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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EGUsphere, https://doi.org/10.5194/egusphere-2025-2084, https://doi.org/10.5194/egusphere-2025-2084, 2025
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We developed an improved model to better understand how water and energy move through natural landscapes (forest, grasslands, croplands, etc) throughout the day. By using detailed data from study-site in Germany, we tested the model and found its good agreement with micro-meteorological measurements. Unlike many other tools, this model works without needing new adjustments and offers a powerful way to study fast-changing water processes in different environments.
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An introduced high-resolution soil moisture monitoring framework combines a 1D water balance model, real-time meteorological data, and a national soil database to present point-based operational data with a user-friendly web platform. Its significance lies in the improvement of forest management by making informed, local-scale decisions crucial for mitigating climate change impacts. In the paper, we present a technical description and validation of the framework and showcase its features.
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This study presents a new version of a framework which allows us to model water balance components at any site on a local scale. Compared with the first version, the second incorporates new datasets used to set up and force the model. In particular, we highlight the ability of the framework to provide seasonal forecasts. This gives potential stakeholders (farmers, foresters, policymakers, etc.) the possibility to forecast, for example, soil moisture drought and thus apply the necessary measures.
Ivan Vorobevskii, Jeongha Park, Dongkyun Kim, Klemens Barfus, and Rico Kronenberg
Hydrol. Earth Syst. Sci., 28, 391–416, https://doi.org/10.5194/hess-28-391-2024, https://doi.org/10.5194/hess-28-391-2024, 2024
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High-resolution precipitation data are often a “must” as input for hydrological and hydraulic models (i.e. urban drainage modelling). However, station or climate projection data usually do not provide the required (e.g. sub-hourly) resolution. In the work, we present two new statistical models of different types to disaggregate precipitation from a daily to a 10 min scale. Both models were validated using radar data and then applied to climate models for 10 stations in Germany and South Korea.
Ivan Vorobevskii, Rico Kronenberg, and Christian Bernhofer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-27, https://doi.org/10.5194/hess-2020-27, 2020
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The paper aims to reveal features of behavior of compound precipitation-discharge extremes in small catchments of Saxony (Germany) using statistical methods with the following advances and innovations: binding meteorological and hydrological drivers of compound extremes, application of multivariate distribution to get return periods of daily-scale extremes, focus on small catchments, test interpolation methods for daily specific discharge, estimation of uncertainty of return period calculation.
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EGUsphere, https://doi.org/10.5194/egusphere-2025-2084, https://doi.org/10.5194/egusphere-2025-2084, 2025
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We developed an improved model to better understand how water and energy move through natural landscapes (forest, grasslands, croplands, etc) throughout the day. By using detailed data from study-site in Germany, we tested the model and found its good agreement with micro-meteorological measurements. Unlike many other tools, this model works without needing new adjustments and offers a powerful way to study fast-changing water processes in different environments.
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Accurate estimates of interception are important to assess the water availability in ecosystems. We analyzed rainfall interception for a forest site from plot to stand scale. During interception, eddy-covariance measurements of evaporation were systematically underestimated accounting for 24% of precipitation, while modelled interception evaporation accounted for 45%. As a consequence, we developed a hybrid correction approach to fit the evaporation data to both the energy and the water balance.
Mana Gharun, Ankit Shekhar, Lukas Hörtnagl, Luana Krebs, Nicola Arriga, Mirco Migliavacca, Marilyn Roland, Bert Gielen, Leonardo Montagnani, Enrico Tomelleri, Ladislav Šigut, Matthias Peichl, Peng Zhao, Marius Schmidt, Thomas Grünwald, Mika Korkiakoski, Annalea Lohila, and Nina Buchmann
Biogeosciences, 22, 1393–1411, https://doi.org/10.5194/bg-22-1393-2025, https://doi.org/10.5194/bg-22-1393-2025, 2025
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The effect of winter warming on forest CO2 fluxes has rarely been investigated. We tested the effect of the warm winter of 2020 on the forest CO2 fluxes across 14 sites in Europe and found that the net ecosystem productivity (NEP) across most sites declined during the warm winter due to increased respiration fluxes.
