Articles | Volume 28, issue 9
https://doi.org/10.5194/hess-28-1999-2024
© Author(s) 2024. 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-28-1999-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 May 2024
Research article |
| 07 May 2024
| 07 May 2024
Evaluation of reanalysis soil moisture products using cosmic ray neutron sensor observations across the globe
Yanchen Zheng
CORRESPONDING AUTHOR
School of Geographical Sciences, University of Bristol, Bristol, UK
School of Civil, Aerospace and Design Engineering, University of Bristol, Bristol, UK
Gemma Coxon
School of Geographical Sciences, University of Bristol, Bristol, UK
Ross Woods
School of Civil, Aerospace and Design Engineering, University of Bristol, Bristol, UK
Daniel Power
School of Civil, Aerospace and Design Engineering, University of Bristol, Bristol, UK
Miguel Angel Rico-Ramirez
School of Civil, Aerospace and Design Engineering, University of Bristol, Bristol, UK
David McJannet
CSIRO Environment, EcoSciences Precinct, Dutton Park, Queensland, Australia
Rafael Rosolem
School of Civil, Aerospace and Design Engineering, University of Bristol, Bristol, UK
Cabot Institute for the Environment, University of Bristol, Bristol, UK
Jianzhu Li
State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin, China
Ping Feng
State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin, China
Related authors
Yanchen Zheng, Gemma Coxon, Mostaquimur Rahman, Ross Woods, Saskia Salwey, Youtong Rong, and Doris E. Wendt
Geosci. Model Dev., 18, 4247–4271, https://doi.org/10.5194/gmd-18-4247-2025, https://doi.org/10.5194/gmd-18-4247-2025, 2025
Short summary
Short summary
Groundwater is vital for people and ecosystems, but most physical models lack the representation of surface–groundwater interactions, leading to inaccurate streamflow predictions in groundwater-rich areas. This study presents DECIPHeR-GW v1, which links surface and groundwater systems to improve predictions of streamflow and groundwater levels. Tested across England and Wales, DECIPHeR-GW shows high accuracy, especially in southeast England, making it a valuable tool for large-scale water management.
Kathryn A. Leeming, John P. Bloomfield, Gemma Coxon, and Yanchen Zheng
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-202, https://doi.org/10.5194/hess-2023-202, 2023
Preprint withdrawn
Short summary
Short summary
In this work we characterise annual patterns in baseflow, the component of streamflow that comes from subsurface storage. Our research identified early-, mid-, and late-seasonality of baseflow across catchments in Great Britain over two time blocks: 1976–1995 and 1996–2015, and found that many catchments have earlier seasonal patterns of baseflow in the second time period. These changes are linked to changes in climate signals: snow-melt in highland catchments and effective rainfall changes.
Yanchen Zheng, Gemma Coxon, Mostaquimur Rahman, Ross Woods, Saskia Salwey, Youtong Rong, and Doris E. Wendt
Geosci. Model Dev., 18, 4247–4271, https://doi.org/10.5194/gmd-18-4247-2025, https://doi.org/10.5194/gmd-18-4247-2025, 2025
Short summary
Short summary
Groundwater is vital for people and ecosystems, but most physical models lack the representation of surface–groundwater interactions, leading to inaccurate streamflow predictions in groundwater-rich areas. This study presents DECIPHeR-GW v1, which links surface and groundwater systems to improve predictions of streamflow and groundwater levels. Tested across England and Wales, DECIPHeR-GW shows high accuracy, especially in southeast England, making it a valuable tool for large-scale water management.
William Veness, Alejandro Dussaillant, Gemma Coxon, Simon De Stercke, Gareth H. Old, Matthew Fry, Jonathan G. Evans, and Wouter Buytaert
EGUsphere, https://doi.org/10.5194/egusphere-2025-2035, https://doi.org/10.5194/egusphere-2025-2035, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
We investigated what users want from the next-generation of hydrological monitoring systems to better support science and innovation. Through literature review and interviews with experts, we found that beyond providing high-quality data, users particularly value additional support for collecting their own data, sharing it with others, and building collaborations with other data users. Designing systems with these needs in mind can greatly boost long-term engagement, data coverage and impact.
Doris Elise Wendt, Gemma Coxon, Saskia Salwey, and Francesca Pianosi
EGUsphere, https://doi.org/10.5194/egusphere-2025-1645, https://doi.org/10.5194/egusphere-2025-1645, 2025
Short summary
Short summary
Groundwater is a highly-used water source, which drought management is complicated. We introduce a socio-hydrological water resource model (SHOWER) to aid drought management in groundwater-rich managed environments. Results show which and when drought management interventions influence surface water and groundwater storage, with integrated interventions having most effect on reducing droughts. This encourages further exploration to reduce water shortages and improve future drought resilience.
Jamie Robert Cameron Brown, Ross Woods, Humberto Ribeiro da Rocha, Debora Regina Roberti, and Rafael Rosolem
EGUsphere, https://doi.org/10.5194/egusphere-2025-883, https://doi.org/10.5194/egusphere-2025-883, 2025
Short summary
Short summary
In recent years, global and regional weather datasets have emerged, but validation with real-world data is crucial, especially in diverse regions like Brazil. This study compares seven key weather variables from five datasets with measurements from 11 sites across Brazil’s main biomes. Results show varying performance across variables and timescales, with one reanalysis product outperforming others overall. Findings suggest it may be a strong choice for multi-variable studies in Brazil.
Adrià Fontrodona-Bach, Bettina Schaefli, Ross Woods, and Joshua R. Larsen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1214, https://doi.org/10.5194/egusphere-2025-1214, 2025
Short summary
Short summary
Investigating changing snow in response to global warming can be done with a simple model and only temperature and precipitation data, simplifying snow dynamics with assumptions and parameters. We provide a large-scale and long-term evaluation of this approach and its performance across diverse climates. Temperature thresholds are more robust over cold climates but melt parameters are more robust over warmer climates with deep snow. The model performs well across climates despite its simplicity.
Yongshin Lee, Andres Peñuela, Francesca Pianosi, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 29, 1429–1447, https://doi.org/10.5194/hess-29-1429-2025, https://doi.org/10.5194/hess-29-1429-2025, 2025
Short summary
Short summary
This study assesses the value of seasonal flow forecasts (SFFs) in informing decision-making for drought management in South Korea and introduces a novel method for assessing values benchmarked against historical operations. Our results showed the importance of considering flow forecast uncertainty in reservoir operations. There was no significant correlation between the forecast accuracy and value. The method for selecting a compromise release schedule was a key control of the value.
Wouter R. Berghuijs, Ross A. Woods, Bailey J. Anderson, Anna Luisa Hemshorn de Sánchez, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1319–1333, https://doi.org/10.5194/hess-29-1319-2025, https://doi.org/10.5194/hess-29-1319-2025, 2025
Short summary
Short summary
Water balances of catchments will often strongly depend on their state in the recent past, but such memory effects may persist at annual timescales. We use global data sets to show that annual memory is typically absent in precipitation but strong in terrestrial water stores and also present in evaporation and streamflow (including low flows and floods). Our experiments show that hysteretic models provide behaviour that is consistent with these observed memory behaviours.
Ting Zhang, Ran Zhang, Jianzhu Li, and Ping Feng
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-393, https://doi.org/10.5194/hess-2024-393, 2025
Revised manuscript under review for HESS
Short summary
Short summary
This study presents a model integrating attention mechanisms and physical constraints to improve flood prediction. It forecasts floods up to 6 hours in advance. The model enhances accuracy by focusing on critical input features and historical patterns. Results demonstrate its superior performance compared to other models, offering improved flood prediction with greater interpretability and alignment with physical laws to aid community preparedness.
Yan Liu, Ting Zhang, Yi Ding, Aiqing Kang, Xiaohui Lei, and Jianzhu Li
Hydrol. Earth Syst. Sci., 28, 5541–5555, https://doi.org/10.5194/hess-28-5541-2024, https://doi.org/10.5194/hess-28-5541-2024, 2024
Short summary
Short summary
In coastal cities, rainfall and tides contribute to compound flooding. This study quantifies the impacts of rainfall and tides on compound flooding and analyzes interactions between different flood types. Findings show that rainfall generally has a greater effect on flooding than tide levels. The interaction between fluvial and pluvial flooding amplifies the flood disaster, with tide levels having the most significant impact during the interaction phase.
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha E. Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
Hydrol. Earth Syst. Sci., 28, 5419–5441, https://doi.org/10.5194/hess-28-5419-2024, https://doi.org/10.5194/hess-28-5419-2024, 2024
Short summary
Short summary
This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within the mHM using the Desilets equation, with uniformly and non-uniformly weighted average soil moisture, and the physically based code COSMIC. The data improved not only soil moisture simulations but also the parameterisation of evapotranspiration in the model.
Jerom P. M. Aerts, Jannis M. Hoch, Gemma Coxon, Nick C. van de Giesen, and Rolf W. Hut
Hydrol. Earth Syst. Sci., 28, 5011–5030, https://doi.org/10.5194/hess-28-5011-2024, https://doi.org/10.5194/hess-28-5011-2024, 2024
Short summary
Short summary
For users of hydrological models, model suitability often hinges on how well simulated outputs match observed discharge. This study highlights the importance of including discharge observation uncertainty in hydrological model performance assessment. We highlight the need to account for this uncertainty in model comparisons and introduce a practical method suitable for any observational time series with available uncertainty estimates.
Saskia Salwey, Gemma Coxon, Francesca Pianosi, Rosanna Lane, Chris Hutton, Michael Bliss Singer, Hilary McMillan, and Jim Freer
Hydrol. Earth Syst. Sci., 28, 4203–4218, https://doi.org/10.5194/hess-28-4203-2024, https://doi.org/10.5194/hess-28-4203-2024, 2024
Short summary
Short summary
Reservoirs are essential for water resource management and can significantly impact downstream flow. However, representing reservoirs in hydrological models can be challenging, particularly across large scales. We design a new and simple method for simulating river flow downstream of water supply reservoirs using only open-access data. We demonstrate the approach in 264 reservoir catchments across Great Britain, where we can significantly improve the simulation of reservoir-impacted flow.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
Short summary
Short summary
Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Siyao Zhang, Jianzhu Li, Ting Zhang, and Ping Feng
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-185, https://doi.org/10.5194/hess-2024-185, 2024
Manuscript not accepted for further review
Short summary
Short summary
Flash drought (FD) in the North China Plain (NCP) from 1981 to 2022 was identified by three methods. It occurs more frequently in central and northern NCP than southern, with longer duration in southern and eastern NCP. FD shows seasonal variations. NCP is prone to severe FDs. There is a decreasing trend in FD, with three hotspots in northwestern, eastern and southwestern NCP. The FD frequency is affected by thresholds in the identification methods. This study may be valuable for FD mitigation.
Kathryn A. Leeming, John P. Bloomfield, Gemma Coxon, and Yanchen Zheng
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-202, https://doi.org/10.5194/hess-2023-202, 2023
Preprint withdrawn
Short summary
Short summary
In this work we characterise annual patterns in baseflow, the component of streamflow that comes from subsurface storage. Our research identified early-, mid-, and late-seasonality of baseflow across catchments in Great Britain over two time blocks: 1976–1995 and 1996–2015, and found that many catchments have earlier seasonal patterns of baseflow in the second time period. These changes are linked to changes in climate signals: snow-melt in highland catchments and effective rainfall changes.
