Articles | Volume 25, issue 9
Hydrol. Earth Syst. Sci., 25, 5153–5174, 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
23 Sep 2021
Research article | 23 Sep 2021
A novel method to identify sub-seasonal clustering episodes of extreme precipitation events and their contributions to large accumulation periods
Jérôme Kopp et al.
No articles found.
S. Mubashshir Ali, Matthias Röthlisberger, Tess Parker, Kai Kornhuber, and Olivia Martius
Weather Clim. Dynam., 3, 1139–1156,Short summary
Persistent weather can lead to extreme weather conditions. One such atmospheric flow pattern, termed recurrent Rossby wave packets (RRWPs), has been shown to increase persistent weather in the Northern Hemisphere. Here, we show that RRWPs are also an important feature in the Southern Hemisphere. We evaluate the role of RRWPs during south-eastern Australian heatwaves and find that they help to persist the heatwaves by forming upper-level high-pressure systems over south-eastern Australia.
Kathrin Wehrli, Fei Luo, Mathias Hauser, Hideo Shiogama, Daisuke Tokuda, Hyungjun Kim, Dim Coumou, Wilhelm May, Philippe Le Sager, Frank Selten, Olivia Martius, Robert Vautard, and Sonia I. Seneviratne
Earth Syst. Dynam., 13, 1167–1196,Short summary
The ExtremeX experiment was designed to unravel the contribution of processes leading to the occurrence of recent weather and climate extremes. Global climate simulations are carried out with three models. The results show that in constrained experiments, temperature anomalies during heatwaves are well represented, although climatological model biases remain. Further, a substantial contribution of both atmospheric circulation and soil moisture to heat extremes is identified.
Alexandre Tuel, Bettina Schaefli, Jakob Zscheischler, and Olivia Martius
Hydrol. Earth Syst. Sci., 26, 2649–2669,Short summary
River discharge is strongly influenced by the temporal structure of precipitation. Here, we show how extreme precipitation events that occur a few days or weeks after a previous event have a larger effect on river discharge than events occurring in isolation. Windows of 2 weeks or less between events have the most impact. Similarly, periods of persistent high discharge tend to be associated with the occurrence of several extreme precipitation events in close succession.
Daniel Steinfeld, Adrian Peter, Olivia Martius, and Stefan Brönnimann
Preprint archivedShort summary
We assess the performance of various fire weather indices to predict wildfire occurrence in Northern Switzerland. We find that indices responding readily to weather changes have the best performance during spring; in the summer and autumn seasons, indices that describe persistent hot and dry conditions perform best. We demonstrate that a logistic regression model trained on local historical fire activity can outperform existing fire weather indices.
Lisa-Ann Kautz, Olivia Martius, Stephan Pfahl, Joaquim G. Pinto, Alexandre M. Ramos, Pedro M. Sousa, and Tim Woollings
Weather Clim. Dynam., 3, 305–336,Short summary
Atmospheric blocking is associated with stationary, self-sustaining and long-lasting high-pressure systems. They can cause or at least influence surface weather extremes, such as heat waves, cold spells, heavy precipitation events, droughts or wind extremes. The location of the blocking determines where and what type of extreme event will occur. These relationships are also important for weather prediction and may change due to global warming.
Hélène Barras, Olivia Martius, Luca Nisi, Katharina Schroeer, Alessandro Hering, and Urs Germann
Weather Clim. Dynam., 2, 1167–1185,Short summary
In Switzerland hail may occur several days in a row. Such multi-day hail events may cause significant damage, and understanding and forecasting these events is important. Using reanalysis data we show that weather systems over Europe move slower before and during multi-day hail events compared to single hail days. Surface temperatures are typically warmer and the air more humid over Switzerland and winds are slower on multi-day hail clusters. These results may be used for hail forecasting.
Timothy H. Raupach, Andrey Martynov, Luca Nisi, Alessandro Hering, Yannick Barton, and Olivia Martius
Geosci. Model Dev., 14, 6495–6514,Short summary
When simulated thunderstorms are compared to observations or other simulations, a match between overall storm properties is often more important than exact matches to individual storms. We tested a comparison method that uses a thunderstorm tracking algorithm to characterise simulated storms. For May 2018 in Switzerland, the method produced reasonable matches to independent observations for most storm properties, showing its feasibility for summarising simulated storms over mountainous terrain.
Alexandre Tuel and Olivia Martius
Nat. Hazards Earth Syst. Sci., 21, 2949–2972,Short summary
Extreme river discharge may be triggered by large accumulations of precipitation over short time periods, which can result from the successive occurrence of extreme-precipitation events. We find a distinct spatiotemporal pattern in the temporal clustering behavior of precipitation extremes over Switzerland, with clustering occurring on the northern side of the Alps in winter and on their southern side in fall. Clusters tend to be followed by extreme discharge, particularly in the southern Alps.
Regula Muelchi, Ole Rössler, Jan Schwanbeck, Rolf Weingartner, and Olivia Martius
Hydrol. Earth Syst. Sci., 25, 3577–3594,Short summary
This study analyses changes in magnitude, frequency, and seasonality of moderate low and high flows for 93 catchments in Switzerland. In lower-lying catchments (below 1500 m a.s.l.), moderate low-flow magnitude (frequency) will decrease (increase). In Alpine catchments (above 1500 m a.s.l.), moderate low-flow magnitude (frequency) will increase (decrease). Moderate high flows tend to occur more frequent, and their magnitude increases in most catchments except some Alpine catchments.
Regula Muelchi, Ole Rössler, Jan Schwanbeck, Rolf Weingartner, and Olivia Martius
Hydrol. Earth Syst. Sci., 25, 3071–3086,Short summary
Runoff regimes in Switzerland will change significantly under climate change. Projected changes are strongly elevation dependent with earlier time of emergence and stronger changes in high-elevation catchments where snowmelt and glacier melt play an important role. The magnitude of change and the climate model agreement on the sign increase with increasing global mean temperatures and stronger emission scenarios. This amplification highlights the importance of climate change mitigation.
