圣路易斯山谷的水库系统变形:在农业地区建模沉降的新框架
Sanaz Vajedian1,2, Ryan Smith3, Willem A Schreüder4
1Wesleyan University, Department of Earth and Environmental Sciences, Middletown, CT 06459, USA.
概括
在圣路易斯山谷的地下水开采导致土地沉降,可用卫星雷达 (InSAR) 和地面传感器 (GNSS) 测量. 先进的数据技术改善了可持续水资源管理的监测.
科学领域:
- 地质科学 地质科学
- 水文学的水文学
- 遥感 遥感 遥感 遥感
背景情况:
- 气候变化加剧了科罗拉多州圣路易斯山谷 (SLV) 的地表水短缺.
- 从未巩固的含水层中提取地下水,就像在SLV中一样,可以导致土地沉降.
- 有效的地下水管理对于SLV的可持续未来至关重要.
研究的目的:
- 为了测量SLV中的土地沉降,使用交叉测量合成孔径雷达 (InSAR) 和全球导航卫星系统 (GNSS) 数据.
- 分析负责观察到沉降和反弹的地下水动态.
- 开发和验证一个可靠的方法,用于在数据稀缺的环境中建模沉降.
主要方法:
- 利用交叉测量合成孔径雷达 (InSAR) 数据进行广域沉降测量.
- 使用全球导航卫星系统 (GNSS) 来验证InSAR衍生的沉降.
- 应用了修改后的DS插值和Singular Spectrum Analysis (SSA) 来填补InSAR数据缺口和降低噪声.
- 使用泰斯曲线插值提高地下水位数据的时间分辨率.
- 校准了一个1D变形模型,整合了井和卫星数据,以捕获水表弹性和不弹性反应.
主要成果:
- 在2015年至2021年间,在SLV中检测到季节性和长期的土地沉降趋势.
- 在封闭的含水层部分观察到每年下沉幅度高达1厘米,季节性波动很大.
- 证明了开发的方法在建模沉降中的有效性,尽管InSAR数据很,地下水测量很少.
结论:
- 集成的InSAR,GNSS和地下水数据分析为监测沉降提供了一种可靠的方法.
- 开发的建模方法为数据有限的地区的沉降评估提供了一条途径.
- 结果为在圣路易斯山谷和类似的干旱/半干旱地区的可持续地下水管理战略提供了关键的见解.
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