Articles | Volume 27, issue 5
https://doi.org/10.5194/hess-27-1151-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-27-1151-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Mar 2023
Research article |
| 16 Mar 2023
| 16 Mar 2023
Projected changes in droughts and extreme droughts in Great Britain strongly influenced by the choice of drought index
Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, UK
Timothy J. Osborn
Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, UK
Water Security Research Centre, University of East Anglia, Norwich, UK
Nans Addor
Geography, College of Life and Environmental Sciences, University of Exeter, Exeter, UK
Geoff Darch
Anglian Water Ltd., Huntingdon, UK
Related authors
Nele Reyniers, Qianyu Zha, Nans Addor, Timothy J. Osborn, Nicole Forstenhäusler, and Yi He
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-132, https://doi.org/10.5194/essd-2024-132, 2024
Preprint under review for ESSD
Short summary
Short summary
We present two sets of bias-corrected UK Climate Projections 2018 (UKCP18) regional projections of temperature, precipitation and potential evapotranspiration for 1981–2080. All 12 members of the UKCP18 regional ensemble were bias-corrected using (1) empirical quantile mapping and (2) a change-preserving variant. The two methods were evaluated and compared to guide dataset application. The datasets improve the usability of UKCP18 and serve as a reference for selecting bias correction methods.
Nele Reyniers, Qianyu Zha, Nans Addor, Timothy J. Osborn, Nicole Forstenhäusler, and Yi He
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-132, https://doi.org/10.5194/essd-2024-132, 2024
Preprint under review for ESSD
Short summary
Short summary
We present two sets of bias-corrected UK Climate Projections 2018 (UKCP18) regional projections of temperature, precipitation and potential evapotranspiration for 1981–2080. All 12 members of the UKCP18 regional ensemble were bias-corrected using (1) empirical quantile mapping and (2) a change-preserving variant. The two methods were evaluated and compared to guide dataset application. The datasets improve the usability of UKCP18 and serve as a reference for selecting bias correction methods.
Wilson C. H. Chan, Nigel W. Arnell, Geoff Darch, Katie Facer-Childs, Theodore G. Shepherd, and Maliko Tanguy
Nat. Hazards Earth Syst. Sci., 24, 1065–1078, https://doi.org/10.5194/nhess-24-1065-2024, https://doi.org/10.5194/nhess-24-1065-2024, 2024
Short summary
Short summary
The most recent drought in the UK was declared in summer 2022. We pooled a large sample of plausible winters from seasonal hindcasts and grouped them into four clusters based on their atmospheric circulation configurations. Drought storylines representative of what the drought could have looked like if winter 2022/23 resembled each winter circulation storyline were created to explore counterfactuals of how bad the 2022 drought could have been over winter 2022/23 and beyond.
Marvin Höge, Martina Kauzlaric, Rosi Siber, Ursula Schönenberger, Pascal Horton, Jan Schwanbeck, Marius Günter Floriancic, Daniel Viviroli, Sibylle Wilhelm, Anna E. Sikorska-Senoner, Nans Addor, Manuela Brunner, Sandra Pool, Massimiliano Zappa, and Fabrizio Fenicia
Earth Syst. Sci. Data, 15, 5755–5784, https://doi.org/10.5194/essd-15-5755-2023, https://doi.org/10.5194/essd-15-5755-2023, 2023
Short summary
Short summary
CAMELS-CH is an open large-sample hydro-meteorological data set that covers 331 catchments in hydrologic Switzerland from 1 January 1981 to 31 December 2020. It comprises (a) daily data of river discharge and water level as well as meteorologic variables like precipitation and temperature; (b) yearly glacier and land cover data; (c) static attributes of, e.g, topography or human impact; and (d) catchment delineations. CAMELS-CH enables water and climate research and modeling at catchment level.
Wilson C. H. Chan, Theodore G. Shepherd, Katie Facer-Childs, Geoff Darch, and Nigel W. Arnell
Hydrol. Earth Syst. Sci., 26, 1755–1777, https://doi.org/10.5194/hess-26-1755-2022, https://doi.org/10.5194/hess-26-1755-2022, 2022
Short summary
Short summary
We select the 2010–2012 UK drought and investigate an alternative unfolding of the drought from changes to its attributes. We created storylines of drier preconditions, alternative seasonal contributions, a third dry winter, and climate change. Storylines of the 2010–2012 drought show alternative situations that could have resulted in worse conditions than observed. Event-based storylines exploring plausible situations are used that may lead to high impacts and help stress test existing systems.
Andrew J. Newman, Amanda G. Stone, Manabendra Saharia, Kathleen D. Holman, Nans Addor, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 25, 5603–5621, https://doi.org/10.5194/hess-25-5603-2021, https://doi.org/10.5194/hess-25-5603-2021, 2021
Short summary
Short summary
This study assesses methods that estimate flood return periods to identify when we would obtain a large flood return estimate change if the method or input data were changed (sensitivities). We include an examination of multiple flood-generating models, which is a novel addition to the flood estimation literature. We highlight the need to select appropriate flood models for the study watershed. These results will help operational water agencies develop more robust risk assessments.
Peter T. La Follette, Adriaan J. Teuling, Nans Addor, Martyn Clark, Koen Jansen, and Lieke A. Melsen
Hydrol. Earth Syst. Sci., 25, 5425–5446, https://doi.org/10.5194/hess-25-5425-2021, https://doi.org/10.5194/hess-25-5425-2021, 2021
Short summary
Short summary
Hydrological models are useful tools that allow us to predict distributions and movement of water. A variety of numerical methods are used by these models. We demonstrate which numerical methods yield large errors when subject to extreme precipitation. As the climate is changing such that extreme precipitation is more common, we find that some numerical methods are better suited for use in hydrological models. Also, we find that many current hydrological models use relatively inaccurate methods.
John P. Bloomfield, Mengyi Gong, Benjamin P. Marchant, Gemma Coxon, and Nans Addor
Hydrol. Earth Syst. Sci., 25, 5355–5379, https://doi.org/10.5194/hess-25-5355-2021, https://doi.org/10.5194/hess-25-5355-2021, 2021
Short summary
Short summary
Groundwater provides flow, known as baseflow, to surface streams and rivers. It is important as it sustains the flow of many rivers at times of water stress. However, it may be affected by water management practices. Statistical models have been used to show that abstraction of groundwater may influence baseflow. Consequently, it is recommended that information on groundwater abstraction is included in future assessments and predictions of baseflow.
Keirnan J. A. Fowler, Suwash Chandra Acharya, Nans Addor, Chihchung Chou, and Murray C. Peel
Earth Syst. Sci. Data, 13, 3847–3867, https://doi.org/10.5194/essd-13-3847-2021, https://doi.org/10.5194/essd-13-3847-2021, 2021
Short summary
Short summary
This paper presents the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS comprises data for 222 unregulated catchments with long-term monitoring, combining hydrometeorological time series (streamflow and 18 climatic variables) with 134 attributes related to geology, soil, topography, land cover, anthropogenic influence and hydroclimatology. It is freely downloadable from https://doi.pangaea.de/10.1594/PANGAEA.921850.
Peter Uhe, Daniel Mitchell, Paul D. Bates, Nans Addor, Jeff Neal, and Hylke E. Beck
Geosci. Model Dev., 14, 4865–4890, https://doi.org/10.5194/gmd-14-4865-2021, https://doi.org/10.5194/gmd-14-4865-2021, 2021
Short summary
Short summary
We present a cascade of models to compute high-resolution river flooding. This takes meteorological inputs, e.g., rainfall and temperature from observations or climate models, and takes them through a series of modeling steps. This is relevant to evaluating current day and future flood risk and impacts. The model framework uses global data sets, allowing it to be applied anywhere in the world.
Gemma Coxon, Nans Addor, John P. Bloomfield, Jim Freer, Matt Fry, Jamie Hannaford, Nicholas J. K. Howden, Rosanna Lane, Melinda Lewis, Emma L. Robinson, Thorsten Wagener, and Ross Woods
Earth Syst. Sci. Data, 12, 2459–2483, https://doi.org/10.5194/essd-12-2459-2020, https://doi.org/10.5194/essd-12-2459-2020, 2020
Short summary
Short summary
We present the first large-sample catchment hydrology dataset for Great Britain. The dataset collates river flows, catchment attributes, and catchment boundaries for 671 catchments across Great Britain. We characterise the topography, climate, streamflow, land cover, soils, hydrogeology, human influence, and discharge uncertainty of each catchment. The dataset is publicly available for the community to use in a wide range of environmental and modelling analyses.
Vinícius B. P. Chagas, Pedro L. B. Chaffe, Nans Addor, Fernando M. Fan, Ayan S. Fleischmann, Rodrigo C. D. Paiva, and Vinícius A. Siqueira
Earth Syst. Sci. Data, 12, 2075–2096, https://doi.org/10.5194/essd-12-2075-2020, https://doi.org/10.5194/essd-12-2075-2020, 2020
Short summary
Short summary
We present a new dataset for large-sample hydrological studies in Brazil. The dataset encompasses daily observed streamflow from 3679 gauges, as well as meteorological forcing for 897 selected catchments. It also includes 65 attributes covering topographic, climatic, hydrologic, land cover, geologic, soil, and human intervention variables. CAMELS-BR is publicly available and will enable new insights into the hydrological behavior of catchments in Brazil.
