探討於生態風險評估之不確定性

A Discussion of Uncertainty in Ecological Risk Assessment

陳宜清(Yi-Ching Chen) ； 陳俊宏(Jun-Hung Chen)

《科學與工程技術期刊》 2卷1期 (2006/03) Pp. 49-60

https://doi.org/10.7117/JSET.200603.0049

摘要

「生態風險評估」是提供一個具有系統性及原則性之架構與方法，能可靠預測生態反應之危機潛勢，補強一般生物生態監測不夠周延及達到全方面考量之缺陷。然而對於生態風險之估計是否可信則是評估有效與否之關鍵，風險評估結果之不確定性產生在於評估模式之程序是否嚴謹完整？所引用資料是否充分可靠？還有資料之密度及監測期長等皆會影響估計值之精準程度。本研究旨在討論生態風險評估之不確定因子為何並定性描述之？尋求不確定性產生之關鍵何在？及如何去確認所得資料之準確性，增加可信度及降低不確定度。利用克利金推估之空間內插可降低因採樣點的密度不足或不均勻所衍生不確定性問題，而蒙地卡羅模擬法可提供為一種解決可信度分析的方法，可應用於不確定度之量化。藉由對不確定性分析之瞭解，期望未來能應用於生態風險估計及風險管理實務，並可獲得更可信的評估及提供應變對策之參考。

關鍵字

生態風險評估 ； 不確定性 ； 克利金推估 ； 蒙地卡羅模擬法

並列摘要

Ecological Risk Assessment (ERA) demonstrates a systematized framework for predicting the potential risks of ecological adversity more confidently than an assessment obtained through general biological ecology monitoring. The key point concerns whether the validity of the assessment is based on credible ecological risk estimation. However, the uncertainty of estimating the results of risk can depend on the rigor and intactness of the assessment processing, the reliability and comprehensiveness of the referential data, and the precision and durability of the monitoring condition. In this study a discussion of analysis of uncertainty in ERA is conducted. The major portion of the research focuses on how to (1) describe the uncertainty factors qualitatively, (2) seek a key to the uncertainty produced, (3) confirm the precision of the inferring information, (4) increase credibility, and (5) reduce the uncertainty. The Kriging estimation for spatial interpolation is applied to reduce the uncertainty induced by less density at the sampled points. Also, the Monte Carlo simulation method offers a type of settlement in credibility for analysis under a shortage of information, as well as the means of estimating uncertainty quantitatively. One can expect risk estimation and management to be implemented more dependably by proper assessment and offer a reference to a countermeasure of the emergency more accurately in the future through a well-considered analysis of uncertainty.

並列關鍵字

ecological risk assessment ； uncertainty ； Kriging estimation ； Monte Carlo simulation