高山峡谷区MPSIAC侵蚀模型适用性研究

武彬彬; 常鸣; 唐亮亮; 刘沛源; 罗超鹏

doi:10.3799/dqkx.2023.134

高山峡谷区MPSIAC侵蚀模型适用性研究

doi: 10.3799/dqkx.2023.134

武彬彬^{1, 2, ,},
常鸣^1, ,,
唐亮亮¹,
刘沛源¹,
罗超鹏¹

1.
成都理工大学地质灾害防治与地质环境保护国家重点实验室, 四川成都 610059
2.
山西华冶勘测工程技术有限公司, 山西太原 030032

基金项目:

第二次青藏高原综合科学考察研究 2019QZKK0902

四川省自然科学基金项目 2024NSFSC0071

详细信息

作者简介:
武彬彬（1998-），硕士研究生，主要从事遥感与地质灾害早期识别研究. ORCID：0000-0001-5409-2682. E-mail：wubinbin@stu.cdut.edu.cn

通讯作者:
常鸣(1985-)，教授，博士，E-mail：changmxq@126.com

中图分类号: P642.23
计量
- 文章访问数: 298
- HTML全文浏览量: 109
- PDF下载量: 34
- 被引次数: 0
出版历程
- 收稿日期: 2022-07-07
- 网络出版日期: 2024-11-08
- 刊出日期: 2024-10-25

Study on Surface Erosion Intensity in Alpine Valley Area

1.
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China
2.
Shanxi Huaye Survey Engineering Technology Co., Ltd., Taiyuan 030032, China

摘要

摘要: 地表侵蚀能够对环境产生巨大的影响，强烈的地表侵蚀是崩塌、滑坡和泥石流等地质灾害的诱发因素.高山峡谷地区地质地貌条件复杂、地表水动力高度发育，区内大范围存在高强度的地表侵蚀.以川西典型高山峡谷区松潘县为研究区，在详细调查区域侵蚀现状的基础上，基于MPSIAC模型建立了高山峡谷地表侵蚀能力评价体系，对松潘县全域进行地表侵蚀强度评价并利用InSAR技术对评价结果进行检验.结果表明，松潘县地表侵蚀强度较高处主要分布于县域东南部岷江乡、镇江关乡等地，较低处主要分布于北部毛儿盖镇、川主寺镇等地.MPSIAC模型经过修正后可以对高山峡谷地区地表侵蚀能力做出准确的评价.
- 高山峡谷地区 /
- MPSIAC模型 /
- 侵蚀强度 /
- InSAR技术 /
- 工程地质学
Abstract: The development of geological disasters is often affected by the surface erosion environment. Landform processes such as collapse, landslide, and debris flow are the most intuitive embodiment of surface erosion. The geological and geomorphological conditions are complex and the surface hydrodynamics are highly developed in alpine canyon areas. In this paper it takes Songpan County, a typical alpine canyon in West Sichuan Province, as the research area. The alpine canyon's surface erosion capacity evaluation system was established based on the MPSIAC model after a detailed investigation of regional erosion status. The surface erosion capacity evaluation of Songpan County was carried out, and the InSAR technology was used to test this result. The result shows that the high-intensity surface erosion of Songpan County is distributed in Minjiang Town and Zhenjiangguan Town in the southeast. In contrast, the low-intensity surface erosion of Songpan County is mainly distributed in Maoergai Town and Chuanzhusi Town in the north.The MPSIAC model can be modified to accurately evaluate surface erosion capacity in alpine canyon areas.
- alpine canyon area /
- MPSIAC model /
- erosion intensity /
- InSAR technology /
- engineering geology

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图 1 研究区地理位置

Fig. 1. The location of the study area

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图 2 研究区地质岩组分布

Fig. 2. The distribution of lithology in the study area

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图 3 研究区土壤分布

Fig. 3. The distribution of soil in the study area

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图 4 研究区降雨分布

Fig. 4. The distribution of rainfall in the study area

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图 5 研究区土地利用类型(a)和地表径流(b)

Fig. 5. The distribution of land use (a) and runoff (b) in the study area

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图 6 研究区坡度

Fig. 6. The distribution of slope in the study area

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图 7 研究区NDVI

Fig. 7. The distribution of NDVI in the study area

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图 8 研究区河流侵蚀指数

Fig. 8. The distribution of SPI in the study area

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图 9 研究区泥石流分布(a)和野外调查(b~e)

