Abstract
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.
Highlights
Surface water quality is a sensitive global environmental issue, as it is important for long-term economic development and environmental sustainability [1,2,3]
The present study proposes empirical algorithms to retrieve water quality parameters (V-phenol, Dissolved oxygen (DO), NH4 -N, NO3 -N) based on Landsat TM5, ETM7, and OLI8 images (2000, 2001, 2002, and 2020) of Erlong Lake, Jilin, northeast China
This study explains the relationship between the water quality parameters (V-phenol, NH4 -N, DO, and NO3 -N) and the reflectance data of the Landsat images (TM5, ETM7, OLI8)
Summary
Surface water quality is a sensitive global environmental issue, as it is important for long-term economic development and environmental sustainability [1,2,3]. How external changes, whether natural or human, affect that quality of water is of great concern [4]. Surface freshwater is an important requirement for the terrestrial environment and the Remote Sens. Over the past three decades, industrialization and urbanization have had an adverse effect on water quality; mutating marine species, such as fish; polluting drinking water; and altering the aquatic ecosystem food chain on the globe [5]. Human activities, such as gushing releases, agrarian concoctions, and misusing water supplies, have a significant impact on surface water quality. Numerous waterways are highly contaminated due to anthropogenic activities in the world [7]
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