Articles | Volume 21, issue 6
Hydrol. Earth Syst. Sci., 21, 2701–2723, 2017
https://doi.org/10.5194/hess-21-2701-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 21, 2701–2723, 2017
https://doi.org/10.5194/hess-21-2701-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
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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Shijie Jiang, Emanuele Bevacqua, and Jakob Zscheischler
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-151, https://doi.org/10.5194/hess-2022-151, 2022
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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.
Colin Manning, Emanuele Bevacqua, Martin Widmann, Douglas Maraun, and Anne F. Van Loon
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2022-15, https://doi.org/10.5194/wcd-2022-15, 2022
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This article shows that climate models largely differ in their representation of persistent dry spells that co-occur with extremely high temperatures. Some models simulate dry spells that are too short and too cool compared to observations, while others simulate dry spells that are too long and too hot. This information is important when interpreting the likelihood of such events in a warmer climate so that we can assess the plausibility of their future projections.
Roberto Villalobos-Herrera, Emanuele Bevacqua, Andreia F. S. Ribeiro, Graeme Auld, Laura Crocetti, Bilyana Mircheva, Minh Ha, Jakob Zscheischler, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 21, 1867–1885, https://doi.org/10.5194/nhess-21-1867-2021, https://doi.org/10.5194/nhess-21-1867-2021, 2021
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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.
Emanuele Bevacqua, Michalis I. Vousdoukas, Theodore G. Shepherd, and Mathieu Vrac
Nat. Hazards Earth Syst. Sci., 20, 1765–1782, https://doi.org/10.5194/nhess-20-1765-2020, https://doi.org/10.5194/nhess-20-1765-2020, 2020
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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
local-rainfall-driven CF and CF in small rivers.
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
Marco Hofmann, Claudia Volosciuk, Martin Dubrovský, Douglas Maraun, and Hans R. Schultz
Earth Syst. Dynam., 13, 911–934, https://doi.org/10.5194/esd-13-911-2022, https://doi.org/10.5194/esd-13-911-2022, 2022
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We modelled water budget developments of viticultural growing regions on the spatial scale of individual vineyard plots with respect to landscape features like the available water capacity of the soils, slope, and aspect of the sites. We used an ensemble of climate simulations and focused on the occurrence of drought stress. The results show a high bandwidth of projected changes where the risk of potential drought stress becomes more apparent in steep-slope regions.
Bastien François and Mathieu Vrac
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-127, https://doi.org/10.5194/nhess-2022-127, 2022
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Compound events (CEs) result from a combination of several climate phenomena. In this study, we propose a new methodology to assess the time of emergence of CEs probabilities and to quantify the contribution of marginal and dependence properties of climate phenomena to the overall CE probability changes. By applying our methodology to two case studies, we show the importance of considering both marginal and dependence properties changes for future risk assessments due to compound events.
Antoine Grisart, Mathieu Casado, Vasileios Gkinis, Bo Vinther, Philippe Naveau, Mathieu Vrac, Thomas Laepple, Bénédicte Minster, Fréderic Prié, Barbara Stenni, Elise Fourré, Hans-Christian Steen Larsen, Jean Jouzel, Martin Werner, Katy Pol, Valérie Masson-Delmotte, Maria Hoerhold, Trevor Popp, and Amaelle Landais
EGUsphere, https://doi.org/10.5194/egusphere-2022-168, https://doi.org/10.5194/egusphere-2022-168, 2022
This preprint is open for discussion and under review for Climate of the Past (CP).
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This manuscript presents a compilation of high resolution (11 cm) water isotopic records including published and new measurements over the last 800 000 years on the EPICA Dome C ice core, Antarctica. Using this new water isotopes (δ18O and δD) combined dataset, we study the variability and possible influence of diffusion at multi-decadal to multi-centennial scale. We observe a stronger variability on the onset of the interglacial interval corresponding to a warm period.
Shijie Jiang, Emanuele Bevacqua, and Jakob Zscheischler
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-151, https://doi.org/10.5194/hess-2022-151, 2022
Preprint under review for HESS
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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.
Moctar Dembélé, Mathieu Vrac, Natalie Ceperley, Sander J. Zwart, Josh Larsen, Simon J. Dadson, Grégoire Mariéthoz, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 26, 1481–1506, https://doi.org/10.5194/hess-26-1481-2022, https://doi.org/10.5194/hess-26-1481-2022, 2022
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Climate change impacts on water resources in the Volta River basin are investigated under various global warming scenarios. Results reveal contrasting changes in future hydrological processes and water availability, depending on greenhouse gas emission scenarios, with implications for floods and drought occurrence over the 21st century. These findings provide insights for the elaboration of regional adaptation and mitigation strategies for climate change.
