Gunhui Chung

A general water supply planning model: Evaluation of decentralized treatment

Increasing population, diminishing supplies and variable climatic conditions can cause difficulties in meeting water demands; especially in arid regions where water resources are limited. Given the complexity of the system and the interactions among users and supplies, a large-scale water supply management model can be useful for decision makers to plan water management strategies to cope with future water demand changes. It can also assist in deriving agreement between competing water needs, consensus and buy-in among users of a proposed long-term water supply plans. The objective of this paper is to present such a general water supply planning tool that is comprised of modular components including water sources, users, recharge facilities, and water and wastewater treatment plants. The model is developed in a system dynamics simulation environment that helps users easily understand the model structure. The model was applied to a realistic hypothetical system and simulated several possible 20-year planning scenarios. In addition to water balances and water quality analyses, construction and operation and maintenance of system components costs were estimated for each scenario. One set of results demonstrates that construction of small-cluster decentralized wastewater treatment system could be more economical than a centralized plant when communities are spatially scattered or located at steep areas where pumping costs may be prohibitive.

Determination of optimal pressure monitoring locations for water distribution systems using entropy theory.

Determination of optimal pressure monitoring location is essential to manage water distribution system efficiently and safely. In this study, entropy theory is applied to overcome defects of previous researches about determining the optimal sensor location. The previous studies required the calibration using historical data, therefore, it was difficult to apply the proposed method in the place where the enough data were not available. Also, most researches have focused on the locations to minimize cost and maximize accuracy of the model, which is not appropriate for the purpose of maintenance of the water distribution system. The proposed method in this study quantify the entropy which is defined as the amount of information calculated from the pressure change due to the variation of discharge. When abnormal condition is occurred in a node, the effect on the entire network is presented by the entropy, and the emitter is used to reproduce actual pressure change pattern in EPANET. The optimal location to install pressure sensors in water distribution system is the nodes having the maximum information from other nodes. The looped and branched networks are evaluated using the proposed model. As a result, entropy theory provides general guideline to select the locations to install pressure sensors and the results can be used to help decision makers.

Optimal reclaimed water network design via two-stage stochastic binary programming

Diminishing supplies and population growth are stressing the limited water resources in many areas. A significant---but underutilized---water resource is reclaimed water, i.e., treated wastewater that is reintroduced for various purposes. In this paper, we present a cost-effective reclaimed water network design for irrigating public and agricultural areas using two-stage stochastic binary programming with random recourse. We consider both construction and energy costs expanded during a twenty-year period. By introducing binary variables that indicate discrete pipe and pump sizes, the nonlinear hydraulic equations, such as the Hazen-Williams equation, are linearized in system formulation. We consider uncertain reclaimed water demands, temporal and spatial population changes with two-stage construction decisions. In order for the system to meet significantly higher demands during the peak times, we consider two pumping conditions: one with average demands, which is used to compute the average energy consumption, and the other with peak demands, which is used for pipe size and pump station capacity selection. We apply our methodology to design a reclaimed water network for a realistic municipal system under estimated demand and population scenarios. We present the optimal total cost and system design, and examine the sensitivity of the system to model parameters.

Optimization of Water Reuse System under Uncertainty

Due to the increased water demand and severe drought as an effect of the global warming, the effluent from wastewater treatment plants becomes considered as an alternative water source to supply agricultural, industrial, and public (gardening) water demand. The effluent from the wastewater treatment plant is a sustainable water source because of its good quality and stable amount of water discharge. In this study, the water reuse system was developed to minimize total construction cost to cope with the uncertain water demand in future using two-stage stochastic linear programming with binary variables. The pipes in the water reuse network were constructed in two stages of which in the first stage, the water demands of users are assumed to be known, while the water demands in the second stage have uncertainty in the predicted value. However, the water reuse system has to be designed now when the future water demands are not known precisely. Therefore, the construction of a pipe parallel with the existing one was allowed to meet the increased water demands in the second stage. As a result, the trade-off of construction costs between a pipe with large diameter and two pipes having small diameters was evaluated and the optimal solution was found. Three scenarios for the future water demand were selected and a hypothetical water reuse network considering the uncertainties was optimized. The results provide the information about the economies of scale in the water reuse network and the long range water supply plan.

Optimal Water Supply Management using Dynamic Simulation

Increasing population is stressing already limited water supplies in the arid southwest US and elsewhere. Large-scale water supply management system is difficult given the complexities of water management policies. The objective of this paper is to develop a set of general water supply planning tool that can assist decision makers with long range planning decisions. The tool consists of simulation and optimization packages. The simulation model is geared to a general audience and developed in a dynamic simulation environment using Powersim Studio. A genetic Algorithm (GA) is linked with the simulation package to determine optimal system expansion and operation policies. Future conditions are assumed to be known with certainty for a sequence of operation periods.