Articles | Volume 17, issue 12
https://doi.org/10.5194/hess-17-4957-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-17-4957-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
10 Dec 2013
Research article |
| 10 Dec 2013
Evapotranspiration and water yield over China's landmass from 2000 to 2010
Y. Liu
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing, 210023, China
International Institute for Earth System Sciences, Nanjing University, Nanjing, 210023, China
Y. Zhou
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing, 210023, China
School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing, 210023, China
W. Ju
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing, 210023, China
International Institute for Earth System Sciences, Nanjing University, Nanjing, 210023, China
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing, 210023, China
International Institute for Earth System Sciences, Nanjing University, Nanjing, 210023, China
S. Wang
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
H. He
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
H. Wang
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
D. Guan
Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China
F. Zhao
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Y. Li
Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810008, China
Y. Hao
Graduate University of Chinese Academy of Sciences, Beijing, 100049, China
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Biogeosciences, 11, 2583–2599, https://doi.org/10.5194/bg-11-2583-2014, https://doi.org/10.5194/bg-11-2583-2014, 2014
P. C. Stoy, M. C. Dietze, A. D. Richardson, R. Vargas, A. G. Barr, R. S. Anderson, M. A. Arain, I. T. Baker, T. A. Black, J. M. Chen, R. B. Cook, C. M. Gough, R. F. Grant, D. Y. Hollinger, R. C. Izaurralde, C. J. Kucharik, P. Lafleur, B. E. Law, S. Liu, E. Lokupitiya, Y. Luo, J. W. Munger, C. Peng, B. Poulter, D. T. Price, D. M. Ricciuto, W. J. Riley, A. K. Sahoo, K. Schaefer, C. R. Schwalm, H. Tian, H. Verbeeck, and E. Weng
Biogeosciences, 10, 6893–6909, https://doi.org/10.5194/bg-10-6893-2013, https://doi.org/10.5194/bg-10-6893-2013, 2013
J. M. Chen, G. Mo, and F. Deng
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-26529-2013, https://doi.org/10.5194/acpd-13-26529-2013, 2013
Revised manuscript not accepted
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
F. Jiang, H. W. Wang, J. M. Chen, L. X. Zhou, W. M. Ju, A. J. Ding, L. X. Liu, and W. Peters
Biogeosciences, 10, 5311–5324, https://doi.org/10.5194/bg-10-5311-2013, https://doi.org/10.5194/bg-10-5311-2013, 2013
X. L. Ren, H. L. He, L. Zhang, L. Zhou, G. R. Yu, and J. W. Fan
Ann. Geophys., 31, 277–289, https://doi.org/10.5194/angeo-31-277-2013, https://doi.org/10.5194/angeo-31-277-2013, 2013
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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, grassland and clay with critical soil moisture higher than average soil moisture may be in a state of water limitation for long periods. Increased water demand could expose western grassland to more vulnerability.
Lu Wang, Haiting Gu, Li Liu, Xiao Liang, Siwei Chen, and Yue-Ping Xu
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To understand how ecohydrological variables evolve jointly and why, this study develops a framework using correlation and causality to construct complex relationships between variables at the system level. Causality provides more detailed information that the compound causes of evolutions regarding any variable can be traced. Joint evolution is controlled by the combination of external drivers and direct causality. Overall, the study facilitates the comprehension of ecohydrological processes.
Annett Bartsch, Aleksandra Efimova, Barbara Widhalm, Xaver Muri, Clemens von Baeckmann, Helena Bergstedt, Ksenia Ermokhina, Gustaf Hugelius, Birgit Heim, and Marina Leibman
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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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Sinan Li, Li Zhang, Jingfeng Xiao, Rui Ma, Xiangjun Tian, and Min Yan
Hydrol. Earth Syst. Sci., 26, 6311–6337, https://doi.org/10.5194/hess-26-6311-2022, https://doi.org/10.5194/hess-26-6311-2022, 2022
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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.
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
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
Cited articles
Amthor, J. S., Chen, J. M., Clein, J. S., Frolking, S. E., Goulden, M. L., Grant, R. F., Kimball, J. S., King, A. W., McGuire, A. D., Nikolov, N. T., Potter, C. S., Wang, S., and Wofsy, S. C.: Boreal forest CO2 exchange and evapotranspiration predicted by nine ecosystem process models: Intermodel comparisons and relationships to field measurements, J. Geophys. Res.-Atmos., 106, 33623–33648, https://doi.org/10.1029/2000jd900850, 2001.
Anderson, R. G., Jin, Y., and Goulden, M. L.: Assessing regional evapotranspiration and water balance across a Mediterranean montane climate gradient, Agr. Forest Meteorol., 166–167, 10–22, https://doi.org/10.1016/j.agrformet.2012.07.004, 2012.
Bunce, J.: Carbon dioxide effects on stomatal responses to the environment and water use by crops under field conditions, Oecologia, 140, 1–10, https://doi.org/10.1007/s00442-003-1401-6, 2004.
Cao, S. X., Chen, L., Shankman, D., Wang, C. M., Wang, X. B., and Zhang, H.: Excessive reliance on afforestation in China's arid and semi-arid regions: Lessons in ecological restoration, Earth-Sci Rev., 104, 240–245, https://doi.org/10.1016/j.earscirev.2010.11.002, 2011.
Chen, B. Z., Chen, J. M., and Ju, W. M.: Remote sensing-based ecosystem-atmosphere simulation scheme (EASS) – Model formulation and test with multiple-year data, Ecol. Model., 209, 277–300, 2007.
Chen, J. M. and Leblanc, S. G.: A four-scale bidirectional reflectance model based on canopy architecture, IEEE T. Geosci. Remote, 35, 1316–1337, 1997.
Chen, J. M., Liu, J., Cihlar, J., and Goulden, M. L.: Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications, Ecol. Model., 124, 99–119, 1999.
