Articles | Volume 27, issue 7
https://doi.org/10.5194/hess-27-1457-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-27-1457-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Apr 2023
Research article |
| 04 Apr 2023
| 04 Apr 2023
Local moisture recycling across the globe
Jolanda J. E. Theeuwen
CORRESPONDING AUTHOR
Copernicus Institute of Sustainable Development, Utrecht University, 3584 TB Utrecht, the Netherlands
Wetsus, European Centre of Excellence for Sustainable Water
Technology, 8911 MA Leeuwarden, the Netherlands
Arie Staal
Copernicus Institute of Sustainable Development, Utrecht University, 3584 TB Utrecht, the Netherlands
Obbe A. Tuinenburg
Copernicus Institute of Sustainable Development, Utrecht University, 3584 TB Utrecht, the Netherlands
Bert V. M. Hamelers
Wetsus, European Centre of Excellence for Sustainable Water
Technology, 8911 MA Leeuwarden, the Netherlands
Department of Environmental Technology, Wageningen University and
Research, 6708 PB Wageningen, the Netherlands
Stefan C. Dekker
Copernicus Institute of Sustainable Development, Utrecht University, 3584 TB Utrecht, the Netherlands
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Obbe A. Tuinenburg, Jolanda J. E. Theeuwen, and Arie Staal
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We provide a global database of moisture flows through the atmosphere using the most recent ERA5 atmospheric reanalysis. Using this database, it is possible to determine where evaporation will rain out again. However, the reverse is also possible, to determine where precipitation originated from as evaporation. This dataset can be used to determine atmospheric moisture recycling rates and therefore how much water is lost for a catchment through the atmosphere.
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Many areas across the globe rely on upwind land areas for their precipitation supply through terrestrial precipitation recycling. Here we simulate global precipitation recycling in four climate- and land-use scenarios until 2100. We find that global terrestrial moisture recycling decreases by 2.1 % with every degree of global warming, but with strong regional differences.
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The temporal changes and spatial patterns in precipitation events do not show a homogeneous tendency across the Sinai Peninsula. Mediterranean cyclones accompanied by the Red Sea and Persian troughs are responsible for the majority of Sinai's extreme rainfall events. Cyclone tracking captures 156 cyclones (rainfall ≥10 mm d-1) either formed within or transferred to the Mediterranean basin precipitating over Sinai.
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Obbe A. Tuinenburg and Arie Staal
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John O'Connor, Maria J. Santos, Karin T. Rebel, and Stefan C. Dekker
Hydrol. Earth Syst. Sci., 23, 3917–3931, https://doi.org/10.5194/hess-23-3917-2019, https://doi.org/10.5194/hess-23-3917-2019, 2019
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The Amazon rainforest has undergone extensive land use change, which greatly reduces the rate of evapotranspiration. Forest with deep roots is replaced by agriculture with shallow roots. The difference in rooting depth can greatly reduce access to water, especially during the dry season. However, large areas of the Amazon have a sufficiently shallow water table that may provide access for agriculture. We used remote sensing observations to compare the impact of deep and shallow water tables.
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Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-194, https://doi.org/10.5194/hess-2019-194, 2019
Revised manuscript not accepted
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Maarten C. Braakhekke, Karin T. Rebel, Stefan C. Dekker, Benjamin Smith, Arthur H. W. Beusen, and Martin J. Wassen
Earth Syst. Dynam., 8, 1121–1139, https://doi.org/10.5194/esd-8-1121-2017, https://doi.org/10.5194/esd-8-1121-2017, 2017
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Nitrogen input in natural ecosystems usually has a positive effect on plant growth. However, too much N causes N leaching, which contributes to water pollution. Using a global model we estimated that N leaching from natural lands has increased by 73 % during the 20th century, mainly due to rising N deposition from the atmosphere caused by emissions from fossil fuels and agriculture. Climate change and increasing CO2 concentration had positive and negative effects (respectively) on N leaching.
Ruud J. van der Ent and Obbe A. Tuinenburg
Hydrol. Earth Syst. Sci., 21, 779–790, https://doi.org/10.5194/hess-21-779-2017, https://doi.org/10.5194/hess-21-779-2017, 2017
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This research seeks out to answer a fundamental question about the functioning of the water cycle in the atmosphere: how much time does a water particle spend in the atmosphere? Based on state-of-the-art data, we derive a global average residence time of water in the atmosphere of 8–10 days. We further show in this paper how the residence time of water varies in time and space. This serves to illustrate why it is so difficult to make weather predictions on timescales longer than a week.
