Environmental vulnerability assessment using Grey Analytic Hierarchy Process based model Satiprasad Sahoo a , Anirban Dhar b, ⁎, Amlanjyoti Kar c a School of Water Resources, Indian Institute of Technology Kharagpur, India b Department of Civil Engineering, Indian Institute of Technology Kharagpur, India c Central Ground Water Board, Bhujal Bhawan, Faridabad, Haryana, India abstract article info Article history: Received 19 August 2015 Received in revised form 14 October 2015 Accepted 14 October 2015 Available online xxxx Keywords: Environmental vulnerability Grey–Analytic Hierarchy Process (Grey–AHP) GIS Remote sensing (RS) Environmental management of an area describes a policy for its systematic and sustainable environmental pro- tection. In the present study, regional environmental vulnerability assessment in Hirakud command area of Odisha, India is envisaged based on Grey Analytic Hierarchy Process method (Grey–AHP) using integrated re- mote sensing (RS) and geographic information system (GIS) techniques. Grey–AHP combines the advantages of classical analytic hierarchy process (AHP) and grey clustering method for accurate estimation of weight coef- ficients. It is a new method for environmental vulnerability assessment. Environmental vulnerability index (EVI) uses natural, environmental and human impact related factors, e.g., soil, geology, elevation, slope, rainfall, tem- perature, wind speed, normalized difference vegetation index, drainage density, crop intensity, agricultural DRASTIC value, population density and road density. EVI map has been classified into four environmental vulner- ability zones (EVZs) namely: ‘low’, ‘moderate’‘high’, and ‘extreme’ encompassing 17.87%, 44.44%, 27.81% and 9.88% of the study area, respectively. EVI map indicates that the northern part of the study area is more vulnerable from an environmental point of view. EVI map shows close correlation with elevation. Effectiveness of the zone classification is evaluated by using grey clustering method. General effectiveness is in between “better” and “common classes”. This analysis demonstrates the potential applicability of the methodology. © 2015 Elsevier Inc. All rights reserved. 1. Introduction Environmental vulnerability zone identification is an important step for a sustainable environmental protection framework. It is defined for an area based on relative likelihood of getting affected due to a set of en- vironmental factors. Surrogate information are used to infer the proba- bility of environmental vulnerability. Environmental vulnerability zones provide an imprecise assessment of environmental protection based on remote sensing and conventional data. Environmental management of an area could be envisaged by adopting qualitative and quantitative analysis of various natural, environment and human factors. There are three major approaches available for predicting environmental vulner- ability for an area: i) index based overlay method, ii) process based mathematical model, and iii) statistical inference analysis. In the pres- ent study, first approach is implemented in terms of environmental vul- nerability index (EVI). EVI is an imprecise measure of vulnerability. A methodology is developed for environmental vulnerability assessment based on the Grey–AHP method. Environmental vulnerability zones are delineated based on indirect inference analysis of influencing factors/features. Presence of large number of influencing features in the analysis increase the complexity. Fraster et al. (2006) described the methods of analysis of participatory process based identification of sustainability indicators for sustainable environmental management. This work show results of long and com- plex sustainability indicators for social, environmental and economic issues. An approach for assessing environmental vulnerability is discussed by Kvaerner et al. (2006) by the using standard environmen- tal impact assessment (EIA) procedure. This approach provided more subjectivity linked to vulnerability assessments. Regional environmen- tal vulnerability assessment is performed by Wang et al. (2008) using remote sensing & GIS techniques. Finally, results are correlated with al- titude. Eco-environmental vulnerability assessment using fuzzy analytic hierarchy process (FAHP) for the Danjiangkou reservoir area, China is presented by Li et al. (2009). This method is developed by combing fuzzy set theory and decision making system in GIS framework. Tran et al. (2010) worked on environmental vulnerability pattern assess- ment based on stressor resource overlay, state-space analysis, and clus- tering analysis methods. Marine environmental vulnerability mapping using GIS based on neuron-fuzzy techniques is presented by Navas et al. (2011). This method mainly focuses on the three-dimensional hy- drodynamic model validation. A study on environmental vulnerability Environmental Impact Assessment Review 56 (2016) 145–154 ⁎ Corresponding author at: Department of Civil Engineering, Indian Institute of Technology Kharagpur, Kharagpur, WB, 721302, India. E-mail addresses: anirban.dhar@gmail.com, anirban@civil.iitkgp.ernet.in (A. Dhar). http://dx.doi.org/10.1016/j.eiar.2015.10.002 0195-9255/© 2015 Elsevier Inc. All rights reserved. Contents lists available at ScienceDirect Environmental Impact Assessment Review journal homepage: www.elsevier.com/locate/eiar