A MUNICIPAL WATER SUPPLY INVESTMENT PROBLEM IN RHODE ISLAND1

ABSTRACT: The traditional “requirements” approach to water system planning presumes perfectly inelastic demand and arbitrarily selects a fixed water requirement per capita per day as a planning target. Economists have often pointed out that such a policy leads to over-investment in water supply facilities; a superior approach would maximize some measure of net benefits incorporating price-sensitive demand. Using a dynamic programming model to depict an investment problem in Rhode Island, we find that ambiguities about how to incorporate price-sensitive demand into a decision framework may make such an approach as arbitrary as the requirements approach. Water conservation responses may be a function of other social parameters than water price; if so, variations in these social parameters should be regarded as economic alternatives to water supply investments.     

PROCEDURE FOR THE ECONOMICAL EVALUATION OF WATER NETWORKS' PARAMETERS1

ABSTRACT: The Generalized Geometric Programming and Branch and Bound technique are used to reach optimally designed water systems with their variables in integer forms. The water systems and constraints are formulated by sets of nonlinear equations. A solution for a specific water system is presented.     

COMPUTER PROGRAMMING FOR MAXIMUM MODELING INFORMATION TRANSFER1

Abstract: The diffuculty in understanding the listings of many available hydrologic models programmed in FORTRAN is a serious limitation to their verification and use. By expending more effort in creating clearly written computer programs, more information can be transferred to those interested in modeling hydrologic process. The use of simulation languages to produce more understandable program listings and increase the flow of informationg is recommended. An example is presented in which surface water runoff from storms on small rural watershedds is modeled.     

IMPLEMENTATION OF AN OPTIMIZATION MODEL FOR OPERATION OF A METROPOLITAN RESERVOIR SYSTEM1

ABSTRACT: A deterministic dynamic programming optimization model with a refining sectioning search procedure is developed and implemented to find least cost withdrawal and release patterns for water supple from a multiple reservoir system serving a metropolitan area. Applications are made to teh four reservoir system operated by the city of Dallas, Texas. A realistic cost structure, including nonlinear power consumption, block rate unit power costs, and flow dependent power consumption for intracity water distribution, is utilized. Applications are made to find least cost operating patterns and, as well, by inclusion of a water loss penalty function, supply patterns which will reduce evaporation water losses for the Dallas system.     

AQUIFER MANAGEMENT UNDER TRANSIENT AND STEADY-STATE CONDITIONS1

ABSTRACT: The equations of transient and steady-state flow in two-dimensional artesian aquifers are approximated using finite differences. The resulting linear difference equations, combined with other linear physical and management constraints and a linear objective function, comprise a linear programming (LP) formulation. Solutions of such LP models are used to determine optimal well distributions and pumping rates to meet given management objectives for a hypothetical transient problem and for a steady-state field problem.     

OPTIMAL CAPACITIES OF WATER SUPPLY RESERVOIRS IN SERIES AND PARALLEL1

ABSTRACT: The planning of water supply reservoirs has traditionally been based on the Rippl or sequent peak analysis which applies to the design of a single reservoir. This paper incorporates the sequent peak method as the central feature in establishing a procedure for determining the sizes of several potential reservoirs located in a system of one or more rivers. Separate algorithms are developed for sites on parallel streams and for sites on the same stream. In both cases the approach is to find the combination of reservoirs which can satisfy a given constant monthly demand at a minimum total construction cost. It is shown that both problems can be cast in the form of a dynamic programming problem. A more complex system is then a combination of reservoirs in parallel and in series. An extension is given if the monthly demand is not constant but each reservoir satisfies a constant fraction of the monthly demand.     

NONLINEAR PROGRAMMING IN RIVER BASIN MODELING1

ABSTRACT: This paper explores the use of nonlinear programming in river basin water quality modelling. Applications recently reported in the literature, along with the author's experience with nonlinear programming, are reviewed. Results obtained using nonlinear programming are compared with the results obtained by other researchers using linear and dynamic programming to solve river basin water quality optimization problems. These water quality models have objective functions with continuous first partial derivatives, several inequality and variable bound constraints, and are of the form: minizie Σ^j=n_j=1Y_j(X_j) subject to Σ^j=n_j=1a_ijX_jb_i, i=1,2, …, m c_jX_jd_j, j= 1,2, …, n The variable X_i is the maximum allowable ratio of the BOD (biochemical oxygen demand) of the effluent outflow to the BOD of the wastewater inflow for treatment plant j, in the range c_j to d_j. The a_ijd and b_i are constants in the DO (dissolved oxygen) and BOD constraints. The resuks show, given certain assumptions about the data, that nonlinear programming is a better solution method for these problems than is either linear programming or dynamic programming.     

Fuzzy goal programming for biodiesel production

ABSTRACT

The energy consumed around the world and especially in Morocco is dominated by oil products. The latter; whether in the global or the national context; are mainly due to diesel, whose climate impacts are well established, suggesting the search for a greener alternative. Despite its virtues, biodiesel is struggling to impose itself for purely economic reasons. Thus, in order to offer a sustainable solution, while keeping in mind the unpredictable fluctuations (price, demand …). This work proposes a generalization of fuzzy goal programming into fully fuzzy goal programming and a relative application, where the aim is to have a final product at a competitive price.     

GENETIC PROGRAMMING: A NEW PARADIGM IN RAINFALL RUNOFF MODELING1

ABSTRACT: Genetic Programming (GP) is a domain‐independent evolutionary programming technique that evolves computer programs to solve, or approximately solve, problems. To verify GP's capability, a simple example with known relation in the area of symbolic regression, is considered first. GP is then utilized as a flow forecasting tool. A catchment in Singapore with a drainage area of about 6 km² is considered in this study. Six storms of different intensities and durations are used to train GP and then verify the trained GP. Analysis of the GP induced rainfall and runoff relationship shows that the cause and effect relationship between rainfall and runoff is consistent with the hydrologic process. The result shows that the runoff prediction accuracy of symbolic regression based models, measured in terms of root mean square error and correlation coefficient, is reasonably high. Thus, GP induced rainfall runoff relationships can be a viable alternative to traditional rainfall runoff models.     

COMPUTATIONAL IMPROVEMENT FOR STOCHASTIC DYNAMIC PROGRAMMING MODELS OF URBAN WATER SUPPLY RESERVOIRS1

ABSTRACT: This paper describes two methods that are introduced to improve the computational effort of stochastic dynamic programming (SDP) as applicable to the operation of multiple urban water supply reservoir systems. The stochastic nature of streamflow is incorporated explicitly by considering it in the form of a multivariate probability distribution. The computationally efficient Gaussian Legendre quadrature method is employed to compute the conditional probabilities of streamflow, which accounts for the serial correlation of streamflow into each storage and the cross correlation between the streamflow into various storages. A realistic assumption of cross correlation of streamflow is introduced to eliminate the need to consider the streamflow combinations which are unlikely to occur in the SDP formulation. A “corridor” approach is devised to eliminate the need to consider the infeasible and/or inferior storage volume combinations in the preceding stage in computing the objective function in the recursive relation. These methods are verified in terms of computational efficiency and accuracy by using a hypothetical example of three interconnected urban water supply reservoirs. Therefore, it can be concluded that these methods allow SDP to be more attractive for deriving optimal operating rules for multiple urban water supply reservoir systems.