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1.
《山地科学学报》2020,17(7):1636-1651
The soil carbon pool which is the sum of soil organic carbon(SOC) and soil inorganic carbon(SIC) is the second largest active store of carbon after the oceans and it is an important component of the global carbon cycle. Hence, accurate estimation of SOC and SIC as important carbon reservoirs in terrestrial ecosystems using fast, inexpensive and non-destructive methods is crucial for planning different climate change policies. The aim of the current research was to examine the effectiveness of Vis-NIR(visible and near-infrared spectroscopy: 350-2500 nm) and MIR(mid-infrared spectroscopy: 4000-400 cm~(-1)) to characterize and estimate soil organic matter(SOM) and carbonates as main components of soil carbon stocks in Juneqan, Charmahal va Bakhtiari, Iran. To do so, a total of 548 soil samples from this area were collected(October 2015) and analyzed in laboratory(August 2017). In order to develop models capable of predicting SOM and carbonates content, seven spectral preprocessing methods comprising Absorbance(Abs), De-trending(Det), Continuum removal(CR), Savitzky-Golay derivatives(SGD), standard normal variate transformation(SNV), multiplicative scatter correction(MSC) and Normalization by range(NBR) were conducted along with five multivariate methods including Random Forest(RF), Partial Least-Squares Regression(PLSR), Artificial Neural Network(ANN), Support Vector Machine(SVM) and Gaussian Process Regression(GPR). The content of carbonates caused spectral reflectance intensity to augment on several ranges of spectrum and strong absorption feature at 2338 nm in the Vis-NIR and 714, 850, 870, 1796, 2150 and 2510 cm~(-1) in the MIR spectra range. SOM absorbed energy in several ranges, but also showed specific peaks in MIR. Both facts are associated with the structure of carbonates and SOM and its interaction with energy. The best combination of preprocessing and calibration models for carbonates quantification in Vis-NIR spectra was Det/PLSR(R~2= 0.74, RPD= 2.19, RMSE= 6.45). For SOM, it was Det/PLSR(R~2= 0.82, RPD= 2.41, RMSE= 0.75). The Det/RF(R~2= 0.87, RPD= 2.44, RMSE= 0.66) for the quantification of SOM and MSC/RF(R~2= 0.84, RPD= 2.84, RMSE= 5.50) for carbonates in MIR spectra range showed the greatest results. The stronger occurrence of spectral bands in MIR as well as the specificity of the absorption features indicated that this range produced better predictions. The obtained results highlighted the significant role of soil spectroscopy technique in predicting SOC and soil carbonates as key components of soil carbon stocks in the study area. Therefore, this technique can be used as a more cost-effective, time saving and nondestructive alternative to traditional methods of soil analysis.  相似文献   

2.
Soil organic matter(SOM) is an important parameter related to soil nutrient and miscellaneous ecosystem services. This paper attempts to improve the performance of traditional partial least square regression(PLSR) model by considering the spatial autocorrelation and soil forming factors. Surface soil samples(n = 180) were collected from Honghu City located in the middle of Jianghan Plain, China. The visible and near infrared(VNIR) spectra and six environmental factors(elevation, land use types, roughness, relief amplitude, enhanced vegetation index, and land surface water index) were used as the auxiliary variables to construct the multiple linear regression(MLR), PLSR and geographically weighted regression(GWR) models. Results showed that: 1) the VNIR spectra can increase about 39.62% prediction accuracy than the environmental factors in predicting SOM; 2) the comprehensive variables of VNIR spectra and the environmental factors can improve about 5.78% and 44.90% relative to soil spectral models and soil environmental models, respectively; 3) the spatial model(GWR) can improve about 3.28% accuracy than MLR and PLSR. Our results suggest that the combination of spectral reflectance and the environmental variables can be used as the suitable auxiliary variables in predicting SOM, and GWR is a promising model for predicting soil properties.  相似文献   

