Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …

Abstract Machine learning is a dynamic field with wide-ranging applications, including
drought modeling and forecasting. Drought is a complex, devastating natural disaster for …

The advancement in science and technology has led to a substantial amount of data from
various fields of agriculture to be incremented in the public domain. Hence a desideratum …

Drought is considered one of the costliest natural disasters that result in water scarcity and
crop damage almost every year. Drought monitoring and forecasting are essential for the …

This paper presents a time-spatial electric vehicle (EV) charging-power demand forecast
model at fast-charging stations located in urban areas. Most previous studies have …

Increasing demand for food and environmental stressors are some of the most challenging
problems that human societies face today and these have encouraged new studies to …

Droughts are prolonged precipitation-deficient periods, resulting in inadequate water
availability and adverse repercussions to crops, animals and humans. Drought forecasting is …

Land use land cover (LULC) change is the crucial driving force that affects the hydrological
processes of a watershed. The changes of LULC have an important influence and are the …

Drought, a climate-related disaster impacting a variety of sectors, poses challenges for
millions of people in South Asia. Accurate and complete drought information with a proper …

Quality and reliable drought prediction is essential for mitigation strategies and planning in
disaster-stricken regions globally. Prediction models such as empirical or data-driven …