Reservoir Operation Optimization: A Nonstructural Solution for Control of Seepage from Lar Reservoir in Iran

Abstract

In this paper, the results of utilizing a deterministic dynamic programming model for operation of Lar Reservoir in Iran are discussed. This reservoir has experienced extensive seepage from the start of its operation. The optimization model consists of a three-step cycle, which began with the optimization of reservoir operation for a given set of streamflows. The optimal policies are then analyzed in a regression procedure to obtain a set of operating rules. After the first run, operating rules from the previous run were placed as a new constraint on the water releases with some pre-assigned tolerance and the cycle continues. The model also consisted of mathematical functions for modeling the seepage from Lar Reservoir as a function of storage head in the reservoir. The loss function in the model was also modified in order to incorporate parameters that reduce the seepage. Results of different scenarios showed the significant effect of optimal policies on reduction of seepage and increasing the reliability of water supply to Tehran Metropolitan Area. A pumping station was also proposed to utilize the inactive part of the reservoir, in access of over 100 MCM, in order to reduce the seepage. The effectiveness of different pumping capacities to reduce the seepage was also investigated.     

Spatial Scale Resolution of Prognostic Hydrological Models: Simulation Performance and Application in Climate Change Impact Assessment

Water Resources Management - In this paper, long-term hydrological response of a watershed to climate change was investigated taking into account the spatial scale effect on the performance of...     

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...     

PROMETHEE with Precedence Order in the Criteria (PPOC) as a New Group Decision Making Aid: An Application in Urban Water Supply Management

In this paper, a new group Multi-Criteria-Decision-Making (MCDM) method is introduced by combining two ??Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE)?? and ??Multi-attribute decision making with dominance in the criteria?? methods. PROMETHEE family of outranking methods is among the recently developed MCDM methods which have received lots of attention in the recent years because of its capacity in ranking finite set of alternative actions based on conflicting criteria. The second method helps the decision makers to consider ambiguity and imprecision of relative importance of each objective (criterion) without allocating importance weights to them. The proposed method of PROMETHEE with Precedence Order in the Criteria (PPOC) not only can address capabilities of PROMETHEE method just with determination of precedence order of criteria, but also can make it possible to have a group decision making environment with conflicting objectives. Operational management of an urban water supply system is a good example of a set of decision making problems with several objectives and Decision Makers (DMs). In this paper, PPOC method has been applied to the case study of Melbourne water supply system, previously analyzed in the literature, to assess a number of operation rules with respect to eight criteria evaluated under single or group decision-making situations. The satisfaction degree of each DM and the overall group ranking results have also been provided in the paper. The proposed method is applicable for different decision making problems in urban water supply management.     

A Multi-Objective Risk-Based Game Theoretic Approach to Reservoir Operation Policy in Potential Future Drought Condition

In this paper, by using the concept of Conditional Value at Risk (CVaR), a Leader-Follower game (LFG) based multi-objective optimization model is developed to determine the optimum 12-month operation policy of a reservoir in potential future dry periods. The minimization of CVaRs of storage loss and agricultural and environmental deficits along with maximization of planned allocation to agricultural sector are considered as leader’s objectives, while the followers try to maximize their share of water rights using Nash bargaining (NB) method. This framework is then used to model the operation policy of Dorudzan basin in Fars province, southwestern Iran. Water demand and daily climate data in the period of 2003 to 2015 for this basin, as well as future projections from fifteen IPCC-AR4 global circulation models (GCMs) for 2018–2030 under A2, B1 and A1B emission scenarios are considered to evaluate future dam operation policies. Future projections are downscaled using the LARS-WG model, which then feeds the HMETS watershed model to simulate the corresponding reservoir inflow time-series. Thereafter, three-hundred 12-month rainfall, evaporation and inflow time series with least inflow volume are used as input for the optimization model, which is solved using NSGA-II and GA algorithms. The results show while the model can determine the operation policy that keeps the associated risks in the acceptable range, it can satisfy the followers demands with respect to the available resources. The results also show that the agricultural sector of the study area can be hugely affected by potential future droughts.

     

Development of a Master Plan for Water Pollution Control Using MCDM Techniques: A Case Study

Abstract

Excessive demand for water due to a growing population, agricultural, and industrial development, along with climate change and depletion of nonrenewable resources have intensified the need for integrated water resources management and water pollution control. This paper presents different aspects of a master plan for water pollution control and the results of a case study for developing a master plan for water resources pollution control in Isfahan Province in Iran. Different components of the water resources system and pollution sources in the study area were identified and the effects of each of the pollution sources on surface and groundwater resources contamination were investigated. Two Multiple Criterion Decision Making (MCDM) techniques, namely Simple Additive Weighting (SAW) method and Analytical Hierarchy Structure (AHP) were used in order to determine the share of agricultural, industrial, and domestic sectors in polluting the water resources. In the application of MCDM techniques, engineering judgments and the information gathered from brain storming sessions with engineering experts and the agencies' officials have also been incorporated in order to overcome the data deficiency in this region for this type of analysis. Based on this study, several specific major categories of water pollution reduction projects were defined and in each category, several projects were identified. The total cost of implementation of the projects was also estimated and the projects were prioritized based on their potential impact on water pollution control.