Kirsti Hakala, Nans Addor, Thibault Gobbe, Johann Ruffieux, and Jan Seibert
Hydrol. Earth Syst. Sci., 24, 3815–3833, https://doi.org/10.5194/hess-24-3815-2020, https://doi.org/10.5194/hess-24-3815-2020, 2020
Short summary
Short summary
Under a changing climate, reliable information on future hydrological conditions is necessary to inform water resource management. Here, we collaborated with a hydropower company that selected streamflow and energy demand indices. Using these indices, we identified stakeholder needs and used this to tailor the production of our climate change impact projections. We show that opportunities and risks for a hydropower company depend on a range of factors beyond those covered by traditional studies.
Satyaban B. Ratna, Timothy J. Osborn, Manoj Joshi, Bao Yang, and Jianglin Wang
Clim. Past, 15, 1825–1844, https://doi.org/10.5194/cp-15-1825-2019, https://doi.org/10.5194/cp-15-1825-2019, 2019
Short summary
Short summary
We examine the relationships in models and reconstructions between multidecadal variability of East Asian temperature and two extratropical modes of variability. The relationship between East Asian temperature and Pacific multidecadal variability is largely driven by internal variability, whereas with Atlantic multidecadal variability it is more strongly influenced by the presence or absence of external forcing. We discuss the implications for diagnosing teleconnections from reconstructions.
Camila Alvarez-Garreton, Pablo A. Mendoza, Juan Pablo Boisier, Nans Addor, Mauricio Galleguillos, Mauricio Zambrano-Bigiarini, Antonio Lara, Cristóbal Puelma, Gonzalo Cortes, Rene Garreaud, James McPhee, and Alvaro Ayala
Hydrol. Earth Syst. Sci., 22, 5817–5846, https://doi.org/10.5194/hess-22-5817-2018, https://doi.org/10.5194/hess-22-5817-2018, 2018
Short summary
Short summary
CAMELS-CL provides a catchment dataset in Chile, including 516 catchment boundaries, hydro-meteorological time series, and 70 catchment attributes quantifying catchments' climatic, hydrological, topographic, geological, land cover and anthropic intervention features. By using CAMELS-CL, we characterise hydro-climatic regional variations, assess precipitation and potential evapotranspiration uncertainties, and analyse human intervention impacts on catchment response.
Conor Murphy, Ciaran Broderick, Timothy P. Burt, Mary Curley, Catriona Duffy, Julia Hall, Shaun Harrigan, Tom K. R. Matthews, Neil Macdonald, Gerard McCarthy, Mark P. McCarthy, Donal Mullan, Simon Noone, Timothy J. Osborn, Ciara Ryan, John Sweeney, Peter W. Thorne, Seamus Walsh, and Robert L. Wilby
Clim. Past, 14, 413–440, https://doi.org/10.5194/cp-14-413-2018, https://doi.org/10.5194/cp-14-413-2018, 2018
Short summary
Short summary
This work reconstructs a continuous 305-year rainfall record for Ireland. The series reveals remarkable variability in decadal rainfall – far in excess of the typical period of digitised data. Notably, the series sheds light on exceptionally wet winters in the 1730s and wet summers in the 1750s. The derived record, one of the longest continuous series in Europe, offers a firm basis for benchmarking other long-term records and reconstructions of past climate both locally and across Europe.
Lieke A. Melsen, Nans Addor, Naoki Mizukami, Andrew J. Newman, Paul J. J. F. Torfs, Martyn P. Clark, Remko Uijlenhoet, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 22, 1775–1791, https://doi.org/10.5194/hess-22-1775-2018, https://doi.org/10.5194/hess-22-1775-2018, 2018
Short summary
Short summary
Long-term hydrological predictions are important for water management planning, but are also prone to uncertainty. This study investigates three sources of uncertainty for long-term hydrological predictions in the US: climate models, hydrological models, and hydrological model parameters. Mapping the results revealed spatial patterns in the three sources of uncertainty: different sources of uncertainty dominate in different regions.
Nans Addor, Andrew J. Newman, Naoki Mizukami, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, https://doi.org/10.5194/hess-21-5293-2017, 2017
Short summary
Short summary
We introduce a data set describing the landscape of 671 catchments in the contiguous USA: we synthesized various data sources to characterize the topography, climate, streamflow, land cover, soil, and geology of each catchment. This extends the daily time series of meteorological forcing and discharge provided by an earlier study. The diversity of these catchments will help to improve our understanding and modeling of how the interplay between catchment attributes shapes hydrological processes.
T. J. Osborn and P. D. Jones
Earth Syst. Sci. Data, 6, 61–68, https://doi.org/10.5194/essd-6-61-2014, https://doi.org/10.5194/essd-6-61-2014, 2014
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Mathematical applications
Using statistical models to depict the response of multi-timescale drought to forest cover change across climate zones
Past, present and future rainfall erosivity in central Europe based on convection-permitting climate simulations
The most extreme rainfall erosivity event ever recorded in China up to 2022: the 7.20 storm in Henan Province
The role of atmospheric rivers in the distribution of heavy precipitation events over North America
Study on a mother wavelet optimization framework based on change-point detection of hydrological time series
Atmospheric water transport connectivity within and between ocean basins and land
Technical Note: Space–time statistical quality control of extreme precipitation observations
The relative importance of antecedent soil moisture and precipitation in flood generation in the middle and lower Yangtze River basin
Rainfall pattern analysis in 24 East Asian megacities using a complex network
Comparison between canonical vine copulas and a meta-Gaussian model for forecasting agricultural drought over China
Analysis of flash droughts in China using machine learning
Performance-based comparison of regionalization methods to improve the at-site estimates of daily precipitation
The use of personal weather station observations to improve precipitation estimation and interpolation
The 2018 northern European hydrological drought and its drivers in a historical perspective
Assimilating shallow soil moisture observations into land models with a water budget constraint
Emerging climate signals in the Lena River catchment: a non-parametric statistical approach
Near-0 °C surface temperature and precipitation type patterns across Canada
A universal multifractal approach to assessment of spatiotemporal extreme precipitation over the Loess Plateau of China
Significant spatial patterns from the GCM seasonal forecasts of global precipitation
Bayesian performance evaluation of evapotranspiration models based on eddy covariance systems in an arid region
Technical note: An improved Grassberger–Procaccia algorithm for analysis of climate system complexity
The influence of long-term changes in canopy structure on rainfall interception loss: a case study in Speulderbos, the Netherlands
Geostatistical assessment of warm-season precipitation observations in Korea based on the composite precipitation and satellite water vapor data
Investigating water budget dynamics in 18 river basins across the Tibetan Plateau through multiple datasets
Does the GPM mission improve the systematic error component in satellite rainfall estimates over TRMM? An evaluation at a pan-India scale
Assessment of an ensemble seasonal streamflow forecasting system for Australia
Technical note: Combining quantile forecasts and predictive distributions of streamflows
Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes
Temporal and spatial changes of rainfall and streamflow in the Upper Tekezē–Atbara river basin, Ethiopia
Seasonal streamflow forecasting by conditioning climatology with precipitation indices
Bias correcting precipitation forecasts to improve the skill of seasonal streamflow forecasts
Flood triggering in Switzerland: the role of daily to monthly preceding precipitation
Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China
Explaining and forecasting interannual variability in the flow of the Nile River
Drought severity–duration–frequency curves: a foundation for risk assessment and planning tool for ecosystem establishment in post-mining landscapes
Characterising the space–time structure of rainfall in the Sahel with a view to estimating IDAF curves
Spatial analysis of precipitation in a high-mountain region: exploring methods with multi-scale topographic predictors and circulation types
Variability of extreme precipitation over Europe and its relationships with teleconnection patterns
Drought evolution characteristics and precipitation intensity changes during alternating dry–wet changes in the Huang–Huai–Hai River basin
Structural break or long memory: an empirical survey on daily rainfall data sets across Malaysia
Calibration of aerodynamic roughness over the Tibetan Plateau with Ensemble Kalman Filter analysed heat flux
Technical Note: Downscaling RCM precipitation to the station scale using statistical transformations – a comparison of methods
Spectral representation of the annual cycle in the climate change signal
Simultaneous estimation of land surface scheme states and parameters using the ensemble Kalman filter: identical twin experiments
Downscaling of surface moisture flux and precipitation in the Ebro Valley (Spain) using analogues and analogues followed by random forests and multiple linear regression
Geostatistical radar-raingauge combination with nonparametric correlograms: methodological considerations and application in Switzerland
El Niño-Southern Oscillation and water resources in the headwaters region of the Yellow River: links and potential for forecasting
A summer climate regime over Europe modulated by the North Atlantic Oscillation
Introducing a rainfall compound distribution model based on weather patterns sub-sampling
Yan Li, Bo Huang, and Henning W. Rust
Hydrol. Earth Syst. Sci., 28, 321–339, https://doi.org/10.5194/hess-28-321-2024, https://doi.org/10.5194/hess-28-321-2024, 2024
Short summary
Short summary
The inconsistent changes in temperature and precipitation induced by forest cover change are very likely to affect drought condition. We use a set of statistical models to explore the relationship between forest cover change and drought change in different timescales and climate zones. We find that the influence of forest cover on droughts varies under different precipitation and temperature quantiles. Forest cover also could modulate the impacts of precipitation and temperature on drought.
