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Forecasting river levels during flash floods using Data Based Mechanistic models, online data assimilation and meteorological forecasts.

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

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Forecasting river levels during flash floods using Data Based Mechanistic models, online data assimilation and meteorological forecasts. / Smith, Paul; Beven, Keith.
2010. Paper presented at British Hydrological Society International symposium, Newcastle, United Kingdom.

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

Harvard

Smith, P & Beven, K 2010, 'Forecasting river levels during flash floods using Data Based Mechanistic models, online data assimilation and meteorological forecasts.', Paper presented at British Hydrological Society International symposium, Newcastle, United Kingdom, 1/07/10.

APA

Smith, P., & Beven, K. (2010). Forecasting river levels during flash floods using Data Based Mechanistic models, online data assimilation and meteorological forecasts.. Paper presented at British Hydrological Society International symposium, Newcastle, United Kingdom.

Vancouver

Smith P, Beven K. Forecasting river levels during flash floods using Data Based Mechanistic models, online data assimilation and meteorological forecasts.. 2010. Paper presented at British Hydrological Society International symposium, Newcastle, United Kingdom.

Author

Smith, Paul ; Beven, Keith. / Forecasting river levels during flash floods using Data Based Mechanistic models, online data assimilation and meteorological forecasts. Paper presented at British Hydrological Society International symposium, Newcastle, United Kingdom.

Bibtex

@conference{25d3819f238344bda2ccb3fbf4a9ec7c,
title = "Forecasting river levels during flash floods using Data Based Mechanistic models, online data assimilation and meteorological forecasts.",
abstract = "The parsimonious time series models used within the Data-Based Mechanistic (DBM) modelling framework are readily transferred into a State-Space form allowing the implementation of data assimilation using the Kalman filter. Multiple case studies have demonstrated the effectiveness of this framework in providing probabilistic forecasts for many hydrological situations, such as flood events on large UK rivers. The recent work presented here has applied the DBM methodology to forecast floods in catchments with a rapid response to rainfall. The resulting DBM models which, amongst other adaptations, utilise meteorological predictions to increase the forecast horizon are demonstrated using a European case study.",
author = "Paul Smith and Keith Beven",
year = "2010",
month = jul,
language = "English",
note = "British Hydrological Society International symposium ; Conference date: 01-07-2010",

}

RIS

TY - CONF

T1 - Forecasting river levels during flash floods using Data Based Mechanistic models, online data assimilation and meteorological forecasts.

AU - Smith, Paul

AU - Beven, Keith

PY - 2010/7

Y1 - 2010/7

N2 - The parsimonious time series models used within the Data-Based Mechanistic (DBM) modelling framework are readily transferred into a State-Space form allowing the implementation of data assimilation using the Kalman filter. Multiple case studies have demonstrated the effectiveness of this framework in providing probabilistic forecasts for many hydrological situations, such as flood events on large UK rivers. The recent work presented here has applied the DBM methodology to forecast floods in catchments with a rapid response to rainfall. The resulting DBM models which, amongst other adaptations, utilise meteorological predictions to increase the forecast horizon are demonstrated using a European case study.

AB - The parsimonious time series models used within the Data-Based Mechanistic (DBM) modelling framework are readily transferred into a State-Space form allowing the implementation of data assimilation using the Kalman filter. Multiple case studies have demonstrated the effectiveness of this framework in providing probabilistic forecasts for many hydrological situations, such as flood events on large UK rivers. The recent work presented here has applied the DBM methodology to forecast floods in catchments with a rapid response to rainfall. The resulting DBM models which, amongst other adaptations, utilise meteorological predictions to increase the forecast horizon are demonstrated using a European case study.

M3 - Conference paper

T2 - British Hydrological Society International symposium

Y2 - 1 July 2010

ER -