Abstract
Forecasting rainfall at the local scale to inform farm-level decisions is complex and it remains an unresolved problem with dire implications for food security. Here, we examine indigenous knowledge forecasting systems used by smallholder farmers in Maondo Agriculture Camp (MAC) of Sesheke District in the Western Province of Zambia to increase their climate change adaptive capacity at the farm level. We adopted a qualitative approach that uses an exploratory-descriptive design. We then used purposive sampling, a non-probability methodological approach, to choose respondents. We applied semi-structured interviews and questionnaires as data collection tools and examined the data using thematic content analysis. We found that > 50% of small-scale farmers receive forecasts produced by the Zambia Meteorological Department (ZMD) through stakeholders’ meetings. Farmers who do not receive ZMD forecasts depend on indigenous knowledge systems. Results further indicate that farmers in the MAC combine several indicators to predict rainfall. Prominent among them include plants, weather-related parameters, and astrological indicators. A cursory inspection of these rainfall predictors revealed several points specifically highlighting three salient thematic contents, i.e. biological, meteorological, and astrological. Results further showed that both conventional science and indigenous knowledge used to forecast rainfall have strengths and weaknesses. We, therefore, conclude that the integration of the two methods has the potential to significantly improve rainfall forecasts and ultimately agricultural productivity at the farm level.
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References
Adanu SK, Abole T, Gbedemah SF (2021) Use of indigenous knowledge to predict rainfall in the Yendi Municipality, Ghana. GeoJournal 87:2805–2816. https://doi.org/10.1007/s10708-021-10403-8
Adger WN, SaleemulHuq S, Brown K, Conway D, Hulme M (2003) Adaptation to climate change in the developing world. Progr Dev Stud 3(3):179–195
Alaka G, Zhang X, Gopalakrishnan S (2022) High-definition hurricanes: improving forecasts with storm-following nests. Bull Am Meteor Soc 103(3):E680–E703. https://doi.org/10.1175/bams-d-20-0134.1
Alam A, Begum H, Masud M, Al-Amin A, Filho W (2020) Agriculture insurance for disaster risk reduction: a case study of Malaysia. Int J Dis Risk Reduction 47:101626. https://doi.org/10.1016/j.ijdrr.2020.101626
Alam, MM, Mohd Ekhwan, T, Siwar, C, & Talib, B (2011). Rainfall variation and changing pattern of agricultural cycle. American J of Environ Sci 7(1): 82–89., Available at SSRN: https://ssrn.com/abstract=2941338
Ali H, Mishra V (2017) Contrasting response of rainfall extremes to increase in surface air and dewpoint temperatures at urban locations in India. Sci Rep 7:1228. https://doi.org/10.1038/s41598-017-01306-1
Anderson, R. (2007). Thematic content analysis: descriptive presentation of qualitative data. Available at: http://rosemarieanderson.com/wp-content/uploads/2014/08/ThematicContentAnalysis.pdf [Accessed 20/09/2022]
Ash A, McIntosh P, Cullen B, Carberry P, Smith M (2007) Constraints and opportunities in applying seasonal climate forecasts in agriculture. Aust J Agric Res 58(10):952. https://doi.org/10.1071/ar06188
Boko, M, Niang, I, Nyong, AC, Vogel, A, Githeko, M, Medany, B, Osman-Elasha, R, & Tabo Yanda, P, (2007). Africa. In: Parry, ML, Canziani, OF, Palutikof, JP, van der Linden, PJ, Hanson, CE (Eds.), Climate change 2007: impacts, adaptation and vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge UK, pp. 433–467.
Born L, Prager S, Ramirez-Villegas J, Imbach P (2021) A global meta-analysis of climate services and decision-making in agriculture. Climate Services 22:100231. https://doi.org/10.1016/j.cliser.2021.100231
Bui A, Johnson F, Wasko C (2019) The relationship of atmospheric air temperature and dew point temperature to extreme rainfall. Environ Res Lett 14(7):074025. https://doi.org/10.1088/1748-9326/ab2a26
Chambers L, Lui S, Plotz R, Hiriasia D, Malsale P, Pulehetoa-Mitiepo R et al (2019) Traditional or contemporary weather and climate forecasts: reaching Pacific communities. Reg Environ Change 19(5):1521–1528. https://doi.org/10.1007/s10113-019-01487-7
Clarkson G, Dorward P, Poskitt S, Mambwe D, Mtonga R K, & Below T. (2021). User needs assessment for climate services in Zambia. CCAFS Working Paper no. 399. Wageningen, the Netherlands: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).
