scholarly journals Impact of Climate Change on Maize and Pigeonpea Yields in Semi-Arid Kenya

2021 ◽  
Author(s):  
Kizito Musundi Kwena ◽  
G.N. Karuku ◽  
F.O. Ayuke ◽  
A.O. Esilaba
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Production Systems ◽  
Maize Yield ◽  
Research Centre ◽  
Climate Data ◽  
Maize Crop ◽  
Impact Of Climate Change ◽  
Industrial Research Organization ◽  
The Impact

The objective of this study was to assess the impact of climate change on intercrops of maize and improved pigeonpea varieties developed. Future climate data for Katumani were downscaled from the National Meteorological Research Centre (CNRM) and Commonwealth Scientific and Industrial Research Organization (CSIRO) climate models using the Statistical Downscaling Model (SDSM) version 4.2. Both models predicted that Katumani will be warmer by 2°C and wetter by 11% by 2100. Agricultural Production Systems Simulator (APSIM) model version 7.3 was used to assess the impact of both increase in temperature and rainfall on maize and pigeonpea yield in Katumani. Maize crop will increase by 141–-150% and 10–-23 % in 2050 and 2100, respectively. Intercropping maize with pigeonpea will give mixed maize yield results. Pigeonpea yields will decline by 10–20 and 4–9% by 2100 under CSIRO and CNRM models, respectively. Intercropping short and medium duration pigeonpea varieties with maize will reduce pigeonpea yields by 60–80 and 70–90% under the CSIRO and CNRM model, respectively. There is a need to develop heat and waterlogging-tolerant pigeonpea varieties to help farmers adapt to climate change and to protect the huge pigeonpea export market currently enjoyed by Kenya.

scholarly journals A~simple model for predicting the global distribution of the N<sub>2</sub> fixing host genus <i>Alnus Mill.</i>: impact of climate change on the global distribution in 2100

2013 ◽  
Vol 10 (8) ◽  
pp. 13049-13095 ◽  
Author(s):  
A. Sakalli
Keyword(s):  
Climate Change ◽  
Nitrogen Fixation ◽  
Climate Models ◽  
Global Distribution ◽  
Linear Functions ◽  
Distribution Model ◽  
Climate Data ◽  
Host Genus ◽  
Impact Of Climate Change ◽  
The Impact

Abstract. The importance of N2-fixing plants has increased in last decades. Alnus (alder) is an important plant group because of its nitrogen fixation ability. Alders are generally distributed in humid locations of boreal, temperate and tropical climate zones, where the nitrogen fixation is an important nitrogen source for other plants. To model the nitrogen fixation by alder, data about the global distribution of alder is absolutely required. In this study a new method and model to predict the distribution of N2-fixing genus on global scale is presented. Three linear functions were defined for the determination of climate area of alder locations. The distribution model was improved with the aid of the soil units from FAO-Unesco Soil Database, and vegetation types from Schmithüsen's biogeographical atlas. The model (Alnus-Distribution-Model, ADM) was also developed to predict the impact of climate change on alder distribution by using climate data of five relevant climate models (PCM, ECHam4, HadCM3, CSIRO2 and CGCM2), and four IPCC climate scenarios (i.e. A1FI, A2, B1 and B2) in 2100. The model covered basic approaches to understand the climate change effect on plant migration in the future.

scholarly journals Reliability of Rain-Fed Maize Yield Simulation Using LARS-WG Derived CMIP5 Climate Data at Mount Makulu, Zambia

2020 ◽  
Vol 12 (11) ◽  
pp. 275
Author(s):  
Charles Bwalya Chisanga ◽  
Elijah Phiri ◽  
Vernon R. N. Chinene
Keyword(s):  
Climate Change ◽  
Simulation Models ◽  
Maize Yield ◽  
Growth And Yield ◽  
Research Station ◽  
Climate Scenarios ◽  
Climate Data ◽  
Impact Of Climate Change ◽  
Rcp 8.5 ◽  
The Impact

The impact of climate change on crop growth and yield can be predicted using crop simulation models. A study was conducted to assess the reliability and uncertainty of simulated maize yield for the near future in 2050s at Mount Makulu (latitude = 15.550o S, longitude = 28.250o E, altitude = 1213 m), Zambia. The Long Ashton Research Station Weather Generator (LARS-WG) was used to generate baseline (1980-2010) and future (2040-2069) climate scenarios for two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). Results showed that mean temperature would increase by 2.09oC (RCP 4.5) and 2.56oC (RCP 8.5) relative to the baseline (1980-2010). However, rainfall would reduce by 9.84% (RCP 4.5) and 11.82% (RCP 8.5). The CERES-Maize model simulated results for rainfed maize growth showed that the simulated parameters; days after planting (DAP), biomass and grain yield would reduce from 2040-2069/1980-2010 under both RCP4.5 and RCP8.5 scenarios. The LARS-WG was successfully for our location can be used in generating climate scenarios for impact studies to inform policy, stakeholders and decision makers. Adaptation strategies to mitigate for the potential impact of climate change includes several sowing dates, cultivar selection that are efficient at using nitrogen fertilizer and planting new cultivars breeds that will thrive under low root soil water content and higher temperatures.

