Kun Zhang | 张琨

Eco-Hydrology & Remote Sensing




Welcome !

I am currently an associate professor at the School of Geospatial Engineering and Science, Sun Yat-Sen University (SYSU). Prior to joining SYSU, I worked as a postdoctoral research fellow at the School of Biological Sciences and the Department of Mathematics, The University of Hong Kong, working with Prof. Jin Wu and Prof. Michael Ng. I also gained research training as a special research associate at the Institute of Tibetan Plateau Research, Chinese Academy of Sciences, supervised by Prof. Xin Li on eco-hydrology and remote sensing.

My research starts from modeling global evapotranspiration and soil water dynamics, focusing on the terrestrial water cycle and its interactions with climate change. The Bayesian approaches have usually been used in my projects to explore the sensitivity and optimization of model parameters and structural errors. By combining process-based model and multi-source remotely sensed and ground-based observations, I am trying to understand the response of the terrestrial water cycle and ecosystem resilience to climate change, particularly under extreme events.


News !
We have recently proposed a Special Issue titled "Remote Sensing for Terrestrial Hydrologic Variables" in the journal Remote Sensing. We warmly welcome submissions from researchers in this field. The deadline for submissions is November 30, 2024. More details can be found at the following website: Click here.


We are looking for self-motivated Ph.D students, Master students, Undergraduate students, and Postdocs to join our team. 课题组招收硕士生、博士生，也非常欢迎优秀的本科生加入。长期招聘博士后和研究助理。我们与香港大学、中国科学院、兰州大学等相关实验室有密切的合作，可推荐课题组成员去相关实验室交流或联合培养。请感兴趣的同学与我邮件联系，期待你的加入！


Contact
  • Email: zhangkun3 (at) mail.sysu.edu.cn

  • Office: Room E920, Hanlin Building 3, Zhuhai Campus of SYSU, Zhuhai, China

Main Research

Terrestrial Evapotranspiration (ET) Modelling

Model parameters are significant factors influencing the model performance. Based on the current commonly used process-based remote sensing evapotranspiration models, we identified and analyzed the key parameter functions under different plant functional types using the eddy covariance (EC) observations across the globe, and gave a more suitable set of optimized parameters using a data-model fusion algorithm under the Bayesian framework (Zhang et al., 2017 ). Moreover, multiscale verification was expanded from the plot scale to the global scale, and the global ET estimates were compared with the mainstream ET products (Zhang et al., 2019 ). In addition, A physically-based ecohydrological model, called Simple Terrestrial Hydrosphere (SiTHv1), was developed and updated (SiTHv2) to estimate the terrestrial ET and ET-related variables based on the groundwater-soil-plant-atmosphere continuum. The major feature in SiTH model is to adjust the allocation of potential plant transpiration to different soil layers combined with root distribution and soil water conditions, which can assure the adaptability of plant growth (Zhu et al., 2019 ; Zhang et al., 2022 ).

Relevant codes are available at GitHub for PT-JPL url and MOD16 url. The terrestrial ET data set based on SiTHv2 (daily, 0.1° globally) can be achieved from the TPDC url.

Estimation of Global Irrigation Water Use

Quantification of the global irrigation water use (IWU) is crucial to understanding the anthropogenic disturbance of the natural hydrological cycle and optimal agricultural water management. However, it is challenging to obtain time series data with the conventional survey-based approach, while the current satellite-based IWU estimations are subject to data gaps and the model structure. Hence, we propose a comprehensive framework to couple the different processes associated with irrigation and integrate multiple satellite observations to estimate the global IWU (Zhang et al., 2022 ). The ensemble IWU estimate demonstrates an improved performance when compared to the IWU obtained from individual satellite observations. Large amounts of IWU are apparent in India, China, the US, Europe, and Pakistan, making up over 70 percent of the global IWU. A general underestimation of IWU is found both in this work and previous studies, due to the coarse resolution and asynchronism of the various satellite products, the changes in irrigated areas, and the deficiency in detecting irrigation events under the case of saturated soil moisture. Nevertheless, the proposed framework has showed advantages in integrating multiple precipitation and soil moisture data to address the uncertainties in estimating global IWU, and is a new attempt to use satellite to monitor global IWU. Generated data set is available at the TPDC url.


