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CLIMATE- AND LAND USE-INDUCED RISKS TO WATERSHED SERVICES IN THE NYANDO RIVER BASIN, KENYA

Published online by Cambridge University Press:  25 March 2011

MWANGI GATHENYA*
Affiliation:
Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000–00200 Nairobi, Kenya
HOSEA MWANGI
Affiliation:
Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000–00200 Nairobi, Kenya
RICHARD COE
Affiliation:
World Agroforestry Centre. P.O. Box 30677 – 00100 Nairobi, Kenya
JOSEPH SANG
Affiliation:
Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000–00200 Nairobi, Kenya
*
Corresponding author: [email protected]

Summary

Climate change and land use change are two forces influencing the hydrology of watersheds and their ability to provide ecosystem services, such as clean and well-regulated streamflow and control of soil erosion and sediment yield. The Soil Water Assessment Tool, SWAT, a distributed, watershed-scale hydrological model was used with 18 scenarios of rainfall, temperature and infiltration capacity of land surface to investigate the spatial distribution of watershed services over the 3587 km2 Nyando basin in Western Kenya and how it is affected by these two forces. The total annual water yield varied over the 50 sub-basins from 35 to 600 mm while the annual sediment yield ranged from 0 to 104 tons ha−1. Temperature change had a relatively minor effect on streamflow and sediment yield compared to change in rainfall and land surface condition. Improvements in land surface condition that result in higher infiltration are an effective adaptation strategy to moderate the effects of climate change on supply of watershed services. Spatial heterogeneity in response to climate and land use change is large, and hence it is necessary to understand it if interventions to modify hydrology or adapt to climate change are to be effective.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2011

