Fourteen grid data sets of different cell resolutions were generated, from 0.5 × 0.5 km to 64 × 64 km, to estimate CH4 and N 2O emissions from paddy soils in the Tai Lake region of China using the Denitrification-Decomposition (DNDC) model. The grids were derived from a polygon-based data set (1:50,000 digital soil map/database), which was the most detailed soil database for the region. Comparison of simulated CH4 and N2O concentrations from input of the 14 grid data sets with the original polygon data demonstrated (1) no distinct variability (relative errors <5%) of the results when grid data sets of cell size 2 km were used as input for the DNDC model; (2) slight variability (<10%) in the results when grid data sets with cell size in the range of 2 to 8 km were used as input; and (3) distinct variability (>10%) in the results when grid data sets with cell size of >8 km were applied as input. A grid data set with a cell size of 8 km was found to be optimal based on accuracy and computational efficiency of DNDC simulations. The results can be used as a guideline for optimizing field sampling strategies for locations where there is a lack of or insufficient soil data, whereby soil data can be collected through sampling in cell centers of designed grid frames.
All Science Journal Classification (ASJC) codes
- Global and Planetary Change
- Environmental Chemistry
- Environmental Science(all)
- Atmospheric Science