• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.39-39
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• 2012

Data assimilation techniques have received growing attention due to their capability to improve prediction in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modelling software are based on a deterministic approach. In this study, we developed a hydrological modelling framework for sequential data assimilation, namely MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modelling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. In this software framework, sequential data assimilation based on the particle filters is available for any hydrologic models considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and radar rainfall estimates is assessed simultaneously in sequential data assimilation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.431-436
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• 2008

Recently, the rapid development of GIS technology has made it possible to handle a various data associated with spatially hydrological parameters with their attribute information. Therefore, there has been a shift in focus from lumped runoff models to distributed runoff models, as the latter can consider temporal and spatial variations of discharge. In this research, a distributed rainfall-runoff model based on physical kinematic wave for analysis of surface and river flow was used to simulate temporal and spatial distribution of long-term discharge. The snowfall and melting process model based on Hydro-BEAM was developed, and various hydrological parameters for input data of the model was extracted from basic GIS data such as DEM, land cover and soil map. The developed model was applied for the Shonai River basin(532) in Japan, which has sufficient meteorological and hydrological data, and displayed precise runoff results to be compared to the hydrograph.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.1
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• pp.27-38
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• 2012

This study is to analyse the hydrological behavior of agricultural reservoir using CAT (Catchment hydrologic cycle Assessment Tool). The CAT is a water cycle analysis model in order to quantitatively assess the characteristics of the short/long-term changes in watershed. It supports the effective design of water cycle improvement facilities by supplementing the strengths and weaknesses of existing conceptual parameter-based lumped hydrologic models and physical parameter-based distributed hydrologic models. The CAT especially supports the analysis of runoff processes in paddy fields and reservoirs. To evaluate the impact of agricultural reservoir operation and irrigation water supply on long-term rainfall-runoff process, the CAT was applied to Idong experimental catchment, operated for research on the rural catchment characteristics and accumulated long term data by hydrological observation equipments since 2000. From the results of the main control points, Idong, Yongdeok and Misan reservoirs, the daily water levels of those points are consistent well with observed water levels, and the Nash-Sutcliffe model efficiencies were 0.32~0.89 (2001~2007) and correlation coefficients were 0.73~0.98.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.181-181
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• 2017

Low impact development (LID) practices has become important to mitigate the damage from natural disasters in urban areas. Thereby many hydrological simulation models can simulate the hydrological impact of LID practices. However, commonly used models are not able to provide specific information to most users such as where LIDs should be placed and what kind of LID should be designed. In this study, a decision support system which can be used with the EPA's SWMM was developed for the determination of LID types and locations of LID practices, named Water Management Prioritization Module (WMPM), was applied to a urbanized university campus. Eight sub-catchments were selected as feasible candidate areas for the planning of LID practices. Pre-designated infiltration trenches and permeable pavements were applied to each selected sub-catchments, followed by peak and total runoffs comparison between before/after planning of LIDs. Moreover, TOPSIS, one of a multi-criteria decision analysis method was used in the procedure of selecting target sub-catchment areas and final prioritization of LID types and locations. As a result, sub-catchments S4 with permeable pavements and S16 with infiltration trenches has shown the most decrease in total and peak runoffs, respectively. Therefore, WMPM was found to be effective in determining the best alternative among various scenarios generated and simulated.

• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.139-153
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• 2017

The variation in runoff due to global climate change and urbanization should be identified quantitatively because these two factors have been significantly accelerated during the last three decades in South Korea. However, only a few research to analyze the impacts due to two factors over different time scales can be found. Therefore, in this study, the hydrological model based approach and the hydrological sensitivity approach were used to separate relative impacts by two factors on monthly, seasonal, and annual time scales at the Soyang River upper basin and the Seom River basin in South Korea. The 3 techniques such as the double mass curve method, the Pettitt's test, and the BCP analysis were performed to detect change point occurred by abrupt change in the collected observed runoff. After detection of change ponts, SWAT models calibrated on the natural periods were used to calculate the changes due to human activities. Also, 6 Budyko based methods were auxiliary to verify the results from hydrological based approach.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.236-241
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• 2023

Water quality problems in rivers, lakes, and estuaries have become serious in Korea. In order to overcome eutrophication of freshwater lakes and river basins, systematic management of water quality is necessary. To manage water quality in freshwater lakes and basins, apply hydrological models suitable for the basin and water quality models such as rivers and lakes to reduce water pollution based on the prediction results of these models. Improvement measures must be presented. In order to apply appropriate water pollution improvement measures in the watershed, accurate pollution sources must be identified and pollution loads must be predicted and presented. Based on GIS, the connection between the pollutant database and the hydrological and water quality prediction model will be integrated based on spatial location, making it possible to provide systematic support to improve watershed water quality by comprehensively including the water quality modeling process. In this paper, in order to accurately predict water pollution in freshwater lakes and river basins, a water quality model system is established using GIS-based spatial information to present a comprehensive water quality management method for freshwater lake basins in the future, and to systematically manage pollution sources through water quality modeling. This study was conducted to easily and efficiently operate hydrological and water quality models using automated spatial information.

