Abstract
The focus of this paper was to investigate the spatial and temporal variability of dry and wet events using the standard precipitation and evapotranspiration index (SPEI) in the Tana River Basin (TRB) in Kenya. The SPEI is a new drought index which incorporates the effect of evapotranspiration on drought analysis thus making it possible to identify changes in water demand in the context of global warming. The SPEI was computed at 6- and 12-month timescales using a 54-year long monthly rainfall data from the Global Precipitation and Climate Center (GPCC) and temperature data from the Climate Research Unit (CRU) both recorded between 1960 and 2013. Both datasets have a spatial resolution of 0.5° by 0.5° and were extracted for every grid point in the basin. The SPEI was used to assess the temporal and spatial evolution of dry and wet events as well as determine their duration, severity, and intensity. The evolution of significant historical dry and wet events and the frequency of occurrence were clearly identified. The index showed that the period between 1960 and 1980 was dominated by dry events while wet events were dominant in the period between 1990 and 2000. The SPEI6 had the longest duration of dry events of 30 months and severity of 44.67 which was observed at grid 5while the highest intensity was 2.18 observed at grid 31. Grid 19 had the longest duration (52 months) and highest severity (88.08) of dry events for SPEI12 and the intensity was highest (1.94) in grid 31. The longest duration (23) and highest severity (40.03) of wet events for SPEI6 were recorded in grid 39. The highest intensity of wet events for SPEI6 was 1.91 at grid 23 and 1.81 at grid 37 for SPEI12. The principal component analysis (PCA) was applied to the SPEI time series in order to assess the spatial pattern of variability of the dry and wet events in the basin. The PCA showed that there were two leading components which explained over 80% of the spatial variation of dry and wet events in the basin. Further, the continuous wavelet transform (CWT) was applied to the PCA scores in order to capture the time-frequency dynamics. The wavelet transform of the SPEI6 and SPEI12 identified significant periodicities of 1 to 2 years across the spectrum.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Baker T, Kiptala J, Olaka L, Oates N (2015) Baseline review and ecosystem services assessment of the Tana River Basin. IWMI working paper 165, Kenya
Beguería S, Vicente-Serrano SM (2013) Package ‘SPEI’. calculation of the Standard Precipitation-Evapotranspiration Index. http://sac.csic.es/spei
Beguería S, Vicente-Serrano SM, Reig F, Latorre B (2014) Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. Int J Climatol 34(10):3001–3023. https://doi.org/10.1002/joc.3887
Bordi I, Fraedrich K, Jiang JM, Sutera A (2004) Spatio-temporal variability of dry and wet periods in eastern China. Theor Appl Climatol 79(1–2):81–91. https://doi.org/10.1007/s00704-004-0053-8
Burke EJ, Brown SJ, Christidis N (2006) Modeling the recent evolution of global drought and projections for the twenty-first century with the Hadley Centre climate model. J Hydrometeorol 7(5):1113–1125. https://doi.org/10.1175/JHM544.1
Caramelo L, Orgaz M (2007) A study of precipitation variability in the Duero Basin (Iberian Peninsula). Int J Climatol 27:327–339. https://doi.org/10.1002/joc
Chen H, Sun J (2015) Changes in drought characteristics over China using the standardized precipitation evapotranspiration index. J Clim 28(13):5430–5447. https://doi.org/10.1175/JCLI-D-14-00707.1
Droogers P, Allen RG (2002) Estimating reference evapotranspiration under. Irrig Drain Syst 16:33–45. https://doi.org/10.1023/A:1015508322413
Dubrovsky M, Svoboda MD, Trnka M, Hayes MJ, Wilhite DA, Zalud Z, Hlavinka P (2009) Application of relative drought indices in assessing climate-change impacts on drought conditions in Czechia. Theor Appl Climatol 96(1–2):155–171. https://doi.org/10.1007/s00704-008-0020-x
Gao X, Zhao Q, Zhao X, Wu P, Pan W, Gao X, Sun M (2017) Temporal and spatial evolution of the standardized precipitation evapotranspiration index (SPEI) in the Loess Plateau under climate change from 2001 to 2050. Sci Total Environ 595:191–200. https://doi.org/10.1016/j.scitotenv.2017.03.226
