Benchmarking ensemble streamflow prediction skill in the UK

Shaun Harrigan,Simon Parry,Christel Prudhomme,Katie Smith,Maliko Tanguy

doi:10.5194/hess-22-2023-2018

Abstract

Abstract. Skilful hydrological forecasts at sub-seasonal to seasonal lead times would be extremely beneficial for decision-making in water resources management, hydropower operations, and agriculture, especially during drought conditions. Ensemble streamflow prediction (ESP) is a well-established method for generating an ensemble of streamflow forecasts in the absence of skilful future meteorological predictions, instead using initial hydrologic conditions (IHCs), such as soil moisture, groundwater, and snow, as the source of skill. We benchmark when and where the ESP method is skilful across a diverse sample of 314 catchments in the UK and explore the relationship between catchment storage and ESP skill. The GR4J hydrological model was forced with historic climate sequences to produce a 51-member ensemble of streamflow hindcasts. We evaluated forecast skill seamlessly from lead times of 1 day to 12 months initialized at the first of each month over a 50-year hindcast period from 1965 to 2015. Results showed ESP was skilful against a climatology benchmark forecast in the majority of catchments across all lead times up to a year ahead, but the degree of skill was strongly conditional on lead time, forecast initialization month, and individual catchment location and storage properties. UK-wide mean ESP skill decayed exponentially as a function of lead time with continuous ranked probability skill scores across the year of 0.75, 0.20, and 0.11 for 1-day, 1-month, and 3-month lead times, respectively. However, skill was not uniform across all initialization months. For lead times up to 1 month, ESP skill was higher than average when initialized in summer and lower in winter months, whereas for longer seasonal and annual lead times skill was higher when initialized in autumn and winter months and lowest in spring. ESP was most skilful in the south and east of the UK, where slower responding catchments with higher soil moisture and groundwater storage are mainly located; correlation between catchment base flow index (BFI) and ESP skill was very strong (Spearman's rank correlation coefficient =0.90 at 1-month lead time). This was in contrast to the more highly responsive catchments in the north and west which were generally not skilful at seasonal lead times. Overall, this work provides scientific justification for when and where use of such a relatively simple forecasting approach is appropriate in the UK. This study, furthermore, creates a low cost benchmark against which potential skill improvements from more sophisticated hydro-meteorological ensemble prediction systems can be judged.

Highlights

Skilful hydrological forecasts at sub-seasonal to seasonal lead times would provide a valuable tool for improved decision making for wide range of sectors such as water resources management (Anghileri et al, 2016), hydropower operations (Hamlet et al, 2002), and agriculture (Letcher et al, 2004), in times of slow onset events such as drought (Simpson et al, 2016)
Results are presented in the following order: First, Ensemble streamflow prediction (ESP) skill is shown for all 365 lead times (LT), by forecast initialization month for a sample of eight representative LTs commonly used in operational hydrological forecasting (i.e. short (1 and 3 days), extended (1 and 2 weeks), monthly (1 month), seasonal (3 and 6 months), and annual (12 months))
The ESP method using simple lumped conceptual hydrological models is currently one of three methods used within the operational Hydrological Outlook UK (HOUK) seasonal hydrological forecasting service and feeds into the Environment Agency’s monthly “Water Situation Report for England”

Summary

Introduction

Skilful hydrological forecasts at sub-seasonal to seasonal lead times would provide a valuable tool for improved decision making for wide range of sectors such as water resources management (Anghileri et al, 2016), hydropower operations (Hamlet et al, 2002), and agriculture (Letcher et al, 2004), in times of slow onset events such as drought (Simpson et al, 2016). ESP was pioneered in the US at the National Weather Service (NWS) during the 1970s and 1980s as a means of providing ensemble forecasts of streamflow for a variety of lead times from 1 day to seasonal and beyond In the UK, the 2010– 2012 drought in England and Wales provided the impetus for the establishment of the first operational seasonal hydrological forecasting service, the Hydrological Outlook UK (HOUK), which went live in June 2013 (Prudhomme et al, 2017; forecasts available at: http://www.hydoutuk.net/). ESP is used as one of three hydrological forecasting methods in HOUK and feeds into the Environment Agency’s monthly “Water Situation Report for England” (operational for groundwater levels in March 2012), providing forward look ESP forecasts of streamflow for 29 catchments out to a 12-month lead time (https://www.gov.uk/government/ collections/water-situation-reports-for-england)

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Results

Discussion

Conclusion