3.
Soil conservation practices can greatly affect the soil erosion process, but limited information is available about its influence on the particle size distribution(PSD) of eroded sediment, especially under natural rainfall. In this study, the runoff, sediment yields, and effective/ultimate PSD were measured under two conventional tillage practices, downhill ridge tillage(DT) and plat tillage(PT) and three soil conservation practices, contour ridge tillage(CT), mulching with downhill ridge tillage(MDT), and mulching with contour ridge tillage(MCT) during 21 natural rainfall events in the lower Jinsha River. The results showed that(1) soil conservation practices had a significant effect on soil erosion. The conventional tillage of DT caused highest runoff depth(0.58 to 29.13 mm) and sediment yield(0.01 to 3.19 t hm-2). Compared with DT, the annual runoff depths and sediment yields of CT, MDT and MCT decreased by 12.24%-49.75% and 40.79%-88.30%, respectively.(2) Soil conservation practices can reduce the decomposition of aggregates in sediments. The ratios of effective and ultimate particle size(E/U) of siltand sand-sized particles of DT and PT plots were close to 1, indicating that they were transported as primary particles, however, values lower/greater than 1 subject to CT, MDT and MCT plots indicated they were transported as aggregates. The ratios of E/U of claysized particles were all less than 1 independently of tillage practices.(3) The sediments of soil conservation practices were more selective than those of conventional tillage practices. For CT, MDT and MCT plots, the average enrichment ratios(ERs) of clay, silt and sand were 1.99, 1.93 and 0.42, respectively, with enrichment of clay and silt and depletion of sand in sediments. However, the compositions of the eroded sediments of DT and PT plots were similar to that of the original soil. These findings support the use of both effective and ultimate particle size distributions for studying the size selectivity of eroded sediment, and provide a scientific basis for revealing the erosion mechanism in the purple soil area of China.  相似文献   

4.
Soil macronutrients(i.e. nitrogen(N), phosphorus(P), and potassium(K)) are important soils components and knowing the spatial distribution of these parameters are necessary at precision agriculture. The purpose of this study was to evaluate the feasibility of different methods such as artificial neural networks(ANN) and two geostatistical methods(geographically weighted regression(GWR) and cokriging(CK)) to estimate N, P and K contents. For this purpose, soil samples were taken from topsoil(0–30 cm) at 106 points and analyzed for their chemical and physical parameters. These data were divided into calibration(n = 84) and validation(n = 22). Chemical and physical variables including clay, p H and organic carbon(OC) were used as auxiliary soil variables to estimate the N, P and K contents. Results showed that the ANN model(with coefficient of determination R~2 = 0.922 and root mean square error RMSE = 0.0079%) was more accurate compared to the CK model(with R~2 = 0.612 and RMSE = 0.0094%), and the GWR model(with R~2 = 0.872 and RMSE = 0.0089%) to estimate the N variable. The ANN model estimated the P with the RMSE of 3.630 ppm, which was respectively 28.93% and 20.00% less than the RMSE of 4.680 ppm and 4.357 ppm from the CK and GWR models. The estimated K by CK, GWR and ANN models have the RMSE of 76.794 ppm, 75.790 ppm and 52.484 ppm. Results indicated that the performance of the CK model for estimation of macro nutrients(N, P and K) was slightly lower than the GWR model. Also, the accuracy of the ANN model was higher than CK and GWR models, which proved to be more effective and reliable methods for estimating macro nutrients.  相似文献   

5.
The purpose of this study was to assess the effect of long-term cultivation and water erosion on the soil organic carbon （OC） in particle-size fractions. The study site is located at Nihegou Watershed in the Southern Loess Plateau, China. The soil at this site is loess with loose and silty structure, and contains macropores. The results showed that the OC concentrations in sediments and in the particle-size fractions of sediments were higher than those in soils and in the particle-size fractions of soils. The OC concentration was highest in the clay particles and was lowest in the sand particles. Clay particles possessed higher OC enrichment ability than silt and sand particles. The proportions of OC in the silt fractions of soil and sediment were the highest （mean value of 53.87% and 58.48%, respectively）, and the total proportion of OC in the clay and silt fractions accounted for 96% and 98% of the total OC in the soil and sediment, respectively. The loss of OC was highest in silt particles, with an average value of 0.16 Mg ha^-1 y^-1, and was lowest in the sand （0.003 Mg ha^-1 y^-l）. This result suggests that the fine particle-size fraction in the removed sediment may be an important indicator to assess soil OC losses.  相似文献   

