Same soil, different climate: Crop model intercomparison on translocated lysimeters

Jannis Groh*, Efstathios Diamantopoulos, Xiaohong Duan, Frank Ewert, Florian Heinlein, Michael Herbst, Maja Holbak, Bahareh Kamali, Kurt-Christian Kersebaum, Matthias Kuhnert, Claas Nendel, Eckart Priesack, Jorg Steidl, Michael Sommer, Thomas Puetz, Jan Vanderborght, Harry Vereecken, Evelyn Wallor, Tobias K. D. Weber, Martin WegehenkelLutz Weihermueller, Horst H. Gerke

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

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 Lauchstadt (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.

Original languageEnglish
Article number20202
Number of pages25
JournalVadose zone journal
Early online date16 May 2022
DOIs
Publication statusE-pub ahead of print - 16 May 2022

Keywords

  • WATER-USE EFFICIENCY
  • HEAT-STRESS
  • EDDY COVARIANCE
  • HARVEST INDEX
  • CHANGE IMPACT
  • WHEAT YIELDS
  • CALIBRATION
  • UNCERTAINTY
  • SIMULATION
  • GROWTH

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