Chen, J. M., Chen, X. Y., Ju, W. M., and Geng, X. Y.: Distributed hydrological model for mapping evapotranspiration using remote sensing inputs, J. Hydrol., 305, 15–39, 2005.
Chen, J. M., Deng, F., and Chen, M. Z.: Locally adjusted cubic-spline capping for reconstructing seasonal trajectories of a satellite-derived surface parameter, IEEE T. Geosci. Remote, 44, 2230–2238, 2006.
Chen, J. M., Mo, G., Pisek, J., Liu, J., Deng, F., Ishizawa, M., and Chan, D.: Effects of foliage clumping on the estimation of global terrestrial gross primary productivity, Global Biogeochem. Cy., 26, GB1019, https://doi.org/10.1029/2010gb003996, 2012.
Cheng, L., Xu, Z., Wang, D., and Cai, X.: Assessing interannual variability of evapotranspiration at the catchment scale using satellite-based evapotranspiration data sets, Water Resour. Res., 47, W09509, https://doi.org/10.1029/2011wr010636, 2011.
Cong, Z. T., Zhao, J. J., Yang, D. W., and Ni, G. H.: Understanding the hydrological trends of river basins in China, J. Hydrol., 388, 350–356, https://doi.org/10.1016/j.jhydrol.2010.05.013, 2010.
Courault, D., Seguin, B., and Olioso, A.: Review on estimation of evapotranspiration from remote sensing data: From empirical to numerical modeling approaches, Irrig. Drain. Syst., 19, 223–249, https://doi.org/10.1007/s10795-005-5186-0, 2005.
Deng, F., Chen, J. M., Plummer, S., Chen, M. Z., and Pisek, J.: Algorithm for global leaf area index retrieval using satellite imagery, IEEE T. Geosci. Remote, 44, 2219–2229, https://doi.org/10.1109/tgrs.2006.872100, 2006.
Dirmeyer, P. A., Gao, X., Zhao, M., Guo, Z., Oki, T., and Hanasaki, N.: GSWP-2: Multimodel analysis and implications for our perception of the land surface, B. Am. Meteorol. Soc., 87, 1381–1397, https://doi.org/10.1175/bams-87-10-1381, 2006.
El Maayar, M. and Chen, J. M.: Spatial scaling of evapotranspiration as affected by heterogeneities in vegetation, topography, and soil texture, Remote Sens. Environ., 102, 33–51, 2006.
Fang, J., Tang, Y., and Son, Y.: Why are East Asian ecosystems important for carbon cycle research?, Sci. China Life Sci., 53, 753–756, https://doi.org/10.1007/s11427-010-4032-2, 2010.
FAO: Food and Agriculture Organization: Global Forest Resources Assessment, Rome, Italy, 2010.
Farquhar, G. D., Caemmerer, S. V., and Berry, J. A.: A biochemical-model of photosynthetic CO2 assimilation in leaves of C3 species, Planta, 149, 78–90, 1980.
Feng, X., Liu, G., Chen, J. M., Chen, M., Liu, J., Ju, W. M., Sun, R., and Zhou, W.: Net primary productivity of China's terrestrial ecosystems from a process model driven by remote sensing, J. Environ. Manage., 85, 563–573, https://doi.org/10.1016/j.jenvman.2006.09.021, 2007.
Fernández-Prieto, D., van Oevelen, P., Su, Z., and Wagner, W.: Editorial "Advances in Earth observation for water cycle science", Hydrol. Earth Syst. Sci., 16, 543–549, https://doi.org/10.5194/hess-16-543-2012, 2012.
Fisher, J. B., Tu, K. P., and Baldocchi, D. D.: Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites, Remote Sens. Environ., 112, 901–919, 2008.
Fisher, J. B., Whittaker, R. J., and Malhi, Y.: ET come home: potential evapotranspiration in geographical ecology, Global Ecol. Biogeogr., 20, 1–18, https://doi.org/10.1111/j.1466-8238.2010.00578.x, 2011.
Friedl, M. A., McIver, D. K., Hodges, J. C. F., Zhang, X. Y., Muchoney, D., Strahler, A. H., Woodcock, C. E., Gopal, S., Schneider, A., Cooper, A., Baccini, A., Gao, F., and Schaaf, C.: Global land cover mapping from MODIS: algorithms and early results, Remote Sens. Environ., 83, 287–302, https://doi.org/10.1016/s0034-4257(02)00078-0, 2002.
Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., and Huang, X.: MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets, Remote Sens. Environ., 114, 168–182, https://doi.org/10.1016/j.rse.2009.08.016, 2010.
Gao, G., Chen, D., Xu, C.-Y., and Simelton, E.: Trend of estimated actual evapotranspiration over China during 1960–2002, J. Geophys. Res.-Atmos., 112, D11120, https://doi.org/10.1029/2006jd008010, 2007.
Gao, H., and Yang, S.: A severe drought event in northern China in winter 2008-2009 and the possible influences of La Nina and Tibetan Plateau, J. Geophys. Res.-Atmos., 114, D24104, https://doi.org/10.1029/2009JD012430, 2009.
Govind, A., Chen, J. M., and Ju, W. M.: Spatially explicit simulation of hydrologically controlled carbon and nitrogen cycles and associated feedback mechanisms in a boreal ecosystem, J. Geophys. Res.-Biogeo., 114, G02006, https://doi.org/10.1029/2008JG000728, 2009a.
Govind, A., Chen, J. M., Margolis, H., Ju, W. M., Sonnentag, O., and Giasson, M. A.: A spatially explicit hydro-ecological modeling framework (BEPS-TerrainLab V2.0): Model description and test in a boreal ecosystem in Eastern North America, J. Hydrol., 367, 200–216, https://doi.org/10.1016/j.jhydrol.2009.01.006, 2009b.
Gowda, P. H., Chavez, J. L., Colaizzi, P. D., Evett, S. R., Howell, T. A., and Tolk, J. A.: Remote sensing based energy balance algorithms for mapping ET: Current status and future challenges, T. ASABE, 50, 1639–1644, 2007.
