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Climate Trends and Their Impact on Sorghum Production in Marigat, Baringo County: A Historical Analysis

DOI: 10.4236/ojmh.2024.142007, PP. 106-129

Keywords: Trends, Precipitation, Temperature, RAI, SPI, SPEI, and MK

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Abstract:

Climate is subject to fluctuations in the majority of the world, mainly caused by rainfall as well as temperature variations. Climate fluctuations in Kenya have resulted in the spread of desert-like conditions in the ASALs region, such as Marigat in Baringo County. As a county, Baringo experiences great variations in climate annually, as well as uncertainty in expected rains, thereby negatively impacting the production of crops such as sorghum. This study applied the rainfall anomaly index (RAI), standardised precipitation evapotranspiration index (SPEI), standard precipitation index (SPI), and Mann-Kendall (MK) statistical test for trends on historical climatic data in analysing both temperature and precipitation data over the period 1990 to 2022 to determine their trend, patterns and how they affect the production of sorghum crops. The machine learning method (R studio) with inputs was used to calculate the SPI, SPEI, RAI and MK trend test. The rainfall varied from below average to above average during the study period with no clear pattern in the RAI, SPEI and SPI values. The years 2020 and 2000 stood out as they had higher and lower rainfall than usual, respectively. The Marigat area generally experienced more rainfall during the high/long rainfall season (AMJJ). The MK trend test on average monthly rainfall, SOND, AMJJ, and annual precipitation confirmed a positive trend in precipitation. However, the short rainy season (SOND) was found to be the most variable period for rainfall, and there was a slight increase in daily average temperatures during this season.

