scholarly journals Towards probabilistic projections of climate change impacts on global crop yields

2008 ◽  
Vol 35 (8) ◽  
Author(s):  
C. Tebaldi ◽  
D. B. Lobell
2019 ◽  
Author(s):  
International Food Policy Research Institute (IFPRI)

2021 ◽  
Vol 310 ◽  
pp. 108649
Author(s):  
Yong Chen ◽  
Gary W. Marek ◽  
Thomas H. Marek ◽  
Dana O. Porter ◽  
David K. Brauer ◽  
...  

2015 ◽  
Vol 15 (6) ◽  
pp. 499-525 ◽  
Author(s):  
Oluwole K Oyebamiji ◽  
Neil R Edwards ◽  
Philip B Holden ◽  
Paul H Garthwaite ◽  
Sibyll Schaphoff ◽  
...  

2015 ◽  
Vol 95 (1) ◽  
pp. 49-61 ◽  
Author(s):  
Ted Huffman ◽  
Budong Qian ◽  
Reinder De Jong ◽  
Jiangui Liu ◽  
Hong Wang ◽  
...  

Huffman, T., Qian, B., De Jong, R., Liu, J., Wang, H., McConkey, B., Brierley, T. and Yang, J. 2015. Upscaling modelled crop yields to regional scale: A case study using DSSAT for spring wheat on the Canadian prairies. Can. J. Soil Sci. 95: 49–61. Dynamic crop models are often operated at the plot or field scale. Upscaling is necessary when the process-based crop models are used for regional applications, such as forecasting regional crop yields and assessing climate change impacts on regional crop productivity. Dynamic crop models often require detailed input data for climate, soil and crop management; thus, their reliability may decrease at the regional scale as the uncertainty of simulation results might increase due to uncertainties in the input data. In this study, we modelled spring wheat yields at the level of numerous individual soils using the CERES–Wheat model in the Decision Support System for Agrotechnology Transfer (DSSAT) and then aggregated the simulated yields from individual soils to regions where crop yields were reported. A comparison between the aggregated and the reported yields was performed to examine the potential of using dynamic crop models with individual soils in a region for the simulation of regional crop yields. The regionally aggregated simulated yields demonstrated reasonable agreement with the reported data, with a correlation coefficient of 0.71 and a root-mean-square error of 266 kg ha−1 (i.e., 15% of the average yield) over 40 regions on the Canadian prairies. Our conclusion is that aggregating simulated crop yields on individual soils with a crop model can be reliable for the estimation of regional crop yields. This demonstrated its potential as a useful approach for using crop models to assess climate change impacts on regional crop productivity.


Author(s):  
Sorush Niknamian

This research evaluated climate change impacts on temperature, precipitation, and runoff using LARS-WG and SWAT models under climate scenarios. First, drought intensity was calculated for the period 1987-2016. Then, the LARS-WG model was calibrated to generate climatological data for future periods. The coefficients of precipitation as well as minimum and maximum temperature changes were simulated as SWAT model inputs. The results of LARS-WG model indicated that temperature will increase in future periods and that changes will occur not only in precipitation rate but also in its pattern. Then, changes in runoff were simulated by introducing downscaled results to SWAT model. The model was calibrated and validated by SWAT-CUP software. Nash-Sutcliffe (NS) coefficients (0.58 and 0.49) and R2 determination coefficients (0.65 and 0.50) were obtained for calibration and validation periods, respectively. The results showed that runoff will increase in spring and summer during 2011-2030 period, but it will decrease in fall and winter. Further, runoff will rise in fall and winter while it will drop in spring and summer throughout 2046-2065 and 2080-2099 periods under all three scenarios. Such seasonal shifts in runoff levels result from climate change consequences in the forms of temperature rise, snowmelt, altered precipitation pattern, etc. Future-period evapotranspiration will rise under all three scenarios with a maximum increase in 2080-2099 period under A2 scenario. Additionally, rainfed crop yields will decline without considerable changes in irrigated and horticultural crop yields.