Fig. 9. The distribution of debris flow (a) and field investigation of debris flow (b-e) in the study area

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图 10 研究区高地侵蚀及相关因子

Fig. 10. Upland erosion and factors in the study area

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图 11 研究区侵蚀强度

Fig. 11. Erosion intensity in the study area

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图 12 InSAR技术对比验证

Fig. 12. InSAR comparison validation

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图 13 青川县验证区侵蚀强度与InSAR形变对比验证图

Fig. 13. The InSAR comparison validation and erosion intensity of Qingchuan County verification area

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表 1 地表地质得分

Table 1. The weight scores of surface geological

分类	评价指标	Y₁
松散土体	非均质, 欠固结	8
碎屑岩	高度易碎岩石	6
碳酸岩	软硬相间的块状岩石	2
变质岩	完整性差，呈薄片-碎片状结构	7
岩浆岩	坚硬的整体状侵入岩岩组	0

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表 2 不同土地利用下的CN值

Table 2. CN values under the different land use

土壤湿度	干燥	适中	湿润
耕地	55	74	88
灌木地	36	56	76
林地	35	55	74
草地	38	58	76
裸荒地	72	86	94
沼泽地	40	60	78
建筑用地	57	79	93
旱地	51	70	85
水域	100	100	100

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表 3 研究区SAR数据参数

Table 3. SAR data parameters in the study area

轨道方向	成像模式	波段	波长(cm)	地面分辨率(m)	重访周期(d)	视角(°)	极化方式
降轨	IW	C	5.6	5×20	12	39	VV

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参考文献(48)

