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首页> 外文期刊>African Crop Science Journal >Enhancing response farming for strategic and tactical management of risks of seasonal rainfall variability.
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Enhancing response farming for strategic and tactical management of risks of seasonal rainfall variability.

机译:加强应对农业,以应对季节性降雨变化风险的战略和战术管理。

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摘要

Seasonal rainfall variability, particularly the uncertainty with respect to the direction and extent that variability will assume in a given season, forms the greatest source of risk to crop production in semi-arid areas of Ethiopia. Equipping vulnerable communities, in advance, with the expected date of onset of a cropping season, is crucial for smallholder farmers to better prepare to respond and manage the uncertainties. Therefore, rainfall prediction, particularly development of models that can foretell the date of onset of next cropping season is crucial in facilitating strategic agronomic planning and tactical management of in-season risks. A twenty-four-year climatic data study was conducted for Melkassa Agricultural Research Centre (MARC) in semi arid Ethiopia, to develop onset date prediction models that can improve strategic and tactical response farming (RF). A sequential simulation model for a build up of 15 to 25 mm soil water by April 1st, was conducted. Simulation results revealed a build up of soil water up to 25 mm, to be the most risk-wise acceptable time of season onset for planting of a 150-day maize crop. In the context of response farming, this was desirable as it offers the opportunity for farmers to consider flexible combination production of maize ( Zea mays L.) varieties of 120 and 90 days in the event of failure of earliest sown 150-day maize crop. Thus, to allow for flexible combination production of the three maize varieties, predictive capacity was found crucial for April onset of the next crop season. Accordingly, based on the consideration of pre-onset rainfall parameters, the first effective rainfall date varied considerably with the date of onset of rainfall. Regression analyses revealed the first effective rainfall date to be the best predictor of the date of onset (R 2=62.5%), and a good indicator of the duration of next season (R 2=42.4%). The identified strategic predictor, the first effective rainfall date, enabled prediction of time of season onset and season length by a lead time of two to three months. This markedly improved Stewart's RF. The date of onset of the next crop season was also found to be a useful predictor of season duration (R 2=87.3%). Strategic agronomic planning should be adjusted according to the first effective rain date, and tactically according to what date of rainfall onset informs us about expectations in the duration and total season water supply.
机译:季节性降雨的可变性,特别是在给定季节中可变性的方向和程度的不确定性,构成了埃塞俄比亚半干旱地区作物生产的最大风险来源。提前为脆弱的社区配备作物季节的预计开始日期,对于小农户更好地准备应对和管理不确定性至关重要。因此,降雨预报,特别是可以预测下一个作物季节开始日期的模型的开发,对于促进战略农业计划和季节风险的战术管理至关重要。在半干旱埃塞俄比亚的梅尔卡萨(Melkassa)农业研究中心(MARC)进行了为期24年的气候数据研究,以开发可改善战略和战术响应农业(RF)的发病日期预测模型。进行了顺序模拟模型,以期在4月1日之前增加15至25 mm的土壤水。模拟结果表明,积水最多25毫米,这是播种150天玉米作物的最危险的季节开始时间。在响应耕作的背景下,这是理想的,因为它为农民提供了机会,在最早播种的150天玉米作物歉收的情况下,可以考虑灵活地组合生产120天和90天的玉米品种(Zea mays L.)。因此,为了能够灵活地组合生产这三个玉米品种,发现预测能力对于下一个作物季节的4月开始至关重要。因此,基于对预雨量参数的考虑,第一有效雨量日期随雨量开始日期而变化很大。回归分析表明,第一个有效降雨日期是发病日期的最佳预测指标(R 2 = 62.5%),并且是下一季持续时间的良好指标(R 2 = 42.4%)。确定的战略预测指标(第一个有效的降雨日期)可以提前两到三个月的时间来预测季节开始时间和季节长度。这显着改善了Stewart的RF。还发现下一个作物季节的发病日期是季节持续时间的有用预测指标(R 2 = 87.3%)。应根据第一个有效的降雨日期来调整战略性农业计划,并在战术上根据降雨的开始日期来告知我们对持续时间和总季节供水的期望。

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