Task 1. Field observed scientific evidence from national and international research
A rigorous assessment of the available field-observed evidence is a pre-requisite for credible research. Within Catchment Change Databases (CCDs) this evidence will be 'weighted' based on its quality and local environmental relevance and will be used directly in the modelling and also provide a resource (at a latter stage) that can be used by NFM practitioners and other researchers across the UK.
e.g., a section of the CCD on wet-canopy evaporation from broadleaf trees
Specific tasks:
The new Catchment Change Databases will include change data (and associated environmental and uncertainty attributes) for hydrological parameters: (1) Proportion of rainfall reaching the ground-surface and proportion of rainfall lost to wet-canopy evaporation for a range of tree species versus grasslands for varied UK seasonal conditions, and (2) Contrasting soil permeability values (surface/topsoil and subsoil) beneath grasslands, peatlands and woodlands under differing management regime. The change data for hydrological parameters (including likelihood weights) we use to parameterise the NFM scenarios in the modelling (Task 4).
For each change in hydrological parameter (or variable), an MS Excel spreadsheet was populated with quantitative information extracted from all primary references (papers detailing specific experimental studies) that may be relevant in the UK context. Each change value or range in values will have associated with it attributes pertinent to our use of that data within the modelling. This will not only include environmental data (e.g., FAO-Unesco soil type; annual rainfall total; rainfall total for the period of the measurements etc.), but also details of the collection method, dataset size and statistics undertaken. The former information allow us to extract change data pertinent to particular areas of our study catchments (e.g. areas of gley soils) or time periods (e.g., rates for winter storms). The latter allowed us to assign multiple likelihood weights (from 0 to 1) to our change data based on our team's estimate of the (1) robustness of the method used in the study (adding comments in the spreadsheet to pertinent work); (2) size of the dataset; (3) robustness of the statistics; and (4) pertinence of the study to the test basins in UK. These likelihood weights are included in the spreadsheet in a transparent way.
Page et al., (2020) was our first paper utilising one of our CCDs
