In this study, South Korea is divided into 5 zones and is studied about the analysis of time-regional distribution of previpitation frequency and rainfall intensity in Korea. In the previpitation frequency analysis, the basic data groups of 39 stations were selected. The diagram of previpitation frequency was drawn, and the time-regional distribution of precipitation frequency was analized. In the rainfall intensity analysis, the basic data groups of 36 stations were selected. The probable rainfall, I-D-F curve, and regression equation between 24hr. and 10min.-18hr. areal depth were obtained. The results of this study are following; 1) The precipitation class of max. recurrence probability in every season except summer was commonly (1) 1-5mm, (2) 0.1-1mm, (3) 5-10mm in order. 2) The zone of max. recurrence frequency owing to the precipitation class was zone II in precipitation frequency of below 20mm, zone IV in precipitation frequency of 30-40mm, zone I in precipitation frequency of above 70mm for a year. 3) The recurrence probability of precipitation in Korea can be represented to the equation of exponential function; $$W(x)=e^{\alpha+\beta}$$ 4) The first and third zones were expected heavy rain for the short and long duration. 5) The I.D.F. curves were drawn, and established that the time interval for the least deviation of I.D.F curve is 10~40min., 40min. -4hr., 4~24hr. 6) The regression equations of areal mean depth between 24hr. and 10min.-18hr. for each zone were obtained. 7)The probable rainfall of 36 points were calculated.
Seo, Jungho;Shin, Hongjoon;Ahn, Hyunjun;Heo, Jun-Haeng
Journal of Korea Water Resources Association
/
v.50
no.3
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pp.211-221
/
2017
In statistical hydrology, various extreme distributions such as the generalized extreme value (GEV), generalized logistic (GLO) and Gumbel (GUM) models have been widely used to analyze the extreme events. In the case of rainfall events in South Korea, the GEV and Gumbel distributions are known to be appropriate among various extreme distribution models. However, the proper probability distribution model may be different depending on the type of extreme events, rainfall duration, region, and statistical characteristics of extreme events. In this regard, it is necessary to apply a wide range of statistical properties that can be represented by the distribution model because it has two shape parameters. In this study, the statistical applicability of rainfall data is analyzed using the Burr XII distribution and the dimensionless L-moment ratio for 620 stations in South Korea. For this purpose, L-skewness and L-kurtosis of the Burr XII distribution are derived and L-moment ratio diagram is drawn and then the applicability of 620 stations was analyzed. As a result, it is found that the Burr XII distribution for the stations of the Han River basin in which L-skewness is relatively larger than L-kurtosis is appropriate, It is possibility of replacing the distribution of commonly used Gumbel or GEV distributions. Therefore, the Burr XII model can be replaced as an appropriate probability model in this basin.
Seven heavy metal concentrations (As, Cd, Cr, Cu, Ni, Pb, Zn) were continuously analyzed for twenty rainfall events in 2017~2018 in an urban basin. The overall and dynamic correlations between runoff characteristics and heavy metal concentrations were examined. The peak metal concentration generally appeared in the initial runoff but found to be delayed when the rainfall intensity was low. The rainfall duration had no relationship with either heavy metal concentrations or their total mass. Dynamics of heavy metal mass (load), with the exception of Cu and Zn, showed strong correlation with the 30 minute rainfall intensity (0.60~0.88) and runoff volume (0.74~0.89). While event mean concentration (EMC) showed positive correlation (0.54~0.73) with antecedent dry days (ADD), no significant relationship was found between runoff volume and pollutant concentration. This implies that the pollutants built up on the surface during dry days are washed off even with low rainfall energy. The dynamics of heavy metal and TSS concentrations showed good correlation (0.68~0.87). This result shows that the metals are transported along with solid particles as adsorbate in surface runoff. Regular street sweeping will reduce significant amount of heavy metal loads in urban surface runoff.
In this study, to determine the optimal order of the full-logged I-D-F polynomial equation, which is mainly used to calculate the probable rainfall over a temporal rainfall duration, the probable rainfall was calculated and the regression coefficients of the full-logged I-D-F polynomial equation was estimated. The optimal variable of the polynomial equation for each station was selected using a stepwise selection method, and statistical significance tests were performed through ANOVA. Using these results, the statistically appropriately calculated rainfall intensity equation for each station was presented. As a result of analyzing the variable selection outputs of the full-logged I-D-F polynomial equation at 9 stations in Gyeongbuk, the 1st to 3rd order equations at 6 stations and the incomplete 3rd order at 1 station were determined as the optimal equations. Since the 1st order equation is similar to the Sherman type equation and the 2nd order one is similar to the general type equation, it was presented as a unified form of rainfall intensity equation for convenience of use by increasing the number of independent variables. Therefore, it is judged that there is no statistical problem in considering only the 3rd order polynomial regression equation for the full-logged I-D-F.
