the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Hydrological, meteorological and watershed controls on the water balance of thermokarst lakes between Inuvik and Tuktoyaktuk, Northwest Territories, Canada
- Department of Geography and Environmental Studies, Wilfrid Laurier University, Waterloo, N2L3C5, Canada
- Department of Geography and Environmental Studies, Wilfrid Laurier University, Waterloo, N2L3C5, Canada
Abstract. Thermokarst lake water balances are becoming increasingly vulnerable to change in the Arctic as air temperature increases and precipitation patterns shift. In the tundra uplands east of the Mackenzie Delta in the Northwest Territories, Canada, previous research has found that lakes responded non-uniformly to changes in precipitation, suggesting that lake and watershed properties moderate the response of lakes to climate change. To investigate how lake and watershed properties and meteoro5 logical conditions influence the water balance of thermokarst lakes in this region, we sampled 25 lakes for isotope analysis five times in 2018, beginning before snowmelt on May 1 and ending on September 3. Water isotope data were used to calculate the ratio of evaporation-to-inflow (E/I) and the average isotope composition of lake source water (δI). We identified four distinct water balance phases as lakes responded to seasonal shifts in meteorological conditions and hydrological processes. During the freshet phase from May 1 to June 15, the median E/I ratio of lakes decreased from 0.20 to 0.13 in response to freshet runoff 10 and limited evaporation due to lake ice presence that persisted for the duration of this phase. During the following warm, dry, and ice-free period from June 15 to July 26, designated the evaporation phase, the median E/I ratio increased to 0.19. During the brief soil wetting phase, E/I ratios did not respond to rainfall between July 26 and August 2, likely because watershed soils absorbed most of the precipitation which resulted in minimal runoff to lakes. The median E/I ratio decreased to 0.11 after an unseasonably cool and rainy August, identified as the recharge phase. Throughout the sampling period, δI remained relatively 15 stable and most lakes contained a greater amount of rainfall-sourced water than snow-sourced water, even after the freshet phase due to snowmelt bypass. The range of average E/I ratios we observed at lakes (0.00–0.43) was relatively narrow and low compared to thermokarst lakes in other regions, likely owing to the large watershed area to lake area (WA/LA), efficient preferential flow pathways for runoff, and a shorter ice-free season. WA/LA strongly predicted average lake E/I ratio (R2 = 0.74), as lakes with smaller WA/LA tended to have higher E/I ratios because they received relatively less inflow. We used this 20 relationship to predict the average E/I ratio of 7340 lakes in the region, finding that lakes are not vulnerable to desiccation in this region, given that all predicted average E/I values were <0.33. If future permafrost thaw and warming cause less runoff to flow into lakes, we expect that lakes with smaller WA/LA will be more influenced by increasing evaporation, while lakes with larger WA/LA will be more resistant to lake-level drawdown. However under wetter conditions, lakes with larger WA/LA will likely experience greater increases in lake level and could be more susceptible to rapid drainage as a result.
Evan J. Wilcox et al.
Status: closed (peer review stopped)
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RC1: 'Comment on hess-2022-279', Anonymous Referee #1, 17 Oct 2022
Overview
This manuscript presents a study of thermokarst lakes in the Northern Territories, Canada, investigating hydrological, meteorological, and watershed controls on the lakes’ water balance. Twenty-five lakes were sampled five times over the spring-summer season in 2018 and analyzed for stable oxygen and hydrogen isotope ratios. The isotope data were used to calculate the evaporation-to-inflow (E/I) ratio and the isotopic composition of lake source water (δI). Four water balance phases were identified, associated with shifts in meteorological and/or hydrological changes. The E/I and δI were compared to meteorological and watershed data (e.g., precipitation amount and watershed area to lake area ratio (WA/LA)). Subsequently, the relationship between WA/LA and E/I was used to estimate the average E/I of 7340 lakes in this region, finding that the lakes are not vulnerable to desiccation, and that lakes with smaller WA/LA are likely to be more influenced by increased evaporation in a future warmer climate.
