Moistube Irrigation characterisation and yield response of canola (Brassica napus) under varied Moistube Irrigation.

Doctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Abstract available in PDF

Simulating second crop maize growth under different irrigation regimes in lower seyhan plain using cropsyst model

CSISS Foundation Inc.;USDa NIFA8th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2019 --16 July 2019 through 19 July 2019 -- --This study aims to evaluate CropSyst model for second crop maize in a Mediterranean Environment under different irrigation regimes including, 40% and 60% of water consumption within one-meter deep soil profile. We examined how soil influences maize yields through a process-based crop modelling called CropSyst, and climate variables observed in the Lower Seyhan Plain, Turkey. CropSyst is a process-based simulation model consist of four stages: i) database creation; ii) model calibration; iii) validation; and iv)model results to simulate the growth and development of potential maize crop. Calibration and validation procedures were implemented using climate, soil, management practices, and rotation data previously measured in the field. Daily climate data derived from 22 meteorological stations (including TARBIL Climate station), additionally, soil series, soil classification including soil profiles, profile depth, pH values, organic matter, salinity, texture, soil volume and total porosity have been transferred into GIS environment for modelling. In the world, a significant portion of the freshwater resources (72%) is used in agricultural irrigation. The rapid increase in world population and the need for more water use across sectors increase the importance of more efficient use of irrigation water. Thus, optimum strategies for management and planning of existing water resources in agriculture become a national and global strategic issue. © 2019 IEEE.National Council for Scientific Research 115Y063This work was supported by the [Scientific and Technological Research Council (TUBITAK) under Grant number (115Y063)