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In this study, comprehensive flood forecasting model for main tributaries in the Han river was developed using the model struc-tures of comprehensive 4 rivers flood forecasting model newly coded in 2012. The main tributaries in the Han river is Joong-RangCheon, Wang-Seok Cheon, Tan Cheon, and An-Yang Cheon. The optimized parameters in the tributaries were proposed as well.In the tributaries, because of the short forecasting time, the model parameters tend to be determined in each basin. Therefore, theoptimized parameters in the newly developed flood forecasting model were proposed. Storage function method is also utilized inthe comprehensive flood forecasting model with the combination of the subsurface flow model which is for calculating infil-tration, percolation, and groundwater flow. Therefore, the newly developed flood forecasting is applicable in the long-term riverflow forecasting. The 2-stage optimization was proposed. In the first stage, parameters in the subsurface flow model were opti-mized using a long-term rainfall-runoff data, and the parameters for the storage function method were optimized in the secondstage using the rainfall events. A range of the optimized parameters was presented, from which the sensitivities and the param-eters could be estimated. However, the understandable interpretation about the ranged parameters was not possible. Therefore, therepresentative parameters were proposed using weighted average, middle value, and representative rainfall events. As a result, theparameter value which provide the smallest error was selected as the final proposed parameter. It could improve the efficiency ofthe runoff forecasting in the practical application.Key words : 4 river comprehensive flood forecasting model, flood forecasting model in main tributaries, storage function method,subsurface flow model, parameter optimization

A significant-but underutilized-water resource is reclaimed water, i.e., treated wastewater that is reintroduced for various purposes. Especially in water scarce regions, reclaimed water is often the only remaining source of water to meet increasing population and water demands. In this paper, we develop a new model formulation for the cost-effective branched reclaimed water network design and solve it with an exact optimization method. We consider both construction and energy costs expended over a twenty-year period. Unlike other formulations, uncertain reclaimed water demands, temporal and spatial population changes are explicitly considered in our two-staged construction and expansion model. In order for the system to meet higher demands during the peak times and to evaluate energy use, 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 dominates pipe size and pump station capacity selection. By introducing binary variables that indicate discrete pipe and pump sizes, we linearize the nonlinear hydraulic equations and objective function terms. We develop methods to significantly reduce the problem dimension by exploiting the problem characteristics and network structure. Our computational results indicate that these methods are very effective. Finally, we apply our model to design a reclaimed water network for a realistic municipal system under estimated demand and population scenarios, and analyze the sensitivity of the system to model parameters. We formulate a cost-effective reclaimed water network design problem.We consider uncertain demands and growth of a community in a twenty-year period.The proposed preprocessing methods significantly reduce the problem dimension.The second-stage demands are the most significant factor for total cost.The value of stochastic solution is most sensitive to the pipe material costs.

Recently, the increase of the abnormal flood events mainly due to the climate change led the severe casualty and property damages particularly in the small and medium size of watersheds. Therefore, in this study, the water level changes cased by climate change in the mainstream and tributaries of the Nakdong river basin were analyzed. As results, 0.35~0.74 m of the water levels in the mainstream were changed and 0.47~0.72 m of alteration in the tributaries. To evaluate the effect of climate change, the expected differences on the relationship between return period and flood level in the tributaries were evaluated using the existing data in the basin plan report for the Nakdong river basin. Also, the effected areas by the climate change were analyzed using the water level alterations caused by climate change and the resulted flooding area in the Nakdong river basin was increased 6.45% in maximum with the consideration of climate change. It is therefore expected that the proposed method to estimate the effected area by climate change might provide the basic information on developing natural disaster mitigation strategies.

