Estimation of Evapotranspiration from Wetlands Using Geospatial and Hydrometeorological Data

  • Jay Krishna Thakur
  • P. K. Srivastava
  • Arun Kumar Pratihast
  • Sudhir Kumar Singh


Over recent decades, wetlands have been recognized increasingly for their high biodiversity and for the important hydrological functions, including flood alleviation, low-flow support, nutrient cycling and groundwater recharge (Thakur, 2010; Thakur et al., 2011). Wetland hydrology is a primary driving force influencing wetland ecology, its development and persistence (Mitsch and Gosselink, 1993). For most wetlands, evapotranspiration (ET) is the major component of water loss, and when considered as its energy equivalent, the latent heat flux (LE), the largest consumer of incoming energy (Reynolds et al., 2000; Wilson et al., 2001). The radiation and the turbulent heating drive the dynamics of the land-atmosphere energy exchanges in the wetlands. Estimation of these radiation and turbulent heating through mass energy balance equations is the core of numerical weather forecast, climate research, water resources and environmental management and long-term agriculture production. Most of the conventional methods which use point measurement in measuring the energy balance, such as Bowen ratio, Penman-Monteith, Priestley and Taylor, give results that can be efficient on local level but could not be extended to large scale or global scale measurement in time and space (Stewart, 1989).


Normalize Deviation Vegetation Index Latent Heat Flux Land Surface Temperature Evaporative Fraction Singhbhum Shear Zone 
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The author (JKT) is highly thankful to Zoltan Vekerdy, Gabriel Norberto Parodi and Mustafa Gokmen for the guidance throughout the research period, data availability and field visit arrangements at Water Resources Department, Faculty of Geo-information Science and Earth Observation (ITC), Universiteit Twente, Enschede, The Netherlands.