Dube T, Moyo P, Ncube M, Nyathi D (2016) The impact of climate change on agro-ecological based livelihoods in Africa: a review. Journal of Sustainable Development 9(1):256–267
Dumenu WK, TakamTiamgne X (2020) Social vulnerability of smallholder farmers to climate change in Zambia: the applicability of social vulnerability index. SN Appl Sci 2:436. https://doi.org/10.1007/s42452-020-2227-0
Dunkerley D (2020) Rainfall intensity in geomorphology: challenges and opportunities. Progress in Physical Geography: Earth and Environ 45(4):488–513. https://doi.org/10.1177/0309133320967893
Ebhuoma E (2020) A framework for integrating scientific forecasts with indigenous systems of weather forecasting in southern Nigeria. Dev Pract 30(4):472–484. https://doi.org/10.1080/09614524.2020.1723494
Ergin E, Altinel B, Aktas E (2021) A mixed method study on global warming, climate change and the role of public health nurses from the perspective of nursing students. Nurse Educ Today 107:105144. https://doi.org/10.1016/j.nedt.2021.105144
Etikan I (2016) Comparison of convenience sampling and purposive sampling. Am J Theor Appl Stat 5(1):1–4
Etuk E, Ayuk J (2021) Agricultural commercialisation, poverty reduction and pro-poor growth: evidence from commercial agricultural development project in Nigeria. Heliyon 7(5):e06818. https://doi.org/10.1016/j.heliyon.2021.e06818
FAO, (2014). Youth and agriculture: key challenges and concrete solutions. ISBN 978–92–5–108475–5. Available at https://www.fao.org/3/i3947e/I3947E.pdf [Accessed: 11/04/2022]
Farnworth, CR. & Munachonga, M. (2010). Gender approaches in agricultural programmes – Zambia country report. A special study of the Agricultural Support Programme (ASP). UTV Working Paper 2010:8 SIDA. Available at: https://www.oecd.org/countries/zambia/46150642.pdf. [Accessed 09 August 2022]
Feleke HG (2015) Assessing weather forecasting needs of smallholder farmers for climate change adaptation in the Central Rift Valley of Ethiopia. J Earth Sci & Climatic Change 6(10):1–8
Ferijal T, Batelaan O, Shanafield M, Alfahmi F (2022) Determination of rainy season onset and cessation based on a flexible driest period. Theor Appl Climatol 148:91–104. https://doi.org/10.1007/s00704-021-03917-1
Guido Z, Zimmer A, Lopus S, Hannah C, Gower D, Waldman K et al (2020) Farmer forecasts: impacts of seasonal rainfall expectations on agricultural decision-making in Sub-Saharan Africa. Clim Risk Manag 30:100247. https://doi.org/10.1016/j.crm.2020.100247
Hachigonta S, Reason C, Tadross M (2007) An analysis of onset date and rainy season duration over Zambia. Theoretical and App Climatology 91(1–4):229–243. https://doi.org/10.1007/s00704-007-0306-4
Hansen JW, Mason SJ, Sun L, Tall A (2011) Review of seasonal climate forecasting for agriculture in sub-Saharan Africa. Exp Agric 47(2):205–240
Haskett JD, Simane B, Smith C (2019) Energy and Climate Change Mitigation Benefits of Faidherbia albida Agroforestry in Ethiopia. Front Environ Sci 7. https://doi.org/10.3389/fenvs.2019.00146
Hunter, D. J, McCallum, J, & Howes, D. (2018). Defining exploratory-descriptive qualitative (EDQ) research and considering its application to healthcare. In Proceedings of Worldwide Nursing Conference 2018 (Worldwide Nursing Conference 2018). http://nursing-conf.org/accepted-papers/#acc-5b9bb119a6443
Ivanic M, Martin W (2018) Sectoral productivity growth and poverty reduction: national and global impacts. World Dev 109:429–439. https://doi.org/10.1016/j.worlddev.2017.07.004
Kadi, M, Njau LN, Mwikya, J, Kamga, A. (2011). The state of climate information services in East African countries. CCAFS working paper 5. Copenhagen, Denmark: Available online at: www.ccafs.cgiar.org
Kalanda-Joshua M, Ngongondo C, Chipeta L, Mpembeka F (2011) Integrating indigenous knowledge with conventional science: enhancing localised climate and weather forecasts in Nessa, Mulanje, Malawi. Physics and Chem of the Earth, Parts a/b/c 36(14–15):996–1003. https://doi.org/10.1016/j.pce.2011.08.001
