• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2B
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• pp.141-153
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• 2009

The occurrence causes of the extreme rainfall to happen in Korea can be distinguished with the typhoons and local downpours. The typhoon events attacked irregularly to induce the heavy rainfall, and the local downpour events mean a seasonal rain front and a local rainfall. Almost every year, the typhoons and local downpours that induced a heavy precipitation be generated extreme disasters like a flooding. Consequently, in this research, There were distinguished the causes of heavy rainfall events with the typhoons and the local downpours at Korea. Also, probability precipitation was computed according to the causes of the local downpour events. An evaluation of local downpours can be used for analysis of heavy rainfall event in short period like a flash flood. The methods of calculation of probability precipitation used the parametric frequency analysis and the Empirical Simulation Technique (EST). The correlation analysis was computed between annual maximum precipitation by local downpour events and sea surface temperature, moisture index for composition of input vectors. At the results of correlation analysis, there were revealed that the relations closely between annual maximum precipitation and sea surface temperature. Also, probability precipitation using EST are bigger than probability precipitation of frequency analysis on west-middle areas in Korea. Therefore, region of west-middle in Korea should prepare the extreme precipitation by local downpour events.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.215-224
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• 2008

The effect of streamflow considering future land use change and vegetation index information by climate change scenario was assessed using SLURP (Semi-distributed Land-Use Runoff Process) model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for the upstream watershed ($260.4km^2$) of Gyeongan water level gauging station. By applying CA-Markov technique, the future land uses (2030, 2060, 2090) were predicted after test the comparison of 2004 Landsat land use and 2004 CA-Markov land use by 1996 and 2000 land use data. The future land use showed a tendency that the forest and paddy decreased while urban, grassland and bareground increased. The future vegetation indices (2030, 2060, 2090) were estimated by the equation of linear regression between monthly NDVI of NOAA AVHRR images and monthly mean temperature of 5 years (1998-2002). Using CCCma CGCM2 simulation result based on SRES A2 and B2 scenario (2030s, 2060s, 2090s) of IPCC and data were downscaled by Stochastic Spatio-Temporal Random Cascade Model (SST-RCM) technique, the model showed that the future runoff ratio was predicted from 13% to 34% while the runoff ratio of 1999-2002 was 59%. On the other hand, the impact on runoff ratio by land use change showed about 0.1% to 1% increase.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.69-78
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• 2006

The rainfall depth-area-duration analysis which is used to characterize precipitation extremes for specification of so-called design storms, provides a basis for evaluation of drought severity when storm depth is replaced by an appropriate measure of drought severity. So we propose a method for constructing drought severity-area-duration curves in this study. Monthly precipitation data over the whole Korea are used to compute SPI. Such SPIs are abstracted to several independent spatial components from EOF analysis. Using Kriging method, these spatial components are used to constitute grid-based SPI data set over the whole Korea including Jeju island with $6km{\times}6km$ resolution. After identifying main drought events, the drought severity-area-duration curves for these events over 32-year period of record are finally constructed. As a result, such curves show the similar shape with storm-based curves in the sense that the drought severity (or rainfall depth) is inversely proportional to drought area from the curves, but drought-based curves are different from storm-based curves in the sense that the drought severity decreasing rate with respect to drought area is much less than depth decreasing rate.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4B
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• pp.413-427
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• 2010

Urbanization means the sudden increment of a population and the industrialization. The hydrologic water cycle causes many changes due to urbanization. Therefore, the affects that urbanization influences on the precipitation events were analyzed. But the precipitation events are very much influenced many meteorological and climatologically indices besides the effect of an urbanization. So, an analysis was performed by using precipitation data observed in many spots of the Korean peninsula. The analysis data are annual precipitation, the duration 1 daily maximum amount of precipitation, the rainy days, and 10 mm over the rainy days, and 80 mm. seasonal precipitation and seasonal rainy days. The analytical method classified 4 clusters in which the precipitation characteristic is similar through the cluster analysis. It compared and analyzed precipitation events of the urban and rural stations. Moreover, the representative rainfall stations were selected and the urban stations and rural stations were compared. In the analyzed result, the increment of the rainy days was conspicuous over 80mm in which it can cause the heavy rainfall. By using time precipitation data, the design precipitation was calculated. Rainfall events over probability precipitation on duration and return period were analyzed. The times in which it exceeds the probability precipitation in which the urban area is used for the hydrologic structure design in comparison with the rural area more was very much exposed to increase.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.497-507
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• 2010

Climate changes affect greatly natural ecosystem, human social and economic system acting on constituting the climate system such as air, ocean, life, glacier and land, etc. and estimating the current impact of climate change would be the most important thing to adapt to the climate changes. This study set the target area to Nakdong river watershed and investigated the impact of climate changes through analyzing precipitation tendency, and to understand the impact of climate changes on hydrological elements, analyzed elasticity of precipitation-streamflow. For the analysis of precipitation trend, collecting the precipitation data of the National Weather Service from major points of Nakdong river watershed, resampling them at the units of year, season and month, used as the data of precipitation trend analysis. To analyze precipitation-streamflow elasticity, collecting area average precipitation and long-term streamflow data provided by WAMIS, annual and seasonal time-series were analyzed. In addition, The results of this study and elasticity, and other abroad study compared with the elasticity analysis and the validity of this study was verified. Results of this study will be able to be utilized for study on a plan to increase of flood control ability of flooding constructs caused by the increase of streamflow around Nakdong river watershed due to climate changes and on a plan of adapting to water environment according to climate changes.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.509-520
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• 2023

