超浅层顶管施工诱发地表沉降规律分析

随着社会化进程的推进,顶管法在各类城市地下管线的施工中得到广泛应用。超浅层顶管施工。绝大多数是在已建道路下进行的,施工时,易发生地表沉降,且沉降量很大,易破坏路面。为此,超浅层顶管施工对周围环境的影响已引起人们足够的重视,其施工及控制技术是目前迫切需要掌握的。利用有限差分软件FLAC3D对顶管施工过程中地表沉降进行模拟,旨在了解超浅层顶管施工引起的力学效应。对超浅层顶管施工引起的地表沉降作出预测,为采取措施减小地表沉降提供依据。     

Estimating soil salinity in Pingluo County of China using QuickBird data and soil reflectance spectra

Soil salinization is a worldwide environmental problem with severe economic and social consequences. In this paper, estimating the soil salinity of Pingluo County, China by a partial least squares regression (PLSR) predictive model was carried out using QuickBird data and soil reflectance spectra. At first, a relationship between the sensitive bands of soil salinity acquired from measured reflectance spectra and the spectral coverage of seven commonly used optical sensors was analyzed. Secondly, the potentiality of QuickBird data in estimating soil salinity by analyzing the correlations between the measured reflectance spectra and reflectance spectra derived from QuickBird data and analyzing the contributions of each band of QuickBird data to soil salinity estimation Finally, a PLSR predictive model of soil salinity was developed using reflectance spectra from QuickBird data and eight spectral indices derived from QuickBird data. The results indicated that the sensitive bands covered several bands of each optical sensor and these sensors can be used for soil salinity estimation. The result of estimation model showed that an accurate prediction of soil salinity can be made based on the PLSR method (R² = 0.992, RMSE = 0.195). The PLSR model's performance was better than that of the stepwise multiple regression (SMR) method. The results also indicated that using spectral indices such as intensity within spectral bands (Int1, Int2), soil salinity indices (SI1, SI2, SI3), the brightness index (BI), the normalized difference vegetation index (NDVI) and the ratio vegetation index (RVI) as independent model variables can help to increase the accuracy of soil salinity mapping. The NDVI and RVI can help to reduce the influences of vegetation cover and soil moisture on prediction accuracy. The method developed in this paper can be applied in other arid and semi-arid areas, such as western China.     

Study on founding of a residential–administrative complex in poor soil conditions in seismic prone region

This paper gives a brief presentation of the study on foundation of a residential business complex. The unfavourable geotechnical conditions of the site considered led to the need to improve the natural foundation soil. The most favourable and rational solution for providing safety and stability of structures was the combination of gravel and a sub-base. Computations were done as follows: analysis of the stress–strain state by using the parameters of the natural non-improved soil and analyses performed by using the parameters of the improved soil. The results from these analyses were used for analysis of the integral soil–structure system. Hence, complete information on the possibility for optimisation of the foundation structure was obtained.     

The use of 137Cs as a tracer in an erosion study in south limburg (the Netherlands) and the influence of chernobyl fallout

The ¹³⁷Cs radioactivity of soils was used as a tracer of soil erosion in a catchment in the Netherlands: 143 samples were analysed to map the ¹³⁷Cs redistribution using geostatistical interpolation methods. Caesium-137 activities on grassland are significantly higher than on arable land. Also, ¹³⁷Cs activities on waning slopes are higher and activities on steep slopes are lower. The soil erosion estimates, derived from the ¹³⁷Cs data, are used to validate the USLE erosion model. The recent Chernobyl nuclear accident also contributed to the ¹³⁷Cs activity. However, the Chernobyl input of ¹³⁷Cs, with a constant ratio of 1.765:1 to ¹³⁴Cs, cannot be used as a tracer of soil erosion. Because of the rapid decay of ¹³⁴Cs, we will not be possible to separate the sources of ¹³⁷Cs in the near future in areas significantly influenced by Chernobyl fallout and in these areas ¹³⁷Cs can no longer be used as a soil erosion tracer.     

Estimation of soil moisture status using near infrared reflectance

The use of a prototype near infrared reflectance meter for estimating the water content of soil is described. The instrument, developed from one used for estimating the water content of forage is based on the measurement of reflectance of infrared light emitted at wavelengths of 1450 nm, a strong water absorption band, and 1300 nm a weak water absorption band. Calibration curves of reflectance and reflectance ratio versus moisture content for pure sands and sand/clay mixes are presented. Problems associated with the measurement of moisture content using this technique on swelling soils are highlighted. The use of a modified form of this instrument for estimating soil moisture status in the field is discussed.     

A relook at NEH‐4 curve number data and antecedent moisture condition criteria

This paper investigates the variation of the popular curve number (CN) values given in the National Engineering Hand Book–Section 4 (NEH‐4) of the Soil Conservation Service (SCS) with antecedent moisture condition (AMC) and soil type. Using the volumetric concept, involving soil, water, and air, a significant condensation of the NEH‐4 tables is achieved. This leads to a procedure for determination of CN for gauged as well as ungauged watersheds. The rainfall‐runoff events derived from daily data of four Indian watersheds exhibited a power relation between the potential maximum retention or CN and the 5‐day antecedent rainfall amount. Including this power relation, the SCS‐CN method was modified. This modification also eliminates the problem of sudden jumps from one AMC level to the other. The runoff values predicted using the modified method and the existing method utilizing the NEH‐4 AMC criteria yielded similar results. Copyright © 2006 John Wiley & Sons, Ltd.     