Extreme climate events, drivers and plant response

In the context of global warming, extreme climate events occur frequently. Heatwave is one of the climate extremes characterized by an abnormally high temperature near the Earth's surface, which has a substantial influence on ecosystem and human health. More than 166,000 people died worldwide due to heatwaves from 1998 to 2017, while the heatwave occurrences are projected to be more intense. Severe and sustained hot temperatures are usually tightly coupled with drought events, due to the enhanced atmospheric moisture demand and accelerated water loss in the soil. With reduced humidity, heatwaves can easily raise the risk of wildfires, which can be devastating to the natural environment and agriculture. Recently, I have been working on heatwave study to identify global heatwave episodes during the past several decades utilizing several data sources, such as ground-based, remote sensing, and reanalysis data. The establishment of heatwave information with high spatial and temporal resolution will be beneficial for explore its interaction with the climate variability and vegetation feedback over time series.


Publication

Published papers

  1. PEM-SMC: An algorithm for optimizing model parameters.
    Zhu, G., Chen, Q., Yu, X., Xu, C., Zhang, K.*, Wang, Y.*, Gong, W., & Che, T.*
    Software Impacts, 2025. 23, 100728. | PDF

  2. Spatial-temporal variations in evapotranspiration across the continental United States: An atmospheric water balance perspective.
    Shang, S., Zhu, G., Zhang, K., Chen, H., Wang, Y., Chen, Y., Zhang, Z., & Ma, N.
    Journal of Hydrology, 2024. 640, 131699. | PDF

  3. Consistent Ground Surface Temperature Climatology Over China: 1956–2022.
    Wang, S., Cao, B., Hao, J., Sun, W., & Zhang, K.
    Journal of Geophysical Research: Atmospheres, 2024. 129(10), e2024JD040916. | PDF

  4. A global dataset of terrestrial evapotranspiration and soil moisture dynamics from 1982 to 2020.
    Zhang, K., Chen, H., Ma, N., Shang, S., Wang, Y., Xu, Q., & Zhu, G.
    Scientific Data, 2024. 11(1), 445. | PDF

  5. Energy partitioning over an irrigated vineyard in arid northwest China: Variation characteristics, influence degree, and path of influencing factors.
    Chen, H., Zhu, Y., Zhu, G., Zhang, Y., He, L., Xu, C., Zhang, K., Wang, J., Ayyamperumal, R., Fan, H., & Wang, B.
    Agricultural and Forest Meteorology, 2024. 350, 109972. | PDF

  6. Exploring the ecological meanings of temperature sensitivity of ecosystem respiration from different methods.
    Zhang, Y., Zhu, G.*, Zhang, K.*, Huang, H., He, L., Xu, C., Chen, H., Su, Y., Zhang, Y., Fan, H., & Wang, B.
    Science of the Total Environment, 2024. 923, 171403 | PDF

  7. Spectra-phenology integration for high-resolution, accurate, and scalable mapping of foliar functional traits using time-series Sentinel-2 data.
    Liu, S., Wang, Z., Lin, Z., Zhao, Y., Yan, Z., Zhang, K., Visser, M., Townsend, P., & Wu, J.
    Remote Sensing of Environment, 2024. 305, 114082 | PDF

  8. Plant canopies exhibit stronger thermoregulation capability at the seasonal than diurnal timescales.
    Guo, Z., Zhang, K., Lin, H., Majcher, B. M., Lee, C. K. F., Still, C. J., & Wu, J.
    Agricultural and Forest Meteorology, 2023. 339, 109582 | PDF

  9. Inconsistency and correction of manually observed ground surface temperatures over snow-covered regions.
    Cao, B., Wang, S., Hao, J., Sun, W., & Zhang, K.
    Agricultural and Forest Meteorology, 2023. 338, 109518 | PDF

  10. The underappreciated importance of solar radiation in constraining spring phenology of temperate ecosystems in the Northern and Eastern United States.
    Gu, Y., Zhao, Y., Guo, Z., Meng, L., Zhang, K., Wang, J., Lee, C. K. F., Xie, J., Wang, Y., Yan, Z., Zhang, H., & Wu, J.
    Remote Sensing of Environment, 2023. 294, 113617. | PDF

