Effects of temporal resolution of input precipitation on the performance of hydrological forecasting
Flood prediction systems rely on good quality precipitation input data and forecasts to drive hydrological models. Most precipitation data comes from daily stations with a good spatial coverage. However, some flood events occur on sub-daily time scales and flood prediction systems could benefit from...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2011-02-01
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Series: | Advances in Geosciences |
Online Access: | http://www.adv-geosci.net/29/21/2011/adgeo-29-21-2011.pdf |
Summary: | Flood prediction systems rely on good quality precipitation input data and
forecasts to drive hydrological models. Most precipitation data comes from
daily stations with a good spatial coverage. However, some flood events
occur on sub-daily time scales and flood prediction systems could benefit
from using models calibrated on the same time scale. This study compares
precipitation data aggregated from hourly stations (HP) and data
disaggregated from daily stations (DP) with 6-hourly forecasts from ECMWF
over the time period 1 October 2006–31 December 2009. The HP and DP data sets were then
used to calibrate two hydrological models, LISFLOOD-RR and HBV, and the
latter was used in a flood case study. The HP scored better than the DP when
evaluated against the forecast for lead times up to 4 days. However, this
was not translated in the same way to the hydrological modelling, where the
models gave similar scores for simulated runoff with the two datasets. The
flood forecasting study showed that both datasets gave similar hit rates
whereas the HP data set gave much smaller false alarm rates (FAR). This
indicates that using sub-daily precipitation in the calibration and
initiation of hydrological models can improve flood forecasting. |
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ISSN: | 1680-7340 1680-7359 |