Meteorological drought signals trigger different types of droughts by propagating in the water
and energy cycle processes. The understanding of the propagation process from …

Efficient methods are necessary for interpolation of precipitation data in geospatial systems.
In recent years, there has been an incremental need to complete rainfall data networks …

A regional inundation early warning system is crucial to alleviating flood risks and reducing
loss of life and property. This study aims to provide real-time multi-step-ahead forecasting of …

A better understanding of precipitation dynamics in the Indian subcontinent is required since
India's society depends heavily on reliable monsoon forecasts. We introduce a non-linear …

Intrinsic predictability is imperative to quantify inherent information contained in a time series
and assists in evaluating the performance of different forecasting methods to get the best …

Precipitation patterns and extremes are significantly influenced by various climatic factors
and large-scale atmospheric circulation patterns. This study uses wavelet coherence …

An accurate and timely forecast of extreme events can mitigate negative impacts and
enhance preparedness. Real-time forecasting of extreme flood events with longer lead times …

In this study, we propose a soft-computing methodology to visibly explore the spatio-
temporal groundwater variations of the Kuo** River basin in southern Taiwan. The self …

Abstract The Variable Infiltration Capacity (VIC) model is a widely used distributed
hydrological model. However, VIC is computationally expensive in hydrologic prediction or …

With the acceleration of global warming, the frequent occurrence of extreme climate events
has inflicted great socio-economies losses and casualties; therefore, it is particularly …