Projected Crop Production under Regional Climate Change Using Scenario Data and Modeling: Sensitivity to Chosen Sowing Date and Cultivar

Abstract

Abstract:A sensitivity analysis of the responses of crops to the chosen production adaptation options under regional climate change was conducted in this study. Projections of winter wheat production for different sowing dates and cultivars were estimated for a major economic and agricultural province of China from 2021 to 2080 using the World Food Study model (WOFOST) under representative concentration pathways (RCPs) scenarios. A modeling chain was established and a correction method was proposed to reduce the bias of the resulting model-simulated climate data. The results indicated that adjusting the sowing dates and cultivars could mitigate the influences of climate change on winter wheat production in Jinagsu. The yield gains were projected from the chosen sowing date and cultivar. The following actions are recommended to ensure high and stable yields under future climate changes: (i) advance the latest sowing date in some areas of northern Jiangsu; and (ii) use heat-tolerant or heat-tolerant and drought-resistant varieties in most areas of Jiangsu rather than the currently used cultivar. Fewer of the common negative effects of using a single climate model occurred when using the sensitivity analysis because our bias correction method was effective for scenario data and because the WOFOST performed well for Jiangsu after calibration.

Grain Yield Observations Constrain Cropland CO2 Fluxes Over Europe

“…Crop scientists have already widely explored the possibility to use WOFOST in an uncoupled crop and atmosphere setup for operational seasonal crop yield forecasts (e.g., Bussay et al, 2015;de Wit & Van Diepen, 2007), and on the longer term for crop production projections under climate change (e.g., Tao et al, 2016;Peltonen-Sainio et al, 2015). A more interesting perspective for atmospheric scientists and hydrologists though is the possibility to fully couple the WOFOST-opt model with an atmospheric model, like has been attempted by Li et al (2013).…”

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“…This, in turn, makes it possible to work out a proper field work schedule, but also, for instance, to prevent pathogen development effectively [1,[24][25][26][27]. It was also proved that changes in phenological periods that are caused by climate changes could affect crop yields [28][29][30]. In most proved that changes in phenological periods that are caused by climate changes could affect crop yields [28][29][30].…”

“…It was also proved that changes in phenological periods that are caused by climate changes could affect crop yields [28][29][30]. In most proved that changes in phenological periods that are caused by climate changes could affect crop yields [28][29][30]. In most countries, the implementation of adopted strategies for adapting agriculture to climate change is still not well advanced [3,31].…”

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“…The use of NWP models in precipitation forecasting is already mounted in lots of operational weather and prediction centers. This will be partially defined with the aid of the demand of progressed precipitation prediction due to the fact that precipitation impacts many financial sectors, including agriculture [5] [6], fisheries [7], transport and different economic activities [8] [9]. Correct precipitation monitoring and prediction is consequently essential for spatial and temporal variability evaluation [9] in addition to weather change studies [10].…”