Year 2021,
Volume: 8 Issue: 2, 193 - 199, 15.06.2021
Sachin Sutariya
,
Hirapara Ankur
,
Mukesh Tiwari
References
- Allen, R. G., Pereira, L. S., Raes, D., Smith, M., & Ab, W. (1998). Fao,1998. Irrigation and Drainage Paper No. 56, FAO, 300. https://doi.org/10.1016/j.eja.2010.12.001
- Arunadevi K, Ramachandran J, Vignesh S, Visuvanathakumar S, & Anupriyanka S. (2017). Comparison of Reference Evapotranspiration in Semi-Arid Region. International Journal of Agriculture Sciences Citation, 9(52), 4886–4888.
- Hargreaves, B. G. H. (1994). REFERENCE EVAPOTRANSPIRATION By George H. Hargreaves, 1 Fellow, ASCE. Journal of Irrigation and Drainage Engineering, 120(6), 1132–1139.
- Kumar, R., Jat, M. K., & Shankar, V. (2012). Methods to estimate irrigated reference crop evapotranspiration - A review. Water Science and Technology, 66(3), 525–535. https://doi.org/10.2166/wst.2012.191
- Mehta, R., Pandey, V., Lunagaria, M. M., & Kumar, A. (2016). Reference and crop evapotranspiration estimation for mustard reference and crop evapotranspiration estimation for mustard and chickpea at different locations of. (January).
- Pandey, P. K., Dabral, P. P., & Pandey, V. (2016). Evaluation of reference evapotranspiration methods for the northeastern region of India. International Soil and Water Conservation Research, 4(1), 52–63. https://doi.org/10.1016/j.iswcr.2016.02.003
- Running, S. W., Mu, Q., Zhao, M., & Moreno, A. (2019). User’s Guide MODIS Global Terrestrial Evapotranspiration (ET) Product (MOD16A2/A3 and Year-end Gap-filled MOD16A2GF/A3GF) NASA Earth Observing System MODIS Land Algorithm (For Collection 6). Retrieved from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/modis/MOD16UsersGuideV2.02019.pdf
- Semmens, K. A., Anderson, M. C., Kustas, W. P., Gao, F., Al, J. G., Mckee, L., … Vélez, M. (2016). Remote Sensing of Environment Monitoring daily evapotranspiration over two California vineyards using Landsat 8 in a multi-sensor data fusion approach. 185, 155–170. https://doi.org/10.1016/j.rse.2015.10.025
- Sharma, D. N., & Tare, V. (2018). Evapotranspiratio estimation using ssebop method with sentinel-2 and landsat-8 data set. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII–5(November), 563–566. https://doi.org/10.5194/isprs-archives-xlii-5-563-2018
- Xiong, Y. J., Zhao, S. H., Tian, F., & Qiu, G. Y. (2015). An evapotranspiration product for arid regions based on the three-temperature model and thermal remote sensing. Journal of Hydrology, 530, 392–404. https://doi.org/10.1016/j.jhydrol.2015.09.050
Estimation of Actual Evapotranspiration in Panam Canal Command Using Remote Sensing and Geographical Information System (GIS)
Year 2021,
Volume: 8 Issue: 2, 193 - 199, 15.06.2021
Sachin Sutariya
,
Hirapara Ankur
,
Mukesh Tiwari
Abstract
Estimation of reference evapotranspiration (ET0) and actual evapotranspiration (ETc) is a key factor for estimation of crop water requirement, water balance and irrigation scheduling. The FAO-56 Penman–Monteith equation has been accepted universally for estimating of reference evapotranspiration (ET0). Considering the high spatial variation of meteorological phenomenon and limited availability of such dense network for data collection, application of remote sensing and GIS has gained momentum for estimation of ET0 and ETc over the larger area with accurately and efficiently. For estimation of ET0 and ETc, the most widely applied MOD16 remote sensing images as well as Landsat 8 remote sensing images are applied in this study of Panam canal command area which is located in the semi-arid middle Gujarat region. Initially, FAO-56 PM method is used to estimate ET0 and MOD16 data is used to estimate ET0, whereas Landsat 8 is used to estimate land surface temperature and then by using the regression equation to estimate maximum and minimum temperature to find out ET0 for the study area. Based on result obtained, it was found that Landsat 8 remote sensing-based data have better capacity to estimate actual evapotranspiration compared to the MOD16 remote sensing data. The better performance of Landsat 8 data compared to MOD16 data is due to the reason that it has better spatial resolution(30m) compared to MOD16 (1 km) remote sensing image and can represent the actual field conditions of farm fields which are generally smaller.
References
- Allen, R. G., Pereira, L. S., Raes, D., Smith, M., & Ab, W. (1998). Fao,1998. Irrigation and Drainage Paper No. 56, FAO, 300. https://doi.org/10.1016/j.eja.2010.12.001
- Arunadevi K, Ramachandran J, Vignesh S, Visuvanathakumar S, & Anupriyanka S. (2017). Comparison of Reference Evapotranspiration in Semi-Arid Region. International Journal of Agriculture Sciences Citation, 9(52), 4886–4888.
- Hargreaves, B. G. H. (1994). REFERENCE EVAPOTRANSPIRATION By George H. Hargreaves, 1 Fellow, ASCE. Journal of Irrigation and Drainage Engineering, 120(6), 1132–1139.
- Kumar, R., Jat, M. K., & Shankar, V. (2012). Methods to estimate irrigated reference crop evapotranspiration - A review. Water Science and Technology, 66(3), 525–535. https://doi.org/10.2166/wst.2012.191
- Mehta, R., Pandey, V., Lunagaria, M. M., & Kumar, A. (2016). Reference and crop evapotranspiration estimation for mustard reference and crop evapotranspiration estimation for mustard and chickpea at different locations of. (January).
- Pandey, P. K., Dabral, P. P., & Pandey, V. (2016). Evaluation of reference evapotranspiration methods for the northeastern region of India. International Soil and Water Conservation Research, 4(1), 52–63. https://doi.org/10.1016/j.iswcr.2016.02.003
- Running, S. W., Mu, Q., Zhao, M., & Moreno, A. (2019). User’s Guide MODIS Global Terrestrial Evapotranspiration (ET) Product (MOD16A2/A3 and Year-end Gap-filled MOD16A2GF/A3GF) NASA Earth Observing System MODIS Land Algorithm (For Collection 6). Retrieved from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/modis/MOD16UsersGuideV2.02019.pdf
- Semmens, K. A., Anderson, M. C., Kustas, W. P., Gao, F., Al, J. G., Mckee, L., … Vélez, M. (2016). Remote Sensing of Environment Monitoring daily evapotranspiration over two California vineyards using Landsat 8 in a multi-sensor data fusion approach. 185, 155–170. https://doi.org/10.1016/j.rse.2015.10.025
- Sharma, D. N., & Tare, V. (2018). Evapotranspiratio estimation using ssebop method with sentinel-2 and landsat-8 data set. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII–5(November), 563–566. https://doi.org/10.5194/isprs-archives-xlii-5-563-2018
- Xiong, Y. J., Zhao, S. H., Tian, F., & Qiu, G. Y. (2015). An evapotranspiration product for arid regions based on the three-temperature model and thermal remote sensing. Journal of Hydrology, 530, 392–404. https://doi.org/10.1016/j.jhydrol.2015.09.050