scholarly journals Climate Change and Agriculture in Ethiopia: A Case Study of Mettu Woreda

2019 ◽  
Vol 3 (3) ◽  
pp. 61-79
Author(s):  
S.N. Singh
Keyword(s):  
Climate Change ◽  
Adverse Effect ◽  
Crop Yields ◽  
Animal Health ◽  
Agricultural Productivity ◽  
Crop Productivity ◽  
Descriptive Statistics ◽  
State And Local ◽  
The Impact

This paper summarizes the arguments and counterarguments within the scientific discussion on the issue of climate change and its affect on agricultural productivity in Ethiopia. The main purpose of the research is to analyze the impact of climate change on the productivity of agricultural crops. Systematization literary sources and approaches for solving the problem associate were analyzed that indicates there is a significant adverse effect of climate change on agricultural productivity as well as allied fields. The relevance of the decision of this scientific problem is that the community participation and state interventions are required at grass-roots level. Investigation of the topic of climate change and agriculture in Ethiopia in the paper is carried out broadly in the following logical sequence at an appropriate empirical standard level. Methodological tools of the research methods were descriptive statistics and the year of research was 2018-19. The object of research is the chosen for Ethiopia as a whole and case study was carried out in Mettu Woreda to verify the significance. The paper presents the results of an empirical analysis of quantitative data, which showed that there is an adverse effect of climate change on agricultural productivity in the region. The climate change affects agricultural productivity and production through shortening of maturity period and to decreasing crop yields, changing livestock feed availability, affecting animal health growth and reproduction depressing the quality and quantity of the crops, changing distribution rate, contracting pastoral zones, expansion of tropical dry forests and expansion of desertification etc.The research empirically confirms and theoretically proves that highlights the coordination between state and local communities are required to combat the adverse effect of climate change. The results of the research can be useful for policy maker, researchers, academicians and other international organizations like UNEP and UNDP etc. Keywords: climate change, random sampling, descriptive statistics, crop productivity, food security and livestock.

Upscaling modelled crop yields to regional scale: A case study using DSSAT for spring wheat on the Canadian prairies

2015 ◽  
Vol 95 (1) ◽  
pp. 49-61 ◽  
Author(s):  
Ted Huffman ◽  
Budong Qian ◽  
Reinder De Jong ◽  
Jiangui Liu ◽  
Hong Wang ◽  
...  
Keyword(s):  
Climate Change ◽  
Spring Wheat ◽  
Input Data ◽  
Crop Yields ◽  
Regional Scale ◽  
Climate Change Impacts ◽  
Crop Productivity ◽  
Canadian Prairies ◽  
Crop Models

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.

An Empirical Evidence of Global Warming and its impact on India’s Agricultural Production

2019 ◽  
Vol 118 (10) ◽  
pp. 332-340
Author(s):  
Dr.P. Prema ◽  
Ms.R. Kanchana
Keyword(s):  
Climate Change ◽  
Agricultural Production ◽  
Agricultural Land ◽  
Crop Yields ◽  
Grain Filling ◽  
Crop Productivity ◽  
Large Country ◽  
Impact Of Climate Change ◽  
Different Types ◽  
The Impact

India is a large country with all types of climates and different kinds of soil requiring different types of farming. Most of the agricultural land in India is dependent on rainfall for irrigation. India has about 15 Agro-climatic zones with different types of farming methods and crops. As most of the population is dependent on agriculture and two-third of the country depend on monsoon rains to aid in agriculture, any change in frequency of the rains will affect these areas critically. Assessment of the effects of global climate changes on agriculture might help to properly anticipate and adapt farming to maximize agricultural production. At the same time agriculture has been shown significant effects on climate change, primarily through the production and release of greenhouse gases such as carbon dioxide, methane, and nitrous oxide. The impact of climate change on agriculture could result in problems like food security and may threaten the livelihood on which much of the population depends. Climate change can affect crop yields ( both positively and negatively), as well as the types of crop that can be grown in certain areas, by impacting agricultural inputs such as water for irrigation, amounts of solar radiation that affect plant growth, as well as prevalence of pests. The impact of climate change on wheat showed that its yield decreased due to the adverse effects of temperature during grain filling and maturity stages of the growth. The results of this study indicate that crop characteristics such as sensitivity of grain filling duration to temperature, play a major role in determining the effects of climate change on crop productivity. Several studies projected increase or decrease in yields of cereal crops, oilseed and pulses crops depending on interaction of temperature and CO2 changes in India. The present study has selected a thirteen years period from 2000 – 2012. .

