Articles | Volume 27, issue 7
https://doi.org/10.5194/hess-27-1583-2023
© Author(s) 2023. 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-27-1583-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Apr 2023
Research article |
| 17 Apr 2023
| 17 Apr 2023
Improving regional climate simulations based on a hybrid data assimilation and machine learning method
Xinlei He
State Key Laboratory of Earth Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, China
Yanping Li
School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK, Canada
Shaomin Liu
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, China
Tongren Xu
State Key Laboratory of Earth Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, China
Fei Chen
National Center for Atmospheric Research, Boulder, CO, USA
Zhenhua Li
School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK, Canada
Zhe Zhang
School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK, Canada
Rui Liu
Institute of Urban Study, School of Environmental and Geographical
Sciences (SEGS), Shanghai Normal University, Shanghai, China
Lisheng Song
School of Geography and Tourism, Anhui Normal University, Wuhu, China
Ziwei Xu
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, China
Zhixing Peng
State Key Laboratory of Earth Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, China
Chen Zheng
Institute of Geographic Sciences and Natural Resources Research,
Chinese Academy of Sciences, Beijing, China
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business-as-usualclimate scenario. Changes in large-scale atmospheric circulation and extent of warming vary with season, and these generally lead to increases, especially after mid-century, in factors associated with winter snowstorms, freezing rain, drought, forest fires, as well as atmospheric forcing of spring floods, although not necessarily summer convection.
Zhenhua Li, Yanping Li, Barrie Bonsal, Alan H. Manson, and Lucia Scaff
Hydrol. Earth Syst. Sci., 22, 5057–5067, https://doi.org/10.5194/hess-22-5057-2018, https://doi.org/10.5194/hess-22-5057-2018, 2018
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The research started by investigating the 2015 growing season drought over the Canadian Prairies and evolved into investigating the connection between growing season rain deficit in the Prairies and MJO (20–90 days tropical oscillation in convective storms). With warm central Pacific sea surface temperature, strong MJOs in the western Pacific cause Rossby wave trains that propagate downstream and favour upper-level ridges and rain deficits over the Canadian Prairies during the growing season.
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Snow albedo plays a key role in the Earth and climate system. It can be affected by impurities and snow properties. This study implements new parameterizations into a widely used snow model to account for effects of snow shape and black carbon–snow mixing state on snow albedo reduction in the Tibetan Plateau. This study points toward an imperative need for extensive measurements and improved model characterization of snow grain shape and aerosol–snow mixing state in Tibet and elsewhere.
Feinan Xu, Weizhen Wang, Jiemin Wang, Ziwei Xu, Yuan Qi, and Yueru Wu
Hydrol. Earth Syst. Sci., 21, 4037–4051, https://doi.org/10.5194/hess-21-4037-2017, https://doi.org/10.5194/hess-21-4037-2017, 2017
Xicai Pan, Daqing Yang, Yanping Li, Alan Barr, Warren Helgason, Masaki Hayashi, Philip Marsh, John Pomeroy, and Richard J. Janowicz
The Cryosphere, 10, 2347–2360, https://doi.org/10.5194/tc-10-2347-2016, https://doi.org/10.5194/tc-10-2347-2016, 2016
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This study demonstrates a robust procedure for accumulating precipitation gauge measurements and provides an analysis of bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada. It highlights the need for and importance of precipitation bias corrections at both research sites and operational networks for water balance assessment and the validation of global/regional climate–hydrology models.
Xicai Pan, Yanping Li, Qihao Yu, Xiaogang Shi, Daqing Yang, and Kurt Roth
The Cryosphere, 10, 1591–1603, https://doi.org/10.5194/tc-10-1591-2016, https://doi.org/10.5194/tc-10-1591-2016, 2016
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Using a 9-year dataset in conjunction with a process-based model, we verify that the common assumption of a considerably smaller thermal conductivity in the thawed season than the frozen season is not valid at a site with a stratified active layer on the Qinghai–Tibet Plateau (QTP). The unique hydraulic and thermal mechanism in the active layer challenges the concept of thermal offset used in conceptual permafrost models and hints at the reason for rapid permafrost warming on the QTP.
Liang Chen, Yanping Li, Fei Chen, Alan Barr, Michael Barlage, and Bingcheng Wan
Atmos. Chem. Phys., 16, 8375–8387, https://doi.org/10.5194/acp-16-8375-2016, https://doi.org/10.5194/acp-16-8375-2016, 2016
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This work is the first time that Noah-MP is used to investigate the impact of parameterizing organic soil at a boreal forest site. Including an organic soil parameterization significantly improved performance of the model in surface energy and hydrology simulations due to the lower thermal conductivity and greater porosity of the organic soil. It substantially modified the partition between direct soil evaporation and vegetation transpiration in the simulation.
Wenjun Tang, Jun Qin, Kun Yang, Shaomin Liu, Ning Lu, and Xiaolei Niu
Atmos. Chem. Phys., 16, 2543–2557, https://doi.org/10.5194/acp-16-2543-2016, https://doi.org/10.5194/acp-16-2543-2016, 2016
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In this paper, we develop a new method to quickly retrieve high-resolution surface solar radiation (SSR) over China by combining MODIS and MTSAT data. The RMSEs of the retrieved SSR at hourly, daily, and monthly scales are about 98.5, 34.2, and 22.1 W m−2. The accuracy is comparable to or even higher than other two satellite radiation products. Finally, we derive an 8-year high-resolution SSR data set (hourly, 5 km) from 2007 to 2014, which would contribute to studies of land surface processes.
X. Cai, Z.-L. Yang, J. B. Fisher, X. Zhang, M. Barlage, and F. Chen
Geosci. Model Dev., 9, 1–15, https://doi.org/10.5194/gmd-9-1-2016, https://doi.org/10.5194/gmd-9-1-2016, 2016
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A terrestrial nitrogen dynamics model is integrated into Noah-MP. The new model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). The addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. This improvement advances the capability of Noah-MP to simultaneously predict weather and water quality.
L. Scaff, D. Yang, Y. Li, and E. Mekis
The Cryosphere, 9, 2417–2428, https://doi.org/10.5194/tc-9-2417-2015, https://doi.org/10.5194/tc-9-2417-2015, 2015
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The bias corrections show significant errors in the gauge precipitation measurements over the northern regions. Monthly precipitation is closely correlated between the stations across the Alaska--Yukon border, particularly for the warm months. Double mass curves indicate changes in the cumulative precipitation due to bias corrections over the study period. Overall the bias corrections lead to a smaller and inverted precipitation gradient across the border, especially for snowfall.
X. Chen, Z. Su, Y. Ma, S. Liu, Q. Yu, and Z. Xu
Atmos. Chem. Phys., 14, 13097–13117, https://doi.org/10.5194/acp-14-13097-2014, https://doi.org/10.5194/acp-14-13097-2014, 2014
T. R. Xu, S. M. Liu, Z. W. Xu, S. Liang, and L. Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-3927-2013, https://doi.org/10.5194/hessd-10-3927-2013, 2013
Preprint withdrawn
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Jesús Sánchez-Dávila, Miquel De Cáceres, Jordi Vayreda, and Javier Retana
Hydrol. Earth Syst. Sci., 28, 3037–3050, https://doi.org/10.5194/hess-28-3037-2024, https://doi.org/10.5194/hess-28-3037-2024, 2024
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Forest blue water is determined by the climate, functional traits, and stand structure variables. The leaf area index (LAI) is the main driver of the trade-off between the blue and green water. Blue water is concentrated in the autumn–winter season, and deciduous trees can increase the relative blue water. The leaf phenology and seasonal distribution are determinants for the relative blue water.
Barry van Jaarsveld, Sandra M. Hauswirth, and Niko Wanders
Hydrol. Earth Syst. Sci., 28, 2357–2374, https://doi.org/10.5194/hess-28-2357-2024, https://doi.org/10.5194/hess-28-2357-2024, 2024
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Drought often manifests itself in vegetation; however, obtaining high-resolution remote-sensing products that are spatially and temporally consistent is difficult. In this study, we show that machine learning (ML) can fill data gaps in existing products. We also demonstrate that ML can be used as a downscaling tool. By relying on ML for gap filling and downscaling, we can obtain a more holistic view of the impacts of drought on vegetation.
Nicholas K. Corak, Jason A. Otkin, Trent W. Ford, and Lauren E. L. Lowman
Hydrol. Earth Syst. Sci., 28, 1827–1851, https://doi.org/10.5194/hess-28-1827-2024, https://doi.org/10.5194/hess-28-1827-2024, 2024
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We simulate how dynamic vegetation interacts with the atmosphere during extreme drought events known as flash droughts. We find that plants nearly halt water and carbon exchanges and limit their growth during flash drought. This work has implications for how to account for changes in vegetation state during extreme drought events when making predictions under future climate scenarios.
Samuel Scherrer, Gabriëlle De Lannoy, Zdenko Heyvaert, Michel Bechtold, Clement Albergel, Tarek S. El-Madany, and Wouter Dorigo
Hydrol. Earth Syst. Sci., 27, 4087–4114, https://doi.org/10.5194/hess-27-4087-2023, https://doi.org/10.5194/hess-27-4087-2023, 2023
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We explored different options for data assimilation (DA) of the remotely sensed leaf area index (LAI). We found strong biases between LAI predicted by Noah-MP and observations. LAI DA that does not take these biases into account can induce unphysical patterns in the resulting LAI and flux estimates and leads to large changes in the climatology of root zone soil moisture. We tested two bias-correction approaches and explored alternative solutions to treating bias in LAI DA.