Adrià Fontrodona-Bach, Bettina Schaefli, Ross Woods, Adriaan J. Teuling, and Joshua R. Larsen
Earth Syst. Sci. Data, 15, 2577–2599, https://doi.org/10.5194/essd-15-2577-2023, https://doi.org/10.5194/essd-15-2577-2023, 2023
Short summary
Short summary
We provide a dataset of snow water equivalent, the depth of liquid water that results from melting a given depth of snow. The dataset contains 11 071 sites over the Northern Hemisphere, spans the period 1950–2022, and is based on daily observations of snow depth on the ground and a model. The dataset fills a lack of accessible historical ground snow data, and it can be used for a variety of applications such as the impact of climate change on global and regional snow and water resources.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
Short summary
Short summary
As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Louisa D. Oldham, Jim Freer, Gemma Coxon, Nicholas Howden, John P. Bloomfield, and Christopher Jackson
Hydrol. Earth Syst. Sci., 27, 761–781, https://doi.org/10.5194/hess-27-761-2023, https://doi.org/10.5194/hess-27-761-2023, 2023
Short summary
Short summary
Water can move between river catchments via the subsurface, termed intercatchment groundwater flow (IGF). We show how a perceptual model of IGF can be developed with relatively simple geological interpretation and data requirements. We find that IGF dynamics vary in space, correlated to the dominant underlying geology. We recommend that IGF
loss functionsmay be used in conceptual rainfall–runoff models but should be supported by perceptualisation of IGF processes and connectivities.
Dagmawi Teklu Asfaw, Michael Bliss Singer, Rafael Rosolem, David MacLeod, Mark Cuthbert, Edisson Quichimbo Miguitama, Manuel F. Rios Gaona, and Katerina Michaelides
Geosci. Model Dev., 16, 557–571, https://doi.org/10.5194/gmd-16-557-2023, https://doi.org/10.5194/gmd-16-557-2023, 2023
Short summary
Short summary
stoPET is a new stochastic potential evapotranspiration (PET) generator for the globe at hourly resolution. Many stochastic weather generators are used to generate stochastic rainfall time series; however, no such model exists for stochastically generating plausible PET time series. As such, stoPET represents a significant methodological advance. stoPET generate many realizations of PET to conduct climate studies related to the water balance, agriculture, water resources, and ecology.
Sarah Shannon, Anthony Payne, Jim Freer, Gemma Coxon, Martina Kauzlaric, David Kriegel, and Stephan Harrison
Hydrol. Earth Syst. Sci., 27, 453–480, https://doi.org/10.5194/hess-27-453-2023, https://doi.org/10.5194/hess-27-453-2023, 2023
Short summary
Short summary
Climate change poses a potential threat to water supply in glaciated river catchments. In this study, we added a snowmelt and glacier melt model to the Dynamic fluxEs and ConnectIvity for Predictions of HydRology model (DECIPHeR). The model is applied to the Naryn River catchment in central Asia and is found to reproduce past change discharge and the spatial extent of seasonal snow cover well.
Rosanna A. Lane, Gemma Coxon, Jim Freer, Jan Seibert, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 26, 5535–5554, https://doi.org/10.5194/hess-26-5535-2022, https://doi.org/10.5194/hess-26-5535-2022, 2022
Short summary
Short summary
This study modelled the impact of climate change on river high flows across Great Britain (GB). Generally, results indicated an increase in the magnitude and frequency of high flows along the west coast of GB by 2050–2075. In contrast, average flows decreased across GB. All flow projections contained large uncertainties; the climate projections were the largest source of uncertainty overall but hydrological modelling uncertainties were considerable in some regions.
Xu Zhang, Jinbao Li, Qianjin Dong, and Ross A. Woods
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-309, https://doi.org/10.5194/hess-2022-309, 2022
Manuscript not accepted for further review
Short summary
Short summary
Accurately estimating long-term evaporation is important for describing water balance. Budyko framework already incorporates precipitation and potential evaporation, while water storage capacity and climate seasonality are usually ignored. Here, we analytically generalize Budyko framework through the Ponce-Shetty model, and physically account these two factors. Our generalized equations perform better than varying Budyko-type equations, and improve the robustness and physical interpretation.
Heye Reemt Bogena, Martin Schrön, Jannis Jakobi, Patrizia Ney, Steffen Zacharias, Mie Andreasen, Roland Baatz, David Boorman, Mustafa Berk Duygu, Miguel Angel Eguibar-Galán, Benjamin Fersch, Till Franke, Josie Geris, María González Sanchis, Yann Kerr, Tobias Korf, Zalalem Mengistu, Arnaud Mialon, Paolo Nasta, Jerzy Nitychoruk, Vassilios Pisinaras, Daniel Rasche, Rafael Rosolem, Hami Said, Paul Schattan, Marek Zreda, Stefan Achleitner, Eduardo Albentosa-Hernández, Zuhal Akyürek, Theresa Blume, Antonio del Campo, Davide Canone, Katya Dimitrova-Petrova, John G. Evans, Stefano Ferraris, Félix Frances, Davide Gisolo, Andreas Güntner, Frank Herrmann, Joost Iwema, Karsten H. Jensen, Harald Kunstmann, Antonio Lidón, Majken Caroline Looms, Sascha Oswald, Andreas Panagopoulos, Amol Patil, Daniel Power, Corinna Rebmann, Nunzio Romano, Lena Scheiffele, Sonia Seneviratne, Georg Weltin, and Harry Vereecken
Earth Syst. Sci. Data, 14, 1125–1151, https://doi.org/10.5194/essd-14-1125-2022, https://doi.org/10.5194/essd-14-1125-2022, 2022
Short summary
Short summary
Monitoring of increasingly frequent droughts is a prerequisite for climate adaptation strategies. This data paper presents long-term soil moisture measurements recorded by 66 cosmic-ray neutron sensors (CRNS) operated by 24 institutions and distributed across major climate zones in Europe. Data processing followed harmonized protocols and state-of-the-art methods to generate consistent and comparable soil moisture products and to facilitate continental-scale analysis of hydrological extremes.
Daniel Sanchez-Rivas and Miguel A. Rico-Ramirez
Atmos. Meas. Tech., 15, 503–520, https://doi.org/10.5194/amt-15-503-2022, https://doi.org/10.5194/amt-15-503-2022, 2022
Short summary
Short summary
In this work, we review the use of quasi-vertical profiles for monitoring the calibration of the radar differential reflectivity ZDR. We validate the proposed method by comparing its results against the traditional approach based on measurements taken at 90°; we observed good agreement as the errors are within 0.2 dB. Additionally, we compare the results of the proposed method with ZDR derived from disdrometers; the errors are reasonable considering factors discussed in the paper.
Shaini Naha, Miguel Angel Rico-Ramirez, and Rafael Rosolem
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
Short summary
Short summary
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 river flow processes. This study describes how the hydrology of a flood-prone river basin in India would respond to the current and future changes in land cover. Our findings indicate that the recurrent flood events occurring in the basin might be influenced by these changes in land cover at the catchment scale.
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
Geosci. Model Dev., 14, 7545–7571, https://doi.org/10.5194/gmd-14-7545-2021, https://doi.org/10.5194/gmd-14-7545-2021, 2021
Short summary
Short summary
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 (
model evaluation).
Daniel Power, Miguel Angel Rico-Ramirez, Sharon Desilets, Darin Desilets, and Rafael Rosolem
Geosci. Model Dev., 14, 7287–7307, https://doi.org/10.5194/gmd-14-7287-2021, https://doi.org/10.5194/gmd-14-7287-2021, 2021
Short summary
Short summary
Cosmic-ray neutron sensors estimate root-zone soil moisture at sub-kilometre scales. There are national-scale networks of these sensors across the globe; however, methods for converting neutron signals to soil moisture values are inconsistent. This paper describes our open-source Python tool that processes raw sensor data into soil moisture estimates. The aim is to allow a user to ensure they have a harmonized data set, along with informative metadata, to facilitate both research and teaching.
E. Andrés Quichimbo, Michael Bliss Singer, Katerina Michaelides, Daniel E. J. Hobley, Rafael Rosolem, and Mark O. Cuthbert
Geosci. Model Dev., 14, 6893–6917, https://doi.org/10.5194/gmd-14-6893-2021, https://doi.org/10.5194/gmd-14-6893-2021, 2021
Short summary
Short summary
Understanding and quantifying water partitioning in dryland regions are of key importance to anticipate the future impacts of climate change in water resources and dryland ecosystems. Here, we have developed a simple hydrological model (DRYP) that incorporates the key processes of water partitioning in drylands. DRYP is a modular, versatile, and parsimonious model that can be used to anticipate and plan for climatic and anthropogenic changes to water fluxes and storage in dryland regions.
Thomas Lees, Marcus Buechel, Bailey Anderson, Louise Slater, Steven Reece, Gemma Coxon, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 25, 5517–5534, https://doi.org/10.5194/hess-25-5517-2021, https://doi.org/10.5194/hess-25-5517-2021, 2021
Short summary
Short summary
We used deep learning (DL) models to simulate the amount of water moving through a river channel (discharge) based on the rainfall, temperature and potential evaporation in the previous days. We tested the DL models on catchments across Great Britain finding that the model can accurately simulate hydrological systems across a variety of catchment conditions. Ultimately, the model struggled most in areas where there is chalky bedrock and where human influence on the catchment is large.
John P. Bloomfield, Mengyi Gong, Benjamin P. Marchant, Gemma Coxon, and Nans Addor
Hydrol. Earth Syst. Sci., 25, 5355–5379, https://doi.org/10.5194/hess-25-5355-2021, https://doi.org/10.5194/hess-25-5355-2021, 2021
Short summary
Short summary
Groundwater provides flow, known as baseflow, to surface streams and rivers. It is important as it sustains the flow of many rivers at times of water stress. However, it may be affected by water management practices. Statistical models have been used to show that abstraction of groundwater may influence baseflow. Consequently, it is recommended that information on groundwater abstraction is included in future assessments and predictions of baseflow.
Thorsten Wagener, Dragan Savic, David Butler, Reza Ahmadian, Tom Arnot, Jonathan Dawes, Slobodan Djordjevic, Roger Falconer, Raziyeh Farmani, Debbie Ford, Jan Hofman, Zoran Kapelan, Shunqi Pan, and Ross Woods
Hydrol. Earth Syst. Sci., 25, 2721–2738, https://doi.org/10.5194/hess-25-2721-2021, https://doi.org/10.5194/hess-25-2721-2021, 2021
Short summary
Short summary
How can we effectively train PhD candidates both (i) across different knowledge domains in water science and engineering and (ii) in computer science? To address this issue, the Water Informatics in Science and Engineering Centre for Doctoral Training (WISE CDT) offers a postgraduate programme that fosters enhanced levels of innovation and collaboration by training a cohort of engineers and scientists at the boundary of water informatics, science and engineering.
Daniel Sanchez-Rivas and Miguel A. Rico-Ramirez
Atmos. Meas. Tech., 14, 2873–2890, https://doi.org/10.5194/amt-14-2873-2021, https://doi.org/10.5194/amt-14-2873-2021, 2021
Short summary
Short summary
In our paper, we propose a robust and operational algorithm to determine the height of the melting level that can be applied to either quasi-vertical profiles (QVPs) or vertical profiles (VPs) of polarimetric radar variables. The algorithm is applied to 1 year of rainfall events that occurred over southeast England and validated using radiosonde data. The algorithm proves to be accurate as the errors (mean absolute error and root mean square error) are close to 200 m.
