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

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.

Download Full-text

What Is the Consensus from Multiple Conclusions of Future Crop Yield Changes Affected by Climate Change in China?

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17249241 ◽

2020 ◽

Vol 17 (24) ◽

pp. 9241

Author(s):

Chengfang Huang ◽

Ning Li ◽

Zhengtao Zhang ◽

Yuan Liu ◽

Xi Chen ◽

...

Keyword(s):

Climate Change ◽

Crop Yield ◽

Crop Yields ◽

Positive Impact ◽

Scientific Evidence ◽

Future Climate Change ◽

Systematic Review Methodology ◽

Uncertainty Interval ◽

The Impact ◽

Yield Decrease

Many studies have shown that climate change has a significant impact on crop yield in China, while results have varied due to uncertain factors. This study has drawn a highly consistent consensus from the scientific evidence based on numerous existing studies. By a highly rational systematic review methodology, we obtained 737 result samples with the theme of climate change affecting China’s crop yields. Then, we used likelihood scale and trend analysis methods to quantify the consensus level and uncertainty interval of these samples. The results showed that: (i) The crop yield decrease in the second half of the 21st century will be greater than 5% of that in the first half. (ii) The crop most affected by climate change will be maize, with the decreased value exceeding −25% at the end of this century, followed by rice and wheat exceeding −10% and −5%. (iii) The positive impact of CO2 on crop yield will change by nearly 10%. Our conclusions clarify the consensus of the impact of future climate change on China’s crop yield, and this study helps exclude the differences and examine the policies and actions that China has taken and should take in response to climate change.

Download Full-text

Impact of climate change on food yield in Senegal: FAVAR approach

Journal of Economic Science Research ◽

10.30564/jesr.v2i1.447 ◽

2019 ◽

Vol 2 (1) ◽

Author(s):

Mamadou Abdoulaye KONTE ◽

Gnalenba ABLOUKA ◽

Paoli BEHANZIN

Keyword(s):

Climate Change ◽

Thermal Shock ◽

Crop Yields ◽

Negative Impact ◽

Positive Impact ◽

Estimation Method ◽

Maize Yield ◽

Impact Of Climate Change ◽

Rainfall Shock ◽

The Impact

The main objective of this research is to evaluate the impact of climate change on food crop yields in Senegal using the Factor Augmented Vector Auto Regression (FAVAR) approach. The estimation method used is principal components analysis. We identified two major shocks representative of climate change. The first is an increase of temperature (thermal shock) and the second is a decrease in the quantity of precipitation (rainfall shock). The data covers the period 1970-2014 and each of the shocks is carried out over the prior year. The impact of each shock is observed along a time horizon of 10 years. The results show a positive impact of the thermal shock on the yields of rice, maize and millet, with a much greater impact on rice and maize yield. Rising temperatures are, however, detrimental to sorghum. A decline in rainfall has a negative impact on the yields of all cereals, which is in line with expectations.

Download Full-text

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.

Download Full-text

Assessing the Impact of Nightlight Gradients on Street Robbery and Burglary in Cincinnati of Ohio State, USA

Remote Sensing ◽

10.3390/rs11171958 ◽

2019 ◽

Vol 11 (17) ◽

pp. 1958 ◽

Cited By ~ 8

Author(s):

Hanlin Zhou ◽

Lin Liu ◽

Minxuan Lan ◽

Bo Yang ◽

Zengli Wang

Keyword(s):

Negative Binomial ◽

Infrared Imaging ◽

Negative Impact ◽

Positive Impact ◽

Negative Binomial Regression ◽

Information Criterion ◽

Binomial Regression ◽

Street Robbery ◽

The Impact

Previous research has recognized the importance of edges to crime. Various scholars have explored how one specific type of edges such as physical edges or social edges affect crime, but rarely investigated the importance of the composite edge effect. To address this gap, this study introduces nightlight data from the Visible Infrared Imaging Radiometer Suite sensor on the Suomi National Polar-orbiting Partnership Satellite (NPP-VIIRS) to measure composite edges. This study defines edges as nightlight gradients—the maximum change of nightlight from a pixel to its neighbors. Using nightlight gradients and other control variables at the tract level, this study applies negative binomial regression models to investigate the effects of edges on the street robbery rate and the burglary rate in Cincinnati. The Akaike Information Criterion (AIC) of models show that nightlight gradients improve the fitness of models of street robbery and burglary. Also, nightlight gradients make a positive impact on the street robbery rate whilst a negative impact on the burglary rate, both of which are statistically significant under the alpha level of 0.05. The different impacts on these two types of crimes may be explained by the nature of crimes and the in-situ characteristics, including nightlight.

