Articles | Volume 27, issue 2
https://doi.org/10.5194/hess-27-363-2023
https://doi.org/10.5194/hess-27-363-2023
Research article
 | 
19 Jan 2023
Research article |  | 19 Jan 2023

Improved soil evaporation remote sensing retrieval algorithms and associated uncertainty analysis on the Tibetan Plateau

Jin Feng, Ke Zhang, Huijie Zhan, and Lijun Chao

Related authors

A D-vine copula-based quantile regression towards merging satellite precipitation products over rugged topography: a case study in the upper Tekeze–Atbara Basin
Mohammed Abdallah, Ke Zhang, Lijun Chao, Abubaker Omer, Khalid Hassaballah, Kidane Welde Reda, Linxin Liu, Tolossa Lemma Tola, and Omar M. Nour
Hydrol. Earth Syst. Sci., 28, 1147–1172, https://doi.org/10.5194/hess-28-1147-2024,https://doi.org/10.5194/hess-28-1147-2024, 2024
Short summary
iHydroSlide3D v1.0: an advanced hydrological–geotechnical model for hydrological simulation and three-dimensional landslide prediction
Guoding Chen, Ke Zhang, Sheng Wang, Yi Xia, and Lijun Chao
Geosci. Model Dev., 16, 2915–2937, https://doi.org/10.5194/gmd-16-2915-2023,https://doi.org/10.5194/gmd-16-2915-2023, 2023
Short summary
The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 1: Model description
Marcos Longo, Ryan G. Knox, David M. Medvigy, Naomi M. Levine, Michael C. Dietze, Yeonjoo Kim, Abigail L. S. Swann, Ke Zhang, Christine R. Rollinson, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4309–4346, https://doi.org/10.5194/gmd-12-4309-2019,https://doi.org/10.5194/gmd-12-4309-2019, 2019
Short summary
The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America
Marcos Longo, Ryan G. Knox, Naomi M. Levine, Abigail L. S. Swann, David M. Medvigy, Michael C. Dietze, Yeonjoo Kim, Ke Zhang, Damien Bonal, Benoit Burban, Plínio B. Camargo, Matthew N. Hayek, Scott R. Saleska, Rodrigo da Silva, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4347–4374, https://doi.org/10.5194/gmd-12-4347-2019,https://doi.org/10.5194/gmd-12-4347-2019, 2019
Short summary
Sensitivity of hydrological models to temporal and spatial resolutions of rainfall data
Yingchun Huang, András Bárdossy, and Ke Zhang
Hydrol. Earth Syst. Sci., 23, 2647–2663, https://doi.org/10.5194/hess-23-2647-2019,https://doi.org/10.5194/hess-23-2647-2019, 2019
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Remote Sensing and GIS
A D-vine copula-based quantile regression towards merging satellite precipitation products over rugged topography: a case study in the upper Tekeze–Atbara Basin
Mohammed Abdallah, Ke Zhang, Lijun Chao, Abubaker Omer, Khalid Hassaballah, Kidane Welde Reda, Linxin Liu, Tolossa Lemma Tola, and Omar M. Nour
Hydrol. Earth Syst. Sci., 28, 1147–1172, https://doi.org/10.5194/hess-28-1147-2024,https://doi.org/10.5194/hess-28-1147-2024, 2024
Short summary
SMPD: a soil moisture-based precipitation downscaling method for high-resolution daily satellite precipitation estimation
Kunlong He, Wei Zhao, Luca Brocca, and Pere Quintana-Seguí
Hydrol. Earth Syst. Sci., 27, 169–190, https://doi.org/10.5194/hess-27-169-2023,https://doi.org/10.5194/hess-27-169-2023, 2023
Short summary
Evaluating the accuracy of gridded water resources reanalysis and evapotranspiration products for assessing water security in poorly gauged basins
Elias Nkiaka, Robert G. Bryant, Joshua Ntajal, and Eliézer I. Biao
Hydrol. Earth Syst. Sci., 26, 5899–5916, https://doi.org/10.5194/hess-26-5899-2022,https://doi.org/10.5194/hess-26-5899-2022, 2022
Short summary
Attribution of global evapotranspiration trends based on the Budyko framework
Shijie Li, Guojie Wang, Chenxia Zhu, Jiao Lu, Waheed Ullah, Daniel Fiifi Tawia Hagan, Giri Kattel, and Jian Peng
Hydrol. Earth Syst. Sci., 26, 3691–3707, https://doi.org/10.5194/hess-26-3691-2022,https://doi.org/10.5194/hess-26-3691-2022, 2022
Short summary
The influence of vegetation water dynamics on the ASCAT backscatter–incidence angle relationship in the Amazon
Ashwini Petchiappan, Susan C. Steele-Dunne, Mariette Vreugdenhil, Sebastian Hahn, Wolfgang Wagner, and Rafael Oliveira
Hydrol. Earth Syst. Sci., 26, 2997–3019, https://doi.org/10.5194/hess-26-2997-2022,https://doi.org/10.5194/hess-26-2997-2022, 2022
Short summary

Cited articles

Abdullah, S. S., Malek, M. A., Abdullah, N. S., Kisi, O., and Yap, K. S.: Extreme Learning Machines: A new approach for prediction of reference evapotranspiration, J. Hydrol., 527, 184–195, https://doi.org/10.1016/j.jhydrol.2015.04.073, 2015. 
Bai, Y., Zhang, S., Bhattarai, N., Mallick, K., Liu, Q., Tang, L., Im, J., Guo, L., and Zhang, J.: On the use of machine learning based ensemble approaches to improve evapotranspiration estimates from croplands across a wide environmental gradient, Agr. Forest Meteorol., 298–299, 108308, https://doi.org/10.1016/j.agrformet.2020.108308, 2021. 
Beaudoing, H. and Rodell, M.: NASA/GSFC/HSL: GLDAS Noah Land Surface Model L4 3 hourly 0.25×0.25 degree V2.1, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/E7TYRXPJKWOQ, 2020. 
Beck, H. E., Wood, E. F., Pan, M., Fisher, C. K., Miralles, D. G., Van Dijk, A. I., McVicar, T. R., and Adler, R. F.: MSWEP V2 global 3-hourly 0.1 precipitation: methodology and quantitative assessment, B. Am. Meteorol. Soc., 100, 473–500, https://doi.org/10.1175/BAMS-D-17-0138.1, 2019. 
Bouchet, R. J.: Evapotranspiration réelle et potentielle, signification climatique, IAHS Publ., 62, 134–142, 1963. 
Download
Short summary
Here we improved a satellite-driven evaporation algorithm by introducing the modified versions of the two constraint schemes. The two moisture constraint schemes largely improved the evaporation estimation on two barren-dominated basins of the Tibetan Plateau. Investigation of moisture constraint uncertainty showed that high-quality soil moisture can optimally represent moisture, and more accessible precipitation data generally help improve the estimation of barren evaporation.