• Journal of Korea Water Resources Association
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• v.43 no.11
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• pp.995-1009
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• 2010

Accelerated soil erosion due to extreme climate change, such as increased rainfall intensity, and human-induced environmental changes, is a widely recognized problem. Existing soil erosion models are generally based on the gross erosion concept to compute annual upland soil loss in tons per acre per year. However, such models are not suitable for event-based simulations of erosion and deposition in time and space. Recent advances in computer geographic information system (GIS) technologies have allowed hydrologists to develop physically based models, and the trend in erosion prediction is towards process-based models, instead of conceptually lumped models. This study aims to propose an effective and robust distributed rainfall-sediment yield-runoff model consisting of basic element modules: a rainfall-runoff module based on the kinematic wave method for subsurface and surface flow, and a runoff-sediment yield-runoff model based on the unit stream power method. The model was tested on the Cheoncheon catchment, upstream of the Yongdam dam using hydrological data for three extreme flood events due to typhoons. The model provided acceptable simulation results with respect to both discharge and sediment discharge even though the simulated sedigraphs were underestimated, compared to observations. The spatial distribution of erosion and deposition demonstrated that eroded sediment loads were deposited in the cells along the channel network, which have a short overland flow length and a gentle local slope while the erosion rate increased as rainfall became larger. Additionally, spatially heterogeneous rainfall intensity, dependant on Thiessen polygons, led to spatially-distinct erosion and deposition patterns.

• Journal of Korea Water Resources Association
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• v.41 no.10
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• pp.995-1007
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• 2008

Studies on modeling the rainfall-runoff relationship which shows nonlinear trend strongly use artificial neural networks theory not only for the prediction but also for the characteristics analysis of the data used by pattern classification. For the pattern classification, the results from Self-Organizing Map (SOM) mention that the map size and array for the SOM training have significantly influenced on the SOM performance. Since there is no deterministic method or theoretical equation to determine the number of rows and columns for the map size, hexagonal array is generally used for the map array. Therefore, this study present a determination of the optimized map structure for the rainfall-runoff analysis in Naju station considering the map size and array simultaneously which can represent the classified characterization of rainfall-runoff relationship. The result showed that the map size of 20$\times$16 hexagonal array with 8-clustered patterns was selected as an appropriate map structure for rainfall-runoff analysis in Naju station.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.31-31
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• 2023

During December 2022, the northeast monsoon, which dominates the south and the Gulf of Thailand, had significant rainfall that impacted the lower southern region, causing flash floods, landslides, blustery winds, and the river exceeding its bank. The Golok River, located in Narathiwat, divides the border between Thailand and Malaysia was also affected by rainfall. In flood management, instruments for measuring precipitation and water level have become important for assessing and forecasting the trend of situations and areas of risk. However, such regions are international borders, so the installed measuring telemetry system cannot measure the rainfall and water level of the entire area. This study aims to predict 72 hours of water level and evaluate the situation as information to support the government in making water management decisions, publicizing them to relevant agencies, and warning citizens during crisis events. This research is applied to machine learning (ML) for water level prediction of the Golok River, Lan Tu Bridge area, Sungai Golok Subdistrict, Su-ngai Golok District, Narathiwat Province, which is one of the major monitored rivers. The eXtreme Gradient Boosting (XGBoost) algorithm, a tree-based ensemble machine learning algorithm, was exploited to predict hourly water levels through the R programming language. Model training and testing were carried out utilizing observed hourly rainfall from the STH010 station and hourly water level data from the X.119A station between 2020 and 2022 as main prediction inputs. Furthermore, this model applies hourly spatial rainfall forecasting data from Weather Research and Forecasting and Regional Ocean Model System models (WRF-ROMs) provided by Hydro-Informatics Institute (HII) as input, allowing the model to predict the hourly water level in the Golok River. The evaluation of the predicted performances using the statistical performance metrics, delivering an R-square of 0.96 can validate the results as robust forecasting outcomes. The result shows that the predicted water level at the X.119A telemetry station (Golok River) is in a steady decline, which relates to the input data of predicted 72-hour rainfall from WRF-ROMs having decreased. In short, the relationship between input and result can be used to evaluate flood situations. Here, the data is contributed to the Operational support to the Special Water Resources Management Operation Center in Southern Thailand for flood preparedness and response to make intelligent decisions on water management during crisis occurrences, as well as to be prepared and prevent loss and harm to citizens.

• Korean Journal of Agricultural Science
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• v.43 no.4
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• pp.507-521
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• 2016

Landslides are one of the most common natural hazards causing significant damage and casualties every year. In Korea, the increasing trend in landslide occurrence in recent decades, caused by climate change, has set off an alarm for researchers to find more reliable methods for landslide prediction. Therefore, an accurate landslide-susceptibility assessment is fundamental for preventing landslides and minimizing damages. However, analyzing the stability of a natural slope is not an easy task because it depends on numerous factors such as those related to vegetation, soil properties, soil moisture distribution, the amount and duration of rainfall, earthquakes, etc. A variety of different methods and techniques for evaluating landslide susceptibility have been proposed, but up to now no specific method or technique has been accepted as the standard method because it is very difficult to assess different methods with entirely different intrinsic and extrinsic data. Landslide prediction methods can fall into three categories: empirical, statistical, and physical approaches. This paper reviews previous research and surveys three groups of landslide prediction methods.

