Articles | Volume 14, issue 12
https://doi.org/10.5194/gmd-14-7345-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-7345-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
STEMMUS-UEB v1.0.0: integrated modeling of snowpack and soil water and energy transfer with three complexity levels of soil physical processes
Lianyu Yu
Faculty of Geo-information Science and Earth Observation (ITC),
University of Twente, Enschede, the Netherlands
Faculty of Geo-information Science and Earth Observation (ITC),
University of Twente, Enschede, the Netherlands
Zhongbo Su
CORRESPONDING AUTHOR
Faculty of Geo-information Science and Earth Observation (ITC),
University of Twente, Enschede, the Netherlands
Key Laboratory of Subsurface Hydrology and Ecological Effect in
Arid Region of Ministry of Education, School of Water and Environment,
Chang'an University, Xi'an, China
Related authors
Mostafa Gomaa Daoud, Fakhereh Alidoost, Yijian Zeng, Bart Schilperoort, Christiaan Van der Tol, Maciek W. Lubczynski, Mhd Suhyb Salama, Eric D. Morway, Christian D. Langevin, Prajwal Khanal, Zengjing Song, Lianyu Yu, Hong Zhao, Gualbert Oude Essink, Victor F. Bense, Michiel van der Molen, and Zhongbo Su
EGUsphere, https://doi.org/10.5194/egusphere-2025-4179, https://doi.org/10.5194/egusphere-2025-4179, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
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This study investigates the groundwater role in soil-plant-atmosphere continuum. An integrated ecohydrological modelling approach was developed by coupling STEMMUS-SCOPE to MODFLOW 6 and applied at three sites over 8 years. The coupled model improved simulations of soil moisture and temperature, evapotranspiration, carbon fluxes and fluorescence. The findings highlight the groundwater critical role in ecosystem dynamics and its contribution to advancing water, energy and carbon cycle modelling.
Lianyu Yu, Yijian Zeng, Huanjie Cai, Mengna Li, Yuanyuan Zha, Jicai Zeng, Hui Qian, and Zhongbo Su
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-221, https://doi.org/10.5194/gmd-2022-221, 2023
Revised manuscript not accepted
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We developed a coupled soil water-groundwater (SW-GW) model, which is verified as physically accurate and applicable in large-scale groundwater problems. The role of vadose zone processes, coupling approach, and spatiotemporal heterogeneity of SW-GW interactions were highlighted as essential to represent the SW-GW system. Given the relevant dataset, the developed SW-GW modeling framework has the potential to portray the processes "from bedrock to atmosphere" in a physically consistent manner.
Mengna Li, Yijian Zeng, Maciek W. Lubczynski, Jean Roy, Lianyu Yu, Hui Qian, Zhenyu Li, Jie Chen, Lei Han, Han Zheng, Tom Veldkamp, Jeroen M. Schoorl, Harrie-Jan Hendricks Franssen, Kai Hou, Qiying Zhang, Panpan Xu, Fan Li, Kai Lu, Yulin Li, and Zhongbo Su
Earth Syst. Sci. Data, 13, 4727–4757, https://doi.org/10.5194/essd-13-4727-2021, https://doi.org/10.5194/essd-13-4727-2021, 2021
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The Tibetan Plateau is the source of most of Asia's major rivers and has been called the Asian Water Tower. Due to its remoteness and the harsh environment, there is a lack of field survey data to investigate its hydrogeology. Borehole core lithology analysis, an altitude survey, soil thickness measurement, hydrogeological surveys, and hydrogeophysical surveys were conducted in the Maqu catchment within the Yellow River source region to improve a full–picture understanding of the water cycle.
Yunfei Wang, Yijian Zeng, Lianyu Yu, Peiqi Yang, Christiaan Van der Tol, Qiang Yu, Xiaoliang Lü, Huanjie Cai, and Zhongbo Su
Geosci. Model Dev., 14, 1379–1407, https://doi.org/10.5194/gmd-14-1379-2021, https://doi.org/10.5194/gmd-14-1379-2021, 2021
Short summary
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This study integrates photosynthesis and transfer of energy, mass, and momentum in the soil–plant–atmosphere continuum system, via a simplified 1D root growth model. The results indicated that the simulation of land surface fluxes was significantly improved by considering the root water uptake, especially when vegetation was experiencing severe water stress. This finding highlights the importance of enhanced soil heat and moisture transfer in simulating ecosystem functioning.
Lianyu Yu, Simone Fatichi, Yijian Zeng, and Zhongbo Su
The Cryosphere, 14, 4653–4673, https://doi.org/10.5194/tc-14-4653-2020, https://doi.org/10.5194/tc-14-4653-2020, 2020
Short summary
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The role of soil water and heat transfer physics in portraying the function of a cold region ecosystem was investigated. We found that explicitly considering the frozen soil physics and coupled water and heat transfer is important in mimicking soil hydrothermal dynamics. The presence of soil ice can alter the vegetation leaf onset date and deep leakage. Different complexity in representing vadose zone physics does not considerably affect interannual energy, water, and carbon fluxes.
Lianyu Yu, Yijian Zeng, and Zhongbo Su
Hydrol. Earth Syst. Sci., 24, 4813–4830, https://doi.org/10.5194/hess-24-4813-2020, https://doi.org/10.5194/hess-24-4813-2020, 2020
Short summary
Short summary
Soil mass and heat transfer processes were represented in three levels of model complexities to understand soil freeze–thaw mechanisms. Results indicate that coupled mass and heat transfer models considerably improved simulations of the soil hydrothermal regime. Vapor flow and thermal effects on water flow are the main mechanisms for the improvements. Given the explicit consideration of airflow, vapor flow and its effects on heat transfer were enhanced during the freeze–thaw transition period.
Mostafa Gomaa Daoud, Fakhereh Alidoost, Yijian Zeng, Bart Schilperoort, Christiaan Van der Tol, Maciek W. Lubczynski, Mhd Suhyb Salama, Eric D. Morway, Christian D. Langevin, Prajwal Khanal, Zengjing Song, Lianyu Yu, Hong Zhao, Gualbert Oude Essink, Victor F. Bense, Michiel van der Molen, and Zhongbo Su
EGUsphere, https://doi.org/10.5194/egusphere-2025-4179, https://doi.org/10.5194/egusphere-2025-4179, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
This study investigates the groundwater role in soil-plant-atmosphere continuum. An integrated ecohydrological modelling approach was developed by coupling STEMMUS-SCOPE to MODFLOW 6 and applied at three sites over 8 years. The coupled model improved simulations of soil moisture and temperature, evapotranspiration, carbon fluxes and fluorescence. The findings highlight the groundwater critical role in ecosystem dynamics and its contribution to advancing water, energy and carbon cycle modelling.
