Project description
Paving the way for sustainable agricultural practices
As the global population grows, agricultural activities intensify, leading to increased fertiliser use and diffuse nutrient emissions. This escalating trend poses a significant threat to water bodies, as nutrient run-off from intensive farming practices degrades water quality. Traditional land and water management approaches often lack the precision needed to identify high-priority areas or offer spatially explicit solutions. In this context, the ERC-funded WaterSmartLand project will pinpoint high-risk areas and propose targeted solutions. Using advanced analysis, modelling and machine learning, the project identifies optimal land management strategies, such as using wetlands and riparian buffer strips, to mitigate nutrient run-off. By harnessing a discrete global grid system data cube and cutting-edge machine learning techniques, the project offers spatially explicit solutions.
Objective
With the growing human population, the diffuse nutrient emissions from agriculture are expected to increase with the rise of fertilizer use. This situation has created a need for sustainable intensification by increasing yields while simultaneously decreasing the environmental impacts. Nature-based solutions (NbS) such as wetlands and riparian buffer strips can efficiently reduce the nutrient runoff from agricultural catchments. However, most land and water management studies mostly do not identify specific priority areas where the nutrient runoff to the water bodies is the highest (hotspots) nor do they provide spatially explicit solutions to improve the environmental conditions. Identification of priority areas will be important for ensuring cost-effective interventions to reduce the impact of intensive agriculture.
The aim of the proposed project is to develop an analysis, modelling, and machine learning (ML) framework for finding spatially optimal land management scenarios for implementing NbS such as wetlands and riparian buffer strips to reduce agricultural nutrient runoff from catchments at different scales. Moreover, the project will identify the landscape predictor variables at different spatial scales for nutrient concentrations and their cross-scale interactions using ML.
We will implement a novel Discrete Global Grid System data cube to manage all environmental data needed for modelling. We will take advantage of the strength and flexibility of existing ML methods to deal with complex ecosystem responses, and to reveal new interactions among water quality predictor variables. ML together with geospatial analysis will help us to develop different spatially explicit NbS allocation scenarios which we will evaluate with process-based hydrological modelling. In addition, we will address the challenges of processing large datasets by using proven parallelisation and distributed computing toolkits.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2023-COG
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51005 Tartu
Estonia
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