WSPC07148 - Laserfiche WebLink

Home Browse Search

, 'l' , distribution systems for single events or continuous simulation (Rossman 1994). This Windows-based system is easy to use and has excellent graphics. similar integrated systems thinking prevailed in other areas of urban infrastructure, especially transportation and land use planning. Large models were developed and tested in numerous cities. However, Lee (1973) wrote an influential paper titled "Requiem for Large-Scale Models" which was highly critical of the potential value of such models. Few urban models were developed after the early 1970's but we are now witnessing a renaissance in the development and use of these models. A recent symposium discussed the change in attitudes since Lee's pessimistic 1973 paper appeared. Wegener (1994) summarizes the state of the art: "Twenty years after Lee's Requiem for Large-Scale Models', the urban modeling field is again full of life. There exist a dozen or so operational urban models of varying degrees of comprehensiveness and sophistication, which have been and are being applied to real-life metropolitan regions for purposes of research and/or policy analysis." The resurgence of interest in urban planning models in the 1990's is partially due to the renewed recognition of the need to link transportation- land use models to urban environmental systems models. 2.3 Risk Management Paradigm 2.3.1 Risk Analysis Framework Risk and reliability are fundamental to engineering analysis. Engineers combine scientific knowledge and associated theory to estimate what should work, with professional experience which tells what bas worked. Engineering planning, design, construction, and operating policies are based on formal codification of this scientific knowledge and experience into accepted prac- tice. Until relatively recently, engineers relied on safety factors to account for the uncertainty in estimating how the system would perform under a single IIworst case" design scenario. Mays and Tung (1992) present a sum- mary of risk analysis applications in water resources. Another major source of information on the use of risk analysis in water resources are the pro- ceedings of a series of conferences on this subject, e.g. Haimes and Stakhiv, Ed. (1989). Uncertainty and risk includes non-technological factors as well as tech- nological factors. Admittedly, it is more complicated to take a prObabilis- tic approach to design. Like other aspects of design, the engineer must decide whether the extra effort is justifiable. In order to quantify the reliability of a system, it is essential to estimate the variability in system performance. This can be done using continuous simulation, Monte Carlo methods, or direct analytical solution of the stochastic differential equations. With contemporary computing capabilities, it is now possible to do these more complex calculations, e.g., using the @Risk add-in for spread- sheets (Palisade Corp. 1994). Within the water resources field, the U.S. Army Corps of Engineers has taken the lead in using these approaches for doing risk analysis of their projects (Greeley-Polhemus Group 1992). U.S. EPA has adopted risk reduction as a major organizing principle (Finkel and Golding, Ed. 1994). Recent renewed interest in both benefit-cost analysis (U.S. Advisory Commission on Intergovernmental Relations 1993) and better integration of environmental values (Floodplain Management Review Committee 1994) have generated additional enthusiasm for pursuing these topics. The underlying philosophy of this research is that probabilistic ap- 5