• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.2
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• pp.45-57
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• 2003

An artificial neural network model was developed to analyze and forecast Short-term river runoff from the Naju watershed, in Korea. Error back propagation neural networks (EBPN) of hourly rainfall and runoff data were found to have a high performance In forecasting runoff. The number of hidden nodes were optimized using total error and Bayesian information criterion. Model forecasts are very accurate (i.e., relative error is less than 3% and $R^2$is greater than 0.99) for calibration and verification data sets. Increasing the time horizon for application data sets, thus mating the model suitable for flood forecasting. decreases the accuracy of the model. The resulting optimal EBPN models for forecasting hourly runoff consists of ten rainfall and four runoff data(ANN0410 model) and ten rainfall and ten runoff data(ANN1010 model). Performances of the ANN0410 and ANN1010 models remain satisfactory up to 6 hours (i.e., $R^2$is greater than 0.92).

• Journal of Environmental Science International
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• v.10 no.3
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• pp.217-223
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• 2001

Where no records are available at a site, a preliminary estimate may be made from relations between floods and catchment chatacteristics. A number of these chatacteristics were chosen for testing and were measured for those catchments where mean annual flood estimates were available. Although the improvement using extended data in regression of flood estimates on catchment characteristics was small, this may be due to the limitations of the regression model. When an individual short term record is to be extended, more detailed attention can be given; an example is presented of the technique which should be adopted in practice, particularly when a short term record covers a period which is known to be biassed. A method of extending the peaks over a threshold series is presented with a numerical example. The extension of records directly from rainfall by means of a conceptual model is discussed, although the application of such methods is likely to be limited by lack of recording raingauge information. Methods of combining information from various sources are discussed in terms of information from catchment characteristics supplemented by records. but are generally applicable to different sources of information. The application of this technique to estimating the probable maximum flood requires more conservative assumptions about the antecedent condition, storm profile and unit hydrograph. It is suggested that the profile and catchment wetness index at the start of the design duration should be based on the assumption that the estimated maximum rainfall occurs in all durations centered on the storm peak.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.101-113
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• 2010

Recently actual rainfall pattern is decreasing rainy days and increasing in rainfall intensity and the frequency of flood occurrence is also increased. To consider recent situation, Engineers use deterministic methods like a PMP(Probable Maximum Precipitation). If design storm wouldn't occur, increasing of design criteria is extravagant. In addition, the biggest structure cause trouble with residents and environmental problem. And then it is necessary to study considering probability of rainfall parameter in each sub-basin for design of water structure. In this study, stochastic rainfall patterns are generated by using log-ratio method, Johnson system and multivariate Monte Carlo simulation. Using the stochastic rainfall patterns, hydrological analysis, hydraulic analysis and 2nd flooding analysis were performed based on GIS for their applicability. The results of simulations are similar to the actual damage area so the methodology of this study should be used about making a flood risk map or regidental shunting rout map against the region.

• Journal of the Korean Data and Information Science Society
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• v.24 no.5
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• pp.1101-1101
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• 2013

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.23-29
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• 2011

This study was conducted to identify the effect of lapse rate application according to elevation on the estimation of large scale watershed rainfall. For the Han river basin (26,018 $km^2$), the 11 years (2000-2010) daily rainfall data from 108 AWS (Automatic Weather Station) were collected. Especially, the 11 heavy rain and typhoon events from 2004 to 2009 were selected for trend analysis. The elevation effect by IDW (Inverse Distance Weights) interpolation showed the change up to +62.7 % for 1,200~1,600m elevation band. The effect based on 19 subbasins of WAMIS (Water Resources Management Information System) water resources unit map, the changes of IDW and Thiessen were -8.0 % (Downstream of Han river)~ +19.7 % (Upstream of Namhan river) and -5.7 %~+15.9 % respectively. It showed the increase trend as the elevation increases. For the 11 years rainfall data analysis, the lapse rate effect of IDW and Thiessen showed increase of 9.7 %~15.5 % and 6.6 %~9.6 % respectively.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.53-56
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• 2014

