Classification of Catchment Risk Areas Using Spatially Distributed Event-based Soil Erosion: A Case of Upper Njoro River Catchment, Kenya

Classification of Catchment Risk Areas Using Spatially Distributed Event-based Soil Erosion: A Case of Upper Njoro River Catchment, Kenya

R.M. Wambua B.M. Mutua D.M. Nyaanga P.M. Kundu 

Department of Agricultural Engineering, Egerton University, Egerton, Kenya

Page: 
281-296
|
DOI: 
https://doi.org/10.2495/D&NE-V3-N4-281-296
Received: 
N/A
|
Accepted: 
N/A
|
Published: 
31 December 2008
| Citation

OPEN ACCESS

Abstract: 

Human-induced soil erosion and drastic change in land use practices have adversely influenced the land degradation and surface runoff response in upper Njoro River catchment. The drainage area is approximately 127 km2. Due to human activities, the land has been exposed to accelerated erosion and low land productivity, water scarcity, decline in ground water recharge, siltation of Lake Nakuru and other sediment sinks. This study was conducted to establish event-based risk areas for prioritized conservation within the catchment. Spatially distributed soil erosion map was created as a ratio of sediment yield to sediment delivery ratio (SDR). Modified Universal Soil Loss Equation (MUSLE) integrated within a Geographical Information Systems environment was used to create the sediment yield map. Spatial data layers for the MUSLE were derived from a 20-m resolution Digital Elevation Model, soil property, land use maps and climatic data of the catchment. Land use map was derived from Landsat imagery via its processing using Integrated Land and Water Information Systems software. The results show that the spatially distributed soil erosion ranged from 0.06 to 0.51 t/ha for a 43.2-mm rainfall event. Spatially distributed SDR ranged from 0.09 to 0.82, while the average SDR for the whole catchment was 0.72. These values were derived using an empirical equation. A new contribution was made by developing spatially distributed slope length factor, SDR, runoff volumes, MUSLE parameters and classified erosion risk areas for prioritized catchment conservation. This means that the event-based soil erosion classifi cation can be adopted for prioritized soil and water conservation within Njoro catchment.

Keywords: 

accelerated erosion, GIS, MUSLE, Njoro, prioritized conservation, water scarcity

  References

[1] UNEP, Deserts and Desertifi cation World Environment Conference, Algiers, 3–5 June 2006.

[2] White, B. & Goh, E.K.H., Systematic reliability-based environmental design of the effi cient engineered landscape profi ling. J. Envr. Engineering, 129(7), pp. 620–628, 2003.

[3] Palmer, M., Bockstael, J., Morgan, G., Wiegand, C., Ness, K.V. & Pissurto, J., Spatial patterning of land use conversion. Journal of Hydrologic Engineering, 7(1), pp. 27–34, 2005.

[4] Kandrika, S. & Venkataratnam, L., A spatially distributed event based model to predict sediment yield. J. Spatial Hydrology, Spring, 5(1), 2005.

[5] Lim, J.K., Sagong, M., Engel, B.A., Tang, Z., Choi, J. & Kim, K., GIS based sediment assessment tool. J. CATENA, 64, pp. 61–80, 2005.

[6] Das, G., Hydrology and Soil Conservation Engineering, Prentice-Hall: New Delhi, 2002.

[7] Morgan, R.P.C., Soil Erosion and Conservation, John Wiley & Sons, Inc.: New York, 1986.

[8] Morgan, R.P.C., Rickson, R.J., McIntyre, K., Brewer, T.R & Altshul, H.J., Soil erosion of the central part of Swaziland Middleveld. Journal of Soil Technology, 11, pp. 263–289, 1997.

[9] Ongweny, G.S. Kiithia, S.M. & Denga, F.O., An Overview of Soil Erosion and Sedimentation Problems in Kenya, eds R.F, Hadly & T. Mizuyama, No. 217 Yokohama, Japan, 1993.

[10] FAO, Guidelines for mapping and measurements of rainfall induced erosion processes, 2005. http://www.fao.org/docrep/X5302e09.htm, accessed on 15 September 2006.

[11] Liu, Q.Q., Chen, L., Li, J.C. & Singh, V.P., Roll waves in overland fl ow. Journal of Hydrologic engineering, 10(2), pp. 110–117, 2005.

