The 2013/14 Thames basin floods: do improved meteorological forecasts lead to more skilful hydrological forecasts at seasonal timescales?

The Thames basin experienced 12 major Atlantic depressions in winter 2013/14 leading to extensive and prolonged fluvial and groundwater flooding. This exceptional weather coincided with highly anomalous meteorological conditions across the globe. Atmospheric relaxation experiments, whereby conditions within specified regions are relaxed towards a reanalysis, have been used to investigate teleconnection patterns. However, no studies have examined whether improvements to seasonal meteorological forecasts translate into more skilful seasonal hydrological forecasts. This study applied relaxation experiments to reforecast the 2013/14 floods for three Thames basin catchments with different hydrogeological characteristics. The tropics played an important role in the development of extreme conditions over the Thames basin. Greatest hydrological forecasting skill was associated with the tropical Atlantic and less with the tropical Pacific, although both captured seasonal meteorological flow anomalies. Relaxation applied over the north-eastern Atlantic produced confident ensemble forecasts, but hydrological extremes were under-predicted; this was unexpected with relaxation applied so close to the UK. Streamflow was most skilfully forecast for the catchment representing a large drainage area with high peak flow. Permeable lithology and antecedent conditions were important for skilfully forecasting groundwater levels. Atmospheric relaxation experiments can improve our understanding of extratropical anomalies and the potential predictability of extreme events such as the Thames 2013/14 floods. Seasonal hydrological forecasts differed to what was expected from the meteorology alone, thus knowledge is gained by considering both components. In the densely populated Thames basin, considering local hydrogeological context can provide an effective early alert of potential high-impact events, allowing for better preparedness

Can seasonal hydrological forecasts inform local decisions and actions? A decision-making activity

While this paper has a hydrological focus (a glossary† is included) the concept of our decision-making activity will be of wider interest and applicable to those involved in all aspects of geoscience communication. Seasonal hydrological forecasts (SHF) provide insight into the river and groundwater levels that might be expected over the coming months. This is valuable for informing future flood or drought risk and water availability, yet studies investigating how SHF are used for decision-making are limited. Our activity was designed to capture how different water sector users, broadly flood and drought forecasters, water resource managers and groundwater hydrologists, interpret and act on SHF to inform decisions in the West Thames, UK. Using a combination of operational and hypothetical forecasts, participants were provided with 3 sets of progressively confident and locally tailored SHF for a flood event in 3 months’ time. Participants played with their ‘day-job’ hat on and were not informed whether the SHF represented a flood, drought or business-as-usual scenario. Participants increased their decision/action choice in response to more confident and locally tailored forecasts. Forecasters and groundwater hydrologists were most likely to request further information about the situation, inform other organisations and implement actions for preparedness. Water resource managers more consistently adopted a ‘watch and wait’ approach. Local knowledge, risk appetite and experience of previous flood events were important for informing decisions. Discussions highlighted that forecast uncertainty does not necessarily pose a barrier to use, but SHF need to be presented at a finer spatial resolution to aid local decision-making. SHF information that is visualised using combinations of maps, text, hydrographs and tables is beneficial for interpretation and better communication of SHF that are tailored to different user groups is needed. Decision-making activities are a great way of creating realistic scenarios that participants can identify with, whilst allowing the activity creators to observe different thought-processes. In this case, participants stated that the activity complemented their everyday work, introduced them to ongoing scientific developments and enhanced their understanding of how different organisations are engaging with and using SHF to aid decision-making across the West Thames

Skilful seasonal forecasts of streamflow over Europe?

