Research article
08 Jun 2017
Research article
| 08 Jun 2017
Multivariate statistical modelling of compound events via pair-copula constructions: analysis of floods in Ravenna (Italy)
Emanuele Bevacqua et al.
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We use explainable machine learning to identify the contribution of recent precipitation, antecedent precipitation, and snowmelt to individual flood events in Europe. More than half of catchments are found dominated by mixed flooding mechanisms. Over the past 70 years, changes in the dominant flooding mechanisms are observed within a number of catchments. Generally, the number of floods induced by snowmelt has declined significantly, while floods triggered by recent precipitation have increased.
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Climate hazards may be caused by events which have multiple drivers. Here we present a method to break down climate model biases in hazard indicators down to the bias caused by each driving variable. Using simplified fire and heat stress indicators driven by temperature and relative humidity as examples, we show how multivariate indicators may have complex biases and that the relationship between driving variables is a source of bias that must be considered in climate model bias corrections.
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Coastal compound flooding (CF), caused by interacting storm surges and high water runoff, is typically studied based on concurring storm surge extremes with either precipitation or river discharge extremes. Globally, these two approaches show similar CF spatial patterns, especially where the CF potential is the highest. Deviations between the two approaches increase with the catchment size. The precipitation-based analysis allows for considering
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Coastal compound flooding (CF), caused by interacting storm surges and high water runoff, is typically studied based on concurring storm surge extremes with either precipitation or river discharge extremes. Globally, these two approaches show similar CF spatial patterns, especially where the CF potential is the highest. Deviations between the two approaches increase with the catchment size. The precipitation-based analysis allows for considering
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Florentin Breton, Mathieu Vrac, Pascal Yiou, Pradeebane Vaittinada Ayar, and Aglaé Jézéquel
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Giulia Carella, Mathieu Vrac, Hélène Brogniez, Pascal Yiou, and Hélène Chepfer
Earth Syst. Sci. Data, 12, 1–20, https://doi.org/10.5194/essd-12-1-2020, https://doi.org/10.5194/essd-12-1-2020, 2020
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Hydrol. Earth Syst. Sci., 23, 773–786, https://doi.org/10.5194/hess-23-773-2019, https://doi.org/10.5194/hess-23-773-2019, 2019
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Lionel Benoit, Mathieu Vrac, and Gregoire Mariethoz
Hydrol. Earth Syst. Sci., 22, 5919–5933, https://doi.org/10.5194/hess-22-5919-2018, https://doi.org/10.5194/hess-22-5919-2018, 2018
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Claire Waelbroeck, Sylvain Pichat, Evelyn Böhm, Bryan C. Lougheed, Davide Faranda, Mathieu Vrac, Lise Missiaen, Natalia Vazquez Riveiros, Pierre Burckel, Jörg Lippold, Helge W. Arz, Trond Dokken, François Thil, and Arnaud Dapoigny
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Douglas Maraun and Martin Widmann
Hydrol. Earth Syst. Sci., 22, 4867–4873, https://doi.org/10.5194/hess-22-4867-2018, https://doi.org/10.5194/hess-22-4867-2018, 2018
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Guillaume Latombe, Ariane Burke, Mathieu Vrac, Guillaume Levavasseur, Christophe Dumas, Masa Kageyama, and Gilles Ramstein
Geosci. Model Dev., 11, 2563–2579, https://doi.org/10.5194/gmd-11-2563-2018, https://doi.org/10.5194/gmd-11-2563-2018, 2018
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It is still unclear how climate conditions, and especially climate variability, influenced the spatial distribution of past human populations. Global climate models (GCMs) cannot simulate climate at sufficiently fine scale for this purpose. We propose a statistical method to obtain fine-scale climate projections for 15 000 years ago from coarse-scale GCM outputs. Our method agrees with local reconstructions from fossil and pollen data, and generates sensible climate variability maps over Europe.
Mathieu Vrac
Hydrol. Earth Syst. Sci., 22, 3175–3196, https://doi.org/10.5194/hess-22-3175-2018, https://doi.org/10.5194/hess-22-3175-2018, 2018
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This study presents a multivariate bias correction method named R2D2 to adjust both the 1d-distributions and inter-variable/site dependence structures of climate simulations in a high-dimensional context, while providing some stochasticity. R2D2 is tested on temperature and precipitation reanalyses and illustrated on future simulations. In both cases, R2D2 is able to correct the spatial and physical dependence, opening proper use of climate simulations for impact (e.g. hydrological) models.
