• Journal of Korea Water Resources Association
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• v.42 no.3
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• pp.213-225
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• 2009

A stationary Markov chain model is a stochastic process with the Markov property. Having the Markov property means that, given the present state, future states are independent of the past states. The Markov chain model has been widely used for water resources design as a main tool. A main assumption of the stationary Markov model is that statistical properties remain the same for all times. Hence, the stationary Markov chain model basically can not consider the changes of mean or variance. In this regard, a primary objective of this study is to develop a model which is able to make use of exogenous variables. The regression based link functions are employed to dynamically update model parameters given the exogenous variables, and the model parameters are estimated by canonical correlation analysis. The proposed model is applied to daily rainfall series at Seoul station having 46 years data from 1961 to 2006. The model shows a capability to reproduce daily and seasonal characteristics simultaneously. Therefore, the proposed model can be used as a short or mid-term prediction tool if elaborate GCM forecasts are used as a predictor. Also, the nonstationary Markov chain model can be applied to climate change studies if GCM based climate change scenarios are provided as inputs.

• Journal of the Korean GEO-environmental Society
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• v.11 no.6
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• pp.69-75
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• 2010

Total suspendid solid (TSS) of non point source pollutants in construction site are in higher concentration than others (BOD, COD etc). Also, the TSS concentration is very sensitive to the rainfall intensity in early stage of construction. There are two methods for treatment of non point source pollutants, which are temporary treatment facility and filtering one. But they have disadvantages. Temporary facility system has very low efficiency and filtering system consumes high energy and takes up large footprint. This study shows how prefabricated flocculation/coagulation system is developped to cover the above weakness and evaluation of the system performance in construction site. The prefabricated flocculation/coagulation system has very high treatment efficiency comparing with temporary and filtering system and takes small footprint. Therefore, it expects that the system leads to prevention of pollution near construction site and reduction of public grievance. Proper coagulant dosage and sludge circulation facility application, controlling the height of sludge interfacial are necessary to maximize the system efficiency.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1131-1142
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• 2020

This study assessed evapotranspiration (ET) methods applying for estimation of paddy rice water demand based on agricultural water supply. The Modified Penman (MP) method and the Penman-Monteith (PM) method recently suggested by Rural Development Administration (RDA) were considered. The 6 Korea Rural Community Corporation (KRC) command areas located in Honam province were selected in this study. The climate characteristics were also analysed with the average annual and the growing season temperatures and rainfalls. As a result, the annual average and the growing season temperature showed the increased trend while the rainfall tended to decrease during 30 years. The paddy rice water demand found to be directly influenced by these climate trends as ET also affected by them. The higher values of paddy rice water demand were obtained from applying MP method compared to the one applying PM method. The lower differences were also obtained from MP method for the comparisons between the paddy rice water demand estimated by both methods with agricultural water supply. Therefore, these results suggest that the MP method is more desirable to use for estimating paddy rice water demand in order to achieve stability of irrigation designs and plans.

• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.903-915
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• 2020

Long-term high-resolution hydro-meteorological data has been recognized as an essential element in establishing the water resources plan. The increasing demand for spatial precipitation in various areas such as climate, hydrology, geography, ecology, and environment is apparent. However, potential limitations of the existing area-weighted and numerical interpolation methods for interpolating precipitation in high altitude areas remains less explored. The proposed PRISM (Precipitation-Elevation Regressions on Independent Slopes Model) model can produce gridded precipitation that can adequately consider topographic characteristics (e.g., slope and altitude), which are not substantially included in the existing interpolation techniques. In this study, the PRISM model was optimized with SCEM-UA (Shuffled Complex Evolution Metropolis-University of Arizona) to produce daily gridded precipitation. As a result, the minimum impact radius was calculated 9.10 km and the maximum 34.99 km. The altitude of coastal weighted was 681.03 m, the minimum and maximum distances from coastal were 9.85 km and 38.05 km. The distance weighting factor was calculated to be about 0.87, confirming that the PRISM result was very sensitive to distance. The results showed that the proposed PRISM model could reproduce the observed statistical properties reasonably well.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.373-380
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• 2016

The NRCS-CN (Natural Resources Conservation Service-Curve Number) method has been practically applied for estimating the effective precipitation. However, there are no criteria which reflect the geographic characteristics of Korea having more than 70% of mountainous and rice paddy areas, leading to significant errors in runoff calculation. Thus, it is required to estimate the runoff curve number considered Korea land use classification, however there are practical difficulties to conduct the accurate research and experimentation. In this study, after selecting target areas (urban, agriculture, forest), we performed the runoff analysis to redetermine CN values for the selected basins. To do this, curve numbers for soil type A were estimated using genetic algorithm, and then curve numbers for soil type (B, C, D) were estimated using CN aligner equation. Comparing the initial curve numbers with the estimated curve numbers, it was observed that the slightly differences at Chunwang(0), Choonyang(-1), Janggi(-3). Through the above process, this study proposed new curve numbers to reflect observed rainfall-runoff.