6.
To accurately characterize the shear wave speed dispersion of seafloor sediments in the northern South China Sea,five types of sediments including silty clay,clayey silt,sandy silt,silty sand,and clayey sand were selected,on which the measurements of the shear wave speed at 0.5-2.0 kHz and related physical properties were performed.Results reveal that the shear wave speed of sediments increases as the frequency increases,and the dispersion enhanced in the sediments in the order of silty clay,clayey silt,sandy silt,silty sand,and clayey sand,at a linear change rate of 0.727,0.787,3.32,4.893,and 6.967 m s?1 kHz?1,respectively.Through regression analysis,linear and logarithmic regression equations for the correlation between shear wave speed and frequency were established for each sediment type and the determination coefficients of regression equations indicate that the correlation is closer to a logarithmic relationship.The Grain-Shearing(GS)and Biot-Stoll models were used to calculate the shear wave speed dispersion of the five sediment types,and the comparison between theoretical prediction and measured results of shear wave speeds shows that the GS model can more accurately describe the shear wave speed dispersion characteristics of these sediments in the frequency band of 0.5-2.0 kHz.In the same band,the predictions obtained by using the Biot-Stoll model are significantly different from the measured data.  相似文献   

7.
Soil samples from several forest areas in China were analyzed by X-ray powder diffractometry after mineral separation and enrichment. The density gradient separation method with sequential extraction by acetone-methylene iodide mixtures was applied for the separation of fine sand fraction of soil samples. The clay fraction (< 2μm) was separated from silt fraction of soil samples prior to examination. Mineral components in some fine sand and clay samples were compared, and their weathering potentiality and buffering capacity against acidic precipitation were discussed.  相似文献   

8.
为研究地埋管换热器在不同岩性地层的换热情况,在鲁西黄河冲洪积平原、山前冲洪积平原和低山丘陵区进行了以粉土、粉质粘土、细砂,粘土、粉质粘土、中粗砂,灰岩和花岗岩为研究对象的热响应试验,初步试验结果表明:每延米换热量(W/m)和平均热导率(W/m·k)花岗岩灰岩粉质粘土、中粗砂粉土、粉细砂。在岩溶地下水富水性强,径流速度快的地段灰岩平均热导率花岗岩。此项研究结果可为不同岩性地层浅层地温能开发利用工程地埋管换热器类型的选择,浅层地温能评价和开发利用提供基础数据。  相似文献   

9.
Soils in the Knersvlakte are particularly prone to crusting and have lower inherent infiltrability than other soils across western southern Africa. Micromorphological techniques were used to examine the structure and porosity of soil crusts in the Knersvlakte to ascertain why crusting is so intense in this region. Quantile regression using boundary lines was employed to examine the relationships between infiltrability and soil properties for all samples （n = 67）. This analysis showed that infiltrability is potentially maximal at low water- dispersible ＇clay plus silt＇ content and low silt content （r^2 = 0.72 and 0.64; respectively, n = 67） （Figure 2）. The strength of crusts, pH, EC, clay mineralogy, and water-dispersible clay, silt and ＇clay plus silt＇ content were compared, and a pore analysis using optical microscopy was undertaken on images of six soil thin sections （n = 6） （circular and parallel polarizers）. Pore analysis was further undertaken on five horizontal slices of equal dimensions taken through each soil thin section. The porosity samples with low infiltrability （〈 100 mm·hr^-1, n = 4） had greater crust strength, lower porosity （both total and in the least porous slice） and greater water-dispersible ＇day plus silt＇ and silt content than the porosity samples with high infiltrability （〉 100mm·hr^-1, n = 2）. The porosity samples with low infiltrability showed a trend of lower pH and greater water dispersible clay percentage. Porosity varied within the porosity samples due to the presence of dense clay/silt bands （〈 0.5 mm in width） with relatively few air vesicles. The porosity samples with horizontal slices of low porosity （but large numbers of air vesicles） had low infiltrability, while those without slices of low porosity （and relatively few air vesicles） had high infiltrability. We conclude that the intense crusting and resultant low infiltrability of soils in the Knersvlakte appears to be related to the formation of thin, dense clay/silt bands in the pedoderm.  相似文献   