References

[1]  Walter, J. (2018) Effects of Changes in Soil Moisture and Precipitation Patterns on Plant-Mediated Biotic Interactions in Terrestrial Ecosystems. Plant Ecology, 219, 1449-1462.
https://doi.org/10.1007/s11258-018-0893-4
[2]  Yang, W., Seager, R. and Cane, M.A. (2014) The East African Long Rains in Observations and Models. Journal of Climate, 27, 7185-7202.
https://doi:10.1175/JCLI-D-13-00447.1
[3]  Omondi, P.A. et al. (2014) Changes in Temperature and Precipitation Extremes over the Greater Horn of Africa Region from 1961 to 2010. International Journal of Climatology, 34, 1262-1277.
https://doi:10.1002/joc.3763
[4]  Landmann, T. and Dubovyk, O. (2014) Spatial Analysis of Human-Induced Vegetation Productivity Decline over Eastern Africa Using a Decade (2001-2011) of Medium Resolution MODIS Time-Series Data. International Journal of Applied Earth Observation and Geoinformation, 33, 76-82.
https://doi.org/10.1016/j.jag.2014.04.020
[5]  Eggen, M., Ozdogan, M., Zaitchik, B., Ademe, D., Foltz, J. and Simane, B. (2019) Vulnerability of Sorghum Production to Extreme, Sub-Seasonal Weather under Climate Change. Environmental Research Letters, 14, Article 045005.
https://doi:10.1088/1748-9326/aafe19
[6]  Lelenguyah, G.L., Kabochi, S.K. and Biwot, J.C.B. (2016) Pastoralists’ Perception on the Trend of Various Climatic, Social and Environmental Variables in Baringo County, Kenya. Journal of Ecological Anthropology, 18.
https://digitalcommons.usf.edu/jea/vol18/iss1/2
[7]  Mwaura, J., Koske, J. and Kiprotich, B. (2017) Economic Value of Water Harvesting for Climate-Smart Adaptation in Semi-Arid Ijara Garissa, Kenya. Environmental Systems Research, 6, Article No. 11.
https://doi:10.1186/s40068-017-0088-3
[8]  Hawinkel, P., et al. (2016) Vegetation Response to Precipitation Variability in East Africa Controlled by Biogeographical Factors. Journal of Geophysical Research: Biogeosciences, 121, 2422-2444.
https://doi.org/10.1002/2016JG003436
[9]  Powell, J.P. and Reinhard, S. (2016) Measuring the Effects of Extreme Weather Events on Yields. Weather and Climate Extremes, 12, 69-79.
https://doi.org/10.1016/j.wace.2016.02.003
[10]  de Morais Cardoso, L., Pinheiro, S.S., Martino, H.D. and Pinheiro-Sant’Ana, H.M. (2017) Sorghum (Sorghum bicolor L.): Nutrients, Bioactive Compounds, and Potential Impact on Human Health. Critical Reviews in Food Science and Nutrition, 57, 372-390.
https://doi.org/10.1080/10408398.2014.887057
[11]  Rowell, D.P., Booth, B.B.B., Nicholson, S.E. and Good, P. (2015) Reconciling Past and Future Rainfall Trends over East Africa. American Meteorological Society, 28, 9768-9788.
https://doi.org/10.1175/JCLI-D-15-0140.1
[12]  Grossi, M.C., Justino, F., de Ávila Rodrigues, R. and Andrade, C.L.T. (2015) Sensitivity of the Sorghum Yield to Individual Changes in Climate Parameters: Modelling Based Approach. Bragantia, 74, 341-349.
https://doi.org/10.1590/1678-4499.0411
[13]  Koskei, E.C., Kitetu, J.J. and Recha, C.W. (2018) Analysis of Spatial Variability in Rainfall Trends in Baringo County, Kenya. African Journal of Environmental Science and Technology, 12, 296-304.
https://doi:10.5897/AJEST2016.2214
[14]  Dunjana, N., et al. (2022) Sorghum as a Household Food and Livelihood Security Crop under Climate Change in South Africa: A Review. South African Journal of Science, 118, 1-6.
https://doi.org/10.17159/sajs.2022/13340
[15]  Kumar, M., et al. (2021) Harnessing Sorghum Landraces to Breed High-Yielding, Grain Mold-Tolerant Cultivars with High Protein for Drought-Prone Environments. Front. Plant Science, 12, Article 659874.
https://doi:10.3389/fpls.2021.659874
[16]  Montes-Vega, M.J., Guardiola-Albert, C. and Rodríguez-Rodríguez, M. (2023) Calculation of the SPI, SPEI, and GRDI Indices for Historical Climatic Data from Doñana National Park: Forecasting Climatic Series (2030-2059) Using Two Climatic Scenarios RCP 4.5 and RCP 8.5 by IPCC. Water, 15, Article 2369.
https://doi.org/10.3390/w15132369
[17]  Yilmaz, B. (2019) Analysis of Hydrological Drought treNds in the GAP Region (Southeastern Turkey) by Mann-Kendall Test and Innovative Şen Method. Applied Ecology and Environmental Research, 17, 3325-3342.
http://dx.doi.org/10.15666/aeer/1702_33253342
[18]  Chávez, L.D., Romero, A.P.E. and Vega, J.R. (2021) Drought Assessment in the Northern Region of Colombia Using the Standardized Precipitation Index (SPI): A Case Study in the Department of La Guajira.
https://doi.org/10.21203/rs.3.rs-1029721/v1
[19]  Kug, J.-S., et al. (2023) Negative CO2 Emissions Mitigate Extremes of the Terrestrial Hydrological Cycle via a Vegetation Physiological Feedback.
https://doi.org/10.21203/rs.3.rs-3176943/v1
[20]  Raja, A. and Gopikrishnan, T. (2022) Drought Prediction and Validation for Desert Region using Machine Learning Methods. International Journal of Advanced Computer Science and Applications, 13, 47-53.
[21]  Sané, O.D., Gaye, A.T., Diakhaté, M. and Aziadekey, M. (2016) Critical Factors of Vulnerability That Enable Medina Gounass (Dakar/Senegal) to Adapt against Seasonal Flood Events. Journal of Geographical Systems, 8, 457-469.
http://dx.doi.org/10.4236/jgis.2016.84038
[22]  Aggile, L.P., Gautam, S. and Reddy, B.S.K. (2022) Analysis of Various Drought Indices over Mathura Region Using Geo-Spatial Technologies. IOP Conference Series: Earth and Environmental Science, 982, Article 012034
https://doi:10.1088/1755-1315/982/1/012034
[23]  Mutti, P.R., et al. (2019) A Detailed Framework for the Characterization of Rainfall Climatology in Semiarid Watersheds. Theoretical and Applied Climatology, 139, 109-125.
https://doi.org/10.1007/s00704-019-02963-0
[24]  Dafouf, S., Lahrach, A., Tabyaoui, H., Hafyani, M.E. and Benaabidate, L. (2022) Meteorological Drought Assessment in the Ziz Watershed (South East of Morocco). Ecological Engineering & Environmental Technology, 23, 243-263.
https://doi.org/10.12912/27197050/152959
[25]  Wang, Q., et al. (2022) An Improved Daily Standardized Precipitation Index Dataset for Mainland China from 1961 to 2018. Scientific Data, 9, Article No. 124.
https://doi.org/10.1038/s41597-022-01201-z
[26]  van Rooy, M.P. (1965) A Rainfall Anomaly Index Independent of Time and Space. Notos, 14, 43-48.
[27]  Lawrence, T.J., et al. (2023) Spatial Changes to Climatic Suitability and Availability of Agropastoral Farming Systems across Kenya (1980-2020). Original Research Article, 52, 186-199.
https://doi:10.1177/00307270231176577
[28]  Bosire, E., Karanja, F., Ouma, G. and Gitau, W. (2018) Assessment of Climate Change Impact on Sorghum Production in Machakos County. Sustainable Food Production, 3, 25-45.
https://doi:10.18052/www.scipress.com/SFP.3.25.
[29]  Rafiq, M., Khan, M.Y., Naqvi, S.H.A., Khatoon, N. and Dahot, M.U. (2017) Mutagenic Effects on the Growth, Reproductive and Yield Parameters of Praecitrullus fistulosus. Pakistan Journal of Scientific & Industrial Research, 60, 132-140.
https://doi:10.52763/pjsir.biol.sci.60.3.2017.132.140
[30]  Londhe, V.M., Jadhav, V.T., Birajdar, S.G., Pawar, P.B., Jadhav, J. and Amrutsagar, V.M. (2020) Studies on Sowing Environment for Sustainable Production of Rabi sorghum (Sorghum bicolour L.) under Climate Change Situation in Scarcity Zone of Maharashtra. International Journal of Chemical Studies, 8, 1800-1803.
https://doi:10.22271/chemi.2020.v8.i5y.10562

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