• Journal of Korean Society on Water Environment
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• v.24 no.1
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• pp.7-18
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• 2008

The objective of this study was to develop and apply a water quality simulation model for the evaluation of ungaged watershed. The Modified WASP5 consisted of three sub-models, LOAD-M, DYN-M, and EUT-M. LOAD-M, an empirical model, estimates runoff loadings using point and non-point source data of villages. Daecheong Dam watershed was selected for the research to calibrate, verify and application of Modified-WASP5. LOAD-M model was established using field data collected from all items of water quality and water quantity gaging stations of the watersheds, and was applied to the ungauged watersheds, taking the watershed properties under consideration. The result of water quality simulation using ModifiedWASP5 shows that the observed BOD data of Yongpo and Daechong Dam in 1999 were 0.8 mg/L and 1.0 mg/L, and simulated data were 0.9 mg/L and 0.9 mg/L, respectively. In case of 1999, average BOD concentrations were 0.8 mg/L and 1.0 mg/L. Simulated concentration showed 1.1 mg/L and 1.5 mg/L, respectively. Generally, the simulation results were in good agreement with the observed data. This study was focused on formulating an integrated model for evaluating ungauged watersheds. Even though simulation results varied slightly due to limited availability of data, the model developed in this study would be a useful tool for the assessment and management of ungauged watersheds.

• Journal of Korean Society on Water Environment
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• v.30 no.2
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• pp.148-158
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• 2014

In order to assess the effect of TMDLs management and improve that in the future, it is necessary to analyze long-term changes in water quality during management period. Therefore, long term trend analysis of BOD was performed on thirty monitoring stations in Geum River TMDL unit watersheds. Nonparametric trend analysis method was used for analysis as the water quality data are generally not in normal distribution. The monthly median values of BOD during 2004~2010 were analyzed by Seasonal Mann-Kendall test and LOWESS(LOcally WEighted Scatter plot Smoother). And the effect of Total Maximum Daily Loads(TMDLs) management on water quality changes at each unit watershed was analyzed with the result of trend analysis. The Seasonal Mann-Kendall test results showed that BOD concentrations had the downward trend at 10 unit watersheds, upward trend at 4 unit watersheds and no significant trend at 16 unit watersheds. And the LOWESS analysis showed that BOD concentration began to decrease after mid-2009 at almost all of unit watersheds having no trend in implementation plan watershed. It was estimated that TMDLs improved water quality in Geum River water system and the improvement of water quality was made mainly in implementation plan unit watershed and tributaries.

• Journal of Korean Society on Water Environment
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• v.30 no.2
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• pp.128-137
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• 2014

The land use of the unit watersheds should be maintained appropriately in order to keep the load allotment stable for the management of Total Maximum Daily Loads (TMDLs). This study classified the land area in four types and analyzed the use of each land type and its changing pattern by calculating the occupation and conversion ratios for the unit watersheds in three river basins. The forest land showed the greatest occupation ratio with 63.0%, followed by the farm land with 23%, the other area with 8.0% and the site area with 6.0% in 2003. The occupation ratio of the site and the other area increased by 0.4% and 0.2% respectively, and that of the farm and the forest land decreased by 0.4% and 0.2% respectively in 2007. The conversion ratio for the site area ranged from 1.65% to 1.97%, for the farm land from -0.47% to -0.33%, for the forest land from -0.10% to -0.04% and for the other area from 0.17% to 1.97%. It can be inferred that the decrease in the farm and the forest land contributed to the increase in the site area and that the increase in the other area was mainly made by the decrease in the forest land. It could be more effective to take into account the changes in the site area and in the forest land in the process of developing the TMDL plans.

• Journal of Korean Society on Water Environment
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• v.32 no.2
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• pp.163-172
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• 2016

This study aimed to develop a plan for effective performance of a watershed through correct identification of a river watershed by using the flowrate of the river and water quality data, which is the basis for the establishment of the water environment policy. The target river for water quality improvement was selected based on the monitoring result for 4 water systems in Chungcheongnamdo province in the recent 3 years. The result of analysis for the distribution of discharge capacity by a pollution source group for the water quality improvement target river showed that most of the target river has a high discharge capacity in the water system for living and livestock. Analysis for the density of the total discharge capacity of the whole watershed of Chungcheongnamdo indicated that the river that needs water quality improvement has high BOD concentration and high discharge load density at the point that this river is located. Thus, for efficient watershed management through selection and concentration, Chungcheongnamdo needs to improve the target river in priority. Stepwise planning is also required to establish and execute the water quality improvement in order to satisfy said target water quality, and establish the index for the water improvement rate for its evaluation.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.83-83
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• 2016

