Effects of soil spatial resolution on quantifying CH₄ and N ₂O emissions from rice fields in the Tai Lake region of China by DNDC model

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.