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Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys

机译:使用重复电磁感应(EMI)调查的沿海农业景观中土壤盐分和作物产量的数字地图

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摘要

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield.
机译:关于土壤和农作物特性的可靠且实时的信息对于根据各个田间单位内特定土壤和农作物的要求制定管理规范非常重要。在受盐影响的农业景观中尤其如此,在其中管理土壤盐分的空间变异性对于最小化盐碱化和最大化农作物产量至关重要。主要目标是使用线性混合效应模型对土壤盐分和作物产量进行校准,并以水平和垂直电磁感应(EMI)测量作为辅助数据,以表征土壤盐分和作物产量的空间分布,并验证空间准确性估计。在每次调查期间,均在252个位置进行了水平和垂直EMI(EM38型)测量,并在64个采样点收集了根区土壤样品和农作物样品。该工作于2012年6月至2013年5月的8个日期定期在沿海盐灾的泥地中进行。利用辅助数据,应用多元线性回归(MLR)和受限最大似然(REML)来校准根区土壤盐度(ECe)和作物年产量(CAO),并使用数字土壤测绘生成土壤ECe和CAO的空间分布( DSM),并使用收集的气象和地下水数据检查空间估算的精度。结果表明,以EMh作为预测因子的简化模型对于根区ECe校准是令人满意的,而同时以EMh和EMv作为预测因子的完整模型满足了CAO校准的要求。所获得的ECe分布图与相应时间的EMI测量值一致,并且从辅助数据生成的CAO的空间分布与从原始作物数据得出的CAO的空间分布一致。顶升过程的统计数据证实了ECe和CAO的空间估计具有可靠性和高精度。在调查期间,观察到ECe总体呈上升趋势,中度盐度和盐度极高的土壤占主导地位。根区ECe的时间动态与每日降雨量,地下水位和地下水数据相一致。需要进行长期的EMI调查和数据收集,以捕获土壤和作物参数的时空变化。这些结果使我们得出结论,作为DSM多源数据的一部分,经济有效的EMI调查可以成功地用于表征土壤盐分的空间变异性,以监测土壤盐分的时空动态。 ,并在空间上估算潜在的农作物产量。

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