摘錄自《流域水文模型參數不確定性量化理論方法與應用》第4章。

概述

敏感性分析最常遇到的問題：

• 計算消耗問題：采用代理模型技術（對于復雜模型而言）或篩選方法（對于多維參數而言）
• 輸入參數的相關性問題：沒有一套完整的數學理論方法量化分析，可從物理意義和實驗角度考慮。如新安江模型的客觀優選方法
• 非線性問題：參數與輸出之間的關系是高度復雜的非線性問題，可采用基于方差分解的理論方法
• 模型交互作用問題：全局分析方法中的方差分解方法可以求得模型參數的二階敏感度和總敏感度
• 多輸出變量問題：水文模型輸出時變數據，如流量過程，可將模型評估目標函數值作為敏感性分析的輸出變量進行分析

敏感性分析方法分類

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常用敏感性分析方法

敏感性分析流程圖

敏感性分析方法

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.edge-pattern-dashed{stroke-dasharray:3}#mermaid-svg-daGRpPqmv1aCpw5y .edge-pattern-dotted{stroke-dasharray:2}#mermaid-svg-daGRpPqmv1aCpw5y .marker{fill:#333}#mermaid-svg-daGRpPqmv1aCpw5y .marker.cross{stroke:#333}:root { --mermaid-font-family: "trebuchet ms", verdana, arial;}#mermaid-svg-daGRpPqmv1aCpw5y {color: rgba(0, 0, 0, 0.75);font: ;}敏感性分析方法Morris篩選法多元回歸分析方法RSA方法Sobol'方法FAST和Extended FAST分析方法基于代理模擬技術的分析方法

基于代理模擬技術的分析方法

耦合方差分解的方法和響應曲面方法，用于分析水文模型參數的一階敏感度、二階敏感度和總敏感度。

定性篩選與定量評價耦合方法

總結

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