Skip to main content
SpringerLink
Log in

A review on evapotranspiration data assimilation based on hydrological models

  • Published:
Journal of Geographical Sciences Aims and scope Submit manuscript

Abstract

Accurate estimation of evapotranspiration (ET), especially at the regional scale, is an extensively investigated topic in the field of water science. The ability to obtain a continuous time series of highly precise ET values is necessary for improving our knowledge of fundamental hydrological processes and for addressing various problems regarding the use of water. This objective can be achieved by means of ET data assimilation based on hydrological modeling. In this paper, a comprehensive review of ET data assimilation based on hydrological modeling is provided. The difficulties and bottlenecks of using ET, being a non-state variable, to construct data assimilation relationships are elaborated upon, with a discussion and analysis of the feasibility of assimilating ET into various hydrological models. Based on this, a new easy-to-operate ET assimilation scheme that includes a water circulation physical mechanism is proposed. The scheme was developed with an improved data assimilation system that uses a distributed time-variant gain model (DTVGM), and the ET-soil humidity nonlinear time response relationship of this model. Moreover, the ET mechanism in the DTVGM was improved to perfect the ET data assimilation system. The new scheme may provide the best spatial and temporal characteristics for hydrological states, and may be referenced for accurate estimation of regional evapotranspiration.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Andersen J, Dybkjaer G, Jensen K H et al., 2002. Use of remotely sensed precipitation and leaf area index in a distributed hydrological model. Journal of Hydrology, 264(1): 34–50.

    Article  Google Scholar 

  • Arnold J G, Williams J R, Srinivasan R et al., 1998. Large area hydrologic modeling and assessment part I: Model development. Journal of the American Water Resources Association, 34(1): 73–89.

    Article  Google Scholar 

  • Beven K, Calver A, Morris E M, 1987. The Institute of Hydrology Distributed Model, 1–33. Wallingford: Institute of Hydrology, 1–33. (IH Report No.98)

    Google Scholar 

  • Beven K J, Kirkby M J, 1979. A physically based, variable contributing area model of basin hydrology/Un modèle à base physique de zone d'appel variable de l'hydrologie du bassin versant. Hydrological Sciences Journal, 24(1): 43–69.

    Article  Google Scholar 

  • Beven K J, Kirkby M J, Schofield N et al., 1984. Testing a physically based flood-forecasting model (TOPMODEL) for three UK catchments. Journal of Hydrology, 69(1–4): 119–143.

    Article  Google Scholar 

  • Cao Lijuan, Liu Jingmiao, Ren Liliang, 2005. Improving on the evapotranspiration calculation of Xinanjinag model. Hydrology, 25(3): 5–9, 19. (in Chinese)

    Google Scholar 

  • Chen H, Yang D, Hong Y et al., 2013. Hydrological data assimilation with the Ensemble Square-Root-Filter: Use of streamflow observations to update model states for real-time flash flood forecasting. Advances in Water Resources, 59: 209–220.

    Article  Google Scholar 

  • Conradt T, Wechsung F, Bronstert A, 2013. Three perceptions of the evapotranspiration landscape: Comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances. Hydrology and Earth System Sciences Discussions, 10(1): 1127–1183.

    Article  Google Scholar 

  • Dumedah G, Coulibaly P, 2013. Evolutionary assimilation of streamflow in distributed hydrologic modeling using in-situ soil moisture data. Advances in Water Resources, 53: 231–241.

    Article  Google Scholar 

  • Evensen G, 2003. The Ensemble Kalman Filter: Theoretical formulation and practical implementation. Ocean Dynamics, 53(4): 343–367.

    Article  Google Scholar 

  • Feddes R A, Kowalik P, Kolinska-Malinka K et al., 1976. Simulation of field water uptake by plants using a soil water dependent root extraction function. Journal of Hydrology, 31(1): 13–26.

    Article  Google Scholar 

  • Feddes R A, Kowallk P, Neuman S P et al., 1976. Finite difference and finite element simulation of field water uptake by plants. Hydrological Sciences Journal, 21(1): 81–98.

