Influence of rainwater harvesting practices on the sorghum (Sorghum bicolor L.) grain yields in the sub-tropical deserts of Sudan ​

S. M. Ahmed, Amar A Abdalla, Adam E. Ahmed, A. A. Elbushra
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Abstract

Food security is climate dependent in the Darfur region, Sudan; ultimately, the extreme drought events have derailed the region into “the world’s first climate change conflict”. Most of the ongoing climate resilience efforts in the region depend on rainwater harvesting (RWH) practices. The objective of this study is to be better understanding of the variability in the performance of the adopted RWH practices in the Darfur region. Datasets of 148 farmers were collected during the year 2022 through a structured questionnaire in the South Darfur state and analyzed based on two different modeling frameworks in the R package: the deep machine learning (the Bagging algorithms) and the logit models. The dependent variable is the rainfed sorghum grain yield, and the independent variables were RWH practices, education level, family size, and distance to the farm. The standardized precipitation index (SPI) explained that every two years the region is experiencing a drought event (1980-2015), with an annual rainfall of 396 mm ± 100 mm. About 82% of farmers mainly adopted RWH for food security in face of the decreased rainfall. The adopted RWH practices (mainly terracing) have increased sorghum grain yields by 72% - 147%. The best grain yield is associated with spate irrigation, and the poorest with illiteracy. The large family size ( greater than 9 people) and good education level offset the negative impacts of both illiteracy and the longer distance to the farm. The terracing and terracing + mulching + deep tillage (as a single package) practices were the most laborious and unsustainable practices in the Darfur region, and are not recommended, especially when the farm distance is greater than 5 km
集雨措施对苏丹亚热带沙漠高粱产量的影响
在苏丹达尔富尔地区,粮食安全取决于气候;最终,极端干旱事件使该地区陷入“世界上第一个气候变化冲突”。该地区正在进行的大多数气候适应工作都依赖于雨水收集(RWH)实践。本研究的目的是更好地了解达尔富尔地区采用的生殖妇女做法的表现差异。在南达尔富尔州,通过结构化问卷收集了148名农民的数据集,并基于R包中的两种不同建模框架:深度机器学习(Bagging算法)和logit模型进行了分析。因变量为旱作高粱籽粒产量,自变量为农作方式、受教育程度、家庭规模和距离。标准化降水指数(SPI)解释说,该地区每两年经历一次干旱事件(1980-2015),年降雨量为396毫米±100毫米。面对降雨减少,约82%的农民主要采用水田灌溉粮食保障。采用的RWH做法(主要是梯田)使高粱籽粒产量提高了72% - 147%。最好的粮食产量与大量灌溉有关,最贫穷的人与文盲有关。庞大的家庭规模(超过9人)和良好的教育水平抵消了文盲和距离农场较远的负面影响。梯田和梯田+覆盖+深耕(作为一个一揽子)做法是达尔富尔地区最费力和不可持续的做法,不推荐,特别是当农场距离大于5公里时
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