Johannes Vogel, Pauline Rivoire, Cristina Deidda, Leila Rahimi, Christoph A. Sauter, Elisabeth Tschumi, Karin van der Wiel, Tianyi Zhang, and Jakob Zscheischler
Earth Syst. Dynam., 12, 151–172,Short summary
We present a statistical approach for automatically identifying multiple drivers of extreme impacts based on LASSO regression. We apply the approach to simulated crop failure in the Northern Hemisphere and identify which meteorological variables including climate extreme indices and which seasons are relevant to predict crop failure. The presented approach can help unravel compounding drivers in high-impact events and could be applied to other impacts such as wildfires or flooding.
Jakob Zscheischler, Philippe Naveau, Olivia Martius, Sebastian Engelke, and Christoph C. Raible
Earth Syst. Dynam., 12, 1–16,Short summary
Compound extremes such as heavy precipitation and extreme winds can lead to large damage. To date it is unclear how well climate models represent such compound extremes. Here we present a new measure to assess differences in the dependence structure of bivariate extremes. This measure is applied to assess differences in the dependence of compound precipitation and wind extremes between three model simulations and one reanalysis dataset in a domain in central Europe.
Pauline Rivoire, Yves Tramblay, Luc Neppel, Elke Hertig, and Sergio M. Vicente-Serrano
Nat. Hazards Earth Syst. Sci., 19, 1629–1638,Short summary
In order to define a dry period, a threshold for wet days is usually considered to account for measurement errors and evaporation. In the present study, we compare the threshold of 1 mm d−1, the most commonly used threshold, to a time-varying threshold describing evapotranspiration to compare how the risk of extreme dry spells is estimated with both thresholds. Results indicate that considering a fixed threshold can underestimate extreme dry spells during the extended summer.
Peter Stucki, Moritz Bandhauer, Ulla Heikkilä, Ole Rössler, Massimiliano Zappa, Lucas Pfister, Melanie Salvisberg, Paul Froidevaux, Olivia Martius, Luca Panziera, and Stefan Brönnimann
Nat. Hazards Earth Syst. Sci., 18, 2717–2739,Short summary
A catastrophic flood south of the Alps in 1868 is assessed using documents and the earliest example of high-resolution weather simulation. Simulated weather dynamics agree well with observations and damage reports. Simulated peak water levels are biased. Low forest cover did not cause the flood, but such a paradigm was used to justify afforestation. Supported by historical methods, such numerical simulations allow weather events from past centuries to be used for modern hazard and risk analyses.
Juan José Gómez-Navarro, Christoph C. Raible, Denica Bozhinova, Olivia Martius, Juan Andrés García Valero, and Juan Pedro Montávez
Geosci. Model Dev., 11, 2231–2247,Short summary
We carry out and compare two high-resolution simulations of the Alpine region in the period 1979–2005. We aim to improve the understanding of the local mechanisms leading to extreme events in this complex region. We compare both simulations to precipitation observations to assess the model performance, and attribute major biases to either model or boundary conditions. Further, we develop a new bias correction technique to remove systematic errors in simulated precipitation for impact studies.
Related subject area
Subject: Global hydrology | Techniques and Approaches: Modelling approachesQuantifying overlapping and differing information of global precipitation for GCM forecasts and El Niño–Southern OscillationInvestigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured meshGlobally widespread and increasing violations of environmental flow envelopesInundation prediction in tropical wetlands from JULES-CaMa-Flood global land surface simulationsSoil moisture estimation in South Asia via assimilation of SMAP retrievalsRevisiting large-scale interception patterns constrained by a synthesis of global experimental dataToward hyper-resolution global hydrological models including human activities: application to Kyushu island, JapanTowards hybrid modeling of the global hydrological cycleThe importance of vegetation in understanding terrestrial water storage variationsLarge-scale sensitivities of groundwater and surface water to groundwater withdrawalA hydrography upscaling method for scale-invariant parametrization of distributed hydrological modelsBright and blind spots of water research in Latin America and the CaribbeanLand surface modeling over the Dry Chaco: the impact of model structures, and soil, vegetation and land cover parametersNonstationary weather and water extremes: a review of methods for their detection, attribution, and managementRobust historical evapotranspiration trends across climate regimesA note on leveraging synergy in multiple meteorological data sets with deep learning for rainfall–runoff modelingGlobal scenarios of irrigation water abstractions for bioenergy production: a systematic reviewCoordination and control – limits in standard representations of multi-reservoir operations in hydrological modelingUncertainty of simulated groundwater recharge at different global warming levels: a global-scale multi-model ensemble studyUbiquitous increases in flood magnitude in the Columbia River basin under climate changeEvaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensorsThe role of household adaptation measures in reducing vulnerability to flooding: a coupled agent-based and flood modelling approachAssessing global water mass transfers from continents to oceans over the period 1948–2016Weak sensitivity of the terrestrial water budget to global soil texture maps in the ORCHIDEE land surface modelThe influence of assimilating leaf area index in a land surface model on global water fluxes and storagesComparison of generalized non-data-driven lake and reservoir routing models for global-scale hydrologic forecasting of reservoir outflow at diurnal time stepsThe pantropical response of soil moisture to El NiñoHESS Opinions: Beyond the long-term water balance: evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watershedsGlobal assessment of how averaging over spatial heterogeneity in precipitation and potential evapotranspiration affects modeled evapotranspiration ratesEvaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modelingQuantification of drainable water storage volumes on landmasses and in river networks based on GRACE and river runoff using a cascaded storage approach – first application on the AmazonGlobal catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimationProjected increases in magnitude and socioeconomic exposure of global droughts in 1.5 and 2 °C warmer climatesSpatiotemporal assimilation–interpolation of discharge records through inverse streamflow routingTowards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasetsClimate change, reforestation/afforestation, and urbanization impacts on evapotranspiration and streamflow in EuropeMulti-decadal hydrologic change and variability in the Amazon River basin: understanding terrestrial water storage variations and drought characteristicsMultimodel assessments of human and climate impacts on mean annual streamflow in ChinaImproving soil moisture and runoff simulations at 3 km over Europe using land surface data assimilationToward continental hydrologic–hydrodynamic modeling in South AmericaGlobal re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershedThe effect of climate type on timescales of drought propagation in an ensemble of global hydrological modelsJoint assimilation of soil moisture retrieved from multiple passive microwave frequencies increases robustness of soil moisture state estimationRemote land use impacts on river flows through atmospheric teleconnectionsUnderstanding terrestrial water storage variations in northern latitudes across scalesAssimilation of river discharge in a land surface model to improve estimates of the continental water cyclesHarnessing big data to rethink land heterogeneity in Earth system modelsPredicting groundwater recharge for varying land cover and climate conditions – a global meta-studyNear-real-time adjusted reanalysis forcing data for hydrologyDeduction of reservoir operating rules for application in global hydrological models
Tongtiegang Zhao, Haoling Chen, Yu Tian, Denghua Yan, Weixin Xu, Huayang Cai, Jiabiao Wang, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 26, 4233–4249,Short summary
This paper develops a novel set operations of coefficients of determination (SOCD) method to explicitly quantify the overlapping and differing information for GCM forecasts and ENSO teleconnection. Specifically, the intersection operation of the coefficient of determination derives the overlapping information for GCM forecasts and the Niño3.4 index, and then the difference operation determines the differing information in GCM forecasts (Niño3.4 index) from the Niño3.4 index (GCM forecasts).
