Articles | Volume 26, issue 12
https://doi.org/10.5194/hess-26-3177-2022
© Author(s) 2022. 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-26-3177-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jun 2022
Research article |
| 22 Jun 2022
| 22 Jun 2022
Modelling evaporation with local, regional and global BROOK90 frameworks: importance of parameterization and forcing
Ivan Vorobevskii
CORRESPONDING AUTHOR
Faculty of Environmental Sciences, Department of Hydrosciences, Institute of Hydrology and Meteorology, Chair of Meteorology, Technische Universität
Dresden, Tharandt 01737, Germany
Thi Thanh Luong
Faculty of Environmental Sciences, Department of Hydrosciences, Institute of Hydrology and Meteorology, Chair of Meteorology, Technische Universität
Dresden, Tharandt 01737, Germany
Rico Kronenberg
Faculty of Environmental Sciences, Department of Hydrosciences, Institute of Hydrology and Meteorology, Chair of Meteorology, Technische Universität
Dresden, Tharandt 01737, Germany
Thomas Grünwald
Faculty of Environmental Sciences, Department of Hydrosciences, Institute of Hydrology and Meteorology, Chair of Meteorology, Technische Universität
Dresden, Tharandt 01737, Germany
Christian Bernhofer
Faculty of Environmental Sciences, Department of Hydrosciences, Institute of Hydrology and Meteorology, Chair of Meteorology, Technische Universität
Dresden, Tharandt 01737, Germany
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X. Wu, N. Vuichard, P. Ciais, N. Viovy, N. de Noblet-Ducoudré, X. Wang, V. Magliulo, M. Wattenbach, L. Vitale, P. Di Tommasi, E. J. Moors, W. Jans, J. Elbers, E. Ceschia, T. Tallec, C. Bernhofer, T. Grünwald, C. Moureaux, T. Manise, A. Ligne, P. Cellier, B. Loubet, E. Larmanou, and D. Ripoche
Geosci. Model Dev., 9, 857–873, https://doi.org/10.5194/gmd-9-857-2016, https://doi.org/10.5194/gmd-9-857-2016, 2016
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The response of crops to changing climate and atmospheric CO2 could have large effects on food production, terrestrial carbon, water, energy fluxes and the climate feedbacks. We developed a new process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module into the land surface model ORCHIDEE. Our model has good ability to capture the spatial gradients of crop phenology, carbon and energy-related variables across Europe.
A. Collalti, S. Marconi, A. Ibrom, C. Trotta, A. Anav, E. D'Andrea, G. Matteucci, L. Montagnani, B. Gielen, I. Mammarella, T. Grünwald, A. Knohl, F. Berninger, Y. Zhao, R. Valentini, and M. Santini
Geosci. Model Dev., 9, 479–504, https://doi.org/10.5194/gmd-9-479-2016, https://doi.org/10.5194/gmd-9-479-2016, 2016
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This study evaluates the performances of the new version (v.5.1) of 3D-CMCC Forest Ecosystem Model in simulating gross primary productivity (GPP), against eddy covariance GPP data for 10 FLUXNET forest sites across Europe. The model consistently reproduces both in timing and in magnitude daily and monthly GPP variability across all sites, with the exception of the two Mediterranean sites. Inclusion of forest structure within simulation ameliorate in some cases the model output.
L. Wingate, J. Ogée, E. Cremonese, G. Filippa, T. Mizunuma, M. Migliavacca, C. Moisy, M. Wilkinson, C. Moureaux, G. Wohlfahrt, A. Hammerle, L. Hörtnagl, C. Gimeno, A. Porcar-Castell, M. Galvagno, T. Nakaji, J. Morison, O. Kolle, A. Knohl, W. Kutsch, P. Kolari, E. Nikinmaa, A. Ibrom, B. Gielen, W. Eugster, M. Balzarolo, D. Papale, K. Klumpp, B. Köstner, T. Grünwald, R. Joffre, J.-M. Ourcival, M. Hellstrom, A. Lindroth, C. George, B. Longdoz, B. Genty, J. Levula, B. Heinesch, M. Sprintsin, D. Yakir, T. Manise, D. Guyon, H. Ahrends, A. Plaza-Aguilar, J. H. Guan, and J. Grace
Biogeosciences, 12, 5995–6015, https://doi.org/10.5194/bg-12-5995-2015, https://doi.org/10.5194/bg-12-5995-2015, 2015
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The timing of plant development stages and their response to climate and management were investigated using a network of digital cameras installed across different European ecosystems. Using the relative red, green and blue content of images we showed that the green signal could be used to estimate the length of the growing season in broadleaf forests. We also developed a model that predicted the seasonal variations of camera RGB signals and how they relate to leaf pigment content and area well.
F. Richter, C. Döring, M. Jansen, O. Panferov, U. Spank, and C. Bernhofer
Hydrol. Earth Syst. Sci., 19, 3457–3474, https://doi.org/10.5194/hess-19-3457-2015, https://doi.org/10.5194/hess-19-3457-2015, 2015
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Predicting hydrological effects of land use change, e.g. enhanced cultivation of short rotation coppices, requires an adequate parameterisation. Measurements and modelling results show that leaf area index, stomatal resistance and in particular start and length of growing season are most sensitive to soil hydrological quantities, like ground water recharge (GWR). Only simulations over 30 years, reflecting long-term climate variability, show even zero GWR, especially in succeeding dry years.
