• Water for future
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• v.8 no.2
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• pp.81-92
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• 1975

Calculation of the monthly water balance for Nakdong River basin for the period from 1958 to 1968 is made by determining three components independently: precipitation, runoff and evapotranspiration. The areal precipitation is computed by the Thiessen method using the records of nine meteorological stations in the basin, and the runoff is the flow gauged at Jindong which is located on the most downstream. For the computation of evapotranspiration, the Morton method is adopted because this method is relatively fit best in the calculation of water balance among the Morton, Penman and Thornthwaite methods. The values of Morton evapotransp iration are corrected by the factor of 0.82 in the basin in order to bring the error to zero. The areal evapotranspiration is the arithmetic mean of the Morton estimates at the stations. Mean water balance components in the Nakdong river basin are 1117.0mm, 600.6mm and 516.4m for precipitation, runoff and evapotranspiration respectively. Accordingly, the mean runoff ratio comes out to be 0.54. The smallest values of runoff coefficient are due for Daegu area, while the largest ones are for the southwest of the basin with the higher rainfall and high elevations there. The amount of runoff obtained by both Thornthwaite and Budyko methods for water balance computations indicate 59 and 60 per cent of actual values which are lower than the expected. An attempt is made to find the best reliable rainfall-runoff relation among the four methods proposed by Schreiber, 01'dekop, Budyko and Sellers. The modified equation of Schreiber type for annual runoff coefficient could be obtained with the smallest mean error of 11 per cent.

• Journal of Environmental Science International
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• v.20 no.1
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• pp.93-106
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• 2011

Physically-based resampling scheme for roughness coefficient of surface runoff considering the spatial landuse distribution was suggested for the purpose of effective operational application of recent grid-based distributed rainfall runoff model. Generally grid scale(mother scale) of hydrologic modeling can be greater than the scale (child scale) of original GIS thematic digital map when the objective basin is wide or topographically simple, so the modeler uses large grid scale. The resampled roughness coefficient was estimated and compared using 3 different schemes of Predominant, Composite and Mosaic approaches and total runoff volume and peak streamflow were computed through distributed rainfall-runoff model. For quantitative assessment of biases between computational simulation and observation, runoff responses for the roughness estimated using the 3 different schemes were evaluated using MAPE(Mean Areal Percentage Error), RMSE(Root-Mean Squared Error), and COE(Coefficient of Efficiency). As a result, in the case of 500m scale Mosaic resampling for the natural and urban basin, the distribution of surface runoff roughness coefficient shows biggest difference from that of original scale but surface runoff simulation shows smallest, especially in peakflow rather than total runoff volume.

• Water Engineering Research
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• v.1 no.3
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• pp.209-222
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• 2000

A spectral formalism was applied to quantify the sampling errors due to spatial and/or temporal gaps in soil moisture measurements. The lack of temporal measurements of the two-dimensional soil moisture field makes it difficult to compute the spectra directly from observed records. Therefore, the space-time soil moisture spectra derived by stochastic models of rainfall and soil moisture was used in their record. Parameters for both models were tuned with Southern Great Plains Hydrology Experiment(SGP'97) data and the Oklahoma Mesonet data. The structure of soil moisture data is discrete in space and time. A design filter was developed to compute the sampling errors for discrete measurements in space and time. This filter has the advantage in its general form applicable for all kinds of sampling designs. Sampling errors of the soil moisture estimation during the SGP'97 Hydrology Experiment period were estimated. The sampling errors for various sampling designs such as satedlite over pass and point measurement ground probe were estimated under the climate condition between June and August 1997 and soil properties of the SGP'97 experimental area. The ground truth design was evaluated to 25km and 50km spatial gap and the temporal gap from zero to 5 days.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.1
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• pp.23-32
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• 2008