In the satellite system design, the design processes from the initial design to launch take about 5 years and the broadcasting satellite lifetime goes over 15 years. Furthermore, global warming phenomenon causes rainfall rate to increase more and more in some regions on the earth. Consequently, at the stage of the satellite link design, we need to consider the future rain attenuation over 20 years. In this paper, we investigated a time-series system model for forecasting to consider the future rainfall rate for the satellite broadcasting service. We found that rainfall rate of the future 20 years is increasing continuously.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.439-439
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• 2015

The temporal and spatial relationship of the weather elements such as rainfall and temperature is closely linked to the streamflow simulation, especially, to the flood forecasting problems. For the study area, Imjin river basin, which has the specific characteristics in geography with river cross operation between North and South Korea, the meteorological information in the northern area is totally deficiency, lead to the inaccuracy of streamflow estimation. In the paper, this problem is solved by using the combination of global (such as soil moisture content, land use) and local hydrologic components data such as weather data (precipitation, evapotranspiration, humidity, etc.) for the model-driven runoff (surface flow, lateral flow and groundwater flow) data in each subbasin. To compute the streamflow in Imjin river basin, this study is applied the hydrologic model SURR (Sejong Univ. Rainfall-Runoff) which is the continuous rainfall-runoff model used physical foundations, originally based on Storage Function Model (SFM) to simulate the intercourse of the soil properties, weather factors and flow value. The result indicates the spatial variation in the runoff response of the different subbasins influenced by the input data. The dependancy of runoff simulation accuracy depending on the qualities of input data and model parameters is suggested in this study. The southern region with the dense of gauges and the adequate data shows the good results of the simulated discharge. Eventually, the application of SURR model in Imjin riverbasin gives the accurate consequence in simulation, and become the subsequent runoff for prediction in the future process.

• Journal of Korea Water Resources Association
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• v.41 no.5
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• pp.545-558
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• 2008

This study estimated the error involved in the areal average rainfall derived from incomplete radar information due to radar partial coverage of a basin or sub-basin. This study considers the Han-River Basin as an application example for the rainfall observation using the Ganghwa rain radar. Among the total of 20 mid-sized sub-basins of the Han-River Basin evaluated in this study, only five sub-basins are fully covered by the radar and three are totally uncovered. Remaining 12 sub-basins are partially covered by the radar to result in incomplete radar information available. When only partial radar information is available, the sampling error decreases proportional to the size of the radar coverage, which also varies depending on the number of clusters. Conditioned that the total area coverage remains the same, the sampling error decreases as the number of clusters increases. This study estimated the sampling error of the areal average rainfall of partially-covered mid-sized sub-basins of the Han- River Basin, and the results show that the sampling error could be at least several % to maximum tens % depending on the relative coverage area.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.747-757
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• 2021

Quantification of extreme rainfall is very important in establishing a flood protection plan, and a general measure of extreme rainfall is expressed as an T-year return level. In this study, a method was proposed for quantifying spatial distribution and uncertainty of daily rainfall depths with various return periods using a hierarchical Bayesian model combined with climate and geographical information, and was applied to the Seoul-Incheon-Gyeonggi region. The annual maximum daily rainfall depth of six automated synoptic observing system weather stations of the Korea Meteorological Administration in the study area was fitted to the generalized extreme value distribution. The applicability and reliability of the proposed method were investigated by comparing daily rainfall quantiles for various return levels derived from the at-site frequency analysis and the regional frequency analysis based on the index flood method. The uncertainty of the regional frequency analysis based on the index flood method was found to be the greatest at all stations and all return levels, and it was confirmed that the reliability of the regional frequency analysis based on the hierarchical Bayesian model was the highest. The proposed method can be used to generate the rainfall quantile maps for various return levels in the Seoul-Incheon-Gyeonggi region and other regions with similar spatial sizes.

• Journal of Korea Water Resources Association
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• v.50 no.1
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• pp.1-15
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• 2017

Information on radar rainfall with high spatio-temporal resolution over large areas has been used to mitigate climate-related disasters such as flash floods. On the other hand, a well-known problem associated with the radar rainfall using the Marshall-Palmer relationship is the underestimation. In this study, we develop a new bias correction scheme based on the quantile regression method. This study employed a bivariate copula function method for the joint simulation between radar and ground gauge rainfall data to better characterize the error distribution. The proposed quantile regression based bias corrected rainfall showed a good agreement with that of observed. Moreover, the results of our case studies suggest that the copula function approach was useful to functionalize the error distribution of radar rainfall in an effective way.