• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.747-755
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• 2010

Distributed Models have relative weak points due to the amount of computer memory and calculation time required for calculating water flow using a numerical analysis based on kinematic wave theory when compared to the conceptual models used so far. Typically, the distributed models have been mainly applied to small basins. It was necessary to decrease the resolution of the grid to make it applicable for large scale watersheds, and because it would take up too much time to calculate using a higher resolution. That has been one of the more difficult factors in applying the model for actual work. In this paper, MPI (Message Passing Interface) technique was applied 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 comparison studies were performed a single domain and a divided small domain in Yongdam Dam watershed in case of typoon 'Ewiniar' at 2006. They were compared to analyze the application effects of parallelization technique. As a result, a maximum of 10 times the amount of calculation time was saved but keeping the level of quality for discharge by using parallelization code rather than a single processor.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4B
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• pp.383-392
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• 2008

It is not always easy to estimate the parameters in hydrologic models due to insufficient hydrologic data when hydraulic structures are designed or water resources plan are established. Therefore, uncertainty analysis are inevitably needed to examine reliability for the estimated results. With regard to this point, this study applies a Bayesian Markov Chain Monte Carlo scheme to the NWS-PC rainfall-runoff model that has been widely used, and a case study is performed in Soyang Dam watershed in Korea. The NWS-PC model is calibrated against observed daily runoff, and thirteen parameters in the model are optimized as well as posterior distributions associated with each parameter are derived. The Bayesian Markov Chain Monte Carlo shows a improved result in terms of statistical performance measures and graphical examination. The patterns of runoff can be influenced by various factors and the Bayesian approaches are capable of translating the uncertainties into parameter uncertainties. One could provide against an unexpected runoff event by utilizing information driven by Bayesian methods. Therefore, the rainfall-runoff analysis coupled with the uncertainty analysis can give us an insight in evaluating flood risk and dam size in a reasonable way.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.345-354
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• 2006

Drought brings on long term damage in contrast to flood, on economic loss in the region, and on ecologic and environmental disruptions. Drought is one of major natural disasters and gives a painful hardship to human beings. So we have tried to quantify the droughts for reducing drought damage and developed the drought indices for drought monitoring and management. The Palmer's drought severity index (PDSI) is widely used for the drought monitoring but it has the disadvanges and limitations in that the PDSI is estimated by considering just climate conditions as pointed out by many researchers. Thus this study uses the SWAT model which can consider soil conditions like soil type and land use in addition to climate conditions. We estimate soil water (SW) and soil moisture index (SMI) by SWAT which is a long term runoff simulation model. We apply the SWAT model to Soyang dam watershed for SMI estimation and compare SMI with PDSI for drought analysis. Say, we calibrate and validate the SWAT model by daily inflows of Soyang dam site and we estimate long term daily soil water. The estimated soil water is used for the computation of SMI based on the soil moisture deficit and we compare SMI with PDSI. As the results, we obtained the determination coefficient of 0.651 which means the SWAT model is applicable for drought monitoring and we can monitor drought in more high resolution by using GIS. So, we suggest that SMI based on the soil moisture deficit can be used for the drought monitoring and management.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.139-150
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• 2024

This study introduced a method of estimating water surface evaporation using the physical-based Penman combination equation (PCE) and the Penman wind function (PWF). A set of regression parameters in the PCE and PWF models were optimized by using the observed evaporation data for the period 2016-2017 in the Yongdam Dam watershed, and their effectiveness was explored. The estimated evaporation over the Deokyu Mountain flux tower demonstrated that the PWF method appears to have more improved results in terms of correlation, but both methods showed overestimation. Further, the PWF method was applied to the observed hydro-meteorological data on the surface of Yongdam Lake. The PWF method outperformed the PCE in the estimation of water surface evaporation in terms of goodness-of-fit measure and visual evaluation. Future studies will focus on a regionalization process which can be effective in estimating water surface evaporation for the ungauged area by linking hydrometeorological characteristics and regression parameters.

• Korean Journal of Ecology and Environment
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• v.41 no.3
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• pp.382-394
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• 2008

The objective of this study was to analyze temporal trends of water chemistry and spatial heterogeneity between the dam site (Daecheong Reservoir, S1) and the downstream (S2$\sim$S4) using water quality dataset (obtained from the Ministry of Environment, Korea) during 2000$\sim$2007. Water quality, based on eight physical and chemical parameters, varied largely depending on the years, sampling sites, and the discharge volume. Conductivity and nutrients (TN and TP) showed a decreasing trend in the downstream (S4) rather than the dam site during the monsoon. Spatial variation increased toward downstream (S4) from Daecheong Reservoir (S1). Also, BOD and COD increased toward downstream. Because of input of nutrient and pollutant nearby S1, lentic ecosystem in monsoon, BOD and COD were slightly increased. whereas relatively decreased in S4, lotic ecosystem in monsoon, by dilution effect of nutrient and pollutant by discharge from upper dam, S1. Spatial variation of SS increased toward downstream (S4) by the side of Daecheong Reservoir (S1). Based on the dataset, efficient water quality management in the point source tributary streams is required for better water quality of downstream. Monthly characteristics of DO showed the lowest value in the monsoon that tend to increase water temperature. DO was lowest in October at S1 because turbid water, input to the Daecheong Reservoir in the monsoon affect to the postmonsoon period. In contrast, water temperature increased toward summer monsoon, in spite of some differences showed between S1 and S4 environment. Overall, the characteristics of water quality in downstream region have close correlation with discharge amount of Daecheong Reservoir. Thus, those characteristics can explain that discharge control of upper dam mainly affect to the water quality variation in downstream reach.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.437-449
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• 2024