가뭄은 발생과정과 피해영향에 따라서 기상학적, 농업적, 수문학적, 사회경제적 가뭄으로 구분되고 있다. 강수의 부족은 기상학적 가뭄을 발생시키고, 기상학적 가뭄이 지속되면 토양수분 부족으로 농작물의 피해를 가져오는 농업적 가뭄이 나타난다. 이어서, 지표 및 지표 아래의 수자원량이 평년수준 이하로 감소하면서 수문학적 가뭄이 발생한다. 이와 같이 다른 종류의 가뭄으로 가뭄이 변화하는 현상을 가뭄 전이(Drought Propagation)라고 한다. 강수량의 부족만으로 판단되는 기상학적 가뭄은 가뭄 상황의 판단은 간단지만, 체감으로 느끼는 가뭄과 차이가 존재한다. 수문학적 가뭄은 실제 물이용과 관련이 높아 효율적인 물 관리를 위해서는 수문학적 가뭄에 대한 정보가 필요하다. 하지만 수문학적 가뭄은 기상학적 인자들뿐만 아니라 수문순환과정의 영향을 받아 가뭄의 발생과정이 복잡하기 때문에 판단 및 예측이 어렵다. 본 연구에서는 가뭄의 전이관계를 도출함으로써, 기상학적 가뭄에서 수문학적 가뭄으로 발전되는 가뭄의 크기를 파악하고자 한다. 가뭄은 판단기준에 따라서 다양하게 정의될 수 있다. 본 연구에서는 기상학적 가뭄은 강우량으로, 수문학적 가뭄은 유역별 댐의 저수율, 유입량 및 지하수위를 활용하여 가뭄을 정의하며, 가뭄사상은 임계수준방법(threshold level approach)과 풀링기법(pooling method)을 수문기상 변수들에 적용하여 추출하였다. 수문학적 가뭄은 기상학적 가뭄이 발생한 이후, 가뭄 상황이 일정기간 지속되는 상황에 발생하는 결과가 확인되었다. 기상학적 가뭄에서 수문학적 가뭄이 전이되는 현상을 바탕으로 기상학적 가뭄의 상황에 따라서 미래의 수문학적 가뭄의 변화 양상에 대하여 예측가능하며, 가뭄의 전이관계는 수문학적 가뭄의 예측을 위한 자료로 활용될 수 있을 것으로 판단된다.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.405-412
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• 2011

Increased Non-permeable areas which have resulted from civilization reduce the volume of groundwater infiltration that is one of the important factors causing water shortage during a dry season. Thus, seeking the efficient method to analyze the volume of groundwater in accurate should be needed to solve water shortage problems. In this study, two different watersheds were selected and precipitation, soil group, and land use were surveyed in a particular year in order to figure out the accuracy of estimated infiltration recharge ratio compared to Web-based Hydrograph Analysis Tool (WHAT). The volume of groundwater was estimated considering Antecedent soil Moisture Condition (AMC) and Curve Number (CN) using Long Term Hydrologic Impact Assessment (L-THIA) model. The results of this study showed that in the case of Kyoung-an watershed, the volume of both infiltration and baseflow seperated from WHAT was 46.99% in 2006 and 33.68% in 2007 each and in Do-am watershed the volume of both infiltration and baseflow was 33.48% in 2004 and 23.65% in 2005 respectively. L-THIA requires only simple data (i.e., land uses, soils, and precipitation) to simulate the accurate volume of groundwater. Therefore, with convenient way of L-THIA, researchers can manage watershed more effectively than doing it with other models. L-THIA has limitations that it neglects the contributions of snowfall to precipitation. So, to estimate more accurate assessment of the long term hydrological impacts including groundwater with L-THIA, further researches about snowfall data in winter should be considered.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.240-240
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• 2020

