Articles | Volume 18, issue 11
https://doi.org/10.5194/hess-18-4363-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-18-4363-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
04 Nov 2014
Research article |
| 04 Nov 2014
Translating aboveground cosmic-ray neutron intensity to high-frequency soil moisture profiles at sub-kilometer scale
R. Rosolem
Queens School of Engineering, University of Bristol, Bristol, UK
T. Hoar
NCAR Data Assimilation Research Section, Boulder, USA
A. Arellano
Department of Atmospheric Sciences, University of Arizona, Tucson, USA
J. L. Anderson
NCAR Data Assimilation Research Section, Boulder, USA
W. J. Shuttleworth
Department of Hydrology and Water Resources, University of Arizona, Tucson, USA
Department of Atmospheric Sciences, University of Arizona, Tucson, USA
T. E. Franz
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, USA
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J. Shuttleworth, R. Rosolem, M. Zreda, and T. Franz
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Short summary
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Hydrol. Earth Syst. Sci., 25, 6339–6357, https://doi.org/10.5194/hess-25-6339-2021, https://doi.org/10.5194/hess-25-6339-2021, 2021
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Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
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Short summary
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Groundwater is increasingly being included in large-scale (continental to global) land surface and hydrologic simulations. However, it is challenging to evaluate these simulations because groundwater is
hiddenunderground and thus hard to measure. We suggest using multiple complementary strategies to assess the performance of a model (
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Observations of winds in the planetary boundary layer remain sparse, making it challenging to simulate and predict the atmospheric conditions that are most important for describing and predicting urban air quality. Here we investigate the application of data assimilation of NO2 columns as will be observed from geostationary orbit to improve predictions and retrospective analysis of wind fields in the boundary layer.
Yong-Fei Zhang, Cecilia M. Bitz, Jeffrey L. Anderson, Nancy S. Collins, Timothy J. Hoar, Kevin D. Raeder, and Edward Blanchard-Wrigglesworth
The Cryosphere, 15, 1277–1284, https://doi.org/10.5194/tc-15-1277-2021, https://doi.org/10.5194/tc-15-1277-2021, 2021
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Sea ice models suffer from large uncertainties arising from multiple sources, among which parametric uncertainty is highly under-investigated. We select a key ice albedo parameter and update it by assimilating either sea ice concentration or thickness observations. We found that the sea ice albedo parameter is improved by data assimilation, especially by assimilating sea ice thickness observations. The improved parameter can further benefit the forecast of sea ice after data assimilation stops.
Andrew Tangborn, Belay Demoz, Brian J. Carroll, Joseph Santanello, and Jeffrey L. Anderson
Atmos. Meas. Tech., 14, 1099–1110, https://doi.org/10.5194/amt-14-1099-2021, https://doi.org/10.5194/amt-14-1099-2021, 2021
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Accurate prediction of the planetary boundary layer is essential to both numerical weather prediction (NWP) and pollution forecasting. This paper presents a methodology to combine these measurements with the models through a statistical data assimilation approach that calculates the correlation between the PBLH and variables like temperature and moisture in the model. The model estimates of these variables can be improved via this method, and this will enable increased forecast accuracy.
Isaac Kipkemoi, Katerina Michaelides, Rafael Rosolem, and Michael Bliss Singer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-48, https://doi.org/10.5194/hess-2021-48, 2021
Manuscript not accepted for further review
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The work is a novel investigation of the role of temporal rainfall resolution and intensity in affecting the water balance of soil in a dryland environment. This research has implications for what rainfall data are used to assess the impact of climate and climate change on the regional water balance. This information is critical for anticipating the impact of a changing climate on dryland communities globally who need it to know when to plant their seeds or where livestock pasture is available.
