• Spatial Information Research
• /
• v.8 no.2
• /
• pp.257-274
• /
• 2000

Recently, natural environment is being forced by the quick increasing of population and industrialization, and especially, capacity and pollution of water resource is being come to the front. It needs to extract the accurate topological and hydrological parameters of watershed in order to manage water resource efficiently. But, these data are processed yet by manual work and simple operation in hydrological fields. In this paper, we presented algorithm that could extract topological any hydrological parameters over Sumjin watershed using GIS and RS and it gives the saving of data processing time and the confidency of data. The extraction procedure of topological characteristics and hydrological parameters is as below. First, watershed and stream are extracted by DEM and curve number is extracted throughout the overlay of landcov map and soil map. Also, we extracted surface parameters like watershed length and the slope of watershed length by Grid computation into watershed and stream. And we gave the method that could extract hydrologic parameters like Muskingum K and sub-basin lag time by executing computation into surface parameters and average SCS curve number being extracted.

• Journal of Environmental Science International
• /
• v.18 no.6
• /
• pp.609-619
• /
• 2009

SWAT-K model is a modified version of the original SWAT, and is known to more accurately estimate the streamflows and pollutant loadings in Korean watersheds. In this study, its hydrological components were compared with those of HSPF in order to analyse the differences in total runoff including evapotranspiration(ET), surface flow, lateral flow and groundwater flow from the Chungju Dam watershed during $2000{\sim}2006$. Averaged annual runoff with SWAT-K overestimated by 1%, and HSPF underestimated it by 3% than observed runoff. Determination coefficients($R^2$) for observed and simulated daily streamflows by both the models were relatively good(0.80 by SWAT-K and 0.82 by HSPF). Potential ET and actual ET by HSPF were lower in winter, but similar or higher than those by SWAT-K. And though there were some differences in lateral and groundwater flows by two models because of the differences in hydrological algorithms, the results were to be reasonable. From the results, it was suggested that we should utilize a proper model considering the characteristic of study area and purposes of the model application because the simulated results from same input data could be different with models used. Also we should develop a novel model appropriate to Korean watersheds by enhancing limitations of the existing models in the future.

• Journal of Korea Water Resources Association
• /
• v.47 no.11
• /
• pp.997-1005
• /
• 2014

This study evaluated hydrological drought the using the annual minimum flow and the annual maximum deficit method and proposed the new concept of water deficit-duration-frequency curves similar to rainfall intensity-duration-frequency curves. The analysis results of the annual minimum flow, the return periods of hydrological drought in the most duration of 1989 and 1996yr were the longest. The analysis results of the annual maximum deficit, the return periods of 60-days and 90-day deficit which are relatively short duration were the longest in 1995yr, about 35-year, Hydrological drought lasted longer was in 1995, the return period was about 20-year. Though duration as well as magnitude is a key variable in drought analysis, it was found that the method using the annual minimum flow duration not distinguish duration.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2004.05b
• /
• pp.1285-1289
• /
• 2004

Elman Discrete Recurrent Neural Networks Model(EDRNNM) was used to be a suitable short-term hydrological forecasting tool yielding a very high degree of flood stage forecasting accuracy at Musung station of Wi-stream one of IHP representative basins in South Korea. A relative new approach method has recurrent feedback nodes and virtual small memory in the structure. EDRNNM was trained by using two algorithms, namely, LMBP and RBP The model parameters, optimal connection weights and biases, were estimated during training procedure. They were applied to evaluate model validation. Sensitivity analysis test was also performed to account for the uncertainty of input nodes information. The sensitivity analysis approach could suggest a reduction of one from five initially chosen input nodes. Because the uncertainty of input nodes information always result in uncertainty in model results, it can help to reduce the uncertainty of EDRNNM application and management in small catchment.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.42 no.4
• /
• pp.67-75
• /
• 2000

A simulation model for reservoir sizing was developed to be applied in a region with insufficient hydrological data. Reservoir storage balance equation was formulated on a monthly basis. Gajiyama equation was generalized to estimate monthly reservoir inflow more accurately. Monthly evaporation equation on a reservoir water surface was introduced , which was functioned with monthly mean temperature. Generalized Gajiyama equation was applied to estmate reservoir inflow of the Sayeon dam. Nash-Sutcliffe's model efficiency was 0.793. Using developed model for reservoir sizing, water supply capacity was analyzed with 118.000㎥/day on the Sayeon dam. This showed a reasonable result as compared with 110000㎥/day in other technical report. For general application of developed model, a virtual reservoir was considered and its dta of surface area and volume by elevation was prepared using DEM. Using the model, size of reservoir was determined and water supply capacity was anlayzed on a virtual reservoir.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.165-165
• /
• 2023

