• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.297-297
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• 2019

최근 기후변화로 인해 전 세계적으로 태풍 및 국지성 집중호우로 인한 피해가 급증하고 있으며, 그로 인한 2차 피해인 산사태와 토석류 피해 또한 빈번하게 발생하고 있다. 한국 또한 토석류로 인해 도심지역의 피해가 급증하고 있으며, 많은 인명피해 및 재산피해가 발생하였다. 현재 한국에서는 산림청의 산사태 예보기준 및 기상청의 호우예보 기준을 사용하고 있으나, 토석류에 대한 예보 기준과 시스템은 부재하다. 따라서 본 연구에서는 토석류 예보를 위해 토석류가 발생했던 피해사례 40종을 수집하여 토석류가 발생했던 시점에서의 누적강우와 강우강도를 이용하여 강우경보지수(Rainfall Triggering Index, RTI)를 산정하였다. 또한 RTI를 강우량의 함수인 한계누적강우량(Critical Accumulated Rainfall, Rc)으로 변환하여 토석류 발생위험지역에 거주하는 일반인들이 강우지수에 대한 이해도를 높이고자 하였다. 토석류 예보를 위하여 RTI 10, 70, 90%에 해당하는 한계누적강우량(Rc)을 산정하여 지속시간에 따른 Rc곡선을 작성하였으며 Nomograph를 이용하여 시간에 따른 토석류 예보 단계를 시각적으로 표출하였다. 또한 실제 토석류가 발생했던 인제, 서울, 청주의 사례에 대해 Nomograph를 작성하여 산림청, 기상청의 예보 기준과 비교 분석하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.204-204
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• 2019

국지성 호우의 증가로 인해 도시 지역의 내수침수피해가 빈번하게 발생하고 있다. 특히 배수의 흐름이 집중되는 저지대 지역과 노후화된 하수관거가 설치된 지역에서 특히 피해가 집중되고 있으며, 이는 도로 측면에 설치된 빗물받이와 같은 하수시설에서 원활하게 배수가 되지 않기 때문에 강우 발생시 도로표면에 노면수가 정체되어 피해가 발생하고 있다. 과거 도로 노면의 형상과 강우의 임계 지속시간을 고려한 적정 우수 유출량 산정에 관한 연구가 진행된 바 있으나, 현재 발생하는 국지성 호우의 형태나 강우강도의 변화에 따른 유출량의 변화가 발생하였으며, 도달시간 산정식에 따른 매개변수의 차이와 새로운 도달시간 산정식의 개발로 도달시간의 결과가 크게 차이가 날 수 있다. 따라서 도로의 침수피해를 막고 교통 안정을 유지하기 위해서는 도로 조건을 고려한 도로 입구 및 하수관의 적절한 설계 등 다양한 연구가 주기적으로 이루어져야 한다. 본 연구에서는 강우 유출 모델인 SWMM 모형과 계산식을 이용하여 도로 표면의 폭과 길이, 도로 종횡단의 변화량, 재 산정한 강우강도에 따른 유출량을 계산하였다. 도로 표면의 폭과 길이, 경사를 다양하게 입력하였으며, 또한 각 Case에 따라 최대 유출량을 생성하는 임계지속기간을 결정하고 다양한 도달시간 산정식의 결과와 비교하여 상관관계를 분석하였다. 분석결과 도달시간은 산정식의 매개변수에 따라 차이가 발생하였으며, 도로표면의 길이와 횡단경사에 크게 영향을 받는 것으로 분석되었으며, 횡단경사보다 종단경사가 클 경우 도달시간이 길어져 유량의 집중을 막는 효과가 있는 것으로 나타났다.

• Membrane and Water Treatment
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• v.10 no.1
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• pp.67-74
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• 2019

Apparent changes in the natural hydrologic cycle causing more frequent floods in urban areas and surface water quality impairment have led stormwater management solutions towards the use of green and sustainable practices that aims to replicate pre-urbanization hydrology. Among the widely documented applications are infiltration techniques that temporarily store rainfall runoff while promoting evapotranspiration, groundwater recharge through infiltration, and diffuse pollutant reduction. In this study, a laboratory-scale infiltration device was built to be able to observe and determine the factors affecting flow variations and corresponding solids removal through a series of experiments employing semi-synthetic stormwater runoff. Results reveal that runoff and solids reduction is greatly influenced by the infiltration capability of the underlying soil which is also affected by rainfall intensity and the available depth for water storage. For gravel-filled structures, a depth of at least 1 m and subsoil infiltration rates of not more than 200 mm/h are suggested for optimum volume reduction and pollutant removal. Moreover, it was found that the length of the structure is more critical than the depth for applications in low infiltration soils. These findings provide a contribution to existing guidelines and current understanding in design and applicability of infiltration systems.

