Analysis of Dry-Spells in the Western Maize-Growing Areas of South Africa
- Investigate the initial and conditional probabilities of dry- and wet-spell pentads using the Markov chain model in the western maize-growing region from mid-January to end of February;
- Determine direction and magnitude of trends of dry-spells using the Mann–Kendal monotonic trend test and the Sen slope estimator.
2. Materials and Methods
2.1. Study Area
2.3. Data Analysis
2.3.1. Calculation of the Wet- and Dry-Spells Using the Markov Chain
2.3.2. Trend Detection Using the Mann–Kendall Test
2.3.3. Sen’s Slope Estimator
2.3.4. Spatial Analysis Interpolation
- It provides a measure of uncertainty attached to the results (i.e., Kriging variance).
- It accounts for direction-dependent relationships (i.e., spatial anisotropy).
- Weights are assigned to observations based on the spatial correlation of data instead of assumptions made by the analyst for IDW.
- Kriging predictions are not constrained to the range of observations used for interpolation.
- Data measured over different spatial supports can be combined, and change in support, such as downscaling or upscaling, can be conducted.
3.1. Total Annual Rainfall
3.2. Dry-Spell Occurrence
3.3. Trend Analysis of Dry-Spells
- An investigation into optimum planting dates by using crop models to avoid the occurrence of dry-spells should be conducted, which is crucial to assist farmers and decision makers in preventing production losses and other adverse effects of dry-spells.
- The impact of climate change on future projections of dry-spells should be investigated.
Conflicts of Interest
- Department of Agriculture, Land Reform and Rural Development (DALRRD). A Profile of the South African Maize Market Value Chain; DALRRD: Pretoria, South Africa, 2020. [Google Scholar]
- Diko, A.; Jun, W. Influencing Factors of Maize Production in South Africa: The case of Mpumalanga, Free State and North West Provinces. Department of Management, Jilin Agricultural University, Changchun, China. Asian J. Adv. Agric. Res. 2020, 14, 25–34. [Google Scholar] [CrossRef]
- Du Plessis, J. Maize Production; Directorate Agricultural Information Services, Department of Agriculture in Cooperation with ARC-Grain Crops Institute; Department of Agriculture: Potchefstroom, South Africa, 2003. [Google Scholar]
- DARDLEA. Water Infrastructure Report for Sabie River Catchment: Internal Document. 2017. Available online: https://www.iucma.co.za/wp-content/uploads/2018/11/Annual%20Report%202017-18.pdf (accessed on 16 January 2017).
- Mengistu, M.G.; Olivier, C.; Botai, J.O.; Adeola, A.M.; Daniel, S. Spatial and temporal analysis of the mid-summer dry-spells for the summer rainfall region of South Africa. South African Weather Service, Private Bag X097, Centurion, South Africa. Water SA 2021, 47, 76–87. [Google Scholar] [CrossRef]
- Mzezewa, J.; Misi, T.; Van Rensburg, L. Characterisation of rainfall at a semi-arid ecotope in the Limpopo Province (South Africa) and its implications for sustainable crop production. Water SA 2010, 36, 19–26. [Google Scholar] [CrossRef][Green Version]
- Tyson, P.D. Climate Change and Variability in Southern Africa; Oxford University Press: Cape Town, South Africa; University of Witwatersrand: Johannesburg, South Africa, 1986. [Google Scholar]
- Pereira, L.S.; Cordery, I.; Iacovides, I. Coping with water scarcity. In Addressing the Challenges; Springer Science and Business Media: Dordrecht, The Netherlands, 2009; 382p. [Google Scholar]
- Taljaard, J.J. Atmospheric Circulation Systems, Synoptic Climatology, and Weather Phenomena of South Africa: Part 6: Rainfall in South Africa; Technical Paper 32; South African Weather Bureau: Pretoria, South Africa, 1996. [Google Scholar]
- Engelbrecht, C.J.; Landman, W.A.; Engelbrecht, F.A.; Malherbe, J. A synoptic decomposition of rainfall over the Cape south coast of South Africa. Clim. Dyn. 2014, 44, 2589–2607. [Google Scholar] [CrossRef]
- Ramos, M.C. Rainfall distribution patterns and their change over time in Mediterranean area. Theor. Appl. Climatol. 2001, 69, 163–170. [Google Scholar] [CrossRef]
- Munodawofa, A. The effect of rainfall characterisation and tillage on sheet erosion and maize grain yield in semi-arid conditions of granitic sandy soils of Zimbabwe. Appl. Environ. Sci. 2012, 2012, 243815. [Google Scholar]
- Belfield, S.; Brown, C. Field Crop Manual: A Guide to Upland Production in Cambodia; ACIAR Project; Australian Centre for International Agriculture Research: Canberra, ACT, Australia, 2008. [Google Scholar]
- Department of Agriculture, Forestry and Fisheries (DAFF). Maize; Directorate Plant Production: Pretoria, South Africa, 2008. [Google Scholar]
