Showing papers in "Journal of Water Resources Planning and Management in 1997"

Genetic Algorithms for Least-Cost Design of Water Distribution Networks

Abstract: This paper describes the development of a computer model GANET that involves the application of an area of evolutionary computing, better known as genetic algorithms, to the problem of least-cost design of water distribution networks. Genetic algorithms represent an efficient search method for nonlinear optimization problems; this method is gaining acceptance among water resources managers/planners. These algorithms share the favorable attributes of Monte Carlo techniques over local optimization methods in that they do not require linearizing assumptions nor the calculation of partial derivatives, and they avoid numerical instabilities associated with matrix inversion. In addition, their sampling is global, rather than local, thus reducing the tendency to become entrapped in local minima and avoiding dependency on a starting point. Genetic algorithms are introduced in their original form followed by different improvements that were found to be necessary for their effective implementation in the optimization of water distribution networks. An example taken from the literature illustrates the approach used for the formulation of the problem. To illustrate the capability of GANET to efficiently identify good designs, three previously published problems have been solved. This led to the discovery of inconsistencies in predictions of network performance caused by different interpretations of the widely adopted Hazen-Williams pipe flow equation in the past studies. As well as being very efficient for network optimization, GANET is also easy to use, having almost the same input requirements as hydraulic simulation models. The only additional data requirements are a few genetic algorithm parameters that take values recommended in the literature. Two network examples, one of a new network design and one of parallel network expansion, illustrate the potential of GANET as a tool for water distribution network planning and management.

Water network rehabilitation with structured messy genetic algorithm

Abstract: The importance of water distribution network rehabilitation, replacement, and expansion is discussed The problem of choosing the best possible set of network improvements to make with a limited budget is presented as a large optimization problem to which conventional optimization techniques are poorly suited A multiobjective approach is described, using capital cost and benefit as dual objectives, enabling a range of noninferior solutions of varying cost to be derived A structured messy genetic algorithm is developed, incorporating some of the principles of the messy genetic algorithm, such as strings that increase in length during the evolution of designs The algorithm is shown to be an effective tool for the current optimization problem, being particularly suited both to the multiobjective approach and to problems that involve the selection of small sets of variables from large numbers of possibilities Two examples are included that demonstrate the features of the method and show that the algorithm performs much better than a standard genetic algorithm for a large network

Optimal Monitoring Network and Ground-Water–Pollution Source Identification

Abstract: A methodology combining an optimal ground-water–quality monitoring network design and an optimal source-identification model is presented. In the first step of the three-step methodology, an embedded nonlinear optimization model is utilized for preliminary identification of pollutant sources (magnitude, location, and duration of activity) based on observed concentration data from arbitrarily located existing wells. The second step utilizes these preliminary identification results and a simulation optimization approach to design an optimal monitoring network that can be implemented in the subsequent time periods. In the third step, the observed concentration data at the designed monitoring well locations are utilized for more accurate identification of the pollutant sources. The design of the monitoring network can be dynamic in nature, with sequential installation of monitoring wells during subsequent time periods. The monitoring network can be implemented in stages, in order to utilize the updated information in the form of observed concentration data from a time-varying (dynamic) network. The performance evaluation of the proposed methodology demonstrates the potential applicability of this methodology and shows significant improvement in the identification of unknown ground-water–pollution sources with limited observation data.

Finding Robust Solutions to Water Resources Problems

Abstract: Water resources planners and managers are continually faced with decisions to be made under uncertainty. In planning problems such as water supply, flood control, and ground-water remediation, the trade-offs among expected cost, cost variability, and system performance and reliability must be assessed amidst inherent variability and imperfect information. Robust optimization (RO) is introduced as a framework for evaluating these trade-offs and controlling the effects of uncertainty in water resources screening models. Upon the introduction of scenarios, which represent realizations of the random parameters in the model, two types of robustness are defined: a policy is optimality-robust if it remains optimal or nearly optimal for all scenarios, and feasibility-robust if it remains feasible or nearly feasible for all scenarios. Applications to urban water transfer planning and ground-water quality management are presented, with optimality robustness related to cost variability and feasibility robustness rel...