The climate change has clearly affected most parts and systems in the globe. Particularly, the recent global warming is pre-sumed as the main reason of the increasing severe flood frequency, resulting a significant damages on the human life and prop-erty. This increasing trend on the occurrence of severe flood is very remarkable in the Korean Peninsula as well. Therefore, theappropriate flood prevention and mitigation methods are required. In this study, to assess the climate change effects on floodingrisk areas in the Nakdong river basin, the flood and river acts from Korea and other countries were investigated and the current sit-uation and problems were analyzed. The flood risk considering climate change were also assessed for the flood risk areas amongthe natural disaster risk areas proposed in 2010 to suggest the future management strategy against the future severe flood damage.The proposed flood risk assessment results for the flood risk areas might be used as a basic information to develop climate changeadaptation strategy.Key words : Climate change, Flood risk assessment, Flood management, Natural disaster risk area

Robustness is generally defined as a system's ability to stay within satisfactory bounds against variations in system factors. Recently, robustness has been indicated to be a useful objective function for the optimal design of water distribution systems (WDSs). While various formulations are possible to represent WDS robustness, few efforts have been made to compare the performances of these formulations. This study examined three potential formulations for quantifying system robustness to provide guidelines on the usage of a robustness index. Giustolisi et al.'s robustness index (see Giustolisi et al. (2009) ‘Deterministic versus stochastic design of water distribution networks’, J. Water Resour. Plann. Manage.135 (2), 117–127) was adopted to calculate nodal robustness, while the system robustness was defined using three different formulations: (1) minimum among nodal robustness values; (2) total sum of nodal robustness; and (3) sum of nodal robustness at multiple critical nodes. The three proposed formulations were compared through application to identify the most appropriate one for enhancing system robustness in general; three representative benchmark networks were optimally designed to minimize the economic cost while maximizing the system robustness.

The researches on the parameter estimation for storage function method have been conducted for a long time using different methods. However, the determination of the optimal parameters takes a long time and there is a controversy that the proposed optimal parameters do not likely represent the physical characteristics of watershed. In this study, the characteristics of the continuity and storage function equation was analyzed and sensitivities were evaluated. As the result, the only optimal solution is suggested among several local optimums. It is also shown that the lag time is able to be determined using the direct runoff starting time of the watershed. From the sensitivity analysis, it is also proved that the determination of the lag time is very important and the only optimal solution could be found easily after selecting the lag time. Therefore, unlike the traditional optimization method, the proposed method does not take a long time to find the optimal solution which is depending on the characteristics of the rainfall events. The fixed coefficient method which is a method to estimate the optimal parameters of storage function method has been modified using the proposed method. Therefore, the practical efficiency to apply storage function method could be enhanced by applying the proposed method. While the traditional method takes care only the error of the runoff hydrograph, it is very important that the proposed method considers the characteristics of the watershed.

Storage function method has been used for flood forecasting in the major rivers in Korea, however, the researches on the relationship between the parameters and runoff characteristics was not sufficient. In addition, there has been a controversy about the optimized parameters without the consideration of the physical characteristics of the basin. Therefore, in this study, the SCE-UA method is used to optimize the parameters and the proposed method was applied with two stage optimization in the Jeongseon and Yeongwol watersheds located in the most upstream in the South Han river. The contour map was developed to investigate parameters and the error surface calculated from the runoff. The proposed parameters is to provide a range of the possible parameter set in a watershed, rather than a specific value. However, the applicability is examined using the average value of the proposed ranged parameters. In this study, the criticism about the optimization technique to find an optimal value having no physical meaning on a watershed is tried to avoid. The objective of this study is to provide a range of parameters for the flood forecasting model and the intuition about the behavior of the parameters, so the efficiency of flood forecasting is increased.

