Calibration of the phenology sub-model of APSIM-Oryza: Going beyond goodness of fit

Nissanka, S. P.; Karunaratne, Asha S.; Perera, Ruchika S.; Weerakoon, W. M. W.; Thorburn, Peter J.; Wallach, Daniel

doi:10.1016/j.envsoft.2015.04.007

Cited by 31 publications

(25 citation statements)

References 24 publications

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“…We selected the Sri Lankan local cultivar BG357 for this study. We modified the Oryza model in APSIM 7.10 by adding the new cultivar BG357 and parameterized the cultivar using the values reported by Zubair et al [53] and Nissanka et al [54]. We set the maximum ponding as 100 mm during the period of 1 December until the end of February.…”

Section: Apsim Simulationmentioning

confidence: 99%

A Functional Analysis of Pedotransfer Functions Developed for Sri Lankan soils: Applicability for Process-Based Crop Models

et al. 2020

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As measurements are expensive and laborious, the estimation of soil hydraulic properties using pedotransfer functions (PTFs) has become popular worldwide. However, the estimation of soil hydraulic properties is not the final aim but an essential input value for other calculations and simulations, mostly in environmental and crop models. This modeling approach is a popular way to assess agricultural and environmental processes. However, it is rarely used in Sri Lanka because soil hydraulic data are rare. We evaluated the functionality of PTFs (developed to estimate field capacity (FC) and the permanent wilting point (PWP) of Sri Lankan soils) for process-based crop models. We used the Agricultural Production Systems sIMulator (APSIM) as the test model. Initially, we confirmed the importance of PWP (LL15) and FC (DUL) by assessing the sensitivity of the soil input parameters on the growth and yield of rice under rainfed conditions. We simulated the growth and yield of rice and the four selected outputs related to the APSIM soil module using the measured and estimated values of FC and PWP. These simulations were conducted for ten years in 16 locations of Sri Lanka, representing wet, intermediate, and dry zones. The simulated total aboveground dry matter and weight of the rough rice, using both input conditions (the measured and PTF-estimated soil hydraulic properties), showed good agreement, with no significant differences between each other. Outputs related to the soil module also showed good agreement, as no significant differences were found between the two input conditions (measured and PTF-estimated soil hydraulic properties). Although the DUL and LL15 are the most influential parameters for the selected outputs of APSIM-Oryza, the estimated FC and PWP values did not change the predictive ability of APSIM. In this way, the functionality of PTFs for APSIM crop modeling is confirmed.Agronomy 2020, 10, 285 2 of 18 world, especially in tropical regions [1]. Pedotransfer functions (PTFs) are predictive functions used to estimate difficult-to-measure soil parameters with easily measurable soil parameters [2]. Point-based PTFs are used to determine soil parameters at specific, conventional values of matric potential [3]. The moisture content at −10 and −33 kPa (representing the field capacity (FC)) and moisture content at -1500 kPa (representing the permanent wilting point (PWP)) are the most common reference values for the soil moisture characteristic curve (SMCC) used for point PTFs [4].Point PTFs were developed [5] for Sri Lankan soil and confirmed the statistical accuracy of these PTFs for Sri Lankan conditions. However, these PTFs cannot perfectly calculate soil hydraulic parameters. In other words, there are always some errors that could be over or underestimated according to soil type. These errors may be different according to the application of the PTFs. Hence, the final estimation of the model quality should be defined by the model's applicability [6] because the estimation of hydraulic properties is not the...

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Section: Apsim Simulationmentioning

confidence: 99%

A Functional Analysis of Pedotransfer Functions Developed for Sri Lankan soils: Applicability for Process-Based Crop Models

et al. 2020

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“…It drives ecosystem productivity (Richardson et al, 2012), carbon (Delpierre et al, 2009), water (Hogg et al, 2000) and nutrient (Cooke & Weih, 2005) cycling processes, as well as energy balance (Wilson & Baldocchi, 2000). Moreover, plant phenology critically affects yield and organoleptic quality of crop harvest (Nissanka et al, 2015) as well as species distributions (Chuine, 2010). The onset of plant activity has been reported to advance by 2.5 days per decade on average during the last 50 years (Menzel et al, 2006), potentially increasing the risk of frost damages on flowers and leaves (Vitasse et al, 2018a).…”

Section: Introductionmentioning

confidence: 99%

Sensitivity analysis of tree phenology models reveals increasing sensitivity of their predictions to winter chilling temperature and photoperiod with warming climate

Gauzere

Lucas

Ronce

et al. 2019

Ecological Modelling

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The phenology of plants is a major driver of agro-ecosystem processes and biosphere feedbacks to the climate system. Phenology models are classically used in ecology and agronomy to project future phenological changes. With our increasing understanding of the environmental cues affecting bud development, phenology models also increase in complexity. But, we expect these cues, and the underlying physiological processes, to have varying influence on bud break date predictions depending on the specific weather patterns in winter and spring. Here, we evaluated the parameter sensitivity of state-of-the-art process-based phenology models that have been widely used to predict forest tree species phenology. We used sensitivity analysis to compare the behavior of models with increasing complexity under specific climatic conditions. We thus assessed whether the influence of the parameters and modeled processes on predictions varies with winter and spring temperatures. We found that the prediction of the bud break date was mainly affected by the response to forcing temperature under current climatic conditions. However, the impact of the parameters driving the response to chilling temperatures and to photoperiod on the prediction of the models increased with warmer winter and spring temperatures. Interaction effects between parameters played an important role on the prediction of models, especially for the most complex models, but did not affect the relative influence of parameters on bud break dates. Our results highlighted that a stronger focus should be given to the characterization of the reaction norms to both forcing and chilling temperature to predict accurately bud break dates in a larger range of climatic conditions and evaluate the evolutionary potential of phenological traits with climate change.

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“…The application of rigorous statistical techniques can be used to calibrate sub model of APSIM-Oryza in phenology aspect, and the original method which is put forward by Sarath et al makes it of great easy to do so. [14].…”

Section: Introductionmentioning

confidence: 99%

Simulation of Winter Wheat Phenology in Beijing Area with DSSAT-CERES Model

Feng

et al. 2016

IFIP Advances in Information and Communication Technology

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The Decision Support for Agrotechnology Transfer (DSSAT) model was a worldwide crop model, and crop accurate simulation of phenology was the premise to realize other functional simulations. The objective of this study was to attempt to calibrate the parameters of wheat phenology coefficients, including cultivar and ecotype coefficients, and develop the winter wheat phenology coefficients of Beijing area. To achieve this goal, field surveys of 7 years in wheat growing seasons in Beijing were carried out during 2005-2012.

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Calibration of the phenology sub-model of APSIM-Oryza: Going beyond goodness of fit

Cited by 31 publications

References 24 publications

A Functional Analysis of Pedotransfer Functions Developed for Sri Lankan soils: Applicability for Process-Based Crop Models

A Functional Analysis of Pedotransfer Functions Developed for Sri Lankan soils: Applicability for Process-Based Crop Models

Sensitivity analysis of tree phenology models reveals increasing sensitivity of their predictions to winter chilling temperature and photoperiod with warming climate

Simulation of Winter Wheat Phenology in Beijing Area with DSSAT-CERES Model

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