Modeling jointly low, moderate, and heavy rainfall intensities without a threshold selection. Issue 4 (9th April 2016)
- Record Type:
- Journal Article
- Title:
- Modeling jointly low, moderate, and heavy rainfall intensities without a threshold selection. Issue 4 (9th April 2016)
- Main Title:
- Modeling jointly low, moderate, and heavy rainfall intensities without a threshold selection
- Authors:
- Naveau, Philippe
Huser, Raphael
Ribereau, Pierre
Hannart, Alexis - Abstract:
- Abstract: In statistics, extreme events are often defined as excesses above a given large threshold. This definition allows hydrologists and flood planners to apply Extreme‐Value Theory (EVT) to their time series of interest. Even in the stationary univariate context, this approach has at least two main drawbacks. First, working with excesses implies that a lot of observations (those below the chosen threshold) are completely disregarded. The range of precipitation is artificially shopped down into two pieces, namely large intensities and the rest, which necessarily imposes different statistical models for each piece. Second, this strategy raises a nontrivial and very practical difficultly: how to choose the optimal threshold which correctly discriminates between low and heavy rainfall intensities. To address these issues, we propose a statistical model in which EVT results apply not only to heavy, but also to low precipitation amounts (zeros excluded). Our model is in compliance with EVT on both ends of the spectrum and allows a smooth transition between the two tails, while keeping a low number of parameters. In terms of inference, we have implemented and tested two classical methods of estimation: likelihood maximization and probability weighed moments. Last but not least, there is no need to choose a threshold to define low and high excesses. The performance and flexibility of this approach are illustrated on simulated and hourly precipitation recorded in Lyon, France.Abstract: In statistics, extreme events are often defined as excesses above a given large threshold. This definition allows hydrologists and flood planners to apply Extreme‐Value Theory (EVT) to their time series of interest. Even in the stationary univariate context, this approach has at least two main drawbacks. First, working with excesses implies that a lot of observations (those below the chosen threshold) are completely disregarded. The range of precipitation is artificially shopped down into two pieces, namely large intensities and the rest, which necessarily imposes different statistical models for each piece. Second, this strategy raises a nontrivial and very practical difficultly: how to choose the optimal threshold which correctly discriminates between low and heavy rainfall intensities. To address these issues, we propose a statistical model in which EVT results apply not only to heavy, but also to low precipitation amounts (zeros excluded). Our model is in compliance with EVT on both ends of the spectrum and allows a smooth transition between the two tails, while keeping a low number of parameters. In terms of inference, we have implemented and tested two classical methods of estimation: likelihood maximization and probability weighed moments. Last but not least, there is no need to choose a threshold to define low and high excesses. The performance and flexibility of this approach are illustrated on simulated and hourly precipitation recorded in Lyon, France. Key Points: Statistical modeling of the full wet rainfall spectrum No threshold selection to apply Extreme Value Theory Joint Extreme Value Theory for both low and high rainfall … (more)
- Is Part Of:
- Water resources research. Volume 52:Issue 4(2016:Apr.)
- Journal:
- Water resources research
- Issue:
- Volume 52:Issue 4(2016:Apr.)
- Issue Display:
- Volume 52, Issue 4 (2016)
- Year:
- 2016
- Volume:
- 52
- Issue:
- 4
- Issue Sort Value:
- 2016-0052-0004-0000
- Page Start:
- 2753
- Page End:
- 2769
- Publication Date:
- 2016-04-09
- Subjects:
- extremes -- rainfall -- inference
Hydrology -- Periodicals
333.91 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1944-7973 ↗
http://www.agu.org/pubs/current/wr/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/2015WR018552 ↗
- Languages:
- English
- ISSNs:
- 0043-1397
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9275.150000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 2165.xml