对代表性降雨事件系列进行选,以评估草地的长期水文性能
Feikai Yang1,2,3, Dafang Fu1,2, Chris Zevenbergen3
1School of Civil Engineering, Southeast University, Nanjing, 210096, China.
Environmental science and pollution research international
|February 23, 2024
概括
研究人员开发了一种方法,使用短期降雨数据准确评估草地的表现. 这种技术使用贝叶斯网络来识别代表性的降雨事件序列,减少了对广泛监测的需求.
科学领域:
- 环境水文学环境水文学
- 水资源管理 水资源管理
- 可持续的排水系统 可持续的排水系统
背景情况:
- 评估草地鱼的水文性能通常需要广泛的长期监测数据.
- 目前使用有限数据模拟性能的方法是不够的.
- 准确的评估对于有效的城市水资源管理和洪水控制至关重要.
研究的目的:
- 为了研究和液压导电性 (Ks) 测试结果与不同事件系列长度的降雨特征之间的关系.
- 确定代表性的短期降雨事件系列,以准确评估草地的水文性能.
- 开发一个预测模型来确定短期降雨数据的代表性.
主要方法:
- 利用了来自荷兰恩舍德 (Enschede) 的全尺寸草地的长期降雨事件数据 (95个事件).
- 开发了一个多变量非线性模型,将Ks与降雨指标 (先前的干旱天,温度,降雨量,持续时间,总降雨量,季节因素) 联系起来.
- 采用集群分析,并提出一个贝叶斯网络用于代表性预测,与来自荷兰乌得勒支的数据 (58事件) 验证.
主要成果:
- 季节性指数 (平均季节性因素) 成为短时间降雨事件系列中最具代表性的指标.
- 贝叶斯网络有效地预测了短期降雨事件系列的代表性.
- 短期系列,当被确定为代表性时,产生了与长期评估相美的结果.
结论:
- 通过使用代表性的短期降雨事件系列来评估草地的长期水文性能是可行的和有希望的.
- 开发的贝叶斯网络为数据稀缺的水文评估提供了有价值的工具.
- 这种方法可以显著减少长时间监测的需要,优化环境研究中的资源配置.
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