2020 ◽  
Author(s):  
Aksara Putthividhya ◽  
Wimolpat Bumbudsanpharoke Khamkanya ◽  
Somkiat Prajamwong

<p>Recent research has demonstrated the multidimensional and multi-sectoral impacts of climate change, evidencing the need to develop national and sub-national integrated tools and policies for the analysis of impacts and adaptation, especially central to local policy recommendation and implementation. This framework combines an area-based economic optimization model with the hydrological model WEAP, and represents the socio-economic, agronomic, and hydrologic systems in a spatially explicit manner covering dimensions and scales relevant to downscaled climate change impacts.  Simulated scenarios are setup to incorporate climate scenario, prior-historic dependence to adaptation conformity, and two policy-based adaptation scenarios. Preliminary results indicate that climate change may impact severely in rain-fed agricultural area and also to irrigation systems reducing water availability and security and crop yields, and increasing in more efficient irrigation water allocation.  The adaptation strategies analysis based on socio-economic, agronomic, and hydrologic dimensions capitalizes the key role of Thailand supply- and demand-side management policy in facilitating adaptation. The under developing framework is currently anticipated to be a useful tool for supporting water resources and climate change policy making.  It can contribute to improve understanding on potential impacts of climate change, multi-sectoral linkages, multi-scale vulnerability, and adaptation programs.   </p>


2015 ◽  
Vol 71 ◽  
pp. 123-134 ◽  
Author(s):  
Heidi Webber ◽  
Gang Zhao ◽  
Joost Wolf ◽  
Wolfgang Britz ◽  
Wim de Vries ◽  
...  

2021 ◽  
Vol 166 (3-4) ◽  
Author(s):  
Angelo C. Gurgel ◽  
John Reilly ◽  
Elodie Blanc

AbstractMany approaches have been used to investigate climate change impacts on agriculture. However, several caveats remain in this field: (i) analyses focus only on a few major crops, (ii) large differences in yield impacts are observed between projections from site-based crops models and Global Gridded Crop Models (GGCMs), (iii) climate change impacts on livestock are rarely quantified, and (iv) several causal relations among biophysical, environmental, and socioeconomic aspects are usually not taken into account. We investigate how assumptions about these four aspects affect agricultural markets, food supply, consumer well-being, and land use at global level by deploying a large-scale socioeconomic model of the global economy with detailed representation of the agricultural sector. We find global welfare impacts several times larger when climate impacts all crops and all livestock compared to a scenario with impacts limited to major crops. At the regional level, food budget can decrease by 10 to 25% in developing countries, challenging food security. The role of land area expansion as a major source of adaptation is highlighted. Climate impacts on crop yields from site-based process crop models generate more challenging socioeconomic outcomes than those from GGCMs. We conclude that the agricultural research community should expand efforts to estimate climate impacts on many more crops and livestock. Also, careful comparison of the GGCMs and traditional site-based process crop models is needed to understand their major implications for agricultural and food markets.


2021 ◽  
Author(s):  
Md. Mahmudul Alam ◽  
Yusnidah Bt Ibrahim ◽  
Shahin Mia

In Malaysia, there is a declining trend in agricultural productivity and crop yields due to various climate events in the recent years. Therefore, this study aims to examine the impacts of climate change, especially El Nino and flood, on the financial performance of Malaysian agro and plantation firms. The study used a panel data set on 33 Malaysian agro and plantation firms listed in Bursa Malaysia for the period of 2003 to 2016. A panel of regression models including GMM, Pooled OLS, Random Effect and Fixed Effect were used to analyze the data. The results show that both the El Nino and flood have significant negative impact on the firms’ financial performance as measured by ROA and ROE. The findings indicate that climate change results in reduction of agricultural production which reduces revenue and consequently the profit of the agro and plantation firms. The study findings might help the firm managers as well as policy makers to take into consideration the environmental factors that affect the overall financial health of the firms and take appropriate adaptation and mitigation policies to climate change at firm level and macro level in the country.


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