Gichuki, P., & Vigerstol, K. (2014). Presentation from the 2014 world water week in Stockholm
Githui F, Gitau W, Bauwens W (2009) Climate change impact on SWAT simulated streamflow in western Kenya. Int J Climatol 1834(December 2008):1823–1834. https://doi.org/10.1002/joc
Hargreaves GH, Allen RG (2003) History and evaluation of Hargreaves evapotranspiration equation. J Irrig Drain Eng-Asce 129(1):53–63. https://doi.org/10.1061/(ASCE)0733-9437(2003)129:1(53)
Hartmann H, Becker S, Jiang T (2012) Precipitation variability in the Yangtze River subbasins. Water Int 37(1):16–31. https://doi.org/10.1080/02508060.2012.644926
Hayes MJ, Svoboda M, LeComte D, Redmond KT, Pasteris P (2005) Drought monitoring: new tools for the 21st century. In: Wilhite D (ed) Drought and water crises: science, technology, and management issues. CRC Press
Hernandez EA, Uddameri V (2014) Standardized precipitation evaporation index (SPEI)-based drought assessment in semi-arid south Texas. Environ Earth Sci 71(6):2491–2501. https://doi.org/10.1007/s12665-013-2897-7
Hisdal H, Tallaksen LM (2003) Estimation of regional meteorological and hydrological drought characteristics: a case study for Denmark. J Hydrol 281(3):230–247. https://doi.org/10.1016/S0022-1694(03)00233-6
Huang J, Zhang J, Zhang Z, Sun S, Yao J (2012) Simulation of extreme precipitation indices in the Yangtze River basin by using statistical downscaling method (SDSM). Theor Appl Climatol 108(3–4):325–343. https://doi.org/10.1007/s00704-011-0536-3
IPCC (2007) Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. J Chem Inf Model 53. https://doi.org/10.1017/CBO9781107415324.004
Jacobs JH, Angerer J, Vitale J, Srinivasan R, Kaitho R (2007) Mitigating economic damage in Kenya’s upper Tana River Basin: an application of arc-view SWAT. J Spat Hydrol 7(1):23–46
Jury MR (2010) Ethiopian decadal climate variability. Theor Appl Climatol 101(1):29–40. https://doi.org/10.1007/s00704-009-0200-3
Kabanda TA, Jury MR (1999) Inter-annual variability of short rains over northern Tanzania. Clim Res 13(3):231–241. https://doi.org/10.3354/cr013231
Kerandi NM, Laux P, Arnault J, Kunstmann H (2016) Performance of the WRF model to simulate the seasonal and interannual variability of hydrometeorological variables in East Africa: a case study for the Tana River basin in Kenya. Theor Appl Climatol 130:1–18. https://doi.org/10.1007/s00704-016-1890-y
Kisaka MO, Mucheru-Muna M, Ngetich FK, Mugwe JN, Mugendi D, Mairura F (2015) Rainfall variability, drought characterization, and efficacy of rainfall data reconstruction: case of Eastern Kenya. Adv Meteorol 2015:1–16. https://doi.org/10.1155/2015/380404
Łabedzki L (2007) Estimation of local drought frequency in Central Poland using the standardized precipitation index SPI. Irrig Drain 56:67–77. https://doi.org/10.1002/ird
Lau K-M, Weng H (1995) Climate signal detection using wavelet Transform: How to Make a Time Series Sing. Bull Am Meteorol Soc. https://doi.org/10.1175/1520-0477(1995)076<2391:CSDUWT>2.0.CO;2
Liebmann B, Hoerling MP, Funk C, Blade ´ I, Dole RM, Allured D, Quan X, Pegion P, Eischeid JK (2014) Understanding recent Eastern Horn of Africa rainfall variability and change. J Clim 27:8630–8645. https://doi.org/10.1175/JCLI-D-13-00714.1
Liu X, Wang S, Zhou Y, Wang F, Li W, Liu W (2015) Regionalization and spatiotemporal variation of drought in China based on standardized precipitation evapotranspiration index (1961-2013). Adv Meteorol 2015:1–18. https://doi.org/10.1155/2015/950262
Lorenzo-lacruz J, Vicente-serrano SM, López-moreno JI, Beguería S, García-ruiz JM (2010) The impact of droughts and water management on various hydrological systems in the headwaters of the Tagus River ( central Spain ). J Hydrol 386(1–4):13–26. https://doi.org/10.1016/j.jhydrol.2010.01.001
Lyon B (2014) Seasonal drought in the Greater Horn of Africa and its recent increase during the March-May long rains. J Clim 27(21):7953–7975. https://doi.org/10.1175/JCLI-D-13-00459.1
Lyon B, Dewitt DG (2012) A recent and abrupt decline in the East African long rains. Geophys Res Lett 39(2):1–5. https://doi.org/10.1029/2011GL050337
