Articles | Volume 26, issue 24
https://doi.org/10.5194/hess-26-6311-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-6311-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Dec 2022
Research article |
| 16 Dec 2022
| 16 Dec 2022
Simulating carbon and water fluxes using a coupled process-based terrestrial biosphere model and joint assimilation of leaf area index and surface soil moisture
Sinan Li
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Beijing 100094, China
College of Resources and Environment, University of Chinese Academy
of Sciences, No. 19A Yuquan Road, Beijing 100049, China
Li Zhang
CORRESPONDING AUTHOR
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Beijing 100094, China
International Research Center of Big Data for Sustainable
Development Goals, Beijing 100094, China
Jingfeng Xiao
CORRESPONDING AUTHOR
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, New Hampshire 03824, USA
Rui Ma
School of Remote Sensing and Information Engineering, Wuhan
University, Wuhan 430079, China
Xiangjun Tian
International Center for Climate and Environment Sciences (ICCES),
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing
100029, China
Min Yan
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Beijing 100094, China
International Research Center of Big Data for Sustainable
Development Goals, Beijing 100094, China
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Xufeng Wang, Tao Che, Jingfeng Xiao, Tonghong Wang, Junlei Tan, Yang Zhang, Zhiguo Ren, Liying Geng, Haibo Wang, Ziwei Xu, Shaomin Liu, and Xin Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-370, https://doi.org/10.5194/essd-2024-370, 2024
Preprint under review for ESSD
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In this study, carbon flux and auxiliary meteorological data were post-processed to create an analysis-ready dataset for 34 sites across six ecosystems in the Heihe River Basin. Eighteen sites have multi-year observations, while 16 were observed only during the 2012 growing season, totaling 1,513 site-months. This dataset can be used to explore carbon exchange, assess ecosystem responses to climate change, support upscaling studies, and evaluate carbon cycle models.
Yi Liu, Jingfeng Xiao, Xing Li, and Yue Li
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-105, https://doi.org/10.5194/hess-2024-105, 2024
Preprint under review for HESS
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This work demonstrates that multi-source satellite-based water and carbon fluxes can capture critical soil moisture at a large spatial scale. In particular, they show water limitation increase in western and southern China, which is due to water demand increase and water available decrease, respectively.
Mana Gharun, Ankit Shekhar, Jingfeng Xiao, Xing Li, and Nina Buchmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-423, https://doi.org/10.5194/egusphere-2024-423, 2024
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In 2022, Europe's forests faced unprecedented dry conditions. Our study aimed to understand how different forest types respond to extreme drought. Using meteorological data and satellite imagery, we compared 2022 with two previous extreme years, 2003 and 2018. Despite less severe drought in 2022, forests showed a 30 % greater decline in photosynthesis compared to 2018 and 60 % more than 2003. This suggests a concerning trend of declining forest resilience to more frequent droughts.
Shanlei Sun, Zaoying Bi, Jingfeng Xiao, Yi Liu, Ge Sun, Weimin Ju, Chunwei Liu, Mengyuan Mu, Jinjian Li, Yang Zhou, Xiaoyuan Li, Yibo Liu, and Haishan Chen
Earth Syst. Sci. Data, 15, 4849–4876, https://doi.org/10.5194/essd-15-4849-2023, https://doi.org/10.5194/essd-15-4849-2023, 2023
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Based on various existing datasets, we comprehensively considered spatiotemporal differences in land surfaces and CO2 effects on plant stomatal resistance to parameterize the Shuttleworth–Wallace model, and we generated a global 5 km ensemble mean monthly potential evapotranspiration (PET) dataset (including potential transpiration PT and soil evaporation PE) during 1982–2015. The new dataset may be used by academic communities and various agencies to conduct various studies.
