scholarly journals Future Impact of Climate Change on the Yield of Cocoa in Ondo State, Nigeria

Author(s):  
Femi S. Omotayo ◽  
Philip G. Oguntunde ◽  
Ayorinde A. Olufayo

This study was carried to determine the trend of cocoa yield and climatic variables and assessment of the impact of climate change on the future yield of cocoa in Ondo State, Nigeria. Annual trend statistics for cocoa yield and climatic variables were analyzed for the state using Mann-Kendall test for trend and Sen’s slope estimates. Downscaled data from six Global Circulation Models (GCMs) were used to examine the impact of climate change on the future yield of cocoa in the study area. The results of trends analysis in Ondo State showed that yield decreased monotonically at the rate of 492.18 tonnes/yr (P<0.05). An increased significant trend was established in annual rainfall trend. While Maximum temperature, minimum temperature, and mean temperature all increased at the rate of 0.02/yr (P<0.001). The ensemble of all the GCMs projected a mid-term future decrease of about 9,334 tonnes/yr by 2050 and a long-term future decrease of 13,504 tonnes/yr of cocoa by 2100. The economic implication of these is that, if the projected change in the yield of cocoa as predicted by the ensemble of all the GCMs should hold for the future, it means that Ondo state may experience a loss of about $22,470,018.22 and $32,308,584.32 by the year 2050 and 2100 respectively according to the present price of the commodity in the world market. Measures are to be taken by the government and farmers to find a way of mitigating the impacts of climate change on the future yield of the cocoa study area. This research should be extended to other cocoa producing areas in Nigeria.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Virgílio A. Bento ◽  
Andreia F. S. Ribeiro ◽  
Ana Russo ◽  
Célia M. Gouveia ◽  
Rita M. Cardoso ◽  
...  

AbstractThe impact of climate change on wheat and barley yields in two regions of the Iberian Peninsula is here examined. Regression models are developed by using EURO-CORDEX regional climate model (RCM) simulations, forced by ERA-Interim, with monthly maximum and minimum air temperatures and monthly accumulated precipitation as predictors. Additionally, RCM simulations forced by different global climate models for the historical period (1972–2000) and mid-of-century (2042–2070; under the two emission scenarios RCP4.5 and RCP8.5) are analysed. Results point to different regional responses of wheat and barley. In the southernmost regions, results indicate that the main yield driver is spring maximum temperature, while further north a larger dependence on spring precipitation and early winter maximum temperature is observed. Climate change seems to induce severe yield losses in the southern region, mainly due to an increase in spring maximum temperature. On the contrary, a yield increase is projected in the northern regions, with the main driver being early winter warming that stimulates earlier growth. These results warn on the need to implement sustainable agriculture policies, and on the necessity of regional adaptation strategies.


2021 ◽  
Author(s):  
Ignacio Martin Santos ◽  
Mathew Herrnegger ◽  
Hubert Holzmann

&lt;p&gt;In the last two decades, different climate downscaling initiatives provided climate scenarios for Europe. The most recent initiative, CORDEX, provides Regional Climate Model (RCM) data for Europe with a spatial resolution of 12.5 km, while the previous initiative, ENSEMBLES, had a spatial resolution of 25 km. They are based on different emission scenarios, Representative Concentration Pathways (RCPs) and Special Report on Emission Scenarios (SRES) respectively.&lt;/p&gt;&lt;p&gt;A study carried out by Stanzel et al. (2018) explored the hydrological impact and discharge projections for the Danube basin upstream of Vienna when using either CORDEX and ENSEMBLES data. This basin covers an area of 101.810&lt;sup&gt;&lt;/sup&gt;km&lt;sup&gt;2&lt;/sup&gt; with a mean annual discharge of 1923 m&lt;sup&gt;3&lt;/sup&gt;/s at the basin outlet. The basin is dominated by the Alps, large gradients and is characterized by high annual precipitations sums which provides valuable water resources available along the basin. Hydropower therefore plays an important role and accounts for more than half of the installed power generating capacity for this area. The estimation of hydropower generation under climate change is an important task for planning the future electricity supply, also considering the on-going EU efforts and the &amp;#8220;Green Deal&amp;#8221; initiative.&lt;/p&gt;&lt;p&gt;Taking as input the results from Stanzel et al. (2018), we use transfer functions derived from historical discharge and hydropower generation data, to estimate potential changes for the future. The impact of climate change projections of ENSEMBLE and CORDEX in respect to hydropower generation for each basin within the study area is determined. In addition, an assessment of the impact on basins dominated by runoff river plants versus basins dominated by storage plants is considered.&lt;/p&gt;&lt;p&gt;The good correlation between discharge and hydropower generation found in the historical data suggests that discharge projection characteristics directly affect the future expected hydropower generation. Large uncertainties exist and stem from the ensembles of climate runs, but also from the potential operation modes of the (storage) hydropower plants in the future.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;References:&lt;/p&gt;&lt;p&gt;Stanzel, P., Kling, H., 2018. From ENSEMBLES to CORDEX: Evolving climate change projections for Upper Danube River flow. J. Hydrol. 563, 987&amp;#8211;999. https://doi.org/10.1016/j.jhydrol.2018.06.057&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;


2021 ◽  
Author(s):  
Sabina Abba-Omar ◽  
Francesca Raffaele ◽  
Erika Coppola ◽  
Daniela Jacob ◽  
Claas Teichmann ◽  
...  

