Articles | Volume 30, issue 12
https://doi.org/10.5194/hess-30-3741-2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
A coupled surface water-groundwater multi-objective optimization framework for coordinated water-ecosystem-agriculture management in arid inland river basin
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- Final revised paper (published on 22 Jun 2026)
- Supplement to the final revised paper
- Preprint (discussion started on 15 Jan 2026)
- Supplement to the preprint
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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CC1: 'Comment on egusphere-2026-55', Nima Zafarmomen, 26 Jan 2026
- AC1: 'Reply on CC1', Xiankui Zeng, 16 Mar 2026
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RC1: 'Comment on egusphere-2026-55', Anonymous Referee #1, 30 Jan 2026
- AC2: 'Reply on RC1', Xiankui Zeng, 16 Mar 2026
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RC2: 'Comment on egusphere-2026-55', Anonymous Referee #2, 03 Feb 2026
- AC3: 'Reply on RC2', Xiankui Zeng, 16 Mar 2026
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RC3: 'Comment on egusphere-2026-55', Anonymous Referee #3, 20 Feb 2026
- AC4: 'Reply on RC3', Xiankui Zeng, 16 Mar 2026
Peer review completion
AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
ED: Reconsider after major revisions (further review by editor and referees) (29 Mar 2026) by Yonggen Zhang
AR by Xiankui Zeng on behalf of the Authors (08 Apr 2026)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (20 Apr 2026) by Yonggen Zhang
RR by Anonymous Referee #2 (20 Apr 2026)
RR by Anonymous Referee #1 (22 May 2026)
RR by Anonymous Referee #3 (26 May 2026)
ED: Publish subject to technical corrections (04 Jun 2026) by Yonggen Zhang
AR by Xiankui Zeng on behalf of the Authors (06 Jun 2026)
Author's response
Manuscript
This paper presents a coupled surface water–groundwater–agriculture multi-objective optimization framework for coordinated management of water resources, ecosystems, and agricultural production in the Tarim River mainstream, an arid inland river basin in China. The authors integrate a basin-scale SRM–GSFLOW hydrological model with a multi-objective optimization model solved using NSGA-III, targeting four competing objectives: maximizing agricultural economic benefit per unit irrigation water (fAB), maximizing groundwater level recovery (fGL), maximizing terminal lake area (fLA), and minimizing agricultural nitrogen load (fTN). Well written and fitted for the publication.
1) Several figures (e.g., Figures 4–7) contain dense scatter plots and parallel coordinate lines that are difficult to interpret at first glance. Adding brief quantitative annotations (e.g., correlation coefficients or key threshold markers) would improve readability and interpretability.
2) The manuscript alternates between the terms WEA and WAE when referring to the water–ecosystem–agriculture system. Please standardize terminology throughout the text for consistency.
3) Although the surrogate model performance is strong (R² =0.98), the paper would benefit from explicitly stating how surrogate prediction errors may influence decision-making, especially near Pareto front extremes where trade-offs are most sensitive.
4) While the study carefully calibrates the coupled SRM–GSFLOW model and validates the surrogate RBF-NN, uncertainty is not explicitly propagated through the optimization results. Key sources of uncertainty, such as climate forcing, groundwater parameters, crop water requirements, and fertilizer coefficients, may significantly affect Pareto fronts and identified “compromise solutions.” I recommend to add this limitation in the conclusion part.
5) I do strongly suggest that the authors consider relevant studies that have explored the "assimilation of Sentinel-derived leaf area index to improve the representation of surface–groundwater interactions in irrigation districts". Citing and briefly discussing such work would strengthen the linkage between the proposed framework and existing literature.