the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Jun 2026
Role of Forest Stand Structure in Groundwater Storage Decline in the Three-North Shelterbelt Forest Region, China
Abstract. Vegetation restoration has significantly altered terrestrial ecosystem dynamics in the Three-North Shelterbelt Forest region (TNSFR), but its impacts on groundwater storage (GWS) remain poorly quantified, particularly as forest stand structure is rarely integrated. This study integrated terrestrial water storage data, land surface model simulation results, and in-situ groundwater observations to assess the spatiotemporal GWS variations. Furthermore, combining meteorological data, forest inventory data, yearbook statistics, and Normalized Difference Vegetation Index (NDVI) data explores how climate and vegetation restoration affect GWS changes. Results show that vegetation restoration in the TNSFR has exhibited a widespread upward trend, with NDVI increasing at an average rate of 0.015 decade⁻¹ over the past two decades. Concurrently, GWS has declined significantly with a mean rate of -5.47 mm yr⁻¹, primarily concentrated in regions with substantial increases in forest coverage. In groundwater-dependent ecosystems, monocultures show higher water consumption than mixed forests, and groundwater decline in mature coniferous forests is linked to high-water-consumption spruce species. Structural equation modeling confirms vegetation restoration as the leading anthropogenic driver of GWS decline in the TNSFR. This study highlights the need for tailored ecological strategies for coordinating ecological recovery with sustainable water management in dryland areas.
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Status: open (until 29 Jul 2026)
- RC1: 'Comment on egusphere-2026-2596', Anonymous Referee #1, 30 Jun 2026 reply
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RC2: 'Comment on egusphere-2026-2596', Anonymous Referee #2, 07 Jul 2026
reply
This manuscript investigates the relationship between vegetation restoration, with particular emphasis on forest stand structure, on groundwater storage changes in the Three-North Shelterbelt Forest Region of China. The topic is relevant and timely, as understanding the trade-offs between ecological restoration and groundwater sustainability is important for dryland management. The consideration of forest age and species composition represents an interesting contribution that extends previous studies based primarily on vegetation greenness or land-cover changes.
Overall, the study is potentially suitable for publication in HESS. However, the manuscript currently presents several methodological and presentation issues. Important assumptions are insufficiently justified, several conclusions appear stronger than the evidence presented, and many results are difficult to evaluate because they are either insufficiently explained or not adequately supported by figures or quantitative analyses. I therefore recommend major revisions before the manuscript can be considered for publication.
My main comments and suggestions are provided below.
- The validation strategy should be described more clearly. It is not entirely clear how the comparison between the GRACE-derived GWSA and groundwater observations was performed, particularly considering the scale mismatch between point observations and the 0.25° GRACE product. Since the validation represents an important component of the study, I also recommend moving at least part of the figures currently presented in the Supplementary Information (Figs. S2–S5) into the main manuscript.
- Several methodological choices require further justification. For example, please explain the rationale for selecting precipitation, evapotranspiration and temperature simultaneously as climatic predictors, particularly given the close relationship between temperature and evapotranspiration. Likewise, Equation (3), which downscales provincial socioeconomic statistics to the grid scale, requires a much clearer explanation. In particular, the definition of the reference gridded dataset (Gridref) and the assumptions underlying this downscaling approach should be described in greater detail.
- Several conclusions presented throughout the Results are insufficiently supported by figures or quantitative analyses. For example: (i) the locations of groundwater gain and loss regions are not clearly shown; (ii) greening hotspots are discussed without explaining how they were identified; (iii) trends for grassland expansion areas are mentioned but not illustrated; (iv) the methodology used to derive the trends shown in Fig. 8b is unclear, and their statistical significance is not reported. Please ensure that all major conclusions are directly supported by figures, quantitative results, or statistical analyses.
- In several places, the Discussion appears to draw stronger conclusions than are directly supported by the analyses. In particular, statements implying that differences in groundwater decline are directly driven by specific forest types or tree species should be interpreted more cautiously, as the analyses presented are largely observational and do not fully separate the effects of forest structure from other spatially varying factors (e.g., climate, topography, irrigation, or geology). I encourage the authors to better discuss the limitations of their approach and moderate some of the causal interpretations.
- The forest structure analysis relies on National Forest Inventory data collected during 2014–2018, whereas groundwater storage trends are calculated for 2003–2023. Please discuss the implications of this temporal mismatch and justify the assumption that forest age, species composition, and stand structure during the inventory period are representative of the entire groundwater trend period.
- The Discussion focuses primarily on the results related to forest structure and the SEM analysis, whereas other important findings (e.g. groundwater trends, climatic controls and validation) receive limited discussion. I encourage the authors to provide a more balanced discussion that places all major findings into the context of previous literature and discusses the limitations of the study.
- Several figures would benefit from improvements. Figure 1 could better illustrate the location of the study area (e.g. by slightly zooming out the overview map) and panels b–c could be enlarged. Figure 2 requires a much more informative caption explaining the different steps of the workflow. In addition, some figure references appear out of sequence (e.g. Fig. 9 before Fig. 6; lines 256–259), and certain figure panels (e.g. Fig. 6g) are difficult to interpret because the captions provide insufficient explanation.
