Evaluation of RothC model for predicting soil organic carbon stock in north-west Ethiopia

Abstract

Assessing soil organic carbon (SOC) is vital for water retention, soil health, nutrient cycling, greenhouse gas emissions, and pollutant reduction and thereby contributes to sustainable agricultural production and food security. Thus, using long-term climate, soil, and land management inputs, the Rothamsted Carbon (RothC) model was applied to assess the current and future SOC stocks in the Anjeni watershed using long term climate, soil and land management data. RothC was calibrated with long-term SOC, land management, and climatic data from the Anjeni watershed in north-west Ethiopia. The correlation coefficient between simulated and observed SOC in 1997 and 2021 were 0.77 and 0.86, respectively, suggesting that the model could characterize the SOC of the Anjeni watershed. Then, the RothC was used to estimate SOC in the watershed for 30 years, from 2022 to 2052, under three slope gradients and four land use type and carbon storage scenarios (business as usual (BAU), low, medium and high carbon inputs). The result indicated that in the lower slope gradient, the current SOC simulation is less than all future scenarios considered under all land use types. Grass/fallow land showed higher current and projected SOC than cultivated land and plantation forest. Moreover, grass/fallow land with a gentle slope gradient had higher SOC than the watershed's middle and high-elevation parts. Overall, the model projected an increase of SOC under different future scenarios that could be due to climate and land use cover changes, the long-term soil-water conservation camping works and better soil and land managements in the watershed. This future assists for water retention, soil health, nutrient cycling, soil aeration, and greenhouse gas emission reduction, which in turn could enhance agricultural productivity, food security, and sustainable development.