BME prediction technique involving the transformation of variables into soft data can improve prediction accuracy considerably, compared to other techniques currently in use, like RK and OK.     

Dry aeolian dust accumulation in rocky deserts: ­a medium‐term field experiment based on short‐term wind tunnel simulations

The spatial pattern of medium‐term (a few months) dry aeolian dust accumulation in rocky deserts is predicted using short‐term deposition and erosion experiments in a wind tunnel. The predictions are tested in a field experiment set up in the northern Negev Desert of Israel. The results show that superimposing wind tunnel deposition and erosion maps usually leads to correct predictions of medium‐term dust accumulation. The predictions are somewhat less confident near the inflection lines of windward hillslopes, where small‐scale irregularities in the local topography make it difficult to locate the exact position of the areas of little accumulation. Elsewhere in the topography predictions are good, and the method works satisfactorily. Highest accumulation occurs on concave windward slopes and, to a lesser extent, on slopes parallel to the wind. Little accumulation occurs on the convex windward slopes and in dust separation bubbles. The smallest accumulation rates are observed immediately upwind of the top of pronounced hills and on leeslopes. The rate of dry dust accumulation measured during the field experiment varied from 17 to 93 g m⁻² a⁻¹, depending on the topographic position of the accumulation plots. For most plots, it was of the order of 30–60 g m⁻² a⁻¹. Copyright © 2000 John Wiley & Sons, Ltd.     

Characterization of field scale soil variability using remotely and proximally sensed data and response surface method

Soil salinization of the reclaimed tidelands is problematic. Therefore, there is a need to characterize the spatial variability of soil salinity associated with soil moisture and other soil properties across the reclaimed tidelands. One approach is the use of easily-acquired ancillary data as surrogates for the arduous conventional soil sampling. In a reclaimed coastal tideland in the south of Hangzhou Gulf, backscattering coefficient (σ⁰) from remotely sensed ALOS/PALSAR radar imagery (HH polarization mode) and apparent soil electrical conductivity (ECa) from a proximally sensed EM38 were used to indicate the spatial distribution of soil moisture and salinity, respectively. After that, response surface methodology (RSM) was employed to determine an optimal set of 12 soil samples using spatially referenced σ⁰ and ECa data. Spatial distributions of three soil chemical properties [i.e. soil organic matter (SOM), available nitrogen (AN), and available potassium (AK)] were predicted using inverse distance weighted method based on the 12 samples and were then compared with the predictions generated using 42 samples obtained from a conventional grid sampling scheme. It was concluded that combination of radar imagery and EM induction data can delineate the spatial variability of two key soil properties (i.e. moisture and salinity) across the study area. Besides, RSM-based sampling using radar imagery and EM induction data was highly effective in characterizing the spatial variability of SOM, AN and AK, compared with the conventional grid sampling. This new approach may be used to assist site specific management in precision agriculture.     

Estimation and prediction of a 2D lognormal diffusion random field

This paper describes techniques for estimation and prediction of two-parameter lognormal diffusion random fields. The drift and diffusion coefficients, which characterize a two-parameter lognormal diffusion under certain conditions, are estimated by maximum likelihood. For data on a regular grid, an alternative method is proposed to estimate the diffusion coefficient. Both of these estimates are compared in several situations. The kriging predictors are formulated involving the drift and diffusion coefficients and the predictions are obtained using the estimates of these coefficients.     

Distribution of local Cs anomalies on the seafloor near the Fukushima Dai-ichi Nuclear Power Plant

An estimated 3.5 ± 0.7 × 10¹⁵ Bq of ¹³⁷Cs is thought to have been discharged into the ocean following the melt down at Fukushima Dai-ichi Nuclear Power Plant (F1NPP). While efforts have been made to monitor seafloor radiation levels, the sampling techniques used cannot capture the continuous distribution of radionuclides. In this work, we apply in situ measurement techniques using a towed gamma ray spectrometer to map the continuous distribution of ¹³⁷Cs on the seafloor within 20 km of the F1NPP. The results reveal the existence of local ¹³⁷Cs anomalies, with levels of ¹³⁷Cs an order of magnitude higher than the surrounding seafloors. The sizes of the anomalies mapped in this work range from a few meters to a few hundreds of meters in length, and it is demonstrated that the distribution of these anomalies is strongly influenced by meter scale features of the terrain.     

