Ground Penetrating Radar (GPR) Identification Method for Agricultural Soil Stratification in a Typical Mollisols Area of Northeast China

In order to achieve a rapid and accurate identification of soil stratification information and accelerate the development of smart agriculture,this paper conducted soil stratification experiments on agricultural soils in the Mollisols area of Northeast China using Ground Penetrating Radar(GPR)and obtained different types of soil with frequencies of 500 MHz,250 MHz,and 100 MHz antennas.The soil profile data were obtained for 500 MHz,250 MHz,and 100 MHz antennas,and the dielectric properties of each type of soil were analyzed.In the image processing procedure,wavelet analysis was first used to decompose the pre-processed radar signal and reconstruct the high-frequency information to obtain the reconstructed signal containing the stratification information.Secondly,the reconstructed signal is taken as an envelope to enhance the stratification information.The Hilbert transform is applied to the envelope signal to find the time-domain variation of the instantaneous frequency and determine the time-domain location of the stratification.Finally,the dielectric constant of each soil horizon is used to obtain the propagation velocity of the electromagnetic wave at the corresponding position to obtain the stratification position of each soil horizon.The research results show that the 500 MHz radar antenna can accurately delineate Ap/Ah,horizon and the absolute accuracy of the stratification is within 5 cm.The effect on the soil stratification below the tillage horizon is not apparent,and the absolute accuracy of the 250 MHz and 100 MHz radar antennas on the stratification is within 9 cm.The overwhelming majority of the overall calculation errors are kept to within 15%.Based on the three central frequency antennas,the soil horizon detection rate reaches 93.3%,which can achieve accurate stratification of soil profiles within 1 m.The experimental and image processing methods used are practical and feasible;however,the GPR will show a missed detection for soil horizons with only slight differences in dielectric properties.Overall,this study can quickly and accurately determine the information of each soil stratification,ultimately providing technical support for acquiring soil configuration information and developing smart agriculture.

A back analysis scheme for refined soil stratification based on integrating borehole and CPT data

Utilizing both borehole and Cone Penetration Testing(CPT)data in soil stratification helps to get more convincing soil stratification results.However,the soil classification results revealed by borehole(Unified Soil Classification System,USCS)and CPT tests(soil behavior type,SBT)are commonly not con-sistent.This study proposes a feasible solution to integrate the borehole and CPT data with the tree-based method.The tree-based method is naturally suitable for soil stratification tasks as it aims to divide the subsurface space into several clusters based on the similarities of the soil types.A novel boundary dic-tionary method is proposed to enhance the model performance on complex soil layer conditions.A prob-abilistic mapping matrix between the USCS-SBT system is built based on a collected municipal database with collocated borehole and CPT data.The optimal soil stratification results can be selected based on considering multiple borehole information and pruning the structure of trees.The structure of the trees can be optimized in a back analysis perspective with the Sequential Model-Based Global Optimization(SMBO)algorithm which aims to maximize the possibility of observing the borehole information based on the USCS-SBT probabilistic mapping matrix.The uncertainties of the optimal soil stratification results can be estimated based on a weighted Gini index method.The performance of the proposed method is validated based on a real case in New Zealand with a cross-validation method.The results indicate that the proposed method is robust and effective.

Soil carbon storage and stratification under different tillage/residue-management practices in double rice cropping system

The importance of soil organic carbon（SOC） sequestration in agricultural soils as climate-change-mitigating strategy has become an area of focus by the scientific community in relation to soil management.This study was conducted to determine the temporal effect of different tillage systems and residue management on distribution, storage and stratification of SOC, and the yield of rice under double rice（Oryza sativa L.） cropping system in the southern China.A tillage experiment was conducted in the southern China during 2005–2011, including plow tillage with residue removed（PT0）, plow tillage with residue retention（PT）, rotary tillage with residue retention（RT）, and no-till with residue retention on the surface（NT）.The soil samples were obtained at the harvesting of late rice in October of 2005, 2007 and 2011.Multiple-year residue return application significantly increased rice yields for the two rice-cropping systems; yields of early and late rice were higher under RT than those under other tillage systems in both years in 2011.Compared with PT0, SOC stocks were increased in soil under NT at 0–5, 5–10, 10–20, and 20–30 cm depths by 33.8, 4.1, 6.6, and 53.3%, respectively, in 2011.SOC stocks under RT were higher than these under other tillage treatments at 0–30 cm depth.SOC stocks in soil under PT were higher than those under PT0 in the 0–5 and 20–30 cm soil layers.Therefore, crop residues played an important role in SOC management, and improvement of soil quality.In the 0–20 cm layer, the stratification ratio（SR） of SOC followed the order NT〉RT〉PT〉PT0; when the 0–30 cm layer was considered, NT also had the highest SR of SOC, but the SR of SOC under PT was higher than that under RT with a multiple-year tillage practice.Therefore, the notion that conservation tillage lead to higher SOC stocks and soil quality than plowed systems requires cautious scrutiny.Nevertheless, some benefits associated with RT system present a greater potential for its adoption in view of the multiple-year environmental sustainability under double rice cropping system in the southern China.

Liquefaction proneness of stratified sand-silt layers based on cyclic triaxial tests

Most studies on liquefaction have addressed homogeneous soil strata using sand or sand with fine content without considering soil stratification.In this study,cyclic triaxial tests were conducted on the stratified sand specimens embedded with the silt layers to investigate the liquefaction failures and void-redistribution at confining stress of 100 kPa under stress-controlled mode.The loosening of underlying sand mass and hindrance to pore-water flow caused localized bulging at the sand-silt interface.It is observed that at a silt thickness of 0.2H(H is the height of the specimen),nearly 187 load cycles were required to attain liquefaction,which was the highest among all the silt thicknesses with a single silt layer.Therefore,0.2H is assumed as the optimum silt thickness(t_(opt)).The silt was placed at the top,middle and bottom of the specimen to understand the effect of silt layer location.Due to the increase in depth of the silt layer from the top position(capped soil state)to the bottom,the cycles to reach liquefaction(N_(cyc,L))increased 2.18 times.Also,when the number of silt layers increased from single to triple,there was an increase of about 880%in N_(cyc,L).The micro-characterization analysis of the soil specimens indicated silty materials transported in upper sections of the specimen due to the dissipated pore pressure.The main parameters,including thickness(t),location(z),cyclic stress ratio(CSR),number of silt layers(n)and modified relative density(D_(r,m)),performed significantly in governing the lique-faction resistance.For this,a multilinear regression model is developed based on critical parameters for prediction of N_(cyc,L).Furthermore,the developed constitutive model has been validated using the data from the present study and earlier findings.