Download Full-text

Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA

Climate ◽

10.3390/cli8120139 ◽

2020 ◽

Vol 8 (12) ◽

pp. 139

Author(s):

Manashi Paul ◽

Sijal Dangol ◽

Vitaly Kholodovsky ◽

Amy R. Sapkota ◽

Masoud Negahban-Azar ◽

...

Keyword(s):

Climate Change ◽

Crop Yield ◽

Crop Yields ◽

Swat Model ◽

Global Climate Models ◽

Climate Projections ◽

Climate Change Scenarios ◽

River Watershed ◽

Temperature And Precipitation ◽

The Impact

Crop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions.

Download Full-text

The Impact of Local Climate Change on Radial Picea abies Growth: A Case Study in Natural Mountain Spruce Stand and Low-Lying Spruce Monoculture

Forests ◽

10.3390/f12081118 ◽

2021 ◽

Vol 12 (8) ◽

pp. 1118

Author(s):

Vladimír Šagát ◽

Ivan Ružek ◽

Karel Šilhán ◽

Pavel Beracko

Keyword(s):

Climate Change ◽

Picea Abies ◽

Negative Impact ◽

Growing Season ◽

Local Climate ◽

Spruce Forests ◽

Spruce Stands ◽

Local Climate Change ◽

Positive Correlations ◽

The Impact

Picea abies L. Karst is undeniably one of the most important tree species growing in Slovakia. In addition to natural mountain spruce forests, monocultures planted in lower areas are also quite common. In this article, we analyze the climate–growth response differences between these two types of spruce stands in the context of local climate change consequences. The study area representing natural mountain spruce forests is located under Osobitá Mt. (Tatra Mountains, Slovakia), while the analyzed low-lying planted monoculture is situated near Biely kríž (Malé Karpaty Mountains, Slovakia). Temporal variation of the dendroclimatological relationships was expressed by the running Spearman correlation coefficient during the observed period 1961–2018. The results showed crucial differences in the dendroclimatological relationships between the selected study areas. For the natural mountain spruce stand, consistent, weak, and positive correlations to the temperature variables were typical, with negative relationships to precipitation during the growing season. In this case, the negative impact of a recent temperature rise was limited. In contrast, the monoculture reacted to the temperature variation during the growing season with fluctuations, while in the case of precipitation, almost no dependence was found. Such incoherency may be a consequence of worsened health conditions, as well as insufficient resiliency to climate-driven stress. The importance of this paper is in its wide applicability, mainly in forestry.

Download Full-text

Sensitivity of wheat yields to rise in growing season temperature: Evidences from panel data analysis

Journal of Agrometeorology ◽

10.54386/jam.v22i2.167 ◽

2021 ◽

Vol 22 (2) ◽

pp. 191-197

Author(s):

K. PHILIP ◽

S.S. ASHA DEVI ◽

G.K. JHA ◽

B.M.K. RAJU ◽

B. SEN ◽

...

Keyword(s):

Climate Change ◽

Panel Data ◽

Growing Season ◽

Maximum Temperature ◽

Data Set ◽

Impact Of Climate Change ◽

Average Maximum ◽

Wide Range ◽

Potential Impact ◽

The Impact

The impact of climate change on agriculture is well studied yet there is scope for improvement as crop specific and location specific impacts need to be assessed realistically to frame adaptation and mitigation strategies to lessen the adverse effects of climate change. Many researchers have tried to estimate potential impact of climate change on wheat yields using indirect crop simulation modeling techniques. Here, this study estimated the potential impact of climate change on wheat yields using a crop specific panel data set from 1981 to 2010,for six major wheat producing states. The study revealed that 1°C increase in average maximum temperature during the growing season reduces wheat yield by 3 percent. Major share of wheat growth and yield (79%) is attributed to increase in usage of physical inputs specifically fertilizers, machine labour and human labour. The estimated impact was lesser than previously reported studies due to the inclusion of wide range of short-term adaptation strategies to climate change. The results reiterate the necessity of including confluent factors like physical inputs while investigating the impact of climate factors on crop yields.

Download Full-text

Analyzing Temperature and Precipitation Influences on Yield Distributions of Canola and Spring Wheat in Saskatchewan

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-16-0258.1 ◽

2017 ◽

Vol 56 (4) ◽

pp. 897-913 ◽

Cited By ~ 9

Author(s):

Ting Meng ◽

Richard Carew ◽

Wojciech J. Florkowski ◽

Anna M. Klepacka

Keyword(s):

