• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.1
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• pp.117-133
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• 2014

In this study, we analysed impacts of the recent increasing trend of exceedance rainfall thresholds for separation of data set and different research periods using Quantile Regression (QR) approach. And also we performed significant test for time series data using linear regression, Mann-Kendall test and Sen test over the Korean major 8-city. Spring and summer precipitation was tend to significant increase, fall and winter precipitation was tend to decrease, and heavy rainy days in last 30 years have increased from 3.1 to 15 percent average. In addition, according to the annual ranking of rainfall occurs Top $10^{th}$ percentile of precipitation for 3IQR (inter quartile range) of the increasing trend, most of the precipitation at the point of increasing trend was confirmed. Quantile 90% percentile of the average rainfall 43.5mm, the increasing trend 0.1412mm/yr, Quantile 99% percentile of the average rainfall 68.0mm, the increasing trend in the 0.1314mm/yr were analyzed. The results can be used to analyze the recent increasing trend for the annual maximum value series information and the threshold extreme hydrologic information. And also can be used as a basis data for hydraulic structures design on reflect recent changes in climate characteristics.

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.815-826
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• 2012

The underestimating trend using existing ordinary regression (OR) based trend analysis has been a well-known problem. The existing OR method based on least squares approximate the conditional mean of the response variable given certain values of the time t, and the usual assumption of the OR method is normality, that is the distribution of data are not dissimilar form a normal distribution. In this regard, this study proposed a quantile regression that aims at estimating either the conditional median or other quantiles of the response variable. This study assess trend in annual daily maximum rainfall series over 64 weather stations through both in OR and QR approach. The QR method indicates that 47 stations out of 67 weather stations are a strong upward trend at 5% significance level while OR method identifies a significant trend only at 13 stations. This is mainly because the OR method is estimating the condition mean of the response variable. Unlike the OR method, the QR method allows us flexibly to detect the trends since the OR is designed to estimate conditional quantiles of the response variable. The proposed QR method can be effectively applied to estimate hydrologic trend for either non-normal data or skewed data.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.43-54
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• 2018

The accurate estimation of reference crop evapotranspiration ($ET_o$) is essential in irrigation water management to assess the time-dependent status of crop water use and irrigation scheduling. The importance of $ET_o$ has resulted in many direct and indirect methods to approximate its value and include pan evaporation, meteorological-based estimations, lysimetry, soil moisture depletion, and soil water balance equations. Artificial neural networks (ANNs) have been intensively implemented for process-based hydrologic modeling due to their superior performance using nonlinear modeling, pattern recognition, and classification. This study adapted two well-known ANN algorithms, Backpropagation neural network (BPNN) and Generalized regression neural network (GRNN), to evaluate their capability to accurately predict $ET_o$ using daily meteorological data. All data were obtained from two automated weather stations (Chupungryeong and Jangsu) located in the Yeongdong-gun (2002-2017) and Jangsu-gun (1988-2017), respectively. Daily $ET_o$ was calculated using the Penman-Monteith equation as the benchmark method. These calculated values of $ET_o$ and corresponding meteorological data were separated into training, validation and test datasets. The performance of each ANN algorithm was evaluated against $ET_o$ calculated from the benchmark method and multiple linear regression (MLR) model. The overall results showed that the BPNN algorithm performed best followed by the MLR and GRNN in a statistical sense and this could contribute to provide valuable information to farmers, water managers and policy makers for effective agricultural water governance.