Grant, R. F., Arain, A., Arora, V., Barr, A., Black, T. A., Chen, J., Wang, S., Yuan, F., and Zhang, Y.: Intercomparison of techniques to model high temperature effects on CO2 and energy exchange in temperate and boreal coniferous forests, Ecol. Model., 188, 217–252, https://doi.org/10.1016/j.ecolmodel.2005.01.060, 2005.
Grant, R. F., Zhang, Y., Yuan, F., Wang, S., Hanson, P. J., Gaumont-Guay, D., Chen, J., Black, T. A., Barr, A., Baldocchi, D. D., and Arain, A.: Intercomparison of techniques to model water stress effects on CO2 and energy exchange in temperate and boreal deciduous forests, Ecol. Model., 196, 289–312, https://doi.org/10.1016/j.ecolmodel.2006.02.015, 2006.
Huang, L., Liu, J., Shao, Q., and Xu, X.: Carbon sequestration by forestation across China: Past, present, and future, Renew. Sust. Energ. Rev., 16, 1291–1299, https://doi.org/10.1016/j.rser.2011.10.004, 2012.
Huntington, T. G.: Evidence for intensification of the global water cycle: Review and synthesis, J. Hydrol., 319, 83–95, 2006.
Hutjes, R. W. A., Kabat, P., Running, S. W., Shuttleworth, W. J., Field, C., Bass, B., Dias, M., Avissar, R., Becker, A., Claussen, M., Dolman, A. J., Feddes, R. A., Fosberg, M., Fukushima, Y., Gash, J. H. C., Guenni, L., Hoff, H., Jarvis, P. G., Kayane, I., Krenke, A. N., Liu, C., Meybeck, M., Nobre, C. A., Oyebande, L., Pitman, A., Pielke, R. A., Raupach, M., Saugier, B., Schulze, E. D., Sellers, P. J., Tenhunen, J. D., Valentini, R., Victoria, R. L., and Vorosmarty, C. J.: Biospheric aspects of the hydrological cycle - Preface, J. Hydrol., 212, 1–21, https://doi.org/10.1016/s0022-1694(98)00255-8, 1998.
Jarvis, P. G.: The interpretation of variations in leaf water potential and stomatal conductance found in canopies in field, Philos. T. Roy. Soc. B, 273, 593–610, 1976.
Jia, Z., Liu, S., Xu, Z., Chen, Y., and Zhu, M.: Validation of remotely sensed evapotranspiration over the Hai River Basin, China, J. Geophys. Res.-Atmos., 117, D13113, https://doi.org/10.1029/2011jd017037, 2012.
Jiang, L. and Islam, S.: A methodology for estimation of surface evapotranspiration over large areas using remote sensing observations, Geophys. Res. Lett., 26, 2773–2776, https://doi.org/10.1029/1999gl006049, 1999.
Jin, Y., Randerson, J. T., and Goulden, M. L.: Continental-scale net radiation and evapotranspiration estimated using MODIS satellite observations, Remote Sens. Environ., 115, 2302–2319, https://doi.org/10.1016/j.rse.2011.04.031, 2011.
Ju, W. M., Chen, J. M., Black, T. A., Barr, A. G., Liu, J., and Chen, B. Z.: Modelling multi-year coupled carbon and water fluxes in a boreal aspen forest, Agr. Forest Meteorol., 140, 136–151, 2006.
Ju, W. M., Gao, P., Wang, J., Zhou, Y. L., and Zhang, X. H.: Combining an ecological model with remote sensing and GIS techniques to monitor soil water content of croplands with a monsoon climate, Agr. Water Manage., 97, 1221–1231, 2010.
Jung, M., Reichstein, M., Ciais, P., Seneviratne, S. I., Sheffield, J., Goulden, M. L., Bonan, G., Cescatti, A., Chen, J., de Jeu, R., Dolman, A. J., Eugster, W., Gerten, D., Gianelle, D., Gobron, N., Heinke, J., Kimball, J., Law, B. E., Montagnani, L., Mu, Q., Mueller, B., Oleson, K., Papale, D., Richardson, A. D., Roupsard, O., Running, S., Tomelleri, E., Viovy, N., Weber, U., Williams, C., Wood, E., Zaehle, S., and Zhang, K.: Recent decline in the global land evapotranspiration trend due to limited moisture supply, Nature, 467, 951–954, https://doi.org/10.1038/nature09396, 2010.
Kelliher, F. M., Leuning, R., Raupach, M. R., and Schulze, E. D.: Maximum conductances for evaporation from global vegetation types, Agr. Forest Meteorol., 73, 1–16, https://doi.org/10.1016/0168-1923(94)02178-m, 1995.
Koster, R. D., Dirmeyer, P. A., Guo, Z. C., Bonan, G., Chan, E., Cox, P., Gordon, C. T., Kanae, S., Kowalczyk, E., Lawrence, D., Liu, P., Lu, C. H., Malyshev, S., McAvaney, B., Mitchell, K., Mocko, D., Oki, T., Oleson, K., Pitman, A., Sud, Y. C., Taylor, C. M., Verseghy, D., Vasic, R., Xue, Y. K., Yamada, T., and Team, G.: Regions of strong coupling between soil moisture and precipitation, Science, 305, 1138–1140, 2004.
Li, J., Yu, Q., Sun, X., Tong, X., Ren, C., Wang, J., Liu, E., Zhu, Z., and Yu, G.: Carbon dioxide exchange and the mechanism of environmental control in a farmland ecosystem in North China Plain, Sci. China Ser. D, 49, 226–240, https://doi.org/10.1007/s11430-006-8226-1, 2006.
Li, X., Ju, W., Zhou, Y., and Chen, S.: Retrieving leaf area index of forests in red soil hilly region using remote sensing data, Second International Conference on Earth Observation for Global Changes (EOGC 2009): Remote Sensing of Earth Surface Changes, Chengdu, China, 74710–74719, 2009.