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
Short summary
Short summary
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.
Gemma Coxon, Nans Addor, John P. Bloomfield, Jim Freer, Matt Fry, Jamie Hannaford, Nicholas J. K. Howden, Rosanna Lane, Melinda Lewis, Emma L. Robinson, Thorsten Wagener, and Ross Woods
Earth Syst. Sci. Data, 12, 2459–2483, https://doi.org/10.5194/essd-12-2459-2020, https://doi.org/10.5194/essd-12-2459-2020, 2020
Short summary
Short summary
We present the first large-sample catchment hydrology dataset for Great Britain. The dataset collates river flows, catchment attributes, and catchment boundaries for 671 catchments across Great Britain. We characterise the topography, climate, streamflow, land cover, soils, hydrogeology, human influence, and discharge uncertainty of each catchment. The dataset is publicly available for the community to use in a wide range of environmental and modelling analyses.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Sebastian J. Gnann, Nicholas J. K. Howden, and Ross A. Woods
Hydrol. Earth Syst. Sci., 24, 561–580, https://doi.org/10.5194/hess-24-561-2020, https://doi.org/10.5194/hess-24-561-2020, 2020
Short summary
Short summary
In many places, seasonal variability in precipitation and evapotranspiration (climate) leads to seasonal variability in river flow (streamflow). In this work, we explore how climate seasonality is transformed into streamflow seasonality and what controls this transformation (e.g. climate aridity and geology). The results might be used in grouping catchments, predicting the seasonal streamflow regime in ungauged catchments, and building hydrological simulation models.
Wouter J. M. Knoben, Jim E. Freer, and Ross A. Woods
Hydrol. Earth Syst. Sci., 23, 4323–4331, https://doi.org/10.5194/hess-23-4323-2019, https://doi.org/10.5194/hess-23-4323-2019, 2019
Short summary
Short summary
The accuracy of model simulations can be quantified with so-called efficiency metrics. The Nash–Sutcliffe efficiency (NSE) has been often used in hydrology, but recently the Kling–Gupta efficiency (KGE) is gaining in popularity. We show that lessons learned about which NSE scores are
acceptabledo not necessarily translate well into understanding of the KGE metric.
Rosanna A. Lane, Gemma Coxon, Jim E. Freer, Thorsten Wagener, Penny J. Johnes, John P. Bloomfield, Sheila Greene, Christopher J. A. Macleod, and Sim M. Reaney
Hydrol. Earth Syst. Sci., 23, 4011–4032, https://doi.org/10.5194/hess-23-4011-2019, https://doi.org/10.5194/hess-23-4011-2019, 2019
Short summary
Short summary
We evaluated four hydrological model structures and their parameters on over 1100 catchments across Great Britain, considering modelling uncertainties. Models performed well for most catchments but failed in parts of Scotland and south-eastern England. Failures were often linked to inconsistencies in the water balance. This research shows what conceptual lumped models can achieve, gives insights into where and why these models may fail, and provides a benchmark of national modelling capability.
Wouter J. M. Knoben, Jim E. Freer, Keirnan J. A. Fowler, Murray C. Peel, and Ross A. Woods
Geosci. Model Dev., 12, 2463–2480, https://doi.org/10.5194/gmd-12-2463-2019, https://doi.org/10.5194/gmd-12-2463-2019, 2019
Short summary
Short summary
Computer models are used to predict river flows. A good model should represent the river basin to which it is applied so that flow predictions are as realistic as possible. However, many different computer models exist, and selecting the most appropriate model for a given river basin is not always easy. This study combines computer code for 46 different hydrological models into a single coding framework so that models can be compared in an objective way and we can learn about model differences.
Gemma Coxon, Jim Freer, Rosanna Lane, Toby Dunne, Wouter J. M. Knoben, Nicholas J. K. Howden, Niall Quinn, Thorsten Wagener, and Ross Woods
Geosci. Model Dev., 12, 2285–2306, https://doi.org/10.5194/gmd-12-2285-2019, https://doi.org/10.5194/gmd-12-2285-2019, 2019
Short summary
Short summary
DECIPHeR (Dynamic fluxEs and ConnectIvity for Predictions of Hydrology) is a new modelling framework that can be applied from small catchment to continental scales for complex river basins. This paper describes the modelling framework and its key components and demonstrates the model’s ability to be applied across a large model domain. This work highlights the potential for catchment- to continental-scale predictions of streamflow to support robust environmental management and policy decisions.
Anne F. Van Loon, Sally Rangecroft, Gemma Coxon, José Agustín Breña Naranjo, Floris Van Ogtrop, and Henny A. J. Van Lanen
Hydrol. Earth Syst. Sci., 23, 1725–1739, https://doi.org/10.5194/hess-23-1725-2019, https://doi.org/10.5194/hess-23-1725-2019, 2019
Short summary
Short summary
We explore the use of the classic
paired-catchmentapproach to quantify human influence on hydrological droughts. In this approach two similar catchments are compared and differences are attributed to the human activity present in one. In two case studies in UK and Australia, we found that groundwater abstraction aggravated streamflow drought by > 200 % and water transfer alleviated droughts with 25–80 %. Understanding the human influence on droughts can support water management decisions.
Nevil Quinn, Günter Blöschl, András Bárdossy, Attilio Castellarin, Martyn Clark, Christophe Cudennec, Demetris Koutsoyiannis, Upmanu Lall, Lubomir Lichner, Juraj Parajka, Christa D. Peters-Lidard, Graham Sander, Hubert Savenije, Keith Smettem, Harry Vereecken, Alberto Viglione, Patrick Willems, Andy Wood, Ross Woods, Chong-Yu Xu, and Erwin Zehe
Proc. IAHS, 380, 3–8, https://doi.org/10.5194/piahs-380-3-2018, https://doi.org/10.5194/piahs-380-3-2018, 2018
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
Short summary
Short summary
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.
Nevil Quinn, Günter Blöschl, András Bárdossy, Attilio Castellarin, Martyn Clark, Christophe Cudennec, Demetris Koutsoyiannis, Upmanu Lall, Lubomir Lichner, Juraj Parajka, Christa D. Peters-Lidard, Graham Sander, Hubert Savenije, Keith Smettem, Harry Vereecken, Alberto Viglione, Patrick Willems, Andy Wood, Ross Woods, Chong-Yu Xu, and Erwin Zehe
Hydrol. Earth Syst. Sci., 22, 5735–5739, https://doi.org/10.5194/hess-22-5735-2018, https://doi.org/10.5194/hess-22-5735-2018, 2018
Andreas Paul Zischg, Guido Felder, Rolf Weingartner, Niall Quinn, Gemma Coxon, Jeffrey Neal, Jim Freer, and Paul Bates
Hydrol. Earth Syst. Sci., 22, 2759–2773, https://doi.org/10.5194/hess-22-2759-2018, https://doi.org/10.5194/hess-22-2759-2018, 2018
Short summary
Short summary
We developed a model experiment and distributed different rainfall patterns over a mountain river basin. For each rainfall scenario, we computed the flood losses with a model chain. The experiment shows that flood losses vary considerably within the river basin and depend on the timing of the flood peaks from the basin's sub-catchments. Basin-specific characteristics such as the location of the main settlements within the floodplains play an additional important role in determining flood losses.
Simon Brenner, Gemma Coxon, Nicholas J. K. Howden, Jim Freer, and Andreas Hartmann
Nat. Hazards Earth Syst. Sci., 18, 445–461, https://doi.org/10.5194/nhess-18-445-2018, https://doi.org/10.5194/nhess-18-445-2018, 2018
Short summary
Short summary
In this study we simulate groundwater levels with a semi-distributed karst model. Using a percentile approach we can assess the number of days exceeding or falling below selected groundwater level percentiles. We show that our approach is able to predict groundwater levels across all considered timescales up to the 75th percentile. We then use our approach to assess future changes in groundwater dynamics and show that projected climate changes may lead to generally lower groundwater levels.
Benoit P. Guillod, Richard G. Jones, Simon J. Dadson, Gemma Coxon, Gianbattista Bussi, James Freer, Alison L. Kay, Neil R. Massey, Sarah N. Sparrow, David C. H. Wallom, Myles R. Allen, and Jim W. Hall
Hydrol. Earth Syst. Sci., 22, 611–634, https://doi.org/10.5194/hess-22-611-2018, https://doi.org/10.5194/hess-22-611-2018, 2018
Short summary
Short summary
Assessing the potential impacts of extreme events such as drought and flood requires large datasets of such events, especially when looking at the most severe and rare events. Using a state-of-the-art climate modelling infrastructure that is simulating large numbers of weather time series on volunteers' computers, we generate such a large dataset for the United Kingdom. The dataset covers the recent past (1900–2006) as well as two future time periods (2030s and 2080s).
David McJannet, Aaron Hawdon, Brett Baker, Luigi Renzullo, and Ross Searle
Hydrol. Earth Syst. Sci., 21, 6049–6067, https://doi.org/10.5194/hess-21-6049-2017, https://doi.org/10.5194/hess-21-6049-2017, 2017
Short summary
Short summary
Satellite and broad-scale model estimates of soil moisture have improved in resolution. However, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. We use a mobile soil moisture monitoring platform, known as the
rover, to derive soil moisture at 9 km and 1 km resolution. We describe methods to calculate soil moisture and present results from multiple surveys. The products produced are well suited to validation studies.
