• KIEAE Journal
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• v.15 no.5
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• pp.5-12
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• 2015

Purpose: Retention and infiltration of small and frequently-occurring rainfall by LID facilities account for a large proportion of the annual precipitation volume. Based on 4 standard facilities such as Porous Pavement, Infiltration Trench, Cylindrical Infiltration Well, Rectangular Infiltration Well by Seoul Metropolitan Handbook of the Prior Consultation for LID. The total retention volume of each facility was calculated according to the type and size. The Purpose of this study is to find out the quantitative relationship between Percentile Rainfall Event and Design Volume of Infiltration Facilities. Methode: For the estimation of Percentile Rainfall Event, Daily Precipitation of Seoul from 2005 to 2014 was sorted ascending and the distribution of percentile was estimated by PERCENTILE spreadsheet function. The managed Rainfall Depth and Percentile of each facility was calculated at the several sizes. In response to the rainwater charge volume of 5.5mm/hr by the Category "Private large site", the 3 types of facilities were planned for example. The calculated Rainfall Depth and Percentile were 54.4mm and 90% by the use of developed Calculation-Module based on the Spreadsheet program. Result: With this Module the existing Designed Infiltration volume which was introduced from Japan was simply converted to the Percentile-Rainfall-Event used in USA.

• Journal of Korean Society on Water Environment
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• v.33 no.3
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• pp.256-272
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• 2017

Extreme rainfall has become more frequent over the Korean peninsula in recent years, causing serious damages. In a changing climate, traditional approaches based on historical records of rainfall and on the stationary assumption can be inadequate and lead to overestimate (or underestimate) the design rainfalls. A main objective of this study is to develop a stochastic disaggregation method of seasonal rainfall to hourly extreme rainfall, and offer a way to derive the nonstationary IDF curves. In this study, we propose a novel approach based on a Four-Parameter Beta (4P-beta) distribution to estimate the nonstationary IDF curves conditioned on the observed (or simulated) seasonal rainfall, which becomes the time-varying upper bound of the 4P beta distribution. Moreover, this study employed a Bayesian framework that provides a better way to take into account the uncertainty in the model parameters. The proposed model showed a comparable design rainfall to that of GEV distribution under the stationary assumption. As a nonstationary rainfall frequency model, the proposed model can effectively translate the seasonal variation into the sub-daily extreme rainfall.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1619-1624
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• 2007

The rainfall frequency estimations are critical in the design of hydraulic structures (such as bridges and culverts) to ensure that they are built economically and safely. In other words, they are not over designed or under designed. However one of the main assumptions in the creation of these analysis is that the rainfall data for a site is stationary. That is, climatic trends and variability in a region have negligible effects on the curves. But as has been proved in recent history, climatic variability and trends do exist and their effects on precipitation have not been negligible. Increasing occurrences of the El Nino phenomenon have lead to droughts and floods around the world, and long term trends in rainfall, both increases and decreases, have been seen in all regions across Korea. The purpose of this paper is to investigate and evaluate impacts of ENSO on rainfall characteries and rainfall frequency estimations in Korea. In this paper, The available rainfall data were categorized into Warm(EL Nino), Cold(La Nina), Normal episodes based on the Cold & Warm Episodes by Season then 50 years of daily rainfall data were generated for each episodic events(EL Nino, La Nina)

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.424-424
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• 2017

Several studies of the world have analyzed the regional rainfall trends in large data sets. However, it reported that the long-term behavior of rainfall was different on spatial and temporal scales. The objective of this study is to determine the local trends of rainfall indices in the Yom River Basin, Thailand. The rainfall indices consist of the annual total precipitation (PRCTPOP), number of heavy rainfall days ($R_{10}$), number of very heavy rainfall days ($R_{20}$), consecutive of dry days (CDD), consecutive of wet days (CWD), daily maximum rainfall ($R_{x1}$), five-days maximum rainfall ($R_{x5}$), and total of annual rainy day ($R_{annual}$). The rainfall data from twelve hydrological stations during the period 1965-2015 were used to analysis rainfall trend. The Mann-Kendall test, which is non-parametric test was adopted to detect trend at 95 percent confident level. The results of these data were found that there is only one station an increasing significantly trend in PRCTPOP index. CWD, which the index is expresses longest annual wet days, was exhibited significant negative trend in three locations. Meanwhile, the significant positive trend of CDD that represents longest annual dry spell was exhibited four locations. Three out of thirteen stations had significant decreasing trend in $R_{annual}$ index. In contrast, there is a station statistically significant increasing trend. The analysis of $R_{x1}$ was showed a station significant decreasing trend at located in the middle of basin, while the $R_{x5}$ of the most locations an insignificant decreasing trend. The heavy rainfall index indicated significant decreasing trend in two rainfall stations, whereas was not notice the increase or decrease trends in very heavy rainfall index. The results of this study suggest that the trend signal in the Yom River Basin in the half twentieth century showed the decreasing tendency in both of intensity and frequency of rainfall.

• Journal of Korea Water Resources Association
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• v.41 no.9
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• pp.959-967
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• 2008

Disaggregation techniques are widely used to transform observed daily rainfall values into hourly ones, which serve as important inputs for flood forecasting purposes. However, an important limitation with most of the existing disaggregation techniques is that they treat the rainfall process as a realization of a stochastic process, thus raising questions on the lack of connection between the structure of the models on one hand and the underlying physics of the rainfall process on the other. The present study introduces a nonlinear deterministic (and specifically chaotic) framework to study the dynamic characteristics of rainfall distributions across different temporal scales (i.e. weights between scales), and thus the possibility of rainfall disaggregation. Rainfall data from the Seoul station (recorded by the Korea Meteorological Administration) are considered for the present investigation, and weights between only successively doubled resolutions (i.e., 24-hr to 12-hr, 12-hr to 6-hr, 6-hr to 3-hr) are analyzed. The correlation dimension method is employed to investigate the presence of chaotic behavior in the time series of weights, and a local approximation technique is employed for rainfall disaggregation. The results indicate the presence of chaotic behavior in the dynamics of weights between the successively doubled scales studied. The modeled (disaggregated) rainfall values are found to be in good agreement with the observed ones in their overall matching (e.g. correlation coefficient and low mean square error). While the general trend (rainfall amount and time of occurrence) is clearly captured, an underestimation of the maximum values are found.

