Development of an erosion model for Langat River Basin, Malaysia, adapting GIS and RS in RUSLE

Abstract

This study is aimed to predict potential soil erosion in the Langat River Basin, Malaysia by integrating Remote Sensing (RS) and Geographical Information System (GIS) with the Revised Universal Soil Loss Equation (RUSLE) model. In RUSLE model, parameters such as rainfall erosivity factor (R), soil erodibility factor (K), slope length and steepness factor (LS), vegetation cover and management factor (C) and support practice factor (P) are determined based on the input data followed by the spatial analysis process in the GIS platform. Rainfall data from 2008-2015 are collected from the 29 rain gauge stations located within the study area. From the analysis, the magnitude of RUSLE model obtained corresponding to the parameter R, K, LS, C and P factors is varied between 800 to 3000 MJ mm ha− 1 h− 1 yr− 1, 0.035–0.5 Mg h MJ− 1 mm− 1, 0–73.00, 0.075–0.77 and 0.2–1.00, respectively. Findings of this study indicates that based on the calculated RUSLE parameter values, about 95% of the Langat River Basin area have been classified as a very low to a low erosion vulnerability. Findings of this study would greatly benefits a decision maker in proposing a suitable soil management and conservation practices for the river basin.

Estimation of soil erodibility in Peninsular Malaysia: A case study using multiple linear regression and artificial neural networks

“…The Peninsular Malaysia receives a mean annual rainfall of approximately 2540 mm [ 49 ]. The soil samples were collected from different sites, based on the available soil series information [ 9 , [50] , [51] , [52] ] situated in Peninsular Malaysia, including Tasik Chini (3°26′00” N - 102°55′00” E) in Pahang state, Penang (Pulau Pinang) Island (5°22′02.3” N - 100°14′55” E) in Penang state, Melaka Tengah District (2°15′00” N - 102°15′00” E) in Melaka state, and across Sungai Langat (2°55′56.9” N - 101°46′34.9” E) in Selangor state near Universiti Kebangsaan Malaysia. The study sites are shown in Fig.…”

“…Adopting suitable soil management practices is the best possible way to prevent undesirable impacts of soil erosion on the environment. The prospective risk of soil erosion and its spatial distribution are required to be estimated for effective conservation of soil [ 8 , 9 ]. Various empirical models for soil erosion assessment have been established, among which the Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE) are broadly implemented around the world [ 10 ].…”

Regional Ecological Security Assessment Based on the Pressure–State–Response Framework: The Demonstration Zone of Yangtze River Delta as an Example

“…where TDS refers to the development speed of the DZGIED; B y is the build-up area in year y; B y−1 is the build-up area in year y − 1. (3) Soil Erosion [57,58]. Soil erosion destroys land resources and causes land degradation, loss of soil fertility, siltation, and other problems.…”

Predicting soil erosion potential under CMIP6 climate change scenarios in the Chini Lake Basin, Malaysia

“…Soil erosion is a native geological process; however, after anthropogenic interference may be categorized as a land quality reduction, which has been a repeated issue for long period across the world for authorities, and particularly, in nations, such as Malaysia (Rendana et al 2018 ). Currently, researchers have investigated land deterioration factors in Malaysia, such as deforestation (Jaafar et al 2020 ), soil acidification (Mahmud and Chong 2022 ), soil salinization (Kh’ng et al 2021 ), land-use changes, and biodiversity loss (Wilkinson et al 2018 ), and water erosion (Islam et al 2020 ). Several studies have tried to combine geographic information systems, remote sensing, and the RUSLE method for the mapping of soil erosion (Anees et al 2018 ; Roslee and Sharir 2019 ).…”