MCDA techniques used in optimization of weights and ratings of DRASTIC model for groundwater vulnerability assessment  

作　　者：Prashant Kumar Reema Sharma Subhasis Bhaumik 

机构地区：[1]CSIR-Central Scientific Instruments Organisation,Chandigarh,160030,India [2]Indian Institute of Engineering Science and Technology,Shibpur,Howrah,711103,India

出　　处：《Data Science and Management》2022年第1期28-41,共14页数据科学与管理（英文）

摘　　要：DRASTIC is a very simple and common model used for the assessment of groundwater to contamination.This model is widely used across the world in various hydrogeological environments for groundwater vulnerability assessment.The Ohio Water Well Association(OWWA)developed DRASTIC model in 1987.Over the years,several modifications have been made in this model as per the need of the regional assessment of groundwater to contamination.This model has fixed weights for its parameters and fixed ratings for the sub-parameters under the main parameters.The weights and ratings of DRASTIC parameters were fixed on the basis of Delphi network technique,which is the best technique for the consensus-building of experts,but it lacks scientific explanations.Over the years,several optimization techniques have been used to optimize these weights and ratings.This work intends to present a critical analysis of decision optimization techniques used to get the optimum values of weights and ratings.The inherent pros and cons and the optimization challenges associated with these techniques have also been discussed.The finding of this study is that the application of MCDA optimization techniques used to optimize the weights and ratings of DRASTIC model to assess the vulnerability of groundwater depend on the availability of hydrogeological data,the pilot study area and the level of required accuracy for earmarking the vulnerable regions.It is recommended that one must choose the appropriate MCDA technique for the particular region because unnecessary complex structure for optimization process takes more time,efforts,resources,and implementation costs.

关 键 词：DRASTIC Model Vulnerability index Analytic Hierarchy Process MCDA techniques Neural networks Fuzzy logic 

分 类 号：P64[天文地球—地质矿产勘探]