• Journal of the Korean Geotechnical Society
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• v.26 no.11
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• pp.75-87
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• 2010

Incessant rainfalls in unsaturated soil raises pore water pressure and drops shear stress. Controlling pore water pressure in unsaturated soil prevents pressure increase and leads to slope stability. Laboratory experiment of pore water absorption in soil tank has been conducted for pore pressure decrease in soil slope under artifical rainfall supplied in varying rainfall indensities. Soil slope failure triggers the deepening of the wetting front to critical depth accompanied by decrease in matric suction induced by water infilteration. This paper addresses an experimental design for absorption pipe to prevent pore pressure increase in unsaturated soil slope from heavy rain. It is expected that absorption pipe will be widely used in unsaturated soil slope to strengthen slope stability.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• KCID journal
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• v.18 no.2
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• pp.87-100
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• 2011

This study is to delineate the watershed hydrological parameters such as area, slope, rain gauge weight, NRCS-CN and time of concentration (Tc) by using the Geographic Information Sytem (GIS) technique, and estimation of design flood for an ungauged watershed. Especially, we attempted to determine the Tc of ungauged watershed and develop simple program using the cell-based algorithm to calculates upstream or downstream flow time along a flow path for each cell. For a $19km^2$ watershed of tributary of Nakdong river (Seupmoon), the parameters including flow direction, flow accumulation, watershed boundary, stream network and Tc map were extracted from 30m Agreeburn DEM (Digital Elevation Model) and landcover map. And NRCS-CN was extracted from 30m landcover map and soil map. Design rainfall estimation for two rainfall gauge which are Sunsan and Jangcheon using FARD2006 that developed by National Institute for Disaster Prevention (NIDP). Using the parameters as input data of HEC-l model, the design flood was estimated by applying Clark unit hydrograph method. The results showed that the design flood of 50 year frequency of this study was $8m^3/sec$ less than that of the previous fundamental plan in 1994. The value difference came from the different application of watershed parameter, different rainfall distribution (Huff quartile vs. Mononobe) and critical durations. We could infer that the GIS-based parameter preparation is more reasonable than the previous hand-made extraction of watershed parameters.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.136-136
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• 2021

In this study, a deep convolutional neural network (DCNN) model is proposed for short-term precipitation forecasting using weather radar-based images. The DCNN model is a combination of convolutional neural networks, autoencoder neural networks, and U-net architecture. The weather radar-based image data used here are retrieved from competition for rainfall forecasting in Korea (AI Contest for Rainfall Prediction of Hydroelectric Dam Using Public Data), organized by Dacon under the sponsorship of the Korean Water Resources Association in October 2020. This data is collected from rainy events during the rainy season (April - October) from 2010 to 2017. These images have undergone a preprocessing step to convert from weather radar data to grayscale image data before they are exploited for the competition. Accordingly, each of these gray images covers a spatial dimension of 120×120 pixels and has a corresponding temporal resolution of 10 minutes. Here, each pixel corresponds to a grid of size 4km×4km. The DCNN model is designed in this study to provide 10-minute predictive images in advance. Then, precipitation information can be obtained from these forecast images through empirical conversion formulas. Model performance is assessed by comparing the Score index, which is defined based on the ratio of MAE (mean absolute error) to CSI (critical success index) values. The competition results have demonstrated the impressive performance of the DCNN model, where the Score value is 0.530 compared to the best value from the competition of 0.500, ranking 16^th out of 463 participating teams. This study's findings exhibit the potential of applying the DCNN model to short-term rainfall prediction using weather radar-based images. As a result, this model can be applied to other areas with different spatiotemporal resolutions.