Dongyu Feng, Zeli Tan, Darren Engwirda, Chang Liao, Donghui Xu, Gautam Bisht, Tian Zhou, Hong-Yi Li, and Ruby Leung
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript accepted for HESSShort summary
Sea level rise, storm surge and river discharge can cause coastal backwater effects in river’s downstream sections, creating critical flood risks. This study simulates the backwater effects using a large-scale river model on a coastal-refined computational mesh. By decomposing the backwater drivers, we revealed their relative importance and long-term variations. Our analysis highlights the increasing strength of backwater effects due to sea level rise and more frequent storm surge.
Vili Virkki, Elina Alanärä, Miina Porkka, Lauri Ahopelto, Tom Gleeson, Chinchu Mohan, Lan Wang-Erlandsson, Martina Flörke, Dieter Gerten, Simon N. Gosling, Naota Hanasaki, Hannes Müller Schmied, Niko Wanders, and Matti Kummu
Hydrol. Earth Syst. Sci., 26, 3315–3336,Short summary
Direct and indirect human actions have altered streamflow across the world since pre-industrial times. Here, we apply a method of environmental flow envelopes (EFEs) that develops the existing global environmental flow assessments by methodological advances and better consideration of uncertainty. By assessing the violations of the EFE, we comprehensively quantify the frequency, severity, and trends of flow alteration during the past decades, illustrating anthropogenic effects on streamflow.
Toby R. Marthews, Simon J. Dadson, Douglas B. Clark, Eleanor M. Blyth, Garry D. Hayman, Dai Yamazaki, Olivia R. E. Becher, Alberto Martínez-de la Torre, Catherine Prigent, and Carlos Jiménez
Hydrol. Earth Syst. Sci., 26, 3151–3175,Short summary
Reliable data on global inundated areas remain uncertain. By matching a leading global data product on inundation extents (GIEMS) against predictions from a global hydrodynamic model (CaMa-Flood), we found small but consistent and non-random biases in well-known tropical wetlands (Sudd, Pantanal, Amazon and Congo). These result from known limitations in the data and the models used, which shows us how to improve our ability to make critical predictions of inundation events in the future.
Jawairia A. Ahmad, Barton A. Forman, and Sujay V. Kumar
Hydrol. Earth Syst. Sci., 26, 2221–2243,Short summary
Assimilation of remotely sensed data into a land surface model to improve the spatiotemporal estimation of soil moisture across South Asia exhibits potential. Satellite retrieval assimilation corrects biases that are generated due to an unmodeled hydrologic phenomenon, i.e., irrigation. The improvements in fine-scale, modeled soil moisture estimates by assimilating coarse-scale retrievals indicates the utility of the described methodology for data-scarce regions.
Feng Zhong, Shanhu Jiang, Albert I. J. M. van Dijk, Liliang Ren, Jaap Schellekens, and Diego G. Miralles
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript accepted for HESSShort summary
A synthesis of rainfall interception data from past field campaigns is performed, including 166 forests and 17 agricultural plots distributed worldwide. These site data are used to constrain and validate an interception model that considers sub-grid heterogeneity and vegetation dynamics. A global, 40-year (1980–2019) interception dataset is generated at a daily temporal and 0.1º spatial resolution. This dataset will serve as a benchmark for future investigations of the global hydrological cycle.
Naota Hanasaki, Hikari Matsuda, Masashi Fujiwara, Yukiko Hirabayashi, Shinta Seto, Shinjiro Kanae, and Taikan Oki
Hydrol. Earth Syst. Sci., 26, 1953–1975,Short summary
Global hydrological models (GHMs) are usually applied with a spatial resolution of about 50 km, but this time we applied the H08 model, one of the most advanced GHMs, with a high resolution of 2 km to Kyushu island, Japan. Since the model was not accurate as it was, we incorporated local information and improved the model, which revealed detailed water stress in subregions that were not visible with the previous resolution.