Optimal Location of Control Valves in Pipe Networks by Genetic Algorithm

Abstract: This paper addresses the problem of appropriate location of control valves in a water supply pipe network and their settings via genetic algorithm (GA) to obtain maximum leakage reduction for given nodal demands and reservoir levels. Embedded in this optimization is the problem of determination of optimal control-valve settings in terms of minimization of system leakage for a given location of valves. It is shown through an example water distribution network that the optimally located valves are much more effective at producing maximum leakage reduction in the network. On the basis of multiple simulations of demand patterns, it was found that the expected value of leakage in a network provided with optimally placed control valves is practically independent of total demand. A study of the effect of varying demands on the optimal location of valves indicated distinct combinations of valve-locations for the different spatial patterns of nodal demands and for different total demands.

Planning Reservoir Operations with Imprecise Objectives

Abstract: Imprecise and noncommensurable objectives for reservoir operation are addressed through fuzzy dynamic programming using an implicit stochastic approach. Fuzzy membership functions for evaluating the achievement of a linguistically described operational goal and linguistically described constraints are estimated from surveys of decision makers. Summary statistics of the membership function values for optimal operation provide easily interpreted measures of degree of satisfaction among diverse objectives. An example application to the proposed Grey Mountain Reservoir on the Cache la Poudre River in northern Colorado showed that the expected degree of satisfaction for water supply objectives (constraints) would exceed 70% in six of 12 months, while 90% satisfaction of the flood control objective could be expected throughout the year. Expected degrees of satisfaction for storage, recreational, fish habitat, and hydropower objectives are substantially lower. Relative variability in predicted degrees of satisfa...

Value of seasonal flow forecasts in Bayesian stochastic programming

Abstract: This paper presents a Bayesian Stochastic Dynamic Programming (BSDP) model to investigate the value of seasonal flow forecasts in hydropower generation. The proposed BSDP framework generates monthly operating policies for the Skagit Hydropower System (SHS), which supplies energy to the Seattle metropolitan area. The objective function maximizes the total benefits resulting from energy produced by the SHS and its interchange with the Bonneville Power Administration. The BSDP-derived operating policies for the SHS are simulated using historical monthly inflows, as well as seasonal flow forecasts during 60 years from January 1929 through December 1988. Performance of the BSDP model is compared with alternative stochastic dynamic programming models. To illustrate the potential advantage of using the seasonal flow forecasts and other hydrologic information, the sensitivity of SHS operation is evaluated by varying (1) the reservoir capacity; (2) the energy demand; and (3) the energy price. The simulation results demonstrate that including the seasonal forecasts is beneficial to SHS operation.

Multiobjective Watershed-Level Planning of Storm-Water Detention Systems

Abstract: Detention basins are the most popular structural measure for urban flood control and have proven effective for both water quantity and quality management. Integrated, watershed-level planning of the layout and sizing of detention systems is essential because localized solutions may actually aggravate the negative impacts of urban drainage. Successive reaching dynamic programming (SRDP) is applied to minimize detention system costs of maintaining ranges of desired downstream peak flow attenuation, with basin and channel routing imbedded within the algorithm. A multiobjective genetic algorithm (MOGA) is also applied to generating nondominated solutions for system cost and detention effect for a watershed-level detention system. These algorithms are applied to a layout and design of a stormwater detention system in the Pazam watershed located in southern Taiwan. The case study confirms the robustness and computational efficiency of the SRDP algorithm, and the MOGA generates a wide range of nondominated solutions for trade-off analysis using a proposed \Ielite solutions conservation\N procedure.

Shortage Management Modeling for Urban Water Supply Systems

Abstract: Water shortages throughout the world have shaped the development of demand management and supply enhancement options to improve water supply reliability. A shortage management model based on two-stage linear programming is presented as a tool to integrate available water resources options while accounting for costs and hydrologic uncertainties. To illustrate the approach, the model is applied to a simplification of the East Bay Municipal Utility District (EBMUD) system. The model is expanded in several case studies to demonstrate its strengths in incorporating the effects of seasonal shortages and uncertainties relating to long-term and short-term management options. Conclusions regarding the effects of uncertainties on shortage management are presented. A special examination is made of conditions encouraging economical development of dual distribution system.

