Assessment of the effect of land use /land cover changes on total runoff from Ofu River catchment in Nigeria
The total runoff from a catchment is dependednt on both the soil characteristics and the land use/land cover (LULC) type. This study was conducted to examine the effect of changes in land cover on the total runoff from Ofu River Catchment in Nigeria. Classified Landsat imageries of 1987, 2001 and 2016 in combination with the soil map extracted from the Digital Soil Map of the World was used to estimate the runoff curve number for 1987, 2001 and 2016. The runoff depth for 35 years daily rainfall data was estimated using Natura Resource Conservation Services Curve Number (NRCS-CN) method. The runoff depths obtained for the respective years were subjected to a one-way analysis of variance at 95% level of significance. P-value < 0.05 was taken as statistically significant. Runoff curve numbers obtained for 1987, 2001 and 2016 were 61.83, 63.26 and 62.79 respectively. The effects of the changes in LULC for 1987-2001, 2001-2016 and 1987-2016 were statistically significant (P<0.001) at 95% confident interval. The average change in runoff depths were 79.81%, -11.10% and 48.09% respectively for 1987-2001, 2001-2016 and 1987-2016. The study concluded that the changes in LULC of the catchment had significant effect on the runoff from the catchment.
Alfa, M.I. 2017. Flood Risk Assessment of Ofu River Catchment in Nigeria. Ongoing PhD research in the Department of Water Resources and Environmental Engineering, Ahmadu Bello University, Zaria, Nigeria.
Anyamba, A. and Tucker, C.J. 2005. Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981–2003. Journal of Arid Environments 63(3): 596-614.
AR-AR Partnership. 2004. Oforachi Irrigation Project Contract Documents Volume III: Main Report Prepared for Lower Benue River Basin Development Authority, Federal Republic of Nigeria (Unpublished).
Franczyk, J. and Chang, H. 2009. The effects of climate change and urbanization on the runoff of the Rock Creek basin in the Portland metropolitan area, Oregon, USA. Hydrological Processes 23(6): 805-815.
Hernandez, M., Miller, S.N., Goodrich, D.C., Goff, B.F., Kepner, W.G., Edmonds, C.M. and Jones, K.B. 2000. Modeling runoff response to land cover and rainfall spatial variability in semi-arid watersheds. Environmental Monitoring and Assessment 64(1): 285-298.
Li, H., Liu, Q.H. and Zou, J. 2009. Relationships of LST to NDBI and NDVI in Changsha-Zhuzhou-Xiangtan area based on MODIS data. Scientia Geographica Sinica 2: 018.
Library of Congress (n.d). Administrative Map of Nigeria. Available at https://www.loc.gov/item/2010592721/. (Accessed 08/06/2017)
Mausel, P.W., Kramber, W.J. and Lee, J.K. 1990. Optimum band selection for supervised classification of multispectral data. Photogrammetric Engineering and Remote Sensing 56: 55-60.
Mustafa, S. and Yusuf, M.I. 2012. A Textbook of Hydrology and Water Resources, Revised Edition. Abuja. Topsmerit Page Publishing Company.
Nunes, A.N., De Almeida, A.C. and Coelho, C.O. 2011. Impacts of land use and cover type on runoff and soil erosion in a marginal area of Portugal. Applied Geography 31(2): 687-699.
Patra, K.C. 2008. Hydrology and Water Resources Engineering, Second Edition. New Delhi. Narosa Publishing House.
Peng, T. and Wang, S.J. 2012. Effects of land use, land cover and rainfall regimes on the surface runoff and soil loss on karst slopes in southwest China. Catena 90: 53-62.
Pettorelli, N., Vik, J.O., Mysterud, A., Gaillard, J.M., Tucker, C.J. and Stenseth, N.C. 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution 20(9): 503-510.
Rozenstein, O. and Karnieli, A. 2011. Comparison of methods for land-use classification incorporating remote sensing and GIS inputs. Applied Geography 31(2): 533-544.
Saghafian, B., Farazjoo, H., Bozorgy, B. and Yazdandoost, F. 2008. Flood intensification due to changes in land use. Water Resources Management 22(8): 1051-1067.
Solín, Ľ., Feranec, J. and Nováček, J. 2011. Land cover changes in small catchments in Slovakia during 1990–2006 and their effects on frequency of flood events. Natural Hazards 56(1): 195-214.
Su, X., He, C., Feng, Q., Deng, X. and Sun, H. 2011. A supervised classification method based on conditional random fields with multi scale region connection calculus model for SAR image. IEEE Geoscience and Remote Sensing Letters 8(3): 497-501.
Suresh, R. 2008. Land and Water Management Principles. Delhi. Standard Publishers Distributors.
Varshney, A. 2013. Improved NDBI differencing algorithm for built-up regions change detection from remote-sensing data: an automated approach. Remote Sensing Letters 4(5): 504-512.
Zimmermann, B., Elsenbeer, H. and De Moraes, J.M. 2006. The influence of land-use changes on soil hydraulic properties: implications for runoff generation. Forest Ecology and Management 222(1): 29-38.
- There are currently no refbacks.
Copyright (c) 2018 Journal of Degraded and Mining Lands Management
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.