Basil Kraft, Martin Jung, Marco Körner, Sujan Koirala, and Markus Reichstein
Hydrol. Earth Syst. Sci., 26, 1579–1614,Short summary
We present a physics-aware machine learning model of the global hydrological cycle. As the model uses neural networks under the hood, the simulations of the water cycle are learned from data, and yet they are informed and constrained by physical knowledge. The simulated patterns lie within the range of existing hydrological models and are plausible. The hybrid modeling approach has the potential to tackle key environmental questions from a novel perspective.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Andreas Güntner, and Martin Jung
Hydrol. Earth Syst. Sci., 26, 1089–1109,Short summary
We assess the effect of how vegetation is defined in a global hydrological model on the composition of total water storage (TWS). We compare two experiments, one with globally uniform and one with vegetation parameters that vary in space and time. While both experiments are constrained against observational data, we found a drastic change in the partitioning of TWS, highlighting the important role of the interaction between groundwater–soil moisture–vegetation in understanding TWS variations.
Marc F. P. Bierkens, Edwin H. Sutanudjaja, and Niko Wanders
Hydrol. Earth Syst. Sci., 25, 5859–5878,Short summary
We introduce a simple analytical framework that allows us to estimate to what extent large-scale groundwater withdrawal affects groundwater levels and streamflow. It also calculates which part of the groundwater withdrawal comes out of groundwater storage and which part from a reduction in streamflow. Global depletion rates obtained with the framework are compared with estimates from satellites, from global- and continental-scale groundwater models, and from in situ datasets.
Dirk Eilander, Willem van Verseveld, Dai Yamazaki, Albrecht Weerts, Hessel C. Winsemius, and Philip J. Ward
Hydrol. Earth Syst. Sci., 25, 5287–5313,Short summary
Digital elevation models and derived flow directions are crucial to distributed hydrological modeling. As the spatial resolution of models is typically coarser than these data, we need methods to upscale flow direction data while preserving the river structure. We propose the Iterative Hydrography Upscaling (IHU) method and show it outperforms other often-applied methods. We publish the multi-resolution MERIT Hydro IHU hydrography dataset and the algorithm as part of the pyflwdir Python package.
Alyssa J. DeVincentis, Hervé Guillon, Romina Díaz Gómez, Noelle K. Patterson, Francine van den Brandeler, Arthur Koehl, J. Pablo Ortiz-Partida, Laura E. Garza-Díaz, Jennifer Gamez-Rodríguez, Erfan Goharian, and Samuel Sandoval Solis
Hydrol. Earth Syst. Sci., 25, 4631–4650,Short summary
Latin America and the Caribbean face many water-related stresses which are expected to worsen with climate change. To assess the vulnerability, we reviewed over 20 000 multilingual research articles using machine learning and an understanding of the regional landscape. Results reveal that the region’s inherent vulnerability is compounded by research blind spots in niche topics (reservoirs and risk assessment) and subregions (Caribbean nations), as well as by its reliance on one country (Brazil).
Michiel Maertens, Gabriëlle J. M. De Lannoy, Sebastian Apers, Sujay V. Kumar, and Sarith P. P. Mahanama
Hydrol. Earth Syst. Sci., 25, 4099–4125,Short summary
In this study, we simulated the water balance over the South American Dry Chaco and assessed the impact of land cover changes thereon using three different land surface models. Our simulations indicated that different models result in a different partitioning of the total water budget, but all showed an increase in soil moisture and percolation over the deforested areas. We also found that, relative to independent data, no specific land surface model is significantly better than another.
Louise J. Slater, Bailey Anderson, Marcus Buechel, Simon Dadson, Shasha Han, Shaun Harrigan, Timo Kelder, Katie Kowal, Thomas Lees, Tom Matthews, Conor Murphy, and Robert L. Wilby
Hydrol. Earth Syst. Sci., 25, 3897–3935,Short summary
Weather and water extremes have devastating effects each year. One of the principal challenges for society is understanding how extremes are likely to evolve under the influence of changes in climate, land cover, and other human impacts. This paper provides a review of the methods and challenges associated with the detection, attribution, management, and projection of nonstationary weather and water extremes.
Sanaa Hobeichi, Gab Abramowitz, and Jason P. Evans
Hydrol. Earth Syst. Sci., 25, 3855–3874,Short summary
Evapotranspiration (ET) links the water, energy and carbon cycle on land. Reliable ET estimates are key to understand droughts and flooding. We develop a new ET dataset, DOLCE V3, by merging multiple global ET datasets, and we show that it matches ET observations better and hence is more reliable than its parent datasets. Next, we use DOLCE V3 to examine recent changes in ET and find that ET has increased over most of the land, decreased in some regions, and has not changed in some other regions
Frederik Kratzert, Daniel Klotz, Sepp Hochreiter, and Grey S. Nearing
Hydrol. Earth Syst. Sci., 25, 2685–2703,Short summary
We investigate how deep learning models use different meteorological data sets in the task of (regional) rainfall–runoff modeling. We show that performance can be significantly improved when using different data products as input and further show how the model learns to combine those meteorological input differently across time and space. The results are carefully benchmarked against classical approaches, showing the supremacy of the presented approach.
Fabian Stenzel, Dieter Gerten, and Naota Hanasaki
Hydrol. Earth Syst. Sci., 25, 1711–1726,Short summary
Ideas to mitigate climate change include the large-scale cultivation of fast-growing plants to capture atmospheric CO2 in biomass. To maximize the productivity of these plants, they will likely be irrigated. However, there is strong disagreement in the literature on how much irrigation water is needed globally, potentially inducing water stress. We provide a comprehensive overview of global irrigation demand studies for biomass production and discuss the diverse underlying study assumptions.
Charles Rougé, Patrick M. Reed, Danielle S. Grogan, Shan Zuidema, Alexander Prusevich, Stanley Glidden, Jonathan R. Lamontagne, and Richard B. Lammers
Hydrol. Earth Syst. Sci., 25, 1365–1388,Short summary
Amid growing interest in using large-scale hydrological models for flood and drought monitoring and forecasting, it is important to evaluate common assumptions these models make. We investigated the representation of reservoirs as separate (non-coordinated) infrastructure. We found that not appropriately representing coordination and control processes can lead a hydrological model to simulate flood and drought events that would not occur given the coordinated emergency response in the basin.
