the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A Global Lake/Reservoir Surface Extent Dataset (GLRSED): An integration of HydroLAKES, GRanD and OpenStreetMap
Bingxin Bai
Lixia Mu
Ge Chen
Yumin Tan
Abstract. Global lake/reservoir surface water extent is the basic input data for many studies. Although there are some datasets at present, there are problems such as incomplete or spatial inconsistency exist among them due to various reasons like different data sources and dynamic change characteristics of the surface water. In this paper, a new Global Lake/Reservoir Surface Extent Dataset (GLRSED) that contains spatial extent and basic attributes (e.g., name, area, lake type and source) of 2.17 million lakes/reservoirs was produced based on HydroLAKES, GRanD and OpenStreetMap. In addition, by overlaying with mountain data, we identified the lakes/reservoirs located in mountain areas. By overlaying with the Global geReferenced Database of Dams (GOODD) and Georeferenced Global Dams and Reserves (GeoDAR) dataset, we partitioned human-managed reservoirs from natural lakes. Lakes/reservoirs on the rivers were identified by overlaying with the SWOT Mission River Database (SWORD). Using the same method, we identified endorheic, glacier-fed and permafrost-fed lakes. Furthermore, the coverage of Surface Water and Ocean Topography (SWOT) ground track to each lake/reservoir in GLRSED was calculated to explore the potential of SWOT for monitoring lakes. These datasets could provide basic data for global lake/reservoir monitoring, enabling the study on the impact of human actions and climate changes on lake/reservoir freshwater availability. The GLRSED database is available at https://doi.org/10.5281/zenodo.8121174 (Bai et al., under review, 2023).
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Bingxin Bai et al.
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RC1: 'Comment on essd-2023-216', Anonymous Referee #1, 29 Aug 2023
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Review of “A Global Lake/Reservoir Surface Extent Dataset (GLRSED): An integration of HydroLAKES, GRanD and OpenStreetMap”
In this work the authors combine multiple hydrological datasets to improve the spatial representation of lakes and reservoirs as well as linking multiple important physical parameters to each water body. This work provide an important product for further inland water research and could specifically benefit from correction and integration with the upcoming SWAT measurements from the US National Aeronautics and Space Administration (NASA) and the French space agency Centre National d’Etudes Spatiales (CNES). I have some points with this manuscript which are listed hereunder, in general more details and clarity is required.
This work construct a Global Lake/Reservoir Surface Extent Dataset (GLRSED) by combining three main datasets (HydroLAKES, GRanD and OpenStreatMap) through a processing step followed by an integration of spatial extent and physical characteristics. Thereafter additional auxiliary data is derived through combination of GLRSED with additional spatial datasets (Mountains, permafrost, glaciers, endorheic catchments, etc.).
As it is now it is not clear how these steps were preformed. It can be inferred from the manuscript, that the spatial integration (spatial overlapping) was performed by finding the largest spatial extent for an arbitrary lake/reservoir present in the main datasets above. This process with each step need to be clearer described in the text. Furthermore Fig. 1 should be split into two figures and additional clarity and information should be provided. The first figure should show the exact working path used for constructing the GLRSED spatial dataset. Including the step where rivers was removed and how spatial interaction was treated, for example was a water body partly or fully removed when it was overlapped by a river segment? The second figure should show the exact derivation of lake type data from the auxiliary datasets including distances used (example the 1 km used for glacier interaction). The spatial overlapping clarification should also be present in the construction of the auxiliary datasets, it should be clear how lakes completely or partially within the set limit was classified.
As for the permafrost-, glacier fed lakes and endorheic lakes, the evidence provided in the manuscript is to general to tag these water bodies as such. In the text the authors classify a lake to be glacier fed if it is within (not clear exact how, see above) 1 km of glaciers, similar for endorheic and permafrost fed lakes. The evidence is enough to say these lakes/reservoirs are located in these regions, in fact the authors acknowledge this act in figure 6, but the details is not enough to classify how a lake or reservoir is fed.
I am missing lake/reservoir depth as a variable, which might be outside the scope of this study. But this work would benefit from the inclusion of this parameter. I leave it up to the authors to decide if they want to include this from the sources below and/or other works.
Choulga, M., Kourzeneva, E., Zakharova, E., and Doganovsky, A.: Estimation of the mean depth of boreal lakes for use in numerical weather prediction and climate modelling, Tellus A, 66, 21295, https://doi.org/10.3402/tellusa.v66.21295, 2014.
Lehner, B. and Döll, P.: Development and validation of a global database of lakes, reservoirs and wetlands, J. Hydrol., 296, 1–22, https://doi.org/10.1016/j.jhydrol.2004.03.028, 2004.
Toptunova, O., Choulga, M., and Kurzeneva, E.: Status and progress in global lake database developments, Adv. Sci. Res., 16, 57–61, https://doi.org/10.5194/asr-16-57-2019, 2019
Short points:
Line 90: add reference for SWOT data (is it SWORD?) and the revisit cycle (21 days?).
Line 91: The reader needs to know how a mountain is defined.
Line 98-99: Why did you use different search words in China and nowhere else? This should be uniform to avoid bias.
Line 130 to 155: Combine and/or extend paragraphs
Fig. 1: redo as described
Fig. 2: Add satellite image as in Fig. 9
Fig. 3: Split into two frames, one with lakes and one with reservoirs
Fig. 4: Normalize lake count and area towards country area, and use the real spatial extent of all countries.
Fig: 6: Simplify legend
Table 2 and S2: Theses tables need more detail, it is hard to follow what they show. Furthermore make sure that Table 2 and Figure. 4a correspond to each other, it looks like Italy shouldn’t be included in the table.
Citation: https://doi.org/10.5194/essd-2023-216-RC1 -
AC1: 'Reply on RC1', B. X. Bai, 25 Sep 2023
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Please refer to the attachment.
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AC1: 'Reply on RC1', B. X. Bai, 25 Sep 2023
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CC1: 'Comment on essd-2023-216', Yaohui Liu, 01 Oct 2023
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The manuscript "A Global Lake/Reservoir Surface Extent Dataset (GLRSED): An integration of HydroLAKES, GRanD and OpenStreetMap" have generated an useful data. In particular, the authors have done a great job that adding additional attributes to the data seems to be beneficial for many scientific studies. However, I find the manuscript suffers from pervasive grammatical errors that negatively impact the readability.
In addition, some specific comments may improve the manuscript:
- The author sometimes use “lakes”, sometimes “reservoirs”, sometimes use “lakes/reservoirs”, “lake/reservoirs” or “lake/reservoir”, which feels very chaotic. Like Line 23、25、37、166, could you please clarify?
- The Table S1 seems important, maybe move it from the supplement to main body better.
- Show the continents of area and count together and in order in Table 2.
- Figure 9 (a) is already shown in Figure 2. It is recommended to remove this duplicate information or delete Figure 2.
- Is the reservoir information contained in the OSM field used for setting the reservoir attributes of the new data? If not, it is recommended to integrate this information.
- Explain the distribution anomalies like OSM data in Italy in the manuscript.
Citation: https://doi.org/10.5194/essd-2023-216-CC1
Bingxin Bai et al.
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A Global Lake/Reservoir Surface Extent Dataset (GLRSED) Bingxin Bai, Lixia Mu, Ge Chen, Yumin Tan https://doi.org/10.5281/zenodo.8121174
Bingxin Bai et al.
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