Ivan Vorobevskii, Thi Thanh Luong, Rico Kronenberg, and Rainer Petzold
Hydrol. Earth Syst. Sci., 28, 3567–3595, https://doi.org/10.5194/hess-28-3567-2024, https://doi.org/10.5194/hess-28-3567-2024, 2024
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An introduced high-resolution soil moisture monitoring framework combines a 1D water balance model, real-time meteorological data, and a national soil database to present point-based operational data with a user-friendly web platform. Its significance lies in the improvement of forest management by making informed, local-scale decisions crucial for mitigating climate change impacts. In the paper, we present a technical description and validation of the framework and showcase its features.
Ivan Vorobevskii, Thi Thanh Luong, and Rico Kronenberg
Nat. Hazards Earth Syst. Sci., 24, 681–697, https://doi.org/10.5194/nhess-24-681-2024, https://doi.org/10.5194/nhess-24-681-2024, 2024
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This study presents a new version of a framework which allows us to model water balance components at any site on a local scale. Compared with the first version, the second incorporates new datasets used to set up and force the model. In particular, we highlight the ability of the framework to provide seasonal forecasts. This gives potential stakeholders (farmers, foresters, policymakers, etc.) the possibility to forecast, for example, soil moisture drought and thus apply the necessary measures.
Ivan Vorobevskii, Jeongha Park, Dongkyun Kim, Klemens Barfus, and Rico Kronenberg
Hydrol. Earth Syst. Sci., 28, 391–416, https://doi.org/10.5194/hess-28-391-2024, https://doi.org/10.5194/hess-28-391-2024, 2024
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High-resolution precipitation data are often a “must” as input for hydrological and hydraulic models (i.e. urban drainage modelling). However, station or climate projection data usually do not provide the required (e.g. sub-hourly) resolution. In the work, we present two new statistical models of different types to disaggregate precipitation from a daily to a 10 min scale. Both models were validated using radar data and then applied to climate models for 10 stations in Germany and South Korea.
Dánnell Quesada-Chacón, Klemens Barfus, and Christian Bernhofer
Geosci. Model Dev., 15, 7353–7370, https://doi.org/10.5194/gmd-15-7353-2022, https://doi.org/10.5194/gmd-15-7353-2022, 2022
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We improved the performance of past perfect prognosis statistical downscaling methods while achieving full model repeatability with GPU-calculated deep learning models using the TensorFlow, climate4R, and VALUE frameworks. We employed the ERA5 reanalysis as predictors and ReKIS (eastern Ore Mountains, Germany, 1 km resolution) as precipitation predictand, while incorporating modern deep learning architectures. The achieved repeatability is key to accomplish further milestones with deep learning.
Judith Marie Pöschmann, Dongkyun Kim, Rico Kronenberg, and Christian Bernhofer
Nat. Hazards Earth Syst. Sci., 21, 1195–1207, https://doi.org/10.5194/nhess-21-1195-2021, https://doi.org/10.5194/nhess-21-1195-2021, 2021
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We examined maximum rainfall values for different durations from 16 years of radar-based rainfall records for whole Germany. Unlike existing observations based on rain gauge data no clear linear relationship could be identified. However, by classifying all time series, we could identify three similar groups determined by the temporal structure of rainfall extremes observed in the study period. The study highlights the importance of using long data records and a dense measurement network.
Theresa Boas, Heye Bogena, Thomas Grünwald, Bernard Heinesch, Dongryeol Ryu, Marius Schmidt, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 14, 573–601, https://doi.org/10.5194/gmd-14-573-2021, https://doi.org/10.5194/gmd-14-573-2021, 2021
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In this study we were able to significantly improve CLM5 model performance for European cropland sites by adding a winter wheat representation, specific plant parameterizations for important cash crops, and a cover-cropping and crop rotation subroutine to its crop module. Our modifications should be applied in future studies of CLM5 to improve regional yield predictions and to better understand large-scale impacts of agricultural management on carbon, water, and energy fluxes.