Qianqian Han, Yijian Zeng, Yunfei Wang, Fakhereh Sarah Alidoost, Francesco Nattino, Yang Liu, and Bob Su
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-183, https://doi.org/10.5194/essd-2025-183, 2025
Revised manuscript under review for ESSD
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Understanding how land interacts with the atmosphere is crucial for studying climate change, yet global high-resolution data on energy, water, and carbon exchanges remain limited. This study introduces a new dataset that estimates these exchanges hourly from 2000 to 2020 by combining physical process model, field measurements, and machine learning with satellite and meteorological data. Our dataset provides valuable insights into how ecosystems respond to climate extremes worldwide.
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
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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.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin G. De Kauwe, Samuel Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig R. Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony P. Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
Biogeosciences, 21, 5517–5538, https://doi.org/10.5194/bg-21-5517-2024, https://doi.org/10.5194/bg-21-5517-2024, 2024
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This paper evaluates land models – computer-based models that simulate ecosystem dynamics; land carbon, water, and energy cycles; and the role of land in the climate system. It uses machine learning and AI approaches to show that, despite the complexity of land models, they do not perform nearly as well as they could given the amount of information they are provided with about the prediction problem.
Zengjing Song, Yijian Zeng, Yunfei Wang, Enting Tang, Danyang Yu, Fakhereh Alidoost, Mingguo Ma, Xujun Han, Xuguang Tang, Zhongjing Zhu, Yao Xiao, Debing Kong, and Zhongbo Su
EGUsphere, https://doi.org/10.5194/egusphere-2024-2940, https://doi.org/10.5194/egusphere-2024-2940, 2024
Preprint archived
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The exchange of water and carbon between the plant and the atmosphere is affected under water stress conditions. In this study, a leaf-water-potential-based water stress factor is considered in the STEMMUS-SCOPE (hereafter STEMMUS-SCOPE-PHS), to replace the conventional soil-moisture-based water stress factor. The results show that leaf water potential reflects the plant water stress well, and the STEMMUS-SCOPE-PHS outperforms STEMMUS-SCOPE in the dynamics of the water, energy and carbon fluxes.
Tobias Karl David Weber, Lutz Weihermüller, Attila Nemes, Michel Bechtold, Aurore Degré, Efstathios Diamantopoulos, Simone Fatichi, Vilim Filipović, Surya Gupta, Tobias L. Hohenbrink, Daniel R. Hirmas, Conrad Jackisch, Quirijn de Jong van Lier, John Koestel, Peter Lehmann, Toby R. Marthews, Budiman Minasny, Holger Pagel, Martine van der Ploeg, Shahab Aldin Shojaeezadeh, Simon Fiil Svane, Brigitta Szabó, Harry Vereecken, Anne Verhoef, Michael Young, Yijian Zeng, Yonggen Zhang, and Sara Bonetti
Hydrol. Earth Syst. Sci., 28, 3391–3433, https://doi.org/10.5194/hess-28-3391-2024, https://doi.org/10.5194/hess-28-3391-2024, 2024
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Pedotransfer functions (PTFs) are used to predict parameters of models describing the hydraulic properties of soils. The appropriateness of these predictions critically relies on the nature of the datasets for training the PTFs and the physical comprehensiveness of the models. This roadmap paper is addressed to PTF developers and users and critically reflects the utility and future of PTFs. To this end, we present a manifesto aiming at a paradigm shift in PTF research.
Yunfei Wang, Yijian Zeng, Zengjing Song, Danyang Yu, Qianqian Han, Enting Tang, Henk de Bruin, and Zhongbo Su
EGUsphere, https://doi.org/10.5194/egusphere-2024-1321, https://doi.org/10.5194/egusphere-2024-1321, 2024
Preprint archived
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Various methods were proposed to estimate irrigation water requirements (IWR). However, the simulated IWR exhibits large differences. This study evaluates six potential evapotranspiration (PET) methods and proposes a practical approach to estimate IWR. The radiation-based methods show promise in approximating daily PET accurately, and the STEMMUS-SCOPE model can reliably estimate IWR. This research enhances our understanding of different PET methods and their implications for water management.
Enting Tang, Yijian Zeng, Yunfei Wang, Zengjing Song, Danyang Yu, Hongyue Wu, Chenglong Qiao, Christiaan van der Tol, Lingtong Du, and Zhongbo Su
Biogeosciences, 21, 893–909, https://doi.org/10.5194/bg-21-893-2024, https://doi.org/10.5194/bg-21-893-2024, 2024
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Our study shows that planting shrubs in a semiarid grassland reduced the soil moisture and increased plant water uptake and transpiration. Notably, the water used by the ecosystem exceeded the rainfall received during the growing seasons, indicating an imbalance in the water cycle. The findings demonstrate the effectiveness of the STEMMUS–SCOPE model as a tool to represent ecohydrological processes and highlight the need to consider energy and water budgets for future revegetation projects.
Qianqian Han, Yijian Zeng, Lijie Zhang, Calimanut-Ionut Cira, Egor Prikaziuk, Ting Duan, Chao Wang, Brigitta Szabó, Salvatore Manfreda, Ruodan Zhuang, and Bob Su
Geosci. Model Dev., 16, 5825–5845, https://doi.org/10.5194/gmd-16-5825-2023, https://doi.org/10.5194/gmd-16-5825-2023, 2023
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Using machine learning, we estimated global surface soil moisture (SSM) to aid in understanding water, energy, and carbon exchange. Ensemble models outperformed individual algorithms in predicting SSM under different climates. The best-performing ensemble included K-neighbours Regressor, Random Forest Regressor, and Extreme Gradient Boosting. This is important for hydrological and climatological applications such as water cycle monitoring, irrigation management, and crop yield prediction.
Kai-Gao Ouyang, Xiao-Wei Jiang, Gang Mei, Hong-Bin Yan, Ran Niu, Li Wan, and Yijian Zeng
Hydrol. Earth Syst. Sci., 27, 2579–2590, https://doi.org/10.5194/hess-27-2579-2023, https://doi.org/10.5194/hess-27-2579-2023, 2023
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Our knowledge on sources and dynamics of rock moisture is limited. By using frequency domain reflectometry (FDR), we monitored rock moisture in a cave. The results of an explainable deep learning model reveal that the direct source of rock moisture responsible for weathering in the studied cave is vapour, not infiltrating precipitation. A physics-informed deep learning model, which uses variables controlling vapor condensation as model inputs, leads to accurate rock water content predictions.
Lianyu Yu, Yijian Zeng, Huanjie Cai, Mengna Li, Yuanyuan Zha, Jicai Zeng, Hui Qian, and Zhongbo Su
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-221, https://doi.org/10.5194/gmd-2022-221, 2023
Revised manuscript not accepted
Short summary
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We developed a coupled soil water-groundwater (SW-GW) model, which is verified as physically accurate and applicable in large-scale groundwater problems. The role of vadose zone processes, coupling approach, and spatiotemporal heterogeneity of SW-GW interactions were highlighted as essential to represent the SW-GW system. Given the relevant dataset, the developed SW-GW modeling framework has the potential to portray the processes "from bedrock to atmosphere" in a physically consistent manner.