According to recent frequent local flash flood due to climate change, the very short-term rainfall forecast using remotely sensed rainfall like radar is necessary to establish. This research is to evaluate the feasibility of GIS-based distributed model coupled with radar rainfall, which can express temporal and spatial distribution, for multipurpose dam operation during flood season. $Vflo^{TM}$ model was used as physically based distributed hydrologic model. The study area was Yongdam dam basin ($930\;km^2$) and the 3 storm events of local convective rainfall in August 2005, and the typhoon.Ewiniar.and.Bilis.collected from Jindo radar was adopted for runoff simulation. Distributed rainfall consistent with hydrologic model grid resolution was generated by using K-RainVieux, pre-processor program for radar rainfall. The local bias correction for original radar rainfall shows reasonable results of which the percent error from the gauge observation is less than 2% and the bias value is $0.886{\sim}0.908$. The parameters for the $Vflo^{TM}$ were estimated from basic GIS data such as DEM, land cover and soil map. As a result of the 3 events of multiple peak hydrographs, the bias of total accumulated runoff and peak flow is less than 20%, which can provide a reasonable base for building operational real-time short-term rainfall-runoff forecast system.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.

• Journal of the Korean earth science society
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• v.36 no.1
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• pp.109-124
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• 2015

A novel approach, hybrid surface rainfall (KNU-HSR) technique developed by Kyungpook Natinal University, was utilized for improving the radar rainfall estimation. The KNU-HSR technique estimates radar rainfall at a 2D hybrid surface consistings of the lowest radar bins that is immune to ground clutter contaminations and significant beam blockage. Two HSR techniques, static and dynamic HSRs, were compared and evaluated in this study. Static HSR technique utilizes beam blockage map and ground clutter map to yield the hybrid surface whereas dynamic HSR technique additionally applies quality index map that are derived from the fuzzy logic algorithm for a quality control in real time. The performances of two HSRs were evaluated by correlation coefficient (CORR), total ratio (RATIO), mean bias (BIAS), normalized standard deviation (NSD), and mean relative error (MRE) for ten rain cases. Dynamic HSR (CORR=0.88, BIAS= $-0.24mm\;hr^{-1}$, NSD=0.41, MRE=37.6%) shows better performances than static HSR without correction of reflectivity calibration bias (CORR=0.87, BIAS= $-2.94mm\;hr^{-1}$, NSD=0.76, MRE=58.4%) for all skill scores. Dynamic HSR technique overestimates surface rainfall at near range whereas it underestimates rainfall at far ranges due to the effects of beam broadening and increasing the radar beam height. In terms of NSD and MRE, dynamic HSR shows the best results regardless of the distance from radar. Static HSR significantly overestimates a surface rainfall at weaker rainfall intensity. However, RATIO of dynamic HSR remains almost 1.0 for all ranges of rainfall intensity. After correcting system bias of reflectivity, NSD and MRE of dynamic HSR are improved by about 20 and 15%, respectively.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.4
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• pp.27-43
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• 1990

This study aimed at developing a generalized model on the estimation of the long - term run - off volume for practical purpose. During the research period of last 3 years( 1986-1988), 3 types of estimation model on the long - term run - off volume(Effective rainfall model, unit hydrograph model and barne's model for dry season) had been developed by the author. In this study, through regressional analysis between determinant factors (bi of effective rainfall model, ai of unit hydrograph model and Wi of barne's model) and catchment characteris- tics(catchment area, distance round the catchment area, massing degree coefficient, river - exte- nsion, river - slope, river - density, infiltration of Watershed) of 11 test case areas by multiple regressional method, a new methodology on the derivation of determinant factors from catchment characteristics in the watershed areas having no hydrological station was developed. Therefore, in the resulting step, estimation equations on run - off volume for practical purpose of which input facor is only rainfall were developed. In the next stage, the derived equations were applied on the Kang - and Namgye - river catchment areas for checking of their goodness. The test results were as follows ; 1. In Kang - river area, average relative estimation errors of 72 hydrographs and of continuous daily run - off volume for 245 days( 1/5/1982 - 31/12) were calculated as 6.09%, 9.58% respectively. 2. In Namgye - river area, average relative estimation errors of 65 hydrographs and of conti- nuous daily run - off volume for 2fl days(5/4/1980-31/12) were 5.68%, 10.5% respectively. In both cases, relative estimation error was averaged as 7.96%, and so, the methodology in this study might be hetter organized than Kaziyama's formula when comparing with the relative error of the latter, 24~54%. However, two case studies cannot be the base materials enough for the full generalization of the model. So, in the future studies, many test case studies of this model should he carries out in the various catchment areas for making its generalization.