  11. Attenuated cooling effects with increasing water-saving irrigation: Satellite evidence from Xinjiang, China.
    Zhang, C., Dong, J., Leng, G., Doughty, R., Zhang, K., Han, S., Zhang, G., Zhang, X., & Ge, Q.
    Agricultural and Forest Meteorology, 2023. 333, 109397 | PDF

  12. The biophysical climate mitigation potential of riparian forest ecosystems in arid Northwest China.
    Su, Y., Luo, F., Zhu, G., Zhang, K., & Zhang, Q.
    Science of The Total Environment, 2023. 862, 160856 | PDF

  13. Does plant ecosystem thermoregulation occur? An extratropical assessment at different spatial and temporal scales.
    Guo, Z., Still, C. J., Lee, C. K. F., Ryu, Y., Blonder, B., Wang, J., Bonebrake, T. C., Hughes, A., Li, Y., Yeung, H. C. H., Zhang, K., Law, Y. K., Lin, Z., & Wu, J.
    New Phytologist, 2023. 238(3), 1004–1018.| PDF

  14. Recent Increase of Spring Precipitation over the Three-River Headwaters Region—Water Budget Analysis Based on Global Reanalysis (ERA5) and ET-Tagging Extended Regional Climate Modeling.
    Shang, S., Arnault, J., Zhu, G., Chen, H., Wei, J., Zhang, K., Zhang, Z., Laux, P., & Kunstmann, H.
    Journal of Climate, 2022. 35(22), 3599–3617. | PDF

  15. A globally robust relationship between water table decline, subsidence rate, and carbon release from peatlands.
    Ma, L., Zhu, G., Chen, B., Zhang, K., Niu, S., Wang, J., Ciais, P., Zuo, H.
    Communications Earth & Environment, 2022. 3(1), Article 1. | PDF

  16. Improvement of evapotranspiration simulation in a physically based ecohydrological model for the groundwater-soil-plant-atmosphere continuum.
    Zhang, K., Zhu, G., Ma, N., Chen, H., Shang, S.
    Journal of Hydrology, 2022. 613, 128440. | PDF

  17. Integrating remote sensing, irrigation suitability and statistical data for irrigated cropland mapping over mainland China.
    Zhang, L., Zhang, K., Zhu, X., Chen, H., Wang, W.
    Journal of Hydrology, 2022. 613, 128413. | PDF

  18. Divergent trends in irrigation-water withdrawal and consumption over mainland China.
    Zhang, L., Zheng, D., Zhang, K., Chen, H., Ge, Y., Li, X.
    Environmental Research Letter, 2022. 17(9), 094001. | PDF

  19. Understanding the dynamics of pandemic models to support predictions of COVID-19 transmission: Parameter sensitivity analysis of the SIR-type model.
    Ma, C., Li, X., Zhao, Z., Liu, F., Zhang, K., Wu, A., Nie, X.
    IEEE Journal of Biomedical and Health Informatics, 2022. 26(6), 2458-2468. | PDF

  20. Estimation of Global Irrigation Water Use by the Integration of Multiple Satellite Observations.
    Zhang, K., Li, X., Zheng, D., Zhang, L., Zhu, G.
    Water Resources Research, 2022. 58(3), e2021WR030031. | PDF | ESI Highly Cited Papers

  21. Daytime and nighttime warming has no opposite effects on vegetation phenology and productivity in the northern hemisphere.
    Zhu, G., Wang, X., Xiao, J., Zhang, K., Wang, Y., He, H., Li, W., Chen, H.
    Science of The Total Environment, 2022. 153386. | PDF

  22. Uncertainties in partitioning evapotranspiration by two remote sensing-based models.
    Chen, H., Zhu, G., Shang, S., Qin, W., Zhang, Y., Su, Y., Zhang, K., Zhu, Y., Xu, C.
    Journal of Hydrology, 2022. 127223. | PDF

  23. Associated atmospheric mechanisms for the increased cold season precipitation over the Three-River Headwaters region from the late 1980s.
    Shang, S., Zhu, G., Wei, J., Li, Y., Zhang, K., Li, R., Arnault, J., Zhang, Z., Laux, P., Yang, Q., Dong, N., Gao, L., Kunstmann, H.
    Journal of Climate, 2021. 34, 8033–8046. | PDF

