Global sensitivity analysis and uncertainty analysis for drought stress parameters in the ORYZA (v3) model

Abstract

Drought stress parameters in crop models have received little attention in the literature. In this study, a global sensitivity analysis on yield simulation was conducted for the drought stress parameters in the ORYZA (v3) model, and sensitive parameters were identified for double-season rice (Oryza sativa L.) (early rice and late rice) by using the Extended FAST method in different scenarios involving two N applications, two soil types, and four depths of plough soil layer. An adaptive metropolis algorithm (MCMC-AM) was used to quantify the uncertainties of these parameters with yield observations under various drought stress conditions. Based on the estimated parameter values, model performance of yield simulation was evaluated for drought stress conditions. Results showed that in a light drought stress situation, the upper limit factor for transpiration decline (FSWTD) was extremely sensitive at low N application, whereas the upper threshold for leaf expansion became more sensitive at high N application. In a moderate drought stress situation, the upper threshold for leaf rolling had high sensitivity under all conditions except for the late rice at low N application. In a heavy drought stress situation, FSWTD always had strong influence on yield, whereas the impacts of other parameters varied under different scenarios. Soil types and plough soil depth had considerable effects on the parameter sensitivities depending on fertilizer application and drought stress level. The empirical posterior distributions of these drought stress parameters for late rice showed very different shapes and variation ranges from that for early rice, and large uncertainties were presented. The yield simulations with a finely calibrated model were overestimated under heavy drought stress, especially for the late rice, which was grown in the dry season. The results highlighted that more attention should be paid for the drought stress parameters in crop models.

Exploration of water–nitrogen coupling effects in paddy field based on ORYZA (v3) model

“…Finally, the model was validated with the yield observations in 2014 under various drought stress conditions. Details of the model calibration and validation can be found in Tan et al ., 28 and the estimated parameter values are presented in Table 1. Note that the parameters regarding nitrogen uptake and allocation, and all other parameters not mentioned here, were set as default values.…”

Crop models and their use in assessing crop production and food security: A review

“…Accordingly, Asia, the world's first rice producer, is where this model is most applied (Table 7). It is widely used to estimate the impacts of the El Niño and Southern Oscillation (ENSO) on rice yield (Zhang et al, 2008); water balance, productivity, and nitrogen dynamics in rice production (Amiri & Rezaei, 2010); rice production under limited nitrogen and water conditions for varied rice genotypes (Sailaja et al, 2013); best sowing date to achieve rainfed rice potential yield under drought events' impacts (Li et al, 2015); high‐yielding cultivars in different nitrogen concentrations, plant densities and seedlings per hill (Yuan et al, 2017); rice growth and yield under salinity effects for various genotypes (Radanielson et al, 2018); transferability and predictability in simulating rice grain yield for direct‐seeded or transplanted rice (Ling et al, 2021); global sensitivity and uncertainty analysis for drought stress parameters (Tan et al, 2021); and, yield gap, water use efficiency (UE), pesticide UE, nitrogen UE, labour UE and energy UE, and associated global warming potential in global rice production (Yuan et al, 2021).…”