A Tool for Carbon Farming Combining Soil Organic Carbon Modelling and Agricultural Decision Support Systems: Adapting the RothC Model to Simulate DSS Informed Agricultural Practices in a Mediterranean Climate

Decision support systems (DSSs) help farmers and decision-makers to find cropping systems which increase productivity while decreasing the use of fertilizers and irrigation; however, few DSSs exist which integrate soil carbon models, especially in Mediterranean climate. Here, we test whether RothC20_N, a version of the widely used RothC model adapted for Mediterranean and arid climates, can estimate the soil water content (SWC), soil organic carbon (SOC), and soil respiration (Rs), observed in two different cropping systems, one traditional and the other informed by the DSS by Horta Srl. The model was calibrated and tested against two long-term (8 years) field experiments in two different areas in Italy. The two sites showed characteristically dry soils during the summer period; RothC20_N was able to predict correctly the soil water content time series observed in both sites. RothC20_N could predict the measured SOC and heterotrophic respiration time series with Nash–Sutcliff efficiency ~0.3, normalized root mean squared error ~0.4, and Kling–Gupta efficiency > 0. This study shows that the multi-objective calibrated RothC20_N is an interesting candidate for inclusion in a DSS to broaden the potential of the DSS to increase the sustainability of agricultural practices by also addressing soil carbon dynamics while maintaining high agricultural productivity.