    Article  Google Scholar 

  • Freeze R A, Harlan R L, 1969. Blueprint for a physically-based, digitally-simulated hydrologic response model. Journal of Hydrology, 9(3): 237–258.

    Article  Google Scholar 

  • Hao Zhenchun, Li Li, Wang Jiahu et al., 2010. Theory and Method of Distributed Hydrological Model. Beijing: Science Press. (in Chinese)

    Google Scholar 

  • Huang Yue, Chen Xi, Bao Anming et al., 2010. Distributed hydrological modeling in Kaidu Basin: MIKE-SHE model calibration and uncertainty estimation. Journal of Glaciology and Geocryology, 32(3): 567–572. (in Chinese)

    Google Scholar 

  • Immerzeel W, Droogers P, 2008. Calibration of a distributed hydrological model based on satellite evapotranspiration. Journal of Hydrology, 349(3/4): 411–424.

    Article  Google Scholar 

  • Irmak A, Kamble B, 2009. Evapotranspiration data assimilation with genetic algorithms and SWAP model for on-demand irrigation. Irrigation Science, 28(1): 101–112.

    Article  Google Scholar 

  • Kustas W P, Norman J M, 1996. Use of remote sensing for evapotranspiration monitoring over land surfaces. Hydrological Sciences Journal, 41(4): 495–516.

    Article  Google Scholar 

  • Lei F, Huang C, Shen H et al., 2014. Improving the estimation of hydrological states in the SWAT model via the ensemble Kalman smoother: Synthetic experiments for the Heihe River Basin in northwest China. Advances in Water Resources, 67: 32–45.

    Article  Google Scholar 

  • Li L, Xia J, Xu C et al., 2010. Evaluation of the subjective factors of the GLUE method and comparison with the formal Bayesian method in uncertainty assessment of hydrological models. Journal of Hydrology, 390(3): 210–221.

    Article  Google Scholar 

  • Li Xin, Huang Chunlin, Che Tao et al., 2007. Progress and prospect of research on land data assimilation system in China. Progress in Natural Science, 17(2): 163–173. (in Chinese)

    Article  Google Scholar 

  • Li Z, Tang R, Wan Z et al., 2009. A review of current methodologies for regional evapotranspiration estimation from remotely sensed data. Sensors, 9(5): 3801–3853.

    Article  Google Scholar 

  • Li Zhijia, Zhang Ke, Yao Cheng, 2006. Comparison of distributed geological models based on GIS technology and DEM. Journal of Hydraulic Engineering, 37(8): 1022–1028. (in Chinese)

    Google Scholar 

  • Liang Shunlin, Li Xin, Xie Xianhong et al., 2013. Land Surface Observations, Modeling and Data Assimilation. Beijing: Higher Education Press, 97–114. (in Chinese)

    Book  Google Scholar 

  • Liang X, Lettenmaier D P, Wood E F et al., 1994. A simple hydrologically based model of land surface water and energy fluxes for general circulation models. Journal of Geophysical Research: Atmospheres, 99(D7): 14415–14428.

    Article  Google Scholar 

  • Liu Sanchao, Zhang Wanchang, Gao Maofang et al., 2007. Simulation of land surface evapotranspiration using distributed hydrological model, remote sensing and GIS technology. Scientia Geographica Sinica, 27(3): 354–358. (in Chinese)

    Google Scholar 

  • Mo X, Liu S, 2001. Simulating evapotranspiration and photosynthesis of winter wheat over the growing season. Agricultural and Forest Meteorology, 109(3): 203–222.

    Article  Google Scholar 

  • Moradkhani H, 2008. Hydrologic remote sensing and land surface data assimilation. Sensors, 8(5): 2986–3004.

    Article  Google Scholar 

  • Pan M, Wood E F, Wójcik R et al., 2008. Estimation of regional terrestrial water cycle using multi-sensor remote sensing observations and data assimilation. Remote Sensing of Environment, 112(4): 1282–1294.