M. Renner, K. Brust, K. Schwärzel, M. Volk, and C. Bernhofer
Hydrol. Earth Syst. Sci., 18, 389–405, https://doi.org/10.5194/hess-18-389-2014, https://doi.org/10.5194/hess-18-389-2014, 2014
D. Lisniak, J. Franke, and C. Bernhofer
Hydrol. Earth Syst. Sci., 17, 2487–2500, https://doi.org/10.5194/hess-17-2487-2013, https://doi.org/10.5194/hess-17-2487-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
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Hydrol. Earth Syst. Sci., 28, 4455–4476, https://doi.org/10.5194/hess-28-4455-2024, https://doi.org/10.5194/hess-28-4455-2024, 2024
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He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 4361–4381, https://doi.org/10.5194/hess-28-4361-2024, https://doi.org/10.5194/hess-28-4361-2024, 2024
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Our findings show that runoff in the Yarlung Zangbo (YZ) basin is primarily driven by rainfall, with the largest glacier runoff contribution in the downstream sub-basin. Annual runoff increased in the upper stream but decreased downstream due to varying precipitation patterns. It is expected to rise throughout the 21st century, mainly driven by increased rainfall.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
Hydrol. Earth Syst. Sci., 28, 4127–4155, https://doi.org/10.5194/hess-28-4127-2024, https://doi.org/10.5194/hess-28-4127-2024, 2024
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Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Hydrol. Earth Syst. Sci., 28, 3777–3797, https://doi.org/10.5194/hess-28-3777-2024, https://doi.org/10.5194/hess-28-3777-2024, 2024
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The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the cellular automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
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We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent 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.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024, https://doi.org/10.5194/hess-28-3457-2024, 2024
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Daily streamflow series for 661 near-natural French catchments are reconstructed over 1871–2012 using two ensemble datasets: HydRE and HydREM. They include uncertainties coming from climate forcings, streamflow measurement, and hydrological model error (for HydrREM). Comparisons with other hydrological reconstructions and independent/dependent observations show the added value of the two reconstructions in terms of quality, uncertainty estimation, and representation of extremes.
María Agostina Bracalenti, Omar V. Müller, Miguel A. Lovino, and Ernesto Hugo Berbery
Hydrol. Earth Syst. Sci., 28, 3281–3303, https://doi.org/10.5194/hess-28-3281-2024, https://doi.org/10.5194/hess-28-3281-2024, 2024
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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, mainly driven by the expansion of the agricultural frontier, 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.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
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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 five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, https://doi.org/10.5194/hess-28-3079-2024, 2024
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We fine-tuned the variable infiltration capacity (VIC) and Noah-MP models across 263 river basins in the Western US. We developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins. Both models performed best in humid areas, and the skills improved post-calibration. VIC outperforms Noah-MP in all but interior dry basins following regionalization. VIC simulates annual mean streamflow and high flow well, while Noah-MP performs better for low flows.
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.
Kyle R. Mankin, Sushant Mehan, Timothy R. Green, and David M. Barnard
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-58, https://doi.org/10.5194/hess-2024-58, 2024
Revised manuscript accepted for HESS
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We assess 60 gridded climate datasets [ground- (G), satellite- (S), reanalysis-based (R)]. Higher-density station data and less-hilly terrain improved climate data. In mountainous and humid regions, dataset types performed similarly; but R outperformed G when underlying data had low station density. G outperformed S or R datasets, though better streamflow modeling did not always follow. Hydrologic analyses need datasets that better represent climate variable dependencies and complex topography.
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.
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.
Amy Charlotte Green, Chris G. Kilsby, and András Bárdossy
EGUsphere, https://doi.org/10.5194/egusphere-2024-26, https://doi.org/10.5194/egusphere-2024-26, 2024
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Weather radar is a crucial tool in rainfall estimation, but radar rainfall estimates are subject to many error sources, with the true rainfall field unknown. A flexible model for simulating errors relating to the radar rainfall estimation process is implemented, inverting standard processing methods. This flexible and efficient model performs well at generating realistic weather radar images visually, for a large range of event types.
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.
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.
Kenza Tazi, Andrew Orr, Javier Hernandez-González, Scott Hosking, and Richard E. Turner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2145, https://doi.org/10.5194/egusphere-2023-2145, 2023
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This work aims to improve the understanding of precipitation patterns in High Mountain Asia, a crucial water source for around 2 billion people. Through a novel machine learning method, we generate high-resolution precipitation predictions including the likelihoods of floods and droughts. Compared to state-of-the-art methods, our method is simpler to implement and more suitable for small datasets. The method also shows comparable or better accuracy to existing benchmark datasets.
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.
Peter E. Levy and the COSMOS-UK team
EGUsphere, https://doi.org/10.5194/egusphere-2023-2041, https://doi.org/10.5194/egusphere-2023-2041, 2023
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Having accurate up-to-date maps of soil moisture is important for many purposes. However, current modelled and remotely-sensed maps are rather coarse and not very accurate. Here, we demonstrate a simple but accurate approach which is closely linked to direct measurements of soil moisture at a network sites across the UK, and to the water balance (precipitation minus drainage and evaporation) measured at a large number of catchments (1212), as well as to remotely-sensed satellite estimates.
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.
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.
Jolanda J. E. Theeuwen, Arie Staal, Obbe A. Tuinenburg, Bert V. M. Hamelers, and Stefan C. Dekker
Hydrol. Earth Syst. Sci., 27, 1457–1476, https://doi.org/10.5194/hess-27-1457-2023, https://doi.org/10.5194/hess-27-1457-2023, 2023
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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.
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.
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Ad-hoc-AG Boden: Bodenkundliche Kartieranleitung, Bundesanstalt für
Geowissenschaften und Rohstoffe in Zusammenarbeit mit den Staatlichen
Geologischen Dienstender Bundesrepublik Deutschland, Hannover, https://www.bgr.bund.de/DE/Themen/Boden/Netzwerke/AGBoden/Downloads/methodenkatalog.pdf?__blob=publicationFile&v=2 (last access: 20 November 2021), 2005.
Alessandri, A., Catalano, F., De Felice, M., van den Hurk, B., and Balsamo,
G.: Varying snow and vegetation signatures of surface albedo feedback on the
Northern Hemisphere land warming, Environ. Res. Lett., https://doi.org/10.1088/1748-9326/abd65f,
2020.
Allen, R., Pereira, L., Raes, D., and Smith, M.: Crop evapotranspiration –
Guidelines for computing crop water requirements – FAO Irrigation and
drainage paper 56, FAO – Food and Agriculture Organization of the United
Nations, Rome, ISBN 92-5-104219-5, 1998.
