Economic Benefits and Uses of Indigenous Seasonal Weather Forecasts in Zimbabwe

Joseph Manzvera

Department of Agricultural Economics and Agribusiness, University of Ghana, Legon, Accra P. O. Box LG 68, Ghana

Kwabena Asomanin Anaman

Department of Agricultural Economics and Agribusiness, University of Ghana, Legon, Accra P. O. Box LG 68, Ghana

Akwasi Mensah-Bonsu

Department of Agricultural Economics and Agribusiness, University of Ghana, Legon, Accra P. O. Box LG 68, Ghana

Alfred Barimah

Department of Economics, University of Ghana, Legon, Accra P. O. Box LG 68, Ghana

DOI: https://doi.org/10.36956/rwae.v5i4.1240

Received: 15 August 2024 | Revised: 2 September 2024 | Accepted: 3 September 2024 | Published Online: 15 October 2024

Copyright © 2024 Joseph Manzvera, Kwabena Asomanin Anaman, Akwasi Mensah-Bonsu, Alfred Barimah . Published by Nan Yang Academy of Sciences Pte. Ltd.

Creative Commons LicenseThis is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.


Abstract

This study presents a seminal contribution regarding the economic value of indigenous seasonal weather forecasts in Zimbabwe. Many farmers (58%) use indigenous seasonal weather forecasts to make maize farming decisions such as selecting suitable varieties. The main indicators used for indigenous seasonal weather forecasts are flowering and fruition of specific trees. Based on travel cost analysis, which incorporates a multi-purpose visit scenario, the study establishes the economic importance of indigenous seasonal weather forecasts with a consumer surplus of US$1,044 per year among the 290 farmers using the forecasts. There is therefore a need to integrate indigenous weather forecasts into national seasonal weather forecasting and disaster risk reduction systems to complement modern seasonal weather forecasts. Co-production of seasonal weather forecasts with farmers is proposed in this regard. This further calls for the need to digitally document, visualize, and disseminate indigenous seasonal weather forecast indicators to a wider audience to increase their use.

Keywords: Indigenous seasonal weather; Maize farmers; Travel cost; Co‑production; Zimbabwe


References

[1] Frischen, J., Meza, I., Rupp, D., et al., 2020. Drought risk to agricultural systems in Zimbabwe: A spatial analysis of hazard, exposure, and vulnerability. Sustainability. 12(3), 1–23. DOI: https://doi.org/10.3390/su12030752

[2] Madamombe, S.M., Ng’ang’a, S.K., Öborn, I., et al., 2024. Climate change awareness and adaptation strategies by smallholder farmers in semi-arid areas of Zimbabwe. International Journal of Agricultural Sustainability. 22(1), 1–18. DOI: https://doi.org/10.1080/14735903.2023.2293588

[3] Musemwa, M., 2019. Climate and societal interaction in southwestern Matabeleland, colonial Zimbabwe: The drought of 1964–66 and its antecedents. Human Geography. 12(1), 5–18. DOI: https://doi.org/10.1177/194277861901200111

[4] Muzerengi, F., Gandidzanwa, C.P., Chirubvu, L., 2023. Impacts of climate change on household food security in Matande communal lands, Mwenezi district in Zimbabwe. Jàmbá: Journal of Disaster Risk Studies. 15(1), 1–11. DOI: https://doi.org/10.4102/jamba.v15i1.1499

[5] Mwadzingeni, L., Mugandani, R., Mafongoya, P., 2022. Risks of climate change on future water supply in smallholder irrigation schemes in Zimbabwe. Water. 14(11), 1–20. DOI: https://doi.org/10.3390/w14111682

[6] Rurinda, J., Mapfumo, P., van Wijk, M.T., et al., 2014. Sources of vulnerability to a variable and changing climate among smallholder households in Zimbabwe: A participatory analysis. Climate Risk Management. 3, 65–78. DOI: https://doi.org/10.1016/j.crm.2014.05.004