10.
人类活动对表层耕地土壤有机碳（Soil Organic Carbon, SOC）影响强烈,但目前大范围复杂地貌地形区的耕地SOC数字制图对人为因素的空间刻画不足。本文以福建省西部耕地为研究对象,基于Sentinel-2/MSI时间序列数据提取轮作模式分类信息（Crop Rotation, CR）,以及可反映轮作模式信息的植被特征变换变量（Harmonic Analysis of Time Series, HANTS）,分别作为农业活动定性和定量因子,将常规气候和地形因子作为自然环境因子,并对不同类型环境变量进行组合（气候+地形、气候+地形+轮作模式、气候+地形+HANTS变量、气候+地形+轮作模式+HANTS变量）。基于随机森林模型（Random Forest, RF）对不同环境变量组合驱动的耕地表层SOC空间预测精度进行对比分析,探索以轮作模式为例的农业活动因子提高耕地表层SOC数字制图精度的可能性。结果表明,同时加入两种农业活动因子的RF模型表现最佳,其模型预测精度相较于纯自然环境变量驱动的模型有明显提高（R2提高了89.47%,RMSE和MAE分别下降了10.66%和12.05%）。轮作模式类型（CR）和HANTS变量两种农业活动因子均被保留参与建模,尤其是轮作模式类型显著影响耕地SOC,在最佳模型的环境变量重要性中排序第四。由此可见,轮作模式相关农业活动因子可有效提高耕地SOC空间预测精度。在所有RF模型中,年降水量（Annual Rainfall, Rainfall）的重要性排名都是第一位。通过最佳模型反演得出该区耕地土壤有机碳均值为18.22±2.99 g/kg,范围为8.25~30.69 g/kg,双季稻和烟稻种植区域SOC含量高于稻菜种植区域。研究结果为复杂地貌地形区耕地土壤有机碳协同变量的更新提供了新的思路。  相似文献   

11.
This study aims to provide a predictive vegetation mapping approach based on the spectral data, DEM and Generalized Additive Models (GAMs). GAMs were used as a prediction tool to describe the relationship between vegetation and environmental variables, as well as spectral variables. Based on the fitted GAMs model, probability map of species occurrence was generated and then vegetation type of each grid was defined according to the probability of species occurrence. Deviance analysis was employed to test the goodness of curve fitting and drop contribution calculation was used to evaluate the contribution of each predictor in the fitted GAMs models. Area under curve (AUC) of Receiver Operating Characteristic (ROC) curve was employed to assess the results maps of probability. The results showed that: 1) AUC values of the fitted GAMs models are very high which proves that integrating spectral data and environmental variables based on the GAMs is a feasible way to map the vegetation. 2) Prediction accuracy varies with plant community, and community with dense cover is better predicted than sparse plant community. 3) Both spectral variables and environmental variables play an important role in mapping the vegetation. However, the contribution of the same predictor in the GAMs models for different plant communities is different. 4) Insufficient resolution of spectral data, environmental data and confounding effects of land use and other variables which are not closely related to the environmental conditions are the major causes of imprecision.  相似文献   

12.
ＩＮＴＲＯＤＵＣＴＩＯＮＯｎｅｏｆｔｈｅｍｏｓｔｅｘｔｅｎｓｉｖｅｓｈｅｌｖｅｓｏｆｔｈｅｗｏｒｌｄｌｙｉｎｇｗｉｔｈｉｎｔｈｅｓｏｕｔｈｅｒｎｐａｒｔｏｆｔｈｅＳｏｕｔｈＣｈｉｎａＳｅａｉｓｔｈｅ1850000ｋｍ2ＳｕｎｄａＳｈｅｌｆｌｏｃａｔｅｄｂｅｔｗｅｅｎｔｈｅｔｈｒｅｅｌａｒｇｅｉｓｌａｎｄｓｏｆＳｕｍａｔｒａ,Ｂｏｒｎｅｏ,ＪａｖａａｎｄｍａｉｎｌａｎｄＡｓｉａ(ＬａＦｏｎｄ,1966).ＴｈｅｎｏｒｔｈｅｒｎｐａｒｔｏｆｔｈｅＳｕｎｄａＳｈｅｌｆｉｓｓｅｐａｒａｔｅｄｆｒｏｍｔｈｅＪａｖａＳｅａｓ…  相似文献   

