• Journal of Wetlands Research
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• v.22 no.1
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• pp.15-23
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• 2020

The purpose of this study is to investigate how the degree of distribution influences the calibration of snow and runoff in distributed hydrological models using a multi-criteria calibration method. The Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) developed by NOAA-National Weather Service (NWS) is employed to estimate optimized parameter sets. We have 3 scenarios depended on the model complexity for estimating best parameter sets: Lumped, Semi-Distributed, and Fully-Distributed. For the case study, the Durango River Basin, Colorado is selected as a study basin to consider both snow and water balance components. This study basin is in the mountainous western U.S. area and consists of 108 Hydrologic Rainfall Analysis Project (HRAP) grid cells. 5 and 13 parameters of snow and water balance models are calibrated with the Multi-Objective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm. Model calibration and validation are conducted on 4km HRAP grids with 5 years (2001-2005) meteorological data and observations. Through case study, we show that snow and streamflow simulations are improved with multiple criteria calibrations without considering model complexity. In particular, we confirm that semi- and fully distributed models are better performances than those of lumped model. In case of lumped model, the Root Mean Square Error (RMSE) values improve by 35% on snow average and 42% on runoff from a priori parameter set through multi-criteria calibrations. On the other hand, the RMSE values are improved by 40% and 43% for snow and runoff on semi- and fully-distributed models.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.21-30
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• 2010

In this paper, the parallel distributed rainfall runoff model(K-DRUM) using MPI(Message Passing Interface) technique was developed to solve the problem of calculation time as it is one of the demerits of the distributed model for performing physical and complicated numerical calculations for large scale watersheds. The K-DRUM model which is based on GIS can simulate temporal and spatial distribution of surface flow and sub-surface flow during flood period, and input parameters of ASCII format as pre-process can be extracted using ArcView. The comparison studies were performed with various domain divisions in Namgang Dam watershed in case of typoon 'Ewiniar' at 2006. The numerical simulation using the cluster system was performed to check a parallelization effectiveness increasing the domain divisions from 1 to 25. As a result, the computer memory size reduced and the calculation time was decreased with increase of divided domains. And also, the tool was suggested in order to decreasing the discharge error on each domain connections. The result shows that the calculation and communication times in each domain have to repeats three times at each time steps in order to minimization of discharge error.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.238-238
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• 2015

There are demands for water environmental analysis of discharge processes in paddy fields, however, it is not fully understood in nutrients discharge process for watershed modeling. As hydrological processes both surface and ground water and agricultural water managements are so complex in paddy fields, the development of lowland paddy fields watershed model is more difficult than upland watershed model. In this research, the improvement of SWAT (Soil and Water Assessment Tool) model for a paddy watershed was conducted. First, modification of surface inundated process was developed in improved pot hole option. Those modification was evaluated by monitoring data. Second, the monitoring data in river and drainage channel in lowland paddy fields from 2012 to 2014 were analyzed to understand discharge characteristics. As a case study, Imbanuma basin, Japan, was chosen as typical land and water use in Asian countries. In this basin, lowland paddy fields are irrigated from river water using small pumps that were located in distribution within the watershed. Daily hydrological fluctuation was too complex to estimate. Then, to understand surface and ground water discharge characteristics in irrigation (Apr-Aug) and non-irrigation (Sep-Mar) period, the water and material balance analysis was conducted. The analysis was composed two parts, watershed and river channel blocks. As results of model simulation, output was satisfactory in NSE, but uncertainty was large. It would be coming from discharge process in return water. The river water and ground water in paddy fields were exchanged each other in 5.7% and 10.8% to river discharge in irrigation and non-irrigation periods, respectively. Through this exchange, nutrient loads were exchanged between river and paddy fields components. It suggested that discharge from paddy fields was not only responded to rainfall but dynamically related with river water table. In general, hydrological models is assumed that a discharge process is one way from watershed to river. However, in lowland paddy fields, discharge process is dynamically changed. This function of paddy fields showed that flood was mitigated and temporally held as storage in ground water. Then, it showed that water quality was changed in mitigated function in the water exchange process in lowland paddy fields. In future, it was expected that hydrological models for lowland paddy fields would be developed with this mitigation function.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.55-64
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• 2008

