Terrain Analysis as a Criterion for Soil Attributes at Wadi Al-Shobeity, Northwestern Coast, Egypt

Document Type : Original Article

Author

Pedology Dept., Water resources and desert land division, Desert Research Center, Egypt.

Abstract

Pedology has developed recently to include quite precise quantified methodologies for soil spatial distribution. These are generally based on the hypothesis that soil properties have distributed spatially over landscape through repeated patterns according to soil forming factors and processes. This study is based on the concept that catenary soil evolution is characterizing watershed basins in response to terrain features which guide drained water movement through or over land surface and consequently affect sediments and solutes transport and redistribution. Studied location occupies 1920 feddans representing the catchment basin of AlShobeity watershed which locate 68 km west of Mersa Matroh. As a toposequence, soils have been surveyed through the observation of thirty soil profiles, along a couple of parallel transects crossing the existing geomorphological units starting from southern plateau towards northern coastal plain. According to field survey and laboratory analysis eight soil mapping units have been differentiated with respect to profile depth, texture, and salinity. Accordingly, about 59.77% of the area is dominated by moderately deep soils, whereas deep and very deep ones covering only 21.6 % of the whole area. Most soils (88.4%) are sandy loam to sandy clay loam in texture. The area is dominated by slightly - to moderately saline soils, only 26.7% of the entire area is considered saline. DEM was generated over grid resolution 100 m, and then used to calculate primary topographic attributes which include slope, aspect, specific catchment area, maximum flow path, and profile curvature. Secondary terrain indices including wetness, stream power, and sediment transport indices were calculated and mapped. Results revealed that elevations of Al-Shobeity watershed decrease downward from 80 to 5 m ASL, in which surface slopes range between 0.3 and 8.4 %. Gentle slopes (1-2%) cover 52.8 % of the ground surface while slopped sites (510%) were found covering only 8.4 % of the entire area. The basin is classified into three classes according to wetness index where 25.8 % of the area is considered "saturation zone". Generally, sediment transport and stream power indices have non significant values except for some scattered zones over 17.5% and 21.6%, respectively, of the total area. Correlation matrix showed that slope is the highest correlated primary terrains attribute orderly with profile depth, salinity, sand, silt, clay, pH, and lime, where correlation coefficient ranged between 0.58 and 0.81. While wetness index was the most correlated secondary terrain quality orderly with sand, profile depth, clay, silt, and salinity, where correlation
coefficient ranged from 0.51 – 0.77. Deep and very deep soils don't exist unless slopes and wetness index were less than 1% and more than 5, respectively. Moreover, saline soils don't occur at slopes and wetness index more than 2% and less than 5, respectively. Stepwise linear regression analysis was used to relate numerically topographic attributes with soil properties. Significant regression coefficients were achieved at 0.01 significance level for soil depth, salinity, sand, and clay, respectively, as 0.68, 0.48, 0.55, and 0.40. Spatial distribution of estimated soil depth, texture, and salinity were mapped based on topographic attributes, and then compared with actual soil properties. Reasonable similarity degree was achieved between measured and estimated soil spatial distribution based on low standard error of prediction, in addition to finding out details and variations inside each soil mapping unit. This study indicate that the terrain-based technique carried out in Al-Shobeity watershed basin has shown a rather successful results concerning the estimation of soil attributes for more than 75 % of the total tested sits. Extrapolation trials may be done to enhance detection of soil variation at traditional maps which permit minimization of costs, efforts, and time.

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