Luca Carraro
Hydrol. Earth Syst. Sci., 27, 3733–3742, https://doi.org/10.5194/hess-27-3733-2023, https://doi.org/10.5194/hess-27-3733-2023, 2023
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Mathematical models are key to the study of environmental processes in rivers. Such models often require information on river morphology from geographic information system (GIS) software, which hinders the use of replicable workflows. Here I present rivnet, an R package for simple, robust, GIS-free extraction and analysis of river networks. The package is designed so as to require minimal user input and is oriented towards ecohydrological, ecological and biogeochemical modeling.
Stephen K. Adams, Brian P. Bledsoe, and Eric D. Stein
Hydrol. Earth Syst. Sci., 27, 3021–3039, https://doi.org/10.5194/hess-27-3021-2023, https://doi.org/10.5194/hess-27-3021-2023, 2023
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Managing streams for environmental flows involves prioritizing healthy stream ecosystems while distributing water resources. Classifying streams of similar types is a useful step in developing environmental flows. Environmental flows are often developed on data-poor streams that must be modeled. This paper has developed a new method of classification that prioritizes model accuracy. The new method advances environmental streamflow management and modeling of data-poor watersheds.
Marissa Kivi, Noemi Vergopolan, and Hamze Dokoohaki
Hydrol. Earth Syst. Sci., 27, 1173–1199, https://doi.org/10.5194/hess-27-1173-2023, https://doi.org/10.5194/hess-27-1173-2023, 2023
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This study attempts to provide a framework for direct integration of soil moisture observations collected from soil sensors and satellite imagery into process-based crop models for improving the representation of agricultural systems. The performance of this framework was evaluated across 19 sites times years for crop yield, normalized difference vegetation index (NDVI), soil moisture, tile flow drainage, and nitrate leaching.
Yunfan Zhang, Lei Cheng, Lu Zhang, Shujing Qin, Liu Liu, Pan Liu, and Yanghe Liu
Hydrol. Earth Syst. Sci., 26, 6379–6397, https://doi.org/10.5194/hess-26-6379-2022, https://doi.org/10.5194/hess-26-6379-2022, 2022
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Multiyear drought has been demonstrated to cause non-stationary rainfall–runoff relationship. But whether changes can invalidate the most fundamental method (i.e., paired-catchment method (PCM)) for separating vegetation change impacts is still unknown. Using paired-catchment data with 10-year drought, PCM is shown to still be reliable even in catchments with non-stationarity. A new framework is further proposed to separate impacts of two non-stationary drivers, using paired-catchment data.
Don A. White, Shiqi Ren, Daniel S. Mendham, Francisco Balocchi-Contreras, Richard P. Silberstein, Dean Meason, Andrés Iroumé, and Pablo Ramirez de Arellano
Hydrol. Earth Syst. Sci., 26, 5357–5371, https://doi.org/10.5194/hess-26-5357-2022, https://doi.org/10.5194/hess-26-5357-2022, 2022
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Of all the planting options for wood production and carbon storage, Eucalyptus species provoke the greatest concern about their effect on water resources. We compared Eucalyptus and Pinus species (the two most widely planted genera) by fitting a simple model to the published estimates of their annual water use. There was no significant difference between the two genera. This has important implications for the global debate around Eucalyptus and is an option for carbon forests.
Zhihui Wang, Qiuhong Tang, Daoxi Wang, Peiqing Xiao, Runliang Xia, Pengcheng Sun, and Feng Feng
Hydrol. Earth Syst. Sci., 26, 5291–5314, https://doi.org/10.5194/hess-26-5291-2022, https://doi.org/10.5194/hess-26-5291-2022, 2022
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Variable infiltration capacity simulation considering dynamic vegetation types and structural parameters is able to better capture the effect of temporally explicit vegetation change and climate variation in hydrological regimes. Vegetation greening including interannual LAI and intra-annual LAI temporal pattern change induced by large-scale ecological restoration and non-vegetation underlying surface change played dominant roles in the natural streamflow reduction of the Yellow River basin.
Pan Chen, Wenhong Li, and Keqi He
Hydrol. Earth Syst. Sci., 26, 4875–4892, https://doi.org/10.5194/hess-26-4875-2022, https://doi.org/10.5194/hess-26-4875-2022, 2022
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The study assessed changes in total nitrogen (TN) and total phosphorus (TP) loads in response to eastern Pacific (EP) and central Pacific (CP) El Niño events over the Corn Belt, USA, using the SWAT model. Results showed that EP (CP) El Niño events improved (exacerbated) water quality in the region. Furthermore, EP El Niño had a much broader and longer impact on water quality at the outlets, but CP El Niño could lead to similar increases in TN/TP loads as EP El Niño at the specific watersheds.
Ralf Loritz, Maoya Bassiouni, Anke Hildebrandt, Sibylle K. Hassler, and Erwin Zehe
Hydrol. Earth Syst. Sci., 26, 4757–4771, https://doi.org/10.5194/hess-26-4757-2022, https://doi.org/10.5194/hess-26-4757-2022, 2022
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In this study, we combine a deep-learning approach that predicts sap flow with a hydrological model to improve soil moisture and transpiration estimates at the catchment scale. Our results highlight that hybrid-model approaches, combining machine learning with physically based models, are a promising way to improve our ability to make hydrological predictions.
Nicholas Jarvis, Jannis Groh, Elisabet Lewan, Katharina H. E. Meurer, Walter Durka, Cornelia Baessler, Thomas Pütz, Elvin Rufullayev, and Harry Vereecken
Hydrol. Earth Syst. Sci., 26, 2277–2299, https://doi.org/10.5194/hess-26-2277-2022, https://doi.org/10.5194/hess-26-2277-2022, 2022
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We apply an eco-hydrological model to data on soil water balance and grassland growth obtained at two sites with contrasting climates. Our results show that the grassland in the drier climate had adapted by developing deeper roots, which maintained water supply to the plants in the face of severe drought. Our study emphasizes the importance of considering such plastic responses of plant traits to environmental stress in the modelling of soil water balance and plant growth under climate change.
Remko C. Nijzink, Jason Beringer, Lindsay B. Hutley, and Stanislaus J. Schymanski
Hydrol. Earth Syst. Sci., 26, 525–550, https://doi.org/10.5194/hess-26-525-2022, https://doi.org/10.5194/hess-26-525-2022, 2022
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Most models that simulate water and carbon exchanges with the atmosphere rely on information about vegetation, but optimality models predict vegetation properties based on general principles. Here, we use the Vegetation Optimality Model (VOM) to predict vegetation behaviour at five savanna sites. The VOM overpredicted vegetation cover and carbon uptake during the wet seasons but also performed similarly to conventional models, showing that vegetation optimality is a promising approach.
Hongyu Li, Yi Luo, Lin Sun, Xiangdong Li, Changkun Ma, Xiaolei Wang, Ting Jiang, and Haoyang Zhu
Hydrol. Earth Syst. Sci., 26, 17–34, https://doi.org/10.5194/hess-26-17-2022, https://doi.org/10.5194/hess-26-17-2022, 2022
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Drying soil layers (DSLs) have been extensively reported in artificial forestland in the Loess Plateau, China, which has limited water resources and deep loess. To address this issue relating to plant root–soil water interactions, this study developed a root growth model that simulates both the dynamic rooting depth and fine-root distribution. Evaluation vs. field data proved a positive performance. Long-term simulation reproduced the evolution process of the DSLs and revealed their mechanisms.
Jiancong Chen, Baptiste Dafflon, Anh Phuong Tran, Nicola Falco, and Susan S. Hubbard
Hydrol. Earth Syst. Sci., 25, 6041–6066, https://doi.org/10.5194/hess-25-6041-2021, https://doi.org/10.5194/hess-25-6041-2021, 2021
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The novel hybrid predictive modeling (HPM) approach uses a long short-term memory recurrent neural network to estimate evapotranspiration (ET) and ecosystem respiration (Reco) with only meteorological and remote-sensing inputs. We developed four use cases to demonstrate the applicability of HPM. The results indicate HPM is capable of providing ET and Reco estimations in challenging mountainous systems and enhances our understanding of watershed dynamics at sparsely monitored watersheds.
Jiehao Zhang, Yulong Zhang, Ge Sun, Conghe Song, Matthew P. Dannenberg, Jiangfeng Li, Ning Liu, Kerong Zhang, Quanfa Zhang, and Lu Hao
Hydrol. Earth Syst. Sci., 25, 5623–5640, https://doi.org/10.5194/hess-25-5623-2021, https://doi.org/10.5194/hess-25-5623-2021, 2021
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To quantify how vegetation greening impacts the capacity of water supply, we built a hybrid model and conducted a case study using the upper Han River basin (UHRB) that serves as the water source area to the world’s largest water diversion project. Vegetation greening in the UHRB during 2001–2018 induced annual water yield (WY) greatly decreased. Vegetation greening also increased the possibility of drought and reduced a quarter of WY on average during drought periods.
Aaron J. Neill, Christian Birkel, Marco P. Maneta, Doerthe Tetzlaff, and Chris Soulsby
Hydrol. Earth Syst. Sci., 25, 4861–4886, https://doi.org/10.5194/hess-25-4861-2021, https://doi.org/10.5194/hess-25-4861-2021, 2021
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Structural changes (cover and height of vegetation plus tree canopy characteristics) to forests during regeneration on degraded land affect how water is partitioned between streamflow, groundwater recharge and evapotranspiration. Partitioning most strongly deviates from baseline conditions during earlier stages of regeneration with dense forest, while recovery may be possible as the forest matures and opens out. This has consequences for informing sustainable landscape restoration strategies.