Pei Zhang, Donghai Zheng, Rogier van der Velde, Jun Wen, Yaoming Ma, Yijian Zeng, Xin Wang, Zuoliang Wang, Jiali Chen, and Zhongbo Su
Earth Syst. Sci. Data, 14, 5513–5542, https://doi.org/10.5194/essd-14-5513-2022, https://doi.org/10.5194/essd-14-5513-2022, 2022
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Soil moisture and soil temperature (SMST) are important state variables for quantifying the heat–water exchange between land and atmosphere. Yet, long-term, regional-scale in situ SMST measurements at multiple depths are scarce on the Tibetan Plateau (TP). The presented dataset would be valuable for the evaluation and improvement of long-term satellite- and model-based SMST products on the TP, enhancing the understanding of TP hydrometeorological processes and their response to climate change.
Hong Zhao, Yijian Zeng, Jan G. Hofste, Ting Duan, Jun Wen, and Zhongbo Su
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-333, https://doi.org/10.5194/hess-2022-333, 2022
Revised manuscript not accepted
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This paper demonstrated the capability of our developed platform for simulating microwave emission and backscatter signals at multi-frequency. The results of associated investigations on impacts of vegetation water (VW) and temperature (T) imply the need to first disentangle the impact of T for the use of high-frequency signals as its variation is more due to dynamic T. Estimated vegetation optical depth is frequency-dependent, while its diurnal variation depends on that of VW despite frequency.
Shaoning Lv, Clemens Simmer, Yijian Zeng, Jun Wen, Yuanyuan Guo, and Zhongbo Su
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-369, https://doi.org/10.5194/tc-2021-369, 2022
Preprint withdrawn
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The freeze-thaw of the ground is an interesting topic to climatology, hydrology, and other earth sciences. The global freeze-thaw distribution is available by passive microwave remote sensing technique. However, the remote sensing technique indirectly detects freeze-thaw states by measuring the brightness temperature difference between frozen and unfrozen soil. Thus, we present different interprets of the brightness signals to the FT-state by using its sub-daily character.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
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The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Mengna Li, Yijian Zeng, Maciek W. Lubczynski, Jean Roy, Lianyu Yu, Hui Qian, Zhenyu Li, Jie Chen, Lei Han, Han Zheng, Tom Veldkamp, Jeroen M. Schoorl, Harrie-Jan Hendricks Franssen, Kai Hou, Qiying Zhang, Panpan Xu, Fan Li, Kai Lu, Yulin Li, and Zhongbo Su
Earth Syst. Sci. Data, 13, 4727–4757, https://doi.org/10.5194/essd-13-4727-2021, https://doi.org/10.5194/essd-13-4727-2021, 2021
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The Tibetan Plateau is the source of most of Asia's major rivers and has been called the Asian Water Tower. Due to its remoteness and the harsh environment, there is a lack of field survey data to investigate its hydrogeology. Borehole core lithology analysis, an altitude survey, soil thickness measurement, hydrogeological surveys, and hydrogeophysical surveys were conducted in the Maqu catchment within the Yellow River source region to improve a full–picture understanding of the water cycle.
Hong-Yu Xie, Xiao-Wei Jiang, Shu-Cong Tan, Li Wan, Xu-Sheng Wang, Si-Hai Liang, and Yijian Zeng
Hydrol. Earth Syst. Sci., 25, 4243–4257, https://doi.org/10.5194/hess-25-4243-2021, https://doi.org/10.5194/hess-25-4243-2021, 2021
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Freezing-induced groundwater migration and water table decline are widely observed, but quantitative understanding of these processes is lacking. By considering wintertime atmospheric conditions and occurrence of lateral groundwater inflow, a model coupling soil water and groundwater reproduced field observations of soil temperature, soil water content, and groundwater level well. The model results led to a clear understanding of the balance of the water budget during the freezing–thawing cycle.
Cunbo Han, Yaoming Ma, Binbin Wang, Lei Zhong, Weiqiang Ma, Xuelong Chen, and Zhongbo Su
Earth Syst. Sci. Data, 13, 3513–3524, https://doi.org/10.5194/essd-13-3513-2021, https://doi.org/10.5194/essd-13-3513-2021, 2021
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Actual terrestrial evapotranspiration (ETa) is a key parameter controlling the land–atmosphere interaction processes and water cycle. However, the spatial distribution and temporal changes in ETa over the Tibetan Plateau (TP) remain very uncertain. Here we estimate the multiyear (2001–2018) monthly ETa and its spatial distribution on the TP by a combination of meteorological data and satellite products. Results have been validated at six eddy-covariance monitoring sites and show high accuracy.
Pei Zhang, Donghai Zheng, Rogier van der Velde, Jun Wen, Yijian Zeng, Xin Wang, Zuoliang Wang, Jiali Chen, and Zhongbo Su
Earth Syst. Sci. Data, 13, 3075–3102, https://doi.org/10.5194/essd-13-3075-2021, https://doi.org/10.5194/essd-13-3075-2021, 2021
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This paper reports on the status of the Tibet-Obs and presents a 10-year (2009–2019) surface soil moisture (SM) dataset produced based on in situ measurements taken at a depth of 5 cm collected from the Tibet-Obs. This surface SM dataset includes the original 15 min in situ measurements collected by multiple SM monitoring sites of three networks (i.e. the Maqu, Naqu, and Ngari networks) and the spatially upscaled SM records produced for the Maqu and Shiquanhe networks.
Jan G. Hofste, Rogier van der Velde, Jun Wen, Xin Wang, Zuoliang Wang, Donghai Zheng, Christiaan van der Tol, and Zhongbo Su
Earth Syst. Sci. Data, 13, 2819–2856, https://doi.org/10.5194/essd-13-2819-2021, https://doi.org/10.5194/essd-13-2819-2021, 2021
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The dataset reported in this paper concerns the measurement of microwave reflections from an alpine meadow over the Tibetan Plateau. These microwave reflections were measured continuously over 1 year. With it, variations in soil water content due to evaporation, precipitation, drainage, and soil freezing/thawing can be seen. A better understanding of the effects aforementioned processes have on microwave reflections may improve methods for estimating soil water content used by satellites.
Yunfei Wang, Yijian Zeng, Lianyu Yu, Peiqi Yang, Christiaan Van der Tol, Qiang Yu, Xiaoliang Lü, Huanjie Cai, and Zhongbo Su
Geosci. Model Dev., 14, 1379–1407, https://doi.org/10.5194/gmd-14-1379-2021, https://doi.org/10.5194/gmd-14-1379-2021, 2021
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This study integrates photosynthesis and transfer of energy, mass, and momentum in the soil–plant–atmosphere continuum system, via a simplified 1D root growth model. The results indicated that the simulation of land surface fluxes was significantly improved by considering the root water uptake, especially when vegetation was experiencing severe water stress. This finding highlights the importance of enhanced soil heat and moisture transfer in simulating ecosystem functioning.
