Enclosed Karst Depression Identification and Analysis for the Pumped Storage Power Station Reservoir Construction Using DEM
An enclosed karst depression, a typical natural negative terrain, has the advantage of less engineering excavation when constructing a reservoir. In this study, the enclosed karst depression and its range identification technique have been developed. What is more, the geometric parameters and spatia...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Geofluids |
| Online Access: | http://dx.doi.org/10.1155/2023/4794665 |
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| author | Yu Bo Zhang Tao Zheng Kexun Zuo Shuangying Han Xiao Wang Senlin Chen Shiwan |
| author_facet | Yu Bo Zhang Tao Zheng Kexun Zuo Shuangying Han Xiao Wang Senlin Chen Shiwan |
| author_sort | Yu Bo |
| collection | DOAJ |
| description | An enclosed karst depression, a typical natural negative terrain, has the advantage of less engineering excavation when constructing a reservoir. In this study, the enclosed karst depression and its range identification technique have been developed. What is more, the geometric parameters and spatial distribution of enclosed karst depressions in Anlong County, Guizhou Province of China, have also been analyzed. Results show that (1) the focus statistic method and local terrain contour tree model were developed to identify enclosed karst depression and its range using regular grid DEM data with 12.5 m spatial resolution, which has been applied to enclosed karst depression identification in Anlong County. (2) 7262 independent and nested depressions with an average density of 3.7/km2 were identified by using the proposed method. The effectiveness and reliability of the proposed model have been verified through comparative analysis and visual recognition comparison. (3) High-density depression areas (5.6 depressions/km2), medium-density depression areas (2.9 depressions/km2), and low-density depression areas (1.1 depressions/km2) were well classified through kernel density analysis. (4) The geometric parameters of enclosed karst depressions (area, perimeter, circularity, depth, elevation, slope, and volume) were all analyzed in the study area. In addition, an indicator called DCK (depression is caused by karstification) was proposed to evaluate the dissolution degree and karstification stage of the enclosed karst depression. Based on the DCK, we determined that around 2.7% of depressions were identified as middle-stage and suitable for reservoir construction with enough volume and good slope stability. The idea and method in this research could provide a technological support for the engineering utilization of enclosed karst depressions. |
| format | Article |
| id | doaj-art-727cb481140a4fdfb6399ec44b0acbd4 |
| institution | Kabale University |
| issn | 1468-8123 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geofluids |
| spelling | doaj-art-727cb481140a4fdfb6399ec44b0acbd42025-02-03T01:29:28ZengWileyGeofluids1468-81232023-01-01202310.1155/2023/4794665Enclosed Karst Depression Identification and Analysis for the Pumped Storage Power Station Reservoir Construction Using DEMYu Bo0Zhang Tao1Zheng Kexun2Zuo Shuangying3Han Xiao4Wang Senlin5Chen Shiwan6Power China Guiyang Engineering Corporation LimitedKey Laboratory of Karst Georesources and EnvironmentPower China Guiyang Engineering Corporation LimitedKey Laboratory of Karst Georesources and EnvironmentPower China Guiyang Engineering Corporation LimitedPower China Guiyang Engineering Corporation LimitedKey Laboratory of Karst Georesources and EnvironmentAn enclosed karst depression, a typical natural negative terrain, has the advantage of less engineering excavation when constructing a reservoir. In this study, the enclosed karst depression and its range identification technique have been developed. What is more, the geometric parameters and spatial distribution of enclosed karst depressions in Anlong County, Guizhou Province of China, have also been analyzed. Results show that (1) the focus statistic method and local terrain contour tree model were developed to identify enclosed karst depression and its range using regular grid DEM data with 12.5 m spatial resolution, which has been applied to enclosed karst depression identification in Anlong County. (2) 7262 independent and nested depressions with an average density of 3.7/km2 were identified by using the proposed method. The effectiveness and reliability of the proposed model have been verified through comparative analysis and visual recognition comparison. (3) High-density depression areas (5.6 depressions/km2), medium-density depression areas (2.9 depressions/km2), and low-density depression areas (1.1 depressions/km2) were well classified through kernel density analysis. (4) The geometric parameters of enclosed karst depressions (area, perimeter, circularity, depth, elevation, slope, and volume) were all analyzed in the study area. In addition, an indicator called DCK (depression is caused by karstification) was proposed to evaluate the dissolution degree and karstification stage of the enclosed karst depression. Based on the DCK, we determined that around 2.7% of depressions were identified as middle-stage and suitable for reservoir construction with enough volume and good slope stability. The idea and method in this research could provide a technological support for the engineering utilization of enclosed karst depressions.http://dx.doi.org/10.1155/2023/4794665 |
| spellingShingle | Yu Bo Zhang Tao Zheng Kexun Zuo Shuangying Han Xiao Wang Senlin Chen Shiwan Enclosed Karst Depression Identification and Analysis for the Pumped Storage Power Station Reservoir Construction Using DEM Geofluids |
| title | Enclosed Karst Depression Identification and Analysis for the Pumped Storage Power Station Reservoir Construction Using DEM |
| title_full | Enclosed Karst Depression Identification and Analysis for the Pumped Storage Power Station Reservoir Construction Using DEM |
| title_fullStr | Enclosed Karst Depression Identification and Analysis for the Pumped Storage Power Station Reservoir Construction Using DEM |
| title_full_unstemmed | Enclosed Karst Depression Identification and Analysis for the Pumped Storage Power Station Reservoir Construction Using DEM |
| title_short | Enclosed Karst Depression Identification and Analysis for the Pumped Storage Power Station Reservoir Construction Using DEM |
| title_sort | enclosed karst depression identification and analysis for the pumped storage power station reservoir construction using dem |
| url | http://dx.doi.org/10.1155/2023/4794665 |
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