Abstract
The objective of this study was to establish a method to calibrate a large-scale laboratory rainfall simulator through developing and implementing an automated rainfall collection system to assess the reliability and accuracy of a rainfall simulator. The automated rainfall collection system was designed to overcome the limitations caused by the traditional manual measurement for obtaining the rainfall intensity and the spatial rainfall distribution in a large experimental area. The developed automated rainfall collection system was implemented to calibrate a large-scale laboratory rainfall simulator. The adequacy of average rainfall intensities automatically collected from the miniature tipping bucket rain gauges was assessed by comparison with those based on the volumetric method using the flowmeter. The functional relationships between the system variables of the rainfall simulator and the simulated intensity and uniformity distribution of rainfall (i.e., operation models) were derived based on a multiple regression approach incorporating correlation analysis on linear and logarithm scales, with consideration of a significance level. The operation models exhibited high accuracy with respect to both the rainfall intensity and the uniformity coefficients.
Highlights
The main purpose of an rainfall simulator (RS) is to provide a reproducible collection of rainfall data as well as to accurately and precisely create a variety of rainfall regimes by controlling the rainfall intensity and duration [2,7,8]
The data collected from rainfall simulation experiments provide fundamental information to understand the dynamic behaviors of runoff generation, infiltration and soil erosion; this information is focused on how surface properties such as slope, soil properties, vegetation cover, and topography within catchments impact the above-mentioned processes [9,10]
RS has has been been calibrated calibrated for for the the rainfall rainfall intensity intensity and and the the uniformity uniformity of of rainfall rainfall distribution distribution at at various system variables: the operating pressurespressures and the oscillatory various combinations combinationsof the of the system variables: the operating and the movements oscillatory including velocity andvelocity time delay
Summary
Rainfall-runoff is an important hydrological process that affects many different types of environmental factors including soil, topography, vegetation, and natural resources within catchments.Runoff studies are often dependent on the characteristics of natural rainfall such as its variability in intensity, spatio-temporal distribution, drop size distribution, drop velocity, and kinetic energy [1].Rainfall simulation is the prevalent method applied in hydrogeomorphological studies that include runoff, infiltration, soil characteristics in catchments, and other study areas for replicating the features and processes of natural rainfall [2].A rainfall simulator (RS) is widely used as research tool to produce runoff, infiltration, and erosion data in field- and laboratory-based studies of hydrological and geomorphological processes [3,4,5,6].The main purpose of an RS is to provide a reproducible collection of rainfall data as well as to accurately and precisely create a variety of rainfall regimes by controlling the rainfall intensity and duration [2,7,8]. Rainfall-runoff is an important hydrological process that affects many different types of environmental factors including soil, topography, vegetation, and natural resources within catchments. Runoff studies are often dependent on the characteristics of natural rainfall such as its variability in intensity, spatio-temporal distribution, drop size distribution, drop velocity, and kinetic energy [1]. A rainfall simulator (RS) is widely used as research tool to produce runoff, infiltration, and erosion data in field- and laboratory-based studies of hydrological and geomorphological processes [3,4,5,6]. The data collected from rainfall simulation experiments provide fundamental information to understand the dynamic behaviors of runoff generation, infiltration and soil erosion; this information is focused on how surface properties such as slope, soil properties, vegetation cover, and topography within catchments impact the above-mentioned processes [9,10]
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