María P. González-Dugo, Xuelong Chen, Ana Andreu, Elisabet Carpintero, Pedro J. Gómez-Giraldez, Arnaud Carrara, and Zhongbo Su
Hydrol. Earth Syst. Sci., 25, 755–768, https://doi.org/10.5194/hess-25-755-2021, https://doi.org/10.5194/hess-25-755-2021, 2021
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Drought is a devastating natural hazard and difficult to define, detect and quantify. Global meteorological data and remote-sensing products present new opportunities to characterize drought in an objective way. In this paper, we applied the surface energy balance model SEBS to estimate monthly evapotranspiration (ET) from 2001 to 2018 over the dehesa area of the Iberian Peninsula. ET anomalies were used to identify the main drought events and analyze their impacts on dehesa vegetation.
Rogier van der Velde, Andreas Colliander, Michiel Pezij, Harm-Jan F. Benninga, Rajat Bindlish, Steven K. Chan, Thomas J. Jackson, Dimmie M. D. Hendriks, Denie C. M. Augustijn, and Zhongbo Su
Hydrol. Earth Syst. Sci., 25, 473–495, https://doi.org/10.5194/hess-25-473-2021, https://doi.org/10.5194/hess-25-473-2021, 2021
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NASA’s SMAP satellite provides estimates of the amount of water in the soil. With measurements from a network of 20 monitoring stations, the accuracy of these estimates has been studied for a 4-year period. We found an agreement between satellite and in situ estimates in line with the mission requirements once the large mismatches associated with rapidly changing water contents, e.g. soil freezing and rainfall, are excluded.
Lianyu Yu, Simone Fatichi, Yijian Zeng, and Zhongbo Su
The Cryosphere, 14, 4653–4673, https://doi.org/10.5194/tc-14-4653-2020, https://doi.org/10.5194/tc-14-4653-2020, 2020
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The role of soil water and heat transfer physics in portraying the function of a cold region ecosystem was investigated. We found that explicitly considering the frozen soil physics and coupled water and heat transfer is important in mimicking soil hydrothermal dynamics. The presence of soil ice can alter the vegetation leaf onset date and deep leakage. Different complexity in representing vadose zone physics does not considerably affect interannual energy, water, and carbon fluxes.
Xu Yuan, Xiaolong Yu, and Zhongbo Su
Ocean Sci., 16, 1285–1296, https://doi.org/10.5194/os-16-1285-2020, https://doi.org/10.5194/os-16-1285-2020, 2020
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This work investigates the variabilities of the barrier layer thickness (BLT) in the tropical Indian Ocean with the Simple Ocean Data Assimilation version 3 ocean reanalysis data. Our results show that the seasonal variation of the BLT is in relation to the changes of thermocline and sea surface salinity. In terms of the interannual timescale, BLT presents a clear seasonal phase locking dominated by different drivers during the Indian Dipole and El Niño–Southern Oscillation events.
Lianyu Yu, Yijian Zeng, and Zhongbo Su
Hydrol. Earth Syst. Sci., 24, 4813–4830, https://doi.org/10.5194/hess-24-4813-2020, https://doi.org/10.5194/hess-24-4813-2020, 2020
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Soil mass and heat transfer processes were represented in three levels of model complexities to understand soil freeze–thaw mechanisms. Results indicate that coupled mass and heat transfer models considerably improved simulations of the soil hydrothermal regime. Vapor flow and thermal effects on water flow are the main mechanisms for the improvements. Given the explicit consideration of airflow, vapor flow and its effects on heat transfer were enhanced during the freeze–thaw transition period.
Cited articles
Barlett, P. A., MacKay, M. D., and Verseghy, D. L.: Modified snow algorithms
in the Canadian Land Surface Scheme: Model runs and sensitivity analysis at
three boreal forest stands, Atmos. Ocean, 44, 207–222,
https://doi.org/10.3137/ao.440301, 2006.
Barrere, M., Domine, F., Decharme, B., Morin, S., Vionnet, V., and Lafaysse, M.: Evaluating the performance of coupled snow–soil models in SURFEXv8 to simulate the permafrost thermal regime at a high Arctic site, Geosci. Model Dev., 10, 3461–3479, https://doi.org/10.5194/gmd-10-3461-2017, 2017.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Bittelli, M., Ventura, F., Campbell, G. S., Snyder, R. L., Gallegati, F.,
and Pisa, P. R.: Coupling of heat, water vapor, and liquid water fluxes to
compute evaporation in bare soils, J. Hydrol., 362, 191–205,
https://doi.org/10.1016/j.jhydrol.2008.08.014, 2008.
Boone, A., Samuelsson, P., Gollvik, S., Napoly, A., Jarlan, L., Brun, E., and Decharme, B.: The interactions between soil–biosphere–atmosphere land surface model with a multi-energy balance (ISBA-MEB) option in SURFEXv8 – Part 1: Model description, Geosci. Model Dev., 10, 843–872, https://doi.org/10.5194/gmd-10-843-2017, 2017.
Boone, A. A. and Etchevers, P.: An intercomparison of three snow schemes of
varying complexity coupled to the same land surface model: Local-scale
evaluation at an alpine site, J. Hydrometeorol., 2, 374-394,
https://doi.org/10.1175/1525-7541(2001)002<0374:AIOTSS>2.0.CO;2, 2001.
Che, T., Li, X., Liu, S., Li, H., Xu, Z., Tan, J., Zhang, Y., Ren, Z., Xiao, L., Deng, J., Jin, R., Ma, M., Wang, J., and Yang, X.: Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China, Earth Syst. Sci. Data, 11, 1483–1499, https://doi.org/10.5194/essd-11-1483-2019, 2019.
Cuntz, M. and Haverd, V.: Physically Accurate Soil Freeze-Thaw Processes in
a Global Land Surface Scheme, J. Adv. Model. Earth Sy.,
10, 54–77, https://doi.org/10.1002/2017ms001100, 2018.
Dall'Amico, M., Endrizzi, S., Gruber, S., and Rigon, R.: A robust and energy-conserving model of freezing variably-saturated soil, The Cryosphere, 5, 469–484, https://doi.org/10.5194/tc-5-469-2011, 2011.
Decharme, B., Brun, E., Boone, A., Delire, C., Le Moigne, P., and Morin, S.: Impacts of snow and organic soils parameterization on northern Eurasian soil temperature profiles simulated by the ISBA land surface model, The Cryosphere, 10, 853–877, https://doi.org/10.5194/tc-10-853-2016, 2016.
Dente, L., Vekerdy, Z., Wen, J., and Su, Z.: Maqu network for validation of
satellite-derived soil moisture products, Int. J. Appl. Earth Obs. Geoinf., 17,
55–65, https://doi.org/10.1016/j.jag.2011.11.004, 2012.
De Vries, D. A.: Simultaneous transfer of heat and moisture in porous media,
Eos T. Am. Geophys. Un. 39, 909–916,
https://doi.org/10.1029/TR039i005p00909, 1958.