Calibration is a process of comparing model results with field data and making the appropriate adjustments so that both results agree. Calibration methods can involve formal optimization methods or manual methods in which the modeler informally examines alternative model parameters. The development of a calibration framework typically involves the following: (1) definition of the model variables, coefficients, and equations; (2) selection of an objective function to measure the quality of the calibration; (3) selection of the set of data to be used for the calibration process; and (4) selection of an optimization/manual scheme for altering the coefficient values in the direction of reducing the objective function. Hydraulic calibration usually involves the modification of system demands, fine-tuning the roughness values of pipes, altering pump operation characteristics, and adjusting other model attributes that affect simulation results, in particular those that have significant uncertainty associated with their values. From the previous steps, it is clear that model calibration is neither unique nor a straightforward technical task. The success of a calibration process depends on the modeler’s experience and intuition, as well as on the mathematical model and procedures adopted for the calibration process. This paper provides a summary of the Battle of the Water Calibration Networks (BWCN), the goal of which was to objectively compare the solutions of different approaches to the calibration of water distribution systems through application to a real water distribution system. Fourteen teams from academia, water utilities, and private consultants participated. The BWCN outcomes were presented and assessed at the 12th Water Distribution Systems Analysis conference in Tucson, Arizona, in September 2010. This manuscript summarizes the BWCN exercise and suggests future research directions for the calibration of water distribution systems.

The urbanization of an undeveloped area often shortens outflow travel time and increases peak discharge from the basin, thereby increasing the downstream flood frequency. Stormwater detention ponds are the most common measure to maintain the outflow from the post-developed basin to a flow similar to that under the pre-developed condition. The design criteria of stormwater detention ponds are to minimize construction cost while achieving the flood control purpose. The tedious and time-consuming, trial-and-error method is commonly used to determine the optimal size and location of the pond and outlet structure for a design storm period. In this study, a stochastic search algorithm, a Genetic Algorithm (GA), is used to optimize the detention pond design. The decision variables are the pond storage, and the pipe diameters and number of pipes for the service outlet. The flood control objective considered in this study is that the peak discharge in the post-developed condition does not exceed that under the pre-developed condition and that the maximum water level in the pond during the flood remains below the allowable water level. The proposed optimization algorithm method was applied to the real design of two detention ponds in South Korea, where it generated better design options comprising smaller pond storage and smaller outlet standpipe dimensions than those of the traditional trial-and-error method, and in a much shorter computational time. Therefore, the stochastic search algorithm, GA, can be successfully applied in the design of a stormwater detention basin to improve accuracy and convenience. The engineers can accordingly assess the development plan in terms of the potential basin disaster more efficiently than is possible when using the tedious computation method.

In this study, Subsystem-Based Pressure Dependent Demand (SPDD) analysis is implemented using the concept of effective supply to eliminate the uncertainties caused by the Head-Outflow Relationship (HOR) in Pressure Dependant Demand (PDD) analysis. This study optimizes the nodal water demands to satisfy the nodal pressure requirement under the abnormal condition defined as the part of the water distribution systems that is closed due to maintenance, rehabilitation, or accidents. The total water supply is optimized and defined as the effective supply, which is the maximum water supply while maintaining the nodal pressure requirements (25 psi) to guarantee the customer’s convenience. A meta-heuristic algorithm, the Harmony Search (HS) algorithm, is applied to optimize the system. To decrease the effect of the HOR uncertainties, an optimization method is proposed in this study using the EPANET model that is widely used for the hydraulic simulation. To evaluate the applicability of the suggested model, Supply Index (SI), Pressure Index (PI), Effective Supply Index (ESI), and Subsystem Importance Index (SII) are also defined and calculated from a real-sized network. This paper firstly tried to perform pressure dependent demand analysis for subsystem without the HOR equation that has been an important issue in water distribution system analysis. The developing method could be a good alternative for the design and maintenance of water distribution systems.

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.

A water supply system needs to be evaluated in order to meet the future water demand and to preserve the natural environment. Because most annual rainfall events occur during the summer in South Korea, it is necessary to develop an efficient water supply plan for the entire year. To cope with future demands, accurate evaluation of supply scenarios are required in order to determine the most feasible plan. In this paper, a water supply system was developed for the Geum River basin, South Korea using an object-oriented system dynamics approach, which enables the decision maker to develop a model that can be easily understood by the stakeholder and the non-modeler. Two different scenarios were applied for the developed water supply system to investigate the long-term water supply plan. Water savings measures to reduce water demands in the residential area were suggested and evaluated. The water quality degradation was predicted and the expansion of the capacity of wastewater treatment plants to cope with the aggravated water quality was suggested.

