Random Forest modelling and evaluation of the performance of a full-scale subsurface constructed wetland plant in Egypt
This article presents a methodology to evaluate and model the performance of subsurface horizontal constructed wetland (SHCW) in Samaha village, Egypt's Delta. The influent and effluent biological oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), total phosphorus...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-11-01
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| Series: | Ain Shams Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2090447922000892 |
| _version_ | 1811296045018120192 |
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| author | Madleen Salem Mohamed EL-Sayed Gabr Mohamed Mossad Hani Mahanna |
| author_facet | Madleen Salem Mohamed EL-Sayed Gabr Mohamed Mossad Hani Mahanna |
| author_sort | Madleen Salem |
| collection | DOAJ |
| description | This article presents a methodology to evaluate and model the performance of subsurface horizontal constructed wetland (SHCW) in Samaha village, Egypt's Delta. The influent and effluent biological oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), total phosphorus (TP), and total nitrogen (TN) were measured and analyzed for the period 2018–2020. The Random Forest process (RF) was applied to predict the removal efficiency of BOD, COD, and TSS using 112 samples, 90% of samples were used as training and 10% as a test. The results show removal efficiency of 72, 77, 78, 49, and 31%, for BOD, COD, TSS, TP, and TN respectively. The Random Forest modeling fit the results well with coefficient of determination (R2) for removal efficiency of BOD, COD, and TSS equal to 0.66, 0.68, and 0.79, respectively. The Random Forest process is a good way to come up with effective management and mitigation strategies. |
| first_indexed | 2024-04-13T05:42:37Z |
| format | Article |
| id | doaj.art-e0257a91a72b4d1682c2c1d47fa665f1 |
| institution | Directory Open Access Journal |
| issn | 2090-4479 |
| language | English |
| last_indexed | 2024-04-13T05:42:37Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ain Shams Engineering Journal |
| spelling | doaj.art-e0257a91a72b4d1682c2c1d47fa665f12022-12-22T03:00:03ZengElsevierAin Shams Engineering Journal2090-44792022-11-01136101778Random Forest modelling and evaluation of the performance of a full-scale subsurface constructed wetland plant in EgyptMadleen Salem0Mohamed EL-Sayed Gabr1Mohamed Mossad2Hani Mahanna3Public Works Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt. In addition, she is working as a civil Engineer in the Higher Institue for Engineering and Technology New DammiettaHead of Civil Engineering Department, Higher Institute for Engineering and Technology, New Dammietta, Ministry of Higher Education, Egypt; Corresponding author.Public Works Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, EgyptPublic Works Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, EgyptThis article presents a methodology to evaluate and model the performance of subsurface horizontal constructed wetland (SHCW) in Samaha village, Egypt's Delta. The influent and effluent biological oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), total phosphorus (TP), and total nitrogen (TN) were measured and analyzed for the period 2018–2020. The Random Forest process (RF) was applied to predict the removal efficiency of BOD, COD, and TSS using 112 samples, 90% of samples were used as training and 10% as a test. The results show removal efficiency of 72, 77, 78, 49, and 31%, for BOD, COD, TSS, TP, and TN respectively. The Random Forest modeling fit the results well with coefficient of determination (R2) for removal efficiency of BOD, COD, and TSS equal to 0.66, 0.68, and 0.79, respectively. The Random Forest process is a good way to come up with effective management and mitigation strategies.http://www.sciencedirect.com/science/article/pii/S2090447922000892BOD removalSubsurface horizontal constructed wetlandPhosphorus removalRandom ForestSewage |
| spellingShingle | Madleen Salem Mohamed EL-Sayed Gabr Mohamed Mossad Hani Mahanna Random Forest modelling and evaluation of the performance of a full-scale subsurface constructed wetland plant in Egypt Ain Shams Engineering Journal BOD removal Subsurface horizontal constructed wetland Phosphorus removal Random Forest Sewage |
| title | Random Forest modelling and evaluation of the performance of a full-scale subsurface constructed wetland plant in Egypt |
| title_full | Random Forest modelling and evaluation of the performance of a full-scale subsurface constructed wetland plant in Egypt |
| title_fullStr | Random Forest modelling and evaluation of the performance of a full-scale subsurface constructed wetland plant in Egypt |
| title_full_unstemmed | Random Forest modelling and evaluation of the performance of a full-scale subsurface constructed wetland plant in Egypt |
| title_short | Random Forest modelling and evaluation of the performance of a full-scale subsurface constructed wetland plant in Egypt |
| title_sort | random forest modelling and evaluation of the performance of a full scale subsurface constructed wetland plant in egypt |
| topic | BOD removal Subsurface horizontal constructed wetland Phosphorus removal Random Forest Sewage |
| url | http://www.sciencedirect.com/science/article/pii/S2090447922000892 |
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