This study explored spatiotemporal variability of water quality in correspondence with hydrometeorological factors in the four stations of Euiam Reservoir located in the upstream region of the North-Han River from May 2012 to December 2015. Seasonal effect was apparent in the variation of water temperature, DO, electric conductivity and TSS during the study period. Stratification in the water column was observed in the near dam site every year and vanished between August and October. Increase of nitrogen nutrients was observed when inflowing discharge was low, while phosphorus increase was distinct both during the early season with increase of inflowing discharge and the period of severe draught persistent. Duration persisting high concentration of Chl-a (>25 mg m-3: the eutrophic status criterion, OECD, 1982) was 1~2 months of the whole year in 2014~2015, while it was almost 4 months in 2013. Water quality of Euiam Reservoir appeared to be affected basically by geomorphology and source of pollutants, such as longitudinally linked instream islands and Aggregate Island, inflowing urban stream, and wastewater treatment plant discharge. While inflowing discharge from the dams upstream and outflow pattern causing water level change seem to largely govern the variability of water quality in this particular system. In the process of spatiotemporal water quality change, factors related to climate (e.g. flood, typhoon, abruptly high rainfall, scorching heat of summer), hydrology (amount of flow and water level) might be attributed to water pulse, dilution, backflow, uptake, and sedimentation. This study showed that change of water quality in Euiam Reservoir was very dynamic and suggested that its effect could be delivered to downstream (Cheongpyeong and Paldang Reservoirs) through year-round discharge for hydropower generation.

Daecheong Reservoir was made by the construction of a large dam (>15 m in height) on the middle to downstream of the Geum River and the discharge systems have the watergate-spillway (WS), a hydropower penstock (HPP), and two intake towers. The purpose of this study was to investigate the limnological anomalies of turbid water reduction, green algae phenomenon, and oligotrophic state in the lower part of reservoir dam site, and compared with hydro-meteorological factors. Field surveys were conducted in two stations of near dam and the outlet of HPP with one week intervals from January to December 2000. Rainfall was closely related to the fluctuations of inflow, outflow and water level. The rainfall pattern was depended on the storm of monsoon and typhoon, and the increase of discharge and turbidity responded more strongly to the intensity than the frequency. Water temperature and DO fluctuations within the reservoir water layer were influenced by meteorological and hydrological events, and these were mainly caused by water level fluctuation based on temperature stratification, density current and discharge types. The discharges of WS and HPP induced to the flow of water bodies and the outflows of turbid water and nutrients such as nitrogen and phosphorus, respectively. Especially, when hypoxic or low-oxygen condition was present in the bottom water, the discharge through HPP has contributed significantly to the outflow of phosphorus released from the sediment into the downstream of dam. In addition, HPP effluent which be continuously operated throughout the year, was the main factor that could change to a low trophic level in the downreservoir (lacustrine zone). And water-bloom (green-tide) occurring in the lower part of reservoir was the result that the water body of upreservoir being transported and diffused toward the downreseroir, when discharging through the WS. Finally, the hydropower effluent was included the importance and dynamics that could have a temporal and spatial impacts on the physical, chemical and biological factors of the reservoir ecosystem.

This study explored spatiotemporal variability of water quality in correspondence with hydrometeorological factors in the five stations of Paldang Reservoir located in the Han River during 4 years from May 2012 to December 2015. Variability of basic water quality factors were largely related with seasonal fluctuations of hydrology. Temperature stratification occurred in the deep dam station, and prolonged hypoxia was observed during the draught year. Nitrogen nutrients were increased with decreasing inflow in which changing pattern of NH4 reversed to NO3 by the effect of treated wastewater effluent. Phosphorus increase was manifest during the period of high inflow or severe drought. Chl-a variation was reversely related with both flow change and AGP (algal growth potential) variations. Our study demonstrated that water quality variability in Paldang Reservoir was largely attributed to both natural and operational changes of inflow and outflow (including water intake) based on major pollution source of the treated wastewater (total amount of 472×103 m3 d-1) entering to the water system from watershed. In the process of water quality variability, meteorological (e.g., flood, typhoon, abnormal rainfall, scorching heat of summer) and hydrological factors (inflow and discharge) were likely to work dynamically with nutrients pulse, dilution, absorption, concentration and sedimentation. We underline comprehensive limnological study related to hydro-meteorolology to understand short- and long-term water quality variability in river-type large reservoir and suggest the necessity of P-free wastewater treatment for the effective measure of reducing pollution level of Paldang drinking water resource.