The major reason to construct large dams is to store surplus water during rainy seasons and utilize it for water supply in dry seasons. Reservoir storage has to meet a pre-defined target to satisfy water demands and cope with a dry season when the availability of water resources are limited temporally as well as spatially. In this study, a Hedging rule that reduces total reservoir outflow as drought starts is applied to alleviate severe water shortages. Five stages for reducing outflow based on the current reservoir storage are proposed as the Hedging rule. The objective function is to minimize the total discrepancies between the target and actual reservoir storage, water supply and demand, and required minimum river discharge and actual river flow. Mixed Integer Linear Programming (MILP) is used to develop a multi-reservoir operation system with the Hedging rule. The developed system is applied for the Han River basin that includes four multi-purpose dams and one water supplying reservoir. One of the fours dams is primarily for power generation. Ten-day-based runoff from subbasins and water demand in 2003 and water supply plan to water users from the reservoirs are used from "Long Term Comprehensive Plan for Water Resources in Korea" and "Practical Handbook of Dam Operation in Korea", respectively. The model was optimized by GAMS/CPLEX which is LP/MIP solver using a branch-and-cut algorithm. As results, 99.99% of municipal demand, 99.91% of agricultural demand and 100.00% of minimum river discharge were satisfied and, at the same time, dam storage compared to the storage efficiency increased 10.04% which is a real operation data in 2003.

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.

Bivariate distributions have been recently employed in hydrologic frequency analysis to analyze the joint probabilistic characteristics of multivariate storm events. This study aims to derive practical solutions of application for the bivariate distribution to estimate design rainfalls corresponding to the desired return periods. Using the Gumbel mixed model, this study constructed rainfall–frequency curves at sample stations in Korea which provide joint relationships between amount, duration, and frequency of storm events. Based on comparisons and analyses of the rainfall–frequency curves derived from univariate and bivariate storm frequency analyses, this study found that conditional frequency analysis provides more appropriate estimates of design rainfalls as it more accurately represents the natural relationship between storm properties than the conventional univariate storm frequency analysis.

A water supply system is a complex network of pipes, canals and storage and treatment facilities that collects, treats, stores, and distributes water to consumers. Increasing population and its associated demands requires systems to be expanded and adapted over time to provide a sustainable water supply. Comprehensive design tools are needed to assist managers determine how to plan for future growth. In this study, a general large-scale water supply system model was developed to minimize the total system cost by integrating a mathematical supply system representation and applying an improved shuffled frog leaping algorithm optimization scheme (SFLA). The developed model was applied to two hypothetical water communities. The operational strategies and the capacities for the system components including water transport and treatment facilities are model decision variables. An explicit representation of energy consumption cost for the transporting water in the model assists in determining the efficacy of satellite wastewater treatment facilities. Although the water supply systems studied contained highly nonlinear terms in the formulation as well as several hundred decisions variables, the stochastic search algorithm, SFLA, successfully found solutions that satisfied all the constraints for the studied networks.

A water supply system is a comprehensive system including the components of water users, sources, treatment plants, and transportation measures. The complex nature of a water supply system, however, has made hard to develop and evaluate a comprehensive and generic water supply system model. In this study, a generic water supply system model is used to evaluate water sustainability for a hypothetical system in the semi-arid area. An environment for object-oriented system dynamics model allows the decision maker to develop a model that can be understood easily by the stakeholder and non-modeler. The modular structure of the generic water supply system also allows for integration of a site specific model by combining modules which a modeler may wish to have in the system. Imported and reclaimed waters to support groundwater as alternative water sources are evaluated in the hypothetical system in this study. As a result, alternative water sources demonstrate an important role to maintain water sustainability of the system when groundwater is the main source.