Magdalena Uber, Michael Haller, Christoph Brendel, Gudrun Hillebrand, and Thomas Hoffmann
Hydrol. Earth Syst. Sci., 28, 87–102, https://doi.org/10.5194/hess-28-87-2024, https://doi.org/10.5194/hess-28-87-2024, 2024
Short summary
Short summary
We calculated past, present and future rainfall erosivity in central Europe from high-resolution precipitation data (3 km and 1 h) generated by the COSMO-CLM convection-permitting climate model. Future rainfall erosivity can be up to 84 % higher than it was in the past. Such increases are much higher than estimated previously from regional climate model output. Convection-permitting simulations have an enormous and, to date, unexploited potential for the calculation of future rainfall erosivity.
Yuanyuan Xiao, Shuiqing Yin, Bofu Yu, Conghui Fan, Wenting Wang, and Yun Xie
Hydrol. Earth Syst. Sci., 27, 4563–4577, https://doi.org/10.5194/hess-27-4563-2023, https://doi.org/10.5194/hess-27-4563-2023, 2023
Short summary
Short summary
An exceptionally heavy rainfall event occurred on 20 July 2021 in central China (the 7.20 storm). The storm presents a rare opportunity to examine the extreme rainfall erosivity. The storm, with an average recurrence interval of at least 10 000 years, was the largest in terms of its rainfall erosivity on record over the past 70 years in China. The study suggests that extreme erosive events can occur anywhere in eastern China and are not necessarily concentrated in low latitudes.
Sara M. Vallejo-Bernal, Frederik Wolf, Niklas Boers, Dominik Traxl, Norbert Marwan, and Jürgen Kurths
Hydrol. Earth Syst. Sci., 27, 2645–2660, https://doi.org/10.5194/hess-27-2645-2023, https://doi.org/10.5194/hess-27-2645-2023, 2023
Short summary
Short summary
Employing event synchronization and complex networks analysis, we reveal a cascade of heavy rainfall events, related to intense atmospheric rivers (ARs): heavy precipitation events (HPEs) in western North America (NA) that occur in the aftermath of land-falling ARs are synchronized with HPEs in central and eastern Canada with a delay of up to 12 d. Understanding the effects of ARs in the rainfall over NA will lead to better anticipating the evolution of the climate dynamics in the region.
Jiqing Li, Jing Huang, Lei Zheng, and Wei Zheng
Hydrol. Earth Syst. Sci., 27, 2325–2339, https://doi.org/10.5194/hess-27-2325-2023, https://doi.org/10.5194/hess-27-2325-2023, 2023
Short summary
Short summary
Under the joint action of climate–human activities the use of runoff data whose mathematical properties have changed has become the key to watershed management. To determine whether the data have been changed, the number and the location of changes, we proposed a change-point detection framework. The problem of determining the parameters of wavelet transform has been solved by comparing the accuracy of identifying change points. This study helps traditional models adapt to environmental changes.
Dipanjan Dey, Aitor Aldama Campino, and Kristofer Döös
Hydrol. Earth Syst. Sci., 27, 481–493, https://doi.org/10.5194/hess-27-481-2023, https://doi.org/10.5194/hess-27-481-2023, 2023
Short summary
Short summary
One of the most striking and robust features of climate change is the acceleration of the atmospheric water cycle branch. Earlier studies were able to provide a quantification of the global atmospheric water cycle, but they missed addressing the atmospheric water transport connectivity within and between ocean basins and land. These shortcomings were overcome in the present study and presented a complete synthesised and quantitative view of the atmospheric water cycle.
Abbas El Hachem, Jochen Seidel, Florian Imbery, Thomas Junghänel, and András Bárdossy
Hydrol. Earth Syst. Sci., 26, 6137–6146, https://doi.org/10.5194/hess-26-6137-2022, https://doi.org/10.5194/hess-26-6137-2022, 2022
Short summary
Short summary
Through this work, a methodology to identify outliers in intense precipitation data was presented. The results show the presence of several suspicious observations that strongly differ from their surroundings. Many identified outliers did not have unusually high values but disagreed with their neighboring values at the corresponding time steps. Weather radar and discharge data were used to distinguish between single events and false observations.
Qihua Ran, Jin Wang, Xiuxiu Chen, Lin Liu, Jiyu Li, and Sheng Ye
Hydrol. Earth Syst. Sci., 26, 4919–4931, https://doi.org/10.5194/hess-26-4919-2022, https://doi.org/10.5194/hess-26-4919-2022, 2022
Short summary
Short summary
This study aims to further evaluate the relative importance of antecedent soil moisture and rainfall on flood generation and the controlling factors. The relative importance of antecedent soil moisture and daily rainfall present a significant correlation with drainage area; the larger the watershed, and the more essential the antecedent soil saturation rate is in flood generation, the less important daily rainfall will be.
Kyunghun Kim, Jaewon Jung, Hung Soo Kim, Masahiko Haraguchi, and Soojun Kim
Hydrol. Earth Syst. Sci., 26, 4823–4836, https://doi.org/10.5194/hess-26-4823-2022, https://doi.org/10.5194/hess-26-4823-2022, 2022
Short summary
Short summary
This study applied a new methodology (complex network), instead of using classic methods, to establish the relationships between rainfall events in large East Asian cities. The relationships show that western China and Southeast Asia have a lot of influence on each other. Moreover, it is confirmed that the relationships arise from the effect of the East Asian monsoon. In future, complex network may be able to be applied to analyze the concurrent relationships between extreme rainfall events.
Haijiang Wu, Xiaoling Su, Vijay P. Singh, Te Zhang, Jixia Qi, and Shengzhi Huang
Hydrol. Earth Syst. Sci., 26, 3847–3861, https://doi.org/10.5194/hess-26-3847-2022, https://doi.org/10.5194/hess-26-3847-2022, 2022
Short summary
Short summary
Agricultural drought forecasting lies at the core of overall drought risk management and is critical for food security and drought early warning. Using three-dimensional scenarios, we attempted to compare the agricultural drought forecast performance of a canonical vine copula (3C-vine) model and meta-Gaussian (MG) model over China. The findings show that the 3C-vine model exhibits more skill than the MG model when using 1– to 3-month lead times for forecasting agricultural drought.
Linqi Zhang, Yi Liu, Liliang Ren, Adriaan J. Teuling, Ye Zhu, Linyong Wei, Linyan Zhang, Shanhu Jiang, Xiaoli Yang, Xiuqin Fang, and Hang Yin
Hydrol. Earth Syst. Sci., 26, 3241–3261, https://doi.org/10.5194/hess-26-3241-2022, https://doi.org/10.5194/hess-26-3241-2022, 2022
Short summary
Short summary
In this study, three machine learning methods displayed a good detection capacity of flash droughts. The RF model was recommended to estimate the depletion rate of soil moisture and simulate flash drought by considering the multiple meteorological variable anomalies in the adjacent time to drought onset. The anomalies of precipitation and potential evapotranspiration exhibited a stronger synergistic but asymmetrical effect on flash droughts compared to slowly developing droughts.
Abubakar Haruna, Juliette Blanchet, and Anne-Catherine Favre
Hydrol. Earth Syst. Sci., 26, 2797–2811, https://doi.org/10.5194/hess-26-2797-2022, https://doi.org/10.5194/hess-26-2797-2022, 2022
Short summary
Short summary
Reliable prediction of floods depends on the quality of the input data such as precipitation. However, estimation of precipitation from the local measurements is known to be difficult, especially for extremes. Regionalization improves the estimates by increasing the quantity of data available for estimation. Here, we compare three regionalization methods based on their robustness and reliability. We apply the comparison to a dense network of daily stations within and outside Switzerland.
András Bárdossy, Jochen Seidel, and Abbas El Hachem
Hydrol. Earth Syst. Sci., 25, 583–601, https://doi.org/10.5194/hess-25-583-2021, https://doi.org/10.5194/hess-25-583-2021, 2021
Short summary
Short summary
In this study, the applicability of data from private weather stations (PWS) for precipitation interpolation was investigated. Due to unknown errors and biases in these observations, a two-step filter was developed that uses indicator correlations and event-based spatial precipitation patterns. The procedure was tested and cross validated for the state of Baden-Württemberg (Germany). The biggest improvement is achieved for the shortest time aggregations.
Sigrid J. Bakke, Monica Ionita, and Lena M. Tallaksen
Hydrol. Earth Syst. Sci., 24, 5621–5653, https://doi.org/10.5194/hess-24-5621-2020, https://doi.org/10.5194/hess-24-5621-2020, 2020
Short summary
Short summary
This study provides an in-depth analysis of the 2018 northern European drought. Large parts of the region experienced 60-year record-breaking temperatures, linked to high-pressure systems and warm surrounding seas. Meteorological drought developed from May and, depending on local conditions, led to extreme low flows and groundwater drought in the following months. The 2018 event was unique in that it affected most of Fennoscandia as compared to previous droughts.
