|Second review of „ Monitoring soil moisture from middle to high elevation in Switzerland: Set-up and first results from the SOMOMOUNT network“ by Pellet et al.|
The manuscript has been extensively reworked and most of the earlier reviewer comments have been appropriately addressed. I also very much appreciate the additional chapter on the effects of soil freezing on soil moisture measurements and the restricted accuracy of liquid soil moisture measurements during frozen conditions. This limited measurement accuracy should be also mentioned later in the interpretation and discussion of the results.
However, there are still several issues that need to be resolved before publication can be recommended.
The different terms “liquid VWC”, “VWC”, “total VWC”, “total soil moisture” and “soil moisture” are used at random, which is confusing for the reader. I suggest to consistently using the term “LSM” for liquid soil moisture and “TSM” for total soil moisture (in the following I will use these abbreviations. Also the axis captions of all figures need to be adopted in this way.
All soil moisture measurements below 0 °C have now been indicated in the figures to indicate frozen soil conditions (i.e. measurements are not representing TSM anymore). However, there are cases where frozen conditions seem to occur above 0 °C. For instance in Fig. 6 (e.g. GFU) one can clearly see that LSM is dropping sharply when temperatures approaches 0 °C, indicating that a substantial part of the soil water within the measurement volume of the sensors has already started to freeze, although soil temperatures is still above 0 °C according to the temperature sensor. This indicates that the temperature measurements are not well representing the measurement volume of the sensor. This is not surprising, since the electromagnetic waves of the soil moistures sensors penetrate a certain part of the soil, whereas the temperature sensor only measures its own temperatures inducing a scale mismatch. In order to circumvent this problem, a higher threshold value for soil temperature should be to be chosen (e.g. 1 °C or higher).
There are still issues related to the special situation at DRE. Only after reading the recent HESSD paper I was able to understand the process of convective heat transport by air circulation within the talus slope. The authors suggest that is effect also explains lower LSM values. They argue that atmospheric air is transported during winter periods into the ground at the location of the monitoring station due to this process, thus when air temperature is well below 0 °C. This would induce soil freezing below the snow cover and thus explaining the observed drop in LSM. However, the soil temperature stays close to 0 °C during this (Figure 6), which is the typical soil situation below an insulating show cover. In addition the drop in LSM happens mostly in 50 cm, which is counter intuitive since freezing should be more pronounced near the soil surface.
Therefore an alternative explanation for the drop in LSM should be considered: Since the DRE soil has a very high porosity (the bulk density of 0.12 g/cm³ show in Tab. 3 means that the porosity is >90 %!), the drop in LSM could be easily explained by exfiltration of soil water into the bed rock fissures below the soil layer or by lateral water transport downhill. In addition, the drop in LSM in winter is only marginal and cannot explain the substantial lower annual mean LSM compared to MLS or FRE. It is more realistic that LSM at MLS and FRE are higher due to the influence of shallow groundwater that keeps the soil saturated for longer time periods (i.e. LSM stays constant at the maximum value), whereas DRE does not show any sign of groundwater influence (i.e. LSM shows high variability and the LSM is well below the soil porosity).
In the sensor comparison (Chapter 4.1) only the R²-values are discussed. However, the RMSE is much better indicator for the accuracy of the LSM measurements.
Chapter 3 should be restructured (only one sub-chapter is a bit awkward).
In general, the manuscript should be carefully checked for syntax and tense errors (preferably by a native speaker).
P1L19: “up to” instead of “until”
P1L21: “VWC” is not defined
P3L22: “Qu et al., 2013”
P3L20-21: Actually, the frequency of the SMT100 sensor is not fixed. The SMT100 sensor generates a pulse, which is inverted and then fed back to the input of the line driver resulting in an “oscillation” frequency that mainly depends on the dielectric permittivity of the surrounding medium (between 150 MHz in water and 340 MHz in air), see Bogena et al. (2017) for more details on the SMT100 technology. Bogena et al. (2017) also showed the effects of temperature on SMT100 reading and demonstrated that any temperature dependency of the measured soil moisture are related to temperature related changes in permittivity and thus are not a result of the SMT100 sensor electronics and thus can be easily corrected using temperature information.
P3L26: According to Bogena et al. (2017) the accuracy of the SMT100 for ideal conditions/media is about 1 vol.% (factory calibration) and even better in case of sensor specific calibration.
P4L4-10: Remove redundancies (e.g. penetration depth)
P10L2-4: This statement is not fully correct. Watanabe and Wake (2009) showed that the relationship of liquid water fraction measured with NMR and the permittivity measured with TDR can be approximated with Topp’s equation for sand (except −0.1 < T > 0 °C), but not for other soil textures like loam. Thus, for most of your sites this means that the LSM measurements have less accuracy during frozen conditions.
P11L3: Check grammar
P11L8: Here you also should mention the very high RMSE at MLS.
P11L21: In fact, the temperatures are typically staying close to 0 °C.
P11L29: A high retention capacity should lead to less variability in temporal soil moisture dynamics.
P11L32: Is the high evaporation rate really only due higher temperature? What about other meteorological parameters, especially low precipitation rates?
P12L18: This is an indication for preferential flow.
P12L29: Why “also”?
P13L13: “event” instead of “daily”
P14L9: Check grammar.
P14L12: Check grammar.
P14L13: Which depth?
P14L27: Please indicate the soil type in terms of FAO classification.
P15L4: Check grammar and repetition.
P15L12: “large elements” is not an appropriate term in this respect.
P16L8: “soil material”, “near the soil surface”
P16L11: The slope is higher than 45°. Better present the slope of a regression.
P16L12: The slope was less steep.
P16L18: Please add the LSM values.
P17L23-24: The statement that temperature is a result of the radiation balance is not correct. Air temperature in mountainous regions typically decreases with elevation according to the moist adiabatic lapse rate due the decrease in atmospheric pressure with elevation and latent heat exchange processes.
P18L2: Explain “surface offset”
P18L18: The term “evolution” is not appropriate here.
P19L10: Fig. 13 is not a conceptual model. You could call it a generalised schematic or similar.
Fig. 6 is overcrowded with time series making it very difficult to read, especially since the colours are also quite similar. Since you are later using only the SMT100 data, I suggest removing all other L. SM data. The 0°C-threshold is not working always (see general comment).
Fig. 7: Precipitation should be shown for the whole period. Use different axis for snow and LSM (the LSM range is too wide).
Fig. 8: You should use the 10 cm temperature data to indicate freezing conditions.
Fig. 10: Yellow is hardly visible.
Bogena, H., J.A. Huisman, B. Schilling, A. Weuthen and H. Vereecken (2017): Effective calibration of low-cost soil water content sensors. Sensors 17(1), 208, doi:10.3390/s17010208.