Abstract:
.Flash flood in the northeast region of Bangladesh damages. agricultural products of
large areas causes deathand. destruction. to roads and bridges. Pre-monsoon flash
floods damage the main crop Boro rice at the time of or just before the time of
harvesting. About 60% of the total runoff in the Northeast Region is produced; mostly
in the form of flash flood generated by the three Indian catchments- the Meghalaya
River catehments~ the Barak River catchments~ and the Tripura River catchments. As . ..'
rain gaugedata in the Indian catchments are not so avai1l:1ble~satellite based rainfall
could be a good resource for estimation of flash flood inflows towards the northeast.
region.
The objectives of the study are to simulate Rainfall Runoff Model of the Northeast
Bangladesh~ the Meghalaya River catchments~ the Barak River catchments~ and the
Tripura River catchment with ..GSMap precipitation data and generate Flash Flood
Forecast using Hydrodynamic Model incorporating WRF predicted precipitation. The
result shows underestima~ion of runoff.As a result bias correction in GSMap rainfall
is needed prior to application into operational flood prediction. With six years of data
from 2009 to 2014; the 7-day moving average bias-adjustment was derived comparing
the gauge observe'rainfall. The bias-adjustments were applied to every catchment.
These bias-adjusted rainfalls when applied to the NAM model resulted in
improvement in runoff for all catchments. The calibrated hydrodynamic model shows
good -result in flood forecasting.
Overall~ findings from this study indicate that the. GSMap underestimates rainfall
signific~nt1y over Barak:, trans boundary and north-east catchments. The accuracy of
GSMap can be improved by applying a. bias-adjustment. Prediction of water level
using bias-adjusted rainfall estimates can improve the accuracy of water level
prediction with considerable increase in the predictive capability of flood prediction
for which the hydrological model needs to be calibrated.
