[HTML][HTML] State of the art in modelling of phosphorus in aquatic systems: review, criticisms and commentary

BJ Robson - Environmental Modelling & Software, 2014 - Elsevier
This systematic review considers how water quality and aquatic ecology models represent
the phosphorus cycle. Although the focus is on phosphorus, many of the observations and …

[HTML][HTML] An evaluation of adaptive surrogate modeling based optimization with two benchmark problems

C Wang, Q Duan, W Gong, A Ye, Z Di, C Miao - Environmental Modelling & …, 2014 - Elsevier
Surrogate modeling uses cheap “surrogates” to represent the response surface of simulation
models. It involves several steps, including initial sampling, regression and adaptive …

Advancements in machine learning for spatiotemporal urban on-road traffic-air quality study: a review

Z Du, H Li, S Chen, X Zhang, L Zhang, Y Liu - Atmospheric Environment, 2025 - Elsevier
Urban traffic that is heterogeneous significantly impacts on urban air quality in both temporal
and spatial scale, while traditional dispersion models struggle to assess it at high temporal …

Emulation of leaf, canopy and atmosphere radiative transfer models for fast global sensitivity analysis

J Verrelst, N Sabater, JP Rivera, J Muñoz-Marí… - Remote Sensing, 2016 - mdpi.com
Physically-based radiative transfer models (RTMs) help understand the interactions of
radiation with vegetation and atmosphere. However, advanced RTMs can be …

An integrated assessment tool to define effective air quality policies at regional scale

C Carnevale, G Finzi, E Pisoni, M Volta… - … Modelling & Software, 2012 - Elsevier
In this paper, the Integrated Assessment of air quality is dealt with at regional scale. First the
paper describes the main challenges to tackle current air pollution control, including …

Emulation techniques for the reduction and sensitivity analysis of complex environmental models

M Ratto, A Castelletti, A Pagano - Environmental Modelling & Software, 2012 - Elsevier
Emulation (also denoted as metamodelling in the literature) is an important and expanding
area of research and represents one of the major advances in the study of complex …

Surrogate-based multi-objective optimization of management options for agricultural landscapes using artificial neural networks

TH Nguyen, D Nong, K Paustian - Ecological Modelling, 2019 - Elsevier
We demonstrate the use of a surrogate-based optimization framework for large-scale and
high-resolution landscape management optimization, using irrigated corn production …

Using task farming to optimise a street-scale resolution air quality model of the west midlands (UK)

J Zhong, C Hood, K Johnson, J Stocker, J Handley… - Atmosphere, 2021 - mdpi.com
High resolution air quality models combining emissions, chemical processes, dispersion
and dynamical treatments are necessary to develop effective policies for clean air in urban …

Comparison of machine learning algorithms for emulation of a gridded hydrological model given spatially explicit inputs

T Lim, K Wang - Computers & Geosciences, 2022 - Elsevier
This study compares the performance of several machine learning algorithms in reproducing
the spatial and temporal outputs of the process-based, hydrological model, ParFlow. CLM …

Including stakeholder input in formulating and solving real-world optimisation problems: Generic framework and case study

W Wu, HR Maier, GC Dandy, R Leonard… - … modelling & software, 2016 - Elsevier
Multi-objective evolutionary algorithms (MOEAs) are becoming increasingly popular for
solving formal environmental and water resources optimisation problems. In the past, the …