Skip to main content
Log in

Performance Comparison of Penman–Monteith and Priestley–Taylor Models Using MOD16A2 Remote Sensing Product

  • Published:
Pure and Applied Geophysics Aims and scope Submit manuscript

Abstract

The aim of this work is to develop and evaluate a performance comparison for estimating satellite-based actual evapotranspiration (AET) using the Penman–Monteith (PM) and Priestley–Taylor (PT) approaches and to create a spatial AET map in an ungauged sub-humid tropical river basin. A few studies have compared the PM and PT model performance with a MODIS evapotranspiration data product (MOD16A2). Estimated AET values by the PT approach (AETPT), PM model with aerodynamic conductance (Ga) computed using the Leuning equation (AETPM), and Ga computed using the Choudhury equation (AETPMCH) were extracted for each of the 304 pixels for each day, and pixelwise comparisons were made with the corresponding MOD16A2 AET estimates for validation. As shown by the low RMSE values (0.19–0.23 mm/day), the PM model suggested in this analysis with Ga computed using the (AETPMCH) equation turned out to be the better model. Also, using the (AETPMCH) equation significantly reduced PBIAS values for all days examined. Topography, land use and land cover (LU/LC), temperature, and moisture availability conditions appear to influence AET variations across the basin. For the eight total Julian days in summer and winter for selected wet (2007) and dry (2012) years the for period 2006–2017, pixelwise maps depicting spatial variability were developed using MATLAB for the AETPMCH approach for selected available cloud-free MODIS image data.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Allen, R. G., Tasumi, M., & Trezza, R. (2007). Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—Model. Journal of Irrigation and Drainage Engineering, 133(4), 380–394.

    Article  Google Scholar 

  • Autovino, D., Minacapilli, M., & Provenzano, G. (2016). Modelling bulk surface resistance by MODIS data and assessment of MOD16A2 evapotranspiration product in an irrigation district of Southern Italy. Agricultural Water Management, 167, 86–94.

    Article  Google Scholar 

  • Bastiaanssen, W. G. (2000). SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. Journal of Hydrology, 229(1–2), 87–100.

    Article  Google Scholar 

  • Bastiaanssen, W. G., Pelgrum, H., Wang, J., Ma, Y., Moreno, J. F., Roerink, G. J., & Van der Wal, T. (1998). A remote sensing surface energy balance algorithm for land (SEBAL).: part 2: validation. Journal of Hydrology, 212, 213–229.

    Article  Google Scholar 

  • Carlson, T. N., & Ripley, D. A. (1997). On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62(3), 241–252.

    Article  Google Scholar 

  • Cherif, I., Alexandridis, T. K., Jauch, E., Chambel-Leitao, P., & Almeida, C. (2015). Improving remotely sensed actual evapotranspiration estimation with raster meteorological data. International Journal of Remote Sensing, 36(18), 4606–4620.

    Article  Google Scholar 

  • Choudhury, B. J., Reginato, R. J., & Idso, S. B. (1986). An analysis of infrared temperature observations over wheat and calculation of latent heat flux. Agricultural and Forest Meteorology, 37(1), 75–88.

    Article  Google Scholar 

  • Cleugh, H. A., Leuning, R., Mu, Q., & Running, S. W. (2007). Regional evaporation estimates from flux tower and MODIS satellite data. Remote Sensing of Environment, 106(3), 285–304.

    Article  Google Scholar 

  • García, M., Sandholt, I., Ceccato, P., Ridler, M., Mougin, E., Kergoat, L., Morillas, L., Timouk, F., Fensholt, R., & Domingo, F. (2013). Actual evapotranspiration in drylands derived from in-situ and satellite data: assessing biophysical constraints. Remote Sensing of Environment, 131, 103–118.

    Article  Google Scholar 

  • Hassan, Q. K., Bourque, C. P. A., Meng, F. R., & Cox, R. M. (2007). A wetness index using terrain-corrected surface temperature and normalized difference vegetation index derived from standard MODIS products: an evaluation of its use in a humid forest-dominated region of eastern Canada. Sensors, 7(10), 2028–2048.

