Monte Carlo Assessment of Sampling Uncertainty of Climate Change Impacts on Water Resources Yield in Yorkshire, England

Nawaz, Rizwan; Adeloye, Adebayo J.

doi:10.1007/s10584-005-9043-9

Cited by 45 publications

(25 citation statements)

References 42 publications

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“…The major source of uncertainty considered is that derived from several GCM scenarios where (1) parameters and algorithms in the hydrological model have been held constant, as determining the range in which the values will vary is difficult to determine and has been found to contribute little towards the uncertainty ; (2) the day-today variability has been confined; and (3) it is assumed that there is no change in the land cover response to climate due to the difficulties in determining the future impacts on the loss of permafrost with respect to vegetation cover and soil properties (Yi et al, 2007). These constraints are consistent with the climate impact assessment approach by Parry and Carter (1998) adopted by the other papers within this special issue (Singh et al, 2010).…”

Section: Introductionmentioning

confidence: 67%

“…This inclusion of future climate uncertainty on hydrological impacts with the use of climate change scenarios is of recent concern (Cameron et al, 2000;Horton et al, 2006;Kriaučiūnienė et al, 2009;Maurer, 2007;Minville et al, 2008;Nawaz and Adeloye, 2006;Prudhomme and Davis, 2009a,b). For an Arctic climate, several studies have examined the impacts of future climate scenarios (Bonsal and Kochtubajda, 2009;Kattsov et al, 2007;Nohara et al, 2006), however, few have examined the hydrological impacts in this region.…”

Section: Introductionmentioning

confidence: 99%

“…For an Arctic climate, several studies have examined the impacts of future climate scenarios (Bonsal and Kochtubajda, 2009;Kattsov et al, 2007;Nohara et al, 2006), however, few have examined the hydrological impacts in this region. One exception is the study by Pohl et al (2007) who examined the effects of GCM projections on a small Arctic headwater basin.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainty in the impacts of projected climate change on the hydrology of a subarctic environment: Liard River Basin

Thorne

2011

Hydrol. Earth Syst. Sci.

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Abstract. Like many high latitude areas, the mountainous region of subarctic Canada has experienced recent warming and is an area of large inter-annual temperature variations, most notably during the winter. Quantifying how climate tendencies affect streamflow, especially in the spring melt season, is critical not only to regional water resource management, but to understanding the influence of freshwater on the Arctic sea-ice cover and global climate system. The impact of projected atmospheric warming on the discharge of the Liard River is unclear. Here, uncertainty in climate projections associated with GCM structure (2 • C prescribed warming) and magnitude of increases in global mean air temperature (1 to 6 • C) on the river discharge are assessed using a well-tested, semi-distributed hydrological model. Analyses have shown that the hydrological impacts are highly dependant on the GCM scenario. Uncertainties between the GCM scenarios are driven by the inconsistencies in projected spatial variability and magnitude of precipitation, rather than warming temperatures. Despite these uncertainties, the entire scenario simulations project that the subarctic nival regime will be preserved in the future, but the magnitude of change in river discharge is highly uncertain. Generally, spring freshet will arrive earlier, autumn to spring discharge will increase whereas summer flow will decrease, leading to an overall increase in annual discharge.

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Section: Introductionmentioning

confidence: 67%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Uncertainty in the impacts of projected climate change on the hydrology of a subarctic environment: Liard River Basin

Thorne

2011

Hydrol. Earth Syst. Sci.

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“…The outputs of these hydrological models then form input to water resources simulation models for the purpose of characterising systems performance (see e.g. Fowler et al, 2003;Nawaz and Adeloye, 2006). However, as widely recognised (see Raje and Mujumdar, 2010), there are uncertainties in GCMs climate change predictions not only between GCMs but also within GCMs (Peel et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Quantifying the uncertainties of climate change effects on the storage-yield and performance characteristics of the Pong multi-purpose reservoir, India

