Simulation of Staple Crop Yields for Determination of Regional Impacts of Climate Change: A Case Study in Chonnam Province, Republic of Korea

This study sought to simulate regional variation in staple crop yields in Chonnam Province, Republic of Korea (ROK), in future environments under climate change based on the calibration of crop models in the Decision Support System for Agricultural Technology Transfer 4.6 package. We reproduced multiple-year yield data for paddy rice (2013–2018), barley (2000–2018), and soybean (2004–2018) grown in experimental fields at Naju, Chonnam Province, using the CERES-Rice, CERES-Barley, and CROPGRO-Soybean models. A geospatial crop simulation modeling (GCSM) system developed using the crop models was then applied to simulate the regional impacts of climate change on the staple crops according to the Representative Concentration Pathway 4.5 and 8.5 scenarios. Simulated crop yields agreed with the corresponding measured crop yields, with root means square deviations of 0.31 ton ha−1 for paddy rice, 0.29 ton ha−1 for barley, and 0.27 ton ha−1 for soybean. We also demonstrated that the GCSM system could effectively simulate spatiotemporal variations in the impact of climate change on staple crop yield. The CERES and CROPGRO models seem to reproduce the effects of climate change on region-wide staple crop production in a monsoonal climate system. Added advancements of the GCSM system could facilitate interpretations of future food resource insecurity and establish a sustainable adaption strategy.

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Assessing the Impacts of Climate change on Crop Yields in different Agro-Climatic Zones of India

Journal of Atmospheric Science Research ◽

10.30564/jasr.v3i4.2269 ◽

2020 ◽

Vol 3 (4) ◽

Author(s):

Naveen P Singh ◽

Bhawna Anand ◽

S K Srivastava ◽

K V Rao ◽

S K Bal ◽

...

Keyword(s):

Climate Change ◽

Crop Yields ◽

Climate Impact ◽

Significant Rise ◽

Agricultural System ◽

Adaptation Measures ◽

Climatic Zones ◽

Emissions Scenarios ◽

The Impact ◽

Impacts Of Climate Change

Thestudy attempts to estimateand predict climate impact on crop yieldsusing future temperature projections under two climate emissions scenarios of RCP 4.5 and 8.5 for threedifferent time periods (2030s, 2050s and 2080s) across Agro-climatic zones (ACZ) of India.During the period 1966-2011, a significant rise was observed in both the annual mean maximum and minimum temperature across ACZs. Rainfall recorded an annual decline in Himalayan Regions and Gangetic Plains and a rise in Coastal Regions, Plateau & Hills and Western Dry Region.Our results showedhigh heterogeneity in climate impact onkharif and rabi crop yields (with both negative and positive estimates) across ACZs.It was found that rainfall had a positive effect on most of crop yields, but was not sufficient enough to counterbalance the impact of temperature.Changes in crop yield were more pronounced forhigheremission scenario of RCP 8.5. Thus, it was evident that the relative impacts of climate change and the associated vulnerability varyby ACZs, hence comprehensive crop and region-specific adaptation measures should be emphasized that helps in enhancing resilience of agricultural system in short to medium term.

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HOW CLIMATE CHANGE CAN INFLUENCE THE AGRICULTURE IN UKRAINE: A REVIEW

Technical and technological aspects of development and testing of new machinery and technologies for agriculture of Ukraine ◽

10.31473/2305-5987-2020-2-27(41)-15 ◽

2020 ◽

Author(s):

N. Maidanovych ◽

Keyword(s):

