Soil polygons are the preferred format for the modeling of denitrificationdecomposition (DNDC) at regional scale because a large area of relatively homogeneous properties can be encompassed within a single boundary. Despite this, it is not yet fully understood how map scales of the soil polygons affect modeling. Six soil polygonal data sets 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 data set (P005) was the most detailed and accurate soil database of the region. DNDC-simulated CH4 concentrations from input of the other five data sets were compared with that obtained by input of the P005 data set using metrics with the following outcomes: (i) Relative variations (VIV, %) of three indices, paddy soil area (APS, ha), annual mean CH4 emission (AME, Gg yr-1), and emission rate (RGE, kg ha-1 yr -1), calculated for 1: 200,000 (P02) data were all <5%; (ii) 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 (iii) 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.
All Science Journal Classification (ASJC) codes
- Soil Science