A Method for Rapid Risk Assessment of Reservoir Dams Based on a Combined Weighting Approach Using AHP-Entropy and Game Theory

Lin Yueqi; Yuan Mingdao; Lai Chengguang; Xu Yunqian; Shen Shijia

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A Method for Rapid Risk Assessment of Reservoir Dams Based on a Combined Weighting Approach Using AHP-Entropy and Game Theory

更新时间：2026-06-30

- A Method for Rapid Risk Assessment of Reservoir Dams Based on a Combined Weighting Approach Using AHP-Entropy and Game Theory
- PEARL RIVER Pages: 1-12(2026)
- 作者机构：
  
  1.广东省水利水电科学研究院，广州 510635
  2.华南理工大学土木与交通学院，广州 510641
  3.水利部粤港澳大湾区水网全域感知与智能调控技术创新中心，广州 510635
- 作者简介：
- 基金信息：
- DOI：
  CLC： TV698 TV122
- Received：17 April 2026，
  
  Revised：2026-06-16，
  
  Accepted：25 June 2026，
  
  Online First：30 June 2026，
- 稿件说明：
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林悦奇，袁明道，赖成光等.基于AHP-熵值法与博弈论组合赋权的水库大坝风险快速评估方法［J］.人民珠江，DOI：10.3969/j.issn.1001-9235.XXXX.XX.001.

Lin Yueqi,Yuan Mingdao,Lai Chengguang,et al.A Method for Rapid Risk Assessment of Reservoir Dams Based on a Combined Weighting Approach Using AHP-Entropy and Game Theory[J].PEARL RIVER,
林悦奇，袁明道，赖成光等.基于AHP-熵值法与博弈论组合赋权的水库大坝风险快速评估方法［J］.人民珠江，DOI：10.3969/j.issn.1001-9235.XXXX.XX.001. DOI：

Lin Yueqi,Yuan Mingdao,Lai Chengguang,et al.A Method for Rapid Risk Assessment of Reservoir Dams Based on a Combined Weighting Approach Using AHP-Entropy and Game Theory[J].PEARL RIVER, DOI：10.3969/j.issn.1001-9235...001.

摘要

针对极端降雨背景下水库大坝风险评估时效性不足、主客观权重分配存在随意性等问题，提出了一种集成AHP-熵值法与博弈论组合赋权的水库大坝风险动态评估模型。首先，从“上游致灾风险因子-工程本体风险因子-下游承灾风险因子”3个维度构建了包含纳雨量、水位波动、结构完整性等6项关键指标的评估体系。其次，引入博弈论（Game Theory）纳什均衡思想，通过最小化主、客观权重向量间的离差实现组合系数的非线性寻优，构建了具备“逻辑电位器”调节机制的动态赋权方案。最后，利用Python开发自动化评估引擎，选取均衡响应型、平稳调蓄型及瞬时响应型3类典型水库进行实证分析。结果表明该模型能够精准捕捉不同降雨脉冲下的风险演化轨迹；在大型水库案例B中，模型通过识别低敏感度库容特征，使风险指数稳定在0.6~0.8的鲁棒区间；在小型水库案例C中，客观权重自动跃升至0.647 6，显著增强了对突发险情的响应灵敏度。研究成果为水库大坝在极端天气下的分钟级应急调度提供了科学支撑。

Abstract

Addressing the issues of insufficient timeliness and subjective arbitrariness

in weight assignment for reservoir dam risk assessment under extreme rainfall

this paper proposes a dynamic risk assessment model integrating the Analytic Hierarchy Process (AHP)

the Entropy Weight Method (EWM)

and Game Theory (GT). A comprehensive evaluation system is first established from three dimensions: "upstream hazard-triggering factors

dam engineering status

and downstream vulnerability

" comprising six key indicators: rainfall absorption capacity (

)

water level safety (

)

safety class (

)

structural integrity (

)

downstream conveyance safety (

)

and downstream exposure (

). To overcome the limitations of single weighting methods

Game Theory is introduced. By minimizing the deviation between the subjective weight vector (from AHP

) and the objective weight vector (from EWM

)

we solve for the Nash equilibrium

yielding optimal combination coefficients

and

. This creates a "logic potentiometer" mechanism that dynamically adjusts the combined weight vector. An automated assessment engine is developed in Python

integrating grey relational analysis (GRA) to map real-time sensor data to a composite risk index

. The model is validated using three typical reservoirs in Guangdong Province

China

characterized by distinct storage sensitivities (

): Case A (medium-sized mountain reservoir

=0.50

balanced response)

Case B (large river reservoir

=0.15

steady regulation)

and Case C (small mountain runoff-type reservoir

=0.90

instantaneous response). Three standard rainfall scenarios—Type I (pre-peak

extreme intensity)

Type II (bimodal

intermittent)

and Type III (uniform

prolonged)—are ap

plied as external drivers. Results demonstrate the model's ability to accurately capture divergent risk evolution trajectories. For Case A

coefficients

=0.47 and

=0.53 achieve a near-perfect balance. In Case B

the model identifies the low-sensitivity storage characteristics

automatically prioritizing expert experience (

=0.58) to maintain a robust

between 0.6 and 0.8. In Case C

under the extreme Type I rainfall

the model dramatically surges the objective weight to

=0.65

enabling it to capture a sharp

-index drop from 0.65 to 0.12

significantly outperforming traditional static methods in sensitivity. The fast mapping layer provides minute-level risk updates

suitable for emergency scheduling. The findings confirm the model's strong universality

offering a standardized yet differentiated framework for various reservoir types and providing critical scientific support for intelligent dam systems and digital twin-based "four pre" (prediction

early warning

pre-evaluation

pre-planning) protocols.

关键词

Keywords

references

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