Climate variability and maize yield in the Limpopo region of South Africa: Results from GME and MELE methods

Akpalu, Wisdom; Rashid, Hassan M.; Ringler, Claudia

doi:10.1080/17565529.2011.582269

Cited by 29 publications

(38 citation statements)

References 6 publications

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“…This is aggravated by the fact that rural households have to cope with both poverty and variability in climate considering that their livelihood strategies are linked to sectors such as agriculture and forestry that are impacted by climate change. Recurrent droughts and floods are considered to be some of the major factors driving people into poverty and to seek non-farm alternatives to sustain their livelihoods (Shewmake 2008;Akpalu et al 2008). In addition, livelihoods of rural people are highly dependent on the use of natural resources and services for the supply of basic needs such as food, shelter, medicine and income generation (Shackleton et al 2007;Kalaba et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Livelihoods, land use and land cover change in the Zambezi Region, Namibia

et al. 2015

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This paper examines the socio-economic drivers of land use and land cover change and assesses the impacts of such changes to rural livelihoods in the Zambezi region of northern Namibia. We carried out a longitudinal analysis of Landsat imagery of land use and land cover. The analysis revealed that the amount of land in the region covered by forest increased significantly in the period from 1991 to 2010 whilst crop/grass land decreased. Focus group meetings, key informant interviews and semi-structured interviews covering 424 households stratified by gender were used. The results show that natural resource uses are vitally important in the rural livelihoods. The drivers of land use and land cover change are agricultural expansion, population increase and illegal logging. Livelihood coping strategies include piecework, food aid, borrowing from relatives and wild food collection. By gender stratification, piecework contributed 37 and 63 % while

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Section: Introductionmentioning

confidence: 99%

Livelihoods, land use and land cover change in the Zambezi Region, Namibia

et al. 2015

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“…The likely impact of climate change on crop yield can be determined either by experimental data or by crop growth simulation models. Akpalu et al (2008) studied the climate impacts on maize yield in the Limpopo Basin of South Africa and showed that increased temperature and rainfall are responsible for the crop yield and the precipitation is more important for crop yield than the temperature. Krishnan et al (2007) analysed the impacts of elevated carbon dioxide and temperature on irrigated rice yield in eastern India using ORYZAI and Info Croprice models and the result shows that increased carbon dioxide concentration can increase rice yield, which is concerned with the sterility of rice spikelets at higher temperature, the sowing ting and the selection of genotypes.…”

Section: Effects Of Climate Change On Crop Production: Research Examplesmentioning

confidence: 99%

The Rainfall Factor of Climate Change Effects on the Agricultural Environment: A Review

Ojo¹,

Ilunga²

2017

American Journal of Applied Sciences

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The study of the climatic elements is vital for sustainable development of agriculture of a region. Particularly, rainfall temporal analyses for trends, fluctuations and periodicities are necessary as such can indirectly furnish the status of an environment. A trend may be quite instructive for different segments of the human and natural systems. Extreme weather events that can lead to events such as drought, prolonged heat spell and flooding while these can be accessed through the statistical analysis of a region's temporal rainfall regime. The global concern on the apparent deterioration in all of the earth's natural systems, particularly the climate sub-system and global warming with climate change pandemic renders credence to trend and periodicity analyses of climatic elements. This paper therefore did a review of studies of cases of climate change effects on the agricultural environment with emphasis on rainfall, as an important factor.

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“…The accelerated decline in dam water spatial extent in 2015 could be due to the drought that year and the increased demand for water for irrigation and domestic uses. Also contributing to wetland degradation in the study area are other factors, which include increased evapotranspiration due to rising temperatures (Akpalu et al, 2009), pollution from acid mine drainage from coal mining (Hobbs et al, 2008), and a declining water table due to increased groundwater abstraction (Beumer, 2010 …”

Section: Seasonal Variations In Wetland Inundated Areamentioning

confidence: 99%

“…Other factors like cultivation, which affects 21% of wetland area, are also contributing to wetland degradation in the catchment. Besides the recurrence of drought and increased anthropogenic activities which are aiding wetland degradation in the study area, there are also other contributing factors, which include: increased evapotranspiration due to increasing temperatures (Akpalu et al, 2009), pollution from acid mine drainage from coal mining (Hobbs et al, 2008), and declining water table due to increased groundwater abstraction (Beumer, 2010). The methodology used in this study not only detects changes in wetland inundated area, but also quantifies the changes that have been taking place over the years.…”

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confidence: 99%

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Determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing

Nhamo

Magidi

Dickens

2017

WSA

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Wetlands can only be well managed if their spatial location and extent are accurately documented, which presents a problem as wetland type and morphology are highly variable. Current efforts to delineate wetland extent are varied, resulting in a host of inconsistent and incomparable inventories. This study, done in the Witbank Dam Catchment in Mpumalanga Province of South Africa, explores a remote-sensing technique to delineate wetland extent and assesses the seasonal variations of the inundated area. The objective was to monitor the spatio-temporal changes of wetlands over time through remote sensing and GIS for effective wetland management. Multispectral satellite images, together with a digital elevation model (DEM), were used to delineate wetland extent. The seasonal variations of the inundated area were assessed through an analysis of monthly water indices derived from the normalised difference water index (NDWI). Landsat images and DEM were used to delineate wetland extent and MODIS images were used to assess seasonal variation of the inundated area. A time-series trend analysis on the delineated wetlands shows a declining tendency from 2000 to 2015, which could worsen in the coming few years if no remedial action is taken. Wetland area declined by 19% in the study area over the period under review. An analysis of NDWI indices on the wetland area showed that wetland inundated area is highly variable, exhibiting an increasing variability over time. An overlay of wetland area on cultivated land showed that 21% of the wetland area is subjected to cultivation which is a major contributing factor to wetland degradation.

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Climate variability and maize yield in the Limpopo region of South Africa: Results from GME and MELE methods

Cited by 29 publications

References 6 publications

Livelihoods, land use and land cover change in the Zambezi Region, Namibia

Livelihoods, land use and land cover change in the Zambezi Region, Namibia

The Rainfall Factor of Climate Change Effects on the Agricultural Environment: A Review

Determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing

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