Changes in Heavy Rainfall in Midwestern United States

Abstract: Characteristics of heavy rainfall events are important in the design of water-handling structures, agriculture, weather modification, and in monitoring climate change. Traditionally it is assumed that the extreme rainfall time series are stationary with no trends. This assumption may not be true for portions of the Midwestern United States. A newly digitized record of precipitation for 304 sites that extends back to 1901 was used to examine this assumption. Results for the entire Midwest show that stations are more likely to experience their heaviest rainfall events in more recent years. An analysis of the geographic distribution of changes in the annual maximum time series shows areas of increases across the Midwest. The impact of the changes in the annual maximum time series can be significant in determining rainfall frequency values and consequent runoff calculations. These results suggest that rainfall frequency studies should be updated on a regular basis for maximum usefulness.

Water Supply Planning Simulation Model Using Mixed-Integer Linear Programming “Engine”

Abstract: This paper presents a simulation model to be used for water supply planning by a metropolitan water utility. Water supply operations for a single, monthly time step are formulated as a mixed integer linear program (or more simply, LP). The LP is then embedded in a month-by-month simulation model. The LP is formulated using a priority-based objective function. The model has been used successfully by the Alameda County Water District (California) staff for its long-range, integrated planning. The model also shows that some of the inherent weaknesses of math programming in general and mixed integer linear programming in particular, can be overcome to build a successful model.

Flood Estimation for Ungauged Catchments Using the GIUH

Abstract: Traditional techniques for design flood estimation use historical rainfall-runoff data and unit hydrographs derived from them. Such procedures are questioned for their reliability due to the climatic and physical changes in the watershed and their application to ungauged areas. To overcome such difficulties, the use of physically based rainfall-runoff estimation methods such as the geomorphological instantaneous unit hydrograph (GIUH) have evolved. In this study, the GIUH is derived from watershed geomorphological characteristics and is then related to the parameters of the Nash instantaneous unit hydrograph (IUH) model for deriving its complete shape. The model parameters of the GIUH and the Nash IUH model are derived using two different approaches. In the first approach (referred to as GIUH-I) the rainfall intensity during each time interval is allowed to vary, whereas in the second approach (referred to as GIUH-II) rainfall intensity is averaged over the entire storm period. This methodology has been a...

Optimal Stochastic Multicrop Seasonal and Intraseasonal Irrigation Control

Abstract: Optimal seasonal multicrop irrigation water allocation and optimal stochastic intraseasonal (daily) irrigation scheduling are carried out using a two-stage decomposition approach based on a stochastic dynamic programming methodology. In the first stage the optimal seasonal water and acreage allocation among several crops or fields is defined using deterministic dynamic programming with the objective of maximizing total benefits from all the crops. The optimization is based on seasonal crop production functions. Seasonal crop production functions are obtained using single-crop stochastic dynamic programming, which incorporates the physics of soil moisture depletion and the stochastic properties of precipitation. In the second stage optimal intraseasonal irrigation scheduling is performed using a single-crop stochastic dynamic programming algorithm, conditional on the optimal seasonal water allocation of stage one. Optimal daily irrigation decision functions are obtained as a function of root-zone soil moisture content and the currently available irrigation water. The methodology is applied to a case study characterized by four crops in which both the optimal irrigation applications and the optimal acreage for each crop are determined.

California's 1995 Water Bank Program: Purchasing Water Supply Options

Abstract: In anticipation of a second consecutive critically dry year, the California Department of Water Resources (DWR) organized the 1995 Drought Water Bank Program. For the first time, DWR purchased water supply options from willing sellers as insurance against a possible water-short year. These options could be used by Water Bank members if needed to meet critical needs. If the options were not needed, sellers kept the option payment. This paper provides a program manager's view of the planning, management, operations, and financing of the 1995 Drought Water Bank Program and shares the writer's experiences in securing options to provide water supply certainty to California water agencies.

