Soil Erosion Prediction Using Morgan-Morgan-Finney Model in a GIS Environment in Northern Ethiopia Catchment

Abstract

Even though scientific information on spatial distribution of hydrophysical parameters is critical for understanding erosion processes and designing suitable technologies, little is known in Geographical Information System (GIS) application in developing spatial hydrophysical data inputs and their application in Morgan-Morgan-Finney (MMF) erosion model. This study was aimed to derive spatial distribution of hydrophysical parameters and apply them in the Morgan-Morgan-Finney (MMF) model for estimating soil erosion in the Mai-Negus catchment, northern Ethiopia. Major data input for the model include climate, topography, land use, and soil data. This study demonstrated using MMF model that the rate of soil detachment varied from <20 t ha−1y−1to >170 t ha−1y−1, whereas the soil transport capacity of overland flow (TC) ranged from 5 t ha−1y−1to >42 t ha−1y−1. The average soil loss estimated by TC using MMF model at catchment level was 26 t ha−1y−1. In most parts of the catchment (>80%), the model predicted soil loss rates higher than the maximum tolerable rate (18 t ha−1y−1) estimated for Ethiopia. Hence, introducing appropriate interventions based on the erosion severity predicted by MMF model in the catchment is crucial for sustainable natural resources management.

Review on Contribution of GIS and RS for Soil Degradation Assessment in Ethiopia

“…hardware and software, data and skilled man) and financial limitation. The spatial distribution of the hydrophysical parameter is the source of evidence about soil erosion procedure and designing appropriate soil and water conservation, it can be emerged by GIS (Tesfahunegn et al, 2014).…”

“…In other views, improper LULCC is directly or indirectly connected with the most commonly known of USLE or RUSLE parameters. They also called spatial variability and they are a key determinate of soil erosion risks (Tesfahunegn et al, 2014). Many scholars confirmed that land degradation in form soil erosion influenced by biophysical factors most of them are included in USLE or RUSLE factors.…”

“…About 1.5 billion tons of soil loss registered annually in Ethiopia (FAO, 1986). In highland parts, the productive potential of the land is reducing by 2.2% per year (Tesfahunegn et al, 2014;FAO, 1986). Soil erosion has both effects; reduce crop yield and destroy irrigation channels (Gelagay and Minale, 2017).…”

Short-term effects of tillage practices on soil properties under Tef [Eragrostis tef (Zucc. Trotter)] crop in northern Ethiopia

“…The sampling was focused mainly on this plow layer because this is the depth where changes in most soil properties are expected to occur due to short-term soil management practices (Tesfahunegn et al, 2014). In addition to this, tef root system is shallow especially at the early stage of the crop and its dense fibrous roots are generally concentrated at the topsoil depth for using soil moisture and nutrients (Ketema, 1993).…”

GIS‐based modelling of soil erosion processes using the modified‐MMF (MMMF) model in a large watershed having vast agro‐climatological differences

“…Due to the simplicity, flexibility and strong physical base, several researchers have implemented the MMF (Morgan et al ., ) and the revised‐MMF(RMMF) (Morgan, ) models for estimating annual soil loss in a wide range of environment across the world, such as in Malaysia (Morgan and Finney, ), Indonesia (Besler, ), Nepal (Shrestha, ), the Rocky Mountains of the USA (Morgan, ), Nepal (Morgan, ), Kenya and Tanzania (Vigiak et al ., ), Hungary (Hudek et al ., ), Spain (López‐Vicente and Navas, ; López‐Vicente et al ., , ), China (Li et al ., , ) and Italy (Svorin, ); Ethopia (Tesfahunegn et al ., ); Thailand (Shrestha et al ., ); India (Jasrotia and Singh, ; Pandey et al ., ; Kothyari et al ., ; Korada and Vala, ).…”