Cost Estimation for the Operation and Maintenance of Automated Monitoring and Early-Warning Equipment for Geological Hazards

被引:0
|
作者
Luo, Gan [1 ]
Tao, Mingqi [1 ]
Wu, Baohe [2 ]
Zhang, Mingzhi [3 ,4 ]
Zhong, Shuai [5 ]
Li, Junfeng [3 ,4 ]
Yang, Xiaodi [2 ]
机构
[1] China Geol Survey, Dev & Res Ctr, Beijing 100037, Peoples R China
[2] Chinese Acad Geol Sci, Inst Explorat Technol, Chengdu 611734, Peoples R China
[3] China Inst Geol Environm Monitoring, Beijing 100081, Peoples R China
[4] Minist Nat Resources, Observat & Res Stn Geol Hazard Sichuan Yaan, Yaan 625099, Peoples R China
[5] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
基金
中国国家自然科学基金;
关键词
geological hazards; automated monitoring and early-warning equipment; operation and maintenance; cost estimation; budget standards; financial sustainability; BUDGET STANDARDS;
D O I
10.3390/su162310505
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Geological hazards impede regional economy sustainability. To limit their destructive impacts on human life and property, the Chinese government has independently developed automated monitoring and early-warning equipment, which has been deployed in over 250,000 locations nationwide, yielding effective early warnings. The smooth operation of this equipment necessitates substantial human, material, and financial resources for its maintenance. To allocate funds rationally, the Ministry of Finance of China has mandated the urgent establishment of budget standards for the operation and maintenance of automated monitoring and early-warning systems for geological hazards. Addressing the research gap in this area, this study meticulously develops a cost model, subcategorizing operating costs, maintenance costs, and management costs. Addressing the intricate issue of maintenance expenditures, this study ingeniously breaks down routine operations and urgent repairs stipulated in technical standards into personnel, materials, and vehicular needs for each equipment type. Considering the total manpower involved in equipment maintenance, the per-unit maintenance cost is determined. This method allocates costs to individual pieces of equipment, thereby sidestepping the quantification hurdle created by varying types and quantities of monitoring equipment at each monitoring site due to various geological disaster types and magnitudes, and technical personnel's maintenance responsibility for multiple equipment types in a single operation. Finally, incorporating regional adjustment coefficients, we have formulated theoretical costs for the operation and maintenance of automated monitoring and early-warning equipment for geological hazards. By contrasting theoretical costs with actual project budgets, the error margin is within 2%. Following nationwide consultation, these theoretical costs have been officially endorsed as the budget standard. These standards will lay the groundwork for project budgeting and review, facilitate efficient fund utilization, and ensure the financial sustainability of monitoring and warning systems for geological hazards. Concurrently, this paper bridges the global lack in budget norms for the operation and upkeep of automated geological disaster monitoring systems. The cost calculation model introduced serves as a pivotal reference globally for the evaluation of analogous system's operations and maintenance expenses.
引用
收藏
页数:17
相关论文
共 50 条
  • [21] Risk monitoring and early-warning technology in production process of colliery
    Cao, QG
    Chen, WX
    Sun, CJ
    Zhang, DZ
    PROGRESS IN SAFETY SCIENCE AND TECHNOLOGY, VOL 4, PTS A and B, 2004, 4 : 2452 - 2457
  • [22] Research on maintenance errors in civil aviation and early-warning expert system
    School of Computer Science and Technology, WUT, Wuhan 430063, China
    不详
    不详
    Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban), 2007, 1 (92-95):
  • [23] THE INTRODUCTION OF THE SYSTEM OF MONITORING AND EARLY-WARNING OF GALE IN DRIVING CONTROL
    Yu, Chuanjin
    Li, Yongle
    Fundamental Research in Structural Engineering: Retrospective and Prospective, Vols 1 and 2, 2016, : 810 - 814
  • [24] Study on risk estimation and early-warning system of insurance company
    Hu Tao
    Zhu Bin
    PROCEEDINGS OF THE 1ST INTERNATIONAL CONFERENCE ON RISK ANALYSIS AND CRISIS RESPONSE, 2007, 2 : 228 - 232
  • [25] Optimization of Low-Cost Monitoring Systems for On-Site Earthquake Early-Warning of Critical Infrastructures
    D'Alessandro, Antonino
    Scudero, Salvatore
    Vitale, Giovanni
    Di Benedetto, Andrea
    Lo Bosco, Giosue
    COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2020, PT II, 2020, 12250 : 963 - 975
  • [26] Estimation for Aerial Detection Effectiveness with Cooperation Efficiency Factors of Early-Warning Aircraft in Early-Warning Detection SoS under BSC Framework
    Zhu Feng
    Hu Xiaofeng
    He Xiaoyuan
    Guo Rui
    Li Kaiming
    Yang Lu
    LIDAR IMAGING DETECTION AND TARGET RECOGNITION 2017, 2017, 10605
  • [27] A Division Method of Determining the Early-Warning Zone on an Expressway for Automated Vehicles
    Wang, Jiawen
    Li, Shaobo
    Lu, Yining
    Wang, Lubang
    DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2020, 2020
  • [28] Construction of the Early-warning Index System for the Risk of the International Logistics Operation
    Zhang, Guohua
    Yuan, Jiali
    2ND IEEE INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER CONTROL (ICACC 2010), VOL. 5, 2010, : 209 - 213
  • [29] Coupling relations and early-warning for "equipment chain" in long-distance pipeline
    Liang, Wei
    Lu, Linlin
    Zhang, Laibin
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2013, 41 (1-2) : 335 - 347
  • [30] Geological hazards: From early warning systems to public health toolkits
    Samarasundera, Edgar
    Hansell, Anna
    Leibovici, Didier
    Horwell, Claire J.
    Anand, Suchith
    Oppenheimer, Clive
    HEALTH & PLACE, 2014, 30 : 116 - 119