Downscaling Groundwater Storage Data in China to a 1-km Resolution Using Machine Learning Methods
Abstract
:1. Introduction
2. Data
2.1. Soil Texture and Soil Type
2.2. Gross Domestic Product
2.3. Population
2.4. Land Use Status Database
2.5. Elevation and Slope
2.6. Annual Maximum Normalized Difference Vegetation Index
2.7. Annual Mean Land Surface Temperature
2.8. Landsat Tree Cover Continuous Fields
2.9. Precipitation
2.10. GRACE Terrestrial Water Storage
2.11. GLDAS Noah V2.1
2.12. In Situ Measurements
3. Methods
3.1. Technical Route
3.2. Random Forest
3.3. Extreme Gradient Boosting (XGBoost)
3.4. Derived GWS
3.5. Mean Shift Clustering Analysis
3.6. Model Evaluation Metrics
4. Results
4.1. The Correlation Coefficient between Individual Variables and Targets
4.2. Model Accuracies
4.3. The Downscaled GWS Analysis
5. Conclusions and Discussion
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Acronym | Variable Description | Resolution |
---|---|---|
DEM | Digital elevation model | 1 km |
LST | Annual mean land surface temperature | 1 km |
Pre | High-spatial-resolution monthly precipitation dataset | 1 km |
Slope | Slope | 1 km |
NDVI | Annual maximum normalized difference vegetation index | 1 km |
GDP | Gross domestic product | 1 km |
LTCCF | Landsat Tree Cover Continuous Fields | 1 km |
LUSD | Land use status database | 1 km |
Pop | Population | 1 km |
Clay | Clay content | 1 km |
Silt | Silt content | 1 km |
Soil | Soil content | 1 km |
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Zhang, J.; Liu, K.; Wang, M. Downscaling Groundwater Storage Data in China to a 1-km Resolution Using Machine Learning Methods. Remote Sens. 2021, 13, 523. https://doi.org/10.3390/rs13030523
Zhang J, Liu K, Wang M. Downscaling Groundwater Storage Data in China to a 1-km Resolution Using Machine Learning Methods. Remote Sensing. 2021; 13(3):523. https://doi.org/10.3390/rs13030523
Chicago/Turabian StyleZhang, Jianxin, Kai Liu, and Ming Wang. 2021. "Downscaling Groundwater Storage Data in China to a 1-km Resolution Using Machine Learning Methods" Remote Sensing 13, no. 3: 523. https://doi.org/10.3390/rs13030523