Spatial Variability of Selected Soil Attributes under Agricultural Land Use System in a Mountainous Watershed, Ethiopia

In the Ethiopian Highlands, research projects were often measuring soil attributes of spatially structured point data but soil variability at a watershed scale is not clearly defined. This study was conducted to assess the correlation among selected soil attributes and to illustrate the spatial pattern and dependence of neighboring observations. The 53.7 km2?study watershed was divided into a 500 m by 500 m square grid using arcgis and at the center of each grid soil samples from 0 to 25 cm depth were collected within 184 locations. The descriptive statistics revealed available phosphorous (AP) had the largest coefficient of variation (CV = 104) while pH was the least variable. There was a positive link between elevation and SOC whereas bulk density (ρd) and pH indicated an inverse relationship with elevation and SOC. The value for nugget/sill of ρd, pH and elevation are less than 0.25, and depicts that it has strong spatial autocorrelation. The value for nugget/?sill of SOC, and TN found between 0.25 and 0.75, and indicate that they have moderate spatial?autocorrelation. With regard to AP, the value for nugget/sill is more than 0.75, which displays a weak?spatial autocorrelation. Semivariograms of ρd, pH and elevation were best fitted to Gaussian model whereas SOC, TN and AP were best fitted to exponential function. Generally, the study verified that soil measurements taken at the given scale through regular sampling interval were adequate to capture the spatial dependence of numerous initial soil assessments in the study watershed.

Predicting the spatial distribution of soil erodibility factor using USLE nomograph in an agricultural watershed,Ethiopia

Soil erosion in the northwestern Amhara region,Ethiopia has been a subject of anxiety,resulting in a major environmental threat to the sustainability and productive capacity of agricultural areas.This study tried to estimate soil erodibility factor(Kfactor)using Universal Soil Loss Equation(USLE)nomograph,and evaluate the spatial distribution of the predicted K-factor in a mountainous agricultural watershed.To investigate the K-factor,the 54 km2 study watershed was divided into a 500 m by 500 m square grid and approximately at the center of each grid,topsoil samples(roughly 10 to 20 cm depth)were collected over 234 locations.Sand,silt,clay and organic matter(OM)percentage were analyzed,while soil permeability and structure class codes were obtained using the United States Department of Agriculture(USDA)document.The resulting coefficient of variation(CV)of the estimated K-factor was 0.31,suggesting a moderate variability.Meanwhile,the value of nugget to sill ratio of K-factor was 0.32,which categorized as moderate spatial autocorrelation.Prediction accuracy and model fitting effect of the Gaussian semivariogram approach was best,suggesting that the Gaussian ordinary Kriging model was more appropriate for predicting Kfactor.The resulting value of the mean error(ME)was 0 and the mean squared deviation ratio(MSDR)was nearly 1,which indicates the Gaussian model was unbiased and reproduced the experimental variance sufficiently.The values of K-factor were smaller(0.0217 to 0.0188)in the northern part and gradually increased(0.0273 to 0.033 Mg h MJ^(-1)mm^(-1))towards the central and south of the study watershed.

Modeling streamflow and sediment using SWAT in Ethiopian Highlands

The coincidence of intensive rainfall events at the beginning of the rainy season and unprotected soil conditions after extreme dry spells expose the Ethiopian Highlands to severe soil erosion.Soil and water conservation measures(SWC)have been applied to counteract land degradation in the endangered areas,but SWC efficiency may vary related to the heterogeneity of the landscape.The Soil and Water Assessment Tool(SWAT)model was used to model hydrology and sediment dynamics of a 53.7 km^(2)watershed,located in the Lake Tana basin,Ethiopia.Spatially distributed stone bund impacts were applied in the model through modification of the surface runoff ratio and adjustment of a support practice factor simulating the trapped amounts of water and sediment at the SWC structure and watershed level.The resulting Nash-Sutcliffe efficiency(NSE)for daily streamflow simulation was 0.56 for the calibration and 0.48 for the validation period,suggesting satisfactory model performance.In contrast,the daily sediment simulation resulted in unsatisfactory model performance,with the NSE value of 0.07 for the calibration and–1.76 for the validation period and this could be as a result of high intensity and short duration rainfall events in the watershed.Meanwhile,insufficient sediment yield prediction may result to some extent from daily based data processing,whereas the driving runoff events and thus sediment loads occur on sub-daily time scales,probably linked with abrupt gully breaks and development.The calibrated model indicated 21.08 Mg/hm^(2)average annual sediment yield,which is far beyond potential soil regeneration rate.Despite the given limits of model calibration,SWAT may support the scaling up and out of experimentally proven SWC interventions to encourage sustainable agriculture in the Ethiopian Highlands.