Improved soil salinity estimation in arid regions: Leveraging bare soil periods and environmental factors

Summary: In the context of global land degradation and increasing salinization of cultivated land, accurately and sustainably estimating soil salinization is essential for effective land management. This study explores a novel approach to improve soil salt content (SSC) monitoring by minimizing the...

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Main Authors: Weitong Ma, Xin Cui, Wenting Han, Huihui Zhang, Liyuan Zhang
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:iScience
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Online Access:http://www.sciencedirect.com/science/article/pii/S2589004225012817
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author Weitong Ma
Xin Cui
Wenting Han
Huihui Zhang
Liyuan Zhang
author_facet Weitong Ma
Xin Cui
Wenting Han
Huihui Zhang
Liyuan Zhang
author_sort Weitong Ma
collection DOAJ
description Summary: In the context of global land degradation and increasing salinization of cultivated land, accurately and sustainably estimating soil salinization is essential for effective land management. This study explores a novel approach to improve soil salt content (SSC) monitoring by minimizing the influence of long-term environmental variability and incorporating relevant environmental factors. Focusing on exposed cultivated land in arid regions, we analyzed the sensitivity of multispectral indices and environmental factors to SSC during pre-seeding and post-harvest bare soil periods. Our findings indicate that soil mechanical composition and salinity indices exhibited strong correlations with SSC, which further enhanced when the periods were analyzed separately. Dividing the bare soil periods improved the model performance, increasing R2 by 10.2%–55.7%, and the support vector regression model performed better, with an R2 of 0.77, RMSE of 0.11%. This approach offers a robust framework for precision agriculture and sustainable land management in salinity-affected regions.
format Article
id doaj-art-c2738a35c8ee4a3c8c8a236c35063c0e
institution Kabale University
issn 2589-0042
language English
publishDate 2025-08-01
publisher Elsevier
record_format Article
series iScience
spelling doaj-art-c2738a35c8ee4a3c8c8a236c35063c0e2025-08-20T03:49:55ZengElsevieriScience2589-00422025-08-0128811302010.1016/j.isci.2025.113020Improved soil salinity estimation in arid regions: Leveraging bare soil periods and environmental factorsWeitong Ma0Xin Cui1Wenting Han2Huihui Zhang3Liyuan Zhang4College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China; Institute of Water-Saving Agriculture in Arid Areas of China, Northwest A&F University, Yangling, Shaanxi 712100, ChinaCAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China; Corresponding authorCollege of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China; Institute of Water-Saving Agriculture in Arid Areas of China, Northwest A&F University, Yangling, Shaanxi 712100, China; Corresponding authorWater Management and Systems Research Unit, USDA-ARS, 2150 Centre Avenue, Bldg. D., Fort Collins, CO 80526, USASchool of Agricultural Engineering, Jiangsu University, Zhenjiang, Jiangsu 210031, ChinaSummary: In the context of global land degradation and increasing salinization of cultivated land, accurately and sustainably estimating soil salinization is essential for effective land management. This study explores a novel approach to improve soil salt content (SSC) monitoring by minimizing the influence of long-term environmental variability and incorporating relevant environmental factors. Focusing on exposed cultivated land in arid regions, we analyzed the sensitivity of multispectral indices and environmental factors to SSC during pre-seeding and post-harvest bare soil periods. Our findings indicate that soil mechanical composition and salinity indices exhibited strong correlations with SSC, which further enhanced when the periods were analyzed separately. Dividing the bare soil periods improved the model performance, increasing R2 by 10.2%–55.7%, and the support vector regression model performed better, with an R2 of 0.77, RMSE of 0.11%. This approach offers a robust framework for precision agriculture and sustainable land management in salinity-affected regions.http://www.sciencedirect.com/science/article/pii/S2589004225012817Earth sciencesSoil scienceRemote sensingAgricultural scienceSoil hydrology
spellingShingle Weitong Ma
Xin Cui
Wenting Han
Huihui Zhang
Liyuan Zhang
Improved soil salinity estimation in arid regions: Leveraging bare soil periods and environmental factors
iScience
Earth sciences
Soil science
Remote sensing
Agricultural science
Soil hydrology
title Improved soil salinity estimation in arid regions: Leveraging bare soil periods and environmental factors
title_full Improved soil salinity estimation in arid regions: Leveraging bare soil periods and environmental factors
title_fullStr Improved soil salinity estimation in arid regions: Leveraging bare soil periods and environmental factors
title_full_unstemmed Improved soil salinity estimation in arid regions: Leveraging bare soil periods and environmental factors
title_short Improved soil salinity estimation in arid regions: Leveraging bare soil periods and environmental factors
title_sort improved soil salinity estimation in arid regions leveraging bare soil periods and environmental factors
topic Earth sciences
Soil science
Remote sensing
Agricultural science
Soil hydrology
url http://www.sciencedirect.com/science/article/pii/S2589004225012817
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AT xincui improvedsoilsalinityestimationinaridregionsleveragingbaresoilperiodsandenvironmentalfactors
AT wentinghan improvedsoilsalinityestimationinaridregionsleveragingbaresoilperiodsandenvironmentalfactors
AT huihuizhang improvedsoilsalinityestimationinaridregionsleveragingbaresoilperiodsandenvironmentalfactors
AT liyuanzhang improvedsoilsalinityestimationinaridregionsleveragingbaresoilperiodsandenvironmentalfactors