Dickinson, R. E., Henderson-Sellers, A., and Kennedy, P. J.:
Biosphere-atmosphere Transfer Scheme (BATS) Version 1e as Coupled to the
NCAR Community Climate Model (No. NCAR/TN-387+STR), University Corporation
for Atmospheric Research, 1993.
Ding, B., Yang, K., Qin, J., Wang, L., Chen, Y., and He, X.: The dependence
of precipitation types on surface elevation and meteorological conditions
and its parameterization, J. Hydrol., 513, 154–163,
https://doi.org/10.1016/j.jhydrol.2014.03.038, 2014.
Ding, B., Yang, K., Yang, W., He, X., Chen, Y., Lazhu, Guo, X., Wang, L.,
Wu, H., and Yao, T.: Development of a Water and Enthalpy Budget-based
Glacier mass balance Model (WEB-GM) and its preliminary validation, Water
Resour. Res., 53, 3146–3178, https://doi.org/10.1002/2016WR018865, 2017.
Domine, F., Picard, G., Morin, S., Barrere, M., Madore, J.-B., and Langlois,
A.: Major Issues in Simulating Some Arctic Snowpack Properties Using Current
Detailed Snow Physics Models: Consequences for the Thermal Regime and Water
Budget of Permafrost, J. Adv. Model. Earth Sy., 11,
34–44, https://doi.org/10.1029/2018ms001445, 2019.
Douville, H., Royer, J. F., and Mahfouf, J. F.: A new snow parameterization
for the Météo-France climate model, Clim. Dynam., 12, 21–35,
https://doi.org/10.1007/BF00208760, 1995.
Dutra, E., Balsamo, G., Viterbo, P., Miranda, P. M. A., Beljaars, A., Schar,
C., and Elder, K.: An improved snow scheme for the ECMWF land surface model:
Description and offline validation, J. Hydrometeorol., 11, 899–916,
https://doi.org/10.1175/2010JHM1249.1, 2010.
Dutra, E., Viterbo, P., Miranda, P. M. A., and Balsamo, G.: Complexity of
snow schemes in a climate model and its impact on surface energy and
hydrology, J. Hydrometeorol., 13, 521–538,
https://doi.org/10.1175/JHM-D-11-072.1, 2012.
Ekici, A., Beer, C., Hagemann, S., Boike, J., Langer, M., and Hauck, C.: Simulating high-latitude permafrost regions by the JSBACH terrestrial ecosystem model, Geosci. Model Dev., 7, 631–647, https://doi.org/10.5194/gmd-7-631-2014, 2014.
Etchevers, P., Martin, E., Brown, R., Fierz, C., Lejeune, Y., Bazile, E.,
Boone, A., Dai, Y.-J., Essery, R., Fernandez, A., Gusev, Y., Jordan, R.,
Koren, V., Kowalczyk, E., Nasonova, N. O., Pyles, R. D., Schlosser, A.,
Shmakin, A. B., Smirnova, T. G., Strasser, U., Verseghy, D., Yamazaki, T.,
and Yang, Z.-L.: Validation of the energy budget of an alpine snowpack
simulated by several snow models (SnowMIP project), Ann. Glaciol., 38,
150–158, https://doi.org/10.3189/172756404781814825, 2004.
Flerchinger, G. N.: The Simultaneous Heat and Water (SHAW) Model: Technical Documentation Version 3.0, Northwest Watershed Research Center, USDA Agricultural Research Service, Boise, Idaho, USA, Technical Rep., 43 pp., 2017.
Flerchinger, G. N. and Saxton, K. E.: Simultaneous heat and water model of
a freezing snow-residue-soil system. I. Theory and development, T.
Am. Soc. Agr. Eng., 32, 565–571, 1989.
Gardiner, M. J., Ellis-Evans, J. C., Anderson, M. G., and Tranter, M.:
Snowmelt modelling on Signy Island, South Orkney Islands, Ann. Glaciol., 26,
161–166, https://doi.org/10.3189/1998aog26-1-161-166, 1998.
Gichamo, T. Z. and Tarboton, D. G.: Ensemble Streamflow Forecasting Using
an Energy Balance Snowmelt Model Coupled to a Distributed Hydrologic Model
with Assimilation of Snow and Streamflow Observations, Water Resour. Res., 55,
10813–10838, https://doi.org/10.1029/2019wr025472, 2019.
Günther, D., Marke, T., Essery, R., and Strasser, U.: Uncertainties in
Snowpack Simulations – Assessing the Impact of Model Structure, Parameter
Choice, and Forcing Data Error on Point-Scale Energy Balance Snow Model
Performance, Water Resour. Res., 55, 2779–2800,
https://doi.org/10.1029/2018wr023403, 2019.
Gusev, Y. M. and Nasonova, O. N.: The simulation of heat and water exchange
in the boreal spruce forest by the land-surf ace model SWAP, J. Hydrol., 280,
162–191, https://doi.org/10.1016/S0022-1694(03)00221-X, 2003.
Hagedorn, B., Sletten, R. S., and Hallet, B.: Sublimation and ice
condensation in hyperarid soils: Modeling results using field data from
Victoria Valley, Antarctica, J. Geophys. Res.-Earth,
112, F03017, https://doi.org/10.1029/2006jf000580, 2007.
Hansson, K., Šimůnek, J., Mizoguchi, M., Lundin, L. C., and van
Genuchten, M. T.: Water flow and heat transport in frozen soil: Numerical
solution and freeze-thaw applications, Vadose Zone J., 3, 693–704, 2004.
Harder, P. and Pomeroy, J. W.: Hydrological model uncertainty due to
precipitation-phase partitioning methods, Hydrol. Process., 28, 4311–4327,
https://doi.org/10.1002/hyp.10214, 2014.
Hrbáček, F., Láska, K., and Engel, Z.: Effect of snow cover on
the active-layer thermal regime – a case study from James Ross island,
Antarctic Peninsula, Permafrost Periglac., 27, 307–315, 2016.
Iwata, Y., Hayashi, M., Suzuki, S., Hirota, T., and Hasegawa, S.: Effects of
snow cover on soil freezing, water movement, and snowmelt infiltration: A
paired plot experiment, Water Resour. Res., 46, W09504,
https://doi.org/10.1029/2009WR008070, 2010.
Jambon-Puillet, E., Shahidzadeh, N., and Bonn, D.: Singular sublimation of
ice and snow crystals, Nat. Commun., 9, 4191,
https://doi.org/10.1038/s41467-018-06689-x, 2018.
Jansson, P. E.: CoupModel: Model Use, Calibration, and Validation, T. ASABE, 55, 1337,
https://doi.org/10.13031/2013.42245, 2012.
Jordan, R.: A one-dimensional temperature model for a snow cover: Technical
documentation for SNTHERM. 89, Cold Regions Research and Engineering Lab
Hanover NH, 1991.
Koren, V., Schaake, J., Mitchell, K., Duan, Q. Y., Chen, F., and Baker, J.
M.: A parameterization of snowpack and frozen ground intended for NCEP
weather and climate models, J. Geophys. Res.-Atmos.,
104, 19569–19585, https://doi.org/10.1029/1999JD900232, 1999.
