HydroDetect: The Identification and Assessment of Climate Change Indicators for an Irish Reference Network of River Flow Stations - an Overview

This paper provides an overview of key findings from the EPA funded HydroDetect project which establishes an Irish Reference Network (IRN) of river flow gauges for monitoring and detecting climate driven trends. The flow archive from 35 hydrometric stations has an average record length of 40 years and draws from the strengths of the existing national hydrometric network. Using criteria based on the quality of flow records and minimisation of artificial influences and land-use change, complimented by expert judgement, the IRN is a valuable resource facilitating more strategic monitoring of climate driven variability and change in hydrological indicators and enabling more confident attribution of detected trends. Here an analysis of trends in mean and high flows for stations in the IRN is presented, with the spatial distribution of trends across the network examined for the period 1976-2009. The following key findings emerge. While there is considerable evidence of change in the IRN, it is difficult at this point in time to attribute these to anthropogenic greenhouse gas induced climate change. Indeed some of the trends identified – decreases in shorter records in winter mean flows and increases in summer flows – are not consistent with expected changes as simulated by Global Climate Models. This should not be surprising given the large variability of river flows relative to climate change signals at this point. Trends in Irish river flows are strongly correlated with the winter North Atlantic Oscillation Index (NAOI). The sensitivity and response of the NAO to greenhouse gas forcing will have obvious implications for Irish hydrology; however the question remains open as to the impact that greenhouse gas forcing has had on recent behaviour of the NAO and how it is likely to respond to future forcing. While it remains challenging to identify anthropogenic climate change signals at the catchment scale due to large natural variability and therefore a low signal to noise ratio, there is high potential for identifying sentinel stations and indicators within the IRN for early detection of climate change signals. These findings heighten the importance of the IRN for monitoring and detecting climate change signals at the catchment scale, for tracking the emergence of signals relative to natural variability and for providing information, free from confounding factors, for validating output from climate change impact assessments and developing adaptation policies

Benchmarking ensemble streamflow prediction skill in the UK

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

A cyclone climatology of the British-Irish Isles 1871-2012

The British-Irish Isles (BI) lie beneath the North Atlantic storm track year-round and thus are impacted by the passage of extra-tropical cyclones. Given recent extreme storminess and projections of enhanced winter cyclone activity for this region, there is much interest in assessing the extent to which the cyclone climate of the region may be changing. We address this by assessing a 142-year (1871-2012) record of cyclone frequency, intensity and 'storminess' derived from the 20th Century Reanalysis V2 (20CR) dataset. We also use this long-term record to examine associations between cyclone activity and regional hydroclimate. Our results confirm the importance of cyclone frequency in driving seasonal precipitation totals which we find to be greatest during summer months. Cyclone frequency and storminess are characterized by pronounced interannual and multi-decadal variability which are strongly coupled to atmospheric blocking in the Euro-Atlantic region, but we detect no evidence of an increasing trend. We observe an upward trend in cyclone intensity for the BI region, which is strongest in winter and consistent with model projections, but promote caution interpreting this given the changing data quality in the 20CR over time. Nonetheless, we assert that long-term reconstruction is helpful for contextualizing recent storminess and for identifying emerging changes in regional hydroclimate linked to cyclones

A global streamflow reanalysis for 1980–2018

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 temporal resolution, large uncertainty and bias in the model output, and limited extent of the dataset in space and time. This research reports on the setup of a gridded hydrological model with quasi-global coverage, able to reproduce a seamless 39-year streamflow simulation in all world’s medium to large river basins. The model was calibrated at 1226 river sections with a total drainage area of 51 million km2 within 66 countries, using ECMWF’s latest atmospheric reanalysis ERA5. A performance assessment revealed large improvements in reproducing past discharge observations, in comparison to the calibration used in the current operational setup of the hydrological model as part of the Copernicus – Global Flood Awareness System (GloFAS, www.globalfloods.eu), with median scores of Kling-Gupta Efficiency KGE = 0.67 and correlation r = 0.8. The simulation bias was also dramatically reduced and narrowed around zero, with more than 60% of stations showing percent bias within ±20%. Pronounced regional differences in the simulation results remain, pointing out the need for detailed investigation of the hydrological processes in specific regions, including parts of Africa and South Asia. In addition, observed discharges with high data quality is key to achieving skillful model output. The new calibrated model will become part of the operational runs of GloFAS in the next system release foreseen for Spring 2020, together with a near real time extension of the streamflow reanalysis

