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TY  - THES
AU  - Boas, Theresa Sophie
TI  - Advancing the representation of agricultural systems in land surface models: systematic model evaluations and technical model developments
VL  - 640
PB  - RWTH Aachen University
VL  - Dissertation
CY  - Jülich
M1  - RWTH-2024-09591
SN  - 978-3-95806-777-6
T2  - Schriften des Forschungszentrums Jülich. Reihe Energie & Umwelt = Energy & environment
SP  - 1 Online-Ressource (xxi, 146 Seiten) : Illustrationen, Diagramme, Karten
PY  - 2024
N1  - Druckausgabe: 2024. - Onlineausgabe: 2024. - Auch veröffentlicht auf dem Publikationsserver der RWTH Aachen University 2025. - Cotutelle-Dissertation
N1  - Dissertation, RWTH Aachen University, 2024. - Dissertation, University of Melbourne, 2024
AB  - Global climate change, with its projected increase in weather extremes and drought risk, presents global and regional agriculture with vulnerability and new challenges. It is crucial to gain a comprehensive understanding and accurate quantification of the intricate dynamics of agricultural land cover and its role within the terrestrial system, especially in the context of climate change. Land surface models play a central role for the research on climate change effects on the Earth's surface and hold particular value in examining the influence of weather patterns on agricultural land at larger spatial scales. The incorporation of a comprehensive crop module in land surface models offers the possibility to study the effect of agricultural land use and land management changes on the terrestrial water, energy and biogeochemical cycles. It may help to improve the simulation of biogeophysical and biogeochemical processes on regional and global scales and thus to study climate change impacts on terrestrial ecosystem as well as the significance of human land cover changes for climate change. Land surface models simulate the complex interactions at the terrestrial land surface in response to atmospheric states, based on land cover and soil type information. In combination with data from different sources, like seasonal weather forecasts, land surface models can potentially provide useful information for water resources or agricultural planning. In this thesis, a systematic evaluation of the state-of-the-art land surface model, the Community Land Model version 5.0 (CLM5), was conducted from point to regional scales in combination with data from a multitude of sources, e.g. from remote sensing, numerical predictions and field observations. A special focus was placed on the representation of arable land and its feedback to weather related factors in the context of climate change. In the first part of this thesis, the performance of the crop module of CLM5 was evaluated at point scale with site specific field data focussing on the simulation of seasonal and inter-annual variations in crop growth, planting and harvesting cycles, and crop yields as well as water, energy and carbon fluxes. In order to better represent agricultural sites, the model was modified by (1) implementing the winter wheat subroutines after Lu et al. (2017) in CLM5; (2) implementing plant specific parameters for sugar beet, potatoes and winter wheat, thereby adding the two crop functional types (CFT) for sugar beet and potatoes to the list of actively managed crops in CLM5; (3) introducing a cover cropping subroutine that allows multiple crop types on the same column within one year. The latter modification allows the simulation of cropping during winter months before usual cash crop planting begins in spring, which is an agricultural management technique with a long history that is regaining popularity to reduce erosion, improve soil health and carbon storage, and is commonly used in the regions evaluated in this study. In comparison with field data, the crop specific parameterizations, as well as the winter wheat subroutines, led to a significant simulation improvement in terms of energy fluxes (RMSE reduction for latent and sensible heat by up to 57 
LB  - PUB:(DE-HGF)11 ; PUB:(DE-HGF)3
DO  - DOI:10.18154/RWTH-2024-09591
UR  - https://publications.rwth-aachen.de/record/994926
ER  -