Measuring evapotranspiration on an eroded cropland by an automated and mobile chamber system: gap filling strategies and impact of soil type and topsoil removal

Dahlmann, Adrian; Hoffmann, Mathias; Verch, Gernot; Schmidt, Marten; Sommer, Michael; Augustin, Jürgen; Dubbert, Maren

doi:https://doi.org/10.5194/hess-2022-323

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https://doi.org/10.5194/hess-2022-323

Preprints

02 Nov 2022

Status: this preprint is currently under review for the journal HESS.

Measuring evapotranspiration on an eroded cropland by an automated and mobile chamber system: gap filling strategies and impact of soil type and topsoil removal

Adrian Dahlmann¹, Mathias Hoffmann¹, Gernot Verch², Marten Schmidt¹, Michael Sommer^3,4, Jürgen Augustin¹, and Maren Dubbert¹ Adrian Dahlmann et al.

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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

Received: 09 Sep 2022 – Discussion started: 02 Nov 2022

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 (WUE_agro). 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 (WUE_agro). The Calcaric Regosol (extremely eroded) shows a maximum of around 37 % lower evapotranspiration and a maximum of around 52 % lower water use efficiency (WUE_agro) 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 (ET_sum) 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: open (until 28 Dec 2022)

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RC1:
'Comment on hess-2022-323', Anonymous Referee #1, 19 Nov 2022 reply
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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Citation: https://doi.org/10.5194/hess-2022-323-RC1

Adrian Dahlmann et al.

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Short summary

In light of ongoing global climate crisis, it is crucial to understand the ecosystem water cycle. Evapotranspiration plays a pivotal role, returning up to 90 % of precipitation to the atmosphere. We studied impacts of soil type and management on an agroecosystem using an automated system coupled with modern gap-filling approaches. We were able to calculate ET in a high spatial and temporal resolution and found significant differences between yield and smaller differences in evapotranspiration.


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