Obtaining the daily actual evapotranspiration through remote sensing techniques application in Brazilian Semiarid

C. K. Borges, R. G. Carneiro, Cleber Assis dos Santos, C. A. D. Dos Santos
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Abstract

Large volumes of water are released to the atmosphere through evaporation from soil and transpiration from vegetation, constituting evapotranspiration (ET). Estimating the water consumption in vegetated areas is important for the management and rational use of this resource. For this study were processed orbital images which correspond to Quixeré-CE, with interest at the Frutacor Farm, where there is predominance the banana crop. The main objective of this study was to assess the accuracy and applicability of S-SEBI and SSEB algorithms with regard to SEBAL to estimate the actual daily evapotranspiration ETa) of a semi-arid region of Northeast Brazil, containing areas of banana orchard, native vegetation (caatinga) and bare soil. S-SEBI. The SSEB and SSEB algorithms showed strong correlation (r > 0.93) with statistical significance of 5%. The S-SEBI exhibited errors less than 12% in the orchard and caatinga and SSEB exhibited greater errors at 22%, though for the bare soil, both models showed large discrepancies when compared with SEBAL, with errors greater than 36%. Therefore, among the two algorithms compared with SEBAL, S-SEBI had a better performance in ETa estimation with lower deviations.
利用遥感技术获取巴西半干旱区的日实际蒸散量
大量的水通过土壤的蒸发和植被的蒸腾作用释放到大气中,构成蒸散发(ET)。植被区用水量的估算对植被资源的管理和合理利用具有重要意义。为了这项研究,我们处理了与quixer - ce相对应的轨道图像,并对香蕉作物占主导地位的弗鲁塔科农场感兴趣。本研究的主要目的是评估S-SEBI和SSEB算法在SEBAL方面的准确性和适用性,以估计巴西东北部半干旱区的实际日蒸散量(ETa),该地区包括香蕉园、原生植被(caatinga)和裸露土壤。S-SEBI。SSEB与SSEB算法呈强相关性(r > 0.93),差异有统计学意义(5%)。S-SEBI模型在果园中的误差小于12%,caatinga和SSEB模型的误差较大,为22%,但对于裸地,两种模型与SEBAL模型相比差异较大,误差均大于36%。因此,在两种算法中,与SEBAL相比,S-SEBI在ETa估计方面的性能更好,偏差更小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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