- Lines 77–78: Please provide additional information on how the aridity classification shown in Fig. 1c was obtained. Although the manuscript refers to the Aridity Index (AI), it does not explain how the index was calculated (or whether it was taken directly from the referenced dataset) nor the threshold values used to define the five climate classes. Including this information in the Methods would improve the reproducibility and interpretation of the analysis.
- Line 104: Please specify the temporal resolution of the China Land Cover Dataset. Does the dataset provide annual land cover maps for the entire 2003–2023 period, or were only selected years available?
- Line 210: The manuscript states that 77.06% of the study area experienced “significant negative trends” in GWS. Please clarify whether this percentage refers to statistically significant trends (e.g. p < 0.05) identified using the Mann–Kendall test. In addition, the reported values of −40 mm and −21.9 mm (line 212) are referred to as “rates” and should therefore be expressed with appropriate time units (e.g. mm yr⁻¹ or mm month⁻¹). Please ensure that trend units are reported consistently throughout the manuscript.
Citation: https://doi.org/10.5194/egusphere-2026-2596-RC2
The manuscript entitled "Role of Forest Stand Structure in Groundwater Storage Decline in the Three-North Shelterbelt Forest Region, China" by Luo et al. investigates the impacts of vegetation restoration and forest stand structure on groundwater storage variation in the TNSFR. The manuscript includes extensive datasets and large-scale analyses. The topic is highly relevant for understanding the ecological consequences of large-scale revegetation programs.
I appreciate the effort invested in data collection, processing, and visualization. It seems that there are gaps between figures and the accompanying text. Although the figures contain a considerable amount of valuable information, the Results section does not fully describe or synthesize the key patterns shown in the figures, which prevents the reader from fully appreciating the contribution of the study.
Here are my comments:
1. This manuscript stated three objectives:
(1)To examine ground water storage (GWS) changes driven by vegetation restoration and climatic factors across the TNSFR from 2003 to 2023;
(2)To assess the impact of vegetation restoration on regional GWS while accounting for stand age and dominant species;
(3)To quantify the direct and indirect impacts of climate change, vegetation restoration, and other anthropogenic activities on GWSA (GWS anomalies) using SEM.
However, the current ms only partially addresses these objectives.
Objective 1: Sections 3.1 and 3.2 mainly describe the temporal variations in GWS, climate variables, and vegetation indices. However, the analyses primarily remain descriptive. Groundwater, climate, and vegetation changes are largely presented independently, making it difficult to evaluate their respective contributions to GWS variations in the TNSFR.
Objective 2: Although several interesting findings are reported in section 3.3, it remains unclear how stand age, forest type, and species jointly regulate groundwater dynamics, or which of these factors plays the dominant role. Additionally, the stated objective is to assess their impacts on regional GWS; however, the implications of these stand-level differences for the regional groundwater decline across the TNSFR are not clearly established. Consequently, the connection between the stand-scale analyses and the regional conclusions remains relatively weak.
Objective 3: Although total effects are reported, the indirect pathways among these drivers are only briefly mentioned, limiting the mechanistic insight that SEM is intended to provide. More importantly, the forest stand characteristics, extensively analyzed in Section 3.3 (e.g., forest type, stand age, and species composition), are not incorporated in SEM (please correct me if I am wrong). As a result, the analyses of forest structure remain largely disconnected from the driver attribution analysis, and the relationships among the three stated objectives are not fully integrated.
2. A considerable portion of Section 3.1 focuses on validating GWSA and SMSA estimates rather than describing groundwater dynamics themselves. These analyses resemble model or data validation and may be more appropriately presented in the Methods section or supplementary materials.
3. Several interpretations, explanations, and quotations are included within the Results section. In my opinion, the Results section should primarily report observations, statistical relationships, and quantitative findings, whereas mechanistic explanations and broader implications should be reserved for Discussion.
4. In several sections, conclusions or interpretations are introduced before the corresponding observations and analyses are presented. As a result, the Results section sometimes reads as a sequence of predetermined conclusions followed by supporting evidence, rather than a progression from observations to interpretation. For example, Line 274: “The results revealed that pure forests exhibited more pronounced groundwater depletion than mixed forests. Specifically, conifer pure stands (CP) showed the most negative GWSA trends, reaching a peak of -1.06 mm month-1 at the mature stage, which was significantly higher than that of conifer mixed stands(CM, -0.31 mm month-1) and broadleaf pure stands (BP, -0.67 mm month-1) at the same age class.” A clear progression from evidence to interpretation would improve the scientific logic and readability of the manuscript.
5. Many figures that appear essential for supporting the main conclusions are placed in the Supplementary Materials despite being repeatedly cited in the main text. If these figures are critical to the interpretation, they should be moved to the main manuscript. Additionally, figures are not positioned close to the corresponding text, which reduces the readability.
6. The manuscript contains numerous abbreviations, long paragraphs, and limited visual separation between different analyses (paragraphs).
7. I am curious about Figure 3b which showed a totally reversed temporal trend between observed and estimated GWSA, could you explain a little bit about this phenomenon?
Overall, I believe the primary limitations of the manuscript lie in its presentation. A clearer linkage between the figures, analyses, and conclusions would greatly improve the readability and scientific impact of the manuscript.