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.     

Space-time mapping of soil salinity using probabilistic bayesian maximum entropy

The mapping of saline soils is the first task before any reclamation effort. Reclamation is based on the knowledge of soil salinity in space and how it evolves with time. Soil salinity is traditionally determined by soil sampling and laboratory analysis. Recently, it became possible to complement these hard data with soft secondary data made available using field sensors like electrode probes. In this study, we had two data sets. The first includes measurements of field salinity (EC_a) at 413 locations and 19 time instants. The second, which is a subset of the first (13 to 20 locations), contains, in addition to EC_a, salinity determined in the laboratory (EC_2.5). Based on a procedure of cross-validation, we compared the prediction performance in the space-time domain of 3 methods: kriging using either only hard data (HK) or hard and mid interval soft data (HMIK), and Bayesian maximum entropy (BME) using probabilistic soft data. We found that BME was less biased, more accurate and giving estimates, which were better correlated with the observed values than the two kriging techniques. In addition, BME allowed one to delineate with better detail saline from non-saline areas.     

Field‐Scale Relationships Among Soil Properties and Shallow Groundwater Quality

It is important to understand the link between land surface/soil properties and shallow groundwater quality. To that end, soil properties and near‐water‐table groundwater chemistry of a shallow, unconfined aquifer were measured on a 100‐m grid on a 64‐ha irrigated field in southeastern North Dakota. Soil properties and hydrochemistry were compared via multivariate analysis that included product‐moment correlations and factor analysis/principal component analysis. Topographic low areas where the water table was in close proximity to the soil surface generally had higher apparent electrical conductivity (EC_a) and higher percent silt and clay than higher positions on the landscape. The majority of the groundwater was characterized by Ca‐ and Mg‐HCO₃ type water and was associated with topographic high areas with lower EC_a and net groundwater recharge. Small topographic depressions were areas of higher EC_a (net groundwater discharge) where salts that precipitated via evapotranspiration and evaporative discharge dissolved and leached to the groundwater during short‐term depression‐focused recharge events. At this site, groundwater quality and soil EC_a were related to surface topography. High‐resolution topography and EC_a measurements are necessary to characterize the land surface/soil properties and surficial groundwater quality at the field‐scale and to delineate areas where the shallow groundwater is most susceptible to contamination.     

Mapping the spatial distribution of subsurface saline material in the Darling River valley

In the Australian landscape larg stores of soluble salt are present naturally. In many cases it is attributable to salts entrapped as marine sediment in earlier geological time. At the district level, the need for information on the presence of saline subsurface material is increasing, particularly for its application to salinity hazard assessment and environmental management. This is the case in irrigated areas, where changes in hydrology can result in secondary salinisation. To reduce the expense, environmental studies use a regression relationship to make use of more readily observed measurements (e.g. electromagnetic (EM) data) which are strongly correlated with the variable of interest. In this investigation a methodology is outlined for mapping the spatial distribution of average subsurface (6–12 m) salinity (EC_e — mS m^? 1) using an environmental correlation with EM34 survey data collected across the Bourke Irrigation District (BID) in the Darling River valley. The EM34 is used in the horizontal dipole mode at coil configurations of 10 (EM34-10), 20 (EM34-20), and 40 (EM34-40). A multiple-linear regression (MLR) relationship is established between average subsurface EC_e and the three EM34 signal data using a forward modeling stepwise linear modeling approach. The spatial distribution of average subsurface salinity generally reflects the known surface expression of point-source salinisation and provides information for future environmental monitoring and natural resource management. The generation of EM34 data on various contrived grids (i.e. 1, 1.5, 2. 2.5 and 3 km) indicates that in terms of accuracy, the data available on the 0.5 (RMSE = 188) and 1 km (RMSE = 283) grid are best, with the least biased predictions achieved using 1 (ME = ? 1) and 2 km (ME = 12) grids. Viewing the spatial distribution of subsurface saline material showed that the 0.5 km spacing is optimal, particularly in order to account for short-range spatial variation between various physiographic units. The Relative Improvement (RI) shows that increasing EM grids from 1, 1.5, 2, 2.5 to 3 km gave RI of ? 53, ? 100%, ? 107%, ? 128% and ? 140%, respectively. We conclude that at a minimum a 1 km grid is needed for reconnaissance EM34 surveying.     