Daecheong Reservoir has suffered eutrophication and water-blooms by blue-green algae from initial impoundment, and algae alert system (AAS) was introduced in 1997. The purpose of this study was to investigate the effect of rainfall and hydrological factors in increase or decrease variability of green-tide and prolonged AAS, studied and analyzed the current situation of AAS has been operating for 19 years(1997~2015) in Daecheong Reservoir. The total issued number of AAS was 46 times, the most frequent period in August and September were 22 times (752 days) and 16 times (431 days), respectively, it accounted for 82.6%. Many number and frequency during this period were significantly associated with rainfall, various discharge and water level. Rainfall and hydrological events are associated with the rainy season of monsoon-Changma and the typhoon, it was concentrated in June~September, total rainfall in this period accounted for 69.9% of the annual rainfall. An increase in inflows was dependent on the intensity, frequency and the amount of rainfall. Accounted for 68.4% of the total annual inflow, it was a time when the most rapidly changing hydrological variability in the reservoir. The total outflow was closely related to rainfall, and compared the distinctive characteristics of hydropower generation and watergate-spillway discharge. In addition, the upreservoir zone of Daecheong Reservoir could be vulnerable to green-tide by regulating discharge of the upstream dam. The issue of AAS was strongly related to the with and without of watergate-spillway discharge. The watergate-spillway discharge had a total of 25 times, it was maximum 17 days from July to September in the year. And the opening times and each duration of the watergate were 1~4 times and the range of 3~37 days, respectively. When the watergate opened, the issue of AAS was maintained to 13 years and the movement of water bodies and green-tide was great about five times than that of non-open, had a profound effect on prolonged AAS within reservoir. In Daecheong Reservoir, Chusori (CHU) area of the So-ok Stream was still showing serious symptoms green-tide levels in the summer, but Janggye (JAN) waters of the main reservoir was pointed out that more important. AAS will be operated by an absolutely consider the rainfall and hydrological effects around the watergate-spillway discharge. The measures of green-tide will be included in the limnological studies more suited to the characteristics of the watershed and reservoir of the our country. Finally, from now on, we will prepare the systematic management and guidelines for vulnerable zone water-blooms that are the source within the reservoir before the monsoon rather than waiting for the arrival of green-tide on the operating stations of AAS.

This review focuses on the hydrological definition and functions of hyporheic zone which has a feature of interaction between surface water and groundwater in natural stream system. This work also investigated how to measure the amount of flow exchange around this zone. As hyporheic zone shows heterogeneous feature due to groundwater level, river bed thickness, and hydraulic conductivity, spatio-temporal variation of interactions between surface-groundwater hydrologic exchange is to be analyzed. The methods to quantify this flow exchange can be classified according to field scale and status, the proper method should be adopted. Especially, Krause et al. (2007), showed that the flow exchange plays an important role in water balance in watershed and can be quantified by using integrated watershed hydrologic modeling.

