Palmer-type soil modelling for evapotranspiration in different climatic regions of Kenya
Abstract
Reference evapotranspiration (ET0) and real evapotranspiration (ET) are vital components in hydrological processes and climate-related studies. Understanding their variability in estimation is equally crucial for micro-meteorology and agricultural planning processes. The primary goal of this study was to analyze and compare estimates of (ET0) and (ET) from two different climatic regions of Kenya using long-term quality controlled synoptic station datasets from 2000 to 2009 with 3-hour time resolution. One weather station (Voi, 63793) was sought from lowlands with an elevation of 579 m and characterized by tropical savannah climate while the other (Kitale, 63661) was sought from Kenya highlands with humid conditions and elevation of 1850 m above sea level. Reference evapotranspiration was calculated based on the FAO 56 standard methodology of a daily basis. One dimension Palmer-type soil model was used for estimating of real evapotranspiration using the wilting point, field capacity, and soil saturation point for each station at 1 m deep soil layer. The ratio of real and reference evapotranspiration dependent on the soil moisture stress linearly. Calculations of estimated evapotranspiration were made on daily and monthly basis. Applications of the site-specific crop coefficients (KC) were also used. The result indicated that the differences among daily and monthly scale calculations of evapotranspiration (ET) were small without and with an application of crop coefficients (ETKc). This was due to high temperatures, global radiation, and also high soil moisture stress due to inadequate precipitation experienced in the tropics where Kenya lies. Results from Voi showed that mean monthly ET0 ranged from 148.3±11.6 mm in November to 175.3±10.8 mm in March while ET was from 8.0±4.5 mm in September to 105.8±50.3 mm in January. From Kitale, ET0 ranged from 121.5±8.5 mm/month in June to 157.1±8.5 mm/month in March while ET ranged from 41.7±32.6 mm/month in March to 126.6±12.2 mm/month in September. This was due to variability in temperature and precipitation between the two climatic regions. The study concludes that ET0 and calculated evapotranspiration variability among the years on a monthly scale is slightly higher in arid and semi-arid climate regions than in humid regions. The study is important in strategizing viable means to enhance optimal crop water use and reduce ET losses estimates for optimal agricultural yields and production maximization in Kenya.
References
Ács, F. and Breuer, H. 2006. Modelling of soil respiration in Hungary. Agrokémia és Talajtan 55. (6): 59-68. (in Hungarian) https://doi.org/10.1556/agrokem.55.2006.1.7
Ács, F., Breuer, H. and Szász, G. 2007. Estimation of actual evapotranspiration and soil water content in the growing season. Agrokémia és Talajtan 56. (2): 217-236. https://doi.org/10.1556/agrokem.56.2007.2.3
Allen, R.G., Pereira, L.S., Raes, D. and Smith, M. 1998. Crop evapotranspiration: FAO Irrigation and Drainage Paper 56. Rome, UN FAO. Available at http://www.fao.org/3/X0490E/X0490E00.htm
Anderson, M.C., Zolin, C.A., Sentelhas, P.C., Hain, C.R., Semmens, K., Yilmaz, M.T., Gao, F., Otkin, J.A. and Tetrault, R. 2016. The Evaporative Stress Index as an indicator of agricultural drought in Brazil: An assessment based on crop yield impacts. Remote Sensing of Environment 174. 82-99. https://doi.org/10.1016/j.rse.2015.11.034
Ayugi, B., Wen, Y.W. and Chepkemoi, D. 2016. Analysis of spatial and temporal patterns of rainfall variations over Kenya. Environmental Earth Sciences 6. (11): 69-83.
