The compilation of a database of soil carbon and land use is described, from which models of soil carbon dioxide emissions across the United Kingdom (UK) can be run. The database gives soil organic carbon, sand, silt and clay contents and bulk densities weighted to reference layers from 0 to 30 cm and from 30 to 100 cm depths. The data are interpolated from information on soil types and land use on a 1 km grid across the UK and are used to estimate soil carbon stocks. For 1990, the baseline year for the Kyoto Protocol on carbon emissions, the estimate is 4562 Tg soil organic carbon in the top 1 m of soil across the UK, with an average density of 18 kg m 22 . The data can be reported by layer (e.g. 54% in topsoils) and country (e.g. 48% in Scotland) as well as by soil and land type.
The management of water resources in compliance with regulatory requirements increasingly uses national environmental impact assessments incorporating models of soil solute transport. Most such models use either continuous functions designed to solve the Richards equation, or capacity-type functions based on water contents between specified soil water pressure heads. The work described here has used three separate sets of measured water-release data representative of the whole of the UK to develop a set of pedotransfer functions (PTFs) for predicting volumetric water contents at seven pressure heads on the water release curve ranging from 0 to −1500 kPa. A theoretically-based structural stratification of the data was proposed and tested. Within each grouping, multiple regression analysis was used to derive equations for predicting the water contents at each pressure head, based on a selected set of predictors. The resulting PTFs gave a significantly better prediction than PTFs derived from the unstratified data and also than the widely used HYPRES PTFs. For all non-sandy horizons not subject to regular cultivation, additional PTFs incorporating a climatic variable, the average annual potential soil moisture deficit (PSMD) gave a further improvement in prediction in drier areas of the UK with PSMD greater than 130 mm. Mean errors associated with using the PTFs to parameterize continuous function models and a capacity model for calculating water availability for cereals (AP cereals ) are ±16.4 and 16.9%, respectively.
Accurate prediction of overland flow requires an understanding of the hydrological processes controlling its occurrence over a range of spatial and temporal scales. This study investigated the factors controlling the initiation of overland flow from grassland on a drumlin. From January 2003 to December 2006, fine scale monitoring of soil moisture, rainfall and overland flow were carried out at a grazed grassland site in Northern Ireland. Logistic regression analyses were used to identify the factors controlling the initiation of overland flow. Relationships between the observed volumetric soil moisture (VSM) and soil moisture deficit (SMD) values predicted from regional meteorological data were also compared. Results demonstrated that although saturation excess overland flow occurs at this site, 59% of overland flow events occurred on days when soil moisture was below field capacity. The logistic regression analysis confirmed that when soils were below field capacity, average rainfall intensity was the most important variable in determining the probability of overland flow occurring followed by the SMD. Although VSM values at this site were correlated with two sets of modelled values of SMD, one based on the meteorological office rainfall and evaporation calculation system model of the UK Meteorological Office and the other based on a study from Ireland, neither model provided accurate indicators of the risk of overland flow. Each significantly overestimated the number of days when soils were at or above field capacity. This uncertainty and the predicted increase in high-intensity rainfall events as a result of climate change pose challenges to the use of SMD as an indicator of the risk of overland flow.
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