    Article  Google Scholar 

  • Hatfield, J. L., Perrier, A., & Jackson, R. D. (1983). Estimation of evapotranspiration at one time-of-day using remotely sensed surface temperatures. Developments in agricultural and managed forest ecology (Vol. 12, pp. 341–350). Elsevier.

    Google Scholar 

  • Jiang, L., & Islam, S. (2001). Estimation of surface evaporation map over southern Great Plains using remote sensing data. Water Resources Research, 37(2), 329–340.

    Article  Google Scholar 

  • Ke, Y., Im, J., Park, S., & Gong, H. (2017). Spatiotemporal downscaling approaches for monitoring 8-day 30 m actual evapotranspiration. ISPRS Journal of Photogrammetry and Remote Sensing, 126, 79–93.

    Article  Google Scholar 

  • Laxmi, K., & Nandagiri, L. (2014). Latent heat flux estimation using trapezoidal relationship between MODIS land surface temperature and fraction of vegetation–application and validation in a humid tropical region. Remote Sensing Letters, 5(11), 981–990.

    Article  Google Scholar 

  • Leuning, R., Zhang, Y. Q., Rajaud, A., Cleugh, H., & Tu, K. (2008). A simple surface conductance model to estimate regional evaporation using MODIS leaf area index and the Penman-Monteith equation. Water Resources Research, 44(W10419), 1–17.

    Google Scholar 

  • Liang, S. (2001). Narrowband to broadband conversions of land surface albedo I: algorithms. Remote Sensing of Environment, 76(2), 213–238.

    Article  Google Scholar 

  • Liu, S., Lu, L., Mao, D., & Jia, L. (2007). Evaluating parameterizations of aerodynamic resistance to heat transfer using field measurements. Hydrology and Earth System Sciences Discussions, 11(2), 769–783.

    Article  Google Scholar 

  • Mahrt, L., & Ek, M. (1984). The influence of atmospheric stability on potential evaporation. Journal of Climate and Applied Meteorology, 23(2), 222–234.

    Article  Google Scholar 

  • Morse, A., Tasumi, M., Allen, R. G., & Kramber, W. J. (2000). Application of the SEBAL methodology for Estimating Consumptive Use of Water and Streamflow Depletion in the Bear River Basin of Idaho through Remote Sensing: Final Report. Idaho Department. of Water Resources, Idaho, pp. 1–107.

  • Mu, Q., Heinsch, F. A., Zhao, M., & Running, S. W. (2007). Development of a global evapotranspiration algorithm based on MODIS and global meteorology data. Remote Sensing of Environment, 111(4), 519–536.

    Article  Google Scholar 

  • Mu, Q., Zhao, M., & Running, S. W. (2011). Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sensing of Environment, 115(8), 1781–1800.

    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 

  • Richards, J. M. (1971). A simple expression for the saturation vapour pressure of water in the range −50 to 140° C. Journal of Physics D: Applied Physics, 4(4), L15.

    Article  Google Scholar 

  • Ruhoff, A. L., Paz, A. R., Aragao, L. E. O. C., Mu, Q., Malhi, Y., Collischonn, W., Rocha, H. R., & Running, S. W. (2013). Assessment of the MODIS global evapotranspiration algorithm using eddy covariance measurements and hydrological modelling in the Rio Grande basin. Hydrological Sciences Journal, 58(8), 1658–1676.

    Article  Google Scholar 

  • Shekar, S. N. C., & Nandagiri, L. (2020). A Penman-Monteith evapotranspiration model with bulk surface conductance derived from remotely sensed spatial contextual information. International Journal of Remote Sensing, 41(4), 1486–1511.

    Article  Google Scholar 

  • Sugita, M., & Brutsaert, W. (1991). Daily evaporation over a region from lower boundary layer profiles measured with radiosondes. Water Resources Research, 27(5), 747–752.