Soil formation and weathering in a permafrost environment of the Swiss Alps: a multi‐parameter and non‐steady‐state approach

Spatially discontinuous permafrost conditions frequently occur in the European Alps. How soils under such conditions have evolved and how they may react to climate warming is largely unknown. This study focuses on the comparison of nearby soils that are characterised by the presence or absence of permafrost (active‐layer thickness: 2–3 m) in the alpine (tundra) and subalpine (forest) range of the Eastern Swiss Alps using a multi‐method (geochemical and mineralogical) approach. Moreover, a new non‐steady‐state concept was applied to determine rates of chemical weathering, soil erosion, soil formation, soil denudation, and soil production. Long‐term chemical weathering rates, soil formation and erosion rates were assessed by using immobile elements, fine‐earth stocks and meteoric ¹⁰Be. In addition, the weathering index (K + Ca)/Ti, the amount of Fe‐ and Al‐oxyhydroxides and clay minerals characteristics were considered. All methods indicated that the differences between permafrost‐affected and non‐permafrost‐affected soils were small. Furthermore, the soils did not uniformly differ in their weathering behaviour. A tendency towards less intense weathering in soils that were affected by permafrost was noted: at most sites, weathering rates, the proportion of oxyhydroxides and the weathering stage of clay minerals were lower in permafrost soils. In part, erosion rates were higher at the permafrost sites and accounted for 79–97% of the denudation rates. In general, soil formation rates (8.8–86.7 t/km²/yr) were in the expected range for Alpine soils. Independent of permafrost conditions, it seems that the local microenvironment (particularly vegetation and subsequently soil organic matter) has strongly influenced denudation rates. As the climate has varied since the beginning of soil evolution, the conditions for soil formation and weathering were not stable over time. Soil evolution in high Alpine settings is complex owing to, among others, spatio‐temporal variations of permafrost conditions and thus climate. This makes predictions of future behaviour very difficult. Copyright © 2016 John Wiley & Sons, Ltd.     

Test of statistical means for the extrapolation of soil depth point information using overlays of spatial environmental data and bootstrapping techniques

Hydrological modelling depends highly on the accuracy and uncertainty of model input parameters such as soil properties. Since most of these data are field surveyed, geostatistical techniques such as kriging, classification and regression trees or more sophisticated soil‐landscape models need to be applied to interpolate point information to the area. Most of the existing interpolation techniques require a random or regular distribution of points within the study area but are not adequate to satisfactorily interpolate soil catena or transect data. The soil landscape model presented in this study is predicting soil information from transect or catena point data using a statistical mean (arithmetic, geometric and harmonic mean) to calculate the soil information based on class means of merged spatial explanatory variables. A data set of 226 soil depth measurements covering a range of 0–6·5 m was used to test the model. The point data were sampled along four transects in the Stubbetorp catchment, SE‐Sweden. We overlaid a geomorphology map (8 classes) with digital elevation model‐derived topographic index maps (2–9 classes) to estimate the range of error the model produces with changing sample size and input maps. The accuracy of the soil depth predictions was estimated with the root mean square error (RMSE) based on a testing and training data set. RMSE ranged generally between 0·73 and 0·83 m ± 0·013 m depending on the amount of classes the merged layers had, but were smallest for a map combination with a low number of classes predicted with the harmonic mean (RMSE = 0·46 m). The results show that the prediction accuracy of this method depends on the number of point values in the sample, the value range of the measured attribute and the initial correlations between point values and explanatory variables, but suggests that the model approach is in general scale invariant. Copyright © 2009 John Wiley & Sons, Ltd.     

Asymmetric hillslope erosion following wildfire in Fourmile Canyon,Colorado

Infrequent, high‐magnitude events cause a disproportionate amount of sediment transport on steep hillslopes, but few quantitative data are available that capture these processes. Here we study the influence of wildfire and hillslope aspect on soil erosion in Fourmile Canyon, Colorado. This region experienced the Fourmile Fire of 2010, strong summer convective storms in 2011 and 2012, and extreme flooding in September 2013. We sampled soils shortly after these events and use fallout radionuclides to trace erosion on polar‐ and equatorial‐facing burned slopes and on a polar‐facing unburned slope. Because these radionuclides are concentrated in the upper decimeter of soil, soil inventories are sensitive to erosion by surface runoff. The polar‐facing burned slope had significantly lower cesium‐137 (¹³⁷Cs) and lead‐210 (²¹⁰Pb) inventories (p < 0.05) than either the polar‐facing unburned slope or equatorial‐facing burned slope. Local slope magnitude does not appear to control the erosional response to wildfire, as relatively gently sloping (~20%) polar‐facing positions were severely eroded in the most intensively burned area. Field evidence and soil profile analyses indicate up to 4 cm of local soil erosion on the polar‐facing burned slope, but radionuclide mass balance indicates that much of this was trapped nearby. Using a ¹³⁷Cs‐based erosion model, we find that the burned polar‐facing slope had a net mean sediment loss of 2 mm (~1 kg m^?2) over a one to three year period, which is one to two orders of magnitude higher than longer‐term erosion rates reported for this region. In this part of the Colorado Front Range, strong hillslope asymmetry controls soil moisture and vegetation; polar‐facing slopes support significantly denser pine and fir stands, which fuels more intense wildfires. We conclude that polar‐facing slopes experience the most severe surface erosion following wildfires in this region, indicating that landscape‐scale aridity can control the geomorphic response of hillslopes to wildfires. Copyright © 2018 John Wiley & Sons, Ltd.     

