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| Titel |
Probabilistic forecasting of shallow, rainfall-triggered landslides using real-time numerical weather predictions |
| VerfasserIn |
J. Schmidt, G. Turek, M. P. Clark, M. Uddstrom, J. R. Dymond |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 8, no. 2 ; Nr. 8, no. 2 (2008-04-14), S.349-357 |
| Datensatznummer |
250005414
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| Publikation (Nr.) |
 copernicus.org/nhess-8-349-2008.pdf |
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| Zusammenfassung |
| A project established at the National Institute of Water and Atmospheric
Research (NIWA) in New Zealand is aimed at developing a prototype of a
real-time landslide forecasting system. The objective is to predict temporal
changes in landslide probability for shallow, rainfall-triggered landslides,
based on quantitative weather forecasts from numerical weather prediction
models. Global weather forecasts from the United Kingdom Met Office (MO)
Numerical Weather Prediction model (NWP) are coupled with a regional data
assimilating NWP model (New Zealand Limited Area Model, NZLAM) to forecast
atmospheric variables such as precipitation and temperature up to 48 h
ahead for all of New Zealand. The weather forecasts are fed into a
hydrologic model to predict development of soil moisture and groundwater
levels. The forecasted catchment-scale patterns in soil moisture and soil
saturation are then downscaled using topographic indices to predict soil
moisture status at the local scale, and an infinite slope stability model is
applied to determine the triggering soil water threshold at a local scale.
The model uses uncertainty of soil parameters to produce probabilistic
forecasts of spatio-temporal landslide occurrence 48~h ahead. The system
was evaluated for a damaging landslide event in New Zealand. Comparison with
landslide densities estimated from satellite imagery resulted in hit rates
of 70–90%. |
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