FlomQ: Improving flood estimation
methods for dam safety in Norway
Deborah Lawrence (NVE)
EnergiForsk HUVA dagen 07.dec.2017
With contributions from Thordis Thorarinsdottir (Norsk Regnesentral),
Emmanuel Paquet (EDF), Thomas Skaugen (NVE)
Norwegian Water Resources and Energy Directorate
Flood estimates required for dam
safety in Norway
■ For design flood: Q1000 or Q500
■ For safety check flood: QPMF, 1.5*Q1000 or 1.5*Q500
■ Both statistical FFA and simple rainfall-runoff models used
■ Analyses must be repeated every 15(20) years
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Question from dam owners: How can we
reduce the ‘uncertainty’ of these estimates?
Our proposal:
* Develop more robust methods
* Quantify uncertainty as feasible
* Keep on measuring!
Norwegian Water Resources and Energy Directorate
FlomQ: ‘Veier til bedre
flomestimering i Norge’
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11.12.2017
WP1 - Modelling of extreme P (e.g. PMP) using an
atmospheric model (AROME): MET, UiO (PhD project)
WP2 - 3-D CFD and physical modelling of discharge rating
curves: NTNU (PhD project)
WP3 - Semi-continuous probabilistic P-Q modelling for
design floods: NVE
WP4 - Regional flood frequency analysis using a
Bayesian statistical approach: NR and NVE
Norwegian Research Council (NFR) – ENERGIX Innovation project
Project owner: EnergiNorge; Project leader: Norsk Regnesentral (NR)
Norwegian Water Resources and Energy Directorate
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11.12.2017
Stochastic ‘semi-continuous’
simulation - SCHADEX
(Paquet et al., J. Hydrol., 2013)
Previously tested for Norwegian catchments
(Lawrence, et al. 2014, NHESS)
Event-based deterministic
model - PQRUT
XX-yr. P (MET)
Snowmelt
Estimate of ‘XX-yr.’ Q
H ≤ T: q
= K2*H
H ≤ T: q
= K2*H
Hours
P o
r S
no
wm
elt (
mm
/h)
H > T: q = K1*(H-T) + K2*T
H ≤ T: q = K2*H
P (mm)
H
(mm)
T(mm)
Norwegian Water Resources and Energy Directorate
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MEWP (Multi-Exponential Weather Pattern-based)
probabilistic model sampled by weather type and season (Garavaglia, et al., HESS 2011)
Reliability and robustness of MEWP approach tested for Norway
Exponential (EXP) distribution more robust than GPD
Reliability is similar for EXP and GPD
Reliability is improved with use of weather pattern subsampling
Fleig and Gailhard, 2012
Norwegian Water Resources and Energy Directorate
DDD hydrological model
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(Skaugen and Onof, 2014, Hyd Proc.)
