Christel Prudhomme

UK Centre for Ecology & Hydrology | CEH · Programme of Water

Long Short Term Memory networks (LSTMs) are used to build single models that predict river discharge across many catchments. These models offer greater accuracy than models trained on each catchment independently if using the same data. However, the same data is rarely available for all catchments. This prevents the use of variables available only...

Climate change has resulted in more frequent occurrences of extreme events, such as flooding and heavy snowfall, which can have a significant impact on densely populated or industrialised areas. Numerical models are used to simulate and predict these extreme events, enabling informed decision-making and planning to minimise human casualties and to...

Global hydrological reanalyses are modelled datasets providing information on river discharge evolution everywhere in the world. With multi‐decadal daily timeseries, they provide long‐term context to identify extreme hydrological events such as floods and droughts. By covering the majority of the world's land masses, they can fill the many gaps in...

Floods are one of the most common natural disasters, with a disproportionate impact in developing countries that often lack dense streamflow gauge networks¹. Accurate and timely warnings are critical for mitigating flood risks², but hydrological simulation models typically must be calibrated to long data records in each watershed. Here we show that...

During protracted dry spells, there is considerable interest from water managers, media and the public in when and how drought termination (DT) will occur. Robust answers to these questions require better understanding of the hydroclimatic drivers of DT than currently available. Integrated vapour transport (IVT) has been found to drive DT in wester...

International humanitarian organisations increasingly turn to forecast teams to support the coordination of efforts to respond to disasters caused by hazards such as tropical cyclones and large‐scale fluvial floods. Such disasters often occur where there is limited local capacity or information available to support decision making and so global for...

Climate change has resulted in more frequent occurrences of extreme events, such as flooding and heavy snowfall, which can have a significant impact on densely populated or industrialised areas. Numerical models are used to simulate and predict these extreme events, enabling informed decision-making and planning to minimise human casualties and pro...

Floods are one of the most common and impactful natural disasters, with a disproportionate impact in developing countries that often lack dense streamflow monitoring networks. Accurate and timely warnings are critical for mitigating flood risks, but accurate hydrological simulation models typically must be calibrated to long data records in each wa...

Our paper aims to improve flood forecasting by establishing whether a global hydrological forecast system could be used as an alternative to a regional system, or whether it could provide additional information. This paper was based on the operational Global Flood Awareness System (GloFAS) of the European Commission Copernicus Emergency Management...

The unprecedented progress in ensemble hydro‐meteorological modelling and forecasting on a range of temporal and spatial scales, raises a variety of new challenges which formed the theme of the Joint Virtual Workshop, ‘Connecting global to local hydrological modelling and forecasting: challenges and scientific advances’. Held from 29 June to 1 July...

Operational global-scale hydrological forecasting systems are used to help manage hydrological extremes such as floods and droughts. The vast amounts of raw data that underpin forecast systems and the ability to generate information on forecast skill have, until now, not been publicly available. As part of the Global Flood Awareness System (GloFAS;...

In this chapter we will discuss the different components required for a hazard forecasting system, aimed to predict high-impact events on different timescales. The components discussed here are the atmospheric forecasting system and hazard forecast models in terms of flooding, drought, fire risk, and human heat stress. Predicting hazardous events i...

Accurate river streamflow forecasts are a vital tool in the fields of water security, flood preparation and agriculture, as well as in industry more generally. Traditional physics-based models used to produce streamflow forecasts have become increasingly sophisticated, with forecasts improving accordingly. However, the development of such models is...

Most people face some level of water insecurity. Wise water management practices to address water security issues typically require data derived from a combination of observation and model data. This data has historically proven difficult to sustainably supply in many areas of the world. We present the design and development of a global, modeled st...

Streamflow forecasts provide vital information to aid emergency response preparedness and disaster risk reduction. Medium-range forecasts are created by forcing a hydrological model with output from numerical weather prediction systems. Uncertainties are unavoidably introduced throughout the system and can reduce the skill of the streamflow forecas...

Abstract Low‐likelihood weather events can cause dramatic impacts, especially when they are unprecedented. In 2020, amongst other high‐impact weather events, UK floods caused more than £300 million damage, prolonged heat over Siberia led to infrastructure failure and permafrost thawing, while wildfires ravaged California. Such rare phenomena cannot...

The representation of snow is a crucial aspect of land-surface modelling, as it has a strong influence on energy and water balances. Snow schemes with multiple layers have been shown to better describe the snowpack evolution and bring improvements to soil freezing and some hydrological processes. In this paper, the wider hydrological impact of the...

Large-ensemble climate model simulations can provide deeper understanding of the characteristics and causes of extreme events than historical observations, due to their larger sample size. However, adequate evaluation of simulated ‘unseen’ events that are more extreme than those seen in historical records is complicated by observational uncertainti...

