Investigation of the contribution of remote-sensing to the estimation of evapotranspiration - A Greek case study

A. Tsouni, Investigation of the contribution of remote-sensing to the estimation of evapotranspiration - A Greek case study, Postgraduate Thesis, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, 2003.



The estimation of actual evapotranspiration is valuable since evapotranspiration consists one of the main components of hydrologic cycle. In the past decades the estimation of evapotranspiration combining conventional meteorological ground measurements with remotely-sensed data has been widely studied and several methods have been developed for this purpose. In the present study, the contribution of remote-sensing to the estimation of evapotranspiration was examined for Greece. More specifically, the daily actual evapotranspiration was calculated for 21 days uniformly distributed during the 2001 summer season (June, July, August) over Thessaly plain, in the Pinios river basin, a region of intensive agricultural activity. For this case-study three different methods were accordingly adapted and were applied: remote-sensing methods Granger (Granger, 2000) and Carlson- Buffum (Carlson and Buffum, 1989) using satellite data in conjunction with ground meteorological measurements and the adapted to satellite data FAO Penman-Monteith method, which constituted the reference method. The satellite data, following the necessary processing (radiometric calibration, geometrical correction and georeference, image to image geometrical correction with afine transformation, correction of sun illumination conditions and area of interest masking), were used in conjunction with surface data from the tree closest meteorological EMY stations (Larisa, Trikala and Agchialos). All three methods, following their appropriate adaptation, exploit visible channels 1 and 2 of NOAA-AVHRR satellite images to calculate albedo and NDVI and infrared channels 4 and 5 to calculate surface temperature. FAO Penman-Monteith and Granger methods require mean surface temperatures, so NOAA-15 satellite images were used, while for Carlson-Buffum method a combination of NOAA-14 and NOAA-15 satellite images was used, since the average rate of surface temperature rise during the morning is required. The results of the application are encouraging. Both Carlson-Buffum and Granger methods follow in general the variations of the FAO Penman-Monteith method. However, they underestimate evapotranspiration during the days with relatively high wind speed. The much simpler Carlson-Buffum method has more variations compared to Granger method, which are not always caused by the wind. Carlson- Buffum method estimates better the daily actual evapotranspiration in the first half of the crop development stage (with an underestimation error reducing from 1.7 to 0 mm), while Granger method gives better estimations for the entire rest period (with an underestimation error varying between 1 and 2 mm from the middle of the crop development stage to the beginning of its last fifth, and between 0 and 0.5 mm at the end of the development stage and the entire stable stage).

PDF Full text:

Other works that reference this work (this list might be obsolete):

1. Papadavid, G. C., A. Agapiou, S. Michaelides and D. G.Hadjimitsis, The integration of remote sensing and meteorological data for monitoring irrigation demand in Cyprus, Nat. Hazards Earth Syst. Sci., 9, 2009-2014, 2009.
2. Hadjimitsis, D. G., and G. Papadavid, Integrated approach of remote sensing and micro-sensor technology for estimating evapotranspiration in Cyprus, Agric Eng Int: CIGR Journal 12 (3-4), 1-11, 2010.
3. Papadavid, G., D. Hadjimitsis, S. Michaelides and A. Nisantzi, Crop evapotranspiration estimation using remote sensing and the existing network of meteorological stations in Cyprus, Adv. Geosci., 30, 39-44, doi: 10.5194/adgeo-30-39-2011, 2011.
4. #Hadjimitsis, D. G. and G. Papadavid, Remote Sensing for Determining Evapotranspiration and Irrigation Demand for Annual Crops, Remote Sensing of Environment - Integrated Approaches, 10.5772/39305, 2013.