the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Apr 2024
Changes in mean evapotranspiration dominate groundwater recharge in semi-arid regions
Abstract. Groundwater is one of the most essential natural resources and is affected by climate variability. However, our understanding of the effects of climate on groundwater recharge (GR), particularly in dry regions, is limited. Future climate projections suggest changes in many statistical characteristics of the potential evapotranspiration (ETref) and the rainfall that dictates the GR. To better understand the relationship between climate statistics and GR, we separately considered changes to the mean, STD, and extreme statistics of the ETref and the rainfall. We simulated the GR under different climate conditions in multiple semi-arid locations worldwide. We find that changes in the average ETref have the most significant impact on GR. Interestingly, we find that changes in the extreme ETref statistics have much weaker effects on the GR than changes in extreme rain statistics. Contradictory results of previous GR studies may be explained by the differences in the projected climate statistics.
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CC1: 'Comment on egusphere-2024-433', Giacomo Medici, 11 Apr 2024
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General comments
Good research in the field of groundwater hydrology that has been approached with a worldwide angle. However, important detail is missing. Please, take into account my minor points to fix the issues.
Specific comments
Line 18. “In recent years, much effort has been devoted to the analysis of the sensitivity of groundwater systems to climate change”. Add recent literature on the effects of climate change in mountain ranges, the aquifer recharge from the snow is very sensitive to the climate:
- Lorenzi, V., Banzato, F., Barberio, M. D., Goeppert, N., Goldscheider, N., Gori, F., Lacchini A., Manetta M, Medici G, Rusi S, Petitta, M. (2024). Tracking flowpaths in a complex karst system through tracer test and hydrogeochemical monitoring: Implications for groundwater protection (Gran Sasso, Italy). Heliyon, 10(2).
- Langman, J. B., Martin, J., Gaddy, E., Boll, J., & Behrens, D. (2022). Snowpack aging, water isotope evolution, and runoff isotope signals, Palouse Range, Idaho, USA. Hydrology, 9(6), 94.
Line 48. Cleary mention the 3 to 4 specific objectives of your research by using numbers (e.g., i, ii and iii).
Line 78. “l is the pore connectivity”. Your research appears to focus on porous aquifers of siliciclastic nature (plio-quaternary age?). This point is not clear by reading the manuscript.
Lines 80-81.“Sand, silt, and clay contents”. The geological nature of your aquifers have not been disclosed, see also my comment above.
Line 184. “Under some future climate predictions, the frequency of extreme events is expected to double”. Please, be more specific. Are you talking about semi-arid / arid regions?
Line 184. “Under some future climate predictions, the frequency of extreme events is expected to double”. This sentence should be expanded and moved to the discussion section.
Lines 231-240. The conclusion is too short, it needs more detail.
Lines 232-234. “Our results suggest...rainfall statistics”. The sentence is unclear and too long. Please, split it in two parts.
Line 237. “Focused processes”. Which processes? Please, be more specific.
Figures and tables
Figure 1a. You also have study sites and aquifers in highly arid settings, this is not clear in the text. You don’t have only semi-aridity.
Figure 1c. You can also report Mean Error, Mean Absolute Error and RMS in the graph.
Citation: https://doi.org/10.5194/egusphere-2024-433-CC1 -
RC1: 'Comment on egusphere-2024-433', Anonymous Referee #1, 20 Apr 2024
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This manuscript investigates the expected effects of climate change on groundwater recharge. The manuscript presents a model (based on 1D Darcy-Richardson that simulates diffuse recharge) that is modeled with current climate conditions (which show generally good agreement with the data in the selected semi-arid regions) and synthetic climate (which is essentially the historical climate but with its statistical properties changed). The model also assumes that ET is limited to evaporation from the topsoil, soil retention curves and hydraulic conductivity are according to Van Genuchten-Mualem (see Eq. 2-3). From the model simulations the paper concludes that
- changes in the average ETref have the most significant impact on GR.
- Changes in the extreme ETref statistics have much weaker effects on the GR than changes in extreme rain statistics.
- In addition, it is stated, that contradictory results of previous GR studies may be explained by the differences in the projected climate statistics.
While the paper has several useful elements, I have a few concerns that inhibit me from recommending publication in its current format. My main concerns are:
- A major conclusion seems to misrepresent actual recharge changes. Namely, it is concluded that mean ET has a bigger influence on recharge than P, but the latter is only true when the ratio of recharge to precipitation is considered, but absolute (in mm/y) or relatively (in %) changes in recharge are very likely much bigger due to precipitation changes. Such an amplifying effect of precipitation on recharge (versus PET on recharge) is because changes in precipitation both the ratio of this precipitation becoming recharge, and the total amount of precipitation that can become recharge. In contrast, changes in PET only affect the ratio of precipitation becoming recharge. The latter is also highlighted in cited most recent work on the climate sensitivity of recharge
- The model claims to be accurate within 5% of recharge but given that recharge/rainfall is typically very low in these arid places so being within 5% can still mean the recharge is off by a lot (for example several 100%). These uncertainties are not reflected in the projections. In addition, several data points appear to exceed the 5% error? More generally it is unclear why the climate projections can be considered accurate?
- The mathematical derivation (Eq. 6-9) is applicable for ET but not for ETref. The argument that is made (that ET is proportional to the ETref) to circumvent this problem is not valid in semi-arid systems. If we follow the Budyko framework as a reference, one can see that in extremely energy-limited systems indeed ET is expected to (almost exactly) linearly (and one-on-one) scale with ETref. However, in more arid places changes in ETref will not be associated will similar ET changes, nor will be their relationship be linear.The expectation of how this behaves can be exemplified using simplified version of the Budyko framework: E/P= 1-exp(-φ) = E/P= 1-exp(-Eref/P). Thus: E= P*(1-exp(-ETref /P)). Thus, dE/d(ETref )= P/(P - exp(ETref/P) P + ETref), which is a nonlinear function for ETref>P. Therefore, the physical relevance of the derivation provided in the manuscript remains unclear to me.
- The model assumes that all evaporation is soil evaporation and no overland flow. It is unclear why this is realistic even with somewhat sparse vegetation. Most of these regions will still have vegetation that evaporates relevant parts of total ET
- The manuscript states surprise that the extreme ETref statistics have much weaker effects on the GR than changes in extreme rain statistics. Isn’t this a result in line with obvious expectation?
- The use of symbols is highly confusing with GR standing for “recharge” and R for “rain”. However, to readers it would make interpretation a lot easier if a single letter was used for a process, and maybe a subscript is needed for further specifications. This avoids that GR reads as G times R. In addition, the use of P for precipitation, and R for recharge seems slightly more conventional. Such formulation would also come in handy when the symbols are used to derive new equations (Eq. 6-9).
Citation: https://doi.org/10.5194/egusphere-2024-433-RC1
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