Electromagnetic induction for mapping textural contrasts of mine tailing deposits

Mine tailings present an important legacy of past and present ore-extraction activities in the Desert Southwest. Inactive mine tailings have no immediate economic role in current mining operations, yet from an environmental point of view it is important that such deposits are stabilized to prevent mass movement, wind or water erosion, leaching of chemicals such as acid mine drainage, and to reduce visual blight. In the presented study, we assess the potential for inferring textural properties of mine tailing deposits with electromagnetic induction (EMI) mapping as a means of informing efforts to establish vegetation at mine waste sites. EMI measurements of apparent electrical conductivity (EC_a) and tailing samples were collected at a mine waste site in Southern Arizona, USA and used to test empirical and theoretical relationships between EC_a and physical and mineralogical properties using linear and Gaussian process regression. Sensitivity analyses of a semi-theoretical and a regression model of EC_a as a function of tailing properties indicated that volumetric clay fraction in the top 60 cm was a primary influence on bulk electrical conductivity along with water content, conductivity of the soil water and the presence of conductive minerals hematite and pyrite. At this site, latitude and longitude were better predictors of clay content than EC_a, and while it was possible to obtain information about the spatial distribution of tailing texture using EMI, simple Kriging of texture data was a more powerful textural mapping technique. We conclude that EMI is a useful tool for mapping tailing texture at waste deposit sites, but due to physical and chemical heterogeneity of tailing deposits, it is necessary to collect more in situ samples than are needed for agricultural applications.     

新疆艾比湖湿地土壤水盐空间变异性分析

为揭示艾比湖湿地土壤退化程度空间分布特征,在离艾比湖湖滨5~15 km,绕湖一周160 km范围内,以湖心质点为中心,将艾比湖划分为东北、东南、西南、西北4个区域,采用传统统计学和地统计学相结合的方法对表层(0~20 cm)土壤盐分、含水量与p H的空间分异特征进行研究.结果表明:绕湖一周不同区域的土壤盐分均属中等变异强度;土壤含水量在西北部属强变异性,而东北、东南和西南部均属中等变异强度;土壤p H在不同区域内均属弱变异强度.绕湖一周除西北部土壤盐分的半方差理论模型较符合球状模型外,其它区域土壤盐分、含水量和p H均符合高斯模型;受结构性因素影响,不同区域土壤盐分、含水量和p H均具有较强的空间相关性;西南部土壤盐分、含水量和p H的Moran's I系数比其它区域的波动大,表明空间相关性较强.艾比湖湿地常年大风、干旱、缺水及沙化盐化的自然因素与引水围堰、种植耐盐碱植物的人为活动造成了采样区表层土壤盐分、含水量和p H的空间分布多呈现不规则条带状格局.艾比湖湿地土壤以盐土为主,重度盐化土次之,土壤盐渍化日益严重.     

基于平均导数方法的声波方程频率域高阶正演

本文首先阐明了基于旋转坐标系的频率域正演算法只能适用于相同横纵向空间采样间隔的局限性,并发展了一种新的基于平均导数方法（average-derivative method,简称ADM）的25点有限差分格式来实现声波方程频率域高精度正演.这种基于平均导数方法的算法将声波频率域方程中空间导数项的差分近似表示为正交方向上5个网格点的加权平均形式,能适用于不同的横纵向空间采样间隔,因此能作为四阶声波频率域正演的一种统一格式,具有很好的适用性.通过优化方法求取空间导数项和加速度项的加权优化系数,从而使数值频散达到极小化,每个波长所需要的网格点数在1%的误差范围内仅为2.78个网格点数.本文通过引入完全匹配层（perfectly matched layer,简称PML）吸收边界条件,有效地消除了人工边界反射.数值模拟结果验证了本文25点ADM算法的有效性和准确性.     

