Lake water-level fluctuation is a complex and dynamic process, characterized by high
stochasticity and nonlinearity, and difficult to model and forecast. In recent years …

The present study proposes a new hybrid evolutionary Adaptive Neuro-Fuzzy Inference
Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a …

Due to global climate change and growing population, fresh water resources are becoming
more vulnerable to pollution. Protecting fresh water resources, especially lakes and the …

Globally, the water‐level fluctuations in lakes are a dynamic and complex process. The
fluctuation is characterized by higher non‐linearity and stochasticity, making it quite hard to …

The predictive ability of a hybrid model integrating the Firefly Algorithm (FFA), as a heuristic
optimization tool with the Multilayer Perceptron (MLP-FFA) algorithm for the prediction of …

Forecasting freshwater lake levels is vital information for water resource management,
including water supply management, shoreline management, hydropower generation …

Accurate forecasting of lake water level (WL) fluctuations is essential for effective
development and management of water resource systems. This study applies the Random …

Rainfall links atmospheric and surficial processes and is one of the most important
hydrologic variables. We apply support vector regression (SVR), which has a high …

Flooding in urban streams can occur suddenly and cause major environmental and
infrastructure destruction. Due to the high amounts of impervious surfaces in urban …

An explicit model management framework is introduced for predictive Groundwater Levels
(GWL), particularly suitable to Observation Wells (OWs) with sparse and possibly …