• Journal of Korean Society on Water Environment
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• v.22 no.5
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• pp.856-864
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• 2006

For estimating the minimum discharge to maintain a river, low flow analysis is required and long term runoff records are needed for the analysis. However, runoff data should be estimated to run a hydrologic model for ungaged river basin. For the reason, parameter estimation is crucial to simulate rainfall-runoff events for those basins using Tank model. In this study, only runoff data recorded for dry season are used for parameter estimation, which is different to other methods based on runoff data recorded for wet and dry seasons. The Harmony Search algorithm is used to determine the optimum parameters for Tank model. The coefficient of determination ($R^2$) is served as the objective function in the Harmony Search. In cases that recorded data are insufficient, the recording interval is changed and Empirical CDF is adopted to analyze the estimated parameters. The suggested method is applied to Yongdam dam, Soyanggang dam, Chungju dam and Seomjingang dam basins. As results, the higher $R^2s$ are obtained when the shorter recording interval, the better recorded data quality, and the more rainfall events recorded along with certain rainfall amount is. Moreover, when the total rainfall is higher than the certain amount, $R^2$ is high. Considering the facts found from this study for the low flow analysis, it is possible to estimate the parameters for Tank model properly with the desired confidence level.

• Journal of the Korean GEO-environmental Society
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• v.12 no.8
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• pp.5-12
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• 2011

This study was performed to analyze the degree of rainfalls, the duration time of rainfalls, the inclination of slopes and other damage causes depending on the ground condition, when the landslide occurs by the rainfall. Based on that, a big and a small model soil box were compared to examine the features of landslides, which is ultimately for forecasting landslides. An artificial rainfall device was installed in the model box, and the large model box has a real-size slope in it. Also, various measures were fulfilled such as collapse forms, a pore pressure, an earth pressure and moisture contents in order to analyze the effect of the model box size on the landslide mechanism and to test the usability of a small model box as a material for landslide experiments.

• Journal of Korean Society of Forest Science
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• v.108 no.2
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• pp.208-215
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• 2019

The goal of this study was to analyze the reactivity of a volumetric water content sensor (soil moisture sensor) and tensiometer and to review their use in the early detection of a shallow landslide. We attempted to demonstrate shallow and rapid slope collapses using three different soil ratios under artificial rainfall at 120 mm/h. Our results showed that the measured value of the volumetric water-content sensor converged to 30~37%, and that of the tensiometer reached -3~-5 kPa immediately before the collapse of the soil under all three conditions. Based on these results, we discussed a temporal range for early warnings of landslides using measurements of the volumetric water content sensors installed at the bottom of the soil slope, but could not generalize and clarify the exact timing for these early warnings. Further experiments under various conditions are needed to determine how to use both sensors for the early detection of shallow landslides.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.709-721
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• 2008

This paper is to test the applicability of ModKIMSTORM (Modified KIneMatic Wave STOrm Runoff Model) by applying it to Namgangdam watershed of $2,293km^2$. Model inputs (DEM, land use, soil related information) were prepared in 500 m spatial resolution. Using five typhoon events (Saomi in 2000, Rusa in 2002, Maemi in 2003, Megi in 2004 and Ewiniar in 2006) and two storm events (May of 2003 and July of 2004), the model was calibrated and verified by comparing the simulated streamflow with the observed one at the outlet of the watershed. The Pearson's coefficient of determination $R^2$, Nash and Sutcliffe model efficiency E, the deviation of runoff volumes $D_v$, relative error of the peak runoff rate $EQ_p$, and absolute error of the time to peak runoff $ET_p$ showed the average value of 0.984, 0.981, 3.63%, 0.003, and 0.48 hr for 4 storms calibration and 0.937, 0.895, 8.08%, 0.138, and 0.73 hr for 3 storms verification respectively. Among the model parameters, the stream Manning's roughness coefficient was the most sensitive for peak runoff and the initial soil moisture content was highly sensitive for runoff volume fitting. We could look into the behavior of hyrologic components from the spatial results during the storm periods and get some clue for the watershed management by storms.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.1
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• pp.66-77
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• 2005

We have investigated microclimatic controls on the spatiotemporal variations of net primary production (NPP) of a rugged forested watershed using the process-based biogeochemical model (BIOME-BGC). To validate the model simulation of water and carbon cycles at the plot scale, we have conducted field survey over deciduous broadleaf forest (DBF) and evergreen needleleaf forest (ENF) since 2000. The modeled values of soil temperature, soil moisture and soil respiration showed high correlation with those from the field measurements. The modeled seasonal changes of NPP showed high correlation with air temperature but no significant correlation with water related parameters. The precipitation frequency turned out to be the best climatic factor to explain the annual variation of NPP. Furthermore, NPP of ENF was more sensitive to precipitation frequency than that of DBF. With changes in vegetation cover and topography, the spatial distribution of NPP was of great heterogeneity, which was negatively correlated with the magnitude of NPP. Despite the annual precipitation of 1,400mm, NPP at the study site was constrained by the amount of water available for the vegetation. Such a modeling result should be verified by the field measurements.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.3
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• pp.133-145
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• 2010

This study analyzed the characteristics of sediment produce by landslide triggered by rainfall. One-dimensional unsaturated groundwater model and infinite slope stability analysis were used to estimate the behavior of soil moisture and slope stability according to rainfall, respectively. Slope stability analysis was performed considering on soil depth and characteristics of trees. As the results considering on recovery of the failed slopes, much amount of sediment was produced in 1963, 1970, and 2002. As the results of verification of simulation results using Landsat 5 TM images, we can find differences of landslide location between the results from model and satellite images. These differences can be caused by uncertainties of the rough parameters in the model. However, in the case that Obong-dam basin was divided into two subbasin, Wangsan-chun and Doma-chun basin, the results of each subbasin show errors around 20%. And only 4% of error occurred in the case of comparing landslide area on the entire Obong-dam basin. These errors seem insignificant considering on the errors which can be caused from the analyses in this study such as estimation of sediment produce, soil cover classification, and estimation of landslide area.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.156-169
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• 2015