Health risk profile for terrestrial radionuclides in soil around artisanal gold mining area at Alsopag,Sudan

This study shows the assessment of radiation hazard parameters due to terrestrial radionuclides in the soil around artisanal gold mining for addressing the issue of natural radioactivity in mining areas. Hence, the levels ²³⁸U, ²³²Th, ⁴⁰K and ²²⁶Ra in soil (using gamma spectrometry), ²²²Rn in soil and ²²²Rn in air were determined. Radiation hazard parameters were then computed. These include absorbed dose D, annual effective dose E, radium equivalent activity Ra_eq, external hazard H_ex, annual gonadal dose equivalent hazard index AGDE and excess lifetime cancer risk ELCR due to the inhalation of radon (²²²Rn) and consumption of radium (²²⁶Ra) in vegetation. Uranium (²³⁸U), thorium (²³²Th) and potassium (⁴⁰K) averages were, respectively, 26, 36 and 685 Becquerel per kilogram (Bq kg^?1). Soil radon (4671 Bq m^?3) and radon in air (14.77 Bq m^?3) were found to be less than worldwide data. Nevertheless, the average ⁴⁰K concentration was 685 Bq kg^?1. This is slightly higher than the United Nations Scientific Committee on the Effects of Atomic Radiation average value of 412 Bq kg^?1. The obtained result indicates that some of the radiation hazard parameters seem unsavory. The mean value of absorbed dose rate (62.49 nGy h^?1) was slightly higher than average value of 57 nGy h^?1 (~?45% from ⁴⁰K), and that of AGDE (444 μSv year^?1) was higher than worldwide average reported value (300 μSv year^?1). This study highlights the necessity to launch extensive nationwide radiation protection program in the mining areas for regulatory control.     

Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data

Soil moisture has a pronounced effect on earth surface processes. Global soil moisture is strongly driven by climate, whereas at finer scales, the role of non‐climatic drivers becomes more important. We provide insights into the significance of soil and land surface properties in landscape‐scale soil moisture variation by utilizing high‐resolution light detection and ranging (LiDAR) data and extensive field investigations. The data consist of 1200 study plots located in a high‐latitude landscape of mountain tundra in north‐western Finland. We measured the plots three times during growing season 2016 with a hand‐held time‐domain reflectometry sensor. To model soil moisture and its temporal variation, we used four statistical modelling methods: generalized linear models, generalized additive models, boosted regression trees, and random forests. The model fit of the soil moisture models were R² = 0.60 and root mean square error (RMSE) 8.04 VWC% on average, while the temporal variation models showed a lower fit of R² = 0.25 and RMSE 13.11 CV%. The predictive performances for the former were R² = 0.47 and RMSE 9.34 VWC%, and for the latter R² = 0.01 and RMSE 15.29 CV%. Results were similar across the modelling methods, demonstrating a consistent pattern. Soil moisture and its temporal variation showed strong heterogeneity over short distances; therefore, soil moisture modelling benefits from high‐resolution predictors, such as LiDAR based variables. In the soil moisture models, the strongest predictor was SAGA (System for Automated Geoscientific Analyses) wetness index (SWI), based on a 1 m² digital terrain model derived from LiDAR data, which outperformed soil predictors. Thus, our study supports the use of LiDAR based SWI in explaining fine‐scale soil moisture variation. In the temporal variation models, the strongest predictor was the field‐quantified organic layer depth variable. Our results show that spatial soil moisture predictions can be based on soil and land surface properties, yet the temporal models require further investigation. Copyright © 2017 John Wiley & Sons, Ltd.     

Using magnetic susceptibility to assess soil degradation in the Eastern Rif,Morocco

The soil in the Rif, Morocco, is at serious risk because increasing anthropogenic pressures are gradually transforming large natural areas into farmland. The distribution of magnetic minerals within the soil profile can be used to assess soil development and degradation. The soils in the study area are severely eroded because of a combination of highly erodible soils, intense rainstorms and scarce vegetation cover. To sample of representative soil profiles, lithology, slope gradient and land use were considered. The ranges of magnetic susceptibility in the soil profiles distinguished between two primary soil groups. Magnetic susceptibility varied in the soil profile and along the soil toposequence, and the variations were related to the differences in the original magnetic composition and the influence of main erosion factors. Lithology is the main factor contributing to the variation in magnetic susceptibility. The magnetic susceptibility values in soils on Tertiary marls (χ = 13·5 × 10^?8 m³ kg^?1) differed significantly from those on Quaternary terraces (χ = 122·1 × 10^?8 m³ kg^?1). Slope affected the distribution of magnetic susceptibility because of the continuous loss of topsoil in some parts of the slope and the deposition of eroded soil in others. Elimination of the natural vegetation cover and a shift to cultivated land for cereals has had a negative impact on soil development and, on similar slopes and substrates, magnetic susceptibility decreased significantly in cultivated soils. The soils on steep slopes that had natural vegetation cover retained the magnetic minerals better than did those on gentler slopes that were under cultivation. Grazing, clearing and, especially, tilling has weakened the soil and made it much more vulnerable to erosion. An analysis of the main factors causing erosion will help to promote rational use of the land and to establish conservation strategies in such fragile agroecosystems. Copyright © 2009 John Wiley & Sons, Ltd.