Lawrence, D. M., Fisher, R. A., Koven, C. D., Oleson, K. W., Swenson, S. C.,
Bonan, G., Collier, N., Ghimire, B., van Kampenhout, L., Kennedy, D.,
Kluzek, E., Lawrence, P. J., Li, F., Li, H., Lombardozzi, D., Riley, W. J.,
Sacks, W. J., Shi, M., Vertenstein, M., Wieder, W. R., Xu, C., Ali, A. A.,
Badger, A. M., Bisht, G., van den Broeke, M., Brunke, M. A., Burns, S. P.,
Buzan, J., Clark, M., Craig, A., Dahlin, K., Drewniak, B., Fisher, J. B.,
Flanner, M., Fox, A. M., Gentine, P., Hoffman, F., Keppel-Aleks, G., Knox,
R., Kumar, S., Lenaerts, J., Leung, L. R., Lipscomb, W. H., Lu, Y., Pandey,
A., Pelletier, J. D., Perket, J., Randerson, J. T., Ricciuto, D. M.,
Sanderson, B. M., Slater, A., Subin, Z. M., Tang, J., Thomas, R. Q., Val
Martin, M., and Zeng, X.: The Community Land Model Version 5: Description of
New Features, Benchmarking, and Impact of Forcing Uncertainty, J. Adv. Model.
Earth Sy., 11, 4245–4287, https://doi.org/10.1029/2018MS001583, 2019.
Lehning, M., Bartelt, P., Brown, B., Russi, T., Stöckli, U., and
Zimmerli, M.: SNOWPACK model calculations for avalanche warning based upon a
new network of weather and snow stations, Cold Reg. Sci. Technol., 30,
145–157, https://doi.org/10.1016/S0165-232X(99)00022-1, 1999.
Leroux, N. R. and Pomeroy, J. W.: Modelling capillary hysteresis effects on
preferential flow through melting and cold layered snowpacks, Adv. Water
Resour., 107, 250–264, https://doi.org/10.1016/j.advwatres.2017.06.024, 2017.
Li, D., Wen, L., Long, X., and Chen, S.: Observation Study on Effects of
Snow Cover on Local Micro Meteorological Characteristics in Maqu, Plateau
Meteorol., 36, 330–339,
https://doi.org/10.7522/j.issn.1000-0534.2016.00074, 2017.
Li, H., Li, X., Yang, D., Wang, J., Gao, B., Pan, X., Zhang, Y., and Hao,
X.: Tracing Snowmelt Paths in an Integrated Hydrological Model for
Understanding Seasonal Snowmelt Contribution at Basin Scale, J.
Geophys. Res.-Atmos., 124, 8874–8895,
https://doi.org/10.1029/2019JD030760, 2019.
Li, X.: Integrated hydrometeorological – snow – frozen ground observations
in the alpine region of the Heihe River Basin, China, Cold and Arid Regions
Science Data Center at Lanzhou (CARD) [data set],
https://doi.org/10.3972/hiwater.001.2019.db, 2019.
Mahat, V. and Tarboton, D. G.: Representation of canopy snow interception, unloading and melt in a parsimonious snowmelt model, Hydrol. Process., 28, 6320–6336, https://doi.org/10.1002/hyp.10116, 2014.
Milly, P. C. D.: Moisture and heat transport in hysteretic, inhomogeneous
porous media: A matric head-based formulation and a numerical model, Water
Resour. Res., 18, 489–498, https://doi.org/10.1029/WR018i003p00489, 1982.
Mualem, Y.: A new model for predicting the hydraulic conductivity of
unsaturated porous media, Water Resour. Res., 12, 513–522,
https://doi.org/10.1029/WR012i003p00513, 1976.
Niu, G. Y., Yang, Z. L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M.,
Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, M., and Xia, Y.: The
community Noah land surface model with multiparameterization options
(Noah-MP): 1. Model description and evaluation with local-scale
measurements, J. Geophys. Res.-Atmos., 116, D12109,
https://doi.org/10.1029/2010JD015139, 2011.
Painter, S. L., Coon, E. T., Atchley, A. L., Berndt, M., Garimella, R.,
Moulton, J. D., Svyatskiy, D., and Wilson, C. J.: Integrated
surface/subsurface permafrost thermal hydrology: Model formulation and
proof-of-concept simulations, Water Resour. Res., 52, 6062–6077,
https://doi.org/10.1002/2015WR018427, 2016.
Pan, X., Helgason, W., Ireson, A., and Wheater, H.: Field-scale water
balance closure in seasonally frozen conditions, Hydrol Earth Syst Sci, 21,
5401-5413, https://doi.org/10.5194/hess-21-5401-2017, 2017.
Pimentel, R., Herrero, J., Zeng, Y., Su, Z., and Polo, M. J.: Study of Snow
Dynamics at Subgrid Scale in Semiarid Environments Combining Terrestrial
Photography and Data Assimilation Techniques, J. Hydrometeorol., 16, 563–578,
https://doi.org/10.1175/jhm-d-14-0046.1, 2015.
Pitman, A. J., Yang, Z.-L., Cogley, J. G., and Henderson-Sellers, A.:
Description of bare essentials of surface transfer for the Bureau of
Meteorology Research Centre AGCM, Macquarie University, North Ryde, NSW, Australia, BMRC Res. Rep., 117 pp., 1991.
Prunty, L. and Bell, J.: Infiltration rate vs. gas composition and pressure
in soil columns, Soil Sci. Soc. Am. J., 71, 1473–1475,
https://doi.org/10.2136/sssaj2007.0072N, 2007.
Richards, L. A.: Capillary Conduction of Liquids Through Porous Mediums,
Physics, 1, 318–333, https://doi.org/10.1063/1.1745010, 1931.
Rutter, N., Essery, R., Pomeroy, J., Altimir, N., Andreadis, K., Baker, I.,
Barr, A., Bartlett, P., Boone, A., Deng, H., Douville, H., Dutra, E., Elder,
K., Ellis, C., Feng, X., Gelfan, A., Goodbody, A., Gusev, Y., Gustafsson,
D., Hellström, R., Hirabayashi, Y., Hirota, T., Jonas, T., Koren, V.,
Kuragina, A., Lettenmaier, D., Li, W.-P., Luce, C., Martin, E., Nasonova,
O., Pumpanen, J., Pyles, R. D., Samuelsson, P., Sandells, M., Schädler,
G., Shmakin, A., Smirnova, T. G., Stähli, M., Stöckli, R., Strasser,
U., Su, H., Suzuki, K., Takata, K., Tanaka, K., Thompson, E., Vesala, T.,
Viterbo, P., Wiltshire, A., Xia, K., Xue, Y., and Yamazaki, T.: Evaluation
of forest snow processes models (SnowMIP2), J. Geophys. Res.-Atmos., 114, D06111, https://doi.org/10.1029/2008JD011063, 2009.