Benjamin Gaubert, Louisa K. Emmons, Kevin Raeder, Simone Tilmes, Kazuyuki Miyazaki, Avelino F. Arellano Jr., Nellie Elguindi, Claire Granier, Wenfu Tang, Jérôme Barré, Helen M. Worden, Rebecca R. Buchholz, David P. Edwards, Philipp Franke, Jeffrey L. Anderson, Marielle Saunois, Jason Schroeder, Jung-Hun Woo, Isobel J. Simpson, Donald R. Blake, Simone Meinardi, Paul O. Wennberg, John Crounse, Alex Teng, Michelle Kim, Russell R. Dickerson, Hao He, Xinrong Ren, Sally E. Pusede, and Glenn S. Diskin
Atmos. Chem. Phys., 20, 14617–14647, https://doi.org/10.5194/acp-20-14617-2020, https://doi.org/10.5194/acp-20-14617-2020, 2020
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This study investigates carbon monoxide pollution in East Asia during spring using a numerical model, satellite remote sensing, and aircraft measurements. We found an underestimation of emission sources. Correcting the emission bias can improve air quality forecasting of carbon monoxide and other species including ozone. Results also suggest that controlling VOC and CO emissions, in addition to widespread NOx controls, can improve ozone pollution over East Asia.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-378, https://doi.org/10.5194/hess-2020-378, 2020
Revised manuscript not accepted
Shaini Naha, Miguel A. Rico-Ramirez, and Rafael Rosolem
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-220, https://doi.org/10.5194/hess-2020-220, 2020
Manuscript not accepted for further review
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Rapid growth in population in developing countries leads to an increase in food demand and as a consequence, percentages of land are being converted to cropland which alters the river flow processes. Therefore we try to understand the exact role of these changes in modifying the river flows through the prediction of the impacts of these changes in the future by taking a clue from the past. This study concludes that recurrent flood events might be influenced by these changes in future.
Hossein Dadashazar, Ewan Crosbie, Mohammad S. Majdi, Milad Panahi, Mohammad A. Moghaddam, Ali Behrangi, Michael Brunke, Xubin Zeng, Haflidi H. Jonsson, and Armin Sorooshian
Atmos. Chem. Phys., 20, 4637–4665, https://doi.org/10.5194/acp-20-4637-2020, https://doi.org/10.5194/acp-20-4637-2020, 2020
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Clearings in the marine-boundary-layer (MBL) cloud deck of the Pacific Ocean were studied. Remote sensing, reanalysis, and airborne data were used along with machine-learning modeling to characterize the spatiotemporal nature of clearings and factors governing their growth. The most significant implications of our results are linked to modeling of fog and MBL clouds, with implications for societal and environmental issues like climate, military operations, transportation, and coastal ecology.
Romane Berthelin, Michael Rinderer, Bartolomé Andreo, Andy Baker, Daniela Kilian, Gabriele Leonhardt, Annette Lotz, Kurt Lichtenwoehrer, Matías Mudarra, Ingrid Y. Padilla, Fernando Pantoja Agreda, Rafael Rosolem, Abel Vale, and Andreas Hartmann
Geosci. Instrum. Method. Data Syst., 9, 11–23, https://doi.org/10.5194/gi-9-11-2020, https://doi.org/10.5194/gi-9-11-2020, 2020
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We present the setup of a soil moisture monitoring network, which is implemented at five karstic sites with different climates across the globe. More than 400 soil moisture probes operating at a high spatio-temporal resolution will improve the understanding of groundwater recharge and evapotranspiration processes in karstic areas.
Fanny Sarrazin, Andreas Hartmann, Francesca Pianosi, Rafael Rosolem, and Thorsten Wagener
Geosci. Model Dev., 11, 4933–4964, https://doi.org/10.5194/gmd-11-4933-2018, https://doi.org/10.5194/gmd-11-4933-2018, 2018
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We propose the first large-scale vegetation–recharge model for karst regions (V2Karst), which enables the analysis of the impact of changes in climate and land cover on karst groundwater recharge. We demonstrate the plausibility of V2Karst simulations against observations at FLUXNET sites and of controlling modelled processes using sensitivity analysis. We perform virtual experiments to further test the model and gain insight into its sensitivity to precipitation pattern and vegetation cover.
Michael A. Brunke, John J. Cassano, Nicholas Dawson, Alice K. DuVivier, William J. Gutowski Jr., Joseph Hamman, Wieslaw Maslowski, Bart Nijssen, J. E. Jack Reeves Eyre, José C. Renteria, Andrew Roberts, and Xubin Zeng
Geosci. Model Dev., 11, 4817–4841, https://doi.org/10.5194/gmd-11-4817-2018, https://doi.org/10.5194/gmd-11-4817-2018, 2018
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The Regional Arctic System Model version 1 (RASM1) was recently developed for high-resolution simulation of the coupled atmosphere–ocean–sea ice–land system in the Arctic. Its simulation of the atmosphere–land–ocean–sea ice interface is evaluated by using the spread in recent reanalyses and a global Earth system model as baselines. Such comparisons reveal that RASM1 simulates precipitation well and improves the simulation of surface fluxes over sea ice.
