UNIVERSAL SOIL LOSS EQUATION (USLE) BASED PLOT SCALE STUDY ON SOIL EROSION

Abstract

Soil erosion is recognised world-wide as a leading cause of land degradation, loss of soil productivity and poor water quality. In India about 5,334 million ton of soil is lost every year. To plan for the soil conservation measures, the accurate prediction of soil loss from a watershed is essential. Among the numerous erosion and soil erosion models, the Universal Soil Loss Equation (USLE), Modified Universal Soil Loss Equation (MUSLE) and Revised Universal Soil Loss Equation (RUSLE) are some of the widely used empirical soil loss equation for prediction of soil loss from a watershed, agricultural land, forest land and construction area. The essential drawback of USLE. RUSLE equations are that they are based on average annual value of its parameter and the regional data of specific area. So their applicability to small temporal scale and other area having different climate, soil and land use is questionable. This study on soil erosion was conducted on 12 plots of size (22m*5m) in size, located at Toda Kalyanpur near Roorkee. Altogether 35 small and large size natural rainfall data were recorded during the study period with a minimum rainfall of 2mm and a maximum rainfall of 1 78mm, runoffs from these plots were obtained for I 9natura1 storm events during the study period from early June 2013 to the end of March 2014. Only 10 rainstorms were such that sediment yield samples could be collected. Similarly, experiments were conducted for 5 artificial rainfall events, and both runoff and sediment yield were measured for these events. The field and laboratory analysis indicated the soil to range from sandy loam to loam. Although the study was carried out with limited instrumentation, limited no. of observations in limited time, significant correlations were observed between the predicted and observed sediment yield for each of 12 plots planted with different crops (Sugarcane, Maize, Black gram. Lentil. Gram. Wheat and Fallow) on different slopes. Among the 30 different combination of land use and slope. 3 of the combination has correlation coefficient greater than 0.9 (i.e. Wheat. 5% slope; Blackram.l% slope; Fallow, 1% slope), 8 of the combination has correlation coefficient greater than 0.8 (i.e. Maize, 5% slope; Blackgram,5% slope; Maize-Lentil, 5%slope; Fallow-Wheat.5%slope: Sugarcane, 3%slope; Blackgram-gram. 3%slope: Black gram. 3% slope; Fallow-Wheat,3%slope),7of the combination has correlation coefficient greater than 0.6 . 3 of combination have correlation coefficient greater than 0.5 and - rest has correlation coefficient less than 0.5 for natural storm event. The correlations were more promising for natural events than artificial events. The data points plotted between observed sediment yield and predicted sediment yield were very near the best-fit line indicating better efficiency of the MUSLE in predicting sediment yield from single storm.