• Geotechnical Engineering
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• v.6 no.2
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• pp.55-66
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• 1990

Many landslides have been taken place during the wet season in Korea. Rainfall in one of the most significant factors relevant to the landsildes, which cause a great loss of lived and properties every year, However, forecast systems for landslides have not been sufficiently established in Korea. In order to minimize a disaster due to landslides, the relationship between landslides and rainfall was investigated based on meteorological records and landslides occrrence ranging from 1977 to 1987. According to rainfall patterns which cause landslides, such as the daily rainfall on failure day or the cumulative rainfalls before failure day, the area in which landslides were taken place, could be divided into three groups of Middl area, Young- Ho Nam area, and Young-Dong Area. And the frequency of landslides was also dependent on the hourly rainfall intensity. It shows from the analyses that prediction of landslides can be made based on both the cumulative rainfall and the hourly rainfall intensity.

• Water for future
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• v.19 no.1
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• pp.5-15
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• 1986

• Journal of Korea Water Resources Association
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• v.52 no.7
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• pp.451-461
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• 2019

The dam reservoir inflow prediction is utilized to ensure for water supply and prevent future droughts. In this study, we predicted the dam reservoir inflow and analyzed how seasonal weather forecasting affected the accuracy of the inflow for even multi-purpose dams. The hindcast and forecast of GloSea5 from KMA were used as input for rainfall-runoff models. TANK, ABCD, K-DRUM and PRMS models which have individual characteristics were applied to simulate inflow prediction. The dam reservoir inflow prediction was assessed for the periods of 1996~2009 and 2015~2016 for the hindcast and forecast respectively. The results of assessment showed that the inflow prediction was underestimated by comparing with the observed inflow. If rainfall-runoff models were calibrated appropriately, the characteristics of the models were not vital for accuracy of the inflow prediction. However the accuracy of seasonal weather forecasting, especially precipitation data is highly connected to the accuracy of the dam inflow prediction. It is recommended to consider underestimation of the inflow prediction when it is used for operations. Futhermore, for accuracy enhancement of the predicted dam inflow, it is more effective to focus on improving a seasonal weather forecasting rather than a rainfall-runoff model.

• Journal of the Korean Geotechnical Society
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• v.32 no.4
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• pp.15-27
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• 2016

This study was conducted to suggest a landslide triggering rainfall threshold (ID curve) for landslide prediction by considering the effect of antecedent rainfall. 202 rainfall data including domestic landslide and rainfall records were used in this study. In order to consider the effect of antecedent rainfall, rainfall data were analyzed by changing Inter Event Time Definition (IETD) and IETD based ID curve were presented by regression analysis. Compared to the findings of the previous studies, the presented ID curve has a tendency to predict the landslides occurring at a relatively low rainfall intensity. It is shown that the proposed ID curve is appropriate and realistic for predicting landslides through the validation of proposed ID curve using records of landslides in 2014. Based on this analysis, it is found that the longer IETD, the greater the effect of antecedent rainfall, and the steeper the gradient of ID curve. It is also found that the rainfall threshold (intensity) is higher for the short period rainfall and lower for the long period rainfall.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.127-132
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• 2011

In this study, calculation results of sediments yield prediction models were compared with the amount of dredging data for the Inje, Gangwon mountain region of Korea. MSDPM and LADMP were used as a sediments prediction model which was calibrated and modified to calculate the sediments yield of Korean mountain region. Both sediments yield prediction models were modified by using Threshold Maximum Rainfall Intensity and Total Minimum Rainfall Intensity and correction coefficient. After comparing with the amount of dredging, it was found that results of MSDPM is more accurate than the results of LADMP. Difference of results of MSDPM and the amount of dredging is 27.6% and difference of results of LADMP and the amount of dredging is 50.6%. Both sediments yield prediction models which were calibrated in this study can be used to calculate the sediments yield for the Korean mountain region.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.67-74
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• 2024

In this paper, we present a study aimed at analyzing how different rainfall measurement methods affect the performance of reservoir water level predictions. This work is particularly timely given the increasing emphasis on climate change and the sustainable management of water resources. To this end, we have employed rainfall data from ASOS, AWS, and Thiessen Network-based measures provided by the KMA Weather Data Service to train our neural network models for reservoir yield predictions. Our analysis, which encompasses 34 reservoirs in Jeollabuk-do Province, examines how each method contributes to enhancing prediction accuracy. The results reveal that models using rainfall data based on the Thiessen Network's area rainfall ratio yield the highest accuracy. This can be attributed to the method's accounting for precise distances between observation stations, offering a more accurate reflection of the actual rainfall across different regions. These findings underscore the importance of precise regional rainfall data in predicting reservoir yields. Additionally, the paper underscores the significance of meticulous rainfall measurement and data analysis, and discusses the prediction model's potential applications in agriculture, urban planning, and flood management.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.20-25
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• 2012

