A Deeper Understanding of Climate Variability Improves Mitigation Efforts, Climate Services, Food Security, and Development Initiatives in Sub-Saharan Africa

Shamseddin M. Ahmed; Hassan A. Dinnar; Adam E. Ahmed; Azharia A. Elbushra; Khalid G. Biro Turk

doi:10.3390/cli12120206

journal article Open Access Dec 02, 2024

A Deeper Understanding of Climate Variability Improves Mitigation Efforts, Climate Services, Food Security, and Development Initiatives in Sub-Saharan Africa

Shamseddin M. Ahmed

Hassan A. Dinnar Adam E. Ahmed

Azharia A. Elbushra Khalid G. Biro Turk

Climate Vol. 12 No. 12 pp. 206 · MDPI AG

View at Publisher Save 10.3390/cli12120206

Abstract

This research utilized the bagging machine learning algorithm along with the Thornthwaite moisture index (TMI) to enhance the understanding of climate variability and change, with the objective of identifying the most efficient climate service pathways in Sub-Saharan Africa (SSA). Monthly datasets at a 0.5° resolution (1960–2020) were collected and analyzed using R 4.2.2 software and spreadsheets. The results indicate significant changes in climatic conditions in Sudan, with aridity escalation at a rate of 0.37% per year. The bagging algorithm illustrated that actual water use was mainly influenced by rainfall and runoff management, showing an inverse relationship with increasing air temperatures. Consequently, sustainable strategies focusing on runoff and temperature control, such as rainwater harvesting, agroforestry and plant breeding were identified as the most effective climate services to mitigate and adapt to climate variability in SSA. The findings suggest that runoff management (e.g., rainwater harvesting) could potentially offset up to 22% of the adverse impacts of climate variability, while temperature control strategies (e.g., agroforestry) could account for the remaining 78%. Without these interventions, climate variability will continue to pose serious challenges to food security, livelihood generations, and regional stability. The research calls for further in-depth studies on the attributions of climate variability using finer datasets.

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References

89

[1]

Shamseddin "Impacts of drought, food security policy and Climate change on performance of irrigation schemes in Sub-Saharan Africa: The case of Sudan" Agric. Water Manag. (2020) 10.1016/j.agwat.2020.106064

[2]

Ayansina "Extreme climate events in sub-Saharan Africa: A call for improving agricultural technology transfer to enhance adaptive capacity" Clim. Serv. (2022) 10.1016/j.cliser.2022.100311

[3]

Ekolu "Long-term variability in hydrological droughts and floods in sub-Saharan Africa: New perspectives from a 65-year daily streamflow dataset" J. Hydrol. (2022) 10.1016/j.jhydrol.2022.128359

[4]

Ekolu "Variability in flood frequency in sub-Saharan Africa: The role of large-scale climate modes of variability and their future impacts" J. Hydrol. (2024) 10.1016/j.jhydrol.2024.131679

[5]

Lefe "Does climate variability matter in achieving food security in Sub-Saharan Africa?" Environ. Chall. (2024) 10.1016/j.envc.2024.100870

[6]

Omotoso "Climate change and variability in sub-Saharan Africa: A systematic review of trends and impacts on agriculture" J. Clean. Prod. (2023) 10.1016/j.jclepro.2023.137487

[7]

Zenda, M., Rudolph, M., and Harley, C. (2024). The Impact of Climate Variability on the Livelihoods of Smallholder Farmers in an Agricultural Village in the Wider Belfast Area, Mpumalanga Province, South Africa. Atmosphere, 15. 10.3390/atmos15111353

[8]

Shamseddin "Climate variability impacts on crop yields and agriculture contributions to gross domestic products in the Nile basin (1961–2016): What did deep machine learning algorithms tell us?" Theor. Appl. Clim. (2024) 10.1007/s00704-024-04858-1

[9]

Lu "Changes in vegetation-water response in the Sahel-Sudan during recent decades" J. Hydrol. Reg. Stud. (2024) 10.1016/j.ejrh.2024.101672

[10]

Tefera "Impact of climate variability and environmental policies on vegetation dynamics in the semi-arid Tigray" Discov. Environ. (2024) 10.1007/s44274-024-00031-7

[11]

Pörtner, H.-O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., and Möller, V. (2022). Climate Change 2022: Impacts, Adaptation, and Vulnerability, Cambridge University Press. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change.

[12]

Bhaga, T., Dube, T., Shekede, M.D., and Shoko, C. (2020). Impacts of Climate Variability and Drought on Surface Water Resources in Sub-Saharan Africa Using Remote Sensing: A Review. Remote Sens., 12. 10.3390/rs12244184

[13]

WMO (2021). State of the Climate in Africa 2020 WMO-No 1275, World Meteorological Organization. Available online: https://library.wmo.int/idurl/4/57682.