해수유통 중인 화성호에서 수문학적 변동이 식물플랑크톤 군집과 적응전략에 미치는 영향을 파악하기 위하여 2012년 5월부터 10월까지 7회에 걸쳐 식물플랑크톤 종조성, 생물량, 환경변수를 조사하였다. 수문학적 이벤트 (해수유통, 강수량)는 화성호의 급격한 염분변동 (2.9~29.1 psu)과 함께 영양염, 투명도를 조절하였다. 식물플랑크톤 종조성은 매 조사마다 강 (class) 수준에서 급격히 변하였고, 클로로필-a는 9.7~104.1 μg L-1의 범위로 6월에 낮고 9월에 높았다. 다변량 분석결과, 식물플랑크톤 천이는 4개의 시기로 구분되었다. Phase I (5~6월)은 해수유통이 빈번한 고염-중온 시기로, 작은 크기의 Gymnodinium sp., Heterosigma akashiwo이 우점하였다. Phase II (7월, 9월)에는 집중호우와 바람의 영향으로 Cylindrotheca closterium가 우점하였고, Phase III (8월)에는 저염-고온 시기로 Oscillatoria spp.가 우점하였으며, Phase IV (10월)는 해수유통이 다시 증가하고 수온이 급감하면서 작은 편모조류인 unid. cryptomonad가 우점하였다. 화성호 식물플랑크톤 군집은 형태적, 생리적 특성에 따라 구분되는 세가지 적응전략, 즉 C (colonistinvasives), S (stress-tolerants), R (ruderals)전략에 따라 구분되었다. Phase I와 IV의 우점종은 CR-전략종으로써, 약한 성층조건을 선호하는 작은 크기의 기회종이였고, Phase II와 III의 우점종은 R-전략종으로써, 유입하천수의 교란에 적응된 중간 크기의 종이다. 이 결과는 향후 해수유통차단에 의한 성층강화가 현재의 식물플랑크톤군집을 더 작은 편모조류의 극우점으로 변화시킬 수 있음을 보여주었다. 결론적으로 화성호의 수문학적 이벤트(해수유통, 강수량)는 염분, 영양염, 성층환경 교란을 조절함으로써 식물플랑크톤의 천이와 대발생을 이끄는 중요한 요인임을 제시한다.

광양만에서 야광충 Noctiluca scintillans의 개체군 동태를 파악하기 위해서 수계지리학적 및 생리생태학적 특성을 2010부터 2012년까지 3년 동안 19 또는 20개 정점에서 조사를 수행하였다. 조사기간 동안 야광충은 하계의 수온범위가 15˚C에서 22˚C로, 염분이 25.0 psu에서 30.0 psu 사이의 환경조건에서 높은 밀도로 출현하였다. 이와 반대로, 그들의 개체군은 동계 4˚C의 낮은 수온 조건에서도 출현하였으나, 동계를 비롯하여 춘계, 추계에는 야광충의 개체수가 현저하게 감소하였다. 특히 27˚C 이상의 높은 수온과 12.0 psu 이하의 낮은 염분조건의 환경에서는 야광충 개체수의 사멸로 이어졌다. 야광충의 먹이원인 Chl.a 농도와는 동계, 춘계, 추계에는 양(+)의 상관관계가 성립되었고, 하계 야광충의 높은 밀도가 관찰되었을 때에는 Chl.a 농도와 음(-)의 상관관계를 보였다. 이는 야광충의 포식압에 의한 영향으로 생각되며, 하계와 같이 야광충의 개체수밀도가 높았을 때에는 식물 플랑크톤(Chl.a)을 현저하게 포식하여 음(-)의 상관성을 나타내었을 것이고, 나머지 계절의 양(+) 상관관계는 야광충의 개체수를 유지하는데 일정량 먹이원이 필요하였다는 것을 의미한다.

