"Enhancement of standardized precipitation evapotranspiration index predictions by machine learning based on regression and soft computing for Iran’s arid and hyper–arid region"
Introduction
Drought is a climate risk that affects access to safe water, crop development, ecological stability, and food production. Therefore, developing drought prediction methods can lead to better management of surface and groundwater resources. Similarly, machine learning can be used to find improved relationships between nonlinear variables in complex systems.
About Ronny Berndtsson
Ronny Berndtsson is co-coordinator of the Lund University Strategic Research Area “Middle East in the Contemporary World (MECW)”, Swedish coordinator of Horizon 2020 project FASTER (Farmers’ adaptation sustainability in Tunisia through excellence in research), and project leader of various other international research projects.
His major fields of research are Hydroclimatological processes by dynamical systems, Rainfall space-time variability and modeling, Soil water and solute transport in heterogeneous soils, Urban drainage and related pollutant transport, and Hydropolitics and Hydrosolidarity in the Middle East.