[14]

Editorial: Broadening the Use of Machine Learning in Hydrology

Chaopeng Shen, Xingyuan Chen, Eric Laloy

Frontiers in Water 10.3389/frwa.2021.681023

[15]

Molina, M., O’Brian, T., Anderson, G., Ashfaq, M., Bennett, K., Collins, W., Dagon, K., Juan, M., and Ullrich, P. (2023). A Review of Recent and Emerging Machine Learning Applications for Climate Variability and Weather Phenomena. Artif. Intell. Earth Syst., 2. 10.1175/aies-d-22-0086.1

[16]

Lalika "Machine learning algorithms for the prediction of drought conditions in the Wami River sub-catchment, Tanzania" J. Hydrol. Reg. Stud. (2024) 10.1016/j.ejrh.2024.101794

[17]

Zhao, Y., Zhang, J., Bai, Y., Zhang, S., Yang, S., Henchiri, M., Seka, A.M., and Nanzad, L. (2022). Drought Monitoring and Performance Evaluation Based on Machine Learning Fusion of Multi-Source Remote Sensing Drought Factors. Remote Sens., 14. 10.3390/rs14246398

[18]

Mosaffa, H., Mojtaba, S., Iman, M., Mojtaba, N., and Jahromi, H. (2022). Application of machine learning algorithms in hydrology. Computers in Earth and Environmental Sciences, Elsevier. 10.1016/b978-0-323-89861-4.00027-0

[19]

Kim "A novel approach to a multi-model ensemble for climate change models: Perspectives on the representation of natural variability and historical and future climate" Weather Clim. Extrem. (2024) 10.1016/j.wace.2024.100688

[20]

Altman "Ensemble methods: Bagging and random forests" Nat. Methods (2017) 10.1038/nmeth.4438

[21]

Leng "Predicting spatial and temporal variability in crop yields: An inter-comparison of machine learning, regression and process-based models" Environ. Res. Lett. (2020) 10.1088/1748-9326/ab7b24

[22]

Frohlich "Water: Reason for Conflict or Catalyst for Peace? The Case of the Middle East. Dans L’Europe en Formation 2012/3 (n° 365)" Eur. Form. (2012)

[23]

Bromwich "Nexus meets crisis: A review of conflict, natural resources and the humanitarian response in Darfur with reference to the water–energy–food nexus" Int. J. Water Res. Dev. (2015) 10.1080/07900627.2015.1030495

[24]

Jacobs "The next generation of climate services" Clim. Serv. (2020) 10.1016/j.cliser.2020.100199

[25]

Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset

Ian Harris, Timothy J. Osborn, Phil Jones et al.

Scientific Data 2020 10.1038/s41597-020-0453-3

[26]

Huang "Analysis of Model-Calculated Soil Moisture over the United States (1931–1993) and Applications to Long-Range Temperature Forecasts" J. Clim. (1996) 10.1175/1520-0442(1996)009<1350:aomcsm>2.0.co;2

[27]

Sha "Physical basis of the potential evapotranspiration and its estimation over land" J. Hydrol. (2024) 10.1016/j.jhydrol.2024.131825

[28]

Pereira "Adaptation of the Thornthwaite scheme for estimating daily reference evapotranspiration" Agric. Water Manag. (2004) 10.1016/j.agwat.2003.11.003

[29]

Karim "Thornthwaite moisture index and depth of suction change under current and future climate—An Australian study" J. Rock Mech. Geotech. Eng. (2024) 10.1016/j.jrmge.2023.09.009

[30]

Karunarathne "Review of calculation procedures of Thornthwaite moisture index and its impact on footing design" Aust. Geomech. (2016)

[31]

Marshall "Examining evapotranspiration trends in Africa" Clim. Dyn. (2012) 10.1007/s00382-012-1299-y

[32]

A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and opportunities

Sergio Gonzalez, Salvador García, Javier Del Ser et al.