Streamflow prediction is a critical task in water resources management and essential for planning and decision-making purposes. However, the streamflow prediction is challenging due to the complexity and non-linear nature of hydrological processes. The transfer learning is a powerful technique that enables a model to transfer knowledge from a source domain to a target domain, improving model performance with limited data in the target domain. In this study, we apply the transfer learning using the Informer model, which is a state-of-the-art deep learning model for streamflow prediction. The model was trained on a large-scale hydrological dataset in the source basin and then fine-tuned using a smaller dataset available in the target basin to predict the streamflow in the target basin. The results demonstrate that transfer learning using the Informer model significantly outperforms the traditional machine learning models and even other deep learning models for streamflow prediction, especially when the target domain has limited data. Moreover, the results indicate the effectiveness of streamflow prediction when knowledge transfer is used to improve the generalizability of hydrologic models in data-sparse regions.

• Journal of Wetlands Research
• /
• v.16 no.2
• /
• pp.235-243
• /
• 2014

According to the "Safety Evaluation Detailed Instructions (Dam)", precise safety inspection is carried out for dams that exceed a certain scale. However, as the Hydrological Safety Evaluation from various evaluation standards is designed to evaluate the safety of existing dams considering PMF, the evaluation is much less applicable for most agricultural reservoirs. Therefore, the Hydrological Safety Guidelines for agricultural reservoirs are expected to be re-evaluated considering the diverse risk factors with the coefficient model and AHP in this study. The coefficient model has been developed by selecting the hydrological safety superordinate subordinate evaluation factors to reflect diverse risk factors of agricultural reservoirs. After calculating the sum of indicators score for each evaluation factors, validation procedures were performed for the questionnaire which a panel answered. The practical coefficient has eventually been estimated for the hydrological safety evaluation considering the diverse risk factors. The conclusions acquired based on the study done are that both most agricultural reservoirs were classified as flood defense capability is insufficient and agricultural reservoirs which meet embankment-freeboard standards considering PMF was overestimated.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2005.05b
• /
• pp.583-587
• /
• 2005

At present, various methods are available to analyze storm runoff data. Among these, application of Z-transform is comparatively simple and new, and the technique can be used to identify rainfall and unit hydrograph from analysis of a single storm runoff. The technique has been developed under the premise that the rainfall-runoff process behaves as a linear system for which the Z-transform of the direct runoff equals the product of the Z-transforms of the transfer function and the rainfall. In the hydrologic literatures, application aspects of this method to the rainfall-runoff process are lacking and some of the results are questionable. Thus, the present study provides the estimation of Z-transform technique by analyzing the application process and the results using hourly runoff data observed at the research basin of International Hydrological Program (IHP), the Pyeongchanggang River basin. This study also provides the backgrounds for the problems that can be included in the application processes of the Z-transform technique.

• Journal of Wetlands Research
• /
• v.23 no.4
• /
• pp.277-286
• /
• 2021

This study compares the long-term hydrological cycles of the Seolmacheon and Cheongmicheon basin by applying the structural equation model (SEM). These two basins are found different especially in their land-use pattern. Both basins have the actual evapotranspiration data measured by the eddy-covariance method as well as the rainfall and runoff data. The length of the data considered in this study is nine years from 2010 to 2018. The structure of the SEM is determined by considering the correlations among the data as well as the general knowledge on the hydrological cycle. As a result, a total of three SEMs are applied sequentially to analyze their fittings. As irony would have it, two basins are found to be similar in the application of one SEM, but different in the application of another. Especially, when considering the feedback process between precipitation and evapotranspiration, two basins are found to be very different. That is, the feedback process between precipitation and evapotranspiration is found to be significant in the Cheongmicheon basin where the portion of agricultural area (i.e., paddy) is more than 40%.

• Journal of Korean Society on Water Environment
• /
• v.36 no.4
• /
• pp.300-313
• /
• 2020

The Bayesian approach can be used to estimate hydrologic model parameters from the prior expert knowledge about the parameter values and the observed data. The purpose of this study was to compare the performance of the two Bayesian methods, the Metropolis-Hastings (MH) algorithm and the Generalized Likelihood Uncertainty Estimation (GLUE) method. These two methods were applied to the TANK model, a hydrological model comprising 13 parameters, to examine the uncertainty of the parameters of the model. The TANK model comprises a combination of multiple reservoir-type virtual vessels with orifice-type outlets and implements a common major hydrological process using the runoff calculations that convert the rainfall to the flow. As a result of the application to the Nam River A watershed, the two Bayesian methods yielded similar flow simulation results even though the parameter estimates obtained by the two methods were of somewhat different values. Both methods ensure the model's prediction accuracy even when the observed flow data available for parameter estimation is limited. However, the prediction accuracy of the model using the MH algorithm yielded slightly better results than that of the GLUE method. The flow duration curve calculated using the limited observed flow data showed that the marginal reliability is secured from the perspective of practical application.