&lt;p&gt;The impact of climate change on precipitation over Southern Africa is of particular interest due to its possible devastating societal impacts. To add to this, simulating precipitation is challenging and models tend to show strong biases over this region, especially during the Austral Summer (DJF) months. One of the reasons for this is the mis-representation of the Angolan Low (AL) and its influence on Southern Africa&amp;#8217;s Summer precipitation in the models. Therefore, this study aims to explore and compare different models&amp;#8217; ability to capture the AL and its link to precipitation variability as well as consider the impact climate change may have on this link. We also explore how the interaction between ENSO, another important mode of variability for precipitation, and the Angolan Low, impact precipitation, how the models simulate this and whether this could change in the future under climate change.&amp;#160;&lt;/p&gt;&lt;p&gt;We computed the position and strength of the AL in reanalysis data and compared these results to three different model ensembles with varying resolutions. Namely, the CORDEX-CORE ensemble (CCORE), a new phase of CORDEX simulations with higher resolutions (0.22 degrees), the lower resolution (0.44 degrees) CORDEX-phase 1 ensemble (C44) and the CMIP5 models that drive the two RCM ensembles. We also used Self Organizing Maps to group DJF yearly anomaly patterns and identify which combination of ENSO and AL strength scenarios are responsible for particularly wet or dry conditions. Regression analysis was performed to analyze the relationships between precipitation and the AL and ENSO. This analysis was repeated for near (2041-2060) and far (2080-2099) future climate and compared with the present to understand how the strength of the AL, and its connection to precipitation variability and ENSO, changes in the future.&amp;#160;&lt;/p&gt;&lt;p&gt;We found that, in line with previous studies, models with stronger AL tend to produce more rainfall. CCORE tends to simulate a stronger AL than C44 and therefore, higher precipitation biases. However, the regression analysis shows us that CCORE is able to capture the relationship between precipitation and the AL strength variability as well as ENSO better than the other ensembles. We found that generally dry rainfall patterns over Southern Africa are associated with a weak AL and El Nino event whereas wet rainfall patterns occur during a strong AL and La Nina year. While the models are able to capture this, they also tend to show more neutral ENSO conditions associated with these wet and dry patterns which possibly indicates less of a connection between AL strength and ENSO than seen in the observed results. Analysis of the future results indicates that the AL weakens, this is shown across all the ensembles and could be a contributing factor to some of the drying seen. These results have applications in understanding and improving model representation of precipitation over Southern Africa as well as providing some insight into the impact of climate change on precipitation and some of its associated dynamics over this region.&lt;/p&gt;


2014 ◽  
Vol 9 (4) ◽  
pp. 432-442 ◽  
Author(s):  
Nobuhiko Sawai ◽  
◽  
Kenichiro Kobayashi ◽  
Apip ◽  
Kaoru Takara ◽  
...  

This paper assesses the impact of climate change in the Black Volta River by using data output from the atmospheric general circulation model with a 20-km resolution (AGCM20) through the Japanese Meteorological Agency (JMA) and the Meteorological Research Institute (MRI). The Black Volta, which flows mainly in Burkina Faso and Ghana in West Africa, is a major tributary of the Volta River. The basin covers 142,056 km2 and has a semi-arid tropical climate. Before applying AGCM20 output to a rainfall–runoff model, the performance of the AGCM20 rainfall data is investigated by comparing it with the observed rainfall in the Black Volta Basin. To assess the possible impact of rainfall change on river flow, a kinematic wave model, which takes into consideration saturated and unsaturated subsurface soil zones, was performed. The rainfall analysis shows that, the correlation coefficient of the monthly rainfall between the observed rainfall and AGCM20 for the present climate (1979–2004) is 0.977. In addition, the analysis shows that AGCM20 overestimates precipitation during the rainy season and underestimates the dry season for the present climate. The analysis of the AGCM20 output shows the precipitation pattern change in the future (2075–2099). In the future, precipitation is expected to increase by 3%, whereas evaporation and transpiration are expected to increase by 5% and by 8%, respectively. Also, daily maximum rainfall is expected to be 20 mm, or 60%, higher. Thus, the future climate in this region is expected to be more severe. The rainfall–runoff simulation is successfully calibrated at the Bamboi discharge gauging station in the Black Volta fromJune 2000 to December 2000 with 0.72 of the Nash–Sutcliffe model efficiency index. The model is applied with AGCM20 outputs for the present climate (1979–2004) and future climate (2075–2099). The results indicate that future discharge will decrease from January to July at the rate of the maximum of 50% and increase fromAugust to December at the rate of the maximumof 20% in the future. Therefore, comprehensive planning for both floods and droughts are urgently needed in this region.