• KCID journal
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• v.14 no.2
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• pp.225-235
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• 2007

The shape of streamflow hydrograph during the early period of spring is very much controlled by the area and depth of snow cover especially in mountainous area. When we simulate the streamfolw of a watershed snowmelt, we need some information for snow cover extent and depth distribution as parameters and input data in the hydrological models. The purpose of this study is to suggest an extraction method of snow cover area and snow depth distribution using Terra MODIS image. Snow cover extent for South Korea was extracted for the period of December 2000 and April 2006. For the snow cover area, the snow depth was interpolated using the snow depth data from 69 meteorological observation stations. With these data, it is necessary to run a hydrological model considering the snow-related data and compare the simulated streamflow with the observed data and check the applicability for the snowmelt simulation.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.226-226
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• 2015

The complex climate system regarding human actions is well represented through global climate models (GCMs). The output from GCMs provides useful information about the rate and magnitude of future climate change. Especially, the temperature variable is most reliable among other GCM outputs. However, hydrological variables (e.g. precipitation) from GCM outputs for future climate change contain too high uncertainty to use in practice. Therefore, we propose a method that simulates temperature variable with increasing in a certain level (e.g. 0.5oC or 1.0oC increase) as a global warming scenario from observed data. In addition, a hydrometeorological variable can be simulated employing block-wise sampling technique associated with the temperature simulation. The proposed method was tested for assessing the future change of the seasonal precipitation in South Korea under global warming scenario. The results illustrate that the proposed method is a good alternative to levy the variation of hydrological variables under global warming condition.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.149-153
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• 2009

Physics-based distributed rainfall-runoff models are now commonly used in a variety of hydrologic applications such as to estimate flooding, water pollutant transport, sedimentation yield and so on. Moreover, it is not surprising that GIS has become an integral part of hydrologic research since this technology offers abundant information about spatial heterogeneity for both model parameters and input data that control hydrological processes. This study presents the development of a distributed rainfall-runoff prediction system for the Guem river basin ($9,835km^2$) using an Object-oriented Hydrological Modeling System (OHyMoS). We developed three types of element modules: Slope Runoff Module (SRM), Channel Routing Module (CRM), and Dam Reservoir Module (DRM) and then incorporated them systemically into a catchment modeling system under the OHyMoS. The study basin delineated by the 250m DEM (resampled from SRTM90) was divided into 14 midsize catchments and 80 sub-catchments where correspond to the WAMIS digital map. Each sub-catchment was represented by rectangular slope and channel components; water flows among these components were simulated by both SRM and CRM. In addition, outflows of two multi-purpose dams: Yongdam and Daechung dams were calculated by DRM reflecting decision makers' opinions. Therefore, the Guem river basin rainfall-runoff modeling system can provide not only each sub-catchment outflow but also dam inand outflow at one hour (or less) time step such that users can obtain comprehensive hydrological information readily for the effective and efficient flood control during a flood season.

• Korean Journal of Remote Sensing
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• v.18 no.1
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• pp.1-12
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• 2002

Landslide prediction modeling has been regarded as one of the important environmental applications in GIS. While, landslide stability in a certain area as collateral process for prediction modeling can be characterized by DEM-based hydrological features such as flow-direction, flow-accumulation, flow-length, wetness index, and so forth. In this study, Slope-Area plot methodology followed by stability index mapping with these hydrological variables is firstly performed for stability analysis with actual landslide occurrences at Boeun area, Korea, and then Landslide prediction modeling based on likelihood ratio model for landslide potential mapping is carried out; in addition, KOMPSAT EOC imagery is used to detect the locations and scalped scale of Landslide occurrences. These two tasks are independently processed for preparation of unbiased criteria, and then results of those are qualitatively compared. As results of this case study, land stability analysis based on DEM-based hydrological variables directly reflects terrain characteristics; however, the results in the form of land stability map by landslide prediction model are not fully matched with those of hydrologic landslide analysis due to the heuristic scheme based on location of existed landslide occurrences within prediction approach, especially zones of not-investigated occurrences. Therefore, it is expected that the resets on the space-robustness of landslide prediction models in conjunction with DEM-based landslide stability analysis can be effectively utilized to search out unrevealed or hidden landslide occurrences.