Land use change and soil loss risk assessment by using  geographical information system (GIS) and usle equation in Ipoh state, Malaysia

Tekhikh,  Abdalfettah

Abstract

Soil erosion is among of the most acute issues facing in the world, from the loss of soil to natural resources and crop farmers. The main objectives of this study were to analyze and Land use Changes from year 2000 to 2015 and possible soil erosion rate in the future. All spatial analysis work has been carried out in GIS Environment using ArcGIS version 10.3 all data that use in this study were obtained from Department of Agriculture in Malaysia. The total area was 1227.80 Km2. Results showed that the proportion of agriculture land in the study area increased significantly from 2000 to 2015 (30% to 34.35% of the total study area, The forest area in the study area has been decreased from 45.1% in 2000 to 42.5% in 2015 because exploited and transformed into u urban area, where the urban area was recorded from 14.34% in 2000 to 17.93% in 2015 with values of 183.1 km2 to 216.16 km2 of study area. Using the USLE equation and GIS technology is a useful and effective tool for predicting the long-term erosion potential and assessing the effects of soil erosion in large areas. Finally, the USLE equation used to calculate the annual average soil loss rate (A) in ton/ha/year for the Ipoh Area. In order to predict the annual average soil loss rate, the R, K, LS, C and P factors from the earlier estimations multiplied using the raster calculator function tool for ArcGIS10.3

References

Devatha, P. et al. (2015). Estimation of Soil loss Using USLE Model for Kulhan Watershed, Chattisgarh- A Case Study. International Conference on Water Resources, Coastal, and Ocean Engineering (pp. 1429-1436). Mangalore, India

Fu BJ, Zhao WW, Chen LD, Zhang QJ, Lü YH, Gulinck H, & Poesen J. (2005). Assessment ofsoil erosion at large watershed scale using RUSLE and GIS: a case study in the LoessPlateau of China. Land Degradation Dev. 16:73–85.

Kim, H. (2006). Soil Erosion Modeling using RUSLE and GIS on the IMHA Watershed,South Korea.

Lambin, E. & Strahlers, A. (1994). Change-vector analysis in multitemporal space: A tool to detect and categorize land-cover change processes using high temporal-resolution satellite data. Remote Sensing of Environment , 231-244.

Machiwal, D. &. Katara, P. (2015). Estimation of Soil Erosion and Identification of Critical Areas for Soil Conservation Measures using RS and GIS-based Universal Soil Loss Equation. National Academy of Agricultural Sciences, 213-226.

Ministry of Natural Resources and Environment Malaysia. (2010). Preparation of Design Guides for Erosion and Sediment Control in Malaysia.

Morgan, R. P. (2005). Soil Erosion and Conservation. Oxford: Blackwell Publishing.

Nations, F. a. (2008). The State of Food and Agriculture 2008: Biofuels: Prospects, Risks and Opportunities. Rome: FAO.

Oldeman, L. R. (1990). World Map of the Status of Human-induced Soil Degradation: An explanatory note. . Wageningen, International Soil Reference and Information Centre; Nairobi, United Nations Environment Program, 27.

Pitt, R. (2007). Erosion Mechanisms and the Revised Universal Soil Loss Equation (RUSLE). In R. Pitt, Construction Site Erosion and Sediment Controls, Planning, Design and Performance. Lancaster: DEStech.

Renard, K. G. (1997). Predicting Soil Erosion by Water: A Guide to Conservation Planning with the RUSLE – Agricultural Handbook No. 703. Washington: USDA.

Singer, M. &. (1999). Soils: An introduction. Upper Saddle River, NJ: Prentice Hall.

Sonneveld, B. G. (2003). A nonparametric/parametric analysis of the Universal Soil Loss Equation. Catena, 9-21.

Stott, A. &. (2000). Political Ecology: Science, Myth and Power. Oxford: Oxford University Press.

opek, R. e. (2014). Comment on "High-resolution global maps of 21st-century forest cover change". Science,344(6187), 981.

Devatha, C., Deshpande, V. and Renukaprasad, M. (2015). Estimation of soil loss using USLE model for Kulhan Watershed, Chattisgarh-A case study. Aquatic Procedia 4: 1429-1436.

Elsheikh, R.F.A., Ouerghi, S. and Elhag, A.R. (2015). Soil erosion risk map based on geographic information system and universal soil loss equation (case study: Terengganu, Malaysia). Ind. J. Sci. Res. Technol 3: 38-43.

Ganasri, B. and Ramesh, H. (2016). Assessment of soil erosion by RUSLE model using remote sensing and GIS-A case study of Nethravathi Basin. Geoscience Frontiers 7(6): 953-961.

Gitas, I.Z., Douros, K., Minakou, C., Silleos, G.N. and Karydas, C.G. (2009). Multi-temporal soil erosion risk assessment in N. Chalkidiki using a modified USLE raster model. EARSeL eProceedings 8(1): 40-52.

Jamshidi, R., Dragovich, D. and Webb, A.A. (2012). Native forest C factor determination using satellite imagery in four sub-catchments. Revisiting Experimental Catchment Studies in Forest Hydrology 353: 64-73.

Kouli, M., Soupios, P. and Vallianatos, F. (2009). Soil erosion prediction using the revised universal soil loss equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece. Environmental Geology 57(3): 483-497.

Lu, D., Li, G., Valladares, G.S. and Batistella, M. (2004). Mapping soil erosion risk in Rondonia, Brazilian Amazonia: using RUSLE, remote sensing and GIS. Land degradation & development 15(5): 499-512.

Morgan, R.P.C. (2005). Soil Erosion and Conservation. Oxford, Blackwell Publishing.

Munodawafa, A. (2007). Assessing nutrient losses with soil erosion under different tillage systems and their implications on water quality. Physics and Chemistry of the Earth, Parts A/B/C 32(15-18): 1135-1140.

Prasannakumar, V., Shiny, R., Geetha, N. and Vijith, H. (2011). Spatial prediction of soil erosion risk by remote sensing, GIS and RUSLE approach: a case study of Siruvani river watershed in Attapady valley, Kerala, India. Environmental Earth Sciences 64(4): 965-972.

Wade, C., Bolding, M., Aust, W., Lakel III, W. and Schilling, E. (2012). Comparing sediment trap data with theUSLE-Forest, RUSLE2, and WEPP-Road erosion models for evaluation of bladed skid trail BMPs. Transactions of the ASABE 55(2): 403-414.

Wischmeier, W.H. and Smith, D.D. (1978). Predicting rainfall erosion losses-a guide to conservation planning. Predicting rainfall erosion losses-a guide to conservation planning.

Zhang, H., Yang, Q., Li, R., Liu, Q., Moore, D., He, P., Ritsema, C.J. and Geissen, V. (2013). Extension of a GIS procedure for calculating the RUSLE equation LS factor. Computers & Geosciences 52: 177-188.