Optimisation of Agricultural Management for Soil Carbon Sequestration Using Deep Reinforcement Learning and Large-Scale Simulations
About the project
Soil carbon sequestration in croplands has tremendous potential to help mitigate climate change; however, it is challenging to develop the optimal management practices for maximisation of the sequestered carbon as well as the crop yield. This project aims to develop an intelligent agricultural management system using deep reinforcement learning (RL) and large-scale soil and crop simulations. To achieve this, we propose to build a simulator to model and simulate the complex soil-water-plant-atmosphere interactions, which will run on high-performance computing platforms.
Massive simulations using such platforms allow the evaluation of the effects of various management practices under different weather and soil conditions in a timely and cost-effective manner. By formulating the management decision as an RL problem, we can leverage the state-of-the-art algorithms to train management policies, which are expected to maximise the stored organic carbon while maximising the crop yield. The whole system will be tested using data of soil and crops in both mid-west of the United States and the Mediterranean region. The proposed research has great potential for impact on climate change and food security, two of the most significant challenges currently facing humanity.
This project is a collaboration between the University of Illinois at Urbana-Champaign, KTH Department of Sustainable Development and Stockholm University, Department of Physical Geography.
Associate Professor in Environmental and Engineering Geosciences at KTH, Co-PI of research Project Optimization of Agricultural Management for Soil Carbon Sequestration Using Deep Reinforcement Learning and Large-Scale Simulations at C3.ai DTI, Digital Futures Faculty+46 8 790 86 93
Professor of Hydrology and Water Resources, Department of Physical Geography at Stockholm University, Researcher in project Optimization of Agricultural Management for Soil Carbon Sequestration Using Deep Reinforcement Learning and Large-Scale Simulations at Digital Futures, Digital Futures Faculty+46 8-16 47 85
Postdoctoral Researcher at Stockholm University, Researcher in project Optimization of Agricultural Management for Soil Carbon Sequestration Using Deep Reinforcement Learning and Large-Scale Simulations at Digital Futurescarla.firstname.lastname@example.org
W. Grafton and Lillian B. Wilkins Professor, University of Illinois at Urbana-Champaignnhovakim@illinois.edu
Assistant Professor, Crop Sciences University of Illinois at Urbana-Champaignnfmartin@illinois.edu