Integration of TOPSIS and Geostatistical Technique for Soil Quality Assessment under Different Land Uses: A Case Study

A. Mustafa
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Abstract

This study aims to assess the soil quality under different land uses by utilizing technique for order preference by similarity to the ideal solution method (TOPSIS) and geostatistical Technique in the Northern part of Sohag Governorate, Egypt. Various soil parameters such as sand, silt, clay content, CEC, ESP OC, ECe, pH, and CaCO3 were determined. Afterward, the geostatistics approach using ordinary kriging interpolation and semivariogram was applied to produce a spatialized and detailed map for each soil parameter. Spherical, Exponential, Gaussian, and J-Bessel geostatistical models were used to define the spatial variability of soil properties based on RMS, MSE, and RMSSE. Based on the TOPSIS method, the soil quality index (SQI) and its ranking under land use types in the study area were calculated. The results of SQI ranged from 38.75% to 55.82% and 27.53% to 52.72%, and 5.75% to 26.73% for old cultivated, new cultivated, and desert soil, respectively. The SQI was classified into three regions. The first has a fair quality index and covers 56.48% (403.91 km2) of the total geographical area (TGA). The soils of this region are located mainly in old cultivated soils and some new ones. The second region was observed in some newly reclaimed soils and desert soils and extended over an area of about 27.75% (198.45 km2). These soils have low values of favorable studied indicators, leading to negative effects on the SQI that are defined as poor. The third region is very poor quality, covers about 15.77% (112.78 km2) of TGA, and is located mainly in desert soils with low beneficial and high non-beneficial studied indicators. Finally, the results indicate that the integration of TOPSIS and geostatistical technique allow for an accurate and practical assessment of the SQI.
TOPSIS与地质统计技术在不同土地利用方式下土壤质量评价中的应用
利用TOPSIS法和地质统计学方法对埃及索哈格省北部不同土地利用方式下的土壤质量进行了排序偏好评价。测定了砂、粉、粘土含量、CEC、ESP、OC、ECe、pH、CaCO3等土壤参数。然后,利用普通克里格插值和半变异函数的地质统计学方法,对每个土壤参数进行了空间化的详细映射。基于RMS、MSE和RMSSE,采用球面、指数、高斯和J-Bessel地统计模型定义土壤性质的空间变异性。基于TOPSIS方法,计算了研究区土壤质量指数(SQI)及其在土地利用类型下的排序。旧土、新土和荒漠土壤SQI分别为38.75% ~ 55.82%、27.53% ~ 52.72%和5.75% ~ 26.73%。SQI被划分为三个区域。第一个区域质量指数较好,占总地理面积的56.48% (403.91 km2)。该地区土壤以老耕土为主,也有少量新耕土。第二区主要分布在一些新开垦的土壤和荒漠土壤中,面积约为27.75% (198.45 km2)。这些土壤的有利研究指标值较低,导致SQI的负面影响被定义为差。第三区质量极差,占总热评价面积的15.77% (112.78 km2),主要分布在荒漠土壤中,研究指标低有益、高无益。最后,结果表明,TOPSIS和地质统计技术的结合可以准确和实用地评估SQI。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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