2.2. Research Approach
The research approach in this study consisted of five main steps. These are (i) identification of hydrophysical parameters which are inputs of MMF model, (ii) field surveys and informal discussions in order to identify representative soil sampling zones within the study catchment for soil sampling and analysis and also the corresponding vegetation cover conditions, (iii) application of empirical relations which are described by Morgan et al. to calculate intermediate MMF model inputs, (iv) application of geostatistic interpolation technique for spatial model inputs development, and (v) application of MMF model in GIS environment while estimating spatially distributed erosion outputs such as total overland transport capacity and soil detachment rate.
2.3. MMF Model Inputs Preparation
Input data for MMF model include rainfall (mm), land use, digital elevation model (DEM) for slope map derivation, soil texture, soil moisture content at field capacity (%w w−1), soil detachability index (g J−1), bulk density of soil (Mg m−3), cohesion of soil surface (KPa), soil moisture storage capacity (), effective hydrological top soil depth (EHD), and ratio of actual to potential evapotranspiration (/). Input data were collected from different sources such as field and laboratory determination, empirical relations, and the literature. Meteorological data such as rainfall and data were obtained from the meteorology station near the study area in 2009. Slope was derived from DEM developed from the topographic-map available at the Ethiopian Mapping Agency for Aksum area. The map was scanned, and contours and spot heights were digitized and tagged with elevation values in a GIS environment. The vector elevation map was converted to raster and projected using the Universal Transverse Mercator 37 North (UTM-37N) reference system.
Crop and soil parameters were collected from 117 plots scattered throughout the catchment considering major land use and cover types (bush land, protected area, cultivated, abandoned fields, grazing land, mixed-forest, and residential). Supervised classification and visual interpretation of the land satellite image of November 2009 was carried out for general land use and cover mapping. In addition to this, crop covers for the different crop types and their corresponding geographic coordinates were collected using field survey in September 2009. Data related to rainfall such as rainfall intensity, number of rainy days, and total rainfall were assumed to be similar in the study catchment. The reason for having only one weather station in the study catchment is that the Office of Meteorology Agency believed that rainfall variability is negligible within such a small area regardless of the differences in elevation. Rainfall intensity was assumed at 25 mm h−1 which is erosive for tropical climates such as Mai-Neguse catchment because no actual intensity data was found for the study catchment. Soil detachability index () (g J−1) was determined from the literature that corresponds to the soil texture observed in the study catchment.
2.4. Soil Sampling Zones and Sample Collection
In order to prepare MMF model soil related inputs, soil sampling that considered soil variability in the study catchment was executed. Sampling approaches that divided a field into small units (zone sampling) can capture variability and provide more information about soil-test levels compared with one composite sample collected from an entire large sampling area. To reduce the number of samples and sampling costs zone sampling is suggested to provide a way to group the spatial variability of soils while maintaining acceptable information about soil properties. Sampling by zone assumes that sampling areas are likely to remain temporally stable.
In this study, the zone sampling technique (divide a field into homogenous units that allow capturing variability and provide more information) was used to collect soil samples based on previous and existing knowledge of the soil and land use systems in the entire study catchment. The natural and management factors across the landscape that influenced soil properties spatial variability were considered while identifying the soil sampling zones. Three soil sampling zones that represented the soil quality (SQ) categories, long-term land use and soil management systems, and different erosion status sites in the catchment were identified using farmers’ opinions and researcher and extension experts’ judgment. The data that divided the catchment into the soil sampling zones was derived during the field reconnaissance surveys in June 2009. The SQ sampling zone was entirely used for arable land in the catchment whereas the other two sampling zones belonged to all the land use systems in the catchment. The sampling zones were further subdivided into different subsampling zones considering the variability within each zone and analytical costs.
The SQ sampling zone was divided into three subzones as high, medium, and low SQ based on farmers’ knowledge. They used indicators such as yield and yield component, soil depth, colour, and fertility conditions to divide into these subzones. The details on how local farmers’ classified soil into different SQ categories in the study catchment can be found in Tesfahunegn et al..
Eight representative long-term land use system sampling zones were identified based on farmers’ historical and present information acquired in the catchment. These are (i) natural forest; (ii) plantation of protected area; (iii) grazed land; (iv) teff (Eragrostis tef)-faba bean (Vicia faba) rotation; (v) teff-wheat (Triticum vulgare)/barley(Hordeum vulgare) rotation; (vi) teff monocropping; (vii) maize (Zea mays) monocropping; and (vii) uncultivated marginal land. The age of the systems varied from 5-6 years for teff monocropping and 20–30 years of maize monocropping system. Average age of the other systems was about 10 years except for the plantation, grazed land, and uncultivated marginal land systems with more than 15 years.
The erosion status-based sampling zone was divided into three subzones as stable, eroded, and deposition (aggrading) sites. Information from the local farmers, extension agents, and researcher’s (first author) observation on the level of topsoil depth (A-horizon), deposition, rills, pedestals, root and subsoil exposure, and gullies indicators were considered while identifying the three erosion-status sampling subzones. Those areas having A-horizon and minimum erosion indicators were considered as stable sites and the reverse of this as eroded sites. Depositional sites were also easily identified as they are mainly located in depression and flat areas with evidences of recent sediment deposition. In total, there were 14 subsampling zones across the erosion-status sites in the catchment for the soil samples collection. After doing all this identification and division, the soil sampling points in each subzone were located at the centre, considering soils in that point best represent the samples. Each sampling point was georeferenced as their distribution in the catchment is shown in Figure 2. The sampling distance was not regular, ranging from 40 to 180 m.
Figure 2: The distribution of soil sampling and vegetation cover points in the study catchment.
Soil samples were collected in June 2009. A total of 51 soil samples (3 subzones × 17 samples) were collected from the SQ based sampling zone. From the long-term land use systems, a total of 24 soil samples (8 subzones × 3 samples) were collected. It was also collected 42 soil/sediment samples (3 subzones × 12 samples in the catchment and 6 sampling points in the reservoir) from the erosion-status sites. The grand total of the composite samples collected across the sampling subzones was 117. Each composite soil sample was collected using 5–8 samples from each representative subsampling zone depending on the size and homogeneity of the sampling area (100–300 m2). All the composite soil samples were collected at the soil depth of 0–20 cm (the plough depth) since this is where most changes are expected to occur due to erosion, long-term land use, and soil management practices. The composite soil samples were pooled into a bucket and mixed thoroughly to homogenize it. Finally, a subsample of 500 g from the pooled composite samples was taken and soil samples were air dried and sieved to pass 2 mm mesh sieves before analysis for soil textures. On the other hand, two undisturbed soil samples were collected from each soil sampling point for bulk density and soil moisture determination. In addition, field level observation and measurement for parameters such as effective hydrological top soil depth (m), ground cover, and cover factor were carried out from the sampling points and georeferenced.
2.5. Soil Analysis
The soil samples collected in the soil sampling zones were determined for soil texture using the Bouyoucos hydrometer method, soil bulk density (BD) by the core method, and soil moisture content at field capacity (w w−1) by equilibrating the soil with water through capillary action in KR box.
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