Spatial Analysis of Environmental Hazards

Spatial Analysis of Environmental Hazards

Assessment and Management of environmental risk of Salty, Sweet and Minab Rivers International Wetlands on the basis of multi-criteria decision-making methods

Authors
Samira Jafariazar 1
Gholam Reza Sabzghabaei 2
Mortaza Tavakoly 2
Soolmaz Dashti 3
1 Master Degree Assessment and Land use of Bebahan khatam Alanbia University of Technology, Behbahan, Iran.
2 Assistant Professor, Department of Environment, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran
3 Assistant Professor, Department of Environment, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran
10.29252/jsaeh.5.4.65
Abstract
Introduction: Wetland ecosystems, especially marine coastal wetlands of the most important and also the most vulnerable are the world's environmental resources. Which has always been sensitive to the fragility of coastal areas, high population density and intensive human activities are faced with the threat of destruction. Based on this, monitoring the trend of the changes in wetlands and their surrounding lands can be effective in the management of these valuable ecosystems. Investigating the environmental risk is a suitable instrument for evaluating and ensuring understanding of the relationships between stressor factors and environmental effects especially in wetland ecosystems. In general, application of methods of evaluating environmental risk is one of the important tools in studying environmental management along with identifying and mitigating potential environmental damaging factors in wetland regions in order to achieve sustainable development. Today, multi-criteria decision-making methods are employed in evaluating the risk in many studies.This study is based on multi-criteria decision-making methods to identify and analyze the risks threatening Tyab- Minab International wetland located in Hormozgan province was conducted.

Materials and methods: Based on the methodology to identify and prioritize risks Delphi, AHP and TOPSIS techniques were used to determine the risk priority number. In the first phase of this study, to identify and screen the main criteria of project selection, Delphi method was used. In this study, the panel of interest was determined based on a combination of experts with different expertise and out of a sample of 20 individuals, in which experts with various expertise gave a score from 1 to 5 (Likert scale) to each criterion. In this way, 32 criteria were identified as the most important and considerable risk for Minab Wetland and further proceeded to the second phase for prioritization and analysis. In this stage, multi-criteria decision-making methods were used, in which hierarchical analysis process was employed for prioritizing the criteria using Expert Choice 11 software. The indices of risk evaluation including the impact intensity, incidence probability, and the sensitivity of the receptive environment in environmental risk evaluation of wetlands do not have an equal value and significance. For this purpose, to weight the factors effective in estimating risk level and for prioritization of risk options, the technique for order of preference by similarly to ideal solution (TOPSIS) and Excel software were benefited from for calculations. The spectrum of scoring to each of the indices of incidence probability, impact intensity, and the sensitivity of the receiving environment was chosen from very low (1) to very high (9) based on hour spectrum. Following investigation of the types and frequency of indices along with the method of score determination of these indices, three indices of risk intensity (C1), risk incidence probability (C2), and the sensitivity of the receiving environment (C3) were chosen for risk ranking using TOPSIS model. Next, after determination of risk priority number using TOPSIS, the risk levels were calculated and evaluated using normal distribution method for each risk. To determine the degree of risk-taking, risks are organized in a descending order, where the elements of the number of the class and the length of the class are determined based on Relations 1 and 2 (n is the number of risks). Next, the risks are categorized based on these classes. Considering the concept of ALARP, the risks under investigation are divided into high risks, medium risks, and low risks. In this study, considering the number and length of classes, the studied risks were categorized in six levels (critical, intolerable, considerable, medium, tolerable, and trivial risks).







(2)









(1)





the number of classes=1+3.3 log (n)

the length of the classes= the greatest risk value - the smallest risk value/the number of classes

Results and discussion: In the first step, the final indices of the wetland's environmental risk were identified and the development of hierarchical tree and classification of the risks threatening wetlands along with their incidence probability in two groups of natural and environmental criteria was performed. Eventually, the final weight of criteria resulting from paired comparisons was obtained in Expert Choice 11 to achieve the score of incidence probability of each risk. Based on the results, among the natural, social, economic, physiochemical, biological, and cultural criteria, drought and climate change, increase urban and rural development, Smugling of fuel, oil pollution, reduce the density of vegetation, indiscriminate exploitation of groundwater were of high priority. The results obtained from ranking the the risks threatening Minab Wetland using TOPSIS suggest that oil pollution, dam construction upstream, persistent drought and climate change, and sometimes alcohol and fuel smuggling and illegal overfishing the priorities are first to fifth. Also Results showed that the respectively based on (Cj+) oil pollution (0/9109), dam construction (0/8121), the drought and climate changes (0/8063) and the smuggling of fuel (0/7520) are in Unbearable level.

Overall, the results indicated that same as this research, wetland ecosystems are subject to many threatening factors, resulting in ecological imbalance and abnormal appearance of the wetland, putting the wetland entity into danger of extinction in terms of fauna and flora.

