首页> 外文期刊>Fresenius Environmental Bulletin >COMPARISON OF THREE LABORATORY AND ONE REGRESSION KRIGING METHOD FOR QUANTITATIVE AND QUALITATIVE ASSESSMENT OF SOIL SALINITY IN THE HARRAN PLAIN, SE TURKEY
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COMPARISON OF THREE LABORATORY AND ONE REGRESSION KRIGING METHOD FOR QUANTITATIVE AND QUALITATIVE ASSESSMENT OF SOIL SALINITY IN THE HARRAN PLAIN, SE TURKEY

机译:土耳其哈兰平原土壤盐度定量和定性评估的三种实验室和一种回归克里格法的比较

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摘要

The Harran Plain occurring in southeastern Turkey, has faced salinity problems since the beginning of irrigated agriculture. Soil salinity is generally most accurately determined from a soil saturation paste (SP) extract. In this study three laboratory (SP, 1:1 and 1:2.5 soil to water ratios) and one kriging technique have been used for the assessment of soil salinity. A total of randomly selected 210 locations, 60 in data set I and 150 in data set II were sampled in 2009 and 2010, respectively, and analyzed for soil electrical conductivity (EC_e dS m~(-1)), sodium adsorption ratio (SAR) and the soluble cations (Ca~(2+), Mg~(2+), Na~+ and K~+). Regression analysis was used for quantitative assessments and a classification approach used for qualitative evaluation of salinity. The kriging of residuals and the values from regressions between 1) soil EC_es obtained from different soil and water ratios (auxilary variables) and 2) soil salinity variables obtained from saturation paste (primary variables) were combined under regression kriging with the goal of estimating soil salinity parameters. Despite significant correlations among different methods, the results of paired t test showed that averages of soil salinity variables measured with different methods were mostly statistically different (P=0.01). The 1:1 soil water ratio produced the closest results to SP, especially after classification of soils into different salinity groups which provided regression R2 values up to 0.99. Using a validation with independent samples per cent classification accuracy and kappa statistics of 91 %, 0.72 (p=0.001) were obtained. Kriging combined with regression under regression kriging improved the estimations of K~+, Mg~(2+) and EC_e slightly but did not show any improvement over different soil to water ratios for the estimation of SAR, Na~+ and Ca~(2+).
机译:自灌溉农业开始以来,发生在土耳其东南部的哈兰平原一直面临盐碱化问题。通常从土壤饱和糊(SP)提取物中最准确地确定土壤盐度。在这项研究中,三个实验室(SP,1:1和1:2.5土壤与水的比例)和一种克里格技术已用于评估土壤盐分。分别于2009年和2010年对总共随机选择的210个位置(数据集I中的60个位置和数据集II中的150个位置)进行了采样,并分析了土壤电导率(EC_e dS m〜(-1)),钠吸附率(SAR) )和可溶性阳离子(Ca〜(2 +),Mg〜(2 +),Na〜+和K〜+)。回归分析用于定量评估,分类方法用于盐度的定性评估。在回归克里金法的基础上,将残差的克里金法和1)从不同土壤和水的比例获得的土壤EC_es(辅助变量)与2)从饱和糊料获得的土壤盐分变量(主要变量)之间的回归值进行组合,以估算土壤盐度参数。尽管不同方法之间存在显着相关性,但配对t检验的结果表明,使用不同方法测得的土壤盐度变量的平均值在统计学上大多存在差异(P = 0.01)。 1:1的土壤水比产生了最接近SP的结果,尤其是在将土壤分类为不同的盐度组之后,其回归R2值高达0.99。使用独立样本进行的验证,分类准确度为%,kappa统计为91%,获得了0.72(p = 0.001)。克里格法与回归克里格法下的回归相结合略微改善了K〜+,Mg〜(2+)和EC_e的估计值,但在不同土壤水比下对SAR,Na〜+和Ca〜(2)的估计没有任何改善。 +)。

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