Predicting soil attributes for environmental modelling

Nurhussen Mehammednur Seid, Birru Yitaferu, Feras M. Ziadat, Andreas Klik, Wondimu Bayu. (31/12/2015). Predicting soil attributes for environmental modelling, in "Mitigating Land Degradation and Improving Livelihoods - An integrated watershed approach". New York, United States of America: Taylor & Francis (Routledge).

Abstract

The UNPRA–Ethiopia project ‘Unlocking the potential of rainfed agriculture in Ethiopia for improved rural livelihoods’ aims to improve the livelihoods of rural communities in the rainfed agro-ecosystem of the Amhara region of Ethiopia. This can be achieved by improving agricultural productivity and con - serving ecosystem resources through integrating affordable and appropriate technologies in a favourable socio-economic environment. One component of the project is to monitor and model the impact of community-based soil and water conservation interventions on land degradation at field and watershed levels. To achieve this, quantitative information and spatial distribution of soil properties are among the main prerequisites. The reliability of land use decisions depends largely on the quality of soil information used to derive them. Ongoing research in digital soil mapping has demonstrated that reasonably accurate soil maps can be produced using quantitative predictive models. The objectives of this study were to provide an approach for predicting soil attributes based on a digital elevation model (DEM) and remote sensing.