Risk assessment of inter-basin water transfer plans through integration of Fault Tree Analysis and Bayesian Network modelling approaches.

Inter-basin water transfer projects are a common method used to balance water resources and meet regional demand, particularly in the drinking water supply sector. The potential failure risk associated with inter-basin water transfer projects was examined using Fault Tree Analysis (FTA) and Fuzzy Fault Tree Analysis (FFTA) methodologies in this study. Additionally, the conversion of Fault Tree models into Bayesian Network (BN) and Fuzzy Bayesian Network (FBN) models was explored. Ten basic events were identified as factors that could affect the success of inter-basin water transfer plans, including socio-political, environmental, water resource, economic, and technical criteria. Fault Tree and Fuzzy Fault Tree models were utilized to conduct a risk analysis, which was then converted into crisp and fuzzy FTA-BN through an integrated approach. This approach was applied to evaluate inter-basin water transfer scenarios from the Great Karun basin to the Central Iran Plateau. The superior scenario among eight water transfer scenarios was found to be water transfer from the Behesht-Abad Basin to Isfahan province and from the Khersan Basin to Kerman and Yazd provinces, with a failure risk of 0.649 and 0.601 respectively, based on the crisp and fuzzy integrated models. Basic events were ranked based on their contribution to the occurrence of the top event using two FIM and BI indices in the Fault Tree model and two indices of MI and SI in the Bayesian Network. Furthermore, after considering the correlation between basic events and risk factors, the risk obtained by crisp and fuzzy integrated models was found to increase to 0.811 and 0.789 respectively. The results of this study demonstrate that an integrated approach can assist decision-makers and stakeholders in evaluating inter-basin water transfer projects.

Enhanced GMCR model for resolving conflicts in a transboundary wetland.

This research proposes an enhanced Graph Model for Conflict Resolution (GMCR) with application to an international wetland. The integrated model enhances GMCR using the Analytical Hierarchy Process (AHP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods to extract the relative preferences of decision-makers in conflict resolution. The Hawizeh/Hoor-Al-Azim Wetland is facing increased dust storms in recent decades which are attributed to drying up of Mesopotamian wetlands, creating the potential for conflicts among riparian countries. The proposed integrated approach was applied in the Hawizeh/Hoor-Al-Azim Wetland fed by the Tigris and Karkheh Rivers. Turkey, Iran, Iraq, and Syria are located in the Tigris River basin, and the Karkheh River originates from the Zagros Mountains in western Iran. The results indicate that the achievement of an environmental balance depends on cooperation between Iran and Iraq to persuade Turkey to release the environmental flow to the wetland. Three strong equilibrium points were identified among 15 feasible states: (a) establishing a regional agreement among Iran, Iraq, and Turkey to reduce the effects of conflicts in the Hawizeh/Hoor-Al-Azim Wetland; (b) coalition of Iran and Iraq to motivate Turkey to reduce water withdrawal from the Tigris River; and finally, (c) exchanging water release for commodity market in Iran and Iraq for Turkey. In general, the economic cooperation among countries can be used as a negotiation tool to solve water conflicts in international wetlands.

Inter-basin water transfer planning with grey COPRAS and fuzzy COPRAS techniques: A case study in Iranian Central Plateau.

To overcome water scarcity and increasing water demands, achieving economic and social development, and to make regional equilibrium especially in countries with climate variations such as Iran, the inter-basin water transfer is considered as one of the crisis reduction methods. In this study, the COPRAS method, which is one of the new MCDM methods, is used for the first time to evaluate inter-basin water transfer projects in three configurations of integer, fuzzy, and grey (intervals). For this purpose, eight inter-basin water transfer scenarios from the Great Karoon Basin to the Central Iranian Plateau, are determined with the aim of overcoming drinking water scarcity. They are assessed by four important and practical criteria for inter-basin water transfer, including technical risks and the difficulty of execution, political and social problems, environmental problems, and cost per cubic meter of water according to the UNESCO standards. The weights of the criteria were obtained using three methods of AHP, DEMATEL, and Shannon entropy in the integer, fuzzy, and grey ways. Then, scenarios were prioritized using the COPRAS method. Finally, the results were ranked using the Borda count method, which is a method to aggregate the different ranking models. In this study, the results showed that among the criteria, technical risks, and then the cost per cubic meter of water are the essential criteria, respectively. Considering all ranking methods shows that among the scenarios, the eighth scenario, including water transfer from Behesht-Abad basin to Isfahan province and from Kharsan basin to Yazd and Kerman provinces, is superior to the other scenarios. Final COPRAS value of this scenario varies between 0.155 and 0.194 depending on the applied ranking method, and its total Borda score is 63. The findings of this study can help the decision-makers to evaluate the inter-basin water transfer projects in uncertain conditions.

