System-level optimization of cultivar, sowing, and water–nitrogen management enhances cotton yield and resource efficiency under future warming in Xinjiang, China

doi:10.1016/j.jia.2026.03.040

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Hongqin Wang^1,², Lei Li^1,², Jiaxue Li^1,², Yong He^1,²^#

¹School of Advanced Agriculture Sciences, University of Science and Technology Beijing, Beijing 100081, China

²Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China

Highlights

System-level optimization of cultivar, sowing date, and water–nitrogen management for irrigated cotton in arid Xinjiang, China.

Locally calibrated APSIM-Cotton with NSGA-III identifies robust climate-smart management strategies.

Climate-smart management strategies are evaluated across Xinjiang, revealing regional potentials and informing adaptation of irrigated cotton to future warming.

Abstract
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摘要

新疆干旱灌溉棉区的棉花生产正面临气候变化引起的水热条件改变的日益严峻的挑战，需要对品种选择、播种时间以及水氮管理进行调整。然而，多数研究集中于单一因素，对品种–播种–水氮管理的综合评估有限。为了评估未来气候条件下灌溉与氮肥管理的综合效应，本研究利用经过本地校准的APSIM-Cotton模型，驱动两个CMIP6情景（SSP2-4.5, SSP5-8.5），在阿拉尔和石河子两个代表性灌溉站点进行模拟。实验设计包括五种熟期类型、八个播种日期（3月31日至5月5日）、五个灌溉阈值（田间持水量的55–75%）以及五个随水施肥水平（每次灌溉10–18 kg N ha⁻¹）。通过多目标NSGA-III优化算法，识别了产量、水分利用效率（WUE）和氮肥利用效率（NUE）的最佳组合，并将优化策略推广至新疆全区。最优策略一致倾向于晚熟品种搭配四月初播种、高灌溉阈值（0.65–0.75 FC）以及相对较高的单次随水施肥量（14–18 kg N ha⁻¹），这种模式在不同时期和两种情景下均表现稳健。与以往田间研究中报道的常规水氮管理相比，在基准气候下，这些最优组合可使产量提高32%以上，水分利用效率提高21%以上，氮肥利用效率提高38%以上。相对于基准气候期（1981–2010），在未来情景下，这些策略使产量提升超过10%，水分利用效率提升超过14%，氮肥利用效率提升超过21%。进一步的区域模拟揭示，南疆在提升水分利用效率方面潜力更大，而北疆在提高氮肥利用效率方面更具优势。这些发现突显了播种时间与水氮管理之间的协同效应，是在未来气候条件下稳定产量和提高资源利用效率的关键途径，为新疆发展高产高效棉花系统提供了科学依据，也为全球类似干旱地区的气候适应性管理提供了参考。

Abstract

Cotton production in Xinjiang’s irrigated arid regions faces growing challenges from climate-induced alterations in hydrothermal conditions, necessitating adjustments in cultivar selection, sowing time, and water–nitrogen management. However, most studies have focused on individual factors, with limited evaluation of integrated cultivar–sowing–water–nitrogen management. To assess the combined effects of irrigation and nitrogen management under future climates, a locally calibrated APSIM-Cotton model was driven by two CMIP6 scenarios (SSP2-4.5, SSP5-8.5) at two representative irrigated sites, Aral and Shihezi. The design included five maturity types, eight sowing dates (31 March–5 May), five irrigation thresholds (55–75% of field capacity, FC), and five fertigation levels (10–18 kg N ha^-1 per irrigation). Multi-objective NSGA-III optimization identified optimal combinations for yield, water use efficiency (WUE), and nitrogen use efficiency (NUE), which were then extended to the regional scale across Xinjiang. Optimal strategies consistently converged on late-maturity cultivars with early-April sowing, high irrigation thresholds (0.65–0.75 FC), and relatively high per-event fertigation (14–18 kg N ha^-1), a pattern robust across periods and both scenarios. Under the baseline climate, these optimal combinations increased yield by >32%, WUE by >21%, and NUE by >38% relative to conventional water–nitrogen management reported in previous field studies. Relative to the baseline (1981–2010) climate period, these strategies increased yield by >10%, WUE by >14%, and NUE by >21% under future scenarios. Regional simulations further revealed that southern Xinjiang holds greater potential for improving WUE, while northern Xinjiang is more advantageous in enhancing NUE. These findings highlight the synergistic effects between sowing time and water–nitrogen management, representing a key pathway to stabilizing yields and improving resource-use efficiency under future climate conditions, informing development of high-yield and efficient cotton systems in Xinjiang and offering insights for climate-adaptive management in similar arid regions worldwide.

Keywords: climate change cotton production water use efficiency nitrogen use efficiency APSIM-cotton multi-objective optimization

Online: 18 March 2026

Fund:

This research was supported by the Science and Technology Major Program of BINGTUAN (2023AA008) and the Key Laboratory of Agricultural Environment of Northwest Oasis, Ministry of Agriculture and Rural Affairs, China (XBLZ-20243).

About author: #Correspondence Yong He, E-mail: heyong01@ustb.edu.cn

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Hongqin Wang, Lei Li, Jiaxue Li, Yong He. 2026. System-level optimization of cultivar, sowing, and water–nitrogen management enhances cotton yield and resource efficiency under future warming in Xinjiang, China. Journal of Integrative Agriculture, Doi:10.1016/j.jia.2026.03.040

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