Robert Reinecke, Hannes Müller Schmied, Tim Trautmann, Lauren Seaby Andersen, Peter Burek, Martina Flörke, Simon N. Gosling, Manolis Grillakis, Naota Hanasaki, Aristeidis Koutroulis, Yadu Pokhrel, Wim Thiery, Yoshihide Wada, Satoh Yusuke, and Petra Döll
Hydrol. Earth Syst. Sci., 25, 787–810,Short summary
Billions of people rely on groundwater as an accessible source of drinking water and for irrigation, especially in times of drought. Groundwater recharge is the primary process of regenerating groundwater resources. We find that groundwater recharge will increase in northern Europe by about 19 % and decrease by 10 % in the Amazon with 3 °C global warming. In the Mediterranean, a 2 °C warming has already lead to a reduction in recharge by 38 %. However, these model predictions are uncertain.
Laura E. Queen, Philip W. Mote, David E. Rupp, Oriana Chegwidden, and Bart Nijssen
Hydrol. Earth Syst. Sci., 25, 257–272,Short summary
Using a large ensemble of simulated flows throughout the northwestern USA, we compare daily flood statistics in the past (1950–1999) and future (2050–1999) periods and find that nearly all locations will experience an increase in flood magnitudes. The flood season expands significantly in many currently snow-dominant rivers, moving from only spring to both winter and spring. These results, properly extended, may help inform flood risk management and negotiations of the Columbia River Treaty.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40,Short summary
We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Yared Abayneh Abebe, Amineh Ghorbani, Igor Nikolic, Natasa Manojlovic, Angelika Gruhn, and Zoran Vojinovic
Hydrol. Earth Syst. Sci., 24, 5329–5354,Short summary
The paper presents a coupled agent-based and flood model for Hamburg, Germany. It explores residents’ adaptation behaviour in relation to flood event scenarios, economic incentives and shared and individual strategies. We found that unique trajectories of adaptation behaviour emerge from different flood event series. Providing subsidies improves adaptation behaviour in the long run. The coupled modelling technique allows the role of individual measures in flood risk management to be examined.
Denise Cáceres, Ben Marzeion, Jan Hendrik Malles, Benjamin Daniel Gutknecht, Hannes Müller Schmied, and Petra Döll
Hydrol. Earth Syst. Sci., 24, 4831–4851,Short summary
We analysed how and to which extent changes in water storage on continents had an effect on global ocean mass over the period 1948–2016. Continents lost water to oceans at an accelerated rate, inducing sea level rise. Shrinking glaciers explain 81 % of the long-term continental water mass loss, while declining groundwater levels, mainly due to sustained groundwater pumping for irrigation, is the second major driver. This long-term decline was partly offset by the impoundment of water in dams.
Salma Tafasca, Agnès Ducharne, and Christian Valentin
Hydrol. Earth Syst. Sci., 24, 3753–3774,Short summary
In land surface models (LSMs), soil properties are inferred from soil texture. In this study, we use different input global soil texture maps from the literature to investigate the impact of soil texture on the simulated water budget in an LSM. The medium loamy textures give the highest evapotranspiration and lowest total runoff rates. However, the different soil texture maps result in similar water budgets because of their inherent similarities, especially when upscaled at the 0.5° resolution.
Xinxuan Zhang, Viviana Maggioni, Azbina Rahman, Paul Houser, Yuan Xue, Timothy Sauer, Sujay Kumar, and David Mocko
Hydrol. Earth Syst. Sci., 24, 3775–3788,Short summary
This study assesses the extent to which a land surface model can be optimized via the assimilation of leaf area index (LAI) observations at the global scale. The model performance is evaluated by the model-estimated LAI and five water flux/storage variables. Results show the LAI assimilation reduces errors in the model-estimated LAI. The LAI assimilation also improves the five water variables under wet conditions, but some of the model-estimated variables tend to be worse under dry conditions.
Joseph L. Gutenson, Ahmad A. Tavakoly, Mark D. Wahl, and Michael L. Follum
Hydrol. Earth Syst. Sci., 24, 2711–2729,Short summary
Global-scale hydrologic forecasts should account for attenuation through lakes and reservoirs. There is no consensus on the best approach to estimating this attenuation in large-spatial-scale hydrologic forecasts. This article investigates two existing parsimonious approaches to estimating reservoir outflows. We test each method at 60 reservoirs in the United States. We find that a method first developed in 2003 can provide a reasonable approximation of diurnal reservoir outflows.
Kurt C. Solander, Brent D. Newman, Alessandro Carioca de Araujo, Holly R. Barnard, Z. Carter Berry, Damien Bonal, Mario Bretfeld, Benoit Burban, Luiz Antonio Candido, Rolando Célleri, Jeffery Q. Chambers, Bradley O. Christoffersen, Matteo Detto, Wouter A. Dorigo, Brent E. Ewers, Savio José Filgueiras Ferreira, Alexander Knohl, L. Ruby Leung, Nate G. McDowell, Gretchen R. Miller, Maria Terezinha Ferreira Monteiro, Georgianne W. Moore, Robinson Negron-Juarez, Scott R. Saleska, Christian Stiegler, Javier Tomasella, and Chonggang Xu
Hydrol. Earth Syst. Sci., 24, 2303–2322,Short summary
We evaluate the soil moisture response in the humid tropics to El Niño during the three most recent super El Niño events. Our estimates are compared to in situ soil moisture estimates that span five continents. We find the strongest and most consistent soil moisture decreases in the Amazon and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. Our results can be used to improve estimates of soil moisture in tropical ecohydrology models at multiple scales.
A. Sankarasubramanian, Dingbao Wang, Stacey Archfield, Meredith Reitz, Richard M. Vogel, Amirhossein Mazrooei, and Sudarshana Mukhopadhyay
Hydrol. Earth Syst. Sci., 24, 1975–1984,Short summary
The Budyko framework which relies on the supply and demand concept could be effectively adapted and extended to quantify the role of drivers – both changing climate and local human disturbances – in altering the land-surface response. This framework is extended with a few illustrative examples for quantifying the variability in land-surface fluxes for natural and human-altered watersheds. Potential for using observed and remotely sensed datasets in capturing this variability is also discussed.