Risk analysis of urban stormwater infrastructure systems using fuzzy spatial multi-criteria decision making.

Design and performance of stormwater infrastructure systems in urban areas have direct implications in social, environmental and public health problems and are of utmost importance to urban authorities and managers. Risk analysis in urban stormwater systems has become a must because of the extensive consequences of flooding in urban areas and limited funding for the rehabilitation and renovation of stormwater systems. Complexity, multidimensionality, and inherent uncertainties of the urban stormwater systems require the risk analysis approach to be comprehensive and able to address different uncertainties and spatial aspects of the problem. The objective of this study is to provide a comprehensive framework for risk analysis in urban stormwater systems. Multi Criteria Decision Making (MCDM), geographic information systems (GIS), and fuzzy sets theory are used to consider the diverse risk-affecting criteria, facilitate the analysis of spatial data and information and formulate the ambiguity and uncertainty of problem, respectively. The presented framework uses a Fuzzy Analytic Hierarchy Process (FAHP) for determining the weights of risk-affecting criteria (i.e. Hydrological and Hydraulic, Traffic, Social, Economic, Environmental, Structural, and Green space) in the presence of multiple decision makers. The Autodesk Storm and Sanitary Analysis model is used for the Hydrological and Hydraulic simulations. FSAW and FTOPSIS methods are used to provide the final product of the framework, i.e., a risk map that presents a risk level for each channel in the network. The framework is applied to District 11 of the capital city of Iran, Tehran as a real case study. The resulted risk maps indicate a high or very high flooding risk for 17.07 to 41.95 km of the stormwater channels in the study area, covering about 10.5 to 26% of the total length of the channels. The presented framework was found to be a suitable risk analysis tool in urban stormwater systems.

Developing an integrated risk management framework for agricultural water conveyance and distribution systems within fuzzy decision making approaches.

Irrigation canal networks, as the primary agricultural water conveyance and delivery systems, are exposed to a variety of hazards affecting the water distribution processes. This study, for the first time, develops a comprehensive risk management framework for the canal network through a Fuzzy Hierarchical method. In this regard, the risk is analyzed by a combination of probability, consequence, and vulnerability against identified hazards based on the hierarchical framework. The developed model is based on fuzzy numbers to consider the uncertainties arise from experts' opinion. To aggregate the calculated risk in the hierarchical framework, the Fuzzy Simple Additive Weighting (FSAW) approach was employed. To enhance the reliability of the water distribution system and decrease the risk of failure, six risk management alternatives are proposed based on the risk assessment results and the most significant hazards. To prioritize managerial scenarios, two sets of criteria were selected including quantitative criteria (consisting of cost of operation and risk reduction) and a qualitative set (compromising social and operational criteria). The risk management scenarios were prioritized based on two rational multi-criteria decision-making (MCDM) methods of a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Simple Additive Weighting (SAW). Regarding different degrees of importance of the criteria, a pair-wise comparison was conducted by a group of experts to determine the relative weight of the criteria. According to the risk assessment results, the riskiest hazards are poor maintenance, seepage, unexpected event, drought, and vandalism of the structure. Moreover, employing the MCDM model in risk-based decision-making reveals that "maintenance improvement" is ranked as the first scenario, with score values of 0.851 and 0.237 employing the SAW, and TOPSIS approaches, respectively.

Risk assessment model to prioritize sewer pipes inspection in wastewater collection networks.

In wastewater systems as one of the most important urban infrastructures, the adverse consequences and effects of unsuitable performance and failure event can sometimes lead to disrupt part of a city functioning. By identifying high failure risk areas, inspections can be implemented based on the system status and thus can significantly increase the sewer network performance. In this study, a new risk assessment model is developed to prioritize sewer pipes inspection using Bayesian Networks (BNs) as a probabilistic approach for computing probability of failure and weighted average method to calculate the consequences of failure values. Finally to consider uncertainties, risk of a sewer pipe is obtained from integration of probability and consequences of failure values using a fuzzy inference system (FIS). As a case study, sewer pipes of a local wastewater collection network in Iran are prioritized to inspect based on their criticality. Results show that majority of sewers (about 62%) has moderate risk, but 12%of sewers are in a critical situation. Regarding the budgetary constraints, the proposed model and resultant risk values are expected to assist wastewater agencies to repair or replace risky sewer pipelines especially in dealing with incomplete and uncertain datasets.