General comments
The manuscript presents an interesting approach to evaluate water balance changes and to estimate E/I, which is relevant for the scope of HESS. The manuscript is well written with an easy-to-follow structure and clear figures. However, there are some issues with the dataset size and associated assumptions that need to be more clearly outlined. I also have some questions concerning the chosen method to infer δI. I have listed my concerns and suggestions for improvement/clarifications below.
Precipitation dataset size: I have some concerns about the small size of the precipitation dataset used for the “isotopic framework”. Are 11 snow samples and 13 rain samples enough to produce a reliable LMWL and estimate δP, or would it be better to use a more conservative approach and use the GMWL? How well do the precipitation samples cover the annual range of precipitation isotopic variability in this region? And why not compare your data to GNIP data from Inuvik (from the 1980s)? Justify your approach to use local precipitation data (because they are most representative for the study area and cover the same period as your lake water dataset?). How does the uncertainty related to the precipitation data affect the uncertainty in the δ* and δI calculations? Some more information about the precipitation samples would be useful to clarify how well estimated δS, δR and δP are. Were the snow samples collected soon after snowfall, or can the “end of winter snowpack” have experienced post-depositional fractionation processes (e.g., sublimation) before sampling? Were the liquid samples event-based and/or representing all precipitation events from May to September 2018? Have the precipitation isotope data been amount-weighted? Please clarify.
Analytical uncertainty: Are duplicate measurements of every fifth sample enough to determine the analytical uncertainty? In many labs, each sample is injected multiple times (sometimes more than 10 times), the first replicate(s) discarded, and the rest used to calculate an average. How did you deal with drift and memory effects?
Isotope framework: I generally like the approach to present an “isotope framework”, but some clarifications are needed when comes to presentation of isotope data and the used terminology. One example is the inconsistent use of the delta notation (δ). Some examples of this are on line 44 where δ is missing when introducing water isotope analysis (which is the analysis of the stable isotope ratios δ18O and δ2H), and ‘δ-δ space’ which should be ‘δ2H-δ18O space’. There is also a parenthesis missing in equation 1, which should be written: δsample = (Rsample/RVSMOW-1) * 103. These fundamental things need to be stated correctly. Furthermore, it is not clear when δI is referring to δ18OI and when/if it refers to δ2HI as well?
Approach to calculate δI: Have you considered using the more recent ‘MWL source implementation’ method by Bowen et al. (2018) to model δI values? Using this approach, you supply a MWL equation (you could test the GMWL and your LMWL to see how much difference it makes) and a hypothesized LEL slope with confidence intervals, as well as your lake water δ2H and δ18O values with uncertainties.
Specific comments
Lines 18-19: Rephrase the sentence starting “WA/LA strongly predicted average lake E/I ratio (R2 = 0.74)…” to “Lakes with smaller WA/LA tended to have higher E/I ratios (R2 = 0.74) because they received relatively less inflow. I think “strongly predicted” is an exaggeration.
Line 40: evaporation-to-inflow ratios. Use this wording throughout the paper (sometimes it says evaporation to inflow, sometimes evaporation/inflow ratio).
Line 44: Change to “In several studies, stable water isotope (δ18O and δ2H) analysis…” and add a couple of references.
Line 60: Explain the concept “snowmelt bypass” here. Now it isn’t explained until in the methods (lines 88-89).
Line 74: Remove “All lakes we selected were either headwater lakes or downstream of lakes that we sampled”, since this information is repeated on lines 76-77.
Line 87: How much did the first day of ice-free season vary between the lakes?
Lines 88-89: Move the definition of snowmelt bypass to the introduction and rephrase it. This sentence does not read well and needs to be clarified.
Line 97: Explain “end-of-winter snow”. Does this mean that you sampled the snow in the end of winter soon after it fell, or that you collected a core of snow accumulating over a longer period? If the latter, how do post-depositional processes impact the isotope values?
Line 98: Are δS and δR amount-weighted? Change to δSnow and δRain throughout the text to match the terms used in Figure 3 (or change to δS and δR in the figure).
Line 107: Equation misses parentheses around (Rsample/RVSMOW - 1)
Lines 113-114: When introducing the “fundamental linear relationships”, describe the global relationship (i.e., the GMWL) as well. This could also be added to Figure 3.