Jianning Ren, Jennifer C. Adam, Jeffrey A. Hicke, Erin J. Hanan, Christina L. Tague, Mingliang Liu, Crystal A. Kolden, and John T. Abatzoglou
Hydrol. Earth Syst. Sci., 25, 4681–4699, https://doi.org/10.5194/hess-25-4681-2021, https://doi.org/10.5194/hess-25-4681-2021, 2021
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Mountain pine beetle outbreaks have caused widespread tree mortality. While some research shows that water yield increases after trees are killed, many others document no change or a decrease. The climatic and environmental mechanisms driving hydrologic response to tree mortality are not well understood. We demonstrated that the direction of hydrologic response is a function of multiple factors, so previous studies do not necessarily conflict with each other; they represent different conditions.
Haidong Zhao, Gretchen F. Sassenrath, Mary Beth Kirkham, Nenghan Wan, and Xiaomao Lin
Hydrol. Earth Syst. Sci., 25, 4357–4372, https://doi.org/10.5194/hess-25-4357-2021, https://doi.org/10.5194/hess-25-4357-2021, 2021
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This study was done to develop an improved soil temperature model for the USA Great Plains by using common weather station variables as inputs. After incorporating knowledge of estimated soil moisture and observed daily snow depth, the improved model showed a near 50 % gain in performance compared to the original model. We conclude that our improved model can better estimate soil temperature at the surface soil layer where most hydrological and biological processes occur.
Brandon P. Sloan, Sally E. Thompson, and Xue Feng
Hydrol. Earth Syst. Sci., 25, 4259–4274, https://doi.org/10.5194/hess-25-4259-2021, https://doi.org/10.5194/hess-25-4259-2021, 2021
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Plants affect the global water and carbon cycles by modifying their water use and carbon intake in response to soil moisture. Global climate models represent this response with either simple empirical models or complex physical models. We reveal that the latter improves predictions in plants with large flow resistance; however, adding dependence on atmospheric moisture demand to the former matches performance of the latter, leading to a new tool for improving carbon and water cycle predictions.
Maria Magdalena Warter, Michael Bliss Singer, Mark O. Cuthbert, Dar Roberts, Kelly K. Caylor, Romy Sabathier, and John Stella
Hydrol. Earth Syst. Sci., 25, 3713–3729, https://doi.org/10.5194/hess-25-3713-2021, https://doi.org/10.5194/hess-25-3713-2021, 2021
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Intensified drying of soil and grassland vegetation is raising the impact of fire severity and extent in Southern California. While browned grassland is a common sight during the dry season, this study has shown that there is a pronounced shift in the timing of senescence, due to changing climate conditions favoring milder winter temperatures and increased precipitation variability. Vegetation may be limited in its ability to adapt to these shifts, as drought periods become more frequent.
Mikael Gillefalk, Dörthe Tetzlaff, Reinhard Hinkelmann, Lena-Marie Kuhlemann, Aaron Smith, Fred Meier, Marco P. Maneta, and Chris Soulsby
Hydrol. Earth Syst. Sci., 25, 3635–3652, https://doi.org/10.5194/hess-25-3635-2021, https://doi.org/10.5194/hess-25-3635-2021, 2021
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We used a tracer-aided ecohydrological model to quantify water flux–storage–age interactions for three urban vegetation types: trees, shrub and grass. The model results showed that evapotranspiration increased in the order shrub < grass < trees during one growing season. Additionally, we could show how
infiltration hotspotscreated by runoff from sealed onto vegetated surfaces can enhance both evapotranspiration and groundwater recharge.
Yuting Yang, Tim R. McVicar, Dawen Yang, Yongqiang Zhang, Shilong Piao, Shushi Peng, and Hylke E. Beck
Hydrol. Earth Syst. Sci., 25, 3411–3427, https://doi.org/10.5194/hess-25-3411-2021, https://doi.org/10.5194/hess-25-3411-2021, 2021
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This study developed an analytical ecohydrological model that considers three aspects of vegetation response to eCO2 (i.e., stomatal response, LAI response, and rooting depth response) to detect the impact of eCO2 on continental runoff over the past 3 decades globally. Our findings suggest a minor role of eCO2 on the global runoff changes, yet highlight the negative runoff–eCO2 response in semiarid and arid regions which may further threaten the limited water resource there.
Yanlan Liu, Nataniel M. Holtzman, and Alexandra G. Konings
Hydrol. Earth Syst. Sci., 25, 2399–2417, https://doi.org/10.5194/hess-25-2399-2021, https://doi.org/10.5194/hess-25-2399-2021, 2021
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The flow of water through plants varies with species-specific traits. To determine how they vary across the world, we mapped the traits that best allowed a model to match microwave satellite data. We also defined average values across a few clusters of trait behavior. These form a tractable solution for use in large-scale models. Transpiration estimates using these clusters were more accurate than if using plant functional types. We expect our maps to improve transpiration forecasts.
Aaron Smith, Doerthe Tetzlaff, Lukas Kleine, Marco Maneta, and Chris Soulsby
Hydrol. Earth Syst. Sci., 25, 2239–2259, https://doi.org/10.5194/hess-25-2239-2021, https://doi.org/10.5194/hess-25-2239-2021, 2021
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We used a tracer-aided ecohydrological model on a mixed land use catchment in northeastern Germany to quantify water flux–storage–age interactions at four model grid resolutions. The model's ability to reproduce spatio-temporal flux–storage–age interactions decreases with increasing model grid sizes. Similarly, larger model grids showed vegetation-influenced changes in blue and green water partitioning. Simulations reveal the value of measured soil and stream isotopes for model calibration.
Yiping Hou, Mingfang Zhang, Xiaohua Wei, Shirong Liu, Qiang Li, Tijiu Cai, Wenfei Liu, Runqi Zhao, and Xiangzhuo Liu
Hydrol. Earth Syst. Sci., 25, 1447–1466, https://doi.org/10.5194/hess-25-1447-2021, https://doi.org/10.5194/hess-25-1447-2021, 2021
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Ecohydrological sensitivity, defined as the response intensity of streamflow to vegetation change, indicates the hydrological sensitivity to vegetation change. The study revealed seasonal ecohydrological sensitivities were highly variable, depending on climate condition and watershed attributes. Dry season ecohydrological sensitivity was mostly determined by topography, soil and vegetation, while wet season ecohydrological sensitivity was mainly controlled by soil, landscape and vegetation.
Xiangyu Luan and Giulia Vico
Hydrol. Earth Syst. Sci., 25, 1411–1423, https://doi.org/10.5194/hess-25-1411-2021, https://doi.org/10.5194/hess-25-1411-2021, 2021
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Crop yield is reduced by heat and water stress, particularly when they co-occur. We quantify the joint effects of (unpredictable) air temperature and soil water availability on crop heat stress via a mechanistic model. Larger but more infrequent precipitation increased crop canopy temperatures. Keeping crops well watered via irrigation could reduce canopy temperature but not enough to always exclude heat damage. Thus, irrigation is only a partial solution to adapt to warmer and drier climates.
Songyan Yu, Hong Xuan Do, Albert I. J. M. van Dijk, Nick R. Bond, Peirong Lin, and Mark J. Kennard
Hydrol. Earth Syst. Sci., 24, 5279–5295, https://doi.org/10.5194/hess-24-5279-2020, https://doi.org/10.5194/hess-24-5279-2020, 2020
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There is a growing interest globally in the spatial distribution and temporal dynamics of intermittently flowing streams and rivers. We developed an approach to quantify catchment-wide flow intermittency over long time frames. Modelled patterns of flow intermittency in eastern Australia revealed highly dynamic behaviour in space and time. The developed approach is transferable to other parts of the world and can inform hydro-ecological understanding and management of intermittent streams.
Natasha MacBean, Russell L. Scott, Joel A. Biederman, Catherine Ottlé, Nicolas Vuichard, Agnès Ducharne, Thomas Kolb, Sabina Dore, Marcy Litvak, and David J. P. Moore
Hydrol. Earth Syst. Sci., 24, 5203–5230, https://doi.org/10.5194/hess-24-5203-2020, https://doi.org/10.5194/hess-24-5203-2020, 2020
Yusen Yuan, Taisheng Du, Honglang Wang, and Lixin Wang
Hydrol. Earth Syst. Sci., 24, 4491–4501, https://doi.org/10.5194/hess-24-4491-2020, https://doi.org/10.5194/hess-24-4491-2020, 2020
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The isotopic composition of ambient water vapor is an important source of atmospheric water vapor and has not been able to be estimated to date using the Keeling plot approach. Here we proposed two new methods to estimate the isotopic composition of ambient water vapor: one using the intersection point method and another relying on the intermediate value theorem.
Valentin Couvreur, Youri Rothfuss, Félicien Meunier, Thierry Bariac, Philippe Biron, Jean-Louis Durand, Patricia Richard, and Mathieu Javaux
Hydrol. Earth Syst. Sci., 24, 3057–3075, https://doi.org/10.5194/hess-24-3057-2020, https://doi.org/10.5194/hess-24-3057-2020, 2020
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Isotopic labeling of soil water is a broadly used tool for tracing the origin of water extracted by plants and computing root water uptake (RWU) profiles with multisource mixing models. In this study, we show how a method such as this may misconstrue time series of xylem water isotopic composition as the temporal dynamics of RWU by simulating data collected during a tall fescue rhizotron experiment with an isotope-enabled physical soil–root model accounting for variability in root traits.
