Collaborative Research: GPS-based terrestrial water storage anomalies during hydrologic extremes: linking hydrologic process, solid-earth response, and monitoring networks

陆地储水量（TWS）是指以土壤水分、地下水、雪、地表水和生物圈等形式储存的总水量。TWS的变化反映了流域尺度对干旱和地下水抽吸等变化的响应。研究地球水循环及其在地球上的作用需要对TWS进行观测，但现有的TWS监测工具并不令人满意。近年来，全球定位系统（GPS）对地表高度的观测已被用于量化TWS的变化。然而，从GPS数据估计的TWS误差尚未量化。这项研究有三个组成部分来研究如何利用GPS观测来监测TWS。首先，通过结合水文数据和地球如何变形的模型，从GPS陆地表面高度估计TWS变化的分辨率和精度将被量化。其次，来自数千个站点的GPS数据将用于估计过去十年和未来美国大陆的TWS变化。第三，将对现有TWS估计值与基于GPS观测的估计值进行比较。该项目的预期成果将通过评估基于gps的TWS数据的误差大小和来源，推动TWS监测的起步。这是将这些数据应用于一系列广泛的水文应用的必要步骤，包括估计土壤水量和地下水补给、干旱的影响以及地下水储存变化引起的沉降。TWS异常观测对于理解水文循环如何响应诸如干旱等强迫是至关重要的。现有的TWS异常监测工具并不适合许多水文应用。最近，GPS地表垂直位移观测数据被用于量化与地下水开采、季节性积雪和干旱相关的TWS异常的时空变化。这些结果表明，基于gps的位移记录可以极大地加强对陆地水循环的监测。然而，迄今为止没有一项研究量化了GPS观测估计的TWS异常的误差。该研究计划有三个组成部分，旨在评估如何最好地利用GPS观测来监测TWS。首先，结合水文载荷数据和地球弹性响应模型，对GPS垂直位置数据估计的TWS异常的分辨率和精度进行量化。其次，来自数千个台站的垂直位置数据将用于估计美国大陆过去十年和未来的TWS异常和相关误差。第三，将现有TWS异常产品与基于GPS定位的产品进行对比。通过对地下水、土壤湿度和雪水当量的现场水文观测分析，差异将与水文过程有关。该项目的预期结果将通过评估基于gps的TWS异常误差如何与水文过程、固体地球响应和大陆尺度监测网络之间的相互作用相关，从而推进TWS监测的起步阶段。这是将这些数据应用于一系列水文应用的必要步骤。

Terrestrial water storage (TWS) is the total amount of water stored as soil moisture, groundwater, snow, in surface water bodies, and in the biosphere. Variations in TWS reflect the watershed-scale response to changes, such as drought and groundwater pumping. Observations of TWS are needed to study the water cycle and its role on the Earth, but existing tools for monitoring TWS variations are not satisfactory. Recently, global positioning system (GPS) observations of the height of the land surface have been used to quantify TWS variations. However, errors in TWS estimated from GPS data have not been quantified. This research has three components to study how GPS observations can be used to monitor TWS. First, the resolution and accuracy of TWS variations estimated from GPS land surface heights will be quantified by combining hydrologic data and a model of how the Earth deforms. Second, GPS data from several thousand stations will be used to estimate TWS variations across the continental United States for the past decade and forward in time. Third, a comparison will be made between existing TWS estimates and estimates based on GPS observations. The expected outcomes of this project will advance the start-of-the-art in TWS monitoring by evaluating the magnitude and sources of errors in GPS-based TWS data. This is a necessary step towards applying these data to a range of wide hydrologic applications, including estimates of soil water volumes and groundwater recharge, the effects of drought, and subsidence caused by changes in groundwater storage. Observations of TWS anomalies are critical for understanding how the hydrologic cycle responds to forcing such as drought. Existing tools for monitoring TWS anomalies are not optimal for many hydrologic applications. Recently, GPS observations of land surface vertical displacement have been used in novel ways to quantify the spatial and temporal variations of TWS anomalies associated with groundwater mining, seasonal snowpack, and drought. These results suggest that GPS-based records of displacement could greatly enhance monitoring of the terrestrial water cycle. However, none of the studies to date have quantified the errors in TWS anomalies estimated from GPS observations. The research plan has three components designed to assess how GPS observations can best be used to monitor TWS. First, the resolution and accuracy of TWS anomalies estimated from GPS vertical position data will be quantified by combining hydrologic loading data and models of the Earth's elastic response. Second, vertical position data from several thousand stations will be used to estimate TWS anomalies and associated errors across the continental United States, retrospectively for the past decade and forward in time. Third, a comparison will be made between existing TWS anomaly products and the product based on GPS positions. Differences will be related to hydrologic processes through analyses of in situ hydrologic observations of groundwater, soil moisture, and snow water equivalent. The expected outcomes of this project will advance the start-of-the-art in TWS monitoring by evaluating how errors in GPS-based TWS anomalies are related to interactions between hydrologic process, the solid earth response, and the monitoring network at the continental scale. This is a necessary step towards applying these data to a range of hydrologic applications.