팔당호에서의 동물플랑크톤 군집 구조와 천이는 몬순 기후에 의한 강우사상의 변화와 수리∙수문학적 요인의 영향을 크게 받았다. 봄과 가을, 겨울 동안에는 강우량이 적은 평수기 혹은 갈수기로 팔당호의 수리학적 체류시간 이 길어짐에 따라 수체가 안정되어 동물플랑크톤 군집 변 화는 온대호수에서의 계절적인 천이 과정을 그대로 반영 하였다. 봄철에 크기가 작고 세대교번이 빠른 윤충류가 급 속히 증가하여 연중 최대 개체수를 나타냈으며, 이후 몸체가 큰 요각류와 지각류로 천이되었다. 봄에는 윤충류가 우점하여 점유율이 90% 이상으로 나타났으며 제1우점종 은 Keratella cochlearis였다. 요각류는 주로 유생(Copepodid, Nauplius)의 형태로 존재하였으며 지각류는 Bosmina longirostris가 주로 출현하였다. 여름에는 집중호우 의 영향으로 수체가 교란되고 팔당댐의 수문조작에 따른 방류량 증가로 동물플랑크톤이 하류로 떠내려가 동물플 랑크톤 개체수는 급감하였다. 집중호우 이후 수체가 안정 화됨에 따라 동물플랑크톤 군집 회복은 성장이 빠른 윤충 류를 위주로 이루어졌으며 가을 이후 수온 변화에 따라 동물플랑크톤 군집 밀도가 점차 감소하고 겨울에는 요각 류 유생(Copepodid, Nauplius)의 우점 비율이 증가하였 다. 불완전한 개방형 생태계를 이루고 있는 팔당호의 특 성상 동물플랑크톤 군집 변화는 기상 변화와 수리∙수문학적 요인에 크게 영향을 받고 있었으며, 특히 여름에는 국지성 집중호우의 빈도와 수량에 따라 동물플랑크톤의 군집 변화가 크게 좌우되었다.

In this study, the prediction technology of Hydrological Quantitative Precipitation Forecast (HQPF) was improved by optimizing the weather predictors used as input data for machine learning. Results comparison was conducted using bias and Root Mean Square Error (RMSE), which are predictive accuracy verification indicators, based on the heavy rain case on August 21, 2021. By comparing the rainfall simulated using the improved HQPF and the observed accumulated rainfall, it was revealed that all HQPFs (conventional HQPF and improved HQPF 1 and HQPF 2) showed a decrease in rainfall as the lead time increased for the entire grid region. Hence, the difference from the observed rainfall increased. In the accumulated rainfall evaluation due to the reduction of input factors, compared to the existing HQPF, improved HQPF 1 and 2 predicted a larger accumulated rainfall. Furthermore, HQPF 2 used the lowest number of input factors and simulated more accumulated rainfall than that projected by conventional HQPF and HQPF 1. By improving the performance of conventional machine learning despite using lesser variables, the preprocessing period and model execution time can be reduced, thereby contributing to model optimization. As an additional advanced method of HQPF 1 and 2 mentioned above, a simulated analysis of the Local ENsemble prediction System (LENS) ensemble member and low pressure, one of the observed meteorological factors, was analyzed. Based on the results of this study, if we select for the positively performing ensemble members based on the heavy rain characteristics of Korea or apply additional weights differently for each ensemble member, the prediction accuracy is expected to increase.

In meteorological data, various studies are being conducted to improve the prediction performance of rainfall with irregular patterns, unlike temperature and solar radiation with certain patterns. Especially in the case of the short-term forecast model for Dong-Nae Forecasts provided by the Korea Meteorological Administration (KMA), forecast data are provided at 6-hour intervals, and there is a limit to analyzing the impact of disasters. In this study, Hydrological Quantitative Precipitation Forecast (HQPF) information was generated by applying the machine learning method to Local ENsemble prediction system (LENS), Radar-AWS Rainrates (RAR), AWS and ASOS observation data and Dong-Nae Forecast provided by the KMA. Through the preprocessing process, the temporal and spatial resolutions of all the data were converted to the same resolution, and the predictor of machine learning was derived through the factor analysis of the predictor. Considering the processing speed and expandability, the XGBoost method of machine learning was applied, and the Probability Matching (PM) method was applied to improve the prediction accuracy of heavy rainfall. As a result of evaluating the HQPF performance produced for 14 heavy rainfall events that occurred in 2020, it was found that the predicted performance of HQPF was improved quantitatively and qualitatively.

In this investigation, the reservoir stability was reviewed using hydrological and physical examination. The results of the review showed that, Both sites were analyzed to lack embankment height and sidewall height in the event of flooding, and it was considered that measures to increase stability should be established in the future by adding more dam cest and increasing side wall of a spill way. In addition, analysis and research will be necessary for other reservoir deteriorated in the future.