Rémon Saaltink, Stefan C. Dekker, Jasper Griffioen, and Martin J. Wassen
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We identified biogeochemical plant–soil feedback processes that occur when oxidation, drying and modification by plants alter sediment conditions. Wetland construction in Markermeer (a lake in the Netherlands) is used as a case study. Natural processes will be utilized during and after construction to accelerate ecosystem development. We conducted a 6-month greenhouse experiment to identify the key biogeochemical processes in the mud when Phragmites australis is used as an eco-engineer.
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Our analysis allows us to infer maps of changing plant water-use efficiency (WUE) for 1901–2010, using atmospheric observations of temperature, humidity and CO2. Our estimated increase in global WUE is consistent with the tree-ring and eddy covariance data, but much larger than the historical WUE increases simulated by Earth System Models (ESMs). We therefore conclude that the effects of increasing CO2 on plant WUE are significantly underestimated in the latest climate projections.
Zun Yin, Stefan C. Dekker, Bart J. J. M. van den Hurk, and Henk A. Dijkstra
Biogeosciences, 13, 3343–3357, https://doi.org/10.5194/bg-13-3343-2016, https://doi.org/10.5194/bg-13-3343-2016, 2016
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Bimodality is found in aboveground biomass and mean annual shortwave radiation in West Africa, which is a strong evidence of alternative stable states. The condition with low biomass and low radiation is demonstrated under which ecosystem state can shift between savanna and forest states. Moreover, climatic indicators have different prediction confidences to different land cover types. A new method is proposed to predict potential land cover change with a combination of climatic indicators.
Patrick W. Bogaart, Ype van der Velde, Steve W. Lyon, and Stefan C. Dekker
Hydrol. Earth Syst. Sci., 20, 1413–1432, https://doi.org/10.5194/hess-20-1413-2016, https://doi.org/10.5194/hess-20-1413-2016, 2016
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A. Staal and B. M. Flores
Biogeosciences, 12, 5563–5566, https://doi.org/10.5194/bg-12-5563-2015, https://doi.org/10.5194/bg-12-5563-2015, 2015
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Remote sensing studies indicate that tropical forest and savanna can be alternative stable states maintained by a feedback between tree cover and fire. Veenendaal et al. (2015) attempted to refute this hypothesis with an extensive field study of the vegetation structure and soil conditions at forest–savanna transition zones. With a re-analysis of their data and a conceptual model, we show that in fact the results agree with the idea of forest–savanna bistability.
J. Mao, K. G. J. Nierop, M. Rietkerk, and S. C. Dekker
SOIL, 1, 411–425, https://doi.org/10.5194/soil-1-411-2015, https://doi.org/10.5194/soil-1-411-2015, 2015
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In this study we show how soil water repellency (SWR) is linked to the quantity and quality of SWR markers in soils mainly derived from vegetation. To predict the SWR of topsoils, we find the strongest relationship with ester-bound alcohols, and for subsoils with root-derived ω-hydroxy fatty acids and α,ω-dicarboxylic acids. From this we conclude that, overall, roots influence SWR more strongly than leaves and subsequently SWR markers derived from roots predict SWR better.
M. Baudena, S. C. Dekker, P. M. van Bodegom, B. Cuesta, S. I. Higgins, V. Lehsten, C. H. Reick, M. Rietkerk, S. Scheiter, Z. Yin, M. A. Zavala, and V. Brovkin
Biogeosciences, 12, 1833–1848, https://doi.org/10.5194/bg-12-1833-2015, https://doi.org/10.5194/bg-12-1833-2015, 2015
B. J. Dermody, R. P. H. van Beek, E. Meeks, K. Klein Goldewijk, W. Scheidel, Y. van der Velde, M. F. P. Bierkens, M. J. Wassen, and S. C. Dekker
Hydrol. Earth Syst. Sci., 18, 5025–5040, https://doi.org/10.5194/hess-18-5025-2014, https://doi.org/10.5194/hess-18-5025-2014, 2014
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Our virtual water network of the Roman World shows that virtual water trade and irrigation provided the Romans with resilience to interannual climate variability. Virtual water trade enabled the Romans to meet food demands from regions with a surplus. Irrigation provided stable water supplies for agriculture, particularly in large river catchments. However, virtual water trade also stimulated urbanization and population growth, which eroded Roman resilience to climate variability over time.
