Spatial variability of soil properties in relation to land use and topography in a typical small watershed of the black soil region,northeastern China

Soil degradation resulted from unreasonable land use and erosion has been a serious problem in the black soil region of northeastern China. This paper seeks to understand the relationships between topsoil properties and topography and land use for land management targeting at improving soil quality in this region. A total of 292 soil samples and 81 volumetric rings were taken from a typical small watershed of the region in June 2005 for examining total carbon (TC), total nitrogen (TN), soil texture (classified into gravel, sand, silt, and clay), and bulk density (ρ _b), respectively. Spatial variability of these soil properties was evaluated with classical statistics and geostatistics methods. The results of classical statistics indicated that TC, TN, sand, silt, clay content, and ρ _b were moderate variables while gravel had great variability. Soil properties were mainly correlated to slope position, elevation and land types. Geostatistical analyses showed that the spatial autocorrelation for TC, TN, and silt was weak, strong for clay and moderate for and ρ _b sand, respectively. The spatial variations of soil properties are affected comprehensively by topographic factors, land use, erosion, and erosion control in this watershed. Past erosion, however, is the most important component to induce change of soil properties. In this small watershed, current soil and water conservation measures play an important role in controlling soil loss. But the restoration of soil properties was unsatisfactory. Comparing with untilled soil of this region, TC, TN, silt content are excessively low; whereas ρ _b, sand and clay content are excessively high; gravel appears at most sampling locations. It is necessary for improving soil properties to protect forest and grassland and change cultivation system of farmlands.     

Spatial analysis and hazard assessment of mercury in soil around the coal-fired power plant: a case study from the city of Baoji, China

Based on systematic sampling of soil around the coal-fired power plant (CFPP), the content of Hg was determined, using atomic fluorescence spectrometry. The result shows that the content of Hg in soil is different horizontally and vertically, ranges from 0.137 to 2.105 mg/kg (the average value is 0.606 mg/kg) and is more than the average content of Hg in Shaanxi, Chinese and world soil. In this study, spatial distribution and hazard assessment of mercury in soils around a CFPP were investigated using statistics, geostatistics and geographic information system (GIS) techniques. Ordinary kriging was carried out to map the spatial patterns of mercury and disjunctive kriging was used to quantify the probability of the Hg concentration higher than the threshold. The maps show that the spatial variability of the Hg concentration in soils was apparent. These results of this study could provide valuable information for risk assessment of environmental Hg pollution and decision support. An erratum to this article can be found at     

Spatial variability of soil organic matter and nutrients in paddy fields at various scales in southeast China

The present study examines the spatial dependency of soil organic matter and nutrients in paddy fields at three different scales using geostatistics and geographic information system techniques (GIS). The spatial variability of soil organic matter (SOM), total nitrogen (TN) and available phosphorus (AP) has been characterized using a total of 460, 131 and 64 samples that were, respectively, collected from the Hangzhou–Jiaxing–Huzhou (HJH) Plain (10 km), Pinghu county (1,000 m) and a test plot area (100 m) within the Pinghu county, Zhejiang province of the southeast China. Semivariograms showed that the SOM and TN had moderate spatial dependency on the large scale of HJH plain and moderate scale of Pinghu county with long spatial correlation distances. At the moderate scale of Pinghu county and the small scale of a test plot area, the AP data did not show any spatial correlation, but had moderate spatial dependency in HJH plain. Spherical and exponential variogram models were best fitted to all these soil properties. Maps of SOM and TN were generated through interpolation of measured values by ordinary kriging, and AP by lognormal kriging. This study suggests that precision management of SOM and TN is feasible at all scales, and precision management of AP is feasible at large scales.     

A Modeling Approach for the Study of Contamination in a Fractured Aquifer

The study of contaminants propagation in fractured and karstic aquifers shows uncertainties caused by the conditions of anisotropy of the medium and by the presence of cavities and residual products that could make fluid flow and solute transport unforeseeable. Therefore, in aquifers characterized by fissured and fractured solid matrix, in order to set up remediation strategies, it is necessary to represent the conditions of groundwater flow and contaminant propagation in such a way as to take into consideration the high heterogeneity connected to the presence of fractures and channels that act as preferential flow ways. The study carried out in a specified site, located in the city of Bari, heavily contaminated by petroliferous substances allows to build a model able to simulate subterranean draining conditions that prove to be as near as possible to the real ones. This simulation could be helpful for the prevision of the dynamic behavior of the aquifer during the period of the treatment in order to allow optimizations on the technical and economical point of view and in order to check the effective functionality of the system in the presence of anthropic constraints.     

