Measuring evapotranspiration on an eroded cropland by an automated and mobile chamber system: gap filling strategies and impact of soil type and topsoil removal
- 1Isotope Biogeochemistry and Gas Fluxes, Leibniz Centre for Agricultural Landscape Research, Müncheberg, 15374, Germany
- 2Experimental Station Dedelow, Leibniz Centre for Agricultural and Landscape Research, Prenzlau, 17291, Germany
- 3Landscape Pedology, Leibniz Centre for Agricultural Landscape Research, Müncheberg, 15374, Germany
- 4Institute of Geography and Environmental Science, University of Potsdam, 14476, Potsdam, Germany
- 1Isotope Biogeochemistry and Gas Fluxes, Leibniz Centre for Agricultural Landscape Research, Müncheberg, 15374, Germany
- 2Experimental Station Dedelow, Leibniz Centre for Agricultural and Landscape Research, Prenzlau, 17291, Germany
- 3Landscape Pedology, Leibniz Centre for Agricultural Landscape Research, Müncheberg, 15374, Germany
- 4Institute of Geography and Environmental Science, University of Potsdam, 14476, Potsdam, Germany
Abstract. In light of ongoing global climate crisis and related increases in extreme hydrological events, it is increasingly crucial to assess ecosystem resilience and - in agricultural systems - to ensure sustainable management and food security. For that, comprehensive understanding of ecosystem water cycle budgets and spatio-temporal dynamics are indispensable. Evapotranspiration (ET) plays a pivotal role returning up to 90 % of ingoing precipitation back to the atmosphere. Here, we studied impacts of soil types and management on an agroecosystems water budgets and agronomic water use efficiencies (WUEagro). To do so, a plot experiment with winter rye (September 17, 2020 to June 30, 2021) was conducted at an eroded cropland which is located in the hilly and dry ground moraine landscape of the Uckermark region in NE Germany. Along the experimental plot (110 m x 16 m), a gantry crane mounted mobile and automated two chamber system (FluxCrane as part of the AgroFlux platform within the CarboZALF-D research site) was used to continuously determine evapotranspiration for the first time. Three soil types representing the full soil erosion gradient related to the hummocky ground moraine landscape (extremely eroded: Calcaric Regosol, strongly eroded: Nudiargic Luvisol, non-eroded: Calcic Luvisol) and additional soil manipulation (topsoil removal and subsoil admixture) were investigated (randomized block design, 3 replicates per treatment). Five different gap-filling approaches were used and compared in light of their potential for reliable water budgets over the entire crop growth period as well as reproduce short-term (day-to-day, diurnal) water flux dynamics. The best calibration performance was achieved with approaches based on machine learning, such as support vector machine (SVM) and artificial neural networks (with Bayesian regularization; ANN_BR), while especially SVM yielded in best predictions of measured ET during validation.
We found significant differences in dry biomass (DM) and minor in evapotranspiration between soil types, resulting in different water use efficiencies (WUEagro). The Calcaric Regosol (extremely eroded) shows a maximum of around 37 % lower evapotranspiration and a maximum of around 52 % lower water use efficiency (WUEagro) compared to the non-eroded Calcic Luvisol. The key period contributing to ~ 70 % of overall ET of the entire growth period was from April until harvest, however differences in the overall ET budget (ETsum) between soil types and manipulation resulted predominantly from small long-term differences between the treatments over the entire growth period.
Adrian Dahlmann et al.
Status: final response (author comments only)
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RC1: 'Comment on hess-2022-323', Anonymous Referee #1, 19 Nov 2022
Review of “Measuring evapotranspiration on an eroded cropland by an automated and mobile chamber system: gap filling strategies and impact of soil type and topsoil removal” by Adrian Dahlmann et al., for HESS.
Summary
This manuscript presents a study of roughly one year of evapotranspiration measurements of a winter rye crop on a number of soil types. The ET measurements are novel, using an automated and mobile chamber system. The study reports and highlights the negative impact of eroded conditions on biomass growth and water use efficiency. Because of the novelty of the ET method, the study also investigates different gap-filling techniques. Here they find that machine learning approaches are better than simpler regression or look-up techniques. While this is an interesting study, I think there are many improvements that can be made to give it more relevance to both application users (farmers, land managers) and to the scientific community.