Rainfall-runoff prediction studies using deep learning while considering catchment attributes have been gaining attention. In this study, we selected two models: the Transformer model, which is suitable for large-scale data training through the self-attention mechanism, and the LSTM-based multi-state-vector sequence-to-sequence (LSTM-MSV-S2S) model with an encoder-decoder structure. These models were constructed to incorporate catchment attributes and predict the inflow of 10 multi-purpose dam watersheds in South Korea. The experimental design consisted of three training methods: Single-basin Training (ST), Pretraining (PT), and Pretraining-Finetuning (PT-FT). The input data for the models included 10 selected watershed attributes along with meteorological data. The inflow prediction performance was compared based on the training methods. The results showed that the Transformer model outperformed the LSTM-MSV-S2S model when using the PT and PT-FT methods, with the PT-FT method yielding the highest performance. The LSTM-MSV-S2S model showed better performance than the Transformer when using the ST method; however, it showed lower performance when using the PT and PT-FT methods. Additionally, the embedding layer activation vectors and raw catchment attributes were used to cluster watersheds and analyze whether the models learned the similarities between them. The Transformer model demonstrated improved performance among watersheds with similar activation vectors, proving that utilizing information from other pre-trained watersheds enhances the prediction performance. This study compared the suitable models and training methods for each multi-purpose dam and highlighted the necessity of constructing deep learning models using PT and PT-FT methods for domestic watersheds. Furthermore, the results confirmed that the Transformer model outperforms the LSTM-MSV-S2S model when applying PT and PT-FT methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.89-97
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• 2006

Soil erosion has caused serious environmental problems which threaten the foundation of natural resources. In this paper, we chose RUSLE erosion model, which could be connected easily with GSIS and available generally in mid-scale watershed among soil erosion models, and extracted factors entered model by using GSIS spatial analysis method. First, this study used GIS database as soil map, DEM, land cover map and rainfall data of typhoon Memi (2003) to analyze soil loss amount of Dam basin. To analyze the changes of soil loss in considering basin characteristics as up-, mid- and downstream, this study calculated soil erodibility factor (K), topographic factors (LS), and cover management factor (C). As a result of analysis, K and LS factors of upstream showed much higher than those of downstream because of the high ratio of forest. But C factor of downstream showed much higher than that of upstream because of the high ratio of agricultural area. As a result of analysis of soil loss, unit soil loss of upstream is 4.3 times than soil loss of downstream. Therefore, the establishment of countermeasures for upstream is more efficient to reduce soil loss.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.4
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• pp.69-75
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• 2014

We investigated flood control capacity of 484 agricultural reservoirs with storage capacity of over 1 million $m^3$ in South Korea. In general, agricultural reservoir secures flood control capacity by setting up limited water level during flood season from late June to mid-September. The flood control capacity of an agricultural reservoir during flood season can be divided into stable flood control capacity during non-flood season, stable flood control capacity associated with limited water level, and unstable flood control capacity associated with limited water level. In general, the flood control capacity significantly (P < 0.001) increased with reservoir capacity irrespective of type of spillway. The unstable flood control capacity accounted for about 20 % of reservoir capacity in the uncontrolled reservoirs. The study reservoirs showed flood control capacity of 0.60-65 billion (B) $m^3$ and stable flood control capacity of 0.43-47 B $m^3$, depending on the upper and lower limited water levels during the flood season. The stable flood control capacity of the gated reservoirs (0.29-0.33 B $m^3$) was about two times than that of reservoirs with uncontrolled spillways (0.14 B $m^3$). The ratios of stable flood control capacity to reservoir capacity for agricultural reservoirs range from 21 to 23 %, similar to that for Daecheong multipurpose dam. Moreover, the reservoirs with over 100 mm ratio of flood control capacity to watershed area accounted for 38 % of total gated reservoirs. The results indicate that many agricultural reservoirs may contribute to controlling flood in the small watersheds during the flood season.

• Journal of Korea Water Resources Association
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• v.37 no.5
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• pp.375-386
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• 2004

A water shortage is one of the most important factors for development and management of water resources. For reliable water shortage measurement in a stream, Korea Water Resources Corporation(KOWACO) founded five foot Parshall flume at Yong-dam experimental watershed in 2000. The Parshall flume has a specially designed shape to facilitate flow measurements by eliminating sediment deposition problem that could lead to an incorrect measurement. In this study, computational fluid dynamics(CFD) model was used to analyze flow behavior of Parshall Flume under free discharge of five headwater level cases. The flow rates computed by CFD model are compared with those by ISO's formula, USBR's formula and stage-discharge rating curves. Flow rates computed by ISO's and USBR's formula are mostly same, but flow rate by CFD model is larger than empirical value by 9% and flow rate by stage-discharge rating curves is less than empirical value by 16%.

• Journal of the Korean GEO-environmental Society
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• v.15 no.8
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• pp.13-21
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• 2014

The Plastic Board Drain is used to improve soft soils deposited in container terminal area at a port. This paper describes settlement behavior of soft ground in this area from PBD installation to the time of operating facilities. Previous researches focused on soil improvement effect of PBD, that is, the settlement occurred during ground improvement period. The residual settlement occurred during operating the facility is very important from the maintenance and management point of view. However, the study of this residual settlement has been rarely conducted. In this study, by analyzing the measured settlement data obtained from the container terminal area at the port, it was verified that the residual settlement induced during operating facilities occurred in a layer with PBD improvement. In addition, by comparison the settlement predicted by a numerical analysis with the settlement measured in the field, it was confirmed that the actual settlement is in the range of predicted settlement.