ALBERT

Description: Paddy soils support important croplands in many parts of the world, especially in Asia. A thorough understanding of nitrogen (N) in Chinese paddy soils would be helpful to comprehend N cycling on farms from a national perspective. The N storage and density of paddy soils in China were evaluated employing 1490 soil profiles and a map of Chinese soils at a scale of 1:1 000 000. Results showed that the mean N density of paddy soils at 0–100 cm was 1240.0 g/m3, with N storage of 569.0 Tg. Paddy soil N density varies with different soil-water regime. In fact, waterlogged conditions can enhance paddy soil N content. Different rotation systems and various fallow systems also can affect paddy soil N density. There are significant relationships of N between both SOC and sand content. But the sensitivity of paddy soil N to climate was weak because of human activity. While this GIS-based analysis is a relatively coarse evaluation of the database, it does provide the first quantitative assessment of paddy soils N storage across China using commonly available digital databases.

Description: Matching soil grid unit resolution with polygon unit map scale is important to minimize uncertainty of regional soil organic carbon (SOC) pool simulation as their strong influences on the uncertainty. A series of soil grid units at varying cell sizes were derived from soil polygon units at the six map scales of 1:50 000 (C5), 1:200 000 (D2), 1:500 000 (P5), 1:1 000 000 (N1), 1:4 000 000 (N4) and 1:14 000 000 (N14), respectively, in the Tai lake region of China. Both format soil units were used for regional SOC pool simulation with DeNitrification–DeComposition (DNDC) process-based model, which runs span the time period 1982 to 2000 at the six map scales, respectively. Four indices, soil type number (STN) and area (AREA), average SOC density (ASOCD) and total SOC stocks (SOCS) of surface paddy soils simulated with the DNDC, were attributed from all these soil polygon and grid units, respectively. Subjecting to the four index values (IV) from the parent polygon units, the variation of an index value (VIV, %) from the grid units was used to assess its dataset accuracy and redundancy, which reflects uncertainty in the simulation of SOC. Optimal soil grid unit resolutions were generated and suggested for the DNDC simulation of regional SOC pool, matching with soil polygon units map scales, respectively. With the optimal raster resolution the soil grid units dataset can hold the same accuracy as its parent polygon units dataset without any redundancy, when VIV 〈 1% of all the four indices was assumed as criteria to the assessment. An quadratic curve regression model y = −8.0 × 10−6x2 + 0.228x + 0.211 (R2 = 0.9994, p 〈 0.05) was revealed, which describes the relationship between optimal soil grid unit resolution (y, km) and soil polygon unit map scale (1:x). The knowledge may serve for grid partitioning of regions focused on the investigation and simulation of SOC pool dynamics at certain map scale.