Comprehensive Risk Assessment for Natural Hazards - Planat
Comprehensive Risk Assessment for Natural Hazards - Planat
Comprehensive Risk Assessment for Natural Hazards - Planat
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84 Chapter 8 — Strategies <strong>for</strong> risk assessment — case studies<br />
projects on an average annual basis can be computed. These<br />
avoided damages constitute the primary benefit of the projects,<br />
and by subtracting the project cost (converted to an<br />
average annual basis) from the avoided damages the net<br />
economic benefit of the projects is obtained.<br />
The traditional approach to planning of flood-damagereduction<br />
projects is similar to the minimum life-cycle cost<br />
earthquake-design method with the constraint of achieving<br />
a specified level of protection. That is, the flood-damagereduction<br />
alternative that maximizes net economic benefits<br />
and provides the specified level of protection would be the<br />
recommended plan unless it was unacceptable with respect<br />
to the “additional considerations.”<br />
The risk-based analysis offers substantial advantages<br />
over traditional methods because it requires that the project<br />
resulting in the maximum net economic benefit be identified<br />
without regard to the level of protection provided.<br />
There<strong>for</strong>e, the vulnerability (from an economic viewpoint)<br />
of the flood-plain areas affected by the project is directly<br />
considered in the analysis, whereas environmental, social<br />
and other aspects of vulnerability are considered through<br />
the “additional considerations” in the decision-making<br />
process. In the example presented in the USACE manual on<br />
risk-based analysis (USACE, 1996), the project that resulted<br />
in the maximum net economic benefit provided a level of<br />
protection equivalent to once, on average, in 320 years.<br />
However, it is possible that in areas of low vulnerability, the<br />
project resulting in the maximum net-economic benefit<br />
could provide a level of protection less than once, on average,<br />
in 100 years. A more accurate level of protection is<br />
computed in the risk-based analysis by including uncertainties<br />
in the probability model of floods and the hydraulic<br />
trans<strong>for</strong>mation of discharge to stage rather than accepting<br />
the expected hydrological frequency as the level of protection.<br />
This more complete computation of the level of<br />
protection eliminates the need to apply additional safety<br />
factors in the project design and results in a more accurate<br />
computation of the damages avoided by the implementation<br />
of a proposed project.<br />
Monte Carlo simulation is applied in the risk-based<br />
analysis to integrate the discharge-frequency, stagedischarge<br />
and stage-damage relations and their respective<br />
uncertainties. These relations and their respective uncertainties<br />
are shown in Figure 8.4. The uncertainty in the<br />
discharge-frequency relation is determined by computing<br />
confidence limits as described by the Interagency Advisory<br />
Committee on Water Data (1982). For gauged locations, the<br />
uncertainty is determined directly from the discharge data.<br />
For ungauged locations, the probability distribution is fit to<br />
the estimated flood quantiles, and an estimated equivalent<br />
record length is used to compute the uncertainty, through<br />
the confidence-limits approach. The uncertainty in the<br />
stage-discharge relation is estimated using different<br />
approaches dependent on available data and methods used.<br />
These approaches include: direct use of corresponding stage<br />
data and streamflow measurements; calibration results <strong>for</strong><br />
hydraulic models if a sufficient number of high water marks<br />
are available; or Monte Carlo simulation considering the<br />
uncertainties in the component input variables (Manning’s<br />
n and cross-sectional geometry) <strong>for</strong> the hydraulic model<br />
Discharge (Q)<br />
Stage (S)<br />
Flood hazard<br />
Exceedance probability<br />
Uncertainty in stage<br />
Discharge (Q)<br />
Uncertainty in discharge<br />
Exceedance probability<br />
(e.g., USACE, 1986). The uncertainty in the stage-damage<br />
relation is determined by using Monte Carlo simulation to<br />
aggregate the uncertainties in components of the economic<br />
evaluation. At present, uncertainty distributions <strong>for</strong> structure<br />
elevation, structure value and contents value are<br />
considered in the analysis.<br />
The Monte Carlo simulation procedure <strong>for</strong> the riskbased<br />
analysis of flood-damage-reduction alternatives<br />
includes the following steps applied to both without-project<br />
and with-project conditions (USACE, 1996).<br />
(1) A value <strong>for</strong> the expected exceedance (or nonexceedance)<br />
probability is randomly selected from a<br />
uni<strong>for</strong>m distribution. This value is converted into a random<br />
value of flood discharge by inverting the expected<br />
flood-frequency relation.<br />
(2) A value of a standard normal variate is randomly selected,<br />
and it is used to compute a random value of error<br />
associated with the flood discharge obtained in step 1.<br />
This random error is added to the flood discharge<br />
obtained in step 1 to yield a flood-discharge value that<br />
includes a crude estimate of the effect of uncertainty<br />
resulting from the sampling error <strong>for</strong> the preselected<br />
probability model of floods. The standard deviation <strong>for</strong><br />
the standard normal variate is determined from the<br />
previously described confidence limits of the flood<br />
quantiles.<br />
(3) The flood discharge obtained in step 2 is converted to<br />
the expected flood stage using the expected stagedischarge<br />
relation.<br />
(4) A value of a standard normal variate is randomly selected,<br />
and it is used to compute a random value of error<br />
associated with the flood stage computed in step 3. This<br />
random error is added to the flood stage computed in<br />
Discharge (Q)<br />
Damage ($)<br />
Uncertainty in damage<br />
Stage (S)<br />
Figure 8.4 — Uncertainty in discharge, stage and damage as<br />
considered in the US Army Corps of Engineers risk-based<br />
approach to flood-damage reduction studies<br />
(after Tseng et al., 1993)