With the resubmitted version of their manuscript, Xu et al provide a significantly improved version of their work. The manuscript was shortened to add more focus. They provide a sound explanation why they chose to apply 2 methods for sensitivity analysis. A better link between previous research at the study site and this study was established and the elaboration of parts of the sensitivity analysis methods was improved.
I agree with the authors that parameter correlation does not have to be addressed in the frame of the local sensitivity analysis as (1) local parameter analysis is by definition very limited in identifying parameter interactions and (2) parameter interactions are explicitly addressed by Morris’s method, which is by definition a “global” parameter sensitivity analysis scheme.
Some confusion came up addressing my comment on including more comparison to the work of others. Indeed, this was partially addressed by including Shoemaker et al. (2004) in the discussion but the link to studies that used sensitivity in karst modelling is still weak. The authors indicate that they are aware of just few karst studies using sensitivity analysis but a quick scan of the literature revealed couple of studies using local (Oehlmann et al., 2014), regional (Chang et al., 2017; Hartmann et al., 2015) and global sensitivity analysis (Chen et al., 2017; Hartmann et al., 2013) in karst modelling for both lumped and distributed modelling approaches.
Including some of these (or similar) references to their manuscript will strengthen the state of the art of karst sensitivity analysis as well as the discussion. After these very minor suggestions have been applied I would feel very confident recommending this study for publication in Hydrology and Earth System Sciences.
References
Chang, Y., Wu, J., Jiang, G. and Kang, Z.: Identification of the dominant hydrological process and appropriate model structure of a karst catchment through stepwise simplification of a complex conceptual model, J. Hydrol., 548, 75–87, doi:http://dx.doi.org/10.1016/j.jhydrol.2017.02.050, 2017.
Chen, Z., Hartmann, A. and Goldscheider, N.: A new approach to evaluate spatiotemporal dynamics of controlling parameters in distributed environmental models, Environ. Model. Softw., 87, 1–16, doi:10.1016/j.envsoft.2016.10.005, 2017.
Hartmann, A., Wagener, T., Rimmer, A., Lange, J., Brielmann, H. and Weiler, M.: Testing the realism of model structures to identify karst system processes using water quality and quantity signatures, Water Resour. Res., 49(6), 3345–3358, doi:10.1002/wrcr.20229, 2013.
Hartmann, A., Gleeson, T., Rosolem, R., Pianosi, F., Wada, Y. and Wagener, T.: A large-scale simulation model to assess karstic groundwater recharge over Europe and the Mediterranean, Geosci. Model Dev., 8(6), 1729–1746, doi:10.5194/gmd-8-1729-2015, 2015.
Oehlmann, S., Geyer, T., Licha, T. and Sauter, M.: Reduction of the ambiguity of karst aquifer modeling through pattern matching of groundwater flow and transport, Hydrol. Earth Syst. Sci., 16, 11593, doi:10.5194/hess-19-893-2015, 2014. |