• Water for future
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• v.4 no.1
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• pp.51-58
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• 1971

Hydrologic data serve as an input to the water resources system. An adequate analysis of hydrologic data is one of the most important steps in the planning of the water resources development program. The natural hydrologic processes, which produce the hydrologic data, are truely 'stochastic' in the sense that natural hydrologic phenomena change with time in accordance with the law of probability as well as with sequential relationship between their occurrences. Therefore, the stochastic approach to the analysis of hydrologic data has become more popular in recent years than the conventional deterministic or probabilistic approach. This paper reviews the mathematical models which can adequately simulate the stochastic behavior of the hydrologic characteristics of a hydrologic system. The actual application of these models in the analysis of hydrologic records(precipipitation and runoff records in particular) is also presented.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.1
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• pp.27-38
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• 2012

This study is to analyse the hydrological behavior of agricultural reservoir using CAT (Catchment hydrologic cycle Assessment Tool). The CAT is a water cycle analysis model in order to quantitatively assess the characteristics of the short/long-term changes in watershed. It supports the effective design of water cycle improvement facilities by supplementing the strengths and weaknesses of existing conceptual parameter-based lumped hydrologic models and physical parameter-based distributed hydrologic models. The CAT especially supports the analysis of runoff processes in paddy fields and reservoirs. To evaluate the impact of agricultural reservoir operation and irrigation water supply on long-term rainfall-runoff process, the CAT was applied to Idong experimental catchment, operated for research on the rural catchment characteristics and accumulated long term data by hydrological observation equipments since 2000. From the results of the main control points, Idong, Yongdeok and Misan reservoirs, the daily water levels of those points are consistent well with observed water levels, and the Nash-Sutcliffe model efficiencies were 0.32~0.89 (2001~2007) and correlation coefficients were 0.73~0.98.

• Water for future
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• v.18 no.2
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• pp.153-161
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• 1985

The methods for hydrologic prediction of streamflows for more efficient and functional operations and automation of the flood warning and forecasting system have been studiedand which have been widely used in the control engineering have been studied and investigated for representation of the dynamic behavior of rainfall-runoff precesses, and formulated into mathematical model form. The applicabilities of the model using the adaptive Kalman filter algorithm to the on-line, real-time prediction of river flows have been worked out. The computer programs in FORTRAN which are developed here can be utilized for more efficient operations and better prediction abilities of flood warning and forecasting systems, and also should be modified for better model performance.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.3
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• pp.41-54
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• 2015

시간-면적 기법을 이용해 유역의 수문과정을 묘사하는 분산형 (distributed) 연속 (continuous) 강우유출모형인 HYSTAR의 거동특성과 주요 매개변수에 대한 민감도를 분석하였다. 유역의 수문조건에 따른 모형거동의 변화를 분석하기 위해 연속되는 4개의 개별 강우사상에 대한 민감도를 조사하고 비교하였다. 또한, 매개변수의 상호작용이 민감도 분석결과에 미치는 영향을 파악하기 위해 두 가지 서로 다른 기법 (one-factor-at-a-time 과 all-factor-at-a-time 방법)을 이용하여 산정된 민감도를 비교하였다. 분석결과, 모형의 직접유출량, 첨두유량 및 도달시간 모의결과는 유출곡선번호 (curve number)에 가장 민감하게 반응하는 것으로 나타났으며, 토양의 깊이, van Genuchten 식의 매개변수, 작물계수에 큰 영향을 받았다. 한편, 모의된 기저유출량은 토양의 깊이를 비롯하여 van Genuchten 식의 매개변수, 작물계수 (crop coefficient), 이방성계수 (anisotropic coefficient), 유출곡선번호의 변화에 민감하였다. 매개변수에 대한 민감도는 분석에 이용된 강우사상에 따라 다르게 나타났으며, 유역의 토양수분조건에 따라 다르게 거동하는 모형의 중요한 특성을 잘 반영하였다. 두 가지 서로 다른 기법을 이용한 민감도 분석결과는 모의된 직접유출량 및 기저유출량의 변화가 매개변수의 상호작용에 의해 제한될 수 있음을 보여 주었다. 본 연구는 HYSTAR 모형의 매개변수에 대한 민감도 분석을 통해서 해당 모형의 거동을 정량적으로 보여주었고, 이를 통해 모형의 건전성 (soundness)을 입증할 수 있는 하나의 근거를 제시하였다. 본 연구결과는 향후 HYSTAR 모형을 이용한 수문분석 시 보정을 위한 매개변수 선정에 활용될 수 있을 것으로 사료된다. 또한, 본 연구결과에서 나타난 민감도의 수문조건 (또는 선정된 강우사상)에 대한 의존성은 연속유출 모형의 민감도 분석을 위한 강우 사상 선정 및 민감도 분석결과의 해석에 유용한 정보를 제공할 수 있을 것으로 기대된다.