Arthur P. Mizzi, David P. Edwards, and Jeffrey L. Anderson
Geosci. Model Dev., 11, 3727–3745, https://doi.org/10.5194/gmd-11-3727-2018, https://doi.org/10.5194/gmd-11-3727-2018, 2018
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Accurate air quality forecasts are critical to protecting human health and the environment. This paper shows how ensemble assimilation of MOPITT CO
compact phase space retrieval(CPSR) profiles in WRF-Chem/DART provides significant improvements in the air quality forecasts over the CONUS when compared to independent remote (IASI CO retrieval profiles) and in situ (IAGOS/MOZAIC) observations. It also extends the CPSR algorithm to assimilation of truncated retrieval profiles.
Ali Aydoğdu, Timothy J. Hoar, Tomislava Vukicevic, Jeffrey L. Anderson, Nadia Pinardi, Alicia Karspeck, Jonathan Hendricks, Nancy Collins, Francesca Macchia, and Emin Özsoy
Nonlin. Processes Geophys., 25, 537–551, https://doi.org/10.5194/npg-25-537-2018, https://doi.org/10.5194/npg-25-537-2018, 2018
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This study presents, to our knowledge, the first data assimilation experiments in the Sea of Marmara. We propose a FerryBox network for monitoring the state of the sea and show that assimilation of the temperature and salinity improves the forecasts in the basin. The flow of the Bosphorus helps to propagate the error reduction. The study can be taken as a step towards a marine forecasting system in the Sea of Marmara that will help to improve the forecasts in the adjacent Black and Aegean seas.
Martin Schrön, Markus Köhli, Lena Scheiffele, Joost Iwema, Heye R. Bogena, Ling Lv, Edoardo Martini, Gabriele Baroni, Rafael Rosolem, Jannis Weimar, Juliane Mai, Matthias Cuntz, Corinna Rebmann, Sascha E. Oswald, Peter Dietrich, Ulrich Schmidt, and Steffen Zacharias
Hydrol. Earth Syst. Sci., 21, 5009–5030, https://doi.org/10.5194/hess-21-5009-2017, https://doi.org/10.5194/hess-21-5009-2017, 2017
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A field-scale average of near-surface water content can be sensed by cosmic-ray neutron detectors. To interpret, calibrate, and validate the integral signal, it is important to account for its sensitivity to heterogeneous patterns like dry or wet spots. We show how point samples contribute to the neutron signal based on their depth and distance from the detector. This approach robustly improves the sensor performance and data consistency, and even reveals otherwise hidden hydrological features.
Christa D. Peters-Lidard, Martyn Clark, Luis Samaniego, Niko E. C. Verhoest, Tim van Emmerik, Remko Uijlenhoet, Kevin Achieng, Trenton E. Franz, and Ross Woods
Hydrol. Earth Syst. Sci., 21, 3701–3713, https://doi.org/10.5194/hess-21-3701-2017, https://doi.org/10.5194/hess-21-3701-2017, 2017
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In this synthesis of hydrologic scaling and similarity, we assert that it is time for hydrology to embrace a fourth paradigm of data-intensive science. Advances in information-based hydrologic science, coupled with an explosion of hydrologic data and advances in parameter estimation and modeling, have laid the foundation for a data-driven framework for scrutinizing hydrological hypotheses. We call upon the community to develop a focused effort towards a fourth paradigm for hydrology.
J. E. Jack Reeves Eyre and Xubin Zeng
The Cryosphere, 11, 1591–1605, https://doi.org/10.5194/tc-11-1591-2017, https://doi.org/10.5194/tc-11-1591-2017, 2017
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We have used extensive air temperature measurements (~ 1400 station-years) to assess more than 10 gridded datasets over the Greenland ice sheet. We recommend the best datasets for estimating past melting of the ice sheet and show that choice of dataset is important for evaluating 31 earth system models. Most, but not all, of the datasets show similar history of temperature changes over the 20th century, and the earth system models generally capture long-term warming but not decadal variations.
Xueling Liu, Arthur P. Mizzi, Jeffrey L. Anderson, Inez Y. Fung, and Ronald C. Cohen
Atmos. Chem. Phys., 17, 7067–7081, https://doi.org/10.5194/acp-17-7067-2017, https://doi.org/10.5194/acp-17-7067-2017, 2017
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We describe a chemical ensemble data assimilation system with high spatial and temporal resolution that simultaneously adjusts meteorological and chemical variables and NOx emissions. We investigate the sensitivity of emission inversions to the accuracy and uncertainty of the wind analyses and the emission update scheme. The results provide insight into optimal uses of the observations from future geostationary satellite missions that will observe atmospheric composition.