Z. Yin, S. C. Dekker, B. J. J. M. van den Hurk, and H. A. Dijkstra
Earth Syst. Dynam., 5, 257–270, https://doi.org/10.5194/esd-5-257-2014, https://doi.org/10.5194/esd-5-257-2014, 2014
Z. Yin, S. C. Dekker, B. J. J. M. van den Hurk, and H. A. Dijkstra
Geosci. Model Dev., 7, 821–845, https://doi.org/10.5194/gmd-7-821-2014, https://doi.org/10.5194/gmd-7-821-2014, 2014
R. J. van der Ent, O. A. Tuinenburg, H.-R. Knoche, H. Kunstmann, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 17, 4869–4884, https://doi.org/10.5194/hess-17-4869-2013, https://doi.org/10.5194/hess-17-4869-2013, 2013
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Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
Spatial variability in the seasonal precipitation lapse rates in complex topographical regions – application in France
Assessing downscaling methods to simulate hydrologically relevant weather scenarios from a global atmospheric reanalysis: case study of the upper Rhône River (1902–2009)
Global total precipitable water variations and trends over the period 1958–2021
Assessing decadal- to centennial-scale nonstationary variability in meteorological drought trends
Identification of compound drought and heatwave events on a daily scale and across four seasons
Potential for historically unprecedented Australian droughts from natural variability and climate change
Flood risk assessment for Indian sub-continental river basins
Key ingredients in regional climate modelling for improving the representation of typhoon tracks and intensities
140-year daily ensemble streamflow reconstructions over 661 catchments in France
Divergent future drought projections in UK river flows and groundwater levels
Predicting extreme sub-hourly precipitation intensification based on temperature shifts
Hydroclimatic processes as the primary drivers of the Early Khvalynian transgression of the Caspian Sea: new developments
Accounting for hydroclimatic properties in flood frequency analysis procedures
An increase in the spatial extent of European floods over the last 70 years
Understanding the influence of “hot” models in climate impact studies: a hydrological perspective
A semi-parametric hourly space–time weather generator
A principal-component-based strategy for regionalisation of precipitation intensity–duration–frequency (IDF) statistics
Accounting for precipitation asymmetry in a multiplicative random cascade disaggregation model
Improving Runoff Simulation in the Western United States with Noah-MP and VIC
Machine learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks
Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach
A genetic particle filter scheme for univariate snow cover assimilation into Noah-MP model across snow climates
Investigating the response of land–atmosphere interactions and feedbacks to spatial representation of irrigation in a coupled modeling framework
Validation of precipitation reanalysis products for rainfall-runoff modelling in Slovenia
The agricultural expansion in South America’s Dry Chaco: Regional hydroclimate effects
Statistical post-processing of precipitation forecasts using circulation classifications and spatiotemporal deep neural networks
Sensitivity of the pseudo-global warming method under flood conditions: a case study from the northeastern US
Hybrid forecasting: blending climate predictions with AI models
Sensitivities of subgrid-scale physics schemes, meteorological forcing, and topographic radiation in atmosphere-through-bedrock integrated process models: a case study in the Upper Colorado River basin
How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation?