Expected Probability and Annual Damage Estimators

Abstract: Controversy continues over the relative merits of traditional frequency estimators and the “expected probability” estimator of flood risk that incorporates an adjustment for parameter uncertainty. Both have solid theoretical motivation, but address different concerns. The description of hydrologic risk and uncertainty provided by new risk and uncertainty procedures adopted by the U.S. Army Corps of Engineers, and risk-based design procedures developed by others are shown to be equivalent to the expected probability model in simple cases. A 1995 National Research Council (NRC) report recommended against use of the expected probability model for evaluating expected annual damages and the probability of flooding; in particular, the NRC analysis and the 1989 Arnell analysis demonstrated that expected probability estimators yield risk and damage estimators that generally have large positive biases. Historical arguments and related issues are reviewed. Resolution of this controversy and success of the new U.S. Army Corps of Engineers (USACE) risk and uncertainty procedures require a clear framework for understanding what is meant by risk, variability, and uncertainty. Such risk analyses can better represent a community’s vulnerability to flooding and the large uncertainty in estimates of expected damages and residual flood risk.

Bootstrap Position Analysis for Forecasting Low Flow Frequency

Abstract: A method of random resampling of residuals from stochastic models is used to generate a large number of 12-month-long traces of natural monthly runoff to be used in a position analysis model for a water-supply storage and delivery system. Position analysis uses the traces to forecast the likelihood of specified outcomes such as reservoir levels falling below a specified level or streamflows falling below statutory passing flows conditioned on the current reservoir levels and streamflows. The advantages of this resampling scheme, called bootstrap position analysis, are that it does not rely on the unverifiable assumption of normality, fewer parameters need to be estimated directly from the data, and accounting for parameter uncertainty is easily done. For a given set of operating rules and water-use requirements for a system, water managers can use such a model as a decision-making tool to evaluate different operating rules.

Dynamic Optimal Ground-Water Reclamation with Treatment Capital Costs

Abstract: A dynamic optimal control algorithm for ground-water remediation was extended to incorporate treatment facility capital costs, as a function of the peak operating rate. Our approach to including the capital costs of treatment required no additional control variables and only a single additional state variable. Incorporation of the capital costs of the treatment facility had the greatest impact on design when the pumping policies were changed at intervals of six months or fewer. For longer management periods, inclusion of treatment facility capital costs had little effect on the selected optimal policies. This work demonstrates that capital treatment costs may significantly impact a dynamic management policy and that these capital costs should be explicitly incorporated into a dynamic management model.

Optimal Operation of Regional System with Diverse Water Quality Sources

Abstract: A management model for optimal operation and control of a regional water system is developed and evaluated. The system consists of numerous water sources with various qualities and consumers with differing flow rates and quality requirements. Flow at the nodes, supplies and demands, and solute mass balance are defined as mass balance constraints. Binary on/off controls for the hydraulic components are defined by continuous nonlinear functions. A two-time step formulation representing on-peak and off-peak power cost periods is solved on a personal computer using GAMS/MINOS. The method is readily extensible to cover more time periods and larger networks.

Evaluation of Water Losses in Distribution Networks

Abstract: A method to determine water losses from distribution networks, domestic connections, unauthorized connections, and domestic meters is presented. This method is based on stratified random sampling and leak flow gauging at connections, observation of users with low monthly consumptions, verification of house flow meters, and measurements in hydrometric districts. The results allow for the identification and causation of water losses in different areas of a city and for planning the actions that must be programmed to prevent additional losses. The method was applied to the drinking water distribution networks in 15 Mexican cities. Of the water supplied to urban distribution systems 24.5 is lost from house connection leaks, 10.6 from defects in mains and secondary lines, and 1.3 due to meter underregistry.

Event tree analysis of lock closure risks

Abstract: The use of event trees and subjective probabilities in risk analysis is illustrated via a case study: the estimation of the probability of closure of Poe Lock on St. Marys River (Sault Ste. Marie, Mich.) because of vessel accidents and other nonstructural failures. The risk of closure is needed to determine the benefits of building a second Poe-class lock at that location. An event tree structures the risk analysis. Probabilities associated with the branches of the tree were developed from a combination of historical data and subjective probabilities. The latter were obtained in workshops with navigation experts. This paper summarizes the risk analysis, and discusses the difficulties associated with obtaining the necessary probabilities. It was found that a 30-day closure could occur about once every 50 years. The results are most sensitive to assumptions concerning how often ships hit lock gates.