• Journal of the Korean Geotechnical Society
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• v.36 no.5
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• pp.5-16
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• 2020

The purpose of this study is to suggest the management criteria through the decision tree analysis for a seepage, which is an important instrumentation type of the fill dam. In the case of the seepage of the dam in Korea, seepage can be increased rapidly because rainfall directly flow into the downstream slope and abutment of dam during rainfalls. Therefore, it is necessary the management criteria for the seepage of the fill dam in consideration of rainfall. In this study, decision tree analysis was performed for a fill dam in Korea by setting the seepage as the response variable and the rainfall and water level of dam as explanatory variables. As the study results, the water level acted as an explanatory variable from the conditions under daily rainfall of 34.75 mm/day, and the branch conditions of the water level were analyzed to be 37.4 m and 35.23 m. 98% of the rainfall data is distributed under the conditions of the daily rainfall of 34.75 mm/day, and coverage of the seepage is indicated from 13.25 L/min to 24.24 L/min. When the rainfall and water level as the influence factors for the seepage were selected, the influence of the rainfall was dominant. Finally, the seepage of fill dam by considering the rainfall and water level was suggested as a management criteria.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.70-82
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• 2020

Recently, a lot of damages have been caused by urban flooding, and heavy rainfall that temporarily occur are the main causes of these phenomenons. The damages caused by urban flooding are identified as the change in the water balance in urban areas. To indirectly identify it, this research analyzed the change in the remote sensing indices on each land cover before and after heavy rainfall by utilizing daily precipitation data and multi-temporal Sentinel-2 satellite imagery. Cases of heavy rain advisory and warning were selected based on the daily precipitation data. And statistical fluctuation were compared by acquiring Sentinel-2 satellite images during the corresponding period and producing them as NDVI, NDWI and NDMI images about each land cover with a radius of 1,000 m based on the Seoul Weather Station. As a result of analyzing the maximum value, minimum value, mean and fluctuation of the pixels that were calculated in each remote sensing index image, there was no significant changes in the remote sensing indices in urban areas before and after heavy rainfall.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.16-16
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• 2011

Statistics of extreme rainfall play a vital role in engineering practice from the perspective of mitigation and protection of infrastructure and human life from flooding. While flood frequency assessments, based on river flood flow data are preferred, the analysis of rainfall data is often more convenient due to the finer spatial nature of rainfall recording networks, often with longer records, and potentially more easily transferable from site to site. The rainfall frequency analysis as a design tool has developed over the years in New Zealand from Seelye's daily rainfall frequency maps in 1947 to Thompson's web based tool in 2010. This paper will present a history of the development of New Zealand rainfall frequency analysis methods, and the details of the latest method, so that comparisons may in future be made with the development of Korean methods. One of the main findings in the development of methods was new knowledge on the distribution of New Zealand rainfall extremes. The High Intensity Rainfall Design System (HIRDS.V3) method (Thompson, 2011) is based upon a regional rainfall frequency analysis with the following assumptions: $\bullet$ An "index flood" rainfall regional frequency method, using the median annual maximum rainfall as the indexing variable. $\bullet$ A regional dimensionless growth curve based on the Generalised Extreme Value (GEV), and using goodness of fit test for the GEV, Gumbel (EV1), and Generalised Logistic (GLO) distributions. $\bullet$ Mapping of median annual maximum rainfall and parameters of the regional growth curves, using thin-plate smoothing splines, a $2km\times2km$ grid, L moments statistics, 10 durations from 10 minutes to 72 hours, and a maximum Average Recurrence Interval of 100 years.

• Journal of Wetlands Research
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• v.10 no.2
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• pp.143-153
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• 2008

The purpose of this paper is to evaluate impacts of ENSO on frequency and spatial distribution of rainfall in South Korea. In this paper, First, rainfall data in 60 climate stations were categorized into Warm(El Nino), Cold(La Nina), Normal episodes based on the Cold & Warm Episodes by Season, then 100 years of daily rainfall data were generated for each episodic events(El Nino, La Nina, Normal) using Markov Chain model. Finally, Estimating frequency based flood and comparison for each episodes were conducted. From the results, it shows that there are significant changes in the rainfall frequency and the spatial distribution of rainfall among Warm(EL Nino), Cold(La Nina) and Normal episodes.

• Journal of Korea Water Resources Association
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• v.42 no.11
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• pp.933-951
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• 2009

Climate change of global warming may affect the water circulation in Korea. Rainfall is occurred with complex of multiple climatic indices. Therefore, the rainfall is one of the most significant index due to climate change in the process of water circulation. In this research, multiple time series data of rainfall events were extracted to represent the rainfall characteristics. In addition, the occurrence of rainfall time series analyzed by annual, seasonal and monthly data. Analysis method used change analysis of mean and standard deviation and trend analysis. Also, changes in rainfall characteristics and the relative error was calculated during the last 10 years for comparison with past data. At the results, significant statistical results weren't showed by randomness of rainfall data. However, amount of rainfall generally increased last 10 years, and number of raining days had trend of decrease. In addition, seasonal and monthly changes in the rainfall characteristics can be found to appear differently.