Determination of soil erosion factors using universal soil loss equation and geographic information system in Ipoh City in Perak State, Malaysia

Determination of soil erosion factors using universal soil loss equation and geographic information system in Ipoh City in Perak State, Malaysia

Soil erosion is among of the most acute issues faced in the world, from the loss of soil to natural resources and crop farmers. Malaysia is a tropical country with high yearly rainfall affecting the loss of the outermost layers of soil. The main objectives of this study was to examine the areas mand...

Full description

Saved in:
Bibliographic Details
Main Author: Mohamed Tekhikh Abdalfettah Addukali
Format: thesis
Language:eng
Published: 2020
Subjects:
N/A
Online Access:https://ir.upsi.edu.my/detailsg.php?det=6818
Tags: Add Tag
No Tags, Be the first to tag this record!
id oai:ir.upsi.edu.my:6818
record_format uketd_dc
institution Universiti Pendidikan Sultan Idris
collection UPSI Digital Repository
language eng
topic N/A
spellingShingle N/A
Mohamed Tekhikh Abdalfettah Addukali
Determination of soil erosion factors using universal soil loss equation and geographic information system in Ipoh City in Perak State, Malaysia
description Soil erosion is among of the most acute issues faced in the world, from the loss of soil to natural resources and crop farmers. Malaysia is a tropical country with high yearly rainfall affecting the loss of the outermost layers of soil. The main objectives of this study was to examine the areas mandatory for the evaluation of soil corrosion in Ipoh city and surrounding areas in Perak state, Malaysia for Year 2000 and Year 2015, and to evaluate the mean yearly soil loss proportion using the USLE model. The total area covered in this study was 1267.83 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, respectively). Similarly, urban area also showed increase from 14.34% in 2000 to 17.93% in 2015 with values of 183.1 km2 to 216.16 km2of study area, respectively. Contrary, open area showed significant reduction in size from 118.76 km2 (8.30% of the study area) in 2000 to 48.80 km2 (3.82% of the study area) in 2015. Forest area also decreased from 45.1% in 2000 to 42.5% in 2015. These reductions resulted to an overall decrease in total areas with very low probability of soil erosion from 90.96% in 2000 to 76.42% in 2015. On the other side of the spectrum, the areas with very high probability of soil erosion increased from 36.78 km2 of the study area in 2000 to 94.85 km2 in 2015, showing 4.58% increase. In conclusion, decrease in forest and open areas significantly contributed to increase in agriculture and urban areas with higher soil erosion probability. Urban planners and land developers exploited the potential land at maximum rate by building residential, commercial and industrial areas. Even though the soil erosion rate in the study area was found not to be at a pressing stage, it can increase in the future if the development activities are done without conservation planning program in the Ipoh city and surrounding areas in Perak state.
