• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.857-871
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• 2013

The interest in rainfall observation and forecasting using remote sensing method like RADAR (Radio Detection and Ranging) and satellite image is increased according to increased damage by rapid weather change like regional torrential rain and flash flood. In this study, the basin runoff was calculated using adaptive neuro-fuzzy technique, one of the data driven model and MAPLE (McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as one of the input variables. The flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated. Six rainfall events occurred at flood season in 2010 and 2011 in Chungju Reservoir basin were used for the input data. The flood estimation results according to the rainfall data used as training, checking and testing data in the model setup process were compared. The 15 models were composed of combination of the input variables and the results according to change of clustering methods were compared and analysed. From this study was that using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation. The model using MAPLE forecasted precipitation data showed relatively better result at inflow estimation Chungju Reservoir.

• Journal of Multimedia Information System
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• v.5 no.4
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• pp.235-244
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• 2018

Potential maximum soil moisture retention (S) is a dominant parameter in the Soil Conservation Service (SCS; now called the USDA Natural Resources Conservation Service (NRCS)) runoff Curve Number (CN) method commonly used in hydrologic modeling for event-based flood forecasting (SCS, 1985). Physically, S represents the depth [L] soil could store water through infiltration. The depth of soil moisture retention will vary depending on infiltration from previous rainfall events; an adjustment is usually made using a factor for Antecedent Moisture Conditions (AMCs). Application of the method for continuous simulation of multiple storms has typically involved updating the AMC and S. However, these studies have focused on a time step where S is allowed to vary at daily or longer time scales. While useful for hydrologic events that span multiple days, this temporal resolution is too coarse for short-term applications such as flash flood events. In this study, an approach for deriving a time-variable potential maximum soil moisture retention curve (S-curve) at hourly time-scales is presented. The methodology is applied to the Napa River basin, California. Rainfall events from 2011 to 2012 are used for estimating the event-based S. As a result, we derive an S-curve which is classified into three sections depending on the recovery rate of S for soil moisture conditions ranging from 1) dry, 2) transitional from dry to wet, and 3) wet. The first section is described as gradually increasing recovering S (0.97 mm/hr or 23.28 mm/day), the second section is described as steeply recovering S (2.11 mm/hr or 50.64 mm/day) and the third section is described as gradually decreasing recovery (0.34 mm/hr or 8.16 mm/day). Using the S-curve, we can estimate the hourly change of soil moisture content according to the time duration after rainfall cessation, which is then used to estimate direct runoff for a continuous simulation for flood forecasting.

• Atmosphere
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• v.14 no.1
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• pp.24-43
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• 2004

This paper describes the detailed characteristics of heavy rainfall events occurred in Chungcheong province on 15 and 16 April and from 6 to 8 August 2002 based on the analysis of raingauge rainfall rate and radar reflectivity from the METRI's X-band Weather Radar located in Cheongju. A synoptic analysis of the case is carried out, first, and then the analysis is devoted to seeing how the radar observes the case and how much information we obtain. The highly resolved radar reflectivity of horizontal and vertical resolutions of 1 km and 500 m, respectively shows a three-dimensional structure of the precipitating system, in a similar sequence with the ground rainfall rate. The radar echo classification algorithm for convective/stratiform cloud is applied. In the convectively-classified area, the radar reflectivity pattern shows a fair agreement with that of the surface rainfall rate. This kind of classification using radar reflectivity is considered to be useful for the precipitation forecasting. Another noteworthy aspect of the case includes the effect of topography on the precipitating system, following the analysis of the surface rainfall rate, topography, and precipitating system. The results from this case study offer a unique opportunity of the usefulness of weather radar for better understanding of structural and variable characteristics of flash flood-producing heavy rainfall events, in particular for their improved forecasting.

• Journal of Wetlands Research
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• v.16 no.1
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• pp.113-124
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• 2014

The observed rainfall may be different along with the altitude of rain gauge, resulting in the fact that the characteristics of rainfall events occurred in urban or mountainous areas are different. Due to the mountainous effects, in higher altitude, the uncertainty involved in the rainfall observation gets higher so that the density of rain gauges should be more dense. Basically, a methodology for the rain gauge network evaluation, considering this altitude effect of rain gauges can account for the mountainous effects and becomes an important step for forecasting flash flood and calibrating of the radar rainfall. For this reason, in this study, we suggest a methodology for rain gauge network evaluation with consideration of the rain gauge's altitude. To explore the density of rain gauges at each level of altitude, the Equal-Altitude-Ratio of the density of rain gauges, which is based on the fixed amount of elevation and the Equal-Area-Ratio of the density of rain gauges, which is based on the fixed amount of basin area are designed. After these two methods are applied to a real watershed, it is found that the Equal-Area-Ratio generates better results for evaluation of a rain gauge network with consideration of rain gauge's altitude than the Equal-Altitude-Ratio does. In addition, for comparison between the soundness of rain gauge networks in other watersheds, the Coefficient of Variation (CV) of the rain gauge density by the Equal-Area-Ratio is served as the index for the evenness of the distribution of the rain gauge's altitude. The suggested method is applied to the five large watersheds in Korea and it is found that rain gauges installed in a watershed having less value of the CV shows more evenly distributed than the ones in a watershed having higher value of the CV.