Articles | Volume 24, issue 12
https://doi.org/10.5194/hess-24-6075-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-6075-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Dec 2020
Research article |
| 23 Dec 2020
| 23 Dec 2020
Key challenges facing the application of the conductivity mass balance method: a case study of the Mississippi River basin
Hang Lyu
CORRESPONDING AUTHOR
Key Laboratory of Groundwater Resources and Environment, Jilin
University, Ministry of Education, Changchun 130026, China
Jilin Provincial Key Laboratory of Water Resources and Environment,
Jilin University, Changchun 130026, China
Chenxi Xia
Key Laboratory of Groundwater Resources and Environment, Jilin
University, Ministry of Education, Changchun 130026, China
Jilin Provincial Key Laboratory of Water Resources and Environment,
Jilin University, Changchun 130026, China
Jinghan Zhang
Key Laboratory of Groundwater Resources and Environment, Jilin
University, Ministry of Education, Changchun 130026, China
Jilin Provincial Key Laboratory of Water Resources and Environment,
Jilin University, Changchun 130026, China
Bo Li
Key Laboratory of Groundwater Resources and Environment, Jilin
University, Ministry of Education, Changchun 130026, China
Jilin Provincial Key Laboratory of Water Resources and Environment,
Jilin University, Changchun 130026, China
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Groundwater level dynamics under freeze-thaw conditions remain unclear. We use interpretable deep learning to simulate water table changes and identify seasonal drivers in seasonally frozen regions. During freeze-thaw, changes in soil water potential cause two-way exchange between soil water and groundwater, while rainfall, runoff, and irrigation dominate in other periods. These insights inform groundwater modeling and management in cold regions.
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Groundwater level dynamics under freeze-thaw conditions remain unclear. We use interpretable deep learning to simulate water table changes and identify seasonal drivers in seasonally frozen regions. During freeze-thaw, changes in soil water potential cause two-way exchange between soil water and groundwater, while rainfall, runoff, and irrigation dominate in other periods. These insights inform groundwater modeling and management in cold regions.
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Short summary
Baseflow separation plays a critical role in science-based management of water resources. This study addressed key challenges hindering the application of the generally accepted conductivity mass balance (CMB). Monitoring data for over 200 stream sites of the Mississippi River basin were collected to answer the following questions. What are the characteristics of a watershed that determine the method suitability? What length of monitoring data is needed? How can the parameters be more accurate?
Baseflow separation plays a critical role in science-based management of water resources. This...