format thesis
qualification_name
qualification_level Master's degree
author Mohamed Tekhikh Abdalfettah Addukali
author_facet Mohamed Tekhikh Abdalfettah Addukali
author_sort Mohamed Tekhikh Abdalfettah Addukali
title Determination of soil erosion factors using universal soil loss equation and geographic information system in Ipoh City in Perak State, Malaysia
title_short Determination of soil erosion factors using universal soil loss equation and geographic information system in Ipoh City in Perak State, Malaysia
title_full Determination of soil erosion factors using universal soil loss equation and geographic information system in Ipoh City in Perak State, Malaysia
title_fullStr Determination of soil erosion factors using universal soil loss equation and geographic information system in Ipoh City in Perak State, Malaysia
title_full_unstemmed Determination of soil erosion factors using universal soil loss equation and geographic information system in Ipoh City in Perak State, Malaysia
title_sort determination of soil erosion factors using universal soil loss equation and geographic information system in ipoh city in perak state, malaysia
granting_institution Universiti Pendidikan Sultan Idris
granting_department Fakulti Teknikal dan Vokasional
publishDate 2020
url https://ir.upsi.edu.my/detailsg.php?det=6818
_version_ 1747833316156899328
spelling oai:ir.upsi.edu.my:68182022-02-24 Determination of soil erosion factors using universal soil loss equation and geographic information system in Ipoh City in Perak State, Malaysia 2020 Mohamed Tekhikh Abdalfettah Addukali N/A Soil erosion is among of the most acute issues faced in the world, from the loss of soil to natural resources and crop farmers. Malaysia is a tropical country with high yearly rainfall affecting the loss of the outermost layers of soil. The main objectives of this study was to examine the areas mandatory for the evaluation of soil corrosion in Ipoh city and surrounding areas in Perak state, Malaysia for Year 2000 and Year 2015, and to evaluate the mean yearly soil loss proportion using the USLE model. The total area covered in this study was 1267.83 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, respectively). Similarly, urban area also showed increase from 14.34% in 2000 to 17.93% in 2015 with values of 183.1 km2 to 216.16 km2of study area, respectively. Contrary, open area showed significant reduction in size from 118.76 km2 (8.30% of the study area) in 2000 to 48.80 km2 (3.82% of the study area) in 2015. Forest area also decreased from 45.1% in 2000 to 42.5% in 2015. These reductions resulted to an overall decrease in total areas with very low probability of soil erosion from 90.96% in 2000 to 76.42% in 2015. On the other side of the spectrum, the areas with very high probability of soil erosion increased from 36.78 km2 of the study area in 2000 to 94.85 km2 in 2015, showing 4.58% increase. In conclusion, decrease in forest and open areas significantly contributed to increase in agriculture and urban areas with higher soil erosion probability. Urban planners and land developers exploited the potential land at maximum rate by building residential, commercial and industrial areas. Even though the soil erosion rate in the study area was found not to be at a pressing stage, it can increase in the future if the development activities are done without conservation planning program in the Ipoh city and surrounding areas in Perak state. 