Katrien Van Eerdenbrugh, Stijn Van Hoey, Gemma Coxon, Jim Freer, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 21, 5315–5337, https://doi.org/10.5194/hess-21-5315-2017, https://doi.org/10.5194/hess-21-5315-2017, 2017
Short summary
Short summary
Consistency in stage–discharge data is investigated using a methodology called Bidirectional Reach (BReach). Various measurement stations in the UK, New Zealand and Belgium are selected based on their historical ratings information and their characteristics related to data consistency. When applying a BReach analysis on them, the methodology provides results that appear consistent with the available knowledge and thus facilitates a reliable assessment of (in)consistency in stage–discharge data.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Martyn P. Clark, Marc F. P. Bierkens, Luis Samaniego, Ross A. Woods, Remko Uijlenhoet, Katrina E. Bennett, Valentijn R. N. Pauwels, Xitian Cai, Andrew W. Wood, and Christa D. Peters-Lidard
Hydrol. Earth Syst. Sci., 21, 3427–3440, https://doi.org/10.5194/hess-21-3427-2017, https://doi.org/10.5194/hess-21-3427-2017, 2017
Short summary
Short summary
The diversity in hydrologic models has led to controversy surrounding the “correct” approach to hydrologic modeling. In this paper we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, summarize modeling advances that address these challenges, and define outstanding research needs.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Naoki Mizukami, Martyn P. Clark, Kevin Sampson, Bart Nijssen, Yixin Mao, Hilary McMillan, Roland J. Viger, Steve L. Markstrom, Lauren E. Hay, Ross Woods, Jeffrey R. Arnold, and Levi D. Brekke
Geosci. Model Dev., 9, 2223–2238, https://doi.org/10.5194/gmd-9-2223-2016, https://doi.org/10.5194/gmd-9-2223-2016, 2016
Short summary
Short summary
mizuRoute version 1 is a stand-alone runoff routing tool that post-processes runoff outputs from any distributed hydrologic models to produce streamflow estimates in large-scale river network. mizuRoute is flexible to river network representation and includes two different river routing schemes. This paper demonstrates mizuRoute's capability of multi-decadal streamflow estimations in the river networks over the entire contiguous Unites States, which contains over 54 000 river segments.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
R. Rosolem, T. Hoar, A. Arellano, J. L. Anderson, W. J. Shuttleworth, X. Zeng, and T. E. Franz
Hydrol. Earth Syst. Sci., 18, 4363–4379, https://doi.org/10.5194/hess-18-4363-2014, https://doi.org/10.5194/hess-18-4363-2014, 2014
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
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: Global hydrology | Techniques and Approaches: Instruments and observation techniques
Evaluation of globally gridded precipitation data and satellite-based terrestrial water storage products using hydrological drought recovery time
HESS Opinions: Towards a common vision for the future of hydrological observatories
Wetting and drying trends in the land–atmosphere reservoir of large basins around the world
Evaporation enhancement drives the European water-budget deficit during multi-year droughts
Combining passive and active distributed temperature sensing measurements to locate and quantify groundwater discharge variability into a headwater stream
Technical note: Evaluation and bias correction of an observation-based global runoff dataset using streamflow observations from small tropical catchments in the Philippines
Hydrology and water resources management in ancient India
Terrestrial water loss at night: global relevance from observations and climate models
Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling
SMOS brightness temperature assimilation into the Community Land Model
SMOS near-real-time soil moisture product: processor overview and first validation results
Estimating annual water storage variations in medium-scale (2000–10 000 km2) basins using microwave-based soil moisture retrievals
Recent trends and variability in river discharge across northern Canada
Effects of changes in moisture source and the upstream rainout on stable isotopes in precipitation – a case study in Nanjing, eastern China
The "Prediflood" database of historical floods in Catalonia (NE Iberian Peninsula) AD 1035–2013, and its potential applications in flood analysis
Regional GRACE-based estimates of water mass variations over Australia: validation and interpretation
Geodynamical processes in the channel connecting the two lobes of the Large Aral Sea
Çağatay Çakan, M. Tuğrul Yımaz, Henryk Dobslaw, E. Sinem Ince, Fatih Evrendilek, Christoph Förste, and Ali Levent Yagci
Hydrol. Earth Syst. Sci., 29, 3359–3377, https://doi.org/10.5194/hess-29-3359-2025, https://doi.org/10.5194/hess-29-3359-2025, 2025
Short summary
Short summary
The study assesses the Global Precipitation Climatology Centre (GPCC) and Global Precipitation Climatology Project (GPCP) precipitation products by estimating hydrological drought recovery time (DRT) using satellite gravimetry data, Jet Propulsion Laboratory mass concentration solution (JPL mascon), and Global Gravity-based Groundwater Project (G3P) terrestrial water storage (TWS) products. The findings reveal that DRTs from GPCC and GPCP are comparable, and JPL mascon shows longer DRT, while G3P demonstrates greater consistency. These results contribute to a deeper understanding of precipitation and water storage dynamics and are essential for meteorological and hydrological research.
Paolo Nasta, Günter Blöschl, Heye R. Bogena, Steffen Zacharias, Roland Baatz, Gabriëlle De Lannoy, Karsten H. Jensen, Salvatore Manfreda, Laurent Pfister, Ana M. Tarquis, Ilja van Meerveld, Marc Voltz, Yijian Zeng, William Kustas, Xin Li, Harry Vereecken, and Nunzio Romano
Hydrol. Earth Syst. Sci., 29, 465–483, https://doi.org/10.5194/hess-29-465-2025, https://doi.org/10.5194/hess-29-465-2025, 2025
Short summary
Short summary
The Unsolved Problems in Hydrology (UPH) initiative has emphasized the need to establish networks of multi-decadal hydrological observatories to tackle catchment-scale challenges on a global scale. This opinion paper provocatively discusses two endmembers of possible future hydrological observatory (HO) networks for a given hypothesized community budget: a comprehensive set of moderately instrumented observatories or, alternatively, a small number of highly instrumented supersites.
Juan F. Salazar, Ruben D. Molina, Jorge I. Zuluaga, and Jesus D. Gomez-Velez
Hydrol. Earth Syst. Sci., 28, 2919–2947, https://doi.org/10.5194/hess-28-2919-2024, https://doi.org/10.5194/hess-28-2919-2024, 2024
Short summary
Short summary
Global change is altering river basins and their discharge worldwide. We introduce the land–atmosphere reservoir (LAR) concept to investigate these changes in six of the world's largest basins. We found that low-latitude basins (Amazon, Paraná, and Congo) are getting wetter, whereas high-latitude basins (Mississippi, Ob, and Yenisei) are drying. If this continues, these long-term trends will disrupt the discharge regime and compromise the sustainability of these basins with widespread impacts.
Christian Massari, Francesco Avanzi, Giulia Bruno, Simone Gabellani, Daniele Penna, and Stefania Camici
Hydrol. Earth Syst. Sci., 26, 1527–1543, https://doi.org/10.5194/hess-26-1527-2022, https://doi.org/10.5194/hess-26-1527-2022, 2022
Short summary
Short summary
Droughts are a creeping disaster, meaning that their onset, duration and recovery are challenging to monitor and forecast. Here, we provide further evidence of an additional challenge of droughts, i.e. the fact that the deficit in water supply during droughts is generally much more than expected based on the observed decline in precipitation. At a European scale we explain this with enhanced evapotranspiration, sustained by higher atmospheric demand for moisture during such dry periods.
Nataline Simon, Olivier Bour, Mikaël Faucheux, Nicolas Lavenant, Hugo Le Lay, Ophélie Fovet, Zahra Thomas, and Laurent Longuevergne
Hydrol. Earth Syst. Sci., 26, 1459–1479, https://doi.org/10.5194/hess-26-1459-2022, https://doi.org/10.5194/hess-26-1459-2022, 2022
Short summary
Short summary
Groundwater discharge into streams plays a major role in the preservation of stream ecosystems. There were two complementary methods, both based on the use of the distributed temperature sensing technology, applied in a headwater catchment. Measurements allowed us to characterize the spatial and temporal patterns of groundwater discharge and quantify groundwater inflows into the stream, opening very promising perspectives for a novel characterization of the groundwater–stream interface.
Daniel E. Ibarra, Carlos Primo C. David, and Pamela Louise M. Tolentino
Hydrol. Earth Syst. Sci., 25, 2805–2820, https://doi.org/10.5194/hess-25-2805-2021, https://doi.org/10.5194/hess-25-2805-2021, 2021
Short summary
Short summary
We evaluate a recently published global product of monthly runoff using streamflow data from small tropical catchments in the Philippines. Using monthly runoff observations from catchments, we tested for correlation and prediction. We demonstrate the potential utility of this product in assessing trends in regional-scale runoff, as well as look at the correlation of phenomenon such as the El Niño–Southern Oscillation on streamflow in this wet but drought-prone archipelago.
Pushpendra Kumar Singh, Pankaj Dey, Sharad Kumar Jain, and Pradeep P. Mujumdar
Hydrol. Earth Syst. Sci., 24, 4691–4707, https://doi.org/10.5194/hess-24-4691-2020, https://doi.org/10.5194/hess-24-4691-2020, 2020
Short summary
Short summary
Like in all ancient civilisations, the need to manage water propelled the growth of hydrological science in ancient India also. In this paper, we provide some fascinating glimpses into the hydrological, hydraulic, and related engineering knowledge that existed in ancient India, as discussed in contemporary literature and recent explorations and findings. Many interesting dimensions of early scientific endeavours emerge as we investigate deeper into ancient texts, including Indian mythology.
Ryan S. Padrón, Lukas Gudmundsson, Dominik Michel, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 24, 793–807, https://doi.org/10.5194/hess-24-793-2020, https://doi.org/10.5194/hess-24-793-2020, 2020
Short summary
Short summary
We focus on the net exchange of water between land and air via evapotranspiration and dew during the night. We provide, for the first time, an overview of the magnitude and variability of this flux across the globe from observations and climate models. Nocturnal water loss from land is 7 % of total evapotranspiration on average and can be greater than 15 % locally. Our results highlight the relevance of this often overlooked flux, with implications for water resources and climate studies.
Hylke E. Beck, Noemi Vergopolan, Ming Pan, Vincenzo Levizzani, Albert I. J. M. van Dijk, Graham P. Weedon, Luca Brocca, Florian Pappenberger, George J. Huffman, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, https://doi.org/10.5194/hess-21-6201-2017, 2017
Short summary
Short summary
This study represents the most comprehensive global-scale precipitation dataset evaluation to date. We evaluated 13 uncorrected precipitation datasets using precipitation observations from 76 086 gauges, and 9 gauge-corrected ones using hydrological modeling for 9053 catchments. Our results highlight large differences in estimation accuracy, and hence, the importance of precipitation dataset selection in both research and operational applications.
Dominik Rains, Xujun Han, Hans Lievens, Carsten Montzka, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 21, 5929–5951, https://doi.org/10.5194/hess-21-5929-2017, https://doi.org/10.5194/hess-21-5929-2017, 2017
Short summary
Short summary
We have assimilated 6 years of satellite-observed passive microwave data into a state-of-the-art land surface model to improve surface soil moisture as well as root-zone soil moisture simulations. Long-term assimilation effects/biases are identified, and they are especially dependent on model perturbations, applied to simulate model uncertainty. The implications are put into context of using such assimilation-improved data for classifying extremes within hydrological monitoring systems.
Nemesio J. Rodríguez-Fernández, Joaquin Muñoz Sabater, Philippe Richaume, Patricia de Rosnay, Yann H. Kerr, Clement Albergel, Matthias Drusch, and Susanne Mecklenburg
Hydrol. Earth Syst. Sci., 21, 5201–5216, https://doi.org/10.5194/hess-21-5201-2017, https://doi.org/10.5194/hess-21-5201-2017, 2017
Short summary
Short summary
The new SMOS satellite near-real-time (NRT) soil moisture (SM) product based on a neural network is presented. The NRT SM product has been evaluated with respect to the SMOS Level 2 product and against a large number of in situ measurements showing performances similar to those of the Level 2 product but it is available in less than 3.5 h after sensing. The new product is distributed by the European Space Agency and the European Organisation for the Exploitation of Meteorological Satellites.
Wade T. Crow, Eunjin Han, Dongryeol Ryu, Christopher R. Hain, and Martha C. Anderson
Hydrol. Earth Syst. Sci., 21, 1849–1862, https://doi.org/10.5194/hess-21-1849-2017, https://doi.org/10.5194/hess-21-1849-2017, 2017
Short summary
Short summary
Terrestrial water storage is defined as the total volume of water stored within the land surface and sub-surface and is a key variable for tracking long-term variability in the global water cycle. Currently, annual variations in terrestrial water storage can only be measured at extremely coarse spatial resolutions (> 200 000 km2) using gravity-based remote sensing. Here we provide evidence that microwave-based remote sensing of soil moisture can be applied to enhance this resolution.
