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Correlation Between soil Water Retention Capability and soil salt Content

Pedosphere 2000年第3期10卷 275-280页

作者： FENG YONGJUN YANG JINGSONG ZHENG JIUHUA College of Resource and Environment Shandong Agriculture UniversityTaian 271018 China Institute of soil Science Chinese Academy of SciencesNanjing 210008China

The soil moisture retention capability of Chao soil and coastal saline Chao soil in Shandong and Zhejiang provinces were measured by pressure membrane method. The main factors influencing soil moisture retention capability were studied by the methods of correlation and path analyses. The results indicated that soil salt content were the main factors influencing soil moisture retention capability. At soil suction of 30-50 kpa, the soil salt content would be the dominant factor.

关键词： influencing factor physical clay soil moisture retention capability soil salt

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Timely monitoring of soil water-salt dynamics within cropland by hybrid spectral unmixing and machine learning models

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International soil and Water Conservation Research 2024年第3期12卷 726-740页

作者： Ruiqi Du Junying Chen Youzhen Xiang Ru Xiang Xizhen Yang Tianyang Wang Yujie He Yuxiao Wu Haoyuan Yin Zhitao Zhang Yinwen Chen College of Water Resources and Architectural Engineering Northwest A&F UniversityYanglingShanxi712100China College of Language and Culture Northwest A&F UniversityYanglingShanxi712100China

soil salinization and water scarcity are main restrictive factors for irrigated agriculture development in arid *** dynamics of soil water and salt content is an important antecedent in remediating salinized soils and optimizing irrigation *** studies mostly used remote sensing technologies to individually monitor water or salt content dynamics in agricultural *** ability to asses different levels of crop water and salt management has been less ***,how to extract effective diagnostic features from remote sensing images derived spectral information is crucial for accurately estimating soil water and salt *** this study,Linear spectral unmixing method(LSU)was used to obtain the contribution of soil water and salt to each band spectrum(abundance),and endmember spectra from Sentinel-2 *** spectral indices and selecting optimal spectal combination were individually based on soil water and salt endmember *** estimation models were constructed using six machine learning algorithms:BP Neural Network(BPNN),Support Vector Regression(SVR),Partial Least Squares Regression(PLSR),Random Forest Regression(RFR),Gradient Boost Regression Tree(GBRT),and eXtreme Gradient Boosting tree(XGBoost).The results showed that the spectral indices calculated from endmember spectra were able to effectively characterize the response of crop spectral properties to soil water and salt,which circumvent spectral ambiguity induced by water-salt *** spectral index was a reliable indicator for estimating water and salt content,with determination coefficients(R2)being 0.55 and 0.57,*** to other models,LSU-XGBoost model achieved the best *** model properly reflected the process of soil water-salt dynamics in farmland during crop growth *** study provided new methods and ideas for soil water-salt estimation in dry irrigated agricultural areas,and provided decision support for gove

关键词： XGBoost Sentinel-2 Spectral unmixing soil water soil salt Irrigation area

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Influence of salt Content on soil Microbial Biomass Carbon

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Asian Agricultural Research 2016年第9期8卷 85-89页

作者： Huanqiang ZHENG Fanzhu QU Kun RONG Xueping LI Department of Resources and Environment Binzhou University Shandong Provincial Key Laboratory of Eco-Environmental Science for Yellow River Delta Binzhou University

soil salinization has become a global issue. Saline and alkaline arable land was taken as research object in this paper and four salt gradients were set(S1: 0.1%; S2:0. 5%; S3:0.9%; S4:1.3%). Through the addition of different substrates( CK: no addition of substrate; N: addition of nitrogen source; C: addition of glucose,C + N: addition of glucose and nitrogen source) to soil,it analyzed the influence of salt content on the soil microbial biomass carbon( SMBC) for the purpose of surveying the response mechanism of soil carbon turnover to salt stress. Results indicated that after addition of different substrates,the SMBC in high salt content(S3 and S4) is obviously lower than that in low salt content( S1 and S2). The decline rate of S3 and S4 is 5. 4% and 14. 2% for no addition of substrate; the decline rate is 9.0% and 24.0% for addition of nitrogen source; the decline rate is 11.5% and 28.0% for addition of carbon source; the decline rate is 19.5% and 39.5% for addition of carbon source + nitrogen source. Compared with no addition of substrates,addition of nitrogen source could not increase the SMBC. Addition of carbon source and carbon + nitrogen can significantly increase the SMBC,and the increase in low salt content soil( 80.0%- 81.0% and 58.0%- 59.0%) is obviously higher than high salt content soil( 52.0%- 69.0%and 34.0%- 50.0%). Generally,when the soil salt content is low( 0.5%),the influence of different substrate treatment is little on the SMBC,and increasing the soil salt content can obviously reduce the SMBC.

关键词： soil microbial biomass carbon Yellow River Delta soil salt Substrate addition

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