  24. Discrepant responses between evapotranspiration- and transpiration-based ecosystem water use efficiency to interannual precipitation fluctuations.
    Gu, C., Tang, Q., Zhu, G., Ma, J., Gu, C., Zhang, K., Sun, S., Yu, Q., Niu, S.
    Agricultural and Forest Meteorology, 2021. 303, 108385. | PDF

  25. High agricultural water consumption led to the continued shrinkage of the Aral Sea during 1992-2015.
    Su, Y., Li, X., Feng, M., Nian, Y., Huang, L., Xie, T., Zhang, K., Chen, Feng, Huang, W., Chen, J., Chen, Fahu.
    Science of The Total Environment, 2021. 777, 145993. | PDF

  26. Merging multiple satellite-based Precipitation products and gauge observations using a novel double machine learning approach.
    Zhang, L., Li, X., Zheng, D., Zhang, K., Ma, Q., Zhao, Y., Ge, Y.
    Journal of Hydrology, 2021. 594, 125969. | PDF

  27. A spatial-temporal continuous dataset of the transpiration to evapotranspiration ratio in China from 1981-2015.
    Niu, Z., He, H., Zhu, G., Ren, X., Zhang, L., Zhang, K.
    Scientific Data, 2020. 7, 369. | PDF

  28. Evapotranspiration Models Using Different LAI and Meteorological Forcing Data from 1982 to 2017.
    Chen, H., Zhu, G., Zhang, K., Bi, J., Jia, X., Ding, B., Zhang, Y., Shang, S., Zhao, N., Qin, W.
    Remote Sensing, 2020. 12, 2473. | PDF

  29. Soil respiration in an irrigated oasis agroecosystem: linking environmental controls with plant activities on hourly, daily and monthly timescales.
    Ma, T., Zhu, G., Ma, J., Zhang, K., Wang, S., Han, T., Shang, S.
    Plant and Soil, 2020. 447, 347–364. | PDF

  30. Sensitivity analysis and estimation using a hierarchical Bayesian method for the parameters of the FvCB biochemical photosynthetic model.
    Han, T., Zhu, G., Ma, J., Wang, S., Zhang, K., Liu, X., Ma, T., Shang, S., Huang, C.
    Photosynthesis Research, 2020. 143, 45–66. | PDF

  31. Development and evaluation of a simple hydrologically based model for terrestrial evapotranspiration simulations.
    Zhu, G., Zhang, K.*, Chen, H., Wang, Y., Su, Y., Zhang, Y., Ma, J.
    Journal of Hydrology, 2019. 577, 123928. | PDF

  32. Parameter Analysis and Estimates for the MODIS Evapotranspiration Algorithm and Multiscale Verification.
    Zhang, K., Zhu, G., Ma, J., Yang, Y., Shang, S., Gu, C.
    Water Resources Research, 2019. 55(3), 2211–2231. | PDF

  33. A Physically Based Method for Soil Evaporation Estimation by Revisiting the Soil Drying Process.
    Wang, Y., Merlin, O., Zhu, G., Zhang, K.
    Water Resources Research, 2019. 55, 9092–9110. | PDF

  34. An increasing trend in the ratio of transpiration to total terrestrial evapotranspiration in China from 1982 to 2015 caused by greening and warming.
    Niu, Z., He, H., Zhu, G., Ren, X., Zhang, L., Zhang, K., Yu, G., Ge, R., Li, P., Zeng, N., Zhu, X.
    Agricultural and Forest Meteorology, 2019. 279, 107701. | PDF

  35. The characteristics of evapotranspiration and crop coefficients of an irrigated vineyard in arid Northwest China.
    Wang, S., Zhu, G., Xia, D., Ma, J., Han, T., Ma, T., Zhang, K., Shang, S.
    Agricultural Water Management, 2019. 212, 388-398. | PDF

  36. Partitioning evapotranspiration using an optimized satellite-based ET model across biomes.
    Gu, C., Ma, J., Zhu, G., Yang, H., Zhang, K., Wang, Y., Gu, C.
    Agricultural and Forest Meteorology, 2018. 259, 355–363. | PDF

  37. A new moving strategy for the sequential Monte Carlo approach in optimizing the hydrological model parameters.
    Zhu, G., Li, X., Ma, J., Wang, Y., Liu, S., Huang, C., Zhang, K., Hu, X.
    Advances in Water Resources, 2018. 114, 164–179. | PDF