Distributions of distances (DD) to and within
the channel network determine runoff
dynamics
Accounting of subsurface saturation state at
four levels + surface
Celerities of water movement in slope
determined by saturation level
DD + celerities give travel times and UHs
DDD-PUB(Skaugen, et al., 2015)
6(5) DDD parameters
estimated by regression
Other ‘calibrated’
parameters set to mean
or standard values
Norwegian Water Resources and Energy Directorate
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11.12.2017
Example: Mevatnet (109 km2)
SCHADEX – DDD
U = -Log(-Log(F))
Q24h (
m3/s
)
T =
10
T =
100
T =
1000
125
SCHADEX – MORDOR
with uncertainty
T =
100
U = -Log(-Log(F))
Q24h (
m3/s
)
T =
1000
T =
10
131Bootstrapping used
to quantify uncertainty
from hydro.model
Norwegian Water Resources and Energy Directorate
Conditions producing a 1000-yr. flood
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Norwegian Water Resources and Energy Directorate
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11.12.2017
SCHADEX – DDD
(calibrated model)
SCHADEX – DDD
(PUB model)
Reinsnosvatn (120 km2) – Use of DDD-PUB model
U = -Log(-Log(F)) U = -Log(-Log(F))
Q24h (
m3/s
)
Q24h (
m3/s
)
T =
10
T =
10
T =
100
T =
100
T =
1000
T =
1000
107110
Norwegian Water Resources and Energy Directorate
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11.12.2017
SCHADEX – DDD
(calibrated model)
SCHADEX – DDD
(PUB model)
Fustvatn (526 km2) – Use of DDD-PUB model
U = -Log(-Log(F)) U = -Log(-Log(F))
Q24h (
m3/s
)
Q24h (
m3/s
)
T =
10
T =
10
T =
100
T =
100
T =
1000
T =
1000
389 520
Norwegian Water Resources and Energy Directorate
Comparison of stochastic simulation
models
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SimScore = 1 - [abs(Umod i – Uobs i)(Uobs i – Uobs i-1)]
SimScore = 0.87
Mevatnet – 148.2
MORDOR
(for 28 test catchments)
U = -Log(-Log(F))
Norwegian Water Resources and Energy Directorate
Regional flood frequency analysis (Saelthun et al., 1997)
Regional formulas used for estimating average annual
flood QM
Inndeling i flomregioner, årsflommer (K1 og K2), vårflommer (a) og høstflommer (b)
Norwegian Water Resources and Energy Directorate
Regional flood frequency analysis (Saelthun et al., 1997)
Regional ‘growth’ curves used to estimate ratio QT/QM
Norwegian Water Resources and Energy Directorate
New regional flood frequency analysis (2017)
Estimate QT for all T simultaneously
Bayesian inference including uncertainty estimate
GEV distribution with each parameter depending on up to
12 catchment characteristics
Location Scale Shape
Norwegian Water Resources and Energy Directorate
New regional flood frequency analysis (2017) 33 catchment properties and 62 monthly meteorological variables were
considered
Stepwise regression used to find model with the lowest AIC
Selected covariates with posterier inclusion probabilities:
Location Scale Shape
Longitude 53 99 6
Latitude 84 100 6
Effective lake percentage 98 100 2
Precipitation in August 100 100 5
Precipitation in April 42 75 5
Catchment area/Catchment length 13 95 11
% Rainfall floods in annual max. series 3 22 58
Catchment gradient 45 12 2
% ‘Snaufjell’ (Sparse veg. above treeline) 22 8 2
Annual runoff for standard reference period 6 11 9
Catchment area 2 5 12
Snowmelting in March 8 16 4
Norwegian Water Resources and Energy Directorate
New regional flood model - Example
Regional FFA (1997)
Regional FFA (2017)Local FFA
10–90% interval
Reg. FFA (2017)
Return period (years)
Retu
rn level (l/s
/km
2)
Norwegian Water Resources and Energy Directorate
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Comparison of old and new regional FFA models
Old model (1997)
New model (2017)
Local GEV model
Norwegian Water Resources and Energy Directorate
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Comparison of current (upper) and FlomQ (lower) methods for ungauged sites
New Regional FFA
New Reg 80% interval
SCHADEX-DDD-PUB
Old Regional FFA
PQRUT_1983
Østlandet Telemark Sørlandet Vestlandet NordlandTRL
Norwegian Water Resources and Energy Directorate
q1000 (mm/d) – Rainfall-runoff simulation
q1
000 (
mm
/d)
–R
egio
nal sta
tistical F
FA
‘Old’ methods
FlomQ methods
Summary comparison of old and new
methods (for ungauged catchments)
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Norwegian Water Resources and Energy Directorate
FLOMQ - Further work■ Summary report with recommendations
■ Final conference 2018 (Week 22 – last week in May)
■ Implementation of new statistical FFA methods in ‘NEVINA’
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http://nevina.nve.no/
Norwegian Water Resources and Energy Directorate
Industrial partners
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