Integrated Land Use Change Analysis For Soil Erosion Study In Ulu Kinta Catchment

• Main Author: Bawahidi, Khaled Saleh Yaslam
• Format: Thesis
• Language: English
• Published: 2006
• Subjects: TA1-2040 Engineering (General). Civil engineering (General)
• Online Access: http://eprints.usm.my/55452/1/00001651734.pdf; http://eprints.usm.my/55452/

Ulu Kinta catchment has experienced rapid changes in land use and land cover from 1991 to 2004. These changes have resulted in increased upland erosion and higher concentrations of suspended sediment within the catchment. The goal of this research was to investigate the application of integrated satellite remote sensing and Geographic Information Systems (GIS) techniques to assess land cover changes and the estimation of soil erosion in the water catchment. Inherent in this research was the interpretation of multi-sensor data collected by several satellite systems, evaluation of the quality of the resulting change information, application of remotely sensing and other ancillary data as input in GIS-based RUSLE model to analyse soil erosion process induced by different land cover changes. Change detection was performed using post-classification comparison method which produced acceptable results, overall accuracy 61.4 % and kappa = 56 %. The study revealed that while the estimated mean annual soil loss rate was approximately 16.2 tons/ha/yr and 52 tons/ha/yr for 1991 and 2004 respectively, soil loss rate as high as 172.0 tons/hr/yr were found on sloping lands from Ulu Kinta catchment. A good correlation of r' = 0.9169 was obtained between modeled annual average soil loss estimation and annual average sediment loads obtained at site. Results of the study indicate that land use changes in the study area have produced environmental problems such as water pollution and soil erosion. In this research, a comprehensive methodology was developed to collect representative data quickly and simply, showing that in a GIS environment the RUSLE model can be applied to determine field-scale soil loss quantitatively and spatially, to predict erosion hazard over given watershed. The study indicates that the RUSLE-GIS model is useful tool for resource management and soil conservation planning.