RDE 278 - Collating data to help assess the water quality implications of land
key details
| Status | complete |
|---|---|
| Category (CPV) | 73200000 |
| Deadline | 11 Sept 2023 |
| Contract start | 12 Sept 2023 |
| Contract end | 15 Mar 2024 |
| Procedure | selective |
| SME suitable | No |
| OCID | ocds-b5fd17-3ac48005-f065-4f7e-9861-f1a4ff419b64 |
Award
| Supplier | Value | Date | Status |
|---|---|---|---|
| UK Centre for Ecology & Hydrology (UKCEH) | £49,760 | 11 Sept 2023 | active |
description
: Land use change could have multiple positive effects on water quality, both by removing sources of agricultural pollution and from the net benefits of new habitat, wetland or woodland creation. Although we have a reasonable understanding of the nutrient pollution from conventional agricultural systems (via models like FARMSCOPER), our understanding of the impacts of uptake of different types of agricultural production or of removing land from production to create new habitats and woodland is less well established.
In order to meet our proposed targets on reducing pollution from agriculture (reducing the loads of N, P and sediment entering the water environment by 40% by 2038), we need both optimisation of current agricultural systems (through compliance with regulations, uptake of on-farm land management measures and technological improvements and innovation) and some targeted land use change.
In order to better understand the co-benefits and trade-offs (e.g. balancing pollution to water with carbon sequestration and impacts on air quality) associated with different land use change scenarios, we need to be able to quantify the net change in pollutant loadings and other environmental pressures associated with the conversion of land to new uses. This work will address those gaps by bringing together data from a range of models and studies to help assess the impact of landscape scale LUC.
This project was awarded by DEFRA.
notice history
1 notice published against this procurement.
| Published | Type | Regime | Notice |
|---|---|---|---|
| 11 Dec 2023 | Award (award) | · | 0f76f442-1925-4411-8510-c5039c48b648-706086 |
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source
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