基于多源水文数据融合的GRACE水储量精度校正

全球水储量的时空变化研究,对理解全球水循环过程、安排农业生产、防治洪涝灾害等具有重要意义.GRACE重力反演与气象实验卫星为获取全球水储量变化提供了直接观测手段,但不同解算模型和方法导致最终水储量产品之间存在差异.针对现阶段GRACE水储量数据产品中所存在的不确定性,拟结合全球水文模型以及陆面模型数据,采用三角帽方法对...

Accuracy Correction of GRACE Water Storage based on Multi-source Hydrological Data

Study on the spatiotemporal changes of global water storage is of great significance for understanding the global water cycle， arranging agricultural production， and preventing natural disasters. GRACE satellite provides direct observation for obtaining changes in water storage on a global scale. However， different solution models and methods lead to differences between the water storage products. To reduce the uncertainty in GRACE data， this paper combines the Global Hydrological Models （GHMs） and Land Surface Models （LSMs） data， and uses the Three-Cornered Hat （TCH） method to analyze the uncertainty of the existing products. On this basis， the idea of point surface fusion is introduced， using GRACE and model simulation data to select training points， and using machine learning methods to correct the accuracy of GRACE satellite data. This article takes California， USA as an example， and uses TCH， long-term quantitative analysis and groundwater well site data to verify the accuracy of the result. The results show that： （1） The correction results have lower uncertainty than the original GRACE data in the uncertainty analysis （GRACE CSR： 25.32 cm， PCR-GLOBWB： 33.10 cm， DBN： 13.85 cm）； （2） In long time series analysis， the correction results are smoother than the original data， reducing abnormal fluctuations； （3） In the verification of the well site， the results show that results have improved in correlation， root mean square error， and average absolute error.