Ayugi, B., Tan, G., Niu, R., Dong, Z., Ojara, M., Mumo, L., Babaousmail, H. and Ongoma, V. 2020. Evaluation of meteorological drought and flood scenarios over Kenya, East Africa. Atmosphere 11. (3): 307. https://doi.org/10.3390/atmos11030307
Beck, H., Zimmermann, N., McVicar, T.R., Vergopolan, N., Berg, A. and Wood, E.F. 2018. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Scientific Data 5. 180214. https://doi.org/10.1038/sdata.2018.214
Bowell, A., Salakpi, E.E., Guigma, K., Muthoka, J.M., Mwangi, J. and Rowhani, P. 2021. Validating commonly used drought indicators in Kenya. Environmental Research Letters 16. (8): 084066. https://doi.org/10.1088/1748-9326/ac16a2
Camberlin, P. and Wairoto, J.G. 1997. Intra-seasonal wind anomalies related to wet and dry spells during "long" and "short" rainy seasons in Kenya. Theoretical Applied Climatology 58. 57-69. https://doi.org/10.1007/BF00867432
Choi, M., Jacobs, J.M., Anderson, M.C. and Bosch, D.D. 2013. Evaluation of drought indices via remotely sensed data with hydrological variables. Journal of Hydrology 476. 265-273. https://doi.org/10.1016/j.jhydrol.2012.10.042
Djaman, K., Irmak, S. and Futakuchi, K. 2017. Daily reference evapotranspiration estimation under limited data in Eastern Africa. Journal of Irrigation and Drainage Engineering 143. (4): 0001154. https://doi.org/10.1061/(ASCE)IR.1943-4774.0001154
Djaman, K., Ndiaye, P.M., Koudahe, K., Bodian, A., Diop, L., O'Neill, M. and Irmak, S. 2018. Spatial and temporal trend in monthly and annual reference evapotranspiration in Madagascar for the 1980-2010 periods. International Journal of Hydrology2. (2): 110-120. https://doi.org/10.15406/ijh.2018.02.00058
Dy, C.Y. and Fung, J.C.-H. 2016. Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model. Journal of Geophysical Research: Atmospheres 121. 8777-8800. https://doi.org/10.1002/2015JD024558
Ferina, J., Vučetić, V., Bašić, T. and Anić, M. 2021. Spatial distribution and long-term changes in water balance components in Croatia. Theoretical Applied Climatology 144. 1311-1333. https://doi.org/10.1007/s00704-021-03593-1
Ghaedi, S. 2021. Anomalies of precipitation and drought in objectively derived climate regions of Iran. Hungarian Geographical Bulletin 70. (2): 163-174. https://doi.org/10.15201/hungeobull.70.2.5
Ghasemi, A. and Zahediasl, S. 2012. Normality tests for statistical analysis: a guide for non-statisticians. International Journal of Endocrinology and Metabolism 10. (2): 486-489. https://doi.org/10.5812/ijem.3505
Government of Kenya, 2013. County Integrated Development Plan, Taita Taveta County. Government of Taita Taveta. Nairobi, Government Printers.
Guerra, E., Snyder, R.L. and Ventura, F. 2011. Crop coefficients to adapt for climate change impact on evapotranspiration. Italian Journal Agrometeorology14. (2): 15-16.
Hao, X., Zhang, S., Li, W., Duan, W., Fang, G., Zhang, Y. and Guo, B. 2018. The uncertainty of Penman-Monteith method and the energy balance closure problem. Journal of Geophysical Research: Atmospheres 123. 7433-7443. https://doi.org/10.1029/2018JD028371
Hobeichi, S., Abramowitz, G., Evans, J. and Ukkola, A. 2018. Derived Optimal Linear Combination Evapotranspiration (DOLCE): A global gridded synthesis ET estimate. Hydrology and Earth System Sciences Discussions 22. 1317-1336. https://doi.org/10.5194/hess-22-1317-2018
Huho, J.M. and Mugalavai, M.E. 2010. The effects of droughts on food security in Kenya. The International Journal of Climate Change: Impacts and Responses 2. (2): 61-72. https://doi.org/10.18848/1835-7156/CGP/v02i02/37312
Huho, J.M. 2017. An analysis of rainfall characteristics in Machakos County, Kenya. IOSR Journal of Environmental Science, Toxicology and Food Technology 11. (4): 64-72. https://doi.org/10.9790/2402-1104026472
Ilyés, C., Wendo, V.A.J.A., Carpio, Y.F. and Szűcs, P.2021. Differences and similarities between precipitation patterns of different climates. Acta Geodaetica et Geophysica 56. 781-800. https://doi.org/10.1007/s40328-021-00360-6
Irmak, S. and Haman, D.Z. 2003. Evapotranspiration: Potential or Reference. Agricultural Engineering Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences. Gainesville, University of Florida, ABE.