    Article  Google Scholar 

  • Tasumi, M., Trezza, R., Allen, R. G., & Wright, J. L. (2003). US Validation tests on the SEBAL model for evapotranspiration via satellite. In 2003 ICID Workshop on Remote Sensing of ET for Large Regions, p. 17.

  • Taylor, C. M., Gounou, A., Guichard, F., Harris, P. P., Ellis, R. J., Couvreux, F., & De Kauwe, M. (2011). Frequency of Sahelian storm initiation enhanced over mesoscale soil-moisture patterns. Nature Geoscience, 4(7), 430–433.

    Article  Google Scholar 

  • Thom, A. S. (1975). Momentum, mass and heat exchange of plant communities (pp. 57–109). Academic Press.

    Google Scholar 

  • Venturini, V., Islam, S., & Rodriguez, L. (2008). Estimation of evaporative fraction and evapotranspiration from MODIS products using a complementary based model. Remote Sensing of Environment, 112(1), 132–141.

    Article  Google Scholar 

  • Verma, S. B., Rosenberg, N. J., Blad, B. L., & Baradas, M. W. (1976). Resistance-energy balance method for predicting evapotranspiration: determination of boundary layer resistance and evaluation of error effects 1. Agronomy Journal, 68(5), 776–782.

    Article  Google Scholar 

  • Viney, N. R. (1991). An empirical expression for aerodynamic resistance in the unstable boundary layer. Boundary-Layer Meteorology, 56(4), 381–393.

    Article  Google Scholar 

  • Xie, X. (1988). An improved energy balance-aerodynamic resistance model used estimation of evapotranspiration on the wheat field. Acta Meteorologica Sinica, 46, 102–106.

    Google Scholar 

  • Yang, K., Tamai, N., & Koike, T. (2001). Analytical solution of surface layer similarity equations. Journal of Applied Meteorology, 40(9), 1647–1653.

    Article  Google Scholar 

  • Yang, Y., Anderson, M. C., Gao, F., Hain, C. R., Semmens, K. A., Kustas, W. P., et al. (2017). Daily landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA, using multi-satellite data fusion. Hydrology and Earth System Sciences, 21(2), 1017–1037.

    Article  Google Scholar 

  • Yao, Y., Liang, S., Cheng, J., Liu, S., Fisher, J. B., Zhang, X., Jia, K., Zhao, X., Qin, Q., Zhao, B., & Han, S. (2013). MODIS-driven estimation of terrestrial latent heat flux in China based on a modified Priestley-Taylor algorithm. Agricultural and Forest Meteorology, 171, 187–202.

    Article  Google Scholar 

  • Yuan, W., Liu, S., Yu, G., Bonnefond, J. M., Chen, J., Davis, K., Desai, A. R., Goldstein, A. H., Gianelle, D., Rossi, F., & Suyker, A. E. (2010). Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data. Remote Sensing of Environment, 114(7), 1416–1431.

    Article  Google Scholar 

  • Zhang, X., Ren, Y., Yin, Z. Y., Lin, Z., & Zheng, D. (2009). Spatial and temporal variation patterns of reference evapotranspiration across the Qinghai-Tibetan Plateau during 1971–2004. Journal of Geophysical Research: Atmospheres, 114(D15105), 1–14.

    Google Scholar 

Download references

Acknowledgements

The authors thank the anonymous reviewers for giving tremendously valuable comments and suggestions to improve the quality of this manuscript, which are gratefully acknowledged.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to N. C. Sanjay Shekar.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shekar, N.C.S., Hemalatha, H.N. Performance Comparison of Penman–Monteith and Priestley–Taylor Models Using MOD16A2 Remote Sensing Product. Pure Appl. Geophys. 178, 3153–3167 (2021). https://doi.org/10.1007/s00024-021-02780-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00024-021-02780-5

Keywords

Navigation