Joost Iwema, Rafael Rosolem, Mostaquimur Rahman, Eleanor Blyth, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 21, 2843–2861, https://doi.org/10.5194/hess-21-2843-2017, https://doi.org/10.5194/hess-21-2843-2017, 2017
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We investigated whether the simulation of water flux from the land surface to the atmosphere (using the Joint UK Land Environment Simulator model) could be improved by replacing traditional soil moisture sensor data with data from the more novel Cosmic-Ray Neutron soil moisture sensor. Despite observed differences between the two types of soil moisture measurement data, we found no substantial differences in improvement in water flux estimation, based on multiple calibration experiments.
Foad Foolad, Trenton E. Franz, Tiejun Wang, Justin Gibson, Ayse Kilic, Richard G. Allen, and Andrew Suyker
Hydrol. Earth Syst. Sci., 21, 1263–1277, https://doi.org/10.5194/hess-21-1263-2017, https://doi.org/10.5194/hess-21-1263-2017, 2017
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Estimates of evapotranspiration are vital for validation of models. However, those datasets are often limited to research applications. Here, we explore using vadose zone modeling with widespread and readily available soil water content monitoring networks. While this work focused on one agricultural site, the framework can be used everywhere there is basic data. The resulting evapotranspiration and soil water content measurements are valuable benchmarks for evaluation of land surface models.
Justin Gibson, Trenton E. Franz, Tiejun Wang, John Gates, Patricio Grassini, Haishun Yang, and Dean Eisenhauer
Hydrol. Earth Syst. Sci., 21, 1051–1062, https://doi.org/10.5194/hess-21-1051-2017, https://doi.org/10.5194/hess-21-1051-2017, 2017
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The human use of water for irrigation is often ignored in models and operational forecasts. We describe four plausible and relatively simple irrigation routines that can be coupled to the next generation of models. The routines are tested against a unique irrigation dataset from western Nebraska. The most aggressive water-saving irrigation routine indicates a potential irrigation savings of 120 mm yr−1 and yield losses of less than 3 % against the crop model benchmark and historical averages.
Mostaquimur Rahman and Rafael Rosolem
Hydrol. Earth Syst. Sci., 21, 459–471, https://doi.org/10.5194/hess-21-459-2017, https://doi.org/10.5194/hess-21-459-2017, 2017
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Modelling water flow through chalk (a fine-grained porous medium traversed by fractures) is important for optimizing water resource management practices in the UK. However, efficient simulations of water movement through chalk are difficult due to the porous nature of chalk, creating high-velocity preferential flow paths. This paper describes a novel approach to representing chalk hydrology in land surface modelling for large-scale applications.
Juli I. Rubin, Jeffrey S. Reid, James A. Hansen, Jeffrey L. Anderson, Nancy Collins, Timothy J. Hoar, Timothy Hogan, Peng Lynch, Justin McLay, Carolyn A. Reynolds, Walter R. Sessions, Douglas L. Westphal, and Jianglong Zhang
Atmos. Chem. Phys., 16, 3927–3951, https://doi.org/10.5194/acp-16-3927-2016, https://doi.org/10.5194/acp-16-3927-2016, 2016
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This work tests the use of an ensemble prediction system for aerosol forecasting, including an ensemble adjustment Kalman filter for MODIS AOT assimilation. Key findings include (1) meteorology and source-perturbed ensembles are needed to capture long-range transport and near-source aerosol events, (2) adaptive covariance inflation is recommended for assimilating spatially heterogeneous observations and (3) the ensemble system captures sharp gradients relative to a deterministic/variational system.
Arthur P. Mizzi, Avelino F. Arellano Jr., David P. Edwards, Jeffrey L. Anderson, and Gabriele G. Pfister
Geosci. Model Dev., 9, 965–978, https://doi.org/10.5194/gmd-9-965-2016, https://doi.org/10.5194/gmd-9-965-2016, 2016
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This paper introduces (i) WRF-Chem/DART – a state-of-the-art chemical transport/data assimilation system, and (ii) compact phase space retrievals (CPSRs). WRF-Chem/DART is NCAR's regional chemical weather forecasting prototype. Such systems require assimilation of chemical composition observations, such as trace gas retrievals. Retrievals are expensive to assimilate. CPSRs reduce those assimilation costs (~ 35 % for MOPITT CO) without loss in forecast skill by removing redundant information.
