Estimation of Actual Evapotranspiration for Irrigated Rice Fields through Remote Sensing Data and Comparison with Empirical and Calculationg Methods

Increasing population growth necessitates more food production, which requires more activities in the agricultural and industrial sectors, which has necessitated the presentation of effective strategies for water resources management. One of the strategies that has been considered in water resources management in recent years, especially in the agricultural sector, is the measurement or estimation of evapotranspiration that The monitoring and evaluation of changes in certain periods of time can be important in determining the amount of water consumed by the plant and planning irrigation, and thus determining the irrigation systems capacity. Also, Conventional ET measurements using lysimeters, the Bowen ratio, and eddy covariance systems (EC) are mainly based on site (field)-measurements. Although they can directly or indirectly measure turbulence fluxes (latent and sensible heat flux; LE and H), conventional techniques likely entail substantial observation errors during bad weather and other conditions. These methods, therefore, cannot represent large-scale terrestrial ET. Since direct and indirect methods of calculating this parameter have limitations; recently, remote sensing methods for calculating evapotranspiration are used. However, remote sensing data combined with some meteorological data provide a means to estimate regional ET, given the advances in remote sensing technology. Some land surface variables related to ET, such as surface albedo, surface emissivity, and land surface temperature, can be estimated directly by remote sensing data. Actual ET can be estimated by a set of equations hierarchically, which converts spectral radiances derived from satellites or airplanes images into actual ET. One of the models based on remotely sensed data is the Surface Energy Balance Algorithm for Land (SEBAL) model, in which the land surface temperature, albedo, emissivity, and normalized difference vegetation index (NDVI) are of significance to estimating regional ET. In the present study, Lenjan County in Isfahan province, which was under rice cultivation, was selected and Surface Energy Balance Algorithm for Land (SEBAL) was implemented on 8 satellite images of Landsat 8 from June to September 2017 (growing season). For this purpose, the main components of the energy balance equation, including net radiation flux, soil heat flux and sensible heat flux to the air for each image, have been calculated and the instantaneous evapotranspiration flux for each pixel is estimated as the residual energy balance equation. To improve the non-dependency on ground data, a general equation was therefore used. The Net Radiation is the electromagnetic balance of all incoming and outgoing fluxes reaching and leaving a flat surface. The amount of shortwave radiation (RS↓) that remains available at the surface is a function of the surface albedo (α). Surface albedo is a reflection coefficient defined as the ratio of the reflected radiant flux to the incident radiant flux over the solar spectrum. It was calculated using satellite image information on spectral radiance for each satellite and the incoming shortwave radiation (RS↓) was computed using the solar constant, the solar incidence angle, a relative earth-sun distance, and a computed atmospheric transmissivity. The incoming longwave radiation (RL↓) was computed using a modified Stefan-Boltzmann equation with atmospheric transmissivity and a selected surface reference temperature. Outgoing longwave radiation (RL↑) was computed using the Stefan-Boltzmann equation with a calculated surface emissivity and surface temperature. Surface temperatures were computed from satellite image information on thermal radiance. The surface emissivity is the ratio of the actual radiation emitted by a surface to that emitted by a black body at the same surface temperature. Soil heat flux was empirically calculated using vegetation indices, surface temperature, and surface albedo. Sensible heat flux wass computed using wind speed observations, estimated surface roughness, and surface to air temperature differences. Sensible heat flux is the part of internal energy of a substance that is proportional to the substance’s temperature. Also, empirical methods of evapotranspiration including Blaney- Criddle, Hargraves- Samani, FAO- Pennman- Monteith and Kimberly- Pennman were also evaluated in the study area. Accordingly, the SEBAL model in the study area has the maximum and minimum daily evapotranspiration in the pictures of June 25 and September 11, equal to 7.95 and 5.88 mm/day. Among the various parameters affecting the SEBAL algorithm, the net radiation flux parameter with consideration of other parameters such as vegetation indices, surface albedo, and incoming and outgoing of radiation, had the most effect on the results of SEBAL algorithm. Among different empirical methods, Hargraves- Samani and Blaney- Ciddle had less percent error which has a suitable correlation with SEBAL results. SEBAL algorithm has been able to estimate the temporal and spatial variation of evapotranspiration in the study area with an acceptable accuracy. Alternatively, this algorithm can be used to replace time-consuming and costly methods of calculating evapotranspiration at different surfaces.