Journal article

Improving scheduling, benchmarking and forecasting to boost irrigation productivity

Andrew Western, Danlu Guo, Arash Parehkar, Zitian Gao, Dongryeol Ryu, Quan Wang

Copernicus GmbH

Abstract

<p>Irrigation water is an expensive and limited resource, and optimized water use is beneficial to saving water while boosting productivity. This project aims to develop integrated irrigation scheduling, benchmarking and forecasting capabilities to inform optimal irrigation practices and the suitable tools and information required for this. To achieve this, we designed a three-year project which combines simulations and field-scale monitoring. One aspect of this project is to develop a comprehensive uncertainty framework to better understand the uncertainty in scheduling, which is informed by soil water models, along with multiple sources of information such as soil, crop, weather and ..

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