Yu‐Ling Bo, Z. Tao, Zheng Kexun, S. Zuo, Han Xiao, Senlin Wang, Shiwan Chen
{"title":"基于DEM的抽水蓄能电站水库建设封闭岩溶凹陷识别与分析","authors":"Yu‐Ling Bo, Z. Tao, Zheng Kexun, S. Zuo, Han Xiao, Senlin Wang, Shiwan Chen","doi":"10.1155/2023/4794665","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":12512,"journal":{"name":"Geofluids","volume":" ","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2023-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enclosed Karst Depression Identification and Analysis for the Pumped Storage Power Station Reservoir Construction Using DEM\",\"authors\":\"Yu‐Ling Bo, Z. Tao, Zheng Kexun, S. Zuo, Han Xiao, Senlin Wang, Shiwan Chen\",\"doi\":\"10.1155/2023/4794665\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":12512,\"journal\":{\"name\":\"Geofluids\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2023-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geofluids\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1155/2023/4794665\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GEOCHEMISTRY & GEOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geofluids","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1155/2023/4794665","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
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 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.
期刊介绍:
Geofluids is a peer-reviewed, Open Access journal that provides a forum for original research and reviews relating to the role of fluids in mineralogical, chemical, and structural evolution of the Earth’s crust. Its explicit aim is to disseminate ideas across the range of sub-disciplines in which Geofluids research is carried out. To this end, authors are encouraged to stress the transdisciplinary relevance and international ramifications of their research. Authors are also encouraged to make their work as accessible as possible to readers from other sub-disciplines.
Geofluids emphasizes chemical, microbial, and physical aspects of subsurface fluids throughout the Earth’s crust. Geofluids spans studies of groundwater, terrestrial or submarine geothermal fluids, basinal brines, petroleum, metamorphic waters or magmatic fluids.