13.
Pakistani marine waters are under an open access regime.Due to poor management and policy implications,blind fishing is continued which may result in ecological as well as economic losses.Thus,it is of utmost importance to estimate fishery resources before harvesting.In this study,catch and effort data,1996-2009,of Kiddi shrimp Parapenaeopsis stylifera fishery from Pakistani marine waters was analyzed by using specialized fishery software in order to know fishery stock status of this commercially important shrimp.Maximum,minimum and average capture production of P.stylifera was observed as 15 912 metric tons(mt)(1997),9 438 mt(2009) and 11 667 mt/a.Two stock assessment tools viz.CEDA(catch and effort data analysis) and ASPIC(a stock production model incorporating covariates) were used to compute MSY(maximum sustainable yield) of this organism.In CEDA,three surplus production models,Fox,Schaefer and Pella-Tomlinson,along with three error assumptions,log,log normal and gamma,were used.For initial proportion(IP) 0.8,the Fox model computed MSY as 6 858 mt(CV=0.204,R~2=0.709) and 7 384 mt(CV=0.149,R~2=0.72) for log and log normal error assumption respectively.Here,gamma error produced minimization failure.Estimated MSY by using Schaefer and Pella-Tomlinson models remained the same for log,log normal and gamma error assumptions i.e.7 083 mt,8 209 mt and 7 242 mt correspondingly.The Schafer results showed highest goodness of fit R~2(0.712) values.ASPIC computed MSY,CV,R~2,F_(MSY)and B_(MSY) parameters for the Fox model as 7 219 mt,0.142,0.872,0.111 and 65 280,while for the Logistic model the computed values remained 7 720 mt,0.148,0.868,0.107 and 72 110 correspondingly.Results obtained have shown that P.stylifera has been overexploited.Immediate steps are needed to conserve this fishery resource for the future and research on other species of commercial importance is urgently needed.  相似文献   

14.
Partial drainage often occurs during piezocone penetration testing on Yellow River Delta silt because of its intermediate physical and mechanical properties between those of sand and clay.Yet,there is no accurate understanding for the range of penetra-tion rates to trigger the partial drainage of silt soils.In order to fully investigate cone penetration rate effects under partial drainage condi-tions,indoor 1 g penetration model tests and numerical simulations of cavity expansion at variable penetration rates were carried out on the Yellow River Delta silt.The boundary effect of the model tests and the variation of key parameters at the different cavity ex-pansion rates were analyzed.The 1 g penetration model test results and numerical simulations results consistently indicated that the penetration rate to trigger the partially drainage of typical silt varied at least three orders of magnitude.The numerical simulations also provide the reference values for the penetration resistance corresponding to zero dilation and zero viscosity at any given normalized penetration rate for silt in Yellow River Delta.These geotechnical properties can be used for the design of offshore platforms in Yel-low River Delta,and the understanding of cone penetration rate effects under the partially drained conditions would provide some technical support for geohazard evaluation of offshore platforms.  相似文献   

15.
The seabed of the Yellow River Delta is formed by the rapid deposition of sediments from the Yellow River. Recent researches have shown that the geological hazards in the Yellow River Delta are mainly related to the liquefaction of silty seabed under cyclic loading. In this paper, based on the theory of Stokes Viscous Principle, a self-design dragging ball apparatus was used to study the fluid characteristics of liquefied and post-liquefied silt more thoroughly. Wave flume and shaking table were used to apply wave loads and vibration loads. The pore pressure, earth pressure, and moving parameters of the dragging ball were recorded during tests. The effect of cyclic loads and excess pore pressure ratio on viscosity of silty soil is discussed. The constitutive model of flow characteristics of liquefied silt is also established. The results indicate that the apparent viscosity of silty soil is much higher than sand. Cyclic loads accelerated the process of silt liquefaction, resulting in the decrease in apparent viscosity. The excess pore pressure ratio (ru) has effect on silt liquefaction. When the soil had not reached the completely liquefied state (ru < 1), the apparent viscosity decreased with the increase of excess pore pressure ratio; when the soil had reached the completely liquefied state (ru = 1), the shear stress decreased with the increase of strain rate. It was determined that silty soil characterized by shear thinning can be viewed as a type of non-Newtonian fluid. The equation of the shear stress and shear strain rates was established by fitting the test data.  相似文献   