• Journal of the Korean Geophysical Society
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• v.9 no.4
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• pp.321-331
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• 2006

Recently, runoff characteristics of urban area are changing because of the increase of impervious area by rapidly increasing of population and industrialization, urbanization. It needs to extract the accurate topologic and hydrologic parameters of watershed in order to manage water resource efficiently. Thus, this study developed more precise input data and more improved parameter estimating procedures using GIS(Geographic Information System) and GA(Genetic Algorithm). For these purposes, XP-SWMM (EXPert-Storm Water Management Model) was used to simulate the urban runoff. The model was applied to An-Yang stream basin that is a typical Korean urban stream basin with several tributaries. The rules for parameter estimation were composed and applied based on quantity parameters that are investigated through the sensitivity analysis. GA algorithm is composed of these rules and facts. The conditions of urban flows are simulated using the rainfall-runoff data of the study area. The data of area, slope, width of each subcatchment and length, slope of each stream reach were acquired from topographic maps, and imperviousness rate, land use types, infiltration capacities of each subcatchment from land use maps, soil maps using GIS. Also we gave the management scheme of urbanization runoff using XP-SWMM. The parameters are estimated by GA from sensitivity analysis which is performed to analyze the runoff parameters.

• Journal of Korea Water Resources Association
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• v.44 no.12
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• pp.929-940
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• 2011

In this study, the future expected discharges are analyzed for Daecheong and Yongdam Dam Watershed in Geum River watershed using A1B scenario based RCM with 27 km spatial resolutions from Korea Meteorological Agency and SWAT model. The direct use of GCM and RCM data for water resources impact assessment is practically hard because the spatial and temporal scales are different. In this study, the problems of spatial and temporal scales were settled by the spatial and temporal downscaling from watershed scale to weather station scale and from monthly to daily of RCM grid data. To generate the detailed hydrologic scenarios of the watershed scale, the multi-site non-stationary downscaling method was used to examine the fluctuations of rainfall events according to the future climate change with considerations of non-stationary. The similarity between simulation and observation results of inflows and discharges at the Yongdam Dam and Daecheong Dam was respectively 90.1% and 84.3% which shows a good agreement with observed data using SWAT model from 2001 to 2006. The analysis period of climate change was selected for 80 years from 2011 to 2090 and the discharges are increased 6% in periods of 2011~2030. The seasonal patterns of discharges will be different from the present precipitation patterns because the simulated discharge of summer was decreased and the discharge of fall was increased.

• Journal of Korea Water Resources Association
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• v.48 no.11
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• pp.937-944
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• 2015

This study proposed a novel technique, namely the Radar Polygon Method (RPM), for areal rainfall estimation based on radar precipitation data. The RPM algorithm has the following steps: 1. Determine a map of the similar rainfall occurrence of which each grid cell contains the binary information on whether the grid cell rainfall is similar to that of the observation gage; 2. Determine the similar rainfall probability map for each gage of which each grid cell contains the probability of having the rainfall similar to that of the observation gage; 3. Determine the governing territory of each gage by comparing the probability maps of the gages. RPM method was applied to the Anseong stream basin. Radar Polygons and Thiessen Polygons of the study area were similar to each other with the difference between the two being greater for the rain gage highly influenced by the orography. However, the weight factor between the two were similar with each other. The significance of this study is to pioneer a new application field of radar rainfall data that has been limited due to short observation period and low accuracy.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.2 s.25
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• pp.13-24
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• 2007

This study is to derive the rainfall intensity formula based on the representative probability distribution using multivariate analysis in Korea. The annual maximum rainfall data at 57 stations having more than 30years long records were used for 12 durations(10min, 1, 2, 3, 4, 5, 6, 8, 10, 12, 18, 24hr). 50 rainfall characteristics elements are analyzed from the collected data. The widely used 14 probability distributions are applied to the basic data in hydrologic frequency analysis. The homogeneous tests(principal component and cluster analysis) are applied to find the rainfall homogeneity. The results of this study are as followings; (1) The homogeneous test shows that there is no appropriate representative distribution for the whole duration in Korea. But hydrological homogeneous regions of point rainfall could be divided by 5 regions. (2) The GEV distribution for zones I, III, IV, V and the Gumbel distribution for zone II are determined as the representative probability distribution. (3) Comparative analysis of the results shows that the probable rainfalls of representative zones are different from those of existing researches. (4) Rainfall intensity formulas are determined on the basis of the linearization technique for the probable rainfall.