Elham Rouholahnejad Freund, Ying Fan, and James W. Kirchner
Hydrol. Earth Syst. Sci., 24, 1927–1938,Short summary
Evapotranspiration (ET) rates and properties that regulate them are spatially heterogeneous. Averaging over spatial heterogeneity in precipitation (P) and potential evapotranspiration (PET) as the main drivers of ET may lead to biased estimates of energy and water fluxes from the land to the atmosphere. We show that this bias is largest in mountainous terrains, in regions with temperate climates and dry summers, and in landscapes where spatial variations in P and PET are inversely correlated.
Shufen Pan, Naiqing Pan, Hanqin Tian, Pierre Friedlingstein, Stephen Sitch, Hao Shi, Vivek K. Arora, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Catherine Ottlé, Benjamin Poulter, Sönke Zaehle, and Steven W. Running
Hydrol. Earth Syst. Sci., 24, 1485–1509,Short summary
Evapotranspiration (ET) links global water, carbon and energy cycles. We used 4 remote sensing models, 2 machine-learning algorithms and 14 land surface models to analyze the changes in global terrestrial ET. These three categories of approaches agreed well in terms of ET intensity. For 1982–2011, all models showed that Earth greening enhanced terrestrial ET. The small interannual variability of global terrestrial ET suggests it has a potential planetary boundary of around 600 mm yr-1.
Hydrol. Earth Syst. Sci., 24, 1447–1465,Short summary
The combined use of GRACE mass anomalies and observed river discharge for the first time allows us to quantify the water storage volumes drainable by gravity on global scales. Modelling of catchment and river network storages in a cascade with different dynamics reveals the time lag between total mass and runoff is caused by a non-zero river network storage. This allows catchment and river network storage volumes to be distinguished and is thus of great importance for water resources management.
Berit Arheimer, Rafael Pimentel, Kristina Isberg, Louise Crochemore, Jafet C. M. Andersson, Abdulghani Hasan, and Luis Pineda
Hydrol. Earth Syst. Sci., 24, 535–559,Short summary
How far can we reach in predicting river flow globally, using integrated catchment modelling and open global data? For the first time, a catchment model was applied world-wide, covering the entire globe with a relatively high resolution. The results show that stepwise calibration provided better performance than traditional modelling of the globe. The study highlights that open data and models are crucial to advance hydrological sciences by sharing knowledge and enabling transparent evaluation.
Lei Gu, Jie Chen, Jiabo Yin, Sylvia C. Sullivan, Hui-Min Wang, Shenglian Guo, Liping Zhang, and Jong-Suk Kim
Hydrol. Earth Syst. Sci., 24, 451–472,Short summary
Focusing on the multifaceted nature of droughts, this study quantifies the change in global drought risks for 1.5 and 2.0 °C warming trajectories by a multi-model ensemble under three representative concentration pathways (RCP2.6, 4.5 and 8.5). Socioeconomic exposures are investigated by incorporating the dynamic shared socioeconomic pathways (SSPs) into the drought impact assessment. The results show that even the ambitious 1.5 °C warming level can cause substantial increases on the global scale.
Colby K. Fisher, Ming Pan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 24, 293–305,Short summary
Poorly monitored river flows in many regions of the world have been hindering our ability to accurately estimate global water usage. In this paper we present a method to derive continuous records of streamflow from a set of in situ gauges. Applying this method to the Ohio River basin, we found that we could reliably generate estimates of streamflow throughout the basin using only a small set of streamflow gauges, which can be useful for global river basins where we do not have good observations.
Frederik Kratzert, Daniel Klotz, Guy Shalev, Günter Klambauer, Sepp Hochreiter, and Grey Nearing
Hydrol. Earth Syst. Sci., 23, 5089–5110,Short summary
A new approach for regional rainfall–runoff modeling using long short-term memory (LSTM)-based models is presented and benchmarked against a range of well-known hydrological models. The approach significantly outperforms regionally calibrated hydrological models but also basin-wise calibrated models. Furthermore, we propose an adaption of the LSTM that allows us to extract the learned catchment understanding of the model and show that it matches our hydrology expert knowledge.
Adriaan J. Teuling, Emile A. G. de Badts, Femke A. Jansen, Richard Fuchs, Joost Buitink, Anne J. Hoek van Dijke, and Shannon M. Sterling
Hydrol. Earth Syst. Sci., 23, 3631–3652,Short summary
Over the past decades, changes in land use and climate over Europe have impacted the average flow of water flowing through rivers and reservoirs (the so-called
water yield). We quantify these changes using a simple but widely tested modelling approach constrained by observations of lysimeters across Europe. Results show that the contribution of land use to changes in water yield are of the same order as changes in climate, showing that impacts of land use changes cannot be neglected.
Suyog Chaudhari, Yadu Pokhrel, Emilio Moran, and Gonzalo Miguez-Macho
Hydrol. Earth Syst. Sci., 23, 2841–2862,Short summary
Comprehensive characterization of extreme drought events in the Amazon is provided with respect to their cause, type, spatial extent, and impact on different water stores. Basin-averaged trends in water storage indicate that the Amazon is getting wetter; however its southern and southeastern portions are getting drier. Water deficit is found to be 3-fold higher than the total water supplied during some drought years. Water deficit due to low precipitation events is absorbed by the groundwater.
Xingcai Liu, Wenfeng Liu, Hong Yang, Qiuhong Tang, Martina Flörke, Yoshimitsu Masaki, Hannes Müller Schmied, Sebastian Ostberg, Yadu Pokhrel, Yusuke Satoh, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 23, 1245–1261,Short summary
Human activities associated with water resource management have significantly increased in China during the past decades. This assessment helps us understand how streamflow has been affected by climate and human activities in China. Our analyses indicate that the climate impact has dominated streamflow changes in most areas, and human activities (in terms of water withdrawals) have increasingly decreased streamflow in the northern basins of China which are vulnerable to future climate change.
