• Title/Summary/Keyword: groundwater-streamflow interaction

Search Result 5, Processing Time 0.026 seconds

Change of Groundwater-Streamflow Interaction according to Groundwater ion in a Green House Land (비닐하우스 지역의 지하수 양수에 따른 지하수-하천수 상호 유동 변화 분석)

  • Kim, Nam Won;Lee, Jeong Woo;Chung, Il Moon;Kim, Chang Hwan
    • Journal of Korea Water Resources Association
    • /
    • v.45 no.10
    • /
    • pp.1051-1067
    • /
    • 2012
  • Increased use of water curtain facilities to keep green house warm during winter cultivation has been known to cause excessive groundwater ion which might lead to decline of groundwater level, resulting in streamflow depletion. Therefore it is required to quantitatively assess the effects of groundwater ion on the streamflow depletion such as magnitude and extent. The objective of this study is to assess the change of stream-aquifer interaction according to groundwater ion near stream. To this end, a green house cultivation land in Sooha-ri, Sindun-myun, Icheon-si, Gyonggi-do was selected as a field experimental site, and monitoring wells were established near and within stream to observe the water level and temperature changes over a long period of time. From the observed water level and temperature data, it was found that the river reach of interest changed to a losing stream pattern during the winter cultivation season due to groundwater level decline around pumping wells near the stream. The continuous exchange rates between stream and aquifer were estimated by plugging the observed water level data series into the experimental relation between head difference and exchange rate, showing the streamflow depletion by 16% of the groundwater pumping rate in Feb, 2011.

Assessing the Impact of Climate Change on Water Resources: Waimea Plains, New Zealand Case Example

  • Zemansky, Gil;Hong, Yoon-Seeok Timothy;Rose, Jennifer;Song, Sung-Ho;Thomas, Joseph
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2011.05a
    • /
    • pp.18-18
    • /
    • 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.

  • PDF

Impacts of Seasonal Pumping on Stream Depletion (계절양수가 하천건천화에 미치는 영향)

  • Lee, Hyeonju;Koo, Min-Ho;Lim, Jinsil;Yoo, Byung-Ho;Kim, Yongcheol
    • Journal of Soil and Groundwater Environment
    • /
    • v.21 no.1
    • /
    • pp.61-71
    • /
    • 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.

Calibration and uncertainty analysis of integrated surface-subsurface model using iterative ensemble smoother for regional scale surface water-groundwater interaction modeling

  • Bisrat Ayalew Yifru;Seoro Lee;Woon Ji Park;Kyoung Jae Lim
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2023.05a
    • /
    • pp.287-287
    • /
    • 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.

  • PDF

Conceptual eco-hydrological model reflecting the interaction of climate-soil-vegetation-groundwater table in humid regions (습윤 지역의 기후-토양-식생-지하수위 상호작용을 반영한 개념적인 생태 수문 모형)

  • Choi, Jeonghyeon;Kim, Sangdan
    • Journal of Korea Water Resources Association
    • /
    • v.54 no.9
    • /
    • pp.681-692
    • /
    • 2021
  • Vegetation processes have a significant impact on rainfall runoff processes through evapotranspiration control, but are rarely considered in the conceptual lumped hydrological model. This study evaluated the model performance of the Hapcheon Dam watershed by integrating the ecological module expressing the leaf area index data sensed remotely from the satellite into the hydrological partition module. The proposed eco-hydrological model has three main features to better represent the eco-hydrological process in humid regions. 1) The growth rate of vegetation is constrained by water shortage stress in the watershed. 2) The maximum growth of vegetation is limited by the energy of the watershed climate. 3) The interaction of vegetation and aquifers is reflected. The proposed model simultaneously simulates hydrologic components and vegetation dynamics of watershed scale. The following findings were found from the validation results using the model parameters estimated by the SCEM algorithm. 1) Estimating the parameters of the eco-hydrological model using the leaf area index and streamflow data can predict the streamflow with similar accuracy and robustness to the hydrological model without the ecological module. 2) Using the remotely sensed leaf area index without filtering as input data is not helpful in estimating streamflow. 3) The integrated eco-hydrological model can provide an excellent estimate of the seasonal variability of the leaf area index.