Thibault Hallouin, Michael Bruen, and Fiachra E. O'Loughlin
Hydrol. Earth Syst. Sci., 24, 1031–1054, https://doi.org/10.5194/hess-24-1031-2020, https://doi.org/10.5194/hess-24-1031-2020, 2020
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A hydrological model was used to compare different parameterisation strategies in view of predicting ecologically relevant streamflow indices in 33 Irish catchments. Compared for 14 different periods, a strategy fitting simulated and observed streamflow indices yielded better performance than fitting simulated and observed streamflow, but it also yielded a less consistent ensemble of parameter sets, suggesting that these indices may not be hydrologically relevant for model parameterisation.
Robert N. Armstrong, John W. Pomeroy, and Lawrence W. Martz
Hydrol. Earth Syst. Sci., 23, 4891–4907, https://doi.org/10.5194/hess-23-4891-2019, https://doi.org/10.5194/hess-23-4891-2019, 2019
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Digital and thermal images taken near midday were used to scale daily point observations of key factors driving actual-evaporation estimates across a complex Canadian Prairie landscape. Point estimates of actual evaporation agreed well with observed values via eddy covariance. Impacts of spatial variations on areal estimates were minor, and no covariance was found between model parameters driving the energy term. The methods can be applied further to improve land surface parameterisations.
Zhongkai Li, Hu Liu, Wenzhi Zhao, Qiyue Yang, Rong Yang, and Jintao Liu
Hydrol. Earth Syst. Sci., 23, 4685–4706, https://doi.org/10.5194/hess-23-4685-2019, https://doi.org/10.5194/hess-23-4685-2019, 2019
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A database of soil moisture measurements from the middle Heihe River basin of China was used to test the potential of a soil moisture database in estimating the soil water balance components (SWBCs). We determined SWBCs using a method that combined the soil water balance method and the inverse Richards equation. This work confirmed that relatively reasonable estimations of the SWBCs in coarse-textured sandy soils can be derived using soil moisture measurements.
Inês Gomes Marques, João Nascimento, Rita M. Cardoso, Filipe Miguéns, Maria Teresa Condesso de Melo, Pedro M. M. Soares, Célia M. Gouveia, and Cathy Kurz Besson
Hydrol. Earth Syst. Sci., 23, 3525–3552, https://doi.org/10.5194/hess-23-3525-2019, https://doi.org/10.5194/hess-23-3525-2019, 2019
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Mediterranean cork woodlands are very particular agroforestry systems present in a confined area of the Mediterranean Basin. They are of great importance due to their high socioeconomic value; however, a decrease in water availability has put this system in danger. In this paper we build a model that explains this system's tree-species distribution in southern Portugal from environmental variables. This could help predict their future distribution under changing climatic conditions.
Samuli Launiainen, Mingfu Guan, Aura Salmivaara, and Antti-Jussi Kieloaho
Hydrol. Earth Syst. Sci., 23, 3457–3480, https://doi.org/10.5194/hess-23-3457-2019, https://doi.org/10.5194/hess-23-3457-2019, 2019
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Boreal forest evapotranspiration and water cycle is modeled at stand and catchment scale using physiological and physical principles, open GIS data and daily weather data. The approach can predict daily evapotranspiration well across Nordic coniferous-dominated stands and successfully reproduces daily streamflow and annual evapotranspiration across boreal headwater catchments in Finland. The model is modular and simple and designed for practical applications over large areas using open data.
Regina T. Hirl, Hans Schnyder, Ulrike Ostler, Rudi Schäufele, Inga Schleip, Sylvia H. Vetter, Karl Auerswald, Juan C. Baca Cabrera, Lisa Wingate, Margaret M. Barbour, and Jérôme Ogée
Hydrol. Earth Syst. Sci., 23, 2581–2600, https://doi.org/10.5194/hess-23-2581-2019, https://doi.org/10.5194/hess-23-2581-2019, 2019
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We evaluated the system-scale understanding of the propagation of the oxygen isotope signal (δ18O) of rain through soil and xylem to leaf water in a temperate drought-prone grassland. Biweekly δ18O observations of the water pools made during seven growing seasons were accurately reproduced by the 18O-enabled process-based model MuSICA. While water uptake occurred from shallow soil depths throughout dry and wet periods, leaf water 18O enrichment responded to both soil and atmospheric moisture.
Christoph Schürz, Brigitta Hollosi, Christoph Matulla, Alexander Pressl, Thomas Ertl, Karsten Schulz, and Bano Mehdi
Hydrol. Earth Syst. Sci., 23, 1211–1244, https://doi.org/10.5194/hess-23-1211-2019, https://doi.org/10.5194/hess-23-1211-2019, 2019
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For two Austrian catchments we simulated discharge and nitrate-nitrogen (NO3-N) considering future changes of climate, land use, and point source emissions together with the impact of different setups and parametrizations of the implemented eco-hydrological model. In a comprehensive analysis we identified the dominant sources of uncertainty for the simulation of discharge and NO3-N and further examined how specific properties of the model inputs control the future simulation results.
Yu-Ting Shih, Pei-Hao Chen, Li-Chin Lee, Chien-Sen Liao, Shih-Hao Jien, Fuh-Kwo Shiah, Tsung-Yu Lee, Thomas Hein, Franz Zehetner, Chung-Te Chang, and Jr-Chuan Huang
Hydrol. Earth Syst. Sci., 22, 6579–6590, https://doi.org/10.5194/hess-22-6579-2018, https://doi.org/10.5194/hess-22-6579-2018, 2018
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DOC and DIC export in Taiwan shows that the annual DOC and DIC fluxes were 2.7–4.8 and 48.4–54.3 ton C km2 yr1, respectively, which were approximately 2 and 20 times higher than the global means of 1.4 and 2.6 ton C km2 yr1, respectively.
Zun Yin, Catherine Ottlé, Philippe Ciais, Matthieu Guimberteau, Xuhui Wang, Dan Zhu, Fabienne Maignan, Shushi Peng, Shilong Piao, Jan Polcher, Feng Zhou, Hyungjun Kim, and other China-Trend-Stream project members
Hydrol. Earth Syst. Sci., 22, 5463–5484, https://doi.org/10.5194/hess-22-5463-2018, https://doi.org/10.5194/hess-22-5463-2018, 2018
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Simulations in China were performed in ORCHIDEE driven by different forcing datasets: GSWP3, PGF, CRU-NCEP, and WFDEI. Simulated soil moisture was compared to several datasets to evaluate the ability of ORCHIDEE in reproducing soil moisture dynamics. Results showed that ORCHIDEE soil moisture coincided well with other datasets in wet areas and in non-irrigated areas. It suggested that the ORCHIDEE-MICT was suitable for further hydrological studies in China.
Matthias J. R. Speich, Heike Lischke, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 22, 4097–4124, https://doi.org/10.5194/hess-22-4097-2018, https://doi.org/10.5194/hess-22-4097-2018, 2018
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To simulate the water balance of, e.g., a forest plot, it is important to estimate the maximum volume of water available to plants. This depends on soil properties and the average depth of roots. Rooting depth has proven challenging to estimate. Here, we applied a model assuming that plants dimension their roots to optimize their carbon budget. We compared its results with values obtained by calibrating a dynamic water balance model. In most cases, there is good agreement between both methods.
Gordon C. O'Brien, Chris Dickens, Eleanor Hines, Victor Wepener, Retha Stassen, Leo Quayle, Kelly Fouchy, James MacKenzie, P. Mark Graham, and Wayne G. Landis
Hydrol. Earth Syst. Sci., 22, 957–975, https://doi.org/10.5194/hess-22-957-2018, https://doi.org/10.5194/hess-22-957-2018, 2018
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In global water resource allocation, robust tools are required to establish environmental flows. In addition, tools should characterize past, present and future consequences of altered flows and non-flow variables to social and ecological management objectives. PROBFLO is a risk assessment method designed to meet best practice principles for regional-scale holistic E-flow assessments. The approach has been developed in Africa and applied across the continent.
Katrina E. Bennett, Theodore J. Bohn, Kurt Solander, Nathan G. McDowell, Chonggang Xu, Enrique Vivoni, and Richard S. Middleton
Hydrol. Earth Syst. Sci., 22, 709–725, https://doi.org/10.5194/hess-22-709-2018, https://doi.org/10.5194/hess-22-709-2018, 2018
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We applied the Variable Infiltration Capacity hydrologic model to examine scenarios of change under climate and landscape disturbances in the San Juan River basin, a major sub-watershed of the Colorado River basin. Climate change coupled with landscape disturbance leads to reduced streamflow in the San Juan River basin. Disturbances are expected to be widespread in this region. Therefore, accounting for these changes within the context of climate change is imperative for water resource planning.
Fernando Jaramillo, Neil Cory, Berit Arheimer, Hjalmar Laudon, Ype van der Velde, Thomas B. Hasper, Claudia Teutschbein, and Johan Uddling
Hydrol. Earth Syst. Sci., 22, 567–580, https://doi.org/10.5194/hess-22-567-2018, https://doi.org/10.5194/hess-22-567-2018, 2018
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Which is the dominant effect on evapotranspiration in northern forests, an increase by recent forests expansion or a decrease by the water use response due to increasing CO2 concentrations? We determined the dominant effect during the period 1961–2012 in 65 Swedish basins. We used the Budyko framework to study the hydroclimatic movements in Budyko space. Our findings suggest that forest expansion is the dominant driver of long-term and large-scale evapotranspiration changes.