A new tool for hillslope hydrologists: spatially distributed groundwater level and soilwater content measured using electromagnetic induction

New methods for obtaining and quantifying spatially distributed subsurface moisture are a high research priority in process hydrology. We use simple linear regression analyses to compare terrain electrical conductivity measurements (EC) derived from multiple electromagnetic induction (EMI) frequencies to a distributed grid of water‐table depth and soil‐moisture measurements in a highly instrumented 50 by 50 m hillslope in Putnam County, New York. Two null hypotheses were tested: H0₍₁₎, there is no relationship between water table depth and EC; H0₍₂₎, there is no relationship between soil moisture levels and EC. We reject both these hypotheses. Regression analysis indicates that EC measurements from the low frequency EM31 meter with a vertical dipole orientation could explain over 80% of the variation in water‐table depth across the test hillslope. Despite zeroing and sensitivity problems encountered with the high frequency EM38, EC measurements could explain over 70% of the gravimetrically determined soil‐moisture variance. The use of simple moisture retrieval algorithms, which combined EC measurements from the EM31 and EM38 meters in both their vertical and horizontal orientations, helped increase the r² coefficients slightly. This first hillslope hydrological analysis of EMI technology in this way suggests that it may be a promising method for the collection of a large number of distributed soilwater and groundwater depth measurements with a reasonable degree of accuracy. Copyright © 2003 John Wiley & Sons, Ltd.     

Electromagnetic induction prediction of soil salinity and groundwater properties in a Tunisian Saharan oasis

Abstract

Electromagnetic induction measurements (EM) were taken in a saline gypsiferous soil of the Saharan-climate Fatnassa oasis (Tunisia) to predict the electrical conductivity of saturated soil extract (ECe) and shallow groundwater properties (depth, Dgw, and electrical conductivity, ECgw) using various models. The soil profile was sampled at 0.2 m depth intervals to 1.2 m for physical and chemical analysis. The best input to predict the log-transformed soil salinity (lnECe) in surface (0–0.2 m) soil was the EMh/EMv ratio. For the 0–0.6 m soil depth interval, the performance of multiple linear regression (MLR) models to predict lnECe was weaker using data collected over various seasons and years (R _a ² = 0.66 and MSE = 0.083 dS m^-1) as compared to those collected during the same period (R _a ² = 0.97, MSE = 0.007 dS m^-1). For similar seasonal conditions, for the Dgw–EMv relationship, R ² was 0.88 and the MSE was 0.02 m for Dgw prediction. For a validation subset, the R ² was 0.85 and the MSE was 0.03 m. Soil salinity was predicted more accurately when groundwater properties were used instead of soil moisture with EM variables as input in the MLR.

Editor D. Koutsoyiannis; Associate editor K. Heal

Citation Bouksila, F., Persson, M., Bahri, A., and Berndtsson, R., 2012. Electromagnetic induction predictions of soil salinity and groundwater properties in a Tunisian Saharan oasis. Hydrological Sciences Journal, 57 (7), 1473–1486.     

Multi-frequency Electromagnetic Induction Survey for Archaeological Prospection: Approach and Results in Han Hangu Pass and Xishan Yang in China

This study presents the potential of multi-frequency electromagnetic induction (EMI) in archaeology. EMI is currently less employed for archaeological prospection with respect to other geophysical techniques. It is capable of identifying shallow subsurface relics by simultaneously measuring the apparent electrical conductivity (EC_a) and apparent magnetic susceptibility (MS_a). Moreover, frequency sounding is able to quantify the depths and vertical shapes of buried structures. In this study, EMI surveys with five frequencies were performed at two heritage sites with different geological conditions: Han Hangu Pass characterized by cinnamon soil and Xishan Yang by sandy loams. In the first site, high EC_a values were observed with variations in depth correlated to archaeological remains. Moreover, electromagnetic anomalies related to an ancient road and five kiln caves were identified. In the second site, an ancient tomb, indicating extremely low EC_a and high MS_a, was discovered. Its electromagnetic properties are attributed to the cavity and ferroferric oxides.     