Major comments
- The focus of the paper is not clear and wanders between the new ET method and its gap-filling, the erosion gradient of soils, the role of ET in the water balance, and other impacts of erosion (e.g., on biomass production). A tighter, clearer focus will help – and then the methods parts can better be written to support the key aim, which is (to me at least) to explore the impact of soil conditions on agronomic and water balance impacts.
- Hypothesis-testing should be performed – it should be clearer both in the abstract and end of the introduction what the expectation is – how should the different soils change agronomic and ET outcomes? How should we be able to anticipate, from the literature, different performance among the gap-filling techniques?
- In general, there are many mistakes in the English language related to article use, comma positions, sentence structure, possessive apostrophe, etc. I have noted some of these below, but a careful edit should be performed with these issues in mind.
Minor comments
- The intro could be condensed, particularly the first paragraph (e.g., L36-40, 47-52, and remove “according to the European Union”).
- Consider moving L53-62 to the site description section in the methods.
- L77-81, Remove/condense; consider “field” instead of plot for eddy covarnacie
- L103-5 consider at minimum three aims (i.e., separate soil type and management from spatio-temporal variability). In general note other comments that there should be clearer hypotheses in this area about expectations related to soil/management type, seasonal development of ET and WUE, and the gap-filling methods
- L141 what kind of digestate?
- Section 2.3 misses info on measurement times, accuracy, precision, etc. of this novel system
- L157 describe the adjacent field a bit – given that the soils and management status can drastically change the soil moisture, how was the adjacent field treated? Also please add where this field is to the site map.
- L180 some chamber info is missing – what is the headspace, how tall is it relative to the biomass)
- L177 consider moving all or some of this on flux calculations and gap-filling to section 2.3
- L214 clarify if there is a moving window to this NLR or it’s just clumping allthe data – if so – how about trying a moving window or adding a term like days after planting (though RVI may be sufficient, it’s not clear – were regressions of the residuals tested?).
- L295 “differ between” and “minor differences” – are statistics performed here? Perhaps also some ranges of values can be given in the text
- L297 it’s not clear what magnitude is being described
- L302 start with the result as a topic sentence, rather than the exposition. The result and not “figure 4” should lead the paragraph.
- L308 the allocation problems could be described / tested? (also “one can quickly see…” can be edited)
- L310 “a large number of negative ET fluxes” – first, how many? Second, is there evidence of dew? A negative ET isn’t so implausible
- L318-320 could be put at the top of the paragraph
- L321 this section could be merged with the previous – consider the treatment effect and then the drivers
- L430 “to the amount of data” – how much? – you have a lot right? What would be sufficient?
- L432 this section is very long- be more concise, move parts that cite other work to other parts of the discussion (or a new section there) – moreover, this section starts with a description of gap-filling – is that the main finding? If so the paper should be reworked so it’s the dominant research question and the rest is a case study to test it. I’d tend to the think the focus should be on soils, management, and the resultant ET
- Fig 1 what do the colors in plot c represent? Where are the soil moisture measurements and adjacent field as indicated in text?
- Fig 2 clarify that this is incoming par and not absorbed, reflected, etc.
- Fig 3 change Okt to Oct, describe here or in the text where are values below zero? Indicate here or in the text whether these are already quality-screened and what those methods were, what is the estimated detection limit?
- Fig 6 some stats perhaps could help tell us if these curves or cumulations are different, significantly
- Fig 7 what are the colors?
- Fig 8 is an nova possible here, which are specifically different from each other?
- Fig A1 can real data be plotted here?
Technical comments
- L13 Add the before ongoing
- L16 change ingoing to incoming (and throughout)
- L17 the paper doesn’t really address the full water budget – perhaps main water budget term would be better?
