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Please use this identifier to cite or link to this item:
http://hdl.handle.net/11019/1080
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| Title: | Pedotransfer functions for Irish soils – estimation of bulk density (ρb) per horizon type |
| Authors: | Reidy, Brian Simo, Iolando Sills, P. Creamer, Rachel E. |
| Keywords: | Soil bulk density pedotransfer functions horizon type bulk densities Ireland |
| Issue Date: | 18-Jan-2016 |
| Publisher: | European Geosciences Union |
| Citation: | Reidy, B., Simo, I., Sills, P., and Creamer, R. E.: Pedotransfer functions for Irish soils – estimation of bulk density (ρb) per horizon type, SOIL, 2016, 2, 25-39, doi:10.5194/soil-2-25-2016 |
| Series/Report no.: | Soil;vol 2 |
| Abstract: | Soil bulk density is a key property in defining soil characteristics. It describes the packing structure of the soil and is also essential for the measurement of soil carbon stock and nutrient assessment. In many older surveys this property was neglected and in many modern surveys this property is omitted due to cost both in laboratory and labour and in cases where the core method cannot be applied. To overcome these oversights pedotransfer functions are applied using other known soil properties to estimate bulk density. Pedotransfer functions have been derived from large international data sets across many studies, with their own inherent biases, many ignoring horizonation and depth variances. Initially pedotransfer functions from the literature were used to predict different horizon type bulk densities using local known bulk density data sets. Then the best performing of the pedotransfer functions were selected to recalibrate and then were validated again using the known data. The predicted co-efficient of determination was 0.5 or greater in 12 of the 17 horizon types studied. These new equations allowed gap filling where bulk density data were missing in part or whole soil profiles. This then allowed the development of an indicative soil bulk density map for Ireland at 0–30 and 30–50 cm horizon depths. In general the horizons with the largest known data sets had the best predictions, using the recalibrated and validated pedotransfer functions. |
| Description: | peer-reviewed This work was conducted as part of the
Irish Soil Information System Project, managed by Teagasc (the Irish Agriculture and Food Development Authority) and co-funded
by the Environmental Protection Agency (EPA) of Ireland through their Science, Technology, Research and Innovation for the
Environment (STRIVE) Programme, as part of the National Development Plan 2007–2013. |
| URI: | http://hdl.handle.net/11019/1080 http://dx.doi.org/10.5194/soil-2-25-2016 |
| Appears in Collections: | Environment, Soils & Land Use
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