• Journal of Korea Water Resources Association
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• v.31 no.1
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• pp.13-25
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• 1998

It is necessary to develop methodologies for the application of artificial neural network into hydrologic rainfall-runoff process, although there is so much applicability by using the functions of associative memory based on recognition for the relationships between causes and effects and the excellent fitting capacity for the nonlinear phenomenon. In this study, some problems are presented in the application procedures of artificial neural networks and the simulation of runoff hydrograph experiences are reviewed with nonlinear functional approximator by artificial neural network for rainfall-runoff relationships in a watershed. which is regarded as hydrdologic black box model. The neural network models are constructed by organizing input and output patterns with the deserved rainfall and runoff data in Pyoungchang river basin under the assumption that the rainfall data is the input pattern and runoff hydrograph is the output patterns. Analyzed with the results. it is possible to simulate the runoff hydrograph with processing element of artificial neural network with any hydrologic concepts and the weight among processing elements are well-adapted as model parameters with the assumed model structure during learning process. Based upon these results. it is expected that neural network theory can be utilized as an efficient approach to simulate runoff hydrograph and identify the relationship between rainfall and runoff as hydrosystems which is necessary to develop and manage water resources.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1870-1875
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• 2006

This study was carried out to investigate the applicability of SAC-SMA model with parameters which were derived from analytical relationships proposed by Koren etc. (2000), with various data of soil properties in a basin. The studied basin is Yongdam dam basin and the daily runoff with 2003-year hydrological data was simulated. Simulated runoff results were compared with those measured at three check points(Chuchun, Donhyang and Yongdam) and analyzed through the statistical techniques such as VE(Volume Error), RMSE(Root Mean Squared Error) and CORR(Correlation). As a result of analyses, the good agreement was obtained between simulated and measured results.

• Journal of Korea Water Resources Association
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• v.41 no.10
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• pp.995-1007
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• 2008

Studies on modeling the rainfall-runoff relationship which shows nonlinear trend strongly use artificial neural networks theory not only for the prediction but also for the characteristics analysis of the data used by pattern classification. For the pattern classification, the results from Self-Organizing Map (SOM) mention that the map size and array for the SOM training have significantly influenced on the SOM performance. Since there is no deterministic method or theoretical equation to determine the number of rows and columns for the map size, hexagonal array is generally used for the map array. Therefore, this study present a determination of the optimized map structure for the rainfall-runoff analysis in Naju station considering the map size and array simultaneously which can represent the classified characterization of rainfall-runoff relationship. The result showed that the map size of 20$\times$16 hexagonal array with 8-clustered patterns was selected as an appropriate map structure for rainfall-runoff analysis in Naju station.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.6
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• pp.81-87
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• 2010

In order to calculate the accurate runoff from a basin, nonlinearity in the relationship between rainfall and runoff has to be considered. Many runoff calculation models assume the linearity in the relationship or are too complicated to be analyzed. Therefore, the storage function method has been used in the prediction of flood because of the simplicity of the model. The storage function method has five parameters with related to the basin and rainfall characteristics which can be estimated by the empirical trial and error method. To optimize these parameters, regression method or optimization techniques such as genetic algorithm have been used, however, it is not easy to optimize them because of the complexity of the method. In this study, the metamodel is proposed to estimate those model parameters. The metamodel is the combination of artificial neural network and genetic algorithm. The model is consisted of two stages. In the first stage, an artificial neural network is constructed using the given rainfall-runoff relationship. In the second stage, the parameters of the storage function method are estimated using genetic algorithm and the trained artificial neural network. The proposed metamodel is applied in the Peong Chang River basin and the results are presented.

