scholarly journals Climate Change Impacts on Winter Wheat Yield in Northern China

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Xiu Geng ◽  
Fang Wang ◽  
Wei Ren ◽  
Zhixin Hao
Keyword(s):  
Climate Change ◽  
Winter Wheat ◽  
Negative Impact ◽  
Climatic Factors ◽  
Wheat Yield ◽  
Growing Season ◽  
Northern China ◽  
Series Data ◽  
Winter Wheat Yield ◽  
Impacts Of Climate Change

Exploring the impacts of climate change on agriculture is one of important topics with respect to climate change. We quantitatively examined the impacts of climate change on winter wheat yield in Northern China using the Cobb–Douglas production function. Utilizing time-series data of agricultural production and meteorological observations from 1981 to 2016, the impacts of climatic factors on wheat production were assessed. It was found that the contribution of climatic factors to winter wheat yield per unit area (WYPA) was 0.762–1.921% in absolute terms. Growing season average temperature (GSAT) had a negative impact on WYPA for the period of 1981–2016. A 1% increase in GSAT could lead to a loss of 0.109% of WYPA when the other factors were constant. While growing season precipitation (GSP) had a positive impact on WYPA, as a 1% increase in GSP could result in 0.186% increase in WYPA, other factors kept constant. Then, the impacts on WYPA for the period 2021–2050 under two different emissions scenarios RCP4.5 and RCP8.5 were forecasted. For the whole study area, GSAT is projected to increase 1.37°C under RCP4.5 and 1.54°C under RCP8.5 for the period 2021–2050, which will lower the average WYPA by 1.75% and 1.97%, respectively. GSP is tended to increase by 17.31% under RCP4.5 and 22.22% under RCP8.5 and will give a rise of 3.22% and 4.13% in WYPA. The comprehensive effect of GSAT and GSP will increase WYPA by 1.47% under RCP4.5 and 2.16% under RCP8.5.

Impacts of climate change on maize and winter wheat yields in China from 1961 to 2010 based on provincial data

2014 ◽  
Vol 153 (5) ◽  
pp. 825-836 ◽  
Author(s):  
C. CHEN ◽  
G. S. ZHOU ◽  
Y. M. PANG
Keyword(s):  
Climate Change ◽  
Winter Wheat ◽  
Wheat Yield ◽  
Maize Yield ◽  
The Other ◽  
National Scale ◽  
Maize Production ◽  
Central Regions ◽  
Winter Wheat Yield ◽  
Impacts Of Climate Change

SUMMARYThe impacts of climate change on maize and winter wheat yields in China from 1961 to 2010 were studied in the current paper, based on provincial data. The results indicated that rising average temperatures resulted in decreased maize yield in most of the study regions, and reduced maize production at a national scale by c. 3·4% relative to the average from 1961 to 2010. Moreover, the warming resulted in a decrease of winter wheat yield in the Huang-Huai-Hai and southwest regions and led to an overall loss in production of c. 5·8% at a national scale. The decrease of diurnal temperature range (DTR) affected maize yield adversely in the west and central regions, but a beneficial DTR effect was observed in the other provinces. The changes in DTR resulted in increased maize production at a national scale by c. 0·6%. However, the generally decreasing trends for DTR resulted in an increasing winter wheat yield in the northwest and south regions but a decreasing yield in the other provinces, and the production of winter wheat at a national scale was reduced by c. 2·9% because of changes in DTR. Changes in precipitation increased maize and winter wheat yields in some provinces but reduced crop yield in others. There was no significant effect of precipitation on maize production at a national scale, but the contribution of precipitation change reached c. 1·6% for winter wheat production.

scholarly journals An Improved CASA Model for Estimating Winter Wheat Yield from Remote Sensing Images

2019 ◽  
Vol 11 (9) ◽  
pp. 1088 ◽  
Author(s):  
Yulong Wang ◽  
Xingang Xu ◽  
Linsheng Huang ◽  
Guijun Yang ◽  
Lingling Fan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Winter Wheat ◽  
Crop Yield ◽  
Satellite Remote Sensing ◽  
Wheat Yield ◽  
Growing Season ◽  
Remote Sensing Images ◽  
Casa Model ◽  
Winter Wheat Yield

