hess-2023-252 “Towards Interpretable LSTM-based Modelling of Hydrological Systems” LA.De la Fuente, MR.Ehsani, HV.Gupta, LE.Condon

This re-submission has a done a good job of addressing comments and corrections. Now it reads better and makes definite linkages between AI/ML and traditional hydrologic modelling that do aid in interpretability of LSTM models. Further they confirm the published experience of hydrologic modellers with regard to results in water-limited versus energy-limited catchments, consideration of the most important inputs, and the number and arrangement of “storages” when constructing their models.

Thank you for allowing me to review your paper for the second time. I appreciate you including some of my previous suggestions in the submission to clarify your experiments and scientific findings.

I propose that this paper be accepted to HESS subject to technical corrections (see comments below). 

Best,

Tadd Bindas

Minor Comments:

Line 90: Grammatical fix: “Explore the similarities and differences between LSTM models and the hydrologic reservoir model.”

Table 1: Are the brackets supposed to be facing outward? (ex: o = ]0,1[ ) Assuming this is the case since this was a minor comment from my previous paper comments. 

Figure 6/7: Can you change the scatter plot dots to a color other than yellow? The choice of color makes the points hard to identify individually.

The authors have revised all my concerns. I recommend publishing this article.