934 research outputs found
Climate Change Impact on Catchment Hydrology & Water Resources for Selected Catchments in Ireland
This paper analyses the likely impacts of changes in climate for nine hydrologically diverse catchments
throughout Ireland. When assessing the impacts of climate change on water resources there is a cascade of
uncertainty that begins with the establishment of future pathways of development and ends with impact
assessment (Wilby, 2005). In order to represent uncertainty in future simulations, statistically downscaled
output from three Global Climate Models (GCMs), forced using two emission scenarios is used to force a
lumped, conceptual rainfall-runoff model for three future time periods; the 2020s, the 2050s and 2080s.
Changes in catchment storage, streamflow and extreme events are assessed through comparison with the
GCM modelled control period 1961-1990. Future simulations suggest that reductions in soil moisture
storage throughout the summer and autumn months are likely for each catchment. The extent of decreases
are largely dependent on the storage potential of individual catchments; the lower the capacity of
catchments to store water, the greater the sensitivity to climate change. Reductions in groundwater storage
during the recharge period will increase the risk of severe drought, as the failure of winter or spring
precipitation may result in prolonged drought periods where the groundwater system is unable to recover.
Greatest reductions in streamflow are likely for the autumn months in the majority of catchments, while
greatest increases are suggested for the month of February. The magnitude and frequency of flood events
are shown to increase, with the greatest increases associated with floods of a higher return period.
Uncertainty in future simulations derived from HYSIM parameter uncertainty is found to be more
important than uncertainty due to emission scenario
Climate Change Scenarios and Challenges for the Water Environment
The provision of downscaled global circulation output is the first stage in assessing the
implications of climate change for the water environment. Using only one global climate
model Sweeney and Fealy, 2003 concluded that projected changes in climate will have
potentially large effects on the water environment in Ireland, particularly on flood and
drought frequencies. Increased winter runoff in western parts as a result of wetter winters and
decreased summer runoff, especially in eastern Ireland as a result of substantial reductions in
summer rainfall are projected. Considerable uncertainties however exist from such projections
since they are based on only one GCM. These uncertainties limit the reliability of such
climate scenarios for future water resource management since different GCMs tend to show
different results for areas such as Ireland. This arises from inherent weaknesses they possess
due to problems of scale and feedback. One way of addressing these uncertainties and
providing more reliable inputs to hydrological models is to use multi- model downscaling, and
this approach is presented here
Changing Precipitation Scenarios: preliminary implications for groundwater flow systems and planning.
Statistical downscaling of a suite of three global climate models for two emission scenarios are used to produce precipitation scenarios for Ireland to 2090. One of these was used to drive a rainfall-runoff model for the River Boyne. The model was calibrated over the 1961-90 base period, validated using 1991-2000 data and run for three future time periods using downscaled GCM output. Significant changes in monthly flow regimes, soil moisture storage and groundwater storage were noted, with summer flows typically reduced by 20%. Negative changes in soil moisture storage also resulted, with soil moisture deficits increasingly extending into the Autumn as the century proceeds. Such a situation is seen to potentially compromise groundwater recharge in individual years and an increasing lag in groundwater recharge was detected. By the 2080s the groundwater recharge lag has developed to the extent that spring and early summer surface flows appear to be still benefiting from winter groundwater recharge while by late autumn groundwater is seriously depleted due to drier summer conditions. Serious implications for water yield from groundwater-fed sources would thus arise in the event of a dry winter being experienced. Greater conservatism in estimating water yields from groundwater sources would seem appropriate and may require to be formally incorporated into planning procedures
Catering for Uncertainty in a Conceptual Rainfall Runoff Model: Model Preparation for Climate Change Impact Assessment and the Application of GLUE using Latin Hypercube Sampling
Changes in Irish climate may pose a number of obstacles for water resource management. There is a need to approach this problem using the catchment as the basic unit of analysis. The application of a lumped conceptual rainfall-runoff model for simulating beyond a baseline calibration set is a major challenge for climate change impact assessment. This is due in no small part to the limitations associated with the use of these models, with uncertainty in model output being associated with model structure and the non-uniqueness of optimised parameter sets. In this paper, HYSIM, an “off-the-shelf” conceptual rainfall runoff model using data on a daily time-step is applied to a suite of catchments throughout Ireland in preparation for use with downscaled climate data. Uncertainties relating to process parameter calibration due to parameter interaction and equifinality are highlighted. In an attempt to improve the reliability of model output the generalised likelihood uncertainty estimation (GLUE) framework is adopted to analyse the uncertainty in model output derived from parametric sources. Traditionally this approach has been applied using Monte Carlo random sampling (MCRS). However, when using an “off-the-shelf” type model, source code may not be available and it may not be feasible to run the model for large MCRS samples without user intervention. In order to make the propagation of uncertainty through the model more efficient, input parameter sets are generated using Latin Hypercube sampling (LHS). A number of acceptable parameter sets are generated and uncertainty bounds are constructed for each time step using the 5th and 95th percentile at each temporal interval. These uncertainty bounds will be used to quantify the uncertainty in simulations carried out beyond the baseline calibration period as they include the error derived from data measurement, model structure, and parameterisation
Assessing the Impact of Climate Change on Water Supply and Flood Hazard in Ireland using Statistical Downscaling and Hydrological Modelling Technique
Although Ireland is relatively well endowed with water resources,
regional shortages can occur at certain times of the year, especially in the
east and south east of the country. The rapid expansion of urban areas
such as Dublin, Cork, and Limerick, associated with recent economic
conditions, is putting an increasing strain on the water supply
infrastructure. The increased demand for water comes mainly from the
industrial and domestic sectors, with domestic demand increasing both as
a result of population growth and rising water consumption per capita.
As a result, low flows are becoming more frequent in some areas and it is
likely that future climate change scenarios will exacerbate these effects.
At the same time, many Irish rivers are prone to flooding, especially
those in the west, with the Shannon being a prime example. Increases in
winter precipitation over the western part of the island are likely to
increase the magnitude and frequency of flood events, and increase the
duration of seasonal flooding. The aim of this research, therefore, is to
simulate patterns of runoff under baseline and future climate scenarios, at
a fine spatial resolution, in order to assess annual and seasonal changes
Bundap Marram Durn Durn: Engagement with Aboriginal women experiencing comorbid chronic physical and mental health conditions
OBJECTIVE: To explore antecedents of health service engagement and experience among urban Aboriginal people with comorbid physical and mental health conditions. METHODS: Focus groups and interviews were conducted with Aboriginal people who had comorbid health conditions and were accessing Aboriginal and/or mainstream services. RESULTS: Nineteen participants, all women, were recruited. Participants' personal histories and prior experience of health services affected effective service utilisation. Participants' service experiences were characterised by long waiting times in the public health system and high healthcare staff turnover. Trusted professionals were able to act as brokers to other clinically and culturally competent practitioners. CONCLUSIONS: Many urban Aboriginal women attended health services with multiple comorbid conditions including chronic disease and mental health issues. Several barriers and enablers were identified concerning the capacity of services to engage and effectively manage Aboriginal patients' condition
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