- Tshililo, F.P. Investigating Rainy Season Characteristics with Reference to Maize Production at the Luvuvhu River Catchment of South Africa. Master’s Thesis, School of Agriculture, Earth, and Environmental Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa, 2017. [Google Scholar]
- Sifer, K.; Yemenu, F.; Kebede, A.; Quarshi, S. Wet and dry-spell analysis for decision making in agricultural water management in the eastern part of Ethiopia, West Haraghe. Int. J. Water Resour. Environ. Eng. 2016, 8, 92–96. [Google Scholar]
- Schulze, R.E. South African Atlas of Agro-Hydrology and Climatology; Report TT82/96. 43; Water Research Commission: Pretoria, South Africa, 1997. [Google Scholar]
- Ray, M.; Biswasi, S.; Sahoo, K.C.; Patro, H. A Markov Chain Approach for Wet and Dry-spell and Probability Analysis. Int. J. Curr. Microbiol. App. Sci. 2018, 6, 1005–1013. [Google Scholar]
- Usman, M.T.; Reason, C.J.C. Dry-spell frequencies and their variability over southern Africa. Clim Res. 2004, 26, 199–211. [Google Scholar] [CrossRef][Green Version]
- Gabriel, K.R.; Neumann, J. On a distribution of weather cycles by length. Q. J. R. Meteorol. Soc. 1957, 83, 375–380. [Google Scholar] [CrossRef]
- Dabral, P.P.; Purkayastha, K.; Aram, A. Dry and wet-spell probability by Markov chain model—A case study of North Lakhimpur (Assam), India. Int. J. Agric. Biol. Eng. 2014, 7, 8–13. [Google Scholar]
- Reddy, S.J. Methodology: Agro-Climatic Analogue Technique and Applications as Relevant to Dry Land Agriculture; Agro Climatology Series Eth 86/21-WMO/UNDP; NMSA: New Delhi, India, 1990; p. 60. [Google Scholar]
- South African Weather Bureau. Climate of South Africa. Part 10. District Rainfall for South Africa and the Annual March of Rainfall over Southern Africa; South African Weather Bureau: Pretoria, South Africa, 1972. [Google Scholar]
- Grain SA and Agricultural Business Chamber of South Africa (AgBiz). South Africa Major and Minor Corn Growing Areas. Available online: https://wandilesihlobo.com/2019/09/12/growing-optimism-about-south-africas-2019-20-maize-harvest/ (accessed on 21 January 2017).
- Kruger, A.C. Climate of South Africa. Climate Regions. WS45; South African Weather Service: Pretoria, South Africa, 2004. [Google Scholar]
- Kruger, A.C.; Nxumalo, M.P. Historical rainfall trends in South Africa: 1921–2015. Water SA 2017, 43, 285–297. [Google Scholar] [CrossRef][Green Version]
- Byakatonda, J.; Parida, B.P.; Kenabatho, P.K.; Moalafhi, D.B. Prediction of onset and cessation of austral summer rainfall and dry-spell frequency analysis in semiarid Botswana. Theor. Appl. Climatol. 2019, 135, 101–117. [Google Scholar] [CrossRef]
- Adhikary, S.K.; Muttil, N.; Yilmaz, A.G. Cokriging for enhanced spatial interpolation of rainfall in two Australian catchments. Hydrol. Process. 2017, 31, 2143–2161. [Google Scholar] [CrossRef][Green Version]
- Usowicz, B.; Lipiec, J.; Łukowski, M.; Słomiński, J. Improvement of Spatial Interpolation of Precipitation Distribution Using Co-Kriging Incorporating Rain-Gauge and Satellite (SMOS) Soil Moisture Data. Remote Sens. 2021, 13, 1039. [Google Scholar] [CrossRef]
- Carrat, F.; Valleron, A.J. Epidemiologic mapping using the “kriging” method: Application to an influenza-like epidemic in France. Am. J. Epidemiol. 1992, 135, 1293–1300. [Google Scholar] [CrossRef] [PubMed]
- Grobler, E.J.M.L. Die midsomerdroogte in the sentrale dele van die somerreenvalgebied van Suid Afrika. MSc. Thesis, University of Stellenbosch, South Africa, 1993. [Google Scholar]
|Climate Region||Climatic Properties||Vegetation||Agricultural Use|
|Dry Highveld||Temperatures often exceed 30 °C in summer months and cool during winter months, with cold nights (<5 °C) observed.|
Over the high-lying areas, snow does occur in winter.
Precipitation ranges from about 450 to 700 mm.
The rainy season reaches its peak during mid-summer in the north and late summer in the south and west.
Winds tend to be from the north to north–easterly direction.
|Vegetation consists of grassland with some trees along streams.||Maize production, cattle and sheep|
|District||Dry-Spell < 15 mm|
|MK Stat||p-Value||Sen’s Slope|
|95% Confidence level—Pentads 40 to 48 (Mid-January-End of February)|
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Daniel, S.; Mengistu, M.G.; Olivier, C.; Clulow, A.D. Analysis of Dry-Spells in the Western Maize-Growing Areas of South Africa. Water 2023, 15, 1056. https://doi.org/10.3390/w15061056
Daniel S, Mengistu MG, Olivier C, Clulow AD. Analysis of Dry-Spells in the Western Maize-Growing Areas of South Africa. Water. 2023; 15(6):1056. https://doi.org/10.3390/w15061056Chicago/Turabian Style
Daniel, Siphamandla, Michael G. Mengistu, Cobus Olivier, and Alistair D. Clulow. 2023. "Analysis of Dry-Spells in the Western Maize-Growing Areas of South Africa" Water 15, no. 6: 1056. https://doi.org/10.3390/w15061056