Application of multi-criteria group decision-making for water quality management.

As waste discharge into numerous river systems escalates, the pollution of water bodies typically rises. Given the limited capacity of rivers to withstand pollution and their constrained self-cleaning capabilities, treated pollutants from waste discharge must be released into the river. Despite numerous models and algorithms proposed for managing river water quality to meet standards, literature, to our awareness, lacks the utilization of a comprehensive multi-criteria group decision-making approach for water quality management, particularly in river systems. Therefore, this research introduces a new, comprehensive multi-criteria group decision-making for the management of water quality in the Haraz River basin, located in Iran. To do so, the water quality of the basin, a one-dimensional water quality model, QUAL2Kw, was employed to simulate and calibrate the water quality along the river. The simulation results revealed that the downstream water quality violates the water quality standards. To mitigate this issue, various scenarios for waste load allocation (WLA) were evaluated, including no wastewater treatment, primary wastewater treatment, advanced secondary wastewater treatment utilizing the activated sludge (AS) method, and advanced wastewater treatment via the membrane bioreactor (MBR) method. Utilizing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Fuzzy TOPSIS group decision-making model, it was determined that the optimal solution was the implementation of secondary wastewater treatment utilizing the activated sludge method for the 11 PS of pollution, while still adhering to Iranian water quality standard. In addition, the findings of the present study indicate that the implementation of primary wastewater treatment, advanced secondary wastewater treatment utilizing AS, and advanced wastewater treatment through MBR within the study area led to a significant enhancement in water quality. This enhancement ranged from 35 to 105% across various scenarios when compared to conditions where no actions were taken to the treatment of water.

Developing sustainable land-use patterns at watershed scale using nexus of soil, water, energy, and food.

Aside from the many services that soil provides, it also stores water and makes it available to crops, which is critical for food security. However, the necessity of further studies for overcoming the existing gap in relation to the role of soil in the water, energy, and food nexus system has been preoccupying the experts and specialists around the world for some time. In this sense, the balance between many key ecosystem components based on the Soil, water, energy, and food (SWEF) nexus framework is one of the key characteristics of holistic and accommodative watershed management systems. To the best of our knowledge, the watershed scale is used as a planning unit for the first time in the current study to construct a conceptual model for adaptive management of optimum land-use/cover allocation using SWEF. The method was then used for the Shazand Watershed, Iran. Numerous metrics, such as soil erosion, soil organic carbon (SOC), water and energy use, mass efficiency, and economic efficiency, were investigated. Finally, a compound indicator was used to generate the SWEF nexus index (SWEFNI) for various land-uses/crops for the node year 2014. SWFENI ranged from 0.19 (worst) for rangeland to 0.78 (best) for almond plantations, according to the findings. The study's present approach may be tested worldwide.

Application of risk-based multiple criteria decision analysis for selection of the best agricultural scenario for effective watershed management.

Effective watershed management requires the evaluation of agricultural best management practice (BMP) scenarios which carefully consider the relevant environmental, economic, and social criteria involved. In the Multiple Criteria Decision-Making (MCDM) process, scenarios are first evaluated and then ranked to determine the most desirable outcome for the particular watershed. The main challenge of this process is the accurate identification of the best solution for the watershed in question, despite the various risk attitudes presented by the associated decision-makers (DMs). This paper introduces a novel approach for implementation of the MCDM process based on a comparative neutral risk/risk-based decision analysis, which results in the selection of the most desirable scenario for use in the entire watershed. At the sub-basin level, each scenario includes multiple BMPs with scores that have been calculated using the criteria derived from two cases of neutral risk and risk-based decision-making. The simple additive weighting (SAW) operator is applied for use in neutral risk decision-making, while the ordered weighted averaging (OWA) and induced OWA (IOWA) operators are effective for risk-based decision-making. At the watershed level, the BMP scores of the sub-basins are aggregated to calculate each scenarios' combined goodness measurements; the most desirable scenario for the entire watershed is then selected based on the combined goodness measurements. Our final results illustrate the type of operator and risk attitudes needed to satisfy the relevant criteria within the number of sub-basins, and how they ultimately affect the final ranking of the given scenarios. The methodology proposed here has been successfully applied to the Honeyoey Creek-Pine Creek watershed in Michigan, USA to evaluate various BMP scenarios and determine the best solution for both the stakeholders and the overall stream health.

A new bankruptcy method for conflict resolution in water resources allocation.

Growing competition over water resources has caused political disputes among stakeholders and has brought conflict resolution in the focus of negotiation processes. In these cases, bankruptcy rules for redistributing an asset when it is not sufficient to meet all claims could be applied. In this paper, we develop a new bankruptcy rule for water resources problems that considers agents' contribution to the total resources as well as their claims, which is in accordance with the UN Watercourses Convention (1997), as important factors for reallocation. Using the Euphrates River and a hypothetical case from the literature as examples, the new rule is compared with four alternative rules. The results show that the novel solution is potentially more powerful to help solving conflicts over river sharing problems.

Sensitivity analysis of the OWA operator.

The successful design and application of the ordered weighted averaging (OWA) method as a decision-making tool depend on the efficient computation of its order weights. The most popular methods for determining the order weights are the fuzzy linguistic quantifiers approach and the minimal variability method, which give different behavior patterns for the OWA. These two methods will be first analyzed in detail by using sensitivity analysis on the outputs of the OWA with respect to the optimism degree of the decision maker, and then the two methods will be compared. The fuzzy linguistic quantifiers approach gives more information about the behavior of the OWA outputs in comparison to the minimal variability method. However, in using the minimal variability method, the OWA has a linear behavior with respect to the optimism degree, and, therefore, it has better computation efficiency. Since maximizing the combined goodness measure and minimizing its sensitivity to optimism degree are conflicting objectives, a new composite measure of goodness will be defined to have more reliability in obtaining optimal solutions. The theoretical results will be illustrated in a water resources management problem.