Towards operational joint river flow and precipitation ensemble verification: considerations and strategies given limited ensemble records

Anderson, Seonaid R.; Csima, Gabriella; Moore, Robert J.; Mittermaier, Marion; Cole, Steven J.

doi:10.1016/j.jhydrol.2019.123966

Cited by 11 publications

(6 citation statements)

References 55 publications

(60 reference statements)

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“…There are also known but important missing processes, notably representation of groundwater flows and storage, within JULES (Batelis et al, 2020) and other UKfocussed hydrological models (e.g., Coxon et al, 2019a). While treating precipitation and other meteorological-related inputs as an additional source of uncertainty among many (e.g., Wagener et al, 2021) can provide a practical constraint for model development, for example by optimizing model configurations with observed inputs, there have been critically few studies of the joint hydrometeorological performance of linked precipitation-to-river flow predictions for the UK (Anderson et al, 2019;Flack et al, 2019). This means that the impact of changes to the quality and characteristics of precipitation forecasts on resulting simulations of soil moisture and river flows are not routinely assessed, while the impact of atmosphere predictions on ocean forecasts tend to be focussed on direct radiation and surface weather forcing rather than an end-to-end assessment of hydrological forcing (e.g., .…”

Section: Introductionmentioning

confidence: 99%

A regional coupled approach to water cycle prediction during winter 2013/14 in the United Kingdom

Lewis

Dadson

2021

Hydrological Processes

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A regional coupled approach to water cycle prediction is demonstrated for the 4-month period from November 2013 to February 2014. This provides the first multicomponent analysis of precipitation, soil moisture, river flow and coastal ocean simulations produced by an atmosphere-land-ocean coupled system focussed on the United Kingdom (UK), running with horizontal grid spacing of around 1.5 km across all components. The Unified Model atmosphere component, in which convection is explicitly simulated, reproduces the observed UK rainfall accumulation (r 2 of 0.95 for water day accumulation), but there is a notable bias in its spatial distribution-too dry over western upland areas and too wet further east. The JULES land surface model soil moisture state is shown to be in broad agreement with a limited number of cosmic-ray neutron probe observations. A comparison of observed and simulated river flow shows

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Section: Introductionmentioning

confidence: 99%

A regional coupled approach to water cycle prediction during winter 2013/14 in the United Kingdom

Lewis

Dadson

2021

Hydrological Processes

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“…Such systems have to perform accurate flood forecasts in terms of location, magnitude and Flash flood forecasting requires integrated chains coupling meteorological and hydrological models (Collier 2007, Hapuarachchi et al 2011. Operational systems used all over the world now combine radar rainfall information and distributed hydrological models (Javelle et al, 2016, Gourley et al 2017, Anderson et al 2019, Corral et al, 2019. Furthermore, Numerical weather prediction (NWP) models are now able to reproduce heavy precipitation at kilometre resolutions for typically 6 to 48-h lead time (see for example in France the AROME model, Sauvage et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Flash flood impacts nowcasting within the PICS project (2018-2022): End-users involvement and first results

Javelle¹,

Payrastre²,

Boudevillain³

et al. 2021

Science and Practice for an Uncertain Future

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Flash-flood events can have catastrophic socio-economic consequences. To reduce their impacts, it is of crucial importance to set up efficient warning systems. Although first operational flash-flood warning systems have recently been implemented, some limitations are clearly identified by end-users: non-exhaustive geographic coverage, limited lead times, warnings based on hazard assessment instead of risk. However, the desirable improvements raise real scientific challenges in various domains. In this context, the PICS (Prevision immediate des impacts des crues soudaines -Flash-flood events impacts nowcasting -2018-2022) project gathers French scientific teams with varied skills (meteorologists, hydrologists, hydraulicians, economists, social geographers) and operational stakeholders (civil security, local authorities, insurance companies, managers of hydroelectric facilities and transport network). Funded by the French national research agency (ANR), it aims to develop and evaluate pre-operational forecasting chains able to estimate the potential impacts of flash floods with short anticipation lead times (up to 6 hours). These modelling chains include different components. Distributed hydrological models transform the observed and forecasted rainfall into runoff. Hydraulic models translate this runoff into potential flooded areas. Impact models incorporate these results to evaluate the potential for social and economic impacts. The research and operational partners selected four case studies based on various criteria, including the occurrence of human impacts and damages, the availability of validation data. Validation data include discharges recorded at gauging stations, but also more original information collected after each event, such as peak discharges and maximum water levels estimated from flood marks, insurance claims, damages observed on infrastructure (roads, railway…), victims interviews, casualties,etc. This presentation focuses on the methodology used for the involvement of representative potential end-users, leading to fruitfull dialogues and informative outcomes. Some of the first results of the project are also presented.