Bo Dan, Xiaogu Zheng, Guocan Wu, and Tao Li
Hydrol. Earth Syst. Sci., 24, 5187–5201, https://doi.org/10.5194/hess-24-5187-2020, https://doi.org/10.5194/hess-24-5187-2020, 2020
Short summary
Short summary
Data assimilation is a procedure to generate an optimal combination of the state variable in geoscience, based on the model outputs and observations. The ensemble Kalman filter (EnKF) scheme is a widely used assimilation method in soil moisture estimation. This study proposed several modifications of EnKF for improving this assimilation. The study shows that the quality of the assimilation result is improved, while the degree of water budget imbalance is reduced.
Eric Pohl, Christophe Grenier, Mathieu Vrac, and Masa Kageyama
Hydrol. Earth Syst. Sci., 24, 2817–2839, https://doi.org/10.5194/hess-24-2817-2020, https://doi.org/10.5194/hess-24-2817-2020, 2020
Short summary
Short summary
Existing approaches to quantify the emergence of climate change require several user choices that make these approaches less objective. We present an approach that uses a minimum number of choices and showcase its application in the extremely sensitive, permafrost-dominated region of eastern Siberia. Designed as a Python toolbox, it allows for incorporating climate model, reanalysis, and in situ data to make use of numerous existing data sources and reduce uncertainties in obtained estimates.
Eva Mekis, Ronald E. Stewart, Julie M. Theriault, Bohdan Kochtubajda, Barrie R. Bonsal, and Zhuo Liu
Hydrol. Earth Syst. Sci., 24, 1741–1761, https://doi.org/10.5194/hess-24-1741-2020, https://doi.org/10.5194/hess-24-1741-2020, 2020
Short summary
Short summary
This article provides a Canada-wide analysis of near-0°C temperature conditions (±2°C) using hourly surface temperature and precipitation type observations from 92 locations for the 1981–2011 period. Higher annual occurrences were found in Atlantic Canada, although high values also occur in other regions. Trends of most indicators show little or no change despite a systematic warming over Canada. A higher than expected tendency for near-0°C conditions was also found at some stations.
Jianjun Zhang, Guangyao Gao, Bojie Fu, Cong Wang, Hoshin V. Gupta, Xiaoping Zhang, and Rui Li
Hydrol. Earth Syst. Sci., 24, 809–826, https://doi.org/10.5194/hess-24-809-2020, https://doi.org/10.5194/hess-24-809-2020, 2020
Short summary
Short summary
We proposed an approach that integrates universal multifractals and a segmentation algorithm to precisely identify extreme precipitation (EP) and assess spatiotemporal EP variation over the Loess Plateau, using daily data. Our results explain how EP contributes to the widely distributed severe natural hazards. These findings are of great significance for ecological management in the Loess Plateau. Our approach is also helpful for spatiotemporal EP assessment at the regional scale.
Tongtiegang Zhao, Wei Zhang, Yongyong Zhang, Zhiyong Liu, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 24, 1–16, https://doi.org/10.5194/hess-24-1-2020, https://doi.org/10.5194/hess-24-1-2020, 2020
Guoxiao Wei, Xiaoying Zhang, Ming Ye, Ning Yue, and Fei Kan
Hydrol. Earth Syst. Sci., 23, 2877–2895, https://doi.org/10.5194/hess-23-2877-2019, https://doi.org/10.5194/hess-23-2877-2019, 2019
Short summary
Short summary
Accurately evaluating evapotranspiration (ET) is a critical challenge in improving hydrological process modeling. Here we evaluated four ET models (PM, SW, PT–FC, and AA) under the Bayesian framework. Our results reveal that the SW model has the best performance. This is in part because the SW model captures the main physical mechanism in ET; the other part is that the key parameters, such as the extinction factor, could be well constrained with observation data.
Chongli Di, Tiejun Wang, Xiaohua Yang, and Siliang Li
Hydrol. Earth Syst. Sci., 22, 5069–5079, https://doi.org/10.5194/hess-22-5069-2018, https://doi.org/10.5194/hess-22-5069-2018, 2018
Short summary
Short summary
The original Grassberger–Procaccia algorithm for complex analysis was modified by incorporating the normal-based K-means clustering technique and the RANSAC algorithm. The calculation accuracy of the proposed method was shown to outperform traditional algorithms. The proposed algorithm was used to diagnose climate system complexity in the Hai He basin. The spatial patterns of the complexity of precipitation and air temperature reflected the influence of the dominant climate system.
César Cisneros Vaca, Christiaan van der Tol, and Chandra Prasad Ghimire
Hydrol. Earth Syst. Sci., 22, 3701–3719, https://doi.org/10.5194/hess-22-3701-2018, https://doi.org/10.5194/hess-22-3701-2018, 2018
Short summary
Short summary
The influence of long-term changes in canopy structure on rainfall interception loss was studied in a 55-year old forest. Interception loss was similar at the same site (38 %), when the forest was 29 years old. In the past, the forest was denser and had a higher storage capacity, but the evaporation rates were lower. We emphasize the importance of quantifying downward sensible heat flux and heat release from canopy biomass in tall forest in order to improve the quantification of evaporation.
Sojung Park, Seon Ki Park, Jeung Whan Lee, and Yunho Park
Hydrol. Earth Syst. Sci., 22, 3435–3452, https://doi.org/10.5194/hess-22-3435-2018, https://doi.org/10.5194/hess-22-3435-2018, 2018
Short summary
Short summary
Understanding the precipitation characteristics is essential to design an optimal observation network. We studied the spatial and temporal characteristics of summertime precipitation systems in Korea via geostatistical analyses on the ground-based precipitation and satellite water vapor data. We found that, under a strict standard, an observation network with higher resolution is required in local areas with frequent heavy rainfalls, depending on directional features of precipitation systems.
Wenbin Liu, Fubao Sun, Yanzhong Li, Guoqing Zhang, Yan-Fang Sang, Wee Ho Lim, Jiahong Liu, Hong Wang, and Peng Bai
Hydrol. Earth Syst. Sci., 22, 351–371, https://doi.org/10.5194/hess-22-351-2018, https://doi.org/10.5194/hess-22-351-2018, 2018
Short summary
Short summary
The dynamics of basin-scale water budgets over the Tibetan Plateau (TP) are not well understood nowadays due to the lack of hydro-climatic observations. In this study, we investigate seasonal cycles and trends of water budget components (e.g. precipitation P, evapotranspiration ET and runoff Q) in 18 TP river basins during the period 1982–2011 through the use of multi-source datasets (e.g. in situ observations, satellite retrievals, reanalysis outputs and land surface model simulations).
Harsh Beria, Trushnamayee Nanda, Deepak Singh Bisht, and Chandranath Chatterjee
Hydrol. Earth Syst. Sci., 21, 6117–6134, https://doi.org/10.5194/hess-21-6117-2017, https://doi.org/10.5194/hess-21-6117-2017, 2017
Short summary
Short summary
High-quality satellite precipitation forcings have provided a viable alternative to hydrologic modeling in data-scarce regions. Ageing TRMM sensors have recently been upgraded to GPM, promising enhanced spatio-temporal resolutions. Statistical and hydrologic evaluation of GPM measurements across 86 Indian river basins revealed improved low rainfall estimates with reduced effects of climatology and topography.
James C. Bennett, Quan J. Wang, David E. Robertson, Andrew Schepen, Ming Li, and Kelvin Michael
Hydrol. Earth Syst. Sci., 21, 6007–6030, https://doi.org/10.5194/hess-21-6007-2017, https://doi.org/10.5194/hess-21-6007-2017, 2017
Short summary
Short summary
We assess a new streamflow forecasting system in Australia. The system is designed to meet the need of water agencies for 12-month forecasts. The forecasts perform well in a wide range of rivers. Forecasts for shorter periods (up to 6 months) are generally informative. Forecasts sometimes did not perform well in a few very dry rivers. We test several techniques for improving streamflow forecasts in drylands, with mixed success.
Konrad Bogner, Katharina Liechti, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 21, 5493–5502, https://doi.org/10.5194/hess-21-5493-2017, https://doi.org/10.5194/hess-21-5493-2017, 2017
Short summary
Short summary
The enhanced availability of many different weather prediction systems nowadays makes it very difficult for flood and water resource managers to choose the most reliable and accurate forecast. In order to circumvent this problem of choice, different approaches for combining this information have been applied at the Sihl River (CH) and the results have been verified. The outcome of this study highlights the importance of forecast combination in order to improve the quality of forecast systems.