The evidence of changes in the climate system is obvious in the world. Nevertheless, at the current techniques for flood frequency analysis, the flood distribution can not reflect climate change or long-term climate cycles. Using a linear regression and a Mann-Kendall test, trends in annual maximum precipitation and flood data for several major gauging sites were evaluated. Moreover, this research considered incorporating flood trends by climate change effects in flood frequency analyses. For five rainfall gauging sites (Seoul, Incheon, Ulleungdo, Jeonju, and Gangneung), upward trends were observed in all gauged annual maximum precipitation records but they were not statistically significant. For three streamflow gauging sites (Andong Dam, Soyanggang Dam, and Daecheong Dam), upward trends were also observed in all gauged annual maximum flood records, but only the flood at Andong Dam was statistically significant. A log-normal trend model was introduced to reflect the observed linear trends in annual maximum flood series and applied to estimate flood frequency and risk for Andong Dam and Soyanggang Dam. As results, when the target year was 2005, 50-year floods of the log-normal trend model were 41% and 21% larger then those of a log-normal model for Andong Dam and Soyanggang Dam, respectively. Moreover, the estimated floods of the log-normal trend model increases as the target year increases.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.65-73
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• 2010

To observe and analyze the characteristics of cloud and precipitation properties, the Cloud physics Observation System (CPOS) has been operated from December 2003 at Daegwallyeong ($37.4^{\circ}N$, $128.4^{\circ}E$, 842 m) in the Taebaek Mountains. The major instruments of CPOS are follows: Forward Scattering Spectrometer Probe (FSSP), Optical Particle Counter (OPC), Visibility Sensor (VS), PARSIVEL disdrometer, Microwave Radiometer (MWR), and Micro Rain Radar (MRR). The former four instruments (FSSP, OPC, visibility sensor, and PARSIVEL) are for the observation and analysis of characteristics of the ground cloud (fog) and precipitation, and the others are for the vertical cloud characteristics (http://weamod.metri.re.kr) in real time. For verification of CPOS products, the comparison between the instrumental products has been conducted: the qualitative size distributions of FSSP and OPC during the hygroscopic seeding experiments, the precipitable water vapors of MWR and radiosonde, and the rainfall rates of the PARSIVEL(or MRR) and rain gauge. Most of comparisons show a good agreement with the correlation coefficient more than 0.7. These reliable CPOS products will be useful for the cloud-related studies such as the cloud-aerosol indirect effect or cloud seeding. The visibility value is derived from the droplet size distribution of FSSP. The derived FSSP visibility shows the constant overestimation by 1.7 to 1.9 times compared with the values of two visibility sensors (SVS (Sentry Visibility Sensor) and PWD22 (Present Weather Detect 22)). We believe this bias is come from the limitation of the droplet size range ($2{\sim}47\;{\mu}m$) measured by FSSP. Further studies are needed after introducing new instruments with other ranges.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.4
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• pp.425-437
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• 2007

Flow distribution of water and sedimentation rate were investigated to understand the hydrodynamics and settling characteristics of particulate materials in a constructed wetland for treatment of non-point sources pollutants, the Sihwa constructed wetland, Korea. The Sihwa constructed wetland is divided into three sub-wetlands(the Banwol, the Donghwa and the Samhwa wetlands) to treat the polluted water from three streams, the Banwol stream, the Donghwa stream and the Samhwa stream. From the results of water flow experiment using dye(Rhodamine 50WT Red), it was found that the water flow in the wetland was prevailing at the waterway and open water. Dye was spread slowly in the closed water area planted by plants. The mean hydraulic retention time(HRT) at the upper area of high wetland and lower wetland of Banwol, was found to be 34.1 hr at the upper area and 74.6 hr at the lower area respectively, totaling approximately 108.7 hr(4.5 days). The sedimentation rate was higher at lower area(sites of B, C and D) of the wetland than upper area(site of A which is settling zone). Based on the forecast for 20 years as to the amount of sediment that can be deposited in the open water in the future, the sediment depth of each area would be like this: A: 6.3 cm, B: 8.3 cm, C: 7.0 cm, D: 9.5 cm. The contents of organic materials in the sediment deposited within the sediment trap were found to be higher overly in the first investigation period which had much rainfall, and B, C and D areas were found to have an increased COD accumulation than A area. Also, nitrogen and phosphorus were found to increase in the down-stream of the wetland. The results of this study suggest that a sustainable research and management for the characteristics of water flow pattern and sedimentation changeable as time passes is needs to maintain or improve the efficiency of water treatment in the constructed wetland.

