Runoff estimation using SCS CN method for Kelantan River Basin - Ahmad Shafuan, Mohammad Faizalhakim; Abu Bakar, Siti Nurhidayu; Ibrahim, Shamsudin; Hakeem, Khalid Rehman; Abdul Malek, Ismail Adnan; Kamarudin, Norizah (2015)
Runoff is one of the basic and crucial hydrological data which is needed in the water resources planning and management e.g. flood mitigation measures, waterways, and storage capacity and erosion control. Generally, runoff is measured or estimated by using two methods; gauged (direct measurement) and ungauged (indirect formula and equation). The most popular methods for runoff estimation is Soil Conservation Service Curve Number (SCS-CN) because it is relatively simple, quick and most reliable way with the minimum data required to estimate runoff for the ungauged basin. The SCS-CN method was developed by United State Department Agriculture (USDA) SCS in 1954, where runoff volume (Q) were calculated using runoff curve number equation. The data needed for this equation are rainfall, land use, hydrologic soil group and antecedent moisture content. This paper is aimed to discuss runoff estimation based on SCS-CN method for Kelantan River Basin (KRB), Peninsular Malaysia that were impacted by the ‘Great Yellow Flood’ in December 2014. The losses of the flood event was estimated more than RM2.81 billion and it was speculated to be caused by illegal and uncontrolled logging. KRB area is 11900km2 or 85% from Kelantan State with land use types of forested area (47%), rubber plantation (17%), oil palm plantation (10%) and others (26%). SCS-CN is used to estimate runoff for flood study in KRB for flood mitigation measures development. The SCS-CN was determined for the KRB based on information obtained from its land use, hydrologic soil group, and antecedent moisture content to estimate runoff generated from this basin. For future, the satellite imagery can be used for better land use classification using high resolution satellite e.g. SPOT 5 (2.5m resolution) and collaborate with Geological Information System (GIS) as well Remote Sensing (RS) software.