Adjoua Moise Famien, Serge Janicot, Abe Delfin Ochou, Mathieu Vrac, Dimitri Defrance, Benjamin Sultan, and Thomas Noël
Earth Syst. Dynam., 9, 313–338, https://doi.org/10.5194/esd-9-313-2018, https://doi.org/10.5194/esd-9-313-2018, 2018
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This study uses the cumulative distribution function transform (CDF-t) method to provide bias-corrected data over Africa using WFDEI as a reference dataset. It is shown that CDF-t is very effective in removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets, particularly for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields.
PAGES Hydro2k Consortium
Clim. Past, 13, 1851–1900, https://doi.org/10.5194/cp-13-1851-2017, https://doi.org/10.5194/cp-13-1851-2017, 2017
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Pascal Yiou, Aglaé Jézéquel, Philippe Naveau, Frederike E. L. Otto, Robert Vautard, and Mathieu Vrac
Adv. Stat. Clim. Meteorol. Oceanogr., 3, 17–31, https://doi.org/10.5194/ascmo-3-17-2017, https://doi.org/10.5194/ascmo-3-17-2017, 2017
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The attribution of classes of extreme events, such as heavy precipitation or heatwaves, relies on the estimate of small probabilities (with and without climate change). Such events are connected to the large-scale atmospheric circulation. This paper links such probabilities with properties of the atmospheric circulation by using a Bayesian decomposition. We test this decomposition on a case of extreme precipitation in the UK, in January 2014.
Claudia Volosciuk, Douglas Maraun, Mathieu Vrac, and Martin Widmann
Hydrol. Earth Syst. Sci., 21, 1693–1719, https://doi.org/10.5194/hess-21-1693-2017, https://doi.org/10.5194/hess-21-1693-2017, 2017
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For impact modeling, infrastructure design, or adaptation strategy planning, high-quality climate data on the point scale are often demanded. Due to the scale gap between gridbox and point scale and biases in climate models, we combine a statistical bias correction and a stochastic downscaling model and apply it to climate model-simulated precipitation. The method performs better in summer than in winter and in winter best for mild winter climate (Mediterranean) and worst for continental winter.
Jérôme Pernin, Mathieu Vrac, Cyril Crevoisier, and Alain Chédin
Adv. Stat. Clim. Meteorol. Oceanogr., 2, 115–136, https://doi.org/10.5194/ascmo-2-115-2016, https://doi.org/10.5194/ascmo-2-115-2016, 2016
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Here, we propose a classification methodology of various space-time atmospheric datasets into discrete air mass groups homogeneous in temperature and humidity through a probabilistic point of view: both the classification process and the data are probabilistic. Unlike conventional classification algorithms, this methodology provides the probability of belonging to each class as well as the corresponding uncertainty, which can be used in various applications.
Anastasios Matsikaris, Martin Widmann, and Johann Jungclaus
Clim. Past, 12, 1555–1563, https://doi.org/10.5194/cp-12-1555-2016, https://doi.org/10.5194/cp-12-1555-2016, 2016
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We have assimilated proxy-based (PAGES 2K) and instrumental (HadCRUT3v) observations into a General Circulation Model (MPI-ESM-CR). Assimilating instrumental data improves the performance of Data Assimilation. No skill on small spatial scales is however found for either of the two schemes. Errors in the assimilated data are therefore not the main reason for this lack of skill; continental mean temperatures cannot provide skill on small spatial scales in palaeoclimate reconstructions.
Benjamin Grouillet, Denis Ruelland, Pradeebane Vaittinada Ayar, and Mathieu Vrac
Hydrol. Earth Syst. Sci., 20, 1031–1047, https://doi.org/10.5194/hess-20-1031-2016, https://doi.org/10.5194/hess-20-1031-2016, 2016
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This original paper provides a guideline to select statistical downscaling methods (SDMs) in climate change impact studies (CCIS) to minimize uncertainty from downscaling. Three SDMs were applied to NCEP reanalysis and 2 GCM data values. We then analyzed the sensitivity of the hydrological model to the various downscaled data via 5 hydrological indicators representing the main features of the hydrograph. Our results enable selection of the appropriate SDMs to be used to build climate scenarios.