Stephen J. Déry, Tricia A. Stadnyk, Matthew K. MacDonald, and Bunu Gauli-Sharma
Hydrol. Earth Syst. Sci., 20, 4801–4818, https://doi.org/10.5194/hess-20-4801-2016, https://doi.org/10.5194/hess-20-4801-2016, 2016
Short summary
Short summary
This manuscript focuses on observed changes to the hydrology of 42 rivers in northern Canada draining one-half of its land mass over the period 1964–2013. Statistical and trend analyses are presented for the 42 individual rivers, 6 regional drainage basins, and collectively for all of northern Canada. A main finding is the reversal of a statistically significant decline in the first half of the study period to a statistically significant 18.1 % incline in river discharge across northern Canada.
Y. Tang, H. Pang, W. Zhang, Y. Li, S. Wu, and S. Hou
Hydrol. Earth Syst. Sci., 19, 4293–4306, https://doi.org/10.5194/hess-19-4293-2015, https://doi.org/10.5194/hess-19-4293-2015, 2015
Short summary
Short summary
We examined the variability of daily stable isotopic composition in precipitation in Nanjing, eastern China. We found that both the upstream rainout effect on stable isotopes related to changes in the Asian summer monsoon and the temperature effect of precipitation stable isotopes associated with the Asian winter monsoon should be taken into account when interpreting the stable isotopic composition of speleothems in the Asian monsoon region.
M. Barriendos, J. L. Ruiz-Bellet, J. Tuset, J. Mazón, J. C. Balasch, D. Pino, and J. L. Ayala
Hydrol. Earth Syst. Sci., 18, 4807–4823, https://doi.org/10.5194/hess-18-4807-2014, https://doi.org/10.5194/hess-18-4807-2014, 2014
Short summary
Short summary
This paper shows an interdisciplinary effort for a common methodology on flood risk analysis: hydraullics, hydrology, climatology and meteorology. Most basic problems of work with historical information are faced. Firsts results of data collection on historical floods for Catalonia (Ne Spain) are showed for period AD 1035-2014.
L. Seoane, G. Ramillien, F. Frappart, and M. Leblanc
Hydrol. Earth Syst. Sci., 17, 4925–4939, https://doi.org/10.5194/hess-17-4925-2013, https://doi.org/10.5194/hess-17-4925-2013, 2013
E. Roget, P. Zavialov, V. Khan, and M. A. Muñiz
Hydrol. Earth Syst. Sci., 13, 2265–2271, https://doi.org/10.5194/hess-13-2265-2009, https://doi.org/10.5194/hess-13-2265-2009, 2009
Cited articles
Albergel, C., De Rosnay, P., Gruhier, C., Muñoz-Sabater, J., Hasenauer, S., Isaksen, L., Kerr, Y., and Wagner, W.: Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations, Remote Sens. Environ., 118, 215–226, https://doi.org/10.1016/j.rse.2011.11.017, 2012.
Al-Yaari, A., Wigneron, J.-P., Ducharne, A., Kerr, Y., De Rosnay, P., De Jeu, R., Govind, A., Al Bitar, A., Albergel, C., and Munoz-Sabater, J.: Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to Land Data Assimilation System estimates, Remote Sens. Environ., 149, 181–195, https://doi.org/10.1016/j.rse.2014.04.006, 2014.
Andreasen, M., Jensen, K. H., Desilets, D., Franz, T. E., Zreda, M., Bogena, H. R., and Looms, M. C.: Status and perspectives on the cosmic-ray neutron method for soil moisture estimation and other environmental science applications, Vadose Zone J., 16, 1–11, https://doi.org/10.2136/vzj2017.04.0086, 2017.
Baatz, R., Bogena, H., Hendricks Franssen, H. J., Huisman, J., Montzka, C., and Vereecken, H.: An empirical vegetation correction for soil water content quantification using cosmic ray probes, Water Resour. Res., 51, 2030–2046, https://doi.org/10.1002/2014WR016443, 2015.
Baatz, R., Hendricks Franssen, H., Euskirchen, E., Sihi, D., Dietze, M., Ciavatta, S., Fennel, K., Beck, H., De Lannoy, G., and Pauwels, V.: Reanalysis in Earth system science: Toward terrestrial ecosystem reanalysis, Rev. Geophys., 59, e2020RG000715, https://doi.org/10.1029/2020RG000715, 2021.
Beaudoing, H. and Rodell, M.: NASA/GSFC/HSL: GLDAS Noah Land Surface Model L4 3 hourly 0.25 x 0.25 degree V2.1, Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/E7TYRXPJKWOQ, 2020.
Beck, H. E., Vergopolan, N., Pan, M., Levizzani, V., van Dijk, A. I. J. M., Weedon, G. P., Brocca, L., Pappenberger, F., Huffman, G. J., and Wood, E. F.: Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling, Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, 2017.
Beck, H. E., Pan, M., Miralles, D. G., Reichle, R. H., Dorigo, W. A., Hahn, S., Sheffield, J., Karthikeyan, L., Balsamo, G., Parinussa, R. M., van Dijk, A. I. J. M., Du, J., Kimball, J. S., Vergopolan, N., and Wood, E. F.: Evaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensors, Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, 2021.
Bierkens, M. F., Bell, V. A., Burek, P., Chaney, N., Condon, L. E., David, C. H., de Roo, A., Döll, P., Drost, N., and Famiglietti, J. S.: Hyper-resolution global hydrological modelling: what is next? “Everywhere and locally relevant”, Hydrol. Process., 29, 310–320, https://doi.org/10.1002/hyp.10391, 2015.
Bogena, H., Huisman, J., Baatz, R., Hendricks Franssen, H. J., and Vereecken, H.: Accuracy of the cosmic-ray soil water content probe in humid forest ecosystems: The worst case scenario, Water Resour. Res., 49, 5778–5791, https://doi.org/10.1002/wrcr.20463, 2013.
Bogena, H. R.: TERENO: German network of terrestrial environmental observatories, Journal of large-scale research facilities JLSRF, 2, A52–A52, https://doi.org/10.17815/jlsrf-2-98, 2016.
Bogena, H. and Ney, P.: Dataset of “COSMOS-Europe: A European network of Cosmic-Ray Neutron Soil Moisture Sensors”, Forschungszentrum Jülich [data set], https://doi.org/10.34731/x9s3-kr48, 2021.
Bogena, H. R., Schrön, M., Jakobi, J., Ney, P., Zacharias, S., Andreasen, M., Baatz, R., Boorman, D., Duygu, M. B., Eguibar-Galán, M. A., Fersch, B., Franke, T., Geris, J., González Sanchis, M., Kerr, Y., Korf, T., Mengistu, Z., Mialon, A., Nasta, P., Nitychoruk, J., Pisinaras, V., Rasche, D., Rosolem, R., Said, H., Schattan, P., Zreda, M., Achleitner, S., Albentosa-Hernández, E., Akyürek, Z., Blume, T., del Campo, A., Canone, D., Dimitrova-Petrova, K., Evans, J. G., Ferraris, S., Frances, F., Gisolo, D., Güntner, A., Herrmann, F., Iwema, J., Jensen, K. H., Kunstmann, H., Lidón, A., Looms, M. C., Oswald, S., Panagopoulos, A., Patil, A., Power, D., Rebmann, C., Romano, N., Scheiffele, L., Seneviratne, S., Weltin, G., and Vereecken, H.: COSMOS-Europe: a European network of cosmic-ray neutron soil moisture sensors, Earth Syst. Sci. Data, 14, 1125–1151, https://doi.org/10.5194/essd-14-1125-2022, 2022.
Brocca, L., Moramarco, T., Melone, F., Wagner, W., Hasenauer, S., and Hahn, S.: Assimilation of surface- and root-zone ASCAT soil moisture products into rainfall-runoff modeling, IEEE T. Geosci. Remote, 50, 2542–2555, 10.1109/TGRS.2011.2177468, 2012.
Brunke, M. A., Fairall, C. W., Zeng, X., Eymard, L., and Curry, J. A.: Which bulk aerodynamic algorithms are least problematic in computing ocean surface turbulent fluxes?, J. Climate, 16, 619–635, https://doi.org/10.1175/1520-0442(2003)016<0619:WBAAAL>2.0.CO;2, 2003.
Chawla, I., Karthikeyan, L., and Mishra, A. K.: A review of remote sensing applications for water security: Quantity, quality, and extremes, J. Hydrol., 585, 124826, https://doi.org/10.1016/j.jhydrol.2020.124826, 2020.
Chen, S., Gan, T. Y., Tan, X., Shao, D., and Zhu, J.: Assessment of CFSR, ERA-Interim, JRA-55, MERRA-2, NCEP-2 reanalysis data for drought analysis over China, Clim. Dynam., 53, 737–757, https://doi.org/10.1007/s00382-018-04611-1, 2019.
Chen, Y. and Yuan, H.: Evaluation of nine sub-daily soil moisture model products over China using high-resolution in situ observations, J. Hydrol., 588, 125054, https://doi.org/10.1016/j.jhydrol.2020.125054, 2020.
Chen, Y., Yang, K., Tang, W., Qin, J., and Zhao, L.: Parameterizing soil organic carbon's impacts on soil porosity and thermal parameters for Eastern Tibet grasslands, Sci. China Earth Sci., 55, 1001–1011, https://doi.org/10.1007/s11430-012-4433-0, 2012.
Cheng, M., Zhong, L., Ma, Y., Zou, M., Ge, N., Wang, X., and Hu, Y.: A study on the assessment of multi-source satellite soil moisture products and reanalysis data for the Tibetan Plateau, Remote Sens., 11, 1196, https://doi.org/10.3390/rs11101196, 2019.
Cooper, H. M., Bennett, E., Blake, J., Blyth, E., Boorman, D., Cooper, E., Evans, J., Fry, M., Jenkins, A., Morrison, R., Rylett, D., Stanley, S., Szczykulska, M., Trill, E., Antoniou, V., Askquith-Ellis, A., Ball, L., Brooks, M., Clarke, M. A., Cowan, N., Cumming, A., Farrand, P., Hitt, O., Lord, W., Scarlett, P., Swain, O., Thornton, J., Warwick, A., and Winterbourn, B.: COSMOS-UK: national soil moisture and hydrometeorology data for environmental science research, Earth Syst. Sci. Data, 13, 1737–1757, https://doi.org/10.5194/essd-13-1737-2021, 2021.
Crow, W. T., Berg, A. A., Cosh, M. H., Loew, A., Mohanty, B. P., Panciera, R., de Rosnay, P., Ryu, D., and Walker, J. P.: Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products, Rev. Geophys., 50, RG2002, https://doi.org/10.1029/2011RG000372, 2012.
Cui, C., Xu, J., Zeng, J., Chen, K.-S., Bai, X., Lu, H., Chen, Q., and Zhao, T.: Soil moisture mapping from satellites: An intercomparison of SMAP, SMOS, FY3B, AMSR2, and ESA CCI over two dense network regions at different spatial scales, Remote Sens., 10, 33, https://doi.org/10.3390/rs10010033, 2018.
Davies, P., Baatz, R., Bogena, H. R., Quansah, E., and Amekudzi, L. K.: Optimal Temporal Filtering of the Cosmic-Ray Neutron Signal to Reduce Soil Moisture Uncertainty, Sensors, 22, 9143, https://doi.org/10.3390/s22239143, 2022.