This paper considers whether there is any added value in using seasonal climate forecasts instead of historical meteorological observations for forecasting streamflow on seasonal timescales over Europe. A Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) seasonal streamflow forecasts (produced by forcing the Lisflood model with the ECMWF System 4 seasonal climate forecasts), benchmarked against the Ensemble Streamflow Prediction (ESP) forecasting approach (produced by forcing the Lisflood model with historical meteorological observations), is undertaken. The results suggest that, on average, the System 4 seasonal climate forecasts improve the streamflow predictability over historical meteorological observations for the first month of lead time only (in terms of hindcast accuracy, sharpness and overall performance). However, the predictability varies in space and time and is greater in winter and autumn. Parts of Europe additionally exhibit a longer predictability, up to seven months of lead time, for certain months within a season. In terms of hindcast reliability, the EFAS seasonal streamflow hindcasts are on average less skilful than the ESP for all lead times. The results also highlight the potential usefulness of the EFAS seasonal streamflow forecasts for decision-making (measured in terms of the hindcast discrimination for the lower and upper terciles of the simulated streamflow). Although the ESP is the most potentially useful forecasting approach in Europe, the EFAS seasonal streamflow forecasts appear more potentially useful than the ESP in some regions and for certain seasons, especially in winter for almost 40% of Europe. Patterns in the EFAS seasonal streamflow hindcasts skill are however not mirrored in the System 4 seasonal climate hindcasts, hinting the need for a better understanding of the link between hydrological and meteorological variables on seasonal timescales, with the aim to improve climate-model based seasonal streamflow forecasting

“Are we talking just a bit of water out of bank? Or is it Armageddon?” Front line perspectives on transitioning to probabilistic fluvial flood forecasts in England

Abstract. The inclusion of uncertainty in flood forecasts is a recent, important yet challenging endeavour. In the chaotic and far from certain world we live in, probabilistic estimates of potential future floods are vital. By showing the uncertainty surrounding a prediction, probabilistic forecasts can give an earlier indication of potential future floods, increasing the amount of time we have to prepare. In practice, making a binary decision based on probabilistic information is challenging. The Environment Agency (EA), responsible for managing risks of flooding in England, is in the process of a transition to probabilistic fluvial flood forecasts. A series of interviews were carried out with EA decision-makers (i.e. duty officers) to understand how this transition might affect their decision-making activities. The interviews highlight the complex and evolving landscape (made of alternative hard scientific facts and soft values) in which EA duty officers operate, where forecasts play an integral role in decision-making. While EA duty officers already account for uncertainty and communicate their confidence in the system they use, they view the transition to probabilistic flood forecasts as both an opportunity and a challenge in practice. Based on the interview results, recommendations are made to the EA to ensure a successful transition to probabilistic forecasts for flood early warning in England. We believe that this paper is of wide interest for a range of sectors at the intersection between geoscience and society. A glossary of technical terms is highlighted by asterisks in the text and included in Appendix A

Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0

Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks, or even months, in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global scale seasonal hydro-meteorological forecasting system: GloFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (GloFAS), GloFAS-Seasonal couples seasonal meteorological forecasts from ECMWF with a hydrological model, to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other forecasting system exists. We describe the key hydro-meteorological components and computational framework of GloFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps

Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game

Probabilistic hydro-meteorological forecasts have over the last decades been used more frequently to communicate forecastuncertainty. This uncertainty is twofold, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic over deterministic forecasts across the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty to transform the probability of occurrence of an event into a binary decision. This paper presents the results of a risk-based decision-making game on the topic of flood protection mitigation, called “How much are you prepared to pay for a forecast?”. The game was played at several workshops in 2015, which were attended by operational forecasters and academics working in the field of hydrometeorology. The aim of this game was to better understand the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants’ willingness-to-pay for a forecast, the results of the game show that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers

A vision for hydrological prediction

IMproving PRedictions and management of hydrological EXtremes (IMPREX) was a European Union Horizon 2020 project that ran from September 2015 to September 2019. Its aim was 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, drought risk assessment, agriculture, navigation, hydropower, and water supply utilities). Through the engagement with stakeholders and continuous feedback between model outputs and water applications, progress was achieved in better understanding the way hydrological predictions can be useful to (and operationally incorporated into) problem solving in the water sector. The work and discussions carried out during the project nurtured further reflections towards a common vision for hydrological prediction. In this article, we summarize the main findings of the IMPREX project within a broader overview of hydrological prediction, providing a vision for improving such predictions. In so doing, we firstly present a synopsis of hydrological and weather forecasting, with a focus on medium-range to seasonal scales of prediction for increased preparedness. Second, the lessons learnt from IMPREX are discussed. The key findings are the gaps highlighted in the global observing system of the hydrological cycle, the degree of accuracy of hydrological models and the techniques of post-processing to correct biases, the origin of seasonal hydrological skill in Europe, and user requirements of hydrometeorological forecasts to ensure their appropriate use in decision-making models and practices. Lastly, a vision for how to improve these forecast systems/products in the future is expounded and these include advancing numerical weather and hydrological models, improved earth monitoring, and more frequent interaction between forecasters and users to tailor the forecasts to applications. We conclude that if these improvements can be implemented in the coming years, earth system and hydrological modelling will become more skilful, thus leading to socioeconomic benefits for the citizens of Europe and beyond