Benthic community response to habitat variation: A case of study from a natural protected area,the Celestun coastal lagoon

Little information currently exists on spatial and temporal benthic community variations in tropical coastal lagoons. Here, the benthic community response to habitat variation in the Celestun coastal lagoon, northwest Yucatan peninsula, was seasonally examined during the 1994–1995 climatic cycle into a grid of 12 sampling sites distributed along the salinity gradient of the lagoon. Habitat variation was assessed through physical factors associated both to the water column (e.g. salinity) and the bottom sediment (e.g. sand, silt and clay fractions). The benthic community response was assessed through species diversity measures and abundance. Under the influence of climatic seasonality, variations in habitat conditions followed by changes in the benthic community characteristics were expected. Results from two-way ANOVAs showed that for the period of study, Celestun lagoon was more heterogeneous along the spatial axis of variability than along the temporal one. Multiple regression analysis showed that salinity was spatially the main factor influencing the benthic community characteristics. Temporally, the sediment characteristics were observed to exert significant effects on the species diversity characteristics but not on abundance. Other variables assessed (dissolved oxygen, pH, temperature and water column transparency) exhibited no significant covariance with species diversity and abundance. Since generated from historical data, these results have the potential to be useful as a benchmark to the establishment of monitoring programs in the light of the increasing anthropogenic pressure on the natural resources of the lagoon and surrounding coastal area.     

Optimal implicit staggered‐grid finite‐difference schemes based on the sampling approximation method for seismic modelling

We propose new implicit staggered‐grid finite‐difference schemes with optimal coefficients based on the sampling approximation method to improve the numerical solution accuracy for seismic modelling. We first derive the optimized implicit staggered‐grid finite‐difference coefficients of arbitrary even‐order accuracy for the first‐order spatial derivatives using the plane‐wave theory and the direct sampling approximation method. Then, the implicit staggered‐grid finite‐difference coefficients based on sampling approximation, which can widen the range of wavenumber with great accuracy, are used to solve the first‐order spatial derivatives. By comparing the numerical dispersion of the implicit staggered‐grid finite‐difference schemes based on sampling approximation, Taylor series expansion, and least squares, we find that the optimal implicit staggered‐grid finite‐difference scheme based on sampling approximation achieves greater precision than that based on Taylor series expansion over a wider range of wavenumbers, although it has similar accuracy to that based on least squares. Finally, we apply the implicit staggered‐grid finite difference based on sampling approximation to numerical modelling. The modelling results demonstrate that the new optimal method can efficiently suppress numerical dispersion and lead to greater accuracy compared with the implicit staggered‐grid finite difference based on Taylor series expansion. In addition, the results also indicate the computational cost of the implicit staggered‐grid finite difference based on sampling approximation is almost the same as the implicit staggered‐grid finite difference based on Taylor series expansion.     

Elastic modelling on a grid with vertically varying spacing1

We present a discrete modelling scheme which solves the elastic wave equation on a grid with vertically varying grid spacings. Spatial derivatives are computed by finite-difference operators on a staggered grid. The time integration is performed by the rapid expansion method. The use of variable grid spacings adds flexibility and improves the efficiency since different spatial sampling intervals can be used in regions with different material properties. In the case of large velocity contrasts, the use of a non-uniform grid avoids spatial oversampling in regions with high velocities. The modelling scheme allows accurate modelling up to a spatial sampling rate of approximately 2.5 gridpoints per shortest wavelength. However, due to the staggering of the material parameters, a smoothing of the material parameters has to be applied at internal interfaces aligned with the numerical grid to avoid amplitude errors and timing inaccuracies. The best results are obtained by smoothing based on slowness averaging. To reduce errors in the implementation of the free-surface boundary condition introduced by the staggering of the stress components, we reduce the grid spacing in the vertical direction in the vicinity of the free surface to approximately 10 gridpoints per shortest wavelength. Using this technique we obtain accurate results for surface waves in transversely isotropic media.     

