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| Titel |
A grid-based distributed flood forecasting model for use with weather radar data: Part 2. Case studies |
| VerfasserIn |
V. A. Bell, R. J. Moore |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 2, no. 2/3 ; Nr. 2, no. 2/3, S.283-298 |
| Datensatznummer |
250000355
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| Publikation (Nr.) |
 copernicus.org/hess-2-283-1998.pdf |
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| Zusammenfassung |
| A simple distributed rainfall-runoff model,
configured on a square grid to make best use of weather radar data, was developed in Part
1 (Bell and Moore, 1998). The simple form of the basic model, referred to as the Simple
Grid Model or SGM, allows a number of model variants to be introduced, including
probability-distributed storage and topographic index representations of runoff production
and formulations which use soil survey and land use data. These models are evaluated here
on three catchments in the UK: the Rhondda in south Wales, the Wyre in north-west England
and the Mole in the Thames Basin near London. Assessment is initially carried out in
simulation mode to focus on the conversion of rainfall to runoff as influenced by (i) use
of radar or raingauge input, (ii) choice of model variant, and (iii) use of a lumped or
distributed model formulation. Weather radar data, in grid square and catchment average
form, and raingauge data are used as alternative estimates of rainfall input to the model.
Results show that when radar data are of good quality, significant model improvement may
be obtained by replacing data from a single raingauge by 2 km grid square radar data. The
performance of the Simple Grid Model with optimised isochrones is only marginally improved
through the use of different model variants and is generally preferred on account of its
simplicity. A more traditional lumped rainfall-runoff model, the Probability-Distributed
Moisture model or PDM, is used as a benchmark against which to assess the performance of
the distributed models. This proves hard to better, although the distributed formulation
of the Grid model proves more reliable for some storm and catchment combinations where
spatial effects on runoff response are evident. Assessment is then carried out in updating
mode to emulate a real-time forecasting environment. First, a state updating form of the
Grid Model is developed and then assessed against an ARMA error-prediction technique. Both
state updating and error prediction give much improved model performance when compared
with simulation mode results. No one updating technique is superior, with the simulation
model formulation having greatest impact on forecast accuracy. However, when the results
from the different catchments are considered together it is apparent that in the rapidly
responding Rhondda catchment state updating gives slightly better results, while in the
slower responding Wyre and Mole catchments, error prediction is slightly superior. This is
attributed to the greater difficulty of reliably adjusting states when there are
significant time delays associated with the catchment response. In general, the influence
of rainfall input type, model variant and distributed versus lumped model reflect the
results obtained in simulation mode. Updating doesn't fully compensate for a poor rainfall
input or a deficient rainfall-runoff model formulation, especially for longer forecast lead
times. |
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