Abstract
Egypt is currently witnessing an extensive desert greening plan with a target of adding one and a half million feddans to the agricultural area. The present study evaluates the soil quality in the western desert fringes of the Nile Delta using three indicator datasets, which involve the total dataset (TDS), the minimum dataset (MDS), and the expert dataset (EDS). Three quality index models are included: the Additive Soil Quality Index (SQI-A), the Weighted Additive Soil Quality Index (SQI-W), and the Nemoro Soil Quality Index (SQI-N). Linear and nonlinear scoring functions are evaluated for scoring soil and terrain indicators. Thirteen soil quality indicators and three terrain indicators were measured in 397 sampling sites for soil quality evaluation. Factor analyses determined five soil and terrain indicators for the minimum dataset and their associated weights. The linear scoring functions reflected the soil system functions more than nonlinear scoring functions. Soil quality estimation by the minimum dataset (MDS) and Weighted Additive Soil Quality Index (SQI-W) is more sensitive than that by SQI-A and SQI-N quality models to explain soil quality indicators. The moderate soil quality grade is the largest quality grade in the studied area. The minimum dataset of soil quality indicators could assist in reducing time and cost of evaluating soil quality and monitoring the temporal changes in soil quality of the region due to the increased agricultural development.
Highlights
Soil is considered one of the most important natural resources for countries where the foundations of human life are mainly based on their suitability for agriculture as well as other anthropogenic activities [1]
Based on the work in [45], the soil temperature regime is “ ermic” and the moisture regime is “Torric.” Two soil orders are dominant in the area, Entisols and Aridisols. e evaluated area has been reclaimed during the last two decades and is cultivated with diverse kinds of fruits and vegetables [46]. is kind of cultivation is usually associated with an increase of underground water irrigation, and the ongoing climate change put a threat on the soil quality and sustainable agriculture that reduces the economic value of the lands [47, 48]
Soil and Terrain Indicator Characteristics. e soil and terrain indicators related to soil quality were subjected to descriptive analyses (Table 2). e quantile range outlier’s statistic indicated no outliers existed in soil and terrain indicator data. e elevation of the sampling sites ranged between −19 and 197 m above mean sea level. e relief intensity (Rlf), sand, Slp, CaCO3, and clay indicators showed high data dispersion indicating that the spatial variations of these soil indicators are large, while the other soil and terrain indicators are of weak spatial variation as they have low data dispersion
Summary
Soil is considered one of the most important natural resources for countries where the foundations of human life are mainly based on their suitability for agriculture as well as other anthropogenic activities [1]. To overcome the financial constraints, the amount of soil quality indicators needs to be reduced to a minimum dataset (MDS) [25, 26]. E concept of minimum datasets was proposed in [27], which is the lowest set of soil quality indicators required to measure or evaluate soil quality to demonstrate the soil’s capacity for sustainable agricultural production. Since factor analysis can minimize abundant input data in the original soil datasets, it is widely utilized in the limitation of the MDS [28, 39]. Factor analysis statistical techniques can identify the most important indicators discriminating soil quality in combined tillage, fertilization, and crop rotation treatments [28]. As the calculation of soil quality is hard [4], an urgent need exists for improving the simple and reliable quantitative evaluation of soil quality through comparison of various available assessment strategies and methods. us, this study attempts to examine the soil quality in the arid region along the desert western fringes of the Nile Delta by (i) assessing the soil quality using three types of indicator datasets (TDS, MDS, and EDS), three types of linear scoring functions, two types of nonlinear scoring functions, and three soil quality index models (additive, weighted additive, and Nemoro quality indices); (ii) suggesting the most suitable indicator method and soil quality index model for the studied region using sensitivity analysis and linear relationships. e findings of the study have a significant value for assessing the soil quality in the rapidly developing area for sustainable management
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