Evaluating different predictive strategies for filling the global GRACE/-FO terrestrial water storage anomalies gap

Author:

Wan Xiangyu,You Wei,Kusche Jürgen,Li Fupeng,Yang Xinchun,Fan Dongming,Pu Lun,Jiang Zhongshan

Funder

Center for Scientific Review

University of East Anglia

National Aeronautics and Space Administration

European Space Agency

Grains Research and Development Corporation

National Natural Science Foundation of China

National Oceanic and Atmospheric Administration

China Shipbuilding Industry

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference104 articles.

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2. The use of GRACE data to monitor natural and anthropogenic induced variations in water availability across Africa;Ahmed;Earth Sci. Rev.,2014

3. Forecasting GRACE data over the african watersheds using artificial neural networks;Ahmed;Remote Sens.,2019

4. Bai, S.J., Kolter, J.Z., Koltun, V., 2018. An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271.

5. Potential impacts of a warming climate on water availability in snow-dominated regions;Barnett;Nature,2005

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