Details of Award
NERC Reference : NE/R011125/1
Fire and water: predicting and mitigating water pollution risk from wildfire ash
Grant Award
- Principal Investigator:
- Professor S Doerr, Swansea University, College of Science
- Co-Investigator:
- Dr C Santin, Swansea University, College of Science
- Grant held at:
- Swansea University, College of Science
- Science Area:
- Atmospheric
- Freshwater
- Terrestrial
- Overall Classification:
- Panel B
- ENRIs:
- Biodiversity
- Environmental Risks and Hazards
- Global Change
- Natural Resource Management
- Pollution and Waste
- Science Topics:
- Pollution/pollution control
- Earth & environmental
- Water quality
- Hydrological Processes
- Forest fires
- Ecosystem Scale Processes
- Catchment management
- Drinking water
- Human health
- Nutrient enrichment
- Water Quality
- Abstract:
- Every year vegetation fires (wildfires and management burns) affect ~4% of the global vegetated land surface. This includes forests, grasslands or peatlands, which provide 60% of the water supply for the world's largest 100 cities and for 70% of for the UK's population. In England 114 km2 of uplands are affected by management burns alone and the UK Fire and Rescue Services attend to over 70,000 vegetation fires per year. Vegetation fires can have serious impacts on water quality, which, combined with the current and projected future further decline in fresh water availability and increase in fire risk in many regions around the world, has given rise to increased attention to water contamination risks from fire. The primary threat is ash left behind by fire, which can be transported very easily into water bodies by water erosion. Ash is typically rich in contaminants and its transfer into water supply catchments has led to numerous drinking-water restrictions and substantial treatments costs in recent years (e.g. for Belfast, Canberra, Denver, Fort McMurray, Sydney). In the UK, losses to the water industry from vegetation fires are estimated at #16 Mill. per year. Models are widely used by scientists and land managers to predict soil erosion or flood risks after disturbance events such as harvesting or wildfire, however, no models currently exist that allow predicting of ash transport and associated water contamination risk following fire. This gap in knowledge and resource seriously compromises the ability of land managers to anticipate water contamination risks from fire and to implement effective mitigation treatments to reduce fire risk, prevent erosion after fire and, adjust water treatment capabilities. This timely project brings together an interdisciplinary team of international experts from the UK, USA and Australia with the aim to address this critical knowledge and tools gap. Building on recent advances and proof-of-concept work in this field, we are now able to (i) obtain critical fundamental knowledge on wildfire ash transport processes and its contamination potential and, using this knowledge, to (b) develop the first end-user probabilistic model that allows predicting ash delivery and associated water contamination risk to the hydrological network. The model will be validated for key fire-prone and fire-managed land cover types that have suffered critical ash-induced water pollution events in the past (including UK uplands, US conifer forest and Australian eucalyptus forest) using the first field dataset on ash transport parameters by water erosion and an extensive dataset on potential contamination by ash obtained through this project for these key regions. To maximize the impact of the project, the web-based model will developed in collaboration with, and be made available to, users from land and catchment management sectors to support effective protection of aquatic ecosystems and drinking water supply from contamination by ash.
- NERC Reference:
- NE/R011125/1
- Grant Stage:
- Completed
- Scheme:
- Standard Grant FEC
- Grant Status:
- Closed
- Programme:
- Standard Grant
This grant award has a total value of £550,396
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DA - Investigators | DA - Estate Costs | DI - Staff | DI - T&S | DA - Other Directly Allocated |
|---|---|---|---|---|---|---|
| £38,009 | £159,345 | £63,182 | £50,305 | £185,743 | £42,196 | £11,616 |
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