Integrating a novel irrigation approximation method with a process-based remote sensing model to estimate multi-years' winter wheat yield over the North China Plain

doi:10.1016/j.jia.2023.02.036

Journal of Integrative Agriculture

2023, Vol. 22

Issue (9): 2865-2881 DOI: 10.1016/j.jia.2023.02.036

Agro-ecosystem & Environment

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Integrating a novel irrigation approximation method with a process-based remote sensing model to estimate multi-years' winter wheat yield over the North China Plain

ZHANG Sha¹, YANG Shan-shan¹, WANG Jing-wen², WU Xi-fang³, Malak HENCHIRI¹, Tehseen JAVED^{1, 4}, ZHANG Jia-hua^2#, BAI Yun^1#

¹Research Center for Space Information and Big Earth Data, College of Computer Science and Technology, Qingdao University, Qingdao 266071, P.R.China

²Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, P.R.China

³School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, P.R.China

⁴Department of Environmental Sciences, Kohat University of Science and Technology, Kohat 26000, Pakistan

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摘要

准确估算区域尺度冬小麦产量对掌握粮食生产情况和保证国家粮食安全十分重要。但目前精确的水资源和区域灌溉信息难以获取，基于遥感模拟区域尺度冬小麦产量的年际和空间变化仍存在较大误差。为此，本研究以中国冬小麦主产区华北平原（NCP）为研究区，发展基于灌溉模式参数（IPPs，即灌溉频率和灌溉时期）近似估计冬小麦灌溉信息的新方法，并将其耦合到一个新发展的遥感过程模型（PRYM–Wheat），以更准确模拟NCP冬小麦产量。本研究使用NCP各县市参考年份（2010–2015）的统计产量确定IPPs的最优值，然后在站点和区域尺度验证耦合了最优IPPs的PRYM–Wheat模拟冬小麦的精度。结果显示，耦合了最优IPPs的PRYM–Wheat模拟参考年份冬小麦产量的相关系数R提升了0.15（37%），均方根误差RMSE减少了0.90 t/hm²（41%）；模拟验证年份（2001–2009和2016–2019）站点尺度、河北省县级尺度、河南省县级尺度和山东省市级尺度的R（RMSE）分别为0.80（0.62 t/hm²）、0.51（0.95 t/hm²）、0.72（1.18 t/hm²）和0.42（0.72 t/hm²）。总体来看，IPPs可以有效提升基于遥感模拟灌溉区区域尺度冬小麦产量的精度，耦合了IPPs的PRYM–Wheat模型可为估算区域冬小麦多年产量提供稳定可靠的方法，为确保区域粮食安全提供科学依据。

Abstract

Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security. However, using the existing remote sensing-based crop yield models to accurately reproduce the inter-annual and spatial variations in winter wheat yields remains challenging due to the limited ability to acquire irrigation information in water-limited regions. Thus, we proposed a new approach to approximating irrigations of winter wheat over the North China Plain (NCP), where irrigation occurs extensively during the winter wheat growing season. This approach used irrigation pattern parameters (IPPs) to define the irrigation frequency and timing. Then, they were incorporated into a newly-developed process-based and remote sensing-driven crop yield model for winter wheat (PRYM–Wheat), to improve the regional estimates of winter wheat over the NCP. The IPPs were determined using statistical yield data of reference years (2010–2015) over the NCP. Our findings showed that PRYM–Wheat with the optimal IPPs could improve the regional estimate of winter wheat yield, with an increase and decrease in the correlation coefficient (R) and root mean square error (RMSE) of 0.15 (about 37%) and 0.90 t ha^–1(about 41%), respectively. The data in validation years (2001–2009 and 2016–2019) were used to validate PRYM–Wheat. In addition, our findings also showed R (RMSE) of 0.80 (0.62 t ha^–1) on a site level, 0.61 (0.91 t ha^–1) for Hebei Province on a county level, 0.73 (0.97 t ha^–1) for Henan Province on a county level, and 0.55 (0.75 t ha^–1) for Shandong Province on a city level. Overall, PRYM–Wheat can offer a stable and robust approach to estimating regional winter wheat yield across multiple years, providing a scientific basis for ensuring regional food security.

Keywords: approximating irrigations process-based model remote sensing winter wheat yield North China Plain

Received: 13 July 2022 Accepted: 06 January 2023

Fund:

This work was supported by the National Natural Science Foundation of China (42101382 and 41901342), the Shandong Provincial Natural Science Foundation (ZR2020QD016), the National Key Research and Development Program of China (2016YFD0300101).

About author: ZHANG Sha, E-mail: zhangsha@qdu.edu.cn; #Correspondence ZHANG Jia-hua, E-mail: zhangjh@radi.ac.cn; BAI Yun, E-mail: baiyun@qdu.edu.cn

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	ZHANG Sha
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	Tehseen JAVED
	ZHANG Jia-hua
	BAI Yun

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ZHANG Sha, YANG Shan-shan, WANG Jing-wen, WU Xi-fang, Malak HENCHIRI, Tehseen JAVED, ZHANG Jia-hua, BAI Yun. 2023. Integrating a novel irrigation approximation method with a process-based remote sensing model to estimate multi-years' winter wheat yield over the North China Plain. Journal of Integrative Agriculture, 22(9): 2865-2881.

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