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Agroecosystem modelling has increasingly focused on the integration of soil biogeochemical processes and crop growth. However, few models are available that offer high computing efficiencies for region-scale simulations, integrated decision support tools, and a structure that allows for easy extension. This paper introduces a new modeling tool to fill this gap: the GDNDC (Gridded DNDC) system for gridded agro-biogeochemical simulations. Based on the established DeNitrification and DeComposition (DNDC) model version-95, its main advancements include (i) implementation of parallel computation to significantly reduce computation time across multiple scales; (ii) a built-in parameter optimization algorithm to improve the predictive accuracy, and (iii) several decision support tools. We demonstrate each of these for county-level maize growth simulations in Liaoning Province (China) and reveal the potential of this new modeling tool to guide both long-term policy decisions regarding optimal fertilizer application and near-term crop yield forecasting for reactive decisions required in times of drought.

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Land-sea riverine carbon transfer (LSRCT) is one of the key processes in the global carbon cycle. Although natural factors (e.g. climate, soil) influence LSRCT, human water management strategies have also been identified as a critical component. However, few systematic approaches quantifying the contribution of coupled natural and anthropogenic factors on LSRCT have been published. This study presents an integrated framework coupling hydrological modeling, field sampling and stable isotope analysis for the quantitative assessment of the impact of human water management practices (e.g. irrigation, dam construction) on LSRCT under different hydrological conditions. By applying this approach to the case study of the Nandu River, China, we find that carbon (C) concentrations originating from different land-uses (e.g. forest, cropland) are relatively stable and outlet C variations are mainly dominated by controlled runoff volumes rather than by input C concentrations. These results indicate that human water management practices are responsible for a reduction of ∼60% of riverine C at seasonal timescales, with an even greater reduction during drought conditions. Annual C discharges have been significantly reduced (e.g. 77 ± 5% in 2015 and 39 ± 11% in 2016) due to changes in human water extraction coupled with climate variation. In addition, isotope analysis also shows that C fluxes influenced by human activities (e.g. agriculture, aquaculture) could contribute the dominant particulate organic carbon under typical climatic conditions, as well as drought conditions. This research demonstrates the substantial effect that human water management practices have on the seasonal and annual fluxes of LSRCT, especially in such small basins. This work also shows the applicability of this integrated approach, using multiple tools to quantify the contribution of coupled anthropogenic and natural factors on LSRCT, and the general framework is believed to be feasible with limited modifications for larger basins in future research.


Innføring i hvordan LCA kan bidra med å vurdere om produksjoner er mer bærekraftig. Bruk av bil over en bestemt avstand som introduksjon. Vise forskjell i klimagassutslipp fra garder for å se dagens situasjon. Vise noen forbedringsmuligheter.