D. Maraun and M. Widmann
Hydrol. Earth Syst. Sci., 19, 3449–3456, https://doi.org/10.5194/hess-19-3449-2015, https://doi.org/10.5194/hess-19-3449-2015, 2015
A. Matsikaris, M. Widmann, and J. Jungclaus
Clim. Past, 11, 81–93, https://doi.org/10.5194/cp-11-81-2015, https://doi.org/10.5194/cp-11-81-2015, 2015
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We compare an off-line and an on-line ensemble-based data assimilation method, for the climate of the 17th century. Both schemes perform better than the simulations without DA, and similar skill on the continental and hemispheric scales is found. This indicates either a lack of control of the slow components in our setup or a lack of skill in the information propagation on decadal timescales. The temporal consistency of the analysis in the on-line method makes it generally more preferable.
T. Alberti, F. Lepreti, A. Vecchio, E. Bevacqua, V. Capparelli, and V. Carbone
Clim. Past, 10, 1751–1762, https://doi.org/10.5194/cp-10-1751-2014, https://doi.org/10.5194/cp-10-1751-2014, 2014
P. Yiou, M. Boichu, R. Vautard, M. Vrac, S. Jourdain, E. Garnier, F. Fluteau, and L. Menut
Clim. Past, 10, 797–809, https://doi.org/10.5194/cp-10-797-2014, https://doi.org/10.5194/cp-10-797-2014, 2014
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We analyse dependences between different flooding drivers around the USA coastline, where the Gulf of Mexico and the southeastern and southwestern coasts are regions of high dependence between flooding drivers. Dependence is higher during the tropical season in the Gulf and at some locations on the East Coast but higher during the extratropical season on the West Coast. The analysis gives new insights on locations, driver combinations, and the time of the year when compound flooding is likely.
Víctor M. Santos, Mercè Casas-Prat, Benjamin Poschlod, Elisa Ragno, Bart van den Hurk, Zengchao Hao, Tímea Kalmár, Lianhua Zhu, and Husain Najafi
Hydrol. Earth Syst. Sci., 25, 3595–3615, https://doi.org/10.5194/hess-25-3595-2021, https://doi.org/10.5194/hess-25-3595-2021, 2021
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We present an application of multivariate statistical models to assess compound flooding events in a managed reservoir. Data (from a previous study) were obtained from a physical-based hydrological model driven by a regional climate model large ensemble, providing a time series expanding up to 800 years in length that ensures stable statistics. The length of the data set allows for a sensitivity assessment of the proposed statistical framework to natural climate variability.
Wenyan Wu, Seth Westra, and Michael Leonard
Hydrol. Earth Syst. Sci., 25, 2821–2841, https://doi.org/10.5194/hess-25-2821-2021, https://doi.org/10.5194/hess-25-2821-2021, 2021
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Flood probability estimation is important for applications such as land use planning, reservoir operation, infrastructure design and safety assessments. However, it is a challenging task, especially in estuarine areas where floods are caused by both intense rainfall and storm surge. This study provides a review of approaches to flood probability estimation in these areas. Based on analysis of a real-world river system, guidance on method selection is provided.
Angelo Breda, Patricia M. Saco, Steven G. Sandi, Neil Saintilan, Gerardo Riccardi, and José F. Rodríguez
Hydrol. Earth Syst. Sci., 25, 769–786, https://doi.org/10.5194/hess-25-769-2021, https://doi.org/10.5194/hess-25-769-2021, 2021
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We study accretion, retreat and transgression of mangrove and saltmarsh wetlands affected by sea-level rise (SLR) using simulations on typical configurations with different levels of tidal obstruction. Interactions and feedbacks between flow, sediment deposition, vegetation migration and soil accretion result in wetlands not surviving the predicted high-emission scenario SLR, despite dramatic increases in sediment supply. Previous simplified models overpredict wetland resilience to SLR.
Peisheng Huang, Karl Hennig, Jatin Kala, Julia Andrys, and Matthew R. Hipsey
Hydrol. Earth Syst. Sci., 24, 5673–5697, https://doi.org/10.5194/hess-24-5673-2020, https://doi.org/10.5194/hess-24-5673-2020, 2020
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Our results conclude that the climate change in the past decades has a remarkable effect on the hydrology of a large shallow lagoon with the same magnitude as that caused by the opening of an artificial channel, and it also highlighted the complexity of their interactions. We suggested that the consideration of the projected drying trend is essential in designing management plans associated with planning for environmental water provision and setting water quality loading targets.
