Condensation irrigation greenhouse dataset.

Highly valuable data related to two types of planting media and two planting conditions, with and without plastic cover, were obtained from condensation irrigation experiments in the greenhouse. Data on the physical model include the humidifier dimensions and the cultivation bed, the pipe diameter and length, the water tank, and its adjustment devices. The measured data consisted of different water balance components in the studied condensation irrigation system, including saline water evaporated in the humidifier, water produced in the planting medium and pipes, water flowing out of the planting medium, transpiration by the plant, and the water storage changes in the planting medium.

Sensitivity-driven simulation development: a case study in forced migration.

This paper presents an approach named sensitivity-driven simulation development (SDSD), where the use of sensitivity analysis (SA) guides the focus of further simulation development and refinement efforts, avoiding direct calibration to validation data. SA identifies assumptions that are particularly pivotal to the validation result, and in response model ruleset refinement resolves those assumptions in greater detail, balancing the sensitivity more evenly across the different assumptions and parameters. We implement and demonstrate our approach to refine agent-based models of forcibly displaced people in neighbouring countries.

VECMAtk: a scalable verification, validation and uncertainty quantification toolkit for scientific simulations.

We present the VECMA toolkit (VECMAtk), a flexible software environment for single and multiscale simulations that introduces directly applicable and reusable procedures for verification, validation (V&V), sensitivity analysis (SA) and uncertainty quantication (UQ). It enables users to verify key aspects of their applications, systematically compare and validate the simulation outputs against observational or benchmark data, and run simulations conveniently on any platform from the desktop to current multi-petascale computers. In this sequel to our paper on VECMAtk which we presented last year [1] we focus on a range of functional and performance improvements that we have introduced, cover newly introduced components, and applications examples from seven different domains such as conflict modelling and environmental sciences.

Uncertainty quantification of dynamic earthquake rupture simulations.

We present a tutorial demonstration using a surrogate-model based uncertainty quantification (UQ) approach to study dynamic earthquake rupture on a rough fault surface. The UQ approach performs model calibration where we choose simulation points, fit and validate an approximate surrogate model or emulator, and then examine the input space to see which inputs can be ruled out from the data. Our approach relies on the mogp_emulator package to perform model calibration, and the FabSim3 component from the VECMA toolkit to streamline the workflow, enabling users to manage the workflow using the command line to curate reproducible simulations on local and remote resources.

The impact of uncertainty on predictions of the CovidSim epidemiological code.

Epidemiological modelling has assisted in identifying interventions that reduce the impact of COVID-19. The UK government relied, in part, on the CovidSim model to guide its policy to contain the rapid spread of the COVID-19 pandemic during March and April 2020; however, CovidSim contains several sources of uncertainty that affect the quality of its predictions: parametric uncertainty, model structure uncertainty and scenario uncertainty. Here we report on parametric sensitivity analysis and uncertainty quantification of the code.