• 한국수자원학회논문집
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• 제45권10호
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• pp.1051-1067
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• 2012

겨울철 작물재배를 위해서 비닐하우스 보온을 위한 수막시설의 이용이 늘어나고 있어 과다한 지하수 이용에 따른 수위 강하 및 하천수 감소를 유발하고 있다. 따라서 수막시설재배 지역에서의 지하수 양수가 지하수 대수층과 연결된 하천에 어떠한 영향을 미치는 지를 정량적으로 평가해야 할 필요가 있다. 본 연구에서는 경기도 이천시 신둔면 수하리 일대 수막시설재배지역에 지하수위와 온도를 계측하기 위한 지하수 관측공을 제내지와 제외지에 설치하고 관측 결과를 분석하여 지하수 양수에 따른 하천-지하수 상호유동계의 변화를 평가하였다. 연구대상지역은 수위와 수온 관측 결과, 수막시설재배기간 동안 지하수 양수의 영향으로 하천수가 지하수계로 유입되는 손실하천의 양상을 나타내었다. 하천바닥층에 대해 침윤계 실험을 통해서 유도한 수두차와 침윤량간의 관계에 자동관측된 수위자료를 대입하여 하천과 지하수계 상호간 유동량의 연속적인 변화를 산정한 결과 수막시설재배가 한창인 2월말에는 지하수 이용량의 약 16% 만큼의 하천수가 감소하는 것으로 분석되었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2011년도 학술발표회
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• 한국지하수토양환경학회지:지하수토양환경
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• 제21권1호
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• pp.61-71
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• 2016

Visual MODFLOW was used for quantifying stream-aquifer interactions caused by seasonal groundwater pumping. A hypothetical conceptual model was assumed to represent a stream-aquifer system commonly found in Korea. The model considered a two-layered aquifer with the upper alluvium and the lower bedrock and a stream showing seasonal water level fluctuations. Our results show that seasonal variation of the stream depletion rate (SDR) as well as the groundwater depletion depends on the stream depletion factor (SDF), which is determined by aquifer parameters and the distance from the pumping well to the stream. For pumping wells with large SDF, groundwater was considerably depleted for a long time of years and the streamflow decreased throughout the whole year. The impacts of return flow were also examined by recalculating SDR with an assumed ratio of immediate irrigation return flow to the stream. Return flow over 50% of pumping rate could increase the streamflow during the period of seasonal pumping. The model also showed that SDR was affected by both the conductance between the aquifer and the stream bed and screen depths of the pumping well. Our results can be used for preliminary assessment of water budget analysis aimed to plan an integrated management of water resources in riparian areas threatened by heavy pumping.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.287-287
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• 2023

Surface water-groundwater interaction (SWGI) is an important hydrological process that influences both the quantity and quality of water resources. However, regional scale SWGI model calibration and uncertainty analysis have been a challenge because integrated models inherently carry a vast number of parameters, modeling assumptions, and inputs, potentially leaving little time and budget to explore questions related to model performance and forecasting. In this study, we have proposed the application of iterative ensemble smoother (IES) for uncertainty analysis and calibration of the widely used integrated surface-subsurface model, SWAT-MODFLOW. SWAT-MODFLOW integrates Soil and Water Assessment Tool (SWAT) and a three-dimensional finite difference model (MODFLOW). The model was calibrated using a parameter estimation tool (PEST). The major advantage of the employed IES is that the number of model runs required for the calibration of an ensemble is independent of the number of adjustable parameters. The pilot point approach was followed to calibrate the aquifer parameters, namely hydraulic conductivity, specific storage, and specific yield. The parameter estimation process for the SWAT model focused primarily on surface-related parameters. The uncertainties both in the streamflow and groundwater level were assessed. The work presented provides valuable insights for future endeavors in coupled surface-subsurface modeling, data collection, model development, and informed decision-making.

• 한국수자원학회논문집
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• 제54권9호
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• pp.681-692
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• 2021

식생 프로세스는 증발산 제어를 통해 강우 유출 프로세스에 상당한 영향을 미치지만, 개념적인 집중형 수문 모형에서는 거의 고려되지 않는다. 본 연구는 인공위성에서 원격으로 감지된 엽면적지수 자료를 표현하는 생태 모듈을 수문 분할 모듈에 통합하여 합천댐 유역에 대한 모형 성능을 평가하였다. 제안된 생태 수문 모형은 습윤 지역의 생태수문 프로세스를 더 잘 표현하기 위하여 크게 세 가지 주요한 특징을 가진다. 1) 식생의 성장률은 유역의 물 부족 스트레스에 의해 제약을 받는다. 2) 식생의 최대 성장은 유역 기후에 의한 에너지에 의해 제약을 받는다. 3) 식생과 대수층의 상호작용이 반영된다. 제안된 모형은 유역 단위의 수문 성분과 식생 동역학을 동시에 모의한다. SCEM 알고리즘에 의해 추정된 모형 매개변수를 이용한 검증 결과로부터 아래와 같은 발견할 수 있었다. 1) 엽면적지수와 하천유량 자료를 이용하여 생태수문모형의 매개변수를 추정하는 것이 생태 모듈이 없는 수문 모형과 비슷한 정확도 및 견고함으로 하천유량을 예측할 수 있다. 2) 필터링이 안된 원격으로 감지된 엽면적지수를 그대로 입력자료로 이용하는 것은 하천유량 예측에 도움이 안된다. 3) 통합된 생태수문모형은 엽면적지수의 계절적인 변동성에 대한 우수한 추정치를 제공할 수 있다.