Uncertainties in assessing the effect of climate change on agriculture using model simulation and uncertainty processing methods

Abstract

Model simulation is an important way to study the effects of climate change on agriculture. Such assessment is subject to a range of uncertainties because of either incomplete knowledge or model technical uncertainties, impeding effective decision-making to climate change. On the basis of uncertainties in the impact assessment at different levels, this article systematically summarizes the sources and propagation of uncertainty in the assessment of the effect of climate change on agriculture in terms of the climate projection, the assessment process, and the crop models linking to climate models. Meanwhile, techniques and methods focusing on different levels and sources of uncertainty and uncertainty propagation are introduced, and shortcomings and insufficiencies in uncertainty processing are pointed out. Finally, in terms of how to accurately assess the effect of climate change on agriculture, improvements to further decrease potential uncertainty are suggested.climate change, agriculture, impact assessment, uncertainty, model simulation Citation:Yao F M, Qin P C, Zhang J H, et al. Uncertainties in assessing the effect of climate change on agriculture using model simulation and uncertainty processing methods.

Simulated Regional Yields of Spring Barley in the United Kingdom under Projected Climate Change

“…Tracking and quantifying the aggregate effect of all uncertainties on simulated yields in climate change studies are difficult and require complex mathematical procedures [44]. The uncertainties can arise from the projected climate change data (due to, for example, uncertainties in the emissions scenarios), the crop growth simulation model, and the soil and crop input data, including sowing dates [37,44,45].…”

“…The uncertainties can arise from the projected climate change data (due to, for example, uncertainties in the emissions scenarios), the crop growth simulation model, and the soil and crop input data, including sowing dates [37,44,45]. Sowing date affects crop phenology and therefore biomass production, abiotic stresses and yields [3,29,46,47].…”

Variety distribution pattern and climatic potential productivity of spring maize in Northeast China under climate change

“…The fourth assessment report of IPCC showed that the average global temperature had increased 0.74±0.18°C in the recent 100 years [1], and the linear trend of recent 50 years would be almost twice as much as that of recent 100 years [2]. Researches showed that due to future climate change, the agricultural production pattern and crop planting system would be changed, and the agriculture production cost and investment cost would be increased [3,4], which would have an important influence on food security production [5]. The climate warming led to an obvious increase in the temperature and aridity, and a decrease in the precipitation due to the high latitude of Northeast China, which had a great influence on agriculture production [6,7].…”

The climatic suitability for maize cultivation in China

“…Global warming is now a reality, and will continue to be so for the foreseeable future [7]. Climate change has resulted in a northward shift and an eastward expansion of the planting boundaries for various maize varieties maturing at different times; early maturing varieties are being replaced by mid-or later-maturing varieties, the plantable area for mid-and later-maturing maize varieties is increasing [8], and the growth period is lengthening in the northwest region [9].…”