Recent breakthroughs in artificial intelligence (AI), and particularly in deep learning (DL),
have created tremendous excitement and opportunities in the earth and environmental …

Understanding hydrological processes is achieved using modeling approaches due to the
extensive and complex interactions between various environmental elements. Hydrological …

Twelve actual evaporation datasets are evaluated for their ability to improve the
performance of the fully distributed mesoscale Hydrologic Model (mHM). The datasets …

A hydrologic model, calibrated using only streamflow data, can produce acceptable
streamflow simulation at the watershed outlet yet unrealistic representations of water …

Water resource development opens up opportunities for improving smallholder farmer
livelihoods in sub-Saharan Africa; however, implementation of water resource interventions …

Predicting surface runoff from catchment to large region is a fundamental and challenging
task in hydrology. This paper presents a comprehensive review for various studies …

Hydrological models are usually calibrated against observed streamflow (Qobs), which is
not applicable for ungauged river basins. A few studies have exploited remotely sensed …

Hydrological prediction is essential for managing and preserving headwater, wetland, and
rural basins, yet it is difficult due to a lack of data. The Long Short-Term Memory (LSTM) …

Irrigation water is one of the most substantial water uses worldwide. Thus, global simulation
studies about water availability and demand typically include irrigation. Nowadays, regional …

Soil moisture and discharge are interrelated variables which play a major role on water
availability, environmental conservation and ecohydrological functioning of a watershed. In …