This study was to evaluate the RCP climate change impact on hydrological components in the Imha-Dam watershed using SWAT(Soil and Water Assessment Tool) Model. The model was calibrated for six year(2002~2007) and validated for six year(2008~2013) using daily observed streamflow data at three watershed stations. The overall simulation results for the total released volume at this point appear reasonable by showing that coefficient of determination($R^2$) were 0.70~0.85 and Nash-Sutcliffe model efficiency(NSE) were 0.67-0.82 for streamflow, respectively. For future hydrologic evaluation, the HadGEM3-RA climate data by scenarios of Representative Concentration Pathway(RCP) 4.5 and 8.5 of the Korea Meteorological Administration were adopted. The biased future data were corrected using 34 years(1980~2013, baseline period) of weather data. Precipitation and temperature showed increase of 10.8% and 4.9%, respectively based on the baseline data. The impacts of future climate change on the evapotranspiration, soil moisture, surface runoff, lateral flow, return flow and streamflow showed changes of +11.2%, +1.9%, +10.0%, +12.1%, +18.2%, and +11.2%, respectively.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.268-275
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• 2005

Early predictions of crop yields call provide information to producers to take advantages of opportunities into market places, to assess national food security, and to provide early food shortage warning. The objectives of this study were to identify the most useful parameters for estimating yields and to compare two model selection methods for finding the 'best' model developed by multiple linear regression. This research was conducted in two 65ha corn/soybean rotation fields located in east central South Dakota. Data used to develop models were small temporal variability information (STVI: elevation, apparent electrical conductivity $(EC_a)$, slope), large temporal variability information (LTVI : inorganic N, Olsen P, soil moisture), and remote sensing information (green, red, and NIR bands and normalized difference vegetation index (NDVI), green normalized difference vegetation index (GDVI)). Second order Akaike's Information Criterion (AICc) and Stepwise multiple regression were used to develop the best-fitting equations in each system (information groups). The models with $\Delta_i\leq2$ were selected and 22 and 37 models were selected at Moody and Brookings, respectively. Based on the results, the most useful variables to estimate corn yield were different in each field. Elevation and $EC_a$ were consistently the most useful variables in both fields and most of the systems. Model selection was different in each field. Different number of variables were selected in different fields. These results might be contributed to different landscapes and management histories of the study fields. The most common variables selected by AICc and Stepwise were different. In validation, Stepwise was slightly better than AICc at Moody and at Brookings AICc was slightly better than Stepwise. Results suggest that the Alec approach can be used to identify the most useful information and select the 'best' yield models for production fields.

• Journal of Korean Society of Disaster and Security
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• v.10 no.1
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• pp.19-27
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• 2017

In recent years, ground subsidence has been frequently occurred by underground cavities due to the excessive groundwater inflow, caused by poor construction and management, during tunnel excavation and underground structure construction. In this study, a numerical model (SEEFLOW3D) was developed to estimate groundwater fluctuations for saturated-unsaturated poros media, evaluates the impact on ground excavation with open cut and non-open cut scenarios. In addition, the visual MODFLOW was applied to demonstrate the verification of the model compared with both results. Our results indicated that the RMSE and NRMSE was obtained to range over -3.95~5.7% and 0.56~4.62%, respectively. The developed model was expected to estimate groundwater discharges and apply analysis tool for optimum design of waterproof wall in future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4B
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• pp.337-346
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• 2010

Climate change has a huge impact on various parts of the world. This study quantified and analyzed the effects on hydrological behavior caused by climate, vegetation canopy and land use change of Soyanggang dam watershed (2,694.4 $km^2$) using the semi-distributed model SWAT (Soil Water Assessment Tool). For the 1997-2006 daily dam inflow data, the model was calibrated with the Nash-Sutcliffe model efficiencies between the range of 0.45 and 0.91. For the future climate change projection, three GCMs of MIROC3.2hires, ECHAM5-OM, and HadCM3 were used. The A2, A1B and B1 emission scenarios of IPCC (Intergovernmental Panel on Climate Change) were adopted. The data was corrected for each bias and downscaled by Change Factor (CF) method using 30 years (1977-2006, baseline period) weather data and 20C3M (20th Century Climate Coupled Model). Three periods of data; 2010-2039 (2020s), 2040-2069 (2050s), 2070-2099 (2080s) were prepared for future evaluation. The future annual temperature and precipitation were predicted to change from +2.0 to $+6.3^{\circ}C$ and from -20.4 to 32.3% respectively. Seasonal temperature change increased in all scenarios except for winter period of HadCM3. The precipitation of winter and spring increased while it decreased for summer and fall for all GCMs. Future land use and vegetation canopy condition were predicted by CA-Markov technique and MODIS LAI versus temperature regression respectively. The future hydrological evaluation showed that the annual evapotranspiration increases up to 30.1%, and the groundwater recharge and soil moisture decreases up to 55.4% and 32.4% respectively compared to 2000 condition. Dam inflow was predicted to change from -38.6 to 29.5%. For all scenarios, the fall dam inflow, soil moisture and groundwater recharge were predicted to decrease. The seasonal vapotranspiration was predicted to increase up to 64.2% for all seasons except for HadCM3 winter.