Various drought indices are widely used for assessing drought conditions which are affected by many factors such as precipitation, soil moisture, and runoff. The values of drought indices varies depending on hydro-meteorological data and calculation formulas, and the judgment of the drought condition may also vary. This study selected four calculation components such as precipitation data length, accumulation period, probability distribution function, and parameter estimation method as the sources of uncertainty in the calculation of standardized precipitation index (SPI), and evaluated their contributions to the uncertainty using root mean square error (RMSE) and linear mixed model (LMM). The RMSE estimated the overall errors in the SPI calculation, and the LMM was used to quantify the uncertainty contribution of each factor. The results showed that as the accumulation period increased and the data period extended, the RMSEs decreased. The comparison of relative uncertainty using LMM indicated that the sample size had the greatest impact on the SPI calculation. In addition, as sample size increased, the relative uncertainty related to the sample size used for SPI calculation decreased and the relative uncertainty associated with accumulation period and parameter estimation increased. In conclusion, to reduce the uncertainty in the SPI calculation, it is essential to collect long-term data first, followed by the appropriate selection of probability distribution models and parameter estimation methods that represent well the data characteristics.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.599-608
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• 2023

The increasing interest in soil moisture data using satellite data for applications of hydrology, meteorology, and agriculture has led to the development of methods for generating soil moisture maps of variable resolution. This study demonstrated the capability of generating soil moisture maps using Sentinel-1 and Sentinel-2 data provided by Google Earth Engine (GEE). The soil moisture map was derived using synthetic aperture radar (SAR) image and optical image. SAR data provided by the Sentinel-1 analysis ready data in GEE was applied with normalized difference vegetation index (NDVI) based on Sentinel-2 and Environmental Systems Research Institute (ESRI)-based Land Cover map. This study produced a soil moisture map in the research area of Victoria, Australia and compared it with field measurements obtained from a previous study. As for the validation of the applied method's result accuracy, the comparative experimental results showed a meaningful range of consistency as 4-10%p between the values obtained using the algorithm applied in this study and the field-based ones, and they also showed very high consistency with satellite-based soil moisture data as 0.5-2%p. Therefore, public open data provided by GEE and the algorithm applied in this study can be used for high-resolution soil moisture mapping to represent regional land surface characteristics.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1125-1134
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• 2023

Out of the total 17,000 reservoirs in Korea, 13,600 small agricultural reservoirs do not have hydrological measurement facilities, making it difficult to predict water storage volume and appropriate operation. This paper examined univariate and multivariate long short-term memory (LSTM) modeling to predict the storage rate of agricultural reservoirs using remote sensing and artificial intelligence. The univariate LSTM model used only water storage rate as an explanatory variable, and the multivariate LSTM model added n-day accumulative precipitation and date of year (DOY) as explanatory variables. They were trained using eight years data (2013 to 2020) for Idong Reservoir, and the predictions of the daily water storage in 2021 were validated for accuracy assessment. The univariate showed the root-mean square error (RMSE) of 1.04%, 2.52%, and 4.18% for the one, three, and five-day predictions. The multivariate model showed the RMSE 0.98%, 1.95%, and 2.76% for the one, three, and five-day predictions. In addition to the time-series storage rate, DOY and daily and 5-day cumulative precipitation variables were more significant than others for the daily model, which means that the temporal range of the impacts of precipitation on the everyday water storage rate was approximately five days.

• Journal of the Korean GEO-environmental Society
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• v.24 no.12
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• pp.31-38
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• 2023

In this study, runoff characteristics analysis was conducted as a basic research to establish a forecasting and warning system for flood risk areas in small mountainous basins in South Korea. The Danyang 1 Bridge basin located in Danyang-gun, Chungcheongbuk-do was selected as the study basin, and the watershed characteristic factors were calculated using Q-GIS based on the digital elevation model (DEM) of the basin. In addition, nine heavy rainfall events were selected from 2020 to 2023 using hydrometeorological data provided by the National Water Resources Management Comprehensive Information System. HEC-HMS rainfall-runoff model was used to analyze the runoff characteristics of small mountainous basins, and rainfall-runoff model simulation was performed by reflecting 9 heavy rainfall events and calculated basin characteristic factors. Based on the rainfall-runoff model, parameter optimization was performed for six heavy rain events with large error rates among the simulated events, and the appropriate parameter range for the Danyang 1 Bridge basin, a small mountainous basin, was calculated to be 0.8 to 3.4. The results of this study will be utilized as foundational data for establishing flood forecasting and warning systems in small mountainous basin, and further research will be conducted to derive the range of parameters according to basin characteristics.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.45-58
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• 2024

Drought risk is expected to increase as the frequency, intensity, and duration of droughts increase due to climate change. Drought risk is related to not only hydro-meteorological factors, but also water supply and demand. Recently, along with climate change, socioeconomic factors have also been recognized to increase drought risk. Therefore, it is necessary to outlook the drought risk considering various conditions for coping with future extreme droughts in a timely manner. In addition, considering various drought scenarios help reduce the uncertainty in future drought outlook. In this study, drought scenarios considering climate change scenarios, population, and water demand were created to outlook drought risk for 160 administrative districts in Korea, then new levels of drought risk were assigned based on the results of drought risk outlook to suggest drought management measures. The results showed that the drought risk will increase in the future in 2020, 2025, and 2030, compared to past. Especially the drought risk is likely twice as high in 2030 under the baseline and high scenarios. Applying the drought outlook results from this study to the new methodology for setting the risk levels shows that most regions are in Response (V) in 2020 and 2030 for baseline and high scenarios.