At the mudstone slope located on the roadside of the Seokri area in Donghae-myeon, Pohang, Gyeongsangbuk-do, this study was performed to analyze the effects of rainfall on the stability of slope through seepage analysis according to the precipitation type of the mudstone slope, referring to the actual case of slope failure. For this, precise geological survey, geophysical exploration and drilling survey for the slope where the failure occurred were performed and followed by analysis of detailed soil layer. For the section where failure surface located, the durability reduction of rocks was measured through slaking/swelling tests and the permeability was measured through in-situ permeability tests for each soil layer. In addition, the change of strength parameter and process of instability were analyzed by back analysis, using Talren 97 and Slope/W programs, in the slope. By applying different precipitation conditions to the geographical conditions of the slope that had actual failure records, the slope stability was analyzed by seepage analysis according to duration of rainfall and rise of groundwater level resulting from the flow of rainfall caused by development of geological structures and the slope surface condition.
KSCE Journal of Civil and Environmental Engineering Research
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v.29
no.1B
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pp.23-33
/
2009
Climate change, abnormal weather, and unprecedented extreme weather events have appeared globally. Interest in their size, frequency, and changes in spatial distribution has been heightened. However, the events do not display regional or regular patterns or cycles. Therefore, it is difficult to carry out quantified evaluation of their frequency and tendency. For more objective evaluation of extreme weather events, this study proposed a rainfall extreme weather index (STARDEX, 2005). To compare the present and future spatio-temporal distribution of extreme weather events, each index was calculated from the past data collected from 66 observation points nationwide operated by Korea Meteorological Administration (KMA). Tendencies up to now have been analyzed. Then, using SRES B2 scenario and 2045s (2031-2050) data from YONU CGCM simulation were used to compute differences among each of future extreme weather event indices and their tendencies were spatially expressed.The results shows increased rainfall tendency in the East-West inland direction during the summer. In autumn, rainfall tendency increased in some parts of Gangwon-do and the south coast. In the meanwhile, the analysis of the duration of prolonged dry period, which can be contrasted with the occurrence of rainfall or its concentration, showed that the dryness tendency was more pronounced in autumn rather than summer. Geographically, the tendency was more remarkable in Jeju-do and areas near coastal areas.
Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.
In this study, we proposed a new concept termed the Secondary Peak Constant (SPC) and discerned the temporal characteristics of independent rainstorm events based on unit time and SPC about 24 observation stations in Seoul. Utilizing rainfall observations from 2000 to 2022, independent rainstorm events discreted from rainfall data per unit time. The temporal characteristics of these events were derived according to unit time, and temporal characteristics of the peak rainfall were identified through the SPC. Finally, the temporal characteristics of independent rainstorm events were examined distinctively when analyzed by unit time and SPC. Independent rainstorm events with smaller unit time showed significantly larger total rainfall, rainfall duration, and rainfall intensity. The temporal characteristics of the largest peak rainfall (1st Peak) within independent rainstorm events followed a sequence of Q4>Q2>Q3>Q1. Additionally, the 2nd Peak rainfall predominantly occurred the location where the 1st Peak appeared. The proportion of independent rainstorm events with multiple peak rainfalls exceeded 50.0% when the SPC was 0.7 or lower. The average number of peak rainfalls within independent rainstorm events ranged from 1.5 to 3.4. This study identified the temporal characteristics of independent rainstorm events based on unit time. Then, the peak rainfall of temporal characteristics was quantified by SPC on this study. Hence, it is evident that the temporal characteristics of independent rainstorm events for specific area can be anlayzed and quantified based on unit time and SPC.
Kim, Dong Young;Yoon, Chun Gyeong;Rhee, Han Pil;Choi, Jae Ho;Hwang, Ha Sun
Journal of Korean Society on Water Environment
/
v.35
no.6
/
pp.497-509
/
2019
After the Total Maximum Daily Loads(TMDLs) was applied, it became beyond the limit of concentration management. However, it does not adequately reflect the characteristics of various watersheds, and causes problems with local governments because of the standard flow set. Thus, in this study, the Han River system is organized into four groups in estimating the Pollution Contribution by applying the Flow Duration Curve(FDC) created by the daily flow of data from the HSPF. And the method of this study is expected to be valuable as basic data for the TMDLs. As a result, Group I contains the main watersheds with no large hydraulic structures and tributary watersheds. There is no specificity in the FDC and the Pollution Contribution is estimated as rainfall runoff. Group II contains watersheds near the city where the FDC is maintained above a certain level during the Low Flow Conditions and the Pollution Contribution is estimated as the discharge flow of large scale point pollution facilities. Group III contains the main watersheds in which the large hydraulic structures are installed and FDC is curved in the Low Flow Conditions. So the Pollution Contribution is estimated as the water quality of the large hydraulic structures. Group IV contains the upstream in mainstream watersheds in which the large hydraulic structures are installed and the FDC is disabled before the Low Flow Conditions. As the flow is concentrated in the High Flow Conditions, the non-point pollution sources are estimated as the Pollution Contribution.
In this study, the separation of short and long durations for estimation the parameters of IDF curve is suggested by using Multi-Objective Genetic Algorithm (MOGA). Objective functions are to minimize root mean squared error (RMSE) and relative RMSE between observed and computed values. The criteria for separation are two; the first one is to estimate more precisely the parameters of IDF curve and the second is to make a single IDF curve without non-continuous duration point. For this purpose 22 rainfall recording gauges operated by Korea Meteorological Administration are selected and three IDF curves that are used generally in South Korea are tested. The result shows that the IDF curve developed by Heo et al. (1999) would be the best of three tested IDF curves, and the suggested parameter estimation method using MOGA can compute more reliable parameters compared with empirical regression analysis.
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