The utilization of rubber dams for water supply and irrigated agriculture is becoming an emerging practice in developing countries. In this study, based on the SWOT (strengths, weaknesses, opportunities, threats) analysis, a variety of standards and processes in project management (PM) are integrated within the framework of the strategic management (SM) of an organization responsible for the management of new small-scale hydraulic infrastructures, e.g., rubber dam projects. The most important internal and external factors in PM and organizational SM of rubber dam projects in Iran are initially identified, adapted, and integrated. Thereafter, the factors are weighted, evaluated, and analyzed using the analytic hierarchy process (AHP) and combined SWOT–AHP methods. Based on the results, the total weighted scores of the internal and external factors are 2.353 and 2.718, respectively. Hence, the derived main strategy of the organization is WO. This means that the weakness factors can be reduced through the opportunities available for projects. Finally, a new methodology called “strategy matrix” resulting from “priority matrix” is proposed to prioritize and determine the organization’s possible strategies. The outputs demonstrate the first three priorities as a mix of the main strategy alternatives, e.g., W1O1, W7O1, and W9O1. The organization, hence, is proposed to use the economic benefits of rubber dam projects to further monitor organizational units, the project’s resource management, and the project’s stakeholder management (not the project’s stakeholders). The proposed research could be conceived as a pilot for sustainable management in developing countries, where strategic project management can produce important operational benefits.
Water supply is a crucial concern for planners across all countries, especially in rural communities. This paper proposes a multidimensional approach to examining the effective criteria for water supply projects in rural areas of Iran. The study compares alternative methods of project implementation and employs three multi-criteria decision-making (MCDM) methods: analytical hierarchy process (AHP), Fuzzy-AHP, and technique for order preference by similarity to ideal solution (TOPSIS) to prioritize criteria, sub-criteria, and alternatives. The results indicate that, among the five options analyzed, diverting water from the river and constructing temporary storage dams are the highest priorities, while pipeline branching to the nearby city or village is given the lowest priority. The study reveals that environmental and economic criteria are more critical than social-security and technical-management criteria, while negative environmental impacts and the possibility of risk-taking by subversive agents are the most important among the 14 sub-criteria studied.
In this study, a novel multiple-pollutant waste load allocation (WLA) model for a river system is presented based on the National Sanitation Foundation Water Quality Index (NSFWQI). This study aims to determine the value of the quality index as the objective function integrated into the fuzzy set theory so that it could decrease the uncertainties associated with water quality goals as well as specify the river's water quality status rapidly. The simulation-optimization (S-O) approach is used for solving the proposed model. The QUAL2K model is used for simulating water quality in different parts of the river system and ant colony optimization (ACO) algorithm is applied as an optimizer of the model. The model performance was examined on a hypothetical river system with a length of 30 km and 17 checkpoints. The results show that for a given number of both the simulator model runs and the artificial ants, the maximum objective function will be obtained when the regulatory parameter of the ACO algorithm (i.e., q0) is considered equal to 0.6 and 0.7 (instead of 0.8 and 0.9). Also, the results do not depend on the exponent of the membership function (i.e., γ). Furthermore, the proposed methodology can find optimum solutions in a shorter time.
A fuzzy multi-objective optimisation model was investigated for water quality management in a river under uncertain conditions. In this study, to deal with multiple pollutants simultaneously, the National Sanitation Foundation's water quality index was considered as one of the model's objective functions based on fuzzy set theory. This made it possible to investigate the overall effect of uncertainties on simultaneous changes. Another objective function was the total treatment costs for wastewater discharged into the river. A water quality simulation model and a non-dominated-archiving ant colony optimisation algorithm were used to determine the values of water quality parameters and the model's optimal solutions, respectively. Furthermore, a simulation–optimisation approach was adopted for facilitating the problem-solving process and applied to a hypothetical case study resembling a river system in Iran. The results show that the proposed model significantly reduced the total wastewater treatment costs compared with a similar single-objective model with a more cautious and a cost-effective approach. Although the treatment costs were increased compared with the similar deterministic model, more feasible approach was taken by considering the uncertainties associated with the objectives. With suitable modifications, the model could be easily adapted for other river systems.
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