Scanlon, B. R. and Milly, P. C. D.: Water and heat fluxes in desert soils:
2. Numerical simulations, Water Resour. Res., 30, 721–733,
https://doi.org/10.1029/93WR03252, 1994.
Schulz, O. and de Jong, C.: Snowmelt and sublimation: field experiments and modelling in the High Atlas Mountains of Morocco, Hydrol. Earth Syst. Sci., 8, 1076–1089, https://doi.org/10.5194/hess-8-1076-2004, 2004.
Shrestha, M., Wang, L., Koike, T., Xue, Y., and Hirabayashi, Y.: Improving the snow physics of WEB-DHM and its point evaluation at the SnowMIP sites, Hydrol. Earth Syst. Sci., 14, 2577–2594, https://doi.org/10.5194/hess-14-2577-2010, 2010.
Šimůnek, J., Šejna, M., Saito, H., Sakai, M., and Van Genuchten,
M.: The HYDRUS-1D Software Package for Simulating the One-Dimensional
Movement of Water, Heat, and Multiple Solutes in Variably-Saturated Media, University of California Riverside, Riverside, California, USA, 330 pp.,
2008.
Slater, A. G., Pitman, A. J., and Desborough, C. E.: The validation of a
snow parameterization designed for use in general circulation models, Int. J.
Climatol., 18, 595–617,
https://doi.org/10.1002/(sici)1097-0088(199805)18:6<595::aid-joc275>3.0.co;2-o, 1998.
Strasser, U., Bernhardt, M., Weber, M., Liston, G. E., and Mauser, W.: Is snow sublimation important in the alpine water balance?, The Cryosphere, 2, 53–66, https://doi.org/10.5194/tc-2-53-2008, 2008.
Su, Z., Wen, J., Dente, L., van der Velde, R., Wang, L., Ma, Y., Yang, K., and Hu, Z.: The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) for quantifying uncertainties in coarse resolution satellite and model products, Hydrol. Earth Syst. Sci., 15, 2303–2316, https://doi.org/10.5194/hess-15-2303-2011, 2011.
Su, Z., De Rosnay, P., Wen, J., Wang, L., and Zeng, Y.: Evaluation of
ECMWF's soil moisture analyses using observations on the Tibetan Plateau,
J. Geophys. Res.-Atmos., 118, 5304–5318,
https://doi.org/10.1002/jgrd.50468, 2013.
Sud, Y. C. and Mocko, D. M.: New Snow-Physics to Complement SSiB Part I:
Design and Evaluation with ISLSCP Initiative I Datasets, J.
Meteorol. Soc. Jpn. Ser. II, 77, 335–348,
https://doi.org/10.2151/jmsj1965.77.1B_335, 1999.
Sultana, R., Hsu, K.-L., Li, J., and Sorooshian, S.: Evaluating the Utah Energy Balance (UEB) snow model in the Noah land-surface model, Hydrol. Earth Syst. Sci., 18, 3553–3570, https://doi.org/10.5194/hess-18-3553-2014, 2014.
Sun, S., Jin, J., and Xue, Y.: A simple snow-atmosphere-soil transfer model,
J. Geophys. Res.-Atmos., 104, 19587–19597,
https://doi.org/10.1029/1999jd900305, 1999.
Swenson, S. C., Lawrence, D. M., and Lee, H.: Improved simulation of the
terrestrial hydrological cycle in permafrost regions by the Community Land
Model, J. Adv. Model. Earth Sy., 4, M08002,
https://doi.org/10.1029/2012MS000165, 2012.
Tarboton, D. G. and Luce, C. H.: Utah Energy Balance Snow Accumulation and
Melt Model (UEB), Computer model technical description and users guide, Utah
Water Research Laboratory and USDA Forest Service Intermountain Research
Station, Logan, Utah, USA, Rep., 64 pp., 1996.
Touma, J. and Vauclin, M.: Experimental and numerical analysis of two-phase
infiltration in a partially saturated soil, Transp. Porous Media, 1,
27–55, https://doi.org/10.1007/BF01036524, 1986.
Ueno, K., Tanaka, K., Tsutsui, H., and Li, M.: Snow Cover Conditions in the
Tibetan Plateau Observed during the Winter of 2003/2004, Arct. Antarct.
Alp. Res., 39, 152–164,
https://doi.org/10.1657/1523-0430(2007)39[152:SCCITT]2.0.CO;2, 2007.
Ueno, K., Sugimoto, S., Tsutsui, H., Taniguchi, K., Hu, Z., and Wu, S.: Role
of patchy snow cover on the planetary boundary layer structure during late
winter observed in the central Tibetan Plateau, J.
Meteorol. Soc. Jpn. Ser. II, 90, 145–155, 2012.
van Genuchten, M. T.: A closed-form equation for predicting the hydraulic
conductivity of unsaturated soils, Soil Sci. Soc. Am. J., 44, 892–898,
https://doi.org/10.2136/SSSAJ1980.03615995004400050002X, 1980.
Verseghy, D. L.: Class – A Canadian land surface scheme for GCMS. I. Soil
model, Int. J. Climatol., 11, 111–133, https://doi.org/10.1002/joc.3370110202,
1991.
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Martin, E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791, https://doi.org/10.5194/gmd-5-773-2012, 2012.
Wang, L., Koike, T., Yang, D., and Yang, K.: Improving the hydrology of the
Simple Biosphere Model 2 and its evaluation within the framework of a
distributed hydrological model, Hydrol. Sci. J., 54, 989–1006,
https://doi.org/10.1623/hysj.54.6.989, 2009.
Wang, L., Zhou, J., Qi, J., Sun, L., Yang, K., Tian, L., Lin, Y., Liu, W.,
Shrestha, M., Xue, Y., Koike, T., Ma, Y., Li, X., Chen, Y., Chen, D., Piao,
S., and Lu, H.: Development of a land surface model with coupled snow and
frozen soil physics, Water Resour. Res., 53, 5085–5103,
https://doi.org/10.1002/2017WR020451, 2017.
Wang, T., Ottlé, C., Boone, A., Ciais, P., Brun, E., Morin, S., Krinner,
G., Piao, S., and Peng, S.: Evaluation of an improved intermediate
complexity snow scheme in the ORCHIDEE land surface model, J.
Geophys. Res.-Atmos., 118, 6064–6079,
https://doi.org/10.1002/jgrd.50395, 2013.
Wang, Y., Zeng, Y., Yu, L., Yang, P., Van der Tol, C., Yu, Q., Lü, X., Cai, H., and Su, Z.: Integrated modeling of canopy photosynthesis, fluorescence, and the transfer of energy, mass, and momentum in the soil–plant–atmosphere continuum (STEMMUS–SCOPE v1.0.0), Geosci. Model Dev., 14, 1379–1407, https://doi.org/10.5194/gmd-14-1379-2021, 2021.
Watson, F. G. R., Newman, W. B., Coughlan, J. C., and Garrott, R. A.:
Testing a distributed snowpack simulation model against spatial
observations, J. Hydrol., 328, 453–466,
https://doi.org/10.1016/j.jhydrol.2005.12.012, 2006.