Xinyan Liu, Tao He, Shunlin Liang, Ruibo Li, Xiongxin Xiao, Rui Ma, and Yichuan Ma
Earth Syst. Sci. Data, 15, 3641–3671, https://doi.org/10.5194/essd-15-3641-2023, https://doi.org/10.5194/essd-15-3641-2023, 2023
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We proposed a data fusion strategy that combines the complementary features of multiple-satellite cloud fraction (CF) datasets and generated a continuous monthly 1° daytime cloud fraction product covering the entire Arctic during the sunlit months in 2000–2020. This study has positive significance for reducing the uncertainties for the assessment of surface radiation fluxes and improving the accuracy of research related to climate change and energy budgets, both regionally and globally.
Brendan Byrne, Junjie Liu, Yonghong Yi, Abhishek Chatterjee, Sourish Basu, Rui Cheng, Russell Doughty, Frédéric Chevallier, Kevin W. Bowman, Nicholas C. Parazoo, David Crisp, Xing Li, Jingfeng Xiao, Stephen Sitch, Bertrand Guenet, Feng Deng, Matthew S. Johnson, Sajeev Philip, Patrick C. McGuire, and Charles E. Miller
Biogeosciences, 19, 4779–4799, https://doi.org/10.5194/bg-19-4779-2022, https://doi.org/10.5194/bg-19-4779-2022, 2022
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Plants draw CO2 from the atmosphere during the growing season, while respiration releases CO2 to the atmosphere throughout the year, driving seasonal variations in atmospheric CO2 that can be observed by satellites, such as the Orbiting Carbon Observatory 2 (OCO-2). Using OCO-2 XCO2 data and space-based constraints on plant growth, we show that permafrost-rich northeast Eurasia has a strong seasonal release of CO2 during the autumn, hinting at an unexpectedly large respiration signal from soils.
Rui Ma, Jingfeng Xiao, Shunlin Liang, Han Ma, Tao He, Da Guo, Xiaobang Liu, and Haibo Lu
Geosci. Model Dev., 15, 6637–6657, https://doi.org/10.5194/gmd-15-6637-2022, https://doi.org/10.5194/gmd-15-6637-2022, 2022
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Parameter optimization can improve the accuracy of modeled carbon fluxes. Few studies conducted pixel-level parameterization because it requires a high computational cost. Our paper used high-quality spatial products to optimize parameters at the pixel level, and also used the machine learning method to improve the speed of optimization. The results showed that there was significant spatial variability of parameters and we also improved the spatial pattern of carbon fluxes.
Jing Fang, Xing Li, Jingfeng Xiao, Xiaodong Yan, Bolun Li, and Feng Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-452, https://doi.org/10.5194/essd-2021-452, 2022
Revised manuscript not accepted
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The dataset provided the vegetation photosynthetic phenology instead of traditional phenology to represent plant seasonal activities. This dataset had the latest period (2001–2020) and a fine spatial resolution (0.05 degree). Our phenology metrics revealed the spatial-temporal patterns of the multiple growing seasons in the Northern Hemisphere. The dataset will facilitate various research such as developing models, evaluating phenology shifts, and monitoring climate change worldwide.
Fei Jiang, Hengmao Wang, Jing M. Chen, Weimin Ju, Xiangjun Tian, Shuzhuang Feng, Guicai Li, Zhuoqi Chen, Shupeng Zhang, Xuehe Lu, Jane Liu, Haikun Wang, Jun Wang, Wei He, and Mousong Wu
Atmos. Chem. Phys., 21, 1963–1985, https://doi.org/10.5194/acp-21-1963-2021, https://doi.org/10.5194/acp-21-1963-2021, 2021
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We present a 6-year inversion from 2010 to 2015 for the global and regional carbon fluxes using only the GOSAT XCO2 retrievals. We find that the XCO2 retrievals could significantly improve the modeling of atmospheric CO2 concentrations and that the inferred interannual variations in the terrestrial carbon fluxes in most land regions have a better relationship with the changes in severe drought area or leaf area index, or are more consistent with the previous estimates about drought impact.
