In this study, the monthly rainfall time series forecasting was investigated based on the
effectiveness of the Seasonal Auto Regressive Integrated Moving Average with EXogenous …

Artificial intelligence (AI) and machine learning (ML) are novel techniques to detect hidden
patterns in environmental data. Despite their capabilities, these novel technologies have not …

Streamflow forecasting plays a key role in improvement of water resource allocation,
management and planning, flood warning and forecasting, and mitigation of flood damages …

Agriculture, meteorological, and hydrological drought is a natural hazard which affects
ecosystems in the central India of Maharashtra state. Due to limited historical data for …

The present study is designed to analyse the annual rainfall variability and trend in 30
meteorological stations of the Asir region for the period of 1970–2017 using the Mann …

Water received in rainfall is a crucial natural resource for agriculture, the hydrological cycle,
and municipal purposes. The changing rainfall pattern is an essential aspect of assessing …

Nature-inspired optimization is an active area of research in the artificial intelligence (AI)
field and has recently been adopted in hydrology for the calibration (training) of both process …

Many real-world applications show growing demand for the prediction of long sequence
time-series, such as electricity consumption planning. Long sequence time-series …

Climate extremes have a significant impact on vegetation. However, little is known about
vegetation response to climatic extremes in Bangladesh. The association of Normalized …

The cities of arid and semi-arid regions have distinctive landscape patterns and large-scale
variations in soil moisture and vegetation cover which causes significant variations in land …