2020 thesis https://ir.upsi.edu.my/detailsg.php?det=6818 https://ir.upsi.edu.my/detailsg.php?det=6818 text eng closedAccess Masters Universiti Pendidikan Sultan Idris Fakulti Teknikal dan Vokasional Angulo-Martnez, M., & Beguera, S. (2009). Estimating rainfall erosivity from daily precipitation records: A comparison among methods using data from the Ebro Basin (NE Spain). Journal of Hydrology, 379(1-2), 111-121.Arnoldus, H. M. J. (1980). An approximation of the rainfall factor in the Universal Soil Loss Equation (pp. 127-132). Chichester: John Wiley and Sons Ltd.Aronica, G., & Ferro, V. (1997). Rainfall erosivity over the Calabrian region. Hydrological sciences journal, 42(1), 35-48.Ashiagbor, G., Forkuo, E. K., Laari, P., & Aabeyir, R. (2013). Modeling soil erosion using RUSLE and GIS tools. International Journal of Remote Sensing & Geoscience, 2(4), 1-17.Baban, S. M., & Wan Yusof, K. (2010). Mapping land use/cover distribution on a mountainous tropical island using remote sensing and GIS. International Journal of Remote Sensing, 22(10), 1909-1918.Bahadur, K. K. (2009). Mapping soil erosion susceptibility using remote sensing and GIS: a case of the Upper Nam Wa Watershed, Nan Province, Thailand. Environmental geology, 57(3), 695-705.Balamurugan, G. (1991). Sediment balance and delivery in a humid tropical urban river basin: the Kelang River, Malaysia. Catena, 18(3-4), 271- 287.Belasri, A., & Lakhouili, A. (2016). Estimation of soil erosion risk using the Universal Soil Loss Equation (USLE) and geo-information technology in Oued El Makhazine watershed, Morocco. Journal of Geographic Information System, 8(01), 98.Bera, A. (2017). Assessment of soil loss by universal soil loss equation (USLE) model using GIS techniques: a case study of Gumti River Basin, Tripura, India. Modeling Earth Systems and Environment, 3(1), 29.Beuchle, R., Grecchi, R. C., Shimabukuro, Y. E., Seliger, R., Eva, H. D., Sano, E., & Achard, F. (2015). Land cover changes in the Brazilian Cerrado and Caatinga biomes from 1990 to 2010 based on a systematic remote sensing sampling approach. Applied Geography, 58, 116-127.Bhattarai, R., & Dutta, D. (2007). Estimation of soil erosion and sediment yield using GIS at catchment scale. Water Resources Management, 21(10), 1635-1647.Blaszczynski, J. (2001). Regional Sheet and Rill Soil Erosion Prediction with the Revised Universal Soil Loss Equation (RUSLE)-GIS Interface. Resource Notes, 46.Bui, D. T., Pradhan, B., Lofman, O., Revhaug, I., & Dick, . B. (2013). Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province, Vietnam. Natural hazards, 66(2), 707-730.Cooper, K. (2011). Evaluation of the relationship between the RUSLE R- Factor and mean annual precipitation. Colo. State, 1, 37.Cressie, N. (1990). The origins of kriging. Mathematical geology, 22(3), 239- 252.Dabral, P., Baithuri, N., & Pandey, A. (2008). Soil erosion assessment in a hilly catchment of North Eastern India using USLE, GIS and remote sensing. Water Resources Management, 22(12), 1783-1798.Dai, F., & Lee, C. (2001). Frequencyvolume relation and prediction of rainfall-induced landslides. Engineering geology, 59(3-4), 253-266.Debella-Gilo, M., & Etzelmller, B. (2009). Spatial prediction of soil classes using digital terrain analysis and multinomial logistic regression modeling integrated in GIS: Examples from Vestfold County, Norway. Catena, 77(1), 8-18.Demirci, A., & Karaburun, A. (2012). Estimation of soil erosion using RUSLE in a GIS framework: a case study in the Buyukcekmece Lake watershed, northwest Turkey. Environmental Earth Sciences, 66(3), 903-913.Devatha, C., Deshpande, V., & 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., & 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.Erdogan, E. H., Erpul, G., & Bayramin, ?. (2007). Use of USLE/GIS methodology for predicting soil loss in a semiarid agricultural watershed. Environmental monitoring and assessment, 131(1-3), 153- 161.Fao, F. (2008). Agriculture Organization of the United Nations (2009). The state of agricultural commodity markets: High food prices and the food crisisexperiences and lessons learned.Flanagan, F. J. (1969). US Geological Survey standardsII. First compilation of data for the new USGS rocks. Geochimica et Cosmochimica Acta, 33(1), 81-120.Genson, I. C. (2006). Erosion and water resources assessment in the Upper Inabanga Watershed, Philippines: application of WEPP and GIS tools.Giri, C., Ochieng, E., Tieszen, L. L., Zhu, Z., Singh, A., Loveland, T., . . . Duke, N. (2011). Status and distribution of mangrove forests of