X. Han, X. Li, G. He, P. Kumbhar, C. Montzka, S. Kollet, T. Miyoshi, R. Rosolem, Y. Zhang, H. Vereecken, and H.-J. H. Franssen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-8-7395-2015, https://doi.org/10.5194/gmdd-8-7395-2015, 2015
Revised manuscript not accepted
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DasPy is a ready to use open source parallel multivariate land data assimilation framework with joint state and parameter estimation using Local Ensemble Transform Kalman Filter. The Community Land Model (4.5) was integrated as model operator. The Community Microwave Emission Modelling platform, COsmic-ray Soil Moisture Interaction Code and the Two-Source Formulation were integrated as observation operators for the multivariate assimilation of soil moisture and soil temperature, respectively.
J. Iwema, R. Rosolem, R. Baatz, T. Wagener, and H. R. Bogena
Hydrol. Earth Syst. Sci., 19, 3203–3216, https://doi.org/10.5194/hess-19-3203-2015, https://doi.org/10.5194/hess-19-3203-2015, 2015
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The cosmic-ray neutron sensor can provide soil moisture content averages over areas of roughly half a kilometre by half a kilometre. Although this sensor is usually calibrated using soil samples taken on a single day, we found that multiple sampling days are needed. The calibration results were also affected by the soil wetness conditions of the sampling days. The outcome of this study will help researchers to calibrate/validate new cosmic-ray neutron sensor sites more accurately.
P. T. S. Oliveira, E. Wendland, M. A. Nearing, R. L. Scott, R. Rosolem, and H. R. da Rocha
Hydrol. Earth Syst. Sci., 19, 2899–2910, https://doi.org/10.5194/hess-19-2899-2015, https://doi.org/10.5194/hess-19-2899-2015, 2015
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We determined the main components of the water balance for an undisturbed cerrado.
Evapotranspiration ranged from 1.91 to 2.60mm per day for the dry and wet seasons, respectively. Canopy interception ranged from 4 to 20% and stemflow values were approximately 1% of gross precipitation.
The average runoff coefficient was less than 1%, while cerrado deforestation has the potential to increase that amount up to 20-fold.
The water storage may be estimated by the difference between P and ET.
A. Hartmann, T. Gleeson, R. Rosolem, F. Pianosi, Y. Wada, and T. Wagener
Geosci. Model Dev., 8, 1729–1746, https://doi.org/10.5194/gmd-8-1729-2015, https://doi.org/10.5194/gmd-8-1729-2015, 2015
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We present a new approach to assess karstic groundwater recharge over Europe and the Mediterranean. Cluster analysis is used to subdivide all karst regions into four typical karst landscapes and to simulate karst recharge with a process-based karst model. We estimate its parameters by a combination of a priori information and observations of soil moisture and evapotranspiration. Independent observations of recharge that present large-scale models significantly under-estimate karstic recharge.
X. Han, H.-J. H. Franssen, R. Rosolem, R. Jin, X. Li, and H. Vereecken
Hydrol. Earth Syst. Sci., 19, 615–629, https://doi.org/10.5194/hess-19-615-2015, https://doi.org/10.5194/hess-19-615-2015, 2015
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This paper presents the joint assimilation of cosmic-ray neutron counts and land surface temperature with parameter estimation of leaf area index at an irrigated corn field. The results show that the data assimilation can reduce the systematic input errors due to the lack of irrigation data. The estimations of soil moisture, evapotranspiration and leaf area index can be improved in the joint assimilation framework.
W. J. Shuttleworth
Hydrol. Earth Syst. Sci., 18, 4403–4406, https://doi.org/10.5194/hess-18-4403-2014, https://doi.org/10.5194/hess-18-4403-2014, 2014
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This paper explains the Matt-Shuttleworth approach clearly, simply and concisely. It shows how this approach can be implemented using a few simple equations and provides access to ancillary calculation resources that can be used for such implementation. If the crop water requirement community considered it preferable to use the Penman-Monteith equation to estimate crop water requirements directly for all crops, this could now be done using the Matt-Shuttleworth approach.
