Articles | Volume 21, issue 6
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.
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
CORRESPONDING AUTHOR
Wegener Center for Climate and Global Change, University of Graz, Graz, Austria
Douglas Maraun
Wegener Center for Climate and Global Change, University of Graz, Graz, Austria
Ingrid Hobæk Haff
Department of Mathematics, University of Oslo, Oslo, Norway
Martin Widmann
School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
Mathieu Vrac
Laboratoire des Sciences du Climat et de l'Environnement, CNRS/IPSL, Gif-sur-Yvette, France
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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
Related subject area
Subject: Coasts and Estuaries | Techniques and Approaches: Modelling approaches
Quantifying cascading uncertainty in compound flood modeling with linked process-based and machine learning models
Mangroves as nature-based mitigation for ENSO-driven compound flood risks in a large river delta
Forecasting estuarine salt intrusion in the Rhine–Meuse delta using an LSTM model
Coastal topography and hydrogeology control critical groundwater gradients and potential beach surface instability during storm surges
Effect of tides on river water behavior over the eastern shelf seas of China
Extreme precipitation events induce high fluxes of groundwater and associated nutrients to coastal ocean
Temporally resolved coastal hypoxia forecasting and uncertainty assessment via Bayesian mechanistic modeling
Assessing the dependence structure between oceanographic, fluvial, and pluvial flooding drivers along the United States coastline
Statistical modelling and climate variability of compound surge and precipitation events in a managed water system: a case study in the Netherlands
Estimating the probability of compound floods in estuarine regions
Accretion, retreat and transgression of coastal wetlands experiencing sea-level rise
Climate change overtakes coastal engineering as the dominant driver of hydrological change in a large shallow lagoon
Dynamic mechanism of an extremely severe saltwater intrusion in the Changjiang estuary in February 2014
A novel approach for the assessment of morphological evolution based on observed water levels in tide-dominated estuaries
Seasonal behaviour of tidal damping and residual water level slope in the Yangtze River estuary: identifying the critical position and river discharge for maximum tidal damping
Sediment budget analysis of the Guayas River using a process-based model
Analytical and numerical study of the salinity intrusion in the Sebou river estuary (Morocco) – effect of the “Super Blood Moon” (total lunar eclipse) of 2015
Linking biogeochemistry to hydro-geometrical variability in tidal estuaries: a generic modeling approach
Impact of the Three Gorges Dam, the South–North Water Transfer Project and water abstractions on the duration and intensity of salt intrusions in the Yangtze River estuary
A 2-D process-based model for suspended sediment dynamics: a first step towards ecological modeling
Revised predictive equations for salt intrusion modelling in estuaries
Impact of the Hoa Binh dam (Vietnam) on water and sediment budgets in the Red River basin and delta
Large-scale suspended sediment transport and sediment deposition in the Mekong Delta
Hydrodynamic controls on oxygen dynamics in a riverine salt wedge estuary, the Yarra River estuary, Australia
Assessing hydrological effects of human interventions on coastal systems: numerical applications to the Venice Lagoon
Environmental flow assessments in estuaries based on an integrated multi-objective method
Modelling climate change effects on a Dutch coastal groundwater system using airborne electromagnetic measurements
An analytical solution for tidal propagation in the Yangtze Estuary, China
Understanding and managing the Westerschelde – synchronizing the physical system and the management system of a complex estuary
David F. Muñoz, Hamed Moftakhari, and Hamid Moradkhani
Hydrol. Earth Syst. Sci., 28, 2531–2553, https://doi.org/10.5194/hess-28-2531-2024, https://doi.org/10.5194/hess-28-2531-2024, 2024
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Linking hydrodynamics with machine learning models for compound flood modeling enables a robust characterization of nonlinear interactions among the sources of uncertainty. Such an approach enables the quantification of cascading uncertainty and relative contributions to total uncertainty while also tracking their evolution during compound flooding. The proposed approach is a feasible alternative to conventional statistical approaches designed for uncertainty analyses.
Ignace Pelckmans, Jean-Philippe Belliard, Olivier Gourgue, Luis Elvin Dominguez-Granda, and Stijn Temmerman
Hydrol. Earth Syst. Sci., 28, 1463–1476, https://doi.org/10.5194/hess-28-1463-2024, https://doi.org/10.5194/hess-28-1463-2024, 2024
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The combination of extreme sea levels with increased river flow typically can lead to so-called compound floods. Often these are caused by storms (< 1 d), but climatic events such as El Niño could trigger compound floods over a period of months. We show that the combination of increased sea level and river discharge causes extreme water levels to amplify upstream. Mangrove forests, however, can act as a nature-based flood protection by lowering the extreme water levels coming from the sea.
Bas J. M. Wullems, Claudia C. Brauer, Fedor Baart, and Albrecht H. Weerts
Hydrol. Earth Syst. Sci., 27, 3823–3850, https://doi.org/10.5194/hess-27-3823-2023, https://doi.org/10.5194/hess-27-3823-2023, 2023
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In deltas, saltwater sometimes intrudes far inland and causes problems with freshwater availability. We created a model to forecast salt concentrations at a critical location in the Rhine–Meuse delta in the Netherlands. It requires a rather small number of data to make a prediction and runs fast. It predicts the occurrence of salt concentration peaks well but underestimates the highest peaks. Its speed gives water managers more time to reduce the problems caused by salt intrusion.
Anner Paldor, Nina Stark, Matthew Florence, Britt Raubenheimer, Steve Elgar, Rachel Housego, Ryan S. Frederiks, and Holly A. Michael
Hydrol. Earth Syst. Sci., 26, 5987–6002, https://doi.org/10.5194/hess-26-5987-2022, https://doi.org/10.5194/hess-26-5987-2022, 2022
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Ocean surges can impact the stability of beaches by changing the hydraulic regime. These surge-induced changes in the hydraulic regime have important implications for coastal engineering and for beach morphology. This work uses 3D computer simulations to study how these alterations vary in space and time. We find that certain areas along and across the beach are potentially more vulnerable than others and that previous assumptions regarding the most dangerous places may need to be revised.
Lei Lin, Hao Liu, Xiaomeng Huang, Qingjun Fu, and Xinyu Guo
Hydrol. Earth Syst. Sci., 26, 5207–5225, https://doi.org/10.5194/hess-26-5207-2022, https://doi.org/10.5194/hess-26-5207-2022, 2022
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Earth system (climate) model is an important instrument for projecting the global water cycle and climate change, in which tides are commonly excluded due to the much small timescales compared to the climate. However, we found that tides significantly impact the river water transport pathways, transport timescales, and concentrations in shelf seas. Thus, the tidal effect should be carefully considered in earth system models to accurately project the global water and biogeochemical cycle.
Marc Diego-Feliu, Valentí Rodellas, Aaron Alorda-Kleinglass, Maarten Saaltink, Albert Folch, and Jordi Garcia-Orellana
Hydrol. Earth Syst. Sci., 26, 4619–4635, https://doi.org/10.5194/hess-26-4619-2022, https://doi.org/10.5194/hess-26-4619-2022, 2022
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Rainwater infiltrates aquifers and travels a long subsurface journey towards the ocean where it eventually enters below sea level. In its path towards the sea, water becomes enriched in many compounds that are naturally or artificially present within soils and sediments. We demonstrate that extreme rainfall events may significantly increase the inflow of water to the ocean, thereby increasing the supply of these compounds that are fundamental for the sustainability of coastal ecosystems.
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
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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...