Climate Change ◽

Crop Yields ◽

Soil Surface ◽

Winter Period ◽

Negative Consequences ◽

Resource Saving ◽

Impact Of Climate Change ◽

Positive Effects ◽

Average Annual Temperature ◽

The Impact

The purpose of this work is to review and analyze the main results of modern research on the impact of climate change on the agro-sphere of Ukraine. Results. Analysis of research has shown that the effects of climate change on the agro-sphere are already being felt today and will continue in the future. The observed climate changes in recent decades have already significantly affected the shift in the northern direction of all agro-climatic zones of Europe, including Ukraine. From the point of view of productivity of the agro-sphere of Ukraine, climate change will have both positive and negative consequences. The positives include: improving the conditions of formation and reducing the harvesting time of crop yields; the possibility of effective introduction of late varieties (hybrids), which require more thermal resources; improving the conditions for overwintering crops; increase the efficiency of fertilizer application. Model estimates of the impact of climate change on wheat yields in Ukraine mainly indicate the positive effects of global warming on yields in the medium term, but with an increase in the average annual temperature by 2 ° C above normal, grain yields are expected to decrease. The negative consequences of the impact of climate change on the agrosphere include: increased drought during the growing season; acceleration of humus decomposition in soils; deterioration of soil moisture in the southern regions; deterioration of grain quality and failure to ensure full vernalization of grain; increase in the number of pests, the spread of pathogens of plants and weeds due to favorable conditions for their overwintering; increase in wind and water erosion of the soil caused by an increase in droughts and extreme rainfall; increasing risks of freezing of winter crops due to lack of stable snow cover. Conclusions. Resource-saving agricultural technologies are of particular importance in the context of climate change. They include technologies such as no-till, strip-till, ridge-till, which make it possible to partially store and accumulate mulch on the soil surface, reduce the speed of the surface layer of air and contribute to better preservation of moisture accumulated during the autumn-winter period. And in determining the most effective ways and mechanisms to reduce weather risks for Ukrainian farmers, it is necessary to take into account the world practice of climate-smart technologies.

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The Impact of Climate Change on Storage-Yield Curves for Multi-Reservoir Systems

Hydrology Research ◽

10.2166/nh.1999.0007 ◽

1999 ◽

Vol 30 (2) ◽

pp. 129-146 ◽

Cited By ~ 3

Author(s):

N. R. Nawaz ◽

A. J. Adeloye ◽

M. Montaseri

Keyword(s):

Climate Change ◽

Surface Fluxes ◽

Runoff Coefficient ◽

Impact Study ◽

Yield Functions ◽

Reservoir Systems ◽

English System ◽

Multiple Reservoir ◽

The Impact ◽

Impacts Of Climate Change

In this paper, we report on the results of an investigation into the impacts of climate change on the storage-yield relationships for two multiple-reservoir systems, one in England and the other in Iran. The impact study uses established protocol and obtains perturbed monthly inflow series using a simple runoff coefficient approach which accounts for non-evaporative losses in the catchment, and a number of recently published GCM-based scenarios. The multi-reservoir analysis is based on the sequent-peak algorithm which has been modified to analyse multiple reservoirs and to accommodate explicitly performance norms and reservoir surface fluxes, i.e. evaporation and rainfall. As a consequence, it was also possible to assess the effect of including reservoir surface fluxes on the storage-yield functions. The results showed that, under baseline conditions, consideration of net evaporation will require lower storages for the English system and higher storages for the Iranian system. However, with perturbed hydroclimatology different impacts were obtained depending on the systems' yield and reliability. Possible explanations are offered for the observed behaviours.

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Assessing the Sensitivity of Main Crop Yields to Climate Change Impacts in China

Atmosphere ◽

10.3390/atmos12020172 ◽

2021 ◽

Vol 12 (2) ◽

pp. 172

Author(s):

Yuan Xu ◽

Jieming Chou ◽

Fan Yang ◽

Mingyang Sun ◽

Weixing Zhao ◽

...

Keyword(s):

Climate Change ◽

Crop Yield ◽

Food Production ◽

Crop Yields ◽

Climatic Factors ◽

Climatic Data ◽

The South ◽

The North ◽

Output Elasticity ◽

The Impact

Quantitatively assessing the spatial divergence of the sensitivity of crop yield to climate change is of great significance for reducing the climate change risk to food production. We use socio-economic and climatic data from 1981 to 2015 to examine how climate variability led to variation in yield, as simulated by an economy–climate model (C-D-C). The sensitivity of crop yield to the impact of climate change refers to the change in yield caused by changing climatic factors under the condition of constant non-climatic factors. An ‘output elasticity of comprehensive climate factor (CCF)’ approach determines the sensitivity, using the yields per hectare for grain, rice, wheat and maize in China’s main grain-producing areas as a case study. The results show that the CCF has a negative trend at a rate of −0.84/(10a) in the North region, while a positive trend of 0.79/(10a) is observed for the South region. Climate change promotes the ensemble increase in yields, and the contribution of agricultural labor force and total mechanical power to yields are greater, indicating that the yield in major grain-producing areas mainly depends on labor resources and the level of mechanization. However, the sensitivities to climate change of different crop yields to climate change present obvious regional differences: the sensitivity to climate change of the yield per hectare for maize in the North region was stronger than that in the South region. Therefore, the increase in the yield per hectare for maize in the North region due to the positive impacts of climate change was greater than that in the South region. In contrast, the sensitivity to climate change of the yield per hectare for rice in the South region was stronger than that in the North region. Furthermore, the sensitivity to climate change of maize per hectare yield was stronger than that of rice and wheat in the North region, and that of rice was the highest of the three crop yields in the South region. Finally, the economy–climate sensitivity zones of different crops were determined by the output elasticity of the CCF to help adapt to climate change and prevent food production risks.

