Quantile-Based Downscaling of Precipitation Using Genetic Programming: Application to IDF Curves in Saskatoon

Hassanzadeh, Elmira; Nazemi, A.; Elshorbagy, Amin

doi:10.1061/(asce)he.1943-5584.0000854

Cited by 62 publications

(40 citation statements)

References 42 publications

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“…Comparison of 3-hr exceedance probabilities from 6 NCEP driven RCM runs in the NARCCAP ensemble (solid line) to observations re-gridded to 3-hr, 50km resolution (dashed line) for a grid cell in Pittsburgh region The first approach involves complex statistical downscaling techniques to obtain the appropriate temporal and spatial resolution of the time series. However, it has been hypothesized that if the engineer is only concerned with designing for extremes, it may be more manageable to avoid downscaling to a continuous time series, and instead adjust empirical quantiles through mapping functions (Hassanzadeh et al 2013). A simple method that has been introduced in the engineering literature involves directly adjusting historical rainfall depths at the point scale, for a given return period and duration, based on the expected change from historical to future conditions at the grid scale (Zhu et al 2012;Forsee and Ahmad 2011).…”

Section: Step 4 Incorporate Climate Model Output Into the Required Ementioning

confidence: 99%

“…Arnbjerg-Nielsen et al 2013;Forsee and Ahmad 2011). These climateinformed local-scale models have also been used to update intensity-duration-frequency curves used in design of infrastructure affected by rainfall (Chandra et al 2015;Cheng and AghaKouchak 2014;Forsee and Ahmad 2011;Zhu 2012;Kuo et al 2015;Hassanzadeh et al 2013;Mirhosseini et al 2013).…”

Section: Introductionmentioning

confidence: 99%

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Framework for Incorporating Downscaled Climate Output into Existing Engineering Methods: Application to Precipitation Frequency Curves

Cook

Anderson

Samaras

2017

J. Infrastruct. Syst.

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Abstract:To improve the resiliency of designs, particularly for long-lived infrastructure, current engineering practice must be updated to incorporate a range of future climate conditions that are likely to be different from the past. However, a considerable mismatch exists between climate model outputs and the data inputs needed for engineering designs. The present work provides a framework for incorporating climate trends into design standards and applications, including: selecting the appropriate climate model source based on the intended application, understanding model performance and uncertainties, addressing differences in temporal and spatial scales, and interpreting results for engineering design. The framework is illustrated through an application to depth-duration-frequency curves, which are commonly used in stormwater design. A change factor method is used to update the curves in a case study of Pittsburgh, PA. Extreme precipitation depth is expected to increase in the future for Pittsburgh for all return periods and durations examined, requiring revised standards and designs. Doubling the return period and using historical, stationary values may enable adequate design for short duration storms; however, this method is shown to be insufficient to enable protective designs for larger duration storms.

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Section: Step 4 Incorporate Climate Model Output Into the Required Ementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Framework for Incorporating Downscaled Climate Output into Existing Engineering Methods: Application to Precipitation Frequency Curves

Cook

Anderson

Samaras

2017

J. Infrastruct. Syst.

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“…These techniques can range from statistical regression models to more sophisticated machine-learning techniques such as artificial neural networks (e.g., Nazemi et al, 2006a) and genetic symbolic regression (e.g., Hassanzadeh et al, 2014). One example would be building functional relationships for estimation of irrigative or non-irrigative water demands and/or uses.…”

Section: Water Resource Management Algorithmsmentioning

confidence: 99%

On inclusion of water resource management in Earth system models – Part 2: Representation of water supply and allocation and opportunities for improved modeling

Nazemi

Wheater

2015

Hydrol. Earth Syst. Sci.