Colin Manning, Emanuele Bevacqua, Martin Widmann, Douglas Maraun, and Anne F. Van Loon
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2022-15, https://doi.org/10.5194/wcd-2022-15, 2022
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This article shows that climate models largely differ in their representation of persistent dry spells that co-occur with extremely high temperatures. Some models simulate dry spells that are too short and too cool compared to observations, while others simulate dry spells that are too long and too hot. This information is important when interpreting the likelihood of such events in a warmer climate so that we can assess the plausibility of their future projections.
Yoann Robin and Mathieu Vrac
Earth Syst. Dynam., 12, 1253–1273, https://doi.org/10.5194/esd-12-1253-2021, https://doi.org/10.5194/esd-12-1253-2021, 2021
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We propose a new multivariate downscaling and bias correction approach called
time-shifted multivariate bias correction, which aims to correct temporal dependencies in addition to inter-variable and spatial ones. Our method is evaluated in a
perfect model experimentcontext where simulations are used as pseudo-observations. The results show a large reduction of the biases in the temporal properties, while inter-variable and spatial dependence structures are still correctly adjusted.
Cedric G. Ngoungue Langue, Christophe Lavaysse, Mathieu Vrac, Philippe Peyrillé, and Cyrille Flamant
Weather Clim. Dynam., 2, 893–912, https://doi.org/10.5194/wcd-2-893-2021, https://doi.org/10.5194/wcd-2-893-2021, 2021
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This work assesses the forecast of the temperature over the Sahara, a key driver of the West African Monsoon, at a seasonal timescale. The seasonal models are able to reproduce the climatological state and some characteristics of the temperature during the rainy season in the Sahel. But, because of errors in the timing, the forecast skill scores are significant only for the first 4 weeks.
Anna Denvil-Sommer, Marion Gehlen, and Mathieu Vrac
Ocean Sci., 17, 1011–1030, https://doi.org/10.5194/os-17-1011-2021, https://doi.org/10.5194/os-17-1011-2021, 2021
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In this work we explored design options for a future Atlantic-scale observational network enabling the release of carbon system estimates by combining data streams from various platforms. We used outputs of a physical–biogeochemical global ocean model at sites of real-world observations to reconstruct surface ocean pCO2 by applying a non-linear feed-forward neural network. The results provide important information for future BGC-Argo deployment, i.e. important regions and the number of floats.
Roberto Villalobos-Herrera, Emanuele Bevacqua, Andreia F. S. Ribeiro, Graeme Auld, Laura Crocetti, Bilyana Mircheva, Minh Ha, Jakob Zscheischler, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 21, 1867–1885, https://doi.org/10.5194/nhess-21-1867-2021, https://doi.org/10.5194/nhess-21-1867-2021, 2021
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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.
Mathieu Vrac and Soulivanh Thao
Geosci. Model Dev., 13, 5367–5387, https://doi.org/10.5194/gmd-13-5367-2020, https://doi.org/10.5194/gmd-13-5367-2020, 2020
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We propose a multivariate bias correction (MBC) method to adjust the spatial and/or inter-variable properties of climate simulations, while also accounting for their temporal dependences (e.g., autocorrelations).
It consists on a method reordering the ranks of the time series according to their multivariate distance to a reference time series.
Results show that temporal correlations are improved while spatial and inter-variable correlations are still satisfactorily corrected.
Emanuele Bevacqua, Michalis I. Vousdoukas, Theodore G. Shepherd, and Mathieu Vrac
Nat. Hazards Earth Syst. Sci., 20, 1765–1782, https://doi.org/10.5194/nhess-20-1765-2020, https://doi.org/10.5194/nhess-20-1765-2020, 2020
Short summary
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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
local-rainfall-driven CF and CF in small rivers.
Bastien François, Mathieu Vrac, Alex J. Cannon, Yoann Robin, and Denis Allard
Earth Syst. Dynam., 11, 537–562, https://doi.org/10.5194/esd-11-537-2020, https://doi.org/10.5194/esd-11-537-2020, 2020
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Recently, multivariate bias correction (MBC) methods designed to adjust climate simulations have been proposed. However, they use different approaches, leading potentially to different results. Therefore, this study intends to intercompare four existing MBC methods to provide end users with aid in choosing such methods for their applications. To do so, a wide range of evaluation criteria have been used to assess the ability of MBC methods to correct statistical properties of climate models.
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
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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.
Lionel Benoit, Mathieu Vrac, and Gregoire Mariethoz
Hydrol. Earth Syst. Sci., 24, 2841–2854, https://doi.org/10.5194/hess-24-2841-2020, https://doi.org/10.5194/hess-24-2841-2020, 2020
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At subdaily resolution, rain intensity exhibits a strong variability in space and time due to the diversity of processes that produce rain (e.g., frontal storms, mesoscale convective systems and local convection). In this paper we explore a new method to simulate rain type time series conditional to meteorological covariates. Afterwards, we apply stochastic rain type simulation to the downscaling of precipitation of a regional climate model.