For the purposes of enhancing usability of Numerical Weather Prediction (NWP), the quantitative precipitation prediction scheme by machine learning has been proposed. In this study, heavy rainfall was corrected for by utilizing rainfall predictors from LENS and Radar from 2017 to 2018, as well as machine learning tools LightGBM and XGBoost. The results were analyzed using Mean Absolute Error (MAE), Normalized Peak Error (NPE), and Peak Timing Error (PTE) for rainfall corrected through machine learning. Machine learning results (i.e. using LightGBM and XGBoost) showed improvements in the overall correction of rainfall and maximum rainfall compared to LENS. For example, the MAE of case 5 was found to be 24.252 using LENS, 11.564 using LightGBM, and 11.693 using XGBoost, showing excellent error improvement in machine learning results. This rainfall correction technique can provide hydrologically meaningful rainfall information such as predictions of flooding. Future research on the interpretation of various hydrologic processes using machine learning is necessary.

본 연구에서는 최근의 토양통 개정 결과를 반영하여 제주도를 대상으로 새로운 수문학적 토양군 분류 방법을 제시하였다. 또한 제시한 수문학적 토양군 분류 방법은 기존의 수문학적 토양군 분류 방법과 비교하여 평가하였다. 이를 위해 본 연구에서 제시한 수문학적 토양군 분류 방법과 기존의 수문학적 토양군 방법들을 적용하여 제주도 전체 유역을 대상으로 CN 값을 산정하고 그 결과를 비교하였다. 그 결과를 정리하면 다음과 같다. (1) 2007년 이후 개정된 토양통을 기존 토양통과 비교한 결과, 토성은 43개의 토양통에서, 배수등급은 1개의 토양통에서, 투수속도는 15개의 토 양통에서, 불투수층 깊이는 26개의 토양통에서 변경된 것으로 확인되었다. (2) 개정된 토양통을 반영하여 제주도의 수문학적 토양군을 분류한 결과, 1987년의 분류 방법을 따를 경우에는 수문학적 토양군 C군(46.43%)이 가장 많이 나타나나, 1995년의 분류 결과에서는 B군(27.69%)이, 2007년의 분류 결과에서는 D군(35.82%)이, 본 연구에서 제시한 분류 결과에서는 B군(49.25%)이 가장 많이 나타나는 것으로 나타났다. (3) 본 연구에서 제시한 방법을 제주도 전체에 적용한 경우에 추정된 CN 값은 기존 방법에 의한 값보다 작은 것으로 나타났다. 이 결과는 기존 방법을 적용할 경우 CN 값이 과대 추정되었을 가능성을 제시하는 것이기도 하다.

본 연구에서는 Lee et al.(2018)의 연구에서 제시한 새로운 수문학적 토양군 분류 방법을 제주도의 3개의 하천유역(중문천, 천미천, 한천)에 적용하고 그 적용성을 평가하였다. 적용의 결과로서 이들 세 유역의 CN 값이 산정되었으며, 이 값은 기존의 세 가지 방법론을 적용한 결과와 비교하였다. 또한 제주도에서의 침투, 강우-유출 해석 등에 사용되는 수문학적 토양군 분류와 관련된 선행 연구들을 검토하여 선택된 방법론에 따라 수문학적 토양 군 분류 결과가 어떻게 다른지를 평가하였다. 그 결과를 정리하면 다음과 같다. (1) 수문학적 토양군 분류 방법에 따른 제주도 대표 유역의 수문학적 토양군 분류 결과를 비교한 결과, Lee et al.(2018)의 토양군 분류 방법을 적용하는 경우에는 B군이 크게 나타났다. 이는 Hu and Jung(1987)의 분 류 방법을 적용하는 경우에서는 C군과 D군이, Jung et al.(1995)의 분류 방법을 적용하는 경우에서 A군과 C군, 마지막으로 RDA(2007)의 분류 방 법을 적용하는 경우에서는 D군이 상대적으로 크게 나타나는 결과와 비교된다. (2) Lee et al.(2018)의 수문학적 토양군 분류 방법을 제주도의 3개 대표 유역에 적용한 결과, 3개 유역 모두 기존 방법에 비해 가장 작은 CN 값이 추정되었다. 마지막으로 (3) 제주도에서의 강우-유출과 관련된 연구를 검토한 결과, 제주도 유역의 CN 값은 기존 방법에 의해 추정된 것에 비해 작을 가능성이 크고, 또한 초기 손실은 0.2S 이상의 큰 값을 가질 것으로 판단되었다.

