A Multi-criteria Decision-making Optimization Model for Flood Management in Reservoirs

Water Resources Management - Flood management in a reservoir-outlet system is a multi-criterion decision-making (MCDM) issue, in which preventing flood damage and flood overtopping, as well as...     

Developing a Multi-Objective Conflict-Resolution Model for Optimal Groundwater Management Based on Fallback Bargaining Models and Social Choice Rules: a Case Study

Conflict-resolution models can be used as practical approaches to consider the contradictions and trade-offs between the involved stakeholders in integrated water resource management. These models are utilized to reach an optimal solution considering agents interactions. In this paper, a new methodology is developed based on multi-objective optimization model (NSGA-II), groundwater simulation model, M5P model tree, fallback bargaining procedures and social choice rules to determine the optimal groundwater management policies with an emphasis on resolving conflicts between stakeholders. By incorporating the multi-objective simulation-optimization model and bargaining methods, the optimal groundwater allocation policies are determined and the preferences of the stakeholders as well as social criteria such as justice are also considered. The obtained data set, based on Monte Carlo analysis of calibrated MODFLOW model, is used for training and validating the M5P meta-models. The validated M5P meta-models are linked with NSGA-II to determine the trade-off curve (Pareto front) for the objectives. Social choice rule and fallback bargaining methods, as conflict-resolution models, are applied to determine the best socio-optimal solution among stakeholders, and their results are compared. The effectiveness of the proposed methodology is verified in a case study of Darian aquifer, Fars province, Iran. Results indicated that the solutions obtained by the proposed conflict-resolution approaches have an appropriate applicability. Total groundwater withdrawal, after applying the optimal groundwater allocations, reduced to 20.85 MCM, resulting in a 4.62 m increase in the mean groundwater level throughout the aquifer.     

Spatio-Temporal Multi-Criteria Optimization of Reservoir Water Quality Monitoring Network Using Value of Information and Transinformation Entropy

Identifying optimal Water Quality Monitoring Stations (WQMS) with high values of information on the entire reservoir status, instead of all potential WQMS would significantly reduce the monitoring network expenditure while providing adequate spatial coverage. This study presented a new methodology for spatio-temporal multi-criteria optimization of reservoir WQMS based on Value of Information (VOI), Transinformation Entropy (TE), Non-dominated Sorting Genetic Algorithm II (NSGA-II), Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), and IRanian Water Quality Index (IRWQI). Although, all mentioned methods and concepts are well-known and have been used in water resources management, but their integration into a specific application for spatio-temporal multi-criteria optimization of reservoir WQMS is definitely an innovation and a contribution to improvement of WQMS design. More specifically, maximizing VOI as a decision-makers’ design criteria for optimization of WQMS, and considering spatial and temporal variations of water quality at different reservoir depths are new innovations in this research. The multi-objective optimization model was based on three objectives: 1) minimizing costs; 2) maximizing VOI; and 3) minimizing TE (redundant information). Considering these objectives, the NSGA-II multi-objective optimization method was used to find Pareto-optimal solutions. The most preferable solution was then determined using PROMETHEE multi-criteria decision making method. The proposed methodology was applied to Karkheh Reservoir with more than 5 billion cubic meter capacity and 60 km length that is one of the largest reservoirs in Southwestern Iran, however, the proposed approach has the ability to be generalized for any generic reservoir. Considering equal weights for criteria, PROMETHEE method resulted in 6 optimized WQMS out of 60 potential ones and a period of 25 days for optimal sampling interval. The optimized monitoring stations were mainly located at deep parts where most water quality variations are expected to occur. To show sensitivity of the model to different weights, 4 scenarios with various relative weights were evaluated in the PROMETHEE method. Results indicated that by increasing the weight of the second criterion (maximizing VOI), the number of optimized WQMS increased and the sampling interval decreased.     

Delineating Capture Zone of a Pumping Well in a Slanting Regional Groundwater Flow to a Stream with a Leaky Layer

In this study, analytical and semi-analytical solutions are derived to delineate capture zone of a pumping well near a stream where a leaky layer exists between the aquifer and the stream. A groundwater regional flow is considered in the aquifer and allowed to have different angles with respect to the stream axis. Three critical pumping rates are introduced. At the first pumping rate, capture zone boundary tangents the interface between the aquifer and the leaky layer; called the in-homogeneity boundary. At the second pumping rate, capture zone boundary tangents the stream boundary and if the rate is increased, a part of pumped water would be withdrawn from the stream. The third pumping rate, which may be smaller or larger than the other two, is defined as the rate at which stream water begins to enter the leaky layer; it may or may not be captured by the pumping well. Four different capture zone configurations (cases) are analyzed for different values of pumping rates, groundwater flow directions, and leaky layer’s thickness and hydraulic conductivity. The first three cases analyze hydraulic situations whereby capture zone does not reach the stream, and hence, no pumped water is withdrawn from the stream. With the lowest pumping rate in the first case, no stream water enters the leaky layer. It enters the leaky layer but not the aquifer in the second, and enters the leaky layer and the aquifer in the third case. In the fourth case, where capture zone boundary intersects the stream, the fraction of pumped stream water to total pumped water is delineated.