Florentin Breton, Mathieu Vrac, Pascal Yiou, Pradeebane Vaittinada Ayar, and Aglaé Jézéquel
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2020-26, https://doi.org/10.5194/esd-2020-26, 2020
Revised manuscript not accepted
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We investigate North Atlantic weather seasonality over 1979–2100 by classifying year-round fields of 500 hPa geopotential height from one reanalysis dataset and 12 climate models. Generally, models have seasonal structures similar to the reanalyses. Historical winter (summer) conditions decrease (increase), due to uniform Z500 increase (i.e. uniform warming). However, relative to the increasing Z500 seasonal cycle, future seasonality (spatial patterns, seasonal cycle) appears almost stationary.
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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Observations of relative humidity for ice clouds over the tropical oceans from a passive microwave sounder are downscaled by incorporating the high-resolution variability derived from simultaneous co-located cloud profiles from a lidar. By providing a method to generate pseudo-observations of relative humidity at high spatial resolution, this work will help revisit some of the current key barriers in atmospheric science.
Anna Denvil-Sommer, Marion Gehlen, Mathieu Vrac, and Carlos Mejia
Geosci. Model Dev., 12, 2091–2105, https://doi.org/10.5194/gmd-12-2091-2019, https://doi.org/10.5194/gmd-12-2091-2019, 2019
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This work is dedicated to a new model that reconstructs the surface ocean partial pressure of carbon dioxide (pCO2) over the global ocean on a monthly 1°×1° grid. The model is based on a feed-forward neural network and represents the nonlinear relationships between pCO2 and the ocean drivers. Reconstructed pCO2 has a satisfying accuracy compared to independent observational data and shows a good agreement in seasonal and interannual variability with three existing mapping methods.
Yoann Robin, Mathieu Vrac, Philippe Naveau, and Pascal Yiou
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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Bias correction methods are used to calibrate climate model outputs with respect to observations. In this article, a non-stationary, multivariate and stochastic bias correction method is developed based on optimal transport, accounting for inter-site and inter-variable correlations. Optimal transport allows us to construct a joint distribution that minimizes energy spent in bias correction. Our methodology is tested on precipitation and temperatures over 12 locations in southern France.
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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We propose a method for unsupervised classification of the space–time–intensity structure of weather radar images. The resulting classes are interpreted as rain types, i.e. pools of rain fields with homogeneous statistical properties. Rain types can in turn be used to define stationary periods for further stochastic rainfall modelling. The application of rain typing to real data indicates that non-stationarity can be significant within meteorological seasons, and even within a single storm.
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
Clim. Past, 14, 1315–1330, https://doi.org/10.5194/cp-14-1315-2018, https://doi.org/10.5194/cp-14-1315-2018, 2018
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Recording the precise timing and sequence of events is essential for understanding rapid climate changes and improving climate model predictive skills. Here, we precisely assess the relative timing between ocean and atmospheric changes, both recorded in the same deep-sea core over the last 45 kyr. We show that decreased mid-depth water mass transport in the western equatorial Atlantic preceded increased rainfall over the adjacent continent by 120 to 980 yr, depending on the type of climate event.
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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Cross-validation of free-running bias-corrected climate change simulations against observations is misleading, because it is typically dominated by internal variability. In particular, a sensible bias correction may be rejected and a non-sensible bias correction may be accepted. We therefore propose to avoid cross-validation when evaluating bias correction of free-running bias-corrected climate change simulations. Instead, one should evaluate temporal, spatial and
process-based aspects.
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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Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited due to a paucity of modern instrumental observations. We review how proxy records of past climate and climate model simulations can be used in tandem to understand hydroclimate variability over the last 2000 years and how these tools can also inform risk assessments of future hydroclimatic extremes.
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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Alexey Katin, Dario Del Giudice, and Daniel R. Obenour
Hydrol. Earth Syst. Sci., 26, 1131–1143, https://doi.org/10.5194/hess-26-1131-2022, https://doi.org/10.5194/hess-26-1131-2022, 2022
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Low oxygen conditions (hypoxia) occur almost every summer in the northern Gulf of Mexico. Here, we present a new approach for forecasting hypoxia from June through September, leveraging a process-based model and an advanced statistical framework. We also show how using spring hydrometeorological information can improve forecast accuracy while reducing uncertainties. The proposed forecasting system shows the potential to support the management of threatened coastal ecosystems and fisheries.
Ahmed A. Nasr, Thomas Wahl, Md Mamunur Rashid, Paula Camus, and Ivan D. Haigh
Hydrol. Earth Syst. Sci., 25, 6203–6222, https://doi.org/10.5194/hess-25-6203-2021, https://doi.org/10.5194/hess-25-6203-2021, 2021
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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...
