{"id":{"repo_id":"soton","oai_identifier":"oai:eprints.soton.ac.uk:69768"},"canonical_url":"https://search.dev.ndltd.org/etd/soton/oai:eprints.soton.ac.uk:69768","repository":{"repo_id":"soton","name":"University of Southampton","base_url":"https://eprints.soton.ac.uk/cgi/oai2"},"display":{"title":"Changes in hydrological extremes and climate variability in the Severn Uplands","abstract":"Hydrological extremes within the UK have increased in intensity, frequency and<br/>persistence over recent years and are predicted to increase in variability throughout the 21st<br/>century. Past and future changes in hydrological extremes relative to climate change were<br/>investigated within Severn Uplands, a climate sensitive catchment. Using the Mann-<br/>Kendall trend detection test, time-series analysis over a 30-year period revealed a<br/>significant increase in winter and autumn precipitation and a decrease in summer<br/>precipitation. The analysis of flow time-series indicated an increase in winter and July<br/>flows and a decrease in spring flows. Changes in climate variability over the same period<br/>showed increases in air temperature and SST, and a reduction in snow cover. Climate<br/>variables were found to largely correlate with hydrological extremes which were<br/>characteristic of certain weather types and largely influenced by the NAO.<br/><br/>To model future flows within the Severn Uplands a hydrological model (HEC-HMS) was<br/>used to simulate hydrological processes. The extreme hydrological event of November-<br/>December 2006 was used to calibrate the model. The difference between using radar and<br/>gauge precipitation data to drive the model was quantified. Radar data resulted in the<br/>smallest prediction accuracy followed by gauge-corrected radar data (corrected using the<br/>mean-field bias where gauge rainfall was interpolated using cokriging) and then gauge<br/>precipitation which had the largest prediction accuracy. Model accuracy was sufficient<br/>using the gauge corrected radar and gauge precipitation data as inputs, so both were altered<br/>for future predictions to investigate the propagation of uncertainty. Predicted changes in<br/>temperature and precipitation by the UKCIP02 scenarios were used to alter the baseline<br/>extreme event to predict changes in peak flow and outflow volume. Both radar- and gaugedriven<br/>hydrological modelling predicted large flow increases for the 21st century with<br/>increases up to 8% by the 2020s, 18% by the 2050s and 30% by the 2080s. Discrepancies<br/>between predictions were observed when using the different data inputs.","abstract_html":"Hydrological extremes within the UK have increased in intensity, frequency and&lt;br/&gt;persistence over recent years and are predicted to increase in variability throughout the 21st&lt;br/&gt;century. Past and future changes in hydrological extremes relative to climate change were&lt;br/&gt;investigated within Severn Uplands, a climate sensitive catchment. Using the Mann-&lt;br/&gt;Kendall trend detection test, time-series analysis over a 30-year period revealed a&lt;br/&gt;significant increase in winter and autumn precipitation and a decrease in summer&lt;br/&gt;precipitation. The analysis of flow time-series indicated an increase in winter and July&lt;br/&gt;flows and a decrease in spring flows. Changes in climate variability over the same period&lt;br/&gt;showed increases in air temperature and SST, and a reduction in snow cover. Climate&lt;br/&gt;variables were found to largely correlate with hydrological extremes which were&lt;br/&gt;characteristic of certain weather types and largely influenced by the NAO.&lt;br/&gt;&lt;br/&gt;To model future flows within the Severn Uplands a hydrological model (HEC-HMS) was&lt;br/&gt;used to simulate hydrological processes. The extreme hydrological event of November-&lt;br/&gt;December 2006 was used to calibrate the model. The difference between using radar and&lt;br/&gt;gauge precipitation data to drive the model was quantified. Radar data resulted in the&lt;br/&gt;smallest prediction accuracy followed by gauge-corrected radar data (corrected using the&lt;br/&gt;mean-field bias where gauge rainfall was interpolated using cokriging) and then gauge&lt;br/&gt;precipitation which had the largest prediction accuracy. Model accuracy was sufficient&lt;br/&gt;using the gauge corrected radar and gauge precipitation data as inputs, so both were altered&lt;br/&gt;for future predictions to investigate the propagation of uncertainty. Predicted changes in&lt;br/&gt;temperature and precipitation by the UKCIP02 scenarios were used to alter the baseline&lt;br/&gt;extreme event to predict changes in peak flow and outflow volume. Both radar- and gaugedriven&lt;br/&gt;hydrological modelling predicted large flow increases for the 21st century with&lt;br/&gt;increases up to 8% by the 2020s, 18% by the 2050s and 30% by the 2080s. Discrepancies&lt;br/&gt;between predictions were observed when using the different data inputs.","abstract_has_math":false,"creators":["Biggs, Eloise M."],"institution":"University of Southampton","degree_name":"Ph.D.","degree_level":"doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Atkinson, Peter M"],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009-09","date_published":"2009-09","updated_at":"2026-07-24T04:36:06Z","subjects":[],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Atkinson, Peter M"]},{"key":"dc:creator","label":"Author","values":["Biggs, Eloise M."