• Journal of Korea Water Resources Association
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• v.36 no.6
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• pp.901-910
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• 2003

The hydrologic behavior of paddy field depends largely on the irrigation and levee height management by farmers. The storage and drainage amount of paddy for storm events certainly influences the stream discharge. To understand the paddy storage effect during storm periods, a daily paddy water balance model embedding farmer's water management was developed by using 4 years (1996, 1997, 2001, 2002) field experimental data at 2 locations (Suwon and Yeoju) From the modeling, it was possible to simulate the daily ponding depth of paddy by treating paddy levee height and threshold pending depth indicating irrigation time as 10 days average parameters of the model. The storage amount(306.9 mm to 343.6 mm) showed little deviation to rainfall amount(425.1 mm to 850.8 mm).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.2
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• pp.257-262
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• 2019

In order to investigate hydrological behavior of the east coast snowfall in February 2014, this study analyzed the changes of the hydrological components due to the snowmelt in the Ssangcheon watershed nearby Sokcho city. The temporal changes of hydrological components through snowfall and snowmelt processes were simulated using SWAT-MODFLOW. As a result of the analysis, snow accumulated until February is fully melted from the late March, 2014, and the stream discharge of April is more than doubled compared to the case of not considering snowmelt. The soil moisture also increased by up to 21 % due to the melting and the groundwater level rose by about 40 cm until the end of April. Thus, the heavy snowfall in February 2014 is considered to play an important role in securing water resources in this region.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.137-148
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• 2008

There have been many cases of using wetlands as an alternative in controlling stormwater, treating mining leachate, and agricultural discharge, and so on, recently. The reality is, however, that the wetlands are not properly applicable because of the lack of enough longterm data for wetlands due to the difficulty of long-term monitoring. Therefore, this study tries to analyze the storage of Upo, Mokpo, Sajipo, and Jjokjibeul in Topyeong watershed using SWAT(Soil and Water Assessment Tool) model, one of the long-term runoff hydrologic model, for the purpose of generating the long-term data and analyzing the hydrologic behavior of wetlands based on the generated data. Also, the changes in runoff at the outlet are analyzed after applying the simulation of constructing washland in Topyeong watershed and the storage in Upo is analyzed. The result shows that the runoff at the outlet of the watershed is decreased in rainy season from July to August and increased in dry season from December to February. In addition, the analysis of Upo storage concludes that Upo can be influenced by the construction of the washland. The duration curve of washland is then analyzed in order to evaluate the wetland's sustainability in terms of washland and it appears that the runoff of washland is simulated to be less than that of the existing wetland. Moreover, runoffs of some washlands are simulated to be less even in wet season. These results lead to the fact that there should be further hydrologic management for constructed washland. Then, the changes in loads (TN and TP) because of constructing washland are analyzed. The result shows that the loads are reduced because of the construction. Also, the changes in loads due to the construction of buffer strips are analyzed to compare the load reductions caused by a washland. Finally, REMM model, a riparian management model, is applied to overcome the hydrologic ambiguousness of SWAT model, and then, the SWAT model results are compared to those of REMM.

• Journal of Korea Water Resources Association
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• v.44 no.1
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• pp.51-64
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• 2011

The objective of this study is to develop a continuous rainfall-runoff model for flood prediction on a large-scale basin. For this study, the hourly surface runoff estimation method based on the variable retention parameter and runoff curve number is developed. This model is composed that the soil moisture to continuous rainfall can be simulated with applying the hydrologic components to the continuous equation for soil moisture. The runoff can be simulated by linking the hydrologic components with the storage function model continuously. The runoff simulation to large basins can be performed by using channel storage function model. Nakdong river basin is selected as the study area. The model accuracy is evaluated at the 8 measurement sites during flood season in 2006 (calibration period) and 2007~2008 (verification period). The calibrated model simulations are well fitted to the observations. Nash and Sutcliffe model efficiencies in the calibration and verification periods exist in the range of 0.81 to 0.95 and 0.70 to 0.94, respectively. The behavior of soil moisture depending on the rainfall and the annual loadings of simulated hydrologic components are rational. From this results, continuous rainfall-runoff model developed in this study can be used to predict the discharge on large basins.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.279-289
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• 2006

The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.

• Journal of Environmental Science International
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• v.16 no.4
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• pp.495-503
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• 2007

In this study, we took the geometrical character of the river channel junction and hydrologic conditions as independent variables, and hydraulic behavior characteristics as an independent variable. The result, after multiple analysis was carried out, proved that, except for the generating area of the accelerating zone of velocity the accelerating zone and both the main channel and the tributary zone of stagnation the stagnation zone, there was correlation of over 90%. Also, derived presumed expression of the hydraulic characteristics of the junction was applied to the real natural channel - the river channel of the Guem-ho main channel(the A-yang bridge to the Guem-ho bridge). As the result, it proved that it represented hydraulic characteristics relatively well.