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Abstract: A seasonal multi-year model for management of water quantities and salinities in regional water supply systems (WSS) was developed and implemented. Water is taken from sources which include aquifers, reservoirs, and desalination plants, and conveyed through a distribution system to consumers who require quantities of water under salinity constraints. The year is partitioned into seasons, and the operation is subject to technological, administrative, and environmental constraints such as water levels and salinities in the aquifers, capacities of the pumping, distribution system, and the desalination plants, and the desalination plants maximum removal ratios. The objective is to operate the system at minimum total cost. The objective function and some of the constraints are nonlinear, leading to a nonlinear optimization problem. The nonlinear optimization problem is solved efficiently by adapting (1) a set of manipulations that reduce the problem size and (2) a novel finite difference scheme for calculating the derivatives required by the optimization solver, entitled the Time-Chained-Method (TCM). The model is demonstrated on a small illustrative example and on a real sized regional water supply system in Israel. [Copyright &y& Elsevier]

A computerized learning algorithm was developed for assessing the extent of biofouling formations on the inner surfaces of water supply pipelines. Four identical pipeline experimental systems with four different types of inlet waters were set up as part of a large cooperative project between academia and industry in Israel on biofouling modeling, prediction, and prevention in pipeline systems. Samples were taken periodically for hydraulic, chemical, and biological analyses. Biofilm sampling was done using Robbins devices, carrying stainless steel coupons. An MT-GA, a hybrid model combining model trees (MTs) and genetic algorithms (GAs) in which the sampled input data are selected by the proposed methodology, was developed. The method outcome is a set of empirical linear rules which form a model tree, iteratively optimized by a GA and verified using the dataset resulting from the empirical field studies. Good correlations were achieved between modeled and observed cell coverage area within the biofilm. Sensitivity analysis was conducted by testing the model's response to changes in: (1) the biofilm measure used as output (target) variable; (2) variability of GA parameters; and (3) input attributes. The proposed methodology provides a new tool for biofouling assessment in pipelines., (Copyright © 2011 Elsevier Ltd. All rights reserved.)