Jan Pisek, Angela Erb, Lauri Korhonen, Tobias Biermann, Arnaud Carrara, Edoardo Cremonese, Matthias Cuntz, Silvano Fares, Giacomo Gerosa, Thomas Grünwald, Niklas Hase, Michal Heliasz, Andreas Ibrom, Alexander Knohl, Johannes Kobler, Bart Kruijt, Holger Lange, Leena Leppänen, Jean-Marc Limousin, Francisco Ramon Lopez Serrano, Denis Loustau, Petr Lukeš, Lars Lundin, Riccardo Marzuoli, Meelis Mölder, Leonardo Montagnani, Johan Neirynck, Matthias Peichl, Corinna Rebmann, Eva Rubio, Margarida Santos-Reis, Crystal Schaaf, Marius Schmidt, Guillaume Simioni, Kamel Soudani, and Caroline Vincke
Biogeosciences, 18, 621–635, https://doi.org/10.5194/bg-18-621-2021, https://doi.org/10.5194/bg-18-621-2021, 2021
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Understory vegetation is the most diverse, least understood component of forests worldwide. Understory communities are important drivers of overstory succession and nutrient cycling. Multi-angle remote sensing enables us to describe surface properties by means that are not possible when using mono-angle data. Evaluated over an extensive set of forest ecosystem experimental sites in Europe, our reported method can deliver good retrievals, especially over different forest types with open canopies.
Uta Moderow, Stefanie Fischer, Thomas Grünwald, Ronald Queck, and Christian Bernhofer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-202, https://doi.org/10.5194/hess-2020-202, 2020
Preprint withdrawn
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We analyzed three different estimates of evapotranspiration (ET) for four different sites along an elevation gradient of a low mountain range over 11 years. We found similar dependencies on meteorological variables for all three different ET estimates. Based on our analyses we recommend using a distinct ET estimate. Analysis further suggests that water temporally stored on plant surfaces should receive more attention. Our results contribute to determining reliable ET estimates.
Ivan Vorobevskii, Rico Kronenberg, and Christian Bernhofer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-27, https://doi.org/10.5194/hess-2020-27, 2020
Preprint withdrawn
Short summary
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The paper aims to reveal features of behavior of compound precipitation-discharge extremes in small catchments of Saxony (Germany) using statistical methods with the following advances and innovations: binding meteorological and hydrological drivers of compound extremes, application of multivariate distribution to get return periods of daily-scale extremes, focus on small catchments, test interpolation methods for daily specific discharge, estimation of uncertainty of return period calculation.
Sergey Chalov, Pavel Terskii, Thomas Pluntke, Ludmila Efimova, Vasiliy Efimov, Vladimir Belyaev, Anna Terskaia, Michal Habel, Daniel Karthe, and Christian Bernhofer
Proc. IAHS, 381, 7–11, https://doi.org/10.5194/piahs-381-7-2019, https://doi.org/10.5194/piahs-381-7-2019, 2019
Solomon Hailu Gebrechorkos, Stephan Hülsmann, and Christian Bernhofer
Hydrol. Earth Syst. Sci., 22, 4547–4564, https://doi.org/10.5194/hess-22-4547-2018, https://doi.org/10.5194/hess-22-4547-2018, 2018
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In Africa field-based meteorological data are scarce; therefore global data sources based on remote sensing and climate models are often used as alternatives. To assess their suitability for a large and topographically complex area in East Africa, we evaluated multiple climate data products with available ground station data at multiple timescales over 21 regions. The comprehensive evaluation resulted in identification of preferential data sources to be used for climate and hydrological studies.
