Measuring water surface width at the national scale for England and Wales using remote sensing and statistical modelling
The vertical transport of CO2 from rivers to the atmosphere has only recently been identified as a significant component of global greenhouse gas (GHG) budgets. Headwater streams are responsible for a disproportionately large quantity of total CO2 evasion, yet are difficult to map comprehensively du...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
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2019
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| Online Access: | https://eprints.nottingham.ac.uk/56509/ |
| _version_ | 1848799339759009792 |
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| author | Clark, Liam D. |
| author_facet | Clark, Liam D. |
| author_sort | Clark, Liam D. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The vertical transport of CO2 from rivers to the atmosphere has only recently been identified as a significant component of global greenhouse gas (GHG) budgets. Headwater streams are responsible for a disproportionately large quantity of total CO2 evasion, yet are difficult to map comprehensively due to their width being smaller than the spatial resolution of most remotely sensed imagery that is currently used for this application. The need to capture these streams is further underlined by recent research that has identified water surface area as a key control of CO2 evasion rate. The challenge of extracting a complete representation of surface waters from remotely sensed imagery means that this critical component of CO2 models is currently poorly understood. This thesis addressed this by applying the novel combination of fuzzy classification, one-class classification, and contouring to derive super-resolution maps of surface waters from high resolution colour infrared aerial imagery. The methodology produced maps of sufficient accuracy to capture a significant proportion of headwater streams, which were measured using a semi-automated GIS-driven technique. Water surface width (WSW) was then estimated at the national scale using a predictive model that utilised widely available or readily calculable landscape variables in conjunction with image-based measurements of WSW. The multiple linear regression model accounted for a high proportion of the variation in WSW (adjusted R2 = 0.75, p < 0.05), allowing the lack of a national-scale dataset of WSW for England and Wales to be addressed. The main explanatory variables included catchment area, hydrological source of flow, rainfall, relief, and for the first time in a predictive model of WSW, a metric quantifying the extent to which the river has been modified. WSW predictions were then applied to CO2 evasion modelling to predict the quantity of CO2 transferred from rivers to the atmosphere in England and Wales, based on previous research that identified the surface area covered by rivers to be a key control of vertical transport. Findings improved on previous attempts at modelling CO2 evasion for England and Wales, and suggest that transfers are currently underestimated, with consequent ramifications for mitigation strategies in the future. |
| first_indexed | 2025-11-14T20:34:06Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-56509 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:34:06Z |
| publishDate | 2019 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-565092025-02-28T14:29:07Z https://eprints.nottingham.ac.uk/56509/ Measuring water surface width at the national scale for England and Wales using remote sensing and statistical modelling Clark, Liam D. The vertical transport of CO2 from rivers to the atmosphere has only recently been identified as a significant component of global greenhouse gas (GHG) budgets. Headwater streams are responsible for a disproportionately large quantity of total CO2 evasion, yet are difficult to map comprehensively due to their width being smaller than the spatial resolution of most remotely sensed imagery that is currently used for this application. The need to capture these streams is further underlined by recent research that has identified water surface area as a key control of CO2 evasion rate. The challenge of extracting a complete representation of surface waters from remotely sensed imagery means that this critical component of CO2 models is currently poorly understood. This thesis addressed this by applying the novel combination of fuzzy classification, one-class classification, and contouring to derive super-resolution maps of surface waters from high resolution colour infrared aerial imagery. The methodology produced maps of sufficient accuracy to capture a significant proportion of headwater streams, which were measured using a semi-automated GIS-driven technique. Water surface width (WSW) was then estimated at the national scale using a predictive model that utilised widely available or readily calculable landscape variables in conjunction with image-based measurements of WSW. The multiple linear regression model accounted for a high proportion of the variation in WSW (adjusted R2 = 0.75, p < 0.05), allowing the lack of a national-scale dataset of WSW for England and Wales to be addressed. The main explanatory variables included catchment area, hydrological source of flow, rainfall, relief, and for the first time in a predictive model of WSW, a metric quantifying the extent to which the river has been modified. WSW predictions were then applied to CO2 evasion modelling to predict the quantity of CO2 transferred from rivers to the atmosphere in England and Wales, based on previous research that identified the surface area covered by rivers to be a key control of vertical transport. Findings improved on previous attempts at modelling CO2 evasion for England and Wales, and suggest that transfers are currently underestimated, with consequent ramifications for mitigation strategies in the future. 2019-07-18 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/56509/1/LClark_Thesis_corrections_final.pdf Clark, Liam D. (2019) Measuring water surface width at the national scale for England and Wales using remote sensing and statistical modelling. PhD thesis, University of Nottingham. Carbon dioxide; River surveys; Data sets; Remote sensing |
| spellingShingle | Carbon dioxide; River surveys; Data sets; Remote sensing Clark, Liam D. Measuring water surface width at the national scale for England and Wales using remote sensing and statistical modelling |
| title | Measuring water surface width at the national scale for England and Wales using remote sensing and statistical modelling |
| title_full | Measuring water surface width at the national scale for England and Wales using remote sensing and statistical modelling |
| title_fullStr | Measuring water surface width at the national scale for England and Wales using remote sensing and statistical modelling |
| title_full_unstemmed | Measuring water surface width at the national scale for England and Wales using remote sensing and statistical modelling |
| title_short | Measuring water surface width at the national scale for England and Wales using remote sensing and statistical modelling |
| title_sort | measuring water surface width at the national scale for england and wales using remote sensing and statistical modelling |
| topic | Carbon dioxide; River surveys; Data sets; Remote sensing |
| url | https://eprints.nottingham.ac.uk/56509/ |