Regionalisation of rainfall depth–duration–frequency curves with different data types in Germany
The suitability of a seasonal ensemble hybrid framework including data-driven approaches for hydrological forecasting
Continuous streamflow prediction in ungauged basins: long short-term memory neural networks clearly outperform traditional hydrological models
Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System
Spatial distribution of oceanic moisture contributions to precipitation over the Tibetan Plateau
Ensemble streamflow prediction considering the influence of reservoirs in Narmada River Basin, India
Declining water resources in response to global warming and changes in atmospheric circulation patterns over southern Mediterranean France
Linking the complementary evaporation relationship with the Budyko framework for ungauged areas in Australia
Risks of seasonal extreme rainfall events in Bangladesh under 1.5 and 2.0 °C warmer worlds – how anthropogenic aerosols change the story
Pan evaporation is increased by submerged macrophytes
Evaluation of water flux predictive models developed using eddy-covariance observations and machine learning: a meta-analysis
Characterizing basin-scale precipitation gradients in the Third Pole region using a high-resolution atmospheric simulation-based dataset
A comparison of hydrological models with different level of complexity in Alpine regions in the context of climate change
Modelling evaporation with local, regional and global BROOK90 frameworks: importance of parameterization and forcing
Hydrological concept formation inside long short-term memory (LSTM) networks
A two-step merging strategy for incorporating multi-source precipitation products and gauge observations using machine learning classification and regression over China
Hydrometeorological evaluation of two nowcasting systems for Mediterranean heavy precipitation events with operational considerations
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Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
Hydrol. Earth Syst. Sci., 28, 2579–2601, https://doi.org/10.5194/hess-28-2579-2024, https://doi.org/10.5194/hess-28-2579-2024, 2024
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The increase in precipitation as a function of elevation is poorly understood in areas with complex topography. In this article, the reproduction of these orographic gradients is assessed with several precipitation products. The best product is a simulation from a convection-permitting regional climate model. The corresponding seasonal gradients vary significantly in space, with higher values for the first topographical barriers exposed to the dominant air mass circulations.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci., 28, 2139–2166, https://doi.org/10.5194/hess-28-2139-2024, https://doi.org/10.5194/hess-28-2139-2024, 2024
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Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
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Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Kyungmin Sung, Max C. A. Torbenson, and James H. Stagge
Hydrol. Earth Syst. Sci., 28, 2047–2063, https://doi.org/10.5194/hess-28-2047-2024, https://doi.org/10.5194/hess-28-2047-2024, 2024
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This study examines centuries of nonstationary trends in meteorological drought and pluvial climatology. A novel approach merges tree-ring proxy data (North American Seasonal Precipitation Atlas – NASPA) with instrumental precipitation datasets by temporally downscaling proxy data, correcting biases, and analyzing shared trends in normal and extreme precipitation anomalies. We identify regions experiencing recent unprecedented shifts towards drier or wetter conditions and shifts in seasonality.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
Hydrol. Earth Syst. Sci., 28, 2065–2080, https://doi.org/10.5194/hess-28-2065-2024, https://doi.org/10.5194/hess-28-2065-2024, 2024
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This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves (CDHW) across four seasons. Using this method, we could establish the start and/or end dates of drought (or heatwave) events. We found an increase in the frequency of heatwaves and CDHW events in Belgium caused by climate change. We also found that different months have different chances of CDHW events.
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
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Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
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A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
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Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-42, https://doi.org/10.5194/hess-2024-42, 2024
Revised manuscript accepted for HESS
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The recent development of the a new meteorological dataset providing precipitation and temperature over France – FYRE Climate – has been transformed to streamflow time series over 1871–2012 through the used of a hydrological model. This led to the creation of the daily hydrological reconstructions called HyDRE and HyDRE. These two reconstructions are evaluated allow to better understand the variability of past hydrology over France.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
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We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
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We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
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Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
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Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
EGUsphere, https://doi.org/10.5194/egusphere-2023-2890, https://doi.org/10.5194/egusphere-2023-2890, 2024
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We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extents' trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
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Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
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Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci., 27, 3719–3732, https://doi.org/10.5194/hess-27-3719-2023, https://doi.org/10.5194/hess-27-3719-2023, 2023
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Intensity–duration–frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, for example, for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations, which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
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High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
EGUsphere, https://doi.org/10.5194/egusphere-2023-2164, https://doi.org/10.5194/egusphere-2023-2164, 2023
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We used a systematic method to fine-tune two widely used models in 263 river basins in the Western U.S. Then, we developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins . We assessed factors that influence the performance of the parameter estimation and extension. We also checked how well the two models could simulate high and low river flows and saw notable enhancements. This helps studies on regional river flow simulation and forecast.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-181, https://doi.org/10.5194/hess-2023-181, 2023
Revised manuscript accepted for HESS
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Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using 5 bias-corrected GCM outputs under three shared socioeconomic pathways, five hydrological models and a deep learning model.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
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In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Yuanhong You, Chunlin Huang, Zuo Wang, Jinliang Hou, Ying Zhang, and Peipei Xu
Hydrol. Earth Syst. Sci., 27, 2919–2933, https://doi.org/10.5194/hess-27-2919-2023, https://doi.org/10.5194/hess-27-2919-2023, 2023
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This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.