scholarly journals Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Models ◽  
Assessment Tool ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Data ◽  
The Future ◽  
The Impact ◽  
Mountainous River

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.

scholarly journals Impact of climate change on sediment yield in the Mekong River basin: a case study of the Nam Ou basin, Lao PDR

2013 ◽  
Vol 17 (1) ◽  
pp. 1-20 ◽  
Author(s):  
B. Shrestha ◽  
M. S. Babel ◽  
S. Maskey ◽  
A. van Griensven ◽  
S. Uhlenbrook ◽  
...  
Keyword(s):  
Climate Change ◽  
Sediment Yield ◽  
General Circulation ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Circulation Model ◽  
Sediment Flux ◽  
Seasonal Temperature ◽  
Impact Of Climate Change ◽  
The Impact

Abstract. This paper evaluates the impact of climate change on sediment yield in the Nam Ou basin located in northern Laos. Future climate (temperature and precipitation) from four general circulation models (GCMs) that are found to perform well in the Mekong region and a regional circulation model (PRECIS) are downscaled using a delta change approach. The Soil and Water Assessment Tool (SWAT) is used to assess future changes in sediment flux attributable to climate change. Results indicate up to 3.0 °C shift in seasonal temperature and 27% (decrease) to 41% (increase) in seasonal precipitation. The largest increase in temperature is observed in the dry season while the largest change in precipitation is observed in the wet season. In general, temperature shows increasing trends but changes in precipitation are not unidirectional and vary depending on the greenhouse gas emission scenarios (GHGES), climate models, prediction period and season. The simulation results show that the changes in annual stream discharges are likely to range from a 17% decrease to 66% increase in the future, which will lead to predicted changes in annual sediment yield ranging from a 27% decrease to about 160% increase. Changes in intra-annual (monthly) discharge as well as sediment yield are even greater (−62 to 105% in discharge and −88 to 243% in sediment yield). A higher discharge and sediment flux are expected during the wet seasons, although the highest relative changes are observed during the dry months. The results indicate high uncertainties in the direction and magnitude of changes of discharge as well as sediment yields due to climate change. As the projected climate change impact on sediment varies remarkably between the different climate models, the uncertainty should be taken into account in both sediment management and climate change adaptation.

scholarly journals Sensitivity of Maize Yield in Smallholder Systems to Climate Scenarios in Semi-Arid Regions of West Africa: Accounting for Variability in Farm Management Practices

Agronomy ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 639 ◽  
Author(s):  
Bright Freduah ◽  
Dilys MacCarthy ◽  
Myriam Adam ◽  
Mouhamed Ly ◽  
Alex Ruane ◽  
...  
Keyword(s):  
Climate Change ◽  
Arid Regions ◽  
Climate Models ◽  
Smallholder Farmers ◽  
Maize Yield ◽  
Climate Scenarios ◽  
Relative Standard ◽  
The Impact ◽  
Semi Arid ◽  
Smallholder Systems

Climate change is estimated to exacerbate existing challenges faced by smallholder farmers in Sub-Sahara Africa. However, limited studies quantify the extent of variation in climate change impact under these systems at the local scale. The Decision Support System for Agro-technological Transfer (DSSAT) was used to quantify variation in climate change impacts on maize yield under current agricultural practices in semi-arid regions of Senegal (Nioro du Rip) and Ghana (Navrongo and Tamale). Multi-benchmark climate models (Mid-Century, 2040–2069 for two Representative Concentration Pathways, RCP4.5 and RCP8.5), and multiple soil and management information from agronomic surveys were used as input for DSSAT. The average impact of climate scenarios on grain yield among farms ranged between −9% and −39% across sites. Substantial variation in climate response exists across farms in the same farming zone with relative standard deviations from 8% to 117% at Nioro du Rip, 13% to 64% in Navrongo and 9% to 37% in Tamale across climate models. Variations in fertilizer application, planting dates and soil types explained the variation in the impact among farms. This study provides insight into the complexities of the impact of climate scenarios on maize yield and the need for better representation of heterogeneous farming systems for optimized outcomes in adaptation and resilience planning in smallholder systems.

scholarly journals The Impact of Climate Change on Material Degradation Criteria in Heritage over Iran: Regional Climate Model Evaluation

2020 ◽  
Vol 172 ◽  
pp. 02006
Author(s):  
Hamed Hedayatnia ◽  
Marijke Steeman ◽  
Nathan Van Den Bossche
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Salt Crystallization ◽  
Climate Modelling ◽  
Impact Of Climate Change ◽  
Climate Change Effects ◽  
The Impact

