IEEE Geoscience and Remote Sensing Magazine - September 2014 - 32

(a)

generating 8 day forecasts of river
levels at entry points of Bangladesh rivers. These forecasts were
then used to initialize the HEC hydrodynamic model that the IWM
staff had been trained on. The
entire process was independently
managed and executed end-toend by IWM staff. Interested readers are referred to experience the
culmination of this application
by visiting two dynamic web portals: a) IWM web portal at http://
apps.iwmbd.com/satfor shown in
Figure 4a; and b) ICIMOD backup
web portal at http://apps.geoportal.icimod.org/BDFloodForecasting shown in Figure 4b.

4. Assessment of the
Promise for reAl-time
Decision-mAking
The full-scale operational launch
was maintained entirely by IWM
staff during the period of June 1
2013 until September 9, 2013 (100
days). This 100 day period essentially covered the Monsoon flood
season where the water levels in
the rivers of Bangladesh gradually
(b)
rise by an order of magnitude (during June-July), overflow into the
figure 4. (a) The web portal displaying the dynamic flood forecasts on a web-GIS interface at
floodplains (during July-Aug) and
IWM website. (b) The web portal displaying the dynamic flood forecasting back up (mirror) services recede to the low pre-Monsoon
on a web-GIS interface at ICIMOD website.
levels (during Aug-Sept). In addition, this period also includes the
marked
inter-seasonal
variability
dictated by local-scale
highly popular, easily available, user-friendly (GUI-driven)
rainfall events, terrain conditions and transboundary huand with a demonstrated track record of user-friendliness.
man impacts (such as the opening of an upstream Ganges
Lastly, we realized that staff had limited operational skill
river barrage known at Farakkha Barrage in India). For each
to handle the unique data
of the 100 days, the corresponding observed water level, as
format of JASON-2 satellite
reported by FFWC in its official forecast website (www.ffwc.
data.
Thus,
an
intermediate
reseArch finDings
gov.bd) along with the official 3 day forecast at each of these
toolbox
for
format
conversion
on Altimetry-bAseD
17 stations were also recorded for a post-Monsoon assesshad to be tailored at short noforecAsting is better
ment of forecast skill.
tice. Details of these adaptaPromoteD in An
Figure 5 demonstrates the comparison of water level hytion features are outlined in
iterAtive mAnner
drographs for 8 days and 3 days lead time with observed
Hossain et al. (2013).
recognizing the
water levels (for the forecast dates). The comparison is preOnce the JASON-2 flood
oPerAtionAl
sented for two river stations (one each for Ganges and Brahforecasting prototype was
maputra rivers). An assessment of the Root Mean Squared
customized
with
the
required
constrAints.
Error (RMSE) and correlation of forecast of JASON-2 systailor-made design modificatem as a function of lead time (from 1 day to 8 days) was
tions, we began the process
also performed for the warning stations with the most comof implementing the system in a real-time mode with the
plete record of observed data. In addition, the danger level,
goal of independent management by the staff of IWM.
defined as the water elevation beyond which large-scale inBeginning from June 1, 2013, JASON-2 data began to be
undation of homesteads or cropland begin, was noted for
downloaded, extracted and then processed routinely for
32

ieee Geoscience and remote sensing magazine

september 2014

http://http:// http://apps.iwmbd.com/satfor http://www.apps.geopor http://tal.icimod.org/BDFloodForecast http://www.ffwc http://www.gov.bd

Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - September 2014