耦合干物质分配系数模拟改进PRYM-Wheat模型提高华北平原区域尺度冬小麦产量估算精度

doi:10.1016/j.jia.2023.09.030

摘要/Abstract

摘要：

准确估算区域尺度冬小麦产量对我国粮食安全和供需平衡预警具有重要意义。目前，大多数遥感过程模型使用“生物量×收获指数（HI）”的方法估算区域尺度冬小麦产量。然而，收获指数的时空差异是造成区域尺度冬小麦产量估算误差的主要原因之一，干物质分配系数（Fr）能够动态反映冬小麦生育期内干物质分配和积累的情况。本研究将站点尺度的冬小麦各器官Fr耦合到冬小麦产量估算的遥感过程模型（PRYM-Wheat）以提高华北平原区域尺度冬小麦产量的估算精度。利用改进后的PRYM-Wheat模型（PRYM-Wheat-Fr）估算冬小麦产量并与统计产量进行精度比较。三年（2000-2002）平均产量结果表明，利用PRYM-Wheat-Fr估算冬小麦产量与统计产量比较的R²=0.55，RMSE=0.94t ha^-1；基于HI的PRYM-Wheat模型（PRYM-Wheat-HI）估算冬小麦产量与统计产量比较的R²=0.30，RMSE=1.62t ha^-1。PRYM-Wheat-Fr模型比PRYM-Wheat-HI模型估算冬小麦产量的R²提高了0.25，RMSE降低了0.68t ha^-1。同时，2013-2015年的验证结果也表明，PRYM-Wheat-Fr的冬小麦产量估算精度优于PRYM-Wheat-HI的冬小麦产量估算精度。所以，PRYM-Wheat-Fr模型能够更好地估算区域尺度冬小麦产量，是估算区域尺度冬小麦产量的有效工具。

Abstract:

The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in China. Presently, most remote sensing process models use the “biomass×harvest index (HI)” method to simulate regional-scale winter wheat yield. However, spatiotemporal differences in HI contribute to inaccuracies in yield simulation at the regional scale. Time-series dry matter partition coefficients (Fr) can dynamically reflect the dry matter partition of winter wheat. In this study, Fr equations were fitted for each organ of winter wheat using site-scale data. These equations were then coupled into a process-based and remote sensing-driven crop yield model for wheat (PRYM-Wheat) to improve the regional simulation of winter wheat yield over the North China Plain (NCP). The improved PRYM-Wheat model integrated with the fitted Fr equations (PRYM-Wheat-Fr) was validated using data obtained from provincial yearbooks. A 3-year (2000–2002) averaged validation showed that PRYM-Wheat-Fr had a higher coefficient of determination (R²=0.55) and lower root mean square error (RMSE=0.94 t ha^–1) than PRYM-Wheat with a stable HI (abbreviated as PRYM-Wheat-HI), which had R² and RMSE values of 0.30 and 1.62 t ha^–1, respectively. The PRYM-Wheat-Fr model also performed better than PRYM-Wheat-HI for simulating yield in verification years (2013–2015). In conclusion, the PRYM-Wheat-Fr model exhibited a better accuracy than the original PRYM-Wheat model, making it a useful tool for the simulation of regional winter wheat yield.

Key words: dry matter partition , remote sensing model , winter wheat yield , North China Plain

. 耦合干物质分配系数模拟改进PRYM-Wheat模型提高华北平原区域尺度冬小麦产量估算精度[J]. Journal of Integrative Agriculture, 2024, 23(4): 1381-1392.

Xuan Li, Shaowen Wang, Yifan Chen, Danwen Zhang, Shanshan Yang, Jingwen Wang, Jiahua Zhang, Yun Bai, Sha Zhang.

Improved simulation of winter wheat yield in North China Plain by using PRYM-Wheat integrated dry matter distribution coefficient [J]. Journal of Integrative Agriculture, 2024, 23(4): 1381-1392.

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