Information Fusion 2020 10.1016/j.inffus.2020.07.007

[33]

Fan, Y., and Dool, H. (2004). Climate Prediction Center global monthly soil moisture data set at 05° resolution for 1948 to present. J. Geophys. Res. Atmos., 109. 10.1029/2003jd004345

[34]

Mohamed "Rainfed-based production of Megathyrsus maximus in sub-Saharan Africa: The case of the semi-arid environment of Sudan African" J. Range Forage Sci. (2022) 10.2989/10220119.2022.2080269

[35]

Starr "Water balance of the Sudanese savannah woodland region" Hydrol. Sci. J. (2015) 10.1080/02626667.2014.914214

[36]

Palmer "Drivers and impacts of Eastern African rainfall variability" Nat. Rev. Earth Environ. (2023) 10.1038/s43017-023-00397-x

[37]

Babaousmail, H., Ayugi, B.O., Onyutha, C., Kebacho, L.L., Ojara, M., and Ongoma, V. (2023). Analysis of Changes in Rainfall Concentration over East Africa. Atmosphere, 14. 10.3390/atmos14111679

[38]

Conway "Rainfall and Water Resources Variability in Sub-Saharan Africa during the Twentieth Century" J. Hydrometeorol. (2009) 10.1175/2008jhm1004.1

[39]

Kotikot, S.M., Smithwick, E., and Greatrex, H. (2024). Observations of enhanced rainfall variability in Kenya, East Africa. Sci. Rep., 14. 10.1038/s41598-024-63786-2

[40]

Onyutha "Trends and variability of temperature and evaporation over the African continent: Relationships with precipitation" Atmósfera (2021)

[41]

Abiye "Potential evapotranspiration trends in West Africa from 1906 to 2015" SN Appl. Sci. (2019) 10.1007/s42452-019-1456-6

[42]

Gadallah "Integrated Approach for Assessment and Monitoring of Forests Conditions in the Drylands of Sudan" Arid. Ecosyst. (2022) 10.1134/s2079096122020032

[43]

Ogou "Hydro-climatic and Water Availability Changes and its Relationship with NDVI in Northern Sub-Saharan Africa" Earth Syst. Environ. (2022) 10.1007/s41748-021-00260-3

[44]

Kumar "Potential and actual evapotranspiration and Landsat derived indices" Glob. J. Environ. Sci. Manag. (2024)

[45]

Mohamed, A., Alarifi, S., and Abdelrady, A. (2023). Sedimentary cover and structural trends affecting the groundwater flow in the Nubian Sandstone Aquifer System: Inferences from geophysical, field and geochemical data. Front. Earth Sci., 11. 10.3389/feart.2023.1173569

[46]

Lombe, P., Elsa, C., and Paulo, R. (2024). Drought Dynamics in Sub-Saharan Africa: Impacts and Adaptation Strategies. Sustainability, 16. 10.3390/su16229902

[47]

Sylla "Projected robust shift of climate zones over West Africa in response to anthropogenic climate change for the late 21st century" Clim. Change (2016) 10.1007/s10584-015-1522-z

[48]

Eltahir "A feedback mechanism in annual rainfall, Central Sudan" J. Hydrol. (1989) 10.1016/0022-1694(89)90195-9

[49]

Reliefweb (2024, November 16). The Sudan: 2020 Flood Response Overview. Available online: https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://openknowledge.fao.org/server/api/core/bitstreams/0d0f41e0-ee2d-494c-9fa7-22792ba8b008/content&ved=2ahUKEwjXr5uV04iKAxXcwAIHHR9IAJkQFnoECB0QAQ&usg=AOvVaw3dONOyndD_Tn8VL_Z8ZBjy.

[50]

Tambal "Increasing urban flood resilience through public participation: A case study of Tuti Island in Khartoum, Sudan" J. Flood Risk Manag. (2024) 10.1111/jfr3.12966

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Details

Published: Dec 02, 2024
Vol/Issue: 12(12)
Pages: 206
License: View

Authors

S

Shamseddin M. Ahmed

Institute of Studies and Consultations, King Faisal University, Al-Ahsa 31982, Saudi Arabia

H

Hassan A. Dinnar

Date Palm Research Center of Excellence, King Faisal University, Al-Ahsa 31982, Saudi Arabia

A

Adam E. Ahmed

Department of Agribusiness and Consumer Sciences, College of Agricultural and Food Sciences, King Faisal University, Al-Ahsa 31982, Saudi Arabia

A

Azharia A. Elbushra

Department of Agribusiness and Consumer Sciences, College of Agricultural and Food Sciences, King Faisal University, Al-Ahsa 31982, Saudi Arabia

K

Khalid G. Biro Turk

Water and Environmental Studies Center, King Faisal University, Al-Ahsa 31982, Saudi Arabia

Cite This Article

Shamseddin M. Ahmed, Hassan A. Dinnar, Adam E. Ahmed, et al. (2024). A Deeper Understanding of Climate Variability Improves Mitigation Efforts, Climate Services, Food Security, and Development Initiatives in Sub-Saharan Africa. Climate, 12(12), 206. https://doi.org/10.3390/cli12120206

A Deeper Understanding of Climate Variability Improves Mitigation Efforts, Climate Services, Food Security, and Development Initiatives in Sub-Saharan Africa

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