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Climate data induced uncertainties in simulated carbon fluxes under corn and soybean systems

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  • Bandaru, Varaprasad

Abstract

Net carbon balance on croplands depends on numerous factors (e.g., crop type, soil, climate) and their interactions. Agroecosystem models are generally used to assess cropland carbon fluxes because of their ability to capture the complex interactive effects of factors influencing carbon balance. For regional carbon flux simulations, generally gridded climate data sets are used because they offer data for each grid cell of the region of interest. However, studies consistently report uncertainties in climate datasets, which affect the accuracy of carbon flux simulations.

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  • Bandaru, Varaprasad, 2022. "Climate data induced uncertainties in simulated carbon fluxes under corn and soybean systems," Agricultural Systems, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:agisys:v:196:y:2022:i:c:s0308521x21002948
    DOI: 10.1016/j.agsy.2021.103341
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    1. Folberth, Christian & Yang, Hong & Gaiser, Thomas & Abbaspour, Karim C. & Schulin, Rainer, 2013. "Modeling maize yield responses to improvement in nutrient, water and cultivar inputs in sub-Saharan Africa," Agricultural Systems, Elsevier, vol. 119(C), pages 22-34.
    2. Christian Folberth & Rastislav Skalský & Elena Moltchanova & Juraj Balkovič & Ligia B. Azevedo & Michael Obersteiner & Marijn van der Velde, 2016. "Uncertainty in soil data can outweigh climate impact signals in global crop yield simulations," Nature Communications, Nature, vol. 7(1), pages 1-13, September.
    3. Aggarwal, P. K., 1995. "Uncertainties in crop, soil and weather inputs used in growth models: Implications for simulated outputs and their applications," Agricultural Systems, Elsevier, vol. 48(3), pages 361-384.
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