Chunjing Qiu, Dan Zhu, Philippe Ciais, Bertrand Guenet, Gerhard Krinner, Shushi Peng, Mika Aurela, Christian Bernhofer, Christian Brümmer, Syndonia Bret-Harte, Housen Chu, Jiquan Chen, Ankur R. Desai, Jiří Dušek, Eugénie S. Euskirchen, Krzysztof Fortuniak, Lawrence B. Flanagan, Thomas Friborg, Mateusz Grygoruk, Sébastien Gogo, Thomas Grünwald, Birger U. Hansen, David Holl, Elyn Humphreys, Miriam Hurkuck, Gerard Kiely, Janina Klatt, Lars Kutzbach, Chloé Largeron, Fatima Laggoun-Défarge, Magnus Lund, Peter M. Lafleur, Xuefei Li, Ivan Mammarella, Lutz Merbold, Mats B. Nilsson, Janusz Olejnik, Mikaell Ottosson-Löfvenius, Walter Oechel, Frans-Jan W. Parmentier, Matthias Peichl, Norbert Pirk, Olli Peltola, Włodzimierz Pawlak, Daniel Rasse, Janne Rinne, Gaius Shaver, Hans Peter Schmid, Matteo Sottocornola, Rainer Steinbrecher, Torsten Sachs, Marek Urbaniak, Donatella Zona, and Klaudia Ziemblinska
Geosci. Model Dev., 11, 497–519, https://doi.org/10.5194/gmd-11-497-2018, https://doi.org/10.5194/gmd-11-497-2018, 2018
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Northern peatlands store large amount of soil carbon and are vulnerable to climate change. We implemented peatland hydrological and carbon accumulation processes into the ORCHIDEE land surface model. The model was evaluated against EC measurements from 30 northern peatland sites. The model generally well reproduced the spatial gradient and temporal variations in GPP and NEE at these sites. Water table depth was not well predicted but had only small influence on simulated NEE.
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
Skilful probabilistic predictions of UK flood risk months ahead using a large-sample machine learning model trained on multimodel ensemble climate forecasts
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Enhanced evaluation of hourly and daily extreme precipitation in Norway from convection-permitting models at regional and local scales
Deep-learning-based sub-seasonal precipitation and streamflow ensemble forecasting over the source region of the Yangtze River
High-resolution land surface modelling over Africa: the role of uncertain soil properties in combination with forcing temporal resolution
Investigating the global and regional response of drought to idealized deforestation using multiple global climate models
Distribution, trends, and drivers of flash droughts in the United Kingdom
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Assessment of seasonal soil moisture forecasts over the Central Mediterranean
Do land models miss key soil hydrological processes controlling soil moisture memory?
Observation-driven model for calculating water-harvesting potential from advective fog in (semi-)arid coastal regions
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Barriers of urban hydro-meteorological simulation: a review
Downscaling the probability of heavy rainfall over the Nordic countries
Modelling convective cell life cycles with a copula-based approach
Downscaling precipitation over High-mountain Asia using multi-fidelity Gaussian processes: improved estimates from ERA5
Mapping soil moisture across the UK: assimilating cosmic-ray neutron sensors, remotely sensed indices, rainfall radar and catchment water balance data in a Bayesian hierarchical model
Assessing rainfall radar errors with an inverse stochastic modelling framework
Enhanced hydrological modelling with the WRF-Hydro lake/reservoir module at Convection-Permitting scale: a case study of the Tana River basin in East Africa
Multi-objective calibration and evaluation of the ORCHIDEE land surface model over France at high resolution
Probabilistic precipitation downscaling for ungauged mountain sites: a pilot study for the Hindu Kush Karakoram Himalaya
Spatiotemporal responses of runoff to climate change in the southern Tibetan Plateau
FROSTBYTE: a reproducible data-driven workflow for probabilistic seasonal streamflow forecasting in snow-fed river basins across North America
The role of land-atmosphere coupling in subseasonal surface air temperature prediction
On the combined use of rain gauges and GPM IMERG satellite rainfall products for hydrological modelling: impact assessment of the cellular-automata-based methodology in the Tanaro River basin in Italy
An increase in the spatial extent of European floods over the last 70 years
140-year daily ensemble streamflow reconstructions over 661 catchments in France
The agricultural expansion in South America's Dry Chaco: regional hydroclimate effects
Machine-learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China
Improving runoff simulation in the Western United States with Noah-MP and VIC models
Spatial variability in the seasonal precipitation lapse rates in complex topographical regions – application in France
Global catalog of soil moisture droughts over the past four decades
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
Implementation of global soil databases in NOAH-MP model and the effects on simulated mean and extreme soil hydrothermal changes
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
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
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
Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach
Simon Moulds, Louise Slater, Louise Arnal, and Andrew W. Wood
Hydrol. Earth Syst. Sci., 29, 2393–2406, https://doi.org/10.5194/hess-29-2393-2025, https://doi.org/10.5194/hess-29-2393-2025, 2025
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Seasonal streamflow forecasts are an important component of flood risk management. Here, we train and test a machine learning model to predict the monthly maximum daily streamflow up to 4 months ahead. We train the model on precipitation and temperature forecasts to produce probabilistic hindcasts for 579 stations across the UK for the period 2004–2016. We show skilful results up to 4 months ahead in many locations, although, in general, the skill declines with increasing lead time.