[7] Amegnaglo, C.J., Mensah-Bonsu, A., Anaman, K.A., 2022. Use and economic benefits of indigenous seasonal climate forecasts: Evidence from Benin, West Africa. Climate and Development. 14(10), 909–920. DOI: https://doi.org/10.1080/17565529.2022.2027740

[8] Sutanto, S.J., Paparrizos, S., Kumar, U., et al., 2024. The performance of climate information service in delivering scientific, local, and hybrid weather forecasts: A study case in Bangladesh. Climate Services. 34, 1–17. DOI: https://doi.org/10.1016/j.cliser.2024.100459

[9] Zinyengere, N., Mhizha, T., Mashonjowa, E., et al., 2011. Using seasonal climate forecasts to improve maize production decision support in Zimbabwe. Agricultural and Forest Meteorology. 151(12), 1792–1799. DOI: https://doi.org/10.1016/j.agrformet.2011.07.015

[10] Grey, M.S., Masunungure, C., Manyani, A., 2020. Integrating local indigenous knowledge to enhance risk reduction and adaptation strategies to drought and climate variability: The plight of smallholder farmers in Chirumhanzu district, Zimbabwe. Jàmbá: Journal of Disaster Risk Studies. 12(1), 1–10. DOI: https://doi.org/10.4102/jamba.v12i1.924

[11] Makaudze, E.M., 2012. Assessing the economic value of El Niño-based seasonal climate forecasts for smallholder farmers in Zimbabwe. Meteorological Applications. 21(3), 535–544. DOI: https://doi.org/10.1002/met.1366

[12] Makuvaro, V., Chitata, T., Tanyanyiwa, E., et al., 2023. Challenges and opportunities in communicating weather and climate information to rural farming communities in central Zimbabwe. American Meteorological Society. 15(1), 109–119. DOI: https://doi.org/10.1175/WCAS-D-22-0016.1

[13] Patt, A., Suarez, P., Gwata, C., 2005. Effects of seasonal climate forecasts and participatory workshops among subsistence farmers in Zimbabwe. Proceedings of the National Academy of Sciences of the United States of America. 102(35), 12623–12628. DOI: https://doi.org/10.1073/pnas.0506125102

[14] Dube, T., Huhn, A.L., Nobre, G.G., et al., 2024. Incorporating indigenous knowledge systems-based climate services in anticipatory action in Zimbabwe: An ex-ante assessment. Frontiers in Climate. 6, 1–15. DOI: https://doi.org/10.3389/fclim.2024.1301908

[15] Kalanda-Joshua, M., Ngongondo, C., Chipeta, L., et al., 2011. Integrating indigenous knowledge with conventional science: Enhancing localised climate and weather forecasts in Nessa, Mulanje, Malawi. Physics and Chemistry of the Earth. 36(14–15), 996–1003. DOI: https://doi.org/10.1016/j.pce.2011.08.001

[16] Ndlovu, J., Ndlovu, M., Nyathi, D., 2023. The role of indigenous climate forecasting systems in building farmers’ resilience in Nkayi District, Zimbabwe. In Climate Crisis: Adaptive Approaches and Sustainability. Springer: Cham, Switzerland. pp. 195–210. DOI: https://doi.org/10.1007/978-3-031-44397-8_11

[17] Chisadza, B., Tumbare, M.J., Nhapi, I., et al., 2013. Useful traditional knowledge indicators for drought forecasting in the Mzingwane catchment area of Zimbabwe. Disaster Prevention and Management. 22(4), 312–325. DOI: https://doi.org/10.1108/DPM-10-2012-0109

[18] Zvobgo, L., Johnston, P., Olagbegi, O.M., et al., 2023. Role of Indigenous and local knowledge in seasonal forecasts and climate adaptation: A case study of smallholder farmers in Chiredzi, Zimbabwe. Environmental Science & Policy. 145, 13–28. DOI: https://doi.org/10.1016/j.envsci.2023.03.017

[19] Filho, W.L., Barbir, J., Gwenzi, J., et al., 2022. The role of indigenous knowledge in climate change adaptation in Africa. Environmental Science & Policy. 136, 250–260. DOI: https://doi.org/10.1016/j.envsci.2022.06.004

