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Evaluation of transpiration in different almond production systems with two-source energy balance models from UAV thermal and multispectral imagery
Irrigation Science ( IF 3 ) Pub Date : 2023-10-31 , DOI: 10.1007/s00271-023-00888-1
Manuel Quintanilla-Albornoz , Xavier Miarnau , Ana Pelechá , Jaume Casadesús , Omar García-Tejera , Joaquim Bellvert

A growing number of intensive irrigated production systems of the almond crop have been established in recent years. However, there is little information regarding the crop water requirements. Remote sensing-based models such as the two-source energy balance (TSEB) have proven to be reliable ways to accurately estimate actual crop evapotranspiration. However, few efforts have been made to validate the transpiration with sap flow measurements in woody row crops with different production systems and water status. In this study, the TSEB Priestley-Taylor (TSEB-PT) and contextual approach (TSEB-2T) models were assessed to estimate canopy transpiration. In addition, the effect of applying a basic clumping index for heterogeneous randomly placed clumped canopies and a rectangular hedgerow clumping index on the TSEB transpiration estimation was assessed. The TSEB inputs were obtained from high resolution multispectral and thermal imagery using an unmanned aerial vehicle. The leaf area index (LAI), stem water potential (Ψstem) and fractional intercepted photosynthetically active radiation (fIPAR) were also measured. Significant differences were observed in transpiration between production systems and irrigation treatments. The combined use of the TSEB-2T with the C&N-R transmittance model gave the best transpiration estimations for all production systems and irrigation treatments. The use of in situ PAR transmittance in the TSEB-2T model significantly improved the root mean squared error. Thus, the better agreement observed with the TSEB when using the C&N-R model and in situ PAR transmittance highlights the importance of improving radiative transfer models for shortwave canopy transmittance, especially in woody row crops.



中文翻译:

利用无人机热图像和多光谱图像的双源能量平衡模型评估不同杏仁生产系统的蒸腾作用

近年来,越来越多的杏仁作物集约化灌溉生产系统得到建立。然而,关于作物需水量的信息很少。基于遥感的模型,例如双源能量平衡(TSEB),已被证明是准确估计实际作物蒸散量的可靠方法。然而,很少有人努力通过不同生产系统和水分状况的木本行间作物的液流测量来验证蒸腾作用。在本研究中,评估了 TSEB Priestley-Taylor (TSEB-PT) 和情境方法 (TSEB-2T) 模型来估计冠层蒸腾量。此外,还评估了应用异质随机放置的丛集冠层的基本丛集指数和矩形树篱丛集指数对 TSEB 蒸腾估计的影响。TSEB 输入是使用无人机从高分辨率多光谱和热图像中获得的。还测量了叶面积指数(LAI)、茎水势(Ψ)和截获光合有效辐射分数(fIPAR)。生产系统和灌溉处理之间的蒸腾作用存在显着差异。TSEB-2T 与 C&N-R 透射率模型的结合使用为所有生产系统和灌溉处理提供了最佳蒸腾估计。在 TSEB-2T 模型中使用原位 PAR 透射率显着改善了均方根误差。因此,使用 C&N-R 模型和原位 PAR 透射率时观察到的与 TSEB 的更好一致性凸显了改进短波冠层透射率的辐射传输模型的重要性,特别是在木本行间作物中。

更新日期:2023-10-31
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