• Journal of Korean Society on Water Environment
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• v.27 no.5
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• pp.572-579
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• 2011

We have examined the runoff characteristics of nonpoint source (NPS) in fields. Two monitoring sites were equipped with an automatic velocity meter and water sampler. Monitoring was conducted at fields 1 and field 2 during the rainfall event. Ten rainfall-runoff events were monitored and analyzed during the study period. The results show that runoff occurred if daily rainfall and intensity were higher than 40 mm and 1.6 mm/hr except a few extreme rainfall events with very high intensity. Runoff of field 1 was approximately twice of that of field 2. Event mean concentrations (EMC) and pollution load of analyzed water quality indices were also higher in field 2 than in field 1. Especially, TN load from field 2 was $75.4 mg/m^2$ and was about 5 times higher than that from field 1. Analysis of Pearson correlation coefficient of water quality parameter indicates that besides of TN all items in fields 1 have tight relationship respectively (p < 0.01). But those of fields 2 have a significant (p < 0.05). Estimating units loading of NPS, we suggested that variable such as soil texture, rainfall amount and intensity and slope were needed to be considered from agricultural landuses. The results of this study can be used as a basic data in the development and implementation of total maximum daily loads (TMDL) in Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.2 no.1
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• pp.53-62
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• 1982

An effort of preliminary type has been made to develope a practical method for the waterway area determination of a drainage outlet in rural or agricultural areas. The Seoul meteorological station was selected as tile index station, and the maximum rainfalls-duration-frequency (R-D-F) relation of short-time intense rainfalls was first established. A frequency analysis of the daily rainfalls for the 75 stations selected throughout the country resulted the 50-year daily rainfall for each station. The rainfall factor, which is defined here as the ration of 50-year daily rainfalls of individual station and the index station, was determined for the 8 climatological regions divided in this study. Following the US SCS method the runoff number of a watershed was given based on the soil type, land-use pattern, and the surface treatment. With this runoff number and the R-D-F relationship the runoff factors for the index station were computed and hence a nomogram could be drawn which makes it possible to determine the runoff factor for a given rainfall number and a rainfall of specific duration and frequency. With this done, the potential runoff of a watershed for a given rainfall duration could be calculated, based on the unit hydrograph theory, by multiplying the rainfall factor, the runoff factor, and the drainage area of the watershed under consideration. Then, the maximum runoff potential was determined by varying the rainfall duration and finding out the duration which results the peak discharge of a gived return period.

• Journal of Korea Water Resources Association
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• v.52 no.9
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• pp.615-626
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• 2019

Soil moisture and runoff have very close relationship. Especially the water retention capacity and drainage characteristics of the soil are determined by various factors of the soil. In this study, a total of 40 rainfall events were identified from the entire rainfall events of Sulma basin in 2016 and 2017. For each selected events, the constant-K method was used to separate direct runoff and baseflow from total flow and calculate the runoff coefficient which shows positive exponential curve with Antecedent Soil Moisture (ASM). In addition to that, the threshold of soil moisture was determined at the point where the runoff coefficient starts increasing dramatically. The threshold of soil moisture shows great correlation with runoff and depth to water table. It was founded that not only ASM but also various factors, such as Initial Soil Moisture (ISM), storage capacity of soil and precipitation, affect the results of runoff response. Furthermore, wet condition and dry condition are separated by ASM threshold and the start and peak response are analyzed. And the results show that the response under wet condition occurred more quickly than that of dry condition. In most events occurred in dry condition, factors reached peak in order of soil moisture, depth to water table and runoff. However, in wet condition, they reached peak in order of depth to water table, runoff and soil moisture. These results will help identify the interaction among factors which affect the runoff, and it will help establish the relationship between various soil conditions and runoff.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.2
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• pp.131-135
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• 2007

This study was performed as an effort to reduce soil loss by investigating the phase of water flow according to soil texture and rainfall pattern and by determining the canopy cover subfactor in the RUSLE (revised universal soil loss equation). Red pepper was planted at the 15% sloped lysimeter of $2m{\times}5m{\times}0.5m$ ($width{\times}length{\times}depth$) with three different textured soils (loam, clay loam and sandy loam) and the relationship between amount and intensity of rainfall; soil loss and the amount of runoff; and amount of rainfall and runoff at different soil texture were measured at the experiment station of the National Institute of Agricultural Science and Technology (NIAST) during May to October of 2005. The amount of runoff increased with increasing amount of rainfall, showing difference in the relative increase rate of runoff at different soil texture. The increase rate of runoff with unit increase of rainfall for the lysimeter with red pepper was 0.44, 0.41 and 0.13 for loam, clayey loam and sandy loam, respectively. The minimum amount of rainfall for runoff was 23.53 mm for sandy loam, 10.35 mm for loam and 5.46 mm for clayey loam, respectively. The canopy cover subfactors of red pepper were 0.425, 0.459, and 0.478 for sandy loam, loam and clayey loam, respectively.

