Inversion of soil salinization at the branch canal scale in the Hetao Irrigation District based on improved spectral indices

The Hetao Irrigation District in Inner Mongolia is a typical arid and semi-arid irrigation district, and the prevention and control of soil salinization has always been a major task in this area. To explore the dynamic changes of soil salinization at the scale of branch canals in the Hetao Irrigatio...

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Main Authors: Yi Zhao, Qingfeng Miao, Haibin Shi, Xianyue Li, Jianwen Yan, Shuya Yang, Cong Hou, Cuicui Yu, Weiying Feng, Jiannan Hao
Format: Article
Language:English
Published: Elsevier 2025-07-01
Series:Agricultural Water Management
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Online Access:http://www.sciencedirect.com/science/article/pii/S0378377425003221
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author Yi Zhao
Qingfeng Miao
Haibin Shi
Xianyue Li
Jianwen Yan
Shuya Yang
Cong Hou
Cuicui Yu
Weiying Feng
Jiannan Hao
author_facet Yi Zhao
Qingfeng Miao
Haibin Shi
Xianyue Li
Jianwen Yan
Shuya Yang
Cong Hou
Cuicui Yu
Weiying Feng
Jiannan Hao
author_sort Yi Zhao
collection DOAJ
description The Hetao Irrigation District in Inner Mongolia is a typical arid and semi-arid irrigation district, and the prevention and control of soil salinization has always been a major task in this area. To explore the dynamic changes of soil salinization at the scale of branch canals in the Hetao Irrigation District, a field experiment was conducted in the Zuo Er Branch Canal downstream of the Hetao Irrigation District. The red-edge band and short-wave infrared band are innovatively integrated into the traditional spectral indices for systematic improvement, and the optimal total soil salinity inversion model is constructed through the optimization strategy of different combinations of multiple bands, which effectively enhances the accuracy of soil salinity inversion. The results showed that (1) the remote sensing reflectance spectral curve showed an overall increasing trend with the increase of soil salinization. (2) Compared with the exponential and logarithmic inversion models, the polynomial model for total soil salinity showed a 7.58 % and 34.27 % increase in R2, a 15.92 % and 27.68 % increase in RPIQ, a 10.26 % and 23.46 % decrease in MAE, and a 13.56 % and 21.40 % decrease in RMSE, respectively. (3) The improvement spectral indices can improve the accuracy of soil salinity inversion. The polynomial soil total salinity inversion model with the highest accuracy, GSIb model, improved R2 and RPIQ by 41.36 % and 42.23 %, and reduced MAE and RMSE by 21.87 % and 29.67 % compared with SI model, which is the optimal soil total salinity inversion model. (4) Compared with the traditional spectral indices, the model constructed by the improved spectral indices was more sensitive to the extreme value of total soil salinity. The study provides an important theoretical basis and reference for the prevention and control of soil salinization in arid and semi-arid regions.
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publisher Elsevier
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series Agricultural Water Management
spelling doaj-art-bc952d62e5aa48f2af35e8725b39ef472025-08-20T02:39:48ZengElsevierAgricultural Water Management1873-22832025-07-0131610960810.1016/j.agwat.2025.109608Inversion of soil salinization at the branch canal scale in the Hetao Irrigation District based on improved spectral indicesYi Zhao0Qingfeng Miao1Haibin Shi2Xianyue Li3Jianwen Yan4Shuya Yang5Cong Hou6Cuicui Yu7Weiying Feng8Jiannan Hao9College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China; Regional Collaborative Innovation Center for Comprehensive Management of Water Resources and Water Environment in the Inner Mongolia Section of the Yellow River Basin, Hohhot 010018, China; Corresponding author at: College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China.College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China; Corresponding author.College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaSchool of Materials Science and Engineering, Beihang University, Beijing 100191, ChinaFengji Canal Water Supply Office, Yichang Sub-centre, Inner Mongolia Hetao Irrigation District Water Resources Development Centre, Bayannur 015100, ChinaThe Hetao Irrigation District in Inner Mongolia is a typical arid and semi-arid irrigation district, and the prevention and control of soil salinization has always been a major task in this area. To explore the dynamic changes of soil salinization at the scale of branch canals in the Hetao Irrigation District, a field experiment was conducted in the Zuo Er Branch Canal downstream of the Hetao Irrigation District. The red-edge band and short-wave infrared band are innovatively integrated into the traditional spectral indices for systematic improvement, and the optimal total soil salinity inversion model is constructed through the optimization strategy of different combinations of multiple bands, which effectively enhances the accuracy of soil salinity inversion. The results showed that (1) the remote sensing reflectance spectral curve showed an overall increasing trend with the increase of soil salinization. (2) Compared with the exponential and logarithmic inversion models, the polynomial model for total soil salinity showed a 7.58 % and 34.27 % increase in R2, a 15.92 % and 27.68 % increase in RPIQ, a 10.26 % and 23.46 % decrease in MAE, and a 13.56 % and 21.40 % decrease in RMSE, respectively. (3) The improvement spectral indices can improve the accuracy of soil salinity inversion. The polynomial soil total salinity inversion model with the highest accuracy, GSIb model, improved R2 and RPIQ by 41.36 % and 42.23 %, and reduced MAE and RMSE by 21.87 % and 29.67 % compared with SI model, which is the optimal soil total salinity inversion model. (4) Compared with the traditional spectral indices, the model constructed by the improved spectral indices was more sensitive to the extreme value of total soil salinity. The study provides an important theoretical basis and reference for the prevention and control of soil salinization in arid and semi-arid regions.http://www.sciencedirect.com/science/article/pii/S0378377425003221ChinaSalinity inversionImproved spectral indicesBranch canal scaleSentinel-2
spellingShingle Yi Zhao
Qingfeng Miao
Haibin Shi
Xianyue Li
Jianwen Yan
Shuya Yang
Cong Hou
Cuicui Yu
Weiying Feng
Jiannan Hao
Inversion of soil salinization at the branch canal scale in the Hetao Irrigation District based on improved spectral indices
Agricultural Water Management
China
Salinity inversion
Improved spectral indices
Branch canal scale
Sentinel-2
title Inversion of soil salinization at the branch canal scale in the Hetao Irrigation District based on improved spectral indices
title_full Inversion of soil salinization at the branch canal scale in the Hetao Irrigation District based on improved spectral indices
title_fullStr Inversion of soil salinization at the branch canal scale in the Hetao Irrigation District based on improved spectral indices
title_full_unstemmed Inversion of soil salinization at the branch canal scale in the Hetao Irrigation District based on improved spectral indices
title_short Inversion of soil salinization at the branch canal scale in the Hetao Irrigation District based on improved spectral indices
title_sort inversion of soil salinization at the branch canal scale in the hetao irrigation district based on improved spectral indices
topic China
Salinity inversion
Improved spectral indices
Branch canal scale
Sentinel-2
url http://www.sciencedirect.com/science/article/pii/S0378377425003221
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