Rainfall and runoff are considered the main components in the hydrological cycle.
Developing an accurate model to capture the dynamic connection between rainfall and …

Water quality prediction is an effective method for managing and protecting water resources
by providing an early warning against water quality deterioration. In general, the existing …

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear,
non-stationary and multi-scale characteristics. To solve this difficulty and improve the …

Since fresh water is limited while agricultural and human water demands are continuously
increasing, optimal prediction and management of streamflows as a source of fresh water is …

Observed streamflow and climate data are used to test the hypothesis that climate change is
already affecting Rio Grande streamflow volume derived from snowmelt runoff in ways …

This study applied the time series analysis approach to model and predict univariate
dissolved oxygen and temperature time series for four water quality assessment stations at …

Data driven models such as Artificial Neural Networks (ANNs) became a very popular tool in
hydrology for a long time, especially in rainfall⿿ runoff modelling. However, it does not have …

Considering the popularity of using data-driven non-linear methods for forecasting
streamflow, there has been no exploration of how well such models perform in climate …

Streamflow prediction has a great significance in hydrology, water resources planning and
management studies. Either long term or short term predictions of streamflow are necessary …

This paper investigates the contribution of Moderate Resolution Imaging Spectroradiometer
(MODIS) satellite Snow Cover Area (SCA) product and in-situ snow depth measurements to …