Kipkemboi, K.B., Kumar, L. and Koech, R. 2021. Climate change and variability in Kenya: a review of impacts on agriculture and food security. Environment, Development and Sustainability 23. 23-43. https://doi.org/10.1007/s10668-020-00589-1
Lakatos, M., Weidinger, T., Hoffmann, L., Bihari, Z. and Horváth, Á. 2020. Computation of daily Penman-Monteith reference evapotranspiration in the Carpathian Region and comparison with Thornthwaite estimates. Advances in Science and Research 16. 251-259. https://doi.org/10.5194/asr-16-251-2020
Lang, D., Zheng, J., Shi, J., Liao, F., Ma, X., Wang, W., Chen, X. and Zhang, M. 2017. A comparative study of potential evapotranspiration estimation by eight methods with FAO Penman-Monteith method in Southwestern China. Water 9. 734. https://doi.org/10.3390/w9100734
Lim, G.-K., Kim, B.-S., Lee, B.-H. and Jeung, S.-J. 2020. Effect of climate change on annual precipitation in Korea using data screening techniques and climate change scenarios. Atmosphere 11. (10): 1027. https://doi.org/10.3390/atmos11101027
Liu, Y., Hao, L., Zhou, D., Pan, C., Liu, P., Xiong, Z. and Sun, G. 2019. Identifying a transition climate zone in an arid river basin using the evaporative stress index. Natural Hazards Earth System Science 19. 2281-2294. https://doi.org/10.5194/nhess-19-2281-2019
Luciani, R., Laneve, G. and Jahjah, M. 2019. Agricultural monitoring, an automatic procedure for crop mapping and yield estimation: The Great Rift Valley of Kenya case. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12. (7): 2196-2208. https://doi.org/10.1109/JSTARS.2019.2921437
Macharia, J.M., Ngetich, F.K. and Shisanya, C.A. 2021. Parameterization, calibration and validation of the DNDC model for carbon dioxide, nitrous oxide and maize crop. Heliyon 7. (5): e06977. https://doi.org/10.1016/j.heliyon.2021.e06977
Marshall, M.T., Funk, C. and Michaelsen, J. 2012. Agricultural drought monitoring in Kenya using evapotranspiration derived from remote sensing and reanalysis data. USGS Staff - Published Research 978. Available at http://digitalcommons.unl.edu/usgsstaffpub/978
Mayaki, W.C., Stone, L.R. and Teare, I.D. 1976. Irrigated and non-irrigated soybean, corn, and grain sorghum root systems. Agronomy Journal 68. 532-534. https://doi.org/10.2134/agronj1976.00021962006800030028x
Mbaisi, C.N., Kipkorir, E.C. and Omondi, P. 2016. The perception of farmers on climate change and variability patterns in the Nzoia River Basin, Kenya. Journal of Natural Sciences Research 6. (20): 89-97. Available at https://core.ac.uk/download/pdf/234656697.pdf
McColl, K.A. 2020. Practical and theoretical benefits of an alternative to the Penman-Monteith evapotranspiration equation. Water Resources Research 56. e2020WR027106. https://doi.org/10.1029/2020WR027106
McColl, K.A. and Rigden, A.J. 2020. Emergent simplicity of continental evapotranspiration. Geophysical Research Letters 47. e2020GL087101. https://doi.org/10.1029/2020GL087101
McMahon, T.A., Peel, M.C., Lowe, L., Srikanthan, R. and McVicar, T.R. 2013. Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences 17. 1331-1363. https://doi.org/10.5194/hess-17-1331-2013
Meteomanz.com by NOAA. Available at http://www.meteomanz.com
Mintz, Y. and Walker, G.K. 1993. Global fields of soil moisture and land surface evapotranspiration derived from observed precipitation and surface air temperature. Journal of Applied Meteorology 32. (8): 1305-1334. https://doi.org/10.1175/1520-0450(1993)032<1305:GFOSMA>2.0.CO;2
Mugo, J.W., Kariuki, P.C. and Musembi, D.K. 2016. Identification of suitable land for green grain production using GIS based analytical hierarchy process in Kitui County, Kenya. Journal of Remote Sensing & GIS 5. 170. https://doi.org/10.4172/2469-4134.1000170
Musyimi, P.K., Székely, B. and Weidinger, T. 2021. Long term (1901-2016) temperature based potential evapotranspiration and aridity index analysis for lower eastern region of Kenya. Egyetemi Meteorológiai Füzetek / Meteorological Notes of University 33. (9): 74-83. https://doi.org/10.31852/EMF.33.2020.074.083
Mwakesi, I., Wahome, R. and Ichang'i, D. 2020. Mining impacts on society: A case study of Taita Taveta County, Kenya. Journal of Environmental Protection 11. 986-997. https://doi.org/10.4236/jep.2020.1111062
Ngetich, K.F., Raes, D., Shisanya, C.A., Mugwe, J., Mucheru-Muna, M., Mugendi, D.N. and Diels, J. 2012. Calibration and validation of AquaCrop model for maize in sub-humid and semiarid regions of central highlands of Kenya. In Third RUFORUM Biennial Meeting 24-28 September 2012, Entebbe, Uganda. Kampala, Uganda, RUFORUM, 1528-1548.