Patricia Lawston-Parker, Joseph A. Santanello Jr., and Nathaniel W. Chaney
Hydrol. Earth Syst. Sci., 27, 2787–2805, https://doi.org/10.5194/hess-27-2787-2023, https://doi.org/10.5194/hess-27-2787-2023, 2023
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Irrigation has been shown to impact weather and climate, but it has only recently been considered in prediction models. Prescribing where (globally) irrigation takes place is important to accurately simulate its impacts on temperature, humidity, and precipitation. Here, we evaluated three different irrigation maps in a weather model and found that the extent and intensity of irrigated areas and their boundaries are important drivers of weather impacts resulting from human practices.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
Hydrol. Earth Syst. Sci., 27, 2559–2578, https://doi.org/10.5194/hess-27-2559-2023, https://doi.org/10.5194/hess-27-2559-2023, 2023
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For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.
María Agostina Bracalenti, Omar Vicente Müller, Miguel Angel Lovino, and Ernesto Hugo Berbery
EGUsphere, https://doi.org/10.5194/egusphere-2023-1427, https://doi.org/10.5194/egusphere-2023-1427, 2023
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The Gran Chaco is a large dry forest in South America that has been heavily deforested, particularly in the Dry Chaco subregion. This deforestation has changed the land’s characteristics, affecting the local and regional climate. The study reveals that deforestation has resulted in reduced precipitation, soil moisture, and runoff, and if intensive agriculture continues, it could make summers in this arid region even drier and hotter.
Tuantuan Zhang, Zhongmin Liang, Wentao Li, Jun Wang, Yiming Hu, and Binquan Li
Hydrol. Earth Syst. Sci., 27, 1945–1960, https://doi.org/10.5194/hess-27-1945-2023, https://doi.org/10.5194/hess-27-1945-2023, 2023
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We use circulation classifications and spatiotemporal deep neural networks to correct raw daily forecast precipitation by combining large-scale circulation patterns with local spatiotemporal information. We find that the method not only captures the westward and northward movement of the western Pacific subtropical high but also shows substantially higher bias-correction capabilities than existing standard methods in terms of spatial scale, timescale, and intensity.
Zeyu Xue, Paul Ullrich, and Lai-Yung Ruby Leung
Hydrol. Earth Syst. Sci., 27, 1909–1927, https://doi.org/10.5194/hess-27-1909-2023, https://doi.org/10.5194/hess-27-1909-2023, 2023
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We examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments and varying the perturbation spatial scales and choice of perturbed meteorological variables to provide a guideline for this increasingly popular regional modeling method. Overall, we recommend PGW experiments be performed with perturbations to temperature or the combination of temperature and wind at the gridpoint scale, depending on the research question.
Louise J. Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023, https://doi.org/10.5194/hess-27-1865-2023, 2023
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Hybrid forecasting systems combine data-driven methods with physics-based weather and climate models to improve the accuracy of predictions for meteorological and hydroclimatic events such as rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. We review recent developments in hybrid forecasting and outline key challenges and opportunities in the field.
Zexuan Xu, Erica R. Siirila-Woodburn, Alan M. Rhoades, and Daniel Feldman
Hydrol. Earth Syst. Sci., 27, 1771–1789, https://doi.org/10.5194/hess-27-1771-2023, https://doi.org/10.5194/hess-27-1771-2023, 2023
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The goal of this study is to understand the uncertainties of different modeling configurations for simulating hydroclimate responses in the mountainous watershed. We run a group of climate models with various configurations and evaluate them against various reference datasets. This paper integrates a climate model and a hydrology model to have a full understanding of the atmospheric-through-bedrock hydrological processes.
Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, Giuseppe Formetta, Christoph Schär, and Marco Borga
Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, https://doi.org/10.5194/hess-27-1133-2023, 2023
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Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Bora Shehu, Winfried Willems, Henrike Stockel, Luisa-Bianca Thiele, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 1109–1132, https://doi.org/10.5194/hess-27-1109-2023, https://doi.org/10.5194/hess-27-1109-2023, 2023
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Rainfall volumes at varying duration and frequencies are required for many engineering water works. These design volumes have been provided by KOSTRA-DWD in Germany. However, a revision of the KOSTRA-DWD is required, in order to consider the recent state-of-the-art and additional data. For this purpose, in our study, we investigate different methods and data available to achieve the best procedure that will serve as a basis for the development of the new KOSTRA-DWD product.