Rui Han and Xiangjun Tian
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-54, https://doi.org/10.5194/gmd-2019-54, 2019
Preprint withdrawn
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This manuscript mainly introduce a new version of the carbon cycle data assimilation system Tan-Tracker (v1), which uses a novel dual-pass assimilation framework and based on an advanced assimilation algorithm NLS-4DVar. Tan-Tracker (v1) aims to find more accurate surface CO2 flux estimates based on satellite XCO2 observations. With a more accurate surface carbon flux, Tan-Tracker (v1) can provide a new perspective on carbon budget and become a better tool for carbon cycle research.
Xu Yue, Nadine Unger, Kandice Harper, Xiangao Xia, Hong Liao, Tong Zhu, Jingfeng Xiao, Zhaozhong Feng, and Jing Li
Atmos. Chem. Phys., 17, 6073–6089, https://doi.org/10.5194/acp-17-6073-2017, https://doi.org/10.5194/acp-17-6073-2017, 2017
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While it is widely recognized that air pollutants adversely affect human health and climate change, their impacts on the regional carbon balance are less well understood. We apply an Earth system model to quantify the combined effects of ozone and aerosol particles on net primary production in China. Ozone vegetation damage dominates over the aerosol effects, leading to a substantial net suppression of land carbon uptake in the present and future worlds.
Jingfeng Xiao, Shuguang Liu, and Paul C. Stoy
Biogeosciences, 13, 3665–3675, https://doi.org/10.5194/bg-13-3665-2016, https://doi.org/10.5194/bg-13-3665-2016, 2016
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This special issue showcases recent advancements on the impacts of disturbances and extreme events on the carbon (C) cycle. Notable advancements include quantifying harvest impacts on forest structure, recovery, and carbon stocks; observed dissolved organic C and methane increases in thermokarst lakes following summer warming; disentangling the roles of herbivores and fire on forest carbon dioxide flux; and improved atmospheric inversion of regional C flux by incorporating disturbances.
Z. Peng, M. Zhang, X. Kou, X. Tian, and X. Ma
Atmos. Chem. Phys., 15, 1087–1104, https://doi.org/10.5194/acp-15-1087-2015, https://doi.org/10.5194/acp-15-1087-2015, 2015
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We associated the smoothing operator with the atmospheric transport model to constitute the persistence dynamical model to forecast the surface CO2 flux scaling factors for the purpose of resolving the "signal-to-noise" problem, as well as transporting the useful observed information onto the next assimilation cycle. Based on this improvement, a regional surface CO2 flux inversion system, CFI-CMAQ, has been developed. The OSSEs showed that the performance of CFI-CMAQ is effective and promising.
X. Tian, Z. Xie, Y. Liu, Z. Cai, Y. Fu, H. Zhang, and L. Feng
Atmos. Chem. Phys., 14, 13281–13293, https://doi.org/10.5194/acp-14-13281-2014, https://doi.org/10.5194/acp-14-13281-2014, 2014
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A new carbon cycle data assimilation system (Tan-Tracker) is developed based on an advanced hybrid assimilation approach, as a part of the preparation for the launch of the Chinese carbon dioxide observation satellite (TanSat). Tan-Tracker adopts a joint data assimilation framework to simultaneously estimate CO2 concentrations and CFs and thus gradually reduce the uncertainty in the CO2 concentration evolution through continuously fitting model CO2 concentration simulations to the observations.