Peyman Abbaszadeh, Fatemeh Gholizadeh, Keyhan Gavahi, and Hamid Moradkhani
Hydrol. Earth Syst. Sci., 29, 2407–2427, https://doi.org/10.5194/hess-29-2407-2025, https://doi.org/10.5194/hess-29-2407-2025, 2025
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The Hybrid Ensemble and Variational Data Assimilation framework for Environmental Systems (HEAVEN) enhances flood predictions by refining hydrologic models through improved data integration and uncertainty management. Tested in three southeastern US watersheds during hurricanes, HEAVEN assimilates real-time United States Geological Survey (USGS) streamflow data, boosting forecast accuracy.
Kun Xie, Lu Li, Hua Chen, Stephanie Mayer, Andreas Dobler, Chong-Yu Xu, and Ozan Mert Göktürk
Hydrol. Earth Syst. Sci., 29, 2133–2152, https://doi.org/10.5194/hess-29-2133-2025, https://doi.org/10.5194/hess-29-2133-2025, 2025
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We compared hourly and daily extreme precipitation across Norway from HARMONIE Climate models at convection-permitting 3 km (HCLIM3) and 12 km (HCLIM12) resolutions. HCLIM3 more accurately captures the extremes in most regions and seasons (except in summer). Its advantages are more pronounced for hourly extremes than for daily extremes. The results highlight the value of convection-permitting models in improving extreme-precipitation predictions and in helping the local society brace for extreme weather.
Ningpeng Dong, Haoran Hao, Mingxiang Yang, Jianhui Wei, Shiqin Xu, and Harald Kunstmann
Hydrol. Earth Syst. Sci., 29, 2023–2042, https://doi.org/10.5194/hess-29-2023-2025, https://doi.org/10.5194/hess-29-2023-2025, 2025
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Hydrometeorological forecasting is crucial for managing water resources and mitigating extreme weather events, yet current long-term forecast products are often embedded with uncertainties. We develop a deep-learning-based modelling framework to improve 30 d rainfall and streamflow forecasts by combining advanced neural networks and physical models. With the flow forecast error reduced by up to 33 %, the framework has the potential to enhance water management and disaster prevention.
Bamidele Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 29, 1659–1683, https://doi.org/10.5194/hess-29-1659-2025, https://doi.org/10.5194/hess-29-1659-2025, 2025
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We studied how soil and weather data affect land model simulations over Africa. By combining soil data processed in different ways with weather data of varying time intervals, we found that weather inputs had a greater impact on water processes than soil data type. However, the way soil data were processed became crucial when paired with high-frequency weather inputs, showing that detailed weather data can improve local and regional predictions of how water moves and interacts with the land.
Yan Li, Bo Huang, Chunping Tan, Xia Zhang, Francesco Cherubini, and Henning W. Rust
Hydrol. Earth Syst. Sci., 29, 1637–1658, https://doi.org/10.5194/hess-29-1637-2025, https://doi.org/10.5194/hess-29-1637-2025, 2025
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Deforestation has a significant impact on climate, yet its effects on drought remain less understood. This study investigates how deforestation affects drought across various climate zones and timescales. Findings indicate that deforestation leads to drier conditions in tropical regions and wetter conditions in arid areas, with minimal effects in temperate zones. Long-term drought is more affected than short-term drought, offering valuable insights into vegetation–climate interactions.