This paper presents a stochastic model to generate daily rainfall occurrences at multiple gauging stations in south Florida. The model developed in this study is a space–time model that takes into account the spatial as well as temporal dependences of daily rainfall occurrence based on a chain-dependent process. In the model, a Markovian method was used to represent the temporal dependence of daily rainfall occurrence and a direct acyclic graph (DAG) method was introduced to encode the spatial dependence of daily rainfall occurrences among gauging stations. The DAG method provides an optimal sequence of generation by maximizing the spatial dependence index of daily rainfall occurrences over the region. The proposed space–time model shows more promising performance in generating rainfall occurrences in time and space than the conventional Markov type model. The space–time model well represents the temporal as well as the spatial dependence of daily rainfall occurrences, which can reduce the complexity in the generation of daily rainfall amounts.

In 1993 P. F. Boulos and T. Altman developed an efficient explicit scheme for determining steady state water quality in a distribution system for conservative and zero-order reacting constituents. This approach is extended here to first- and second-order reactions and a general reaction relationship is discussed. Mass balance relationships and nonconservative reaction kinetics lead to a general matrix for constituent analysis. The directed graph that results in steady flow conditions permits single equations to be solved sequentially providing the water quality distribution throughout the system. The method can be used to solve for linear and nonlinear conditions and is demonstrated for first-order decay and growth and second-order decay on a 13-pipe system.

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.

This study adopts the Harmony Search (HS) meta-heuristic algorithm (Geem et al., 2001; Kim et al., 2001) to calibrate a hydraulic simulation model (EPANET) for C-Town. The algorithm conceptualizes a musical process of searching for a perfect state of harmony (optimal solution) and allows a random search without initial values, thus removing the necessity for information on derivatives. The calibration procedure is implemented in a manner that the sum of errors between two data sets: the measured SCADA data and the values derived from the HS algorithm. The calibration process is implemented into three stages – preprocess, rough tuning, and fine tuning. In the preprocess stage the original SCADA data and pump control rules are modified to complement missing data and operation rules. In the rough and fine tuning stages the C-town network is divided into five sub-networks based on supply zones. Pipe roughness factors in each sub-network are calibrated by pipe diameters which are divided into five groups. Therefore, total number of decision variables in each sub-network is 168 nodal water demand factors and 5 pipe roughness coefficients. The entire C-town network is also calibrated using each already calibrated sub-network as the initial populations. It is found that the simple network in the downstream end can be calibrated separately; thus, the network division does accelerate the convergence speed. Several parameters of the HS algorithm such as HMCR and PAR can be adjusted to find better calibration results

The optimal design of water distribution system has been usually performed with fixed hydraulic variables and single objective. However, a realistic water distribution system should take inherent uncertainties of data into consideration. This study suggests a method to minimize the system cost and maximize the robustness of network based on uncertainties in nodal demands and pipe roughness coefficients. Multi-Objective Genetic Algorithm (MOGA) implements two separate optimization models for the least cost and the best robustness design as the initial population. The model considers the uncertainties in roughness coefficient and water demand by using Latin Hypercube sampling technique with the assumption of beta probability density function. Several beta probability density functions with wide range of data are evaluated in the procedure. The proposed approach is tested in case study of the

It is of utmost importance for public health to identify optimal location for sensors to detect all possible contamination events. However, it has been difficult due to several reasons including the complex nature of water distribution system, inadequate technologies to detect every contaminant, and most of all, limited budget. The usual techniques for optimizing sensor locations require significant computational power and time, thus making it difficult to apply in real systems. This study simplifies the computation by utilizing network analysis, betweenness centrality, and shortest path algorithm. Betweenness centrality defines the centrality of a node in terms of degree to which the node falls on the shortest path between other pairs of nodes. In addition to network analysis, Multi-Objective Genetic Algorithm and travel time matrix are used to consider the sensitivity of flow directions in pipes, presenting Pareto solutions. Consequently, the proposed method will minimize detection time and number of sensors needed. It is expected to benefit the most when the water distribution network is large and complicated.