A. I. Gevaert, A. J. Teuling, R. Uijlenhoet, S. B. DeLong, T. E. Huxman, L. A. Pangle, D. D. Breshears, J. Chorover, J. D. Pelletier, S. R. Saleska, X. Zeng, and P. A. Troch
Hydrol. Earth Syst. Sci., 18, 3681–3692, https://doi.org/10.5194/hess-18-3681-2014, https://doi.org/10.5194/hess-18-3681-2014, 2014
P. Shao, X. Zeng, and X. Zeng
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esdd-5-991-2014, https://doi.org/10.5194/esdd-5-991-2014, 2014
Revised manuscript not accepted
J. Shuttleworth, R. Rosolem, M. Zreda, and T. Franz
Hydrol. Earth Syst. Sci., 17, 3205–3217, https://doi.org/10.5194/hess-17-3205-2013, https://doi.org/10.5194/hess-17-3205-2013, 2013
H. M. Worden, D. P. Edwards, M. N. Deeter, D. Fu, S. S. Kulawik, J. R. Worden, and A. Arellano
Atmos. Meas. Tech., 6, 1633–1646, https://doi.org/10.5194/amt-6-1633-2013, https://doi.org/10.5194/amt-6-1633-2013, 2013
T. E. Franz, M. Zreda, R. Rosolem, and T. P. A. Ferre
Hydrol. Earth Syst. Sci., 17, 453–460, https://doi.org/10.5194/hess-17-453-2013, https://doi.org/10.5194/hess-17-453-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
Observation-driven model for calculating water-harvesting potential from advective fog in (semi-)arid coastal regions
Review of gridded climate products and their use in hydrological analyses reveals overlaps, gaps, and the need for a more objective approach to selecting model forcing datasets
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
Multi-objective calibration and evaluation of the ORCHIDEE land surface model over France at high resolution
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
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 variable infiltration capacity
Distribution, trends and drivers of flash droughts in the United Kingdom
Are dependencies of extreme rainfall on humidity more reliable in convection-permitting climate models?
Spatial variability in the seasonal precipitation lapse rates in complex topographical regions – application in France
What Are the Key Soil Hydrological Processes to Control Soil Moisture Memory?
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
Leveraging a Disdrometer Network to Develop a Probabilistic Precipitation Phase Model in Eastern Canada
Assessment of seasonal soil moisture forecasts over Central Mediterranean toward groundwater management
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
A genetic particle filter scheme for univariate snow cover assimilation into Noah-MP model across snow climates
Investigating the response of land–atmosphere interactions and feedbacks to spatial representation of irrigation in a coupled modeling framework
Validation of precipitation reanalysis products for rainfall-runoff modelling in Slovenia
Statistical post-processing of precipitation forecasts using circulation classifications and spatiotemporal deep neural networks
Sensitivity of the pseudo-global warming method under flood conditions: a case study from the northeastern US
Hybrid forecasting: blending climate predictions with AI models
Sensitivities of subgrid-scale physics schemes, meteorological forcing, and topographic radiation in atmosphere-through-bedrock integrated process models: a case study in the Upper Colorado River basin
Local moisture recycling across the globe
How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation?
Regionalisation of rainfall depth–duration–frequency curves with different data types in Germany
The suitability of a seasonal ensemble hybrid framework including data-driven approaches for hydrological forecasting
Continuous streamflow prediction in ungauged basins: long short-term memory neural networks clearly outperform traditional hydrological models
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.
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.
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.
He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 4361–4381, https://doi.org/10.5194/hess-28-4361-2024, https://doi.org/10.5194/hess-28-4361-2024, 2024
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Our findings show that runoff in the Yarlung Zangbo (YZ) basin is primarily driven by rainfall, with the largest glacier runoff contribution in the downstream sub-basin. Annual runoff increased in the upper stream but decreased downstream due to varying precipitation patterns. It is expected to rise throughout the 21st century, mainly driven by increased rainfall.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
Hydrol. Earth Syst. Sci., 28, 4127–4155, https://doi.org/10.5194/hess-28-4127-2024, https://doi.org/10.5194/hess-28-4127-2024, 2024
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Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Hydrol. Earth Syst. Sci., 28, 3777–3797, https://doi.org/10.5194/hess-28-3777-2024, https://doi.org/10.5194/hess-28-3777-2024, 2024
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The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the cellular automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
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We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024, https://doi.org/10.5194/hess-28-3457-2024, 2024
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Daily streamflow series for 661 near-natural French catchments are reconstructed over 1871–2012 using two ensemble datasets: HydRE and HydREM. They include uncertainties coming from climate forcings, streamflow measurement, and hydrological model error (for HydrREM). Comparisons with other hydrological reconstructions and independent/dependent observations show the added value of the two reconstructions in terms of quality, uncertainty estimation, and representation of extremes.