Kamuti T (2022) Integration of indigenous knowledge systems in Zimbabwe’s climate change policy. Sustainable Development Goals Series 153–164. https://doi.org/10.1007/978-3-030-99411-2_12
Kavu S, Kajongwe C, Ebhuoma EE (2022) Climate change experts’ perspective on the role of indigenous knowledge systems in climate change adaptation in Southern Africa. Sustainable Development Goals Series 67–80. https://doi.org/10.1007/978-3-030-99411-2_6
Kijazi AL, Chang’a LB, Liwenga ET, Kanemba A, Nindi SJ (2013) The use of indigenous knowledge in weather and climate prediction in Mahenge and Ismani wards. Tanzania J Geogr Reg Plann 6(7):274–280
Kongnso ME (2022) Indigenous adaptation of pastoralists to climate variability and range land management in the ndop plain, North West Region, Cameroon. Sustainable Development Goals Series 13–26. https://doi.org/10.1007/978-3-030-99411-2_2
Koskei, E.C. (2020). Awareness and adaptation to climate change in arid and semi-arid lands. A case of Baringo county, Kenya. Int. J. of Adv. Res. 8 (Sep). 332–338] (ISSN 2320–5407).
Libanda B (2021) Public Institutional Structures for Disaster Preparedness in the Cereal Value Chain: A Zambian Case Study. GeoHazards 2(4):352–365. https://doi.org/10.3390/geohazards2040019
Lemos MC, Kirchhoff CJ, Ramprasad V (2012) Narrowing the climate information usability gap. Nat Clim Chang 2(11):789–794. https://doi.org/10.1038/nclimate1614
LenderinkGand van Meijgaard E (2010) Linking increases in hourly precipitation extremes to atmospheric temperature and moisture changes Environ. Res Lett 5:025208
Libanda B, Mie Z, Nyasa L et al (2020) Deciphering the performance of satellite-based daily rainfall products over Zambia. Acta Geophys 68:903–919. https://doi.org/10.1007/s11600-020-00429-w
Lyamchai C, Yanda P, Sayula G, & Kristjanson P. (2011). Summary of baseline household survey results: Lushoto, Tanzania. CGIAR research program on climate change, agriculture and food security (CCAFS).
Magaya S, Fitchett JM (2022) Approaching positionality in research on indigenous knowledge systems. Sustainable Development Goals Series 81–93. https://doi.org/10.1007/978-3-030-99411-2_7
Makondo CC, Thomas DSG (2020) Seasonal and intra-seasonal rainfall and drought characteristics as indicators of climate change and variability in Southern Africa: a focus on Kabwe and Livingstone in Zambia. Theor Appl Climatol 140:271–284. https://doi.org/10.1007/s00704-019-03029-x
Masinde M (2015) An innovative drought early warning system for sub-Saharan Africa: integrating modern and indigenous approaches. African J Sci Technol Innov Dev 7:8–25. https://doi.org/10.1080/20421338.2014.971558
McNaught R, Warrick O, Cooper A (2014) Communicating climate change for adaptation in rural communities: a pacific study. Reg Environ Change 14(4):1491–1503
Mijiyawa AG, Oloufade DK (2019) State capacity agricultural productivity and poverty reduction in African countries. J Eco Dev 44(1):39–67. https://doi.org/10.35866/caujed.2019.44.1.003
Mijiyawa AG, Oloufade DK (2019) State capacity, agricultural productivity and poverty reduction in African countries. J Eco Dev 44(1):39–67. https://doi.org/10.35866/caujed.2019.44.1.003
MoA (2019) Small-scale farmers register - Maondo Agriculture Camp. MoA: Sesheke
Minogue K (2010) Folklore confirmed: the moon’s phase affects rainfall. Science. https://doi.org/10.1126/article.29815
Moyo-Nyoni N (2022) Adopting indigenous knowledge systems to enhance peace education programs for climate change and adaptation in Zimbabwe. Sustainable Development Goals Series 27–38. https://doi.org/10.1007/978-3-030-99411-2_3
