Assessing aggregate stability of soils under various land use/land cover in a watershed of Mid-Himalayan Landscape

• Main Authors: Abhisek Kumar Singh, Suresh Kumar, Justin George Kalambukattu
• Format: Article
• Language: English
• Published: Federation of Eurasian Soil Science Societies 2019-04-01
• Series: Eurasian Journal of Soil Science
• Subjects: Land Use/ land cover; Mid-Himalaya; soil aggregate stability; terrain parameters.
• Online Access: http://ejss.fesss.org/10.18393/ejss.514319

Soil aggregate stability is considered as an important indicator of soil quality in the landscapes witnessing land degradation due to soil erosion by water. An increase in anthropogenic activities over the period of time has accelerated soil erosion that necessitated need to assess soil aggregate stability in various land use/land cover in the hilly and mountainous landscape. The study investigated the soil aggregate stability of surface soils in different land use/ land cover classes, hillslope unites as well as in respect to terrain parameters in the watershed. The watershed located in mid- Himalayan region of Tehri Garhwal district, Uttarakhand, India covering an area of 196 ha. The elevation of the watershed ranges from 1200 m to 1927 m. CartoDEM was used to derive terrain parameters i.e., aspect, slope and terrain indices like Terrain Wetness Index (TWI) and Stream Power Index (SPI) of the watershed. Among the various land use /land cover classes, aggregate stability in crop land was found to be in the range of 0.16 (lower hillslope) to 0.28 (mid hillslope), in forest ranged from 0.18 (mid hillslope) to 0.28 (upper hillslope) and in dense scrub ranged from 0.16 (middle slope) to 0.32 (upper/lower hillslope). The aggregate stability was further analyzed in relation with various soil (carbon, nitrogen, sand, silt, clay and pH) and terrain (slope, elevation, TWI and SPI) variables. Among these variables soil carbon, nitrogen, elevation, TWI and SPI were found to have moderate to high degree of correlation with soil aggregate stability. Prediction model developed by using the various significant soil and terrain parameters were found to be more effective (r2 = 0.50) than the models developed using only soil parameters (r2= 0.36) or only terrain parameters (r2= 0.37).