• Korean Journal of Agricultural Science
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• v.51 no.1
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• pp.79-86
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• 2024

As the frequency and intensity of heavy rains increase, the vulnerability of agriculture to disasters also increases. Consequently, there is a need to improve flood and inundation predictions. To enhance the accuracy of inundation predictions, it is essential to monitor water level and discharge data within agricultural areas. This study was conducted to monitor water levels and rainfall in the Cheongju Sindae area from 2022 to 2023, and the data was utilized as input and validation data for agricultural inundation modeling. Four irrigation drainage canals were installed to a square-shaped concrete structure where the water level gauge is. It was then confirmed that the water level rises with rainfall. The flow velocities were monitored during periods of heavy rainfall. The rating curve, which estimates water level and flow velocity based on observations, was estimated using the software K-HQ. The resulting curve was presented with the Coefficient of Determination (R²). K-HQ was also used to calculate the equation for the rating curve, taking outliers into account at each data point. Outliers were extracted and the rating curve was recalculated. As the coefficient of determination of three out of four stations exceeded 0.95, the estimated rating curve may be considered reliable for discharge estimation. This study provides critical data for enhancing agricultural inundation modeling accuracy and drainage improvement projects.

• Journal of the Korean earth science society
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• v.37 no.7
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• pp.420-433
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• 2016

The purpose of this study is to improve the calibration matrixes of 2-D and 3-D convective rainfall rates (CRR) using the brightness temperature of the infrared $10.8{\mu}m$ channel (IR), the difference of brightness temperatures between infrared $10.8{\mu}m$ and vapor $6.7{\mu}m$ channels (IR-WV), and the normalized reflectance of the visible channel (VIS) from the COMS satellite and rainfall rate from the weather radar for the period of 75 rainy days from April 22, 2011 to October 22, 2011 in Korea. Especially, the rainfall rate data of the weather radar are used to validate the new 2-D and 3-DCRR calibration matrixes suitable for the Korean peninsula for the period of 24 rainy days in 2011. The 2D and 3D calibration matrixes provide the basic and maximum CRR values ($mm\;h^{-1}$) by multiplying the rain probability matrix, which is calculated by using the number of rainy and no-rainy pixels with associated 2-D (IR, IR-WV) and 3-D (IR, IR-WV, VIS) matrixes, by the mean and maximum rainfall rate matrixes, respectively, which is calculated by dividing the accumulated rainfall rate by the number of rainy pixels and by the product of the maximum rain rate for the calibration period by the number of rain occurrences. Finally, new 2-D and 3-D CRR calibration matrixes are obtained experimentally from the regression analysis of both basic and maximum rainfall rate matrixes. As a result, an area of rainfall rate more than 10 mm/h is magnified in the new ones as well as CRR is shown in lower class ranges in matrixes between IR brightness temperature and IR-WV brightness temperature difference than the existing ones. Accuracy and categorical statistics are computed for the data of CRR events occurred during the given period. The mean error (ME), mean absolute error (MAE), and root mean squire error (RMSE) in new 2-D and 3-D CRR calibrations led to smaller than in the existing ones, where false alarm ratio had decreased, probability of detection had increased a bit, and critical success index scores had improved. To take into account the strong rainfall rate in the weather events such as thunderstorms and typhoon, a moisture correction factor is corrected. This factor is defined as the product of the total precipitable waterby the relative humidity (PW RH), a mean value between surface and 500 hPa level, obtained from a numerical model or the COMS retrieval data. In this study, when the IR cloud top brightness temperature is lower than 210 K and the relative humidity is greater than 40%, the moisture correction factor is empirically scaled from 1.0 to 2.0 basing on PW RH values. Consequently, in applying to this factor in new 2D and 2D CRR calibrations, the ME, MAE, and RMSE are smaller than the new ones.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.8
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• pp.549-553
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• 2014

Variation of sewage sludge interface height and flow rate by rainfall were applied to the actual public sewage treatment plant, and the efficiency of sewage treatment was evaluated by measuring $BOD_5$, $COD_{Mn}$, SS, T-N, and T-P. When both flow and interfacial height are increased, the treatment efficiencies in terms of the five water pollutants are decreased. Among them SS is the most critical pollutant in rainfall. When 0.5 Q inflow was applied, the efficiencies were 74.2% at the sludge interface height of 0.5 m, 76.4% at 1.0 m, 70.2% at 1.5 m, and 60.7% at 2.0 m. When 1.0 Q inflow was applied, the efficiencies were 71.7% at the sludge interface height of 0.5 m, 71.9% at 1.0 m, 46.4% at 1.5 m, and -38.0% at 2.0 m. Operation at 2.0 Q~2.0 m and 3.0 Q~1.0 m above the sludge rising phenomenon occurred causing adverse effects on the public bodies. If the flow rate increases, the processing efficiency is reduced from 74.2% to 17.3%, even though the sludge interface height was maintained at 0.5 m, so that the inflow adjustment was most important during rainfall, and the interface height of 1.0 m should be maintained to minimize the adverse effect on public water system.