Estimating Expected Annual Damage for Levee Retrofits

Abstract: The U.S. Army Corps of Engineers (USACE) has instituted a new analysis methodology for estimating the expected annual damage (EAD) and resulting economic benefits accruing to proposed flood damage-reduction projects. Although the methodology is new, it still, in effect, uses expected probability to estimate the frequency of flooding and EAD. The National Research Council (NRC) in a review of USACE's study of the American River levees stated that the use of expected probability results in significantly biased estimates of EAD. An alternative damage model to that proposed by NRC is used to show that expected probability leads to an unbiased estimate of EAD. The damage model proposed requires that an unbiased estimate of damage results when applied to many projects. A simulation study demonstrates that EAD estimated with expected probability is unbiased, whereas the NRC's recommended estimator is biased.

Control model for hydroelectric energy value optimization

Abstract: A hydropower scheduling model that aims at minimizing thermal station-operation costs subject to various water- and power-demand constraints is described. The cost structure of the thermal power system is represented through incremental power-generation cost (or lambda) curves, which can be determined by running load-dispatching models. The model includes two control modules: one for the most efficient load allocation among the hydroplant turbines and another for the determination of the best hourly sequence of hydroplant power loads over the control horizon. These two modules are able to represent hydropower facilities and reservoir-management features in good detail, and the lambda curves effectively incorporate the essential elements of the thermal power system. The model is tested in the Lanier-Allatoona-Carters system in the southeastern United States and is shown to be computationally efficient even for very long control horizons.

Evaluation and Presentation of Dam Failure and Flood Risks

Abstract: Safety studies for existing dams have found that some do not satisfy current estimates of the probable maximum flood (PMF). An event or influence diagram can describe the random factors that contribute to major inflow floods and that determine reservoir operation and possible downstream damages during a flood event. This allows calculation of the probability of dam failure and the distributions of damages and loss of life using combinations of various analytical and Monte Carlo methods. This paper discusses the efficiency of different evaluation methods: event trees, simple Monte Carlo sampling, Latin hypercube sampling, importance sampling, and a analytical/stratified Monte Carlo (A/SMC) method. The analysis suggests that the A/SMC method and importance sampling have great potential for the efficient estimation of dam failure risks. Numerical examples employ the distributions of damages and loss of life to show the character of trade-offs presented by many dam safety decisions and illustrate problems with the partitioned multiobjective risk method (PMRM). The use of partial expected damage and loss of life functions is recommended to show the importance of low-probability/high-consequence events.

Discussion and Closure: Comparison of Methods for Predicting Deficient-Network Performance

Abstract: The authors have shed some much needed light on the poorly understood and much neglected issue of the pressuredriven analysis of water distribution networks with particular reference to less than fully satisfactory performance (Lumbers 1996). The authors' algorithm for network analysis with pressure-dependent nodal outflows appears in essence to be an iterative two-phase formulation in which each major iteration consists of a traditional demand-driven analysis followed by a formula-based calculation of improved nodal outflows. Taken together with Chandapillai (1991), the aforementioned twolevel iterative technique is useful for appraising the performance of distribution networks if nodal outflows and pressures are less than fully satisfactory. Such a situation is commonly encountered in distribution network reliability analysis (Tanyimboh and Templeman 1993, 1994, 1995). The discussers' preliminary results would appear to suggest that further research into algorithms for pressure-driven simulation is required to improve the computational efficiency of the approach. Nevertheless, the authors have presented some interesting results worth commenting on. Eq. (6), a special case of (8) (Chandapillai 1991), is quite useful

Comparison of Methods for Yield Assessment of Multiple Reservoir Systems

Abstract: This paper compares four different methods for estimating the yield of a multiple reservoir system These include simulation, a combined simulation-optimization model (WATHNET), a full optimization model, and a simplified optimization model called the yield model Simulation is used widely in practice and provides a good approximation of the behavior of the system but requires a set of operating rules to be specified The optimization methods automatically determine operating rules and are therefore quite useful in estimating the yield of a new system that has not yet been operated The four methods are used to estimate the safe historical yield of the Canberra water supply system (Australia) It was found that the full optimization model and the yield model provide high estimates of the system yield because they assume perfect knowledge of future inflows WATHNET presents a reasonable compromise in estimating the system yield using implied operating rules that are achievable in practice