Sandra M. Hauswirth, Marc F. P. Bierkens, Vincent Beijk, and Niko Wanders
Hydrol. Earth Syst. Sci., 27, 501–517, https://doi.org/10.5194/hess-27-501-2023, https://doi.org/10.5194/hess-27-501-2023, 2023
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Forecasts on water availability are important for water managers. We test a hybrid framework based on machine learning models and global input data for generating seasonal forecasts. Our evaluation shows that our discharge and surface water level predictions are able to create reliable forecasts up to 2 months ahead. We show that a hybrid framework, developed for local purposes and combined and rerun with global data, can create valuable information similar to large-scale forecasting models.
Richard Arsenault, Jean-Luc Martel, Frédéric Brunet, François Brissette, and Juliane Mai
Hydrol. Earth Syst. Sci., 27, 139–157, https://doi.org/10.5194/hess-27-139-2023, https://doi.org/10.5194/hess-27-139-2023, 2023
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Predicting flow in rivers where no observation records are available is a daunting task. For decades, hydrological models were set up on these gauges, and their parameters were estimated based on the hydrological response of similar or nearby catchments where records exist. New developments in machine learning have now made it possible to estimate flows at ungauged locations more precisely than with hydrological models. This study confirms the performance superiority of machine learning models.
Shaun Harrigan, Ervin Zsoter, Hannah Cloke, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 27, 1–19, https://doi.org/10.5194/hess-27-1-2023, https://doi.org/10.5194/hess-27-1-2023, 2023
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Real-time river discharge forecasts and reforecasts from the Global Flood Awareness System (GloFAS) have been made publicly available, together with an evaluation of forecast skill at the global scale. Results show that GloFAS is skillful in over 93 % of catchments in the short (1–3 d) and medium range (5–15 d) and skillful in over 80 % of catchments in the extended lead time (16–30 d). Skill is summarised in a new layer on the GloFAS Web Map Viewer to aid decision-making.
Ying Li, Chenghao Wang, Ru Huang, Denghua Yan, Hui Peng, and Shangbin Xiao
Hydrol. Earth Syst. Sci., 26, 6413–6426, https://doi.org/10.5194/hess-26-6413-2022, https://doi.org/10.5194/hess-26-6413-2022, 2022
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Spatial quantification of oceanic moisture contribution to the precipitation over the Tibetan Plateau (TP) contributes to the reliable assessments of regional water resources and the interpretation of paleo archives in the region. Based on atmospheric reanalysis datasets and numerical moisture tracking, this work reveals the previously underestimated oceanic moisture contributions brought by the westerlies in winter and the overestimated moisture contributions from the Indian Ocean in summer.
Urmin Vegad and Vimal Mishra
Hydrol. Earth Syst. Sci., 26, 6361–6378, https://doi.org/10.5194/hess-26-6361-2022, https://doi.org/10.5194/hess-26-6361-2022, 2022
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Floods cause enormous damage to infrastructure and agriculture in India. However, the utility of ensemble meteorological forecast for hydrologic prediction has not been examined. Moreover, Indian river basins have a considerable influence of reservoirs that alter the natural flow variability. We developed a hydrologic modelling-based streamflow prediction considering the influence of reservoirs in India.
Camille Labrousse, Wolfgang Ludwig, Sébastien Pinel, Mahrez Sadaoui, Andrea Toreti, and Guillaume Lacquement
Hydrol. Earth Syst. Sci., 26, 6055–6071, https://doi.org/10.5194/hess-26-6055-2022, https://doi.org/10.5194/hess-26-6055-2022, 2022
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The interest of this study is to demonstrate that we identify two zones in our study area whose hydroclimatic behaviours are uneven. By investigating relationships between the hydroclimatic conditions in both clusters for past observations with the overall atmospheric functioning, we show that the inequalities are mainly driven by a different control of the atmospheric teleconnection patterns over the area.
Daeha Kim, Minha Choi, and Jong Ahn Chun
Hydrol. Earth Syst. Sci., 26, 5955–5969, https://doi.org/10.5194/hess-26-5955-2022, https://doi.org/10.5194/hess-26-5955-2022, 2022
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We proposed a practical method that predicts the evaporation rates on land surfaces (ET) where only atmospheric data are available. Using a traditional equation that describes partitioning of precipitation into ET and streamflow, we could approximately identify the key parameter of the predicting formulation based on land–atmosphere interactions. The simple method conditioned by local climates outperformed sophisticated models in reproducing water-balance estimates across Australia.
