@article{ZicheRiekRussetal.2021, author = {Ziche, Daniel and Riek, Winfried and Russ, Alexander and Hentschel, Rainer and Martin, Jan}, title = {Water Budgets of Managed Forests in Northeast Germany under Climate Change - Results from a Model Study on Forest Monitoring Sites}, series = {Applied Sciences}, volume = {11}, journal = {Applied Sciences}, number = {5}, publisher = {MDPI}, issn = {2076-3417}, doi = {10.3390/app11052403}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:eb1-opus-2470}, pages = {18}, year = {2021}, abstract = {To develop measures to reduce the vulnerability of forests to drought, it is necessary to estimate specific water balances in sites and to estimate their development with climate change scenarios. We quantified the water balance of seven forest monitoring sites in northeast Germany for the historical time period 1961-2019, and for climate change projections for the time period 2010-2100. We used the LWF-BROOK90 hydrological model forced with historical data, and bias-adjusted data from two models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) downscaled with regional climate models under the representative concentration pathways (RCPs) 2.6 and 8.5. Site-specific monitoring data were used to give a realistic model input and to calibrate and validate the model. The results revealed significant trends (evapotranspiration, dry days (actual/potential transpiration < 0.7)) toward drier conditions within the historical time period and demonstrate the extreme conditions of 2018 and 2019. Under RCP8.5, both models simulate an increase in evapotranspiration and dry days. The response of precipitation to climate change is ambiguous, with increasing precipitation with one model. Under RCP2.6, both models do not reveal an increase in drought in 2071-2100 compared to 1990-2019. The current temperature increase fits RCP8.5 simulations, suggesting that this scenario is more realistic than RCP2.6}, language = {en} } @article{GrohDiamantopoulosDuanetal.2022, author = {Groh, Jannis and Diamantopoulos, Efstathios and Duan, Xiaohong and Ewert, Frank and Heinlein, Florian and Herbst, Michael and Holbak, Maja and Kamali, Bahareh and Kersebaum, Kurt-Christian and Kuhnert, Matthias and Nendel, Claas and Priesack, Eckart and Steidl, J{\"o}rg and Sommer, Michael and P{\"u}tz, Thomas and Vanderborght, Jan and Vereecken, Harry and Wallor, Evelyn and Weber, Tobias K. D. and Wegehenkel, Martin and Weiherm{\"u}ller, Lutz and Gerke, Horst H.}, title = {Same soil, different climate: Crop model intercomparison on translocated lysimeters}, series = {Vadose Zone Journal}, volume = {21}, journal = {Vadose Zone Journal}, number = {4}, publisher = {Wiley}, issn = {1539-1663}, doi = {10.1002/vzj2.20202}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:eb1-opus-5395}, year = {2022}, abstract = {Crop model intercomparison studies have mostly focused on the assessment of predictive capabilities for crop development using weather and basic soil data from the same location. Still challenging is the model performance when considering complex interrelations between soil and crop dynamics under a changing climate. The objective of this study was to test the agronomic crop and environmental flux-related performance of a set of crop models. The aim was to predict weighing lysimeter-based crop (i.e., agronomic) and water-related flux or state data (i.e., environmental) obtained for the same soil monoliths that were taken from their original environment and translocated to regions with different climatic conditions, after model calibration at the original site. Eleven models were deployed in the study. The lysimeter data (2014-2018) were from the Dedelow (Dd), Bad Lauchst{\"a}dt (BL), and Selhausen (Se) sites of the TERENO (TERrestrial ENvironmental Observatories) SOILCan network. Soil monoliths from Dd were transferred to the drier and warmer BL site and the wetter and warmer Se site, which allowed a comparison of similar soil and crop under varying climatic conditions. The model parameters were calibrated using an identical set of crop- and soil-related data from Dd. Environmental fluxes and crop growth of Dd soil were predicted for conditions at BL and Se sites using the calibrated models. The comparison of predicted and measured data of Dd lysimeters at BL and Se revealed differences among models. At site BL, the crop models predicted agronomic and environmental components similarly well. Model performance values indicate that the environmental components at site Se were better predicted than agronomic ones. The multi-model mean was for most observations the better predictor compared with those of individual models. For Se site conditions, crop models failed to predict site-specific crop development indicating that climatic conditions (i.e., heat stress) were outside the range of variation in the data sets considered for model calibration. For improving predictive ability of crop models (i.e., productivity and fluxes), more attention should be paid to soil-related data (i.e., water fluxes and system states) when simulating soil-crop-climate interrelations in changing climatic conditions.}, language = {en} }