Matthew B. Switanek, Peter A. Troch, Christopher L. Castro, Armin Leuprecht, Hsin-I Chang, Rajarshi Mukherjee, and Eleonora M. C. Demaria
Hydrol. Earth Syst. Sci., 21, 2649–2666, https://doi.org/10.5194/hess-21-2649-2017, https://doi.org/10.5194/hess-21-2649-2017, 2017
Short summary
Short summary
The commonly used bias correction method called quantile mapping assumes a constant function of error correction values between modeled and observed distributions. Our article finds that this function cannot be assumed to be constant. We propose a new bias correction method, called scaled distribution mapping, that does not rely on this assumption. Furthermore, the proposed method more explicitly accounts for the frequency of rain days and the likelihood of individual events.
Tesfay G. Gebremicael, Yasir A. Mohamed, Pieter v. Zaag, and Eyasu Y. Hagos
Hydrol. Earth Syst. Sci., 21, 2127–2142, https://doi.org/10.5194/hess-21-2127-2017, https://doi.org/10.5194/hess-21-2127-2017, 2017
Short summary
Short summary
This study was conducted to understand the spatio-temporal variations of streamflow in the Tekezē basin. Results showed rainfall over the basin did not significantly change. However, streamflow experienced high variabilities at seasonal and annual scales. Further studies are needed to verify hydrological changes by identifying the physical mechanisms behind those changes. Findings are useful as prerequisite for studying the effects of catchment management dynamics on the hydrological processes.
Louise Crochemore, Maria-Helena Ramos, Florian Pappenberger, and Charles Perrin
Hydrol. Earth Syst. Sci., 21, 1573–1591, https://doi.org/10.5194/hess-21-1573-2017, https://doi.org/10.5194/hess-21-1573-2017, 2017
Short summary
Short summary
The use of general circulation model outputs for streamflow forecasting has developed in the last decade. In parallel, traditional streamflow forecasting is commonly based on historical data. This study investigates the impact of conditioning historical data based on circulation model precipitation forecasts on seasonal streamflow forecast quality. Results highlighted a trade-off between the sharpness and reliability of forecasts.
Louise Crochemore, Maria-Helena Ramos, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 20, 3601–3618, https://doi.org/10.5194/hess-20-3601-2016, https://doi.org/10.5194/hess-20-3601-2016, 2016
Short summary
Short summary
This study investigates the way bias correcting precipitation forecasts can improve the skill of streamflow forecasts at extended lead times. Eight variants of bias correction approaches based on the linear scaling and the distribution mapping methods are applied to the precipitation forecasts prior to generating the streamflow forecasts. One of the main results of the study is that distribution mapping of daily values is successful in improving forecast reliability.
P. Froidevaux, J. Schwanbeck, R. Weingartner, C. Chevalier, and O. Martius
Hydrol. Earth Syst. Sci., 19, 3903–3924, https://doi.org/10.5194/hess-19-3903-2015, https://doi.org/10.5194/hess-19-3903-2015, 2015
Short summary
Short summary
We investigate precipitation characteristics prior to 4000 annual floods in Switzerland since 1961. The floods were preceded by heavy precipitation, but in most catchments extreme precipitation occurred only during the last 3 days prior to the flood events. Precipitation sums for earlier time periods (like e.g. 4-14 days prior to floods) were mostly average and do not correlate with the return period of the floods.
G. H. Fang, J. Yang, Y. N. Chen, and C. Zammit
Hydrol. Earth Syst. Sci., 19, 2547–2559, https://doi.org/10.5194/hess-19-2547-2015, https://doi.org/10.5194/hess-19-2547-2015, 2015
Short summary
Short summary
This study compares the effects of five precipitation and three temperature correction methods on precipitation, temperature, and streamflow through loosely coupling RCM (RegCM) and a distributed hydrological model (SWAT) in terms of frequency-based indices and time-series-based indices. The methodology and results can be used for other regions and other RCM and hydrologic models, and for impact studies of climate change on water resources at a regional scale.
M. S. Siam and E. A. B. Eltahir
Hydrol. Earth Syst. Sci., 19, 1181–1192, https://doi.org/10.5194/hess-19-1181-2015, https://doi.org/10.5194/hess-19-1181-2015, 2015
Short summary
Short summary
This paper explains the different natural modes of interannual variability in the flow of the Nile River and also presents a new index based on the sea surface temperature (SST) over the southern Indian Ocean to forecast the flow of the Nile River. It also presents a new hybrid forecasting algorithm that can be used to predict the Nile flow based on indices of the SST in the eastern Pacific and southern Indian oceans.
D. Halwatura, A. M. Lechner, and S. Arnold
Hydrol. Earth Syst. Sci., 19, 1069–1091, https://doi.org/10.5194/hess-19-1069-2015, https://doi.org/10.5194/hess-19-1069-2015, 2015
G. Panthou, T. Vischel, T. Lebel, G. Quantin, and G. Molinié
Hydrol. Earth Syst. Sci., 18, 5093–5107, https://doi.org/10.5194/hess-18-5093-2014, https://doi.org/10.5194/hess-18-5093-2014, 2014
D. Masson and C. Frei
Hydrol. Earth Syst. Sci., 18, 4543–4563, https://doi.org/10.5194/hess-18-4543-2014, https://doi.org/10.5194/hess-18-4543-2014, 2014
Short summary
Short summary
The question of how to utilize information from the physiography/topography in the spatial interpolation of rainfall is a long-standing discussion in the literature. In this study we test ideas that go beyond the approach in popular interpolation schemes today. The key message of our study is that these ideas can at best marginally improve interpolation accuracy, even in a region where a clear benefit would intuitively be expected.
A. Casanueva, C. Rodríguez-Puebla, M. D. Frías, and N. González-Reviriego
Hydrol. Earth Syst. Sci., 18, 709–725, https://doi.org/10.5194/hess-18-709-2014, https://doi.org/10.5194/hess-18-709-2014, 2014
D. H. Yan, D. Wu, R. Huang, L. N. Wang, and G. Y. Yang
Hydrol. Earth Syst. Sci., 17, 2859–2871, https://doi.org/10.5194/hess-17-2859-2013, https://doi.org/10.5194/hess-17-2859-2013, 2013
F. Yusof, I. L. Kane, and Z. Yusop
Hydrol. Earth Syst. Sci., 17, 1311–1318, https://doi.org/10.5194/hess-17-1311-2013, https://doi.org/10.5194/hess-17-1311-2013, 2013
J. H. Lee, J. Timmermans, Z. Su, and M. Mancini
Hydrol. Earth Syst. Sci., 16, 4291–4302, https://doi.org/10.5194/hess-16-4291-2012, https://doi.org/10.5194/hess-16-4291-2012, 2012
L. Gudmundsson, J. B. Bremnes, J. E. Haugen, and T. Engen-Skaugen
Hydrol. Earth Syst. Sci., 16, 3383–3390, https://doi.org/10.5194/hess-16-3383-2012, https://doi.org/10.5194/hess-16-3383-2012, 2012
T. Bosshard, S. Kotlarski, T. Ewen, and C. Schär
Hydrol. Earth Syst. Sci., 15, 2777–2788, https://doi.org/10.5194/hess-15-2777-2011, https://doi.org/10.5194/hess-15-2777-2011, 2011
S. Nie, J. Zhu, and Y. Luo
Hydrol. Earth Syst. Sci., 15, 2437–2457, https://doi.org/10.5194/hess-15-2437-2011, https://doi.org/10.5194/hess-15-2437-2011, 2011
G. Ibarra-Berastegi, J. Saénz, A. Ezcurra, A. Elías, J. Diaz Argandoña, and I. Errasti
Hydrol. Earth Syst. Sci., 15, 1895–1907, https://doi.org/10.5194/hess-15-1895-2011, https://doi.org/10.5194/hess-15-1895-2011, 2011
R. Schiemann, R. Erdin, M. Willi, C. Frei, M. Berenguer, and D. Sempere-Torres
Hydrol. Earth Syst. Sci., 15, 1515–1536, https://doi.org/10.5194/hess-15-1515-2011, https://doi.org/10.5194/hess-15-1515-2011, 2011
A. Lü, S. Jia, W. Zhu, H. Yan, S. Duan, and Z. Yao
Hydrol. Earth Syst. Sci., 15, 1273–1281, https://doi.org/10.5194/hess-15-1273-2011, https://doi.org/10.5194/hess-15-1273-2011, 2011
G. Wang, A. J. Dolman, and A. Alessandri
Hydrol. Earth Syst. Sci., 15, 57–64, https://doi.org/10.5194/hess-15-57-2011, https://doi.org/10.5194/hess-15-57-2011, 2011
F. Garavaglia, J. Gailhard, E. Paquet, M. Lang, R. Garçon, and P. Bernardara
Hydrol. Earth Syst. Sci., 14, 951–964, https://doi.org/10.5194/hess-14-951-2010, https://doi.org/10.5194/hess-14-951-2010, 2010
Cited articles
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop
evapotranspiration-Guidelines for computing crop water requirements, FAO
Irrigation and drainage paper 56, Food and Agricultural Organisation of the United Nations (FAO), Rome, 300 pp., D05109, ISBN 92-5-104219-5, 1998. a
Arnell, N. and Freeman, A.: The effect of climate change on agro-climatic
indicators in the UK, Climatic Change, 165, 1–26,
https://doi.org/10.1007/s10584-021-03054-8, 2021. a, b, c
Bachmair, S., Svensson, C., Hannaford, J., Barker, L. J., and Stahl, K.: A quantitative analysis to objectively appraise drought indicators and model drought impacts, Hydrol. Earth Syst. Sci., 20, 2589–2609, https://doi.org/10.5194/hess-20-2589-2016, 2016. a, b, c
Bachmair, S., Tanguy, M., Hannaford, J., and Stahl, K.: How well do
meteorological indicators represent agricultural and forest drought across
Europe?, Environ. Res. Lett., 13, 034042, https://doi.org/10.1088/1748-9326/aaafda,
2018. a
Barker, L. J., Hannaford, J., Chiverton, A., and Svensson, C.: From meteorological to hydrological drought using standardised indicators, Hydrol. Earth Syst. Sci., 20, 2483–2505, https://doi.org/10.5194/hess-20-2483-2016, 2016. a, b, c, d
Berg, A. and Sheffield, J.: Climate Change and Drought: The Soil
Moisture Perspective, Current Climate Change Reports, 4, 180–191,
https://doi.org/10.1007/s40641-018-0095-0, 2018. a
Blauhut, V., Stahl, K., Stagge, J. H., Tallaksen, L. M., De Stefano, L., and Vogt, J.: Estimating drought risk across Europe from reported drought impacts, drought indices, and vulnerability factors, Hydrol. Earth Syst. Sci., 20, 2779–2800, https://doi.org/10.5194/hess-20-2779-2016, 2016. a
Blenkinsop, S. and Fowler, H. J.: Changes in Drought Frequency, Severity and
Duration for the British Isles Projected by the PRUDENCE Regional
Climate Models, J. Hydrol., 342, 50–71, https://doi.org/10.1016/j.jhydrol.2007.05.003,
2007. a
Bloomfield, J. P., Marchant, B. P., and McKenzie, A. A.: Changes in groundwater drought associated with anthropogenic warming, Hydrol. Earth Syst. Sci., 23, 1393–1408, https://doi.org/10.5194/hess-23-1393-2019, 2019. a, b, c
Blyth, E. M., Martínez-de la Torre, A., and Robinson, E. L.: Trends in
Evapotranspiration and Its Drivers in Great Britain: 1961 to 2015, Prog.