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.193-200
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• 2020

Hydrological drought is directly associated with lack of available water in rivers, reservoirs, and groundwater. It is important to analyze hydrological drought for efficient water resource management because most of rainfall is concentrated in wet seasons and water supply is highly dependent on dams and reservoirs in South Korea. Generally, a threshold level method is useful for defining hydrological droughts. However, this method causes interdependent problems between drought events which result in skewed results in further statistical analysis. Therefore, it is necessary to determine a proper threshold level to represent regional drought characteristics. In this study, applying 50~99 percentiles of daily flow-duration curve, hydrological drought events were extracted, and independence tests were conducted for 12 watersheds. The Poisson independence test showed that 87~99 percentiles were available for most stations except for Yeoju and Pyeongtaek. The generalized Pareto independence test showed that 80~90 percentiles were the most common. Mean excess plot showed that 80 ~ 90 percentiles were the most common. Therefore, the common ranges of the three independent tests were determined for each station and proper threshold levels were recommended for large river basins; 70~76 percentiles for the Han River basin, 87~91 percentiles for the Nakdong River basin, 86~98 percentiles for the Geum River basin, and 85~87 percentiles for the Youngsan and Seomjin River basin.

• Journal of Korea Water Resources Association
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• v.49 no.10
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• pp.851-861
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• 2016

Recently, natural disasters, which are hard to predict and prevent, are rapidly increasing due to climate change worldwide. Particularly the damage scale of urban areas is increasing because of local torrential rainfall. In urban areas, the rain water cannot flow to pipes well due to the high percentage of impervious areas by the indiscriminate development. As a result, the inundation damage is getting higher in urban areas. So we need to characterize the interception of the grate inlets to ensure good drainage in impervious areas. But Korean installation criteria of grate inlets does not reflect road and drainage sector characteristics so the grate inlets do not function properly in many areas. In this study, we suggest the interception capacity equations about grate inlets through hydraulic experiments in various conditions. Therefore, the interception capacity changes are analyzed according to bearing bar slopes of grate inlets, grate inlet sizes and shapes and connecting pipe numbers. Though this, we developed the interception capacity equations about domestic grate inlets.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.525-533
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• 2008

Global circulation models (GCMs) have been used to study impact of climate change on water resources for hydrologic models as inputs. Recently, regional circulation models (RCMs) have been used widely for climate change study, but the RCMs have been rarely used in the climate change impacts on water resources in Korea. Therefore, this study is intended to use a set of climate scenarios derived by RegCM3 RCM ($27km{\times}27km$), which is operated by Korea Meteorological Administration. To begin with, the RCM precipitation data surrounding major rainfall stations are extracted to assess validation of the scenarios in terms of reproducing low frequency behavior. A comprehensive comparison between observation and precipitation scenario is performed through statistical analysis, wavelet transform analysis and EOF analysis. Overall analysis confirmed that the precipitation data driven by RegCM3 shows capabilities in simulating hydrological low frequency behavior and reproducing spatio-temporal patterns. However, it is found that spatio-temporal patterns are slightly biased and amplitudes (variances) from the RCMs precipitation tend to be lower than the observations. Therefore, a bias correction scheme to correct the systematic bias needs to be considered in case the RCMs are applied to water resources assessment under climate change.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.14 no.4
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• pp.229-239
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• 2009

To understand major factors that affected on distinct Cochlodinium bloom scale in Korean coasts in 2007 and 2008, oceanographic and meteorological characteristics during Cochlodinium bloom period were compared. The main reason for large scale blooms in 2007, covering both southern coast and eastern coast with about 10 million US dollars fish kills, was attributed to sufficient nutrient supply by heavy rainfall, upwelling in the coast arising from irregular wind shift, weak thermocline and low grazing pressure by zooplanktons during Cochlodimum bloom development period. On the contrary, small scale blooms in 2008 covering only inshore areas of southern coast without fish kills was attributed to the low nutrient level in coastal areas by long persistent drought and strong influence of oligotrophic offshore water onto inshore and high grazing pressure by extra ordinarily abundant zooplanktons during Cochlodinium development period. Conclusively, it was estimated that nutrient level, strength of offshore water and feeding pressure might play a significant role in the difference of bloom scale between the two years.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.199-207
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• 2024

Local reservoirs are crucial sources for agricultural water supply, necessitating stable water level management to prepare for extreme climate conditions such as droughts. Water level prediction is significantly influenced by local climate characteristics, such as localized rainfall, as well as seasonal factors including cropping times, making it essential to understand the correlation between input and output data as much as selecting an appropriate prediction model. In this study, extensive multivariate data from over 400 reservoirs in Jeollabuk-do from 1991 to 2022 was utilized to train and validate a water level prediction model that comprehensively reflects the complex hydrological and climatological environmental factors of each reservoir, and to analyze the impact of each input feature on the prediction performance of water levels. Instead of focusing on improvements in water level performance through neural network structures, the study adopts a basic Feedforward Neural Network composed of fully connected layers, batch normalization, dropout, and activation functions, focusing on the correlation between multivariate input data and prediction performance. Additionally, most existing studies only present short-term prediction performance on a daily basis, which is not suitable for practical environments that require medium to long-term predictions, such as 10 days or a month. Therefore, this study measured the water level prediction performance up to one month ahead through a recursive method that uses daily prediction values as the next input. The experiment identified performance changes according to the prediction period and analyzed the impact of each input feature on the overall performance based on an Ablation study.