The accurate and timely monitoring and evaluation of the regional grain crop yield is more significant for formulating import and export plans of agricultural products, regulating grain markets and adjusting the planting structure. In this study, an improved Carnegie–Ames–Stanford approach (CASA) model was coupled with time-series satellite remote sensing images to estimate winter wheat yield. Firstly, in 2009 the entire growing season of winter wheat in the two districts of Tongzhou and Shunyi of Beijing was divided into 54 stages at five-day intervals. Net Primary Production (NPP) of winter wheat was estimated by the improved CASA model with HJ-1A/B satellite images from 39 transits. For the 15 stages without HJ-1A/B transit, MOD17A2H data products were interpolated to obtain the spatial distribution of winter wheat NPP at 5-day intervals over the entire growing season of winter wheat. Then, an NPP-yield conversion model was utilized to estimate winter wheat yield in the study area. Finally, the accuracy of the method to estimate winter wheat yield with remote sensing images was verified by comparing its results to the ground-measured yield. The results showed that the estimated yield of winter wheat based on remote sensing images is consistent with the ground-measured yield, with R2 of 0.56, RMSE of 1.22 t ha−1, and an average relative error of −6.01%. Based on time-series satellite remote sensing images, the improved CASA model can be used to estimate the NPP and thereby the yield of regional winter wheat. This approach satisfies the accuracy requirements for estimating regional winter wheat yield and thus may be used in actual applications. It also provides a technical reference for estimating large-scale crop yield.

scholarly journals Effects of climate change and adaptation options on winter wheat yield under rainfed Mediterranean conditions in southern Portugal

2019 ◽  
Vol 154 (1-2) ◽  
pp. 159-178 ◽  
Author(s):  
Chenyao Yang ◽  
Helder Fraga ◽  
Wim van Ieperen ◽  
Henrique Trindade ◽  
João A. Santos
Keyword(s):  
Climate Change ◽  
Winter Wheat ◽  
Wheat Yield ◽  
Winter Wheat Yield ◽  
Southern Portugal ◽  
Adaptation Options ◽  
Mediterranean Conditions

scholarly journals Assessment of current climate conditions changes in the territory of Ciscaucasia for the purposes of forecasting winter wheat yield

2021 ◽  
Vol 16 (1) ◽  
pp. 117-127
Author(s):  
S. N. Volkov ◽  
S. V. Savinova ◽  
E. V. Cherkashina ◽  
D. A Shapovalov ◽  
V. V. Bratkov ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Climatic Factors ◽  
Wheat Yield ◽  
Climatic Conditions ◽  
Climate Conditions ◽  
Average Value ◽  
Current Climate ◽  
Close Relationship ◽  
Winter Wheat Yield ◽  
High Level

Аim. Assessment of current climate changes in the territory of Ciscaucasia in order to predict the yield of winter wheat.Methods .Integral indicators of climatic conditions for agricultural production were employed. For the investigations, we selected five‐year periods for which the meteorological parameters were averaged, and to identify trends the data of specific five‐year periods were compared with the average value for the entireseries of observations (1960‐2020).Results. The deviation of precipitation in April was highest in 2011‐2015, when it increased by 22 mm, and in 1986‐1990 and 1991‐1995, when it decreased by 15 and 10 mm respectively. In Eastern Ciscaucasia,where conditions are more arid than in the Western and Central regions, in both the rise in air temperature and the amount of precipitation, especially in April and May, increased in the 21stcentury for the entire period of active vegetation.Conclusion.It was established that the value of the hydrothermal coefficient practically did not change during the 1960‐2020 period. In the late 1990s and early 2000s, there was an increase in productivity against the background of a relatively high level of annual precipitation and this stability is confirmed at the present time. There is a very close relationship between natural and climatic factors and the level of winter wheat yield.