Phys. Geog., 43, 666–693,
https://doi.org/10.1177/0309133319841891, 2019. a, b
Ceppi, P., Zappa, G., Shepherd, T. G., and Gregory, J. M.: Fast and slow
components of the extratropical atmospheric circulation response to CO2
forcing, J. Climate, 31, 1091–1105, https://doi.org/10.1175/JCLI-D-17-0323.1, 2018. a
Chiang, F., Mazdiyasni, O., and AghaKouchak, A.: Evidence of anthropogenic
impacts on global drought frequency, duration, and intensity, Nat. Commun., 12,
1–10, https://doi.org/10.1038/s41467-021-22314-w, 2021. a, b
Cook, B. I., Smerdon, J. E., Seager, R., and Coats, S.: Global Warming and 21st
Century Drying, Clim. Dynam., 43, 2607–2627, https://doi.org/10.1007/s00382-014-2075-y,
2014. a
Dai, A.: Drought under Global Warming: A Review, WIRES Clim Change, 2, 45–65,
https://doi.org/10.1002/wcc.81, 2011. a
Denissen, J., Teuling, A., Pitman, A., Koirala, S., Migliavacca, M., Li, W.,
Reichstein, M., Winkler, A., Zhan, C., and Orth, R.: Widespread Shift from
Ecosystem Energy to Water Limitation with Climate Change, Nat. Clim. Change,
12, 677–684, https://doi.org/10.1038/s41558-022-01403-8, 2022. a
Dewes, C. F., Rangwala, I., Barsugli, J. J., Hobbins, M. T., and Kumar, S.:
Drought Risk Assessment under Climate Change Is Sensitive to Methodological
Choices for the Estimation of Evaporative Demand, PLOS ONE, 12, e0174045,
https://doi.org/10.1371/journal.pone.0174045, 2017. a, b
Feng, S. and Fu, Q.: Expansion of global drylands under a warming climate, Atmos. Chem. Phys., 13, 10081–10094, https://doi.org/10.5194/acp-13-10081-2013, 2013. a
Feng, S., Trnka, M., Hayes, M., and Zhang, Y.: Why Do Different Drought
Indices Show Distinct Future Drought Risk Outcomes in the U.S.
Great Plains?, J. Climate, 30, 265–278, https://doi.org/10.1175/JCLI-D-15-0590.1,
2017. a, b
Folland, C. K., Hannaford, J., Bloomfield, J. P., Kendon, M., Svensson, C., Marchant, B. P., Prior, J., and Wallace, E.: Multi-annual droughts in the English Lowlands: a review of their characteristics and climate drivers in the winter half-year, Hydrol. Earth Syst. Sci., 19, 2353–2375, https://doi.org/10.5194/hess-19-2353-2015, 2015. a
Fu, Q. and Feng, S.: Responses of Terrestrial Aridity to Global Warming, J. Geophys. Res.-Atmos., 119, 7863–7875, https://doi.org/10.1002/2014JD021608, 2014. a
Gampe, D., Zscheischler, J., Reichstein, M., O’Sullivan, M., Smith, W. K.,
Sitch, S., and Buermann, W.: Increasing impact of warm droughts on northern
ecosystem productivity over recent decades, Nat. Clim. Change, 11, 772–779,
https://doi.org/10.1038/s41558-021-01112-8, 2021. a, b
García-Valdecasas Ojeda, M., Gámiz-Fortis, S. R.,
Romero-Jiménez, E., Rosa-Cánovas, J. J., Yeste, P.,
Castro-Díez, Y., and Esteban-Parra, M. J.: Projected changes in the
Iberian Peninsula drought characteristics, Sci. Total Environ., 757, 143702,
https://doi.org/10.1016/j.scitotenv.2020.143702, 2021. a, b
Gohar, L., Bernie, D., Good, P., and Lowe, J. A.: UKCP18 Derived Projections of
Future Climate over the UK, Met Office Hadley Centre, Exeter, UK, 2018. a
Greve, P., Roderick, M. L., Ukkola, A. M., and Wada, Y.: The Aridity Index
under Global Warming, Environ. Res. Lett., 14, 124006,
https://doi.org/10.1088/1748-9326/ab5046, 2019. a, b, c
Grossiord, C., Buckley, T. N., Cernusak, L. A., Novick, K. A., Poulter, B.,
Siegwolf, R. T. W., Sperry, J. S., and McDowell, N. G.: Plant Responses to
Rising Vapor Pressure Deficit, New Phytol., 226, 1550–1566,
https://doi.org/10.1111/nph.16485, 2020. a, b
Hanlon, H. M., Bernie, D., Carigi, G., and Lowe, J. A.: Future Changes to High
Impact Weather in the UK, Climatic Change, 166, 50,
https://doi.org/10.1007/s10584-021-03100-5, 2021. a, b, c, d
Haro-Monteagudo, D., Daccache, A., and Knox, J.: Exploring the utility of
drought indicators to assess climate risks to agricultural productivity in a
humid climate, Hydrol. Res., 49, 539–551, https://doi.org/10.2166/nh.2017.010, 2018. a, b
Hollis, D., McCarthy, M., Kendon, M., Legg, T., and Simpson, I.: HadUK-Grid –
A new UK dataset of gridded climate observations, Geosci Data J, 6, 151–159,
https://doi.org/10.1002/gdj3.78, 2019. a
Ionita, M. and Nagavciuc, V.: Changes in drought features at the European level over the last 120 years, Nat. Hazards Earth Syst. Sci., 21, 1685–1701, https://doi.org/10.5194/nhess-21-1685-2021, 2021. a, b
Karimi, M., Vicente-Serrano, S. M., Reig, F., Shahedi, K., Raziei, T., and
Miryaghoubzadeh, M.: Recent trends in atmospheric evaporative demand in
Southwest Iran: implications for change in drought severity, Theor. Appl.