基于平均导数优化方法的VTI介质频率空间域正演

本文提出了一种新的基于平均导数优化方法(average-derivative optimal method,简称ADM)的二维VTI介质qP波波动方程频率空间域二阶9点格式,这种新算法将二维VTI介质qP波波动方程中中心空间导数项的差分近似表示为正交方向上3个网格点的加权平均形式.通过最小二乘优化方法求取空间导数项和加速度项的加权优化系数从而使数值频散达到极小化,每个波长所需要的网格点数在1%的误差范围内仅为3.57个网格点数,而VTI介质常规9点差分格式在相同的误差范围内则需要约12个网格点数,新方法的计算精度明显提高.复杂BP2007 2D VTI海洋标准模型数值模拟结果也验证了本文VTI介质9点ADM算法的有效性和准确性.     

Inversion of multi-frequency electromagnetic induction data for 3D characterization of hydraulic conductivity

Electromagnetic induction (EMI) instruments provide rapid, noninvasive, and spatially dense data for characterization of soil and groundwater properties. Data from multi-frequency EMI tools can be inverted to provide quantitative electrical conductivity estimates as a function of depth. In this study, multi-frequency EMI data collected across an abandoned uranium mill site near Naturita, Colorado, USA, are inverted to produce vertical distribution of electrical conductivity (EC) across the site. The relation between measured apparent electrical conductivity (EC_a) and hydraulic conductivity (K) is weak (correlation coefficient of 0.20), whereas the correlation between the depth dependent EC obtained from the inversions, and K is sufficiently strong to be used for hydrologic estimation (correlation coefficient of ? 0.62). Depth-specific EC values were correlated with co-located K measurements to develop a site-specific ln(EC)–ln(K) relation. This petrophysical relation was applied to produce a spatially detailed map of K across the study area. A synthetic example based on EC_a values at the site was used to assess model resolution and correlation loss given variations in depth and/or measurement error. Results from synthetic modeling indicate that optimum correlation with K occurs at ~ 0.5 m followed by a gradual correlation loss of 90% at 2.3 m. These results are consistent with an analysis of depth of investigation (DOI) given the range of frequencies, transmitter–receiver separation, and measurement errors for the field data. DOIs were estimated at 2.0 ± 0.5 m depending on the soil conductivities. A 4-layer model, with varying thicknesses, was used to invert the EC_a to maximize available information within the aquifer region for improved correlations with K. Results show improved correlation between K and the corresponding inverted EC at similar depths, underscoring the importance of inversion in using multi-frequency EMI data for hydrologic estimation.     

Nitrogen over enrichment in subtropical Pearl River estuarine coastal waters: Possible causes and consequences