the world using earth observation satellite data. Global Ecology and Biogeography, 20(1), 154-159.Gregersen, B., Aalbk, J., Lauridsen, P., Kaas, M., Lopdrup, U., Veihe, A., & van der Keur, P. (2003). Land use and soil erosion in Tikolod, Sabah, Malaysia. ASEAN Review of Biodiversity and Environmental conservation (ARBEC), Jan-Mac.Gregory, P. J. (2006). Roots, rhizosphere and soil: the route to a better understanding of soil science? European journal of soil science, 57(1), 2-12.Hacisalihoglu, S. (2007). Determination of soil erosion in a steep hill slope with different land-use types: a case study in Mertesdorf (Ruwertal/Germany). Journal of Environmental Biology, 28(2), 433.Hassan, Z., & Harun, S. (2018). Hydrological Response of a Catchment to Climate Change in the Kurau River Basin, Perak, Malaysia.Haynes, R. J., & Naidu, R. (1998). Influence of lime, fertilizer and manure applications on soil organic matter content and soil physical conditions: a review. Nutrient cycling in agroecosystems, 51(2), 123- 137.Huggett, R. J., & Cheesman, J. (2002). Topography and the Environment: Pearson Education.Ismail, I., Harun, S. N., & Zin, M. (2006). A perception survey of domestic tourists towards historical buildings in Ipoh town, Malaysia.Itami, R. M., & Raulings, R. J. (1993). SAGE Introductory Guidebook: Digital Land Systems Research.Ito, A. (2007). Simulated impacts of climate and land?cover change on soil erosion and implication for the carbon cycle, 1901 to 2100. Geophysical research letters, 34(9).Julien, P., Ghani, A. A., Zakaria, N., Abdullah, R., & Chang, C. (2009). Case study: flood mitigation of the Muda river, Malaysia. Journal of Hydraulic Engineering, 136(4), 251-261.Khan, S., Chaudhary, R., Singh, A., Nath, D., & Yadav, S. S. (2018). Soil erosion assessment of non-river catchment in Madhya Pradesh using universal soil loss equation with remote sensing and GIS tools. IJCS, 6(2), 2165-2173.Khosrokhani, M., & Pradhan, B. (2014). Spatio-temporal assessment of soil erosion at Kuala Lumpur metropolitan city using remote sensing data and GIS. Geomatics, Natural Hazards and Risk, 5(3), 252-270.Khudair, B. H., & Sadeq, N. S. (2018). Determining and Predicting the Water Demand Dynamic System Model Mapping Urban Crawling and Monitoring Using Remote Sensing Techniques and GIS. Journal of Engineering, 24(6), 103-113.Kouli, M., Soupios, P., & 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.Laflen, J., & Moldenhauer, W. (2003). The USLE story. Special Publication, WASWC.Lambin, E. F., & Strahlers, A. H. (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, 48(2), 231-244.Lian, C. W., Seng, C. M., & Chai, W. Y. (2006). Spatial, environmental and entomological risk factor analysis on a rural dengue outbreak in Lundu District in Sarawak, Malaysia. Trop Biomed, 23(1), 85-96.Lim, K. J., Sagong, M., Engel, B. A., Tang, Z., Choi, J., & Kim, K.-S. (2005). GIS-based sediment assessment tool. Catena, 64(1), 61-80.Liu, B., Nearing, M. A., & Risse, L. M. (1994). Slope gradient effects on soil loss for steep slopes. Transactions of the ASAE, 37(6), 1835-1840.Lu, D., Li, G., Valladares, G. S., & Batistella, M. (2004). Mapping soil erosion risk in Rondonia, Brazilian Amazonia: using RUSLE, remote sensing and GIS. Land degradation & development, 15(5), 499-512.Machiwal, D., Katara, P., & Mittal, H. (2015). Estimation of soil erosion and identification of critical areas for soil conservation measures using RS and GIS-based universal soil loss equation. Agricultural Research, 4(2), 183-195.Malczewski, J. (2006). GIS?based multicriteria decision analysis: a survey of the literature. International journal of geographical information science, 20(7), 703-726.Mir, S. I., Gasim, M. B., Rahim, S. A., & Toriman, M. E. (2010). Soil loss assessment in the Tasik Chini catchment, Pahang, Malaysia.Mongkolsawat, C., Thirangoon, P., & Sriwongsa, S. (1994). Soil erosion mapping with universal soil loss equation and GIS. Paper presented at the 15th Asian Conference on Remote