Estimating Flood Frequency and Average Annual Damage

Abstract: In the National Research Council (NRC) report, “Flood Risk Management and the American River Basin—An Evaluation,” the use of expected probability (accounting for sampling uncertainty) in estimating flood frequencies and average annual flood damages, as practiced by the Corps of Engineers, was concluded to be biased. Alternative procedures recommended in the report are based on studies of samples drawn from a Gaussian population with a fixed damage function. There is no extension of the study to diverse populations (many flood locations) with different flow-damage functions, but conclusions drawn are that the recommended procedures provide frequency and damage estimates that are nearly unbiased. Rationale behind the report study is examined, and it is demonstrated herein that expected-probability procedures used by the Corps are indeed appropriate for flood-frequency estimation and for estimation of average annual flood damages.

Integrated Decision Support System for Tank Irrigation System Operation

Abstract: An integrated decision support system (DSS) that aids the operation of a tank (small-scale reservoir) irrigation system in south India is described. The DSS includes a data subsystem, a model subsystem, a knowledge base, and a user interface. The knowledge base of the DSS was developed from the knowledge derived from field experts as well as from the results of an optimization model. The DSS was evaluated to assess its decision-making capability using five years of data. Shortages in irrigation water supply simulated from the DSS were less than those occurring in the actual operation practiced by water authorities. The forecasts of system variables, namely, inflow and evapotranspiration were found to be adequate for real-time operation of the tank system.

Network Flow Programming Model for Multireservoir Sizing

Abstract: The paper describes a network flow programming (NFP) model for sizing of reservoirs in a multiple reservoir design problem. It is a multiperiod model, where all single period networks, representing reservoirs, rivers, canals, and demand points, are interconnected in adjacent periods by reservoir carryover arcs. Flows in carryover arcs represent reservoir storage and the maximum flow in an arc for a reservoir indicates storage capacity requirement for that reservoir. The carryover arcs are split into multiple arcs representing multiple zones in the storage capacity. Reservoir capacities are obtained by optimizing the flow in carryover arcs. The model enables to plan reservoirs for a desirable reliability in fulfillment of demands. The concept of preference matrix (PM) has been introduced to reflect the interreservoir and interzonal competitiveness based on the objective function. Applicability of the model is demonstrated by estimating the capacities of seven reservoirs in a water transfer scheme in India ...

Trihalomethane Precursor Model for Lake Youngs, Washington

Abstract: A mathematical model is developed to estimate trihalomethane formation potential (THMFP) in Lake Youngs, Wash. The model simulates both seasonal trends and spatial variations. The model kinetic framework includes total organic carbon (TOC), THMFP, chlorophyll \ia, zooplankton, Secchi disk depth, dissolved oxygen, dissolved TDP, and total phosphorus (TP). Calculated THMFP concentrations are dependent on external watershed TOC loading, algal cell densities, and TOC associated with extracellular products. Model performance is evaluated by comparison of calculated results with measured data from Lake Youngs. Analyses illustrate how THMFP concentrations in the raw water supply changes as a function of watershed TP and TOC loading. A general assessment considers the role of watershed land-use control, reservoir management, alternative treatment technologies, and the operation of the water supply distribution system in complying with finished drinking water standards for THM.

Estimating Non-Point-Source Loads and Associated Water Quality Impacts

Abstract: A water quality modeling project was undertaken to estimate non-point-source loading and associated water quality impacts for the Carson River in Nevada. As part of the modeling initiative, the WASP5 program was modified to simulate attached algae. Simulation results showed that a 48 reduction of total phosphorus (TP) load would be required to achieve the existing in-stream TP annual average standard of 0.10 mg-P/L. While this reduction decreased the predicted areal extent of water quality degradation, stream reaches immediately downstream of agricultural loading still experienced high algal populations and large concomitant diel dissolved oxygen fluctuations due to the fact that phosphorus is not rate limiting for algae growth at concentrations near 0.10 mg-P/L. A simulated 97 reduction of TP load was required to decrease significantly the population of attached algae, while only a 70 reduction of total non-point-source loading (both nitrogen and phosphorus) achieved similar results.