    Article  Google Scholar 

  • Pipunic C, Walker P, Western A, 2008. Assimilation of remotely sensed data for improved latent and sensible heat flux prediction: A comparative synthetic study. Remote Sensing of Environment, 112(4): 1295–1305.

    Article  Google Scholar 

  • Priestley C H B, Taylor R J, 1972. On the assessment of surface heat flux and evaporation using large-scale parameters. Monthly Weather Review, 100(2): 81–92.

    Article  Google Scholar 

  • Qin C, Jia Y, Su Z et al., 2008. Integrating remote sensing information into a distributed hydrological model for improving water budget predictions in large-scale basins through data assimilation. Sensors, 8(7): 4441–4465.

    Article  Google Scholar 

  • Refshaard J C, Storm B, Singh V P, 1995. MIKE SHE. In: Computer Models of Watershed Hydrology. Water Resources Publications, 809–846.

    Google Scholar 

  • Renard B, Kavetski D, Kuczera G et al., 2010. Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors. Water Resources Research, 46(5): W05521.

    Article  Google Scholar 

  • Rosenberg N J, 1983. Microclimate: The Biological Environment. New York: John Wiley & Sons.

    Google Scholar 

  • Schuurmans M, Troch A, Veldhuizen A et al., 2003. Assimilation of remotely sensed latent heat flux in a distributed hydrological model. Advances in Water Resources, 26(2): 151–159.

    Article  Google Scholar 

  • Song Xiaomeng, Zhan Chesheng, Kong Fanzhe et al., 2011. A review on uncertainty analysis of large-scale hydrological cycle modeling system. Acta Geographica Sinica, 66(3): 396–406. (in Chinese)

    Google Scholar 

  • Spies R R, Franz K J, Hogue T S et al., 2014. Distributed hydrologic modeling using satellite-derived potential evapotranspiration. Journal of Hydrometeorology, 16(1): 129–146.

    Article  Google Scholar 

  • Tang H, Li Z L, 2014. Estimation and validation of evapotranspiration from thermal infrared remote sensing data. In: Quantitative Remote Sensing in Thermal Infrared. Berlin and Heidelberg: Springer, 145–201.

    Chapter  Google Scholar 

  • Trudel M, Leconte R, Paniconi C, 2014. Analysis of the hydrological response of a distributed physically-based model using post-assimilation (EnKF) diagnostics of streamflow and in situ soil moisture observations. Journal of Hydrology, 514: 192–201.

    Article  Google Scholar 

  • Vázquez R F, 2003. Effect of potential evapotranspiration estimates on effective parameters and performance of the MIKE SHE-code applied to a medium-size catchment. Journal of Hydrology, 270(3): 309–327.

    Article  Google Scholar 

  • Vinukollu R K, Wood E F, Ferguson C R et al., 2011. Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: Evaluation of three process-based approaches. Remote Sensing of Environment, 115(3): 801–823.

    Article  Google Scholar 

  • Wang Kun, Mo Xingguo, Lin Zhonghui et al., 2010. Improvement and validation of vegetation interface process model. Chinese Journal of Ecology, 29(2): 387–394. (in Chinese)

    Google Scholar 

  • Wang Yongfen, Mo Xingguo, Hao Yanbin et al., 2008. Simulation seasonal and interannual variations of ecosystem evapotranspiration and its components in Inner Mongolia steppe with VIP model. Journal of Plant Ecology, 32(5): 1052–1060. (in Chinese)

    Google Scholar 

  • Wu Mengying, Wang Zhonggen, Dang Suzhen, 2012. Simulation and analysis of runoff in the upper reaches of the Heihe River basin. Resources Science, 34(10): 1913–1921. (in Chinese)

    Google Scholar 

  • Xia J, O'Connor K M, Kachroo R K et al., 1997. A non-linear perturbation model considering catchment wetness and its application in river flow forecasting. Journal of Hydrology, 200(1): 164–178.

