Process Mining Approach of a New Water Quality Index for Long-Term Assessment under Uncertainty Using Consensus-Based Fuzzy Decision Support System

One of the biggest challenges in water quality monitoring is how to optimize big Data gathered from a wide range of resources. This paper presented a new software-based pathway of process mining approach for extending a flexible WQI (Water Quality Index) that would deal with uncertainties derived from missing data occurrence in short- and long-term assessments. The methodology is based on integration of four multi-criteria group decision-making models coupled with fuzzy simulation including AHP (Analytical Hierarchy Process), fuzzy OWA (Ordered Weighting Average), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and fuzzy TOPSIS that were used for data mining and group consensus evaluation.. Examining the methodology on groundwater resources being supplied for drinking in Shiraz, Iran showed high integrity, accuracy, and proximity-to-real interpretation of water quality. This was the first study where decision-making risks such as Decision Makers’ risk-prone or risk-aversion attitudes (optimistic degree), DMs’ power, and consensus degree of each water quality parameter have been considered in WQI research. The proposed index offered a flexible choice in defining the intended project duration, stakeholders’ judgments, types of water use and water resource, standards, as well as type and number of water quality parameters. Thus, beside sustaining the unity in structure, this methodology could be suggested as a potentially WQI for other regions. The presented methodology would help more efficient monitoring of water resources for drinking purpose with respect to water quality.

     

Nonlinear Interval Parameter Programming Combined with Cooperative Games: a Tool for Addressing Uncertainty in Water Allocation Using Water Diplomacy Framework

Water Resources Management - This paper shows the utility of a new interval cooperative game theory as an effective water diplomacy tool to resolve competing and conflicting needs of water users...     

Determining the Main Factors in Declining the Urmia Lake Level by Using System Dynamics Modeling

Urmia Lake in Iran is the second largest saline lake in the world. This ecosystem is the home for different species. Due to various socio-economical and ecological criteria, Urmia Lake has important role in the Northwestern part of the country but it has faced many problems in recent years. Because of droughts, overuse of surface water resources and dam constructions, water level has decreased in such a way that one quarter of the lake has changed to saline area in the last 10 years. The purpose of this research is to determine the main factors which reduce the lake’s water level. To this end, a simulation model, based on system dynamics method, is developed for the Urmia Lake basin to estimate the lake’s level. After successful verification of the model, results show that (among the proposed factors) changes in inflows due to the climate change and overuse of surface water resources is the main factor for 65% of the effect, constructing four dams is responsible for 25% of the problem, and less precipitation on lake has 10% effect on decreasing the lake’s level in the recent years. In the future, the model also can be used by managers as a decision support system to find the effects of building new dams or other infrastructures.     

Urban Water Management Using Fuzzy-Probabilistic Multi-Objective Programming with Dynamic Efficiency

This paper introduces a new multi-objective optimization model for integrated urban water management. The model, based on compromise programming, is applied for the case of Tabriz city in Iran. The water demand of this city is rapidly growing and because of the limited resources, water supply is now more vulnerable to any mismanagement. Therefore the model attempts to optimize the water supply plan of city concerning three main objectives of maximizing the water supply, minimizing the cost and minimizing the environmental hazards. Due to the vagueness in defining the first objective, it is modeled by using the fuzzy set theory. Further, the uncertainty in satisfying some constraints is tackled by using the chance constraint approach. The decision variables are the extent of water withdrawal from the city aquifer, three different water transfer schemes and also the extent of demand management by leaks detection and pipes rehabilitation. Then the fuzzy-probabilistic multi-objective model is solved by considering the new idea of dynamic efficiency in the utility of decision maker and the results provide the optimum water supply in the planning horizon. The model results in robust solutions in which the demand management option dominates the new water transfer. Implementing the results of this model supports the environmental conservation and sustainable development.     

Multi-criteria Decision Making for Integrated Urban Water Management

The city of Zahedan, in South-eastern Iran, has high population growth, limited local freshwater resources and inadequate water distribution system resulting in water supply failures in recent years. This paper will investigate integration of several demand management measures such as leakage detection on water distribution network, water metering and low volume water fixtures as well as the conjunctive use of surface and groundwater resources of this city. For integration of water management criteria, compromise programming will be used as a multi-objective decision making method. The criteria include minimizing the cost, maximizing water supply and minimizing the social hazards due to the water supply operations. This model will derive optimum long-term plans for implementation of water resources. The results will show that demand management can delay a water transfer project for Zahedan city up to 10 years. Compromise programming is as an efficient tool for integrated water resources management in urban areas and the method is capable to being used by decision-makers in other cases.     

Localization of Groundwater Vulnerability Assessment Using Catastrophe Theory

Groundwater vulnerability is assessed by the DRASTIC method, which is more popular among the alternatives available. The challenge taken on board is to treat its inherent subjectivity in estimating the values of the embedded weights as recommended by USEPA for all aquifers. This paper uses a catastrophe based multi-objective evaluation system and applies it to the DRASTIC method to avoid undue preferences by decision maker. Thus, catastrophe fuzzy membership functions are used to treat the dependency of state variables on control parameters and thereby to determine the weights embedded in DRASTIC parameters. The proposed method estimates the weights of DRASTIC parameters with respect to local condition of study area. The Maragheh-Bonab aquifer in Iran is under threat by agricultural and industrial activities and therefore its vulnerability is assessed by the proposed method as well as by the general and pesticide DRASTIC methods. Comparison of results with the special distribution of nitrate-N (NO3-N) shows that the improved DRASTIC has a higher correlation index with respect to the general and pesticide DRASTIC methods. Also in seeking more reliability, the addition of new parameters is possible in the proposed method.