The practice of fast conditional simulations through the LU decomposition of the covariance matrix

The LU-matrix approach to conditional simulations allows fast generation of large numbers of realizations for a given stochastic process. Simplicity, flexibility, and quality are its main advantages. Its implementation for cases where dense grids and/or large numbers of conditioning data cause computational problems is discussed. A case study is presented.     

A geostatistical approach for areal rainfall statistics assessment

Areal rainfall statistics are more relevant in flood hydrology and water resources management than point rainfall statistics when it comes to help designing dams or hydraulic structures. This paper presents a geostatistically based method to derive the areal statistics from point statistics. Assuming that the distribution models of point rainfall and areal belong to the same class of models and that the rainfall process is stationary, it is shown how the parameters of the areal distribution model can directly be computed from the parameters of the point distribution models in case of a non stationary process, an approximation is derived that yielded good results when applied to a mountainous region in Southern France. The method also allows the computation of the areal reduction factors in a very general form.     

A geostatistical approach for areal rainfall statistics assessment

Areal rainfall statistics are more relevant in flood hydrology and water resources management than point rainfall statistics when it comes to help designing dams or hydraulic structures. This paper presents a geostatistically based method to derive the areal statistics from point statistics. Assuming that the distribution models of point rainfall and areal belong to the same class of models and that the rainfall process is stationary, it is shown how the parameters of the areal distribution model can directly be computed from the parameters of the point distribution models in case of a non stationary process, an approximation is derived that yielded good results when applied to a mountainous region in Southern France. The method also allows the computation of the areal reduction factors in a very general form.     

Optimizing a piezometric network in the estimation of the groundwater budget: a case study from a crystalline-rock watershed in southern India

An estimate of the groundwater budget at the catchment scale is extremely important for the sustainable management of available water resources. Water resources are generally subjected to over-exploitation for agricultural and domestic purposes in agrarian economies like India. The double water-table fluctuation method is a reliable method for calculating the water budget in semi-arid crystalline rock areas. Extensive measurements of water levels from a dense network before and after the monsoon rainfall were made in a 53 km² watershed in southern India and various components of the water balance were then calculated. Later, water level data underwent geostatistical analyses to determine the priority and/or redundancy of each measurement point using a cross-validation method. An optimal network evolved from these analyses. The network was then used in re-calculation of the water-balance components. It was established that such an optimized network provides far fewer measurement points without considerably changing the conclusions regarding groundwater budget. This exercise is helpful in reducing the time and expenditure involved in exhaustive piezometric surveys and also in determining the water budget for large watersheds (watersheds greater than 50 km²).     

Conditional Simulation with Patterns

An entirely new approach to stochastic simulation is proposed through the direct simulation of patterns. Unlike pixel-based (single grid cells) or object-based stochastic simulation, pattern-based simulation simulates by pasting patterns directly onto the simulation grid. A pattern is a multi-pixel configuration identifying a meaningful entity (a puzzle piece) of the underlying spatial continuity. The methodology relies on the use of a training image from which the pattern set (database) is extracted. The use of training images is not new. The concept of a training image is extensively used in simulating Markov random fields or for sequentially simulating structures using multiple-point statistics. Both these approaches rely on extracting statistics from the training image, then reproducing these statistics in multiple stochastic realizations, at the same time conditioning to any available data. The proposed approach does not rely, explicitly, on either a statistical or probabilistic methodology. Instead, a sequential simulation method is proposed that borrows heavily from the pattern recognition literature and simulates by pasting at each visited location along a random path a pattern that is compatible with the available local data and any previously simulated patterns. This paper discusses the various implementation details to accomplish this idea. Several 2D illustrative as well as realistic and complex 3D examples are presented to showcase the versatility of the proposed algorithm.     

Hydrogeological modeling of radionuclide transport in low permeability media: a comparison between Boom Clay and Ypresian Clay

Deep low-permeability clay layers are considered as suitable environments for disposal of high-level radioactive waste. In Belgium, the Boom Clay is the reference host formation and the Ypresian Clay an alternative host formation for research and safety and feasibility assessment of deep disposal of nuclear waste. In this study, two hydrogeological models are built to calculate the radionuclide fluxes that would migrate from a potential repository through these two clay formations. Transport parameter heterogeneity is incorporated in the models using geostatistical co-simulations of hydraulic conductivity, diffusion coefficient and diffusion accessible porosity. The calculated radionuclide fluxes in the two clay formations are compared. The results show that in the Ypresian Clay larger differences between the fluxes through the lower and the upper clay boundary occur, larger total output radionuclide amounts are calculated and a larger effect of parameter heterogeneity on the calculated fluxes is observed, compared to the Boom Clay.