    Article  Google Scholar 

  • Xia Jun, 2002. Theory and Method of Hydrologic Nonlinearity. Wuhan: Wuhan University Press. (in Chinese)

    Google Scholar 

  • Xia Jun, Wang Gangsheng, Lv Aifeng et al., 2003. A research on distributed time variant gain modeling. Acta Geographica Sinica, 58(5): 789–796. (in Chinese)

    Google Scholar 

  • Xia Jun, Wang Gangsheng, Tan Ge et al., 2004. Hydrology nonlinear systems and distributed time-variant gain model. Science in China: Series D, 34(11): 1062–1071. (in Chinese)

    Google Scholar 

  • Xia Jun, Ye Aizhong, Wang Gangsheng, 2005. A distributed time-variant gain model applied to Yellow River (I): Model theories and structures. Engineering Journal of Wuhan University, 38(6): 10–15. (in Chinese)

    Google Scholar 

  • Xie X, Zhang D, 2010. Data assimilation for distributed hydrological catchment modeling via ensemble Kalman filter. Advances in Water Resources, 33(6): 678–690.

    Article  Google Scholar 

  • Xu X, Li J, Tolson B A, 2014. Progress in integrating remote sensing data and hydrologic modeling. Progress in Physical Geography. doi: 10.1177/0309133314536583.

    Google Scholar 

  • Xu Zongxue et al., 2008. Hydrological Model. Beijing: Science Press. (in Chinese)

    Google Scholar 

  • Xu Zongxue, Cheng Lei, 2010. Progress on studies and applications of the distributed hydrological models. Journal of Hydraulic Engineering, 1(3): 5–6. (in Chinese)

    Google Scholar 

  • Yin Jian, Zhan Chesheng, Gu Hongliang et al., 2014. A case study of evapotranspiration data assimilation based on hydrological model. Advances in Earth Science, 29(9): 1075–1084. (in Chinese)

    Google Scholar 

  • Yu Z, Deng J, Liu C, 2014. Application of VIC model to hydrological response caused by urbanization in Dongjiang Basin. Journal of Water Resources Research, 3(1): 78–83. (in Chinese)

    Article  Google Scholar 

  • Zhang Ronghua, Du Junping, Sun Rui, 2012. Review of estimation and validation of regional evapotranspiration based on remote sensing. Advances in Earth Science, 27(12): 1295–1307. (in Chinese)

    Google Scholar 

  • Zhao Lingling, 2013. The evapotranspiration estimation methods study in hydrological cycle simulation [D]. Beijing: University of Chinese Academy of Sciences. (in Chinese)

    Google Scholar 

  • Zhao Lingling, Xia Jun, Xu Chongyu et al., 2013. A review of evapotranspiration estimation methods in hydrological models. Acta Geographica Sinica, 68(1): 127–136. (in Chinese)

    Google Scholar 

  • Zhao L W, Zhao W Z, 2014. Evapotranspiration of an oasis-desert transition zone in the middle stream of Heihe River, Northwest China. Journal of Arid Land, 6(5): 529–539.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Water Sciences, Beijing Normal University, Beijing, 100875, China

    Qingqing Dong, Huixiao Wang & Mingcheng Zhu

  2. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, 100101, China

    Chesheng Zhan & Feiyu Wang

  3. University of Chinese Academy of Sciences, Beijing, 100049, China

    Feiyu Wang

Authors
  1. Qingqing Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chesheng Zhan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Huixiao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Feiyu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mingcheng Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chesheng Zhan.

Additional information

Foundation: National Key Basic Research Program of China (973 Program), No.2015CB452701; National Natural Science Foundation of China, No.41271003, No.41371043, No.41401042

Author: Dong Qingqing (1990–), Master Candidate, specialized in evapotranspiration data assimilation.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dong, Q., Zhan, C., Wang, H. et al. A review on evapotranspiration data assimilation based on hydrological models. J. Geogr. Sci. 26, 230–242 (2016). https://doi.org/10.1007/s11442-016-1265-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11442-016-1265-4

Keywords

Search

Navigation