基于GPS双频信号增强的雪水当量估计

Estimation of Snow Water Equivalent Based on GPS Dual-frequency Signal Enhancement

雪水当量是重要的积雪参数之一,对气候变化预测与水资源管理等有重要意义。GPS干涉反射技术(GPS-IR)是一种十分有效的积雪深度监测技术,结合积雪密度估计模型可实现雪水当量的估计。基于此,提出了一种GPS-IR双频积雪参数反演增强方法。首先,利用美国板块边界观测(PBO)AB33测站2016年水文年与P019测站2020年水文年的L1和L2C信号信噪比数据,通过GPS-IR技术获取了两个测站的双频反射高度,建立了双频反射高度的线性关系模型,并通过该模型填补了L2C信号反射高度缺测数据,进而获取双频增强积雪深度时间序列,然后通过积雪密度估计模型转换得到雪水当量日估计值,最后采用SNOTEL测站实测积雪参数进行检验。结果表明:基于L2C信号的积雪深度反演精度要优于L1信号,基于增强方法的积雪深度反演精度介于L1信号和L2C信号之间;基于增强方法的雪水当量反演精度与L2C信号基本相当,且均优于L1信号;增强方法在AB33测站与P019测站分别有效填补了基于L2C信号的积雪深度/雪水当量时间序列25.8%与13.7%的空缺数据。本文提出的增强方法充分利用了GPS双频信号数据资源,可获取高连续性的GPS积雪深度和雪水当量,为设备缺乏地区的雪水当量估计、水环境监测等研究提供参考。

Snow water equivalent(SWE)is one of the important snow parameters,and is of great significance to climate change prediction and water resource management.GPS interferometric reflectometry(GPS-IR)is an effective technique for snow depth monitoring.Combined with the snow density model,the SWE can be estimated.An efficient framework to enhance the snow parameters estimation with GPS-IR dual-frequency data was presented.Firstly,by applying GPS-IR to the dual-frequency signal to noise ratio(SNR)data recorded by two Plate Boundary Observatory(PBO)GPS stations AB33 and P019 in water years of 2016 and 2020,the corresponding daily measurements of reflector heights were obtained.Secondly,based on the linear relationship between the L1 and L2C signal reflector heights,a simple linear model to calibrate the L1 to L2C signal results was proposed.Finally,the calibrated reflector heights were used to obtain the daily snow depth measurements,which were then converted to SWE by an empirical snow density model.By using in-situ observations from Snow Telemetry(SNOTEL)sites,the results show that the precision of L2C signal snow depth measurement is better than that of L1 signal;the precision of the snow depth measurements from the enhanced method is moderate but closer to the precision of L2C signal;the precision of SWE from the enhanced method is comparable to that of L2C signal,and both are better than that of L1 signal;the dual-frequency enhanced method effectively fills 25.8%and 13.7%data gaps in the L2C signal snow depth/SWE time series at stations AB33 and P019,respectively.The proposed method makes full use of the GPS dual-frequency SNR data resources,and can obtain high-continuity GPS snow depth and snow water equivalent,which provides data for the effective estimation of snow water equivalent and water environment monitoring in areas with poor equipment.