Climate Change and Water Resources

Abstract included in text

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 and Water Resources

Abstract included in text

Mechanisms of Psychological Distress following War in the Former Yugoslavia: The Role of Interpersonal Sensitivity

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.This study was funded by a grant from the European Commission, contract number INCO-CT-2004-509176. AN was supported by a Clinical Early Career Research Fellowship (113295) and a Project Grant (104288

Bench-to-bedside review : targeting antioxidants to mitochondria in sepsis

Peer reviewedPublisher PD

Advancing Tests of Relativistic Gravity via Laser Ranging to Phobos

Phobos Laser Ranging (PLR) is a concept for a space mission designed to advance tests of relativistic gravity in the solar system. PLR's primary objective is to measure the curvature of space around the Sun, represented by the Eddington parameter $\gamma$, with an accuracy of two parts in $10^7$, thereby improving today's best result by two orders of magnitude. Other mission goals include measurements of the time-rate-of-change of the gravitational constant, $G$ and of the gravitational inverse square law at 1.5 AU distances--with up to two orders-of-magnitude improvement for each. The science parameters will be estimated using laser ranging measurements of the distance between an Earth station and an active laser transponder on Phobos capable of reaching mm-level range resolution. A transponder on Phobos sending 0.25 mJ, 10 ps pulses at 1 kHz, and receiving asynchronous 1 kHz pulses from earth via a 12 cm aperture will permit links that even at maximum range will exceed a photon per second. A total measurement precision of 50 ps demands a few hundred photons to average to 1 mm (3.3 ps) range precision. Existing satellite laser ranging (SLR) facilities--with appropriate augmentation--may be able to participate in PLR. Since Phobos' orbital period is about 8 hours, each observatory is guaranteed visibility of the Phobos instrument every Earth day. Given the current technology readiness level, PLR could be started in 2011 for launch in 2016 for 3 years of science operations. We discuss the PLR's science objectives, instrument, and mission design. We also present the details of science simulations performed to support the mission's primary objectives.Comment: 25 pages, 10 figures, 9 table

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

Theoretical analysis of biogas potential prediction from agricultural waste

AbstractA simplistic theoretical study of anaerobic digestion in order to predict the biogas amount of agricultural waste is proposed. A wide variety of models exist, but most of them rely on algebraic equations instead of biochemical equations and require many input parameters as well as computation time. This work provides a simplified model that predicts the biogas amount produced and could be applied for agricultural energy feasibility studies for instance dimensioning bioreactors digesting animal waste slurries. The method can be used for other feedstock materials and repeated for other similar applications, in an effort to expand anaerobic digestion systems as a clean energy source