dot
Detailansicht
Katalogkarte GBA
Katalogkarte ISBD
Suche präzisieren
Drucken
Download RIS
Hier klicken, um den Treffer aus der Auswahl zu entfernen
Titel The challenge of forecasting high streamflows 1-3 months in advance with lagged climate indices in southeast Australia
VerfasserIn J. C. Bennett, Q. J. Wang, P. Pokhrel, D. E. Robertson
Medientyp Artikel
Sprache Englisch
ISSN 1561-8633
Digitales Dokument URL
Erschienen In: Natural Hazards and Earth System Sciences ; 14, no. 2 ; Nr. 14, no. 2 (2014-02-13), S.219-233
Datensatznummer 250118271
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/nhess-14-219-2014.pdf
 
Zusammenfassung
Skilful forecasts of high streamflows a month or more in advance are likely to be of considerable benefit to emergency services and the broader community. This is particularly true for mesoscale catchments (< 2000 km2) with little or no seasonal snowmelt, where real-time warning systems are only able to give short notice of impending floods. In this study, we generate forecasts of high streamflows for the coming 1-month and coming 3-month periods using large-scale ocean–atmosphere climate indices and catchment wetness as predictors. Forecasts are generated with a combination of Bayesian joint probability modelling and Bayesian model averaging. High streamflows are defined as maximum single-day streamflows and maximum 5-day streamflows that occur during each 1-month or 3-month forecast period. Skill is clearly evident in the 1-month forecasts of high streamflows. Surprisingly, in several catchments positive skill is also evident in forecasts of large threshold events (exceedance probabilities of 25%) over the next month. Little skill is evident in forecasts of high streamflows for the 3-month period. We show that including lagged climate indices as predictors adds little skill to the forecasts, and thus catchment wetness is by far the most important predictor. Accordingly, we recommend that forecasts may be improved by using accurate estimates of catchment wetness.
 
Teil von