缓解松嫩平原土壤盐渍化的地下水位阈值估算

IF 4.7 2区 地球科学 Q1 WATER RESOURCES
Yiding Ding , Haishen Lü , Ligang Xu , Robert Horton , Mingliang Jiang , Yonghua Zhu , Junxiang Cheng , Hongxiang Fan , Jianbin Su
{"title":"缓解松嫩平原土壤盐渍化的地下水位阈值估算","authors":"Yiding Ding ,&nbsp;Haishen Lü ,&nbsp;Ligang Xu ,&nbsp;Robert Horton ,&nbsp;Mingliang Jiang ,&nbsp;Yonghua Zhu ,&nbsp;Junxiang Cheng ,&nbsp;Hongxiang Fan ,&nbsp;Jianbin Su","doi":"10.1016/j.ejrh.2025.102326","DOIUrl":null,"url":null,"abstract":"<div><h3>Study region</h3><div>The Songnen Plain is a key part of China’s largest plain, situated in northeastern China.</div></div><div><h3>Study focus</h3><div>Soil salinization has become one of the largest ecological issues in the Songnen Plain, and regulating groundwater levels is a crucial strategy for mitigating it. To address this, a comprehensive framework is developed to estimate the groundwater table threshold for soil salinization by integrating field sampling, remote sensing big data, and machine learning models.</div></div><div><h3>New hydrological insights for the region</h3><div>The soil salinity inversion model, which utilizes a random forest algorithm, achieves the highest accuracy (R<sup>2</sup> = 0.75, d = 0.94, RPD = 2.05), outperforming SVM, LightGBM, and XGBoost algorithms. From 2020–2023, areas with mild salinization accounted for 9.3 % of the total area, while moderate salinization accounted for 3.2 %, severe salinization accounted for 4.0 %, and saline soil areas accounted for 0.6 %. A probabilistic model further identifies groundwater depth thresholds for salinization: 2.3 m for sandy soil, 3.1 m for loamy soil, and 1.1 m for silty soil. Based on current groundwater depths, it is anticipated that 15.5 % of the Songnen Plain area will continue to be affected by soil salinization or remain at risk of potential salinization.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102326"},"PeriodicalIF":4.7000,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimating the groundwater table threshold for mitigating soil salinization in the Songnen Plain of China\",\"authors\":\"Yiding Ding ,&nbsp;Haishen Lü ,&nbsp;Ligang Xu ,&nbsp;Robert Horton ,&nbsp;Mingliang Jiang ,&nbsp;Yonghua Zhu ,&nbsp;Junxiang Cheng ,&nbsp;Hongxiang Fan ,&nbsp;Jianbin Su\",\"doi\":\"10.1016/j.ejrh.2025.102326\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Study region</h3><div>The Songnen Plain is a key part of China’s largest plain, situated in northeastern China.</div></div><div><h3>Study focus</h3><div>Soil salinization has become one of the largest ecological issues in the Songnen Plain, and regulating groundwater levels is a crucial strategy for mitigating it. To address this, a comprehensive framework is developed to estimate the groundwater table threshold for soil salinization by integrating field sampling, remote sensing big data, and machine learning models.</div></div><div><h3>New hydrological insights for the region</h3><div>The soil salinity inversion model, which utilizes a random forest algorithm, achieves the highest accuracy (R<sup>2</sup> = 0.75, d = 0.94, RPD = 2.05), outperforming SVM, LightGBM, and XGBoost algorithms. From 2020–2023, areas with mild salinization accounted for 9.3 % of the total area, while moderate salinization accounted for 3.2 %, severe salinization accounted for 4.0 %, and saline soil areas accounted for 0.6 %. A probabilistic model further identifies groundwater depth thresholds for salinization: 2.3 m for sandy soil, 3.1 m for loamy soil, and 1.1 m for silty soil. Based on current groundwater depths, it is anticipated that 15.5 % of the Songnen Plain area will continue to be affected by soil salinization or remain at risk of potential salinization.</div></div>\",\"PeriodicalId\":48620,\"journal\":{\"name\":\"Journal of Hydrology-Regional Studies\",\"volume\":\"59 \",\"pages\":\"Article 102326\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2025-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Hydrology-Regional Studies\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2214581825001508\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"WATER RESOURCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydrology-Regional Studies","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214581825001508","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"WATER RESOURCES","Score":null,"Total":0}
引用次数: 0

摘要

研究区域松嫩平原位于中国东北部,是中国最大平原的重要组成部分。研究重点土壤盐渍化已成为松嫩平原最大的生态问题之一,调控地下水位是缓解土壤盐渍化的重要策略。为了解决这个问题,我们开发了一个综合框架,通过整合现场采样、遥感大数据和机器学习模型来估计土壤盐渍化的地下水位阈值。采用随机森林算法的土壤盐度反演模型具有最高的精度(R2 = 0.75, d = 0.94, RPD = 2.05),优于SVM、LightGBM和XGBoost算法。2020-2023年,轻度盐渍化面积占总面积的9.3 %,中度盐渍化面积占3.2 %,重度盐渍化面积占4.0 %,盐渍化面积占0.6 %。概率模型进一步确定了地下水盐渍化的深度阈值:沙质土为2.3 m,壤土为3.1 m,粉质土为1.1 m。根据目前的地下水深度,预计松嫩平原15.5 %的地区将继续受到土壤盐渍化的影响或仍有潜在的盐渍化风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating the groundwater table threshold for mitigating soil salinization in the Songnen Plain of China

Study region

The Songnen Plain is a key part of China’s largest plain, situated in northeastern China.

Study focus

Soil salinization has become one of the largest ecological issues in the Songnen Plain, and regulating groundwater levels is a crucial strategy for mitigating it. To address this, a comprehensive framework is developed to estimate the groundwater table threshold for soil salinization by integrating field sampling, remote sensing big data, and machine learning models.

New hydrological insights for the region

The soil salinity inversion model, which utilizes a random forest algorithm, achieves the highest accuracy (R2 = 0.75, d = 0.94, RPD = 2.05), outperforming SVM, LightGBM, and XGBoost algorithms. From 2020–2023, areas with mild salinization accounted for 9.3 % of the total area, while moderate salinization accounted for 3.2 %, severe salinization accounted for 4.0 %, and saline soil areas accounted for 0.6 %. A probabilistic model further identifies groundwater depth thresholds for salinization: 2.3 m for sandy soil, 3.1 m for loamy soil, and 1.1 m for silty soil. Based on current groundwater depths, it is anticipated that 15.5 % of the Songnen Plain area will continue to be affected by soil salinization or remain at risk of potential salinization.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Hydrology-Regional Studies
Journal of Hydrology-Regional Studies Earth and Planetary Sciences-Earth and Planetary Sciences (miscellaneous)
CiteScore
6.70
自引率
8.50%
发文量
284
审稿时长
60 days
期刊介绍: Journal of Hydrology: Regional Studies publishes original research papers enhancing the science of hydrology and aiming at region-specific problems, past and future conditions, analysis, review and solutions. The journal particularly welcomes research papers that deliver new insights into region-specific hydrological processes and responses to changing conditions, as well as contributions that incorporate interdisciplinarity and translational science.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信