Storylines of UK drought based on the 2010–2012 event

Chan, Wilson C. H.; Shepherd, Theodore G.; Smith, Katie; Darch, Geoff; Arnell, Nigel W.

doi:10.5194/hess-26-1755-2022

Cited by 18 publications

(17 citation statements)

References 88 publications

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“…This finding is consistent with many previous studies on future projections in hydrometeorological drought in the UK (e.g. Rudd et al 2019;Kay et al 2021b;Chan et al 2022). Projections of groundwater levels and groundwater drought showed more substantial variability across the study sites.…”

Section: Groundwater Levelssupporting

confidence: 92%

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Divergent future drought projections in UK river flows and groundwater levels

Parry

Mackay

Chitson

et al. 2023

Preprint

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Abstract. Hydrological drought is a serious issue globally which is likely to be amplified by 21st century climate change. In the UK, the impacts of changes in river flow and groundwater drought severity in a future of climate change and higher water demand are potentially severe. Recent publication of a new nationally-consistent set of river flow and groundwater level projections based on state-of-the-art UKCP18 climate projections offers a unique opportunity to quantitatively assess future UK hydrological drought susceptibility. The dataset includes a transient, multi-model ensemble of hydrological projections driven by a single regional climate model (RCM) for 200 catchments and 54 boreholes spanning a period from 1961 to 2080. Assessment of a baseline period (1989–2018) shows that the RCM-driven projections adequately reproduce observed river flow and groundwater level regimes, improving our confidence in using these models for assessment of future drought. Across all hydrological models and most catchments, future low river flows are projected to decline consistently out to 2080. Drought durations, intensities and severities are all projected to increase in most UK catchments. However, the trajectory of low groundwater levels and groundwater drought characteristics diverge from those of river flows. Whilst groundwater levels at most boreholes are projected to decline (consistent with river flows), the majority of boreholes show <10 % reduction in transient low groundwater levels by 2080 and eight show moderate increases. Groundwater drought characteristics in the far future (2050–2079) are often similar to those of the baseline (1989–2018), and in some instances droughts are projected to be most prolonged and severe in the near future (2020–2049). A number of explanatory factors for this divergence are discussed. The sensitivity to seasonal changes in precipitation and potential evapotranspiration is proposed as a principal driver of divergence because low river flows are more influenced by shorter-term rainfall deficits in the summer half-year, whilst groundwater drought appears to be offset somewhat by the wetter winter signal in the RCM projections. Our results have fundamental importance for water management, demonstrating a widespread increase in river flow drought severity and diminishing low flows that could have profound societal and environmental impacts unless mitigated. Furthermore, the divergence in projections of drought in river flows and groundwater levels brings into question the balance between surface and subsurface water resources. The projected contrast in fortunes of surface and subsurface water resources identified for the UK may be replicated in other parts of the world where climate projections suggest a shift towards drier summers and wetter winters.

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Section: Groundwater Levelssupporting

confidence: 92%

“…Figures 4 and 5). In common with many studies based on an RCM ensemble, the climatologies provided may not be fully representative of low likelihood, high impact events, for which storyline methodologies may be more useful (Chan et al 2022).…”

Section: Rcm Uncertainty In Future Projectionsmentioning

confidence: 99%

Divergent future drought projections in UK river flows and groundwater levels

Parry

Mackay

Chitson

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…As previously highlighted, the most extreme hydrological events identified here tend to occur before the availability of digital discharge records and, therefore, offer new insight into the range of variability in drought characteristics. Recent research is highlighting the utility of storylines (plausible changes to the factors that impacted the unfolding of past events) for informing adaptation to credible extreme events (Shepherd et al ., 2018); others have used such approaches to evaluate how extreme drought events may change in a warmer world (e.g., Chan et al ., 2021). Our work provides a foundation for such approaches to adaptation planning across Irish catchments.…”