• Economic and Environmental Geology
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• v.42 no.4
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• pp.343-356
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• 2009

SCS method was applied to make the assessments of direct runoff according to land use changes in Jeju island. Land uses were obtained from 5 year-period remote sensing time series data from 1975 to 2000 which are provided by Water Management Information System (WAMIS). Hydrologic soil groups were categorized based on soil series of National Academy of Agricultural Sciences (NAAS), and permeable geologic structures such as Sumgol, Gotzawal and so on. The land uses of Jeju island are obviously characterized by urban-agricultural areas increases, and forest areas decrease. According to land use changes, curve number (CN) for Jeju island was consistently increased from 65.3 in 1975 to 69.6 in 2000. From 1975 to 2000, the amount of direct runoff and ratios increased due to CN changes. When the rainfall data in 1995 was applied to each year, the direct runoff amounts were $299.0{\sim}351.6\;mm$, and runoff ratios were $15.1{\sim}17.7%$. In the case of the application of the rainfall data in 2000, the direct runoff amounts were $136.9{\sim}161.5\;mm$, and runoff ratios were $9.7{\sim}11.5%$. Since direct runoff can be closely related to groundwater recharge and sustainable groundwater yield, the groundwater influence caused by land use changes or district exploitations should be considered for the reasonable water management and development in Jeju island.

• Korean Journal of Ecology and Environment
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• v.35 no.2 s.98
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• pp.79-91
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• 2002

A time variable modeling study was performed for seasonal variations of vertical temperature profiles in the Okjung Lake located in upstream of the Sumjin River. Based on the model structure of the US Army Corps of Engineer's CE-QUAL-W2, the lake was divided into 3 branches, 50 longitudinal segments and 49 vertical layers and vertical profiles of water temperature and current velocity were simulated over one year. The model results were calibrated and verified against vertical profiles of water temperature measured every month from March 1998 to February 1999 at 5 different locations. The model results showed a good agreement with the field measurements. The hydrologic balance during this period was validated by comparing the simulated values of surface elevation level with the measured data. There was some discrepancy in July data between the model results and the fleld measurements. This could be attributed partially to the inadequacy of the model to the highly hydrodynamic nature of water body and partially to the lack of accuracy in local atmospheric temperature data during summer monsoon period. The model results have shown that there was no seasonal over-turn in most part of the Okjung Lake, where water temperature maintained above $4^{\circ}C$ over one year. In the upstream shal-low area (depth<20 meter), however, temperature at surface layer fell below $4^{\circ}C$ and water was frozen such that slight over-turn would occur during winter period. From this study, we concluded that the Okjung Lake is oligomictic. This conclusionis significantly different from the general pattern that the lakes located from $20^{\circ}C$ to $40^{\circ}C$ latitude would be warm monomictic. From the examination of simulated current velocity distribution, it was found that the upstream inflows would infiltrate into mesolimnion of the lake during hydrodynamic summer monsoon periods due to the thermal density of water.

• Journal of Korea Water Resources Association
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• v.47 no.5
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• pp.435-446
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• 2014

Various drought indices developed from previous studies can not consider the inherent uncertainty of drought because they assess droughts using a pre-defined threshold. In this study, to consider inherent uncertainty embedded in monthly streamflow data, Hidden Markov Model (HMM) based drought index (HMDI) was proposed and then probabilistic assessment of hydrologic drought was performed using HMDI instead of using pre-defined threshold. Using monthly streamflow data (1966~2009) of Pyeongchang river and Upper Namhan river provided by Water Management Information System (WAMIS), applying the HMM after moving-averaging the data with 3, 6, 12 month windows, this study calculated the posterior probability of hidden state that becomes the HMDI. For verifying the method, this study compared the HMDI and Standardized Streamflow Index (SSI) which is one of drought indices using a pre-defined threshold. When using the SSI, only one value can be used as a criterion to determine the drought severity. However, the HMDI can classify the drought condition considering inherent uncertainty in observations and show the probability of each drought condition at a particular point in time. In addition, the comparison results based on actual drought events occurred near the basin indicated that the HMDI outperformed the SSI to represent the drought events.