Anderson, M. C., Norman, J. M., Mecikalski, J. R., Otkin, J. A., and Kustas,
W. P.: A climatological study of evapotranspiration and moisture stress
across the continental United States based on thermal remote sensing: 1.
Model formulation, J. Geophys. Res., 112, https://doi.org/10.1029/2006JD007506, 2007.
Anderson, M. C., Norman, J. M., Kustas, W. P., Houborg, R., Starks, P. J.,
and Agam, N.: A thermal-based remote sensing technique for routine mapping
of land-surface carbon, water and energy fluxes from field to regional
scales, Remote Sens. Environ., 112, 4227–4241, https://doi.org/10.1016/j.rse.2008.07.009, 2008.
Baldocchi, D.: Flux Footprints Within and Over Forest Canopies,
Bound.-Lay. Meteorol., 85, 273–292,
https://doi.org/10.1023/A:1000472717236, 1997.
Baldocchi, D., Falge, E., Gu, L., Olson, R., Hollinger, D., Running, S.,
Anthoni, P., Bernhofer, C., Davis, K., Evans, R., Fuentes, J., Goldstein,
A., Katul, G., Law, B., Lee, X., Malhi, Y., Meyers, T., Munger, W., Oechel,
W., U, K. T. P., Pilegaard, K., Schmid, H. P., Valentini, R., Verma, S.,
Vesala, T., Wilson, K., and Wofsy, S.: FLUXNET: A New Tool to Study the
Temporal and Spatial Variability of Ecosystem-Scale Carbon Dioxide, Water
Vapor, and Energy Flux Densities, B. Am. Meteorol. Soc., 82, 2415–2434,
https://doi.org/10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2, 2001.
Beven, K. J., Kirkby, M. J., Freer, J. E., and Lamb, R.: A history of TOPMODEL, Hydrol. Earth Syst. Sci., 25, 527–549, https://doi.org/10.5194/hess-25-527-2021, 2021.
BingTM Maps tiles:
https://www.bing.com/maps, last access: 15 February 2020.
Bonan, G. B., Patton, E. G., Finnigan, J. J., Baldocchi, D. D., and Harman,
I. N.: Moving beyond the incorrect but useful paradigm: reevaluating
big-leaf and multilayer plant canopies to model biosphere-atmosphere fluxes
– a review, Agr. Forest Meteorol., 306, 108435,
https://doi.org/10.1016/j.agrformet.2021.108435, 2021.
Boulet, G., Mougenot, B., Lhomme, J.-P., Fanise, P., Lili-Chabaane, Z., Olioso, A., Bahir, M., Rivalland, V., Jarlan, L., Merlin, O., Coudert, B., Er-Raki, S., and Lagouarde, J.-P.: The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat, Hydrol. Earth Syst. Sci., 19, 4653–4672, https://doi.org/10.5194/hess-19-4653-2015, 2015.
Buchhorn, M., Smets, B., Bertels, L., Lesiv, M., Tsendbazar, N.-E., Herold,
M., and Fritz, S.: Copernicus Global Land Service, Land Cover 100 m,
collection 3, epoch 2019, Globe 2020, Zenodo [data set], https://doi.org/10.5281/zenodo.3939050, 2020.
Carminati, A. and Javaux, M.: Soil Rather Than Xylem Vulnerability Controls
Stomatal Response to Drought, Trends Plant Sci., 25, 868–880,
https://doi.org/10.1016/j.tplants.2020.04.003, 2020.
Cerro, R. T. G. del, Subathra, M. S. P., Kumar, N. M., Verrastro, S., and
George, S. T.: Modelling the daily reference evapotranspiration in semi-arid
region of South India: A case study comparing ANFIS and empirical models, Information Processing in Agriculture, 8,
173–184, https://doi.org/10.1016/j.inpa.2020.02.003, 2021.
Chang, L.-L., Dwivedi, R., Knowles, J. F., Fang, Y.-H., Niu, G.-Y.,
Pelletier, J. D., Rasmussen, C., Durcik, M., Barron-Gafford, G. A., and
Meixner, T.: Why Do Large-Scale Land Surface Models Produce a Low Ratio of
Transpiration to Evapotranspiration?, J. Geophys. Res.-Atmos., 123, 9109–9130,
https://doi.org/10.1029/2018JD029159, 2018.
Copernicus Climate Change Service (C3S): ERA5: Fifth generation of ECMWF
atmospheric reanalyses of the global climate, ERA5 hourly data on single
levels from 1979 to present, https://doi.org/10.24381/cds.adbb2d47, 2020.
Dijk, A. I. J. M. van, Gash, J. H., Gorsel, E. van, Blanken, P. D.,
Cescatti, A., Emmel, C., Gielen, B., Harman, I. N., Kiely, G., Merbold, L.,
Montagnani, L., Moors, E., Sottocornola, M., Varlagin, A., Williams, C. A.,
and Wohlfahrt, G.: Rainfall interception and the coupled surface water and
energy balance, Agr. Forest Meteorol., 214–215, 402–415,
https://doi.org/10.1016/j.agrformet.2015.09.006, 2015.
Drought 2018 Team and ICOS Ecosystem Thematic Centre: Drought-2018 ecosystem
eddy covariance flux product for 52 stations in FLUXNET-Archive format, https://doi.org/10.18160/YVR0-4898, 2020.
Efstratiadis, A. and Koutsoyiannis, D.: The multiobjective evolutionary
annealing-simplex method and its application in calibrating hydrological
models, in: Geophysical Research Abstracts, European Geosciences
Union General Assembly, Vienna, Austria,
https://doi.org/10.13140/RG.2.2.32963.81446, 2005.
European Environment Agency: Corine Land Cover (CLC) 2012, Version
2020_20u1, http://land.copernicus.eu/pan-european/corine-land-cover/clc-2012/view (last access: 20 November 2021), 2020.
Federer, A. and Douglas, L.: Brook: A Hydrologic Simulation Model for
Eastern Forests, 2nd ed., Water Resource Research Center University of New
Hampshire, Durham, New Hampshire, https://scholars.unh.edu/cgi/viewcontent.cgi?article=1171&context=nh_wrrc_scholarship (last access: 20 November 2021), 1983.