16.
Gravelly soils are made up of gravel, sand, silt and clay. They are widely used in engineering applications such as rock-fill dams with clay cores, which are the main researches at present. The strength and mechanical properties of the gravelly soils are affected by the content of coarse grain, fine particles, and their adhesive states. These Properties can be verified by laboratory unconsolidated undrained triaxial tests with grain size less than 5 mm and by large scale direct-shear tests with original grain content. Fine particles of the loose gravelly slopes are released under rainfalls, alternated the structures and mechanical properties, even affected the slope stability. There are a series of large scale direct-shear tests with different coarse grain contents to study the influence of fine particles releasing and migration, results showed the strength behavior of the gravelly soils were affected by the coarse grain content （5） and the inflection coarse grain contents. In order to study the erosion features of the gravelly soil slopes on rainfall conditions and the slopes stability alteration, we had carried out one sort of artificial rainfall local and model experiments, the runoff sediment contents were monitored during the experiments. Result showed that the shapes of the slopes surface transformed periodically, runoff sediment contents were divided into five phases according to the experiment phenomena, runoff sediment contents maintained downtrend during the rain time and the downtrend was obviouslyinterpreted by one descend belt no matter the rainfall intensity and the slope angels. Particle size analysis released the deposit on the slope surface lost almost all of the clay, most of the silt and sand after the experiments, this meant the fine particles releasing, migration and accumulation process on condition of rainfall resulted in the instability factor of the slopes even induced landslide or debris flow.  相似文献   

17.
Correlation, multiple regression, and path analyses were used to investigate the relationships between body weight and three other morphological traits in juvenile Japanese sea cucumbers Apostichopus japonicus. We measured live body weight(BW), body length(BL), numbers of papillae(NP), and numbers of tube feet(NF) at 60, 80, 100, and 130 days post-hatching(dph). We calculated path correlation coe cients, correlation indices( R~2), and coe cients of determination with BW as the dependent variable and the other morphological traits as independent variables. The coe cient of variation for BW was high across all age groups, and all measured morphological traits were significantly correlated( P 0.01). BL had the greatest direct ef fect on BW across all age groups(60 dph, 0.526; 80 dph, 0.404; 100 dph, 0.620;and 130 dph, 0.681), while NF had the greatest indirect ef fect on BW across all age groups(60 dph, 0.528;80 dph, 0.452; 100 dph, 0.666; and 130 dph, 0.603). Regression analyses between morphological traits and BW indicated that R 2 was greater than 0.85 only in the 100-dph specimens. The indirect ef fects of the other measured morphological traits on BW were age-dependent. The optimal regression equations,as determined with stepwise regression, were, for 60-dph specimens: BW_(60)=10~((-3.04+0.092 BL+0.014 NP+0.014 NF))( R~2 =0.632); for 80-dph specimens: BW _(80)=10~((-3.035+0.056 BL+0.017 NP+0.02 NF))( R~2 =0.686); for 100-dph specimens:BW_(100) =10~((-3.742+0.069 BL+0. 633*l g( NP)+0. 464*l g( NF)))( R~2 =0.893); and for 130-dph specimens: BW_(130)=10~((-2.472+0.065 BL+0.012 NP))( R~2 =0.774). Our work clarified the correlation between various morphological traits and body weight of a commercially-important sea cucumber species( A. japonicus). Our predictive models for body weight might be useful for the aquaculture and selective breeding of A. japonicus. These models might also provide theoretical support for the indirect selection of traits that are di cult to select directly.  相似文献   

