A new approach to estimate daily evapotranspiration, based on Landsat data and FAO56 principles

作物系数 蒸散量 环境科学 天蓬 卫星 遥感 作物 水文学(农业) 地理 林业 地质学 生态学 岩土工程 考古 航空航天工程 工程类 生物
作者
Shadman Veysi,Aryan Heidari Motlagh,Ali Nasrolahi,Abdur Rahim Safi
出处
期刊:International Journal of Remote Sensing [Informa]
卷期号:44 (15): 4727-4752 被引量:2
标识
DOI:10.1080/01431161.2023.2237662
摘要

ABSTRACTThe accurate estimation of evapotranspiration is crucial for enhancing crop water productivity and effectively managing water resources. This research offers a novel method that integrates satellite data and crop coefficients to calculate ETc and ETa on a daily basis and overcome the limitation of low temporal frequency of non-commercial satellite data. The study was carried out in the southern part of Khuzestan Province, Iran, on sugarcane crops in the Amirkabir Agro-industries area. The method involves obtaining Landsat-8 data with an 8-day temporal resolution, which was used to estimate Land Surface Temperature (LST) using a Single-Channel Algorithm. The estimated LST was then validated with in-situ canopy temperature measurements and used to predict the crop stress coefficient (Ks) based on its relationship with the crop water stress index (CWSI). The crop coefficient (Kc) was obtained using the Surface Energy Balance Algorithm for Land (SEBAL) algorithm, and both Ks and Kc were utilized to calculate daily ETa by multiplying by the daily reference evapotranspiration (ET0) obtained from local meteorological data. The results indicated that the crop coefficients of sugarcane in the initial and mid-stages were 12% and 18% higher, respectively, compared to the FAO56 guideline. The aggregated decadal and monthly ETa showed good agreement with the WaPOR datasets, with an RMSE of 8.7 and 1.93 mm, respectively. This approach offers a potential solution to the challenge of obtaining remote sensing data with a higher temporal frequency.KEYWORDS: Daily EvapotranspirationCWSIstress coefficientWaPORsugarcane AcknowledgementsThe authors gratefully acknowledge the Amir Kabir agro-industry unit employees who cooperated and interacted constructively with us in situ data collection. Also, the authors thank FAO for launching the WaPOR database, to which the results are compared for validation.Disclosure statementThe authors have no pecuniary or other personal interest, direct or indirect, in any matter that raises or may raise a conflict with our duties to influence the result of research as authors of the article.
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