Flash flooding is one of the most hazardous natural events, and it is frequently responsible
for loss of life and severe damage to infrastructure and the environment. Research into the …

Accurate flood mapping is crucial for enhancing community resilience in the face of flooding.
Among the several factors that affect the flood extent, the effect of fluvial dynamics is not …

In this study, a method based on coupling discrete wavelet transforms (WA) and artificial
neural networks (ANN) for flow forecasting applications in non-perennial rivers in semi-arid …

Air quality time series consists of complex linear and non-linear patterns and are difficult to
forecast. Box–Jenkins Time Series (ARIMA) and multilinear regression (MLR) models have …

Artificial neural networks (ANNs) becomes very popular tool in hydrology, especially in
rainfall–runoff modelling. However, a number of issues should be addressed to apply this …

For the past several years, Cyprus has been facing an unprecedented water crisis. Four
options that have been considered to help resolve the problem of drought in Cyprus include …

In this study, a new method of stand-alone short-term spring snowmelt river flood forecasting
was developed based on wavelet and cross-wavelet analysis. Wavelet and cross-wavelet …

Although neural networks have been widely applied to various hydrological problems,
including river flow forecasting, for at least 15years, they have usually been trained by …

In this study, short‐term river flood forecasting models based on wavelet and cross‐wavelet
constituent components were developed and evaluated for forecasting daily stream flows …

This study aims to investigate the performance of Precipitation Estimation from Remotely
Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN …