Model for floodplain management in urbanizing areas

A target land use pattern found using a dynamic programming model is shown to be a useful reference for comparing the success of floodplain management policies. At least in the test case, there is interdependence in the land use allocation for floodplain management--that is, a good solution includes some reduction of current land use in the floodplain and some provision of detention storage. For the test case, current floodplain management policies are not sufficient; some of the existing floodplain use should be removed. Although specific land use patterns are in part sensitive to potential error in land value data and to inaccuracy in the routing model, the general conclusion that some existing use must be removed is stable within the range of likely error. Trend surface analysis is shown to be a potentially useful way of generating bid price data for use in land use allocation models. Sensitivity analysis of the dynamic programming model with respect to routing of hydrographs is conducted through simulation based on expected distributions of error.U.S. Geological SurveyU.S. Department of the InteriorOpe

Optimal design of water distribution networks using fuzzy optimization

A new heuristic approach for the design of water distribution networks involving a robust fuzzy linear program optimization in which the capital costs of the network are minimized while maintaining the nodal heads at demand nodes within a satisfactory region as defined by the customers at those nodes is presented. Iterative interaction between the fuzzy linear program and a network solver is used to ensure hydraulic consistency. Level of service is modelled by the residual nodal head available at demand nodes with the subjective nature of customers' satisfaction with the nodal head being represented through fuzzy sets which reflect more realistically consumers' attitudes toward pressure variations in the supply of water. Non-probabilistic uncertainty in the demand is modelled by a trapezoidal possibility distribution function. The model is demonstrated by application to an example network. A new heuristic approach for the design of water distribution networks involving a robust fuzzy linear program optimization in which the capital costs of the network are minimized while maintaining the nodal heads at demand nodes within a satisfactory region as defined by the customers at those nodes is presented. Iterative interaction between the fuzzy linear program and a network solver is used to ensure hydraulic consistency. Level of service is modelled by the residual nodal head available at demand nodes with the subjective nature of customers' satisfaction with the nodal head being represented through fuzzy sets which reflect more realistically consumers' attitudes toward pressure variations in the supply of water. Non-probabilistic uncertainty in the demand is modelled by a trapezoidal possibility distribution function. The model is demonstrated by application to an example network

Reliability-based optimal design of water distribution networks

A new approach for reliability-based optimization of water distribution networks is presented. The approach is capable of recognizing the uncertainty in nodal demands and pipe capacity as well as the effects of mechanical failure of system components. A probabilistic hydraulic model is used in the model to account for uncertainty in nodal demands and pipe capacity. The primary innovation of the model is the use of a first-order reliability-method-based algorithm to compute approximate values of the capacity reliability of water distribution networks. Capacity reliability is defined as the probability that the nodal demand is met at or over the prescribed minimum pressure for a fixed network configuration under random nodal demands and random pipe roughnesses. The model also incorporates a strategy for identifying the critical nodes on which the reliability constraints are imposed in the cost minimizing step. The computational efficiency of the optimization is shown to be enhanced by deriving the first-order derivatives analytically using a sensitivity-analysis-based technique. The efficiency and capacity of the proposed algorithm are illustrated by application to two sample networks. A new approach for reliability-based optimization of water distribution networks is presented. The approach is capable of recognizing the uncertainty in nodal demands and pipe capacity as well as the effects of mechanical failure of system components. A probabilistic hydraulic model is used in the model to account for uncertainty in nodal demands and pipe capacity. The primary innovation of the model is the use of a first-order reliability-method-based algorithm to compute approximate values of the capacity reliability of water distribution networks. Capacity reliability is defined as the probability that the nodal demand is met at or over the prescribed minimum pressure for a fixed network configuration under random nodal demands and random pipe roughnesses. The model also incorporates a strategy for identifying the critical nodes on which the reliability constraints are imposed in the cost minimizing step. The computational efficiency of the optimization is shown to be enhanced by deriving the first-order derivatives analytically using a sensitivity-analysis-based technique. The efficiency and capacity of the proposed algorithm are illustrated by application to two sample networks

Assessing the capacity reliability of ageing water distribution systems

This paper presents two new efficient algorithms for estimating the capacity reliability of ageing water distribution systems recognising the uncertainties in nodal demands and the pipe capacity. Capacity reliability is defined as the probability that the nodal demand is met at or over the prescribed minimum pressure for a fixed network configuration. Uncertainties in the nodal demands and values of pipe roughness are modelled by a probabilistic approach. The impacts of these uncertainties on the hydraulic performance of water distribution systems are then assessed by probabilistic hydraulic models based on the mean value first order second moment (MVFOSM) method and the first order reliability method (FORM) respectively. The performances of the models are evaluated and compared by application to an example network. Results from this application indicate that both models provide reasonably accurate estimates of capacity reliability of a deteriorated distribution network in the cases that the uncertainty in the random variables is small. However, FORM performs much better in cases involving large variability in the nodal demands and pipe roughnesses