Line 114: Change ‘δ-δ space’ to ‘δ2H-δ18O space' (also on line 122).
Line 116: Is δP the average between the two δS and δR values, or the average of the full range of rain and snow values?
Lines 116-122: As it is explained now, it is not clear how the LEL was defined. Looking at Figure 3, the slope of the LEL is different between δP and δSSL compared to between δSSL and δ*? It also says that δSSL is located along the LEL. Which line is the LEL equation referring to? Why is it not a straight line from δP to δ*? Please clarify.
Line 122: What does SSL stand for? Add reference for δSSL definition.
Lines 126-128: Describe the δI calculation here as well (not only in the appendix).
Line 131: “where δL is the isotope composition of the lake water and δE is the isotope composition of evaporated vapour from the lake (Gonfiantini, 1986)”
Line 136: cumulated rainfall?
Lines 150-151: What do you mean by “data were transformed if the distribution was non-uniform”?
Line 152: Rephrase this sentence (removing the “strong”) and add the R2-value.
Line 170: This is the first time you use δ18OI. Does δI mentioned throughout the paper refer to δ2HI and δ18OI collectively, or δ18OI? Please clarify.
Line 170: “We observed distinct shifts in lake water isotope composition along the LEL…” – This is not easy to read from Figure 3. Do you mean for individual lakes, or the lakes in general? It could be interesting to indicate which lake is which, to be able to compare the different lakes’ responses during P1-P4. This could for example be done (in a supplementary figure?) by giving the lakes different colors, and assign each sampling date a different symbol, and/or by drawing lines between data points from the same lake.
Lines 174 and 180: Remove “very”.
Lines 178 and 184: Change “compositions” to “values”
Lines 193-194: “On September 3, some lakes plotted close to the LMWL, indicating that their waters had experienced negligible amounts of evaporation (Figure 3).” Does this mean that the same lakes plotted on the LEL before, and that the high precipitation amounts during P4 “reset” the lake water to be closer to δI by removing the old evaporation signal?
Line 196: Two thirds of the lakes.
Line 221: Remove “results” before “appears”.
Lines 245 and 246: Change “cooler” to “lower”.
Line 278: Earlier you mention only 5 downstream lakes (e.g., in Table 1). Where did the 6th lake come from (also presented in Figure 5)?
Line 320: evaporation
Line 321: led
Line 329: remove “as high as”
Line 357: Is δPs the value referred to as δP in Table A1, or where do you present that value?
Figure 1: Add overview map (e.g., Canada), and add black triangles and red square to legend.
Figure 2: Add reference to meteorological data. Clarify that you show the cumulative precipitation amounts. The sample days are shown by vertical dashed, not dotted lines. Mean daily air temperatures are indicated by horizontal dashed lines.
Figure 3: Please explain all elements in the caption, e.g., that the δSnow, δRain (which are called δS and δR in the text) and δP are averages (it looks like δRain displays the median, but maybe the average and median are very close?), what the box and whisker plots show, and that the numbers refer to sampling dates. It would also be good to add the GMWL for reference. Which line does the LEL equation refer to? The line between δP and δSSL and the line between δSSL and δ* have different slopes. Why? Change color for the snow samples or the May 1 samples, as it is confusing that both are displayed in grey. You could also use different symbols for precipitation samples and lake samples, to make them easier to differentiate.
Figure 4: It says four sampling dates in the caption but should be five. What do you mean by “lake-specific” change in E/I in (c)? Why not also present a panel with the measured δ18O values, to see how much these values differ from δ18OI?
Figure 6: Are the temperatures and precipitation values in from the year of lake water sampling or the 1980-2020 values? And how were the curves in the three lowermost panels generated? The E/I values at the sampling dates are not the same as presented in Figure 4b? And how were the values between the sampling dates interpolated? Please clarify.
Table 1: Change Polygon Extent to Ice-wedge Polygon Coverage.
Table 2: Clarify in caption that you mean δ18OI. What do you mean by “adjusted R2”?