Mahfouz P, Mitri G, Jazi M, Karam F (2016) Investigating the temporal variability of the standardized precipitation index in Lebanon. Climate 4(2):27. https://doi.org/10.3390/cli4020027
Mwale D, Gan TY (2004) Wavelet analysis of variability, teleconnectivity, and predictability of the September–November east african rainfall. Journal of Applied Meteorology 44:256–269
Nakaegawa T, Wachana C (2012) First impact assessment of hydrological cycle in the Tana River Basin, Kenya, under a changing climate in the late 21st century. Hydrol Res Lett 6:29–34. https://doi.org/10.3178/hrl.6.29
Nicholson SE, Nyenzi BS (1990) Temporal and spatial variability of SSTs in the tropical Atlantic and Indian oceans. Meteorog Atmos Phys 42(12):1–17. https://doi.org/10.1016/S0198-0254(06)80174-3
Ogallo LJ (1982) Quasi-periodic patterns in the East African rainfall records. Ken va. J Sci Technol 3:43–54
Okazawa H, Toyoda H, Suzuki S, Shimada S, Nishimaki R (2009) Long-term discharge analysis using the EPA method for the Tana River in Kenya. J Arid Land Stud 19:57–60
Oludhe C, Sankarasubramanian A, Sinha T, Devineni N, Lall U (2013) The role of multimodel climate forecasts in improving water and energy management over the Tana River Basin, Kenya. J Appl Meteorol Climatol 52(11):2460–2475. https://doi.org/10.1175/JAMC-D-12-0300.1
Ongoma V, Chen H (2017) Temporal and spatial variability of temperature and precipitation over East Africa from 1951 to 2010. Meteorol Atmos Phys 129:131–144. https://doi.org/10.1007/s00703-016-0462-0
Potop V, Možný M, Soukup J (2012) Drought evolution at various time scales in the lowland regions and their impact on vegetable crops in the Czech Republic. Agric For Meteorol 156:121–133. https://doi.org/10.1016/j.agrformet.2012.01.002
Rajeevan M, Bhate J, Kale JD, Lal B (2006) High resolution daily gridded rainfall data for the Indian region: analysis of break and active monsoon spells. Curr Sci 91(3):296–306. https://doi.org/10.1007/s12040-007-0019-1
Raziei T, Bordi I, Pereira LS (2011) An application of GPCC and NCEP/NCAR datasets for drought variability analysis in Iran. Water Resour Manag 25(4):1075–1086. https://doi.org/10.1007/s11269-010-9657-1
Rodhe H, Virji H (1976) Trends and periodicities in East African rainfall data. Mon Weather Rev 104(March 1976):307–315. https://doi.org/10.1175/1520-0493(1976)104<0307:TAPIEA>2.0.CO;2
Rosch A, Schmidbauer H (2014) WaveletComp : a guided tour through the R-package, 1–38
Rowell DP, Booth BBB, Nicholson SE, Good P (2015) Reconciling past and future rainfall trends over East Africa. J Clim 28(24):9768–9788. https://doi.org/10.1175/JCLI-D-15-0140.1
Santos CA, Ideião SM (2005) Application of the wavelet transform for analysis of precipitation and runoff time series. Predictions in Ungauged Basins: Promise and Progress (Proceedings of symposium S7 held during the Seventh IAHS Scientific Assembly at Foz do Iguaçu, Brazil, April 2005). IAHS Publ. 303, 2006
Santos JF, Pulido-Calvo I, Portela MM (2010) Spatial and temporal variability of droughts in Portugal. Water Resour Res 46(3):1–13. https://doi.org/10.1029/2009WR008071
Schneider U, Becker A, Finger P, Meyer-Christoffer A, Ziese M, Rudolf B (2014) GPCC's new land-surface precipitation climatology based on quality-controlled in-situ data and its role in quantifying the global water cycle, Theor Appl Climatology 115:15–40. https://doi.org/10.1007/s00704-013-0860-x; http://link.springer.com/article/10.1007%2Fs00704-013-0860-x
Shi B, Zhu X, Hu Y, Yang Y (2017) Drought characteristics of Henan province in 1961-2013 based on standardized precipitation evapotranspiration index. J Geogr Sci 27(3):311–325. https://doi.org/10.1007/s11442-017-1378-4
Shongwe ME, van Oldenborgh GJ, van den Hurk B, van Aalst M (2011) Projected changes in mean and extreme precipitation in Africa under global warming. Part II: East Africa. J Clim 24(14):3718–3733. https://doi.org/10.1175/2010JCLI2883.1
