Rainfall-derived growing season characteristics for agricultural impact assessments in South Africa
Rainfall-derived growing season characteristics for agricultural impact assessments in South Africa
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DOI：
10.1007/s00704-013-0896-y
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发表时间：
2014-02-01
影响因子：
3.4
通讯作者：
Todd, Martin C.
中科院分区：
文献类型：
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作者：
Ambrosino, Chiara;Chandler, Richard E.;Todd, Martin C.
在农业实践主要由依赖自给自足农业的小农主导的地区，降水量的变化给这些地区带来了巨大压力。在时间和空间上对这种变异性的理解取得进展，对于提高农业系统的复原力具有重要作用。这一需求在非洲大陆等世界地区尤为迫切，非洲大陆已经受到包括贫困和经济和政治不稳定在内的多重压力的影响。在这篇文章中，我们通过南非东北部的一个案例研究，探索了广义线性模型(GLMS)的使用。使用GLM将当地降水变率与以前的次大陆尺度分析确定的大尺度气候驱动因素联系起来，并评估了所产生的模式模拟与农业应用相关的降水特征的能力。我们特别关注一套生长季节指数，建议用来调查与该地区玉米生产相关的季节内特征。根据研究区内9个测站的日平均降雨量序列计算了7个指数。作为将GLMS用于这类应用的第一次尝试，结果令人鼓舞，并表明这些模型能够再现一系列与农业相关的指数。然而，建议进一步研究空间相关性结构，以改进降雨衍生特征的多站点生成。
Precipitation variability imposes significant pressure in areas where agricultural practice is dominated by smallholder farmers who are dependent on subsistence farming. Advances in the understanding of this variability, in both time and space, have an important role to play in increasing the resilience of agricultural systems. The need is particularly pressing in regions of the world such as the African continent, which is already affected by multiple stresses including poverty and economic and political instability. In this paper, we explore the use of generalised linear models (GLMs) for this purpose, via a case study from north-east South Africa. A GLM is used to link the local rainfall variability to large-scale climate drivers identified from previous subcontinental-scale analyses, and the ability of the resulting model to simulate precipitation features that are relevant in agricultural applications is evaluated. We focus in particular on a set of growing season indices, proposed for the investigation of intraseasonal characteristics relevant for maize production in the region. Seven indices were computed from spatially averaged daily rainfall series from nine stations in the study area. As a first attempt to use GLMs for this type of application, the results are encouraging and suggest that the models are able to reproduce a range of agriculture-relevant indices. However, further research into spatial correlation structure is recommended to improve the multisite generation of the rainfall-derived characteristics.