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A new version of the Century ecosystem model, modified to better represent chemically and physically recalcitrant organic amendments by allowing the addition of organic waste products (OWP) as a mixture of plant material and surface slow soil organic matter (SOM) controlled by the Indicator of Residual Organic Carbon (IROC), and field observations from a 16‐year wheat corn rotation experiment near Paris, France, were used to assess the long‐term impacts of applying agricultural and municipal organic waste products (OWP) on soil carbon (C) sequestration, grain C and nutrient content, and soil nutrient status. Sixteen years of observed grain C, nitrogen (N), phosphorus (P), and potassium (K) and soil C and nutrient data were used to calibrate and validate the performance of IROC‐Century. A suite of future management scenarios, simulated using this calibrated model, explored multiple frequencies of applications of OWP and fertilizer to evaluate their long‐term impacts on grain C and nutrient content, soil C sequestration, and NO3− leaching. The model effectively simulated the impact of biennial additions of four OWP types on soil C, N, P, and K during the 16‐year experiment. Measured and simulated OWP +fertilizer resulted in higher soil C (highest for well‐decomposed [55%] vs. less‐decomposed [37%] OWP) and N content, while total soil accumulation of N, P, and K was determined by the content of the OWP, regardless of IROC, and OWP greatly reduced the need to add chemical fertilizer while increasing crop production and N, P, and K uptake by the crop. Simulation scenarios using IROC‐Century for future management suggest that the optimal cropping management system to maintain high corn and wheat production and reduce NO3− leaching is to apply OWP biennially for 12 years along with fertilizer and then reduce OWP to every fourth year while continuing to add fertilizer to the wheat crop only. However, reducing the number of OWP additions in these scenarios did decrease the rate of soil carbon sequestration.

The simulation of wastewater treatment plants allows obtaining predictive results when one needs to understand, evaluate, optimize or design a plant. However, one of the bottlenecks of the simulation feasibility is to obtain reliable and dynamic influent data. This difficulty is even more important when alternative scenarios are considered, such as source-separated streams. The present paper offers an influent generator to simulate scenarios where urine is separated at source and at a user-specified level of retention. The proposed tool contains several blocks to include different contribution (household and industrial wastewater) and, due to its flexibility, allows the user to easily modify the parameters to fit other case studies. The tool allowed generating dynamic, long-term and predictive data for both urine and wastewater streams. Also, the extensive set of state variables ensured the generation of influents for different modeling platforms.