Li, X., Liang, S., Yuan, W., Yu, G., Cheng, X., Chen, Y., Zhao, T., Feng, J., Ma, Z., Ma, M., Liu, S., Chen, J., Shao, C., Li, S., Zhang, X., Zhang, Z., Sun, G., Chen, S., Ohta, T., Varlagin, A., Miyata, A., Takagi, K., Saiqusa, N., and Kato, T.: Estimation of evapotranspiration over the terrestrial ecosystems in China, Ecohydrology, https://doi.org/10.1002/eco.1341, in press, 2012.
Li, Z., Yu, G., Xiao, X., Li, Y., Zhao, X., Ren, C., Zhang, L., and Fu, Y.: Modeling gross primary production of alpine ecosystems in the Tibetan Plateau using MODIS images and climate data, Remote Sens. Environ., 107, 510–519, https://doi.org/10.1016/j.rse.2006.10.003, 2007.
Li, Z., Tang, R., Wan, Z., Bi, Y., Zhou, C., Tang, B., Yan, G., and Zhang, X.: A review of current methodologies for regional evapotranspiration estimation from remotely sensed data, Sensors-Basel, 9, 3801–3853, https://doi.org/10.3390/s90503801, 2009.
Li, Z., Gao, Z., Gao, W., Shi, R., and Liu, C.: Spatio-temporal feature of land use/land cover dynamic changes in China from 1999 to 2009, T. Chin. Soc. Agr. Eng., 27, 312–322, 2011.
Li, Z. Q., Yu, G. R., Wen, X. F., Zhang, L. M., Ren, C. Y., and Fu, Y. L.: Energy balance closure at ChinaFLUX sites, Sci. China Ser. D, 48, 51–62, https://doi.org/10.1360/05zd0005, 2005.
Liu, J., Chen, J. M., Cihlar, J., and Park, W. M.: A process-based boreal ecosystem productivity simulator using remote sensing inputs, Remote Sens. Environ., 62, 158–175, 1997.
Liu, J., Chen, J. M., Cihlar, J., and Chen, W.: Net primary productivity distribution in the BOREAS region from a process model using satellite and surface data, J. Geophys. Res.-Atmos., 104, 27735–27754, 1999.
Liu, J., Chen, J. M., and Cihlar, J.: Mapping evapotranspiration based on remote sensing: An application to Canada's landmass, Water Resour. Res., 39, 1189, https://doi.org/10.1029/2002WR001680, 2003.
Liu, J. Y., Zhang, Q., and Hu, Y. F.: Regional differences of China's urban expansion from late 20th to early 21st century based on remote sensing information, Chin. Geogr. Sci., 22, 1–14, https://doi.org/10.1007/s11769-012-0510-8, 2012.
Liu, M. L., Tian, H. Q., Chen, G. S., Ren, W., Zhang, C., and Liu, J. Y.: Effects of land-use and land-cover change on evapotranspiration and water yield in China during 1900–2000, J. Am. Water Resour. Assoc., 44, 1193–1207, https://doi.org/10.1111/j.1752-1688.2008.00243.x, 2008.
Liu, M. L., Tian, H. Q., Lu, C. Q., Xu, X. F., Chen, G. S., and Ren, W.: Effects of multiple environment stresses on evapotranspiration and runoff over eastern China, J. Hydrol., 426, 39–54, https://doi.org/10.1016/j.jhydrol.2012.01.009, 2012.
Liu, R., Chen, J. M., Liu, J., Deng, F., and Sun, R.: Application of a new leaf area index algorithm to China's landmass using MODIS data for carbon cycle research, J. Environ. Manage., 85, 649–658, 2007.
Liu, S. and Gong, P.: Change of surface cover greenness in China between 2000 and 2010, Chinese Sci. Bull., 57, 2835–2845, https://doi.org/10.1007/s11434-012-5267-z, 2012.
Liu, Y., Yu, G., Wen, X., Wang, Y., Song, X., Li, J., Sun, X., Yang, F., Chen, Y., and Liu, Q.: Seasonal dynamics of CO2 fluxes from subtropical plantation coniferous ecosystem, Sci. China Ser. D, 49, 99–109, https://doi.org/10.1007/s11430-006-8099-3, 2006.
Liu, Y., Ju, W., Chen, J., Zhu, G., Xing, B., Zhu, J., and He, M.: Spatial and temporal variations of forest LAI in China during 2000–2010, Chinese Sci. Bull., 57, 2846–2856, https://doi.org/10.1007/s11434-012-5064-8, 2012.
Liu, Y., Ju, W., He, H., Wang, S., Sun, R., and Zhang, Y.: Changes of net primary productivity in China during recent 11 years detected using an ecological model driven by MODIS data, Front. Earth Sci., 7, 112–127, https://doi.org/10.1007/s11707-012-0348-5, 2013.
Loveland, T. R. and Belward, A. S.: The IGBP-DIS global 1 km land cover data set, DISCover: First results, Int. J. Remote Sens., 18, 3289–3295, https://doi.org/10.1080/014311697217099, 1997.
Lu, E., Luo, Y., Zhang, R., Wu, Q., and Liu, L.: Regional atmospheric anomalies responsible for the 2009–2010 severe drought in China, J. Geophys. Res.-Atmos., 116, D21114, https://doi.org/10.1029/2011jd015706, 2011.
Ma, Z. and Fu, C.: Some evidence of drying trend over northern China from 1951 to 2004, Chinese Sci. Bull., 51, 2913–2925, https://doi.org/10.1007/s11434-006-2159-0, 2006.
Matsushita, B. and Tamura, M.: Integrating remotely sensed data with an ecosystem model to estimate net primary productivity in East Asia, Remote Sens. Environ., 81, 58–66, 2002.
Meehl, G. A. and Tebaldi, C.: More intense, more frequent, and longer lasting heat waves in the 21st century, Science, 305, 994–997, https://doi.org/10.1126/science.1098704, 2004.
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011.
