Separating precipitation and evapotranspiration from noise – a new filter routine for high-resolution lysimeter data

Peters, André; Nehls, Thomas; Schonsky, Horst; Wessolek, Gerd

doi:10.5194/hess-18-1189-2014

Cited by 79 publications

(68 citation statements)

References 22 publications

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“…The lysimeter readings are affected by large random fluctuations caused by wind and other factors that influence the measurement. Therefore, the AWAT filter (Peters et al, 2014) in a second correction step was applied on the minute-wise summed leachate and on the weights for each individual lysimeter. First, the AWAT routine gathers information about signal strength and data noise by fitting a polynomial to each data point within an interval of 31 min.…”

Section: Lysimetermentioning

confidence: 99%

“…They pointed out that the adequate filter method for lysimeter measurements is still a challenge, especially at high temporal resolution, due the fact that noise of lysimeter measurements varies strongly with weather conditions and mass balance dynamics. Peters et al (2014) recently introduced a filter algorithm for high-precision lysimeters, which combines a variable smoothing time window with a noise-dependent threshold filter that accounts for the factors mentioned above. They showed that their Adaptive Window and Adaptive Threshold (AWAT) filter improves actual evapotranspiration and precipitation estimates from noisy lysimeter measurements compared to smoothing methods for lysimeter data using the Savitzky-Golay filter or simple moving averages used in other lysimeter studies (e.g., Vaughan and Ayars, 2009;Huang et al, 2012;Nolz et al, 2013;Schrader et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Differences in the thermal, wind, and radiation regime between a lysimeter device and its surroundings (oasis effect) (Zenker, 2003) as well as lysimeter management (e.g., inaccuracies in biomass determination) can affect the measurements. Wind or animal-induced mechanical vibrations can influence the weighing system but can be handled by accurate data processing using filtering and smoothing algorithms (Schrader et al, 2013;Peters et al, 2014). Vaughan and Ayars (2009) examined lysimeter measurement noise for data at a temporal resolution of 1 min, caused by wind loading.…”

Section: Introductionmentioning

confidence: 99%

“…Additional soil moisture, soil temperature, and meteorological measurements at this TERENO test site enable a detailed analysis of differences between the different measurement techniques. The lysimeter data (ET a -LYS) are processed with the AWAT filter (Peters et al, 2014), which allows a simultaneous estimation of P and ET a at a high temporal resolution, and the comparison is carried out with energy-balance-corrected EC data (ET a -EC). Actual ET estimates are additionally compared to the full-form PenmanMonteith equation (Allen et al, 1998) accounting for the effects of variable grass cover height.…”

Section: Introductionmentioning

confidence: 99%

“…ET a differences between lysimeter and EC were mainly related to differences in grass height caused by harvest and the EC footprint. The lysimeter data were also used to estimate precipitation amounts in combination with a filter algorithm for the high-precision lysimeters recently introduced by Peters et al (2014). The estimated precipitation amounts from the lysimeter data differ significantly from precipitation amounts recorded with a standard rain gauge at the Rollesbroich test site.…”

mentioning

confidence: 99%

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Actual evapotranspiration and precipitation measured by lysimeters: a comparison with eddy covariance and tipping bucket

Gebler¹,

Franssen²,

Pütz³

et al. 2015

Hydrol. Earth Syst. Sci.

155

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Abstract. This study compares actual evapotranspiration (ET a ) measurements by a set of six weighable lysimeters, ET a estimates obtained with the eddy covariance (EC) method, and evapotranspiration calculated with the full-form Penman-Monteith equation (ET PM ) for the Rollesbroich site in the Eifel (western Germany). The comparison of ET a measured by EC (including correction of the energy balance deficit) and by lysimeters is rarely reported in the literature and allows more insight into the performance of both methods. An evaluation of ET a for the two methods for the year 2012 shows a good agreement with a total difference of 3.8 % (19 mm) between the ET a estimates. The highest agreement and smallest relative differences (< 8 %) on a monthly basis between both methods are found in summer. ET a was close to ET PM , indicating that ET was energy limited and not limited by water availability. ET a differences between lysimeter and EC were mainly related to differences in grass height caused by harvest and the EC footprint. The lysimeter data were also used to estimate precipitation amounts in combination with a filter algorithm for the high-precision lysimeters recently introduced by Peters et al. (2014). The estimated precipitation amounts from the lysimeter data differ significantly from precipitation amounts recorded with a standard rain gauge at the Rollesbroich test site. For the complete year 2012 the lysimeter records show a 16 % higher precipitation amount than the tipping bucket. After a correction of the tipping bucket measurements by the method of Richter (1995) this amount was reduced to 3 %. With the help of an onsite camera the precipitation measurements of the lysimeters were analyzed in more detail. It was found that the lysimeters record more precipitation than the tipping bucket, in part related to the detection of rime and dew, which contribute 17 % to the yearly difference between both methods. In addition, fog and drizzle explain an additional 5.5 % of the total difference. Larger differences are also recorded for snow and sleet situations. During snowfall, the tipping bucket device underestimated precipitation severely, and these situations contributed also 7.9 % to the total difference. However, 36 % of the total yearly difference was associated with snow cover without apparent snowfall, and under these conditions snow bridges and snow drift seem to explain the strong overestimation of precipitation by the lysimeter. The remaining precipitation difference (about 33 %) could not be explained and did not show a clear relation to wind speed. The variation of the individual lysimeters devices compared to the lysimeter mean are small, showing variations up to 3 % for precipitation and 8 % for evapotranspiration.

