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Soil Quality Assessment Based on a Minimum Data Set: A Case Study of a County in the Typical River Delta Wetlands

Author

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  • Mingliang Jiang

    (Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Ligang Xu

    (Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China)

  • Xiaobing Chen

    (Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China)

  • Hua Zhu

    (Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Hongxiang Fan

    (Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China)

Abstract

Purpose: The Yellow River delta boasts rich land resources but lacks fresh water and exhibits poor natural conditions. To rationally develop and utilize the land resources therein, it is necessary to evaluate the soil quality. Methods: Adopting specific screening conditions, principal component analysis (PCA) was used to construct a minimum data set (MDS) from 10 soil indicators. Then, a complete soil quality evaluation index system of the Yellow River delta was developed. The soil quality comprehensive index (SQI) method was used to assess the soil quality in the Kenli District, and the soil quality grades and spatial distribution were analyzed. Results: (1) The average SQI of the Kenli District is 0.523, and the best soil quality is concentrated near the Yellow River, especially in Huanghekou town. (2) The normalized difference vegetation index was positively correlate with SQI, whereas Dr (nearest distance between the sampling site and Yellow River) and Ds (nearest distance between the sampling site and Bohai Sea) were negatively correlated with SQI. Elev (sampling site elevation) was not correlated with SQI. (3) The SQI of agricultural planting is greater than that of the natural land type and significantly greater than that of nudation. The main factors limiting farmland soil quality are SK (water-soluble potassium) and pH, whereas the factor limiting the natural land type are the soil nutrient indicators. Conclusions: To improve soil quality and develop and utilize land resources, the towns should adopt systematic land development/utilization methods based on local conditions. These results have important guiding significance and practical value for the more objective and accurate evaluation of soil quality in coastal areas and the development and utilization of land resources.

Suggested Citation

  • Mingliang Jiang & Ligang Xu & Xiaobing Chen & Hua Zhu & Hongxiang Fan, 2020. "Soil Quality Assessment Based on a Minimum Data Set: A Case Study of a County in the Typical River Delta Wetlands," Sustainability, MDPI, vol. 12(21), pages 1-21, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:21:p:9033-:d:437511
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    References listed on IDEAS

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    1. Chunsheng Wu & Qingsheng Liu & Guoxia Ma & Gaohuan Liu & Fang Yu & Chong Huang & Zhonghe Zhao & Li Liang, 2019. "A Study of the Spatial Difference of the Soil Quality of The Mun River Basin during the Rainy Season," Sustainability, MDPI, vol. 11(12), pages 1-14, June.
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    Cited by:

    1. Deepesh Goyal & Varun Joshi & Neha Gupta & Marina M. S. Cabral-Pinto, 2022. "Soil Quality Assessment in a Landslide Chronosequence of Indian Himalayan Region," Land, MDPI, vol. 11(10), pages 1-18, October.
    2. Wei Fang & Xuemei Zhong & Xinhua Peng & Linyuan Li & Shaoliang Zhang & Lei Gao, 2023. "Soil Quality Mediates the Corn Yield in a Thin-Layer Mollisol in Northeast China," Land, MDPI, vol. 12(6), pages 1-15, June.

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