A nonstationary index-flood technique for estimating extreme quantiles for annual maximum streamflow

O’Brien, Nicole; Burn, Donald H.

doi:10.1016/j.jhydrol.2014.09.041

Cited by 56 publications

(36 citation statements)

References 42 publications

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“…much of Russia; Semyonov and Korshunov, 2006;Adam and Lettenmaier, 2008; Figure 1a). Olsen et al, 1999;Douglas and Fairbank, 2011); (2) non-stationary statistical techniques (O'Brien and Burn, 2014;Salas and Obeysekera, 2014;Westra et al, 2014); (3) modelling of site-specific streamflow changes under projected future climates (e.g. design flows) have assumed climate stationarity (e.g.…”

Section: Incorporating Climate Change Into Riparian Restoration Plannmentioning

confidence: 99%

“…The literature suggests four general approaches for climateinformed design flow estimates: (1) stationary methods using updated or recent precipitation and streamflow records (e.g. Olsen et al, 1999;Douglas and Fairbank, 2011); (2) non-stationary statistical techniques (O'Brien and Burn, 2014;Salas and Obeysekera, 2014;Westra et al, 2014); (3) modelling of site-specific streamflow changes under projected future climates (e.g. Hodgkins and Dudley, 2013); and (4) modelling of streamflow changes throughout a stream network under projected future climates (e.g.…”

Section: Incorporating Climate Change Into Riparian Restoration Plannmentioning

confidence: 99%

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Incorporating climate change projections into riparian restoration planning and design

et al. 2015

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Climate change and associated changes in streamflow may alter riparian habitats substantially in coming decades. Riparian restoration provides opportunities to respond proactively to projected climate change effects, increase riparian ecosystem resilience to climate change, and simultaneously address effects of both climate change and other human disturbances. However, climate change may alter which restoration methods are most effective and which restoration goals can be achieved. Incorporating climate change into riparian restoration planning and design is critical to long-term restoration of desired community composition and ecosystem services.In this review, we discuss and provide examples of how climate change might be incorporated into restoration planning at the key stages of assessing the project context, establishing restoration goals and design criteria, evaluating design alternatives, and monitoring restoration outcomes. Restoration planners have access to numerous tools to predict future climate, streamflow, and riparian ecology at restoration sites. Planners can use those predictions to assess which species or ecosystem services will be most vulnerable under future conditions, and which sites will be most suitable for restoration. To accommodate future climate and streamflow change, planners may need to adjust methods for planting, invasive species control, channel and floodplain reconstruction, and water management. Given the considerable uncertainty in future climate and streamflow projections, riparian ecological responses, and effects on restoration outcomes, planners will need to consider multiple potential future scenarios, implement a variety of restoration methods, design projects with flexibility to adjust to future conditions, and plan to respond adaptively to unexpected change.

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Section: Incorporating Climate Change Into Riparian Restoration Plannmentioning

confidence: 99%

Section: Incorporating Climate Change Into Riparian Restoration Plannmentioning

confidence: 99%

Incorporating climate change projections into riparian restoration planning and design

et al. 2015

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“…According to the Global Health Observatory data of the World Health Organization (WHO 2015), 54% of the global population live in urban areas as of 2014, an increase of 20% from 1960. O'Brien andBurn (2014) and references therein showed evidence of increasing amplitude and decreasing time-to-peak in flooding events as a result of increasing impervious areas. The annual flood loss data for the United States (National Weather Service, NWS, 2015; see Figure 1 below) indicate that although flood warning has been improving, owing to the increase in both detection and understanding of the causes of heavy-to-extreme precipitation, floods still cause large losses with an annual average in the last 30 y of 89 fatalities and $8.2 billion in damages (Kunkel, Karl, Brooks et al 2013;Kunkel, Karl, Easterling et al 2013).…”

Section: Introductionmentioning

confidence: 98%

Assessing the Impact of Variations in Hydrologic, Hydraulic and Hydrometeorological Controls on Inundation in Urban Areas

Nazari

Seo

Muttiah

2016

JWMM

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There is a great need for timely prediction of the extent and depth of flooding and related hazards in highly populated urban areas such as the Dallas-Fort Worth metroplex (DFW). The hydrologic, hydraulic and hydrometeorological processes involved and the large number of factors that control them are complex, interrelated and generally scale dependent, which makes real time prediction of flood inundation in urban areas particularly challenging. In addition, a large number of human created structures such as channels, pipes, culverts, buildings, parking lots and manholes add complexity. With continuing urbanization and climate change, it is critical that the dynamics of urban flooding be better understood to improve prediction and to mitigate water related hazards under changing conditions. In this work, we assess how different factors may impact urban flood inundation using the 1D-2D PCSWMM model through a series of controlled simulation experiments. The main study area is the 3.3 km 2 Forest Park-Berry catchment in Fort Worth in North Central Texas, which has a high density of underground storm drainage.Specifically, we assess the impact of variations in precipitation and impervious cover on simulated inundation maps.

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“…For at‐site frequency analyses, formal treatments of time‐varying risk have also been well developed based on temporal trends [ Cunderlik and Ouarda , ; Leclerc and Ouarda , ; Delgado et al ., ; O'Brien and Burn , ; Jiang et al ., ] or conditioned on climate and landscape covariates [ Chowdhury and Sharma , ; Steinschneider and Brown , ; Sun et al ., ; Lima et al ., ; Zhang et al ., ], although there have been fewer applications that have been extended for regionalization. The use of climate and landscape covariates is particularly appealing for inference of causal relationships that drive hydrologic variability and change rather than temporal trends that may be unsubstantiated for inferences of future recurrence intervals [ Koutsoyiannis and Montanari , ] and uninformative for short‐term (i.e., seasonal) forecast development.…”

Section: Introductionmentioning

confidence: 99%

A hierarchical Bayesian model for regionalized seasonal forecasts: Application to low flows in the northeastern United States

Ahn

Palmer

2017

Water Resources Research

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This study presents a regional, probabilistic framework for seasonal forecasts of extreme low summer flows in the northeastern United States conditioned on antecedent climate and hydrologic conditions. The model is developed to explore three innovations in hierarchical modeling for seasonal forecasting at ungaged sites: (1) predictive climate teleconnections are inferred directly from ocean fields instead of predefined climate indices, (2) a parsimonious modeling structure is introduced to allow climate teleconnections to vary spatially across streamflow gages, and (3) climate teleconnections and antecedent hydrologic conditions are considered jointly for regional forecast development. The proposed model is developed and calibrated in a hierarchical Bayesian framework to pool regional information across sites and enhance regionalization skill. The model is validated in a cross‐validation framework along with five simpler nested formulations to test specific hypotheses embedded in the full model structure. Results indicate that each of the three innovations improve out‐of‐sample summer low‐flow forecasts, with the greatest benefits derived from the spatially heterogeneous effect of climate teleconnections. We conclude with a discussion of possible model improvements from a better representation of antecedent hydrologic conditions at ungaged sites.

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A nonstationary index-flood technique for estimating extreme quantiles for annual maximum streamflow

Cited by 56 publications

References 42 publications

Incorporating climate change projections into riparian restoration planning and design

Incorporating climate change projections into riparian restoration planning and design

Assessing the Impact of Variations in Hydrologic, Hydraulic and Hydrometeorological Controls on Inundation in Urban Areas

A hierarchical Bayesian model for regionalized seasonal forecasts: Application to low flows in the northeastern United States

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