Effects of soil map scales on simulating soil organic carbon changes of upland soils in Eastern China

Geoderma ◽  
2018 ◽  
Vol 312 ◽  
pp. 159-169 ◽  
Author(s):  
Liming Zhang ◽  
Yaling Liu ◽  
Xiaodi Li ◽  
Linbin Huang ◽  
Dongsheng Yu ◽  
...  
Geoderma ◽  
2019 ◽  
Vol 337 ◽  
pp. 1105-1115 ◽  
Author(s):  
Liming Zhang ◽  
Qiaofeng Zheng ◽  
Yaling Liu ◽  
Shaogui Liu ◽  
Dongsheng Yu ◽  
...  

2012 ◽  
Vol 9 (10) ◽  
pp. 15175-15211
Author(s):  
S. Liu ◽  
Y. Wei ◽  
W. M. Post ◽  
R. B. Cook ◽  
K. Schaefer ◽  
...  

Abstract. The Unified North American Soil Map (UNASM) was developed to provide more accurate regional soil information for terrestrial biosphere modeling. The UNASM combines information from state-of-the-art US STATSGO2 and Soil Landscape of Canada (SLCs) databases. The area not covered by these datasets is filled with the Harmonized World Soil Database version 1.1 (HWSD1.1). The UNASM contains maximum soil depth derived from the data source as well as seven soil attributes (including sand, silt, and clay content, gravel content, organic carbon content, pH, and bulk density) for the top soil layer (0–30 cm) and the sub soil layer (30–100 cm) respectively, of the spatial resolution of 0.25° in latitude and longitude. There are pronounced differences in the spatial distributions of soil properties and soil organic carbon between UNASM and HWSD, but the UNASM overall provides more detailed and higher-quality information particularly in Alaska and Central Canada. To provide more accurate and up-to-date estimate of soil organic carbon stock in North America, we incorporated Northern Circumpolar Soil Carbon Database (NCSCD) into the UNASM. The estimate of total soil organic carbon mass in the upper 100 cm soil profile based on the improved UNASM is 347.70 Pg, of which 24.7% is under trees, 14.2% is under shrubs, and 1.3% is under grasses and 3.8% under crops. This UNASM data will provide a resource for use in land surface and terrestrial biogeochemistry modeling both for input of soil characteristics and for benchmarking model output.


2017 ◽  
Vol 174 ◽  
pp. 81-91 ◽  
Author(s):  
Liming Zhang ◽  
Guangxiang Wang ◽  
Qiaofeng Zheng ◽  
Yaling Liu ◽  
Dongsheng Yu ◽  
...  

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