Conclusion: Nowadays, for assessment of environmental risk, various methods are used, each of which has positive and negative points given the studied environment and the conditions governing it. Therefore, one cannot reject or approve one method with total confidence. By employing novel methods in risk evaluation, the intensity of risk incidences and, in turn, the damages and losses incurred to the environment can be prevented or at least mitigated. Further, it is also possible to move in line with proper and optimal management of environmental resources, especially wetlands and with sustainable development. Undoubtedly, understanding and recognition of the factors threatening wetlands, according to the importance and the impact of them, Prevent and cope with the threats and accurate project preparation and implementation of wetland conservation plans and environmental management.
Keywords
Risk assessment
Wetlands International
Environment
AHP
TOPSIS
Barbier, E.B. 2011, Coastal wetland restoration and the Deepwater Horizon oil spill, Vanderbilt LawRev, 64, 1821–1849.
Bassi, N.; M. Dinesh Kumai, A. Sharma, and P. Pardha- Saradhi. 2014. Status of wetlands in India: A review of extent, ecosystem benefits, threats and management strategies, Journal of Hydrology: Regional Studies, 2, 1-19.
Bowen, William M. 1993. AHP: Multiple Criteria Evaluation, in Klosterman, R. et al (Eds). Spreadsheet Models for Urban and Regional Analysis, New Brunswick: center for Urban Policy Research.
Day, J.W.; Boesch, Jr.; Clairain, E.J.; Kemp, G.P.; Laska, S.B.; Mitsch, W.J.; Orth, K.; Mashriqui, H.; Reed, D.R.; Shabman, L. and et al. 2007. Restoration of the Mississippi Delta: Lessons from hurricanes Katrina and Rita, Science, 315, 1679–1684.
De Lange, H.J.; S. Sala, M. Vighi, and J.H. Faber. 2010. Ecological vulnerability in risk assessment: A review and perspectives, Science of the Total Environment. 408: 3871–3879.
Eldin, N. and K. A. Eldrandly. 2004. A Computer - Aided System for Site Selection of Major Capital Investment, 1st ASCAAD International, e-Design in Architecture, Dhahran, Saudi Arab.
Ghermandi, A.; J.C.J.M. Van den Bergh, L.M. Brander, and P.A.L.D. Nunes. 2008. The Economic Value of Wetland Conservation and Creation: A Meta-Analysis. [Working Paper 79]. Fondazione Eni Enrico Mattei, Milan, Italy.
Kellett, B.M.; T. Walse, and K.L. Baristow. 2005. Ecological Risk Assessment for the Wetlands of the Lower‌ Burdekin. CSIRO Land and Water Technical Report 26/05, Pp.34.
Malekmohammadi, B. and L. Rahimi Blouchi. 2014. Ecological risk assessment of wetland ecosystems using Multi Criteria‌ Decision Making and Geographic Information System, Ecological Indicators, 41, 133–144.
McAllister, D.E.; J.F. Craig, N. Davidson, S. Delany, and M. Seddon. 2001. Biodiversity Impacts of Large Dams, International :::::::::union:::::::::for Conservation of Nature and United Nations Environmental Programme, Gland and Nairobi.
Millennium Ecosystem Assessment (MEA). 2005. Ecosystems and Human Well-being: Wetlands and Water Synthesis. WorldResources Institute, Washington, DC.
Molur, S.; K.G. Smith, B.A. Daniel, and W.R.T. Darwall. 2011. The status and Distribution of Freshwater Biodiversity in the WesternGhats, India. International :::::::::union::::::::: for Conservation of Nature, Cambridge and Gland.
Niering, W. 1985. Wetlands, New York: Knopf.
Paustenbach, D.J. 2002. Human & Ecological Risk Assessment, Theory & Practice New York: John Wiley & Sons.
Prato, T. 2012. Increasing resilience of natural protected areas to future climate change: A fuzzy adaptive management approach, Ecological Modelling. 242 (1): 46-53.
Saaty, T.L. and L.G. Vargas. 1991. Prediction, Projection and Forecasting. Kluwer Academic Publishers.Dordrecht. 251 p.
Saaty, T.L. 1980. The analaytic hierarchy process: Planning, Priority setting, Resourse Allocation. McGrawhill, New York, NY, 437 p.
Shea, D. and W. Thorsen. 2012. Ecological Risk Assessment, Department of Biology. North Carolina State University, Raleigh, North Carolina, USA, Progress in Molecular Biology and Translational Science 112: 1173- 1877.
Shiliang, S.; M. Jiang, Y. Liu, and R. Li. 2012. Risk Assessment on Falling from Height based on AHP-fuzzy. Original Research Article Procedia Engineering. 45: 112-118.
Simaityte, J.; J. Agugutis, and B. Gailiusis. 2006. Risk - Based Water Level Control in Kaunas Hydropower System, Environmental Research, Engineering and Management.
Ten Brink, P.; T. Badura, A. Farmer, and D. Russi. 2012. The economics of Ecosystem and Biodiversity for Water and Wetlands: ABriefing Note. Institute for European Environmental Policy, London.
Zanakis, S.H.; A. Solomon, N. Wishart, and S. Dublish. 1998. Multi-attribute decision making a simulation comparison of selection methods. Operational Research 107: 507- 529.
Zedler, J.B. and S. Kercher. 2005. Wetland resources: status, trends, ecosystem services and restorability, Annu. Rev. Environ.Resour. 30 (1): 39–74.
Zhang, sh.; B. Sun, L. Yan, and ch. Wang. 2013. Risk identification on hydropower project using the FAHP and extension of TOPSIS methods under interval-valued fuzzy environment, Natural Hazards 65 (1): 359-373.