2015

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Abstract. Climate change is predicted to affect water resources infrastructure due to its effect on rainfall, temperature and evapotranspiration. However, there are huge uncertainties on both the magnitude and direction of these effects. The Pong reservoir on the Beas River in northern India serves irrigation and hydropower needs. The hydrology of the catchment is highly influenced by Himalayan seasonal snow and glaciers, and Monsoon rainfall; the changing pattern of the latter and the predicted disappearance of the former will have profound effects on the performance of the reservoir. This study employed a Monte-Carlo simulation approach to characterise the uncertainties in the future storage requirements and performance of the reservoir. Using a calibrated rainfall-runoff (R-R) model, the baseline runoff scenario was first simulated. The R-R inputs (rainfall and temperature) were then perturbed using plausible delta-changes to produce simulated climate change runoff scenarios. Stochastic models of the runoff were developed and used to generate ensembles of both the current and climatechange perturbed future scenarios. The resulting runoff ensembles were used to simulate the behaviour of the reservoir and determine "populations" of reservoir storage capacity and performance characteristics. Comparing these parameters between the current and the perturbed provided the population of climate change effects which was then analysed to determine the uncertainties. The results show that contrary to the usual practice of using single records, there is wide variability in the assessed impacts. This variability or uncertainty will, no doubt, complicate the development of climate change adaptation measures; however, knowledge of its sheer magnitude as demonstrated in this study will help in the formulation of appropriate policy and technical interventions for sustaining and possibly enhancing water security for irrigation and other uses served by Pong reservoir.

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“…There have been many studies of the impact of climate change on river flows in different parts of the UK (e.g. Charlton and Arnell, 2011;Diaz-Nieto and Wilby, 2005;Holman, 2006;Kay et al, 2009;Ledbetter et al, 2011;Limbrick et al, 2000;Lopez et al, 2009;Nawaz and Adeloye, 2006;Prudhomme and Davies, 2009;Prudhomme et al, 2010;Wilby and Harris, 2006;Kay and Jones, 2010), but coverage is uneven and methods vary. This means it is very difficult to compare different locations, complicating the identification of appropriate adaptation responses.…”

Section: Introductionmentioning

confidence: 99%

Future Flows Climate: an ensemble of 1-km climate change projections for hydrological application in Great Britain

Prudhomme

Dadson

Morris

et al. 2012

Earth Syst. Sci. Data

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Abstract. The dataset Future Flows Climate was developed as part of the project "Future Flows and Groundwater Levels" to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications, and to enable climate change uncertainty and climate variability to be accounted for in the assessment of their possible impacts on the environment.Future Flows Climate is derived from the Hadley Centre's ensemble projection HadRM3-PPE that is part of the basis of UKCP09 and includes projections in available precipitation (water available to hydrological processes after snow and ice storages have been accounted for) and potential evapotranspiration. It corresponds to an 11-member ensemble of transient projections from January 1950 to December 2098, each a single realisation from a different variant of HadRM3. Data are provided on a 1-km grid over the HadRM3 land areas at a daily (available precipitation) and monthly (PE) time step as netCDF files.Because systematic biases in temperature and precipitation were found between HadRM3-PPE and gridded temperature and precipitation observations for the 1962-1991 period, a monthly bias correction procedure was undertaken, based on a linear correction for temperature and a quantile-mapping correction (using the gamma distribution) for precipitation followed by a spatial downscaling. Available precipitation was derived from the bias-corrected precipitation and temperature time series using a simple elevation-dependant snow-melt model. Potential evapotranspiration time series were calculated for each month using the FAO-56 Penman-Monteith equations and bias-corrected temperature, cloud cover, relative humidity and wind speed from HadRM3-PPE along with latitude of the grid and the day of the year.Future Flows Climate is freely available for non-commercial use under certain licensing conditions. It is the dataset used to generate Future Flows Hydrology, an ensemble of transient projections of daily river flow and monthly groundwater time series for representative river basins and boreholes in Great Britain.

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Monte Carlo Assessment of Sampling Uncertainty of Climate Change Impacts on Water Resources Yield in Yorkshire, England

Cited by 45 publications

References 42 publications

Uncertainty in the impacts of projected climate change on the hydrology of a subarctic environment: Liard River Basin

Uncertainty in the impacts of projected climate change on the hydrology of a subarctic environment: Liard River Basin

Quantifying the uncertainties of climate change effects on the storage-yield and performance characteristics of the Pong multi-purpose reservoir, India

Future Flows Climate: an ensemble of 1-km climate change projections for hydrological application in Great Britain

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