Amor Ines

Adjunct Research Scientist
Agricultural Modeling, Remote Sensing and Agriculture

  • Email: ude.aibmuloc.irinull@seni


Amor Ines is an agro-hydrologist working on integrations of advanced modeling techniques, remote sensing (RS) and seasonal climate forecasts for decision support in agriculture and water management. He holds a BS in agricultural engineering, magna cum laude, and an MS and PhD in water engineering and management with a focus on irrigation engineering and management, and integrated water resources management.

Research Interests

Linking climate information in agriculture and water management; remote sensing in agriculture and water management; climate-based crop forecasting methods; statistical downscaling of climate (seasonal; climate change time scale); data assimilation applied to soil-water-atmosphere-plant models from field to regional scale; development and applications of evolutionary-biological algorithms (genetic algorithms, etc.) to agriculture and water management; agro-hydrological modeling/vadose zone hydrology (variably saturated flows); high-performance computing for RS-agro-hydrological modeling; stochastic/deterministic water resources systems analyses (optimization and operational management).

Some Useful Tools

Tomorrow’s Rice: A web-based crop simulation system for rice.

How to use video demo. A collaboration with Chubu U., AIT and ListenField Co.

Multiple Regression Tool for Crop Predictability Analysis (Fortran)

GCM Bias Correction Tool for Cropping System Modeling (Fortran)

Quasi-analytic Tool for Modeling Solute Transport in the Soil Profile (Fortran)

VACC – A vulnerability assessment tool for agro-forestry crops under climate change (Fortran)

H20_Balance_Polygon_V01a – A polygon-based regional crop water balance model (Fortran)

predictWTD – A tool for predicting crop yields at different lead-times in the growing season (Fortran)