Random forests (RF) is a supervised machine learning algorithm, which has recently started
to gain prominence in water resources applications. However, existing applications are …

Reference Evapotranspiration (ET o) is a complex, dynamic and non-linear hydrological
process. Accurate estimation of ET o has long been an eminent topic of interest in the …

Accurate estimation of reference evapotranspiration (ET 0) is of great importance for the
regional water resources planning and irrigation scheduling design. The FAO-56 Penman …

Accurate estimation of reference evapotranspiration (ETo) is required in many fields, eg
irrigation scheduling design, agricultural water management, crop growth modeling and …

Precise reference evapotranspiration (ETo) estimation and prediction are the first steps to
realize efficient agricultural water resources management. As machine learning methods are …

Establishing a computational model for accurate prediction of reference crop
evapotranspiration (ET 0) is critical for regional water resources planning and irrigation …

Accurate prediction of reference evapotranspiration (ET o) is pivotal to the determination of
crop water requirement and irrigation scheduling in agriculture as well as water resources …

As the standard method to compute reference evapotranspiration (ET 0), Penman-Monteith
(PM) method requires eight meteorological input variables, which makes it difficult to apply …

Abstract Land Use and Land Cover (LULC) maps are vital prerequisites for weather
prediction models. This study proposes a framework to generate LULC maps based on the …

Soil temperature (T s) plays a key role in physical, biological and chemical processes in
terrestrial ecosystems. Accurate estimation of T s at various soil depths is crucial for land …