Ruksana H. Rimi, Karsten Haustein, Emily J. Barbour, Sarah N. Sparrow, Sihan Li, David C. H. Wallom, and Myles R. Allen
Hydrol. Earth Syst. Sci., 26, 5737–5756, https://doi.org/10.5194/hess-26-5737-2022, https://doi.org/10.5194/hess-26-5737-2022, 2022
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Extreme rainfall events are major concerns in Bangladesh. Heavy downpours can cause flash floods and damage nearly harvestable crops in pre-monsoon season. While in monsoon season, the impacts can range from widespread agricultural loss, huge property damage, to loss of lives and livelihoods. This paper assesses the role of anthropogenic climate change drivers in changing risks of extreme rainfall events during pre-monsoon and monsoon seasons at local sub-regional-scale within Bangladesh.
Brigitta Simon-Gáspár, Gábor Soós, and Angela Anda
Hydrol. Earth Syst. Sci., 26, 4741–4756, https://doi.org/10.5194/hess-26-4741-2022, https://doi.org/10.5194/hess-26-4741-2022, 2022
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Due to climate change, it is extremely important to determine evaporation as accurately as possible. In nature, there are sediments and macrophytes in the open waters; thus, one of the aims was to investigate their effect on evaporation. The second aim of this paper was to estimate daily evaporation by using different models, which, according to results, have high priority in the evaporation prediction. Water management can obtain useful information from the results of the current research.
Haiyang Shi, Geping Luo, Olaf Hellwich, Mingjuan Xie, Chen Zhang, Yu Zhang, Yuangang Wang, Xiuliang Yuan, Xiaofei Ma, Wenqiang Zhang, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 26, 4603–4618, https://doi.org/10.5194/hess-26-4603-2022, https://doi.org/10.5194/hess-26-4603-2022, 2022
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There have been many machine learning simulation studies based on eddy-covariance observations for water flux and evapotranspiration. We performed a meta-analysis of such studies to clarify the impact of different algorithms and predictors, etc., on the reported prediction accuracy. It can, to some extent, guide future global water flux modeling studies and help us better understand the terrestrial ecosystem water cycle.
Yaozhi Jiang, Kun Yang, Hua Yang, Hui Lu, Yingying Chen, Xu Zhou, Jing Sun, Yuan Yang, and Yan Wang
Hydrol. Earth Syst. Sci., 26, 4587–4601, https://doi.org/10.5194/hess-26-4587-2022, https://doi.org/10.5194/hess-26-4587-2022, 2022
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Our study quantified the altitudinal precipitation gradients (PGs) over the Third Pole (TP). Most sub-basins in the TP have positive PGs, and negative PGs are found in the Himalayas, the Hengduan Mountains and the western Kunlun. PGs are positively correlated with wind speed but negatively correlated with relative humidity. In addition, PGs tend to be positive at smaller spatial scales compared to those at larger scales. The findings can assist precipitation interpolation in the data-sparse TP.
Francesca Carletti, Adrien Michel, Francesca Casale, Alice Burri, Daniele Bocchiola, Mathias Bavay, and Michael Lehning
Hydrol. Earth Syst. Sci., 26, 3447–3475, https://doi.org/10.5194/hess-26-3447-2022, https://doi.org/10.5194/hess-26-3447-2022, 2022
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High Alpine catchments are dominated by the melting of seasonal snow cover and glaciers, whose amount and seasonality are expected to be modified by climate change. This paper compares the performances of different types of models in reproducing discharge among two catchments under present conditions and climate change. Despite many advantages, the use of simpler models for climate change applications is controversial as they do not fully represent the physics of the involved processes.
Ivan Vorobevskii, Thi Thanh Luong, Rico Kronenberg, Thomas Grünwald, and Christian Bernhofer
Hydrol. Earth Syst. Sci., 26, 3177–3239, https://doi.org/10.5194/hess-26-3177-2022, https://doi.org/10.5194/hess-26-3177-2022, 2022
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In the study we analysed the uncertainties of the meteorological data and model parameterization for evaporation modelling. We have taken a physically based lumped BROOK90 model and applied it in three different frameworks using global, regional and local datasets. Validating the simulations with eddy-covariance data from five stations in Germany, we found that the accuracy model parameterization plays a bigger role than the quality of the meteorological forcing.