Federer, C. A.: BROOK 90: A simulation model for evaporation, soil water,
and streamflow, http://www.ecoshift.net/brook/brook90.htm (last access: 20 November 2021), 2002.
Federer, C. A., Vörösmarty, C., and Fekete, B.: Sensitivity of
Annual Evaporation to Soil and Root Properties in Two Models of Contrasting
Complexity, J. Hydrometeorol., 4, 1276–1290,
https://doi.org/10.1175/1525-7541(2003)004<1276:SOAETS>2.0.CO;2, 2003.
Feng, Y., Cui, N., Zhao, L., Hu, X., and Gong, D.: Comparison of ELM, GANN,
WNN and empirical models for estimating reference evapotranspiration in
humid region of Southwest China, J. Hydrol., 536, 376–383,
https://doi.org/10.1016/j.jhydrol.2016.02.053, 2016.
Fisher, J. B., Melton, F., Middleton, E., Hain, C., Anderson, M., Allen, R.,
McCabe, M. F., Hook, S., Baldocchi, D., Townsend, P. A., Kilic, A., Tu, K.,
Miralles, D. D., Perret, J., Lagouarde, J.-P., Waliser, D., Purdy, A. J.,
French, A., Schimel, D., Famiglietti, J. S., Stephens, G., and Wood, E. F.:
The future of evapotranspiration: Global requirements for ecosystem
functioning, carbon and climate feedbacks, agricultural management, and
water resources, Water Resour. Res., 53, 2618–2626, https://doi.org/10.1002/2016WR020175, 2017.
Foken, T.: The Energy Balance Closure Problem: An Overview, Ecol. Appl, 18, 1351–1367,
2008.
Groh, J., Puhlmann, H., and Wilpert, K.: Calibration of a soil-water balance
model with a combined objective function for the optimization of the water
retention curve, Hydrol. Wasserbewirts., 57, 152–162,
https://doi.org/10.5675/HyWa_2013,4_1, 2013.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition
of the mean squared error and NSE performance criteria: Implications for
improving hydrological modelling, J. Hydrol., 377, 80–91,
https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009.
Habel, R., Puhlmann, H., and Müller, A.-C.: The water budget of forests
the big unknown outside of our intensive monitoring plots?, FORECOMON 2021,
Birmensdorf, Switzerland, https://forecomon2021.thuenen.de/fileadmin/forecomon/Presentations/132_Puhlmann_2.pdf, last access: 20 November 2021.
Haddeland, I., Clark, D. B., Franssen, W., Ludwig, F., Voß, F., Arnell,
N. W., Bertrand, N., Best, M., Folwell, S., Gerten, D., Gomes, S., Gosling,
S. N., Hagemann, S., Hanasaki, N., Harding, R., Heinke, J., Kabat, P.,
Koirala, S., Oki, T., Polcher, J., Stacke, T., Viterbo, P., Weedon, G. P.,
and Yeh, P.: Multimodel Estimate of the Global Terrestrial Water Balance:
Setup and First Results, J. Hydrometeorol., 12, 869–884,
https://doi.org/10.1175/2011JHM1324.1, 2011.
Harding, R., Best, M., Blyth, E., Hagemann, S., Kabat, P., Tallaksen, L. M.,
Warnaars, T., Wiberg, D., Weedon, G. P., van Lanen, H., Ludwig, F., and
Haddeland, I.: WATCH: Current Knowledge of the Terrestrial Global Water
Cycle, J. Hydrometeorol., 12, 1149–1156, 2011.
Hengl, T., Mendes de Jesus, J., Heuvelink, G. B. M., Ruiperez Gonzalez, M.,
Kilibarda, M., Blagotić, A., Shangguan, W., Wright, M. N., Geng, X.,
Bauer-Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, R. A.,
Batjes, N. H., Leenaars, J. G. B., Ribeiro, E., Wheeler, I., Mantel, S., and
Kempen, B.: SoilGrids250m: Global gridded soil information based on machine
learning, Plos One, 12, 1–40, https://doi.org/10.1371/journal.pone.0169748, 2017.
Hoek van Dijke, A. J., Mallick, K., Schlerf, M., Machwitz, M., Herold, M., and Teuling, A. J.: Examining the link between vegetation leaf area and land–atmosphere exchange of water, energy, and carbon fluxes using FLUXNET data, Biogeosciences, 17, 4443–4457, https://doi.org/10.5194/bg-17-4443-2020, 2020.
Hollinger, D. Y. and Richardson, A. D.: Uncertainty in eddy covariance
measurements and its application to physiological models, Tree. Physiol.,
25, 873–885, https://doi.org/10.1093/treephys/25.7.873, 2005.
Imukova, K., Ingwersen, J., Hevart, M., and Streck, T.: Energy balance closure on a winter wheat stand: comparing the eddy covariance technique with the soil water balance method, Biogeosciences, 13, 63–75, https://doi.org/10.5194/bg-13-63-2016, 2016.
Jung, M., Reichstein, M., Margolis, H. A., Cescatti, A., Richardson, A. D.,
Arain, M. A., Arneth, A., Bernhofer, C., Bonal, D., Chen, J., Gianelle, D.,
Gobron, N., Kiely, G., Kutsch, W., Lasslop, G., Law, B. E., Lindroth, A.,
Merbold, L., Montagnani, L., Moors, E. J., Papale, D., Sottocornola, M.,
Vaccari, F., and Williams, C.: Global patterns of land-atmosphere fluxes of
carbon dioxide, latent heat, and sensible heat derived from eddy covariance,
satellite, and meteorological observations, J. Geophys. Res.-Biogeo., 116,
https://doi.org/10.1029/2010JG001566, 2011.
Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F.: World Map of
the Köppen-Geiger climate classification updated, Meteorol. Z., 15, 259–263,
https://doi.org/10.1127/0941-2948/2006/0130, 2006.
Kronenberg, R. and Bernhofer, C.: A method to adapt radar-derived
precipitation fields for climatological applications, Meteorol. Appl., 22, 636–649,
https://doi.org/10.1002/met.1498, 2015.