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Section: Lysimetermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Actual evapotranspiration and precipitation measured by lysimeters: a comparison with eddy covariance and tipping bucket

Gebler¹,

Franssen²,

Pütz³

et al. 2015

Hydrol. Earth Syst. Sci.

155

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The effect of plant size and branch traits on rainfall interception of 10 temperate tree species

Pflug

Voortman²,

Cornelissen

et al. 2021

Ecohydrology

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Rainfall interception by vegetation plays an important role in the hydrological cycle.Next to rainfall characteristics, interception is influenced by tree size, crown structure and bark morphology. How tree traits determine interception across functionally and morphologically wide-ranging tree species is poorly understood. We determined interception ratios (interception:gross precipitation) and canopy storage capacities of seven temperate deciduous broadleaved (Acer pseudoplatanus L., Betula pendula Roth, Carpinus betulus L., Fagus sylvatica L., Populus tremula L., Sorbus aucuparia L.) and three evergreen coniferous tree species (Picea abies (L.) Karsten, Pinus sylvestris L., Pseudotsuga menziesii (Mirb.) Franco) as well as the influence of various tree traits on interception parameters. Interception was measured directly with natural rainfall by means of gravimetry on potted trees, 2-8 m tall, for seven consecutive months. Our results show that (a) the coniferous species had larger canopy storage capacities and larger interception ratios than the broadleaved species both during (summer) and outside the growing season (winter); (b) the absolute tree interception (in kg) of the broadleaved species was positively related to stem diameter at breast height, tree and crown height, maximum branch length, the total branch surface area and above ground dry weight; and (c) interception per unit crown projected area (in mm) of all species was positively related to branch length and branch surface area per unit crown projected area. These results can be used to estimate interception parameters from plant traits and to simulate interception losses of trees in a more reliable manner.

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Quantifying evapotranspiration from dominant Arctic vegetation types using lysimeters

2022

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The thermal and hydraulic properties of the moss and organic layer regulate energy fluxes, permafrost stability, and hydrologic function in Arctic tundra. Our goal was to quantify evapotranspiration (ET) from dominant vegetation types in Arctic tundra. We designed and deployed a network of electronic automated weighing micro‐lysimeters (n = 58, area = 0.06 m2). We selectively clipped groups of plants from a subset of lysimeters to isolate ET from moss, tussocks, and mixed vascular plants. High rates of evaporation (E) recorded during the study period in the moss E lysimeters (64 mm) and high ET in the tussock ET lysimeters (60 mm) show that mosses and sedge tussocks (Eriophorum vaginatum) are the major constituents of local tundra ET. Moss E was consistently higher than ET from mixed vascular species with moss understory indicating that moss E dominates tundra water efflux at sites with moss understory. The ET partitioning presented here will allow for improved prediction of changes in water flux associated with observed and future vegetation change. Future changes in the composition and cover of mosses and vascular plants will not only alter partitioning of tundra ET but may also affect the significant role plants play in the moisture regime and thermodynamics of Arctic permafrost soils.

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Separating precipitation and evapotranspiration from noise – a new filter routine for high-resolution lysimeter data

Cited by 79 publications

References 22 publications

Actual evapotranspiration and precipitation measured by lysimeters: a comparison with eddy covariance and tipping bucket

Actual evapotranspiration and precipitation measured by lysimeters: a comparison with eddy covariance and tipping bucket

The effect of plant size and branch traits on rainfall interception of 10 temperate tree species

Quantifying evapotranspiration from dominant Arctic vegetation types using lysimeters

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