  38. A hierarchical Bayesian approach for multi-site optimization of a satellite-based evapotranspiration model.
    Su, Y., Feng, Q., Zhu, G., Gu, C., Wang, Y., Shang, S., Zhang, K., Han, T., Chen, H., Ma, J.
    Hydrological Processes, 2018. 32, 3907–3923. | PDF

  39. Parameter sensitivity analysis and optimization for a satellite‐based evapotranspiration model across multiple sites using Moderate Resolution Imaging Spectroradiometer and flux data.
    Zhang, K., Ma, J., Zhu, G., Ma, T., Han, T., Feng, L. L.
    Journal of Geophysical Research: Atmospheres , 2017. 122(1), 230-245. | PDF

  40. Evaluating the complementary relationship for estimating evapotranspiration using the multi-site data across north China.
    Zhu, G., Zhang, K., Li, X., Liu, S., Ding, Z., Ma, J., Huang, C., Han, T., He, J.
    Agricultural and Forest Meteorology, 2016. 230, 33-44. | PDF

  41. Multi‐model ensemble prediction of terrestrial evapotranspiration across north China using Bayesian model averaging.
    Zhu, G., Li, X., Zhang, K., Ding, Z., Han, T., Ma, J., Huang, C., He, J., Ma, T.
    Hydrological Processes, 2016. 30(16), 2861-2879. | PDF

  42. Energy exchange and evapotranspiration over irrigated seed maize agroecosystems in a desert-oasis region, northwest China.
    Zhang, Y., Zhao, W., He, J., Zhang, K.
    Agricultural and Forest Meteorology, 2016. 223, 48–59. | PDF

  43. Hysteresis loops between canopy conductance of grapevines and meteorological variables in an oasis ecosystem.
    Bai, Y., Zhu, G., Su, Y., Zhang, K., Han, T., Ma, J., Wang, W., Ma, T., Feng, L.
    Agricultural and Forest Meteorology, 2015. 214, 319-327. | PDF

  44. Simultaneous parameterization of the two-source evapotranspiration model by Bayesian approach: application to spring maize in an arid region of northwest China.
    Zhu, G.F., Li, X., Su, Y.H, Zhang, K., Bai, Y., Ma, J.Z., Li, C.B., Hu, X.L., He, J.H.
    Geoscientific Model Development, 2014. 7, 741-775. | PDF

  45. Modelling evapotranspiration in an alpine grassland ecosystem on Qinghai‐Tibetan plateau.
    Zhu, G., Su, Y., Li, X., Zhang, K., Li, C., Ning, N.
    Hydrological Processes, 2015. 28(3), 610-619. | PDF

  46. Energy flux partitioning and evapotranspiration in a sub‐alpine spruce forest ecosystem.
    Zhu, G., Lu, L., Su, Y., Wang, X., Cui, X., Ma, J., He, J., Zhang, K., Li, C.
    Hydrological Processes, 2015. 28(19), 5093-5104. | PDF

  47. Estimating actual evapotranspiration from an alpine grassland on Qinghai-Tibetan plateau using a two-source model and parameter uncertainty analysis by Bayesian approach.
    Zhu, G., Su, Y., Li, X., Zhang, K., Li, C.
    Journal of Hydrology, 2013. 476, 42-51. | PDF


    48. In Chinese

  48. Changes in Transpiration and Evapotranspiration of Grapevines (Vitis vinifera L.) in Arid Oasis in Northwestern China
    Wang Shangtao, Zhao Nan, Zhang Yang, Zhang Kun, Zhu Gaofeng.
    Journal of Irrigation and Drainage, 2021. 40(12):1-6. | PDF

  49. Research progress on parameter sensitivity analysis in ecological and hydrological models of remote sensing
    Ma Hanqing, Zhang Kun, Ma Chunfeng, Wu Xiaodan, Wang Chen, Zheng Yi, Zhu Gaofeng, Yuan Wenping, Li Xin.
    National Remote Sensing Bulletin, 2021. 20219089. | PDF

  50. Spatiotemporal Variation of Temperature and Precipitation in Northwest China in recent 54 Years.
    Shang, S., Lian, L., Ma, T., Zhang, K., Han, T.
    Arid Zone Research, 2018. 35(01):68-76. | PDF