Abdullah, M., Feagin, R., Musawi, L., 2017. The Use of Spatial Empirical Models to Estimate Soil Erosion in Arid Ecosystems. Environmental Monitoring and Assessment, 189(2): 78. https://doi.org/10.1007/s10661-017-5784-y
Abuzied, S. M., Pradhan, B., 2021. Hydro-Geomorphic Assessment of Erosion Intensity and Sediment Yield Initiated Debris-Flow Hazards at Wadi Dahab Watershed, Egypt. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 15(3): 221-246. https://doi.org/10.1080/17499518.2020.1753781
Alijani, A., Alijani, A., Ghadimvand, N. K., et al., 2017. Analyzing Factors Affecting Erosion and Sedimentary Deposits Using the Empirical Method of PSIAC. Open Journal of Geology, 7(8): 1078-1093. https://doi.org/10.4236/ojg.2017.78072
Arabameri, A., Tiefenbacher, J. P., Blaschke, T., et al., 2020. Morphometric Analysis for Soil Erosion Susceptibility Mapping Using Novel GIS-Based Ensemble Model. Remote Sensing, 12(5): 874. https://doi.org/10.3390/rs12050874
Cruslock, E. M., Naylor, L. A., Foote, Y. L., et al., 2010. Geomorphologic Equifinality: A Comparison between Shore Platforms in Höga Kusten and FÅRÖ, Sweden and the Vale of Glamorgan, South Wales, UK. Geomorphology, 114(1-2): 78-88. https://doi.org/10.1016/j.geomorph.2009.02.019
Daneshvar, M. R. M., Bagherzadeh, A., 2012. Evaluation of Sediment Yield in PSIAC and MPSIAC Models by Using GIS at Toroq Watershed, Northeast of Iran. Frontiers of Earth Science, 6(1): 83-94. https://doi.org/10.1007/s11707-011-0189-7
Dragičević, N., Karleuša, B., Ožanić, N., 2019. Different Approaches to Estimation of Drainage Density and Their Effect on the Erosion Potential Method. Water, 11(3): 593. https://doi.org/10.3390/w11030593
Guo, B., Tao, H. P., Liu, B. T., et al., 2012. Characteristics and Analysis of Soil Erosion in Li Count after Wenchuan Earthquake Based on GIS and USLE. Transactions of the Chinese Society of Agricultural Engineering, 28(14): 118-126 (in Chinese with English abstract).
Hou, N., Wang, Y., Zhao, H., et al., 2021. Effects of Tillage Erosion on Sediment Yield of Purple Soil under Different Slopes. Mountain Research, 39(4): 495-505 (in Chinese with English abstract).
Lee, S., An, H., Kim, M., et al., 2022. A Simple Deposition Model for Debris Flow Simulation Considering the Erosion-Entrainment-Deposition Process. Remote Sensing, 14(8): 1904. https://doi.org/10.3390/rs14081904
Li, G., 2015. The Assessment of Debris Flow Risk Based on GIS (Dissertation). China University of Geosciences, Beijing (in Chinese with English abstract).
Li, Z. X., Zhao, H., Zou, H. T., et al., 2019. Comparison of Soil Erosion Estimation Methods at County Scale Based on CSLE Model and Sampling Unit. Transactions of the Chinese Society of Agricultural Engineering, 35(14): 141-148 (in Chinese with English abstract).
Ling, H. P., Tang, C., Su, X. Q., 2008. Division of Geological Disaster Prevention and Control in Qingchuan County, Sichuan Province. The Chinese Journal of Geological Hazard and Control, 19(1): 134-136, 140 (in Chinese with English abstract).
Liu, P. Y., Chang, M., Wu, B. B., et al., 2022. Route Selection of Landslide Prone Area in Wenchuan Section of ChengduWenchuan Expressway Based on SBAS-InSAR. Earth Science, 47(6): 2048-2057 (in Chinese with English abstract).
Lü, K. X., Wang, Z. Y., Jiang, Q. O., et al., 2021. Effect of Vegetation Coverage Change on Soil Erosion Control Efficiency in Guishui River Basin. Science of Soil and Water Conservation, 19(4): 69-77 (in Chinese with English abstract).
Lü, X. T., 2018. The Response of Debris Flow to Forest Vertical Differentiation in the Upper Reaches of Min River (Dissertation). Southwest University of Science and Technology, Chengdu (in Chinese with English abstract).
Ma, P. H., Peng, J. B., Zhuang, J. Q., et al., 2022. Initiation Mechanism of Loess Mudflows by Flume Experiments. Journal of Earth Science, 33(5): 1166-1178. https://doi.org/10.1007/s12583-022-1660-y
Noori, H., Karami, H., Farzin, S., et al., 2018. Investigation of RS and GIS Techniques on MPSIAC Model to Estimate Soil Erosion. Natural Hazards, 91(1): 221-238. https://doi.org/10.1007/s11069-017-3123-9
