评估印度马哈纳迪河流域的洪水潜力,使用重力恢复和气候实验 (GRACE) 数据和非静止框架下的地形洪水易感指数
Sachin Bhere1, Manne Janga Reddy2,3
1Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai, 4000076, India. studentsachinbhere@gmail.com.
Environmental science and pollution research international
|February 9, 2024
概括
通过使用重力恢复和气候实验 (GRACE) 数据,可以更好地评估Mahanadi河流盆地的极端洪水事件. 这种新方法准确地模拟了洪水的潜力和频率,有助于水资源管理.
科学领域:
- 水文学的水文学
- 遥感 遥感 遥感 遥感
- 气候科学 气候科学
背景情况:
- 玛哈纳迪河流域的极端洪水事件造成了重大的社会经济损失.
- 有限的水文气象站阻碍了对洪水大小的准确评估.
- 重力恢复和气候实验 (GRACE) 数据为监测水文极端提供了潜在的解决方案.
研究的目的:
- 通过使用GRACE衍生的陆地水储 (TWS) 和基于分析层次过程 (AHP) 的地形洪水易感度来估计洪水潜力.
- 将这些新数据源纳入非静止洪水频率模型.
- 评估大型河流盆地的综合洪水潜力指数 (CFPI) 的适用性.
主要方法:
- 利用GRACE卫星数据进行陆地水储量 (TWS) 估计.
- 采用分析层次过程 (AHP) 进行地形洪水易感性分析.
- 开发了综合洪水潜力指数 (CFPI),并将其整合到非静止洪水频率建模中.
主要成果:
- 高CFPI值 (>0.6) 与极端洪水事件和较高的河流排水相关.
- CFPI准确地反映了洪水的大小,例如,2012年35年回报期事件的0.67.
- 在多个地点观察到CFPI和河流排放之间存在强烈的相关性 (r > 0.8).
- 与时间或气候指数相比,CFPI集成改善了非静态洪水频率模型.
结论:
- 基于GRACE的CFPI是有效的识别洪水风险的大盆地,如玛哈纳迪.
- 改进的建模方法提高了洪水回归水平估计的准确性.
- 这种方法支持水资源项目的更好的水文设计.
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