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干旱区地理 ›› 2026, Vol. 49 ›› Issue (1): 69-79.doi: 10.12118/j.issn.1000-6060.2025.031 cstr: 32274.14.ALG2025031

• 地表过程研究 • 上一篇    下一篇

基于变权-云模型理论的尉-且沙漠公路沙害综合评价

吕明坤1,2,3(), 刘春梅4, 杨向军5, 凌远5, 李生宇1,2,3(), 吕振涛1,2,3   

  1. 1 中国科学院新疆生态与地理研究所国家荒漠-绿洲生态建设工程技术研究中心,新疆 乌鲁木齐 830011
    2 中国科学院新疆生态与地理研究所荒漠与绿洲生态国家重点实验室,新疆 乌鲁木齐 830011
    3 中国科学院大学,北京 100049
    4 新疆交通投资(集团)有限责任公司,新疆 乌鲁木齐 830000
    5 新疆交通科学研究院有限责任公司,新疆 乌鲁木齐 830000
  • 收稿日期:2025-01-15 修回日期:2025-05-12 出版日期:2026-01-25 发布日期:2026-01-18
  • 通讯作者: 李生宇(1975-),男,博士,正高级工程师,主要从事风沙地貌与风沙工程等方面的研究. E-mail: oasis@ms.xjb.ac.cn
  • 作者简介:吕明坤(2000-),男,硕士研究生,主要从事干旱区风沙地貌等方面的研究. E-mail: lvmingkun1107@163.com
  • 基金资助:
    第三次新疆综合科学考察课题(2021xjkk0305);新疆交投集团2023年第一批科研项目(XJJTZKX-FWCG-202401-0043);新疆交投交通强国项目(Jtqg050)

Comprehensive evaluation of sand hazards on the Yuli-Qiemo desert highway based on the variable weight-cloud model theory

LYU Mingkun1,2,3(), LIU Chunmei4, YANG Xiangjun5, LING Yuan5, LI Shengyu1,2,3(), LYU Zhentao1,2,3   

  1. 1 National Engineering Technology Research Center for Desert-Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
    2 State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
    3 University of Chinese Academy of Sciences, Beijing 100049, China
    4 Xinjiang Communications Investment (Group) Co. Ltd., Urumqi 830000, Xinjiang, China
    5 Xinjiang Academy of Transportation Sciences Co. Ltd., Urumqi 830000, Xinjiang, China
  • Received:2025-01-15 Revised:2025-05-12 Published:2026-01-25 Online:2026-01-18

摘要:

沙漠公路风沙灾害评估是公路建设和运维的重要基础,但以往评价主观性强,亟待构建客观准确的评价体系。以尉犁至且末沙漠公路(尉-且沙漠公路)为研究对象,基于2023年的实地调研和数据分析,首先采用变权-云模型理论,选取10个关键指标,采用改进层次分析法确定恒权权重,构建公路沙害评价体系;其次结合双重赋分评价法与计算机技术批量计算状态值,通过变权理论动态调整权重;最后利用云模型划分沙害等级,并与历史数据进行对比验证。结果表明:(1)基于双重赋分评价法,通过计算机自动批量处理指标分级与动态权重调整,实现了全路段状态值的高效、准确评价,将评价范围从单一路段拓展至全路段。(2)与各路段历史沙害记录对比验证,相关系数(r)达0.91(P<0.001),表明二者在95%置信区间内呈现极显著正相关,避免了评估中人为的主观影响。(3)尉-且沙漠公路整体沙害问题较为严重,公路沿线三级沙害路段占比最高(65.46%),四级沙害路段其次(30.91%),无一级沙害路段。公路沙害风险呈南北两端低、中间高、自北向南逐渐加重的空间分布规律。其中,K180~K250和K30~K60路段沙害最为严重,应重点预防。研究结果为沙漠公路沙害风险识别和预测提供了新方法,为沙漠公路沙害预防和治理提供了重要依据。

关键词: 尉-且沙漠公路, 风沙灾害, 变权云模型, 双重赋分评价法, 动态权重调整

Abstract:

Assessing aeolian sand hazards is fundamental to the construction, operation, and maintenance of desert highways. However, conventional evaluation methods often suffer from excessive subjectivity, highlighting the need for an objective and robust assessment framework. Focusing on the Yuli-Qiemo desert highway in China, this study proposes a novel, data-driven method for evaluating aeolian sand-hazard risks, based on extensive field investigations conducted in 2023 and analyses. First, a variable-weight cloud model was established, incorporating ten key indicators. A modified analytic hierarchy was used to determine the indicator fixed weights. Second, a dual-score evaluation method, integrated with computational algorithms, enabled automated batch processing of indicator stratification and dynamic weight adjustment based on variable-weight theory. Third, the variable-weight cloud model was used to classify hazard levels, which were validated against historical sand hazard records. The results indicate that (1) The proposed method enables efficient and accurate assessment of aeolian sand hazards along entire highways, transitioning from isolated segment evaluation to full-route analysis. This is achieved through the automated computation of state values and real-time adjustment of indicator weights. (2) Comparison with historical sand hazard records yielded a correlation coefficient of 0.91 (P<0.001), indicating a significant positive correlation within the 95% confidence interval and demonstrating the method’s ability to reduce human subjectivity. (3) The overall aeolian sand-hazard risk of the Yuli-Qiemo desert highway is high. Grade III hazard segments dominate (65.46%), followed by grade IV (30.91%), with no segments classified as grade I. The risk is low at the northern and southern ends of the highway, high in the middle segments, and gradually increases in severity from north to south. Middle segments K180-K250 and K30-K60 are the most severely affected and warrant prioritized mitigation efforts. This novel method for identifying and predicting aeolian sand hazard risks along desert highways offers critical insights to inform targeted prevention and control strategies.

Key words: Yuli-Qiemo desert highway, sand hazard, variable-weight cloud model, dual-score evaluation method, dynamic weight adjustment