Inversion Of Soil Water Content By Using Apparent Electrical Conductivity And Its 3D Visualization

Soil profile moisture information is an important reference for the implementation of irrigation volume in cotton fields with under-membrane drip irrigation in South Xinjiang,and it is also an important basis for developing reasonable irrigation strategies in cotton fields.How to obtain soil profile moisture information in a low-cost,rapid and non-destructive way in arid and non-arid areas,and accordingly to carry out 3D visualization and spatio-temporal variability study of soil profile moisture content,has become a hot spot and difficult research point in the academic soil science.In this thesis,we model and invert the soil profile moisture information at multiple depths by using the apparent conductivity data acquired by the geodetic conductivity meter EM38-MK2 in a typical machine-picked cotton field in Alar,South Xinjiang as the study area.Based on the soil apparent conductivity data collected by EM38-MK2 and in situ simultaneous collection of water content data of soil profile samples at multiple depths,multiple linear regression,ordinary kriging interpolation method and 3D inverse distance weight interpolation method were used to carry out accurate interpretation of soil water content information in the field,3D visualization of soil moisture content and distribution map of irrigation volume at field scale in cotton fields with under-film drip irrigation The research work includes the following three aspects The main research work includes the following three aspects.（1）Multi-temporal variation of soil moisture in cotton fields based on electromagnetic induction dataIn April,the coefficient of determination（R2）and the relative analytical error（RPD）of the 60-80 cm inversion model were the smallest in the same period,and the model stability and prediction ability were weak.After the last drip irrigation（August 25）,the R2 and RPD of the 60-80 cm inversion model were 0.89and 2.81,respectively,which were the highest in the same period,and the root mean square error RMSE and mean relative error MRE were 1.21%and 1.21%,respectively.The R2 and RPD of the inversion model for the apparent conductivity of 20-40 cm soil layer in October were the highest in the same period,and the model stability and prediction ability were stronger.The single-period model was better than the full-period model,with the R2 of the single-period model ranging from 0.62 to 0.80 and the R2 of the full-period model ranging from 0.22 to 0.54.The RPD comparison showed that the full-period model for each soil layer was inferior to the corresponding soil layer model for the single period,indicating that the predictive ability of the full-period model was inferior to that of the single-period model.The predicted soil water content and coefficient of variation decreased with increasing soil depth in April,July and October,and the predicted soil water content increased with increasing soil depth in September;except for the predicted water content data of 20-40 cm in October,which were close to normal distribution,the kurtosis of each soil layer in each period was far from 3 and did not conform to normal distribution,which conformed to normal distribution after logarithmic transformation.（2）Study on the three-dimensional spatial and temporal variability of soil moisture in cotton fields with under-membrane drip irrigation based on electromagnetic induction dataThe multi-temporal study of soil water dynamics in the field in the arid zone of South Xinjiang is beneficial to the formulation of reasonable irrigation methods and strategies.In this study,the characteristics of rapid,efficient and nondestructive acquisition of soil apparent conductivity by electromagnetic induction technology were used to establish a soil apparent conductivity inversion soil water content model in combination with indoor water content analysis of in situ soil samples;a multiple linear regression model predicting soil water content in four periods was used as the data source,and a three-dimensional inverse distance weight interpolation method was used to map the three-dimensional distribution of soil water content.The results showed that the apparent soil conductivity could invert the soil water content;the accuracy of the inverse model at the same depth of soil layer varied slightly in each period,among which the inverse model from 0 to 20 cm had the least fluctuation and maintained between 0.72 and 0.79.Under the influence of frequent activities of cotton roots,the inversion models of 20～40 cm and 40～60 cm in the root layer showed a larger variation in R2 compared with the inversion model of 0～20 cm in the surface layer,which ranged from 0.57 to 0.80.Under the influence of the high and low groundwater level,the R2of the non-root layer 60～80cm and 80～100cm models basically conformed to the characteristics of floating changes in groundwater level,i.e.,the R2 of the model increased when the water level rose.The three-dimensional distribution map of soil water content visualizes the high and low soil water content and its distribution in each period.In the non-irrigated period,the bottom soil water can be replenished from the shallow groundwater in a certain amount,but the surface soil water is easily lost due to the dry climate,especially in the sandy soil area where the water residence time is short.During the irrigation period,the soil area in the surface layer with light drought degree was greatly reduced compared with the non-irrigation period,and the spatial variability of soil moisture in the vertical direction was narrowed,but the soil water content in the horizontal direction still had large spatial variability due to different soil textures,especially in the surface layer with high salt area and sandy soil area,where the soil water content was still low after repeated irrigation.The results of the study confirm that it is feasible to map the three-dimensional distribution of soil water content by three-dimensional inverse distance interpolation.This method can not only provide an important reference basis for irrigation in arid areas,but also provide some guidance suggestions for the development of irrigation strategies in farmland.（3）Research on the amount of soil irrigation in cotton fields with under-membrane drip irrigationFrom July to September,the local maximum irrigation rate in the study area decreased from 2200 m³ha^-1 to 1700 m³ ha^-1 as the number of irrigations increased.These were the western half of the northern end,the central area and the southern eastern area.After one drip irrigation,the irrigation amount in the west half of the north end and the east side of the south area decreased significantly,while the central area still needed a lot of irrigation;after the last irrigation,the central area was significantly improved and the irrigation amount decreased.The results of this study proved that it is feasible to use EM38-MK2 to monitor and evaluate the soil moisture content of farmland at different periods to achieve efficient irrigation volume in the field.This study has made new advances in the following aspects.（1）In this study,soil moisture content in the rhizosphere of field-scale crops in the arid zone was modeled and inverted by using soil apparent conductivity data obtained from the EM38-MK2 geodesic conductivity meter.The method takes full advantage of the fast,efficient and non-destructive data collection of EM38-MK2 to monitor the moisture content of field-scale soil profiles with minimal damage to the original soil morphology and structure.It reduces the cost of acquiring soil profile moisture content in the field and provides reference significance for the amount of irrigation in the field by observing the dynamic changes of soil moisture content in the field over multiple periods.（2）To show the specific distribution of soil moisture in three-dimensional space in more detail and comprehensively,this study inverts the soil moisture content of the field mesh apparent conductivity data acquired by EM38-MK2 geodetic conductivity meter in automatic mode.The water content data of different soil layers from the inverse performance were visualized in three dimensions using the inverse distance weight interpolation method.（3）The field-scale irrigation amount of soil moisture was calculated using the field water holding capacity as the maximum irrigation amount,and the field-scale irrigation amount distribution map was drawn,taking into account only the soil moisture condition.Combined with the distribution map of irrigation volume in several periods,we monitor and evaluate the soil moisture content in several local areas of the field where the irrigation volume is always high to ensure that the soil moisture can adequately meet the demand of cotton in several growth stages and reduce the possibility of cotton growth problems caused by soil moisture content factors.