当前位置: X-MOL 学术Expo. Health › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Next Stages in Aquifer Vulnerability Studies by Integrating Risk Indexing with Understanding Uncertainties by using Generalised Likelihood Uncertainty Estimation
Exposure and Health ( IF 6.7 ) Pub Date : 2021-03-20 , DOI: 10.1007/s12403-021-00389-6
Sina Sadeghfam , Rahman Khatibi , Ata Allah Nadiri , Karim Ghodsi

A strategy is presented in this paper on the DRASTIC framework to integrate: (i) reducing subjectivities; (ii) transforming vulnerability indexing to risk indexing; and (iii) understanding inherent uncertainties. Notably, indexing refers to relative values for spatial comparisons within an aquifer using a set of incorporated data layers. The strategy also pools together catastrophe theory, fuzzy membership function and Generalised Likelihood Uncertainty Estimation (GLUE), for which data layers are transformed into a limited number of parameters. The strategy produces some anecdotal evidence from a study area, despite the sparse data availability that (i) treating subjectivities by a fuzzy-catastrophe scheme enhances accuracy and (ii) GLUE provides an insight, such that hotspots of high vulnerability have lower uncertainty, whereas low-vulnerable areas are associated with higher uncertainty. Also, risk indexing reveals that the study area suffers from inappropriate planning practices both in agricultural activities and in groundwater abstraction.



中文翻译:

通过使用广义似然不确定性估计将风险索引与理解不确定性集成在一起,进行含水层脆弱性研究的下一阶段

本文针对DRASTIC框架提出了一种策略,以整合:(i)减少主观性;(ii)将脆弱性索引转换为风险索引;(iii)了解内在的不确定性。值得注意的是,索引是指使用一组合并的数据层在含水层内进行空间比较的相对值。该策略还将灾难理论,模糊隶属度函数和广义似然不确定性估计(GLUE)合并在一起,为此将数据层转换为有限数量的参数。尽管数据稀少,该策略仍能从研究领域获得一些轶事证据,其中(i)通过模糊巨灾方案处理主观性可以提高准确性,并且(ii)GLUE可以提供洞察力,例如高脆弱性热点的不确定性较低,低脆弱地区与更高的不确定性相关。同样,风险指数显示该研究区域在农业活动和地下水抽取中都遭受了不适当的规划实践。

更新日期:2021-03-21
down
wechat
bug