肯尼亚尼扬多河下游流域堤防特征对粮食作物生产的影响

Berryl Atieno Ojung’a, Irene Nzisa Mutavi, Denis Masika
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摘要

堤防将河岸社区的洪水风险降至最低。在肯尼亚的尼扬多盆地,修建了堤坝,以尽量减少洪水对河岸平原上人类活动的影响。堤防特性会改变淤积速率。尽管存在这些动态因素,一些农民现在使用肥料作为应对营养缺乏的新方法。肯尼亚已经就洪水对人类活动的影响进行了几项研究;然而,堤防存在时间、长度和高度等特征与其对粮食作物生产的影响之间没有明确的联系。尼扬多的堤坝减少了该地区的洪水;然而,人们对堤防特征对粮食作物的影响尚不清楚。因此,本研究的目的是探讨堤防特征对粮食作物生产的影响。使用计划理论。采用描述性横断面研究设计。目标人口为34,460户。通过简单随机抽样和进行问卷调查,至少招募了384名户主,而有目的抽样有助于确定研究领域的相关专家。主要数据是通过采访主要线人和重点小组讨论获得的。其他工具包括观察和摄影。二手数据来源于出版物和印刷媒体,使用SPSS软件进行数据分析。定性数据通过编码和数据组织成主题和子主题进行分析,并进行概括。多重决定系数(R2)结果表明,堤防性状的综合变化可解释作物总产量变化的45.4% (R2 = .454, p = .039)。堤防特征对作物产量有显著影响
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Influence of Dykes’ Characteristics on Food Crop Production in Lower River Nyando Basin, Kenya
Dykes minimise flood risks among riparian communities. In Nyando basin, Kenya, dykes were constructed to minimise flood impacts on human activities in the riparian plains. The dyke characteristics could change the rate of silting. In spite of these dynamics, some farmers now use fertilisers as a new way of coping with nutrient deficiency. Several researches have been done in Kenya on the effects of floods on human activities; however, there is no clear link between dyke characteristics like period of existence, length and height and their influence on food crop production. The dykes in Nyando have reduced floods in the region; however, it is not clearly understood how the dyke characteristics influence the food crop. Therefore, the purpose of this study was to examine the influence of dyke characteristics on food crop production. Planning Theory was used. Descriptive cross-sectional research design applied. The target population stood at 34,460 households. At least 384 Household heads were recruited via simple random sampling and a questionnaire administered, while purposive sampling was useful in identifying relevant experts in the field of study. Primary data was obtained by interviewing key informants and focused group discussions. Other tools include observation and photography. Secondary data was obtained from publications and print media, and SPSS was utilised in data analysis. Qualitative data was analysed by coding and organisation of data into themes and sub-themes where generalisation was made. The results from the multiple coefficients of determination (R2) indicated that 45.4% (R2 = .454, p = .039) of the variation in the general crop yield was explainable by the combined change in Dyke Characteristics. The dykes’ characteristics significantly influenced crop production
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