Jianrong Zhu, Xinyue Cheng, Linjiang Li, Hui Wu, Jinghua Gu, and Hanghang Lyu
Hydrol. Earth Syst. Sci., 24, 5043–5056, https://doi.org/10.5194/hess-24-5043-2020, https://doi.org/10.5194/hess-24-5043-2020, 2020
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An extremely severe saltwater intrusion event occurred in February 2014 in the Changjiang estuary and seriously influenced the water intake of the reservoir. For the event cause and for freshwater safety, the dynamic mechanism was studied with observed data and a numerical model. The results indicated that this event was caused by a persistent and strong northerly wind, which formed a horizontal estuarine circulation, surpassed seaward runoff and drove highly saline water into the estuary.
Huayang Cai, Ping Zhang, Erwan Garel, Pascal Matte, Shuai Hu, Feng Liu, and Qingshu Yang
Hydrol. Earth Syst. Sci., 24, 1871–1889, https://doi.org/10.5194/hess-24-1871-2020, https://doi.org/10.5194/hess-24-1871-2020, 2020
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Understanding the morphological changes in estuaries due to natural processes and human interventions is especially important with regard to sustainable water management and ecological impacts on the estuarine environment. In this contribution, we explore the morphological evolution in tide-dominated estuaries by means of a novel analytical approach using the observed water levels along the channel. The method could serve as a useful tool to understand the evolution of estuarine morphology.
Huayang Cai, Hubert H. G. Savenije, Erwan Garel, Xianyi Zhang, Leicheng Guo, Min Zhang, Feng Liu, and Qingshu Yang
Hydrol. Earth Syst. Sci., 23, 2779–2794, https://doi.org/10.5194/hess-23-2779-2019, https://doi.org/10.5194/hess-23-2779-2019, 2019
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Tide–river dynamics play an essential role in large-scale river deltas as they exert a tremendous impact on delta morphodynamics, salt intrusion and deltaic ecosystems. For the first time, we illustrate that there is a critical river discharge, beyond which tidal damping is reduced with increasing river discharge, and we explore the underlying mechanism using an analytical model. The results are useful for guiding sustainable water management and sediment transport in tidal rivers.
Pedro D. Barrera Crespo, Erik Mosselman, Alessio Giardino, Anke Becker, Willem Ottevanger, Mohamed Nabi, and Mijail Arias-Hidalgo
Hydrol. Earth Syst. Sci., 23, 2763–2778, https://doi.org/10.5194/hess-23-2763-2019, https://doi.org/10.5194/hess-23-2763-2019, 2019
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Guayaquil, the commercial capital of Ecuador, is located along the Guayas River. The city is among the most vulnerable cities to future flooding ascribed to climate change. Fluvial sedimentation is seen as one of the factors contributing to flooding. This paper describes the dominant processes in the river and the effects of past interventions in the overall sediment budget. This is essential to plan and design effective mitigation measures to face the latent risk that threatens Guayaquil.
Soufiane Haddout, Mohammed Igouzal, and Abdellatif Maslouhi
Hydrol. Earth Syst. Sci., 20, 3923–3945, https://doi.org/10.5194/hess-20-3923-2016, https://doi.org/10.5194/hess-20-3923-2016, 2016
Chiara Volta, Goulven Gildas Laruelle, Sandra Arndt, and Pierre Regnier
Hydrol. Earth Syst. Sci., 20, 991–1030, https://doi.org/10.5194/hess-20-991-2016, https://doi.org/10.5194/hess-20-991-2016, 2016
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A generic estuarine model is applied to three idealized tidal estuaries representing the main hydro-geometrical estuarine classes. The study provides insight into the estuarine biogeochemical dynamics, in particular the air-water CO2/sub> flux, as well as the potential response to future environmental changes and to uncertainties in model parameter values. We believe that our approach could help improving upscaling strategies to better integrate estuaries in regional/global biogeochemical studies.
M. Webber, M. T. Li, J. Chen, B. Finlayson, D. Chen, Z. Y. Chen, M. Wang, and J. Barnett
Hydrol. Earth Syst. Sci., 19, 4411–4425, https://doi.org/10.5194/hess-19-4411-2015, https://doi.org/10.5194/hess-19-4411-2015, 2015
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This paper demonstrates a method for calculating the probability of long-duration salt intrusions in the Yangtze Estuary and examines the impact of the Three Gorges Dam, the South-North Water Transfer Project and local abstractions on that probability. The relationship between river discharge and the intensity and duration of saline intrusions is shown to be probabilistic and continuous. That probability has more than doubled under the normal operating rules for those projects.
