Modeling the Impacts of Land Cover Changes on Stream Flow Response in Thiba River Basin in Kenya
Journal of Water Resources and Ocean Science
Volume 6, Issue 1, February 2017, Pages: 1-13
Received: Jan. 10, 2017; Accepted: Jan. 21, 2017; Published: Feb. 10, 2017
Views 3576      Downloads 171
Samuel M. Kasuni, Department of Water and Waste Water Engineering, Kenya Water Institute, Nairobi, Kenya
Johnson U. Kitheka, Department of Hydrology and Water Resources Management, South Eastern Kenya University, Kitui, Kenya
Article Tools
Follow on us
Soil and Water Assessment Tool (SWAT) was used to model the impacts of land cover changes on stream flow regime in the Thiba River basin covering a surface area of 1648 km2 in central region of Kenya. The basin is characterized by intensive agricultural activities including the largest rice irrigation scheme in Kenya. A study was undertaken to test the capability of the model in predicting stream flow response under changing land use conditions in a typical tropical river basin. Classified land use maps of 1984, 2004 and 2014 were analyzed to investigate land use changes in the basin. Field based survey, National Irrigation Board (NIB), Kenya Meteorological Department and Water Resources Management Authority (WRMA) provided hydro-meteorological data for the study. The results of the study shows that forest cover in the Thiba River basin has decreased by 18.39 % between 1984 and 2014 while area under rice cultivation increased by 9.38 % in the same period. The SWAT Model results showed that there is a significant relationship between the observed and simulated average monthly stream flows in the Thiba River Basin. The Nash-Sutcliffe Efficiency (NSE) and coefficient of determination (R2) during calibration period (1983-1988) were 0.82 and 0.9, respectively, while for the validation period (1989-1993) they were 0.79 and 0.87, respectively. The average monthly stream flows increased by 6.01 m3/s during the wet season and decreased by 1.92 m3/s during the dry season. The changes in stream flow were attributed to the land cover change and rainfall variability. About 35% of dry season flow and 3% of wet season flow was found to have been directly abstracted from the Thiba River. The study recommends that the basin stakeholders should optimize utilization of abstracted water to avert future catastrophic stream flow fluctuations, possibly flooding during the wet season and low or dry riverbeds during the dry months. The high water demand in the dry months can be met by constructing water storage reservoirs to harvest the high runoff during the wet months. Also, it's important that further research on impact of climate change be conducted to better understand the relationship between catchment hydrology and climate change.
Arc-SWAT Model, Hydrological Modeling, Land Use and Land Cover Change, Thiba River Basin, Kenya
To cite this article
Samuel M. Kasuni, Johnson U. Kitheka, Modeling the Impacts of Land Cover Changes on Stream Flow Response in Thiba River Basin in Kenya, Journal of Water Resources and Ocean Science. Vol. 6, No. 1, 2017, pp. 1-13. doi: 10.11648/j.wros.20170601.11
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
A. Stipinovich, “Change in Land Cover and Water Abstraction : Modelling Runoff Effects in the Bot River Catchment,” Department of Geography and Environmental Studies. University of Stellenbosch, Msc. Thesis, 2005.
R. DeFries and K. N. Eshleman, “Land-use change and hydrologic processes: a major focus for the future,” Hydrol. Process., vol. 18, pp. 2183–2186, 2004.
K. Price, “Effects of watershed topography, soils, land use, and climate on baseflow hydrology in humid regions: A review,” Prog. Phys. Geogr., vol. 35, no. 4, pp. 465–492, 2011.
J. K. W. Ngaira, “Challenges of water resource management and food production in a changing climate in Kenya,” J. Geogr. Reg. Plan., vol. 2, no. 4, pp. 97–103, 2009.
V. U. Smakhtin, R. L. Shilpakar, and D. A. Hughes, “Hydrology-based assessment of environmental flows : an example from Nepal,” Hydrol. Sci., vol. 51, no. 2, pp. 207–222, 2006.
J. Gikonyo, “River water abstraction monitoring for the Upper Ewaso Ng’iro river basin, Kenya,” in SPPE workshop madagascar, 1997, pp. 20–22.
National Irrigation Board, “Special Assistance for For Project Formulation for Mwea Irrigation Development Project, Kenya,” 2009.
Muchiri M. L, “Climate change impacts on water use strategies in Mwea irrigation Scheme, Kirinyaga County, Kenya. Department of Environmental Education. Kenyatta University, Kenya.,” 2013.
Kirinyaga County, “Republic of Kenya Kirinyaga County First County Intergrated Report,” 2013.
H.. Notter, B., MacMillan, L., Viviroli, D., Weingartner, R., Liniger, “. Impacts of environmental change on water resources in the Mt. Kenya region,” hydrology, vol. 343, no. 12, p. 13, 2007.