In this study, hydrological safety assessment on dam facilities was estimated using dam hydrological safety evaluation result and in-depth inspection assessment result and considering climate change scenario. Hydrological safety assessment of the existing dam was performed by calculating the PMP/PMF using the climate change scenario. In this study, it was evaluated hydrological safety assessment of existing dam considering climate change scenario(RCP 8.5).

본 연구는 기상학적 및 수문학적 가뭄지수를 이용하여 가뭄사상의 첨두 심도 발생시점과 가뭄발생 기간에 대한 연구를 수행하였다. 연구를 수행하기 위해 사용한 가뭄지수로 기상학적 가뭄지수는 표준강수지수(Standardized Precipitation Index, SPI)를 사용하였으며, 수문학적 가뭄지수로는 하천가뭄지수(Streamflow Drought Index, SDI)와 표준하천유량지수(Standardized Streamflow Index, SSI)를 이용하였다. 연구 대상지역은 농촌과 도시가 공존하는 청미천 유역을 선택하였으며, 평가기간은 1985년 1월부터 2017년 6월까지 32.5년을 평가하였다 하천유량은 SWAT 모형을 이용하여 산정하였다. 수집한 데이터를 이용하여 가뭄지수를 산정한 후에 시계열을 토대로 가뭄의 특성을 분석하였다. 그 결과 수문학적 가뭄은 기상학적 가뭄이 발생한 후에 발생하는 것을 확인할 수 있다. SDI가 SSI보다 SPI와의 첨두 발생시점, 가뭄 시작일의 차이와 평균 가뭄기간이 더 크게 나지만, 가뭄지수의 심도를 비교해보면 일반적으로 SSI가 SDI 보다 심각한 심도를 나타내고 있다. 그러므로 가뭄의 특성을 확인하기 위해서는 기상학적, 수문학적 가뭄지수 등 다양한 가뭄지수를 검토해야 한다.

물순환에 영향을 미치는 원인과 결과를 분석하는 기존의 연구들은 대부분 강우-유출모형을 사용하고 있어 모형의 구축 및 매개변수의 보정과 검증에 많은 노력이 필요하다. 본 연구에서는 수문기상자료만을 이용하여 유량의 변동성분을 정량화할 수 있는 수문학적 민감도 분석기법을 화천댐 상류유역에 적용하고 화천댐 유입량에 대한 1967~2017년 동안의 변동량을 자연적 요인과 인위적 요인으로 분리하여 제시하였다. 다양한 변동점 탐색기법을 사용한 결과 1999년이 통계적으로 유의한 변동점으로 탐색되었으며, 이를 활용하여 수문학적 민감도 분석을 5가지의 Budyko 함수들을 이용하여 산정한 결과 평균적으로 18.99억 m3/y의 유입량 감소가 임남댐 건설로 인하여 발생된 것을 알 수 있었다. 이와 같은 결과는 기존 연구자들의 화천댐 유입량 감소량에 비해 다소 크게 산정된 결과이며, 이는 2000년대 이후 증가된 강우량 및 화천댐 유입량의 감소가 주된 영향을 미친 결과로 추정된다. 향후 월별, 계절별 단위의 분석이 추가로 연구될 필요가 있으며, 미래의 기후변화 상황을 고려한 예측을 통한 실효성 있는 계획이 수립될 필요가 있을 것으로 판단된다.