Spatiotemporal evolution of deformation and LSTM prediction model over the slope of the deep excavation section at the head of the South-North Water Transfer Middle Route Canal
Slope deformation is one of the focal issues of concern during the normal operation and maintenance of the South-North Water Transfer Middle Route Project. To study the slope deformation evolution in the deep excavation section at the head of the canal, we applied 88 views of Sentinel-1A ascending i...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-02-01
|
| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024023326 |
| _version_ | 1797267653824348160 |
|---|---|
| author | Laizhong Ding Chunyi Li Zhen Lei Changjie Zhang Lei Wei Zengzhang Guo Ying Li Xin Fan Daokun Qi Junjian Wang |
| author_facet | Laizhong Ding Chunyi Li Zhen Lei Changjie Zhang Lei Wei Zengzhang Guo Ying Li Xin Fan Daokun Qi Junjian Wang |
| author_sort | Laizhong Ding |
| collection | DOAJ |
| description | Slope deformation is one of the focal issues of concern during the normal operation and maintenance of the South-North Water Transfer Middle Route Project. To study the slope deformation evolution in the deep excavation section at the head of the canal, we applied 88 views of Sentinel-1A ascending image data from 2017 to 2019 and MT-InSAR(Multi-temporal InSAR) deformation monitoring technology to obtain long-time series deformation rates and cumulative deformation fields over the slope in the study area. Based on the analysis of the time-series monitoring data of the deformation field sample points, a LSTM (Long Short Term Memory Network) slope deformation predictive model was constructed to predict the slope deformation for the next 12 months at 12 sample points of the deep excavation slope. The impact of rainfall on slope deformation was investigated, and the reliability of the LSTM model was verified by using the measured data. The results show that the average annual deformation rate of the slope ranges from 10mm/a to 25mm/a, the maximum cumulative deformation is about 60 mm, and the slope of the excavated section is generally in an uplifted state. The rainfall-induced repeated uplift or subsidence of the canal slopes together with the peak deformation was closely related to the amount of rainfall during the wet season, and the longer the duration of the wet season, the more obvious the crest. Among the12 sample sites, the minimum and maximum deformation predicted using the LSTM model were 51.7 mm and 73.9 mm respectively, with the lowest correlation coefficient of 0.994 and the highest of 0.999. The maximum and minimum values of RMSE (Root Mean Square Error) were 4.4 mm and 3.6 mm respectively, indicating reliable prediction results. The results of the study can provide reference for the prevention and control of geological hazards in the South-North Water Transfer Canal. |
| first_indexed | 2024-03-08T00:08:50Z |
| format | Article |
| id | doaj.art-1eba1d07188c4ceaa1d6a14463243507 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-25T01:20:01Z |
| publishDate | 2024-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-1eba1d07188c4ceaa1d6a144632435072024-03-09T09:27:54ZengElsevierHeliyon2405-84402024-02-01104e26301Spatiotemporal evolution of deformation and LSTM prediction model over the slope of the deep excavation section at the head of the South-North Water Transfer Middle Route CanalLaizhong Ding0Chunyi Li1Zhen Lei2Changjie Zhang3Lei Wei4Zengzhang Guo5Ying Li6Xin Fan7Daokun Qi8Junjian Wang9School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, 454000, China; Institute of Surveying Mapping and Geoinformation, Zhengzhou, 450007, ChinaSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, 454000, China; Corresponding author.Institute of Surveying Mapping and Geoinformation, Zhengzhou, 450007, ChinaInstitute of Surveying Mapping and Geoinformation, Zhengzhou, 450007, ChinaInstitute of Surveying Mapping and Geoinformation, Zhengzhou, 450007, China; Corresponding author.School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, 454000, ChinaInstitute of Surveying Mapping and Geoinformation, Zhengzhou, 450007, ChinaInstitute of Surveying Mapping and Geoinformation, Zhengzhou, 450007, ChinaState Grid Henan Economic Research Institute, Zhengzhou, 450007, ChinaInstitute of Surveying Mapping and Geoinformation, Zhengzhou, 450007, ChinaSlope deformation is one of the focal issues of concern during the normal operation and maintenance of the South-North Water Transfer Middle Route Project. To study the slope deformation evolution in the deep excavation section at the head of the canal, we applied 88 views of Sentinel-1A ascending image data from 2017 to 2019 and MT-InSAR(Multi-temporal InSAR) deformation monitoring technology to obtain long-time series deformation rates and cumulative deformation fields over the slope