Yoo, Chul Sang

In this study, a hydrological analysis of rainwater harvesting facilities was conducted using a model based on the IHACRES model. Using this model, the rainfall, rainfall loss, inflow to the storage tank, tank storage volume, overflow from the tank, and rainwater consumption data were simulated to evaluate the hydrological characteristics of the rainwater harvesting facilities. This study evaluated three rainwater harvesting facilities in Korea. The results of the study are summarized as follows

Abstract The effect of global warming (represented by general circulation model monthly rainfall predictions) on the daily rainfall distribution is investigated using a mixed Gamma distribution to estimate the change of rainfall quantiles. A mixed distribution is used to overcome the limitation of conventional frequency analysis, which uses a continuous distribution, as this is not applicable for the assessment of the effects of global warming. To summarize the results: (1) Even though the varia

In this study we compared applications of mixed and continuous distribution functions to the theory of entropy for the evaluation of rain gauge networks. The use of a mixed distribution function to evaluate rain gauge networks has an important advantage of considering rainfall intermittency in both time and space. Parameters of both mixed and continuous distribution functions were estimated using the daily rainfall data collected in the Choongju Dam Basin, Korea. The optimal number of rain gauge

This study evaluated five models of rainfall temporal distribution (i.e., the Yen and Chow model, Mononobe model, alternating block method, Huff model, and Keifer and Chu model), with the annual maximum rainfall events selected from Seoul, Korea, from 1961 to 2016. Three different evaluation measures were considered: the absolute difference between the rainfall peaks of the model and the observed, the root mean square error, and the pattern correlation coefficient. Also, sensitivity analysis was

Abstract In this study, the correction problem of mean‐field bias of radar rain rate was investigated using the concept of linear regression. Three different relationships were reviewed for their slopes to be used as the bias correction factor: Relationship 1 (R1) is based on the conventional linear regression, relationship 2 (R2) is forced to pass the origin and relationship 3 (R3) is the line whose slope is the G / R ratio. In other words, R1 is the regression line connecting the intercept and

LID are spread on a small scale throughout target area, therefore, evaluation of their overall effect on flood reduction is not straightforward. As one solution dealing with this problem, Yoo et al. (2012) proposed a methodology for quantifying the flood runoff reduction effect of storage facilities by curve number (CN). Introduction of various infiltration or storage facilities causes the decrease in CN, which can be calculated using the runoff. The result derived was summarized in a graph show

This study evaluated 20 general circulation models (GCMs) of the Coupled Model Intercomparison Project, Phase 5 (CMIP5), which provide the prediction results for the period of 2006 to 2014, the period from which the observation data (the Global Precipitation Climatology Project (GPCP) data) are available. Both the GCM predictions of precipitation and the GPCP data were compared for three data structures—the global, zonal, and grid mean—with conventional statistics like the root mean square error