Kronenberg, R. and Oehlschlägel, L. M.: BROOK90 in R, https://github.com/rkronen/Brook90_R (last access: 20 November 2011), 2019.
Lawrence, D. M., Thornton, P. E., Oleson, K. W., and Bonan, G. B.: The
Partitioning of Evapotranspiration into Transpiration, Soil Evaporation, and
Canopy Evaporation in a GCM: Impacts on Land–Atmosphere Interaction, J. Hydrometeorol., 8,
862–880, https://doi.org/10.1175/JHM596.1, 2007.
Leaf, C. and Brink, G.: Hydrologic simulation model of Colorado subalpine
forest, Forest Service, U.S. Dept. of Agriculture, https://doi.org/10.5962/bhl.title.99244, 1973.
Lehmann, P., Merlin, O., Gentine, P., and Or, D.: Soil Texture Effects on
Surface Resistance to Bare-Soil Evaporation, Geophys. Res. Lett.,
45, 10398–10405, https://doi.org/10.1029/2018GL078803, 2018.
Leuning, R., Zhang, Y. Q., Rajaud, A., Cleugh, H., and Tu, K.: A simple
surface conductance model to estimate regional evaporation using MODIS leaf
area index and the Penman-Monteith equation, Water Resour. Res., 44,
https://doi.org/10.1029/2007WR006562, 2008.
Lide, D.: CRC Handbook of Chemistry and Physics, 85th ed., CRC Press, ISBN 978-0-8493-0485-9, 2005.
Liu, M., Bárdossy, A., Li, J., and Jiang, Y.: Physically-based modeling of topographic effects on spatial evapotranspiration and soil moisture patterns through radiation and wind, Hydrol. Earth Syst. Sci., 16, 357–373, https://doi.org/10.5194/hess-16-357-2012, 2012.
Luo, X., Chen, J. M., Liu, J., Black, T. A., Croft, H., Staebler, R., He,
L., Arain, M. A., Chen, B., Mo, G., Gonsamo, A., and McCaughey, H.:
Comparison of Big-Leaf, Two-Big-Leaf, and Two-Leaf Upscaling Schemes for
Evapotranspiration Estimation Using Coupled Carbon-Water Modeling, J. Geophys. Res.-Biogeo., 123, 207–225,
https://doi.org/10.1002/2017JG003978, 2018.
Luong, T. T. and Wiemann, S.: EXTRUSO framework, https://github.com/GeoinformationSystems/xtruso_R (last access: 20 November 2021), 2019.
Luong, T. T., Pöschmann, J., Vorobevskii, I., Wiemann, S., Kronenberg,
R., and Bernhofer, C.: Pseudo-Spatially-Distributed Modeling of Water
Balance Components in the Free State of Saxony, J. Hydrol., 7, 84, https://doi.org/10.3390/hydrology7040084, 2020.
Mallick, K., Toivonen, E., Trebs, I., Boegh, E., Cleverly, J., Eamus, D.,
Koivusalo, H., Drewry, D., Arndt, S. K., Griebel, A., Beringer, J., and
Garcia, M.: Bridging Thermal Infrared Sensing and Physically-Based
Evapotranspiration Modeling: From Theoretical Implementation to Validation
Across an Aridity Gradient in Australian Ecosystems, Water Resour. Res., 54, 3409–3435,
https://doi.org/10.1029/2017WR021357, 2018.
Mapzen Data Products: Amazon Web Service Terrain Tiles, https://registry.opendata.aws/terrain-tiles/ (last access: 20 November 2021), 2020.
Martens, B., De Jeu, R. A. M., Verhoest, N. E. C., Schuurmans, H., Kleijer,
J., and Miralles, D. G.: Towards Estimating Land Evaporation at Field Scales
Using GLEAM, Remote Sens., 10, 1720, https://doi.org/10.3390/rs10111720, 2018.
Mauder, M., Genzel, S., Fu, J., Kiese, R., Soltani, M., Steinbrecher, R.,
Zeeman, M., Banerjee, T., De Roo, F., and Kunstmann, H.: Evaluation of
energy balance closure adjustment methods by independent evapotranspiration
estimates from lysimeters and hydrological simulations, Hydrol. Process., 32, 39–50,
https://doi.org/10.1002/hyp.11397, 2018.
McDonald, J. E.: On the Ratio of Evaporation to Precipitation, B. Am. Meteorol. Soc., 42, 185–189,
1961.
McNally, A., McCartney, S., Ruane, A. C., Mladenova, I. E., Whitcraft, A.
K., Becker-Reshef, I., Bolten, J. D., Peters-Lidard, C. D., Rosenzweig, C.,
and Uz, S. S.: Hydrologic and Agricultural Earth Observations and Modeling
for the Water-Food Nexus, Front. Environ. Sci., 7, 23, https://doi.org/10.3389/fenvs.2019.00023,
2019.
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011.
Miralles, D. G., Jiménez, C., Jung, M., Michel, D., Ershadi, A., McCabe, M. F., Hirschi, M., Martens, B., Dolman, A. J., Fisher, J. B., Mu, Q., Seneviratne, S. I., Wood, E. F., and Fernández-Prieto, D.: The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets, Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, 2016.
Moorhead, J. E., Marek, G. W., Gowda, P. H., Lin, X., Colaizzi, P. D.,
Evett, S. R., and Kutikoff, S.: Evaluation of Evapotranspiration from Eddy
Covariance Using Large Weighing Lysimeters, Agronomy, 9, 99,
https://doi.org/10.3390/agronomy9020099, 2019.
Mueller, B., Seneviratne, S. I., Jimenez, C., Corti, T., Hirschi, M.,
Balsamo, G., Ciais, P., Dirmeyer, P., Fisher, J. B., Guo, Z., Jung, M.,
Maignan, F., McCabe, M. F., Reichle, R., Reichstein, M., Rodell, M.,
Sheffield, J., Teuling, A. J., Wang, K., Wood, E. F., and Zhang, Y.:
Evaluation of global observations-based evapotranspiration datasets and IPCC
AR4 simulations, Geophys. Res. Lett., 38, https://doi.org/10.1029/2010GL046230, 2011.