Wicky, J. and Hauck, C.: Numerical modelling of convective heat transport by air flow in permafrost talus slopes, The Cryosphere, 11, 1311–1325, https://doi.org/10.5194/tc-11-1311-2017, 2017.
Yang, Z.-L., Dickinson, R. E., Robock, A., and Vinnikov, K. Y.: Validation
of the Snow Submodel of the Biosphere–Atmosphere Transfer Scheme with
Russian Snow Cover and Meteorological Observational Data, J. Climate, 10,
353–373, https://doi.org/10.1175/1520-0442(1997)010<0353:votsso>2.0.co;2, 1997.
Yi, Y., Kimball, J. S., Rawlins, M. A., Moghaddam, M., and Euskirchen, E. S.: The role of snow cover affecting boreal-arctic soil freeze–thaw and carbon dynamics, Biogeosciences, 12, 5811–5829, https://doi.org/10.5194/bg-12-5811-2015, 2015.
You, Y., Meng, H., Dong, J., and Rudlosky, S.: Time-Lag Correlation Between
Passive Microwave Measurements and Surface Precipitation and Its Impact on
Precipitation Retrieval Evaluation, Geophys. Res. Lett., 46, 8415–8423,
https://doi.org/10.1029/2019gl083426, 2019.
Yu, L., Zeng, Y., Su, Z., Cai, H., and Zheng, Z.: The effect of different evapotranspiration methods on portraying soil water dynamics and ET partitioning in a semi-arid environment in Northwest China, Hydrol. Earth Syst. Sci., 20, 975–990, https://doi.org/10.5194/hess-20-975-2016, 2016.
Yu, L., Zeng, Y., Wen, J., and Su, Z.: Liquid-Vapor-Air Flow in the Frozen
Soil, J. Geophys. Res.-Atmos., 123, 7393–7415,
https://doi.org/10.1029/2018jd028502, 2018a.
Yu, L., Zeng, Y., Su, Z., and Wen, J.: HydroThermal Dynamics of Frozen Soils on the Tibetan Plateau during 2015–2016, 4TU.ResearchData [data set], https://doi.org/10.4121/uuid:cc69b7f2-2448-4379-b638-09327012ce9b, 2018b.
Yu, L., Fatichi, S., Zeng, Y., and Su, Z.: The role of vadose zone physics in the ecohydrological response of a Tibetan meadow to freeze–thaw cycles, The Cryosphere, 14, 4653–4673, https://doi.org/10.5194/tc-14-4653-2020, 2020a.
Yu, L., Zeng, Y., and Su, Z.: STEMMUS-UEB v1.0: Integrated Modeling of
Snowpack and Soil Mass and Energy Transfer with Three Levels of Soil
Physical Process Complexities, Zenodo [code],
https://doi.org/10.5281/zenodo.3975846, 2020b.
Yu, L., Zeng, Y., and Su, Z.: Understanding the mass, momentum, and energy transfer in the frozen soil with three levels of model complexities, Hydrol. Earth Syst. Sci., 24, 4813–4830, https://doi.org/10.5194/hess-24-4813-2020, 2020c.
Zeng, Y. and Su, Z.: STEMMUS source code, GitHub [code], available at: https://github.com/yijianzeng/STEMMUS, last access: 11 December 2020.
Zeng, Y., Su, Z., Wan, L., Yang, Z., Zhang, T., Tian, H., Shi, X., Wang, X., and Cao, W.: Diurnal pattern of the drying front in desert and its application for determining the effective infiltration, Hydrol. Earth Syst. Sci., 13, 703–714, https://doi.org/10.5194/hess-13-703-2009, 2009a.
Zeng, Y., Wan, L., Su, Z., Saito, H., Huang, K., and Wang, X.: Diurnal soil
water dynamics in the shallow vadose zone (field site of China University of
Geosciences, China), Environ. Geol., 58, 11–23,
https://doi.org/10.1007/s00254-008-1485-8, 2009b.
Zeng, Y., Su, Z., Wan, L., and Wen, J.: Numerical analysis of air-water-heat
flow in unsaturated soil: Is it necessary to consider airflow in land
surface models?, J. Geophys. Res.-Atmos., 116, D20107,
https://doi.org/10.1029/2011JD015835, 2011a.
Zeng, Y., Su, Z., Wan, L., and Wen, J.: A simulation analysis of the
advective effect on evaporation using a two-phase heat and mass flow model,
Water Resour. Res., 47, W10529, https://doi.org/10.1029/2011WR010701, 2011b.
Zeng, Y., Su, Z., van der Velde, R., Wang, L., Xu, K., Wang, X., and Wen,
J.: Blending Satellite Observed, Model Simulated, and in Situ Measured Soil
Moisture over Tibetan Plateau, Remote Sensing, 8, 268, https://doi.org/10.3390/rs8030268, 2016.
Zeng, Y. J. and Su, Z. B.: STEMMUS: Simultaneous Transfer of Engery, Mass
and Momentum in Unsaturated Soil,University of
Twente, Faculty of Geo-Information and Earth Observation (ITC), Enschede, ISBN: 978-90-6164-351-7,
2013.
Zhang, T.: Influence of the seasonal snow cover on the ground thermal
regime: An overview, Rev. Geophys., 43, RG4002,
https://doi.org/10.1029/2004rg000157, 2005.
Zhao, H., Zeng, Y., Lv, S., and Su, Z.: Analysis of soil hydraulic and thermal properties for land surface modeling over the Tibetan Plateau, Earth Syst. Sci. Data, 10, 1031–1061, https://doi.org/10.5194/essd-10-1031-2018, 2018a.
Zhao, H., Zeng, Y., and Su, Z.: Soil Hydraulic and Thermal Properties for Land Surface Modelling over the Tibetan Plateau, 4TU.ResearchData [data set], https://doi.org/10.4121/uuid:c712717c-6ac0-47ff-9d58-97f88082ddc0, 2018b.
Zheng, D., Van der Velde, R., Su, Z., Wang, X., Wen, J., Booij, M. J.,
Hoekstra, A. Y., and Chen, Y.: Augmentations to the Noah Model Physics for
Application to the Yellow River Source Area. Part I: Soil Water Flow, J.
Hydrometeorol., 16, 2659–2676, https://doi.org/10.1175/JHM-D-14-0198.1, 2015.
Short summary
We developed an integrated soil–snow–atmosphere model (STEMMUS-UEB) dedicated to the physical description of snow and soil processes with various complexities. With STEMMUS-UEB, we demonstrated that the snowpack affects not only the soil surface moisture conditions (in the liquid and ice phase) and energy-related states (albedo, LE) but also the subsurface soil water and vapor transfer, which contributes to a better understanding of the hydrothermal implications of the snowpack in cold regions.
We developed an integrated soil–snow–atmosphere model (STEMMUS-UEB) dedicated to the physical...