Stagge J, Tallaksen L (2014) Standardized precipitation-evapotranspiration index (SPEI): sensitivity to potential evapotranspiration model and parameters. Int Assoc Hydrol Sci (IAHS) 10(October):367–373 Retrieved from http://www.researchgate.net/profile/Chong_Yu_Xu/publication/270576580_Standardized_precipitation-evapotranspiration_index_(SPEI)_Sensitivity_to_potential_evapotranspiration_model_and_parameters/links/54b386240cf220c63cd2836a.pdf. Accessed 16 Feb 2018
The World Bank (2011) The drought and food crisis in the horn of africa
Torrence C, Compo GP (1998) A practical guide to wavelet analysis. Bull Am Meteor Soc 79(1):61–78. https://doi.org/10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2
Vicente-serrano SM, Beguería S, López-moreno JI, Juan I (2010) A multiscalar drought index sensitive to global warming : the standardized precipitation evapotranspiration index. J Clim 23:1696–1718. https://doi.org/10.1175/2009JCLI2909.1
Vicente-Serrano SM, Beguería S, Lorenzo-Lacruz J, Camarero JJ, López-Moreno JI, Azorin-Molina C et al (2012) Performance of drought indices for ecological, agricultural, and hydrological applications. Earth Interact 16(10):1–27. https://doi.org/10.1175/2012EI000434.1
Wagesho N, Goel NK, Jain MK (2013) Temporal and spatial variability of annual and seasonal rainfall over Ethiopia. Hydrol Sci J 58(2):354–373. https://doi.org/10.1080/02626667.2012.754543
Wambua RM, Mutua BM, Raude JM (2015) Spatio-temporal drought characterization for the upper Tana River Basin, Kenya using Standardized Precipitation Index (SPI). World Journal of Environmental Engineering 3(4):111–120. https://doi.org/10.12691/wjee-3-4-2
Williams AP, Funk C (2011) A westward extension of the warm pool leads to a westward extension of the Walker circulation , drying Eastern Africa. Clim Dyn 37(2011):2417–2435. https://doi.org/10.1007/s00382-010-0984-y
Worqlul AW, Maathuis B, Adem AA, Demissie SS, Langan S, Steenhuis TS (2014) Comparison of rainfall estimations by TRMM 3B42, MPEG and CFSR with ground-observed data for the Lake Tana basin in Ethiopia. Hydrol Earth Syst Sci 18(12):4871–4881. https://doi.org/10.5194/hess-18-4871-2014
Wu C, Xian Z, Huang G (2016) Meteorological drought in the Beijiang River basin, South China: current observations and future projections. Stoch Environ Res Risk Assess 30:1821–1834. https://doi.org/10.1007/s00477-015-1157-7
Yu M, Li Q, Hayes MJ, Svoboda MD, Heim RR (2014) Are droughts becoming more frequent or severe in China based on the standardized precipitation evapotranspiration index: 1951-2010? Int J Climatol 34(3):545–558. https://doi.org/10.1002/joc.3701
Zambreski ZT (2016) A stastical assessment of drought variability and climate prediction for Kansas. A Master Degree Thesis for Kansas State University
Zhang Q, Xu C, Zhang Z (2009) Observed changes of drought / wetness episodes in the Pearl River basin, China, using the standardized precipitation index and aridity index. Theor Appl Climatol 98:89–99. https://doi.org/10.1007/s00704-008-0095-4
Zhao G, Mu X, Hörmann G, Fohrer N, Xiong M, Su B (2012) Spatial patterns and temporal variability of dryness/wetness in the Yangtze River. Quat Int 282:5–13. https://doi.org/10.1016/j.quaint.2011.10.020
Acknowledgements
This work was supported by the Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions, through the second author. The first author would like to thank the Chinese Scholarship Council (CSC) for the scholarship afforded to him. Special thanks go to Nanjing University of Information Science and Technology for providing the required facilities for data analysis and for all other forms of support. Appreciation goes to the Consortium for Spatial Information of the Consultative Group for International Agricultural Research (CGIAR-CSI) for providing SRTM 90 database used for processing the digital elevation (http://srtm.csi.cgiar.org), the GPCC and CRU for providing data, and the R-program team for providing the tools for analysis.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Polong, F., Chen, H., Sun, S. et al. Temporal and spatial evolution of the standard precipitation evapotranspiration index (SPEI) in the Tana River Basin, Kenya. Theor Appl Climatol 138, 777–792 (2019). https://doi.org/10.1007/s00704-019-02858-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00704-019-02858-0