Reference
Bowen, G.J., Putman, A., Brooks, J.R., Bowling, D.R., Oerter, E.J., Good, S.P., 2018. Inferring the source of evaporated waters using stable H and O isotopes. Oecologia 187 (4), 1025–1039. https://doi.org/10.1007/s00442-018-4192-5.
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RC2: 'Comment on hess-2022-279', Seifu Kebede Gurmessa, 17 Nov 2022
The manuscript employs the well known isotope mass balance formulations to compute the water balance, namely, the evaporative water loss to total inflow (E/I) ratio in 25 Thermokarst lakes in Canada. The authors subsequently compare the E/I to the lake and catchment geometry and cover [Catchment Area to Lake area ratio, Lake Depth, Vegetation, gradient, Lake area etc]. Interestingly, the E/I ratio of the 25 lakes correlate well (R2=0.74) with the Catchment/Lake area ratio, allowing the authors to compute the E/I ratio for 7340 Thermokarst lakes without needing the hydrologic or isotopic measurement in these lakes.
The 25 lakes have similar range in depth (0-4 m) dictating the volume of the water in the lakes is proportional to their area (because of similarity in lake depth). This would mean the underlying mechanism for the good correlation between E/I and Catchment/Lake area ratio is that the later is a good surrogate for Catchment/Lake Volume and thus to residence time (Volume/Inflow). The major question now is what would happen if the lakes (25 lakes) vertical dimension was significantly variable and if the 7340 lakes have variable depth properties? The validity of the assumption that the lakes have similar depth property must be clearly reflected in the manuscript or the uncertainties of using the approach or extending the approach beyond these lakes needs to be highlighted in the manuscript.
Other detailed comments (13 comments) are provide in the attached PDF.
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RC3: 'Comment on hess-2022-279', Anonymous Referee #3, 17 Nov 2022
The authors investigated how lake and watershed properties and meteorological conditions influence the water balance of thermokarst lakes in the tundra uplands east of the Mackenzie Delta in the Northwest Territories of Canada. They sampled 25 lakes for isotope analysis five times in 2018, beginning before snowmelt on May 1 and ending on September 3 to calculate the ratio of evaporation-to-inflow (E/I) into the lakes and estimates the average isotope composition of lake source water (δI). They indicated the range of average E/I ratios compared very well with watershed area to lake area (WA/LA) parameter (R2 = 0.74). Furthermore, they used this relationship to predict the average E/I ratio of 7340 lakes in the region, finding that lakes are not vulnerable to desiccation in the region. The authors have a good data and other measurements that could compliment isotopic computations to establish a surrogate.
While the general idea for finding a surrogate parameter which is easier and less expensive to measure or used to estimate E/I ratios laudable, the competent application of the time-tested evaporation model (water -isotope -mass balance method) used by the authors to justify this surrogate build up is doubtful. There are several assumptions that were made or glossed over in the paper that are difficult to justify, and these make it difficult to accept the results as they are presented. A major update of the assumptions and re-evaluation of the E/I computations is suggested.
Below are a few suggestions to improve the paper.
The authors indicated that the 25 lakes cover a range of watershed sizes, surface areas, among other characteristics (which include vegetation, land use type, rolling hills etc) and that the lakes were sampled as either a headwater lakes or a downstream lakes (line 70-75). The above information suggests the ff:
1) that the isotopic behaviour/ responses to evaporation from these lakes may vary widely and hence there is the need to individually and separately evaluate the LEL, h, delta P, delta A, and finally E/I and not lump them together as shown in Figure 3; I encourage the authors to study Bam and Ireson 2019 https://doi.org/10.1016/j.jhydrol.2018.12.032 since this work is similar.
2) there is a need to account for the inflow and outflow fluxes to these lakes, I did not see this accounting process or equations, neither was there a stated assumption that these fluxes have been considered negligible within the case and the period and why;
3) If even we assume that these lakes are well-mixed throughout the period (this assumption was not made though), precipitation addition and output fluxes are negligible and hence E/I ratios could be computed; we know a range of other factors that do significantly affect evaporation rates from lakes and hence lake isotope composition and ultimately the E/I. Among these are the exposed surface area, depth, the geometry/ basin bathymetry, vegetation cover etc., are all these the same of the 25 lakes? I believe the authors have sufficient data to account for these parameters, since the ultimate goal is to find a surrogate.