Müller Schmied, H., Adam, L., Eisner, S., Fink, G., Flörke, M., Kim, H., Oki, T., Portmann, F. T., Reinecke, R., Riedel, C., Song, Q., Zhang, J., and Döll, P.: Variations of global and continental water balance components as impacted by climate forcing uncertainty and human water use, Hydrol. Earth Syst. Sci., 20, 2877–2898, https://doi.org/10.5194/hess-20-2877-2016, 2016.
Murray, F. W.: On the Computation of Saturation Vapor Pressure, J. Appl. Meteorol. Climatol., 6, 203–204,
https://doi.org/10.1175/1520-0450(1967)006<0203:OTCOSV>2.0.CO;2, 1967.
Myhre, G. and Myhre, A.: Uncertainties in Radiative Forcing due to Surface
Albedo Changes Caused by Land-Use Changes, J. Climate, 16,
1511–1524, https://doi.org/10.1175/1520-0442(2003)016<1511:UIRFDT>2.0.CO;2, 2003.
Myneni, R., Knyazikhin, Y., and Park, T.: MCD15A2H MODIS/Terra+Aqua Leaf
Area Index/FPAR 8-day L4 Global 500m SIN Grid V006, https://doi.org/10.5067/MODIS/MCD15A2H.006, 2015.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual
models part I – A discussion of principles, J. Hydrol, 10, 282–290,
https://doi.org/10.1016/0022-1694(70)90255-6, 1970.
Page, J.: 1 – The Role of Solar Radiation Climatology in the Design of
Photovoltaic Systems, in: Practical Handbook of Photovoltaics, edited by:
Markvart, T. and Castañer, L., Elsevier Science, Amsterdam, 5–66,
https://doi.org/10.1016/B978-185617390-2/50004-0, 2003.
Pan, S., Pan, N., Tian, H., Friedlingstein, P., Sitch, S., Shi, H., Arora, V. K., Haverd, V., Jain, A. K., Kato, E., Lienert, S., Lombardozzi, D., Nabel, J. E. M. S., Ottlé, C., Poulter, B., Zaehle, S., and Running, S. W.: Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling, Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020, 2020.
Paredes, P., Pereira, L. S., Almorox, J., and Darouich, H.: Reference grass
evapotranspiration with reduced data sets: Parameterization of the FAO
Penman-Monteith temperature approach and the Hargeaves-Samani equation using
local climatic variables, Agr. Water Manage., 240, 106210,
https://doi.org/10.1016/j.agwat.2020.106210, 2020.
Park, S. and Park, S. K.: Parameterization of the snow-covered surface albedo in the Noah-MP Version 1.0 by implementing vegetation effects, Geosci. Model Dev., 9, 1073–1085, https://doi.org/10.5194/gmd-9-1073-2016, 2016.
Pastorello, G., Trotta, C., Canfora, E., Chu, H., Christianson, D., Cheah,
Y.-W., Poindexter, C., Chen, J., Elbashandy, A., Humphrey, M., Isaac, P.,
Polidori, D., Reichstein, M., Ribeca, A., van Ingen, C., Vuichard, N.,
Zhang, L., Amiro, B., Ammann, C., Arain, M. A., Ardö, J., Arkebauer, T.,
Arndt, S. K., Arriga, N., Aubinet, M., Aurela, M., Baldocchi, D., Barr, A.,
Beamesderfer, E., Marchesini, L. B., Bergeron, O., Beringer, J., Bernhofer,
C., Berveiller, D., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer,
G., Boike, J., Bolstad, P. V., Bonal, D., Bonnefond, J.-M., Bowling, D. R.,
Bracho, R., Brodeur, J., Brümmer, C., Buchmann, N., Burban, B., Burns,
S. P., Buysse, P., Cale, P., Cavagna, M., Cellier, P., Chen, S., Chini, I.,
Christensen, T. R., Cleverly, J., Collalti, A., Consalvo, C., Cook, B. D.,
Cook, D., Coursolle, C., Cremonese, E., Curtis, P. S., D'Andrea, E., da
Rocha, H., Dai, X., Davis, K. J., Cinti, B. D., Grandcourt, A. de, Ligne, A.
D., De Oliveira, R. C., Delpierre, N., Desai, A. R., Di Bella, C. M.,
Tommasi, P. di, Dolman, H., Domingo, F., Dong, G., Dore, S., Duce, P.,
Dufrêne, E., Dunn, A., Dušek, J., Eamus, D., Eichelmann, U.,
ElKhidir, H. A. M., Eugster, W., Ewenz, C. M., Ewers, B., Famulari, D.,
Fares, S., Feigenwinter, I., Feitz, A., Fensholt, R., Filippa, G., Fischer,
M., Frank, J., Galvagno, M., et al.: The FLUXNET2015 dataset and the ONEFlux
processing pipeline for eddy covariance data, Scientific Data, 7, 225,
https://doi.org/10.1038/s41597-020-0534-3, 2020.
Perez-Priego, O., El-Madany, T. S., Migliavacca, M., Kowalski, A. S., Jung,
M., Carrara, A., Kolle, O., Martín, M. P., Pacheco-Labrador, J.,
Moreno, G., and Reichstein, M.: Evaluation of eddy covariance latent heat
fluxes with independent lysimeter and sapflow estimates in a Mediterranean
savannah ecosystem, Agr. Forest Meteorol., 236, 87–99,
https://doi.org/10.1016/j.agrformet.2017.01.009, 2017.
Planet dump: https://planet.osm.org, https://www.openstreetmap.org (last access: 20 November 2021), 2022.
Potapov, P., Li, X., Hernandez-Serna, A., Tyukavina, A., Hansen, M. C.,
Kommareddy, A., Pickens, A., Turubanova, S., Tang, H., Silva, C. E.,
Armston, J., Dubayah, R., Blair, J. B., and Hofton, M.: Mapping global
forest canopy height through integration of GEDI and Landsat data, Remote
Sens. Environ., 253, 112165,
https://doi.org/10.1016/j.rse.2020.112165, 2021.