Water balance modelling in lateritic terrain

An analytical approximate model for unsaturated flow in a spatially variable field, coupled with infiltration and evapotranspiration at the upper boundary and a fluctuating water-table at the lower boundary, has been developed. The unsaturated flow equations depend on parameterizations of θ(Φ) and K(Φ). They are based on the notion of a moving, discontinuous front. The field heterogeneity refers to saturated hydraulic conductivity only. Horizontal variability is considered, and the flow medium is approximated as a set of uncorrelated, vertically homogeneous columns. Expectations and variances obtained with this approach have been compared with observations of the field hydrological processes. Three important aspects of the hydrology in this lateritic terrain are rapid water-table response, Hortonian surface runoff generation and soil suction variability. The stochastic conceptualization used explains to a high degree these characteristics, although some limitations are demonstrated.     

Generating soil thickness maps by means of geomorphological-empirical approach and random forest algorithm in Wanzhou County,Three Gorges Reservoir

Soil thickness, intended as depth to bedrock, is a key input parameter for many environmental models. Nevertheless, it is often difficult to obtain a reliable spatially exhaustive soil thickness map in wide-area applications, and existing prediction models have been extensively applied only to test sites with shallow soil depths. This study addresses this limitation by showing the results of an application to a section of Wanzhou County (Three Gorges Reservoir Area, China), where soil thickness varies from 0 to ～40 m. Two different approaches were used to derive soil thickness maps: a modified version of the geomorphologically indexed soil thickness (GIST) model, purposely customized to better account for the peculiar setting of the test site, and a regression performed with a machine learning algorithm, i.e., the random forest, combined with the geomorphological parameters of GIST (GIST-RF). Additionally, the errors of the two models were quantified, and validation with geophysical data was carried out. The results showed that the GIST model could not fully contend with the high spatial variability of soil thickness in the study area: the mean absolute error was 10.68 m with the root-mean-square error (RMSE) of 12.61 m, and the frequency distribution residuals showed a tendency toward underestimation. In contrast, GIST-RF returned a better performance with the mean absolute error of 3.52 m and RMSE of 4.56 m. The derived soil thickness map could be considered a critical fundamental input parameter for further analyses.     

Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin,India

Drought is a natural phenomenon posing severe implications for soil, groundwater and agricultural yield. It has been recognized as one of the most pervasive global change drivers to affect the soil. Soil being a weakly renewable resource takes a long time to form, but it takes no time to degrade. However, the response of soil to drought conditions as soil loss is not manifested in the existing literature. Thus, this study makes a concerted effort to analyze the relationship between drought conditions and soil erosion in the middle sub-basin of the Godavari River in India. MODIS remote sensing data was utilized for driving drought indices during 2000–2019. Firstly, we constricted Temperature condition index (TCI) and Vegetation Condition Index (VCI) from Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI) derived from MODIS data. TCI and VCI were then integrated to determine the Vegetation Health Index (VHI). Revised Universal Soil Loss Equation (RUSLE) was utilized for estimating soil loss. The relationship between drought condition and vegetation was ascertained using the Pearson correlation. Most of the northern and southern watersheds experienced severe drought condition in the sub-basin during 2000–2019. The mean frequency of the drought occurrence was 7.95 months. The average soil erosion in the sub-basin was estimated to be 9.88 t ha^?1 year^?1. A positive relationship was observed between drought indices and soil erosion values (r value being 0.35). However, wide variations were observed in the distribution of spatial correlation. Among various factors, the slope length and steepness were found to be the main drivers of soil erosion in the sub-basin. Thus, the study calls for policy measures to lessen the impact of drought and soil erosion.     

The Energy Relationship between Ions and Soil Particles based on Wien Effect and Its Application in Soil Science

The interaction between ions and soil particles plays an important role in the mobilization and bioavailability of ions in soils, which is one of the main research areas of soil chemistry. The new method based on suspension Wien effect has been developed recently to determine the binding energy and adsorption energy between ions and soil particles. Compared with other methods on the basis of adsorption isotherm or ions activity, Wien effect method has more advantages including convenience and direct measurement. The term suspension Wien effect refers to the increase of electrical conductivity of suspension with increasing applied electrical field. In this review paper, we introduced the fundamentals of suspension Wien effect, the apparatus about the Wien effect measurement, and along with demonstrating their application to quantifying the particles-ions interactions for several systems of soils. Our studies indicated that divalent cations have larger binding energies and adsorption energies on soil particles than monovalent because of the electrostatic interaction. However, few studies about the interaction between Cr³⁺ and La³⁺ on soil particles showed that the binding energy and adsorption energy of trivalent cations are lower than those of divalent cations because of hydrolysis. Soil properties such as soil organic matter, soil pH, and iron oxides significantly affected the binding energy and adsorption energy of ions. Our results deepened our understanding about the non specific adsorption of ions in soil chemistry, and enlarged the research area of soil chemistry in fundamental and methodology.