Nicholson, S.E. 2017. Climate and climatic variability of rainfall over eastern Africa. Review of Geophysics 55. 590-635. https://doi.org/10.1002/2016RG000544
Nyaoro, D., Schade, D. and Schmidt, K. 2016. Assessing the Evidence: Migration, Environment and Climate Change in Kenya. Geneva, International Organization for Migration IOM. Available at https://www.preventionweb.net/files/50534_assessingtheevidencekenya.pdf
Nyberg, J.M., Ambjörnsson, E.L., Wetterlind, J. and Öborn, I. 2020. Smallholders' awareness of adaptation and coping measures to deal with rainfall variability in Western Kenya. Agroecology and Sustainable Food Systems 44. (10): 1280-1308. https://doi.org/10.1080/21683565.2020.1782305
Obiero, J. and Onyando, J. 2013. Climate, developments in earth surface processes. In Kenya: A Natural Outlook Geo-Environmental Resources and Hazards. Developments in Earth Surface Processes 16. Eds.: Paron, P., Olago, O. and Omuto. T., Amsterdam, Elsevier, 39-50. https://doi.org/10.1016/B978-0-444-59559-1.00005-0
Obwocha, E.B., Ramisch, J.J., Duguma, L. and Orero, L. 2022. The relationship between climate change, variability, and food security: Understanding the impacts and building resilient food systems in West Pokot County, Kenya. Sustainability 14. 765. https://doi.org/10.3390/su14020765
Ogallo, L.A., Omay, P., Kabaka, G. and Lutta, I. 2019. Report on Historical Climate Baseline Statistics for Taita Taveta, Kenya. Nairobi, IGAD Climate Prediction and Application Centre.
Okello, C., Greggio, N., Giambastiani, B.M.S., Wambiji, N., Nzeve, J. and Antonellini, M. 2020. Modelling projected changes in soil water budget in coastal Kenya under different long-term climate change scenarios. Water 12. 2455. https://doi.org/10.3390/w12092455
Omondi, J.O., Mungai, N.W., Ouma, J.P. and Baijukya, F.P. 2017. Shoot water content and reference evapotranspiration for determination of crop evapotranspiration. African Crop Science Journal 25. (4): 387-403. https://doi.org/10.4314/acsj.v25i4.1
Palmer, W.C. 1965. Meteorological Drought. U.S. Research Paper 45. Indicator codes CLIM 029, LSI 007. Washington, DC, US Weather Bureau.
Peel, M.C., Finlayson, B.L. and McMahon, T.A. 2007. Updated world map of the Köppen-Geiger climate classification. Hydrology and Earth System Sciences Discussions EGU 11. 1633-1644. https://doi.org/10.5194/hess-11-1633-2007
Penman, H.L. 1948. Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London, Series A. Mathematical and Physical Sciences 193. (1032): 120-145. https://doi.org/10.1098/rspa.1948.0037
Ransom, J., Endres, G.J., Berlund, D.R., Endres, G.J. and McWilliams, D.A. 2014. Corn Growth and Management: Quick Guide. Fargo, ND, North Dakota State University Extension Service.
Sadick, A., Gaisie, E., Adjei, E.O., Agyeman, K.,Nketia, K.A. and Asamoah, E. 2015. Assessment of the relationship between actual evapotranspiration, reference evapotranspiration and precipitation. A case study of Tono irrigation scheme. International Journal of Scientific Research in Science and Technology 1. (5): 307-317.
Shanahan, J.F. and Nielsen, D.C. 1987. Influence of growth retardants (anti-gibberellins) on corn vegetative growth, water use, and grain yield under different levels of water stress. Agronomy Journal 79. 103-109. https://doi.org/10.2134/agronj1987.00021962007900010022x
Shilenje, Z.W., Murage, P. and Ongoma, V. 2015. Estimation of potential evaporation based on Penman equation under varying climate, for Murang'a County, Kenya. Pakistan Journal of Meteorology 12. (23): 33-42.
Stegman, E.C. 1982. Corn grain yield as influenced by timing of evapotranspiration deficits. Irrigation Science 3. 75-87. https://doi.org/10.1007/BF00264851
Tyagi, N.K., Sharma, D.K. and Luthra, S.K. 2003. Determination of evapotranspiration for maize and berseem clover. Irrigation Science 21. (4): 173-181. https://doi.org/10.1007/s00271-002-0061-3
Venton, C.C. 2018. Economics of Resilience to Drought Kenya Analysis. USAID Center for Resilience. Nairobi, USAID Kenya.
Wambugu, P.W., Mathenge, P.W., Auma, E.O. and van Rheenen, H.A. 2012. Constraints to on-farm maize (Zea mays L.) seed production in Western Kenya: Plant growth and yield. International Scholarly Research Notices Article ID 153412. https://doi.org/10.5402/2012/153412
Yao, A.Y.M. 1974. Agricultural potential estimated from the ratio of actual to potential evapotranspiration. Agricultural Meteorology 13. 405-417. https://doi.org/10.1016/0002-1571(74)90081-8
Yang, Z., Qiang, Z. and Xiaocui, H. 2016.Evapotranspiration trend and its relationship with precipitation over Loess Plateau during the last three decades. Advances in Meteorology 2016 Article ID 6809749, 10. https://doi.org/10.1155/2016/6809749
Zotarelli, L., Dukes, M.D., Romero, C.C., Migliaccio,K.W. and Morgan, K.T. 2010. Step by Step Calculation of the Penman-Monteith Evapotranspiration (FAO-56 method). Institute of Food and Agricultural Sciences. Gainesville, University of Florida, AE 459.
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