Potential of Sentinel Images to Evaluate Physicochemical Parameters Concentrations in Water Bodies—Application in a Wetlands System in Northern Colombia
This research demonstrated the feasibility of applying Sentinel-2 images to generate empirical models and estimate physicochemical parameters concentration, particularly nutrients in the wetland system called Bajo Sinú wetlands complex, Colombia. Spearman correlations were determined between water q...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-02-01
|
| Series: | Water |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4441/15/4/789 |
| _version_ | 1797617753542098944 |
|---|---|
| author | César Padilla-Mendoza Franklin Torres-Bejarano Gabriel Campo-Daza Luis Carlos González-Márquez |
| author_facet | César Padilla-Mendoza Franklin Torres-Bejarano Gabriel Campo-Daza Luis Carlos González-Márquez |
| author_sort | César Padilla-Mendoza |
| collection | DOAJ |
| description | This research demonstrated the feasibility of applying Sentinel-2 images to generate empirical models and estimate physicochemical parameters concentration, particularly nutrients in the wetland system called Bajo Sinú wetlands complex, Colombia. Spearman correlations were determined between water quality parameters, which were monitored at 17 points in the wetland on 5 February 2021, with Sentinel-2 images reflectance values from the same monitoring date; the correlations allowed the identification of statistically significant bands in the multiple linear regression algorithm implementation to determine empirical water quality models. The results show significant correlations between the optically active parameters, TSS-Turbidity, which in turn correlated with the optically inactive parameters Turbidity-NO<sub>3</sub> and TSS-DO, as well as non-optically active parameters among themselves, TDS-NO<sub>3</sub> and TDS-TP; the empirical models presented higher than 74.5% fit (R<sup>2</sup>), particularly DO (R<sup>2</sup> = 0.948), NO<sub>3</sub> (R<sup>2</sup> = 0.858) and TP (R<sup>2</sup> = 0.779) were the models with the highest fits (R<sup>2</sup>). These models allowed us to properly estimate the spatial distribution of nutrient-forming compounds in the wetlands complex. The determinant role played by turbidity in this type of water body is highlighted; it acts as a connecting constituent that makes the estimation of water quality parameters without spectral response through remote sensing feasible. Sentinel-2 images and multiple linear regression algorithms have been shown to be effective in estimating the concentration of water quality parameters without spectral response, such as NO<sub>3</sub> and TP in shallow tropical wetlands, due to the processes of transformation, interaction and dependence between the different environmental variables in aquatic ecosystems. |
| first_indexed | 2024-03-11T08:00:13Z |
| format | Article |
| id | doaj.art-e64fdad24dcf4aa7b28131e5c5c617a0 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-11T08:00:13Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-e64fdad24dcf4aa7b28131e5c5c617a02023-11-16T23:53:31ZengMDPI AGWater2073-44412023-02-0115478910.3390/w15040789Potential of Sentinel Images to Evaluate Physicochemical Parameters Concentrations in Water Bodies—Application in a Wetlands System in Northern ColombiaCésar Padilla-Mendoza0Franklin Torres-Bejarano1Gabriel Campo-Daza2Luis Carlos González-Márquez3Environmental Engineering Department, Universidad de Córdoba, Montería 230002, ColombiaEnvironmental Engineering Department, Universidad de Córdoba, Montería 230002, ColombiaEnvironmental Engineering Department, Universidad de Córdoba, Montería 230002, ColombiaEngineering and Technology Department, Universidad Autónoma de Occidente, Unidad Regional Guasave, Guasave 81048, Sinaloa, MexicoThis research demonstrated the feasibility of applying Sentinel-2 images to generate empirical models and estimate physicochemical parameters concentration, particularly nutrients in the wetland system called Bajo Sinú wetlands complex, Colombia. Spearman correlations were determined between water quality parameters, which were monitored at 17 points in the wetland on 5 February 2021, with Sentinel-2 images reflectance values from the same monitoring date; the correlations allowed the identification of statistically significant bands in the multiple linear regression algorithm implementation to determine empirical water quality models. The results show significant correlations between the optically active parameters, TSS-Turbidity, which in turn correlated with the optically inactive parameters Turbidity-NO<sub>3</sub> and TSS-DO, as well as non-optically active parameters among themselves, TDS-NO<sub>3</sub> and TDS-TP; the empirical models presented higher than 74.5% fit (R<sup>2</sup>), particularly DO (R<sup>2</sup> = 0.948), NO<sub>3</sub> (R<sup>2</sup> = 0.858) and TP (R<sup>2</sup> = 0.779) were the models with the highest fits (R<sup>2</sup>). These models allowed us to properly estimate the spatial distribution of nutrient-forming compounds in the wetlands complex. The determinant role played by turbidity in this type of water body is highlighted; it acts as a connecting constituent that makes the estimation of water quality parameters without spectral response through remote sensing feasible. Sentinel-2 images and multiple linear regression algorithms have been shown to be effective in estimating the concentration of water quality parameters without spectral response, such as NO<sub>3</sub> and TP in shallow tropical wetlands, due to the processes of transformation, interaction and dependence between the different environmental variables in aquatic ecosystems.https://www.mdpi.com/2073-4441/15/4/789wetlandswater quality modelsremote sensing |
| spellingShingle | César Padilla-Mendoza Franklin Torres-Bejarano Gabriel Campo-Daza Luis Carlos González-Márquez Potential of Sentinel Images to Evaluate Physicochemical Parameters Concentrations in Water Bodies—Application in a Wetlands System in Northern Colombia Water wetlands water quality models remote sensing |
| title | Potential of Sentinel Images to Evaluate Physicochemical Parameters Concentrations in Water Bodies—Application in a Wetlands System in Northern Colombia |
| title_full | Potential of Sentinel Images to Evaluate Physicochemical Parameters Concentrations in Water Bodies—Application in a Wetlands System in Northern Colombia |
| title_fullStr | Potential of Sentinel Images to Evaluate Physicochemical Parameters Concentrations in Water Bodies—Application in a Wetlands System in Northern Colombia |
| title_full_unstemmed | Potential of Sentinel Images to Evaluate Physicochemical Parameters Concentrations in Water Bodies—Application in a Wetlands System in Northern Colombia |
| title_short | Potential of Sentinel Images to Evaluate Physicochemical Parameters Concentrations in Water Bodies—Application in a Wetlands System in Northern Colombia |
| title_sort | potential of sentinel images to evaluate physicochemical parameters concentrations in water bodies application in a wetlands system in northern colombia |
| topic | wetlands water quality models remote sensing |
| url | https://www.mdpi.com/2073-4441/15/4/789 |
| work_keys_str_mv | AT cesarpadillamendoza potentialofsentinelimagestoevaluatephysicochemicalparametersconcentrationsinwaterbodiesapplicationinawetlandssysteminnortherncolombia AT franklintorresbejarano potentialofsentinelimagestoevaluatephysicochemicalparametersconcentrationsinwaterbodiesapplicationinawetlandssysteminnortherncolombia AT gabrielcampodaza potentialofsentinelimagestoevaluatephysicochemicalparametersconcentrationsinwaterbodiesapplicationinawetlandssysteminnortherncolombia AT luiscarlosgonzalezmarquez potentialofsentinelimagestoevaluatephysicochemicalparametersconcentrationsinwaterbodiesapplicationinawetlandssysteminnortherncolombia |