Jute mallow (Corchorus olitorius L.) is an annual crop grown for human consumption of its nutritious leaves in many regions of the world. Despite its importance for household food security and farmers’ income, reliable information on the crop’s water requirements is still quite scarce. To overcome this knowledge gap, the irrigation needs of jute mallow grown in the Akkar region in Syria were investigated. The analysis focused on a three-year period (2017–2019) where the SIMDualKc model was calibrated and validated for simulating soil water contents and computing the soil water balance in jute mallow plots irrigated with basin and drip methods. The model was further used to determine the probabilities of the demand for irrigation water in scenarios considering different crop season lengths, irrigation methods, and application depths over a longer period of 23 years (1998–2020). The SIMDualKc model was able to simulate soil water contents measured in the field plots, returning root mean square error values lower than 0.001 m³ m^-3 and modeling efficiencies ranging from 0.358 to 0.812. The calibrated basal (non-stressed) crop coefficients (K_cb) were 0.15, 0.95, and 0.95 for the initial (K_{cb ini}), mid-season (K_{cb mid}), and end-season (K_{cb end}) stages, respectively. The crop was harvested twice per season, with the drip treatments presenting the highest water productivity and economic indicators. In contrast, the basin treatment resulted in substantial percolation losses, which affected yields and indicators. Although net irrigation requirements showed a large variation for the extremes of the long-term weather time series, differences between the years representing average water demand and those representing very high water demand were only found for the drip irrigation scenarios. This study contributes to improving irrigation water management of jute mallow in the Syrian Akkar region, and for the sustainability of local production systems.

黄麻锦葵 ( Corchorus olitoriusL.) 是一种一年生作物，在世界许多地区供人类食用其营养丰富的叶子。尽管它对家庭粮食安全和农民收入很重要，但关于作物需水量的可靠信息仍然非常缺乏。为了克服这一知识差距，对叙利亚阿卡地区种植的黄麻锦葵的灌溉需求进行了调查。分析集中在三年期间（2017-2019 年），其中 SIMDualKc 模型经过校准和验证，用于模拟土壤含水量并计算采用盆栽和滴灌法灌溉的黄麻锦葵地块的土壤水平衡。该模型进一步用于确定在考虑不同作物季节长度、灌溉方法和 23 年（1998-2020 年）较长时期内不同应用深度的情景中灌溉水需求的概率。³ m ^-3和建模效率范围从 0.358 到 0.812。初始 (K _{cb ini} )、季中 (K _{cb mid} ) 和季末 (K _{cb end} ) 的校准基础（非胁迫）作物系数 (K _cb ) 分别为 0.15、0.95 和 0.95) 阶段。该作物每季收获两次，滴灌处理表现出最高的水生产力和经济指标。相比之下，盆地处理导致了大量的渗透损失，从而影响了产量和指标。尽管净灌溉需求在长期天气时间序列的极端情况下显示出很大的变化，但仅在滴灌情景中发现了代表平均需水量的年份和代表非常高的需水量的年份之间的差异。这项研究有助于改善叙利亚阿卡地区黄麻锦葵的灌溉水管理，并有助于当地生产系统的可持续性。