Decker, M., Brunke, M. A., Wang, Z., Sakaguchi, K., Zeng, X., and Bosilovich, M. G.: Evaluation of the reanalysis products from GSFC, NCEP, and ECMWF using flux tower observations, J. Climate, 25, 1916–1944, https://doi.org/10.1175/JCLI-D-11-00004.1, 2012.
Deng, M., Meng, X., Lu, Y., Li, Z., Zhao, L., Hu, Z., Chen, H., Shang, L., Wang, S., and Li, Q.: Impact and Sensitivity Analysis of Soil Water and Heat Transfer Parameterizations in Community Land Surface Model on the Tibetan Plateau, J. Adv. Model. Earth Sy., 13, e2021MS002670, https://doi.org/10.1029/2021MS002670, 2021.
Deng, Y., Wang, S., Bai, X., Wu, L., Cao, Y., Li, H., Wang, M., Li, C., Yang, Y., and Hu, Z.: Comparison of soil moisture products from microwave remote sensing, land model, and reanalysis using global ground observations, Hydrol. Process., 34, 836–851, https://doi.org/10.1002/hyp.13636, 2020.
Desilets, D. and Zreda, M.: Footprint diameter for a cosmic-ray soil moisture probe: Theory and Monte Carlo simulations, Water Resour. Res., 49, 3566–3575, https://doi.org/10.1002/wrcr.20187, 2013.
Desilets, D., Zreda, M., and Prabu, T.: Extended scaling factors for in situ cosmogenic nuclides: new measurements at low latitude, Earth Planet. Sc. Lett., 246, 265-276, https://doi.org/10.1016/j.epsl.2006.03.051, 2006.
Desilets, D., Zreda, M., and Ferré, T. P.: Nature's neutron probe: Land surface hydrology at an elusive scale with cosmic rays, Water Resour. Res., 46, W11505, https://doi.org/10.1029/2009WR008726, 2010.
Dimitrova-Petrova, K., Rosolem, R., Soulsby, C., Wilkinson, M. E., Lilly, A., and Geris, J.: Combining static and portable Cosmic ray neutron sensor data to assess catchment scale heterogeneity in soil water storage and their integrated role in catchment runoff response, J. Hydrol., 601, 126659, https://doi.org/10.1016/j.jhydrol.2021.126659, 2021.
Dong, J., Ochsner, T. E., Zreda, M., Cosh, M. H., and Zou, C. B.: Calibration and validation of the COSMOS rover for surface soil moisture measurement, Vadose Zone J., 13, 1–8, https://doi.org/10.2136/vzj2013.08.0148, 2014.
Dorigo, W., Gruber, A., De Jeu, R., Wagner, W., Stacke, T., Loew, A., Albergel, C., Brocca, L., Chung, D., and Parinussa, R.: Evaluation of the ESA CCI soil moisture product using ground-based observations, Remote Sens. Environ., 162, 380–395, https://doi.org/10.1016/j.rse.2014.07.023, 2015.
Duygu, M. B. and Akyürek, Z.: Using cosmic-ray neutron probes in validating satellite soil moisture products and land surface models, Water, 11, 1362, https://doi.org/10.3390/w11071362, 2019.
El Khalki, E. M., Tramblay, Y., Massari, C., Brocca, L., Simonneaux, V., Gascoin, S., and Saidi, M. E. M.: Challenges in flood modeling over data-scarce regions: how to exploit globally available soil moisture products to estimate antecedent soil wetness conditions in Morocco, Nat. Hazards Earth Syst. Sci., 20, 2591–2607, https://doi.org/10.5194/nhess-20-2591-2020, 2020.
ESA Land Cover CCI Project Team and Defourny, P.: ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Land Cover Maps, Version 2.0.7, Centre for Environmental Data Analysis [data set], https://catalogue.ceda.ac.uk/uuid/b382ebe6679d44b8b0e68ea4ef4b701c (last access: 6611 November 2021), 2019.
Evans, J., Ward, H., Blake, J., Hewitt, E., Morrison, R., Fry, M., Ball, L., Doughty, L., Libre, J., and Hitt, O.: Soil water content in southern England derived from a cosmic-ray soil moisture observing system – COSMOS-UK, Hydrol. Process., 30, 4987–4999, https://doi.org/10.1002/hyp.10929, 2016.
Ford, T. W. and Quiring, S. M.: Comparison of contemporary in situ, model, and satellite remote sensing soil moisture with a focus on drought monitoring, Water Resour. Res., 55, 1565–1582, https://doi.org/10.1029/2018WR024039, 2019.
Franz, T. E., Zreda, M., Ferre, T., Rosolem, R., Zweck, C., Stillman, S., Zeng, X., and Shuttleworth, W.: Measurement depth of the cosmic ray soil moisture probe affected by hydrogen from various sources, Water Resour. Res., 48, W08515, https://doi.org/10.1029/2012WR011871, 2012.
Franz, T. E., Zreda, M., Rosolem, R., and Ferre, T. P. A.: A universal calibration function for determination of soil moisture with cosmic-ray neutrons, Hydrol. Earth Syst. Sci., 17, 453–460, https://doi.org/10.5194/hess-17-453-2013, 2013a.
Franz, T. E., Zreda, M., Rosolem, R., Hornbuckle, B. K., Irvin, S. L., Adams, H., Kolb, T. E., Zweck, C., and Shuttleworth, W. J.: Ecosystem-scale measurements of biomass water using cosmic ray neutrons, Geophys. Res. Lett., 40, 3929–3933, https://doi.org/10.1002/grl.50791, 2013b.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., and Reichle, R.: The modern-era retrospective analysis for research and applications, version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Global Modeling and Assimilation Office (GMAO): MERRA-2 tavg1_2d_slv_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Single-Level Diagnostics V5.12.4, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/VJAFPLI1CSIV, 2015.
González-Zamora, Á., Sánchez, N., Pablos, M., and Martínez-Fernández, J.: CCI soil moisture assessment with SMOS soil moisture and in situ data under different environmental conditions and spatial scales in Spain, Remote Sens. Environ., 225, 469–482, https://doi.org/10.1016/j.rse.2018.02.010, 2019.
Gruber, A., Dorigo, W. A., Zwieback, S., Xaver, A., and Wagner, W.: Characterizing coarse-scale representativeness of in situ soil moisture measurements from the International Soil Moisture Network, Vadose Zone J., 12, 1–16, https://doi.org/10.2136/vzj2012.0170, 2013.
Gruber, A., De Lannoy, G., Albergel, C., Al-Yaari, A., Brocca, L., Calvet, J.-C., Colliander, A., Cosh, M., Crow, W., and Dorigo, W.: Validation practices for satellite soil moisture retrievals: What are (the) errors?, Remote Sens. Environ., 244, 111806, https://doi.org/10.1016/j.rse.2020.111806, 2020.
Hagan, D. F. T., Parinussa, R. M., Wang, G., and Draper, C. S.: An evaluation of soil moisture anomalies from global model-based datasets over the people's republic of China, Water, 12, 117, https://doi.org/10.3390/w12010117, 2019.
Harris, I., Jones, P. D., Osborn, T. J., and Lister, D. H.: Updated high©\resolution grids of monthly climatic observations–the CRU TS3. 10 Dataset, Int. J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711, 2014.
Hawdon, A., McJannet, D., and Wallace, J.: Calibration and correction procedures for cosmic-ray neutron soil moisture probes located across Australia, Water Resour. Res., 50, 5029–5043, https://doi.org/10.1002/2013WR015138, 2014.
Hengl, T., Mendes de Jesus, J., Heuvelink, G. B., Ruiperez Gonzalez, M., Kilibarda, M., Blagotiæ, A., Shangguan, W., Wright, M. N., Geng, X., and Bauer-Marschallinger, B.: SoilGrids250m: Global gridded soil information based on machine learning, PLoS one, 12, e0169748, https://doi.org/10.1371/journal.pone.0169748, 2017.
Iwema, J., Rosolem, R., Baatz, R., Wagener, T., and Bogena, H. R.: Investigating temporal field sampling strategies for site-specific calibration of three soil moisture–neutron intensity parameterisation methods, Hydrol. Earth Syst. Sci., 19, 3203–3216, https://doi.org/10.5194/hess-19-3203-2015, 2015.
Iwema, J., Rosolem, R., Rahman, M., Blyth, E., and Wagener, T.: Land surface model performance using cosmic-ray and point-scale soil moisture measurements for calibration, Hydrol. Earth Syst. Sci., 21, 2843–2861, https://doi.org/10.5194/hess-21-2843-2017, 2017.
Iwema, J., Schrön, M., Koltermann Da Silva, J., Schweiser De Paiva Lopes, R., and Rosolem, R.: Accuracy and precision of the cosmic-ray neutron sensor for soil moisture estimation at humid environments, Hydrol. Process., 35, e14419, https://doi.org/10.1002/hyp.14419, 2021.
JMA: JRA-55: Japanese 55-year Reanalysis, Daily 3-Hourly and 6-Hourly Data, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory [data set], https://doi.org/10.5065/D6HH6H41, 2013.
Jonard, F., Bircher, S., Demontoux, F., Weihermüller, L., Razafindratsima, S., Wigneron, J.-P., and Vereecken, H.: Passive L-band microwave remote sensing of organic soil surface layers: A tower-based experiment, Remote Sens., 10, 304, https://doi.org/10.3390/rs10020304, 2018.
Karra, K., Kontgis, C., Statman-Weil, Z., Mazzariello, J. C., Mathis, M., and Brumby, S. P.: Global land use/land cover with Sentinel 2 and deep learning, 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, 11–16 July 2021, 4704–4707, https://doi.org/10.1109/IGARSS47720.2021.9553499, 2021.
Karthikeyan, L., Chawla, I., and Mishra, A. K.: A review of remote sensing applications in agriculture for food security: Crop growth and yield, irrigation, and crop losses, J. Hydrol., 586, 124905, https://doi.org/10.1016/j.jhydrol.2020.124905, 2020.
Kêdzior, M. and Zawadzki, J.: Comparative study of soil moisture estimations from SMOS satellite mission, GLDAS database, and cosmic-ray neutrons measurements at COSMOS station in Eastern Poland, Geoderma, 283, 21–31, https://doi.org/10.1016/j.geoderma.2016.07.023, 2016.
Kim, H., Parinussa, R., Konings, A. G., Wagner, W., Cosh, M. H., Lakshmi, V., Zohaib, M., and Choi, M.: Global-scale assessment and combination of SMAP with ASCAT (active) and AMSR2 (passive) soil moisture products, Remote Sens. Environ., 204, 260–275, https://doi.org/10.1016/j.rse.2017.10.026, 2018.
Kim, H., Wigneron, J.-P., Kumar, S., Dong, J., Wagner, W., Cosh, M. H., Bosch, D. D., Collins, C. H., Starks, P. J., and Seyfried, M.: Global scale error assessments of soil moisture estimates from microwave-based active and passive satellites and land surface models over forest and mixed irrigated/dryland agriculture regions, Remote Sens. Environ., 251, 112052, https://doi.org/10.1016/j.rse.2020.112052, 2020.
Kim, S., Liu, Y. Y., Johnson, F. M., Parinussa, R. M., and Sharma, A.: A global comparison of alternate AMSR2 soil moisture products: Why do they differ?, Remote Sens. Environ., 161, 43–62, https://doi.org/10.1016/j.rse.2015.02.002, 2015.