Jie Zhu, Ge Sun, Wenhong Li, Yu Zhang, Guofang Miao, Asko Noormets, Steve G. McNulty, John S. King, Mukesh Kumar, and Xuan Wang
Hydrol. Earth Syst. Sci., 21, 6289–6305, https://doi.org/10.5194/hess-21-6289-2017, https://doi.org/10.5194/hess-21-6289-2017, 2017
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Forested wetlands provide myriad ecosystem services threatened by climate change. This study develops empirical hydrologic models by synthesizing hydrometeorological data across the southeastern US. We used global climate projections to model hydrological changes for five wetlands. We found all wetlands are predicted to become drier by the end of this century. This study suggests that climate change may substantially affect wetland biogeochemical cycles and other functions in the future.
Guiomar Ruiz-Pérez, Julian Koch, Salvatore Manfreda, Kelly Caylor, and Félix Francés
Hydrol. Earth Syst. Sci., 21, 6235–6251, https://doi.org/10.5194/hess-21-6235-2017, https://doi.org/10.5194/hess-21-6235-2017, 2017
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Plants are shaping the landscape and controlling the hydrological cycle, particularly in arid and semi-arid ecosystems. Remote sensing data appears as an appealing source of information for vegetation monitoring, in particular in areas with a limited amount of available field data. Here, we present an example of how remote sensing data can be exploited in a data-scarce basin. We propose a mathematical methodology that can be used as a springboard for future applications.
Rui Rivaes, Isabel Boavida, José M. Santos, António N. Pinheiro, and Teresa Ferreira
Hydrol. Earth Syst. Sci., 21, 5763–5780, https://doi.org/10.5194/hess-21-5763-2017, https://doi.org/10.5194/hess-21-5763-2017, 2017
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We analyzed the influence of considering riparian requirements for the long-term efficiency of environmental flows. After a decade, environmental flows disregarding riparian requirements promoted riparian degradation and consequently the change in the hydraulic characteristics of the river channel and the modification of the available habitat area for fish species. Environmental flows regarding riparian vegetation requirements were able to sustain the fish habitat close to the natural condition.
José María Santiago, Rafael Muñoz-Mas, Joaquín Solana-Gutiérrez, Diego García de Jalón, Carlos Alonso, Francisco Martínez-Capel, Javier Pórtoles, Robert Monjo, and Jaime Ribalaygua
Hydrol. Earth Syst. Sci., 21, 4073–4101, https://doi.org/10.5194/hess-21-4073-2017, https://doi.org/10.5194/hess-21-4073-2017, 2017
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High-time-resolution models for streamflow and stream temperature are used in this study to predict future brown trout habitat loss. Flow reductions falling down to 51 % of current values and water temperature increases growing up to 4 ºC are predicted. Streamflow and temperature will act synergistically affecting fish. We found that the thermal response of rivers is influenced by basin geology and, consequently, geology will be also an influent factor in the cold-water fish distribution shift.
Mie Andreasen, Karsten H. Jensen, Darin Desilets, Marek Zreda, Heye R. Bogena, and Majken C. Looms
Hydrol. Earth Syst. Sci., 21, 1875–1894, https://doi.org/10.5194/hess-21-1875-2017, https://doi.org/10.5194/hess-21-1875-2017, 2017
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The cosmic-ray method holds a potential for quantifying canopy interception and biomass. We use measurements and modeling of thermal and epithermal neutron intensity in a forest to examine this potential. Canopy interception is a variable important to forest hydrology, yet difficult to monitor remotely. Forest growth impacts the carbon-cycle and can be used to mitigate climate changes by carbon sequestration in biomass. An efficient method to monitor tree growth is therefore of high relevance.
Cited articles
Ahmad, S. K., Kumar, S. V., Lahmers, T. M., Wang, S., Liu, P., Wrzesien, M. L., Bindlish, R., Getirana, A., Locke, K. A., Holmes, T. R., and Otkin, J. A.: Flash Drought Onset and Development Mechanisms Captured with Soil Moisture and Vegetation Data Assimilation, Water Resour. Res., 58, e2022WR032894, https://doi.org/10.1029/2022WR032894, 2022.
Brajard, J., Carrassi, A., Bocquet, M., and Bertino, L.: Combining data
assimilation and machine learning to emulate a dynamical model from sparse
and noisy observations: A case study with the Lorenz 96 model, J. Comput. Sci., 44, 101171, https://doi.org/10.1016/j.jocs.2020.101171, 2020.
Buizza, C., Quilodrán Casas, C., Nadler, P., Mack, J., Marrone, S.,
Titus, Z., Le Cornec, C., Heylen, E., Dur, T., Baca Ruiz, L., Heaney, C.,
Díaz Lopez, J. A., Kumar, K. S. S., and Arcucci, R.: Data Learning:
Integrating Data Assimilation and Machine Learning, J. Comput. Syst. Sci., 58, 101525, https://doi.org/10.1016/j.jocs.2021.101525, 2022.
Campo, L., Castelli, F., Entekhabi, D., and Caparrini, F.: Land-atmosphere
interactions in an high resolution atmospheric simulation coupled with a
surface data assimilation scheme, Nat. Hazards Earth Syst. Sci., 9,
1613–1624, https://doi.org/10.5194/nhess-9-1613-2009, 2009.
Cazes Boezio, G. and Ortelli, S.: Use of the WRF-DA 3D-Var Data Assimilation
System to Obtain Wind Speed Estimates in Regular Grids from Measurements at
Wind Farms in Uruguay, Data, 4, 142, https://doi.org/10.3390/data4040142, 2019.
CDS: ECMWF Reanalysis v5 (ERA5) Data, https://cds.climate.copernicus.eu/cdsapp#!/search?type=dataset, last access: 8 January 2022.
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.
Chen, F. and Dudhia, J.: Coupling an Advanced Land Surface–Hydrology Model
with the Penn State – NCAR MM5 Modeling System. Part I: Model Implementation
and Sensitivity, Mon. Wether. Rev., 129, 569–585,
https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2, 2001.
Chen, R., Song, Y., Kang, E., Han, C., Liu, J., Yang, Y., Qing, W. W., and
Liu, Z. W.: A cryosphere-hydrology observation system in a small alpine
watershed in the Qilian mountains of China and its meteorological gradient,
Arct. Antarct. Alp. Res., 46, 505–523, https://doi.org/10.1657/1938-4246-46.2.505, 2014.
Chen, Y. Y., Yang, K., Tang, W. J., 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.
Comellas Prat, A., Federico, S., Torcasio, R. C., Fierro, A. O., and Dietrich, S.: Lightning data assimilation in the WRF-ARW model for short-term rainfall forecasts of three severe storm cases in Italy, Atmos. Res., 247, 105246, https://doi.org/10.1016/j.atmosres.2020.105246, 2021.
Cuntz, M., Mai, J., Samaniego, L., Clark, M., Wulfmeyer, V., Branch, O.,
Attinger, S., and Thober, S.: The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model. J.
Geophys. Res.-Atmos., 121, 10676–10700, https://doi.org/10.1002/2016JD025097, 2016.
Erlandsen, H. B., Haddeland, I., Tallaksen, L. M., and Kristiansen, J.: The
Sensitivity of the Terrestrial Surface Energy and Water Balance Estimates in
the WRF Model to Lower Surface Boundary Representations: A South Norway Case
Study, J. Hydrometeorol., 18, 265–284, https://doi.org/10.1175/JHM-D-15-0146.1, 2017.
Forman, B. A. and Xue, Y.: Machine learning predictions of passive microwave
brightness temperature over snow-covered land using the special sensor
microwave imager (SSM/I), Phys. Geogr., 38, 176–196, https://doi.org/10.1080/02723646.2016.1236606, 2017.
Gao, Y., Chen, F., Barlage, M., Liu, W., Cheng, G., Li, X., Yu, Y., Ran, Y.,
Li, H., Peng, H., and Ma, M.: Enhancement of land surface information and its impact on atmospheric modeling in the Heihe River Basin, northwest China, J. Geophys. Res., 113, D20S90, https://doi.org/10.1029/2008JD010359, 2008.
Gentine, P., Massmann, A., Lintner, B. R., Hamed Alemohammad, S., Fu, R.,
Green, J. K., Kennedy, D., and Vilà-Guerau de Arellano, J.: Land–atmosphere interactions in the tropics-a review, Hydrol. Earth Syst.
Sci., 23, 4171–4197, https://doi.org/10.5194/hess-23-4171-2019, 2019.
GLASS: Download of the GLASS products, http://www.glass.umd.edu/, last access: 8 January 2022.
Gottwald, G. A. and Reich, S.: Combining machine learning and data assimilation to forecast dynamical systems from noisy partial observations,
Chaos, 31, 101103, https://doi.org/10.1063/5.0066080, 2021.
Grzeschik, M., Bauer, H.-S., Wulfmeyer, V., Engelbart, D., Wandinger, U.,
Mattis, I., Althausen, D., Engelmann, R., Tesche, M., and Riede, A.: Four-dimensional variational analysis of water-vapor Raman lidar data and
their impact on mesoscale forecasts, J. Atmos. Ocean. Tech., 25, 1437–1453,
https://doi.org/10.1175/2007JTECHA974.1, 2008.
