Xiaoliang Sun, Yao Du, Jiawen Xu, Hao Tian, Yamin Deng, Yiqun Gan, Yanxin Wang
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引用次数: 0
Abstract
Lacustrine groundwater discharge (LGD) is an important water and nutrient source for lakes. Despite its importance, high-resolution quantifying the spatial variability of LGD remains challenging. Particularly, little studies have explored the impact of the interaction zone structure between lakes and aquifers on this variability. Present study presents a high-resolution quantitative estimation of LGD spatial patterns in an oxbow lake by combining thermal remote sensing with a 222Rn mass balance model. The vertical distribution characteristics of various parameters including lake water temperature, 222Rn concentration, electrical conductivity, and δ18O were examined to elucidate the influence of groundwater on the distribution pattern of lake surface temperature (LST). Regression equations were formulated to correlate LST with lake water 222Rn concentration across different water depth zones, enabling the inverse calculation of the 222Rn concentration in the water of the entire lake. Utilizing a 222Rn mass balance model across all grid points, the LGD rate was determined to vary from 0 to 330.96 mm/d, with an average of 55.02 ± 19.61 mm/d. In shallow water zones, the accumulation of lacustrine sediments has resulted in isolation from confined aquifers, causing LGD to primarily occur as springs in nearshore lake areas. Conversely, the direct connection between the deepwater zone of the lake and the water-rich confined aquifer has resulted in a higher LGD rate in the lake interior. Present study not only offers a novel approach for quantifying the spatial patterns of LGD but also provides valuable insights for LGD studies conducted in lakes globally.
期刊介绍:
Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.