Integration of remote sensing, RUSLE and GIS to model potential soil loss and sediment yield (SY)

Abstract

Land use activities within a basin serve as one of the contributing factors which cause deterioration of river water quality through its potential effect on erosion. Sediment yield in the form of suspended solid in the river water body which is transported to the coastal area occurs as a sign of lowering of the water quality. Hence, the aim of this study was to determine potential soil loss using the Revised Universal Soil Loss Equation (RUSLE) model and the sediment yield, in the Geographical Information Systems (GIS) environment within selected sub-catchments of Pahang River Basin. RUSLE was used to estimate potential soil losses and sediment yield by utilizing information on rainfall erosivity (<i>R</i>) using interpolation of rainfall data, soil erodibility (<i>K</i>) using field measurement and soil map, vegetation cover (<i>C</i>) using satellite images, topography (LS) using DEM and conservation practices (<i>P</i>) using satellite images. The results indicated that the rate of potential soil loss in these sub-catchments ranged from very low to extremely high. The area covered by very low to low potential soil loss was about 99%, whereas moderate to extremely high soil loss potential covered only about 1% of the study area. Sediment yield represented only 1% of the potential soil loss. The sediment yield (SY) value in Pahang River turned out to be higher closer to the river mouth because of the topographic character, climate, vegetation type and density, and land use within the drainage basin

Erosion risk assessment for prioritization of conservation measures in Geleda watershed, Blue Nile basin, Ethiopia

“…4) factors were used to calculate and map the LS-factor (Fig. 5d) as has been applied by other studies such as Bewket and Teferi (2009) and Kamaludin et al (2013). The slope length and steepness values were drawn from the ASTER GDEM (30 m resolution) using the ArcGIS Spatial analyst tool and the Arc Hydro tool.…”

Pemodelan Spasial Erosi Kualitatif Berbasis Raster Studi Kasus di DAS Serang, Kabupaten Kulonprogo

“…Vrieling, Sterk dan Vigiak (2006) dalam penelitiannya hanya menggunakan faktor vegetasi dan lereng dalam prediksi erosi dan menghasilkan akurasi 80%. Padahal dalam beberapa penelitian selain kedua faktor tersebut, faktor erodibilitas tanah juga memberikan pengaruh terhadap terjadinya erosi (Farhan, Zregat dan Farhan, 2013;Kamaludin et al, 2013) Pendekatan yang digunakan dalam penelitian ini adalah pendekatan kualitatif dimana keluaran model (output) tidak menampilkan informasi besaran prediksi erosi secara kuantitatif tetapi tingkatan secara kualitatif karena besaran nilai secara numerik suatu variabel pada dasarnya adalah nilai yang bisa berubah pada periode tertentu sedangkan pada kualitatif cenderung lebih konstan dan tidak berubah (Bredeweg et al, 2009). Model erosi kuantitatif dapat diandalkan untuk melihat perubahan dinamis dari karakteristik produktivitas lahan, namun memiliki dasar empiris yang lemah, sulit diterapkan pada skala nasional dan membutuhkan interpretasi yang cermat (Sonneveld, Keyzar, dan Stroosnijder, 2011).…”

Prioritization of Flood Vulnerability Zones Using Remote Sensing and GIS for Hydrological Modelling

“…Suspended sediment is empirically one of the best indicators of sediment delivery into the drainage system (Kamaludin et al, 2013). Soil particles can be transported over a short or a longer distance before being deposited (Department of Irrigation and Drainage (DID), 2010).…”