María Agostina Bracalenti, Omar V. Müller, Miguel A. Lovino, and Ernesto Hugo Berbery
Hydrol. Earth Syst. Sci., 28, 3281–3303, https://doi.org/10.5194/hess-28-3281-2024, https://doi.org/10.5194/hess-28-3281-2024, 2024
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The Gran Chaco is a large, dry forest in South America that has been heavily deforested, particularly in the dry Chaco subregion. This deforestation, mainly driven by the expansion of the agricultural frontier, has changed the land's characteristics, affecting the local and regional climate. The study reveals that deforestation has resulted in reduced precipitation, soil moisture, and runoff, and if intensive agriculture continues, it could make summers in this arid region even drier and hotter.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
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Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, https://doi.org/10.5194/hess-28-3079-2024, 2024
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We fine-tuned the variable infiltration capacity (VIC) and Noah-MP models across 263 river basins in the Western US. We developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins. Both models performed best in humid areas, and the skills improved post-calibration. VIC outperforms Noah-MP in all but interior dry basins following regionalization. VIC simulates annual mean streamflow and high flow well, while Noah-MP performs better for low flows.
Iván Noguera, Jamie Hannaford, and Maliko Tanguy
EGUsphere, https://doi.org/10.5194/egusphere-2024-1969, https://doi.org/10.5194/egusphere-2024-1969, 2024
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In this study, we present a detailed characterisation of flash drought in United Kingdom over the period 1969–2021.The spatiotemporal distribution of flash droughts is highly variable, with important regional and seasonal contrasts. In the UK, flash drought occurrence responds primarily to precipitation variability, although the atmospheric evaporative demand (AED) is important as a secondary driver. The atmospheric and oceanic conditions during flash droughts development were also analyzed.
Geert Lenderink, Nikolina Ban, Erwan Brisson, Ségolène Berthou, Virginia Edith Cortés-Hernández, Elizabeth Kendon, Hayley Fowler, and Hylke de Vries
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-132, https://doi.org/10.5194/hess-2024-132, 2024
Revised manuscript accepted for HESS
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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.
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.
Mohammad Ali Farmani, Ali Behrangi, Aniket Gupta, Ahmad Tavakoly, Matthew Geheran, and Guo-Yue Niu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1256, https://doi.org/10.5194/egusphere-2024-1256, 2024
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This study investigates how key hydrological processes enhance soil water retention and release in land surface models, crucial for accurate weather and climate forecasting. Experiments show that soil hydraulics effectively sustain soil moisture. Additionally, allowing surface water ponding and improving soil permeability through macropores both enhance soil moisture persistency in the models.
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.
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-78, https://doi.org/10.5194/hess-2024-78, 2024
Revised manuscript accepted for HESS
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Observations from a study site network in eastern Canada showed a temperature interval the overlapping probabilities for rain, snow or a mix of both. Models using random forest algorithms were developed to classify the precipitation phase using meteorological data to evaluate operational applications. They showed significantly improved phase classification compared to benchmarks, but misclassification led to costlier errors. However, accurate prediction of mixed phase remains a challenge.
Lorenzo Silvestri, Miriam Saraceni, Giulia Passadore, and Paolina Bongioannini Cerlini
EGUsphere, https://doi.org/10.5194/egusphere-2024-889, https://doi.org/10.5194/egusphere-2024-889, 2024
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This work demonstrates that seasonal forecasts of soil moisture are a valuable resource for groundwater management in certain areas of the Central Mediterranean. 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.
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.
Yuanhong You, Chunlin Huang, Zuo Wang, Jinliang Hou, Ying Zhang, and Peipei Xu
Hydrol. Earth Syst. Sci., 27, 2919–2933, https://doi.org/10.5194/hess-27-2919-2023, https://doi.org/10.5194/hess-27-2919-2023, 2023
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This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.
Patricia Lawston-Parker, Joseph A. Santanello Jr., and Nathaniel W. Chaney
Hydrol. Earth Syst. Sci., 27, 2787–2805, https://doi.org/10.5194/hess-27-2787-2023, https://doi.org/10.5194/hess-27-2787-2023, 2023
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Irrigation has been shown to impact weather and climate, but it has only recently been considered in prediction models. Prescribing where (globally) irrigation takes place is important to accurately simulate its impacts on temperature, humidity, and precipitation. Here, we evaluated three different irrigation maps in a weather model and found that the extent and intensity of irrigated areas and their boundaries are important drivers of weather impacts resulting from human practices.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
Hydrol. Earth Syst. Sci., 27, 2559–2578, https://doi.org/10.5194/hess-27-2559-2023, https://doi.org/10.5194/hess-27-2559-2023, 2023
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For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.
Tuantuan Zhang, Zhongmin Liang, Wentao Li, Jun Wang, Yiming Hu, and Binquan Li
Hydrol. Earth Syst. Sci., 27, 1945–1960, https://doi.org/10.5194/hess-27-1945-2023, https://doi.org/10.5194/hess-27-1945-2023, 2023
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We use circulation classifications and spatiotemporal deep neural networks to correct raw daily forecast precipitation by combining large-scale circulation patterns with local spatiotemporal information. We find that the method not only captures the westward and northward movement of the western Pacific subtropical high but also shows substantially higher bias-correction capabilities than existing standard methods in terms of spatial scale, timescale, and intensity.