Mugabe F, Mubaya C, Nanja D, Gondwe P, Munodawafa A, Mutswangwa E, Chagonda I, Masere P, Dimes J, Murewi C (2011). Use of indigenous knowledge systems and scientific methods for climate forecasting in Southern Zambia and North Western Zimbabwe. Zimbabwe Journal of Technological Sciences 1(1). https://doi.org/10.4314/zjts.v1i1.65216
Mulele SC, Kanyamuna CS, Kanyamuna LM, Kanyamuna V (2021) The effect of information literacy on maize production: case study of small-scale farmers in Inonge Village, Kazungula District of Zambia. Advances in Social Sciences Research Journal 8(8):208–229
Musonda B, Yuanshu J, Vedaste I, Moses O (2020) Analysis of long-term variations of drought characteristics using standardized precipitation index over Zambia. Atmosphere 11(12):1268. https://doi.org/10.3390/atmos11121268
Nciizah AD, Wakindiki IC (2014) Rainfall intensity effects on crusting and mode of seedling emergence in some quartz-dominated South African soils. Water SA 40(4):587–594
ND-GAINS (2020). University of Notre Dame Global Adaptation Index Country Index Technical Report. Available at: https://gain.nd.edu/ [Accessed: 31/07/2022]
Ngoma H, Lupiya P, Kabisa M, Hartley F (2021) Impacts of climate change on agriculture and household welfare in Zambia: an economy-wide analysis. Clim Change 167:55. https://doi.org/10.1007/s10584-021-03168-z
Ninh LK (2021) Economic role of education in agriculture: evidence from rural Vietnam. J of Econ and Dev 23(1):47–58. https://doi.org/10.1108/JED-05-2020-0052
Nuñez L (2005) Tools for forecasting or warning as well as hazard assessment to reduce impact of natural disasters on agriculture, forestry and fisheries. Natural Disasters and Extreme Events in Agriculture 71–92. https://doi.org/10.1007/3-540-28307-2_5
Nyadzi E, Werners S, Biesbroek R, Ludwig F (2020) Techniques and skills of indigenous weather and seasonal climate forecast in northern Ghana. Climate and Development 13(6):551–562. https://doi.org/10.1080/17565529.2020.1831429
Nyadzi E, Werners S, Biesbroek R, Ludwig F (2022) Towards weather and climate services that integrate indigenous and scientific forecasts to improve forecast reliability and acceptability in Ghana. Environmental Development 42:100698. https://doi.org/10.1016/j.envdev.2021.100698
Nyamekye AB, Dewulf A, Slobbe EV, Termeer K, Pinto C (2018) Governance arrangements and adaptive decision-making in rice farming systems in Northern Ghana. NJAS - Wageningen J Life Sci 86–87:39–50. https://doi.org/10.1016/j.njas.2018.07.004
Orlove B, Roncoli C, Kabugo M, Majugu A (2010) Indigenous climate knowledge in southern Uganda: the multiple components of a dynamic regional system. Clim Chang 100(2):243–265
Palgrave CK (2002) Trees of southern Africa. Struik Publications, Cape Town. ISBN-10 1868723895
Partey ST, Dakorah AD, Zougmoré RB, Ouédraogo M, Nyasimi M, Nikoi GK, Huyer S (2020) Gender and climate risk management: evidence of climate information use in Ghana. Clim Change 158:61–75. https://doi.org/10.1007/s10584-018-2239-6
Printezis I, Grebitus C (2020) College-age millennials’ preferences for food supplied by urban agriculture. Frontiers in Sustainable Food Systems 4. https://doi.org/10.3389/fsufs.2020.00048
Radeny M, Desalegn A, Mubiru D, Kyazze F, Mahoo H, Recha J et al (2019) Indigenous knowledge for seasonal weather and climate forecasting across East Africa. Clim Change 156(4):509–526. https://doi.org/10.1007/s10584-019-02476-9
Shikwambana S, Malaza N, Shale K (2021) Impacts of rainfall and temperature changes on smallholder agriculture in the Limpopo Province. South Africa Water 13:2872. https://doi.org/10.3390/w13202872
Starosta, AH, Ewing, B, & Schneider, A (2018). Female farmers in Zambia: positive prospects for productivity. Available at: https://land-links.org/wp-content/uploads/2016/09/TGCC-Gender-Brief_FINAL_topostclean_7.5.2018.pdf [Accessed 09 August 2022]
Tropical African Plants: X (1933) Bulletin of miscellaneous information (Royal Botanic Gardens, Kew) 1933(3):142–151. https://doi.org/10.2307/4113529