New Zealand suffers from regular floods, these being the most common source of insurance claims for damage from natural hazard events in the country. This paper describes the origin and distribution of the largest floods in New Zealand, and describes the systems used to monitor and predict floods. In New Zealand, broad-scale heavy rainfall (and flooding), is the result of warm moist air flowing out from the tropics into the mid-latitudes. There is no monsoon in New Zealand. The terrain has a substantial influence on the distribution of rainfall, with the largest annual totals occurring near the South Island's Southern Alps, the highest mountains in the country. The orographic effect here is extreme, with 3km of elevation gained over a 20km distance from the coast. Across New Zealand, short duration high intensity rainfall from thunderstorms also causes flooding in urban areas and small catchments. Forecasts of severe weather are provided by the New Zealand MetService, a Government owned company. MetService uses global weather models and a number of limited-area weather models to provide warnings and data streams of predicted rainfall to local Councils. Flood monitoring, prediction and warning are carried out by 16 local Councils. All Councils collect their own rainfall and river flow data, and a variety of prediction methods are utilized. These range from experienced staff making intuitive decisions based on previous effects of heavy rain, to hydrological models linked to outputs from MetService weather prediction models. No operational hydrological models are linked to weather radar in New Zealand. Councils provide warnings to Civil Defence Emergency Management, and also directly to farmers and other occupiers of flood prone areas. Warnings are distributed by email, text message and automated voice systems. A nation-wide hydrological model is also operated by NIWA, a Government-owned research institute. It is linked to a single high resolution weather model which runs on a super computer. The NIWA model does not provide public forecasts. The rivers with the greatest flood flows are shown, and these are ranked in terms of peak specific discharge. It can be seen that of the largest floods occur on the West Coast of the South Island, and the greatest flows per unit area are also found in this location.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.425-433
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• 2009

Spatial models suitable for describing the evolving random fields in climate and environmental systems have been developed by many researchers. In general, rainfall in South Korea is highly variable in intensity and amount across space. This study characterizes the monthly and regional variation of rainfall fields using the spatial modeling. The main objective of this research is spatial prediction with the Bayesian hierarchical modeling (kriging) in order to further our understanding of water resources over space. We use the Bayesian approach in order to estimate the parameters and produce more reliable prediction. The Bayesian kriging also provides a promising solution for analyzing and predicting rainfall data.

• Atmosphere
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• v.16 no.4
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• pp.319-332
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• 2006

This study examines the capability of the WRF (Weather Research and Forecasting) model in reproducing heavy rainfall that developed over the Korean peninsula on 26-27 June 2005. The model is configured with a triple nesting with the highest horizontal resolution at a 3-km grid, centered at Yang-dong, Gyeonggi-province, which recorded the rainfall amount of 376 mm. In addition to the control experiment employing realistic orography over Korea, two consequent sensitivity experiments with 1) no orography, and 2) no land over Korea were designed to investigate orographic effects on the development of heavy rainfall. The model was integrated for 48 hr, starting at 1200 UTC 25 June 2005. The overall features of the large-scale patterns including a cyclone associated with the heavy rainfall are reasonably reproduced by the control run. The spatial distribution of the simulated rainfall over Korea agreed fairly well with the observed. The amount of predicted maximum rainfall at the 3-km grid is 377 mm, which located about 50 km southeast from the observed point, Yang-Dong, indicating that the WRF model is capable of predicting heavy rainfall over Korea at the cloud resolving resolutions. Further, it was found that the complex orography over the Korean peninsula plays a role in enhancing the rainfall intensity by about 10%. The land-sea contrast over the peninsula was fund to be responsible for additional 10% increase of rainfall amount.

• Journal of Korea Water Resources Association
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• v.40 no.6 s.179
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• pp.447-458
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• 2007

In this study, the coastal urban flood prediction and warning system based on HEC-RAS and SWMM were investigated to evaluate a watershed of On-Cheon stream in Busan which has characteristics of costal area cased by flooding of coastal urban areas. The basis of this study is a selection of various geological data from the numerical map that is a watershed of On-Cheon stream and computation of hydrologic GIS data. Thiessen method was used for analyzing of rainfall on the On-Cheon stream and 6th regression equation, which is Huff's Type II was time-distribution of rainfall. To evaluate the deployment of flood prediction and warning system, risk depth was used on the 3 selected areas. To find the threshold runoff for hydraulic analysis of stream, HEC-RAS was used and flood depth and threshold runoff was considered with the effect of tidal water level. To estimate urban flash flood trigger rainfall, PCSWMM 2002 was introduced for hydrologic analysis. Consequently, not only were the criteria of coastal urban flood prediction and warning system decided on the watershed of On-Cheon stream, but also the deployment flow charts of flood prediction and warning system and operation system was evaluated. This study indicates the criteria of flood prediction and warning system on the coastal areas and modeling methods with application of ArcView GIS, HEC-RAS and SWMM on the basin. For the future, flood prediction and warning system should be considered and developed to various basin cases to reduce natural flood disasters in coastal urban area.