Monteith, J. L.: Evaporation and the environment, Proc. Symp. Exp. Biol., 19, 205–234, 1965.
Mu, Q., Heinsch, F. A., Zhao, M., and Running, S. W.: Development of a global evapotranspiration algorithm based on MODIS and global meteorology data, Remote Sens. Environ., 111, 519–536, 2007.
Mu, Q., Zhao, M., Running, S. W., Liu, M., and Tian, H.: Contribution of increasing CO2 and climate change to the carbon cycle in China's ecosystems, J. Geophys. Res.-Biogeo., 113, G01018, https://doi.org/10.1029/2006jg000316, 2008.
Mu, Q. Z., Zhao, M. S., and Running, S. W.: Improvements to a MODIS global terrestrial evapotranspiration algorithm, Remote Sens. Environ., 115, 1781–1800, 2011.
Mueller, B., Seneviratne, S. I., Jimenez, C., Corti, T., Hirschi, M., Balsamo, G., Ciais, P., Dirmeyer, P., Fisher, J. B., Guo, Z., Jung, M., Maignan, F., McCabe, M. F., Reichle, R., Reichstein, M., Rodell, M., Sheffield, J., Teuling, A. J., Wang, K., Wood, E. F., and Zhang, Y.: Evaluation of global observations-based evapotranspiration datasets and IPCC AR4 simulations, Geophys. Res. Lett., 38, https://doi.org/10.1029/2010gl046230, 2011.
Oki, T. and Kanae, S.: Global hydrological cycles and world water resources, Science, 313, 1068–1072, https://doi.org/10.1126/science.1128845, 2006.
Peng, S., Chen, A., Xu, L., Cao, C., Fang, J., Myneni, R. B., Pinzon, J. E., Tucker, C. J., and Piao, S.: Recent change of vegetation growth trend in China, Environ. Res. Lett., 6, 044027, https://doi.org/10.1088/1748-9326/6/4/044027, 2011.
Piao, S. L., Friedlingstein, P., Ciais, P., de Noblet-Ducoudre, N., Labat, D., and Zaehle, S.: Changes in climate and land use have a larger direct impact than rising CO2 on global river runoff trends, P. Natl. Acad. Sci. USA, 104, 15242–15247, https://doi.org/10.1073/pnas.0707213104, 2007.
Piao, S. L., Yin, L., Wang, X. H., Ciais, P., Peng, S. S., Shen, Z. H., and Seneviratne, S. I.: Summer soil moisture regulated by precipitation frequency in China, Environ. Res. Lett., 4, 044012, https://doi.org/10.1088/1748-9326/4/4/044012, 2009.
Piao, S. L., Ciais, P., Huang, Y., Shen, Z. H., Peng, S. S., Li, J. S., Zhou, L. P., Liu, H. Y., Ma, Y. C., Ding, Y. H., Friedlingstein, P., Liu, C. Z., Tan, K., Yu, Y. Q., Zhang, T. Y., and Fang, J. Y.: The impacts of climate change on water resources and agriculture in China, Nature, 467, 43–51, 2010.
Piao, S. L., Ciais, P., Lomas, M., Beer, C., Liu, H. Y., Fang, J. Y., Friedlingstein, P., Huang, Y., Muraoka, H., Son, Y. H., and Woodward, I.: Contribution of climate change and rising CO2 to terrestrial carbon balance in East Asia: A multi-model analysis, Global Planet. Change, 75, 133–142, 2011.
Piao, S. L., Ito, A., Li, S. G., Huang, Y., Ciais, P., Wang, X. H., Peng, S. S., Nan, H. J., Zhao, C., Ahlström, A., Andres, R. J., Chevallier, F., Fang, J. Y., Hartmann, J., Huntingford, C., Jeong, S., Levis, S., Levy, P. E., Li, J. S., Lomas, M. R., Mao, J. F., Mayorga, E., Mohammat, A., Muraoka, H., Peng, C. H., Peylin, P., Poulter, B., Shen, Z. H., Shi, X., Sitch, S., Tao, S., Tian, H. Q., Wu, X. P., Xu, M., Yu, G. R., Viovy, N., Zaehle, S., Zeng, N., and Zhu, B.: The carbon budget of terrestrial ecosystems in East Asia over the last two decades, Biogeosciences, 9, 3571–3586, https://doi.org/10.5194/bg-9-3571-2012, 2012.
Pisek, J., Chen, J. M., and Deng, F.: Assessment of a global leaf area index product from SPOT-4 VEGETATION data over selected sites in Canada, Can. J. Remote Sens., 33, 341–356, 2007.
Potter, C. S., Wang, S. S., Nikolov, N. T., McGuire, A. D., Liu, J., King, A. W., Kimball, J. S., Grant, R. F., Frolking, S. E., Clein, J. S., Chen, J. M., and Amthor, J. S.: Comparison of boreal ecosystem model sensitivity to variability in climate and forest site parameters, J. Geophys. Res.-Atmos., 106, 33671–33687, https://doi.org/10.1029/2000jd000224, 2001.
Qin, N., Chen, X., Fu, G., Zhai, J., and Xue, X.: Precipitation and temperature trends for the Southwest China: 1960–2007, Hydrol. Process., 24, 3733–3744, https://doi.org/10.1002/hyp.7792, 2010.
Qin, Z., Yu, Q., Xu, S. H., Hu, B. M., Sun, X. M., Liu, E. M., Wang, J. S., Yu, G. R., and Zhu, Z. L.: Water, heat fluxes and water use efficiency measurement and modeling above a farmland in the North China Plain, Sci. China Ser. D, 48, 207–217, 2005.
Rodell, M., McWilliams, E. B., Famiglietti, J. S., Beaudoing, H. K., and Nigro, J.: Estimating evapotranspiration using an observation based terrestrial water budget, Hydrol. Process., 25, 4082–4092, https://doi.org/10.1002/hyp.8369, 2011.