[12] Raude, J.M., Determination of Soil Loss and Surface Runoff Under Varying Rainfall Intensity in Different Land Use Practices in the River Njoro Catchment, MSc Thesis, Department of Agricultural Engineering, Egerton University, 2006.

[13] Schwab, G.O., Fangmeier, D.D., Elliot, W.J. & Frevert, R.K., Soil and Water Conservation Engineering, 4th edn, John Willey and Sons Inc.: New York, 1993.

[14] Shaw, E.M., Hydrology in Practice, 3rd edn, Chapman & Hall Co.: London, 1994.

[15] Baldyga, T.J., Assessing Land Cover change Impacts in Kenya’s River Njoro Watershed Using Remote Sensing and Hydrologic Modeling, MSc Thesis, University of Wyoming, 2005.

[16] Gichaba, M., Chivonga, W., Baldyga, T.J. & Miller, S.N., Assessing the impact of land cover change in Kenya using remote sensing and hydrological modelling. ASPRS Annual Conference Proceedings, Denver:, Colorado, 2004.

[17] Otieno, H., Estimation of Direct Runoff and Sediment Yield in the Upper Njoro River Catchment in Kenya, MSc Thesis, Department of Agricultural Engineering, Egerton University, 2006.

[18] Biamah, E.K., Sharma, T.C. & Stroosnider, L., Simulation of watershed peak runoff rate using the Nash model. Journal of Engineering in Agriculture and Environment, 2, pp. 49–56, 2002.

[19] Li, K.Y., Coe, M.T., Ramankutty, N & De Jong, R., Modeling hydrological impact of land use change in West Africa. Journal of Hydrology, No. 337, pp. 258–268, 2007.

[20] Wambua, S.M., Efforts at integrated water resource management, Network for Water and Sanitation (NETWAS), 2002. http://www.netwas.org/newsletter/articles/2002/05/01, accessed on 1 September 2006.

[21] Barkhordari, J., Accessing the Effect of Land Use Changes on the Hydrologic Regime by RS and GIS, PhD Thesis, Netherlands, 2003.

[22] Mitasova, H., Hofi eRka J., Zlocha, M. & Hverson, L.R., Modeling topographic potential for erosion and deposition using GIS. Journal of GIS, 10(5), pp. 629–641, 1996.

[23] Castillo, V.M., Plaza, G.A. & Mena M.M., The role of antecedent soil water content in the runoff response of semi-arid catchments. Journal of Hydrology, 284(1/4), pp. 114–130, 2003.

[24] Nurmohamed, R., Naipal, S. & De Smedi, F., Hydrological modeling of the upper Suriname River basin using Wetspa and ArcView GIS. Journal of Spatial Hydrology, 1(1), pp. 67–88, 2006.

[25] Singh, V.P. & Fiorentino, M. (eds), Geographical Information Systems in Hydrology, Springer-Verlag: London, 1996.

[26] Mainuri, Z.G., Land Use Effects on Spatial Distribution of Soil Aggregate Stability within the River Njoro Watershed, Kenya, MSc Thesis, Department of Geography, Egerton University, 2005.

[27] Nash, J. & Sutcliffe, J., River rate forecasting through conceptual models. J. Hydrology, 10, pp. 282–290, 1970.

[28] Jetten, V.G., LISEM: a physically-based runoff and erosion model, 2005. http://www.geog.uu.nl/lisem.html, accessed on 11 august 2006.

[29] Williams, J.R., Sediment graph model based on an instantaneous sediment graph. Journal of Water Resources Research, 14(4), pp. 659–664, 1978.

[30] Haan C.T., Barfi eld, B.J. & Hayes, J.C., Design Hydrology and Sedimentology for Small Catchments, Academic Press: California, USA, 1978.

[31] Williams J.R., Sediment delivery ratios determined with sediment and runoff models, proceedings of symposium on erosion in inland water. Hydrological Sci., No. 122, pp 168–179, 1977.

[32] Chow, V.T., Maidment, D.R. & Mays, L.W., Applied Hydrology, McGraw-Hill: New York, 1988. 

[33] Wiliiams, R.R., Nicks, A.D. & Arnorl, J.G., Simulator of water resources in rural basins. Journal of Hydraulic Engineering, 11(6), pp. 82–92, 1988.