  51. Scale expansion of evapotranspiration in different vegetation types based on the artificial neural network.
    Feng, L., Zhang, K., Han, T., Ma, T., Sun, S., Zhu, G.
    Journal of Lanzhou University: Natural Sciences, 2017. 53(2), 186-193. | PDF

  52. Temporal-spatial variation characteristic in grapevine soil respiration and its relationship with the soil temperature and moisture.
    Ma, T., Zhu, G., Zhang, K., Feng, L.
    Journal of Lanzhou University: Natural Sciences, 2016. 52(1), 43-50. | PDF

  53. Characteristics and seasonal variations of plant leaf photosynthesis.
    Han, T., Feng, L, Ma, T., Zhang, K., Bai, Y., Zhu, G.
    Journal of Lanzhou University: Natural Sciences, 2016. 52(4), 492-497. | PDF

  54. Migration and accumulation of nitrate in soil profiles in Dunhuang.
    Zhao, M., Ma, J., Sun, P., Zhao, W., Zhang, K.
    Journal of Arid Land Resources and Environment, 2016. (05), 135-142. | PDF

  55. Investigation of spatial representativeness for flux data of continental river basin in arid region of northwestern China.
    Zhang, K., Han, T., Zhu, G., Bai, Y., Ma, T.
    Arid Land Geography, 2015. 38(04), 743-752. | PDF

  56. Analysis of variation of sap flow velocity and water consumption of grapevine in the Nanhu oasis, Dunhuang, China.
    Bai, Y., Zhu, G., Zhang, K., Ma, T.
    Journal of Desert Research, 2015. 35(1), 175-181. | PDF

  57. Research of transpiration and evapotranspiration from a grapevine canopy combining the sap flow and eddy covariance techniques.
    Bai, Y., Zhu, G., Zhang, K., Ma, T.
    Acta Ecologica Sinica, 2015. 35(23), 7821-7831. | PDF

  58. Characteristics of spatial distribution and accumulation of nitrate in the unsaturated soil profiles in Dunhuang.
    Zhao, M., Ma, J., Sun, P., Zhao, W., Zhang, K.
    Environmental Chemistry, 2015. (10), 1823-1831. | PDF

  59. Gap filling for evapotranspiration based on BP artificial neural networks.
    Zhang, K., Zhu, G., Bai, Y., Ma, T.
    Journal of Lanzhou University: Natural Sciences, 2015. 50(3), 348-355. | PDF

  60. Organic carbon density and storage in different soils on the Loess Plateau.
    Fu, D., Liu, M., Liu, L., Zhang, K., Zuo, J.
    Arid Zone Research, 2015. 31(01), 44-50. | PDF

Papers in review

  1. Heatwaves on the rise: the role of El Niño-Southern Oscillation and local water-energy exchanges in shaping global patterns.
    Zhang, K., Li, J., Guo, Z., Liu, S., Zhu, G., Shang, S., Zhang, J., Ng, M.*, & Wu, J*.
    Journal of Geophysical Research: Atmospheres, Major Revision

  2. Global prevalence of compound heatwaves in recent decades.
    Zhang, K., Li, J.*, Ng, M.*, Guo, Z., Tai, A., Liu, S., Zhang, J., Wang, X., & Wu, J*.
    Advances in Climate Change Research, Under review

  3. Long-term trend and interannual variability in global terrestrial evapotranspiration are driven by divergent regions.
    Chen, H.#, Zhang, K.#, Zhu, G., Fan, L., Li, X., Wang, Y., Wang, X., Zhu, Y., Shang, S., & Xiao, J.
    Geophysical Research Letters, Under review

  4. Weakened biophysical cooling effects of irrigation with increasing water-saving technology.
    Zhang, C., Ge, Q.*, Li, Y., Thiery, W., Peng, S., Leng, G., Zhao, G., Jin, Z., Li, W., Zhang, K., Zhang, X., Han, S., Zhang, G., Xiao, X., & Dong, J.*
    Remote Sensing of Environment, Under review

  5. Can large-scale satellite products track the effects of atmospheric dryness and soil water deficit on ecosystem productivity under droughts?
    Wang, X., Guo, Z., Zhang, K., Fu, Z., Lee, C., Yang, D., Detto, M., Ryu, Y., Zhang, Y., & Wu, J.*
    Geophysical Research Letters, Under review


