A review on interpretable and explainable artificial intelligence in hydroclimatic applications

H Başağaoğlu, D Chakraborty, CD Lago, L Gutierrez… - Water, 2022 - mdpi.com
This review focuses on the use of Interpretable Artificial Intelligence (IAI) and eXplainable
Artificial Intelligence (XAI) models for data imputations and numerical or categorical …

[PDF][PDF] A novel selection method of CMIP6 GCMs for robust climate projection

MM Hamed, MS Nashwan, S Shahid - Int. J. Climatol, 2022 - researchgate.net
The selection of Global climate models (GCMs) is a major challenge for reliable projection of
climate. A novel method is introduced in this study to select couple model intercomparison …

Future precipitation changes in Egypt under the 1.5 and 2.0 C global warming goals using CMIP6 multimodel ensemble

MS Nashwan, S Shahid - Atmospheric Research, 2022 - Elsevier
Abstract Rainfall projections for 1.5 and 2.0° C warming can explain regional precipitation
response to emission reductions under the Paris Agreements' goals. Assessment of such …

[PDF][PDF] Inter-comparison of historical simulation and future projections of rainfall and temperature by CMIP5 and CMIP6 GCMs over Egypt

MM Hamed, MS Nashwan, S Shahid - Int. J. Climatol, 2022 - researchgate.net
Abstract The Global Climate Models (GCMs) performances of the recently released Coupled
Model Intercomparison Project phase 6 (CMIP6) compared to its predecessor, CMIP5, are …

Multi-criteria performance evaluation of gridded precipitation and temperature products in data-sparse regions

IM Lawal, D Bertram, CJ White, AH Jagaba, I Hassan… - Atmosphere, 2021 - mdpi.com
Inadequate climate data stations often make hydrological modelling a rather challenging
task in data-sparse regions. Gridded climate data can be used as an alternative; however …

Application of Boruta algorithms as a robust methodology for performance evaluation of CMIP6 general circulation models for hydro-climatic studies

IM Lawal, D Bertram, CJ White, SRM Kutty… - Theoretical and Applied …, 2023 - Springer
Regional climate models are essential for climate change projections and hydrologic
modelling studies, especially in watersheds that are overly sensitive to changes in climate …

Evaluation of empirical reference evapotranspiration models using compromise programming: A case study of Peninsular Malaysia

MKI Muhammad, MS Nashwan, S Shahid, T Ismail… - Sustainability, 2019 - mdpi.com
Selection of appropriate empirical reference evapotranspiration (ETo) estimation models is
very important for the management of agriculture, water resources, and environment …

Spatial mapping of the provenance of storm dust: Application of data mining and ensemble modelling

H Gholami, A Mohamadifar, AL Collins - Atmospheric Research, 2020 - Elsevier
Spatial modelling of storm dust provenance is essential to mitigate its on-site and off-site
effects in the arid and semi-arid environments of the world. Therefore, the main aim of this …

[PDF][PDF] A novel framework for selecting general circulation models based on the spatial patterns of climate

MS Nashwan, S Shahid - International Journal of Climatology, 2020 - researchgate.net
General circulation models (GCMs), used for climate change projections, should be able to
simulate both the temporal variability and spatial patterns of the observed climate. However …

Machine-learning algorithms for predicting land susceptibility to dust emissions: The case of the Jazmurian Basin, Iran

H Gholami, A Mohamadifar, A Sorooshian… - Atmospheric pollution …, 2020 - Elsevier
In this study, we apply six machine-learning algorithms (XGBoost, Cubist, BMARS, ANFIS,
Cforest and Elasticnet) to investigate the susceptibility of the Jazmurian Basin in …