Iván Noguera, Jamie Hannaford, and Maliko Tanguy
Hydrol. Earth Syst. Sci., 29, 1295–1317, https://doi.org/10.5194/hess-29-1295-2025, https://doi.org/10.5194/hess-29-1295-2025, 2025
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The study provides a detailed characterisation of flash drought in the UK for 1969–2021. The spatio-temporal distribution and trends of flash droughts are highly variable, with important regional and seasonal contrasts. In the UK, flash drought development responds primarily to precipitation variability, while the atmospheric evaporative demand plays a secondary role. We also found that the North Atlantic Oscillation is the main circulation pattern controlling flash drought development.
Geert Lenderink, Nikolina Ban, Erwan Brisson, Ségolène Berthou, Virginia Edith Cortés-Hernández, Elizabeth Kendon, Hayley J. Fowler, and Hylke de Vries
Hydrol. Earth Syst. Sci., 29, 1201–1220, https://doi.org/10.5194/hess-29-1201-2025, https://doi.org/10.5194/hess-29-1201-2025, 2025
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Future extreme rainfall events are influenced by changes in both absolute and relative humidity. The impact of increasing absolute humidity is reasonably well understood, but the role of relative humidity decreases over land remains largely unknown. Using hourly observations from France and the Netherlands, we find that lower relative humidity generally leads to more intense rainfall extremes. This relation is only captured well in recently developed convection-permitting climate models.
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci., 29, 1135–1158, https://doi.org/10.5194/hess-29-1135-2025, https://doi.org/10.5194/hess-29-1135-2025, 2025
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Precipitation data from an automated observational network in eastern Canada showed a temperature interval where rain and snow could coexist. Random forest models were developed to classify the precipitation phase using meteorological data to evaluate operational applications. The models demonstrated significantly improved phase classification and reduced error compared to benchmark operational models. However, accurate prediction of mixed-phase precipitation remains challenging.
Lorenzo Silvestri, Miriam Saraceni, Bruno Brunone, Silvia Meniconi, Giulia Passadore, and Paolina Bongioannini Cerlini
Hydrol. Earth Syst. Sci., 29, 925–946, https://doi.org/10.5194/hess-29-925-2025, https://doi.org/10.5194/hess-29-925-2025, 2025
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This work demonstrates that seasonal forecasts of soil moisture are a valuable resource for groundwater management in the areas of the Central Mediterranean where longer memory timescales are found. In particular, they show significant correlation coefficients and forecast skill for the deepest soil moisture at 289 cm depth. Wet and dry events can be predicted 6 months in advance, and, in general, dry events are better captured than wet events.
Mohammad A. Farmani, Ali Behrangi, Aniket Gupta, Ahmad Tavakoly, Matthew Geheran, and Guo-Yue Niu
Hydrol. Earth Syst. Sci., 29, 547–566, https://doi.org/10.5194/hess-29-547-2025, https://doi.org/10.5194/hess-29-547-2025, 2025
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Soil moisture memory (SMM) shows how long soil stays moist after rain, impacting climate and ecosystems. Current models often overestimate SMM, causing inaccuracies in evaporation predictions. We enhanced a land model, Noah-MP, to include better water flow and ponding processes, and we tested it against satellite and field data. This improved model reduced overestimations and enhanced short-term predictions, helping create more accurate climate and weather forecasts.
Felipe Lobos-Roco, Jordi Vilà-Guerau de Arellano, and Camilo del Río
Hydrol. Earth Syst. Sci., 29, 109–125, https://doi.org/10.5194/hess-29-109-2025, https://doi.org/10.5194/hess-29-109-2025, 2025
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Water resources are fundamental for the social, economic, and natural development of (semi-)arid regions. Precipitation decreases due to climate change obligate us to find new water resources. Fog harvesting (FH) emerges as a complementary resource in regions where it is abundant but untapped. This research proposes a model to estimate FH potential in coastal (semi-)arid regions. This model could have broader applicability worldwide in regions where FH could be a viable water source.
