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[水文与气候影响下黄河三角洲土壤盐分的时空动态变化]

[Spatiotemporal dynamics of soil salinity in the Yellow River Delta under the impacts of hydrology and climate.].

作者信息

Zhang Zi-Xuan, Song Yu-Tong, Zhang Hui-Zhong, Li Xin-Ju, Niu Bei-Bei

机构信息

College of Resources and Environment, Shandong Agricultural University, Tai'an 271018, Shandong, China.

National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources, Tai'an 271018, Shandong, China.

出版信息

Ying Yong Sheng Tai Xue Bao. 2021 Apr;32(4):1393-1405. doi: 10.13287/j.1001-9332.202104.012.

Abstract

In recent years, soil salinization in the Yellow River Delta under the effects of hydrology, climate and human activities have become increasingly prominent. Based on the 20 Landsat series images of Hekou, Kenli, Dongying districts and Lijin County of Dongying City selected from 1985 to 2018, numerical regression correction method was used to perform image spectral consistency conversion. The partial least squares regression method was used to construct quantitative inversion models of soil salt content. The soil salt content of the study area were retrieved by the best salt prediction model. The temporal and spatial characteristics of soil salt changes in the Yellow River Delta were analyzed. The results showed that the soil salt inversion model constructed with 10 sensitive spectral indices performed higher prediction accuracy, with coefficient of determination =0.769 and RMSE=1.125 for calibration, =0.752 and RMSE=1.203 for validation, and relative prediction deviation (RPD)=2.08. Using the measured soil salt data in 2016 to verify the inversion accuracy of the model, the correlation between the measured value and the inverted value was 0.7279. The model was used to map the soil salinity of the Yellow River Delta based on 20 images from 1985 to 2018. The abnormal soil salinity retrieval values was all less than 10%. During the study period, the soil salinity showed an overall trend of rising first and then falling which was lowest in 1985 (3.14 g·kg) and highest in 1995 (5.86 g·kg). Spatially, the area of heavily saline soil and saline soil in the study area decreased, and that of mildly and moderately saline soil significantly increased (66.6%). The total area of saline soil showed an increasing trend. The effects of hydrological and climatic conditions on soil salinity exhibited hysteresis. The increases of temperature promoted soil salinity, with the relationship between the soil salinity and the average temperatures in the past six months and one year being significantly correlated (=0.507 and 0.538). Soil salinity did not correlate with regional precipitation, and was most affected by the Yellow River streamflow in the previous season (=-0.543).

摘要

近年来,受水文、气候及人类活动影响,黄河三角洲地区土壤盐渍化问题日益突出。基于选取的东营市河口区、垦利区、东营区及利津县1985年至2018年的20景Landsat系列影像,采用数值回归校正方法进行影像光谱一致性转换。运用偏最小二乘回归方法构建土壤盐分含量定量反演模型,通过最优盐分预测模型反演研究区土壤盐分含量,分析黄河三角洲土壤盐分变化的时空特征。结果表明,利用10个敏感光谱指数构建的土壤盐分反演模型预测精度较高,校正决定系数=0.769,均方根误差=1.125;验证决定系数=0.752,均方根误差=1.203,相对预测偏差(RPD)=2.08。利用2016年实测土壤盐分数据验证模型反演精度,实测值与反演值的相关性为0.7279。基于1985年至2018年的20景影像,利用该模型绘制黄河三角洲土壤盐度图,土壤盐分反演异常值均小于10%。研究期间,土壤盐度总体呈先上升后下降趋势,1985年最低(3.14 g·kg),1995年最高(5.86 g·kg)。空间上,研究区重度盐渍土和盐渍土面积减少,轻度和中度盐渍土面积显著增加(66.6%),盐渍土总面积呈增加趋势。水文和气候条件对土壤盐度的影响具有滞后性。温度升高促进土壤盐度增加,土壤盐度与过去6个月和1年的平均气温呈显著相关(=0.507和0.538)。土壤盐度与区域降水量无关,受上一季黄河径流量影响最大(=-0.543)。

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