Improved weighted ensemble learning for predicting the daily reference evapotranspiration under the semi-arid climate conditions.

Evapotranspiration is an important quantity required in many applications, such as hydrology and agricultural and irrigation planning. Reference evapotranspiration is particularly important, and the prediction of its variations is beneficial for analyzing the needs and management of water resources. In this paper, we explore the predictive ability of hybrid ensemble learning to predict daily reference evapotranspiration (RET) under the semi-arid climate by using meteorological datasets at 12 locations in the Andalusia province in southern Spain.

Dynamics of pruning waste and spent horse litter co-composting as determined by chemical parameters.

Co-composting of pruning waste and horse manure was monitored by different parameters. A windrow composting pile, having the dimensions 2.5m (height) x 30m (length) was established.