Pal, S. C., Chakrabortty, R., 2019. Simulating the Impact of Climate Change on Soil Erosion in Sub-Tropical Monsoon Dominated Watershed Based on RUSLE, SCS Runoff and MIROC5 Climatic Model. Advances in Space Research, 64(2): 352-377. doi: 10.1016/j.asr.2019.04.033
Saha, A., Ghosh, M., Pal, S. C., 2020. Understanding the Morphology and Development of a Rill-Gully: An Empirical Study of Khoai Badland, West Bengal, India. Gully Erosion Studies from India and Surrounding Regions. Springer, Cham: 147-161. https://doi.org/10.1007/978-3-030-23243-6_9
Sun, C., Tang, C. S., Cheng, Q., et al., 2022. Stability of Soil Slope under Soil-Atmosphere Interaction. Earth Science, 47(10): 3701-3722 (in Chinese with English abstract).
Wu, A. P., Wang, X. Y., Huang, J. Y., et al., 2021. Improvement of SCS-CN Model Based on Antecedent Precipitation and Rainfall Duration. Transactions of the Chinese Society of Agricultural Engineering, 37(22): 85-94 (in Chinese with English abstract).
Xiao, J. B., Sun, Z. X., Liu, Z., et al., 2017. Effects of Rainfall Erosion Factor, Vegetation Type and Coverage on Soil Erosion of Sloping Farmland. Transactions of the Chinese Society of Agricultural Engineering, 33(22): 159-166 (in Chinese with English abstract).
Yan, Y. Q., Guo, C. B., Zhong, N., et al., 2022. Deformation Characteristics of Jiaju Ancient Landslide Based on InSAR Monitoring Method, Sichuan, China. Earth Science, 47(12): 4681-4697(in Chinese with English abstract).
Yang, T., Zhang, Z. J., Wang, X. K., et al., 2021. Feasibility Study on Monitoring Soil Erosion Using Persistent Scatterer Synthetic Aperture Radar Interferometry Technology. Transactions of the Chinese Society of Agricultural Engineering, 37(14): 127-134 (in Chinese with English abstract).
Zhang, J. H., Yao, F. M., 2004. Soil Erosion in Xingguo County of Jiangxi Province. Journal of Beijing Forestry University, 26(1): 53-56 (in Chinese with English abstract).
Zhang, S., Xiong, D. H., Wu, H., et al., 2021. Research on Spatial Variation of Soil Erosion in Sunshui River Basin Based on RUSLE Model. Journal of Soil and Water Conservation, 35(5): 24-30 (in Chinese with English abstract).
Zhang, Y. Y., Li, T. H., 2018. Soil Erosion in Shenzhen City Based on GIS and RUSLE Model. Journal of Basic Science and Engineering, 26(6): 1189-1202 (in Chinese with English abstract).
Zhou, C., Chang, M., Xu, L., et al., 2020. Risk Assessment of Typical Urban Mine Geological Disasters in Guizhou Province. Geomatics and Information Science of Wuhan University, 45(11): 1782-1791 (in Chinese with English abstract).
Zhu, B. B., Li, Z. B., Li, P., et al., 2009. Dynamic Changes of Soil Erodibility during Process of Land Degradation and Restoration. Transactions of the Chinese Society of Agricultural Engineering, 25(2): 56-61 (in Chinese with English abstract).
郭兵, 陶和平, 刘斌涛, 等, 2012. 基于GIS和USLE的汶川地震后理县土壤侵蚀特征及分析. 农业工程学报, 28(14): 118-126.
侯宁, 王勇, 赵虎, 等, 2021. 耕作侵蚀对不同坡度下紫色土侵蚀产沙的影响. 山地学报, 39(4): 495-505.
李果, 2015. 基于GIS的泥石流危险性评价研究(硕士学位论文). 北京: 中国地质大学(北京).
李子轩, 赵辉, 邹海天, 等, 2019. 基于CSLE模型和抽样单元法的县域土壤侵蚀估算方法对比. 农业工程学报, 35(14): 141-148.
凌昊平, 唐川, 苏小琴, 2008. 四川省青川县地质灾害防治区划. 中国地质灾害与防治学报, 19(1): 134-136, 140.
刘沛源, 常鸣, 武彬彬, 等, 2022. 基于SBAS-InSAR技术的成汶高速汶川段滑坡易发区选线研究. 地球科学, 47(6): 2048-2057. doi: 10.3799/dqkx.2022.069
律可心, 王子晔, 姜群鸥, 等, 2021. 妫水河流域植被覆盖变化对土壤侵蚀控制效率的影响. 中国水土保持科学(中英文), 19(4): 69-77.
吕夏婷, 2018. 岷江上游泥石流活动对森林植被垂直分异的响应研究(硕士学位论文). 成都: 西南科技大学.
孙畅, 唐朝生, 程青, 等, 2022. 土体-大气相互作用下土质边坡稳定性研究. 地球科学, 47(10): 3701-3722. doi: 10.3799/dqkx.2022.275
吴艾璞, 王晓燕, 黄洁钰, 等, 2021. 基于前期雨量和降雨历时的SCS-CN模型改进. 农业工程学报, 37(22): 85-94.
肖继兵, 孙占祥, 刘志, 等, 2017. 降雨侵蚀因子和植被类型及覆盖度对坡耕地土壤侵蚀的影响. 农业工程学报, 33(22): 159-166.
闫怡秋, 郭长宝, 钟宁, 等, 2022. 基于InSAR形变监测的四川甲居古滑坡变形特征. 地球科学, 47(12): 4681-4697. doi: 10.3799/dqkx.2022.162
杨通, 张智杰, 王效科, 等, 2021. 基于PS-InSAR技术监测土壤侵蚀可行性研究. 农业工程学报, 37(14): 127-134.
张佳华, 姚凤梅, 2004. 江西兴国土壤侵蚀动态的研究. 北京林业大学学报, 26(1): 53-56.
张素, 熊东红, 吴汉, 等, 2021. 基于RUSLE模型的孙水河流域土壤侵蚀空间分异特征. 水土保持学报, 35(5): 24-30.
张园眼, 李天宏, 2018. 基于GIS和RUSLE模型的深圳市土壤侵蚀研究. 应用基础与工程科学学报, 26(6): 1189-1202.
周超, 常鸣, 徐璐, 等, 2020. 贵州省典型城镇矿山地质灾害风险评价. 武汉大学学报(信息科学版), 45(11): 1782-1791.
朱冰冰, 李占斌, 李鹏, 等, 2009. 土地退化/恢复中土壤可蚀性动态变化. 农业工程学报, 25(2): 56-61.