Duration (IFD) - Innovyze Insider Blog

New Intensity-FrequencyDuration (IFD) Design Rainfalls
Estimates
Janice Green
Bureau of Meteorology
17 April 2013
Current IFDs – AR&R87
Current IFDs – AR&R87
Current IFDs - AR&R87
•
Options for estimating IFDs
– Read the six master charts to obtain intensities for basic durations and
frequencies; read regional coefficient of skewness from master chart; read short
duration factors from appropriate curves; estimate intensities for LPIII
distribution for basic ARIs and durations using Diagram 2.2; estimate LPIII
intensities for other durations using Diagram 2.1
– Software developed to derive IFD relationships eg AusIFD
www.ens.gu.edu.au/eve/research/AusIfd/AusIfdVer2
– Engage HAS at Bureau to provide estimates @ $100
– Computerised Design IFD Rainfall System (CDIRS) on-line
www.bom.gov.au/hydro/has/ifd.shtml
Current IFDs – CDIRS On-line
Current IFDs – CDIRS On-line
Current IFDs – CDIRS On-line
Current IFDs – CDIRS On-line
Current IFDs
• Developed by Bureau of Meteorology nearly 30 years ago
• Used a database comprising information primarily from the Bureau’s
network of daily read and pluviograph stations
• Adopted statistical techniques considered appropriate at the time
• Focus of the IFDs was the design of structures on relatively large
rural catchments and therefore durations of less than five minutes
were not considered necessary.
Basic approach
Rainfall data
 Establishment of database
 Quality controlling of data
Series of
extreme values
Frequency
Analysis
Regionalisation
Gridding
 Annual Maximum Series
 Partial Duration Series
 Extraction of L-moments
 Choice of probability distribution
 Sub-daily and sub-hourly statistics
 Index rainfall approach
 Regions of Influence
 Explanatory variables
 Gridding technique
Dissemination
 Outputs
 Medium
AR&R87 IFDs – Adopted Approach
Aspect
ARR87
Data
BoM stations only
Record length
~ up to 1983; 7500 daily read > 30 years; 600 pluviographs > 6 years
Frequency analysis
Annual maximum series; method of moments; Log-Pearson Type III
Daily to sub-daily
Principal Component Analysis
Mapping
Subjective (meteorological analysis); ANUSPLIN used to translate hand
drawn contours into grid format (CDIRS)
Frequency
ARIs 1 year to 100 year
Duration
5 minute to 72 hour (3 day)
Dissemination
Maps; HAS; CDIRS on-line
Climate change
Stationary climate assumed; climatic trends negligible effect on IFDs
IFD2015 – Adopted Approach
Aspect
IFD2013
Data
Bureau stations plus stations from other data collecting agencies
Record length
up to 2011; 8074 daily read > 30 years (+2 >20 years); 2280
pluviographs > 8 years (754 Bureau; 1526 Regs)
Frequency analysis
Annual maximum series; L-moment; GEV
Daily to sub-daily
Bayesian Generalised Least Squares Regression
Mapping
ANUSPLIN
Frequency
1 EY to 1% AEP
Duration
1 minute to 168 hour (7 day)
Dissemination
New webpage on Bureau’s website
Climate change
Stationarity of long term stations explicitly assessed and no significant
trends identified; therefore using complete period of record
Data base
• Bureau of Meteorology Australian Data Archive for Meteorology
(ADAM )
– Contains 19711 daily read rainfall stations (both open & closed) for
period from 1800 to 2011
– Contain 1467 continuous stations – both pluviograph & TBRG
•
Water Act 2007 identified the Bureau’s new responsibilities including
•
Water Regulations 2008 provided ready access to rainfall data collected by
other organisations
•
In particular, data from dense continuous rainfall networks operated by
urban water utilities and councils:
– ~350 daily read rainfall stations
– ~2175 continuous rainfall stations
collecting and publishing water information
Spatial coverage of daily read
rainfall stations
Spatial coverage of continuous
rainfall stations
•
Data base
• Finalisation of data base
– Initially December 2010
Data base
• Finalisation of data base
– Initially December 2010
Data base
• Finalisation of data base
– Initially December 2010
– Updated to December 2011
Data base
• Finalisation of data base
– Initially December 2010
– Updated to December 2011
Data base
• Finalisation of data base
– Initially December 2010
– Updated to December 2011
– Updated to March 2012
– ?????
