Generating realistic perturbed hydrometeorological time series to inform scenario-neutral climate impact assessments

Culley, Sam; Bennett, Bree; Westra, Seth; Maier, Holger R.

doi:10.1016/j.jhydrol.2019.06.005

Cited by 23 publications

(10 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This can occur when two model inputs (e.g., water supply and water demand) are lined up from worst to best, and the two worst values (e.g., lowest water supply and highest water demand) are paired, and so forth, leading to a clear set of worst to best points in the hypercube (Beh et al, 2014, 2015a, 2015b). Uniform : Figure 4c depicts a uniform sampling of the entire hypercube to consider a wide range of plausible futures, as is often done in the water resources literature (Culley et al, 2016, 2019; Hadka et al, 2015; Hall et al, 2012; Herman et al, 2015; Kasprzyk et al, 2013; Kwakkel, 2017; Kwakkel et al, 2015; Kwakkel, Walker, et al, 2016; McPhail et al, 2018; Quinn et al, 2017, 2018; Singh et al, 2015; Trindade et al, 2017; Watson & Kasprzyk, 2017; Weaver et al, 2013; Zeff et al, 2014). …”

Section: Case Studymentioning

confidence: 99%

“…When scenarios correspond to coherent descriptions of alternative hypothetical futures (e.g., van Notten et al, 2005), the number of scenarios considered is generally small (~3–9, see Table S1 in the supporting information), and scenarios are generally identified using some type of human input, such as the use of participatory approaches involving a variety of stakeholders (e.g., Wada et al, 2019). In contrast, when scenarios are designed to represent a broad range of combined changes in future conditions, the number of scenarios considered is generally large (~100–15,000, see Table S1 in the supporting information), and scenarios are generated using numerical modeling and/or sampling‐ or optimization‐based approaches, with minimal stakeholder input (e.g., Culley et al, 2016, 2019; Hadka et al, 2015; Hall et al, 2012; Herman et al, 2014, 2015; Kasprzyk et al, 2013; Kwakkel et al, 2015; Kwakkel, 2017; Kwakkel, Walker, et al, 2016; McPhail et al, 2018; Quinn et al, 2017, 2018; Singh et al, 2015; Trindade et al, 2017; Watson & Kasprzyk, 2017; Weaver et al, 2013; Zeff et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Impact of Scenario Selection on Robustness

McPhail

Maier

Westra

et al. 2020

Water Resources Research

Self Cite

View full text Add to dashboard Cite

Multiple plausible future scenarios are being used increasingly in preference to a single deterministic or probabilistic prediction of the future in the long-term planning of water resources systems. These scenarios enable the determination of the robustness of a system-the consideration of performance across a range of plausible futures-and allow an assessment of which possible future system configurations result in a greater level of robustness. There are many approaches to selecting scenarios, and previous studies have observed that the choice of scenarios might affect the estimated robustness of the system. However, these observations have been anecdotal and qualitative. This paper develops a systematic, quantitative methodology for exploring the influence of scenario selection on the robustness and the ranking of decision alternatives. The methodology is illustrated on the Lake Problem. The quantitative results obtained confirm the qualitative observations of previous works, showing that the selection of scenarios is important, as it has a large influence on the robustness value calculated for each decision alternative. However, we show that it has a relatively small influence on how those decision alternatives are ranked. This implies that despite the difference in robustness values, similar decision outcomes will be reached in this case study, regardless of the basis on which the scenarios are obtained. It is also revealed that the impact of the scenarios on the robustness values is due to complex interactions with the system model and robustness metrics.

show abstract

Section: Case Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact of Scenario Selection on Robustness

McPhail

Maier

Westra

et al. 2020

Water Resources Research

Self Cite

View full text Add to dashboard Cite

show abstract

“…Changes in temperature and precipitation extremes do not necessarily scale with mean changes, which has been found in CMIP5 projections, for example for the Mediterranean region with an intensification of heat and water stress ( Sillmann et al, 2013 ). One way to incorporate variability changes in the sensitivity analysis is the use of weather generators to systematically perturb parameters affecting the variability, such as the number of wet days, in addition to the total precipitation ( Rötter et al, 2011 , Culley et al, 2019 ).…”

Section: Discussionmentioning

confidence: 99%

Estimating impact likelihoods from probabilistic projections of climate and socio-economic change using impact response surfaces

Fronzek

Honda

Ito

et al. 2022

Climate Risk Management

View full text Add to dashboard Cite

“…In response to these challenges, "scenario-led" frameworks have been recently developed to depict the water system performance under possible climate conditions [90][91][92][93][94]. Yet, the results of stress tests depend on the approach used for generation of stochastic climate scenarios [95]. Moreover, the results of vulnerability assessments are still uncertain, particularly if hydrological model are used for projection of streamflow series [96].…”

Section: Discussionmentioning

confidence: 99%

Trade-Offs between Human and Environment: Challenges for Regional Water Management under Changing Conditions

Hassanzadeh

2019

Water

View full text Add to dashboard Cite

Water resource systems are under unprecedented pressure mainly due to rapid socio-economic growth, weak water and land management decisions, as well as variability and change in climate conditions. These pressures have disrupted the functionality of freshwater ecosystems and have generated water management challenges in various regions across the globe. Here, we showcase the potential trade-offs in the Province of Saskatchewan, Canada, between upstream human activities and downstream environmental needs under changing water availability conditions. We showed that an increase in irrigation areas can boost provincial economy but alter timing, magnitude and rhythmicity of the peak flows reaching downstream ecosystems. This indicates that the business as usual management might not be able to handle such emerging challenges. To improve water management, we argue that there is a need to better represent the dynamic interactions between human water use and water quantity and quality conditions and their influence on ecosystems. In addition, impact assessment frameworks need to be improved to better identify system vulnerabilities under changing natural and anthropogenic conditions. Moreover, due to the key role of stakeholders in adopting land and water management decisions, their viewpoints need to be understood and included in management decisions.

show abstract

Generating realistic perturbed hydrometeorological time series to inform scenario-neutral climate impact assessments

Cited by 23 publications

References 21 publications

Impact of Scenario Selection on Robustness

Impact of Scenario Selection on Robustness

Estimating impact likelihoods from probabilistic projections of climate and socio-economic change using impact response surfaces

Trade-Offs between Human and Environment: Challenges for Regional Water Management under Changing Conditions

Contact Info

Product

Resources

About