Simulating soil organic carbon dynamics using RothC in grasslands range and croplands Saral Research Center Kurdistan Province

RothC is among the most successful models in terms of simulating the impacts of climate change and management activities in natural ecosystems on local and global scales. The current research was carried out to assess and validate RothC in studying SOC content from 1990 to 2020 and defining the scenarios of maintaining the current situations (scenario 1), climate change (scenario 2), manure fertilizing till 2100 (scenario 3), and climate change with manure fertilizing till 2100 (scenario 4) in grasslands, range, and croplands in Saral Research Center, Kurdistan Province, under rotations of wheat-uncultivation and wheat-pea. The parameters of the model were determined by using the measured data from the soils sampled at two years (2018 and 2019) from Saral Research Center and the local weather data, Next, the model was validated by comparison of the predicted values with the measured SOC data. Assessment of the measured and simulated data through validation for different land uses revealed that RothC could satisfactorily predict the changes in SOC contents under different fertilizing and climate change scenarios so that root mean square error (RMSE) and the simulation efficiency were calculated as 8.92% and 74.0%, respectively. The simulation results indicated that compared to scenario1, climate change in the studied land uses will cause a decrease in SOC contents till 2100. Manure fertilizing (scenario3) would be the best scenario so that by using this strategy the grassland, with 59.83 ton SOC per hectare until the end of the current century. According to the results predicted by the model, the highest SOCrate (32.9%) and the most change in SOC sequestration (ΔSOCs) (0.16 t/h) during the next 80 years were calculated in the range under scenario 3; whereas the lowest values (-32.0% and -0.11 t/h, respectively), were achieved in croplands under rotations of wheat-uncultivation under scenario2.