Ryu, Y., Baldocchi, D. D., Ma, S., and Hehn, T.: Interannual variability of evapotranspiration and energy exchange over an annual grassland in California, J. Geophys. Res.-Atmos., 113, D09104, https://doi.org/10.1029/2007jd009263, 2008.
Ryu, Y., Baldocchi, D. D., Kobayashi, H., van Ingen, C., Li, J., Black, T. A., Beringer, J., van Gorsel, E., Knohl, A., Law, B. E., and Roupsard, O.: Integration of MODIS land and atmosphere products with a coupled-process model to estimate gross primary productivity and evapotranspiration from 1 km to global scales, Global Biogeochem. Cy., 25, GB4017, https://doi.org/10.1029/2011gb004053, 2011.
Sahoo, A. K., Pan, M., Troy, T. J., Vinukollu, R. K., Sheffield, J., and Wood, E. F.: Reconciling the global terrestrial water budget using satellite remote sensing, Remote Sens. Environ., 115, 1850–1865, https://doi.org/10.1016/j.rse.2011.03.009, 2011.
Sasai, T., Saigusa, N., Nasahara, K. N., Ito, A., Hashimoto, H., Nemani, R., Hirata, R., Ichii, K., Takagi, K., Saitoh, T. M., Ohta, T., Murakami, K., Yamaguchi, Y., and Oikawa, T.: Satellite-driven estimation of terrestrial carbon flux over Far East Asia with 1-km grid resolution, Remote Sens. Environ., 115, 1758–1771, https://doi.org/10.1016/j.rse.2011.03.007, 2011.
Saxton, K. E., Rawls, W. J., Romberger, J. S., and Papendick, R. I.: Estimating generalized soil-water characteristics from texture, Soil. Sci. Soc. Am. J., 50, 1031–1036, 1986.
Schaefer, K., Schwalm, C. R., Williams, C., Arain, M. A., Barr, A., Chen, J. M., Davis, K. J., Dimitrov, D., Hilton, T. W., Hollinger, D. Y., Humphreys, E., Poulter, B., Raczka, B. M., Richardson, A. D., Sahoo, A., Thornton, P., Vargas, R., Verbeeck, H., Anderson, R., Baker, I., Black, T. A., Bolstad, P., Chen, J., Curtis, P. S., Desai, A. R., Dietze, M., Dragoni, D., Gough, C., Grant, R. F., Gu, L., Jain, A., Kucharik, C., Law, B., Liu, S., Lokipitiya, E., Margolis, H. A., Matamala, R., McCaughey, J. H., Monson, R., Munger, J. W., Oechel, W., Peng, C., Price, D. T., Ricciuto, D., Riley, W. J., Roulet, N., Tian, H., Tonitto, C., Torn, M., Weng, E., and Zhou, X.: A model-data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis, J. Geophys. Res.-Biogeo., 117, G03010, https://doi.org/10.1029/2012jg001960, 2012.
Schwalm, C. R., Williams, C. A., Schaefer, K., Anderson, R., Arain, M. A., Baker, I., Barr, A., Black, T. A., Chen, G., Chen, J. M., Ciais, P., Davis, K. J., Desai, A., Dietze, M., Dragoni, D., Fischer, M. L., Flanagan, L. B., Grant, R., Gu, L., Hollinger, D., Izaurralde, R. C., Kucharik, C., Lafleur, P., Law, B. E., Li, L., Li, Z., Liu, S., Lokupitiya, E., Luo, Y., Ma, S., Margolis, H., Matamala, R., McCaughey, H., Monson, R. K., Oechel, W. C., Peng, C., Poulter, B., Price, D. T., Riciutto, D. M., Riley, W., Sahoo, A. K., Sprintsin, M., Sun, J., Tian, H., Tonitto, C., Verbeeck, H., and Verma, S. B.: A model-data intercomparison of CO2 exchange across North America: Results from the North American Carbon Program site synthesis, J. Geophys. Res., 115, G00H05, https://doi.org/10.1029/2009jg001229, 2010.
Sellers, P. J., Randall, D. A., Collatz, G. J., Berry, J. A., Field, C. B., Dazlich, D. A., Zhang, C., Collelo, G. D., and Bounoua, L.: A revised land surface parameterization (SiB2) for atmospheric GCMs, Part I: Model formulation, J. Climate, 9, 676-705, 1996.
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil moisture-climate interactions in a changing climate: A review, Earth-Sci. Rev., 99, 125–161, https://doi.org/10.1016/j.earscirev.2010.02.004, 2010.
Shangguan, W., Dai, Y., Liu, B., Ye, A., and Yuan, H.: A soil particle-size distribution dataset for regional land and climate modelling in China, Geoderma, 171–172, 85–91, https://doi.org/10.1016/j.geoderma.2011.01.013, 2012.
Sonnentag, O., Chen, J. M., Roulet, N. T., Ju, W., and Govind, A.: Spatially explicit simulation of peatland hydrology and carbon dioxide exchange: Influence of mesoscale topography, J. Geophys. Res.-Biogeo., 113, G02005, https://doi.org/10.1029/2007JG000605, 2008.
Sprintsin, M., Chen, J. M., Desai, A., and Gough, C. M.: Evaluation of leaf-to-canopy upscaling methodologies against carbon flux data in North America, J. Geophys. Res.-Biogeo., 117, G01023, https://doi.org/10.1029/2010jg001407, 2012.
Su, Z.: The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes, Hydrol. Earth Syst. Sci., 6, 85–100, https://doi.org/10.5194/hess-6-85-2002, 2002.
Sun, G., McNulty, S. G., Lu, J., Amatya, D. M., Liang, Y., and Kolka, R. K.: Regional annual water yield from forest lands and its response to potential deforestation across the southeastern United States, J. Hydrol., 308, 258–268, https://doi.org/10.1016/j.jhydrol.2004.11.021, 2005.
Sun, G., Zhou, G. Y., Zhang, Z. Q., Wei, X. H., McNulty, S. G., and Vose, J. M.: Potential water yield reduction due to forestation across China, J. Hydrol., 328, 548–558, https://doi.org/10.1016/j.jhydrol.2005.12.013, 2006.
