The need for accurate predictions of water quality in rivers has encouraged researchers to
develop new methods and to improve the predictive ability of conventional models. In recent …

Since the middle of the twentieth century, artificial intelligence (AI) models have been used
widely in engineering and science problems. Water resource variable modeling and …

Operational flood control systems depend on reliable and accurate forecasts with a suitable
lead time to take necessary actions against flooding. This study proposed a Long Short …

Long lead-time streamflow forecasting is of great significance for water resources planning
and management in both the short and long terms. Despite of some studies using machine …

In the present study, three different artificial intelligence based non-linear models, ie feed
forward neural network (FFNN), adaptive neuro fuzzy inference system (ANFIS), support …

For accurate estimation of streamflow of a mountainous river basin, a novel hybrid method is
developed in this study, where gradient-based optimization (GBO) algorithm is employed to …

The applicability of four machine learning (ML) methods, ANFIS-PSO, ANFIS-FCM, MARS
and M5Tree, together with multi model simple averaging (MM-SA) ensemble method, is …

Flood occurs as a result of high intensity and long-term rainfalls accompanied by snowmelt
which flow out of the main river channel onto the flood prone areas and damage the …

Rapid and accurate urban flood forecasting with high temporal resolution is critical to
address future flood risks under urbanization and climate change. Machine learning models …

Hydrologic models require atmospheric, dynamic and static models to simulate river flow
from catchments. Thus the accuracy of hydrologic modelling highly depends on the data …