Abstract
Understanding topography effects on soil properties is vital to modelling landscape hydrology and establishing sustainable on-field management practices. This research focuses on an arable area (117 km2) in Southwestern Ethiopia where agricultural fields and bush cover are the dominant land uses. We postulate that adapting either of the soil data resources, coarse resolution FAO-UNESCO (Food and Agriculture Organization of the United Nations Educational, Scientific and Cultural Organization) soil data or pedo-transfer functions (PTFs) is not reliable to indicate future watershed management directions. The FAO-UNESCO data does not account for scale issues and assigns the same soil property at different landscape gradients. The PTFs, on the other hand, do not account for environmental effects and fail to provide all the required data. In this regard, mapping soil property spatial dynamics can help understand landscape physicochemical processes and corresponding land use changes. For this purpose, soil samples were collected across the watershed following a gridded sampling scheme. In areas with heterogeneous topography, soil is spatially variable as influenced by land use and slope. To understand the spatial variation, this research develops indicators, such as topographic index, soil topographic wetness index, elevation, aspect, and slope. Pearson correlation (r), among others, was used to investigate terrain effects on selected soil properties: organic matter (OM), available water content (AWC), sand content (%), clay content (%), silt content (%), electrical conductivity (EC), moist bulk density (MBD), and saturated hydraulic conductivity (Ksat). The results show that there were statistically significant correlations between elevation-based variables and soil physical properties. Among the variables considered, the ‘r’ value between topographic index and soil attributes (i.e., OM, EC, AWC, sand, clay, silt, and Ksat) were 0.66, 0.5, 0.7, 0.55, 0.62, 0.4, and 0.66, respectively. In conclusion, while understanding topography effects on soil properties is vital, implementing either FAO-UNESCO or PTFs soil data do not provide appropriate information pertaining to scale issues.
Highlights
Soils vary widely as a function of their position on the landscape [1,2,3] and agricultural management, land use, and cultivation intensity [4,5]
92% of the catchment was covered with three soil types: chromic vertisol (33.3%), chromic luvisol (30.2%) and pellic vertisol (28.2%)
The results show that there was a spatial correlation between slope, sand, silt, clay, available water content (AWC), electrical conductivity (EC), organic matter (OM), and moist bulk density (MBD)
Summary
Soils vary widely as a function of their position on the landscape [1,2,3] and agricultural management, land use, and cultivation intensity [4,5]. 2020, 4, 1 tool used by pedologists in soil classification and mapping [6]. To account for these unpredicted soil property spatial variation and relationships, studies [7] recommend employing geostatistical analysis tools. Ceddia et al [6] highlighted that soil physical attributes are related to topography over a landscape and it was viable to use cokriging point iteration with topography as an auxiliary variable. The spatial variation of soil properties can be determined using pedo-transfer functions (PTFs) [9]
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