Improving the Resolution of GRACE/InSAR Groundwater Storage Estimations Using a New Subsidence Feature Weighted Combination Scheme
, Wei Zheng 1,2,*,†, Wenjie Yin 3,†, Guohua Kang 1, Qihuan Huang 4 and Yifan Shen 5
Round 1
Reviewer 1 Report
Thank you for inviting me to review the entitled manuscript "Improving the resolution of GRACE/InSAR groundwater storage estimations using a new subsidence feature weighted combination scheme". The manuscript is relatively complete and very interesting for readers. It can be published with minimum effort. I encouraged the authors to consider these comments and revise the manuscript accordingly.
Line#85-98 I believe the main section of this paper is spatial downscaling to improve the resolution of GRACE data. The literature about spatial downscaling, models, and data is poorly written. It, therefore, demanded adding more details about why spatial downscaling is applied, how it works, and what methods are applicable to perform it with more recent literature. I believe these studies can be helpful for lecture and methods point of view:
1-. Spatial Downscaling of GRACE Data Based on XGBoost Model for Improved Understanding of Hydrological Droughts in the Indus Basin Irrigation System (IBIS). Remote Sensing. 2023 Jan;15(4):873: 2- Spatial downscaling of GRACE TWSA data to identify spatiotemporal groundwater level trends in the Upper Floridan Aquifer, Georgia, USA. remote sensing. 2019 Nov 23;11(23):2756.: 3- Combining APHRODITE Rain Gauges-Based Precipitation with Downscaled-TRMM Data to Translate High-Resolution Precipitation Estimates in the Indus Basin. Remote Sensing, 15(2), p.318: 4- A self‐calibration variance‐component model for spatial downscaling of GRACE observations using land surface model outputs. Water Resources Research, 57(1), p.e2020WR028944: 5- Constructing high-resolution groundwater drought at spatial-temporal scale using GRACE satellite data based on machine learning in the Indus Basin. Journal of Hydrology, 612, p.128295: 5- Reconstructing high-resolution gridded precipitation data using an improved downscaling approach over the high altitude mountain regions of Upper Indus Basin (UIB). Science of The Total Environment, 784, p.147140.: 6- Improving the spatial resolution of GRACE-derived terrestrial water storage changes in small areas using the machine learning spatial downscaling method. Remote Sensing, 13(23), p.4760: 7- Combining downscaled-GRACE data with SWAT to improve the estimation of groundwater storage and depletion variations in the Irrigated Indus Basin (IIB). Science of the Total Environment, 838, p.156044.
These studies have used several linear and nonlinear machine models and you can expand the literature of spatial downscaling and highlight why you are using the NSFWC scheme.
Introduction: List the main goal of the study along with sub-objectives to achieve it.
Line# 160 Define GLDAS NOAH??
The resolution of Fig. 2 is soo poor.
Equation: 3 What is SMSA SWSA? Also, what is the assumption to consider only these two components while ignoring the canopy water storage and surface runoff? The authors need to justify it.
Other sections of the manuscript are written well. Just minor grammar mistakes that need to check.
The manuscript can be accepted with minor revisions.
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
Dear All,
I have posted my comments on the file.
Best regards,
Comments for author File: Comments.pdf
Author Response
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Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Dear All,
The manuscript has been improved greatly. It could be accepted for publication.
Great work
