Global Land Surface Water Yield and Its Efficiency Dataset in 0.5°x0.5° Pixels (1981-2022)
GAO Han1
1 College of Hydrology and Water Resources，Hohai University，Nanjing 210000，China
DOI:10.3974/geodb.2023.08.09.V1
Published:Aug. 2023
Visitors：3787 Data Files Downloaded：166
Data Downloaded：5699.55 MB Citations：
Key Words：
global,water yield,water yield efficiency,significant change
Abstract：
The Global Land Surface Water Yield and Its Efficiency Datasets in 0.5°x0.5° Pixels (1981-2022) was developed based on CRU precipitation and GLEAM evapotranspiration remote sensing products, covering global with a spatial resolution of 0.5°x0.5°. Firstly, the original monthly precipitation and evapotranspiration data were synthesized to the annual scale, and the difference between them was calculated to obtain the water yield dataset by pixel. Then divide the water yield data by the annual precipitation to obtain the water yield efficiency data at a year scale. Finally, the regions with significant inter-annual changes in global water yield were estimated using the Mann-Kendall test and the permutation test. The dataset is consisted of raster data and tabular data. The raster data include the following global data from 1981 to 2022: (1) spatial global annual water yield, (2) spatial annual global water yield utilization efficiency, (3) spatial significant changes in global water yield. The tabular data include: (1) inter-annual changes in global land water yield and water yield efficiency from 1981 to 2022, (2) statistics on the number of true and false positive pixels of significant changes in global water yield before and after correction. The dataset is archived in .nc and .xlsx formats, and consists of 4 files with data size of 193 MB (Compressed into one file with 34.3 MB).
Foundation Item：
National Natural Science Foundation of China (41971374)
Data Citation：
GAO Han. Global Land Surface Water Yield and Its Efficiency Dataset in 0.5°x0.5° Pixels (1981-2022)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2023. https://doi.org/10.3974/geodb.2023.08.09.V1.
References：
[1] Harris, I., Osborn, T. J., Jones, P., et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset [J]. Scientific Data, 2020, 7: 109.
[2] Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., et al. Global land-surface evaporation estimated from satellite-based Observations [J]. Hydrology and Earth System Science, 2011, 15: 453–469.
[3] Cortés, J., Mahecha, M. D., Reichstein, M., et al. Where are global vegetation greening and browning trends significant? [J]. Geophysical Research Letters, 2021, 48: e2020GL091496.
Data Product:
| ID |
Data Name |
Data Size |
Operation |
| 1 |
WaterYield1981-2022.rar |
35158.64KB |
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