Flood Forecast Based On Numerical Weather
Prediction And Distributed Runoff Model
Author(s)
H. Kardhana, H. Tatesawa & A. Mano
Abstract
The accuracy of quantitative precipitation forecast from numerical weather
prediction (NWP) grows as higher resolutions are achieved by the computation
capacity of supercomputers. Various distributed dataset, globally and locally,
with better spatial and temporal resolution has been rapidly developed. The
objective of this paper is to have a flood forecast model that utilises these great
benefits and gives reliable accuracy.
Another asset of a flood forecast model is a conceptual-distributed runoff
model; it has been chosen because of its simplicity. Calibration and validation of
the model has been met by good agreement for events in 2002 in the case of a
237 km2 operational scale basin. These results are based on input Grid Point
Value (GPV) precipitation of Japan radar observation.
Forecasted Precipitation was based on a GPV Mesoscale Model of Japan
NWP. It had an 18 hour lead time and updated four times a day. Flood
forecasting based on input from forecasted precipitation shows that the accuracy
decreases as lead-time increased. It is clear that flood forecasting depends on
precipitation forecast accuracy.
Observed precipitation and discharge are used for model updating to
determine initial data for flood forecasting. The simplicity of the runoff model
gives advantage on water content estimation in soil storage. It is necessary
because the runoff model might have basic errors and it needs to have better
initial data. Updating calculated discharge with observed discharge approximates
the estimation. By estimating more correctly, the model shows to be more
reliable.
Keywords: flood forecast, quantitative precipitation forecast, numerical weather
prediction, runoff model, updating.
Keywords
flood forecast, quantitative precipitation forecast, numerical weather
prediction, runoff model, updating.
Related Book
Other papers in this volume
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