Advancing simulations of water fluxes, soil moisture and drought stress by using the LWF-Brook90 hydrological model in R
dc.contributor.author
Schmidt-Walter, Paul
dc.contributor.author
Trotsiuk, Volodymyr
dc.contributor.author
Meusburger, Katrin
dc.contributor.author
Zacios, Martina
dc.contributor.author
Meesenburg, Henning
dc.date.accessioned
2020-08-07T06:49:05Z
dc.date.available
2020-06-03T15:48:26Z
dc.date.available
2020-06-04T07:41:16Z
dc.date.available
2020-08-07T06:49:05Z
dc.date.issued
2020-09-15
dc.identifier.issn
0168-1923
dc.identifier.issn
1873-2240
dc.identifier.other
10.1016/j.agrformet.2020.108023
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/417994
dc.description.abstract
Soil vegetation atmosphere transport (SVAT) models are important for the quantification of water fluxes, soil water availability, drought stress and their uncertainties under climate change. We present LWFBrook90R, an enhanced implementation of the well-established, process-based SVAT model LWF-Brook90 for the R environment for statistical computing. The package provides new functions and sub-models for model parameterization, and facilitates parallel computing, sensitivity analysis and inverse calibration of the model. A case study comprising i) basic forward water balance simulations for temperate grassland vegetation, deciduous and evergreen forest, ii) a parallelized sensitivity analysis, and iii) Bayesian calibrations based on soil water storage observed in a poplar (Populus nigra × P. maximowiczii) Short Rotation Forest (SRF) demonstrates the utility of the R package. The sensitivity analysis revealed parameters affecting plant-available soil water storage capacity and the vegetation's timing and level of water demand to be most important for the annual course of simulated soil water storage, with seasonal and interannual differences in parameter importance rankings. The subsequent calibration yielded a very high agreement between daily simulated and observed soil water storage (0-200 cm soil depth) for the calibration and validation datasets, with Nash-Sutcliffe efficiencies of 0.97 and 0.95, respectively. The final model predicted high though realistic rates of annual evapotranspiration (2011: 844 ± 3.8 mm y-1, 2012: 733 ± 4.5 mm y-1) for the poplar SRF, regularly exceeding grass reference evaporation (ET0) by 20-47% during the months of the growing season. However, basing calibrations solely on observed soil water storage probably resulted in biased partitioning of evapotranspiration towards interception losses. The integration of the LWF-Brook90 hydrological model into R with its wide variety of extensions was successfully tested and may provide efficient, reliable and reproducible water balance predictions by facilitating complex statistical analyses and large-scale applications of the model.
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.subject
Climate impact
en_US
dc.subject
Water balance
en_US
dc.subject
Evapotranspiration
en_US
dc.subject
Model calibration
en_US
dc.subject
Sensitivity analysis
en_US
dc.subject
Short rotation
en_US
dc.title
Advancing simulations of water fluxes, soil moisture and drought stress by using the LWF-Brook90 hydrological model in R
en_US
dc.type
Journal Article
dc.date.published
2020-05-29
ethz.journal.title
Agricultural and Forest Meteorology
ethz.journal.volume
291
en_US
ethz.journal.abbreviated
Agric. for. meteorol.
ethz.pages.start
108023
en_US
ethz.size
13 p.
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Amsterdam
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02703 - Institut für Agrarwissenschaften / Institute of Agricultural Sciences::03648 - Buchmann, Nina / Buchmann, Nina
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02703 - Institut für Agrarwissenschaften / Institute of Agricultural Sciences::03648 - Buchmann, Nina / Buchmann, Nina
en_US
ethz.date.deposited
2020-06-03T15:48:37Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2020-08-07T06:49:22Z
ethz.rosetta.lastUpdated
2021-02-15T15:57:01Z
ethz.rosetta.versionExported
true
ethz.COinS
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