Understanding how climate change accelerates or slows down the process of material deterioration is the first step towards assessing adaptive approaches for the preservation of historical heritage. Analysis of the climate change effects on the degradation risk assessment parameters like salt crystallization cycles is of crucial importance when considering mitigating actions. Due to the vulnerability of cultural heritage in Iran to climate change, the impact of this phenomenon on basic parameters plus variables more critical to building damage like salt crystallization index needs to be analyzed. Regional climate modelling projections can be used to asses the impact of climate change effects on heritage. The output of two different regional climate models, the ALARO-0 model (Ghent University-RMI, Belgium) and the REMO model (HZG-GERICS, Germany), is analyzed to find out which model is more adapted to the region. So the focus of this research is mainly on the evaluation to determine the reliability of both models over the region. For model validation, a comparison between model data and observations was performed in 4 different climate zones for 30 years to find out how reliable these models are in the field of building pathology.

scholarly journals The impact of climate change on the resin productivity of dammar tree (Agathis alba) in Inamosol subdistrict, West Seram district, Maluku-Indonesia

2021 ◽  
Vol 883 (1) ◽  
pp. 012079
Author(s):  
J M Matinahoru
Keyword(s):  
Climate Change ◽  
Relative Humidity ◽  
Sampling Technique ◽  
Climate Data ◽  
Purposive Sampling ◽  
Impact Of Climate Change ◽  
Average Temperature ◽  
Change Factors ◽  
Temperature And Humidity ◽  
The Impact

Abstract This research was aimed to determine the impact of climate change on the resin productivity of dammar tree. This research will be useful as data and information for farmers and government to maintain the resin of dammar tree to be optimal and sustainable in production. This research was conducted in Inamosol Sub-district, West Seram District, Maluku Indonesia, during September-October 2020. Village and farmer samples were determined by purposive sampling technique. The selected villages were Honitetu, Hukuanakota and Rambatu. Furthermore, from each village, It was ten farmers to select for interviews and filling the questionnaire. The results showed that the average resin production of farmers in 2019 was 904.2 kg/farmer, while in 2020 was 523.7 kg/farmer. This means that it occurred a decline in resin production in 2020 about 42.08 % for each farmer—the leading cause of the decreased production as climate change factors, namely rainfall, temperature and humidity. Based on climate data of West Seram District in 2019 indicated that rainfall has occurred during six months with an average temperature of 27 °C and relative humidity of 82 %. Meanwhile, in 2020 the rainfall occurs for nine months with an average temperature of 26.5 °C, and relative humidity of 85 %.

scholarly journals Simulating the Impact of Climate Change on Maize Productivity in Trans-gangetic Plains using Info Crop Model

2020 ◽  
Author(s):  
Baljeet Kaur ◽  
Som Pal Singh ◽  
P.K. Kingra
Keyword(s):  
Climate Change ◽  
Maize Yield ◽  
Maximum Temperature ◽  
Climatic Data ◽  
Data Set ◽  
Gangetic Plains ◽  
Impact Of Climate Change ◽  
Model Average ◽  
In Trans ◽  
The Impact

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.

scholarly journals Modelling the impact of climate change on maize yield in Victoria Nile Sub-basin, Uganda

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Joash Bwambale ◽  
Khaldoon A. Mourad
Keyword(s):  
Climate Change ◽  
Food Security ◽  
Crop Production ◽  
Maize Yield ◽  
Well Being ◽  
Adaptation Measures ◽  
Impact Of Climate Change ◽  
Aquacrop Model ◽  
Supplementary Irrigation ◽  
The Impact

AbstractAgriculture is the backbone of Uganda’s economy, with about 24.9% contribution to the gross domestic product (GDP) as per the Uganda National Household Survey 2016/17. Agricultural productivity (yield per hectare) is still low due to the high dependence on rain-fed subsistence farming. Climate change is expected to further reduce the yield per hectare. Therefore, this study aims to evaluate the potential impact of climate change on maize yield in the Victoria Nile Sub-basin using the AquaCrop model. It further assesses the possible adaptation measures to climate change. The Hadley Centre Global Environmental Model version 2–Earth System (HadGEM2-ES) data downloaded from the Coordinated Regional Downscaling Experiment (CORDEX) was used to simulate maize yield in the near future (2021–2040), mid future (2041–2070) and late future (2071–2099). Results show that maize yield is likely to reduce by as high as 1–10%, 2–42% and 1–39% in the near, mid and late futures, respectively, depending on the agro-ecological zone. This decline in maize yield can have a significant impact on regional food security as well as socio-economic well-being since maize is a staple crop. The study also shows that improving soil fertility has no significant impact on maize yield under climate change. However, a combined application of supplementary irrigation and shifting the planting dates is a promising strategy to maintain food security and socio-economic development. This study presents important findings and adaptation strategies that policymakers and other stakeholders such as farmers can implement to abate the effects of climate change on crop production.

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