Attribution of detected changes in streamflow using multiple working hypotheses

This paper revisits a widely cited study of the Boyne catchment in east Ireland that attributed greater streamflow from the mid-1970s to increased precipitation linked to a shift in the North Atlantic Oscillation. Using the method of multiple working hypotheses we explore a wider set of potential drivers of hydrological change. Rainfall-runoff models are used to reconstruct streamflow to isolate the effect of climate, taking account of both model structure and parameter uncertainty. The Mann-Kendall test for monotonic trend and Pettitt change point test are applied to explore signatures of change. Contrary to earlier work, arterial drainage and simultaneous onset of field drainage in the 1970s and early 1980s are now invoked as the predominant drivers of change in annual mean and high flows within the Boyne. However, a change in precipitation regime is also present in March, thereby amplifying the effect of drainage. This new explanation posits that multiple drivers acting simultaneously were responsible for the observed change, with the relative contribution of each driver dependant on the timescale investigated. This work demonstrates that valuable insights can be gained from a systematic application of the method of multiple working hypotheses in an effort to move towards more rigorous attribution, which is an important part of managing emerging impacts on hydrological systems. © Author(s) 2014

HydroDetect : The Identification and Assessment of Climate Change Indicators for an Irish Reference Network of River Flow Stations. Climate Change Research Programme (CCRP) 2007-2013 Report Series No. 27. ISBN 978-1-84095-507-1

Abstract included in text

Designation and trend analysis of the updated UK Benchmark Network of river flow stations: the UKBN2 dataset

Observational trend analysis is fundamental for tracking emerging changes in river flows and placing extreme events in their longer-term historical context, particularly as climate change is expected to intensify the hydrological cycle. However, human disturbance within catchments can introduce artificial changes and confound any underlying climate-driven signal. The UK Benchmark Network (UKBN), designated in the early 2000s, comprised a subset of National River Flow Archive (NRFA) stations that were considered near-natural and thus appropriate for identification and interpretation of climate-driven hydrological trends. Here, the original network was reviewed and updated, resulting in the UKBN2 dataset consisting of 146 near-natural catchments. Additionally, the UKBN2 provides user guidance on the suitability of each station for the assessment of low, medium, and high flows. A trend analysis was performed on the updated UKBN2 dataset and results show that while the strength and direction of changes are dependent on the period of record selected, previously detected patterns of river flow change in the UK remain robust for longer periods (>50 years), despite the recent prevalence of extremes. Such a quality assured observational dataset will provide a foundation for future scientific efforts to better understand the changing nature of the hydrological cycle

Extreme multi-basin flooding linked with extra-tropical cyclones [Poster]

Fluvial floods are typically investigated as ‘events’ at the single basin-scale, hence flood management authorities may underestimate the threat of flooding across multiple basins driven by large-scale and nearly concurrent atmospheric event(s). We pilot a national-scale statistical analysis of the spatio-temporal characteristics of extreme multi-basin flooding (MBF) episodes, using peak river flow data for 260 basins in Great Britain (1975-2014), a sentinel region for storms impacting northwest and central Europe. During the most widespread MBF episode, 108 basins (~46% of the study area) recorded Annual Maximum (AMAX) discharge within a 16-day window. Such episodes are associated with persistent cyclonic and westerly atmospheric circulations, atmospheric rivers, and precipitation falling onto previously saturated ground, leading to hydrological response times <40h and documented flood impacts. Furthermore, peak flows tend to occur after 0-13 days of very severe gales causing combined and spatially-distributed, yet differentially time-lagged, wind and flood damages. These findings have implications for emergency responders, insurers and contingency planners worldwide

Future hot-spots for hydro-hazards in Great Britain: a probabilistic assessment

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 statistical framework was developed to quantify changes in frequency, magnitude, and duration, and assess time of year for both droughts and floods, and the uncertainty associated with climate model projections. This approach was applied to a spatially coherent statistical database of daily river flows (Future Flows Hydrology) across Great Britain to assess changes between the baseline (1961–1990) and the 2080s (2069–2098). The results showed that hydro-hazard hot-spots are likely to develop along the western coast of England and Wales and across north-eastern Scotland, mainly during the winter (floods) and autumn (droughts) seasons, with a higher increase in drought hazard in terms of magnitude and duration. These results suggest a need for adapting water management policies in light of climate change impact, not only on the magnitude, but also on the timing of hydro-hazard events, and future policy should account for both extremes together, alongside their potential future evolution