강우 시 우수관로 내부의 수리 거동(유속, 수위)에 영향을 미치는 대표적인 매개변수는 관로의 조도계수와 손실계수 등이 있다. 이 중 조도계수는 관로 내부의 퇴적 및 협잡물로 인한 조도높이 변화에 따른 관로 내의 수리학적 거동을 평가할 수 있는 매개변수이며 손실계수는 관로의 확대, 축소, 만곡 등에 의한 에너지 감쇄 효과에 따른 관로 내 수리학적 변화를 평가할 수 있는 매개변수이다. 본 연구에서는 서울시 주요 배수구역에 대해 관로 조도계수 및 손실계수 변화에 따른 수위, 유속 변동성을 SWMM으로 분석하였다. 연구에 적용한 대상 배수구역은 반포 02 (방배1), 안양천 13 (봉천1), 성내 05 (길동), 안양천 11(신림4), 반포 03 (방배2), 안양천 01 (오류1), 성내 03 (천호)로 총 7개 배수구역이다. 모형수행을 위한 조건으로 조도계수는 0.015 ~ 0.120 구간에 대해 0.003 단위로 증가시키며 총 12개 CASE를 적용하였으며 손실계수는 0.0 ~ 0.5 구간에 대해 0.1 단위로 총 6개 CASE를 적용하였다. 관로 수리특성에 따른 수심, 유속의 변화량 분석 결과는 관로 및 유역의 크기별로 변화의 폭이 매우 크므로 상자-수염그림(Box-whisker plot) 이용하여 중간값의 변화 정도를 검토하였다. 조도계수 증가에 따른 수심증가, 유속 감소치의 중간값을 분석한 결과 조도계수가 0.013에서 0.034로 증가 시 수심은 40.6% 증가하고 유속은 47.4% 감소하는 것으로 검토되었다(그림 1, 2). 한편, 손실계수 증가에 따른 수심증가, 유속 감소치의 중간값을 분석한 결과 조도계수가 0.0에서 1.6으로 증가시 수심은 15.7% 증가하고 유속은 15.0% 감소하는 것으로 검토되었다. 이상과 같은 연구의 성과는 우수관로 내부의 다양한 여건 변화가 강우 시 관로 내 수리특성에 미치는 영향을 판단하기 위한 기초 자료로 활용할 수 있으며 향후, 우수관로 모니터링 결과와 연계하여 유지관리 방안 수립에 활용할 수 있을 것으로 판단된다.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.617-628
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• 2021

Drought is a major natural disaster that causes serious social and economic losses. Local drought forecasts can provide important information for drought preparedness. In this study, we propose a new machine learning model that predicts drought by using historical drought indices and meteorological data from 10 sites from 1981 to 2020 in the southeastern part of the Korean Peninsula, Busan-Ulsan-Gyeongnam. Using Bayesian optimization techniques, a hyper-parameter-tuned Random Forest, XGBoost, and Light GBM model were constructed to predict the evaporative demand drought index on a 6-month time scale after 1-month. The model performance was compared by constructing a single site model and a regional model, respectively. In addition, the possibility of improving the model performance was examined by constructing a fine-tuned model using data from a individual site based on the regional model.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.91-91
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• 2020

IPCC (Intergovernmental Panel on Climate Change) 5차 평가보고서에 의하면 최근 배출 온실가스의 양은 관측 이래 최고 수준이며 온실가스로 인한 기후변화는 인간계와 자연계에 광범위한 영향을 주고 있다고 보고하였다. 기후변화의 영향은 국제적으로 빙하 감소, 사막화, 해수면 상승 등 뚜렷하게 나타나고 있다. 이러한 기후변화에 대응하기 위해 온실가스 완화 정책과 동시에 새로운 기후변화 환경에 적응하는 것이 필요하다. 기후변화 적응이란 현재 나타나고 있거나 미래에 나타날 것으로 예상되는 기후변화의 파급효과와 영향에 대응할 수 있도록 하는 모든 행동이며 이를 위해서는 기후변화 영향분석이 수반되어야 한다. MOTIVE 연구단에서는 기후변화 적응대책 수립의 지원을 목표로 7개 부문(건강, 물관리, 농업, 산림, 생태, 해양, 수산)에서 "한국형 통합평가 모형"을 개발하고 있다. 각 부문에서 개발하는 프로세스 모델은 시스템에 대한 지식을 가진 상황에서 사용하면 신뢰할 수 있는 예측 결과를 얻을 수 있지만, 부문별 통합을 통한 영향 분석 시 타 분야에 대한 지식이 수반되어야 하는 어려움을 가진다. 이를 위해 본 연구에서는 시스템 내의 물리적 프로세스에 대한 요구 없이 입출력 데이터만을 이용하여 결과를 신속하게 추정하는 데이터 모델링(기계학습)을 이용하였다. 데이터 모델링을 위한 데이터는 다양한 자연 현상에 대한 BANPOL(수질 프로세스 모델) 분석을 통한 자료를 이용하여 학습 자료를 구축하였다. 즉, 데이터 모델링은 BANPOL 모델을 대리하는 메타모델이며, 낙동강 표준유역에 대한 유량 및 수질을 높은 상관성으로 추정하였다. 원 모델보다 정확도는 낮을 수 있으나 메타모델의 개발을 통한 웹 시스템을 개발하여 비전문가의 구동 및 신속한 기후 시나리오를 적용할 수 있는 환경을 개발하였다.