18.
《山地科学学报》2020,17(9):2179-2202
Residual soils are weathering products of rocks that are commonly found under unsaturated conditions. The properties of residual soils are a function of the degree of weathering. A series of index properties, engineering properties and geophysics survey examinations were performed on residual soils from two major geological formations in Iran. In the present research, the index properties of residual soils in the south of Mashhad city in Iran are investigated.Natural and artificial trenches were analyzed for evaluating the weathering profiles and collecting soil samples. Disturbed and undisturbed samples were obtained from each of the soil profile horizons resulting from weathering of different parent rocks.Subsequently, physical properties and mechanical properties of the soil samples were determined in accordance with ASTM standards. Also, the mineralogical composition, chemistry, and texture of the soil were evaluated in 51 profiles. The field observations showed the difference in the weathering profile of residual soils deposited on various rocks(igneous, sedimentary, and metamorphic). These profiles mainly consisted of two horizons includingresidual soil on top and saprolite at the bottom. The results of laboratory tests and geotechnical data showed that the properties of residual soil samples change by depth. Moreover, depending on the type of origin rock, the properties are different in various types of residual soils. In most of the samples, the moisture content of soil horizons was also increased by depth. Based on the unified soil classification(USCS), the soils of the upper horizons appeared to be classified as ML(Lean silt) and CL(Lean clay) while the soils of the lower horizons(saprolite zone) fall in SC(clayey sand), SM(silty sand), and SW(wellgraded sand) classes. Moreover, the results demonstrated that the particle size of the soil was increased by depth. Comparison of results of the geotechnical tests showed that properties of residual soils are changed by variations of depth, weathering level, and type of parent rock. Considering the concentration of the number of lines and the concentration of the points of intersection, the length and dimension fractal of lineaments in the southeastern part of the study area, it is evident that this zone possesses weathering severity and soil thickness. Fieldwork data from this zone have also verified the severity of weathering conditions. The analysis of lineaments trends in different parts of the study area indicated that the lineaments with the NW-SE trend have a strong effect on weathering development. The weathering depth depends on the orientation of bedding joints with respect to the slope in the study area. Slope inclination and soil thickness are controlled by weathering and erosion processes.  相似文献   

19.
Timely monitoring and early warning of soil salinity are crucial for saline soil management. Environmental variables are commonly used to build soil salinity prediction model. However, few researches have been done to summarize the environmental sensitive variables for soil electrical conductivity(EC) estimation systematically. Additionally, the performance of Multiple Linear Regression(MLR), Geographically Weighted Regression(GWR), and Random Forest regression(RFR) model, the representative of current main methods for soil EC prediction, has not been explored. Taking the north of Yinchuan plain irrigation oasis as the study area, the feasibility and potential of 64 environmental variables, extracted from the Landsat 8 remote sensed images in dry season and wet season, the digital elevation model, and other data, were assessed through the correlation analysis and the performance of MLR, GWR, and RFR model on soil salinity estimation was compared. The results showed that: 1) 10 of 15 imagery texture and spectral band reflectivity environmental variables extracted from Landsat 8 image in dry season were significantly correlated with soil EC, while only 3 of these indices extracted from Landsat 8 image in wet season have significant correlation with soil EC. Channel network base level, one of the terrain attributes, had the largest absolute correlation coefficient of 0.47 and all spatial location factors had significant correlation with soil EC. 2) Prediction accuracy of RFR model was slightly higher than that of the GWR model, while MLR model produced the largest error. 3) In general, the soil salinization level in the study area gradually increased from south to north. In conclusion, the remote sensed imagery scanned in dry season was more suitable for soil EC estimation, and topographic factors and spatial location also play a key role. This study can contribute to the research on model construction and variables selection for soil salinity estimation in arid and semiarid regions.  相似文献   

20.
In the current study, the efficiency of Wavelet-based Least Square Support Vector Machine(WLSSVM) model was examined for prediction of daily and monthly Suspended Sediment Load(SSL) of the Mississippi River. For this purpose, in the first step, SSL was predicted via ad hoc LSSVM and Artificial Neural Network(ANN) models; then,streamflow and SSL data were decomposed into subsignals via wavelet, and these decomposed sub-time series were imposed to LSSVM and ANN to simulate discharge-SSL relationship. Finally, the ability of WLSSVM was compared with other models in multistep-ahead SSL predictions. The results showed that in daily SSL prediction, LSSVM has better outcomes with Determination Coefficient(DC)=0.92 than ad hoc ANN with DC=0.88. However unlike daily SSL, in monthly modeling, ANN has a bit accurate upshot.WLSSVM and wavelet-based ANN(WANN) models showed same consequences in daily and different in monthly SSL predictions, and adding wavelet led to more accuracy of LSSVM and ANN. Furthermore,conjunction of wavelet to LSSVM and ANN evaluated via multi-step-ahead SSL predictions and, e.g.,DC LSSVM=0.4 was increased to the DC WLSSVM=0.71 in 7-day ahead SSL prediction. In addition, WLSSVM outperformed WANN by increment of time horizon prediction.  相似文献   

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