Use of high‐resolution NWP rainfall and river flow forecasts for advance warning of the Carlisle flood, north‐west England

Roberts, Nigel; Cole, Steven J.; Forbes, R. M.; Moore, Robert J.; Boswell, Daniel

doi:10.1002/met.94

Cited by 76 publications

(75 citation statements)

References 20 publications

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“…Other applications of NWP (e.g. Roberts et al, 2009) show that finer resolutions are capable of producing more accurate predictions, and that physics configuration, resolution and initial conditions highly influence the WRF model performance (Kryza et al, 2013). The similarity of results regardless of resolution found in this study may be also related to deficiencies in the parameterisation of the model, or to the inability to sufficiently resolve the topography.…”

Section: Evaluating Precipitation Forecasts From the Wrf Modelmentioning

confidence: 57%

Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas

Rogelis

Werner

2018

Hydrol. Earth Syst. Sci.

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Abstract. Numerical weather prediction (NWP) models are fundamental to extend forecast lead times beyond the concentration time of a watershed. Particularly for flash flood forecasting in tropical mountainous watersheds, forecast precipitation is required to provide timely warnings. This paper aims to assess the potential of NWP for flood early warning purposes, and the possible improvement that bias correction can provide, in a tropical mountainous area. The paper focuses on the comparison of streamflows obtained from the post-processed precipitation forecasts, particularly the comparison of ensemble forecasts and their potential in providing skilful flood forecasts. The Weather Research and Forecasting (WRF) model is used to produce precipitation forecasts that are post-processed and used to drive a hydrologic model. Discharge forecasts obtained from the hydrological model are used to assess the skill of the WRF model. The results show that post-processed WRF precipitation adds value to the flood early warning system when compared to zeroprecipitation forecasts, although the precipitation forecast used in this analysis showed little added value when compared to climatology. However, the reduction of biases obtained from the post-processed ensembles show the potential of this method and model to provide usable precipitation forecasts in tropical mountainous watersheds. The need for more detailed evaluation of the WRF model in the study area is highlighted, particularly the identification of the most suitable parameterisation, due to the inability of the model to adequately represent the convective precipitation found in the study area.

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Section: Evaluating Precipitation Forecasts From the Wrf Modelmentioning

confidence: 57%

Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas

Rogelis

Werner

2018

Hydrol. Earth Syst. Sci.

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“…Roberts et al (2009) noted that the radar data generally had lower rainfall amounts than the gauged network. This study was of the January 2005 Carlisle event, which will be focussed upon within this thesis, and concluded that the rain gauge data provided the most accurate measurements.…”

Section: Subcatchmentmentioning

confidence: 95%

“…This may have been caused by the formation of a sting jet (Browning and Field, 2004), a mesoscale air flow originating in the cloud head of a deepening cyclone and gaining speed as it descends to the tip of the cloud head. Furthermore, orographic enhancement of rainfall occurred due to the seeder-feeder mechanism (Bader and Roach, 1977;Roberts et al, 2009), whereby rain becomes more intense as it falls through lower level clouds formed as moist air flows over mountainous terrain. (Roberts et al 2009) from the Forecasters Reference book (Meteorological Office, 1997) The rarity of the event is linked to its duration, rather than the intensity of the rainfall.…”

Section: Figure 47 Map Showing Storm Track and Areas Affected By Flomentioning

confidence: 99%

“…Furthermore, orographic enhancement of rainfall occurred due to the seeder-feeder mechanism (Bader and Roach, 1977;Roberts et al, 2009), whereby rain becomes more intense as it falls through lower level clouds formed as moist air flows over mountainous terrain. (Roberts et al 2009) from the Forecasters Reference book (Meteorological Office, 1997) The rarity of the event is linked to its duration, rather than the intensity of the rainfall. Overall, this storm has been estimated as having a return period of 50-100 years (0.02-0.01 annual probability).…”

Section: Figure 47 Map Showing Storm Track and Areas Affected By Flomentioning

confidence: 99%

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Rural land management impacts on catchment scale flood risk

