Abstract
IntroductionWet grassland sites have accumulated large amounts of carbon in their soil over millennia. While under excessive drainage and intensive agriculture, these sites have shown substantial losses of the stored carbon to the atmosphere, the current climate mitigation strategies see a conversion of this process through rewetting. Situated in the fringe of ascending groundwater, these sites respond very sensitively to changes in the water table, both in the vegetation and the turn-over processes in the soil. While researchers have extensively investigated how wet grasslands respond to changes in environmental conditions or management practices from various perspectives, there is a lack of a comprehensive simultaneous study addressing the intricate interplay of water, carbon, and nitrogen cycles in these ecosystems. This study aimed at addressing the water, carbon, and nitrogen dynamics in a wet grassland site using a process-based agroecosystem model to prepare the model for future scenario simulations under various options for rewetting.Material and methodThe study site is situated in the Spreewald wetlands, where a lysimeter station featuring four lysimeters with different groundwater level management practices has been installed. Within the lysimeter station, a weather station records the meteorological conditions. Above-ground biomass is measured after each cut, and various parameters including evapotranspiration, gross primary productivity, ecosystem respiration, nitrogen amount in biomass, nitrate leaching, and N2O are monitored. The process-based model employed in this study is the MONICA model (Model for Nitrogen and Carbon in Agro-ecosystems). The SPOTPY algorithm was used for optimising the model.ResultsPresented in three categories are the results: firstly, evapotranspiration as a vital component of the water cycle; followed by gross primary productivity and ecosystem respiration, offering insights into the carbon cycle. Additionally, nitrogen content in biomass, nitrate leachate, and N2O are examined, providing information related to the nitrogen balance.Within a wet grassland ecosystem, MONICA has effectively reproduced these essential variables, showcasing remarkable performance with rRMSE ranging between 0.05 to 0.81, and Willmott’s Refined Index of Agreement dr ≥ 0.3 in all cases. This substantiates its capability to simulate the impacts of environmental or management changes, particularly those associated with modifications in surface-near groundwater conditions. The model's robust replication of crucial variables emphasizes its suitability for comprehensive assessments in dynamic ecological scenarios.Keywords: Wet grasslands, Carbon, Nitrogen, MONICA, SPOTPY algorithm
Published Version
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