Water Quality Index (WQI) as a Potential Proxy for Remote Sensing Evaluation of Water Quality in Arid Areas

Water Resource Sustainability Management plays a vitally important role in ensuring sustainable development, especially in water-stressed arid regions throughout the world. In order to achieve sustainable development, it is necessary to study and monitor the water quality in the arid region of Centr...

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Autores principales:	Fei Zhang, Ngai Weng Chan, Changjiang Liu, Xiaoping Wang, Jingchao Shi, Hsiang-Te Kung, Xinguo Li, Tao Guo, Weiwei Wang, Naixin Cao
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	Water Quality Index (WQI) Ebinur Lake remote sensing Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
Acceso en línea:	https://doaj.org/article/bb12ebd79c13429991fb72f46c1b9a00
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spelling	oai:doaj.org-article:bb12ebd79c13429991fb72f46c1b9a002021-11-25T19:15:58ZWater Quality Index (WQI) as a Potential Proxy for Remote Sensing Evaluation of Water Quality in Arid Areas10.3390/w132232502073-4441https://doaj.org/article/bb12ebd79c13429991fb72f46c1b9a002021-11-01T00:00:00Zhttps://www.mdpi.com/2073-4441/13/22/3250https://doaj.org/toc/2073-4441Water Resource Sustainability Management plays a vitally important role in ensuring sustainable development, especially in water-stressed arid regions throughout the world. In order to achieve sustainable development, it is necessary to study and monitor the water quality in the arid region of Central Asia, an area that is increasingly affected by climate change. In recent decades, the rapid deterioration of water quality in the Ebinur Lake basin in Xinjiang (China) has severely threatened sustainable economic development. This study selected the Ebinur Lake basin as the study target, with the purpose of revealing the response between the water quality index and water body reflectivity, and to describe the relationship between the water quality index and water reflectivity. The methodology employed remote sensing techniques that establish a water quality index monitoring model to monitor water quality. The results of our study include: (1) the Water Quality Index (WQI) that was used to evaluate the water environment in Ebinur Lake indicates a lower water quality of Ebinur Lake, with a WQI value as high as 4000; (2) an introduction of the spectral derivative method that realizes the extraction of spectral information from a water body to better mine the information of spectral data through remote sensing, and the results also prove that the spectral derivative method can improve the relationship between the water body spectral and WQI, whereby R<sup>2</sup> is 0.6 at the most sensitive wavelengths; (3) the correlation between the spectral sensitivity index and WQI was greater than 0.6 at the significance level of 0.01 when multi-source spectral data were integrated with the spectral index (DI, RI and NDI) and fluorescence baseline; and (4) the distribution map of WQI in Ebinur Lake was obtained by the optimal model, which was constructed based on the third derivative data of Sentinel 2 data. We concluded that the water quality in the northwest of Ebinur Lake was the lowest in the region. In conclusion, we found that remote sensing techniques were highly effective and laid a foundation for water quality detection in arid areas.Fei ZhangNgai Weng ChanChangjiang LiuXiaoping WangJingchao ShiHsiang-Te KungXinguo LiTao GuoWeiwei WangNaixin CaoMDPI AGarticleWater Quality Index (WQI)Ebinur Lakeremote sensingHydraulic engineeringTC1-978Water supply for domestic and industrial purposesTD201-500ENWater, Vol 13, Iss 3250, p 3250 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Water Quality Index (WQI) Ebinur Lake remote sensing Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
spellingShingle	Water Quality Index (WQI) Ebinur Lake remote sensing Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 Fei Zhang Ngai Weng Chan Changjiang Liu Xiaoping Wang Jingchao Shi Hsiang-Te Kung Xinguo Li Tao Guo Weiwei Wang Naixin Cao Water Quality Index (WQI) as a Potential Proxy for Remote Sensing Evaluation of Water Quality in Arid Areas
description	Water Resource Sustainability Management plays a vitally important role in ensuring sustainable development, especially in water-stressed arid regions throughout the world. In order to achieve sustainable development, it is necessary to study and monitor the water quality in the arid region of Central Asia, an area that is increasingly affected by climate change. In recent decades, the rapid deterioration of water quality in the Ebinur Lake basin in Xinjiang (China) has severely threatened sustainable economic development. This study selected the Ebinur Lake basin as the study target, with the purpose of revealing the response between the water quality index and water body reflectivity, and to describe the relationship between the water quality index and water reflectivity. The methodology employed remote sensing techniques that establish a water quality index monitoring model to monitor water quality. The results of our study include: (1) the Water Quality Index (WQI) that was used to evaluate the water environment in Ebinur Lake indicates a lower water quality of Ebinur Lake, with a WQI value as high as 4000; (2) an introduction of the spectral derivative method that realizes the extraction of spectral information from a water body to better mine the information of spectral data through remote sensing, and the results also prove that the spectral derivative method can improve the relationship between the water body spectral and WQI, whereby R<sup>2</sup> is 0.6 at the most sensitive wavelengths; (3) the correlation between the spectral sensitivity index and WQI was greater than 0.6 at the significance level of 0.01 when multi-source spectral data were integrated with the spectral index (DI, RI and NDI) and fluorescence baseline; and (4) the distribution map of WQI in Ebinur Lake was obtained by the optimal model, which was constructed based on the third derivative data of Sentinel 2 data. We concluded that the water quality in the northwest of Ebinur Lake was the lowest in the region. In conclusion, we found that remote sensing techniques were highly effective and laid a foundation for water quality detection in arid areas.
format	article
author	Fei Zhang Ngai Weng Chan Changjiang Liu Xiaoping Wang Jingchao Shi Hsiang-Te Kung Xinguo Li Tao Guo Weiwei Wang Naixin Cao
author_facet	Fei Zhang Ngai Weng Chan Changjiang Liu Xiaoping Wang Jingchao Shi Hsiang-Te Kung Xinguo Li Tao Guo Weiwei Wang Naixin Cao
author_sort	Fei Zhang
title	Water Quality Index (WQI) as a Potential Proxy for Remote Sensing Evaluation of Water Quality in Arid Areas
title_short	Water Quality Index (WQI) as a Potential Proxy for Remote Sensing Evaluation of Water Quality in Arid Areas
title_full	Water Quality Index (WQI) as a Potential Proxy for Remote Sensing Evaluation of Water Quality in Arid Areas
title_fullStr	Water Quality Index (WQI) as a Potential Proxy for Remote Sensing Evaluation of Water Quality in Arid Areas
title_full_unstemmed	Water Quality Index (WQI) as a Potential Proxy for Remote Sensing Evaluation of Water Quality in Arid Areas
title_sort	water quality index (wqi) as a potential proxy for remote sensing evaluation of water quality in arid areas
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/bb12ebd79c13429991fb72f46c1b9a00
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Water Quality Index (WQI) as a Potential Proxy for Remote Sensing Evaluation of Water Quality in Arid Areas

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