Pypker, T. G., Bond, B. J., Link, T. E., Marks, D., and Unsworth, M. H.: The
importance of canopy structure in controlling the interception loss of
rainfall: Examples from a young and an old-growth Douglas-fir forest,
Agr. Forest Meteorol., 130, 113–129,
https://doi.org/10.1016/j.agrformet.2005.03.003, 2005.
Raupach, M. and Finnigan, J.: “Single-Layer Models of Evaporation From
Plant Canopies Are Incorrect but Useful, Whereas Multilayer Models Are
Correct but Useless”: Discuss, Functional Plant Biol., 15, 705–716, 1988.
Reed, P. and Devireddy, V.: Groundwater monitoring design: a case study
combining epsilon dominance archiving and automatic parameterization for the
NSGA-II, in: Applications of Multi-Objective Evolutionary Algorithms,
79–100, World Scientific Publishing, https://doi.org/10.1142/9789812567796_0004, 2004.
Richardson, A. D., Aubinet, M., Barr, A. G., Hollinger, D. Y., Ibrom, A.,
Lasslop, G., and Reichstein, M.: Uncertainty Quantification, in: Eddy
Covariance: A Practical Guide to Measurement and Data Analysis, edited by:
Aubinet, M., Vesala, T., and Papale, D., Springer Netherlands, Dordrecht,
173–209, https://doi.org/10.1007/978-94-007-2351-1_7, 2012.
Richter, D.: Ergebnisse methodischer Untersuchungen zur Korrektur des
systematischen Meßfehlers des Hellmann-Niederschlagsmessers von Dieter
Richter, Deutscher Wetterdienst, Offenbach am Main, Deutscher Wetterdienst, ISBN 978-3-88148-309-4, 1995.
Rudd, A. C. and Kay, A. L.: Use of very high resolution climate model data
for hydrological modelling: estimation of potential evaporation, Hydrol. Res., 47, 660–670, https://doi.org/10.2166/nh.2015.028, 2015.
Sächsisches Landesamt für Umwelt, Landwirtschaft und Geologie:
Bodenkarte 1:50 000, https://www.boden.sachsen.de/digitale-bodenkarte-1-50-000-19474.html
(last access: 20 November 2021), 2020.
Schulz, S., Becker, R., Richard-Cerda, J. C., Usman, M., aus der Beek, T.,
Merz, R., and Schüth, C.: Estimating water balance components in
irrigated agriculture using a combined approach of soil moisture and energy
balance monitoring, and numerical modelling, Hydrol. Process., 35,
https://doi.org/10.1002/hyp.14077, 2021.
Schwärzel, K., Feger, K.-H., Häntzschel, J., Menzer, A., Spank, U.,
Clausnitzer, F., Köstner, B., and Bernhofer, C.: A novel approach in
model-based mapping of soil water conditions at forest sites, Forest Ecol. Manage., 258,
2163–2174, https://doi.org/10.1016/j.foreco.2009.03.033, 2009.
Sentelhas, P. C., Gillespie, T. J., and Santos, E. A.: Evaluation of FAO
Penman–Monteith and alternative methods for estimating reference
evapotranspiration with missing data in Southern Ontario, Canada,
Agr. Water Manage., 97, 635–644,
https://doi.org/10.1016/j.agwat.2009.12.001, 2010.
Shuttleworth, W. J. and Wallace, J. S.: Evaporation from sparse crops-an
energy combination theory, Q. J. Roy. Meteorol. Soc., 111, 839–855,
https://doi.org/10.1002/qj.49711146910, 1985.
Spank, U., Schwärzel, K., Renner, M., Moderow, U., and Bernhofer, C.:
Effects of measurement uncertainties of meteorological data on estimates of
site water balance components, J. Hydrol., 492, 176–189,
https://doi.org/10.1016/j.jhydrol.2013.03.047, 2013.
Staatsbetrieb Geobasisinformation und Vermessung Sachsen: Digitales
Geländemodell Sachsen 10 m, https://www.landesvermessung.sachsen.de/verfugbarkeit-aktualitat-5305.html
(last access: 20 November 2021), 2020.
Su, H., McCabe, M. F., Wood, E. F., Su, Z., and Prueger, J. H.: Modeling
Evapotranspiration during SMACEX: Comparing Two Approaches for Local- and
Regional-Scale Prediction, J. Hydrometeorol., 6, 910–922, https://doi.org/10.1175/JHM466.1,
2005.
Twine, T. E., Kustas, W. P., Norman, J. M., Cook, D. R., Houser, P. R.,
Meyers, T. P., Prueger, J. H., Starks, P. J., and Wesely, M. L.: Correcting
eddy-covariance flux underestimates over a grassland, Agr. Forest Meteorol., 103, 279–300,
https://doi.org/10.1016/S0168-1923(00)00123-4, 2000.
Verhoef, A. and Egea, G.: Modeling plant transpiration under limited soil
water: Comparison of different plant and soil hydraulic parameterizations
and preliminary implications for their use in land surface models,
Agr. Forest Meteorol., 191, 22–32,
https://doi.org/10.1016/j.agrformet.2014.02.009, 2014.
Vilhar, U.: Comparison of drought stress indices in beech forests: a
modelling study, iForest – Biogeosciences and Forestry, 635–642, https://doi.org/10.3832/ifor1630-008, 2016.
Vorobevskii, I.: Global BROOK90 source code, https://doi.org/10.5281/zenodo.6535132, 2021.
Vorobevskii, I., Kronenberg, R., and Bernhofer, C.: Global BROOK90 R
Package: An Automatic Framework to Simulate the Water Balance at Any
Location, Water, 12, 2037, https://doi.org/10.3390/w12072037, 2020.
Vorobevskii, I.: Supplement materials for publication: Modelling evaporation with local, regional and global BROOK90 frameworks: importance of parameterization and forcing, HydroShare, https://doi.org/10.4211/hs.567d7bdc7b84465ca333b6e0c011853a, 2021.