Climatol., 142, 945–958, https://doi.org/10.1007/s00704-020-03349-3, 2020. a
Kay, A. L., Bell, V. A., Blyth, E. M., Crooks, S. M., Davies, H. N., and
Reynard, N. S.: A Hydrological Perspective on Evaporation: Historical Trends
and Future Projections in Britain, J. Water Clim. Change, 4, 193–208,
https://doi.org/10.2166/wcc.2013.014, 2013. a, b
Kay, A. L., Lane, R. A., and Bell, V. A.: Grid-Based Simulation of Soil
Moisture in the UK: Future Changes in Extremes and Wetting and Drying
Dates, Environ. Res. Lett., 17, 074029, https://doi.org/10.1088/1748-9326/ac7a4e, 2022. a
Kendon, M., Marsh, T., and Parry, S.: The 2010–2012 Drought in
England and Wales, Weather, 68, 88–95, https://doi.org/10.1002/wea.2101, 2013. a
Keyantash, J. and Dracup, J. A.: The Quantification of Drought: An
Evaluation of Drought Indices, B. Am. Meteorol. Soc., 83, 1167–1180,
https://doi.org/10.1175/1520-0477-83.8.1167, 2002. a
Lane, R. A. and Kay, A. L.: Climate Change Impact on the Magnitude and
Timing of Hydrological Extremes Across Great Britain, Frontiers in
Water, 3, 684982, https://doi.org/10.3389/frwa.2021.684982, 2021. a
Lange, S.: Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0), Geosci. Model Dev., 12, 3055–3070, https://doi.org/10.5194/gmd-12-3055-2019, 2019. a
Lange, S.: ISIMIP3BASD (2.4.1.), Zenodo [code], https://doi.org/10.5281/zenodo.3898426, 2020. a
Lee, M.-H., Im, E.-S., and Bae, D.-H.: A Comparative Assessment of Climate
Change Impacts on Drought over Korea Based on Multiple Climate
Projections and Multiple Drought Indices, Clim. Dynam., 53, 389–404,
https://doi.org/10.1007/s00382-018-4588-2, 2019. a
Lehner, F., Coats, S., Stocker, T. F., Pendergrass, A. G., Sanderson, B. M.,
Raible, C. C., and Smerdon, J. E.: Projected Drought Risk in 1.5 ∘C and
2 ∘C Warmer Climates, Geophys. Res. Lett., 44, 7419–7428,
https://doi.org/10.1002/2017GL074117, 2017. a
Lloyd-Hughes, B.: The Impracticality of a Universal Drought Definition, Theor.
Appl. Climatol., 117, 607–611, https://doi.org/10.1007/s00704-013-1025-7, 2014. a
Manning, C., Widmann, M., Bevacqua, E., Loon, A. F. V., Maraun, D., and Vrac,
M.: Soil Moisture Drought in Europe: A Compound Event of
Precipitation and Potential Evapotranspiration on Multiple Time
Scales, J. Hydrometeorol., 19, 1255–1271, https://doi.org/10.1175/JHM-D-18-0017.1,
2018. a, b, c
Marsh, T., Cole, G., and Wilby, R.: Major Droughts in England and
Wales, 1800–2006, Weather, 62, 87–93, https://doi.org/10.1002/wea.67,
2007. a
Massari, C., Avanzi, F., Bruno, G., Gabellani, S., Penna, D., and Camici, S.: Evaporation enhancement drives the European water-budget deficit during multi-year droughts, Hydrol. Earth Syst. Sci., 26, 1527–1543, https://doi.org/10.5194/hess-26-1527-2022, 2022. a, b, c
Met Office, Hollis, D., McCarthy, M., Kendon, M., Legg, T., and Simpson, I.:
HadUK-Grid Gridded Climate Observations on a 1 km grid over the UK, v1.0.1.0
(1862–2018), Centre for Environmental Data Analysis [data set], https://doi.org/10.5285/d134335808894b2bb249e9f222e2eca8,
2019. a
Milly, P. C. D. and Dunne, K. A.: Potential Evapotranspiration and Continental
Drying, Nat. Clim. Change, 6, 946–949, https://doi.org/10.1038/nclimate3046, 2016. a, b
Miralles, D. G., Gentine, P., Seneviratne, S. I., and Teuling, A. J.:
Land–Atmospheric Feedbacks during Droughts and Heatwaves: State of
the Science and Current Challenges, Ann. NY Acad. Sci., 1436, 19–35,
https://doi.org/10.1111/nyas.13912, 2019. a
Murphy, J. M., Harris, G. R., Sexton, D. M. H., Kendon, E. J., Bett, P. E.,
Clark, R. T., Eagle, K. E., Fosser, G., Fung, F., Lowe, J. A., McDonald,
R. E., McInnes, R. N., McSweeney, C. F., Mitchell, J. F. B., Rostron, J. W.,
Thornton, H. E., Tucker, S., and Yamazaki, K.: UKCP18 Land Projections:
Science Report, Met Office, 2018. a, b, c, d, e
Pendergrass, A. G., Meehl, G. A., Pulwarty, R., Hobbins, M., Hoell, A.,
AghaKouchak, A., Bonfils, C. J. W., Gallant, A. J. E., Hoerling, M.,
Hoffmann, D., Kaatz, L., Lehner, F., Llewellyn, D., Mote, P., Neale, R. B.,
Overpeck, J. T., Sheffield, A., Stahl, K., Svoboda, M., Wheeler, M. C., Wood,
A. W., and Woodhouse, C. A.: Flash Droughts Present a New Challenge for
Subseasonal-to-Seasonal Prediction, Nat. Clim. Change, 10, 191–199,
https://doi.org/10.1038/s41558-020-0709-0, 2020. a
Phillips, I. D. and McGregor, G. R.: The Utility of a Drought Index for
Assessing the Drought Hazard in Devon and Cornwall, South West
England, Meteorol. Appl., 5, 359–372, https://doi.org/10.1017/S1350482798000899, 1998. a
Rahiz, M. and New, M.: 21st Century Drought Scenarios for the UK, Water
Resour. Manag., 27, 1039–1061, https://doi.org/10.1007/s11269-012-0183-1, 2013. a, b, c, d
Reyniers, N., Osborn, T., Addor, N., and Darch, G.: Projected changes in
droughts and extreme droughts in Great Britain are strongly influenced by the
choice of drought index: UKCP18-based bias adjusted potential
evapotranspiration, Zenodo [data set], https://doi.org/10.5281/zenodo.6320707,
2022a. a
Reyniers, N., Osborn, T., Addor, N., and Darch, G.: Projected changes in
droughts and extreme droughts in Great Britain are strongly influenced by the
choice of drought index: UKCP18-based SPI and SPEI data, Zenodo [data set],
https://doi.org/10.5281/zenodo.6123020, 2022b. a
Richards, J.: A simple expression for the saturation vapour pressure of water
in the range −50 to 140∘ C, J. Phys. D Appl. Phys., 4, L15, https://doi.org/10.1088/0022-3727/4/4/101, 1971. a
Robinson, E., Blyth, E., Clark, D., Comyn-Platt, E., and Rudd, A.: Climate
hydrology and ecology research support system potential evapotranspiration
dataset for Great Britain (1961–2017) [CHESS-PE], NERC Environmental
Information Data Centre [data set], https://doi.org/10.5285/9116e565-2c0a-455b-9c68-558fdd9179ad,
2020. a, b
Robinson, E. L., Brown, M. J., Kay, A. L., Lane, R. A., Chapman, R., Bell, V. A., and Blyth, E. M.: Hydro-PE: gridded datasets of historical and future Penman-Monteith potential evaporation for the United Kingdom, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2022-288, in review, 2022. a
Rodda, J. and March, T.: The 1975/76 Drought – a Contemporary
and Retrospective View, Centre for Ecology & Hydrology, p. 58,
http://nora.nerc.ac.uk/id/eprint/15011/1/CEH_1975-76_Drought_Report_Rodda_and_Marsh.pdf (last access: 30 January 2023),
2011. a
Satoh, Y., Shiogama, H., Hanasaki, N., Pokhrel, Y., Boulange, J. E. S., Burek,
P., Gosling, S. N., Grillakis, M., Koutroulis, A., Müller Schmied, H., Thiery, W., and Yokohata, T.: A
quantitative evaluation of the issue of drought definition: a source of
disagreement in future drought assessments, Environ. Res. Lett., 16, 104001,
https://doi.org/10.1088/1748-9326/ac2348, 2021. a, b
Scheff, J., Mankin, J. S., Coats, S., and Liu, H.: CO2-plant Effects Do Not
Account for the Gap between Dryness Indices and Projected Dryness Impacts in
CMIP6 or CMIP5, Environ. Res. Lett., 16, 034018,
https://doi.org/10.1088/1748-9326/abd8fd, 2021. a, b
Schönbeck, L. C., Schuler, P., Lehmann, M. M., Mas, E., Mekarni, L.,
Pivovaroff, A. L., Turberg, P., and Grossiord, C.: Increasing Temperature and
Vapour Pressure Deficit Lead to Hydraulic Damages in the Absence of Soil
Drought, Plant, Cell Environ., 45, 3275–3289, https://doi.org/10.1111/pce.14425,
2022. a
Seneviratne, S. I.: Historical Drought Trends Revisited, Nature, 491, 338–339,
https://doi.org/10.1038/491338a, 2012. a
Seneviratne, S. I., Lüthi, D., Litschi, M., and Schär, C.:
Land–Atmosphere Coupling and Climate Change in Europe, Nature,
443, 205–209, https://doi.org/10.1038/nature05095, 2006. a
Seneviratne, S. I., Zhang, X., Adnan, M., Badi, W., Dereczynski, C., Di Luca, A., Ghosh, S., Iskandar, I., Kossin, J., Lewis, S., Otto, F., Pinto, I., Satoh, M., Vicente-Serrano, S. M., Wehner, M., and Zhou, B.: Weather and Climate Extreme Events in a Changing Climate, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1513–1766, https://doi.org/10.1017/9781009157896.013, 2021. a, b
Sheffield, J., Wood, E. F., and Roderick, M. L.: Little Change in Global
Drought over the Past 60 Years, Nature, 491, 435–438,
https://doi.org/10.1038/nature11575, 2012. a, b
Spinoni, J., Vogt, J. V., Naumann, G., Barbosa, P., and Dosio, A.: Will Drought
Events Become More Frequent and Severe in Europe?, Int. J. Climatol., 38,
1718–1736, https://doi.org/10.1002/joc.5291, 2018. a, b, c
Stagge, J. H., Kohn, I., Tallaksen, L. M., and Stahl, K.: Modeling drought
impact occurrence based on meteorological drought indices in Europe, J.
