Flood
Forecasting
|
| in
a deltaic region
such as Bangladesh, is a difficult problem. A large amount of data is required
in order to initialize the
hyrdological models. |
Three
factors guided
the development of the CFAB flood forecasting schemes:
• Hydrological data required to run models is difficult to obtain
and much of it is sensitive and retained by different nations.
• State-of-the-art hydrological models require a substantial
investment in technology and man power.
• Reliable and timely forecast are needed now.
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for
example,
rainfall data over the entire catchment regions of the Ganges and Brahmaputra
is required in addition to river flow data, soil and crop
information and the amount of water that is retained within each catchment
by agriculture and water resource use.
Figure: Daily Ganges and Brahmaputra discharge at the boundaries of
Bangladesh. The discharge is the primary predictand of CFAB. |
 |
Based on these factors,
the generation of CFAB forecasts has got underway.
|
• The basic variables forecast are the discharges of
the Brahmaputra and the Ganges into Bangladesh.
• CFAB takes advantage of
the short-term empirical forecast developed by the Flood Forecast and Warning
Center (FWMC).
• The CFABdepends on data from satellites from NOAA National Center
for Environmental Protection (NOAA/NCEP) and model output from the European
Center for Medium Range Weather Forecasts (ECMWF).
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• Critical data sets are the discharge data at the boundaries
of Bangladesh and the sea-level variability in the Bay of Bengal.
• Forecasts are made on a range of times scales. • Models are as simple as possible and easily adaptable to the
technology currently available in Bangladesh.
• Models areadaptable for future improvement as science evolves.
• Documentation will accompany the transfer of
the forecast models to Bangladesh. |
| Short
range (1-10 days): |
| The basic aim is to generate discharge forecasts at the boundaries of
Bangladesh which will be coupled to the FFWC empirical flood forecasts
of the intra-Bangladesh region. This combined scheme provides: |
- up to 12 days forecasts
- early decisions for flood mitigation
- early decisions for disaster management
|
| These forecasts will benefit the agricultural sector. The farming community
will be able to act or react to minimize loss and optimize gain, especially
at planting and harvest times. |
| We have three forecasting techniques (A, B and C) devised for the short
range forecasts.Method A is more complicated and has the capacity to enable
risk management. Method B is a subset of Method A i.e. less complex but
is readily transportable for near-time use in Bangladesh. |
|
Method A
:- This method uses the full forecasting products
generated by The method uses the full forecasting products generated by
NOAA/NCEP and ECMWF. Precipitation forecasts are integrated over each
basin catchment. The ECMWF model uses ensemble techniques. Therefore,
a probabilistic forecast of integrated rainfall is calculated. A total
of 51 forecasts are integrated every 12 hours.
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Method B
:- This method uses a subsection of the ECMWF forecasts
and a linear regression technique to generate the discharge forecast. The
ensemble mean of the ECWMF forecasts is used to train a linear regression
equation. Once the coefficients of the regression are calculated, the ensemble
mean is extended for the 6-day period.
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Method C
:- This method is a more complex version of
Method B.It uses an increasing number of linear regressions relating to
ensemble members.
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Advantages and disadvantages
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- possible to calculate the probability of various discharge intensities
- requires considerable computing power
- considerable technical training
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- relatively accurate forecasts
- only one time series is necessary
- inability to calculate probabilities
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- probabilistic forecasts are possible
- increase in computation time
- increase in amount of data transfer
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Recommendation and Requirements
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1) use Method B initially to gain experience, and to test
the utility of the forecasts.
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2) test and compare the discharge forecasts produced by these methods
with those from the existing FFWC empirical models.
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3) adopt either Method C or Method A
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Medium range (20-25 days):
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| The forecast with maximum applicability to agriculture planning
and water management is a forecast that is on the time scale of three to
four weeks. This is referred to as the intraseasonal time scale. During a
monsoon season, the precipitation goes through a series of low-frequency
periods of wet and dry periods that are far greater in amplitude than the
interannual variability of the monsoon. These medium range (or intraseasonal)
forecasts can also provide sufficient forewarning so that resources can
be marshaled for the
mitigation
of a
disaster . |
| With field experiments and research investigations we have
increased our appreciation and understanding of the intraseasonal variability
of the monsoon. The CFAB research group has developed a new empirical method
that provides relatively accurate forecasts of the week-to-week variability
of the
monsoon for several weeks in advance. |
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|
Figure :- 20-day forecast of rainfall over theGangetic Plain
for the summer of 2002 using the new medium-range empirical forecast scheme.
Black curve is the observed and red curve is the forecast made 20 days
ahead. |
Figure :- Forecast
of the Brahmaputra discharge into Bangladesh for the 1997 summer. Blue
curve is the observed and black curve is the forecast made for pentad
periods. |
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Advantages
and disadvantages |
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