Modeling Water Quality Parameters Using Landsat Multispectral Images: A Case Study of Erlong Lake, Northeast China

Autor:	Zhijun Tong, Ahmed M. El-Zeiny, Muhammad Hussain, Cheechouyang Faichia, Muhammad Tayyab, Bazel Al-Shaibah, Xingpeng Liu, Mingxi Zhang, Jiquan Zhang
Rok vydání:	2021
Předmět:	Pollution Hydrology Coefficient of determination 010504 meteorology & atmospheric sciences Science media_common.quotation_subject Multispectral image modeling Spectral bands 010501 environmental sciences water quality 01 natural sciences Water resources remote sensing Waves and shallow water Landsat images General Earth and Planetary Sciences Environmental science Radiometric dating Erlong Lake Water quality 0105 earth and related environmental sciences media_common
Zdroj:	Remote Sensing, Vol 13, Iss 1603, p 1603 (2021) Remote Sensing Volume 13 Issue 9 Pages: 1603
ISSN:	2072-4292
DOI:	10.3390/rs13091603
Popis:	Erlong Lake is considered one of the largest lakes in midwest Jilin, China, and one of the drinking water resources in neighboring cities. The present study aims to explore the usage of Landsat TM5, ETM7, and OLI8 images to assess water quality (V-phenol, dissolved oxygen (DO), NH4-N, NO3-N) in Erlong Lake, Jilin province, northeast China. Thirteen multispectral images were used in this study for May, July, August, and September in 2000, 2001, 2002, and October 2020. Radiometric and atmospheric corrections were applied to all images. All in situ water quality parameters were strongly correlated to each other, except DO. The in situ measurements (V-phenol, dissolved oxygen, NH4-N, NO3-N) were statistically correlated with various spectral band combinations (blue, green, red, and NIR) derived from Landsat imagery. Regression analysis reported that there are strong relationships between the estimated and retrieved water quality from the Landsat images. Moreover, in calibrations, the highest value of the coefficient of determination (R2) was ≥0.85 with (RMSE) = 0.038; the lowest value of R2 was >0.30 with RMSE= 0.752. All generated models were validated in different statistical indices; R2 was up to 0.95 for most cases, with RMSE ranging from 1.390 to 0.050. Finally, the empirical algorithms were successfully assessed (V-phenol, dissolved oxygen, NH4-N, NO3-N) in Erlong Lake, using Landsat images with very good accuracy. Both in situ and model retrieved results showed the same trends with non-significant differences. September of 2000, 2001, and 2002 and October of 2020 were selected to assess the spatial distributions of V-phenol, DO, NH4-N, and NO3-N in the lake. V-phenol, NH4-N, and NO3-N were reported low in shallow water but high in deep water, while DO was high in shallow water but low in deep water of the lake. Domestic sewage, agricultural, and urban industrial pollution are the most common sources of pollution in the Erlong Lake.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::088d82d647559b351a7172fea2667984 https://doi.org/10.3390/rs13091603 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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