An automated method for mapping physical soil and water conservation structures on cultivated land using GIS and remote sensing techniques

An efficient and reliable automated model that can map physical Soil and Water Conservation (SWC) structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ArcGIS®, ERDAS IMAGINE®, and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures: (1) a high-pass spatial filter algorithm was applied to detect linear features, (2) morphological processing was used to remove unwanted linear features, (3) the raster format was vectorized, (4) the vectorized linear features were split per hectare (ha) and each line was then classified according to its compass direction, and (5) the sum of all vector lengths per class of direction per ha was calculated. Finally, the direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Therefore, the model is useful for predicting and mapping physical SWC structures areas across diverse areas.     

Smallholder Farmers’ perception and adaptation to climate variability and change in Fincha sub-basin of the Upper Blue Nile River Basin of Ethiopia

GeoJournal - Climate variability and change make agricultural sector a risky venture for smallholders’ farmers. This paper presents an assessment of smallholder farmers’ perceptions of...     

Spatial and temporal variability of summer rainfall over Ethiopia from observations and a regional climate model experiment

The spatial and temporal variability of rainfall over Ethiopia during the summer (JJAS) season is studied using observations (both station and satellite based) and model simulation data. The simulation dataset is generated using the fourth version of the International Center for Theoretical Physics Regional Climate Model (RegCM4) for the period 1989–2005. Ethiopia is first divided into 12 homogeneous regions using criteria including rotated empirical orthogonal function (REOF), spatial correlation, seasonal cycles, and topographical features. Spatially averaged observed and simulated rainfall time series are then generated and analyzed for each region. Standardized rainfall anomalies of the observations and the simulated data are highly correlated over the northern, western, northeastern, central, and southwestern regions, while a weak correlation is found over the border regions of the country. The dominant modes of rainfall variability are identified using REOF, while time–frequency variations of different dominant modes are described by wavelet analysis. The first leading patterns of rainfall and upper wind (averaged between 100 and 300 hPa) are highly correlated and exhibit similar features between simulation and observations over the northern, western, southwestern, and eastern regions of Ethiopia. The second loading pattern of rainfall and the first loading pattern of low-level wind (averaged between 850 and 1,000 hPa) exhibit a dipole structure across the southwestern and northeastern regions of the country. The dominant signals in the first rotated principal component (RPC) of rainfall and upper level wind fields show a period of 4–5 and 2–3 years, while the dominant signals in the second RPC show a period of 2–3 years at a 0.05 significance level. The correlations of significant RPCs across gauge, gridded, and model rainfall fields with that of low and upper level winds show the presence of a significant relationship (correlation exceeding ～0.6). Overall, the RegCM4 shows a good performance in simulating the spatial and temporal variability of precipitation over Ethiopia.     

Managing crop stubble during fallow period for soil water conservation: field experiment and modelling

In the arid and semi-arid environments where the rainfall is limited and variable, fallow period soil moisture conservation using stubble is one of the ways of increasing the soil moisture required for crop sowing and development. However, the effectiveness of moisture conservation using stubble depends on the paddock management, soil water content, and rainfall characteristics. To assess the effect of stubble rate and amount of rainfall on the soil moisture conservation, a two-season field experiment was conducted using four stubble rates (0, 2, 4, 6 t/ha) and two water supply amounts. The soil water dynamics was also analysed using a validated Agricultural Production System Simulator (APSIM). In the relatively wet summer season with a high initial soil water content, the amount of water stored in the 2, 4, and 6 t/ha stubble rate treatment plots was higher than that of the bare plots by 10.4, 15.9, and 17.8 mm, respectively. However, in the summer season with a relatively high amount of in-season water input and low initial soil water content, the soil water storage was increased by 29.4, 35.6, and 43.0 mm, respectively. Comparing the results of the two seasons, the highest increase was observed for the 2 t/ha stubble rate. The amount of conserved soil moisture was found to be the highest when the soil profile water content at the start of the summer-fallow period is low and the amount of rain during the summer season is high. The good agreement between the measured and APSIM-simulated soil water contents (R ² = 0.812), indicates that the model can be used to assess the soil water dynamics under a fallow condition. The APSIM-simulated soil water balance using the weather data of the past 100 years indicated that in a year with low start-of-fallow period soil water content, a 6 t/ha stubble rate can increase the end-of-fallow period soil moisture by up to 60 %.     

Impact of precipitation and temperature changes on hydrological responses of small-scale catchments in the Ethiopian Highlands

The hydrological response of catchments with different rainfall patterns was assessed to understand the availability of blue and green water and the impacts of changing precipitation and temperature in the Ethiopian Highlands. Monthly discharge of three small-scale catchments was simulated, calibrated, and validated with a dataset of more than 30 years. Different temperature and precipitation scenarios were used to compare the hydrological responses in all three catchments. Results indicate that runoff reacts disproportionately strongly to precipitation and temperature changes: a 24% increase in precipitation led to a 50% increase in average annual runoff, and an average annual rainfall–runoff ratio that was 20% higher. An increase in temperature led to an increase of evapotranspiration and resulted in a decrease in the rainfall–runoff ratio. But a comparison of combined results with different climate change scenarios shows that downstream stakeholders can expect a higher share of available blue water in the future.