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Modeling the Impact of Climate Changes on Crop Yield: Irrigated vs. Non-Irrigated Zones in Mississippi

Remote Sensing ◽

10.3390/rs13122249 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2249

Author(s):

Sadia Alam Shammi ◽

Qingmin Meng

Keyword(s):

Climate Change ◽

Crop Yield ◽

Crop Yields ◽

Negative Impact ◽

Positive Impact ◽

Information Criterion ◽

Growing Season ◽

Maximum Temperature ◽

Linear Regression Models ◽

The Impact

Climate change and its impact on agriculture are challenging issues regarding food production and food security. Many researchers have been trying to show the direct and indirect impacts of climate change on agriculture using different methods. In this study, we used linear regression models to assess the impact of climate on crop yield spatially and temporally by managing irrigated and non-irrigated crop fields. The climate data used in this study are Tmax (maximum temperature), Tmean (mean temperature), Tmin (minimum temperature), precipitation, and soybean annual yields, at county scale for Mississippi, USA, from 1980 to 2019. We fit a series of linear models that were evaluated based on statistical measurements of adjusted R-square, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). According to the statistical model evaluation, the 1980–1992 model Y[Tmax,Tmin,Precipitation]92i (BIC = 120.2) for irrigated zones and the 1993–2002 model Y[Tmax,Tmean,Precipitation]02ni (BIC = 1128.9) for non-irrigated zones showed the best fit for the 10-year period of climatic impacts on crop yields. These models showed about 2 to 7% significant negative impact of Tmax increase on the crop yield for irrigated and non-irrigated regions. Besides, the models for different agricultural districts also explained the changes of Tmax, Tmean, Tmin, and precipitation in the irrigated (adjusted R-square: 13–28%) and non-irrigated zones (adjusted R-square: 8–73%). About 2–10% negative impact of Tmax was estimated across different agricultural districts, whereas about −2 to +17% impacts of precipitation were observed for different districts. The modeling of 40-year periods of the whole state of Mississippi estimated a negative impact of Tmax (about 2.7 to 8.34%) but a positive impact of Tmean (+8.9%) on crop yield during the crop growing season, for both irrigated and non-irrigated regions. Overall, we assessed that crop yields were negatively affected (about 2–8%) by the increase of Tmax during the growing season, for both irrigated and non-irrigated zones. Both positive and negative impacts on crop yields were observed for the increases of Tmean, Tmin, and precipitation, respectively, for irrigated and non-irrigated zones. This study showed the pattern and extent of Tmax, Tmean, Tmin, and precipitation and their impacts on soybean yield at local and regional scales. The methods and the models proposed in this study could be helpful to quantify the climate change impacts on crop yields by considering irrigation conditions for different regions and periods.

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Extreme weather highlights longer-term Canada concerns

Emerald Expert Briefings ◽

10.1108/oxan-db266493 ◽

2022 ◽

Keyword(s):

Climate Change ◽

Indigenous Peoples ◽

Clean Energy ◽

Focused Attention ◽

Content Type ◽

Weather Patterns ◽

Extreme Cold ◽

The Impact ◽

Ways Of Life ◽

Impacts Of Climate Change

Significance The extreme cold comes as the province is still dealing with the damage caused by unprecedented levels of heat and wildfires last summer and then record levels of rainfall and flooding in November. Its experience has focused attention on Canada’s wider vulnerability to the impact of shifting weather patterns and climate change. Impacts The natural resource sectors that are vital to Canada’s economy face an increasingly difficult environment for extraction. Indigenous peoples across the country will see their traditional ways of life further disrupted by climate change. The increasingly evident impacts of climate change on day-to-day life will see voters demand greater action from government. Significant investment in green initiatives, clean energy and climate resiliency initiatives will boost green industries.

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