在干旱农田的现代灌系统下进行全面的作物适应性评估
Ahmed S Abuzaid1, Hassan H Abbas1, Mostafa A Mostafa1
1Soils and Water Department, Faculty of Agriculture, Benha University, Banha, Egypt.
PloS one
|June 18, 2025
概括
本研究介绍了使用分析层次过程 (AHP) 和地理信息系统 (GIS) 内的模糊逻辑用于农业适用性测绘的综合框架. 调查结果强调小麦是干旱地区最适合种植的作物,其次是玉米和大豆,指导可持续的土地利用.
科学领域:
- 农业科学 农业科学
- 环境科学 环境科学
- 地理信息科学 地理信息科学
背景情况:
- 传统的农业适用性分析方法是主观的和不确定的.
- 开发客观可靠的方法对于干旱地区的可持续农业至关重要.
研究的目的:
- 开发和验证一个综合框架,将分析层次过程 (AHP) 与地理信息系统 (GIS) 中的模糊逻辑结合起来.
- 为了在埃及的一个干旱地区,在中心轴灌下,为小麦,大豆和玉米生成精确的农业适用性地图.
主要方法:
- 利用了气象数据,数字海拔模型,土壤概况和地下水质量数据.
- 在GIS环境中使用AHP来确定因子权重和模糊逻辑的评分标准.
- 基于对选定作物的加权和算法生成适用性地图.
主要成果:
- 气候非常适合冬季作物 (小麦,大豆) 和微不足道的玉米.
- 土壤盐度,盐度和深度是景观的关键决定因素;地下水质量显著影响适用性 (46%).
- 小麦显示的适用性最高 (90%S1,10%S2),其次是玉米 (55%S1,42%S2,35%S3) 和大豆 (53%S2,47%S3).
结论:
- 综合AHP-模糊逻辑-GIS框架为干旱地区的农业适用性评估提供了可复制和客观的方法.
- 地下水质量和景观因素是研究干旱地区作物生产的关键约束因素.
- 适应性地图优先考虑小麦种植,为可持续的粮食生产战略提供宝贵的见解.
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