• Magazine of the Korean Society of Agricultural Engineers
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• v.30 no.2
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• pp.31-43
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• 1988

The Purpose of this study is to develop the rainfall-delayed response model (RDR Model) which influences the baseflow proportion of rivers as a result of the antecedent precipitation of the previous several months. The assesment of accurate baseflows in the rivers is one of the most important elements for the planning of seasonal water supply for agriculture, water resources development, hydrological studies for the availability of water and design criteria for various irrigation facilities. The Palukan river gauging site which is located in the Pulukan catchment on Bali Island, Indonesia was selected to develop this model. The basic data which has been used comprises the available historic flow records at 19 hydrologic gauging stations and 77 rainfall stations on Bali Island in the study. The methology adopted for the derivation of the RDR model was the water balance equation which is commonly used for any natural catcbment ie.P=R+(catchment losses) -R+(ET+DP+DSM+DGW). The catchment losses consist of evapotranspiration, deep percolation. change in soil moisture, and change in groundwater storage. The catchment areal rainfall has been generated by applying the combination method of Thiessen polygon and Isohyetal lines in the studies. The results obtained from the studies may be summarized as follows ; 1. The rainfall-runoff relationship derived from the water balance equation is as shown below, assuming a relationship of the form Y=AX+B. Finally these two equations for the annual runoff were derived ; ARO$_1$=0.855 ARF-821, ARF>=l,400mm ARO$_2$=0.290ARF- 33, ARF<1,400mm 2. It was found that the correction of observed precipitation by a combination of Thiessen polygons and Isohyetal lines gave good correlation. 3. Analysis of historic flow data and rainfall, shows that surface runoff and base flow are 52 % and 48% (equivalent to 59.4 mm) of the annual runoff, respectively. 4. Among the eight trial RDR models run, Model C provided the correlation with historic flow data. The number of months over which baseflow is distributed and the relative proportions of rainfall contributing in each month, were estimated by performing several trial runs using data for the Pulukan catchment These resulted in a value for N of 4 months with contributing proportions of 0.45, 0.50, 0.03 and 0.02. Thus the baseflow in any month is given by : P$_1$(n) =0.45 P(n) +0.50 P(n-I ) +0.03 P(n-$_2$) +0.02 P(n-$_3$) 5. The RDR model test gave estimated flows within +3.4 % and -1.0 % of the observed flows. 6. In the case of 3 consecutive no rain months, it was verified that 2.8 % of the dependable annual flow will be carried over the following year and 5.8 % of the potential annual baseflow will be transfered to the next year as a result of the rainfall-delayed response. The results of evaluating the pefformance of the RDR Model was generally satisfactory.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.26-41
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• 2016

Catchment Hydrologic Cycle Assess Tool (CAT) is a model for hydrologic cycle assessment based on physical parameters. In this study, CAT was applied for short-term runoff simulation and connected with model-independent parameter estimation (PEST) for auto-calibrating parameters. The model performance was compared with HEC-HMS, which is widely used for short-term runoff simulation. The study area is the Pangyo Watershed ($22.9km^2$), which includes the Unjung-Cheon and Geumto-Cheon tributaries of the Tan-Cheon stream. Simulation periods were selected from six rainfall events of a two-year period (2006-2007). For the runoff simulation, CAT was applied using three types of infiltration methods (excess rainfall, Green and Ampt and Horton). Sensitivity analysis was carried out to select the parameters and then CAT was optimized using PEST. The model performance of HEC-HMS and CAT-PEST for the rainfall events were within an acceptable limit with Nash Sutcliffe efficiencies (NSE) of 0.63-0.91 and 0.42-0.93, respectively. The simulation results of HEC-HMS have high accuracy in the case of rainfall events that have a sensitive relationship between initial soil moisture conditions and runoff characteristics. The results of CAT-PEST indicated the possibility of reflecting a real runoff system using various physical parameters.