Abstract

Composting has emerged as a valuable route for the disposal of urban waste, with the prospect of applying composts on arable fields as organic amendments. Proper management of urban waste composts (UWC) requires a capacity to predict their impacts on carbon and nitrogen dynamics in the field, an issue in which simulation models are expected to play a prominent role. Here, we used a deterministic soil-crop model to simulate C–N dynamics in an arable field amended with three types of UWC (green waste and sludge, biodegradable waste, and solid waste), and a reference amendment (farmyard manure). The model is a version of CERES in which the soil C–N module was substituted with the NCSOIL model, whose microbiological parameters were determined from either laboratory incubation data or biochemical fractionation in a previous paper. CERES was tested against data from a field trial set up in 1998 in the Paris area, and managed as a maize (Zea mays L.)–wheat (Triticum aestivum L.) rotation. Comparison of observed and simulated data over the first 4 years of the field trial showed that CERES predicted the soil moisture and inorganic N dynamics reasonably well, as well as the variations in soil organic C. In particular, the parameterization of UWC organic matter from biochemical fractions achieved a similar fit as the parameterization based on incubation data. Wheat yields were also correctly predicted, but a systematic under-estimation of maize yields pointed at an under-estimation of spring and summer mineralization of N by CERES. Simulated N fluxes showed that the organic amendments induced an additional leaching ranging from 1 to 8 kg N ha−1 yr−1, which can be related to the initial mineral N content of the amendments. After 4 years, the composts had mineralized 3–8% of their initial organic N content, depending on their stability. Composts with slower N release had higher N availability for the crops. CERES could thus be used to aid in selecting the timing of compost application, in relation to its stability, based on both environmental and agronomical criteria.

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