Talks

  • Estimation of Long-term Global Terrestrial Evapotranspiration and Its Components Using a Process-Based Model Integrated with Remote Sensing Data.
    AGU24, H13S-05. December 9th-13th, 2024. Washington D.C. (Oral)

  • Variation of global compound heatwaves and their associations with climate variability.
    EGU General Assembly, EGU23-4268. April 23th-28th, 2023. Vienna. (Poster)

  • Estimation of Global Irrigation Water Use by Integrating Multiple Satellite Observations.
    Asia Oceania Geosciences Society (AOGS 2021), 18th Annual Meeting. August 4th, 2021. Virtual. (Oral)

  • Potential of global irrigation estimates from multiple satellite observations.
    China Society of Natural Resources, Annual Meeting (2020-2021). June 18th, 2021. Chengdu. (Oral)

  • A better estimation of global terrestrial evapotranspiration by data-model fusion scheme.
    Hydrology and Water Resources sub-forum, Annual Meeting of Chinese Hydraulic Society. October 19th, 2020. Beijing. (Oral)

  • Parameter sensitivity analysis and optimization for a global remote sensing-based evapotranspiration model.
    EGU General Assembly, EGU2019-4742. April 7th-12th, 2019. Vienna. (Oral)

  • Improvement of a satellite-based evapotranspiration model based on multiple in-situ flux observations.
    The 15th Water Resources Commission, China Society of Natural Resources. December 10th-12th, 2017. Shenzhen. (Oral)

  • Oasis flux observation and data gap filling based on artificial neural networks.
    Annual Meeting of HiWATER. January 8th-10th, 2013. Beijing. (Oral)

Data & Code


Global dataset of terrestrial evapotranspiration and soil moisture (1982-2020)

Total ET Plant Transpiration Soil Evaporation Interception SWC at 3 layers

Daily Global 0.1° Download



Satellite-based Global Irrigation Water Use dataset (2011-2018)

IWU

Monthly Global 0.25° Download

Affiliations

Associate Professor

Apr. 2024 – present

Sun Yat-Sen University (SYSU)

School of Geospatial Engineering and Science

Postdoctoral Fellow

Nov. 2021 – Mar. 2023

The University of Hong Kong (HKU)

Department of Mathematics & School of Biological Sciences

Supervised by Prof. Michael Ng and Prof. Jin Wu

Special Research Associate

Sep. 2018 – Oct. 2021

Institute of Tibetan Plateau Research, Chinese Academy of Sciences (ITPCAS)

National Tibetan Plateau Data Center (TPDC)

Supervised by Prof. Xin Li




Education

Ph.D. in Physical Geography (Eco-Hydrology)

Sep. 2012 – Jul. 2018

Lanzhou University, Lanzhou, China

Key Laboratory of West China's Environmental System

Supervised by Prof. Gaofeng Zhu and Prof. Jinzhu Ma

Joint Ph.D. in Eco-Hydrology

Oct. 2016 – Nov. 2017

Flinders University, Adelaide, Australia

National Centre for Groundwater Research and Training (NCGRT)

Supervised by Prof. Huade Guan

B.S. in Geographic Information System

Sep. 2008 – Jul. 2012

Northwest A&F University, Yangling, China

School of Natural Resources and Environment

Fundings

The Young Scientists Fund of the National Natural Science Foundation of China


Quantitative estimates for water cycle closure and uncertainties of endorheic basins along the Silk Road

PI, 2019–2022, ￥300,000

The China Postdoctoral Science Foundation


Estimation of irrigation water use and its hydrological implication in Heihe river basin based on multi-source remote sensing data

PI, 2019–2021, ￥80,000

Journal Reviewer

Global Change Biology Science Bulletin
Remote Sensing of Environment Water Resources Research
Journal of Hydrology Hydrology and Earth System Sciences
WIREs Water Scientific Data
GIScience & Remote Sensing IEEE JSTAR
Remote Sensing Software Impact

Awards & Honors

Western Environment Award, 2020
Lanzhou University, China
National Scholarship, 2017
Ministry of Education, China
CSC Scholarship, 2016
CSC Scholarship, 2016
First-class Academic Scholarship, 2012-2014
Lanzhou University, China