• Journal of Industrial Technology
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• v.25 no.B
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• pp.19-25
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• 2005

To use land more efficiently under urbanization trend, Kangwon Province often covers open channels of creeks and uses them as parking lots or roads. A covered open channel section tends to form a rectangular culvert. Therefore, a creek with covered open channels can function as a storm drain. At the time of light rainfall, there are no significant differences except water flowing pattern between a creek with a covered open channel and a creek without it. Recently, however, the frequent occurrence of heavy rainfalls limited at a small, definite area has become problematic. When the heavy rainfall causes the carrying capacity of a creek to be exceeded,the creek with covered open channel has a more serious problem than the creek without it has. Therefore, we made an interpretation of data and conducted hydraulic model experiment to come up with economical solution to this problem.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.33-39
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• 2008

Most New Zealanders reside in coastal regions and four of the larger cities are situated on active floodplains. There have been many recent storm events with rainfall AEPs of 1/150 or rarer and there have been recent flood-related disasters. Insurance claim statistics indicate that the frequency of floods is increasing. Such statistics are alarming local government authorities, insurance companies and populations in low-lying areas. The underlying physical and hydrologic causes of the flood disasters are investigated. It is found that the present numbers of rare rainfall events are not unexpected and there does not appear to be any significant trend evident in the occurrence of river floods. What is revealed is that the river floods appear clustered in certain decades. The clusters do not occur at the same times in different parts of the county. Recently there have been more floods in the north of New Zealand which is where more of the population lives. Also, the increase in population has seen more houses built in locations prone to flooding. Thus the increase in flood-related insurance claims is attributed to more people getting in the way of floods, rather than an increase in the number of floods that have occurred.

• Current Research on Agriculture and Life Sciences
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• v.32 no.3
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• pp.135-143
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• 2014

The variability and temporal trends of the annual and seasonal minimum and maximum temperature, rainfall, relative humidity, wind speed, sunshine hours, and runoff were analyzed for 5 major rivers in Korea from 1960 to 2010. A simple regression and non-parametric methods (Mann-Kendall test and Sen's estimator) were used in this study. The analysis results show that the minimum temperature ($T_{min}$) had a higher increasing trend than the maximum temperature ($T_{max}$), and the average temperature increased by about $0.03^{\circ}C\;yr.^{-1}$. The relative humidity and wind speed decreased by $0.02%\;yr^{-1}$ and $0.01m\;s^{-1}yr^{-1}$, respectively. With the exception of the Han River basin, the regression analysis and Mann-Kendall and Sen results failed to detect trends for the runoff and rainfall over the study period. Rapid land use changes were linked to the increase in the runoff in the Han River basin. The sensitivity of the evapotranspiration and ultimately the runoff to the meteorological variables was in the order of relative humidity > sunshine duration > wind speed > $T_{max}$ > $T_{min}$. Future studies should investigate the interaction of the variables analyzed herein, and their relative contributions to the runoff trends.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6B
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• pp.583-596
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• 2006

Evaporation is an essential parameter in Global water-energy cycle and the variability of evaporation affects water resources planning and managements. In this study, the temporal variability of pan evaporation data was analyzed and trend analysis of the data using Mann-Kendall test. The relationships among evaporation and rainfall, air temperature, humidity, cloudness were analyzed. Even though the longterm trends of air temperature and rainfall increases, that of evaporation except Jinju and Yeosoo results decreases as worldwide observations. Results demonstrate that decrease of pan evaporation represents increase of terrestrial evaporation as Brutsaert and Parlange(1998)'s analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1B
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• pp.29-39
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• 2012

Climate change has been obtained researchers' interest, especially in water resources engineering to adjust current conditions to the new circumstance influenced by climate change. In this study, WRF-ARW will be evaluated the capability to estimate distributed precipitation using global weather information instead of the data from rainfall observatory or radar. Cheongmi watershed is selected and adopted to generate a distributed rainfall-runoff model using ModClark. The results from the distributed model with precipitation data from WRF-ARW and the lumped model using observed precipitation data were compared to the observed discharge values. The final results showed that the distributed model, ModClark generated similar pattern of hydrograph to the observations in terms of the time and amount of peak discharge. In addition, the trend of hydrograph from the distributed model presented similar pattern to the observations.

• Journal of Wetlands Research
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• v.13 no.3
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• pp.623-631
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• 2011

In recent decade, the occurrences of typhoon and severe storm events are increasing trend due to the climate change. And the intensity of natural disaster is more and more stronger and the loss of life and damage of property are also increasing. Therefore, this study tried to understand the impact of climate change on urban drainage system for prevention and control of natural disaster and for this, we selected Gyeyang-gu, Incheon city as a study area. We investigated the climate models and scenarios for the selection of proper model and scenario, then we estimated frequency based rainfall in hourly unit considering climate change. The XP-SWMM model was used to estimate the future flood discharge on urban drainage system using the estimated frequency based rainfall. As a result, we have known that the study area will be overflown in the future and so we may need prepare proper measures for the flood prevention and control.