W. Wang, J. Xiao, S. V. Ollinger, A. R. Desai, J. Chen, and A. Noormets
Biogeosciences, 11, 6667–6682, https://doi.org/10.5194/bg-11-6667-2014, https://doi.org/10.5194/bg-11-6667-2014, 2014
F. Deng, J. M. Chen, Y. Pan, W. Peters, R. Birdsey, K. McCullough, and J. Xiao
Biogeosciences, 10, 5335–5348, https://doi.org/10.5194/bg-10-5335-2013, https://doi.org/10.5194/bg-10-5335-2013, 2013
Related subject area
Subject: Ecohydrology | Techniques and Approaches: Remote Sensing and GIS
Circumarctic land cover diversity considering wetness gradients
Multi-decadal floodplain classification and trend analysis in the Upper Columbia River valley, British Columbia
Estimating leaf moisture content at global scale from passive microwave satellite observations of vegetation optical depth
Untangling irrigation effects on maize water and heat stress alleviation using satellite data
Information-based uncertainty decomposition in dual-channel microwave remote sensing of soil moisture
Assessing the large-scale plant–water relations in the humid, subtropical Pearl River basin of China
Technical note: Accounting for snow in the estimation of root zone water storage capacity from precipitation and evapotranspiration fluxes
Long-term water stress and drought assessment of Mediterranean oak savanna vegetation using thermal remote sensing
Temporal interpolation of land surface fluxes derived from remote sensing – results with an unmanned aerial system
Pattern and structure of microtopography implies autogenic origins in forested wetlands
The influence of water table depth on evapotranspiration in the Amazon arc of deforestation
Does the Normalized Difference Vegetation Index explain spatial and temporal variability in sap velocity in temperate forest ecosystems?
Comparison of MODIS and SWAT evapotranspiration over a complex terrain at different spatial scales
Evolution of the vegetation system in the Heihe River basin in the last 2000 years
Laser vision: lidar as a transformative tool to advance critical zone science
Attribution of satellite-observed vegetation trends in a hyper-arid region of the Heihe River basin, Western China
Evapotranspiration and water yield over China's landmass from 2000 to 2010
Satellite-based analysis of recent trends in the ecohydrology of a semi-arid region
Soil moisture controls on patterns of grass green-up in Inner Mongolia: an index based approach
Groundwater surface water interactions and the role of phreatophytes in identifying recharge zones
Quantifying the performance of automated GIS-based geomorphological approaches for riparian zone delineation using digital elevation models
Climate change, growing season water deficit and vegetation activity along the north–south transect of eastern China from 1982 through 2006
Hydrological differentiation and spatial distribution of high altitude wetlands in a semi-arid Andean region derived from satellite data
The impact of in-canopy wind profile formulations on heat flux estimation in an open orchard using the remote sensing-based two-source model
The use of remote sensing to quantify wetland loss in the Choke Mountain range, Upper Blue Nile basin, Ethiopia
Annett Bartsch, Aleksandra Efimova, Barbara Widhalm, Xaver Muri, Clemens von Baeckmann, Helena Bergstedt, Ksenia Ermokhina, Gustaf Hugelius, Birgit Heim, and Marina Leibman
Hydrol. Earth Syst. Sci., 28, 2421–2481, https://doi.org/10.5194/hess-28-2421-2024, https://doi.org/10.5194/hess-28-2421-2024, 2024
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Wetness gradients and landcover diversity for the entire Arctic tundra have been assessed using a novel satellite-data-based map. Patterns of lakes, wetlands, general soil moisture conditions and vegetation physiognomy are represented at 10 m. About 40 % of the area north of the treeline falls into three units of dry types, with limited shrub growth. Wetter regions have higher landcover diversity than drier regions.
Italo Sampaio Rodrigues, Christopher Hopkinson, Laura Chasmer, Ryan J. MacDonald, Suzanne E. Bayley, and Brian Brisco
Hydrol. Earth Syst. Sci., 28, 2203–2221, https://doi.org/10.5194/hess-28-2203-2024, https://doi.org/10.5194/hess-28-2203-2024, 2024
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The research evaluated the trends and changes in land cover and river discharge in the Upper Columbia River Wetlands using remote sensing and hydroclimatic data. The river discharge increased during the peak flow season, resulting in a positive trend in the open-water extent in the same period, whereas open-water area declined on an annual basis. Furthermore, since 2003 the peak flow has occurred 11 d earlier than during 1903–1928, which has led to larger discharges in a shorter time.