Impacts of climate change and alternative adaptation options on winter wheat yield and water productivity in a dry climate in Central Europe

2012 ◽  
Vol 150 (5) ◽  
pp. 537-555 ◽  
Author(s):  
S. THALER ◽  
J. EITZINGER ◽  
M. TRNKA ◽  
M. DUBROVSKY
Keyword(s):  
Climate Change ◽  
Winter Wheat ◽  
Water Demand ◽  
Wheat Yield ◽  
N Leaching ◽  
Climate Scenarios ◽  
Management Options ◽  
Minimum Tillage ◽  
Winter Wheat Yield ◽  
Management Changes

SUMMARYThe main objective of the present crop simulation study was to determine the impact of climate change on the winter wheat production of a dry area situated in north-east Austria (Marchfeld region) based on the CERES-Wheat crop-growth simulation model associated with global circulation models (GCMs). The effects of some of the feasible regional- and farm-based adaptation measures (management options) on crop yield and water and nitrogen (N) balance under the climate scenarios were simulated. Climate scenarios were defined based on the ECHAM5, HadCM3 and NCAR PCM GCM simulations for future conditions (2021–50) as described in the Special Report on Emission Scenarios A1B (Nakicenovic & Swart 2000). The potential development, yield, water demand and soil N leaching were estimated for winter wheat and all of the defined climates (including rising CO2 levels) and management scenarios (soil cultivation, windbreaks and irrigation).The results showed that a warming of 2°C in the air temperature would shorten the crop-growing period by up to 20 days and would decrease the potential winter wheat yield on nearly all of the soil types in the region. Particularly, high-yield reductions were projected for light-textured soils such as Parachernozems. A change from ploughing to minimum tillage within the future scenario would lead to an increase of up to 8% of the mean yield of winter wheat. This effect mainly resulted from improved water supply to the crop, associated with higher soil water storage capacity and decrease of unproductive water losses. Hedgerows, which reduce the wind speed, were predicted to have particularly positive effects on medium and moderately fine-textured soils such as Chernozems and Fluvisols. With both management changes, regional mean-yield level can be expected to be +4% in comparison with no management changes in the future conditions. Compared with the baseline period, water demand for the potential yield of winter wheat would require 6–37 mm more water per crop season (area-weighted average). The highest water demand would be on medium-textured soils, which make up the largest amount of area in the study region. Additionally, the effects of snow accumulation near hedgerows would further increase the yield, but would also lead to higher N leaching rates. However, specific management options, such as minimum tillage and hedgerows, could contribute towards reducing the increasing water demand.

Climate change, winter wheat yield and soil erosion on the English south downs

1991 ◽  
Vol 37 (4) ◽  
pp. 415-433 ◽  
Author(s):  
D.T. Favis-Mortlock ◽  
R. Evans ◽  
J. Boardman ◽  
T.M. Harris
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
Winter Wheat ◽  
Wheat Yield ◽  
Winter Wheat Yield

scholarly journals Impacts of climate change on agricultural production in Nepal: Case of Kavre and Jumla districts

2014 ◽  
Vol 2 ◽  
pp. 43-50
Author(s):  
K.S. Pandey ◽  
H. Shrestha ◽  
L.P. Devkota
Keyword(s):  
Climate Change ◽  
Agricultural Production ◽  
Time Series Data ◽  
Negative Impact ◽  
Wheat Yield ◽  
Series Data ◽  
National Bureau ◽  
Specific Objective ◽  
Analytical Tools ◽  
The Impact

The study the analyzed relationship of climate change with agricultural production in Kavre and Jumla districts. The specific objective of the study was to find out the dimension and linkage between agricultural production and climatic parameters in Kavre and Jumla. Time series data were analysed for the study. The data was sourced from the Department of Hydrology Meteorology, Department of Agriculture, and National Bureau of Statistics. Descriptive statistics, linear analysis test and back ward difference filter were the analytical tools used to determine the impact of climate change on productivity. During harvest period, the correlation of rice yield with temperature and rainfall was negative at Kavre but positive at Jumla. Similarly, the correlation of wheat yield with temperature and rainfall was positive at Kavre but negative at Jumla. The result showed that extreme fluctuation in weather caused negative impact on production in Jumla in compared to Kavre districts.

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