Sensing, Bangalore, India.Moore, I. D., & Burch, G. J. (1986). Physical Basis of the Length-slope Factor in the Universal Soil Loss Equation 1. Soil Science Society of America Journal, 50(5), 1294-1298.Moore, I. D., & Wilson, J. P. (1992). Length-slope factors for the Revised Universal Soil Loss Equation: Simplified method of estimation. Journal of Soil and Water Conservation, 47(5), 423-428.Morgan, R. P. C. (2009). Soil erosion and conservation: John Wiley & Sons.O'Callaghan, J. F., & Mark, D. M. (1984). The extraction of drainage networks from digital elevation data. Computer vision, graphics, and image processing, 28(3), 323-344.Oldeman, L., Hakkeling, R., & Sombroek, W. (1990). World map of the status of human-induced soil degradation (GLASOD). Nairobi: United Nations Environment Program and International Soil Reference and Information Centre (UNEP/ISRIC).Onori, F., De Bonis, P., & Grauso, S. (2006). Soil erosion prediction at the basin scale using the revised universal soil loss equation (RUSLE) in a catchment of Sicily (southern Italy). Environmental geology, 50(8), 1129-1140.Parveen, R., & Kumar, U. (2012). Integrated approach of universal soil loss equation (USLE) and geographical information system (GIS) for soil loss risk assessment in Upper South Koel Basin, Jharkhand. Journal of Geographic Information System, 4(06), 588.Pimentel, D. (2006). Soil erosion: a food and environmental threat. Environment, development and sustainability, 8(1), 119-137.Pimentel, D., & Skidmore, E. L. (1999). Rates of soil erosion. Science, 286(5444), 1477-1477.Pirasteh, S., Pradhan, B., Safari, H. O., & Ramli, M. F. (2013). Coupling of DEM and remote-sensing-based approaches for semi-automated detection of regional geostructural features in Zagros mountain, Iran. Arabian Journal of Geosciences, 6(1), 91-99.Pitt, R., Clark, S. E., & Lake, D. W. (2007). Construction site erosion and sediment controls: Planning, design and performance: DEStech Publications, Inc.Pradhan, B., Chaudhari, A., Adinarayana, J., & Buchroithner, M. F. (2012). Soil erosion assessment and its correlation with landslide events using remote sensing data and GIS: a case study at Penang Island, Malaysia. Environmental monitoring and assessment, 184(2), 715.Pradhan, B., Lee, S., & Buchroithner, M. F. (2010). A GIS-based back- propagation neural network model and its cross-application and validation for landslide susceptibility analyses. Computers, Environment and Urban Systems, 34(3), 216-235.Pradhan, B., Sezer, E. A., Gokceoglu, C., & Buchroithner, M. F. (2010). Landslide susceptibility mapping by neuro-fuzzy approach in a landslide-prone area (Cameron Highlands, Malaysia). IEEE Transactions on Geoscience and Remote Sensing, 48(12), 4164-4177.Pradhan, B., & Youssef, A. M. (2010). Manifestation of remote sensing data and GIS on landslide hazard analysis using spatial-based statistical models. Arabian Journal of Geosciences, 3(3), 319-326.Prasannakumar, V., Shiny, R., Geetha, N., & 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.Prasannakumar, V., Vijith, H., Abinod, S., & Geetha, N. (2012). Estimation of soil erosion risk within a small mountainous sub-watershed in Kerala, India, using Revised Universal Soil Loss Equation (RUSLE) and geo- information technology. Geoscience Frontiers, 3(2), 209-215.Reich, P., Eswaran, H., & Beinroth, F. (1999). Global dimensions of vulnerability to wind and water erosion. Paper presented at the Sustaining the global farm".(Eds.): Stott, DE, Mohtar, R. H. and Steinhardt, GC, Selected Papers from the 10th International Soil Conservation Organization Meeting, Purdue University and USDA- ARS National Soil Erosion Research Laboratory.Renard, f. (1997). Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE) (Vol. 703). the University of Virginia: U.S. Department of Agriculture, Agricultural Research Service.Renard, K., & Foster, G. (1997). Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE) (Vol. 703). the University of Virginia: U.S. Department of Agriculture, Agricultural Research Service.Renard, K., Foster, G., & Weesies, G. (1997). Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). Agriculture handbook ((703).Rizeei, H. M., Pradhan, B., Saharkhiz, M. A., & Ahmad, N. (2016). Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models. Geocarto international.Rizeei, H. M., Saharkhiz, M. A., Pradhan, B., & Ahmad, N. (2016). Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models. Geocarto International, 31(10), 1158-1177.Rogerson, P. A., & Fotheringham, A. S. (1994). GIS and spatial analysis: introduction and overview. Spatial analysis and GIS, 1-10.Rojas-Gonzlez, A. M. (2008). Soil erosion calculation using remote sensing and GIS in RO grande de Arecibo Watershed, Puerto Rico. Paper presented at the Proceedings ASPRS 2008 Annual Conference Bridging the Horizons: New Frontiers in Geospatial Collaboration, Portland, Oregon, April 28thMay 2nd.Said, N. (2008). Determination of soil erosion parameters for Malaysian conditions using remote sensing and Geographic Information System approach. Universiti Teknologi Malaysia.Shahid, S. A., Abdelfattah, M. A., Omar, S. A., Harahsheh, H., Othman, Y., & Mahmoudi, H. (2010). Mapping and Monitoring of Soil Salinization Remote Sensing, GIS, Modeling, Electromagnetic Induction and Conventional MethodsCase Studies. Paper presented at the Proceedings of the International Conference on Soils and Groundwater Salinization in Arid Countries.Sharma, K., Menenti, M., Huygen, J., & Fernandez, P. (1996). Distributed numerical rainfallrunoff modelling in an arid region using thematic mapper data and a geographical information system. Hydrological Processes, 10(9), 1229-1242.Sheikh, A. H., Palria, S., & Alam, A. (2011). Integration of GIS and universal soil loss equation (USLE) for soil loss estimation in a Himalayan watershed. Recent Research in Science and Technology, 3(3).Suzuki, S., & Nakagoshi, N. (2008). Expansion of bamboo forests caused by reduced bamboo-shoot harvest under different natural and artificial conditions. Ecological Research, 23(4), 641-647.Teh, S. H. (2011a). Soil erosion modeling using RUSLE and GIS on Cameron highlands, Malaysia for hydropower development. Journal of Ecological Engineering.Teh, S. H. (2011b). Soil erosion modeling using RUSLE and GIS on Cameron highlands, Malaysia for hydropower development.Teh, S. H. (2011c). Soil erosion modeling using RUSLE and GIS on Cameron highlands, Malaysia for hydropower development.Tim, U. S., Jain, D., & Liao, H. H. (1996). Interactive Modeling of Ground?Water Vulnerability Within a Geographic Information System Environment a. Groundwater, 34(4), 618-627.Yusof, F. M., Jamil, N. R., Aini, N., & Manaf, L. A. (2016). Land use change and soil loss risk assessment by using geographical information system (GIS): A case study of lower part of Perak River. Paper presented at the IOP Conference Series: Earth and Environmental Science. Akgun, A. (2012). A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at ?zmir, Turkey. Landslides, 9(1), 93-106.Webb, T. J., Woodward, F. I., Hannah, L., & Gaston, K. J. (2005). Forest coverrainfall relationships in a biodiversity hotspot: the Atlantic forest of Brazil. Ecological Applications, 15(6), 1968-1983.Willis, E. O. (1974). Populations and local extinctions of birds on Barro Colorado Island, Panama. Ecological Monographs, 44(2), 153-169.Wischmeier, W. H., & Smith, D. D. (1965). Predicting rainfall-erosion losses from cropland east of the Rocky Mountains: Guide for selection of practices for soil and water conservation (Vol. 282): Agricultural Research Service, US Department of Agriculture Washington DC.Wischmeier, W. H., & Smith, D. D. (1978). Predicting rainfall erosion losses- a guide to conservation planning. Predicting rainfall erosion losses-a guide to conservation planning.Zhou, T., Zhang, L., & Li, H. (2008). Changes in global land monsoon area and total rainfall accumulation over the last half century. Geophysical research letters, 35(16).

Similar Items