The estimation of actual evapotranspiration of irrigated agricultural and Gardens in Nahavand plain using algorithm SEBAL

Introduction

Evapotranspiration that includes evaporation from the soil surface and transpiration from vegetation, is one of the most important factors of water loss. Also, it is one of the most effective components of the water balance in a catchment in arid and semi-arid regions of the world. Therefore, it is an important physical parameter for water resource management and determining the plant water requirement in the agricultural sector. so far, many experimental methods have been proposed to calculate evapotranspiration, but, they are only suitable at the local scale and cannot be generalized to large areas due to regional dynamics and changes. whereas the accurate estimation of it is also very difficult and expensive, Therefore, in the present study, calculated the amount of evapotranspiration in the irrigated agricultural sector by using of landsat 8 satellite images and Surface Energy Balance Algorithm (SEBAL) in Nahavand Plain. in SEBAL algorithm by estimating all energy components on the earth's surface, including net radiation flux, soil heat flux, and sensible heat flux and using the energy balance equation, evapotranspiration is calculated. Remote sensing also has the ability to show evapotranspiration spatial distribution in addition to estimating the amount of its, because, it is the only technology that extracts factors such as surface temperature, albedo coefficient and plant index in a way compatible with the environment and is also economically affordable.

Materials and Methods

in this research, in order to estimate daily actual evapotranspiration of the irrigated agricultural and gardens of Nahavand Plain, extracted irrigated agricultural land use map by using of Sentinel 2 satellite images, Then, by using of Landsat 8 satellite images (13 images, from 13 April to 22 October during the growth period of the irrigated crops) and Surface Energy Balance Algorithm (SEBAL), evapotranspiration maps were obtained during the irrigated crops growth period in 2021. These Landsat 8satellite images are obtained by the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) onboard the satellites and are widely used for water resource applications. The OLI sensor has 9 bands and the TIRS has two bands (10th and 11th are the thermal bands). Landsat images are at intervals of 16-days with a spatial resolution of 30 m. In all images, the imaging time was 7:21. Then, due to FAO- Penman monteith method is one of the most important and reliable reference methods in evapotranspiration calculations, in this research, this method was used as a basis for evaluation and comparison. Finally, in order to evaluate the efficiency of SEBAL method in estimating the actual evapotranspiration of irrigated crops and gardens in Nahavand Plain used RMSE function (Root Mean Squares of Errors).

Results and Discussion

According to the results of the SEBAL algorithm, the highest mean of actual evapotranspiration was related to images 2021.09.04 and 2021.08.19 which fall in the middle of the growing period of irrigated crops. In addition, the surface albedo is noted to be relatively low for these days with the high NDVI values indicating high absorption of radiation by the vegetation during this period. Net solar radiation is directly contingent upon the incoming longwave and shortwave radiations, both of which directly influence the surface temperature. Therefore, areas with higher surface temperatures have higher net solar radiation. The net radiation flux has a direct relationship with NDVI, Greenness, and wetness parameters and is inversely related to albedo, Brightness, and Ts. The vegetative moisture and sensible heat flux are higher on days with high NDVI. Higher NDVI values are an indication of an increase in vegetation greenness, therefore essentially an increase in evapotranspiration is expected to be observed. The lowest mean of actual evapotranspiration is related to the northeast of the case study; due to lack of sufficient surface and ground water resources and consequently the reduction of agricultural lands in this region. Finally, in order to investigate the accuracy of SEBAL method in calculating evapotranspiration, compared the results of SEBAL method with the results of FAO- Penman monteith method. The results of this comparison showed that the SEBAL method with RMSE 0.82 has appropriate efficiency for estimating evapotranspiration.

Conclusion

Due to an increase in population and shortage of water resources, especially in the agricultural sector, researchers are looking for ways to better manage the available water resources. Evapotranspiration rate is one of the most important components of the global hydrologic cycle and has a significant influence on energy balance and climate. the using of indirect methods such as remote sensing can be an important step for estimating the water need of agricultural products, planning and management the country, s water resources. Therefore, according to the position of Nahavand city as the agricultural hub of Hamedan province, in this study, the actual evapotranspiration of the irrigated agricultural land use using of landsat 8 satellite images and SEBAL Algorithm was investigated in this area. According to the results of the SEBAL algorithm, the highest mean of actual evapotranspiration in all of the investigated images is related to the southeast and center of the studied area. that the reason of this matter is location of this area in the main branch of the Gamasiab River and focused the irrigated agricultural and gardens in this area. The final results of this research indicated high precision of SEBAL algorithm in estimating evapotranspiration. Thus, the high accuracy and low error indicate that the SEBAL method could be aptly used to estimate evapotranspiration on a regional scale, in the respective time range. Also, the results obtained from the SEBAL method assisted in understanding the spatial and temporal changes in different stages of plant growth.