- L92, 114 change build to built
- L95 change the aim was to the paper’s aim is…
- L102 reword “This enabled to asses”
- L103-4 be consistent with WUE vs WUEagro
- L114 the description of CarboZALF repeats the intro (and this sentence is too long)
- L120 “organic fertilized” interrupts the flow; it can be omitted
- L129 just topsoil (not topsoils) – and was not were
- L135 weighed not weighted
- L146 and elsewhere the “by” is not needed
- L155 remove comma after both
- L163 channel not canal
- L166 write out three, clarify “10 seconds = 10 records”
- L174 perhaps replace “further called” “what we term the”
- L208 change I to 1 (i.e., “eye” to “one”)
- L208-210 consider re-organizing like: “a simple stat approach: (1) MDV), two empirical… (2, 3), and two machine learning..(4,5) for consistent structure
- L258 add values after NSE
- L259 remove “the” and the s in parameters
- L269 change photosynthetic to photosynthetically
- L274 remove “in the observed period” or otherwise reword
- L275-6 to where does this downward trend go (Describe/quantify in text so one doesn’t have to look at the figure to determine it)
- L282 has a unique date style compared to the rest of the text
- L285 “nearly no differences” – perhaps negligible?
- L287 “clearly” ?
- L327 remove s from variables
- L330 remove used
- L331 change offers to offered
- L333 consider fewer rather than less
- L335 remove comma
- L337 reword – no need for “As well as” twice
- L337 add of after suitability
- L365 change was to were
- L397 change were spanning over to spanned
- L402 add t to constraints
- L445 remove comma after demonstrate
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RC2: 'Comment on hess-2022-323', Anonymous Referee #2, 16 Dec 2022
The authors present evapotranspiration (ET), water use efficiency (WUE) and ET gap-filling strategies along a toposequence of erosion for one growing season of winter wheat in NE Germany. In addition, a comparison between topsoil addition/removal is included in the study. ET is measured with a novel automatic chamber system comprising large transparent cylindrical chambers which are lowered on a collar from above using a crane. The advantage of this system is the relatively large measurement area and less impact of the automatic chamber as compared to other chamber systems. The study can be recommended for publication, however, there are aspects which should be considered for revision. (1) a complete revision from a native English speaker would improve the readability of the manuscript (disclaimer: saying that without being a native English speaker myself). (2) The method section should include more information on how ET was measured. (3) The discussion and conclusion section would need complete revision; the prior needs more focus on the study, the latter is too long and should be condensed to the most important aspects. (4) the measured ET has not been compared to other ET methodologies; this discussion point should be further strengthened. See details below:
Abstract:
L33: please include month of harvest here
L34: the concluding sentence is not clear to the reader, what is meant by “small long-term differences”?
Introduction
L39-40: Please include a reference showing that climate change and increase in human population are responsible for increased land use for agriculture.
L44/57: what is meant by “fertility” and “fertile” here? Probably better to use the term “plant production”, “yield” “productive” etc. because fertility and fertile refers to generative reproduction
L47: is it 10-40% of rainfall?
L48-50: not sure, if this is a trend. NE Germany has typically lower rainfall compared to the rest of Germany, should not be related to climate change
L82: should probably read “field scale” here, using eddy covariance on plot level is difficult.
L83: if this is the footprint of eddy-covariance: please keep in mind that the footprint (in field crops) is probably lower than millions of square meters – especially at daytime (which is the important time period for ET) and during the growing season. The measurement height must be quite high then to reach such a huge footprint.
L103: include “WUEagro” in brackets here.
L109: should read “soil surface”
L113: should read “study” instead of “investigations”
L124 and following: please remove brackets where not needed.
L126 and following: probably better to use the term “topsoil modification” as in L121.
L129/140: should read “fertilizer application” instead of “fertilization”
L129: should probably be 3 of 6 plots per soil type
L130-135: it is not clear to the reader why this modification of the soil was done? What is the reason for it? What can be taken from the comparison of modified vs. non-modified? This needs further explanation in the Introduction, Method, and Discussion section.
L134: How much soil was added to each of the soil types?
L140: what was the amount of macronutrients applied?
L141-142: could this be a problem when comparing non-modified vs. modified plots? Did the modification improve germination of the crop?
