Support vector machine and data assimilation framework for Groundwater Level Forecasting using GRACE satellite data
Authors:
- Di LiuDLDi Liu
- Ashok K. MishraAMAshok K. Mishra
- Zhongbo YuZYZhongbo Yu
- Haishen LüHLHaishen Lü
- Yajie LiYLYajie Li
- 1 December 2021
- journal article
- research article
- Published by Elsevier in Journal of Hydrology
- Vol. 603
Abstract
No abstract availableKeywords
Funding Information
- National Aeronautics and Space Administration
- National Natural Science Foundation of China (51709074, 51909058)
- National Key Laboratory of Water Disaster Prevention (20195018812, 20195025612, 520004412)
- National Key Research and Development Program of China (2016YFC0402710, 2018YFC0407704, 41761134090, 41830752, 51539003)
- Fundamental Research Funds for the Central Universities (B210202006)
This publication has 93 references indexed in Scilit:
- Ground water and climate changeNature Climate Change, 2012
- An annual load forecasting model based on support vector regression with differential evolution algorithmApplied Energy, 2012
- Past and future contribution of global groundwater depletion to sea‐level riseGeophysical Research Letters, 2012
- Ground referencing GRACE satellite estimates of groundwater storage changes in the California Central Valley, USAWater Resources Research, 2012
- Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across EuropeRemote Sensing of Environment, 2011
- A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquiferJournal of Hydrology, 2011
- Statistical downscaling of daily precipitation using support vector machines and multivariate analysisJournal of Hydrology, 2010
- Modeling daily discharge responses of a large karstic aquifer using soft computing methods: Artificial neural network and neuro-fuzzyJournal of Hydrology, 2010
- Estimating groundwater storage changes in the Mississippi River basin (USA) using GRACEHydrogeology Journal, 2006
- The gravity recovery and climate experiment: Mission overview and early resultsGeophysical Research Letters, 2004