Kyle R. Mankin, Sushant Mehan, Timothy R. Green, and David M. Barnard
Hydrol. Earth Syst. Sci., 29, 85–108, https://doi.org/10.5194/hess-29-85-2025, https://doi.org/10.5194/hess-29-85-2025, 2025
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We assess 63 gridded ground (G), satellite (S), and reanalysis (R) climate datasets. Higher-density station data and less-hilly terrain improved climate data. In mountainous and humid regions, dataset types performed similarly; however, R outperformed G when underlying data had low station density. G outperformed S or R datasets, although better streamflow modeling did not always follow. Hydrologic analyses need datasets that better represent climate variable dependencies and complex topography.
Xuan Chen, Job Augustijn van der Werf, Arjan Droste, Miriam Coenders-Gerrits, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2024-3988, https://doi.org/10.5194/egusphere-2024-3988, 2025
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Our research highlights the need to integrate urban land surface and hydrological models to better predict and manage compound climate disasters in cities. We find that inadequate representation of water surfaces, hydraulic systems, and detailed building representations are key areas for improvement in future models. Coupled models show promise but face challenges at regional and neighbourhood scales. Interdisciplinary communication is crucial to enhance urban hydrometeorological simulations.
Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler
Hydrol. Earth Syst. Sci., 29, 45–65, https://doi.org/10.5194/hess-29-45-2025, https://doi.org/10.5194/hess-29-45-2025, 2025
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We present a new method to calculate the chance of heavy downpour and the maximum rainfall expected over a 25-year period. It is designed to analyse global climate models' reproduction of past and future climates. For the Nordic countries, it projects a wetter climate in the future with increased intensity but not necessarily more wet days. The analysis also shows that rainfall intensity is sensitive to future greenhouse gas emissions, while the number of wet days appears to be less affected.
Chien-Yu Tseng, Li-Pen Wang, and Christian Onof
Hydrol. Earth Syst. Sci., 29, 1–25, https://doi.org/10.5194/hess-29-1-2025, https://doi.org/10.5194/hess-29-1-2025, 2025
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This study presents a new algorithm to model convective storms. We used advanced tracking methods to analyse 165 storm events in Birmingham (UK) and reconstruct storm cell life cycles. We found that cell properties like intensity and size are interrelated and vary over time. The new algorithm, based on vine copulas, accurately simulates these properties and their evolution. It also integrates an exponential shape function for realistic rainfall patterns, enhancing its hydrological applicability.
Kenza Tazi, Andrew Orr, Javier Hernandez-González, Scott Hosking, and Richard E. Turner
Hydrol. Earth Syst. Sci., 28, 4903–4925, https://doi.org/10.5194/hess-28-4903-2024, https://doi.org/10.5194/hess-28-4903-2024, 2024
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This work aims to improve the understanding of precipitation patterns in High-mountain Asia, a crucial water source for around 1.9 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 accuracy comparable to or better than existing benchmark datasets.
Peter E. Levy and the COSMOS-UK team
Hydrol. Earth Syst. Sci., 28, 4819–4836, https://doi.org/10.5194/hess-28-4819-2024, https://doi.org/10.5194/hess-28-4819-2024, 2024
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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 that is closely linked to direct measurements of soil moisture at a network sites across the UK, to the water balance (precipitation minus drainage and evaporation) measured at a large number of catchments (1212) and to remotely sensed satellite estimates.
Amy C. Green, Chris Kilsby, and András Bárdossy
Hydrol. Earth Syst. Sci., 28, 4539–4558, https://doi.org/10.5194/hess-28-4539-2024, https://doi.org/10.5194/hess-28-4539-2024, 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 in generating realistic weather radar images visually for a large range of event types.