Accurate river streamflow forecasts are a vital tool in the fields of water security, flood preparation and agriculture, as well as in industry more generally. Over the last century, physics-based models traditionally used to produce streamflow forecasts have become increasingly sophisticated, with forecasts improving accordingly. However, the deve...

Streamflow forecasts provide vital information to aid emergency response preparedness and disaster risk reduction. Medium-range forecasts are created by forcing a hydrological model with output from numerical weather prediction systems. Uncertainties are unavoidably introduced throughout the system and can reduce the skill of the streamflow forecas...

Ensemble members from weather and climate predictions can be used to generate large samples of simulated weather events, allowing the estimation of extreme (hitherto unseen) events. Here, we provide a protocol and open workflow for applying the ‘UNSEEN’ method for hydro-climatic extremes globally, based on Copernicus Climate Change Services (C3S) s...

Skilful hydrological forecasts can benefit decision-making in water resources management and other water-related sectors that require long-term planning. In Ireland, no such service exists to deliver forecasts at the catchment scale. In order to understand the potential for hydrological forecasting in Ireland, we benchmark the skill of ensemble str...

The land-surface developments of the European Centre for Medium-range Weather Forecasts (ECMWF) are based on the Carbon-Hydrology Tiled Scheme for Surface Exchanges over Land (CHTESSEL) and form an integral part of the Integrated Forecasting System (IFS), supporting a wide range of global weather, climate and environmental applications. In order to...

The land-surface developments of the European Centre for Medium-range Weather Forecasts (ECMWF) are based on the Carbon-Hydrology Tiled Scheme for Surface Exchanges over Land (CHTESSEL) and form an integral part of the Integrated Forecasting System (IFS), supporting a wide range of global weather, climate and environmental applications. In order to...

Despite being one of the most damaging natural hazards, droughts and their spatiotemporal dynamics are typically not well understood. Great Britain, which is the focus of this work, has experienced many major drought episodes in the past, causing a range of socioeconomic and environmental impacts. Here, we apply a recently developed technique to id...

Precipitation is a key component of the global water cycle and plays a crucial role in flooding, droughts, and water supply. One way to manage its socioeconomic effects is based on precipitation forecasts from numerical weather prediction (NWP) models, and an important step to improve precipitation forecasts is by diagnosing NWP biases. In this stu...

Riverine plastic pollution is of global concern due to its negative impact on ecosystem health and human livelihood. Recent studies show a strong link between river discharge and plastic transport, but the role of floods is still unresolved. We combined high resolution mismanaged plastic waste data and river flood extents with increasing return per...

Skilful hydrological forecasts can benefit decision-making in water resources management and other water-related sectors that require long-term planning. In Ireland, no such service exists to deliver forecasts at the catchment scale. In order to understand the potential for hydrological forecasting in Ireland, we benchmark the skill of Ensemble Str...

Sample sizes of observed climate extremes are typically too small to reliably constrain return period estimates when there is non-stationary behaviour. To increase the historical record 100-fold, we apply the UNprecedented Simulated Extreme ENsemble (UNSEEN) approach, by pooling ensemble members and lead times from the ECMWF seasonal prediction sys...

Operational global-scale hydrological forecasting systems are widely used to help manage hydrological extremes such as floods and droughts. The vast amounts of raw data that underpin forecast systems and the ability to generate information on forecast skill have, until now, not been publicly available. As part of the Global Flood Awareness System (...

Estimating how much water is flowing through rivers at the global scale is challenging due to a lack of observations in space and time. A way forward is to optimally combine the global network of earth system observations with advanced numerical weather prediction (NWP) models to generate consistent spatio-temporal maps of land, ocean, and atmosphe...

Global flood forecasting systems rely on predefining flood thresholds to highlight potential upcoming flood events. Existing methods for flood threshold definition are often based on reanalysis datasets using a single threshold across all forecast lead times, such as in the Global Flood Awareness System. This leads to inconsistencies between how th...

The mean radiant temperature (MRT) and the Universal Thermal Climate Index (UTCI) are widely used as human biometeorology parameters to assess the linkages between outdoor environment and human well-being. Historically computed from meteorological station measurements, we here present ERA5-HEAT (Human thErmAl comforT), the first historical dataset...

Riverine plastic pollution is of global concern due to its negative impact on ecosystem health and human livelihood. Recent studies show a strong link between river discharge and plastic transport, but the role of floods is still unresolved. We combined high resolution mismanaged plastic waste data and river flood extents with increasing return per...

Sample sizes of observed climate extremes are typically too small to reliably constrain non-stationary behaviour. To facilitate detection of non-stationarities in 100-year precipitation values over a short period of 35 years (1981-2015), we apply the UNprecedented Simulated Extreme ENsemble (UNSEEN) approach, by pooling ensemble members and lead ti...

