### abstract

- Daily runoff from 27 plots (5 m ? 2 m) recorded during two rainy seasons in the Tigray highlands (Ethiopia) were analysed together with daily rainfall to calculate runoff curve numbers for hillslopes covered by semi-natural vegetation in varying stages of vegetation restoration. Curve number model parameters were derived using a least squares fitting procedure on the collected rainfall-runoff datasets. Curve numbers varied from 29 to 97. Land use type was an important explanatory factor for the variation in curve numbers, whereas hydrologic soil group was not. Curve numbers were negatively correlated with vegetation cover. Taking into account antecedent soil moisture conditions did not improve runoff prediction using the curve number method. As runoff prediction was less accurate in areas with low curve numbers, two separate regression functions relating curve numbers with vegetation cover were proposed for different land use types
- Daily runoff from 27 plots (5 m Ã° 2 m) recorded during two rainy seasons in the Tigray highlands (Ethiopia) were analysed together with daily rainfall to calculate runoff curve numbers for hillslopes covered by semi-natural vegetation in varying stages of vegetation restoration. Curve number model parameters were derived using a least squares fitting procedure on the collected rainfallrunoff datasets. Curve numbers varied from 29 to 97. Land use type was an important explanatory factor for the variation in curve numbers, whereas hydrologic soil group was not. Curve numbers were negatively correlated with vegetation cover. Taking into account antecedent soil moisture conditions did not improve runoff prediction using the curve number method. As runoff prediction was less accurate in areas with low curve numbers, two separate regression functions relating curve numbers with vegetation cover were proposed for different land use types
- Daily runoff from 27 plots (5 m × 2 m) recorded during two rainy seasons in the Tigray highlands (Ethiopia) were analysed together with daily rainfall to calculate runoff curve numbers for hillslopes covered by semi-natural vegetation in varying stages of vegetation restoration. Curve number model parameters were derived using a least squares fitting procedure on the collected rainfall-runoff datasets. Curve numbers varied from 29 to 97. Land use type was an important explanatory factor for the variation in curve numbers, whereas hydrologic soil group was not. Curve numbers were negatively correlated with vegetation cover. Taking into account antecedent soil moisture conditions did not improve runoff prediction using the curve number method. As runoff prediction was less accurate in areas with low curve numbers, two separate regression functions relating curve numbers with vegetation cover were proposed for different land use types
- Daily runoff from 27 plots (5m x 2m) recorded during two rainy seasons in the Tigray highlands (Ethiopia) were analysed together with daily rainfall to clculated runoff curve numbers for hillslopes covered by semi-natural vegetation in varying stages of vegetation restoration. Curve numbers model parameters were derived using a least squares fitting procedure on the collected rainfall-runoff datasets. Curve numbers varied form 29 to 97. Land use type was an important explanatory factor for the variation in curve numbers, whereas hydrologic soil group was not. Curve numbers were negatively correlated with vegetation cover. Taking into account antecendent soil mosture conditions did not improve runoff prediction using the curve number method. As runoff prediction was less accurate in areas with low curve numbers, two separate regression functions relating curve numbers with vetetation cover were proposed for different land use types. Copyright (C) 2008 john Wiley & Sons. Ltd.