Pattison¹

2010

Role of Hydrology in Managing Consequences of a Changing Global Environment

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The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source• a link is made to the metadata record in Durham E-Theses• the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full Durham E-Theses policy for further details. Most approaches to this problem aim to upscale from individual grid cells to whole catchments, something that restricts the complexity of possible process representation, produces models that may not be parsimonious with the data needed to calibrate them and, faced with data uncertainties, provides computational limitations on the extent to which model uncertainty can be fully explored. Rather than upscaling to problems of concern, this thesis seeks to downscale from locations of known flood risk, as a means of identifying where land use management changes might be beneficial and then uses numerical modelling to identify the kinds of management changes required in those downscaled locations. Thus, the aim of this thesis is to test an approach to understanding the impacts of rural land management upon flood risk based upon catchment-to-source downscaling.This thesis uses the case study of the River Eden catchment (2400 km 2 ) as a test (1) it was shown to have a significant impact on downstream flood risk; and (2) it had range of data and information needed for modelling land use changes.The second part of this thesis explored the land management scenarios that could be used to reduce flood risk at the catchment scale. The scenarios to be tested were determined through a stakeholder participation approach, whereby workshops were held to brainstorm and prioritise land management options, and then to identify specific locations within the Eamont sub-catchment where they could tested. There were two main types of land management scenarios chosen: (1) landscape-scale changes, including afforestation and compaction; and (2) corresponding to a 5.8% decrease in peak discharge. A key conclusion is that land management practices have been shown to have an effect on catchment scale flooding, even for extreme flood events. However, the effect of land management scenarios are both spatially and temporally dependent i.e. the same land management practice has different effects depending on where it is implemented, and when implemented in the same location has different effects on different flood events.

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“…A lumped conceptual rainfall-runoff model was used: the probability distributed model (PDM) as described by Moore (2007) and previously applied to a range of flood studies in the UK (e.g. Lamb 1999, Kay et al 2007, Roberts et al 2009). The PDM represents runoff by individual point cylinders whose storage capacity varies across the catchment according to a Pareto probability distribution.…”

Section: Continuous Simulationmentioning

confidence: 99%

Flood frequency estimation using a joint probability approach within a Monte Carlo framework

Svensson

Kjeldsen

Jones

2013

Hydrological Sciences Journal

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Event-based methods are used in flood estimation to obtain the entire flood hydrograph. Previously, such methods adopted in the UK have relied on pre-determined values of the input variables (e.g. rainfall and antecedent conditions) to a rainfall-runoff model, which is expected to result in an output flood of a particular return period. In contrast, this paper presents a method that allows all the input variables to take on values across the full range of their individual distributions. These values are then brought together in all possible combinations as input to an event-based rainfall-runoff model in a Monte Carlo simulation approach. Further, this simulation strategy produces a long string of events (on average 10 per year), where dependencies from one event to the next, as well as between different variables within a single event, are accounted for. Frequency analysis is then applied to the annual maximum peak flows and flow volumes.Key words flood frequency estimation; joint probability; Monte Carlo simulation; hydrological event modelling; uncertainty analysis; sensitivity analysis; river flow; rainfall; soil moisture deficit; Great Britain Prédétermination des crues utilisant une méthode de probabilités conjointes dans un cadre de simulation Monte-Carlo Résumé Les méthodes événementielles sont utilisées en prédétermination des crues afin d'obtenir un hydrogramme de crue complet. Précédemment, ces méthodes adoptées au Royaume-Uni dépendaient de valeurs prédéterminées des variables d'entrée (par ex. données de pluies et conditions antérieures) d'un modèle pluiedébit, qui devait produire une crue de sortie correspondant à une certaine période de retour. Par opposition, cet article présente une méthode permettant à toutes les variables d'entrée de prendre des valeurs sur toute la gamme de leurs distributions propres. Ces valeurs sont alors assemblées en décrivant toutes les combinaisons possibles, pour servir d'entrée à un modèle pluie-débit événementiel dans une approche de simulation Monte-Carlo. De plus, cette stratégie de simulation produit une longue séquence d'évènements (en moyenne 10 par an), où sont prises en compte aussi bien les dépendances entre un évènement et le suivant que celles entre diverses variables au sein d'un même évènement. Une analyse de fréquence est alors appliquée aux débits de pointe et aux volumes d'écoulement maximaux annuels.

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Use of high‐resolution NWP rainfall and river flow forecasts for advance warning of the Carlisle flood, north‐west England

Cited by 76 publications

References 20 publications

Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas

Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas

Rural land management impacts on catchment scale flood risk

Flood frequency estimation using a joint probability approach within a Monte Carlo framework

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