Ground-based GNSS is used for multi-parameter inversion of surface environment in frozen soil areas
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摘要: 季节性冻土具有周期性地表抬升/沉降的物理特性，传统测量方法已不能满足当前高精度、实时的监测需求. 地基GNSS是一种低成本、全天时、全天候、能够实现连续监测的新兴地基遥感技术. 实验应用美国的板块边界观测台网(plate boundary observational GNSS network，PBO)计划SG27测站2013—2021年观测数据，使用地基GNSS技术解译了阿拉斯加巴罗永久冻土区域典型异常年份降雪、无雪期地表形变、测站形变、土壤湿度、大气水汽变化，并通过PBO实测降雪数据验证异常年雪深反演精度，通过测站形变结果验证反演结果为冻土活动层形变，同时对水汽与土壤湿度进行相关性分析. 结果显示：反演雪深与实测雪深绝对系数R2为0.8155，均方根误差(root mean squared error，RMSE)为0.0643，平均绝对误差(mean absolute error，MAE)为0.0402；通过水汽与土壤湿度变化趋势图发现两者具有较弱滞后性对应关系，但仅表现在趋势而非幅度值上. 表明地基GNSS在长时序冻土环境监测中存在巨大的应用潜力.Abstract: Seasonal frozen soil has the physical characteristics of periodic surface uplift/settlement, and traditional measurement methods can no longer meet the current high-precision and real-time monitoring needs. Ground-based GNSS is a low-cost, all-day, all-weather, and emerging ground-based remote sensing technology that can achieve continuous monitoring. In this paper, based on the observation data of SG27 station of the U.S. Continental plate boundary observation (PBO) GNSS netuork program from 2013 to 2021, the ground-based GNSS technology is used to interpret the snow in typical abnormal years in the Permafrost region of Barrow, Alaska, and the surface deformation, station deformation, soil moisture, and atmospheric water vapor changes in the last nine years of long time series snow free period. The retrieval accuracy of snow depth in abnormal years is verified through the PBO measured snow data, Verify that the inversion result is the deformation of the permafrost active layer through the deformation results of the measuring station, and conduct correlation analysis between water vapor and soil moisture. The results show that the absolute coefficient R2 of retrieved snow depth and measured snow depth is 0.8155, the root mean square error (RMSE) is 0.0643, and the mean absolute error (MAE) is 0.0402; Through the trend chart of water vapor and soil moisture changes, it is found that there is a weak lag relationship between the two on the rainfall threshold, but only in the trend rather than the amplitude. It shows that ground-based GNSS has great application potential in long-term permafrost environmental monitoring..
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Key words:
- seasonal permafrost /
- foundation GNSS /
- surface subsidence /
- atmospheric water vapor /
- soil moisture
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