Knoben, W. J., Woods, R. A., and Freer, J. E.: A quantitative hydrological climate classification evaluated with independent streamflow data, Water Resour. Res., 54, 5088–5109, https://doi.org/10.1029/2018WR022913, 2018.
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., and Endo, H.: The JRA-55 reanalysis: General specifications and basic characteristics, J. Meteorol. Soc. Jpn. II, 93, 5–48, https://doi.org/10.2151/jmsj.2015-001, 2015.
Köhli, M., Schrön, M., Zreda, M., Schmidt, U., Dietrich, P., and Zacharias, S.: Footprint characteristics revised for field-scale soil moisture monitoring with cosmic-ray neutrons, Water Resour. Res., 51, 5772–5790, https://doi.org/10.1002/2015WR017169, 2015.
Koster, R. D., Guo, Z., Yang, R., Dirmeyer, P. A., Mitchell, K., and Puma, M. J.: On the nature of soil moisture in land surface models, J. Climate, 22, 4322–4335, https://doi.org/10.1175/2009JCLI2832.1, 2009.
Lawrence, D. M. and Slater, A. G.: Incorporating organic soil into a global climate model, Clim. Dynam., 30, 145–160, 2008.
Li, C., Zhao, T., Shi, C., and Liu, Z.: Assessment of precipitation from the CRA40 dataset and new generation reanalysis datasets in the global domain, Int. J. Climatol., 41, 5243–5263, https://doi.org/10.1002/joc.7127, 2021.
Li, H., Robock, A., Liu, S., Mo, X., and Viterbo, P.: Evaluation of reanalysis soil moisture simulations using updated Chinese soil moisture observations, J. Hydrometeorol., 6, 180–193, https://doi.org/10.1175/JHM416.1, 2005.
Li, M., Wu, P., and Ma, Z.: A comprehensive evaluation of soil moisture and soil temperature from third-generation atmospheric and land reanalysis data sets, Int. J. Climatol., 40, 5744–5766, https://doi.org/10.1002/joc.6549, 2020.
Ling, X., Huang, Y., Guo, W., Wang, Y., Chen, C., Qiu, B., Ge, J., Qin, K., Xue, Y., and Peng, J.: Comprehensive evaluation of satellite-based and reanalysis soil moisture products using in situ observations over China, Hydrol. Earth Syst. Sci., 25, 4209–4229, https://doi.org/10.5194/hess-25-4209-2021, 2021.
Liu, Z., Shi, C., Zhou, Z., Jiang, L., Liang, X., Zhang, T., Liao, J., Liu, J., Wang, M., and Yao, S.: CMA global reanalysis (CRA-40): Status and plans, Proc. 5th International Conference on Reanalysis, Rome, Italy, https://climate.copernicus.eu/sites/default/files/repository/Events/ICR5/Talks/zhinqua liu_13pm.pdf, 13–17 November, 2017 (data available at: https://data.cma.cn/data/detail/dataCode/NAFP_CRA40_FTM_DAY_NC.html, last access: 27 April 2021).
Ma, H., Zeng, J., Chen, N., Zhang, X., Cosh, M. H., and Wang, W.: Satellite surface soil moisture from SMAP, SMOS, AMSR2 and ESA CCI: A comprehensive assessment using global ground-based observations, Remote Sens. Environ., 231, 111215, https://doi.org/10.1016/j.rse.2019.111215, 2019.
Mahto, S. S. and Mishra, V.: Does ERA-5 outperform other reanalysis products for hydrologic applications in India?, J. Geophys. Res.-Atmos., 124, 9423–9441, https://doi.org/10.1029/2019JD031155, 2019.
Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, 2017 (data available at: https://www.gleam.eu/, last access: 12 June 2021).
Martínez-Fernández, J., González-Zamora, A., Sánchez, N., Gumuzzio, A., and Herrero-Jiménez, C.: Satellite soil moisture for agricultural drought monitoring: Assessment of the SMOS derived Soil Water Deficit Index, Remote Sens. Environ., 177, 277–286, https://doi.org/10.1016/j.rse.2016.02.064, 2016.
Massari, C., Brocca, L., Barbetta, S., Papathanasiou, C., Mimikou, M., and Moramarco, T.: Using globally available soil moisture indicators for flood modelling in Mediterranean catchments, Hydrol. Earth Syst. Sci., 18, 839–853, https://doi.org/10.5194/hess-18-839-2014, 2014.
Massari, C., Camici, S., Ciabatta, L., and Brocca, L.: Exploiting satellite-based surface soil moisture for flood forecasting in the Mediterranean area: State update versus rainfall correction, Remote Sens., 10, 292, https://doi.org/10.3390/rs10020292, 2018.
McClean, F., Dawson, R., and Kilsby, C.: Intercomparison of global reanalysis precipitation for flood risk modelling, Hydrol. Earth Syst. Sci., 27, 331–347, https://doi.org/10.5194/hess-27-331-2023, 2023.
McJannet, D., Stenson, M., Sommer, A., and Hawdon, A.: CosmOz – The Australian Cosmic-ray Soil Moisture Sensor Network, Version 1.0.0, Terrestrial Ecosystem Research Network (TERN) [data set], https://doi.org/10.25901/5e7ab81af0394, 2021.
Miralles, D. G., Crow, W. T., and Cosh, M. H.: Estimating spatial sampling errors in coarse-scale soil moisture estimates derived from point-scale observations, J. Hydrometeorol., 11, 1423–1429, https://doi.org/10.1175/2010JHM1285.1, 2010.
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., Van Den Berg, M. J., Gash, J. H., Parinussa, R. M., De Jeu, R. A., Beck, H. E., Holmes, T. R., Jiménez, C., Verhoest, N. E., and Dorigo, W. A.: El Niño – La Niña cycle and recent trends in continental evaporation, Nat. Clim. Change, 4, 122–126, https://doi.org/10.1038/nclimate2068, 2014.
Montzka, C., Bogena, H. R., Zreda, M., Monerris, A., Morrison, R., Muddu, S., and Vereecken, H.: Validation of spaceborne and modelled surface soil moisture products with cosmic-ray neutron probes, Remote Sens., 9, 103, https://doi.org/10.3390/rs9020103, 2017.
Muñoz Sabater, J.: ERA5-Land hourly data from 1981 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.e2161bac, 2019.
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: a state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021.
Mwangi, S., Zeng, Y., Montzka, C., Yu, L., and Su, Z.: Assimilation of cosmic-ray neutron counts for the estimation of soil ice content on the eastern Tibetan Plateau, J. Geophys. Res.-Atmos., 125, e2019JD031529, https://doi.org/10.1029/2019JD031529, 2020.
Naz, B. S., Kollet, S., Franssen, H.-J. H., Montzka, C., and Kurtz, W.: A 3 km spatially and temporally consistent European daily soil moisture reanalysis from 2000 to 2015, Sci. Data, 7, 1–14, https://doi.org/10.1038/s41597-020-0450-6, 2020.
Nicolai-Shaw, N., Hirschi, M., Mittelbach, H., and Seneviratne, S. I.: Spatial representativeness of soil moisture using in situ, remote sensing, and land reanalysis data, J. Geophys. Res.-Atmos., 120, 9955–9964, https://doi.org/10.1002/2015JD023305, 2015.
Peng, J., Niesel, J., Loew, A., Zhang, S., and Wang, J.: Evaluation of satellite and reanalysis soil moisture products over southwest China using ground-based measurements, Remote Sens., 7, 15729–15747, https://doi.org/10.3390/rs71115729, 2015.
Peng, J., Tanguy, M., Robinson, E. L., Pinnington, E., Evans, J., Ellis, R., Cooper, E., Hannaford, J., Blyth, E., and Dadson, S.: Estimation and evaluation of high-resolution soil moisture from merged model and Earth observation data in the Great Britain, Remote Sens. Environ., 264, 112610, https://doi.org/10.1016/j.rse.2021.112610, 2021.
Power, D., Rico-Ramirez, M. A., Desilets, S., Desilets, D., and Rosolem, R.: Cosmic-Ray neutron Sensor PYthon tool (crspy 1.2.1): an open-source tool for the processing of cosmic-ray neutron and soil moisture data, Geosci. Model Dev., 14, 7287–7307, https://doi.org/10.5194/gmd-14-7287-2021, 2021a.
Power, D., Rico-Ramirez, M. A., Desilets, S., Desilets, D., and Rosolem, R.: crspy: v1.2.1, v1.2.1, Zenodo [code], https://doi.org/10.5281/zenodo.5543669, 2021b.
Qin, Y., Wu, T., Wu, X., Li, R., Xie, C., Qiao, Y., Hu, G., Zhu, X., Wang, W., and Shang, W.: Assessment of reanalysis soil moisture products in the permafrost regions of the central of the Qinghai–Tibet Plateau, Hydrol. Process., 31, 4647–4659, https://doi.org/10.1002/hyp.11383, 2017.
Reichle, R., De Lannoy, G., Koster, R. D., Crow, W. T., Kimball, J. S., Liu, Q., and Bechtold, M.: SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update, Version 7, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/LWJ6TF5SZRG3, 2022.
Reichle, R., De Lannoy, G., Koster, R. D., Crow, W. T., Kimball, J. S., Liu, Q., and Bechtold, M.: SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update, Version 7. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/LWJ6TF5SZRG3, 2022.
Reichle, R. H., De Lannoy, G. J., Liu, Q., Ardizzone, J. V., Colliander, A., Conaty, A., Crow, W., Jackson, T. J., Jones, L. A., and Kimball, J. S.: Assessment of the SMAP level-4 surface and root-zone soil moisture product using in situ measurements, J. Hydrometeorol., 18, 2621–2645, 2017a.
Reichle, R. H., De Lannoy, G. J., Liu, Q., Koster, R. D., Kimball, J. S., Crow, W. T., Ardizzone, J. V., Chakraborty, P., Collins, D. W., and Conaty, A. L.: Global assessment of the SMAP Level-4 surface and root-zone soil moisture product using assimilation diagnostics, J. Hydrometeorol., 18, 3217–3237, 2017b.
Reichle, R. H., Liu, Q., Koster, R. D., Crow, W. T., De Lannoy, G. J. M., Kimball, J. S., Ardizzone, J. V., Bosch, D., Colliander, A., Cosh, M., Kolassa, J., Mahanama, S. P., Prueger, J., Starks, P., and Walker, J. P.: Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product, J. Adv. Model. Earth Sy., 11, 3106–3130, https://doi.org/10.1029/2019MS001729, 2019.
Renzullo, L. J., Van Dijk, A., Perraud, J.-M., Collins, D., Henderson, B., Jin, H., Smith, A., and McJannet, D.: Continental satellite soil moisture data assimilation improves root-zone moisture analysis for water resources assessment, J. Hydrol., 519, 2747–2762, https://doi.org/10.1016/j.jhydrol.2014.08.008, 2014.
Rivera Villarreyes, C. A., Baroni, G., and Oswald, S. E.: Integral quantification of seasonal soil moisture changes in farmland by cosmic-ray neutrons, Hydrol. Earth Syst. Sci., 15, 3843–3859, https://doi.org/10.5194/hess-15-3843-2011, 2011.
Rodell, M., Houser, P., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C.-J., Arsenault, K., Cosgrove, B., Radakovich, J., and Bosilovich, M.: The global land data assimilation system, B Am. Meteorol. Soc., 85, 381–394, https://doi.org/10.1175/BAMS-85-3-381, 2004.
