Simulation of alfalfa yield with AquaCrop
Dirk Raes,
Elias Fereres,
Margarita García Vila,
Yannick Curnel,
David Knoden,
Sema Kale Çelik,
Yusuf Ucar,
Mevlüt Türk and
Joost Wellens
Agricultural Water Management, 2023, vol. 284, issue C
Abstract:
The AquaCrop simulation model, originally designed for annual crops, is expanded here to simulate alfalfa, a perennial forage crop. A new routine was added to the model to mimic the assimilate partitioning between above and below-ground plant parts to account for the utilization of reserves in Spring and for their storage in the Fall. The simulation of the transfer of assimilates requires only three extra crop parameters which makes the model also easy to calibrate. To evaluate the model, yield data collected in Louvain-La-Neuve (Belgium), Isparta (Turkey), and Ottawa (Canada) for different alfalfa cultivars, various years and field and irrigation management strategies were used. To assess the accuracy and robustness of the simple assimilate remobilization process, simulations were run for the three different environments with a common set of crop parameters which were parameterized. The dispersion between the observed and simulated cumulative dry above-ground biomass during the growing cycle was small (r² = 0.97; nRMSE = 11%; Nash-Sutcliffe model EF = 0.97), and a systematic over- or underestimation by the model was not observed (Willmott’s index of agreement, d = 0.99). When evaluating the goodness of fit of the 81 individual harvest events, the results were still very satisfactory although the nRMSE doubled. The simulations indicated that the AquaCrop model adapted to perennial crops and with a novel storage-remobilization routine, could predict well alfalfa yields in various climates and environments, with and without water and fertility stress, and for three different alfalfa cultivars.
Keywords: AquaCrop; Crop simulation models; Alfalfa; Perennial forage crops; Transfer of assimilates; Length of growing cycle; Natural self-thinning (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:agiwat:v:284:y:2023:i:c:s0378377423002068
DOI: 10.1016/j.agwat.2023.108341
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