He, J., Yang, K., Tang, W. Lu, H., Qin, J., Chen, Y. Y., and Li, X.: The
first high-resolution meteorological forcing dataset for land process studies over China, Sci. Data, 7, 25, https://doi.org/10.1038/s41597-020-0369-y, 2020.
He, X., Xu, T., Bateni, S. M., Ek, M., Liu, S., and Chen, F.: Mapping Regional Evapotranspiration in Cloudy Skies via Variational Assimilation of
All-Weather Land Surface Temperature Observations, J. Hydrol., 585, 124790,
https://doi.org/10.1016/j.jhydrol.2020.124790, 2020.
He, X., Xu, T., Bateni, S. M., Ki, S. J., Xiao, J., Liu, S., Song, L., and
He, X.: Estimation of Turbulent Heat Fluxes and Gross Primary Productivity by Assimilating Land Surface Temperature and Leaf Area Index, Water Resour. Res., 57, e2020WR028224, https://doi.org/10.1029/2020WR028224, 2021.
He, X., Liu, S., Xu, T., Yu, K., Gentine, P., Zhang, Z., Xu, Z., Jiao, D.,
and Wu, D.: Improving predictions of evapotranspiration by integrating multi-source observations and land surface model, Agr. Water Manage., 272,
107827, https://doi.org/10.1016/j.agwat.2022.107827, 2022.
Hu, Y. Q., Gao, Y. X., Wang, J. M., Ji, G. L., Shen, Z. B., Cheng, L. S., Cheng, J. Y., and Li, S. Q.: Some achievements in scientific research during HEIFE, Plateau Meteorol., 13, 225–236, 1994.
Janjic, Z.: The Step-mountain eta coordinate model: Further developments of
the convection, viscous sublayer, and turbulence closure schemes. Mon.
Weather Rev., 122, 927–945, https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2, 1994.
Jia, X., Willard, J., Karpatne, A., Read, J. S., Zwart, J. A., Steinbach, M.,
and Kumar, V.: Physics-Guided Machine Learning for Scientific Discovery: An
Application in Simulating Lake Temperature Profiles, ACM/IMS Trans. Data Sci., 2, 1–26, https://doi.org/10.1145/3447814, 2021.
Jung, M., Schwalm, C., Migliavacca, M., Walther, S., Camps-Valls, G., Koirala, S., Anthoni, P., Besnard, S., Bodesheim, P., Carvalhais, N.,
Chevallier, F., Gans, F., Goll, D. S., Haverd, V., Köhler, P., Ichii, K.,
Jain, A. K., Liu, J., Lombardozzi, D., Nabel, J. E. M. S., Nelson, J. A.,
O'Sullivan, M., Pallandt, M., Papale, D., Peters, W., Pongratz, J.,
Rödenbeck, C., Sitch, S., Tramontana, G., Walker, A., Weber, U., and
Reichstein, M.: Scaling carbon fluxes from eddy covariance sites to globe:
synthesis and evaluation of the FLUXCOM approach, Biogeosciences, 17,
1343–1365, https://doi.org/10.5194/bg-17-1343-2020, 2020.
Koppa, A., Rains, D., Hulsman, P., Poyatos, R., and Miralles, D. G.: A deep
learning-based hybrid model of global terrestrial evaporation, Nat. Commun.,
13, 1912, https://doi.org/10.1038/s41467-022-29543-7, 2022.
Levis, S., Bonan, G. B., Kluzek, E., Thornton, P. E., Jones, A., Sacks, W. J., and Kucharik, C. J.: Interactive Crop Management in the Community Earth
System Model (CESM1): Seasonal Influences on Land–Atmosphere Fluxes, J.
Climate, 25, 4839–4859, https://doi.org/10.1175/jcli-d-11-00446.1, 2012.
Li, X., Li, Xiaowen, Li, Z., Ma, M., Wang, J., Xiao, Q., Liu, Q., Che, T., Chen, E., Yan, G., Hu, Z., Zhang, L., Chu, R., Su, P., Liu, Q., Liu, S., Wang, Jindi, Niu, Z., Chen, Y., Jin, R., Wang, W., Ran, Y., Xin, X., and Ren, H.: Watershed Allied Telemetry Experimental Research, J. Geophys. Res., 114, D22103, https://doi.org/10.1029/2008JD011590, 2009.
Li, X., Cheng, G., and Liu, S.: Heihe watershed allied telemetry experimental research (HiWATER): scientifc objectives and experimental design, B. Am. Meteorol. Soc., 94, 1145–1160, https://doi.org/10.1175/BAMS-D-12-00154.1, 2013.
Li, X., Yang, K., and Zhou, Y.: Progress in the study of oasis-desert
interactions, Agr. Forest Meteorol., 230, 1–7, https://doi.org/10.1016/j.agrformet.2016.08.022, 2016.
Li, X., Cheng, G., Lin, H., Cai, X., Fang, M., Ge, Y., Hu, X., Chen, M., and
Li, W.: Watershed System Model: The Essentials to Model Complex Human-Nature
System at the River Basin Scale, J. Geophys. Res.-Atmos., 123, 3019–3034,
https://doi.org/10.1002/2017JD028154, 2018.
Li, X., Zhang, L., Zheng, Y., Yang, D., Wu, F., Tian, Y., Han, F., Gao, B.,
Li, H., Zhang, Y., Ge, Y., Cheng, G., Fu, B., Xia, J., Song, C., and Zheng, C.: Novel hybrid coupling of ecohydrology and socioeconomy at river basin
scale: A watershed system model for the Heihe River basin, Environ. Model.
Softw., 141, 105058, https://doi.org/10.1016/j.envsoft.2021.105058, 2021.
Li, X., Cheng, G., Fu, B., Xia, J., Zhang, L., Yang, D., Zheng, C., Liu, S., Li, X., Song, C., Kang, S., Li, X., Che, T., Zheng, Y., Zhou, Y., Wang, H., and Ran, Y.: Linking Critical Zone With Watershed Science: The Example of the Heihe River Basin, Earth's Future, 10, e2022EF002966, https://doi.org/10.1029/2022EF002966, 2022.
Liang, S., Cheng, J., Jia, K., Jiang, B., Liu, Q., Xiao, Z., Yao, Y., Yuan,
W., Zhang, X., Zhao, X., and Zhou, J.: The Global Land Surface Satellite (GLASS) Product Suite, B. Am. Meteorol. Soc., 102, E323–E337,
https://doi.org/10.1175/BAMS-D-18-0341.1, 2021.
Ling, X. L., Fu, C. B., Guo, W. D., and Yang, Z. L.: Assimilation of remotely
sensed LAI into CLM4CN using DART, J. Adv. Model. Earth Syst., 11, 2768–2786, https://doi.org/10.1029/2019MS001634, 2019.
Liu, R., Liu, S., Yang, X., Lu, H., Pan, X., Xu, Z., Ma, Y., and Xu, T.: Wind Dynamics Over a Highly Heterogeneous Oasis Area: An Experimental and Numerical Study, J. Geophys. Res.-Atmos., 123, 8418–8440, https://doi.org/10.1029/2018JD028397, 2018.
Liu, R., Sogachev, A., Yang, X., Liu, S., Xu, T., and Zhang, J.: Investigating microclimate effects in an oasis-desert interaction zone, Agr. Forest Meteorol., 290, 107992, https://doi.org/10.1016/j.agrformet.2020.107992, 2020.
Liu, S., Xu, Z., Song, L., Zhao, Q., Ge, Y., Xu, T., Ma, Y., Zhu, Z., Jia, Z., and Zhang, F.: Upscaling evapotranspiration measurements from multi-site
to the satellite pixel scale over heterogeneous land surfaces, Agr. Forest
Meteorol., 230–231, 97–113, https://doi.org/10.1016/j.agrformet.2016.04.008, 2016.
Liu, S., Li, X., Xu, Z., Che, T., Xiao, Q., Ma, M., Liu, Q., Jin, R., Guo, J., Wang, L., Wang, W., Qi, Y., Li, H., Xu, T., Ran, Y., Hu, X., Shi, S., Zhu, Z., Tan, J., Zhang, Y., and Ren, Z.: The Heihe Integrated Observatory
Network: A Basin-Scale Land Surface Processes Observatory in China, Vadose
Zone J., 17, 180072, https://doi.org/10.2136/vzj2018.04.0072, 2018.
Liu, L., Ma, Y., Menenti, M., Su, R., Yao, N., and Ma, W.: Improved parameterization of snow albedo in Noah coupled with Weather Research and
Forecasting: applicability to snow estimates for the Tibetan Plateau, Hydrol. Earth Syst. Sci., 25, 4967–4981, https://doi.org/10.5194/hess-25-4967-2021, 2021.
Liu, X., Chen, F., Barlage, M., Zhou, G., and Niyogi, D.: Noah-MP-Crop:
Introducing dynamic crop growth in the Noah-MP land surface model, J. Geophys. Res.-Atmos., 121, 13953–13972, https://doi.org/10.1002/2016jd025597, 2016.
Ma, X., Yang, K., La, Z., Lu, H., Jiang, Y., Zhou, X., Yao, X., and Li, X.:
Importance of Parameterizing Lake Surface and Internal Thermal Processes in
WRF for Simulating Freeze Onset of an Alpine Deep Lake, J. Geophys. Res.-Atmos., 127, e2022JDO36759, https://doi.org/10.1029/2022JD036759, 2022.
