• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.5
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• pp.41-50
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• 2024

An increasing pattern of extreme rainfall recently affected the rural infrastructures with catastrophic damage, especially the overtopping of a fill dam embankment in the Republic of Korea. The overtopping was caused by the sudden increase in reservoir water level over the dam crest level, and it was not easy work to predict a priori because of its non-linear behavior. Fuzzy time series (FTS) is a fuzzy-logic inference procedure and is suited to apply to non-linear prediction methods such as machine learning. This study used the Wangshin reservoir and Goesan-dam cases, which experienced overtopping in 2023 and 2022, respectively. Wangshin Reservoir was a typical agricultural fill dam and needed to stack more available data, with only the daily storage rate (water level) of 7 years, starting on 2 May 2016. Therefore, we used Goesan-dam data to select appropriate variables and compare the analysis result, which was stacked with about 17 years of records. The analyses adapted LSTM to compare with FTS. As a result, the reservoir water level was applied to predict the overtopping water level, and it was shown that the FTS method could predict the actual water levels effectively according to the result of comparison with LSTM. Then, the FTS method was expected to predict reservoir water level a priori to make appropriate countermeasures on overtopping events as one of the alternatives.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.795-805
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• 2021

In this study, after developing an LSTM-based deep learning model for estimating daily runoff in the Soyang River Dam basin, the accuracy of the model for various combinations of model structure and input data was investigated. A model was built based on the database consisting of average daily precipitation, average daily temperature, average daily wind speed (input up to here), and daily average flow rate (output) during the first 12 years (1997.1.1-2008.12.31). The Nash-Sutcliffe Model Efficiency Coefficient (NSE) and RMSE were examined for validation using the flow discharge data of the later 12 years (2009.1.1-2020.12.31). The combination that showed the highest accuracy was the case in which all possible input data (12 years of daily precipitation, weather temperature, wind speed) were used on the LSTM model structure with 64 hidden units. The NSE and RMSE of the verification period were 0.862 and 76.8 m³/s, respectively. When the number of hidden units of LSTM exceeds 500, the performance degradation of the model due to overfitting begins to appear, and when the number of hidden units exceeds 1000, the overfitting problem becomes prominent. A model with very high performance (NSE=0.8~0.84) could be obtained when only 12 years of daily precipitation was used for model training. A model with reasonably high performance (NSE=0.63-0.85) when only one year of input data was used for model training. In particular, an accurate model (NSE=0.85) could be obtained if the one year of training data contains a wide magnitude of flow events such as extreme flow and droughts as well as normal events. If the training data includes both the normal and extreme flow rates, input data that is longer than 5 years did not significantly improve the model performance.

• Journal of Korea Water Resources Association
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• v.53 no.11
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• pp.1039-1047
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• 2020

Atmospheric rivers, which transport large amount of water vapor from mid-latitude to the inland, are an important driving force of water cycle and extreme hydrologic phenomenas. The main objective of this study is to analyze the hydrological impact of the AR landfalls on the Korean Peninsula in 2000 - 2015. The result showed that the AR is closely related to the characteristics of precipitation, water level and runoff in the Korean Peninsula. The landfalls of the AR affected about 57% of annual precipitation on the Korean Peninsula, and had a greatest impact on the summer rainfall. It also affected the water level and runoff at the five major rivers of Korea, and water levels exceeding the thresholds of flood warning were observed when the AR landed. Moreover, it was found that the runoff above the third quartile with AR landfalls. These results suggest that the AR not only has a significant influence on the hydrological characteristics of the Korean Peninsula, but also have a close relationship with the extreme hydrological events like floods. The results of this study are expected to be used as the reference for the analysis of the impact of the AR on the various fields in the Korean Peninsula.

• Journal of Korea Water Resources Association
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• v.49 no.2
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• pp.107-119
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• 2016

Since future climate scenarios indicate that extreme precipitation events will intensity, probable maximum precipitations (PMPs) without being taken climate change into account are very likely to be underestimated. In this study future PMPs in accordance with the variation of future rainfall are estimated. The hydro-meteorologic method is used to calculate PMPs. The orographic transposition factor is applied in place of the conventional terrain impact factor which has been used in previous PMPs estimation reports. Future DADs are indirectly obtained by using bias-correction and moving-averaged changing factor method based on daily precipitation projection under KMA RCM (HEDGEM3-RA) RCP 8.5 climate change scenario. As a result, future PMPs were found to increase and the spatially-averaged annual PMPs increase rate in 4-hour and $25km^2$ was projected to be 3 mm by 2045. In addition, the increased rate of future PMPs is growing increasingly in the future, but it is thought that the uncertainty of estimating PMPs caused by future precipitation projections is also increased in the distant future.

• Journal of Korea Water Resources Association
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• v.46 no.7
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• pp.755-765
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• 2013

This study developed a real-time dam's hydrologic variables prediction model (DHVPM) and evaluated its performance for simulating historical dam inflow and outflow in the Chungju dam basin. The DHVPM consists of the Sejong University River Forecast (SURF) model for hydrologic modeling and an autoreservoir operation method (Auto ROM) for dam operation. SURF model is continuous rainfall-runoff model with data assimilation using an ensemble Kalman filter technique. The four extreme events including the maximum inflow of each year for 2006~2009 were selected to examine the performance of DHVPM. The statistical criteria, the relative error in peak flow, root mean square error, and model efficiency, demonstrated that DHVPM with data assimilation can simulate more close to observed inflow than those with no data assimilation at both 1-hour lead time, except the relative error in peak flow in 2007. Especially, DHVPM with data assimilation until 10-hour lead time reduced the biases of inflow forecast attributed to observed precipitation error. In conclusion, DHVPM with data assimilation can be useful to improve the accuracy of inflow forecast in the basin where real-time observed inflow are available.