Matthias Forkel, Luisa Schmidt, Ruxandra-Maria Zotta, Wouter Dorigo, and Marta Yebra
Hydrol. Earth Syst. Sci., 27, 39–68, https://doi.org/10.5194/hess-27-39-2023, https://doi.org/10.5194/hess-27-39-2023, 2023
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The live fuel moisture content (LFMC) of vegetation canopies is a driver of wildfires. We investigate the relation between LFMC and passive microwave satellite observations of vegetation optical depth (VOD) and develop a method to estimate LFMC from VOD globally. Our global VOD-based estimates of LFMC can be used to investigate drought effects on vegetation and fire risks.
Peng Zhu and Jennifer Burney
Hydrol. Earth Syst. Sci., 26, 827–840, https://doi.org/10.5194/hess-26-827-2022, https://doi.org/10.5194/hess-26-827-2022, 2022
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Satellite data were used to disentangle water and heat stress alleviation due to irrigation. Our findings are as follows. (1) Irrigation-induced cooling was captured by satellite LST but air temperature failed. (2) Irrigation extended maize growing season duration, especially during grain filling. (3) Water and heat stress alleviation constitutes 65 % and 35 % of the irrigation benefit. (4) The crop model simulating canopy temperature better captures the irrigation benefit.
Bonan Li and Stephen P. Good
Hydrol. Earth Syst. Sci., 25, 5029–5045, https://doi.org/10.5194/hess-25-5029-2021, https://doi.org/10.5194/hess-25-5029-2021, 2021
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We found that satellite retrieved soil moisture has large uncertainty, with uncertainty caused by the algorithm being closely related to the satellite soil moisture quality. The information provided by the two main inputs is mainly redundant. Such redundant components and synergy components provided by two main inputs to the satellite soil moisture are related to how the satellite algorithm performs. The satellite remote sensing algorithms may be improved by performing such analysis.
Hailong Wang, Kai Duan, Bingjun Liu, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 25, 4741–4758, https://doi.org/10.5194/hess-25-4741-2021, https://doi.org/10.5194/hess-25-4741-2021, 2021
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Using remote sensing and reanalysis data, we examined the relationships between vegetation development and water resource availability in a humid subtropical basin. We found overall increases in total water storage and surface greenness and vegetation production, and the changes were particularly profound in cropland-dominated regions. Correlation analysis implies water availability leads the variations in greenness and production, and irrigation may improve production during dry periods.
David N. Dralle, W. Jesse Hahm, K. Dana Chadwick, Erica McCormick, and Daniella M. Rempe
Hydrol. Earth Syst. Sci., 25, 2861–2867, https://doi.org/10.5194/hess-25-2861-2021, https://doi.org/10.5194/hess-25-2861-2021, 2021
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Root zone water storage capacity determines how much water can be stored belowground to support plants during periods without precipitation. Here, we develop a satellite remote sensing method to estimate this key variable at large scales that matter for management. Importantly, our method builds on previous approaches by accounting for snowpack, which may bias estimates from existing approaches. Ultimately, our method will improve large-scale understanding of plant access to subsurface water.
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.
Sheng Wang, Monica Garcia, Andreas Ibrom, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 24, 3643–3661, https://doi.org/10.5194/hess-24-3643-2020, https://doi.org/10.5194/hess-24-3643-2020, 2020
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Remote sensing only provides snapshots of rapidly changing land surface variables; this limits its application for water resources and ecosystem management. To obtain continuous estimates of surface temperature, soil moisture, evapotranspiration, and ecosystem productivity, a simple and operational modelling scheme is presented. We demonstrate it with temporally sparse optical and thermal remote sensing data from an unmanned aerial system at a Danish bioenergy plantation eddy covariance site.