Bibi S. Naz, Wolfgang Kurtz, Carsten Montzka, Wendy Sharples, Klaus Goergen, Jessica Keune, Huilin Gao, Anne Springer, Harrie-Jan Hendricks Franssen, and Stefan Kollet
Hydrol. Earth Syst. Sci., 23, 277–301,Short summary
This study investigates the value of assimilating coarse-resolution remotely sensed soil moisture data into high-resolution land surface models for improving soil moisture and runoff modeling. The soil moisture estimates in this study, with complete spatio-temporal coverage and improved spatial resolution from the assimilation, offer a new reanalysis product for the monitoring of surface soil water content and other hydrological fluxes at 3 km resolution over Europe.
Vinícius A. Siqueira, Rodrigo C. D. Paiva, Ayan S. Fleischmann, Fernando M. Fan, Anderson L. Ruhoff, Paulo R. M. Pontes, Adrien Paris, Stéphane Calmant, and Walter Collischonn
Hydrol. Earth Syst. Sci., 22, 4815–4842,Short summary
Providing reliable estimates of water fluxes at the continental scale is challenging. We extended a regional hydrological model to the entirety of South America and assessed its performance using multiple observations. After a comparison with global models, we show the extent to which estimates of daily river discharge can be improved, even by using global forcing data. Issues of global-/continental-scale modeling and future directions for simulating discharge in this continent are discussed.
David R. Casson, Micha Werner, Albrecht Weerts, and Dimitri Solomatine
Hydrol. Earth Syst. Sci., 22, 4685–4697,Short summary
In high-latitude (> 60° N) watersheds, measuring the snowpack and predicting of snowmelt runoff are uncertain due to the lack of data and complex physical processes. This provides challenges for hydrological assessment and operational water management. Global re-analysis datasets have great potential to aid in snowpack representation and snowmelt prediction when combined with a distributed hydrological model, though they still have clear limitations in remote boreal forest and tundra environments.
Anouk I. Gevaert, Ted I. E. Veldkamp, and Philip J. Ward
Hydrol. Earth Syst. Sci., 22, 4649–4665,Short summary
Drought is a natural hazard that has severe environmental and socioeconomic impacts around the globe. Here, we quantified the time taken for drought to propagate from precipitation droughts to soil moisture and streamflow droughts. Results show that propagation timescales are strongly related to climate type, with fast responses in tropical regions and slow responses in arid regions. Insight into the timescales of drought propagation globally may help improve seasonal drought forecasting.
Anouk I. Gevaert, Luigi J. Renzullo, Albert I. J. M. van Dijk, Hans J. van der Woerd, Albrecht H. Weerts, and Richard A. M. de Jeu
Hydrol. Earth Syst. Sci., 22, 4605–4619,Short summary
We assimilated three satellite soil moisture retrievals based on different microwave frequencies into a hydrological model. Two sets of experiments were performed, first assimilating the retrievals individually and then assimilating each set of two retrievals jointly. Overall, assimilation improved agreement between model and field-measured soil moisture. Joint assimilation resulted in model performance similar to or better than assimilating either retrieval individually.
Lan Wang-Erlandsson, Ingo Fetzer, Patrick W. Keys, Ruud J. van der Ent, Hubert H. G. Savenije, and Line J. Gordon
Hydrol. Earth Syst. Sci., 22, 4311–4328,Short summary
Winds carry air moisture from one place to another. Thus, land-use change that alters air moisture content can also modify downwind rainfall and distant river flows. This aspect has rarely been taken into account in studies of river flow changes. We show here that remote land-use change effect on rainfall can exceed that of local, and that foreign nation influence on river flows is much more prevalent than previously thought. This has important implications for both land and water governance.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Annette Eicker, Manfred Fink, Christoph Niemann, and Martin Jung
Hydrol. Earth Syst. Sci., 22, 4061–4082,Short summary
In this study, we adjust a simple hydrological model to several observational datasets, including satellite observations of the land's total water storage. We apply the model to northern latitudes and find that the dominating factor of changes in the total water storage depends on both the spatial and temporal scale of analysis. While snow dominates seasonal variations, liquid water determines year-to-year variations, yet with increasing contribution of snow when averaging over larger regions.
Fuxing Wang, Jan Polcher, Philippe Peylin, and Vladislav Bastrikov
Hydrol. Earth Syst. Sci., 22, 3863–3882,Short summary
This work improves river discharge estimation by taking advantages of observation and model simulations. The new estimation takes into account both gauged and un-gauged rivers, and it compensates model systematic errors and missing processes (e.g., human water usage). This improved estimation is important not only for water resources management and ecosystem health over continent but also for ocean dynamics and salinity.
Nathaniel W. Chaney, Marjolein H. J. Van Huijgevoort, Elena Shevliakova, Sergey Malyshev, Paul C. D. Milly, Paul P. G. Gauthier, and Benjamin N. Sulman
Hydrol. Earth Syst. Sci., 22, 3311–3330,Short summary
The petabytes of existing global environmental data provide an invaluable asset to improve the characterization of land heterogeneity in Earth system models. This study introduces a clustering algorithm that summarizes a domain's heterogeneity through spatially interconnected clusters. A series of land model simulations in central California using this approach illustrate the critical role that multi-scale heterogeneity can have on the macroscale water, energy, and carbon cycles.
Chinchu Mohan, Andrew W. Western, Yongping Wei, and Margarita Saft
Hydrol. Earth Syst. Sci., 22, 2689–2703,Short summary
To ensure a sustainable supply of groundwater, scientific information about what is going into the system as recharge and what is taken out of the system via pumping is essential. This study identified the most influential factors in groundwater recharge and developed an empirical global recharge model. The meteorological and vegetation factors were the most important factors, and the long-term global average recharge was 134 mm per year. This model will aid in groundwater policy-making.
