Land cover change is a major environmental concern in the northwestern highlands of Ethiopia. This study detected land cover transitions over the past 30 years in the Chemoga basin (total area = 118,359 ha). Land cover maps were generated via the supervised classification of Landsat images with the help of the Google Earth (GE) images. A total of 218 unchanged land features sampled from GE images were used as the training datasets. Classification accuracy was evaluated by comparing classified images with 165 field observations during the 2017 field visit. The overall accuracy was 85.4% and the kappa statistic was 0.81, implying that the land classification was satisfactory. Agricultural land is the dominant land cover in the study basin, and increased in extent by 2,337 ha from 1987 to 2017. The second and third most dominant land cover types, grassland and woodland, decreased by 1.9% and 3.6%, respectively, over the past 30 years. The increase in agricultural lands was mostly due to the conversion of grasslands and woodlands, although some agricultural lands changed to Eucalyptus plantations and human settlements. The results revealed that the expansion of built-up space and agricultural lands was the major driver of fragmentation of the landscape, and degradation of natural resources in the Chemoga basin, Ethiopia.

Soil erosion control dams are widely used as part of measures to reduce damage caused by debris flow all over the world. Engineering considerations are needed for proper design of erosion control dams, but in the Republic of Korea, the impact force of debris flow is not fully reflected in the current design criteria of the dam. Against this backdrop, this study was conducted to estimate the impact force of debris flow for the practical purpose of designing erosion control dam. Simulated flume experiments were performed to develop the relationship to estimate the flow velocity as well as the impact force of debris flow. Experimental results showed that increases both in sediment mixture volume and flume slope gradient led to an increase in flow velocity. Especially, it was found that as clay content increased gradually, the flume slope gradient had greater impact on the increase of flow velocity. Also, it was proved that the impact force of debris flow was well fitted to the hydrodynamic model as it showed linear correlation with the flow velocity. Then, the debris‐flow velocity model was established based on the factor related to the debris‐flow velocity. Finally, the dynamic model to estimate the impact force of debris flow was introduced utilizing correlations between the established debris‐flow velocity model and Froude number. Both models which were developed with using statistically significant watershed characteristics succeeded in explaining the experiment results in a more accurate way compared to existing models. Therefore, it is highly expected that these models can be fully utilized to estimate impact force of debris flow which will be required to design erosion control dams in practical use through overcoming their identified limitations.