• Journal of Korea Water Resources Association
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• v.51 no.5
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• pp.383-393
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• 2018

The regional frequency analysis is the method which uses not only sample of target station but also sample of neighborhood stations in which are classified as hydrological homogeneous regions. Consequently, identification of homogeneous regions is a very important process in regional frequency analysis. In this study, homogeneous regions for regional frequency analysis of precipitation were identified by the self-organizing map (SOM) which is one of the artificial neural network. Geographical information and hourly rainfall data set were used in order to perform the SOM. Quantization error and topographic error were computed for identifying the optimal SOM map. As a result, the SOM model organized by $7{\times}6$ array with 42 nodes was selected and the selected stations were classified into 6 clusters for rainfall regional frequency analysis. According to results of the heterogeneity measure, all 6 clusters were identified as homogeneous regions and showed more homogeneous regions compared with the result of previous study.

• Journal of the Korean earth science society
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• v.33 no.7
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• pp.596-607
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• 2012

The R-Z relationship is one of important error factors to determine the accuracy of radar rainfall estimation. In this study, we have explored the effect of the R-Z relationships derived from disdrometer data in estimating the radar rainfall. The heavy rain event that produced flooding in St-Remi, Quebec, Canada has been occurred. We have tried to investigate the severity of rain for this event using high temporal (2.5 min) and spatial resolution ($1^{\circ}$ by 250 m) radar data obtained from the McGill S-band radar. Radar data revealed that the heavy rain cells pass directly over St-Remi while the coarse raingauge network was not sufficient to detect this rain event. The maximum 30 min (1 h) accumulation reaches about 39 (42) mm in St-Remi. During the rain event, the two disdrometers (POSS; Precipitation Occurrence Sensor System) were available: One used for the reflectivity calibration by comparing disdrometer Z and radar Z and the other for deriving disdrometric R-Z relationships. The result shows the significant improvement with the disdrometric reflectivity-dependent R-Z relationships against the climatological R-Z relationship. The bias in radar rain estimation is reduced from +12% to -2% and the root-mean squared error from 16 to 10% for daily accumulation. Using the estimated radar rainfall rate with disdrometric R-Z relationships, the flood event was well captured with proper timing and amount.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.3
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• pp.87-101
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• 1990

The purpose of this study is to estimate the flood discharge and runoff volume at a stream by using geomorphologic parameters obtained from the topographic maps following the law of stream classification and ordering by Horton and Strahier. The present model is modified from Cheng' s model which derives the geomorphologic instantaneous unit hydrograph. The present model uses the results of Laplace transformation and convolution intergral of probability density function of the travel time at each state. The stream flow velocity parameters are determined as a function of the rainfall intensity, and the effective rainfall is calculated by the SCS method. The total direct runoff volume until the time to peak is estimated by assuming a triangular hydrograph. The model is used to estimate the time to peak, the flood discharge, and the direct runoff at Andong, Imha. Geomchon, and Sunsan basin in the Nakdong River system. The results of the model application are as follows : 1.For each basin, as the rainfall intensity doubles form 1 mm/h to 2 mm/h with the same rainfall duration of 1 hour, the hydrographs show that the runoff volume doubles while the duration of the base flow and the time to peak are the same. This aggrees with the theory of the unit hydrograph. 2.Comparisions of the model predicted and observed values show that small relative errors of 0.44-7.4% of the flood discharge, and 1 hour difference in time to peak except the Geomchon basin which shows 10.32% and 2 hours respectively. 3.When the rainfall intensity is small, the error of flood discharge estimated by using this model is relatively large. The reason of this might be because of introducing the flood velocity concept in the stream flow velocity. 4.Total direct runoff volume until the time to peak estimated by using this model has small relative error comparing with the observed data. 5.The sensitivity analysis of velocity parameters to flood discharge shows that the flood discharge is sensitive to the velocity coefficient while it is insensitive to the ratio of arrival time of moving portion to that of storage portion of a stream and to the ratio of arrival time of stream to that of overland flow.