Abstract
Runoff potentiality of a watershed was assessed based on identifying curve number (CN), soil conservation service (SCS), and functional data analysis (FDA) techniques. Daily discrete rainfall data were collected from weather stations in the study area and analyzed through lowess method for smoothing curve. As runoff data represents a periodic pattern in each watershed, Fourier series was introduced to fit the smooth curve of eight watersheds. Seven terms of Fourier series were introduced for the watersheds 5 and 8, while 8 terms of Fourier series were used for the rest of the watersheds for the best fit of data. Bootstrapping smooth curve analysis reveals that watersheds 1, 2, 3, 6, 7, and 8 are with monthly mean runoffs of 29, 24, 22, 23, 26, and 27 mm, respectively, and these watersheds would likely contribute to surface runoff in the study area. The purpose of this study was to transform runoff data into a smooth curve for representing the surface runoff pattern and mean runoff of each watershed through statistical method. This study provides information of runoff potentiality of each watershed and also provides input data for hydrological modeling.
Highlights
Runoff from a watershed depends on rainfall, infiltration, and watershed characteristics and it can be measured daily, monthly, or annually
Each soil series is classified based on soil characteristics and texture and they fall under C and D hydrologic soil groups (Figure 4)
Curve numbers were identified for different hydrologic soil groups in each watershed in Alor Gajah and
Summary
Runoff from a watershed depends on rainfall, infiltration, and watershed characteristics and it can be measured daily, monthly, or annually. Watershed runoff is a major concern due to its impact on environmental, agricultural, and flood potential. To assess environmental impact or flood potential, it is needed to know the watershed runoff contribution to the river or streams due to rainfall. Surface runoff information may be used for groundwater resource modeling by incorporating infiltration information due to rainfall [4]. Agricultural practices and land use patterns have changed over time due to economic benefits [10,11,12], and these changes are contributing to runoff [13]. Land cover or vegetation may contribute to evapotranspiration losses and infiltration rate and may affect the runoff quantity in watershed area [14–
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