• Journal of Wetlands Research
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• v.21 no.4
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• pp.354-364
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• 2019

Sri Lanka is an island nation susceptible to climate-related disasters and extreme weather events. Kurunegala City is the developing capital city of the North-Western Province of Sri Lanka. Changes in rainfall patterns and a steadily increasing annual average temperature amounting to 0.69±0.37℃ were observed in the city area. Generally, urban areas are at risk due to the lack of climate change adaptation provisions incorporated in the development plans. This study was conducted to investigate the characteristics of Krunegala City, Sri Lanka and develop an appropriate climate change adaptation plan for the city. Site investigation and qualitative risk assessment were conducted to devise a plan relevant to the climate change adaptation needs of the city. Qualitative risk analyses revealed that drinking water, water resources, and health and infrastructure risks were among the major concerns in Kurunegala City. Low impact development (LID) technologies were found to be applicable to induce non-point source pollutant reduction, relieve urban heat island phenomenon, and promote sound water circulation systems. These technologies can be effective means of alleviating water shortage and reducing urban temperature. The measures and strategies presented in this study can serve as reference for developing climate change adaptation plans in areas experiencing similar adverse effects of climate change.

• Journal of Korea Water Resources Association
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• v.48 no.6
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• pp.463-477
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• 2015

The recent unusual climate and extreme weather events have frequently given unexpected disaster and damages, facing difficulties in the management of water resources. In particular, climate change could result in intensified typhoons, and this would be the worst case scenario that can happen. The primary objective of this study is to identify the patterns of typhoon-induced precipitation and the associated synoptic pattern. This study focused on analyzing precipitation patterns over the South Korea using historic records as opposed to a specified season or duration, and further investigates the potential connection with heavy rainfall to synoptic patterns. In this study, we used the best track data provided by the Regional Specialized Meteorological Center of Japan for 40 years from 1973 to 2012. The patterns of the typhoon-induced precipitation were categorized into four groups according to a given typhoon track information, and then the associated synoptic climatology patterns were further investigated. The results demonstrate that the typhoon-induced precipitation patterns could be grouped and potentially simulated according to the identified synoptic patterns. Our future work will focus on developing a short-term forecasting model of typhoon-induced precipitation considering the identified climate patterns as inputs.

• Ecology and Resilient Infrastructure
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• v.10 no.4
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• pp.116-124
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• 2023

As the flood damage on small streams increase due to the increase in frequency of extreme climate events, the need to measure hydraulic data of them has increased for disaster risk management. National Disaster Management Institute, Ministry of Interior and Safety develops CADMT, a CCTV-based automatic discharge measurement technology, and operates pilot small streams to verify its performance and develop disaster risk management technology. The research selects two small streams such as the Neungmac and the Jungsunpil streams to develop the Nomograph by using the 4-Parameter Logistic method using only the observed rainfall data from the Automatic Weather System operated by the Korea Meteorological Agency closest to the small streams and discharge data collected by using the CADMT. To evaluate developed Nomograph, the research forecasts floods discharges in each small stream and compares the result with the observed discharges. As a result of the evaluations, the forecasted value is found to represent the observed value well, so if more accurate observed data are collected and the Nomograph based on it is developed in the future, the high-accuracy flood prediction and warning will be possible.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.743-754
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• 2023

The global occurrence of myriad natural disasters and incidents, catalyzed by climate change and extreme meteorological conditions, has engendered substantial human and material losses. International organizations such as the International Charter have established an enduring collaborative framework for real-time coordination to provide high-resolution satellite imagery and geospatial information. These resources are instrumental in the management of large-scale disaster scenarios and the expeditious execution of recovery operations. At the national level, the operational deployment of advanced National Earth Observation Satellites, controlled by National Geographic Information Institute, has not only catalyzed the advancement of geospatial data but has also contributed to the provisioning of damage analysis data for significant domestic and international disaster events. This special edition of the National Disaster Management Research Institute delineates the contemporary landscape of major disaster incidents in the year 2023 and elucidates the strategic blueprint of the government's national disaster safety system reform. Additionally, it encapsulates the most recent research accomplishments in the domains of artificial satellite systems, information and communication technology, and spatial information utilization, which are paramount in the institution's disaster situation management and analysis efforts. Furthermore, the publication encompasses the most recent research findings relevant to data collection, processing, and analysis pertaining to disaster cause and damage extent. These findings are especially pertinent to the institute's on-site investigation initiatives and are informed by cutting-edge technologies, including drone-based mapping and LiDAR observation, as evidenced by a case study involving the 2023 landslide damage resulting from concentrated heavy rainfall.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.721-733
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• 2023

As the frequency of extreme rainfall events increase due to climate change, climate change adaptation measures have been proposed by the central and local governments. In order to reduce flood damage in urban areas, various flood response policies, such as low impact development techniques and enhancement of the capacity of rainwater drainage networks, have been proposed. When these policies are established, regional characteristics and policy-effectiveness from the cost-benefit perspective must be considered for the flood mitigation measures. In this study, capacity enhancement of rainwater pipe networks and low impact development techniques including green roof and permeable pavement techniques are selected. And the flood reduction effect of the target watershed, Gwanak campus of Seoul National University, was analyzed using SWMM model which is an urban runoff simulation model. In addition, along with the quantified urban flooding reduction outputs, construction and operation costs for various policy scenarios were calculated so that cost-benefit analyses were conducted to analyze the effectiveness of the applied policy scenarios. As a result of cost-benefit analysis, a policy that adopts both permeable pavement and rainwater pipe expansion was selected as the best cost-effective scenario for flood mitigation. The research methodology, proposed in this study, is expected to be utilized for decision-making in the planning stage for flood mitigation measures for each region.