Geostatistical approach in estimating the capacity volume of the mudflow reservoir
Mudflow reservoirs play a crucial role in mitigating flood risks triggered by natural events like heavy rains and snowmelt, safeguarding surrounding areas from potential inundation. However, sedimentation poses a significant challenge by reducing the capacity and effectiveness of these mudflow reser...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2024-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/120/e3sconf_gi2024_07003.pdf |
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| author | Khasanov Khojiakbar Babajanova Nodira Chymyrov Akylbek Reyimov Dayanch Salokhitdinova Sevar |
| author_facet | Khasanov Khojiakbar Babajanova Nodira Chymyrov Akylbek Reyimov Dayanch Salokhitdinova Sevar |
| author_sort | Khasanov Khojiakbar |
| collection | DOAJ |
| description | Mudflow reservoirs play a crucial role in mitigating flood risks triggered by natural events like heavy rains and snowmelt, safeguarding surrounding areas from potential inundation. However, sedimentation poses a significant challenge by reducing the capacity and effectiveness of these mudflow reservoirs over time. This study focused on estimating the capacity of the Kalkama mudflow reservoir, constructed in 1987, using a geostatistical approach. Bathymetric survey data were analyzed using various interpolation methods. Kriging (Ordinary Kriging) provided the best performance with the lowest RMSE (0.28) and a high R² (0.99), indicating it is the most accurate method for this dataset. Based on this method, a spatial model of the mudflow reservoir was developed to assess its current capacity. Findings indicate a capacity loss of 2.33 million m³ (23.6%) over 36 years, alongside a 22% reduction in surface area at Full Storage Level, and the dead volume was completely filled with sediment. |
| format | Article |
| id | doaj-art-7824038410a142b98bf842b6f1757ce2 |
| institution | Kabale University |
| issn | 2267-1242 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj-art-7824038410a142b98bf842b6f1757ce22024-11-21T11:28:29ZengEDP SciencesE3S Web of Conferences2267-12422024-01-015900700310.1051/e3sconf/202459007003e3sconf_gi2024_07003Geostatistical approach in estimating the capacity volume of the mudflow reservoirKhasanov Khojiakbar0Babajanova Nodira1Chymyrov Akylbek2Reyimov Dayanch3Salokhitdinova Sevar4"Tashkent Institute of Irrigation and Agricultural Mechanization Engineers" National Research University"Tashkent Institute of Irrigation and Agricultural Mechanization Engineers" National Research UniversityKyrgyz State Technical University named after I. RazzakovInternational horse breeding academy named after Aba AnnaevNational University of Uzbekistan named after Mirzo UlugbekMudflow reservoirs play a crucial role in mitigating flood risks triggered by natural events like heavy rains and snowmelt, safeguarding surrounding areas from potential inundation. However, sedimentation poses a significant challenge by reducing the capacity and effectiveness of these mudflow reservoirs over time. This study focused on estimating the capacity of the Kalkama mudflow reservoir, constructed in 1987, using a geostatistical approach. Bathymetric survey data were analyzed using various interpolation methods. Kriging (Ordinary Kriging) provided the best performance with the lowest RMSE (0.28) and a high R² (0.99), indicating it is the most accurate method for this dataset. Based on this method, a spatial model of the mudflow reservoir was developed to assess its current capacity. Findings indicate a capacity loss of 2.33 million m³ (23.6%) over 36 years, alongside a 22% reduction in surface area at Full Storage Level, and the dead volume was completely filled with sediment.https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/120/e3sconf_gi2024_07003.pdf |
| spellingShingle | Khasanov Khojiakbar Babajanova Nodira Chymyrov Akylbek Reyimov Dayanch Salokhitdinova Sevar Geostatistical approach in estimating the capacity volume of the mudflow reservoir E3S Web of Conferences |
| title | Geostatistical approach in estimating the capacity volume of the mudflow reservoir |
| title_full | Geostatistical approach in estimating the capacity volume of the mudflow reservoir |
| title_fullStr | Geostatistical approach in estimating the capacity volume of the mudflow reservoir |
| title_full_unstemmed | Geostatistical approach in estimating the capacity volume of the mudflow reservoir |
| title_short | Geostatistical approach in estimating the capacity volume of the mudflow reservoir |
| title_sort | geostatistical approach in estimating the capacity volume of the mudflow reservoir |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/120/e3sconf_gi2024_07003.pdf |
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