in the study area. Based on the analysis of the time-series monitoring data of the deformation field sample points, a LSTM (Long Short Term Memory Network) slope deformation predictive model was constructed to predict the slope deformation for the next 12 months at 12 sample points of the deep excavation slope. The impact of rainfall on slope deformation was investigated, and the reliability of the LSTM model was verified by using the measured data. The results show that the average annual deformation rate of the slope ranges from 10mm/a to 25mm/a, the maximum cumulative deformation is about 60 mm, and the slope of the excavated section is generally in an uplifted state. The rainfall-induced repeated uplift or subsidence of the canal slopes together with the peak deformation was closely related to the amount of rainfall during the wet season, and the longer the duration of the wet season, the more obvious the crest. Among the12 sample sites, the minimum and maximum deformation predicted using the LSTM model were 51.7 mm and 73.9 mm respectively, with the lowest correlation coefficient of 0.994 and the highest of 0.999. The maximum and minimum values of RMSE (Root Mean Square Error) were 4.4 mm and 3.6 mm respectively, indicating reliable prediction results. The results of the study can provide reference for the prevention and control of geological hazards in the South-North Water Transfer Canal.http://www.sciencedirect.com/science/article/pii/S2405844024023326South-North Water TransferMT-InSARExpansive soilsLSTM |
| spellingShingle | Laizhong Ding Chunyi Li Zhen Lei Changjie Zhang Lei Wei Zengzhang Guo Ying Li Xin Fan Daokun Qi Junjian Wang Spatiotemporal evolution of deformation and LSTM prediction model over the slope of the deep excavation section at the head of the South-North Water Transfer Middle Route Canal Heliyon South-North Water Transfer MT-InSAR Expansive soils LSTM |
| title | Spatiotemporal evolution of deformation and LSTM prediction model over the slope of the deep excavation section at the head of the South-North Water Transfer Middle Route Canal |
| title_full | Spatiotemporal evolution of deformation and LSTM prediction model over the slope of the deep excavation section at the head of the South-North Water Transfer Middle Route Canal |
| title_fullStr | Spatiotemporal evolution of deformation and LSTM prediction model over the slope of the deep excavation section at the head of the South-North Water Transfer Middle Route Canal |
| title_full_unstemmed | Spatiotemporal evolution of deformation and LSTM prediction model over the slope of the deep excavation section at the head of the South-North Water Transfer Middle Route Canal |
| title_short | Spatiotemporal evolution of deformation and LSTM prediction model over the slope of the deep excavation section at the head of the South-North Water Transfer Middle Route Canal |
| title_sort | spatiotemporal evolution of deformation and lstm prediction model over the slope of the deep excavation section at the head of the south north water transfer middle route canal |
| topic | South-North Water Transfer MT-InSAR Expansive soils LSTM |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024023326 |
| work_keys_str_mv | AT laizhongding spatiotemporalevolutionofdeformationandlstmpredictionmodelovertheslopeofthedeepexcavationsectionattheheadofthesouthnorthwatertransfermiddleroutecanal AT chunyili spatiotemporalevolutionofdeformationandlstmpredictionmodelovertheslopeofthedeepexcavationsectionattheheadofthesouthnorthwatertransfermiddleroutecanal AT zhenlei spatiotemporalevolutionofdeformationandlstmpredictionmodelovertheslopeofthedeepexcavationsectionattheheadofthesouthnorthwatertransfermiddleroutecanal AT changjiezhang spatiotemporalevolutionofdeformationandlstmpredictionmodelovertheslopeofthedeepexcavationsectionattheheadofthesouthnorthwatertransfermiddleroutecanal AT leiwei spatiotemporalevolutionofdeformationandlstmpredictionmodelovertheslopeofthedeepexcavationsectionattheheadofthesouthnorthwatertransfermiddleroutecanal AT zengzhangguo spatiotemporalevolutionofdeformationandlstmpredictionmodelovertheslopeofthedeepexcavationsectionattheheadofthesouthnorthwatertransfermiddleroutecanal AT yingli spatiotemporalevolutionofdeformationandlstmpredictionmodelovertheslopeofthedeepexcavationsectionattheheadofthesouthnorthwatertransfermiddleroutecanal AT xinfan spatiotemporalevolutionofdeformationandlstmpredictionmodelovertheslopeofthedeepexcavationsectionattheheadofthesouthnorthwatertransfermiddleroutecanal AT daokunqi spatiotemporalevolutionofdeformationandlstmpredictionmodelovertheslopeofthedeepexcavationsectionattheheadofthesouthnorthwatertransfermiddleroutecanal AT junjianwang spatiotemporalevolutionofdeformationandlstmpredictionmodelovertheslopeofthedeepexcavationsectionattheheadofthesouthnorthwatertransfermiddleroutecanal |