4) the choice or search for delta P (initial lake water isotope composition) using the intersection point of the LMWL and LEL is not clear. We see in Figure 3 that both May (and Sept ) samples plotted on or above the LMWL and if for anything the isotopic compositions of the May /June samples could be used as the starting point for those lakes to estimate the E/I between May and Sept or August. Extrapolating the LEL to the bottom to meet the LMWL to find initial source water has been proven to be unrealiable (sese Bennettin et al., 2018, https://doi.org/10.5194/hess-22-2881-2018) .
I would recommend that since five (5 ) samples were collected from each of the 25 lakes from May to Sept, it will be useful an LEL is constructed for each of the lakes and used together with the rainfall isotopes and temperature measurements to estimate the dA for each of these lakes (see Bam and Ireson 2019; Bennett et al., 2008; Gibson et al., 2008a,b,2016; Gibson and Reid, 2014; Skrzypek et al., 2015). Use the May/June sample isotope composition as the initial lake water isotope to estimate the E/I for the period (May/June to Sept where feasible).
There cannot be any E/I estimate outside the ice-free period, water fluxes lost during the dry winter periods originate from the sublimation of frozen ice over and snow, which covers on the surface of the lakes. The lakes are closed to evaporative losses prior to the open-water season.
Other observations are made in the pdf document attached
Status: closed (peer review stopped)
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RC1: 'Comment on hess-2022-279', Anonymous Referee #1, 17 Oct 2022
Overview
This manuscript presents a study of thermokarst lakes in the Northern Territories, Canada, investigating hydrological, meteorological, and watershed controls on the lakes’ water balance. Twenty-five lakes were sampled five times over the spring-summer season in 2018 and analyzed for stable oxygen and hydrogen isotope ratios. The isotope data were used to calculate the evaporation-to-inflow (E/I) ratio and the isotopic composition of lake source water (δI). Four water balance phases were identified, associated with shifts in meteorological and/or hydrological changes. The E/I and δI were compared to meteorological and watershed data (e.g., precipitation amount and watershed area to lake area ratio (WA/LA)). Subsequently, the relationship between WA/LA and E/I was used to estimate the average E/I of 7340 lakes in this region, finding that the lakes are not vulnerable to desiccation, and that lakes with smaller WA/LA are likely to be more influenced by increased evaporation in a future warmer climate.
General comments
The manuscript presents an interesting approach to evaluate water balance changes and to estimate E/I, which is relevant for the scope of HESS. The manuscript is well written with an easy-to-follow structure and clear figures. However, there are some issues with the dataset size and associated assumptions that need to be more clearly outlined. I also have some questions concerning the chosen method to infer δI. I have listed my concerns and suggestions for improvement/clarifications below.
Precipitation dataset size: I have some concerns about the small size of the precipitation dataset used for the “isotopic framework”. Are 11 snow samples and 13 rain samples enough to produce a reliable LMWL and estimate δP, or would it be better to use a more conservative approach and use the GMWL? How well do the precipitation samples cover the annual range of precipitation isotopic variability in this region? And why not compare your data to GNIP data from Inuvik (from the 1980s)? Justify your approach to use local precipitation data (because they are most representative for the study area and cover the same period as your lake water dataset?). How does the uncertainty related to the precipitation data affect the uncertainty in the δ* and δI calculations? Some more information about the precipitation samples would be useful to clarify how well estimated δS, δR and δP are. Were the snow samples collected soon after snowfall, or can the “end of winter snowpack” have experienced post-depositional fractionation processes (e.g., sublimation) before sampling? Were the liquid samples event-based and/or representing all precipitation events from May to September 2018? Have the precipitation isotope data been amount-weighted? Please clarify.
Analytical uncertainty: Are duplicate measurements of every fifth sample enough to determine the analytical uncertainty? In many labs, each sample is injected multiple times (sometimes more than 10 times), the first replicate(s) discarded, and the rest used to calculate an average. How did you deal with drift and memory effects?