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2009-09"]},{"key":"dc:date.issued","label":"Date","values":["2009-09"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Geography (pre 2011 reorg)","School of Geography"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Southampton"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://eprints.soton.ac.uk/69768/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Ph.D."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://eprints.soton.ac.uk/69768/1/EloiseBiggs_PhDThesis.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Hydrological extremes within the UK have increased in intensity, frequency and<br/>persistence over recent years and are predicted to increase in variability throughout the 21st<br/>century. Past and future changes in hydrological extremes relative to climate change were<br/>investigated within Severn Uplands, a climate sensitive catchment. Using the Mann-<br/>Kendall trend detection test, time-series analysis over a 30-year period revealed a<br/>significant increase in winter and autumn precipitation and a decrease in summer<br/>precipitation. The analysis of flow time-series indicated an increase in winter and July<br/>flows and a decrease in spring flows. Changes in climate variability over the same period<br/>showed increases in air temperature and SST, and a reduction in snow cover. Climate<br/>variables were found to largely correlate with hydrological extremes which were<br/>characteristic of certain weather types and largely influenced by the NAO.<br/><br/>To model future flows within the Severn Uplands a hydrological model (HEC-HMS) was<br/>used to simulate hydrological processes. The extreme hydrological event of November-<br/>December 2006 was used to calibrate the model. The difference between using radar and<br/>gauge precipitation data to drive the model was quantified. Radar data resulted in the<br/>smallest prediction accuracy followed by gauge-corrected radar data (corrected using the<br/>mean-field bias where gauge rainfall was interpolated using cokriging) and then gauge<br/>precipitation which had the largest prediction accuracy. Model accuracy was sufficient<br/>using the gauge corrected radar and gauge precipitation data as inputs, so both were altered<br/>for future predictions to investigate the propagation of uncertainty. Predicted changes in<br/>temperature and precipitation by the UKCIP02 scenarios were used to alter the baseline<br/>extreme event to predict changes in peak flow and outflow volume. Both radar- and gaugedriven<br/>hydrological modelling predicted large flow increases for the 21st century with<br/>increases up to 8% by the 2020s, 18% by the 2050s and 30% by the 2080s. Discrepancies<br/>between predictions were observed when using the different data inputs."]},{"key":"dc:format","label":"Dc Format","values":["text"]},{"key":"dc:title","label":"Title","values":["Changes in hydrological extremes and climate variability in the Severn Uplands"]}]}],"canonical_facts":{"dc:contributor.advisor":["Atkinson, Peter M"],"dc:creator":["Biggs, Eloise M."],"dc:date":["2009-09"],"dc:date.issued":["2009-09"],"dc:description.abstract":["Hydrological extremes within the UK have increased in intensity, frequency and<br/>persistence over recent years and are predicted to increase in variability throughout the 21st<br/>century. Past and future changes in hydrological extremes relative to climate change were<br/>investigated within Severn Uplands, a climate sensitive catchment. Using the Mann-<br/>Kendall trend detection test, time-series analysis over a 30-year period revealed a<br/>significant increase in winter and autumn precipitation and a decrease in summer<br/>precipitation. The analysis of flow time-series indicated an increase in winter and July<br/>flows and a decrease in spring flows. Changes in climate variability over the same period<br/>showed increases in air temperature and SST, and a reduction in snow cover. Climate<br/>variables were found to largely correlate with hydrological extremes which were<br/>characteristic of certain weather types and largely influenced by the NAO.<br/><br/>To model future flows within the Severn Uplands a hydrological model (HEC-HMS) was<br/>used to simulate hydrological processes. The extreme hydrological event of November-<br/>December 2006 was used to calibrate the model. The difference between using radar and<br/>gauge precipitation data to drive the model was quantified. Radar data resulted in the<br/>smallest prediction accuracy followed by gauge-corrected radar data (corrected using the<br/>mean-field bias where gauge rainfall was interpolated using cokriging) and then gauge<br/>precipitation which had the largest prediction accuracy. Model accuracy was sufficient<br/>using the gauge corrected radar and gauge precipitation data as inputs, so both were altered<br/>for future predictions to investigate the propagation of uncertainty. Predicted changes in<br/>temperature and precipitation by the UKCIP02 scenarios were used to alter the baseline<br/>extreme event to predict changes in peak flow and outflow volume. Both radar- and gaugedriven<br/>hydrological modelling predicted large flow increases for the 21st century with<br/>increases up to 8% by the 2020s, 18% by the 2050s and 30% by the 2080s. Discrepancies<br/>between predictions were observed when using the different data inputs."],"dc:format":["text"],"dc:identifier.uri":["https://eprints.soton.ac.uk/69768/1/EloiseBiggs_PhDThesis.pdf"],"dc:publisher.department":["Geography (pre 2011 reorg)","School of Geography"],"dc:publisher.institution":["University of Southampton"],"dc:relation.isreferencedby":["https://eprints.soton.ac.uk/69768/"],"dc:title":["Changes in hydrological extremes and climate variability in the Severn Uplands"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["Ph.D."]},"updated_at":"2026-07-24T04:36:06Z"}