Wackernagel, H.: Multivariate Geostatistics: an Introduction with
Applications, 3rd ed., Springer-Verlag, Berlin Heidelberg, 388 pp., ISBN 978-3-662-05294-5, 2003.
Wang, S., Pan, M., Mu, Q., Shi, X., Mao, J., Brümmer, C., Jassal, R. S.,
Krishnan, P., Li, J., and Black, T. A.: Comparing Evapotranspiration from
Eddy Covariance Measurements, Water Budgets, Remote Sensing, and Land
Surface Models over Canada, J. Hydrometeorol., 16, 1540–1560,
https://doi.org/10.1175/JHM-D-14-0189.1, 2015.
Wang, Z., Schaaf, C. B., Sun, Q., Kim, J., Erb, A. M., Gao, F., Román,
M. O., Yang, Y., Petroy, S., Taylor, J. R., Masek, J. G., Morisette, J. T.,
Zhang, X., and Papuga, S. A.: Monitoring land surface albedo and vegetation
dynamics using high spatial and temporal resolution synthetic time series
from Landsat and the MODIS BRDF/NBAR/albedo product, Int. J. Apl. Earth Obs., 59, 104–117,
https://doi.org/10.1016/j.jag.2017.03.008, 2017.
Warm Winter 2020 Team and ICOS Ecosystem Thematic Centre: Warm Winter 2020
ecosystem eddy covariance flux product for 73 stations in FLUXNET-Archive
format – release 2022-1 (Version 1.0), ICOS Carbon Portal, https://doi.org/10.18160/2G60-ZHAK, 2022.
Wegehenkel, M. and Gerke, H. H.: Comparison of real evapotranspiration
measured by weighing lysimeters with simulations based on the Penman formula
and a crop growth model, J. Hydrol. Hydromech., 61, 161–172,
https://doi.org/10.2478/johh-2013-0021, 2013.
Wei, Z., Yoshimura, K., Wang, L., Miralles, D. G., Jasechko, S., and Lee,
X.: Revisiting the contribution of transpiration to global terrestrial
evapotranspiration, Geophys. Res. Lett., 44, 2792–2801, https://doi.org/10.1002/2016GL072235,
2017.
Widmoser, P. and Michel, D.: Partial energy balance closure of eddy covariance evaporation measurements using concurrent lysimeter observations over grassland, Hydrol. Earth Syst. Sci., 25, 1151–1163, https://doi.org/10.5194/hess-25-1151-2021, 2021.
Wilson, K., Goldstein, A., Falge, E., Aubinet, M., Baldocchi, D., Berbigier,
P., Bernhofer, C., Ceulemans, R., Dolman, H., Field, C., Grelle, A., Ibrom,
A., Law, B. E., Kowalski, A., Meyers, T., Moncrieff, J., Monson, R., Oechel,
W., Tenhunen, J., Valentini, R., and Verma, S.: Energy balance closure at
FLUXNET sites, Agr. Forest Meteorol., 113, 223–243,
https://doi.org/10.1016/S0168-1923(02)00109-0, 2002.
Wilson, K. B., Hanson, P. J., Mulholland, P. J., Baldocchi, D. D., and
Wullschleger, S. D.: A comparison of methods for determining forest
evapotranspiration and its components: sap-flow, soil water budget, eddy
covariance and catchment water balance, Agr. Forest Meteorol., 106, 153–168,
https://doi.org/10.1016/S0168-1923(00)00199-4, 2001.
Winter, J. M. and Eltahir, E. A. B.: The Sensitivity of Latent Heat Flux to
Changes in the Radiative Forcing: A Framework for Comparing Models and
Observations, J. Climate, 23, 2345–2356, https://doi.org/10.1175/2009JCLI3158.1, 2010.
Wu, J., Liu, L., Sun, C., Su, Y., Wang, C., Yang, J., Liao, J., He, X., Li,
Q., Zhang, C., and Zhang, H.: Estimating Rainfall Interception of Vegetation
Canopy from MODIS Imageries in Southern China, Remote Sens., 11, 2468,
https://doi.org/10.3390/rs11212468, 2019.
Yan, H., Wang, S. Q., Billesbach, D., Oechel, W., Zhang, J. H., Meyers, T.,
Martin, T. A., Matamala, R., Baldocchi, D., Bohrer, G., Dragoni, D., and
Scott, R.: Global estimation of evapotranspiration using a leaf area
index-based surface energy and water balance model, Remote Sens.
Environ., 124, 581–595, https://doi.org/10.1016/j.rse.2012.06.004, 2012.
Yang, B., Lee, D. K., Heo, H. K., and Biging, G.: The effects of tree
characteristics on rainfall interception in urban areas, Landsc. Ecol. Eng., 15, 289–296,
https://doi.org/10.1007/s11355-019-00383-w, 2019.
Zeng, Z., Piao, S., Lin, X., Yin, G., Peng, S., Ciais, P., and Myneni, R.
B.: Global evapotranspiration over the past three decades: estimation based
on the water balance equation combined with empirical models, Environ. Res. Lett., 7, 014026,
https://doi.org/10.1088/1748-9326/7/1/014026, 2012.
Zhang, Y., Leuning, R., Hutley, L. B., Beringer, J., McHugh, I., and Walker,
J. P.: Using long-term water balances to parameterize surface conductances
and calculate evaporation at 0.05∘ spatial resolution, Water Resour. Res., 46,
https://doi.org/10.1029/2009WR008716, 2010.
Zhang, Y., Chiew, F. H. S., Peña-Arancibia, J., Sun, F., Li, H., and
Leuning, R.: Global variation of transpiration and soil evaporation and the
role of their major climate drivers, J. Geophys. Res.-Atmos., 122, 6868–6881, https://doi.org/10.1002/2017JD027025, 2017.
Zink, M., Kumar, R., Cuntz, M., and Samaniego, L.: A high-resolution dataset of water fluxes and states for Germany accounting for parametric uncertainty, Hydrol. Earth Syst. Sci., 21, 1769–1790, https://doi.org/10.5194/hess-21-1769-2017, 2017.
Short summary
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.
In the study we analysed the uncertainties of the meteorological data and model parameterization...