Hydrol., 530, 37–50, https://doi.org/10.1016/j.jhydrol.2015.09.039, 2015a. a, b
Stagge, J. H., Tallaksen, L. M., Gudmundsson, L., Van Loon, A. F., and Stahl,
K.: Candidate distributions for climatological drought indices (SPI and
SPEI), Int. J. Climatol., 35, 4027–4040, https://doi.org/10.1002/joc.4267,
2015b. a, b, c
Stagge, J. H., Kingston, D. G., Tallaksen, L. M., and Hannah, D. M.: Observed
drought indices show increasing divergence across Europe, Sci. Rep.-UK, 7,
1–10, https://doi.org/10.1038/s41598-017-14283-2, 2017. a, b, c, d
Sutanto, S. J. and Van Lanen, H. A. J.: Streamflow drought: implication of drought definitions and its application for drought forecasting, Hydrol. Earth Syst. Sci., 25, 3991–4023, https://doi.org/10.5194/hess-25-3991-2021, 2021. a
World Meteorological Organization and Global Water Partnership: Handbook of Drought Indicators and Indices (Svoboda, M. and Fuchs, B. A.), Integrated Drought Management Programme (IDMP), Integrated Drought Management Tools and Guidelines Series 2, Geneva, 45 pp., ISBN 978-92-63-11173-9 and 978-91-87823-24-4, 2016. a
Tanguy, M., Haslinger, K., Svensson, C., Parry, S., Barker, L. J., Hannaford,
J., and Prudhomme, C.: Regional differences in spatiotemporal drought
characteristics in Great Britain, Frontiers in Environmental Science, 9, 639649, https://doi.org/10.3389/fenvs.2021.639649, 2021. a
Teuling, A. J., Hirschi, M., Ohmura, A., Wild, M., Reichstein, M., Ciais, P.,
Buchmann, N., Ammann, C., Montagnani, L., Richardson, A. D., Wohlfahrt, G.,
and Seneviratne, S. I.: A Regional Perspective on Trends in Continental
Evaporation, Geophys. Res. Lett., 36, L02404, https://doi.org/10.1029/2008GL036584, 2009. a
Teuling, A. J., Seneviratne, S. I., Stöckli, R., Reichstein, M., Moors, E.,
Ciais, P., Luyssaert, S., van den Hurk, B., Ammann, C., Bernhofer, C.,
Dellwik, E., Gianelle, D., Gielen, B., Grünwald, T., Klumpp, K.,
Montagnani, L., Moureaux, C., Sottocornola, M., and Wohlfahrt, G.:
Contrasting Response of European Forest and Grassland Energy Exchange to
Heatwaves, Nat. Geosci., 3, 722–727, https://doi.org/10.1038/ngeo950, 2010. a
Tomas-Burguera, M., Vicente-Serrano, S. M., Peña-Angulo, D.,
Domínguez-Castro, F., Noguera, I., and El Kenawy, A.: Global
characterization of the varying responses of the standardized precipitation
evapotranspiration index to atmospheric evaporative demand, J. Geophys. Res.-Atmos., 125, e2020JD033017, https://doi.org/10.1029/2020JD033017, 2020. a
Touma, D., Ashfaq, M., Nayak, M. A., Kao, S.-C., and Diffenbaugh, N. S.: A
Multi-Model and Multi-Index Evaluation of Drought Characteristics in the 21st
Century, J. Hydrol., 526, 196–207, https://doi.org/10.1016/j.jhydrol.2014.12.011, 2015. a, b
Turner, S., Barker, L. J., Hannaford, J., Muchan, K., Parry, S., and Sefton,
C.: The 2018/2019 Drought in the UK: A Hydrological Appraisal, Weather, 76, 248–253, https://doi.org/10.1002/wea.4003, 2018. a
ukcp18 data: UKCP18 Spatial Files, GitHub [data set], https://github.com/ukcp-data/ukcp-spatial-files, last access: 12 October 2021. a
UNEP: World atlas of desertification, ISBN/ISSN: 0340555122, 1992. a
Vicente-Serrano, S. M., Beguería, S., and López-Moreno, J. I.: A
Multiscalar Drought Index Sensitive to Global Warming: The
Standardized Precipitation Evapotranspiration Index, J. Climate, 23,
1696–1718, https://doi.org/10.1175/2009JCLI2909.1, 2009. a
Vicente-Serrano, S. M., Van der Schrier, G., Beguería, S.,
Azorin-Molina, C., and Lopez-Moreno, J.-I.: Contribution of Precipitation
and Reference Evapotranspiration to Drought Indices under Different Climates,
J. Hydrol., 526, 42–54, https://doi.org/10.1016/j.jhydrol.2014.11.025, 2015. a
Vicente-Serrano, S. M., Peña-Gallardo, M., Hannaford, J., Murphy, C.,
Lorenzo-Lacruz, J., Dominguez-Castro, F., López-Moreno, J. I.,
Beguería, S., Noguera, I., Harrigan, S., and Vidal, J.-P.: Climate,
Irrigation, and Land Cover Change Explain Streamflow Trends in
Countries Bordering the Northeast Atlantic, Geophys. Res. Lett., 46,
10821–10833, https://doi.org/10.1029/2019GL084084, 2019.
a
Vicente-Serrano, S. M., Domínguez-Castro, F., Murphy, C., Hannaford, J.,
Reig, F., Peña-Angulo, D., Tramblay, Y., Trigo, R. M., Mac Donald, N.,
Luna, M. Y., Mc Carthy, M., Van der Schrier, G., Turco, M., Camuffo, D.,
Noguera, I., García-Herrera, R., Becherini, F., Della Valle, A.,
Tomas-Burguera, M., and El Kenawy, A.: Long-Term Variability and Trends in
Meteorological Droughts in Western Europe (1851–2018), Int. J. Climatol.,
41, E690–E717, https://doi.org/10.1002/joc.6719, 2021. a, b
Vicente‐Serrano, S. M., McVicar, T. R., Miralles, D. G., Yang, Y., and
Tomas‐Burguera, M.: Unraveling the Influence of Atmospheric Evaporative
Demand on Drought and Its Response to Climate Change, WIRES Clim. Change, 11,
e632, https://doi.org/10.1002/wcc.632, 2020. a, b, c
Vidal, J.-P. and Wade, S.: A Multimodel Assessment of Future Climatological
Droughts in the United Kingdom, Int. J. Climatol., 29, 2056–2071,
https://doi.org/10.1002/joc.1843, 2009. a
Wang, T., Tu, X., Singh, V. P., Chen, X., and Lin, K.: Global data assessment
and analysis of drought characteristics based on CMIP6, J. Hydrol., 596,
126091, https://doi.org/10.1016/j.jhydrol.2021.126091, 2021. a
Watts, G., Battarbee, R. W., Bloomfield, J. P., Crossman, J., Daccache, A.,
Durance, I., Elliott, J. A., Garner, G., Hannaford, J., Hannah, D. M., Hess,
T., Jackson, C. R., Kay, A. L., Kernan, M., Knox, J., Mackay, J., Monteith,
D. T., Ormerod, S. J., Rance, J., Stuart, M. E., Wade, A. J., Wade, S. D.,
Weatherhead, K., Whitehead, P. G., and Wilby, R. L.: Climate Change and Water
in the UK – Past Changes and Future Prospects, Prog. Phys. Geog., 39, 6–28, https://doi.org/10.1177/0309133314542957, 2015. a
Wilhite, D. A. and Glantz, M. H.: Understanding the Drought Phenomenon:
The Role of Definitions, Water Int., 111–120, 1985. a
Yevjevich, V.: An Objective Approach to Definitions and Investigations of
Continental Hydrologic Droughts, J. Hydrol., 7, 353,
https://doi.org/10.1016/0022-1694(69)90110-3, 1967. a, b
Zhao, M., A, G., Liu, Y., and Konings, A. G.: Evapotranspiration Frequently
Increases during Droughts, Nat. Clim. Change, 12, 1024–1030,
https://doi.org/10.1038/s41558-022-01505-3, 2022. a, b, c
Short summary
In an analysis of future drought projections for Great Britain based on the Standardised Precipitation Index and the Standardised Precipitation Evapotranspiration Index, we show that the choice of drought indicator has a decisive influence on the resulting projected changes in drought characteristics, although both result in increased drying. This highlights the need to understand the interplay between increasing atmospheric evaporative demand and drought impacts under a changing climate.
In an analysis of future drought projections for Great Britain based on the Standardised...