Crop Yield ◽

Spring Wheat ◽

Climate Model ◽

Crop Yields ◽

Wheat Yield ◽

Growing Season ◽

Weather Data ◽

Growth Stages ◽

Yield Distribution ◽

The Impact

AbstractThe IPCC indicates that global mean temperature increases of 2°C or more above preindustrial levels negatively affect such crops as wheat. Canadian climate model projections show warmer temperatures and variable rainfall will likely affect Saskatchewan’s canola and spring wheat production. Drier weather will have the greatest impact. The major climate change challenges will be summer water availability, greater drought frequencies, and crop adaptation. This study investigates the impact of precipitation and temperature changes on canola and spring wheat yield distributions using Environment Canada weather data and Statistics Canada crop yield and planted area for 20 crop districts over the 1987–2010 period. The moment-based methods (full- and partial-moment-based approaches) are employed to characterize and estimate asymmetric relationships between climate variables and the higher-order moments of crop yields. A stochastic production function and the focus on crop yield’s elasticity imply choosing the natural logarithm function as the mean function transformation prior to higher-moment function estimation. Results show that average crop yields are positively associated with the growing season degree-days and pregrowing season precipitation, while they are negatively affected by extremely high temperatures in the growing season. The climate measures have asymmetric effects on the higher moments of crop yield distribution along with stronger effects of changing temperatures than precipitation on yield distribution. Higher temperatures tend to decrease wheat yields, confirming earlier Saskatchewan studies. This study finds pregrowing season precipitation and precipitation in the early plant growth stages particularly relevant in providing opportunities to develop new crop varieties and agronomic practices to mitigate climate changes.

Download Full-text

Impact Assessment of Climate Change on Paddy Yield: A Case Study of Nepal Agriculture Research Council (NARC), Tarahara, Nepal

Journal of the Institute of Engineering ◽

10.3126/jie.v8i3.5941 ◽

1970 ◽

Vol 8 (3) ◽

pp. 147-167 ◽

Cited By ~ 3

Author(s):

Yam K Rai ◽

Bhakta B Ale ◽

Jawed Alam

Keyword(s):

Climate Change ◽

Solar Radiation ◽

Research Council ◽

Crop Yields ◽

Rice Yield ◽

Weather Data ◽

Maximum Temperature ◽

Future Climate Change ◽

Climate Change Scenarios ◽

The Impact

Climate change and global warming are burning issues, which significantly threat agriculture and global food security. Change in solar radiation, temperature and precipitation will influence the change in crop yields and hence economy of agriculture. It is possible to understand the phenomenon of climate change on crop production and to develop adaptation strategies for sustainability in food production, using a suitable crop simulation model. CERES-Rice model of DSSAT v4.0 was used to simulate the rice yield of the region under climate change scenarios using the historical weather data at Nepal Agriculture Research Council (NARC) Tarahara (1989-2008). The Crop Model was calibrated using the experimental crop data, climate data and soil data for two years (2000-2001) and was validated by using the data of the year 2002 at NARC Tarahara. In this study various scenarios were undertaken to analyze the rice yield. The change in values of weather parameters due to climate change and its effects on the rice yield were studied. It was observed that increase in maximum temperature up to 2°C and 1°C in minimum temperature have positive impact on rice yield but beyond that temperature it was observed negative impact in both cases of paddy production in ambient temperature. Similarly, it was observed that increased in mean temperature, have negative impacts on rice yield. The impact of solar radiation in rice yield was observed positive during the time of study period. Adjustments were made in the fertilizer rate, plant density per square meter, planting date and application of water rate to investigate suitable agronomic options for adaptation under the future climate change scenarios. Highest yield was obtained when the water application was increased up to 3 mm depth and nitrogen application rate was 140 kg/ha respectively. DOI: http://dx.doi.org/10.3126/jie.v8i3.5941 JIE 2011; 8(3): 147-167

Download Full-text

THE POTENTIAL IMPACT OF CLIMATE CHANGE ON AGRICULTURE IN WEST AFRICA: A BIO-ECONOMIC MODELING APPROACH

Climate Change Economics ◽

10.1142/s2010007819500155 ◽

2019 ◽

Vol 10 (04) ◽

pp. 1950015

Author(s):

BORIS O. K. LOKONON ◽

AKLESSO Y. G. EGBENDEWE ◽

NAGA COULIBALY ◽

CALVIN ATEWAMBA

Keyword(s):

Climate Change ◽

Land Use ◽

Crop Production ◽

Crop Yields ◽

Negative Impact ◽

Economic Modeling ◽

Climate Conditions ◽

Impact Of Climate Change ◽

Potential Impact ◽

The Impact

This paper investigates the impact of climate change on agriculture in the Economic Community of West African States (ECOWAS). To that end, a bio-economic model is built and calibrated on 2004 base year dataset and the potential impact is evaluated on land use and crop production under two representative concentration pathways coupled with three socio-economic scenarios. The findings suggest that land use change may depend on crop types and prevailing future conditions. As of crop production, the results show that paddy rice, oilseeds, sugarcane, cocoa, coffee, and sesame production could experience a decline under both moderate and harsh climate conditions in most cases. Also, doubling crop yields by 2050 could overall mitigate the negative impact of moderate climate change. The magnitude and the direction of the impacts may vary in space and time.

Download Full-text