Hong Kong is surrounded by estuarine, coastal and oceanic waters. In this study, monthly averages over a 10 year time series of salinity, temperature, chlorophyll a (chl a), dissolved oxygen (DO), dissolved inorganic nitrogen (DIN), silicate (SiO₄) and orthophosphate (PO₄) at three representative stations around Hong Kong were used to examine if excess nitrogen in estuarine influenced waters is due to P limitation. The monthly distribution clearly shows the dominant influence of the seasonal change in river discharge in the Pearl River estuary and adjacent coastal waters. In winter, the river discharge is small and more oceanic waters are dominant and as a result, salinity is high, and chlorophyll and nutrients are low. In summer, when the river discharge is high, salinity decreases and nutrients increase. DIN is very high, reaching 100 μM in the estuary. This indicates over enrichment of nitrogen relative to P and consequently there is an excess of N in coastal waters of Hong Kong. P remains low (∼1 μM) and can potentially limit both phytoplankton biomass and N utilization which was demonstrated in field incubation experiments. P limitation would result in excess N being left in the estuarine influenced waters south of Hong Kong. Phosphate concentration is lower in the Pearl River estuary than in many other eutrophied estuaries. Therefore, this relatively low PO₄ concentration should be a significant factor limiting a further increase in the magnitude of algal biomass and in the degree of eutrophication in the Pearl River estuary. The export of the excess N offshore into the northern South China Sea may result in an increase in the size of the region that is P limited in summer.     

针对复杂地形的三种地震波走时算法及对比

复杂地形条件下地震波走时算法对于研究复杂地形地区的成像问题有着重要的意义.为了得到精度高且适应于复杂地形的走时算法,首先提出阶梯网格迎风差分法.然后将该方法与不等距网格有限差分法和混合网格线性插值法进行对比研究,得出如下结论:混合网格线性插值法的计算精度最高,但其计算效率最低;阶梯网格迎风差分法的计算精度最低,但其计算效率最高;不等距网格有限差分法的计算精度和计算效率均居中;而究竟选取哪种算法作为给定复杂地形模型的地震波走时算法,应该综合考虑地形的特点、所研究问题对计算精度及计算效率的要求等因素.最后通过一个计算实例验证了三种算法在面对复杂地形、近地表及地下复杂介质等复杂地质条件时均有很好的适应性和稳定性.     

Soil water content and salinity determination using different dielectric methods in saline gypsiferous soil / Détermination de la teneur en eau et de la salinité de sols salins gypseux à l'aide de différentes méthodes diélectriques

Abstract

Measurements of dielectric permittivity and electrical conductivity were taken in a saline gypsiferous soil collected from southern Tunisia. Both time domain reflectometry (TDR) and the new WET sensor based on frequency domain reflectometry (FDR) were used. Seven different moistening solutions were used with electrical conductivities of 0.0053–14 dS m^?1. Different models for describing the observed relationships between dielectric permittivity (K _a ) and water content (θ), and bulk electrical conductivity (EC _a ) and pore water electrical conductivity (EC _p ) were tested and evaluated. The commonly used K _a –θ models by Topp et al. (1980) and Ledieu et al. (1986) cannot be recommended for the WET sensor. With these models, the RMSE and the mean relative error of the predicted θ were about 0.04 m³ m^?3 and 19% for TDR and 0.08 m³ m^?3 and 54% for WET sensor measurements, respectively. Using the Hilhorst (2000) model for EC _p predictions, the RMSE was 1.16 dS m^?1 and 4.15 dS m^?1 using TDR and the WET sensor, respectively. The WET sensor could give similar accuracy to TDR if calibrated values of the soil parameter were used instead of standard values.     

Comparison of soil salinity and solute transport for different cultivated soil types in northeastern Egypt / Comparaison de la salinité du sol et du transport de solutés pour différents types de sols cultivés du nord-est de l'Egypte

Abstract

The soil salinity distribution and solute transport properties of three different soil types were investigated and compared within a project area in northeastern Egypt. For this purpose, dye tracer experiments and salinity sampling were carried out. The resulting salinity maps showed that the soil salinity in the cultivated western site of the project area is 8–10 times higher than that in the cultivated eastern site. However, the cultivated soil displayed significantly lower salinity with higher uniformity as compared to the uncultivated soil. The preferential flow phenomenon was less apparent in the cultivated soil. This is mainly due to tillage which disrupts the structure of the soil so that deep cracks are no longer connected to the soil surface. This reduces the risk for groundwater contamination through preferential flow. The study showed that careful and continuous monitoring of the salinity status is needed now and in the future.