[20] Alemayehu, A., Behaylu, A., Agumass, G., et al., 2023. Farmers’ traditional knowledge on climate change and weather forecast: The case of Menze Gera Midir district, Ethiopia. Environmental Development. 47, 1–11. DOI: https://doi.org/10.1016/j.envdev.2023.100908

[21] Gwenzi, J., Mashonjowa, E., Mafongoya, P.L., et al., 2016. The use of indigenous knowledge systems for short and long-range rainfall prediction and farmers’ perceptions of science-based seasonal forecasts in Zimbabwe. International Journal of Climate Change Strategies and Management. 8(3), 440–462. DOI: https://doi.org/10.1108/IJCCSM-03-2015-0032

[22] Mugi-Ngenga, E.W., Kiboi, M.N., Mucheru-Muna, M.W., et al., 2021. Indigenous and conventional climate knowledge for enhanced farmers’ adaptation to climate variability in the semi-arid agro-ecologies of Kenya. Environmental Challenges. 5, 1–12. DOI: https://doi.org/10.1016/j.envc.2021.100355

[23] Dube, E., Munsaka, E., 2018. The contribution of indigenous knowledge to disaster risk reduction activities in Zimbabwe: A big call to practitioners. Jàmbá: Journal of Disaster Risk Studies. 10(1), 1–8. DOI: https://doi.org/10.4102/jamba.v10i1.493

[24] Paparrizos, S., Attoh, E.M.N.A.N., Sutanto, S.J., et al., 2023. Local rainfall forecast knowledge across the globe used for agricultural decision-making. Science of The Total Environment. 899, 1–15. DOI: https://doi.org/10.1016/j.scitotenv.2023.165539

[25] Guye, M., Legesse, A., Mohammed, Y., 2022. Indigenous weather forecasting among Gujii pastoralists in southern Ethiopia: Towards monitoring drought. Pastoralism. 12(43), 1–16. DOI: https://doi.org/10.1186/s13570-022-00258-0

[26] Chambers, L., Lui, S., Plotz, R., et al., 2019. Traditional or contemporary weather and climate forecasts: Reaching pacific communities. Regional Environmental Change. 19, 1521–1528. DOI: https://doi.org/10.1007/s10113-019-01487-7

[27] Kniveton, D., Visman, E., Tall, A., et al., 2015. Dealing with uncertainty: Integrating local and scientific knowledge of the climate and weather. Disasters. 39(s1), s35–s53. DOI: https://doi.org/10.1111/disa.12108

[28] United Nations Development Programme, (UNDP) [Internet]. The Climate Dictionary. Available from: https://www.undp.org/publications/climate-dictionary (cited 30 May 2024).

[29] Chipangura, N., 2019. Towards the decriminalisation of artisanal gold mining in eastern Zimbabwe. The Extractive Industries and Society. 6(1), 154–161. DOI: https://doi.org/10.1016/j.exis.2018.09.003

[30] Gohori, O., van der Merwe, P., 2022. Tourism and community empowerment: The perspectives of local people in Manicaland province, Zimbabwe. Tourism Planning & Development. 19(2), 81–99. DOI: https://doi.org/10.1080/21568316.2021.18738 38

[31] Gillespie, R., Collins, D., Bennett, J., 2017. Adapting the travel cost method to estimate changes in recreation benefits in the Hawkesbury–Nepean River. Australasian Journal of Environmental Management. 24(4), 375–391. DOI: https://doi.org/10.1080/14486563.2017.1354 236

[32] Anaman, K.A., Quaye, R., Amankwah, E., 2017. Evaluation of public weather services by users in the formal services sector in Accra, Ghana. Modern Economy. 8(7), 1–26. DOI: https://doi.org/10.4236/me.2017.87065

[33] Anaman, K.A., Lellyett, S.C., 1996. Assessment of the benefits of an enhanced weather information service for the cotton industry in Australia. Meteorological Applications. 3(2), 127–135. DOI: https://doi.org/10.1002/met.5060030203