Isotope framework: I generally like the approach to present an “isotope framework”, but some clarifications are needed when comes to presentation of isotope data and the used terminology. One example is the inconsistent use of the delta notation (δ). Some examples of this are on line 44 where δ is missing when introducing water isotope analysis (which is the analysis of the stable isotope ratios δ18O and δ2H), and ‘δ-δ space’ which should be ‘δ2H-δ18O space’. There is also a parenthesis missing in equation 1, which should be written: δsample = (Rsample/RVSMOW-1) * 103. These fundamental things need to be stated correctly. Furthermore, it is not clear when δI is referring to δ18OI and when/if it refers to δ2HI as well?
Approach to calculate δI: Have you considered using the more recent ‘MWL source implementation’ method by Bowen et al. (2018) to model δI values? Using this approach, you supply a MWL equation (you could test the GMWL and your LMWL to see how much difference it makes) and a hypothesized LEL slope with confidence intervals, as well as your lake water δ2H and δ18O values with uncertainties.
Specific comments
Lines 18-19: Rephrase the sentence starting “WA/LA strongly predicted average lake E/I ratio (R2 = 0.74)…” to “Lakes with smaller WA/LA tended to have higher E/I ratios (R2 = 0.74) because they received relatively less inflow. I think “strongly predicted” is an exaggeration.
Line 40: evaporation-to-inflow ratios. Use this wording throughout the paper (sometimes it says evaporation to inflow, sometimes evaporation/inflow ratio).
Line 44: Change to “In several studies, stable water isotope (δ18O and δ2H) analysis…” and add a couple of references.
Line 60: Explain the concept “snowmelt bypass” here. Now it isn’t explained until in the methods (lines 88-89).
Line 74: Remove “All lakes we selected were either headwater lakes or downstream of lakes that we sampled”, since this information is repeated on lines 76-77.
Line 87: How much did the first day of ice-free season vary between the lakes?
Lines 88-89: Move the definition of snowmelt bypass to the introduction and rephrase it. This sentence does not read well and needs to be clarified.
Line 97: Explain “end-of-winter snow”. Does this mean that you sampled the snow in the end of winter soon after it fell, or that you collected a core of snow accumulating over a longer period? If the latter, how do post-depositional processes impact the isotope values?
Line 98: Are δS and δR amount-weighted? Change to δSnow and δRain throughout the text to match the terms used in Figure 3 (or change to δS and δR in the figure).
Line 107: Equation misses parentheses around (Rsample/RVSMOW - 1)
Lines 113-114: When introducing the “fundamental linear relationships”, describe the global relationship (i.e., the GMWL) as well. This could also be added to Figure 3.
Line 114: Change ‘δ-δ space’ to ‘δ2H-δ18O space' (also on line 122).
Line 116: Is δP the average between the two δS and δR values, or the average of the full range of rain and snow values?
Lines 116-122: As it is explained now, it is not clear how the LEL was defined. Looking at Figure 3, the slope of the LEL is different between δP and δSSL compared to between δSSL and δ*? It also says that δSSL is located along the LEL. Which line is the LEL equation referring to? Why is it not a straight line from δP to δ*? Please clarify.
Line 122: What does SSL stand for? Add reference for δSSL definition.
Lines 126-128: Describe the δI calculation here as well (not only in the appendix).
Line 131: “where δL is the isotope composition of the lake water and δE is the isotope composition of evaporated vapour from the lake (Gonfiantini, 1986)”
Line 136: cumulated rainfall?
Lines 150-151: What do you mean by “data were transformed if the distribution was non-uniform”?
Line 152: Rephrase this sentence (removing the “strong”) and add the R2-value.
Line 170: This is the first time you use δ18OI. Does δI mentioned throughout the paper refer to δ2HI and δ18OI collectively, or δ18OI? Please clarify.
Line 170: “We observed distinct shifts in lake water isotope composition along the LEL…” – This is not easy to read from Figure 3. Do you mean for individual lakes, or the lakes in general? It could be interesting to indicate which lake is which, to be able to compare the different lakes’ responses during P1-P4. This could for example be done (in a supplementary figure?) by giving the lakes different colors, and assign each sampling date a different symbol, and/or by drawing lines between data points from the same lake.