114

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Abstract. Human water use has significantly increased during the recent past. Water withdrawals from surface and groundwater sources have altered terrestrial discharge and storage, with large variability in time and space. These withdrawals are driven by sectoral demands for water, but are commonly subject to supply constraints, which determine water allocation. Water supply and allocation, therefore, should be considered together with water demand and appropriately included in Earth system models to address various large-scale effects with or without considering possible climate interactions. In a companion paper, we review the modeling of demand in large-scale models. Here, we review the algorithms developed to represent the elements of water supply and allocation in land surface and global hydrologic models. We note that some potentially important online implications, such as the effects of large reservoirs on land-atmospheric feedbacks, have not yet been fully investigated. Regarding offline implications, we find that there are important elements, such as groundwater availability and withdrawals, and the representation of large reservoirs, which should be improved. We identify major sources of uncertainty in current simulations due to limitations in data support, water allocation algorithms, host large-scale models as well as propagation of various biases across the integrated modeling system. Considering these findings with those highlighted in our companion paper, we note that advancements in computation and coupling techniques as well as improvements in natural and anthropogenic process representation and parameterization in host large-scale models, in conjunction with remote sensing and data assimilation can facilitate inclusion of water resource management at larger scales. Nonetheless, various modeling options should be carefully considered, diagnosed and intercompared. We propose a modular framework to develop integrated models based on multiple hypotheses for data support, water resource management algorithms and host models in a unified uncertainty assessment framework. A key to this development is the availability of regional-scale data for model development, diagnosis and validation. We argue that the time is right for a global initiative, based on regional case studies, to move this agenda forward.

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“…Global climate models have too-coarse spatial resolution to provide direct information about possible changes to IDF relationships, and various downscaling techniques have been proposed to extract relevant information. Recent studies of changes in IDF curves with focus on Canada include Mailhot et al (2007Mailhot et al ( , 2012, Eum and Simonovic (2012), Burn and Taleghani (2013) and Hassanzadeh et al (2013).…”

Section: Introductionmentioning

confidence: 99%

Assessing the impact of climate change on the frequency of floods in the Red River basin

Rasmussen

2015

Canadian Water Resources Journal / Revue canadienne des ressour

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The impact of climate change on the frequency distribution of spring floods in the Red River basin is investigated. Several major floods in the last couple of decades have caused major damages and inconvenience to people living in the Red River flood plain south of Winnipeg, and have raised the question of whether climate change is at least partly responsible for what appears to be more frequent occurrences of high spring runoff. To investigate whether this is the case, a regression model is used to associate spring peak flow at the US-Canada border with predictor variables that include antecedent precipitation in the previous fall (used as a proxy for soil moisture at freeze-up), winter snow accumulation and spring precipitation. Data from the Coupled Model Intercomparison Project -Phase 5 (CMIP5) are used to derive information about possible changes to the predictor variables in the future, and this information is then used to derive flood distributions for future climate conditions. While mean monthly precipitation during the winter months is expected to increase, winters are expected to be shorter in warmer climates and evaporation losses are expected to be higher, resulting in a net reduction in average snow pack accumulations. On the other hand, precipitation during the active snowmelt period is expected to increase. The average of future flood distributions obtained from an ensemble of 16 climate models is close to the distribution fitted to observed data, but there is considerable uncertainty surrounding the average, highlighting the difficulty in assessing changes in the frequency of extreme events.Dans cet article, nous essayons de déterminer l'effet des changements climatiques sur la fréquence des crues de la rivière Rouge. Dans les quelques dernières décennies, plusieurs inondations graves ont causé des dommages importants et perturbé la vie des personnes qui habitent à proximité de la rivière, au sud de la ville de Winnipeg, et soulevé la question à savoir si les changements climatiques contribuent à ce qui semble être une occurrence plus fréquente d'eaux de ruissellement élevées. Afin de répondre à cette question, nous utilisons un modèle de régression pour estimer le débit de pointe au printemps à la frontière entre le Canada et les États-Unis, en fonction des variables explicatives qui incluent la précipitation de l'automne précédent (qui serve à calculer approximativement l'humidité du sol au gel), ainsi que les précipitations hivernales et printanières. Le modèle de régression est estimé à partir de données historiques. Les données du Projet d'intercomparaison de modèles climatiques (CMIP5) sont utilisées pour obtenir de l'information sur des changements éventuels possibles des variables explicatives du modèle de régression, information qui servira par la suite à estimer la distribution statistique des crues selon les conditions climatiques futures. Les modèles climatiques indiquent que dans les climats plus chauds, les précipitations hivernales augmenteront, que les hivers seront plus courts et...

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Quantile-Based Downscaling of Precipitation Using Genetic Programming: Application to IDF Curves in Saskatoon

Cited by 62 publications

References 42 publications

Framework for Incorporating Downscaled Climate Output into Existing Engineering Methods: Application to Precipitation Frequency Curves

Framework for Incorporating Downscaled Climate Output into Existing Engineering Methods: Application to Precipitation Frequency Curves

On inclusion of water resource management in Earth system models – Part 2: Representation of water supply and allocation and opportunities for improved modeling

Assessing the impact of climate change on the frequency of floods in the Red River basin

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