Meng, X., Lü, S., Gao, Y., and Guo, J.: Simulated effects of soil moisture on oasis selfmaintenance in a surrounding desert environment in
Northwest China, Int. J. Climatol., 35, 4116–4125, https://doi.org/10.1002/joc.4271, 2015.
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.: Radiative transfer for inhomogeneous atmosphere: RRTM, a validated
correlated-k model for the longwave, J. Geophys. Res.-Atmos., 102, 16663–16682, https://doi.org/10.1029/97JD00237, 1997.
Moosavi, A., Rao, V., and Sandu, A.: Machine learning based algorithms for
uncertainty quantification in numerical weather prediction models, J. Comput. Syst. Sci., 50, 101295, https://doi.org/10.1016/j.jocs.2020.101295, 2021.
NASA: Welcome to AppEEARS!, https://appeears.earthdatacloud.nasa.gov/, last access: 5 December 2020.
Nearing, G. S., Ruddell, B. L., Clark, M. P., Nijssen, B., and Peters-Lidard,
C.: Benchmarking and Process Diagnostics of Land Models, J. Hydrometeorol., 19, 1835–1852, https://doi.org/10.1175/JHM-D-17-0209.1, 2018.
Nelli, N. R., Temimi, M., Fonseca, R. M., Weston, M. J., Thota, M. S., Valappil, V. K., Branch, O., Wulfmeyer, V., Wehbe, Y., Al Hosary, T., Shalaby, A., Al Shamsi, N., and Al Naqbi, H.: Impact of Roughness Length on WRF Simulated Land-Atmosphere Interactions Over a Hyper-Arid Region, Earth Space Sci., 7, e2020EA001165, https://doi.org/10.1029/2020EA001165, 2020.
Ozdogan, M. and Salvucci, G. D.: Irrigation-induced changes in potential
evapotranspiration in Southeastern Turkey: Test and application of Bouchet's
complementary hypothesis, Water Resour. Res., 40, W04301, https://doi.org/10.1029/2003WR002822, 2004.
Pan, X., Li, X., Yang, K., He, J., Zhang, Y., and Han, X.: Comparison of
Downscaled Precipitation Data over a Mountainous Watershed: A Case Study in
the Heihe River Basin, J. Hydrometeorol. 15, 1560–1574, https://doi.org/10.1175/JHM-D-13-0202.1, 2014.
Pan, X., Li, X., Cheng, G., and Hong, Y.: Effects of 4D-Var Data Assimilation Using Remote Sensing Precipitation Products in a WRF Model over the Complex Terrain of an Arid Region River Basin, Remote Sens., 9, 963, https://doi.org/10.3390/rs9090963, 2017.
Pan, X. D., Guo, X. J., Li, X., Niu, X. L., Yang, X. J., Feng, M., Che, T., Jin, R., Ran, Y. H., Guo, J. W., Hu, X. L., and Wu, A. D.: National Tibetan Plateau Data Center: Promoting Earth System Science on the Third Pole, B. Am.
Meteorol. Soc., 102, E2062–E2078, https://doi.org/10.1175/BAMS-D-21-0004.1, 2021a.
Pan, X., Ma, W., Zhang, Y., and Li, H.: Refined Characteristics of Moisture
Cycling over the Inland River Basin Using the WRF Model and the Finer Box
Model: A Case Study of the Heihe River Basin, Atmosphere, 12, 399, https://doi.org/10.3390/atmos12030399, 2021b.
Pilguj, N., Taszarek, M., Pajurek, Ł., and Kryza, M.: High-resolution
simulation of an isolated tornadic supercell in Poland on 20 June 2016, Atmos. Res., 218, 145–159, https://doi.org/10.1016/j.atmosres.2018.11.017, 2019.
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K.,
Keller, M., Tölle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S.,
Schmidli, J., Lipzig, N. P. M., and Leung, R.: A review on regional
convection-permitting climate modeling: Demonstrations, prospects, and
challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014RG000475, 2015.
Rahman, A., Maggioni, V., Zhang, X., Houser, P., Sauer, T., and Mocko, D. M.:
The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil
Moisture into a Land Surface Model, Remote Sens., 14, 437, https://doi.org/10.3390/rs14030437, 2022.
Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J., Carvalhais, N., and Prabhat.: Deep learning and process understanding for
data-driven Earth system science, Nature, 566, 195–204, https://doi.org/10.1038/s41586-019-0912-1, 2019.
Sawada, Y., Koike, T., and Walker, J. P.: A land data assimilation system for
simultaneous simulation of soil moisture and vegetation dynamics: LDAS For
Ecohydrological Model, J. Geophys. Res.-Atmos., 120, 5910–5930, https://doi.org/10.1002/2014JD022895, 2015.
Seo, E., Lee, M. I., and Reichle, R. H.: Assimilation of SMAP and ASCAT soil
moisture retrievals into the JULES land surface model using the Local Ensemble Transform Kalman Filter, Remote Sens. Environ., 253, 112222, https://doi.org/10.1016/j.rse.2020.112222, 2021.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Liu, Z., Berner, J.,
Wang, W., Powers, J. G., Duda, M. G., Barker, D. M., and Huang, X. Y.: A
Description of the Advanced Research WRF Version 4, NCAR Tech. Note NCAR/TN-556+STR, NCAR, 145 pp., https://doi.org/10.5065/1dfh-6p97, 2019.
Smedman, A., Högström, U., Sahlee, E., and Johansson, C.: Critical
re-evaluation of the bulk transfer coefficient for heat over the ocean, Q.
J. Roy. Meteorol. Soc., 133, 227–250, https://doi.org/10.1002/qj.6, 2007.
Song, X., Liu, F., Zhang, G., Li, D., and Zhao, Y.: Estimation of soil
texture at a regional scale using local soil-landscape models, Soil Sci., 181, 435–445, https://doi.org/10.1097/SS.0000000000000180, 2016.
Thompson, G., Field, P. R., Rasmussen, R. M., and Hall, W. D.: Explicit
forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a new snow parameterization, Mon. Weather Rev., 136, 5095–5115, https://doi.org/10.1175/2008mwr2387.1, 2008.
Sun, S., Zheng, D., Liu, S., Xu, Z., Xu, T., Zheng, H., and Yang, X.: Assessment and improvement of Noah-MP for simulating water and heat exchange
over alpine grassland in growing season, Sci. China Earth Sci., 64, 536–552, https://doi.org/10.1007/s11430-021-9852-2, 2021.
Tian, J., Qin, J., Yang, K., Zhao, L., Chen, Y., Lu, H., Li, X., and Shi, J.: Improving surface soil moisture retrievals through a novel assimilation algorithm to estimate both model and observation errors, Remote Sens. Environ., 269, 112802, https://doi.org/10.1016/j.rse.2021.112802, 2022.
Wang, G. X. and Cheng, G. D.: Water resource development and its influence
on the environment in arid areas of China-the case of the Hei River basin,
J. Arid Environ., 43, 121–131, https://doi.org/10.1006/jare.1999.0563, 1999.
Wang, L., Chen, R., Song, Y., Yang, Y., Liu, J., Han, C., and Liu, Z.:
Precipitation–altitude relationships on different timescales and at different precipitation magnitudes in the Qilian Mountains, Theor. Appl. Climatol., 134, 875–884, https://doi.org/10.1007/s00704-017-2316-1, 2018.
Wang, X., Pang, G., Yang, M., Wan, G., and Liu, Z.: Precipitation changes in
the Qilian Mountains associated with the shifts of regional atmospheric
water vapour during 1960–2014, Int. J. Climatol., 38, 4355–4368, https://doi.org/10.1002/joc.5673, 2018.
Wang, X., Tolksdorf, V., Otto, M., and Scherer, D.: WRF-based dynamical
downscaling of ERA5 reanalysis data for High Mountain Asia: Towards a new
version of the High Asia Refined analysis, Int. J. Climatol., 41, 743–762,
https://doi.org/10.1002/joc.6686, 2021.
Wen, X., Lu, S., and Jin, J.: Integrating Remote Sensing Data with WRF for
Improved Simulations of Oasis Effects on Local Weather Processes over an
Arid Region in Northwestern China, J. Hydrometeorol., 13, 573–587, https://doi.org/10.1175/JHM-D-10-05001.1, 2012.
WRF: Weather Research and Forecasting Model, GitHub [code], https://github.com/wrf-model, last access: 28 December 2021.
Wu, D., Liu, S., Wu, X., Xu, T., Xu, Z., He, X., and Shi, H.: Evaluation of
the intrinsic temperature sensitivity of ecosystem respiration in typical
ecosystems of an endorheic river basin, Agr. Forest Meteorol., 333, 109393,
https://doi.org/10.1016/j.agrformet.2023.109393, 2023.
Wu, W. Y., Yang, Z. L., Zhao, L., and Lin, P.: The impact of multi-sensor
land data assimilation on river discharge estimation, Remote Sens. Environ.,
279, 113138, https://doi.org/10.1016/j.rse.2022.113138, 2022.
Xia, Y., Hao, Z., Shi, C., Li, Y., Meng, J., Xu, T., Wu, X., and Zhang, B.:
Regional and Global Land Data Assimilation Systems: Innovations, Challenges,
and Prospects, J. Meteorol. Res., 33, 159–189, https://doi.org/10.1007/s13351-019-8172-4, 2019.