VITA (1977) Reforestation in arid lands. VITA Publications, Manual Series, p 37E
Washington R, James R, Pearce H, Pokam W, Moufouma-Okia W (2013) Congo Basin rainfall climatology: can we believe the climate models? Philosophical Transactions of the Royal Society b: Biological Sciences 368(1625):20120296. https://doi.org/10.1098/rstb.2012.0296
Washington R, Hart NC, and Woolnough SJ, (2021). Decreasing rainfall to year 2100 - role of the Congo Air Boundary. Available at: https://gtr.ukri.org/projects?ref=NE%2FV011928%2F1#/tabOverview. [Accessed: 12/04/2022]
Wasko C, Lu WT, & Mehrotra R. (2018). Relationship of extreme precipitation, dry-bulb temperature, and dew point temperature across Australia Environ. Res. Lett. 13074031
WMA (2013) Ethical principles for medical research involving human subjects, JAMA 310(20):2191. https://doi.org/10.1001/jama.2013.281053
Worden S, Fu R, Chakraborty S, Liu J, Worden J (2021) Where does moisture come from over the congo basin? J Geophys Res Biogeosci 126(8). https://doi.org/10.1029/2020jg006024
ZAMSTAT (2022) Zambia district population, ZAMSTAT: Lusaka. Available at: https://www.zamstats.gov.zm/. Accessed 19 June 2022
Ziervogel G (2001) Global science, local problems: seasonal forecast use in a Basotho Village’, open meeting of the global environmental change research community, Rio de Janeiro, 6–8 October, 2001
Acknowledgements
The first author carried out this study while being supported by the ZMD/UNDP CIEWS Project, their financial support is appreciated. The work embodied herein would not have been possible without Respondents in Maondo Agriculture Camp (MAC) and Mr Sabelo Mwanakalanga Sibanda who assisted with data collection — thank you. Mr Alfred Daka, a lecturer in the School of Agriculture and Natural Resources at Mulungushi University, is also appreciated for providing feedback on the initial draft of this manuscript. The Editor and Reviewers are also appreciated for their comments that further helped to improve this work.
Funding
This research was carried out as part of the Strengthening Climate Information and Early Warning Systems project (CIEWS; Project Number 00086729; https://www.adaptation-undp.org/projects/ldcf-ews-zambia) funded by the United Nations Development Programme (UNDP). The project was led by the Zambia Meteorological Department (ZMD). Overall, the project aimed at enhancing the capacity of ZMD to monitor and forecast extreme weather events and climate change. It also sought to maximise efficient and effective use of hydro-meteorological and environmental information for generating early warnings and informing long-term development plans. It should be noted, however, that neither UNDP nor ZMD were involved in the conception, analytical design, data analyses, interpretation of the data, manuscript writing, or the decision to submit this work for publication.
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The first author developed the theoretical formalism and led the data collection, analyses, and manuscript writing. The second author contributed to the presentation of the storyline and results. Both MM and BL contributed equally to the final version of the manuscript.
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While the first author works for ZMD, we declare that the author was not solely responsible for the interpretation of results embodied in this work and therefore, this has not in any way affected the conclusions herein.
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Mushimbei, M., Libanda, B. Adapting to a changing climate: indigenous biotic rainfall forecasting in Western Zambia. Int J Biometeorol 67, 253–263 (2023). https://doi.org/10.1007/s00484-022-02402-2
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DOI: https://doi.org/10.1007/s00484-022-02402-2