| Popis: |
Risk-informed decision analyses for dam safety require the development of flood frequency curves to estimate the probability of hydrologic loading conditions from common to very rare floods. A stochastic approach for estimating flood frequency curves with uncertainty bounds is presented in this chapter. Stochastic flood simulation approaches treat hydrometeorological inputs and watershed model parameters as variables instead of fixed values, considering the fact that a flood could be caused by an infinite number of different combinations of inputs. Considering physical complexity and the number of variables involved in the process of flood simulation, it is practically impossible to fully quantify uncertainties associated with flood quantile estimates. Uncertainties associated with observed values of various meteorological inputs (rainfall, temperature, freezing level, snowpack areal extent, etc.) could be reduced by combining existing ground observation with remote sensing data from radar, radiosonde, and satellite observations. The goal is to derive a mean–frequency curve and uncertainty bounds for the various flood characteristics in a manner that reasonably captures the current understanding of the hydrologic behavior of the watershed as well as the effect of uncertainties in estimating the flood frequency characteristics. It is therefore necessary to use a parsimonious approach in the selection of inputs and parameters to be included in the uncertainty analysis. A two-step approach to the development of uncertainty bounds is presented, where Step 1 involves global sensitivity analyses to determine which inputs and model parameters have the greatest effect on the magnitude of the flood characteristics of interest and Step 2 involves performing the uncertainty analysis on the inputs/parameters identified in Step 1. |
