Application of Remote Sensing for Estimating the Evapotranspiration to Assess Grape Water Requirement in Marvast Plain using MODIS Terra Satellite Products

Abstract: Today, due to water use and facing the world with problems such as water deficit and drought, short-term and long-term consumption management and planning is essential to achieve the goals set for water resources. The lack of data lysimeter measurements to estimate water requirements of plants is one of the biggest challenges that exist in the agricultural sector. On the other hand, using new methods to more accurately estimate the actual evapotranspiration and consequently, vegetation coefficient for different plants, especially the dominant cultivation in the plains of the country, can help better planning and management of water resources. In this study, using MODIS images and SEBAL algorithm, evapotranspiration for Marvast in Yazd province in four months (February, May, August ,November) 2017 was estimated. Maximum evapotranspiration the same time with the heating season is August and the plant occurred chlorophyll maximum amount of which is 582 mm. Then, with decreasing plant density, the evapotranspiration trend was reduced, which was the minimum evapotranspiration in February. Extraction of grapevine coefficient by FAO method showed that its amount was satisfied in May (1.23) and August (1.14).
Due to the high rate of evapotranspiration and heat in these two months, the plant's need for water has been greater. Vegetation rates in the fall (November 0.25) and winter (February 29/09) were lower than during the growing season due to reduced leaf cover and reduced evaporation and transpiration. Then the values of evapotranspiration and water requirement of grapes were calculated with 5 other methods and were compared with the FAO method using statistical indicators of absolute error (MAE). The results showed that the experimental model of Hargreaves-Samani and Blaney-Criddle had a better performance in estimating the evapotranspiration of reference crop. In addition, results indicates the Hargreaves-Samani is the superior method and other methods are ranked in the next orders. Trajkovic and Bereti’s method did not show proper results, especially in the warm months.
Keywords: Marvast Plain, SEBAL Model, FAO Penman-Monteith, Grape water requirement
Introduction
Evapotranspiration is one of the most important factors in the hydrology cycle and one of the determinants of energy equations at ground level and water balance and its estimation is required in various fields of science such as hydrology, agriculture, forest and pasture management and water resources management (Omidvar et al., 2013). Climatic or meteorological methods based on point data may not have good estimates of large-scale evapotranspiration(Sun et al., 2011). But remote sensing techniques allow it to cover a large area of the study area simultaneously, monitor and study evapotranspiration. With the help of this technique, the spatial distribution of the factors required for the evapotranspiration models and their temporal variations between two consecutive imaging is provided. Among the methods available for estimating evapotranspiration through remote sensing, energy balance methods are the most prominent. Existing algorithms include SEBAL, SSEB, and TSEB dual-source algorithms (Bastiaanssen,2000 ،et al., 2007 Senay). One of the algorithms that is highly regarded for estimating real transpiration evaporation using satellite images is the Sabal algorithm (Bahman abadi et al., 2018). The Sebal algorithm is a method based on empirical and physical relationships to estimate real evapotranspiration with minimum terrestrial data, and its algorithm was first proposed by et al Bastiaanssen in 1998.
Methodology
Two databases were needed to investigate evapotranspiration in the Marvast area. First Terra Modis satellite imagery database for four months (February, May, November, August) downloaded from the EOS Data Portal website. There are numerous Modis products that used raw data (MOD021KM) in this study. The preprocessing steps of atmospheric, geometric and radiometric corrections have been performed with appropriate algorithms to provide a high quality homogeneous dataset. Then, the actual evapotranspiration was calculated using images corrected by the Sebal algorithm. The second data base from the Marvast Meteorological Station was used to calculate the potential evapotranspiration using two experimental methods FAO Penman Monteith and Hargreaves Samani.
Conclusion
Due to limited groundwater resources in Marvast, Yazd province, And given that summer grape bushes that have high evapotranspiration, If affected by water scarcity, it can cause problems such as yield loss by extracting the grape coefficient which is the dominant crop of Marvast. By dividing the estimated actual evapotranspiration value by the Sebal model into the reference evapotranspiration estimated by the two models FAO Penman Monteith and Hargreaves-Samani, It was calculated every four months. Which amounted to May (1.23 and 1.39) and August (1.14 and 1.85), Due to the high evapotranspiration and heat in the two months the plant needs more water. Crop coefficients were lower in the fall (November 0.25 and 0.53) and winter (February 0.29 and 0.43) due to reduced leaf area cover and reduced evapotranspiration, respectively. Due to the limitation of water resources in arid and semiarid areas such as Marvast and the lack of atmospheric depletion, knowing the water requirement of plants will increase water productivity and improve crop quality.