Ling Zhang, Lu Li, Zhongshi Zhang, Joël Arnault, Stefan Sobolowski, Anthony Musili Mwanthi, Pratik Kad, Mohammed Abdullahi Hassan, Tanja Portele, and Harald Kunstmann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-278, https://doi.org/10.5194/hess-2024-278, 2024
Revised manuscript accepted for HESS
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To address challenges related to unreliable hydrological simulations, we present an enhanced hydrological simulation with a refined climate model and a more comprehensive hydrological model. The model with the two parts outperforms that without, especially in migrating bias in peak flow and dry-season flow. Our findings highlight the enhanced hydrological simulation capability with the refined climate and lake module contributing 24 % and 76 % improvement, respectively.
Peng Huang, Agnès Ducharne, Lucia Rinchiuso, Jan Polcher, Laure Baratgin, Vladislav Bastrikov, and Eric Sauquet
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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We conducted a high-resolution hydrological simulation from 1959 to 2020 across France. We used a simple trial-and-error calibration to reduce the biases of the simulated water budget compared to observations. The selected simulation satisfactorily reproduces water fluxes, including their spatial contrasts and temporal trends. This work offers a reliable historical overview of water resources and a robust configuration for climate change impact analysis at the nationwide scale of France.
Marc Girona-Mata, Andrew Orr, Martin Widmann, Daniel Bannister, Ghulam Hussain Dars, Scott Hosking, Jesse Norris, David Ocio, Tony Phillips, Jakob Steiner, and Richard E. Turner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2805, https://doi.org/10.5194/egusphere-2024-2805, 2024
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We introduce a novel method for improving daily precipitation maps in mountain regions and pilot it across three basins in the Hindu Kush Karakoram Himalaya (HKH). The approach leverages climate model and weather station data, along with statistical / machine learning techniques. Our results show this approach outperforms traditional methods, especially in remote, ungauged areas, suggesting it could be used to improve precipitation maps across much of the HKH, as well as other mountain regions.
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.
Yuna Lim, Andrea M. Molod, Randal D. Koster, and Joseph A. Santanello
EGUsphere, https://doi.org/10.5194/egusphere-2024-2312, https://doi.org/10.5194/egusphere-2024-2312, 2024
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To better utilize a given set of predictions, identifying “forecasts of opportunity” has great value. It can help anticipate when prediction skill will be higher. This study reveals that when strong L-A coupling is detected 3–4 weeks into a forecast, the prediction skill for surface air temperature at this lead increases across the Midwest and northern Great Plains. Regions experiencing strong L-A coupling exhibit warm and dry anomalies, leading to improved predictions of abnormally warm events.
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.
Jan Řehoř, Rudolf Brázdil, Oldřich Rakovec, Martin Hanel, Milan Fischer, Rohini Kumar, Jan Balek, Markéta Poděbradská, Vojtěch Moravec, Luis Samaniego, and Miroslav Trnka
EGUsphere, https://doi.org/10.5194/egusphere-2024-1434, https://doi.org/10.5194/egusphere-2024-1434, 2024
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We present a robust method for identification and classification of global land drought events (GLDEs) based on soil moisture. Two models were used to calculate soil moisture and delimit soil drought over global land from 1980–2022, which was clustered into 775/630 GLDEs. Using four spatiotemporal and three motion-related characteristics, we categorized GLDEs into seven severity and seven dynamic categories. The frequency of GLDEs has generally increased in recent decades.
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.
Kazeem Ishola, Gerald Mills, Ankur Sati, Benjamin Obe, Matthias Demuzere, Deepak Upreti, Gourav Misra, Paul Lewis, Daire Walsh, Tim McCarthy, and Rowan Fealy
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-304, https://doi.org/10.5194/hess-2023-304, 2024
Revised manuscript accepted for HESS
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The global soil information contributes to uncertainty in many models that monitor soil hydrothermal changes. Using the NOAH-MP model with two different global soil information, we show under-represented soil properties in wet loam soil, leading to dry bias in soil moisture. The dry bias is higher and drought categories are more severe in SOILGRIDS. We conclude that models should consider using detailed regionally-derived soil information, to reduce model uncertainties.
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.
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.
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.
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.
Cited articles
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...