Sun, R., Chen, J. M., Zhu, Q. J., Zhou, Y. Y., Liu, J., Li, J. T., Liu, S. H., Yan, G. J., and Tang, S. H.: Spatial distribution of net primary productivity and evapotranspiration in Changbaishan Natural Reserve, China, using Landsat ETM+ data, Can. J. Remote Sens., 30, 731–742, 2004.
Trenberth, K. E., Jones, P. D., Ambenje, P., Bojariu, R., Easterling, D., Klein Tank, A., Parker, D., Rahimzadeh, F., Renwick, J. A., Rusticucci, M., Soden, B., and Zhai, P.: Observations: Surface and Atmospheric Climate Change, in: Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge, UK and New York, NY, USA, 2007.
Trenberth, K. E., Fasullo, J. T., and Kiehl, J.: Earth's global energy budget, B. Am. Meteorol. Soc., 90, 311–323, https://doi.org/10.1175/2008bams2634.1, 2009.
Twine, T. E., Kucharik, C. J., and Foley, J. A.: Effects of land cover change on the energy and water balance of the Mississippi River basin, J. Hydrometeorol., 5, 640–655, https://doi.org/10.1175/1525-7541(2004)005<0640:eolcco>2.0.co;2, 2004.
Verstraeten, W. W., Veroustraete, F., and Feyen, J.: Assessment of evapotranspiration and soil moisture content across different scales of observation, Sensors-Basel, 8, 70–117, https://doi.org/10.3390/s8010070, 2008.
Vinukollu, R. K., Wood, E. F., Ferguson, C. R., and Fisher, J. B.: Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: Evaluation of three process-based approaches, Remote Sens. Environ., 115, 801–823, 2011.
Wang, A. H., Lettenmaier, D. P., and Sheffield, J.: Soil Moisture Drought in China, 1950–2006, J. Climate, 24, 3257–3271, 2011.
Wang, K. and Dickinson, R. E.: A review of global terrestrial evapotranspiration: observation, modeling, climatology, and climatic variability, Rev. Geophys., 50, Rg2005, https://doi.org/10.1029/2011rg000373, 2012.
Wang, K. and Liang, S.: An improved method for estimating global evapotranspiration based on satellite determination of surface net radiation, vegetation index, temperature, and soil moisture, J. Hydrometeorol., 9, 712–727, https://doi.org/10.1175/2007jhm911.1, 2008.
Wang, K., Dickinson, R. E., Wild, M., and Liang, S.: Evidence for decadal variation in global terrestrial evapotranspiration between 1982 and 2002: 2. Results, J. Geophys. Res.-Atmos., 115, D20113, https://doi.org/10.1029/2010jd013847, 2010.
Wang, L., Li, C., Ying, Q., Cheng, X., Wang, X., Li, X., Hu, L., Liang, L., Yu, L., Huang, H., and Gong, P.: China's urban expansion from 1990 to 2010 determined with satellite remote sensing, Chinese Sci. Bull., 57, 2802–2812, https://doi.org/10.1007/s11434-012-5235-7, 2012.
Wang, Q., Tenhunen, J., Falge, E., Bernhofer, C., Granier, A., and Vesala, T.: Simulation and scaling of temporal variation in gross primary production for coniferous and deciduous temperate forests, Global Change Biol., 10, 37–51, 2004.
Wang, Q. F., Niu, D., Yu, G. R., Ren, C. Y., Wen, X. F., Chen, J. M., and Ju, W. M.: Simulating the exchanges of carbon dioxide, water vapor and heat over Changbai Mountains temperate broadleaved Korean pine mixed forest ecosystem, Sci. China Ser. D, 48, 148–159, https://doi.org/10.1360/05zd0015, 2005.
Wen, X., Yu, G., Sun, X., Li, Q., Ren, C., and Han, S.: Net water vapour exchange over a mixed needle and broad-leaved forest in Changbai Mountain during autumn, J. Geogr. Sci., 13, 463–468, 2003.
Wen, X. F., Yu, G. R., Sun, X. M., Li, Q. K., Liu, Y. F., Zhang, L. M., Ren, C. Y., Fu, Y. L., and Li, Z. Q.: Soil moisture effect on the temperature dependence of ecosystem respiration in a subtropical Pinus plantation of southeastern China, Agr. Forest Meteorol., 137, 166–175, 2006.
Xiao, J., Sun, G., Chen, J., Chen, H., Chen, S., Dong, G., Gao, S., Guo, H., Guo, J., Han, S., Kato, T., Li, Y., Lin, G., Lu, W., Ma, M., McNulty, S., Shao, C., Wang, X., Xie, X., Zhang, X., Zhang, Z., Zhao, B., Zhou, G., and Zhou, J.: Carbon fluxes, evapotranspiration, and water use efficiency of terrestrial ecosystems in China, Agr. Forest Meteorol., 182–183, 76–90, https://doi.org/10.1016/j.agrformet.2013.08.007, 2013.
Yan, H., Wang, S. Q., Billesbach, D., Oechel, W., Zhang, J. H., Meyers, T., Martin, T. A., Matamala, R., Baldocchi, D., Bohrer, G., Dragoni, D., and Scott, R.: Global estimation of evapotranspiration using a leaf area index-based surface energy and water balance model, Remote Sens. Environ., 124, 581–595, https://doi.org/10.1016/j.rse.2012.06.004, 2012.
Yang, Y., Shang, S., and Jiang, L.: Remote sensing temporal and spatial patterns of evapotranspiration and the responses to water management in a large irrigation district of North China, Agr. Forest Meteorol., 164, 112–122, https://doi.org/10.1016/j.agrformet.2012.05.011, 2012.