Rosolem, R., Shuttleworth, W., Zreda, M., Franz, T. E., Zeng, X., and Kurc, S.: The effect of atmospheric water vapor on neutron count in the cosmic-ray soil moisture observing system, J. Hydrometeorol., 14, 1659–1671, https://doi.org/10.1175/JHM-D-12-0120.1, 2013.
Rosolem, R., Hoar, T., Arellano, A., Anderson, J. L., Shuttleworth, W. J., Zeng, X., and Franz, T. E.: Translating aboveground cosmic-ray neutron intensity to high-frequency soil moisture profiles at sub-kilometer scale, Hydrol. Earth Syst. Sci., 18, 4363–4379, https://doi.org/10.5194/hess-18-4363-2014, 2014.
Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D., Hou, Y., Chuang, H., Iredell, M., Ek, M., Meng, J., Yang, R., Mendez, M. P., van den Dool, H., Zhang, Q., Wang, W., Chen, M., and Becker, E.: NCEP Climate Forecast System Version 2 (CFSv2) Selected Hourly Time-Series Products, Research Data Archive at the National Center for Atmospheric Research [data set], https://doi.org/10.5065/D6N877VB, 2011.
Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D., Hou, Y.-T., Chuang, H.-y., and Iredell, M.: The NCEP climate forecast system version 2, J. Climate, 27, 2185–2208, https://doi.org/10.1175/JCLI-D-12-00823.1, 2014.
Schmidt, T., Schrön, M., Li, Z., and Peng, J.: Intercomparison of current soil moisture products from remote sensing and modeling over COSMOS field sites in Germany, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10336, https://doi.org/10.5194/egusphere-egu22-10336, 2022.
Schrön, M., Köhli, M., Scheiffele, L., Iwema, J., Bogena, H. R., Lv, L., Martini, E., Baroni, G., Rosolem, R., Weimar, J., Mai, J., Cuntz, M., Rebmann, C., Oswald, S. E., Dietrich, P., Schmidt, U., and Zacharias, S.: Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity, Hydrol. Earth Syst. Sci., 21, 5009–5030, https://doi.org/10.5194/hess-21-5009-2017, 2017.
Sigouin, M. J., Dyck, M., Si, B. C., and Hu, W.: Monitoring soil water content at a heterogeneous oil sand reclamation site using a cosmic-ray soil moisture probe, J. Hydrol., 543, 510–522, https://doi.org/10.1016/j.jhydrol.2016.10.026, 2016.
Stanley, S., Antoniou, V., Askquith-Ellis, A., Ball, L. A., Bennett, E.S., Blake, J. R., Boorman, D. B., Brooks, M., Clarke, M., Cooper,H. M., Cowan, N., Cumming, A., Evans, J. G., Farrand, P., Fry,M., Hitt, O. E., Lord, W. D., Morrison, R., Nash, G. V., Rylett,D., Scarlett, P. M., Swain, O. D., Szczykulska, M., Thornton,J. L., Trill, E. J., Warwick, A. C., and Winterbourn, B.: Daily and sub-daily hydrometeorological and soil data (2013–2019) [COSMOS-UK], NERC Environmental Information Data Centre [data set], https://doi.org/10.5285/b5c190e4-e35d-40ea-8fbe-598da03a1185, 2021.
Stillman, S., Zeng, X., and Bosilovich, M. G.: Evaluation of 22 precipitation and 23 soil moisture products over a semiarid area in southeastern Arizona, J. Hydrometeorol., 17, 211–230, https://doi.org/10.1175/JHM-D-15-0007.1, 2016.
Tavakol, A., Rahmani, V., Quiring, S. M., and Kumar, S. V.: Evaluation analysis of NASA SMAP L3 and L4 and SPoRT-LIS soil moisture data in the United States, Remote Sens. Environ., 229, 234–246, 2019.
Upadhyaya, D. B., Evans, J., Muddu, S., Tomer, S. K., Al Bitar, A., Yeggina, S., Morrison, R., Fry, M., Tripathi, S. N., and Mujumdar, M.: The Indian COSMOS Network (ICON): validating L-band remote sensing and modelled soil moisture data products, Remote Sens., 13, 537, https://doi.org/10.3390/rs13030537, 2021.
Wang, A. and Zeng, X.: Evaluation of multireanalysis products with in situ observations over the Tibetan Plateau, J. Geophys. Res.-Atmos., 117, D05102, https://doi.org/10.1029/2011JD016553, 2012.
Wen, X., Lu, H., Li, C., Koike, T., and Kaihotsu, I.: Inter-comparison of soil moisture products from SMOS, AMSR-E, ECWMF and GLDAS over the Mongolia Plateau, Proc. SPIE, 9260, 103–110, https://doi.org/10.1117/12.2068952, 2014.
Willmott, C. J. and Feddema, J. J.: A more rational climatic moisture index, Prof. Geogr., 44, 84–88, 1992.
Wood, E. F., Roundy, J. K., Troy, T. J., Van Beek, L., Bierkens, M. F., Blyth, E., de Roo, A., Döll, P., Ek, M., and Famiglietti, J.: Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water, Water Resour. Res., 47, W05301, https://doi.org/10.1029/2010WR010090, 2011.
Wu, Z., Feng, H., He, H., Zhou, J., and Zhang, Y.: Evaluation of soil moisture climatology and anomaly components derived from ERA5-land and GLDAS-2.1 in China, Water Resour. Manage., 35, 629–643, https://doi.org/10.1007/s11269-020-02743-w, 2021.
Xing, Z., Fan, L., Zhao, L., De Lannoy, G., Frappart, F., Peng, J., Li, X., Zeng, J., Al-Yaari, A., and Yang, K.: A first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of Qinghai-Tibet Plateau, Remote Sens. Environ., 265, 112666, https://doi.org/10.1016/j.rse.2021.112666, 2021.
Xu, L., Chen, N., Zhang, X., Moradkhani, H., Zhang, C., and Hu, C.: In-situ and triple-collocation based evaluations of eight global root zone soil moisture products, Remote Sens. Environ., 254, 112248, https://doi.org/10.1016/j.rse.2020.112248, 2021.
Yamazaki, D., Ikeshima, D., Tawatari, R., Yamaguchi, T., O'Loughlin, F., Neal, J. C., Sampson, C. C., Kanae, S., and Bates, P. D.: A high-accuracy map of global terrain elevations, Geophys. Res. Lett., 44, 5844–5853, https://doi.org/10.1002/2017GL072874, 2017.
Yang, S., Li, R., Wu, T., Hu, G., Xiao, Y., Du, Y., Zhu, X., Ni, J., Ma, J., and Zhang, Y.: Evaluation of reanalysis soil temperature and soil moisture products in permafrost regions on the Qinghai-Tibetan Plateau, Geoderma, 377, 114583, https://doi.org/10.1016/j.geoderma.2020.114583, 2020.
Yang, Y., Zhang, J., Bao, Z., Ao, T., Wang, G., Wu, H., and Wang, J.: Evaluation of multi-source soil moisture datasets over central and eastern agricultural area of China using in situ monitoring network, Remote Sens., 13, 1175, https://doi.org/10.3390/rs13061175, 2021.
Yee, M. S., Walker, J. P., Rüdiger, C., Parinussa, R. M., Koike, T., and Kerr, Y. H.: A comparison of SMOS and AMSR2 soil moisture using representative sites of the OzNet monitoring network, Remote Sens. Environ., 195, 297–312, https://doi.org/10.1016/j.rse.2017.04.019, 2017.
Zacharias, S., Bogena, H., Samaniego, L., Mauder, M., Fuß, R., Pütz, T., Frenzel, M., Schwank, M., Baessler, C., and Butterbach-Bahl, K.: A network of terrestrial environmental observatories in Germany, Vadose Zone J., 10, 955–973, https://doi.org/10.2136/vzj2010.0139, 2011.
Zeng, J., Li, Z., Chen, Q., Bi, H., Qiu, J., and Zou, P.: Evaluation of remotely sensed and reanalysis soil moisture products over the Tibetan Plateau using in-situ observations, Remote Sens. Environ., 163, 91–110, https://doi.org/10.1016/j.rse.2015.03.008, 2015.
Zheng, J., Zhao, T., Lü, H., Shi, J., Cosh, M. H., Ji, D., Jiang, L., Cui, Q., Lu, H., and Yang, K.: Assessment of 24 soil moisture datasets using a new in situ network in the Shandian River Basin of China, Remote Sens. Environ., 271, 112891, https://doi.org/10.1016/j.rse.2022.112891, 2022.
Zheng, Y., Li, J., Dong, L., Rong, Y., Kang, A., and Feng, P.: Estimation of Initial Abstraction for Hydrological Modeling Based on Global Land Data Assimilation System–Simulated Datasets, J. Hydrometeorol., 21, 1051–1072, https://doi.org/10.1175/JHM-D-19-0202.1, 2020.
Zheng, Y., Li, J., Zhang, T., Rong, Y., and Feng, P.: Exploring the Application of Flood Scaling Property in Hydrological Model Calibration, J. Hydrometeorol., 22, 3255–3274, https://doi.org/10.1175/JHM-D-21-0123.1, 2021.
Zheng, Y., Coxon, G., Woods, R., Li, J., and Feng, P.: A framework for estimating the probability distribution of event runoff coefficient in ungauged catchments, Water Resour. Res., 59, e2022WR033227, https://doi.org/10.1029/2022WR033227, 2023.
Zhu, D., Ciais, P., Krinner, G., Maignan, F., Jornet Puig, A., and Hugelius, G.: Controls of soil organic matter on soil thermal dynamics in the northern high latitudes, Nat. Commum., 10, 1–9, https://doi.org/10.1038/s41467-019-11103-1, 2019.
Zhu, Z., Tan, L., Gao, S., and Jiao, Q.: Observation on soil moisture of irrigation cropland by cosmic-ray probe, IEEE Geosci. Remote S., 12, 472–476, https://doi.org/10.1109/LGRS.2014.2346784, 2014.
Zreda, M., Desilets, D., Ferré, T., and Scott, R. L.: Measuring soil moisture content non-invasively at intermediate spatial scale using cosmic-ray neutrons, Geophys. Res. Lett., 35, L21402, https://doi.org/10.1029/2008GL035655, 2008.
Zreda, M., Shuttleworth, W. J., Zeng, X., Zweck, C., Desilets, D., Franz, T., and Rosolem, R.: COSMOS: the COsmic-ray Soil Moisture Observing System, Hydrol. Earth Syst. Sci., 16, 4079–4099, https://doi.org/10.5194/hess-16-4079-2012, 2012 (data avaliable at: http://cosmos.hwr.arizona.edu/, last access: 5 June 2021).
Short summary
Reanalysis soil moisture products are a vital basis for hydrological and environmental research. Previous product evaluation is limited by the scale difference (point and grid scale). This paper adopts cosmic ray neutron sensor observations, a novel technique that provides root-zone soil moisture at field scale. In this paper, global harmonized CRNS observations were used to assess products. ERA5-Land, SMAPL4, CFSv2, CRA40 and GLEAM show better performance than MERRA2, GLDAS-Noah and JRA55.
Reanalysis soil moisture products are a vital basis for hydrological and environmental research....