In this study the impacts of Soil Moisture and Ocean Salinity (SMOS) soil moisture data assimilation upon the streamflow prediction of the operational Global Flood Awareness System (GloFAS) were investigated. Two GloFAS experiments were performed, one which used hydro-meteorological forcings produced with the assimilation of the SMOS data, the othe...

IMproving PRedictions and management of hydrological EXtremes (IMPREX) was a European Union Horizon 2020 project that ran from September 2015 to September 2019. IMPREX aimed to improve society’s ability to anticipate and respond to future extreme hydrological events in Europe across a variety of uses in the water-related sectors (flood forecasting,...

ECMWF has begun to produce pre-operational forecasts of thermal-related human comfort indices in real time using meteorological forcing data - air temperature, humidity, wind speed and radiation - from its Integrated Forecasting System (IFS). The high-resolution and probabilistic forecasts, which predict the Universal Thermal Climate Index (UTCI) a...

Abstract. Abstract. Estimating how much water is flowing through rivers at the global scale is challenging due to a lack of observations in space and time. A way forward is to optimally combine the global network of earth system observations with advanced numerical weather prediction (NWP) models to generate consistent spatio-temporal maps of land,...

Global and continental scale hydrological reanalysis datasets receive growing attention due to their increasing number of applications, ranging from water resources management, climate change studies, water related hazards and policy support. Until recently, their use was mostly limited to qualitative assessments, due to their coarse spatial and te...

Global hydrological forecasts are now produced operationally on a daily basis. However, the lack of global river discharge observations precludes routine flood forecast evaluation, an essential step in providing more skilful and reliable forecasts. A vision is expounded for greater and more timely exchange of global river discharge observations, wh...

Hydrological droughts occur in all climate zones and can have severe impacts on society and the environment. Understanding historical drought occurrence and quantifying severity is crucial for underpinning drought risk assessments and developing drought management plans. However, hydrometric records are often short and capture only a limited range...

Hurricane Harvey caused at least 70 confirmed deaths, with estimated losses in the Houston urban area reaching above $150 billion, making it one of the costliest natural disasters ever in the United States. Here we tested two types of forecast index to provide surface flooding (inundation) warning over the Houston area: a meteorological index based...

Drought management plans (DMPs) require an overview of future climate conditions for ensuring long-term relevance of existing decision-making processes. To that end, impact studies are expected to best reproduce decision-making needs linked with catchment intrinsic sensitivity to climate change. The objective of this study is to apply a risk-based...

Simulations of water fluxes at high spatial resolution that consistently cover historical observations, seasonal forecasts, and future climate projections are key to providing climate services aimed at supporting operational and strategic planning, and developing mitigation and adaptation policies. The End-to-end Demonstrator for improved decision-...

Hydrological models can provide estimates of streamflow pre- and post-observations, which enable greater understanding of past hydrological behaviour, and potential futures. In this paper, a new multi-objective calibration method was derived and tested for 303 catchments in the UK, and the calibrations were used to reconstruct river flows back to 1...

Land surface models (LSMs) have traditionally been designed to focus on providing lower-boundary conditions to the atmosphere with less focus on hydrological processes. State-of-the-art application of LSMs includes a land data assimilation system (LDAS), which incorporates available land surface observations to provide an improved realism of surfac...

Hydrological droughts occur in all climate zones and can have severe impacts on society and the environment. Understanding historical drought occurrence and quantifying severity is crucial for underpinning drought risk assessments and the developing drought management plans. However, hydrometric records are often short and capture only a limited ra...

Early warning systems (EWS) for river flooding are strategic tools for effective disaster risk management in many world regions. When driven by ensemble Numerical Weather Predictions (NWP), flood EWS can provide skillful streamflow forecasts beyond the monthly time scale in large river basins. Yet, effective flood detection is challenged by accurat...

This study develops a coherent framework to detect those catchment types associated with a high risk of maladaptation to future flood risk. Using the “scenario-neutral” approach to impact assessment the sensitivity of Irish catchments to fluvial flooding is examined in the context of national climate change allowances. A predefined sensitivity doma...

Supporting Information S1

In an increasing hydro-climatic risk context as a result of climate change, this work aims to identify future hydro-hazard hot-spots as a result of climate change across Great Britain. First, flood and drought hazards were defined and selected in a consistent and parallel approach with a threshold method. Then, a nation-wide systematic and robust s...

Projections of runoff from global multi-model ensembles provide a valuable basis for the estimation of future hydrological extremes. However, projections suffer from uncertainty that originates from different error sources along the modeling chain. Hydrological impact studies have generally partitioned these error sources into global impact and glo...