Quality Control
• Previous work had undertaken QCing on a largely manual basis
• Enormous amount of data that needed to be quality controlled
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–
–
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> 20 000 daily read stations - Bureau
> 1500 pluviograph stations – Bureau
~350 daily read rainfall stations – Water Regulations
~2175 continuous rainfall stations – Water Regulations
• Disparate amount and type of QCing undertaken by data providers
• Necessitated automating as much of QCing as possible
• However still required manual QCing using Bureau’s Quality
Monitoring System (QMS)
QCing daily read data
• Quality Controlling of daily read data:
– Infilling of missing data
– Disaggregation of flagged accumulated daily rainfall totals
– Detection of suspect data, identification and correction of:
• Unflagged accumulated totals
• Time shifts
– Identification of gross errors - data inconsistent with neighbouring
records but not either of the above two categories
– Manual correction gross errors identified as having a high probability of
being incorrect
QCing daily read data using QMS
QCing of continuous data
•
QCing of continuous rainfall data considerably more complicated:
– significantly more data due to shorter time step
– sparsity of continuous station network means fewer stations with which to
compare
– small rainfall depths extremely difficult to QC
•
Needed to reduce amount of data to be QC’d to a manageable amount
•
Developed approach QC’d the PDS
– 5 x number of years of record
•
Durations of:
– 5, 10, 15, 30 minutes
– 1, 2, 3, 6, 12 hours
– 1, 2, 3 days
•
Number of PDS values to be QC’d > 1,000,000
QCing continuous data
• Issues with Continuous Rainfall Data
– Time shifts of clock - DINES
– Missed pulses – TBRG
• QCing procedure compared values to:
– AWAP (Australian Water Availability Product) gridded daily rainfall data
– Co-located or nearby daily read stations
– AWS (Automatic Weather Stations)
– Synoptic stations
Trialling of frequency distributions
• Frequency analysis
– Previously adopted Log-Pearson Type III fitted by method of
moments
– Used 58 Bureau long-term continuous rainfall stations to trial a
range of distributions
• From each of the 58 continuous rainfall stations
extracted both the AMS and the PDS
Trialling of frequency distributions
•
AMS & PDS extracted for durations of :
– 6, 12, 18, and 30 minutes
– 1, 2, 3, 6, and 12 hours
•
Calculated L-moments and fit five distributions:
–
–
–
–
–
•
Generalised Logistic (GLO)
Generalised Extreme Value (GEV)
Generalised Normal (GNO)
Pearson Type III (PE3)
Generalised Pareto (GPA).
Assessed goodness of fit using Hosking and Wallis (1997) goodness of fit
measure ZDist
Trialling of frequency distributions
• AMS
– the GEV gave the most acceptable fit for all durations except 3
and 12 hours
– however, with the exception of the GPA, the other distributions
also showed acceptable fits
• PDS
– the GPA gave the most acceptable fit for all durations
Extraction of L-moments
• L-moments used to summarise statistical properties of AMS and PDS
– Index rainfall (mean)
– L-skewness
– L-CV
• L-moments expected to be more robust against large outliers in the
data, particularly for the higher order moments.
• To reduce uncertainty in the parameter estimates, minimum station
record lengths have been adopted
– 30 years for daily rainfall stations and
– 9 years for sub daily rainfall stations.