L143: When was glyphosate applied? The term “Round-up” can be removed.
L144-152: It would be recommendable to explain the whole system here, i.e., analyzers and sensors, variables taken, measurement rate, length of measurement, how many measurement per day etc.
L144: Did the chambers have fans?
L150-151: not sure what is meant here with “parallel”
L155-159: please include which sensors were used. Also, a discussion on inside and outside PAR and Temp is helpful here.
L159: Is the SM measurement comparable when measured in an adjacent field without the treatment effects?
L161: should read “plots”
L166 the area of measurement probably depends on the measurement height here, please include.
L166/167: it is not clear how many measurements were taken with this information, please re-phrase.
L172: Please describe further what is meant by “stagnation”
L182-183: Please include the exact number of measurements. It is not clear how many measurements per day were made, how often was measured, how much original data was available.
L184: Were nighttime data included in the calculations? This may impact mean values.
L189: please include the step how ET was converted from mmol to kg (for WUE).
L195-197: please include how much data was there originally, how much data was excluded as outlier per treatment, and later, how much data was gap-filled.
L197 please write out “interquartile range”
L206: should read “2.5.2”
L244/311: why use SVM alone and not all gap-filling strategies and discuss it?
L250: why not include NEE/GPP here and calculate WUE as GPP/ET? The LI850 would give the corresponding CO2 flux for it? The PAR and Temp could help to calculate respiration.
L259-260: would a multilinear model work to estimate/explain ET? Is there difference among treatments or can the data be combined?
Results:
L264-265: should be part of Method section
L283-291: not sure about the approximation sign here ~: RVI values are shown with accuracy of two digits.
L293-295: should be part of Method section, and in more detail.
L296-300: please include actual ET values here.
L308: what is meant by “allocation problems”?
L309: what is the difference between Table 1 and 2. The table description does not tell.
L311: could it be a solution to set negative values to zero? Were these nighttime values?
L319-320: should be part of section 3.6.
Discussion
L328: Micro Bowen ratio systems have a relatively small footprint and can be used for small scales.
L330: “used, new” please re-phrase: the reader may think: “either it is used or new”
L332: Please re-phrase, because eddy covariance ET flux is averaged over 30-minute intervals and measures at 20 Hz.
L334: it is not clear from the current version of the manuscript, if the ET is measured reliably (I suspect so, but it is not clear to the reader at this point). Please include a Discussion section about it.
L340: it is not clear what “long term” means here.
L244: it is not clear what “more dynamically” means.
L345: why not include VPD in the study here. It should be possible to calculate it. It may give more insight the crop-atmosphere interaction.
L346: how does PAR impact ET? There is significant relationship, but an explanation is missing.
L347: exclude “in summary”
L349: only one measurement from an adjacent field available.
L382-383: what is meant by “static differences”?
L395: should read “ET”
L395-398: should be part of a separate section on the accuracy of the ET measurements.
L405-410: please re-phrase this statement.
L427-429: why not include wind speed in this study? Were no measurements available? Strong winds are mentioned L447, so maybe the crane is equipped with an anemometer?
L412: please adjust LUT then for this study. There is room for improvement, as can be seen in Figure 5. It seems that a few events are off, which if excluded improve the R2 substantially.
Conclusion – in general too long and rather a discussion than a conclusion. Please consider moving L433-444 and L454-464 (and others) to the discussion section, and re-write the conclusion as a summary of the most important findings.
L466: Why not include it in this study?
Figure 3: “replicates summarized” – is it the mean or the sum of three replicates?
Table B2 and Figure 7 could be combined.
Figure 8. what is the standard deviation and what is the mean in the figure? Also, please discuss the effect of DM and ET on WUE in the Discussion section in more detail. E.g., it seems quite interesting that modified and non-modified Regosols have similar ET but different DM which impacts WUE.
Fiugre A1/Figure 6: what kind of variation is shown in the graph?
Figure 6: seasonal ET, is this the cumulative ET shown here?
Adrian Dahlmann et al.
Adrian Dahlmann et al.
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