Analysis and estimation of tallgrass prairie evapotranspiration in the central United States

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• 作者：Pradeep Wagle^a ; ¹ ; ^{pradeep.wagle@ou.edu} ; ^{pradeep.wagle@okstate.edu} ; Xiangming Xiao^a ; ^b ; Prasanna Gowda^c ; Jeffrey Basara^d ; Nathaniel Brunsell^e ; Jean Steiner^c ; Anup K.C^f
• 关键词：Artificial neural network ; Eddy covariance ; ET modeling ; Empirical model ; Remote sensing ; Wavelet cross-correlation analysis
• 刊名：Agricultural and Forest Meteorology
• 出版年：2017
• 出版时间：15 January 2017
• 年：2017
• 卷：232
• 期：Complete
• 页码：35-47
• 全文大小：1555 K
• 卷排序：232

文摘

Cross-site variability in evapotranspiration (ET) was similar at all timescales. Climatic drivers of ET change over multiple timescales. ET was modeled using enhanced vegetation index & photosynthetically active radiation. The modeled ET was significantly improved compared to the standard MODIS ET product.