Estimation of sub-daily rainfalls
• Shift in focus to urban design on small catchments
necessitating the provision of IFD estimates for durations
as short as one minute
• Far fewer continuous rainfall stations than daily read
rainfall stations
Spatial coverage of daily read
rainfall stations
Spatial coverage of continuous
rainfall stations
•
Derivation of short duration IFDs
• Need a method to improve spatial coverage of sub-daily
data
• Most commonly done using information from daily
stations
– Statistics of sub-daily data are inferred from those of daily data
• Techniques adopted include:
– Factoring of the 24 hour IFDs
– Principal component analysis (PCA)
– Partial least squares regression (PLSR)
Derivation of short duration IFDs
• However, major weakness of the previously adopted
approaches is their inability to account for:
– Variation in record lengths from site to site
– Inter-station correlation
• An approach that avoids these problems is Bayesian
Generalised Least Squares Regression (BGLSR)
Approach to be adopted
•
Statistics to be derived (predictands) are:
– Index rainfall (mean)
– L-skewness
– L-CV
•
Predictors to be used are:
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–
–
–
–
–
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Location (latitude & longitude)
Elevation
Slope
Aspect
Distance from coast
Mean annual rainfall
Index rainfall, L-skewness & L-CV at 24, 48 & 72 hours
Regionalisation
• Regionalisation recognises for stations with short records
– considerable uncertainty when estimating the parameters of
probability distributions and
– short records can bias estimates of rainfall statistics
• Overcome by combining information from multiple
rainfall stations
– more accurate estimates of the probability distribution
parameters can be made
Regionalisation
• Substitute space for time
REGIONALISATION
Regionalisation
• Index rainfall approach adopted to do this (Hosking & Wallis)
• Station point estimates have been regionalised using a Region of
Influence Approach (ROI).
• Trialled various approaches => ROIs defined as circle which is
expanded until it includes 500 station years of record
• Circular ROIs defined with distance defined in three dimensions
– Latitude
– Longitude
– Elevation
Region of influence
Region of influence
Region of influence
Gridding
• Regionalisation gave estimates of GEV parameters at all station
locations
– Combined with the mean of the AMS (index) at that site to estimate
rainfall quantiles for any required exceedance probability.
• However IFD estimates required across Australia, not just at station
locations.
• Results of the analyses needed to be extended in some way to
ungauged locations.
Gridding
•
Translation from point to gridded rainfall estimates carried out with thin
plate smoothing splines implemented using ANUSPLIN.
•
ANUSPLIN (Hutchinson 2007) was chosen to grid the GEV parameters so
that IFD estimates are available for any point in Australia.
•
GEV parameters are being gridded in ANUSPLIN, as:
– earlier testing showed little difference in quantile estimates if point parameter or
point rainfall depths gridded.
– Gridding rainfall parameters gives more flexibility in the choice of exceedance
probabilities that can be extracted and
– requires fewer grids to be processed in ANUSPLIN.
•
Appropriate level of smoothing chosen through generalised cross validation
by minimising the predictive error of the fitted surface
Interpolation – point to grid
SHAPE GRID
SCALE GRID
MEAN GRID
Gridding
Index
Alpha
Kappa
Interpolation – point to grid
SHAPE GRID
SCALE GRID
MEAN GRID
Y = 1 in 100 AEP
Y = 1 in 50 AEP
Y = 1 in 20 AEP
Y = 1 in 10 AEP
Y = 1 in 5AEP
Y = 1 in 2 AEP
ANUSPLIN Output Example
Outputs
• Revised IFDs will be provided as depths in millimetres
(not intensities)
• Revised IFDs will be provided for standard durations
of:
– 1, 2, 3, 4, 5, 10, 15, 30 minutes
– 1, 2, 3, 6, 12 hours
– 1, 2, 3, 4, 5, 6, 7 days
Outputs
• Revised IFDs will be provided for standard EY and
AEPs of:
– 1EY (1 Exceedance Per Year)
– 50%, 20%, 10%, 5%, 2%, 1% AEP
– New AR&R probability terminology
Revised IFDs
• Revised IFDs will be disseminated
– In electronic form
– Via new web page accessed from Bureau of Meteorology
website
• Revised IFDs will be released 2 Phases
Phase 1
• Phase 1
– Revised IFDs for a point
– Functionality of Phase 1 web pages => same as current CDIRS
web page
• Except raw data from 6 master charts, skew & short duration
maps
– CDIRS and IFD 2013 run in parallel for ~ 18 months
Phase 1 IFD Web page
Phase 1 IFD Web page
Phase 2
• Phase 2 - Enhancements
– Multiple locations
– Dynamic map
– Areal reduction factors
– Temporal patterns
– Areal IFDs
Phase 2
• Phase 2 - Enhancements
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Seasonal IFDs
Sub-annual IFDs eg 2EY, 12 EY
Uncertainty estimates
Advice provided for IFDs < 1 minute and > 7 days
Rainfall frequency curve to 0.05% AEP (incorporating
CRCFORGE estimates)
– Climate change adjustments to IFDs
More information….
Leave your business card
Janice Green
(02) 6232 3558
[email protected]
or
[email protected]