Effects of Soil Assessment Unit Scale On Quantifying CH4 Emissions From Rice Fields In the Tai-Lake Region of China by DNDC Model.

Soil polygons and grids have been used as assessment units to represent soil properties in regional scale modeling, with the common outcome being that modeling error will be lower if all features within the assessment unit are more homogeneous. However, it is more difficult for raster cells to be homogeneous than polygons, as polygon boundaries can be manipulated to better fit the natural alignment of the feature. Soil polygons are the preferred format for the regional scale modeling. Despite this, it is not yet fully understood how map scales of soil assessment units affect modeling, and how to identify an optimal map scale for the regional scale modeling. Six soil polygonal datasets were generated from soil vector maps at scales of 1:50,000 ~ 1:14,000,000, to estimate CH₄ emissions from paddy soils in the Tai-Lake region of China using the DNDC model. The 1:50,000 scale dataset (P005) was the most detailed and accurate soil database of the region. DNDC simulated CH₄ concentrations from input of the other 5 datasets were compared with that obtained by input of the P005 dataset using metrics with the following outcomes. a.) Relative variations (VIV, %) of three indices, paddy soil area (APS, ha), annual mean CH₄ emission (AME, Gg y^-1) and emission rate (RGE, kg ha^-1 y^-1), calculated for 1: 200,000 (P02) data were all < 5%, b.) VIVs associated with the three indices assessed for 1:500,000 (P05) and 1:1,000,000 (P1) data ranged from 0.8% to 15%, and c.) VIVs for the three indices determined for 1:4,000,000 (P4) and 1:14,000,000 (P14) data were all > 20%, the greatest equaling 138%. Accuracy and computational efficiency assessments of regional scale DNDC modeling indicate that P02 scale input are preferred, those at scales of P4 and P14 are the source of unacceptable error, and even greater uncertainty exists when assessment units at scales of P05 and P1 are used. The results provide guidelines for modeling soil carbon/nitrogen cycle and climate change impacts in China. Further, they help build a global understanding concerning appropriate scale input data for carbon/nitrogen cycle modeling.