There has been a strong tendency in recent decades to develop real-time urban flood
prediction models for early warning to the public due to a large number of worldwide urban …

Surrogate models replace computationally expensive simulations of physically‐based
models to obtain accurate results at a fraction of the time. These surrogate models, also …

Sensitivity analysis is now considered a standard practice in environmental modeling.
Several open-source libraries, such as the Sensitivity Analysis Library (SALib), have been …

Recent breakthroughs in artificial intelligence (AI), and particularly in deep learning (DL),
have created tremendous excitement and opportunities in the earth and environmental …

In many fields, such as environmental risk assessment, agronomic system behavior,
aerospace engineering, and nuclear safety, mathematical models turned into computer code …

Sensitivity analysis is defined as 'the study of how the uncertainty in the output of a model
(numerical or otherwise) can be apportioned to different sources of uncertainty in the model …

Urban flooding is a major problem for cities around the world, with significant socio-
economic consequences. Conventional real-time flood forecasting models rely on …

Urban energy poverty remains a critical challenge affecting millions worldwide, with
significant implications for socio-economic development and sustainability. This study …

Sensitivity analysis (SA) as a 'formal'and 'standard'component of scientific development and
policy support is relatively young. Many researchers and practitioners from a wide range of …

Crop models are essential tools for analysing the effects of climate variability, change on
crop growth and development and the potential impact of adaptation strategies. Despite their …