Developing observational methods to drive future hydrological science: can we make a start as a community?

Hydrology is still, and for good reasons, an inexact science, even if evolving hydrological understanding has provided a basis for improved water management for at least the last three millennia. The limitations of that understanding have, however, become much more apparent and important in the last century as the pressures of increasing populations, and the anthropogenic impacts on catchment forcing and responses, have intensified. At the same time, the sophistication of hydrological analyses and models has been developing rapidly, often driven more by the availability of computational power and geographical data sets than any real increases in understanding of hydrological processes. This sophistication has created an illusion of real progress but a case can be made that we are still rather muddling along, limited by the significant uncertainties in hydrological observations, knowledge of catchment characteristics and related gaps in conceptual understanding, particularly of the sub-surface. These knowledge gaps are illustrated by the fact that for many catchments we cannot close the water balance without significant uncertainty, uncertainty that is often neglected in evaluating models for practical applications

An efficient approach for estimating streamflow forecast skill elasticity

Seasonal streamflow prediction skill can derive from catchment initial hydrological conditions (IHCs) and from the future seasonal climate forecasts (SCFs) used to produce the hydrological forecasts. Although much effort has gone into producing state-of-the-art seasonal streamflow forecasts from improving IHCs and SCFs, these developments are expensive and time consuming and the forecasting skill is still limited in most parts of the world. Hence, sensitivity analyses are crucial to funnel the resources into useful modelling and forecasting developments. It is in this context that a sensitivity analysis technique, the variational ensemble streamflow prediction assessment (VESPA) approach, was recently introduced. VESPA can be used to quantify the expected improvements in seasonal streamflow forecast skill as a result of realistic improvements in its predictability sources (i.e., the IHCs and the SCFs) - termed ‘skill elasticity’ - and to indicate where efforts should be targeted. The VESPA approach is however computationally expensive, relying on multiple hindcasts having varying levels of skill in IHCs and SCFs. This paper presents two approximations of the approach that are computationally inexpensive alternatives. These new methods were tested against the original VESPA results using 30 years of ensemble hindcasts for 18 catchments of the contiguous United States. The results suggest that one of the methods, End Point Blending, is an effective alternative for estimating the forecast skill elasticities yielded by the VESPA approach. The results also highlight the importance of the choice of verification score for a goal-oriented sensitivity analysis

Knowledge gaps in our perceptual model of Great Britain’s hydrology

There is a no lack of significant open questions in the field of hydrology. How will hydrological connectivity between freshwater bodies be altered by future human alterations to the hydrological cycle? Where does water go when it rains? Or what is the future space-time variability of flood and drought events? However, the answers to these questions will vary with location due to the specific and often poorly understood local boundary conditions and system properties that control the functional behaviour of a catchment or any other hydrologic control volume. We suggest that an open, shared and evolving perceptual model of a region’s hydrology is critical to tailor our science questions, as it would be for any other study domain from the plot to the continental scale. In this opinion piece, we begin to discuss the elements of and point out some knowledge gaps in the perceptual model of the terrestrial water cycle of Great Britain. We discuss six major knowledge gaps and propose four key ways to reduce them. While the specific knowledge gaps in our perceptual model do not necessarily transfer to other places, we believe that the development of such perceptual models should be at the core of the debate for all hydrologic communities, and we encourage others to have a similar debate for their hydrologic domain