Soil erodibility indices under different land uses in Ri-Bhoi district of Meghalaya (India)

Abstract

In absence of soil erosion plots for determination of erodibility index (K) for erosion models like Universal Soil Loss Equation (USLE) or Revised Universal Soil Loss Equation (RUSLE) to estimate soil erosion, empirical relations are used. In the present study, soil erodibility index was determined for entire Ri-bhoi district of Meghalaya based on soil physical and chemical properties through empirical relationship and presented in a map form. Dominant land uses of the district were identified through geo-spatial tools which were viz. agriculture, forest, jhum land and wasteland. Soil samples from surface depth (01–15 cm) were collected from areas of different dominant land uses. Twenty five sampling points were selected under each land use type and geo-coded them on the base map of Ri-bhoi district. Apart from K-index, Clay Ratio, Modified Clay Ratio and Critical Soil Organic Matter were also determined for understanding the effect of primary soil particles on erodibility. In agriculture land use system K-index values were found in the range of 0.08–0.41 with an average of 0.25 ± 0.02. In case of jhum, forest and wasteland these were in the range of 0.08–0.42 with an average of 0.20 ± 0.01; 0.09–0.40 with an average of 0.22 ± 0.02, and 0.10–0.34 with an average value of 0.23 ± 0.02, respectively. Clay ratio (2.74) and Modified clay ratio (2.41) were observed to be higher in forest LUS, lower clay ratio (1.97) and modified clay ratio (1.81) were found in the wasteland indicating erosion susceptibility in forested area. The values of Critical Level of Organic Matter (CLOM) for the district ranged from 4.72 to 16.56. Out of 100 samples, only one sample had CLOM value less than 5 and rest 99 samples had values more than 5 indicating that the soils of the district had moderate to stable soil structure and offer resistance to erosion. All the indices values of geo-coded points were then interpolated in the Arc-GIS environment to produce land use based maps for Ri-bhoi district of Meghalaya. As K-index is a quantitative parameter which is used in models, the index can be then interpolated for estimation of soil erosion through USLE or RUSLE for any given situation.

Modelling Alternatives for Highland Soil Structural Degradation and Erodibility, Bui Plateau, Cameroon

“…Factors that influence aggregate stability are important in evaluating the ease with which soils erode by water and/or wind, the potential of soils to crust and/or seal, soil permeability, quasi-steady state infiltration rates and seedling emergence and in predicting the capacity of soils to sustain long-term crop production [4]. Apart from quantitative indices for soil erodibility to estimate soil erosion some other indices are also used by researchers to understand the proneness of soil to erosion [29]. The soil aggregate stability index (ISS) developed by [30] have been widely used to assess soil structural degradation.…”

“…Critical level of organic matter (CLOM) is also an indicator of erosion susceptibility [29]. Its estimation is If the value of CLOM is less than 5%, it is indicated that soil loses its structure and becomes highly susceptible to erosion.…”

Landslides and Gullies Interact as Sources of Lake Sediments in a Rifting Context: Insights from a Highly Degraded Mountain Environment

“…The clay ratio of soil, calculated as the percentage of sand and silt fractions over the percentage of clay, is used as an index of soil erodibility [70], with low clay-ratio soils considered to have a low erodibility and higher-ratio soils to be more erodible [70]. Except in the Sile, where the clay ratio is increasing as the GLDs decrease, no clear relation between clay ratio and density was observed in the other three catchments (Appendix A Figure A3).…”

The Physicochemical Properties of Deposited Sediments at the Maruba Dam Reservoir Inlet, Machakos County, Kenya

“…e dried-up part of the reservoir was designated as the study area, where sediment samples were picked from ten different locations (Figure 2). e sampling points were selected randomly and geo-referenced using a hand-held Garmin GPSMAP 65s global positioning system (GPS) gadget [34]. Undisturbed soil samples were collected using core rings, whereas about two kilograms of disturbed soil was collected in appropriate bags.…”