Application of Revised Universal Soil Loss Equation (Rusle) Model to Assess Soil Erosion in “Kalu Ganga” River Basin in Sri Lanka

Abstract

Soil erosion is one of the main forms of land degradation. Erosion contributes to loss of agricultural land productivity and ecological and esthetic values of natural environment, and it impairs the production of safe drinking water and hydroenergy production. Thus, assessment of soil erosion and identifying the lands more prone to erosion are vital for erosion management process. Revised Universal Soil Loss Equation (Rusle) model supported by a GIS system was used to assess the spatial variability of erosion occurring at Kalu Ganga river basin in Sri Lanka. Digital Elevation Model (30 × 30 m), twenty years’ rainfall data measured at 11 rain gauge stations across the basin, land use and soil maps, and published literature were used as inputs to the model. The average annual soil loss in Kalu Ganga river basin varied from 0 to 134 t ha−1 year−1 and mean annual soil loss was estimated at 0.63 t ha−1 year−1. Based on erosion estimates, the basin landscape was divided into four different erosion severity classes: very low, low, moderate, and high. About 1.68% of the areas (4714 ha) in the river basin were identified with moderate to high erosion severity (>5 t ha−1 year−1) class which urgently need measures to control soil erosion. Lands with moderate to high soil erosion classes were mostly found in Bulathsinghala, Kuruwita, and Rathnapura divisional secretarial divisions. Use of the erosion severity information coupled with basin wide individual RUSLE parameters can help to design the appropriate land use management practices and improved management based on the observations to minimize soil erosion in the basin.

GIS and RS Based Soil Erosion Modelling in Sri Lanka: A Review

“…These two methods may be suitable for the Sri Lankan conditions since the constants used in these two equations have been developed under tropical, sub-tropical, and Sri Lankan conditions. Furthermore, studies carried out by Jayarathne et al (2010); Wijesundara et al (2018), and Panditharathne et al (2019) show that one mapping tool of R factor is the Kriging tool in ArcGIS TM and QGIS TM and the other method is Inverse Distance Weighted (IDW) in ArcGIS TM and QGIS TM environment. However, with carrying out of cross-validation, it has been revealed that the IDW method has provided the least error for mapping rainfall variability and R factor over the Kriging method (Panditharathne et al, 2019).…”

“…Thus, K values of above ~85% of studies are more accurate while K values of Dissanayake et al (2019) and Wijesundara et al (2018) are the most accurate according to the explanation by Renard et al (1991). (Wijesekara and Samarakoon, 2001) From available literature of previous studies (Joshua, 1977) 02 (Senanayake et al, 2013) From available literature of previous studies (Bandara and Somasiri, 1991) (Zijister, 1989) 03 (Jayarathne et al, 2010) From available literature of previous studies 04 (Senanayake et al, 2020) From available literature of previous studies (Fayas et al, 2019) (Senanayake et al, 2013) (Wijesekara and Samarakoon, 2001) 05 (Dissanayake et al, 2019) Nomography is used to compute the values of K based on soil properties (Wischmeier and Smith, 1978) (Ganasri and Ramesh, 2016) (Mapa et al, 2010) 06 (Panditharathne et al, 2019) From available literature of previous studies (Jayarathne et al, 2010) (Wijesundara et al, 2018) (Fayas et al, 2019)…”

“…Where, S is the slope gradient in percentage 04 (Wijesekara and Samarakoon, 2001) 05 (Panditharathne et al, 2019)…”

“…These undesirable consequences of soil erosion lead to degrading agricultural lands and natural environments rapidly (Shougang and Ruishe, 2014). Thus, soil erosion is listed and classified as a severe environmental issue that the world is facing (Panditharathne et al, 2019). As explained by Castro Filho et al (2001), loss of soil due to erosion is found to be the main causative factor of land degradation in the world while 85% of land degradation is occurred due to the erosion process which reduced arable lands up to 17% (Singh and Panda, 2017;Wijesundara et al, 2018).…”

“…This results in increasing the expenses for fertilizers and ultimately lands are abandoned (Singh and Panda, 2017) due to nutrient loss of arable lands, increasing the runoff by exposed impermeable soil and reducing the retained water availability (Ganasri and Ramesh, 2016). Moreover, Soil erosion paves the way to loss of esthetic values of the natural environment (Panditharathne et al, 2019) and habitat losses take place due to soil erosion while habitat loss is considered as one of the most prominent causes of biodiversity degradation (Dissanayake et al, 2019). Furthermore, as explained by Jayasekara and Kadupitiya (2018), due to the existence of long term soil erosion in drainage basins, the water storage capacity of reservoirs also gets reduced due to the delivery of sediments into reservoirs.…”