• Korean Journal of Environmental Agriculture
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• v.30 no.2
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• pp.153-159
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• 2011

BACKGROUND: This experiment was conducted to investigate the distribution and burden characteristics of heavy metal in the rainwater sampled at Taean area, in the middle part of Korea, from April 2002 to October 2003. METHODS AND RESULTS: The relationship between concentration of heavy metal and other chemical properties in the rainwaters was also evaluated. Chemical properties in the rainwater were various differences with raining periods and years. It appeared that a weighted average pH values of rainwater was ranged from 5.0 to 5.1. Heavy metal concentrations in the rainwater were ranked as Pb > Zn > Cu > Ni > As > Cr > Cd. As compared with heavy metal concentrations of rainwater in 2002, Cu, Pb, and Zn were higher than other elements in 2003. There were positive correlation between major ionic components, such as ${NH_4}^+$, $Ca^{2+}$, $Mg^{2+}$, $K^+$, $Na^+$, ${SO_4}^{2-}$ and ${NO_3}^-$, and As, Cd, Zn, Cr, and Ni concentrations in rainwater. For heavy metal distribution of rainwater, the order of average enrichment factor was Cd > Pb > As > Cu > Zn > Ni > Cr, and these were relatively higher than the natural components such as Fe, Mg and Ca. The monthly enrichment factor were relatively high, from August to October at Taean. The monthly amount of heavy metal precipitation was high in the rainy season from July to August because of great influence of rainfall. CONCLUSION(s): The results of this study suggest that the heavy metals(Cd, Pb, As, Cu, and Zn) of rainwater is strongly influenced by anthropogenic sources rather than natural sources.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.21-36
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• 2019

Dead fuel moisture content is a key variable in fire danger rating as it affects fire ignition and behavior. This study evaluates simple regression models estimating the moisture content of standardized 10-h fuel stick (10-h FMC) at three sites with different characteristics(urban and outside/inside the forest). Equilibrium moisture content (EMC) was used as an independent variable, and in-situ measured 10-h FMC was used as a dependent variable and validation data. 10-h FMC spatial distribution maps were created for dates with the most frequent fire occurrence during 2013-2018. Also, 10-h FMC values of the dates were analyzed to investigate under which 10-h FMC condition forest fire is likely to occur. As the results, fitted equations could explain considerable part of the variance in 10-h FMC (62~78%). Compared to the validation data, the models performed well with R2 ranged from 0.53 to 0.68, root mean squared error (RMSE) ranged from 2.52% to 3.43%, and bias ranged from -0.41% to 1.10%. When the 10-h FMC model fitted for one site was applied to the other sites, $R^2$ was maintained as the same while RMSE and bias increased up to 5.13% and 3.68%, respectively. The major deficiency of the 10-h FMC model was that it poorly caught the difference in the drying process after rainfall between 10-h FMC and EMC. From the analysis of 10-h FMC during the dates fire occurred, more than 70% of the fires occurred under a 10-h FMC condition of less than 10.5%. Overall, the present study suggested a simple model estimating 10-h FMC with acceptable performance. Applying the 10-h FMC model to the automatic mountain weather observation system was successfully tested to produce a national-scale 10-h FMC spatial distribution map. This data will be fundamental information for forest fire research, and will support the policy maker.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.193-205
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• 2023

A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.

• Geotechnical Engineering
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• v.2 no.1
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• pp.27-44
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• 1986

The measured soil data are analyzed to the descriptive statistics and classified into the four models of uncorrelated-normal (UNNO), uncorrelated-nonnormal (VNNN), correlatedonnormal(CONN), and correlated-nonnormal(CONN) . This paper presents the comparisons of reliability index and check points using the advanced first-order second-moment method with respect to the four models as well as BASIC Program. A sin91e-mode Performance function is consisted of the basic design variables of bearing capacity and settlements on shallow foundations and input the above analyzed soil informations. The main conclusions obtained in this study are summarized as follows: 1. In the bearing capacity mode, cohesion and bearing-capacity factors by C-U test are accepted for normal and lognormal distribution, respectively, and negatively low correlated to each other. Since the reliability index of the CONN model is the lowest one of the four model, which could be recommended a reliability.based design, whereas the other model might overestimate the geotechnical conditions. 2. In the case of settlements mode, the virgin compression ratio and preccnsolidation pressure are fitted for normal and lognormal distribution, respectively. Constraining settlements to the lower ones computed by deterministic method, The CONN model is the lowest reliability of the four models.