Comparative study of GCMs, RCMs, downscaling and hydrological models: a review toward future climate change impact estimation
N Chokkavarapu, VR Mandla - SN Applied Sciences, 2019 - Springer
Water resources are naturally influenced by weather, topography, geology and environment.
These factors cause difficulties in evaluating future water resources under changing climate …
These factors cause difficulties in evaluating future water resources under changing climate …
Evaluation of CMIP6 precipitation simulations across different climatic zones: Uncertainty and model intercomparison
This study analyzes the performance of precipitation estimates from historical runs of the
CMIP6 (Climate Model Intercomparison Project Phase 6) over the climatic regions of Iran. In …
CMIP6 (Climate Model Intercomparison Project Phase 6) over the climatic regions of Iran. In …
Downscaling approaches of climate change projections for watershed modeling: Review of theoretical and practical considerations
Water resources managers must increasingly consider climate change implications of,
whether the concern is floods, droughts, reservoir management, or reliably supplying …
whether the concern is floods, droughts, reservoir management, or reliably supplying …
Accounting for the multiple natures of missing values in label-free quantitative proteomics data sets to compare imputation strategies
Missing values are a genuine issue in label-free quantitative proteomics. Recent works have
surveyed the different statistical methods to conduct imputation and have compared them on …
surveyed the different statistical methods to conduct imputation and have compared them on …
Bias correction capabilities of quantile mapping methods for rainfall and temperature variables
M Enayati, O Bozorg-Haddad… - Journal of Water and …, 2021 - iwaponline.com
This study aims to conduct a thorough investigation to compare the abilities of quantile
mapping (QM) techniques as a bias correction method for the raw outputs from general …
mapping (QM) techniques as a bias correction method for the raw outputs from general …
Uncertainty analysis of climate change impacts on flood frequency by using hybrid machine learning methods
In the present study, for the first time, a new framework is used by combining metaheuristic
algorithms, decomposition and machine learning for flood frequency analysis under climate …
algorithms, decomposition and machine learning for flood frequency analysis under climate …
[HTML][HTML] Comparative analysis of CMIP5 and CMIP6 in conjunction with the hydrological processes of reservoir catchment, Chhattisgarh, India
Study region Mahanadi reservoir project complex (MRP), Chhattisgarh, India Study focus
This study assesses and compares the performance of the Coupled Model Intercomparison …
This study assesses and compares the performance of the Coupled Model Intercomparison …
Modeling slump of ready mix concrete using genetic algorithms assisted training of Artificial Neural Networks
The paper explores the usefulness of hybridizing two distinct nature inspired computational
intelligence techniques viz., Artificial Neural Networks (ANN) and Genetic Algorithms (GA) …
intelligence techniques viz., Artificial Neural Networks (ANN) and Genetic Algorithms (GA) …
Low impact development practices mitigate urban flooding and non-point pollution under climate change
Climate change-induced extreme rainfall events exacerbate the failure in stormwater
hydraulic and water quality management. As a promising alternative for stormwater …
hydraulic and water quality management. As a promising alternative for stormwater …
Estimating uncertainty and its temporal variation related to global climate models in quantifying climate change impacts on hydrology
Uncertainty estimation of climate change impacts on hydrology has received much attention
in the research community. The choice of a global climate model (GCM) is usually …
in the research community. The choice of a global climate model (GCM) is usually …