Lines 174 and 180: Remove “very”.
Lines 178 and 184: Change “compositions” to “values”
Lines 193-194: “On September 3, some lakes plotted close to the LMWL, indicating that their waters had experienced negligible amounts of evaporation (Figure 3).” Does this mean that the same lakes plotted on the LEL before, and that the high precipitation amounts during P4 “reset” the lake water to be closer to δI by removing the old evaporation signal?
Line 196: Two thirds of the lakes.
Line 221: Remove “results” before “appears”.
Lines 245 and 246: Change “cooler” to “lower”.
Line 278: Earlier you mention only 5 downstream lakes (e.g., in Table 1). Where did the 6th lake come from (also presented in Figure 5)?
Line 320: evaporation
Line 321: led
Line 329: remove “as high as”
Line 357: Is δPs the value referred to as δP in Table A1, or where do you present that value?
Figure 1: Add overview map (e.g., Canada), and add black triangles and red square to legend.
Figure 2: Add reference to meteorological data. Clarify that you show the cumulative precipitation amounts. The sample days are shown by vertical dashed, not dotted lines. Mean daily air temperatures are indicated by horizontal dashed lines.
Figure 3: Please explain all elements in the caption, e.g., that the δSnow, δRain (which are called δS and δR in the text) and δP are averages (it looks like δRain displays the median, but maybe the average and median are very close?), what the box and whisker plots show, and that the numbers refer to sampling dates. It would also be good to add the GMWL for reference. Which line does the LEL equation refer to? The line between δP and δSSL and the line between δSSL and δ* have different slopes. Why? Change color for the snow samples or the May 1 samples, as it is confusing that both are displayed in grey. You could also use different symbols for precipitation samples and lake samples, to make them easier to differentiate.
Figure 4: It says four sampling dates in the caption but should be five. What do you mean by “lake-specific” change in E/I in (c)? Why not also present a panel with the measured δ18O values, to see how much these values differ from δ18OI?
Figure 6: Are the temperatures and precipitation values in from the year of lake water sampling or the 1980-2020 values? And how were the curves in the three lowermost panels generated? The E/I values at the sampling dates are not the same as presented in Figure 4b? And how were the values between the sampling dates interpolated? Please clarify.
Table 1: Change Polygon Extent to Ice-wedge Polygon Coverage.
Table 2: Clarify in caption that you mean δ18OI. What do you mean by “adjusted R2”?
Reference
Bowen, G.J., Putman, A., Brooks, J.R., Bowling, D.R., Oerter, E.J., Good, S.P., 2018. Inferring the source of evaporated waters using stable H and O isotopes. Oecologia 187 (4), 1025–1039. https://doi.org/10.1007/s00442-018-4192-5.
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RC2: 'Comment on hess-2022-279', Seifu Kebede Gurmessa, 17 Nov 2022
The manuscript employs the well known isotope mass balance formulations to compute the water balance, namely, the evaporative water loss to total inflow (E/I) ratio in 25 Thermokarst lakes in Canada. The authors subsequently compare the E/I to the lake and catchment geometry and cover [Catchment Area to Lake area ratio, Lake Depth, Vegetation, gradient, Lake area etc]. Interestingly, the E/I ratio of the 25 lakes correlate well (R2=0.74) with the Catchment/Lake area ratio, allowing the authors to compute the E/I ratio for 7340 Thermokarst lakes without needing the hydrologic or isotopic measurement in these lakes.
The 25 lakes have similar range in depth (0-4 m) dictating the volume of the water in the lakes is proportional to their area (because of similarity in lake depth). This would mean the underlying mechanism for the good correlation between E/I and Catchment/Lake area ratio is that the later is a good surrogate for Catchment/Lake Volume and thus to residence time (Volume/Inflow). The major question now is what would happen if the lakes (25 lakes) vertical dimension was significantly variable and if the 7340 lakes have variable depth properties? The validity of the assumption that the lakes have similar depth property must be clearly reflected in the manuscript or the uncertainties of using the approach or extending the approach beyond these lakes needs to be highlighted in the manuscript.