Jacob S. Diamond, Daniel L. McLaughlin, Robert A. Slesak, and Atticus Stovall
Hydrol. Earth Syst. Sci., 23, 5069–5088, https://doi.org/10.5194/hess-23-5069-2019, https://doi.org/10.5194/hess-23-5069-2019, 2019
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We found evidence for spatial patterning of soil elevation in forested wetlands that was well explained by hydrology. The patterns that we found were strongest at wetter sites, and were weakest at drier sites. When a site was wet, soil elevations typically only belonged to two groups: tall "hummocks" and low "hollows. The tall, hummock groups were spaced equally apart from each other and were a similar size. We believe this is evidence for a biota–hydrology feedback that creates hummocks.
John O'Connor, Maria J. Santos, Karin T. Rebel, and Stefan C. Dekker
Hydrol. Earth Syst. Sci., 23, 3917–3931, https://doi.org/10.5194/hess-23-3917-2019, https://doi.org/10.5194/hess-23-3917-2019, 2019
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The Amazon rainforest has undergone extensive land use change, which greatly reduces the rate of evapotranspiration. Forest with deep roots is replaced by agriculture with shallow roots. The difference in rooting depth can greatly reduce access to water, especially during the dry season. However, large areas of the Amazon have a sufficiently shallow water table that may provide access for agriculture. We used remote sensing observations to compare the impact of deep and shallow water tables.
Anne J. Hoek van Dijke, Kaniska Mallick, Adriaan J. Teuling, Martin Schlerf, Miriam Machwitz, Sibylle K. Hassler, Theresa Blume, and Martin Herold
Hydrol. Earth Syst. Sci., 23, 2077–2091, https://doi.org/10.5194/hess-23-2077-2019, https://doi.org/10.5194/hess-23-2077-2019, 2019
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Satellite images are often used to estimate land water fluxes over a larger area. In this study, we investigate the link between a well-known vegetation index derived from satellite data and sap velocity, in a temperate forest in Luxembourg. We show that the link between the vegetation index and transpiration is not constant. Therefore we suggest that the use of vegetation indices to predict transpiration should be limited to ecosystems and scales where the link has been confirmed.
Olanrewaju O. Abiodun, Huade Guan, Vincent E. A. Post, and Okke Batelaan
Hydrol. Earth Syst. Sci., 22, 2775–2794, https://doi.org/10.5194/hess-22-2775-2018, https://doi.org/10.5194/hess-22-2775-2018, 2018
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In recent decades, evapotranspiration estimation has been improved by remote sensing methods as well as by hydrological models. However, comparing these methods shows differences of up to 31 % at a spatial resolution of 1 km2. Land cover differences and catchment averaged climate data in the hydrological model were identified as the principal causes of the differences in results. The implication is that water management will have to deal with large uncertainty in estimated water balances.
Shoubo Li, Yan Zhao, Yongping Wei, and Hang Zheng
Hydrol. Earth Syst. Sci., 21, 4233–4244, https://doi.org/10.5194/hess-21-4233-2017, https://doi.org/10.5194/hess-21-4233-2017, 2017
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This study aims to investigate the evolution of natural and crop vegetation systems over the past 2000 years accommodated with the changes in water regimes at the basin scale. It is based on remote-sensing data and previous historical research. The methods developed and the findings obtained from this study could assist in understanding how current ecosystem problems were created in the past and what their implications for future river basin management are.