J. FAO, IIASA, ISRIC, ISSCAS, “Harmonized World Soil Database (version 1.2).,” FAO, Rome, Italy IIASA, Laxenburg, Austria, 2012.
J. H. Geertsma, R, Wilschut, L. I. Kauffman, “Review for the green water credits pilot operations in Kenya. Green Water Credits Report 8. ISRIC Report 2010/02. Wageningen, the Netherlands: ISRIC-World Soil Information.,” 2010.
M. W. Ndegwa, “International Journal of Advances in Management and Economics An Assessment of the Socio- Economic Status of Rice Farmers in Mwea Irrigation Scheme.,” Manag. J., vol. 3, no. 1, 2014.
P. Maingi, J. Hutting, C. Njoronge, and K. Dijkshoorn, “Soil and terrain conditions for the Upper Tana River catchment, Kenya. Green Water Credits Report 11 / ISRIC Report 2010/09.,” ISRIC – World Soil Information, Wageningen (47p. with data set), 2010.
A. Di Gregorio and J. Latham, “Africover Land Cover Classification and Mapping Project,” L. Use, L. Cover Soil Sci., vol. I, 2000.
Q. Liu, H. and Zhou, “Accuracy analysis of remote sensing change detection by rule based rationality evaluation with post-classification comparison,” IInternational J. Remote Sens., vol. 25, no. 5, pp. 1037–1050, 2004.
B. Vilaysane, K. Takara, P. Luo, and I. Akkharath, “Hydrological stream flow modelling for calibration and uncertainty analysis using SWAT model in the Xedone river basin, Lao PDR,” Procedia Environ. Sci., vol. 28, pp. 380–390, 2015.
J. G. Arnold, D. N. Moriasi, P. W. Gassman, K. C. Abbaspour, M. J. White, R. Srinivasan, C. Santhi, R. D. Harmel, A. Van Griensven, M. W. VanLiew, N. Kannan, and M. K. Jha, “Swat: Model Use, Calibration, and Validation,” Asabe, vol. 55, no. 4, pp. 1491–1508, 2012.
L. R. Ahuja, M. J. Shaffer, J. D. Hanson, and K. W. Rojas, “Root Zone Water Quality Model Sensitivity Analysis using Monte Carlo Simulation,” ASAE, vol. 43, no. 4, pp. 883–895, 2000.
S. Sorooshian and V. K. Gupta, “Model calibration,” in Computer Models of Watershed Hydrology, Water Resources Publications, Highlands Ranch, 1995, pp. 23–68.
M. W. Van Liew, J. G. Arnold, and D. D. Bosch, “Problems and Potential of Auto-calibrating a Hydrologic Model,” ASAE, vol. 48, no. 3, pp. 1025–1040, 2005.
J. G. Arnold, D. N. Moriasi, P. W. Gassman, and M. J. White, “SWAT : Model use, calibration, and validation,”. Biol. Syst. Eng. Pap. Publ. Pap. 406., 2012.
K. Abbaspour, “SWAT-Calibration and uncertainty programs (CUP)-User Manual,” 2015.
J. C. Refsgaard, “Parameterisation, calibration, And validation of distributed hydrological models,” J. Hydrol., vol. 198, no. 1, pp. 69–97, 1997.
F. Githui, W. Gitau, F. Mutua, and W. Bauwens, “Climate change impact on SWAT simulated streamflow in western Kenya.,” Int. J. Clim., vol. 29, pp. 1823–1834, 2009.
M. E. Coffey, S. R. Workman, J. L. Taraba, and A. W. Fogle, “Statistical procedures for evaluating daily and monthly hydrologic model predictions.,” ASAE, vol. 47, no. 1, pp. 59–68, 2004.
P. Krause and D. P. Boyle, “Advances in Geosciences Comparison of different efficiency criteria for hydrological model assessment,” Adv. Geosci., vol. 5, pp. 89–97, 2005.
T. J. Baker and S. N. Miller, “Using the Soil and Water Assessment Tool ( SWAT ) to assess land use impact on water resources in an East African watershed,” J. Hydrol., vol. 486, pp. 100–111, 2013.
C. Santhi, J. G. Arnold, J. R. Williams, W. A. Dugas, R. Srinivasan, and L. M. Hauck, “Validation of the SWAT model on a large river basin with point and nonpoint sources,” J. Am. Water Resour. Assoc., vol. 37, no. 5, pp. 1169–1188, 2001.
K. Tadele and G. Förch, “Impact of land use/cover change on streamflow: the case of Hare River Watershed, Ethiopia,” Symp. (LARS), Arba Minch, Ethiop., pp. 80–85, 2007.
Science Publishing Group
1 Rockefeller Plaza,
10th and 11th Floors,
New York, NY 10020
Tel: (001)347-983-5186