2015 ◽  
Vol 42 (9) ◽  
pp. 634-644 ◽  
Author(s):  
Netra P. Timalsina ◽  
Knut T. Alfredsen ◽  
Ånund Killingtveit

The ice conditions in a regulated river will depend on the climatic changes as well as the changes to the hydropower operation strategies in the future. The existing literature shows that very few studies have been carried out to investigate the impact of climate change on the river ice regime, which is important for operation of hydropower in cold climates. In this study, a series of modelling tools have been used to transform the climate change signal in terms of precipitation and air temperature into cross-section based river ice assessment in a basin with a complicated hydropower system. The study is based on the EURO-CORDEX climate change data extracted from a regional climate model driven by a suite of five general circulation models with three representative concentration pathways. Hydrological model simulation results show that the winter and spring flow will be increased, which will have an impact on the river ice conditions towards the middle and end of this century. Reservoir-hydropower model simulation shows that the production flows in the winter will be increased in the future. River ice model simulation shows the number of days with freezing water temperature are reduced in the future climate, and correspondingly days with frazil ice are reduced at most of the locations in the study area. The future period with ice cover will also be shortened. The paper also demonstrates a general methodology and procedure to simulate future ice conditions in a regulated river combining multiple models and data sets.


2021 ◽  
Vol 19 (4) ◽  
pp. 266-281
Author(s):  
Allan Sriratana Tabucanon ◽  
◽  
Areeya Rittima ◽  
Detchasit Raveephinit ◽  
Yutthana Phankamolsil ◽  
...  

Bhumibol Dam is the largest dam in the central region of Thailand and it serves as an important water resource. The dam’s operation relies on reservoir operating rules that were developed on the basis of the relationships among rainfall-inflow, water balance, and downstream water demand. However, due to climate change, changing rainfall variability is expected to render the reliability of the rule curves insecure. Therefore, this study investigated the impact of climate change on the reliability of the current reservoir operation rules of Bhumibol Dam. The future scenarios from 2000 to 2099 are based on EC-EARTH under RCP4.5 and RCP8.5 scenarios downscaled by RegCM4. MIKE11 HD was developed for the inflow simulation. The model generates the inflow well (R2=0.70). Generally, the trend of increasing inflow amounts is expected to continue in the dry seasons from 2000-2099, while large fluctuations of inflow are expected to be found in the wet seasons, reflecting high uncertainties. In the case of standard deviations, a larger deviation is predicted under the RCP8.5 scenario. For the reservoir’s operation in a climate change study, standard operating procedures were applied using historical release records to estimate daily reservoir release needed to serve downstream water demand in the future. It can be concluded that there is high risk of current reservoir operating rules towards the operation reliability under RCP4.5 (80% reliability), but the risk is lower under RCP8.5 (87% reliability) due to increased inflow amounts. The unmanageability occurs in the wet season, cautioning the need to redesign the rules.


2021 ◽  
Vol 38 (4) ◽  
pp. 1118-1124
Author(s):  
Sayed Mohibul HOSSEN ◽  
◽  
Mohd Tahir ISMAIL ◽  
Mosab I. TABASH ◽  
Suhaib ANAGREH ◽  
...  

In this study, we aim to highlight the impact of climate change as well as seasonality on tourist’s arrival in Bangladesh. The SANCOVA modeling framework modified by the ANCOVA model is used to examine the impact of climate change on tourists’ arrivals. The results show seasonality has a 91% effect on tourist’s arrival in Bangladesh. The maximum and minimum variation of climatic variables on tourists’ arrival in Bangladesh is rainfall and humidity, respectively. The winter and summer seasons have similar and more impact on tourist’s arrival in Bangladesh. Our findings indicate that the tourism industry of Bangladesh is more vulnerable to seasonal variation than the overall economy. The present study has significant implications for both policymakers and tourisms destination alike to plan for tourism in Bangladesh.


2021 ◽  
Vol 22 (2) ◽  
pp. 191-197
Author(s):  
K. PHILIP ◽  
S.S. ASHA DEVI ◽  
G.K. JHA ◽  
B.M.K. RAJU ◽  
B. SEN ◽  
...  

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.


Author(s):  
Baljeet Kaur ◽  
Som Pal Singh ◽  
P.K. Kingra

Background: Climate change is a nonpareil threat to the food security of hundred millions of people who depends on agriculture for their livelihood. A change in climate affects agricultural production as climate and agriculture are intensely interrelated global processes. Global warming is one of such changes which is projected to have significant impacts on environment affecting agriculture. Agriculture is the mainstay economy in trans-gangetic plains of India and maize is the third most important crop after wheat and rice. Heat stress in maize cause several changes viz. morphological, anatomical and physiological and biochemical changes. Methods: In this study during 2014-2018, impact of climate change on maize yield in future scenarios was simulated using the InfoCrop model. Average maize yield from 2001-15 was collected for Punjab, Haryana and Delhi to calibrate and validate the model. Future climatic data set from 2020 to 2050 was used in the study to analyse the trends in climatic parameters.Result: Analysis of future data revealed increasing trends in maximum temperature and minimum temperature. Rainfall would likely follow the erratic behaviour in Punjab, Haryana and Delhi. Increase in temperature was predicted to have negative impact on maize yield under future climatic scenario.


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