Peter Berg, Chantal Donnelly, and David Gustafsson
Hydrol. Earth Syst. Sci., 22, 989–1000,Short summary
A new product (Global Forcing Data, GFD) that provides bias-adjusted meteorological forcing data for impact models, such as hydrological models, is presented. The main novelty with the product is the near-real time updating of the data which allows more up-to-date impact modeling. This is performed by combining climatological data sets with climate monitoring data sets. The potential in using the data to initialize hydrological forecasts is further investigated.
Hubertus M. Coerver, Martine M. Rutten, and Nick C. van de Giesen
Hydrol. Earth Syst. Sci., 22, 831–851,Short summary
Global hydrological models aim to model hydrological processes, like flows in a river, on a global scale, as opposed to traditional models which are regional. A big challenge in creating these models is the inclusion of impacts on the hydrological cycle caused by humans, for example by the operation of large (hydropower) dams. The presented study investigates a new way to include these impacts by dams into global hydrological models.
Doswell III, C. A., Brooks, H. E., and Maddox, R. A.: Flash flood forecasting: An ingredients-based methodology, Weather Forecast., 11, 560–581, https://doi.org/10.1175/1520-0434(1996)011<0560:FFFAIB>2.0.CO;2, 1996. a
European Environment Agency: Economic losses from climate-related extremes in Europe, available at: https://www.eea.europa.eu/data-and-maps/indicators/direct-losses-from-weather-disasters-4/assessment, (last access: 26 January 2021), 2020. a
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1979 to present, Copernicus Climate Change Service (C3S), CDS – Climate Data Store [data set], https://doi.org/10.24381/cds.adbb2d47, 2018. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a, b
IPCC: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Field, C. B., Barros, V. R., Dokken, D. J., Mach, K. J., Mastrandrea, M. D., Bilir, T. E., Chatterjee, M., Ebi, K. L., Estrada, Y. O., Genova, R. C., Girma, B., Kissel, E. S., Levy, A. N., MacCracken, S., Mastrandrea, P. R., and White, L. L., available at: https://www.ipcc.ch/report/ar5/wg2/ (last access: 15 September 2021), 2014. a
Jordahl, K., den Bossche, J. V., Wasserman, J., McBride, J., Gerard, J., Fleischmann, M., Tratner, J., Perry, M., Farmer, C., Hjelle, G. A., Gillies, S., Cochran, M., Bartos, M., Culbertson, L., Eubank, N., Maxalbert, Rey, S., Bilogur, A., Arribas-Bel, D., Ren, C., Wilson, J., Journois, M., Wolf, L. J., Wasser, L., Özak, Ö., Notoya, Y., Leblanc, F., Holdgraf, C., and Greenhall, A.: geopandas/geopandas: v0.6.0, https://doi.org/10.5281/zenodo.3463125, 2019. a
Lackmann, G.: Midlatitude Synoptic Meteorology: Dynamics, Analysis, and Forecasting, American Meteorological Society, Boston, MA, 2011. a
Lehner, B. and Grill, G.: Global river hydrography and network routing: baseline data and new approaches to study the world’s large river systems, Hydrol. Process., 27, 2171–2186, 2013. a
Lehner, B. and Grill, G.: HydroBASINS, available at: https://www.hydrosheds.org/downloads, last access: 16 September 2021. a
Martius, O., Sodemann, H., Joos, H., Pfahl, S., Winschall, A., Croci-Maspoli, M., Graf, M., Madonna, E., Mueller, B., Schemm, S., Sedláček, J., Sprenger, M., and Wernli, H.: The role of upper-level dynamics and surface processes for the Pakistan flood of July 2010, Q. J. Roy. Meteor. Soc., 139, 1780–1797, https://doi.org/10.1002/qj.2082, 2013. a
Priestley, M. D. K., Dacre, H. F., Shaffrey, L. C., Hodges, K. I., and Pinto, J. G.: The role of serial European windstorm clustering for extreme seasonal losses as determined from multi-centennial simulations of high-resolution global climate model data, Nat. Hazards Earth Syst. Sci., 18, 2991–3006, https://doi.org/10.5194/nhess-18-2991-2018, 2018. a
Raymond, C., Horton, R. M., Zscheischler, J., Martius, O., AghaKouchak, A., Balch, J., Bowen, S. G., Camargo, S. J., Hess, J., Kornhuber, K., Oppenheimer, M., Ruane, A. C., Wahl, T., and White, K.: Understanding and managing connected extreme events, Nat. Clim. Change, 10, 611–621, https://doi.org/10.1038/s41558-020-0790-4, 2020. a
Ripley, B. D.: Spatial Statistics, John Wiley & Sons, Hoboken, NJ, 1981. a
Stephenson, A. G.: evd: Extreme Value Distributions, R News, 2, 0, available at: https://CRAN.R-project.org/doc/Rnews/ (last access: 15 Septebmer 2021), 2002. a
Wilks, D. S.: Statistical Methods in the Atmospheric Sciences, vol. 100, Academic press, Oxford, Waltham, MA, 2011. a
Zscheischler, J., Martius, O., Westra, S., Bevacqua, E., Raymond, C., Horton, R. M., van den Hurk, B., AghaKouchak, A., Jézéquel, A., Mahecha, M. D., Maraun, D., Ramos, A. M., Ridder, N. N., Thiery, W., and Vignotto, E.: A typology of compound weather and climate events, Nat. Rev. Earth Environ., 1, 333–347, https://doi.org/10.1038/s43017-020-0060-z, 2020. a
Episodes of extreme rainfall events happening in close temporal succession can lead to floods with dramatic impacts. We developed a novel method to individually identify those episodes and deduced the regions where they occur frequently and where their impact is substantial. Those regions are the east and northeast of the Asian continent, central Canada and the south of California, Afghanistan, Pakistan, the southwest of the Iberian Peninsula, and north of Argentina and south of Bolivia.
Episodes of extreme rainfall events happening in close temporal succession can lead to floods...