Section: Discussionmentioning

confidence: 99%

Historical droughts in Irish catchments 1767–2016

O’Connor

Murphy

Matthews

et al. 2022

Intl Journal of Climatology

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Recent prolonged dry periods in summer 2018 and spring 2020 have reawakened interest in drought in Ireland, prompting questions regarding historical drought occurrence and potential long‐term risks. Employing 250 years of monthly precipitation and flow reconstructions, we investigate historical drought in Irish catchments evaluating the characteristics (number of events, duration, and deficits) of moderate, severe, and extreme droughts as well as the propagation of meteorological to hydrological drought. Using standardized indices, we identify three distinct catchment types. Cluster 1 catchments, located in the wetter northwest are characterized by small areas, low groundwater storage, and the highest frequency of hydrological drought relative to other catchments. Cluster 3 catchments, located in the drier east and southeast have larger areas, greater groundwater storage, the highest frequency of meteorological drought but the least hydrological droughts. However, once established, droughts in Cluster 3 tend to be more persistent with large accumulated deficits. Cluster 2 catchments, located in the southwest and west, are intermediate to Clusters 1 and 3, with hydrological droughts typically of shorter durations, reduced accumulated deficits but greater mean deficits. The most extreme droughts based on accumulated deficits across all catchments occurred in 1803–1806, 1854–1859, 1933–1935, 1944–1945, 1953–1954, and 1975–1977. Although not as severe, droughts in 1887–1888, 1891–1894, and 1971–1974 also appear as significant extremes. Changes in drought characteristics reveal a complex picture with the direction, magnitude, and significance of trends dependent on the accumulation period used to define drought, the period of record analysed, and the reference period used to standardize indices. Of particular note is a tendency towards shorter, more intense meteorological and hydrological droughts. Our findings offer important insight for drought and water management in Ireland given the paucity of extreme droughts in short observed river flow records.

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“…Finally, we need move towards what we refer to as 'impact-based drought prediction' by linking our drought forecasting tools with drought impact assessment models. Storyline-based concepts [194,195] especially when centred on actual or even expected drought impacts can be the first step toward developing impact-based drought prediction models. We acknowledge that our current drought prediction models are far from ideal and have limited long-range predictability.…”

Section: Final Remarksmentioning

confidence: 99%

Status and prospects for drought forecasting: opportunities in artificial intelligence and hybrid physical–statistical forecasting

AghaKouchak

Pan

Mazdiyasni

et al. 2022

Phil. Trans. R. Soc. A.

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Despite major improvements in weather and climate modelling and substantial increases in remotely sensed observations, drought prediction remains a major challenge. After a review of the existing methods, we discuss major research gaps and opportunities to improve drought prediction. We argue that current approaches are top-down, assuming that the process(es) and/or driver(s) are known—i.e. starting with a model and then imposing it on the observed events (reality). With the help of an experiment, we show that there are opportunities to develop bottom-up drought prediction models—i.e. starting from the reality (here, observed events) and searching for model(s) and driver(s) that work. Recent advances in artificial intelligence and machine learning provide significant opportunities for developing bottom-up drought forecasting models. Regardless of the type of drought forecasting model (e.g. machine learning, dynamical simulations, analogue based), we need to shift our attention to robustness of theories and outputs rather than event-based verification. A shift in our focus towards quantifying the stability of uncertainty in drought prediction models, rather than the goodness of fit or reproducing the past, could be the first step towards this goal. Finally, we highlight the advantages of hybrid dynamical and statistical models for improving current drought prediction models. This article is part of the Royal Society Science+ meeting issue ‘Drought risk in the Anthropocene’.

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Storylines of UK drought based on the 2010–2012 event

Cited by 18 publications

References 88 publications

Divergent future drought projections in UK river flows and groundwater levels

Divergent future drought projections in UK river flows and groundwater levels

Historical droughts in Irish catchments 1767–2016

Status and prospects for drought forecasting: opportunities in artificial intelligence and hybrid physical–statistical forecasting

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