Other detailed comments (13 comments) are provide in the attached PDF.
-
RC3: 'Comment on hess-2022-279', Anonymous Referee #3, 17 Nov 2022
The authors investigated how lake and watershed properties and meteorological conditions influence the water balance of thermokarst lakes in the tundra uplands east of the Mackenzie Delta in the Northwest Territories of Canada. They sampled 25 lakes for isotope analysis five times in 2018, beginning before snowmelt on May 1 and ending on September 3 to calculate the ratio of evaporation-to-inflow (E/I) into the lakes and estimates the average isotope composition of lake source water (δI). They indicated the range of average E/I ratios compared very well with watershed area to lake area (WA/LA) parameter (R2 = 0.74). Furthermore, they used this relationship to predict the average E/I ratio of 7340 lakes in the region, finding that lakes are not vulnerable to desiccation in the region. The authors have a good data and other measurements that could compliment isotopic computations to establish a surrogate.
While the general idea for finding a surrogate parameter which is easier and less expensive to measure or used to estimate E/I ratios laudable, the competent application of the time-tested evaporation model (water -isotope -mass balance method) used by the authors to justify this surrogate build up is doubtful. There are several assumptions that were made or glossed over in the paper that are difficult to justify, and these make it difficult to accept the results as they are presented. A major update of the assumptions and re-evaluation of the E/I computations is suggested.
Below are a few suggestions to improve the paper.
The authors indicated that the 25 lakes cover a range of watershed sizes, surface areas, among other characteristics (which include vegetation, land use type, rolling hills etc) and that the lakes were sampled as either a headwater lakes or a downstream lakes (line 70-75). The above information suggests the ff:
1) that the isotopic behaviour/ responses to evaporation from these lakes may vary widely and hence there is the need to individually and separately evaluate the LEL, h, delta P, delta A, and finally E/I and not lump them together as shown in Figure 3; I encourage the authors to study Bam and Ireson 2019 https://doi.org/10.1016/j.jhydrol.2018.12.032 since this work is similar.
2) there is a need to account for the inflow and outflow fluxes to these lakes, I did not see this accounting process or equations, neither was there a stated assumption that these fluxes have been considered negligible within the case and the period and why;
3) If even we assume that these lakes are well-mixed throughout the period (this assumption was not made though), precipitation addition and output fluxes are negligible and hence E/I ratios could be computed; we know a range of other factors that do significantly affect evaporation rates from lakes and hence lake isotope composition and ultimately the E/I. Among these are the exposed surface area, depth, the geometry/ basin bathymetry, vegetation cover etc., are all these the same of the 25 lakes? I believe the authors have sufficient data to account for these parameters, since the ultimate goal is to find a surrogate.
4) the choice or search for delta P (initial lake water isotope composition) using the intersection point of the LMWL and LEL is not clear. We see in Figure 3 that both May (and Sept ) samples plotted on or above the LMWL and if for anything the isotopic compositions of the May /June samples could be used as the starting point for those lakes to estimate the E/I between May and Sept or August. Extrapolating the LEL to the bottom to meet the LMWL to find initial source water has been proven to be unrealiable (sese Bennettin et al., 2018, https://doi.org/10.5194/hess-22-2881-2018) .
I would recommend that since five (5 ) samples were collected from each of the 25 lakes from May to Sept, it will be useful an LEL is constructed for each of the lakes and used together with the rainfall isotopes and temperature measurements to estimate the dA for each of these lakes (see Bam and Ireson 2019; Bennett et al., 2008; Gibson et al., 2008a,b,2016; Gibson and Reid, 2014; Skrzypek et al., 2015). Use the May/June sample isotope composition as the initial lake water isotope to estimate the E/I for the period (May/June to Sept where feasible).
There cannot be any E/I estimate outside the ice-free period, water fluxes lost during the dry winter periods originate from the sublimation of frozen ice over and snow, which covers on the surface of the lakes. The lakes are closed to evaporative losses prior to the open-water season.
Other observations are made in the pdf document attached
Evan J. Wilcox et al.
Evan J. Wilcox et al.
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