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“…With the recent advancements in quantitative precipitation estimate (QPE) and quantitative precipitation forecast (QPF) models, large-scale flood forecasting systems have been developed (Emerton et al 2016). Such systems have been operated at the continental to nationwide scales; for example, the European Flood Awareness System (EFAS) (Bartholmes et al 2009;Thielen et al 2009) in Europe, the Community Hydrologic Prediction System (CHPS) in USA (Demargne et al 2014), the Hydrological Forecasting System (HyFS) in Australia (Hapuarachchi et al 2017), the Grid-to-grid Model (G2G) in England and Wales (Anderson et al 2019;Price et al 2012) and Scotland (Cranston et al 2012), and AIGA (Adaptation d'Information Géographique pour l'Alerte en Crue) in France (Javelle et al 2016). For site-specific flood predictions at a fine scale, for example, EC-JRC (European Commission -Joint Research Centre) provides a rainfall-driven flash flood indicator within the EFAS framework called the European Precipitation Index based on Climatology (EPIC) (Alfieri and Thielen 2015) and a runoff-driven indicator called the European Runoff Index based on Climatology (ERID) (Raynaud et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Ensemble flash flood predictions using a high-resolution nationwide distributed rainfall-runoff model: case study of the heavy rain event of July 2018 and Typhoon Hagibis in 2019

Sayama

Yamada

Sugawara

et al. 2020

Prog Earth Planet Sci

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The heavy rain event of July 2018 and Typhoon Hagibis in October 2019 caused severe flash flood disasters in numerous parts of western and eastern Japan. Flash floods need to be predicted over a wide range with long forecasting lead time for effective evacuation. The predictability of flash floods caused by the two extreme events is investigated by using a high-resolution (~ 150 m) nationwide distributed rainfall-runoff model forced by ensemble precipitation forecasts with 39 h lead time. Results of the deterministic simulation at nowcasting mode with radar and gauge composite rainfall could reasonably simulate the storm runoff hydrographs at many dam reservoirs over western Japan for the case of heavy rainfall in 2018 (F18) with the default parameter setting. For the case of Typhoon Hagibis in 2019 (T19), a similar performance was obtained by incorporating unsaturated flow effect in the model applied to Kanto Region. The performance of the ensemble forecast was evaluated based on the bias ratios and the relative operating characteristic curves, which suggested the higher predictability in peak runoff for T19. For the F18, the uncertainty arises due to the difficulty in accurately forecasting the storm positions by the frontal zone; as a result, the actual distribution of the peak runoff could not be well forecasted. Overall, this study showed that the predictability of flash floods was different between the two extreme events. The ensemble spreads contain quantitative information of predictive uncertainty, which can be utilized for the decision making of emergency responses against flash floods.

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Towards operational joint river flow and precipitation ensemble verification: considerations and strategies given limited ensemble records

Cited by 11 publications

References 55 publications

A regional coupled approach to water cycle prediction during winter 2013/14 in the United Kingdom

A regional coupled approach to water cycle prediction during winter 2013/14 in the United Kingdom

Flash flood impacts nowcasting within the PICS project (2018-2022): End-users involvement and first results

Ensemble flash flood predictions using a high-resolution nationwide distributed rainfall-runoff model: case study of the heavy rain event of July 2018 and Typhoon Hagibis in 2019

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