Xiao, Z., Liang, S., Wang, J., Chen, P., Yin, X., Zhang, L., and Song, J.:
Use of general regression neural networks for generating the GLASS leaf area
index product from time-series MODIS surface re?ectance, IEEE Trans. Geosci.
Remote, 52, 209–223, https://doi.org/10.1109/TGRS.2013.2237780, 2014.
Xie, Y., Wang, P., Bai, X., Khan, J., Zhang, S., Li, L., and Wang, L.: Assimilation of the leaf area index and vegetation temperature condition
index for winter wheat yield estimation using Landsat imagery and the CERES-Wheat model, Agr. Forest Meteorol., 246, 194–206, https://doi.org/10.1016/j.agrformet.2017.06.015, 2017.
Xie, Z., Liu, S., Zeng, Y., Gao, J., Qin, P., Jia, B., Xie, J., Liu, B., Li,
R., Wang, Y., and Wang, L.: A High-Resolution Land Model With Groundwater
Lateral Flow, Water Use, and Soil Freeze-Thaw Front Dynamics and its Applications in an Endorheic Basin. J. Geophys. Res.-Atmos., 123, 7204–7222, https://doi.org/10.1029/2018JD028369, 2018.
Xu, T., Valocchi, A. J., Choi, J., and Amir, E.: Use of Machine Learning
Methods to Reduce Predictive Error of Groundwater Models, Groundwater, 52,
448–460, https://doi.org/10.1111/gwat.12061, 2014.
Xu, T., Guo, Z., Liu, S., He, X., Meng, Y., Xu, Z., Xia, Y., Xiao, J., Zhang, Y., Ma, Y., and Song, L.: Evaluating Different Machine Learning Methods for Upscaling Evapotranspiration from Flux Towers to the Regional Scale, J. Geophys. Res.-Atmos., 123, 8674–8690, https://doi.org/10.1029/2018JD028447, 2018.
Xu, T., He, X., Bateni, S. M., Auligne, T., Liu, S., Xu, Z., Zhou, J., and
Mao, K.: Mapping regional turbulent heat fluxes via variational assimilation
of land surface temperature data from polar orbiting satellites, Remote Sens. Environ., 221, 444–461, https://doi.org/10.1016/j.rse.2018.11.023, 2019.
Xu, T., Chen, F., He, X., Barlage, M., Zhang, Z., Liu, S., and He, X.: Improve the Performance of the Noah-MP-Crop Model by Jointly Assimilating Soil Moisture and Vegetation Phenology Data, J. Adv. Model. Earth Syst., 13, e2020MS002394, https://doi.org/10.1029/2020MS002394 2021.
Xu, Z., Liu, S., Zhu, Z., Zhou, J., Shi, W., Xu, T., Yang, X., Zhang, Y.,
and He, X.: Exploring evapotranspiration changes in a typical endorheic basin through the integrated observatory network, Agr. Forest Meteorol., 290, 108010, https://doi.org/10.1016/j.agrformet.2020.108010, 2020.
Yang, Z. L., Niu, G. Y., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M.,
Longuevergne, L., Manning, K., Niyogi, D., Tewari, M., and Xia, Y.: The
community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins, J. Geophys. Res., 116, D12110, https://doi.org/10.1029/2010JD015140, 2011.
Yi, L., Yong, B., Chen, J., Zheng, Z., and Li, L.: Impact of 4D-Var Data
Assimilation on Performance of the Coupled Land–Atmosphere Model WRF–TOPX:
A Case Study of a Flood Event in the Wangjiaba Watershed, China, J. Hydrometeorol., 22, 689–701, https://doi.org/10.1175/JHM-D-20-0161.1, 2021.
Yue, S., Yang, K., Lu, H., Zhou, X., Chen, D., and Guo, W.: Representation
of Stony Surface-Atmosphere Interactions in WRF Reduces Cold and Wet Biases
for the Southern Tibetan Plateau, J. Geophys. Res.-Atmos., 126, e2021JD035291, https://doi.org/10.1029/2021JD035291, 2021.
Zhang, G., Chen, F., and Gan, Y.: Assessing uncertainties in the Noah-MP
ensemble simulations of a cropland site during the Tibet Joint International
Cooperation program field campaign: Uncertainty In NOAH-MP Simulations, J.
Geophys. Res.-Atmos. 121, 9576–9596, https://doi.org/10.1002/2016JD024928, 2016.
Zhang, M., Luo, G., Hamdi, R., Qiu, Y., Wang, X., Maeyer, P. D., and Kurban,
A.: Numerical Simulations of the Impacts of Mountain on Oasis Effects in Arid Central Asia, Atmosphere, 8, 212, https://doi.org/10.3390/atmos8110212, 2017.
Zhang, M., Luo, G., Cao, X., Hamdi, R., Li, T., Cai, P., Ye, H., and He, H.: Numerical Simulation of the Irrigation Effects on Surface Fluxes and Local Climate in Typical Mountain–Oasis–Desert Systems in the Central Asia Arid Area, J. Geophys. Res.-Atmos., 124, 12485–12506, https://doi.org/10.1029/2019JD030507, 2019.
Zhang, X., Xiong, Z., and Tang, Q.: Modeled effects of irrigation on surface
climate in the Heihe River Basin, Northwest China: Modeling Effects of Irrigation, J. Geophys. Res.-Atmos., 122, 7881–7895, https://doi.org/10.1002/2017JD026732, 2017.
Zhang, Y., Liu, S., Song, L., Li, X., Jia, Z., Xu, T., Xu, Z., Ma, Y., Zhou,
J., Yang, X., He, X., Yao, Y., and Hu, G.: Integrated Validation of Coarse
Remotely Sensed Evapotranspiration Products over Heterogeneous Land Surfaces, Remote Sens., 14, 3467, https://doi.org/10.3390/rs14143467, 2022.
Zhang, Z., Barlage, M., Chen, F., Li, Y., Helgason, W., Xu, X., Liu, X., and
Li, Z.: Joint Modeling of Crop and Irrigation in the central United States
Using the Noah-MP Land Surface Model, J. Adv. Model. Earth Syst., 12, e2020MS002159, https://doi.org/10.1029/2020MS002159, 2020.
Zhang, Z., Arnault, J., Laux, P., Ma, N., Wei, J., Shang, S., and Kunstmann,
H.: Convection-permitting fully coupled WRF-Hydro ensemble simulations in high mountain environment: impact of boundary layer- and lateral flow parameterizations on land–atmosphere interactions, Clim. Dynam., 59, 1355–1376, https://doi.org/10.1007/s00382-021-06044-9, 2021a.
Zhang, Z., Arnault, J., Laux, P., Ma, N., Wei, J., and Kunstmann, H.: Diurnal cycle of surface energy fluxes in high mountain terrain: High-resolution fully coupled atmosphere-hydrology modelling and impact of lateral flow, Hydrol. Process., 35, e14454, https://doi.org/10.1002/hyp.14454, 2021b.
Zhang, Z., Chen, F., Barlage, M., Bortolotti, L. E., Famiglietti, J., Li, Z.,
Ma, X., and Li, Y.: Cooling effects revealed by modeling of wetlands and
land-atmosphere interactions, Water Resour. Res., 58, e2021WR030573, https://doi.org/10.1029/2021WR030573, 2022.
Zhao, J., Feng, H., Xu, T., Xiao, J., Guerrieri, R., Liu, S., Wu, X., He, X., and He, X.: Physiological and environmental control on ecosystem water use efficiency in response to drought across the northern hemisphere, Sci. Total Environ., 758, 143599, https://doi.org/10.1016/j.scitotenv.2020.143599, 2021.
Zhao, L. and Yang, Z. L.: Multi-sensor land data assimilation: Toward a
robust global soil moisture and snow estimation, Remote Sens. Environ., 216,
13–27, https://doi.org/10.1016/j.rse.2018.06.033, 2018.
Zhao, W. L., Gentine, P., Reichstein, M., Zhang, Y., Zhou, S., Wen, Y., Lin,
C., Li, X., and Qiu, G. Y.: Physics-Constrained Machine Learning of Evapotranspiration. Geophys. Res. Lett., 46, 14496–14507, https://doi.org/10.1029/2019GL085291, 2019.
Zheng, C., Liu, S., Song, L., Xu, Z., Guo, J., Ma, Y., Ju, Q., and Wang, J.:
Comparison of sensible and latent heat fluxes from optical-microwave
scintillometers and eddy covariance systems with respect to surface energy
balance closure, Agr. Forest Meteorol., 331, 109345, https://doi.org/10.1016/j.agrformet.2023.109345, 2023.
Zhong, B., Ma, P., Nie, A., Yang, A., Yao, Y., Lü, W., Zhang, H., and Liu, Q.: Land cover mapping using time series HJ-1/CCD data, Sci. China Earth Sci., 57, 1790–1799, https://doi.org/10.1007/s11430-014-4877-5, 2014.
Zhou, Y., Liao, W., and Li, X.: The contributions of individual factors to the oasis cold island effect intensity in the Heihe River Basin, Agr. Forest
Meteorol., 312, 108706, https://doi.org/10.1016/j.agrformet.2021.108706, 2022.
Short summary
This study highlights the role of integrating vegetation and multi-source soil moisture observations in regional climate models via a hybrid data assimilation and machine learning method. In particular, we show that this approach can improve land surface fluxes, near-surface atmospheric conditions, and land–atmosphere interactions by implementing detailed land characterization information in basins with complex underlying surfaces.
This study highlights the role of integrating vegetation and multi-source soil moisture...