Zeyu Xue, Paul Ullrich, and Lai-Yung Ruby Leung
Hydrol. Earth Syst. Sci., 27, 1909–1927, https://doi.org/10.5194/hess-27-1909-2023, https://doi.org/10.5194/hess-27-1909-2023, 2023
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We examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments and varying the perturbation spatial scales and choice of perturbed meteorological variables to provide a guideline for this increasingly popular regional modeling method. Overall, we recommend PGW experiments be performed with perturbations to temperature or the combination of temperature and wind at the gridpoint scale, depending on the research question.
Louise J. Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023, https://doi.org/10.5194/hess-27-1865-2023, 2023
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Hybrid forecasting systems combine data-driven methods with physics-based weather and climate models to improve the accuracy of predictions for meteorological and hydroclimatic events such as rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. We review recent developments in hybrid forecasting and outline key challenges and opportunities in the field.
Zexuan Xu, Erica R. Siirila-Woodburn, Alan M. Rhoades, and Daniel Feldman
Hydrol. Earth Syst. Sci., 27, 1771–1789, https://doi.org/10.5194/hess-27-1771-2023, https://doi.org/10.5194/hess-27-1771-2023, 2023
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The goal of this study is to understand the uncertainties of different modeling configurations for simulating hydroclimate responses in the mountainous watershed. We run a group of climate models with various configurations and evaluate them against various reference datasets. This paper integrates a climate model and a hydrology model to have a full understanding of the atmospheric-through-bedrock hydrological processes.
Jolanda J. E. Theeuwen, Arie Staal, Obbe A. Tuinenburg, Bert V. M. Hamelers, and Stefan C. Dekker
Hydrol. Earth Syst. Sci., 27, 1457–1476, https://doi.org/10.5194/hess-27-1457-2023, https://doi.org/10.5194/hess-27-1457-2023, 2023
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Evaporation changes over land affect rainfall over land via moisture recycling. We calculated the local moisture recycling ratio globally, which describes the fraction of evaporated moisture that rains out within approx. 50 km of its source location. This recycling peaks in summer as well as over wet and elevated regions. Local moisture recycling provides insight into the local impacts of evaporation changes and can be used to study the influence of regreening on local rainfall.
Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, Giuseppe Formetta, Christoph Schär, and Marco Borga
Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, https://doi.org/10.5194/hess-27-1133-2023, 2023
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Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Bora Shehu, Winfried Willems, Henrike Stockel, Luisa-Bianca Thiele, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 1109–1132, https://doi.org/10.5194/hess-27-1109-2023, https://doi.org/10.5194/hess-27-1109-2023, 2023
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Rainfall volumes at varying duration and frequencies are required for many engineering water works. These design volumes have been provided by KOSTRA-DWD in Germany. However, a revision of the KOSTRA-DWD is required, in order to consider the recent state-of-the-art and additional data. For this purpose, in our study, we investigate different methods and data available to achieve the best procedure that will serve as a basis for the development of the new KOSTRA-DWD product.
Sandra M. Hauswirth, Marc F. P. Bierkens, Vincent Beijk, and Niko Wanders
Hydrol. Earth Syst. Sci., 27, 501–517, https://doi.org/10.5194/hess-27-501-2023, https://doi.org/10.5194/hess-27-501-2023, 2023
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Forecasts on water availability are important for water managers. We test a hybrid framework based on machine learning models and global input data for generating seasonal forecasts. Our evaluation shows that our discharge and surface water level predictions are able to create reliable forecasts up to 2 months ahead. We show that a hybrid framework, developed for local purposes and combined and rerun with global data, can create valuable information similar to large-scale forecasting models.
Richard Arsenault, Jean-Luc Martel, Frédéric Brunet, François Brissette, and Juliane Mai
Hydrol. Earth Syst. Sci., 27, 139–157, https://doi.org/10.5194/hess-27-139-2023, https://doi.org/10.5194/hess-27-139-2023, 2023
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Predicting flow in rivers where no observation records are available is a daunting task. For decades, hydrological models were set up on these gauges, and their parameters were estimated based on the hydrological response of similar or nearby catchments where records exist. New developments in machine learning have now made it possible to estimate flows at ungauged locations more precisely than with hydrological models. This study confirms the performance superiority of machine learning models.
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