北京市农林科学院机构知识库

Estimation of water productivity in winter wheat using the AquaCrop model with field hyperspectral data

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文献类型：外文期刊

作者： Jin, Xiuliang ¹ ; Yang, Guijun ² ; Li, Zhenhai ² ; Xu, Xingang ² ; Wang, Jihua ⁴ ; Lan, Yubin ⁵ ;

作者机构： 1.Chinese Acad Sci, Northeast Inst Geog & Agroecol, Key Lab Wetland Ecol & Environm, Changchun 130102, Jilin, Peoples R China

2.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

3.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

4.Beijing Res Ctr Agri Food Testing & Farmland Moni, Beijing 100097, Peoples R China

5.South China Agr Univ, Coll Engn, Guangzhou 510642, Guangdong, Peoples R China

关键词： Water productivity;AquaCrop model;Spectral index;Lookup table;Winter wheat

期刊名称：PRECISION AGRICULTURE （影响因子：5.385；五年影响因子：5.004 ）

ISSN： 1385-2256

年卷期： 2018 年 19 卷 1 期

页码：

收录情况： SCI

摘要： Water productivity (WP) is a key element of agricultural water management in agricultural irrigated regions. The objectives of this study were: (i) to estimate biomass of winter wheat using spectral indices; (ii) integrate the estimation of biomass data with the AquaCrop model using a lookup table for higher accuracy biomass simulation; (iii) show estimation accuracy of the data assimilation method in yield and WP. Spectral variables and concurrent biomass, yield and WP of samples were acquired at the Xiaotangshan experimental site in Beijing, China, during the 2008/2009, 2009/2010, 2010/2011 and 2011/2012 winter wheat growing seasons. The results showed that all spectral indices had a highly significant relationship with biomass, especially normalized difference matter index, with R-2 and RMSE values of 0.84 and 1.43 t/ha, respectively. Simulation of biomass and yield by the AquaCrop model were in good agreement with the measured biomass and yield of winter wheat. The results showed that the data assimilation method (R-2 = 0.79 and RMSE = 0.12 kg/m(3)) could be used to estimate WP. The result indicated that the AquaCrop model could be used to estimate yield and WP with the aid of remote sensing for improving agricultural water resources management.

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