[34] Marshall, A., 1890. Principles of Economics: Palgrave Classics in Economics. Palgrave Macmillan: United Kingdom. pp. 1–754. (Reprinted 1980). DOI: https://doi.org/10.1057/9781137375261

[35] Cameron, A.C., Trivedi, P.K., 2005. Microeconometrics: Methods and Applications. Cambridge University Press: Cambridge. pp. 1–1056. DOI: https://doi.org/10.1017/CBO9780511811241

[36] Hoyos, D., Riera, P., 2013. Convergent validity between revealed and stated recreation demand data: Some empirical evidence from the Basque Country, Spain. Journal of Forest Economics. 19(3), 234–248. DOI: https://doi.org/10.1016/j.jfe.2013.02.003

[37] Wieland, R.C., Horowitz, J., 2007. Estimating the recreational consumer surplus at Maryland’s state-owned forests. Report for Harry R. Hughes Center for Agro-Ecology, University of Maryland. Available from: https://agnr.umd.edu/sites/agnr.umd.edu/files/files/documents/Hughes%20Center/Scientific%20Research/Wieland%20Final%20Report%202008%20Part%20C.pdf (cited 30 May 2024).

[38] Navrud, S., Mungatana, E.D., 1994. Environmental valuation in developing countries: The recreational value of wildlife viewing. Ecological Economics. 11(2), 135–151. DOI: https://doi.org/10.1016/0921-8009(94)90024-8

[39] Cetin, N.I., Bourget, G., Tezer, A., 2021. Travel-cost method for assessing the monetary value of recreational services in the Ömerli Catchment. Ecological Economics. 190, 1–12. DOI: https://doi.org/10.1016/j.ecolecon.2021.107192

[40] de Menezes, D.Q.F., Prata, D.M., Secchi, A.R., et al., 2021. A review on robust M-estimators for regression analysis. Computers & Chemical Engineering. 147, 1–30. DOI: https://doi.org/10.1016/j.compchemeng.2021.107254

[41] Wooldridge, J.M., 2013. Introductory Econometrics: A Modern Approach, 5th ed. South Western: United States of America. pp. 1–910.

[42] Sureiman, O., Mangera, C.M., 2020. F-test of overall significance in regression analysis simplified. Journal of the Practice of Cardiovascular Sciences. 6(2), 116–122. DOI: https://doi.org/10.4103/jpcs.jpcs_18_20

[43] Nyadzi, E., Werners, S.E., Biesbroek, R., et al., 2021.Techniques and skills of indigenous weather and seasonal climate forecast in Northern Ghana. Climate and Development. 13(6), 551–562.DOI: https://doi.org/10.1080/17565529.2020.1831429

[44] Radeny, M., Desalegn, A., Mubiru, D., et al., 2019. Indigenous knowledge for seasonal weather and climate forecasting across East Africa. Climatic Change. 156, 509–526. DOI: https://doi.org/10.1007/s10584-019-02476-9

[45] Zougmoré, R., Segnon, A.C., Thornton, P., 2023. Harnessing indigenous knowledge and practices for effective adaptation in the Sahel. Current Opinion in Environmental Sustainability. 65, 1–7. DOI: https://doi.org/10.1016/j.cosust.2023.101389

[46] Balehegn, M., Balehey, S., Fu, C., et al., 2019. Indigenous weather and climate forecasting knowledge among Afar pastoralists of north-eastern Ethiopia: Role in adaptation to weather and climate variability. Pastoralism. 9(8), 1–14. DOI: https://doi.org/10.1186/s13570-019-0143-y

[47] Chicco, D., Warrens, M.J., Jurman, G., 2021. The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation. PeerJ Computer Science. 7, 1–24. DOI: https://doi.org/10.7717/peerj-cs.623

[48] Cameron, A.C., Windmeijer, F.A.G., 1997. An R-squared measure of goodness of fit for some common nonlinear regression models. Journal of Econometrics. 77(2), 329–342. DOI: https://doi.org/10.1016/S0304-4076(96)01818-0

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