Description
Crop-growth models are powerful tools for supporting optimal planning and management of agricultural water use globally. Here, we present AquaCrop-OSPy, an open source, Python implementation of the crop-water productivity model AquaCrop. The model provides a user friendly, flexible and computationally efficient solution to support agricultural water management, which can be readily integrated with other Python modules or code bases and run instantly via a web browser using Google Colab. This Talk demonstrates a number of model applications such as optimizing rule based irrigation strategies, or learning irrigation management strategies from scratch using deep reinforcement learning.