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

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.

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

Atmosphere ◽  
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.

Heat-related mortality under climate change and the impact of adaptation through air conditioning: A case study from Thessaloniki, Greece

2021 ◽  
pp. 111285
Author(s):  
Panayiotis Kouis ◽  
Kyriaki Psistaki ◽  
George Yiallouros ◽  
Antonis Michanikou ◽  
Maria G. Kakkoura ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Conditioning ◽  
The Impact ◽  
Related Mortality

scholarly journals Potential Impacts of Future Climate Change Scenarios on Ground Subsidence

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 219 ◽  
Author(s):  
Antonio-Juan Collados-Lara ◽  
David Pulido-Velazquez ◽  
Rosa María Mateos ◽  
Pablo Ezquerro
Keyword(s):  
Climate Change ◽  
Land Subsidence ◽  
Ground Subsidence ◽  
Lower Percentage ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Fine Grained ◽  
Fine Grained Material ◽  
The Impact

In this work, we developed a new method to assess the impact of climate change (CC) scenarios on land subsidence related to groundwater level depletion in detrital aquifers. The main goal of this work was to propose a parsimonious approach that could be applied for any case study. We also evaluated the methodology in a case study, the Vega de Granada aquifer (southern Spain). Historical subsidence rates were estimated using remote sensing techniques (differential interferometric synthetic aperture radar, DInSAR). Local CC scenarios were generated by applying a bias correction approach. An equifeasible ensemble of the generated projections from different climatic models was also proposed. A simple water balance approach was applied to assess CC impacts on lumped global drawdowns due to future potential rainfall recharge and pumping. CC impacts were propagated to drawdowns within piezometers by applying the global delta change observed with the lumped assessment. Regression models were employed to estimate the impacts of these drawdowns in terms of land subsidence, as well as to analyze the influence of the fine-grained material in the aquifer. The results showed that a more linear behavior was observed for the cases with lower percentage of fine-grained material. The mean increase of the maximum subsidence rates in the considered wells for the future horizon (2016–2045) and the Representative Concentration Pathway (RCP) scenario 8.5 was 54%. The main advantage of the proposed method is its applicability in cases with limited information. It is also appropriate for the study of wide areas to identify potential hot spots where more exhaustive analyses should be performed. The method will allow sustainable adaptation strategies in vulnerable areas during drought-critical periods to be assessed.

scholarly journals The Pitfalls of Relating Weeds, Herbicide Use, and Crop Yield: Don't Fall Into the Trap! A Critical Review

2020 ◽  
Vol 2 ◽  
Author(s):  
Nathalie Colbach ◽  
Sandrine Petit ◽  
Bruno Chauvel ◽  
Violaine Deytieux ◽  
Martin Lechenet ◽  
...  
Keyword(s):  
Crop Yield ◽  
Weed Management ◽  
Crop Production ◽  
Yield Loss ◽  
Crop Yields ◽  
Cropping Systems ◽  
Crop Productivity ◽  
Arable Farming ◽  
Herbicide Use ◽  
The Impact

The growing recognition of the environmental and health issues associated to pesticide use requires to investigate how to manage weeds with less or no herbicides in arable farming while maintaining crop productivity. The questions of weed harmfulness, herbicide efficacy, the effects of herbicide use on crop yields, and the effect of reducing herbicides on crop production have been addressed over the years but results and interpretations often appear contradictory. In this paper, we critically analyze studies that have focused on the herbicide use, weeds and crop yield nexus. We identified many inconsistencies in the published results and demonstrate that these often stem from differences in the methodologies used and in the choice of the conceptual model that links the three items. Our main findings are: (1) although our review confirms that herbicide reduction increases weed infestation if not compensated by other cultural techniques, there are many shortcomings in the different methods used to assess the impact of weeds on crop production; (2) Reducing herbicide use rarely results in increased crop yield loss due to weeds if farmers compensate low herbicide use by other efficient cultural practices; (3) There is a need for comprehensive studies describing the effect of cropping systems on crop production that explicitly include weeds and disentangle the impact of herbicides from the effect of other practices on weeds and on crop production. We propose a framework that presents all the links and feed-backs that must be considered when analyzing the herbicide-weed-crop yield nexus. We then provide a number of methodological recommendations for future studies. We conclude that, since weeds are causing yield loss, reduced herbicide use and maintained crop productivity necessarily requires a redesign of cropping systems. These new systems should include both agronomic and biodiversity-based levers acting in concert to deliver sustainable weed management.

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

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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