F. M. Achete, M. van der Wegen, D. Roelvink, and B. Jaffe
Hydrol. Earth Syst. Sci., 19, 2837–2857, https://doi.org/10.5194/hess-19-2837-2015, https://doi.org/10.5194/hess-19-2837-2015, 2015
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Suspended sediment concentration (SSC) levels are important indicator for the ecology of estuaries. Observations of SSC are difficult to make, therefore we revert to coupled 2-D hydrodynamic-sediment process-based transport models to make predictions in time (seasonal and yearly) and space (meters to kilometers). This paper presents calibration/validation of SSC for the Sacramento-San Joaquin Delta and translates SSC to turbidity in order to couple with ecology models.
J. I. A. Gisen, H. H. G. Savenije, and R. C. Nijzink
Hydrol. Earth Syst. Sci., 19, 2791–2803, https://doi.org/10.5194/hess-19-2791-2015, https://doi.org/10.5194/hess-19-2791-2015, 2015
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We revised the predictive equations for two calibrated parameters in salt intrusion model (the Van der Burgh coefficient K and dispersion coefficient D) using an extended database of 89 salinity profiles including 8 newly conducted salinity measurements. The revised predictive equations consist of easily measured parameters such as the geometry of estuary, tide, friction and the Richardson number. These equations are useful in obtaining the first estimate of salinity distribution in an estuary.
V. D. Vinh, S. Ouillon, T. D. Thanh, and L. V. Chu
Hydrol. Earth Syst. Sci., 18, 3987–4005, https://doi.org/10.5194/hess-18-3987-2014, https://doi.org/10.5194/hess-18-3987-2014, 2014
N. V. Manh, N. V. Dung, N. N. Hung, B. Merz, and H. Apel
Hydrol. Earth Syst. Sci., 18, 3033–3053, https://doi.org/10.5194/hess-18-3033-2014, https://doi.org/10.5194/hess-18-3033-2014, 2014
L. C. Bruce, P. L. M. Cook, I. Teakle, and M. R. Hipsey
Hydrol. Earth Syst. Sci., 18, 1397–1411, https://doi.org/10.5194/hess-18-1397-2014, https://doi.org/10.5194/hess-18-1397-2014, 2014
C. Ferrarin, M. Ghezzo, G. Umgiesser, D. Tagliapietra, E. Camatti, L. Zaggia, and A. Sarretta
Hydrol. Earth Syst. Sci., 17, 1733–1748, https://doi.org/10.5194/hess-17-1733-2013, https://doi.org/10.5194/hess-17-1733-2013, 2013
T. Sun, J. Xu, and Z. F. Yang
Hydrol. Earth Syst. Sci., 17, 751–760, https://doi.org/10.5194/hess-17-751-2013, https://doi.org/10.5194/hess-17-751-2013, 2013
M. Faneca Sànchez, J. L. Gunnink, E. S. van Baaren, G. H. P. Oude Essink, B. Siemon, E. Auken, W. Elderhorst, and P. G. B. de Louw
Hydrol. Earth Syst. Sci., 16, 4499–4516, https://doi.org/10.5194/hess-16-4499-2012, https://doi.org/10.5194/hess-16-4499-2012, 2012
E. F. Zhang, H. H. G. Savenije, S. L. Chen, and X. H. Mao
Hydrol. Earth Syst. Sci., 16, 3327–3339, https://doi.org/10.5194/hess-16-3327-2012, https://doi.org/10.5194/hess-16-3327-2012, 2012
A. van Buuren, L. Gerrits, and G. R. Teisman
Hydrol. Earth Syst. Sci., 14, 2243–2257, https://doi.org/10.5194/hess-14-2243-2010, https://doi.org/10.5194/hess-14-2243-2010, 2010
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Short summary
We develop a conceptual model to quantify the risk of compound events (CEs), i.e. extreme impacts to society which are driven by statistically dependent climatic variables. Based on this model we study compound floods, i.e. joint storm surge and high river level, in Ravenna (Italy). The model includes meteorological predictors which (1) provide insight into the physical processes underlying CEs, as well as into the temporal variability, and (2) allow us to statistically downscale CEs.
We develop a conceptual model to quantify the risk of compound events (CEs), i.e. extreme...