An optimal data set approach for erosion-impacted soil quality
assessments---A case study of an agricultural catchment in the Mollisol
region of Northeast China
Abstract
Given that soil erosion is a primary cause of land degradation globally,
it has been receiving increasing attention in food production regions,
such as the Mollisol region in northeastern China. This study assessed
soil quality under soil erosion degradation using a novel optimal data
set (ODS) approach and a comparative minimum data set (MDS) approach
based on soil quality indices (SQIs) within an agriculture watershed in
Bin County, Heilongjiang Province, China. SQIs selection was contingent
on multiple soil factors. Soil erosion rates was determined using
cesium-137 technique. Relationships between soil quality and erosion or
deposition rates were also analyzed. Results showed that erosion
primarily drove soil redistribution, and soil quality grades were
generally extremely low (approx. 80% of sampling sites), based on
results from both the MDS and ODS approaches. However, soil quality
varied significantly between erosion and deposition sites, it increased
from upstream to midstream to downstream areas. Moreover, changes in
SQIs and erosion rates exhibited spatially opposite trends, indicative
of the impact that soil erosion has on soil quality, which was also
confirmed by comparing representative soil properties at soil erosion
and deposition sites. The good correlation between the MDS and ODS
approaches indicated the feasibility of the ODS approach in estimating
soil quality. Finally, the ODS approach is a cause-related method
applying a relatively strict indicator selection procedure, which,
compared to the MDS approach, could theoretically obtain more reliable
results. Further studies are nevertheless necessary to assess the
feasibility of this novel approach in other cases.