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Effects of soil map scales on simulating soil organic carbon changes of upland soils in Eastern China

Zhang, Liming, Liu, Yaling, Li, Xiaodi, Huang, Linbin, Yu, Dongsheng, Shi, Xuezheng, Chen, Hanyue, Xing, Shihe
Geoderma 2017
administrative area, bulk density, databases, models, pH, soil organic carbon, soil texture, uncertainty, upland soils, China
Digital soil maps with different scales have been widely used to quantify soil organic carbon (SOC) dynamics in the upland-crop fields. However, most of the regional SOC modeling often uses soil maps with a fixed scale, thus how varying map scales influence modeled SOC dynamics has rarely been quantified. Different map scales have different levels of details in describing the soil properties (e.g., soil texture, SOC content, bulk density, and pH) for a specific area, with the high resolution map having finer spatial representation. In this study, six digital upland soil databases of the northern Jiangsu Province in Eastern China at scales of 1:50,000 (P5), 1:250,000 (P25), 1:500,000 (P50), 1:1,000,000 (P100), 1:4,000,000 (P400), and 1:10,000,000 (P1000) have been used to drive the DeNitrification-DeComposition (DNDC, version 9.5) model to quantify SOC changes for the period of 1980–2009. This suite of scales selections covers all basic soil map scales in China. Our simulations indicate that the regional total SOC changes from 1980 to 2009 in the top layer (0–50cm) for upland soils using P5, P25, P50, P100, P400, and P1000 soil maps were 37.89, 34.91, 36.04, 37.05, 39.28 and 38.46 Tg C, respectively. Taking the regional total SOC changes based on the most detailed soil map, P5, as a reference, the relative deviation of those derived from the P25, P50, P100, P400, and P1000 were 7.86%, 4.86%, 2.21%, 3.67%, and 1.51%, respectively. Although the relative deviation of regional total SOC changes for most soil maps are low, disparities exist among SOC changes for different soil groups (i.e. 4.8 to 981%) and for administrative areas level (i.e. 0.32 to 151%). The results indicate that SOC estimates are significantly influenced by soil map scale. Lack of detailed soil information, like representation of many soil types and spatial variations in soil types, in coarse-scale maps result in the large uncertainties in the estimates of SOC changes. This study stresses the needs of detailed soil digital maps for accurate quantification of regional SOC changes.