Articles | Volume 26, issue 21
https://doi.org/10.5194/hess-26-5515-2022
https://doi.org/10.5194/hess-26-5515-2022
Research article
 | 
07 Nov 2022
Research article |  | 07 Nov 2022

Effects of passive-storage conceptualization on modeling hydrological function and isotope dynamics in the flow system of a cockpit karst landscape

Guangxuan Li, Xi Chen, Zhicai Zhang, Lichun Wang, and Chris Soulsby

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Cited articles

Adinehvand, R., Raeisi, E., and Hartmann, A.: A step-wise semi-distributed simulation approach to characterize a karst aquifer and to support dam construction in a datascarce environment, J. Hydrol., 554, 470–481, https://doi.org/10.1016/j.jhydrol.2017.08.056, 2017. 
Ala-aho, P., Tetzlaff, D., McNamara, J. P., Laudon, H., and Soulsby, C.: Using isotopes to constrain water flux and age estimates in snow-influenced catchments using the STARR (Spatially distributed Tracer-Aided Rainfall–Runoff) model, Hydrol. Earth Syst. Sci., 21, 5089–5110, https://doi.org/10.5194/hess-21-5089-2017, 2017. 
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Benettin, P., Kirchner, J. W., Rinaldo, A., and Botter, G.: Modeling chloride transport using travel time distributions at Plynlimon, Wales, Water Resour. Res., 51, 3259–3276, https://doi.org/10.1002/2014WR016600, 2015. 
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Short summary
We developed a coupled flow–tracer model to understand the effects of passive storage on modeling hydrological function and isotope dynamics in a karst flow system. Models with passive storages show improvement in matching isotope dynamics performance, and the improved performance also strongly depends on the number and location of passive storages. Our results also suggested that the solute transport is primarily controlled by advection and hydrodynamic dispersion in the steep hillslope unit.
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