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提取流水表形状指标的协议,用于时间序列洪水水文分析
Amir Mohammad Arash1, Kirstie Fryirs1, Timothy J Ralph1
1School of Natural Sciences, Macquarie University, North Ryde, NSW, Australia.
PloS one
|January 10, 2025
概括
本研究介绍了一个Python工作流来分析流水图形,分类不同的洪水类型和计算关键指标. 这种方法使得在大型数据集中对水文变化进行一致的评估.
科学领域:
- 水文学的水文学
- 环境科学 环境科学
- 地理空间分析的研究.
背景情况:
- 分析流水图对于理解各种规模的水文变化至关重要.
- 对众多水谱仪的手动分析耗时,并限制了全面的评估.
- 需要一个标准化的协议来一致地导出和验证水文仪表的指标.
研究的目的:
- 介绍Python工作流程,用于从公共测量站记录中提取和分析流水图.
- 根据形态学定义的流量和洪水类型来对水文图进行分类.
- 为了计算不同的站点和下游水文图形形状指标.
主要方法:
- 利用Python从开放访问测量站数据中进行自动化水文图提取.
- 实施了对道内新鲜,高流量和上岸洪水类型的分类系统.
- 计算的指标,如 kurtosis,斜率,峰值阶段,以及各种衰减和速度指数,结合了 GIS 数据.
主要成果:
- 开发了一种灵活的工作流程,用于从不同时间分辨率量化水文图形形状指标.
- 在澳大利亚新南威尔士州沿海地区使用117个测量站演示了工作流的应用.
- 创建了一套量化指标的数据集,用于跟踪水文变化和描述区域水文.
结论:
- Python 工作流提供了一种一致且高效的方法来分析大型水文图数据集.
- 计算的指标有助于跟踪流量和洪水的动态,随着时间的推移和跨地区.
- 该协议是用于水文学变化检测和确定进一步建模区域的宝贵工具.
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