Global sensitivity analysis of the APSIM-Oryza rice growth model under different environmental conditions

Global Sensitivity Analysis of the Advanced ORYZA-N Model with Different Rice Types and Irrigation Regimes

Identifying important parameters in crop models is critical for model application. This study conducted a sensitivity analysis of 23 selected parameters of the advanced rice model ORYZA-N using the Extended FAST method. The sensitivity analysis was applied for three rice types (single-season rice in cold regions and double-season rice (early rice and late rice) in subtropical regions) and two irrigation regimes (traditional flood irrigation (TFI) and shallow-wet irrigation (SWI)). This study analyzed the parameter sensitivity of six crop growth outputs at four developmental stages and yields. Furthermore, we compared the variation in parameter sensitivity on model outputs between TFI and SWI scenarios for single-season rice, early rice, and late rice. Results indicated that parameters RGRLMX, FRPAR, and FLV0.5 significantly affected all model outputs and varied over developmental stages. Water stress in paddy fields caused by water-saving irrigation had more pronounced effects on single-season rice than on double-season rice.

Sensitivity analysis of cultivar parameters to simulate wheat crop growth and yield under moisture and temperature stress conditions

Sensitivity of cultivar input parameters were characterised on the outputs of yield and growth variables using a web based crop simulation model Web InfoCrop Wheat. The crop model was assessed for each combination of seventeen input cultivar parameters tested under moisture and temperatures stress conditions in four different ecological regions. Three model outputs, total dry matter at harvest, grain yield at harvest and duration of the crop were chosen for subsequent evaluation. The most dominant cultivar parameters were identified to be TPOPT (Optimum Temp), TTVG (Thermal time for germination to 50% Flowering), KDFMAX (Extinction coefficient of leaves at flowering), GNOCF (Slope of storage organ number/m² to dry matter during storage organ formation), POTGWT (Potential storage organ weight) and PHOTOSENS (Photoperiod sensitivity) which were associated with growth, thermal time accumulation, leaf area index, grain number and photosensitivity. Comparison of crop simulations with all the cultivar parameters incorporated from the experimental observations and those with only the most sensitive cultivar parameters incorporated was performed. Outputs of the crop simulation were significantly correlated with results from the field experiments. The present study could save time and effort in generating all the cultivar parameters required to perform the crop simulation under moisture and temperature stress conditions. The most significant cultivar parameters (TPOPT, TTVG, KDFMAX, GNOCF, POTGWT and PHOTOSENS) identified through the sensitivity analysis conducted in this study could significantly simulate the crop growth and yield of wheat.

Critical period and pathways of water borne nitrogen loss from a rice paddy in northeast China

Rice paddy nitrogen (N) loss is a great concern leading to a high risk of receiving water pollution. Various models have been applied as practical tools for simulation of the nutrient loss amount, and pathways or yield change affected by management factors in previous studies. However, N loss features of rice paddies in northern regions have received less attention and few model simulation studies have combined crop yield and N loss to simultaneously meet the needs of yield maintenance and environmental protection. To consider benefits to local farmers and to assess the paddy N loss features and factors in northeast China, rice yields and water borne N losses in 2013-2017 were simulated using the APSIM-Oryza model applied to Xingkai Lake Farm. Different from subtropical regions, high field ridges and lower rainfall limit local paddy overflow occurrence except after unexpected storms after irrigation in dry years or serial rainfall events, which result in subsurface N loss during stages of tillering (Ti) to flowering (Fl) which comprise the dominant pathway accounting for 50.03-69.99% of the total water borne N loss. The correlation analysis results also indicate irrigation and the applied N amount more significantly affect local paddy N loss than does precipitation. In each year, stimulated by an increase in the applied N amount, increasing rice yield (symbolizing crop growth status) indicated N loss implicitly rose. But under similar applied N amount range, inter-annual N loss results showed weaker growth status result in a higher N loss. Based on local N loss features, nutrient conservation practices including planting density increase or side strip application, and net N loss reduction practices including intermittent or recycling irrigation are recommended to limit nutrient loss from a paddy field which would be helpful for optimization of local nutrient conservation and surrounding water environment protection.

Geographical variations in gross primary production and evapotranspiration of paddy rice in the Korean Peninsula

The quantification of canopy photosynthesis and evapotranspiration of crops (ET_c) is essential to appreciate the effects of environmental changes on CO₂ flux and water availability in agricultural ecosystems and crop productivity. This study simulated the canopy photosynthesis and ET processes of paddy rice (Oryza sativa) based on the development of physiological modules (i.e., gross primary production [GPP] and ET_c) and their incorporation into the GRAMI-rice model that uses remote sensing data. We also projected spatiotemporal variations in the GPP, ET, yield, and biomass of paddy rice at maturity using the updated GRAMI-rice model combined with geostationary satellite images to identify the relationships of canopy photosynthesis and ET_c with crop productivity. GPP and ET data for paddy rice were obtained from three KoFlux sites in South Korea in 2015 and 2016. Vegetation indices were acquired from the Geostationary Ocean Color Imager (GOCI) of the Communication Ocean and Meteorological Satellite (COMS) from 2012 to 2017 and integrated into GRAMI-rice. GPP and ET_c estimates using GRAMI-rice were in close agreement with flux tower estimates with Nash-Sutcliffe efficiency ranges of 0.40-0.79 for GPP and 0.49-0.62 for ET_c. Also, GRAMI-rice was reasonably well incorporated with the COMS GOCI imagery and reproduced spatiotemporal variations in the GPP and ET of rice in the Korean peninsula. The current study results demonstrate that the updated GRAMI-rice model with the canopy photosynthesis and ET_c modules is capable of reproducing spatiotemporal variations in CO₂ assimilation and ET of paddy rice at various geographical scales and for regions of interest that are observable by satellite sensors (e.g., inaccessible North Korea).