Evaluation of heavy metal phytotoxicity to Helianthus annuus L. using seedling vigor index-soil model

A mathematical model to estimate seedling vigor index (SVI) of sunflower (Helianthus annuus L.) seeds in soils contaminated with heavy metals was developed. This model was used to quantitatively describe the complex effects of heavy metal concentrations in soils (C_s) on seed germination and seedling growth. Negative linear regressions between relative seed germination percentage (GP), root length (L_r), and shoot length (L_s) versus log C_s varied as a function of soil properties and type and concentration of heavy metals. With an increase in the heavy metal concentration in soils, the predicted SVI values decreased and reasonably described the experimental SVI values within an 80% prediction band. This demonstrates that SVI values can be predicted, a priori, using SVI-soil models. Based on the sensitivity analysis, root elongation was more significantly affected by the external environment than shoot elongation. Consequently, the SVI-soil model developed in this study can explain heavy metal phytotoxicity to sunflower in complex soil systems. Further research using a diverse range of hyperaccumulator plants and soils is required to render SVI-soil model more available for complex systems in predictions of heavy metal phytotoxicity and hyperaccumulating behaviors of hyperaccumulator plants in various soil systems.

Uncertainty quantification based cloud parameterization sensitivity analysis in the NCAR community atmosphere model

Using uncertainty quantification techniques, we carry out a sensitivity analysis of a large number (17) of parameters used in the NCAR CAM5 cloud parameterization schemes. The LLNL PSUADE software is used to identify the most sensitive parameters by performing sensitivity analysis. Using Morris One-At-a-Time (MOAT) method, we find that the simulations of global annual mean total precipitation, convective, large-scale precipitation, cloud fractions (total, low, mid, and high), shortwave cloud forcing, longwave cloud forcing, sensible heat flux, and latent heat flux are very sensitive to the threshold-relative-humidity-for-stratiform-low-clouds ([Formula: see text] and the auto-conversion-size-threshold-for-ice-to-snow [Formula: see text] The seasonal and regime specific dependence of some parameters in the simulation of precipitation is also found for the global monsoons and storm track regions. Through sensitivity analysis, we find that the Somali jet strength and the tropical easterly jet associated with the south Asian summer monsoon (SASM) show a systematic dependence on [Formula: see text] and [Formula: see text]. The timing of the withdrawal of SASM over India shows a monotonic increase (delayed withdrawal) with an increase in [Formula: see text]. Overall, we find that [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] are the most sensitive cloud parameters and thus are of high priority in the model tuning process, in order to reduce uncertainty in the simulation of past, present, and future climate.

Sobol Global Sensitivity Analysis of a Coupled Surface/Subsurface Water Flow and Reactive Solute Transfer Model on a Real Hillslope

The migration and fate of pesticides in natural environments is highly complex. At the hillslope scale, the quantification of contaminant fluxes and concentrations requires a physically based model. This class of model has recently been extended to include coupling between the surface and the subsurface domains for both the water flow and solute transport regimes. Due to their novelty, the relative importance of and interactions between the main model parameters has not yet been fully investigated. In this study, a global Sobol sensitivity analysis is performed on a vineyard hillslope for a one hour intensive rain event with the CATHY (CATchment HYdrology) integrated surface/subsurface model. The event-based simulation involves runoff generation, infiltration, surface and subsurface solute transfers, and shallow groundwater flow. The results highlight the importance of the saturated hydraulic conductivity K s and the retention curve shape parameter n and they reveal a strong role for parameter interactions associated with the exchange processes represented in the model. The mass conservation errors generated by the model are lower than 1% in 99.7% of the simulations. Boostrapping analysis of sampling methods and errors associated with the Sobol indices highlights the relevance of choosing a large sampling size (at least N = 1000) and raises issues associated with rare but extreme output results.