Extent And Volume Of Soil Loss Using Rusle Model In Agulu–Nanka–Oko And Ekwulobia Gully Erosion Complexes Of Anambra State, South Eastern Nigeria

Abstract

Over 65% of the soil on earth is said to have displayed degradation phenomenon as a result of soil erosion, salinity and desertification (Abegunde, et al., 2006). Anambra State is known to be under severe erosion problems with the Agulu-Nanka-Oko and Ekwulobia gully as the epicenter of gully development in the state. The study attempts to utilize the revised version of the Universal Soil Loss Equation (RUSLE), combined with remote sensing and GIS technology to estimate the extent of soil loss so that planning of management techniques can be suggested. GIS data layers including, rainfall erosivity (R), soil erodability (K), slope length and steepness (LS), cover management (C) and conservation practice (P) factors were computed to determine their effects on average annual soil loss in the study area. The classified soil loss map shows that 4.92% of the total area has soil loss between 0.432 – 12.473 (ton/ha/yr) followed by 49.93% of the total area with rate of soil erosion between 12.474 – 30.534 (ton/ha/yr). Next is 16.88% of the total area with average annual soil loss between 30.535 – 53.412 (ton/ha/yr). Other soil loss categories cover 27.33% and 0.94% of total area with average annual soil loss between 53.413 – 88.330 (ton/ha/yr) and between 88.881 – 153. 953 respectively. The total area of soil loss is 599.17 (Km2). It is therefore recommended that Sustainable solutions which increase vegetation cover and curtail soil erosion should be integrated in the recovery plan for the study area. To reduce soil loss, intervention should be focused on slope length and steepness factor (LS), Crop Management Factor (C) and Support Practice (P) factors as the Soil Erodibility (K) and Rainfall Erosivity (R) factors cannot be changed. It is necessary to educate and empower the communities of the need for vegetation, soil and water conservation.

Keywords: Soil erosion, soil loss, RUSLE, Remote sensing and GIS