Yao, Y., Liang, S., Cheng, J., Liu, S., Fisher, J. B., Zhang, X., Jia, K., Zhao, X., Qin, Q., Zhao, B., Han, S., Zhou, G., Zhou, G., Li, Y., and Zhao, S.: MODIS-driven estimation of terrestrial latent heat flux in China based on a modified Priestley–Taylor algorithm, Agr. Forest Meteorol., 171–172, 187–202, https://doi.org/10.1016/j.agrformet.2012.11.016, 2013.
Yu, D. Y., Shi, P. J., Han, G. Y., Zhu, W. Q., Du, S. Q., and Xun, B.: Forest ecosystem restoration due to a national conservation plan in China, Ecol. Eng., 37, 1387–1397, https://doi.org/10.1016/j.ecoleng.2011.03.011, 2011.
Yu, G. R., Wen, X. F., Sun, X. M., Tanner, B. D., Lee, X. H., and Chen, J. Y.: Overview of ChinaFLUX and evaluation of its eddy covariance measurement, Agr. Forest Meteorol., 137, 125–137, 2006.
Yu, P., Krysanova, V., Wang, Y., Xiong, W., Mo, F., Shi, Z., Liu, H., Vetter, T., and Huang, S.: Quantitative estimate of water yield reduction caused by forestation in a water-limited area in northwest China, Geophys. Res. Lett., 36, L02406, https://doi.org/10.1029/2008gl036744, 2009.
Yuan, W. P., Liu, S. G., Yu, G. R., Bonnefond, J. M., Chen, J. Q., Davis, K., Desai, A. R., Goldstein, A. H., Gianelle, D., Rossi, F., Suyker, A. E., and Verma, S. B.: Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data, Remote Sens. Environ., 114, 1416–1431, https://doi.org/10.1016/j.rse.2010.01.022, 2010.
Zeng, Z. Z., Piao, S. L., Lin, X., Yin, G. D., Peng, S. S., Ciais, P., and Myneni, R. B.: Global evapotranspiration over the past three decades: estimation based on the water balance equation combined with empirical models, Environ. Res. Lett., 7, 014026, https://doi.org/10.1088/1748-9326/7/1/014026, 2012.
Zhang, F., Ju, W., Chen, J., Wang, S., Yu, G., Li, Y., Han, S., and Asanuma, J.: Study on evapotranspiration in East Asia using the BEPS ecological model, J. Nat. Resour., 25, 1596–1606, 2010.
Zhang, F., Chen, J. M., Chen, J., Gough, C. M., Martin, T. A., and Dragoni, D.: Evaluating spatial and temporal patterns of MODIS GPP over the conterminous U.S. against flux measurements and a process model, Remote Sens. Environ., 124, 717–729, https://doi.org/10.1016/j.rse.2012.06.023, 2012a.
Zhang, F., Ju, W., Shen, S., Wang, S., Yu, G., and Han, S.: Variations of terrestrial net primary productivity in East Asia, Terr. Atmos. Ocean Sci., 23, 425–437, https://doi.org/10.3319/tao.2012.03.28.01(a), 2012b.
Zhang, K., Kimball, J. S., Mu, Q. Z., Jones, L. A., Goetz, S. J., and Running, S. W.: Satellite based analysis of northern ET trends and associated changes in the regional water balance from 1983 to 2005, J. Hydrol., 379, 92–110, https://doi.org/10.1016/j.jhydrol.2009.09.047, 2009.
Zhang, K., Kimball, J. S., Nemani, R. R., and Running, S. W.: A continuous satellite-derived global record of land surface evapotranspiration from 1983 to 2006, Water Resour. Res., 46, W09522, https://doi.org/10.1029/2009wr008800, 2010.
Zhang, L., Dawes, W. R., and Walker, G. R.: Response of mean annual evapotranspiration to vegetation changes at catchment scale, Water Resour. Res., 37, 701–708, https://doi.org/10.1029/2000wr900325, 2001.
Zhang, M., Yu, G. R., Zhuang, J., Gentry, R., Fu, Y. L., Sun, X. M., Zhang, L. M., Wen, X. F., Wang, Q. F., Han, S. J., Yan, J. H., Zhang, Y. P., Wang, Y. F., and Li, Y. N.: Effects of cloudiness change on net ecosystem exchange, light use efficiency, and water use efficiency in typical ecosystems of China, Agr. Forest Meteorol., 151, 803–816, 2011a.
Zhang, Q., Xu, C.-Y., Chen, Y. D., and Ren, L.: Comparison of evapotranspiration variations between the Yellow River and Pearl River basin, China, Stoch. Env. Res. Risk A, 25, 139–150, https://doi.org/10.1007/s00477-010-0428-6, 2011b.
Zhang, Y. Q. and Wegehenkel, M.: Integration of MODIS data into a simple model for the spatial distributed simulation of soil water content and evapotranspiration, Remote Sens. Environ., 104, 393–408, 2006.
Zhang, Y. Q., Leuning, R., Chiew, F. H. S., Wang, E. L., Zhang, L., Liu, C. M., Sun, F. B., Peel, M. C., Shen, Y. J., and Jung, M.: Decadal trends in evaporation from global energy and water balances, J. Hydrometeorol., 13, 379–391, https://doi.org/10.1175/jhm-d-11-012.1, 2012.
Zhao, M. and Running, S. W.: Drought-induced reduction in global terrestrial net primary production from 2000 through 2009, Science, 329, 940–943, https://doi.org/10.1126/science.1192666, 2010.
Zhou, L., Wang, S., Chen, J., Feng, X., Ju, W., and Wu, W.: The spatial-temporal characteristics of evapotranspiration of China's terrestrial ecosystems during 1991–2000, Resour. Sci., 31, 962–972, 2009.
Zhu, Q. A., Jiang, H., Liu, J. X., Wei, X. H., Peng, C. H., Fang, X. Q., Liu, S. R., Zhou, G. M., Yu, S. Q., and Ju, W. M.: Evaluating the spatiotemporal variations of water budget across China over 1951–2006 using IBIS model, Hydrol. Process., 24, 429–445, 2010.
