Monitoring and predicting radionuclide uptake and dynamics for optimizing remediation of radioactive Contaminated Agricultural Land (D1.50.19)


Innovative monitoring and prediction techniques present a unique solution to enhancing readiness and capabilities of societies for optimizing the remediation of agricultural areas affected by large-scale nuclear accidents. In this CRP, new field, laboratory and machine-learning modelling tools will be developed, tested and validated for predicting and monitoring the fate of radionuclide uptake by crops and related dynamics at the landscape level, with the emphasis on those under-explored environments and related main crop categories. Laboratory, greenhouse and field-based research using stable caesium and strontium isotopes in combination with integrated time and space dependent modelling and machine learning will be used to predict radiocaesium and radiostrontium crop uptake and movement in the case of a large-scale nuclear accident affecting food and agriculture. Operation research will be applied to guide the use of remediation techniques at landscape level (i.e. selection, optimization and prioritization). Protocols will be developed and adapted for innovative spatio-temporal decision support systems for remediation of agricultural land, based on machine learning and operations research integrated with Geographic Information System (GIS) techniques.


The overall objective is to enhance readiness and capabilities of societies for optimizing remediation of agricultural areas affected by large-scale nuclear accidents through innovative monitoring, decision-making and prediction techniques.

The specific objectives are (1) to combine experimental studies with field monitoring and modelling to understand and predict the role of environmental conditions on radiocaesium and radiostrontium transfer in the food chains and their dynamics at landscape level in particular for under-explored agro-ecological environments such as arid, tropical and monsoonal climates and (2) to customise the remedial options in agriculture to these under-explored agro-ecological environments and to adapt and develop innovative decision support systems for optimizing remediation of agricultural lands affected by nuclear accidents, based on machine learning and operations research techniques.


Eleven countries participate in this CRP: seven research contract holders from Belarus, Chile, Morocco, P. R. China (two institutions), Russia, Ukraine; two technical contract holders from France and Macedonia; and six agreement holders from Belgium (two institutions), Japan (three institutions) and India.


The CRP D1.50.19 was developed as a follow up to CRP D1.50.15. It was formulated based on recommendations from a consultants’ meeting held at the IAEA, Vienna, 20-22 February 2019. Expert consultants from Belgium, Japan, Ukraine and Russia noted that the importance of optimisation of remediation based on monitoring and prediction of the fate of radiocaesium and radiostrontium in agriculture is essential for returning the affected territories to normal environmental conditions. The First Research Coordination Meeting (RCM) –was held on 21-24 October 2019. During this meeting the objectives and experimental plans of the national research projects were discussed and adjusted to be in line with the objectives and work plan of the CRP. Common guidelines for implementing the national project activities and collaboration networks were established.

Since the beginning of CRP a series of laboratory-experiments has been carried on improving remediation of radioactive contamination in farmland. The CRP team has designed the roadmap to develop new isotope techniques to better understand the dynamics of radiocaesium in the soil. Significant progress has been achieved in the application of advanced mathematical approaches for improving the prediction of soil properties based on Mid-Infrared Spectroscopy and enhancing the decision-making for the optimization of remediation of radioactively contaminated agricultural soils. Further, decision-support tools are being developed to improve strategies for remediation of radioactive contamination in agriculture.

The second RCM of this CRP is planned to be held on 4-8 October 2021 in Japan.

Project Officer:

G. Dercon and L. Heng