Download presentation

Presentation is loading. Please wait.

Published byWyatt Pollock Modified over 3 years ago

1
Applied Hydrology RSLAB-NTU Lab for Remote Sensing Hydrology and Spatial Modeling 1 Flood Risk Analysis – the USACE Approach Professor Ke-Sheng Cheng Dept. of Bioenvironmental Systems Engineering National Taiwan University

2
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 2 The Levee Certification Program Many flood damage reduction projects involve the construction of levees. The USACE s (US Army Corps of Engineers) historical approach to coping with hydrological and hydraulic uncertainties of large floods was based on a best estimate of the levee height required to withstand a given flood, which was then augmented by a standard increment of levee height called freeboard.

3
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 3 The best estimate has traditionally been based on the expected height of a design flood (for example, the100-year flood). A standard freeboard of 3 feet was then added above the expected height. With the Corps adoption of risk analysis techniques in early 1990s, the freeboard standard for levee certification was abandoned in favor of the new risk analysis standard.

4
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 4 The new USACE approach was reviewed by the Committee on Risk-Based Analysis for Flood Damage Reduction of the National Research Council which is organized by the National Academy of Sciences and the National Academy of Engineers.

5
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 5 The committee recommends that the federal levee certification program focus not upon some level of assurance of passing the 100- year flood, but rather upon annual exceedance probability – the probability that an area protected by a levee system will be flooded by any potential flood. How sure can we be that if we protect ourselves from a flow of 100- year return period, we will actually be protecting ourselves from all flows that occur less frequently, on average, than once in 100 years?

6
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 6 USACE Risk Analysis Techniques The Corpss objective in flood damage reduction studies is to determine the expected annual damage (EAD) along a section of river caused by possible floods, and to compare changes in those damages as a function of project alternatives. For a flood of annual probability p (p=1/T, T: return period), a corresponding value of flood damage D(p) can be estimated.

7
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 7 The EAD is the average value of such damages taken over floods of all different annual exceedance probabilities and over a long period of years. The current Corps method divides the calculation of EAD into three steps: Determining flood frequencies, which describe the probability of floods equal or greater than some discharge Q occurring within a given period of time (usually 1-year).

8
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 8 Determining stage-discharge relations, which describe how high the flow of water in a reach of river (the stage) might be for a given discharge. Determining damage-stage relations, which describe the amount of damage that might occur, given a certain height of flow.

9
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 9 Basis of the Corpss EAD Computation Annual exceedance probabilities of p = 0.5, 0.2, 0.1, 0.04, 0.02, 0.01, 0.004, and are used for EAD calculation.

10
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 10 There are uncertainties in the probability of exceedance distribution of annual peak flows the discharge-stage function the stage-damage function Stochastic simulation techniques are used to generate a single realization of each of the three relationships.

11
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 11 Uncertainty in annual peak flow

12
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 12 Peak flow records are commonly used to estimate the chance of a flood of a given or greater magnitude. But such estimates are uncertain due to Limited number of observations of past peak flows The changing and varying character of the drainage basin that influences the peak flow resulting from a specific rainfall.

13
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 13 Monte Carlo simulation is used to generate new realizations of each of the three curves using various exceedance probabilities. The Monte Carlo simulation is repeated for a few thousand cycles of generating realizations and computing EAD.

14
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 14 Assessment of Engineering Performance The target stage is defined as the water surface elevation in a reach at which significant economic damage occurs. The 1% chance of flooding damage is found from the flood-frequency curve. A fraction of this damage (usually 10%) is taken and used to determine the corresponding stage from the damage-stage curve, which then becomes the target stage for the reach.

15
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 15 Engineering performance can be measured by conditional probabilities dependent on the occurrence of a flood of a given severity (e.g., the 100-year flood) or dependent on the annual probabilities integrated over all the floods that could occur within a given year.

16
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 16 Corpss method for measuring engineering performance Annual exceedance probability – the probability that the target stage will be exceeded in any year considering all potential floods. Conditional nonexceedance probability – the probability that the target stage will not be exceeded given a specific flood severity.

17
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 17 In each cycle of the above Monte Carlo procedure, a new realization of the flood- frequency curve and the stage-discharge curve is generated. The flood-frequency is defined at discrete intervals of annual flood probability (p = 0.5, 0.2, 0.1, 0.04, 0.02, 0.01, 0.004, and 0.002).

18
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 18 Distribution of the target stage nonexceedance probability Each cycle of the Monte Carlo procedure yields an estimate of the annual exceedance probability for the target stage. N cycles of the Monte Carlo procedure are conducted to yield a distribution of the annual exceedance probability for the target stage. The chance that the target stage will be exceeded at least one in n years is computed as, where p e is the expected annual exceedance probability.

19
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 19 Conditional nonexceedance probabilities at the target stage For each value of p*, there corresponds an H*, determined in a similar manner. After N Monte Carlo cycles are completed, a set of N values of H* exists, of which a subset, n, have stages not exceeding the target stage. The conditional nonexceedance probability of the target stage is given by n/N.

20
Lab for Remote Sensing Hydrology and Spatial Modeling RSLAB-NTU 20

Similar presentations

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google