Integrated use of GIS, RS and USLE model for LULC change analysis and soil erosion risk mapping in the Lake Hawassa Watershed, Southern Ethiopia

Soil erosion is a worldwide problem leading to loss of nutrient rich top soil resulting in reduction of agricultural productivity that threatens the livelihood of agrarian societies. Assessment of soil loss due to water-induced erosion using Models is essential to quantify and map erosion prone areas for possible application of soil conservation measures. In the current study, GIS, RS, and USLE model were integrated with the aim to quantify LULC classes, estimate soil loss rates, and identify priority areas for conservation in the Lake Hawassa Watershed for the two temporal instants, 1975 and 2020. The use of thematic recoding and model maker during LULC classification process has improved the accuracy of thematic classes, producing more than 89% for both classified images. The LULC change analysis showed that agricultural land and built-up area expanded by 0.44% and 15.26% per annum, respectively over the last 45 years. The declines in vegetation cover coupled with steep slopes have contributed to the increase in soil loss from 1975 to 2020 by 65%. The model estimated annual soil erosion rate in 1975 that ranged from nil to 158.77 t ha(-1 )yr(-1) with a mean annual soil loss rate of 25.16 t ha(-1 )yr(-1). Likewise, the annual soil loss estimated for the year 2020 varied from zero to 262.48 t ha(-1 )yr(-1) with a mean annual soil loss rate of 28.20 t ha(-1 )yr(-1). Generally, a total of 23,580.59 and 27,783.35 tons of soil have been lost per annum for the year 1975 and 2020, respectively, which is a direct reflection of vegetation clearance. The identified highest three severity classes combined accounted for 50.54% in 1975 and 55.40% of the entire soil loss in 2020 and these losses occurred on areas less than 2% in both 1975 and 2020 periods. Besides, 23.48% and 31.04% of soil loss rates exceeded the established tolerable limit of soil loss for the study area. The integrated use of USLE model, GIS and RS have identified erosion risk areas that could help apply conservation measures.