Environmental Engineering Reference
In-Depth Information
able to prioritize the need for further data collec-
tion or engineering investigations on a common
basis alongside structural measures. Structured
sensitivity analysis (Gouldby et al. 2010) can help
highlight critical epistemic uncertainties (such as
within toe level, crest level, and asset condition
as well as the modelling methods; Fig. 15.3).
[Note: Model structure and local anomalies (re-
flecting the heterogeneity of the soil conditions for
example) are not easily incorporated into such an
analysis and continue to demand significant ex-
pert input.]
.
The ability progressively to refine the analysis
detail - attributing risk to an asset, and an asso-
ciated understanding of the critical contributors to
the uncertainty in that estimate, enables the de-
cision-maker to target further analysis or data
collection as appropriate for the decision in hand.
Although a tiered analysis is a well-recognized
concept (e.g. DETR 2000), until recently it has
been very difficult to achieve a hierarchical pro-
cess whereby data and models evolve (rather than
change) from one tier to the next (Sayers and
Meadowcroft 2005).
.
Support to develop optimal investment strate-
gies - asset managers face difficult choices: (i)
where to act? (ii) when to act, now or later? and
(iii) how to act, collect more data, undertake more
analysis or intervene? Increasingly it is not possi-
ble, or acceptable, to answer these questions in-
tuitively. The utility of formal optimization
methods, and their applicability and practicality
for use in flood risk management, is now being
explored and trialled with considerable promise
(McGahey and Sayers 2008; Philips. 2006; Wood-
ward et al. 2010).
Asset Management Tools and Techniques:
Key Features
Good asset management decision aids share a
number of good practice principles (Table 15.1).
The translation of these good practice principles
into practical tools (which provide the richness of
evidence described in earlier sections) is receiving
considerable attentionworldwide - e.g. Infrastruc-
ture Management Theme of the Flood Risk Man-
agement Research Consortium (FRMRC), the
Environment Agency R&D programme and the
US Army Corps of Engineers (USACE) research
agenda. Typically these tools have a number of
common features, as shown in Figure 15.4 and
discussed below.
0.8
Return Period of storm (years) - 20
Return Period of storm (years) - 80
Return Period of storm (years) - 200
Return Period of storm (years) - 1000
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Breach
Probability
Breach
Width
Multiplier
Crest Level
Defence
Ground Level Hydrographic
Multiplier
Load
Weir
State
Constant
Name of the input variable to Stage 1of the analysis (defence inflow volume)
Fig. 15.3
Relative importance of the uncertainties within asset descriptors and model parameters to the uncertainty
within the risk attributed to a specific asset.
