the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Mapping groundwater dependent ecosystems using a high-resolution global groundwater model
Abstract. Global population growth, economic growth, and climate change have led to a decline in groundwater resources, which are essential for sustaining groundwater dependent ecosystems (GDEs). To understand their spatial and temporal dependency on groundwater, we developed a framework for mapping GDEs at a large scale, using results from a high-resolution global groundwater model. To evaluate the proposed framework, we focus on the Australian continent because of the abundance of groundwater depth observations and the presence of a GDE atlas. We first classify GDEs into three categories: aquatic (rivers and lakes), wetlands (inland wetlands), and terrestrial (phreatophyte) GDEs. We then define a set of rules for identifying these different ecosystems, which are based, among others, on groundwater levels, and groundwater discharge. We run the groundwater model in both steady state and transient mode (period of 1979–2019) and apply the set of rules to map the different types of GDEs using model outputs. For steady-state, GDEs are mapped based on presence or absence, and results are evaluated against the Australian GDE atlas using a hit rate, false alarm, and critical success index. Results show a hit rate above 80 % for each of the three GDE types. From transient runs, we analyse the changes in groundwater dependency between two time periods, 1979–1999 and 1999–2019 and observe a decline in the average number of months that GDEs depend on groundwater resources, pointing at an increasing threat to these ecosystems. The proposed framework and methodology provide a basis for analysing how global impacts of climate change and water use may affect GDEs extent and health.
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Status: open (until 24 Oct 2024)
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RC1: 'Comment on hess-2024-112', Tom Gleeson, 08 May 2024
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Overall, I think this is an interesting, important and worthwhile manuscript. I appreciate the purpose (improved temporal-resolution modeling of different GDE types) as well as the method (coupled hydrologic model) and geographic focus (Australia where there is good data), and the results seem reasonable. I have a few critiques of the methods that I think would improve the manuscript.
I hate suggesting to include a few contributions that I have been a part of but i can't see anyway around this. This is a recent overview of groundwater and ecosystems that could provide more background on terminology and processes: Gleeson, T., Huggins, X., Vázquez Suñé, E.. Arrojo-Agudo, P., Connor, R. (2022) Groundwater and Ecosystems. Chapter 6 of Groundwater: Making the invisible visible, UNESCO World Water Development Report.
I would be good to at least mention that you are not covering subsurface ecosystems.We took a similar approach to mapping terrestrial and aquatic ecosystems in this: Huggins, X., Gleeson, T., Serrano, D., Zipper, S., Jehn, F., Rohde, M.M., Abell, R., Vigerstol, K., Hartmann, A. (2023) Overlooked risks and opportunities in groundwatersheds of the world’s protected areas. Nature Sustainability.
We used an inference based terrestrial and aquatic inference-based approach to map terrestrial GDEs, lentic aquatic GDEs and lotic aquatic GDEs.Based on these, my most significant critique is dividing GDEs in lentic (non-flowing; lakes/wetlands) vs. lotic (flowing; rivers, streams) rather than aquatic vs wetland. Ecologists often differentiate this way since they function very differently.
This critique leads to my next concern: defining aquatic ecosystem dependency as the ratio to groundwater discharge to streamflow. This might be appropriate for rivers or streams but is inappropriate for lakes which may have very little flow but still may groundwater dependent.
Two more methodological concerns:
5 m is deep water table as minimum for wetlands seems too deep and needs more justification to me...
I was also surprised that the difference between known and likely GDEs was not distinguished. I would test the importance of this assumption.Citation: https://doi.org/10.5194/hess-2024-112-RC1
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