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Data Details

Spatial Dataset of Forest Water Retention in China Based on Meta-analysis


WUXi1,2Wenjiao*1,3TAO Fulu*1,3
1 Key Laboratory of Land Surface Pattern and Simulation,State Key Laboratory of Resources and Environmental Information System,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China2 Jiangsu Province Surveying & Mapping Engineering Institute,Nanjing 210013,China3 College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100049,China

DOI:10.3974/geodb.2022.03.06.V1

Published:Mar. 2022

Visitors:1563       Data Files Downloaded:127      
Data Downloaded:5908.29 MB      Citations:

Key Words:

China,forest water retention,Meta analysis,spatial pattern

Abstract:

The spatial dataset of forest water retention in China by meta-analysis methodology was developed based on the parameters and influencing factors of forest water retention at 1045 observation sites throughout China. The empirical model was used to estimate canopy interception capacity, litter maximum water-holding capacity, soil water storage capacity and forest water retention capacity. Then, the random forest model was used to predict the spatial pattern of forest water retention in 10 km x 10 km grid. The dataset includes: (1) forest water retention data in each forest type in 10 km x 10 km grid, including: canopy interception capacity, litter maximum water-holding capacity, soil water storage capacity, forest water retention capacity, canopy interception amount, litter maximum water-holding amount, soil water storage amount and forest water retention amount; (2) statistics of forest water retention in each provinces of China; (3) data of forest water retention at 1045 observation sites in China. The dataset is archived in .xlsx and .shp data formats, and consists of 9 data files with data size of 118 MB (Compressed into one data file with 46.5 MB). The analysis paper based on the dataset was published in Ecological Indicators, Vol. 132, 2021.

Foundation Item:

Ministry of Science and Technology of P. R. China (2017YFA0604703); Chinese Academy of Sciences (XDA20010202, XDA23100202, 2018071); National Natural Science Foundation of China (41930647);

Data Citation:

WUXi, Wenjiao*, TAO Fulu*. Spatial Dataset of Forest Water Retention in China Based on Meta-analysis[J/DB/OL]. Digital Journal of Global Change Data Repository, 2022. https://doi.org/10.3974/geodb.2022.03.06.V1.

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