Thomas Lees, Steven Reece, Frederik Kratzert, Daniel Klotz, Martin Gauch, Jens De Bruijn, Reetik Kumar Sahu, Peter Greve, Louise Slater, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 26, 3079–3101, https://doi.org/10.5194/hess-26-3079-2022, https://doi.org/10.5194/hess-26-3079-2022, 2022
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Despite the accuracy of deep learning rainfall-runoff models, we are currently uncertain of what these models have learned. In this study we explore the internals of one deep learning architecture and demonstrate that the model learns about intermediate hydrological stores of soil moisture and snow water, despite never having seen data about these processes during training. Therefore, we find evidence that the deep learning approach learns a physically realistic mapping from inputs to outputs.
Huajin Lei, Hongyu Zhao, and Tianqi Ao
Hydrol. Earth Syst. Sci., 26, 2969–2995, https://doi.org/10.5194/hess-26-2969-2022, https://doi.org/10.5194/hess-26-2969-2022, 2022
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How to combine multi-source precipitation data effectively is one of the hot topics in hydrometeorological research. This study presents a two-step merging strategy based on machine learning for multi-source precipitation merging over China. The results demonstrate that the proposed method effectively distinguishes the occurrence of precipitation events and reduces the error in precipitation estimation. This method is robust and may be successfully applied to other areas even with scarce data.
Alexane Lovat, Béatrice Vincendon, and Véronique Ducrocq
Hydrol. Earth Syst. Sci., 26, 2697–2714, https://doi.org/10.5194/hess-26-2697-2022, https://doi.org/10.5194/hess-26-2697-2022, 2022
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The hydrometeorological skills of two new nowcasting systems for forecasting Mediterranean intense rainfall events and floods are investigated. The results reveal that up to 75 or 90 min of forecast the performance of the nowcasting system blending numerical weather prediction and extrapolation of radar estimation is higher than the numerical weather model. For lead times up to 3 h the skills are equivalent in general. Using these nowcasting systems for flash flood forecasting is also promising.
Alexandre Tuel, Bettina Schaefli, Jakob Zscheischler, and Olivia Martius
Hydrol. Earth Syst. Sci., 26, 2649–2669, https://doi.org/10.5194/hess-26-2649-2022, https://doi.org/10.5194/hess-26-2649-2022, 2022
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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.
Hanieh Seyedhashemi, Jean-Philippe Vidal, Jacob S. Diamond, Dominique Thiéry, Céline Monteil, Frédéric Hendrickx, Anthony Maire, and Florentina Moatar
Hydrol. Earth Syst. Sci., 26, 2583–2603, https://doi.org/10.5194/hess-26-2583-2022, https://doi.org/10.5194/hess-26-2583-2022, 2022
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Stream temperature appears to be increasing globally, but its rate remains poorly constrained due to a paucity of long-term data. Using a thermal model, this study provides a large-scale understanding of the evolution of stream temperature over a long period (1963–2019). This research highlights that air temperature and streamflow can exert joint influence on stream temperature trends, and riparian shading in small mountainous streams may mitigate warming in stream temperatures.
Shakirudeen Lawal, Stephen Sitch, Danica Lombardozzi, Julia E. M. S. Nabel, Hao-Wei Wey, Pierre Friedlingstein, Hanqin Tian, and Bruce Hewitson
Hydrol. Earth Syst. Sci., 26, 2045–2071, https://doi.org/10.5194/hess-26-2045-2022, https://doi.org/10.5194/hess-26-2045-2022, 2022
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To investigate the impacts of drought on vegetation, which few studies have done due to various limitations, we used the leaf area index as proxy and dynamic global vegetation models (DGVMs) to simulate drought impacts because the models use observationally derived climate. We found that the semi-desert biome responds strongly to drought in the summer season, while the tropical forest biome shows a weak response. This study could help target areas to improve drought monitoring and simulation.
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Short summary
Evaporation changes over land affect rainfall over land via moisture recycling. We calculated the local moisture recycling ratio globally, which describes the fraction of evaporated moisture that rains out within approx. 50 km of its source location. This recycling peaks in summer as well as over wet and elevated regions. Local moisture recycling provides insight into the local impacts of evaporation changes and can be used to study the influence of regreening on local rainfall.
Evaporation changes over land affect rainfall over land via moisture recycling. We calculated...
