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Empirical Estimation of Nutrient, Organic Matter and Algal Chlorophyll in a Drinking Water Reservoir Using Landsat 5 TM Data
- Source :
- Remote Sensing, Vol 13, Iss 2256, p 2256 (2021), Remote Sensing, Volume 13, Issue 12, Pages: 2256
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- The main objective of this study was to develop empirical models from Landsat 5 TM data to monitor nutrient (total phosphorus: TP), organic matter (biological oxygen demand: BOD), and algal chlorophyll (chlorophyll-a: CHL-a). Instead of traditional monitoring techniques, such models could be substituted for water quality assessment in aquatic systems. A set of models were generated relating surface reflectance values of four bands of Landsat 5 TM and in-situ data by multiple linear regression analysis. Radiometric and atmospheric corrections improved the satellite image quality. A total of 32 compositions of different bands of Landsat 5 TM images were considered to find the correlation coefficient (r) with in-situ measurement of TP, BOD, and CHL-a levels collected from five sampling sites in 2001, 2006, and 2010. The results showed that TP, BOD, and CHL-a correlate well with Landsat 5 TM band reflectance values. TP (r = −0.79) and CHL-a (r = −0.79) showed the strongest relations with B1 (Blue). In contrast, BOD showed the highest correlation with B1 (Blue) (r = −0.75) and B1*B3/B4 (Blue*Red/Near-infrared) (r = −0.76). Considering the r values, significant bands and their compositions were identified and used to generate linear equations. Such equations for Landsat 5 TM could detect TP, BOD, and CHL-a with accuracies of 67%, 65%, and 72%, respectively. The developed empirical models were then applied to all study sites on the Paldang Reservoir to monitor spatio-temporal distributions of TP, BOD, and CHL-a for the month of September using Landsat 5 TM images of the year 2001, 2006, and 2010. The results showed that TP, BOD, and CHL-a decreased from 2001 to 2006 and 2010. However, S3 and S4 still have water quality issues and are influenced by climatic and anthropogenic factors, which could significantly affect reservoir drinking water quality. Overall, the present study suggested that the Landsat 5 TM may be appropriate for estimating and monitoring water quality parameters in the reservoir.
- Subjects :
- chemistry.chemical_classification
Biochemical oxygen demand
010504 meteorology & atmospheric sciences
Correlation coefficient
multiple regression
Science
Empirical modelling
Paldang Reservoir
Soil science
010501 environmental sciences
01 natural sciences
water quality parameters
chemistry.chemical_compound
Nutrient
chemistry
Chlorophyll
Linear regression
General Earth and Planetary Sciences
Environmental science
Organic matter
empirical models
Water quality
0105 earth and related environmental sciences
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 13
- Issue :
- 2256
- Database :
- OpenAIRE
- Journal :
- Remote Sensing
- Accession number :
- edsair.doi.dedup.....02db772cf4d5c693566af33a6fc301f8