  1. Brutsaert W. Aspects of bulk atmospheric boundary layer similarity under free convective conditions. Reviews of Geophysics. 1999;37(4):439–451.CrossRefGoogle Scholar
  2. Campbell RB, Phene CJ. Estimating potential evaporation from screened pan evaporation. Agricultural meteorology. 1976;16:343–352.CrossRefGoogle Scholar
  3. Cox P, Betts R, Bunton C, Essery R, Rowntree P, Smith J. The impact of new land surface physics on the GCM simulation of climate and climate sensitivity. Climate Dynamics. 1999;15(3):183–203.CrossRefGoogle Scholar
  4. Gokmen, M., Vekerdy, Z. and Verhoef, W. (2009). Earth Observation for Quantifying Ecohydrological Fluxes. Paper presented at the European Geosciences Union (EGU) Conference.Google Scholar
  5. Hupet F, Vanclooster M. Effect of the sampling frequency of meteorological variables on the estimation of the reference evapotranspiration. Journal of Hydrology. 2001;243(3–4):192–204.CrossRefGoogle Scholar
  6. Jia L, Yrisarry J, Ibanez M, Cuesta A. Estimation of sensible heat flux using the Surface Energy Balance System (SEBS) and ATSR measurements. Physics and Chemistry of the Earth, Parts A/B/C. 2003;28(1–3):75–88.CrossRefGoogle Scholar
  7. Jin X, Wan L, Su Z. Research on evaporation of Taiyuan basin area by using remote sensing. HAL - CCSD; 2005.Google Scholar
  8. Kakane VCK, Sogaard, H. Estimation of Surface Temperature and Rainfall in Ghana. Geografisk Tidsskrift, Danish Journal of Geography. 1997;97:76–85.Google Scholar
  9. Kalmar A, Currie DJ. A global model of island biogeography. Global Ecology and Biogeography. 2006;15(1):72–81.CrossRefGoogle Scholar
  10. Maidment, D.R. (Ed.). (1993). Handbook of Hydrology: McGraw-Hill Professional.Google Scholar
  11. Massman WJ. A model study of kBH-1 for vegetated surfaces using localized near-field Lagrangian theory. Journal of Hydrology. 1999;223(1–2):27–43.CrossRefGoogle Scholar
  12. Mitsch, W.J. and Gosselink, J.G. (Eds.). (1993). Wetlands (Second ed.): Van Nostrand Reinhold, New York.Google Scholar
  13. Moran M, Clarke T, Inoue Y, Vidal A. Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index. Remote Sensing of Environment. 1994;49(3):246–263.CrossRefGoogle Scholar
  14. Nemani RR, Running SW. Estimation of Regional Surface-Resistance to Evapotranspiration from Ndvi and Thermal-Ir Avhrr Data. Journal of Applied Meteorology. 1989;28(4):276–284.CrossRefGoogle Scholar
  15. Noilhan J, Planton S. A simple parameterization of land surface processes for meteorological models. Monthly Weather Review. 1989;117(3):536–549.CrossRefGoogle Scholar
  16. Qin C, Jia Y, Su Z, Zhou Z, Qiu Y, Suhui S. Integrating Remote Sensing Information into a Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation. Sensors. 2008;8(7):4441–4465.CrossRefGoogle Scholar
  17. Reynolds JF, Kemp PR, Tenhunen JD. Effects of long-term rainfall variability on evapotranspiration and soil water distribution in the Chihuahuan Desert: a modeling analysis. Plant Ecology. 2000;150(1):145–159.CrossRefGoogle Scholar
  18. Sandholt I, Rasmussen K, Andersen J. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sensing of Environment. 2002;79(2–3):213–224.CrossRefGoogle Scholar
  19. Shukla J, Mintz Y. Influence of land-surface évapotranspiration on the earth's climate. Science. 1982;215(4539):1498.CrossRefGoogle Scholar
  20. Singh SK, Thakur JK, Singh UK. Environmental Monitoring of Land cover/land use change in Shiwalik Hills, Rupnagar District of Punjab. Paper presented at the International Conference on Global Climate Change: India using Remote Sensing and Ancillary data; 2010.Google Scholar
  21. Srivastava PK, Majumdar TJ, Bhattacharya AK. Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data. Advances in Space Research. 2009;43(10):1563–1574.CrossRefGoogle Scholar
  22. Stewart JB. On the use of the Penrnan-Monteith equation for determining area! évapotranspiration. B.C., Canada: Paper presented at the Estimation of Areal Evapotranspiration Vancouver; 1989.Google Scholar
  23. Su H, McCabe MF, Wood EF, Su Z, Prueger JH. Modeling Evapotranspiration during SMACEX: Comparing Two Approaches for Local and Regional-Scale Prediction. Journal of Hydrometeorology. 2005;6(6):910.CrossRefGoogle Scholar
  24. Su Z. The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes. Hydrology and Earth System Sciences. 2002;6:85–100.CrossRefGoogle Scholar
  25. Su, Z. and Jacobs, C. (2001). ENVISAT: actual evaporation. BCRS Report 2001: USP-2 Report 2001 01-02, Beleidscommissie Remote Sensing (BCRS) Delft.Google Scholar
  26. Su Z, Pelgrum H, Menenti M. Aggregation effects of surface heterogeneity in land surface processes. Hydrol. Earth Syst. Sci.. 1999;3(4):549–563.CrossRefGoogle Scholar
  27. Su Z, Yacob A, Wen J, Roerink G, He Y, Gao B, Boogaard H, Diepen CV. Assessing relative soil moisture with remote sensing data: theory, experimental validation, and application to drought monitoring over the North China Plain. Physics and Chemistry of the Earth. 2003;28:89–101.CrossRefGoogle Scholar
  28. Szilagyi J, Jozsa J. New findings about the complementary relationship- based evaporation estimation methods. Journal of Hydrology. 2008;354(1–4):171–186.CrossRefGoogle Scholar
  29. Tektas A. Determination of Biological diversity. Biyolojik Çeçitliligin Tespiti/ Tuz Gölü Projesi: Corporate head office of special environmental protection; 2007.Google Scholar
  30. Thakur, J.K. (2010). Eco-hydrological wetland monitoring in a semi-arid region (A case study of Konya Closed Basin, Turkey). Faculty of International Institute for Geo-Information Science and Earth Observation (ITC), Universiteit Twente, Enschede, the Netherlands.Google Scholar
  31. Thakur JK, Singh SK. Eco-hydrological monitoring of wetlands in a semi-arid region using remote sensing, GIS, GPS and various data sets: a case study of Konya closed basin. Paper presented at the IAH: Turkey; 2010. 2010.Google Scholar
  32. Thakur JK, Singh SK, Diwakar J. Estimation of actual evapotranspiration (ETa) using Surface Energy Balance System (SEBS) and remote sensing approach for Water Resources Management of Wetlands in Semi Arid region. Nagpur, India: Paper presented at the Sustainable Water Resource Management and Treatment Technology; 2011a.Google Scholar
  33. Thakur JK, Srivastava PK, Singh SK, Vekerdy Z. Ecological monitoring of wetlands in semi-arid region of Konya closed basin. Turkey. Regional Environmental Change. 2011b. doi:10.1007/s10113-011-0241-x.Google Scholar
  34. van der Kwast, J., Timmermans, W., Gieske, A., Su, Z., Olioso, A., Jia, L., Elbers, J., Karssenberg, D. and Jong, (2009). Evaluation of the Surface Energy Balance System (SEBS) applied to ASTER imagery with flux-measurements at the SPARCGoogle Scholar
  35. 2004 site (Barrax, Spain). Hydrology and Earth System Sciences Discussions, 6(1), 1165-1196.Google Scholar
  36. Weng Q, Lu D, Schubring J. Estimation of land surface temperature- vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment. 2004;89(4):467–483.CrossRefGoogle Scholar
  37. Wilson KB, Hanson PJ, Mulholland PJ, Baldocchi DD, Wullschleger SD. A comparison of methods for determining forest evapotranspiration and its components: Sap-flow, soil water budget, eddy co variance and catchment water balance. Agricultural and Forest Meteorology. 2001;106(2):153–168.CrossRefGoogle Scholar
  38. Yao AYM. Agricultural potential estimated from the ratio of actual to potential evapotranspiration. Agricultural Meteorology. 1974;13(3):405–417.CrossRefGoogle Scholar
  39. Yue W, Xu J, Tan W, Xu L. The relationship between land surface temperature and NDVI with remote sensing: application to Shanghai Landsat 7 ETM+ data. International Journal of Remote Sensing. 2007;28(15):3205–3226.CrossRefGoogle Scholar
  40. Zeki Camur M, Mutlu H. Major-ion geochemistry and mineralogy of the Salt Lake (Tuz Golu) basin, Turkey. Chemical Geology. 1996;127(4):313–329.CrossRefGoogle Scholar

Copyright information

© Capital Publishing Company 2011

Authors and Affiliations

  • Jay Krishna Thakur
    • 1
  • P. K. Srivastava
    • 2
  • Arun Kumar Pratihast
    • 3
  • Sudhir Kumar Singh
    • 4
  1. 1.Department of Hydrogeology and Environmental Geology, Institute of GeosciencesMartin Luther UniversityHalleGermany
  2. 2.Water and Environment Management Research Centre Department of Civil EngineeringUniversity of BristolBristolUnited Kingdom
  3. 3.Center for Geo-informationWageningen UniversityWageningenThe Netherlands
  4. 4.Department of Atmospheric and Ocean ScienceUniversity of AllahabadAllahabadIndia

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