Feasible Application of PCLake Model to Predict Water Quality in Tropical Reservoirs
The PCLake model has not previously been used for tropical reservoirs. This study attempted to apply the PCLake model to predict the chlorophyll a concentrations (Chl-a) in a tropical reservoir in Thailand. Sensitivity analyses were performed for the constants affecting the prediction of Chl-a in th...
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| Format: | Article |
| Language: | English |
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Mahidol University
2024-01-01
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| Series: | Environment and Natural Resources Journal |
| Subjects: | |
| Online Access: | https://ph02.tci-thaijo.org/index.php/ennrj/article/view/250923 |
| _version_ | 1797352391304019968 |
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| author | Pongsakorn Wongpipun Sanya Sirivithayapakorn Narumol Vongthanasunthorn |
| author_facet | Pongsakorn Wongpipun Sanya Sirivithayapakorn Narumol Vongthanasunthorn |
| author_sort | Pongsakorn Wongpipun |
| collection | DOAJ |
| description | The PCLake model has not previously been used for tropical reservoirs. This study attempted to apply the PCLake model to predict the chlorophyll a concentrations (Chl-a) in a tropical reservoir in Thailand. Sensitivity analyses were performed for the constants affecting the prediction of Chl-a in the phytoplankton module. The model calibration was performed by using the adjusted value of the most sensitive constant with the observed data from July to December 2020. The effects of the initial trophic state of the reservoir on the simulated Chl-a were evaluated. The results showed that Chl-a were sensitive to six constants. Among these constants, the value of the specific extinction of detritus (cExtSpDet) was adjusted using the calculated values from the typical limnological parameters of the studied reservoir. Statistical analyses of the results of calibration and the subsequent validation with the observed data from February to September 2022 were listed as follows: NSE=0.55 and 0.37, RSR=0.67 and 0.79, and PBIAS=27% and 9%, respectively. The initial trophic state of the reservoir had no influence on the long-term prediction of Chl-a. This preliminary effort indicates that the PCLake model can be used to predict Chl-a, which is representative of algal biomass in tropical reservoirs and is essential to water quality models, without complex modifications. |
| first_indexed | 2024-03-08T13:15:50Z |
| format | Article |
| id | doaj.art-e3ffd603e627426386dbb9667134038f |
| institution | Directory Open Access Journal |
| issn | 1686-5456 2408-2384 |
| language | English |
| last_indexed | 2024-03-08T13:15:50Z |
| publishDate | 2024-01-01 |
| publisher | Mahidol University |
| record_format | Article |
| series | Environment and Natural Resources Journal |
| spelling | doaj.art-e3ffd603e627426386dbb9667134038f2024-01-18T08:26:36ZengMahidol UniversityEnvironment and Natural Resources Journal1686-54562408-23842024-01-01221344310.32526/ennrj/22/20230251Feasible Application of PCLake Model to Predict Water Quality in Tropical ReservoirsPongsakorn Wongpipun0Sanya Sirivithayapakorn1Narumol Vongthanasunthorn2Department of Environmental Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900, ThailandDepartment of Environmental Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900, ThailandFaculty of Science and Engineering, Saga University, Saga City, JapanThe PCLake model has not previously been used for tropical reservoirs. This study attempted to apply the PCLake model to predict the chlorophyll a concentrations (Chl-a) in a tropical reservoir in Thailand. Sensitivity analyses were performed for the constants affecting the prediction of Chl-a in the phytoplankton module. The model calibration was performed by using the adjusted value of the most sensitive constant with the observed data from July to December 2020. The effects of the initial trophic state of the reservoir on the simulated Chl-a were evaluated. The results showed that Chl-a were sensitive to six constants. Among these constants, the value of the specific extinction of detritus (cExtSpDet) was adjusted using the calculated values from the typical limnological parameters of the studied reservoir. Statistical analyses of the results of calibration and the subsequent validation with the observed data from February to September 2022 were listed as follows: NSE=0.55 and 0.37, RSR=0.67 and 0.79, and PBIAS=27% and 9%, respectively. The initial trophic state of the reservoir had no influence on the long-term prediction of Chl-a. This preliminary effort indicates that the PCLake model can be used to predict Chl-a, which is representative of algal biomass in tropical reservoirs and is essential to water quality models, without complex modifications.https://ph02.tci-thaijo.org/index.php/ennrj/article/view/250923pclakealgaeeutrophicationlakenutrientreservoir |
| spellingShingle | Pongsakorn Wongpipun Sanya Sirivithayapakorn Narumol Vongthanasunthorn Feasible Application of PCLake Model to Predict Water Quality in Tropical Reservoirs Environment and Natural Resources Journal pclake algae eutrophication lake nutrient reservoir |
| title | Feasible Application of PCLake Model to Predict Water Quality in Tropical Reservoirs |
| title_full | Feasible Application of PCLake Model to Predict Water Quality in Tropical Reservoirs |
| title_fullStr | Feasible Application of PCLake Model to Predict Water Quality in Tropical Reservoirs |
| title_full_unstemmed | Feasible Application of PCLake Model to Predict Water Quality in Tropical Reservoirs |
| title_short | Feasible Application of PCLake Model to Predict Water Quality in Tropical Reservoirs |
| title_sort | feasible application of pclake model to predict water quality in tropical reservoirs |
| topic | pclake algae eutrophication lake nutrient reservoir |
| url | https://ph02.tci-thaijo.org/index.php/ennrj/article/view/250923 |
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