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Gill, Laurence
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Gill, Laurence
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Gill, Laurence
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Now showing 1 - 3 of 3
- PublicationSources of nitrogen and phosphorus emissions to Irish rivers and coastal waters: Estimates from a nutrient load apportionment framework(Elsevier, 2017-12-01)
; ; ; ; ; More than half of surface water bodies in Europe are at less than good ecological status according to Water Framework Directive assessments, and diffuse pollution from agriculture remains a major, but not the only, cause of this poor performance. Agri-environmental policy and land management practices have, in many areas, reduced nutrient emissions to water. However, additional measures may be required in Ireland to further decouple the relationship between agricultural productivity and emissions to water, which is of vital importance given on-going agricultural intensification. The Source Load Apportionment Model (SLAM) framework characterises sources of phosphorus (P) and nitrogen (N) emissions to water at a range of scales from sub-catchment to national. The SLAM synthesises land use and physical characteristics to predict emissions from point (wastewater, industry discharges and septic tank systems) and diffuse sources (agriculture, forestry, etc.). The predicted annual nutrient emissions were assessed against monitoring data for 16 major river catchments covering 50% of the area of Ireland. At national scale, results indicate that total average annual emissions to surface water in Ireland are over 2700 t yr- 1 of P and 82,000 t yr- 1 of N. The proportional contributions from individual sources show that the main sources of P are from municipal wastewater treatment plants and agriculture, with wide variations across the country related to local anthropogenic pressures and the hydrogeological setting. Agriculture is the main source of N emissions to water across all regions of Ireland. These policy-relevant results synthesised large amounts of information in order to identify the dominant sources of nutrients at regional and local scales, contributing to the national nutrient risk assessment of Irish water bodies571Scopus© Citations 92 - PublicationSpatially distributed potential evapotranspiration modeling and climate projections(Elsevier, 2018-08-15)
; ; ; ; Evapotranspiration integrates energy and mass transfer between the Earth's surface and atmosphere and is the most active mechanism linking the atmosphere, hydrosphsophere, lithosphere and biosphere. This study focuses on the fine resolution modeling and projection of spatially distributed potential evapotranspiration on the large catchment scale as response to climate change. Six potential evapotranspiration designed algorithms, systematically selected based on a structured criteria and data availability, have been applied and then validated to long-term mean monthly data for the Shannon River catchment with a 50 m2 cell size. The best validated algorithm was therefore applied to evaluate the possible effect of future climate change on potential evapotranspiration rates. Spatially distributed potential evapotranspiration projections have been modeled based on climate change projections from multi-GCM ensembles for three future time intervals (2020, 2050 and 2080) using a range of different Representative Concentration Pathways producing four scenarios for each time interval. Finally, seasonal results have been compared to baseline results to evaluate the impact of climate change on the potential evapotranspiration and therefor on the catchment dynamical water balance. The results present evidence that the modeled climate change scenarios would have a significant impact on the future potential evapotranspiration rates. All the simulated scenarios predicted an increase in potential evapotranspiration for each modeled future time interval, which would significantly affect the dynamical catchment water balance. This study addresses the gap in the literature of using GIS-based algorithms to model fine-scale spatially distributed potential evapotranspiration on the large catchment systems based on climatological observations and simulations in different climatological zones. Providing fine-scale potential evapotranspiration data is very crucial to assess the dynamical catchment water balance to setup management scenarios for the water abstractions. This study illustrates a transferable systematic method to design GIS-based algorithms to simulate spatially distributed potential evapotranspiration on the large catchment systems.233Scopus© Citations 50 - PublicationFuture Water Vulnerability in Ireland: An Integrated Water Resources, Climate and Land Use Changes Model(2016-11-15)
; ; ; Water resources management and policies need to consider the dynamic nature of any catchment’s water balance, particularly in planning stage, to develop effective strategies for the future. The main goal of this research is to create an innovative and integrated environmental modelling tool (GEOCWB) by applying Machine Learning Techniques to a Geographic Information system (GIS). The developed tool uses as test and validation case the trans-boundary Shannon river basin. Climate change projections for the Shannon River catchment are simulated and presented using GEO-CWB for several climate variables from multi-GCM ensembles for three future time intervals using a range of different Representative Concentration Pathways (RCPs). As part of the integrated environmental modelling approach, the future spatially distributed urban expansion scenarios and land use changes for Shannon river basin are simulated and presented based on realistic land cover change models and projected to several time intervals. This is achieved using a hybrid modelling technique combining a logistic regression and a cellular automata (CA) model for developing spatial patterns of urban expansion. The research presented here provides an appropriate methodology for long-term changes analysis in European trans-boundary river’s water level and streamflow parameters after using a customized GISbased algorithm to simplify the hydrological system. GEO-CWB provides an integrated GIS tool for modelling potential evapotranspiration on the catchment scale. The GEO-CWB tool has been developed to help and support water sector modellers, planners, and decision makers to simulate and predict future spatially distributed dynamic water balances using a GIS environment at a catchment scale in response to the future change in climate variables and land use. Several Machine Learning Techniques are applied on the outcomes of the GEO-CWB model for the Shannon River in order to model and predict the water level and streamflow parameters for some stations along the river for daily time steps.523