A. A. Harpold, J. A. Marshall, S. W. Lyon, T. B. Barnhart, B. A. Fisher, M. Donovan, K. M. Brubaker, C. J. Crosby, N. F. Glenn, C. L. Glennie, P. B. Kirchner, N. Lam, K. D. Mankoff, J. L. McCreight, N. P. Molotch, K. N. Musselman, J. Pelletier, T. Russo, H. Sangireddy, Y. Sjöberg, T. Swetnam, and N. West
Hydrol. Earth Syst. Sci., 19, 2881–2897, https://doi.org/10.5194/hess-19-2881-2015, https://doi.org/10.5194/hess-19-2881-2015, 2015
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This review's objective is to demonstrate the transformative potential of lidar by critically assessing both challenges and opportunities for transdisciplinary lidar applications in geomorphology, hydrology, and ecology. We find that using lidar to its full potential will require numerous advances, including more powerful open-source processing tools, new lidar acquisition technologies, and improved integration with physically based models and complementary observations.
Y. Wang, M. L. Roderick, Y. Shen, and F. Sun
Hydrol. Earth Syst. Sci., 18, 3499–3509, https://doi.org/10.5194/hess-18-3499-2014, https://doi.org/10.5194/hess-18-3499-2014, 2014
Y. Liu, Y. Zhou, W. Ju, J. Chen, S. Wang, H. He, H. Wang, D. Guan, F. Zhao, Y. Li, and Y. Hao
Hydrol. Earth Syst. Sci., 17, 4957–4980, https://doi.org/10.5194/hess-17-4957-2013, https://doi.org/10.5194/hess-17-4957-2013, 2013
M. Gokmen, Z. Vekerdy, W. Verhoef, and O. Batelaan
Hydrol. Earth Syst. Sci., 17, 3779–3794, https://doi.org/10.5194/hess-17-3779-2013, https://doi.org/10.5194/hess-17-3779-2013, 2013
H. Liu, F. Tian, H. C. Hu, H. P. Hu, and M. Sivapalan
Hydrol. Earth Syst. Sci., 17, 805–815, https://doi.org/10.5194/hess-17-805-2013, https://doi.org/10.5194/hess-17-805-2013, 2013
T. S. Ahring and D. R. Steward
Hydrol. Earth Syst. Sci., 16, 4133–4142, https://doi.org/10.5194/hess-16-4133-2012, https://doi.org/10.5194/hess-16-4133-2012, 2012
D. Fernández, J. Barquín, M. Álvarez-Cabria, and F. J. Peñas
Hydrol. Earth Syst. Sci., 16, 3851–3862, https://doi.org/10.5194/hess-16-3851-2012, https://doi.org/10.5194/hess-16-3851-2012, 2012
P. Sun, Z. Yu, S. Liu, X. Wei, J. Wang, N. Zegre, and N. Liu
Hydrol. Earth Syst. Sci., 16, 3835–3850, https://doi.org/10.5194/hess-16-3835-2012, https://doi.org/10.5194/hess-16-3835-2012, 2012
M. Otto, D. Scherer, and J. Richters
Hydrol. Earth Syst. Sci., 15, 1713–1727, https://doi.org/10.5194/hess-15-1713-2011, https://doi.org/10.5194/hess-15-1713-2011, 2011
C. Cammalleri, M. C. Anderson, G. Ciraolo, G. D'Urso, W. P. Kustas, G. La Loggia, and M. Minacapilli
Hydrol. Earth Syst. Sci., 14, 2643–2659, https://doi.org/10.5194/hess-14-2643-2010, https://doi.org/10.5194/hess-14-2643-2010, 2010
E. Teferi, S. Uhlenbrook, W. Bewket, J. Wenninger, and B. Simane
Hydrol. Earth Syst. Sci., 14, 2415–2428, https://doi.org/10.5194/hess-14-2415-2010, https://doi.org/10.5194/hess-14-2415-2010, 2010
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Short summary
Accurate estimation for global GPP and ET is important in climate change studies. In this study, the GLASS LAI, SMOS, and SMAP datasets were assimilated jointly and separately in a coupled model. The results show that the performance of joint assimilation for GPP and ET is better than that of separate assimilation. The joint assimilation in water-limited regions performed better than in humid regions, and the global assimilation results had higher accuracy than other products.
Accurate estimation for global GPP and ET is important in climate change studies. In this study,...