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References

REFERENCES

Batjes, N. H. and Gicheru, P. (2004). Soil data derived from SOTER studies of carbon stocks and change in Kenya. (GEF-SOC Project; Version 1.0), Technical Report 2004/1. ISRIC – World Soil Information, Wageningen.Google Scholar
Calder, I. (1999). The Blue Revolution: Land Use and Integrated Resource Management. London: Earthscan Publications.Google Scholar
Christensen, J. H., Hewitson, B., Busuioc, A., Chen, A., Gao, X., Held, I., Jones, R., Kolli, R. K., Kwon, W.-T., Laprise, R., Magaña Rueda, V., Mearns, L., Menéndez, C. G., Räisänen, J., Rinke, A., Sarr, A. and Whetton, P. (2007). Regional climate projections. In Climate Change 2007:The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. (Eds Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M. and Miller, H. L.. Cambridge, UK: Cambridge University Press.Google Scholar
Cohen, M. J., Brown, M. T. and Shepherd, K. D. (2006). Estimating the environmental costs of soil erosion at multiple scales in Kenya using emergy synthesis. Agricultural Ecosystems and Environment 114:249269.CrossRefGoogle Scholar
Cooper, P. J. M., Dimes, J., Rao, K. P. C., Shapiro, B., Shiferaw, B. and Twomlow, S. (2008). Coping better with current climatic variability in the rain-fed farming systems of sub-Saharan Africa: An essential first step in adapting to future climate change? Agriculture, Ecosystems and Environment 126:2435.CrossRefGoogle Scholar
Dale, V. H. (1997). The relationship between land-use change and climate change. Ecological Applications 7:753769.CrossRefGoogle Scholar
Easterling, D. R., Meehl, G. A., Parmesan, C., Changnon, S. A. Karl, T. R. and Mearns, L. O. (2000). Climate extremes: Observations, modeling and impacts. Science 289:20682074.CrossRefGoogle ScholarPubMed
Ferraro, P. J. (2009). Regional review of payments for watershed services: Sub-Saharan Africa. Sustainable Forestry 28:140.Google Scholar
FAO (1988). Revised Legend of the FAO-UNESCO Soil Map of the World. ISRIC Report No. 60, Food and Agriculture Organization, Rome, Italy.Google Scholar
FAO (2006). World Reference Base for Soil Resources 2006. World Soil Resources Reports No. 103, Food and Agriculture Organization of the United Nations, Rome, Italy.Google Scholar
Green, W. H. and Ampt, G. A. (1911). Studies on soil physics,1. The flow of air and water through soils. Journal of Agricultural Sciences 4:1124.Google Scholar
Jayakrishnan, R., Srinivasan, R., Santhi, C. and Arnold, J. G. (2005). Advances in the application of the SWAT model for water resources management. Hydrological Processes 19:749762.CrossRefGoogle Scholar
Lal, R. (2003). Soil erosion and the global carbon budget. Environment International 29:437450.Google ScholarPubMed
Ma, X., Xu, J. and van Noordwijk, M. (2010). Sensitivity of streamflow from a Himalayan catchment to plausible changes in land cover and climate. Hydrological Processes, 24, 13791390CrossRefGoogle Scholar
Maidment, D. R. (Ed) (1993). Handbook of Hydrology. New York: McGraw-Hill.Google Scholar
MoWD (Ministry of Water Development) (1992). The Study on the National Water Master Plan. Japan International Cooperation Agency (JICA).Google Scholar
Muthusi, F. M., Gathenya, M., Gadain, H., Kaluli, W. and Lenga, F. K. (2005). Application of the USGS Streamflow Model to the Nyando Basin, Western Kenya. European Journal of Scientific Research 12:919.Google Scholar
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., Srinivasan, R. and Williams, J. R. (2002a). Soil and Water Asssessment Tool, Users Manual Version 2000. Texas Water Resources Institute, College Station, Texas, USA.Google Scholar
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., Williams, J. R. and King, K. W. (2002b). Soil and Water Asssessment Tool, Theoretical Documentation Version 2000. Texas Water Resources Institute, College Station, Texas, USA.Google Scholar
Obled, Ch., Wendling, J. and Beven, K. (1994). The sensitivity of hydrological models to spatial rainfall patterns: an evaluation using observed data. Journal of Hydrology 159:305333.CrossRefGoogle Scholar
Ochola, W. O. and Kerkides, P. (2003). A Markov chain simulation model for predicting critical wet and dry spells in Kenya: analysing rainfall events in the Kano Plains. Irrigation and Drainage 52:327342.CrossRefGoogle Scholar
Payne, R. W. Harding, S. A., Murray, D. A., Soutar, D. M., Baird, D. B., Glaser, A. I., Channing, I. C., Welham, S. J. Gilmour, A. R. Thompson, R. and Webster, R. (2009). GenStat® for WindowsTM 12th Edition Introduction. VSN International, UK.Google Scholar
Ponce, V. M. and Hawkins, R. H. (1996). Runoff curve number: has it reached maturity. Journal of Hydrologic Engineering 1:1119.CrossRefGoogle Scholar
Republic of Kenya (2010). The 2009 Population and Housing Census. Volume 1A Population Distribution and Administrative Units. Kenya National Bureau of Statistics.Google Scholar
Sang, J., Gathenya, M. and Ndegwa, G. (2007). Evaluation of reservoirs as flood mitigation measure in Nyando Basin, Western Kenya Using SWAT. European Journal of Scientific Research 18:231239.Google Scholar
Setegn, S. G., Srinivasan, R. and Dargahi, B. (2008). Hydrological modelling in the Lake Tana Basin, Ethiopia using SWAT model. The Open Hydrology Journal 2:2538.CrossRefGoogle Scholar
Singh, V. P. and Frevert, D. K. (2006). Introduction. In Watershed Models, 319 (Eds Singh, V. P., Frevert, V. P. and D. K.). London: Taylor & Francis.Google Scholar
Southgate, D., Sanders, J. and Ehui, S. (1990). Resource degradation in Africa and Latin America: Population pressure, policies, and property arrangements. American Journal of Agricultural Economics 72:12591263.CrossRefGoogle Scholar
Swallow, B. M., Sang, J. K., Nyabenge, M., Bundotich, D. K., Duraiappah, A. K. and Yatich, T. 2009. Tradeoffs, synergies and traps among ecosystem services in the Lake Victoria basin of East Africa. Environmental Science and Policy 12:504519.CrossRefGoogle Scholar
Tubiello, F., Schmidhuber, J., Howden, M., Neofotis, P. G., Park, S., Fernandes, E. and Thapa, D. (2008). Climate change response strategies for agriculture: Challenges and opportunities for the 21st Century. Agriculture and Rural Development, Discussion Paper 42, The World Bank.Google Scholar
United Nations (2009.) Innovative socio-economic policy for improving environmental performance: Payments for ecosystem services. ESCAP, UN. Available at http://www.greengrowth.org/download/2009/PES_Publication_Draft.pdf [Accessed 17 January 2011].Google Scholar
USDA-SCS (United States Department of Agriculture -Soil Conservation Service) (1993). National Engineering Handbook: Chapter 4 Hydrology. USDA, Washington, D.C.Google Scholar
Van Mullem, J. A. (1989). Runoff and peak discharges using Green-and-Ampt infiltration model. Journal of Hydrologic Engineering, ASCE, 117:354370.Google Scholar
Williams, J. R. 1975. Sediment routing for agricultural watersheds. Water Resources Bulletin 11:965974.CrossRefGoogle Scholar
Wischmeier, W. H. and Smith, D. D. (1978) Predicting rainfall erosion losses – A guide to conservation planning. USDA Agricultural Handbook No. 537. US Govt. Print Office, Washington, USA.Google Scholar
World Agroforestry Centre (2006). Improved Land Management in the Lake Victoria Basin: Final Report on the TransVic project. ICRAF Occasional Paper No. 7. Nairobi. World Agroforestry Centre. Published by the World Agroforestry Centre, Nairobi, Kenya.Google Scholar
Young, A. (1989). Agroforestry for soil conservation. Wallingford, UK: CAB International.Google Scholar