Advances in the understanding of physical, chemical, and biological processes influencing
water quality, coupled with improvements in the collection and analysis of hydrologic data …

Environmentally conscious manufacturing (ECM) has become an important strategy and
proactive approach for the iron and steel sector of India to produce environment friendly and …

This study investigates the capability of sequence-to-sequence machine learning (ML)
architectures in an effort to develop streamflow forecasting tools for Canadian watersheds …

The Red River of the North is vulnerable to floods, which have caused significant damage
and economic loss to inhabitants. A better capability in flood-event prediction is essential to …

In this work, we develop and test two artificial neural networks (ANNs) to forecast streamflow
in ungauged basins. The model inputs include time-lagged records of precipitation and …

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 …

Streamflow forecasting is of great importance to water resources management and flood
defense. On the other hand, a better understanding of the streamflow process is …

This paper presents the application of autoregressive integrated moving average (ARIMA),
seasonal ARIMA (SARIMA), and Jordan-Elman artificial neural networks (ANN) models in …

Drought is a climatic event that can cause significant damage both in natural environment
and in human lives. Drought forecasting is an important issue in water resource planning …

In order for a practical application of structural health monitoring to be considered
successful, not only is the detection of anomalies important but so is the tracking of various …