Flood Risk Assessment: Flood Frequency Analysis Flashcards

1
Q

What are the three main learning goals of flood frequency analysis?

A

Understand its purpose, develop a cumulative distribution function, relate CDF to return period.

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2
Q

What is a flood frequency curve?

A

A plot relating peak discharge to a measure of frequency.

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3
Q

What are the two key questions flood frequency estimation answers?

A
  1. How rare was that flood?
  2. How big a flood should infrastructure be designed for?
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4
Q

POT → __
AM (Annual Maxima) → __

A
  • Values over a threshold, more data
  • One peak per year, simpler
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5
Q

True/False
Annual maxima series includes all floods per year.

A

False (only the largest)

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6
Q

What is the hydrological year start month in the UK?

A

October

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7
Q

If record < 14 years and POT = AM length, use ____ to estimate Q.

A

POT

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8
Q

True/False
Annual maxima should be used if you have long records.

A

True

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9
Q

What are the two rules for independent POT events?

A

3× average rise time between peaks and inter-peak minimum < ⅔ first peak

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10
Q

If average rise time is 15 hrs, peaks must be ≥ __ hrs apart to be independent.

A

45 hrs

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11
Q

Constructing the Flood Frequency Curve (n large)
Formula :
P(q > qd) ≈

A

1 − m/n
Where: m = cumulative frequency, n = total samples

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12
Q

CDF is obtained by dividing cumulative frequency by __.

A

sample size (n)

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13
Q

Formula
Return period: T =

A

1 / P(q > qd)

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14
Q

What is the probability a 10-year flood does not occur in 1 year?

A

0.9 (1 − 1/10)

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15
Q

P(no flood in N years) =

A

(1 − 1/T)^N

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16
Q

P(flood at least once) =

A

1 − (1 − 1/T)^N

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17
Q

Formula
P(x floods in n years) =

A

nCx · p^x · (1 - p)^(n - x)
Where p = P(q > qd)

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18
Q

For POT sampling:
T = _____

A

(n / t) × 1 / (1 − F(qd))
Where: n = years, t = POT samples

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19
Q

If F(qd) = 0.9, t = 40, n = 20, what’s the return period?

A

5 years

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20
Q

What problems arise with small n?

A

Flat sections between points, P(q > qmax) = 0

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21
Q

Plotting Position Formulas
Formula
Weibull:

A

Pm(q ≤ qm) = m / (N + 1)

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22
Q

Formula
Gringorten:

A

Pm(q ≤ qm) = (m − 0.44) / (N + 0.12)

23
Q

Why not use P = m/N directly?

A

Leads to T = ∞ for largest value → physically meaningless

24
Q

True/False
Plotting positions give a continuous probability curve.

25
Q

What is a limitation of plotting positions?

A

Cannot extrapolate beyond observed max value

26
Q

What distribution is fitted for flood frequency extrapolation?

A

The Gumbel distribution (Extreme Value Type I)

27
Q

To estimate floods with return periods longer than your record, you must ______ data.

A

extrapolate

28
Q

What are possible distributions for extrapolation?

A

Log-normal, Beta, Gamma

29
Q

What distribution is typically used for extreme floods?

30
Q

Gumbel Distribution Basics
Formula
CDF:

A

F(qₐ) = exp( -exp( (a - qₐ) / b ) )

31
Q

Transformation
Gumbel variate:

A

z = -ln( -ln[ F(qₐ) ] ) ⇒ qₐ = bz + a

32
Q

What is the Gumbel variate z used for?

A

It linearises the distribution for regression

33
Q

List the 4 Gumbel parameter estimation methods.

A

Linear regression, Moment matching, L-moment matching, Maximum likelihood

34
Q

True/False
Hydrologists typically prefer maximum likelihood methods.

A

False (they prefer L-moments)

35
Q

What plotting position formula is used to estimate F(qd)?

A

Gringorten formula

36
Q

Formula
Sample mean:

A

m = (1 / N) × Σ qₐ

37
Q

Formula
Sample variance:

A

s² = (1 / (N - 1)) × Σ (qₐ - m)²

38
Q

Gumbel Moment Equations

A

b = (√6 / π) × s
a = m - 0.5772 × b

39
Q

Why is the L-moment method more robust?

A

It reduces sensitivity to outliers by avoiding squaring deviations.

40
Q

True/False
Outliers can significantly bias Gumbel parameters.

41
Q

List 3 checks to ensure data quality before fitting a distribution.

A
  • Inspect time series for errors
  • Remove serial dependence
  • Plot fitted CDF and remove outliers
42
Q

What two methods should be used to estimate Gumbel parameters>

A

Method of moments and L-moments

43
Q

What two approaches help when flow data is scarce?

A
  1. Use regional flood frequency analysis
  2. Generate synthetic flow using hydrological models
44
Q

L-Moment Matching
Formula Recall

A

b = L₂ / ln(2)
a = L₁ − 0.5772 × b

45
Q

Regional Flood Frequency Analysis
Formula

A

0.0213 × AREA^0.94 × STMFRQ^0.27 × S1085^0.16 × SOIL^1.23 × RSMD^1.03 × (1 + LAKE)^-0.85

46
Q

Regional Flood Frequency Analysis
RSMD →
S1085 →
LAKE →

A
  • wetness index
  • channel slope
  • % of catchment routed through lake/reservoir
47
Q

What is the “index flood” in regional analysis?

A

The median or mean peak flow, used to scale the growth curve.

48
Q

The Flood Estimation
Formula

A

Q_Med = 3.4451 × AREA^0.3062 × SAAR^0.1536 × FARL^0.0460 × BFIHOST^0.8510

49
Q

SAAR →
FARL →
BFIHOST →

A
  • average annual rainfall
  • fraction of area through lakes/reservoirs
  • baseflow index
50
Q

Rainfall frequency is summarised using ______ curves.

A

Depth-Duration-Frequency (DDF)

51
Q

What two factors define a rainfall event’s rarity?

A

Depth and duration

52
Q

What approach is used when no reliable flow data exist?

A

Use of historical maximum flood or regional/global datasets

53
Q

Why might L-moment estimates be preferred?

A

More robust to outliers and better suited for skewed data