Commercial success of big data has led to speculation that big-data-like reasoning could
partly replace theory-based approaches in science. Big data typically has been applied to …

It is important to develop the integrated flood and landslide modeling system driven by radar
and satellite to predict these hazards to mitigate their damages. In this study, we investigated …

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 …

A large number of historical simulations and future climate projections are available from
Global Climate Models, but these are typically of coarse resolution, which limits their …

Local-scale climate change adaptation is receiving more attention to reduce the adverse
effects of climate change. The process of develo** adaptation measures at local-scale …

Abstract The Loess Plateau in China is one of the most erosive regions in the world,
especially under warming climate conditions, which are aggravating evapotranspiration and …

In order to overcome limitations of climate projections from Global Climate Models (GCMs),
such as coarse spatial resolution and biases, in this study, the Statistical Down-Scaling …

Abstract Statistical Downscaling Model (SDSM) is a powerful model for climate change
assessment. However, its usage remains very gray with limited studies on climate change …

Identifying general circulation models (GCMs) that represent the climate of a specific area is
crucial for climate change studies. However, the uncertainties in GCMs caused by …

For many regions of the world, current climate change projections are only available at
coarser spatial resolution from Global Climate Models (GCMs) that cannot directly be used …