Talk:100-year flood

Text presently in this article at subheads Upslope factors, Downslope factors, and Prediction might fit better in Flood forecasting. Justaxn (talk) 19:13, 1 July 2015 (UTC)Reply

• I question if moving that text would be appropriate. The flood forecasting article focuses on short term projections, while this article focuses on longer term projections. While information compiled over the longer term can be an important part of flood forecasting, short term precipitation forecasting is the primary variable in flood forecasting. The 100-year flood is commonly understood as a benchmark for longer-term planning, with time to consider a correspondingly expanded data collection effort. Thewellman (talk) 20:53, 1 July 2015 (UTC)Reply

The topic seems to be scattered in several places, and I agree Flood forecasting is not ideal. Similar ideas appear in Hydrology#Modeling, Hydrological modeling, and Runoff model. Perhaps one of the 4 should be improved and all the others should have a See Also. In any case, the physics of rainfall-runoff and calculations of a design flow rate for insufficiently-gaged sites shouldn't be in 100-year flood. We do need a link to those ideas, of course, perhaps from the statement under Probability uncertainty about regional regressions and hydrologic models. Justaxn (talk) 18:58, 4 July 2015 (UTC)Reply

• I question your assertion about this information being inappropriate to this subject. I suggest discussion of assumptions in the frequency predictions is appropriate and necessary to understanding limitations of floodplain mapping. Coincidence is especially significant. Construction of a flood storage reservoir upstream of the location of interest may be assumed to reduce flood magnitude and frequency, but reservoir failure may generate increased flood magnitude on a presumably reduced frequency. Consequences of coincidence tend to average out over larger watersheds which are the focus of planning; but it is somewhat misleading to suggest floodplain mapping covers locations with a single square mile of runoff area without discussing the increased uncertainty of prediction for small watersheds because of assumptions made in extrapolation of the tail of distribution of such factors as rainfall intensity, snowpack, and small channel maintenance conditions leading to increased probability of significant coincidence. I have found widespread ignorance of the increased steepness of flood flow variation in small watersheds. Many assume 24-hour precipitation intensity significant to large watersheds is also an appropriate design criterion in smaller drainage basins, and the reduced cost of designing for inappropriately low flows may be attractive to the smaller funding population residing in small drainage basins. Thewellman (talk) 00:28, 5 July 2015 (UTC)Reply

Almost 200 articles link to this one, so this content can reach a wide audience. Floodplain mapping, flood safety in design, and related hydraulic engineering are important and complex topics. My point is we can't do them justice within this article. Perhaps we need a new section(s) with a sentence or two on the topics I propose to delete and you propose to add. New headings might be Use in floodplain mapping and Use in river engineering. Then this article would show the many links to related topics while remaining primarily about statistics and uncertainty. Would you care to propose some specific text that should appear? I quite agree that we should inform the public better about the many real and large uncertainties in projections of potential flood severity. Justaxn (talk) 17:43, 6 July 2015 (UTC)Reply

• I don't understand your objection to the present text. I don't see any reason to remove material from this 18K article. Our difficulty agreeing on subsidiary topics indicates the article is not presently large enough to break into smaller pieces. Topics for main article links may become evident if this article grows beyond 30K; but short summary paragraphs will still be appropriate. Perhaps you can find sources documenting a floodplain mapping approach considering local building codes (or their absence) to address the foreseeable coincidental consequences of cascading failure of a system of drainage structures designed for 10- or 25-year return period storms during less frequent events.

Floodplain maps seem to emphasize natural water channels and neglect the artificial channels and dams created by the cut and fill of transportation corridors. Fill prisms may be converted to dams unless drainage structures are sized to pass the debris likely to be transported by flood flow, rather than sized for flood flow alone. This is more likely in small runoff basins drained by culverts too small to pass floating trees. Planning should anticipate sudden release of water impounded behind saturated fill prisms without overflow structures; and, until such failure occurs, possible diversion of runoff through transportation corridors into adjacent drainages.

Would you care to propose text describing evaluation of precipitation datasets? (specifically how and why one might separate orographic from convective precipitation events in historical data rather than attempting to normalize both within a single probability distribution) I have seen datasets including a few outliers at the upper end of the frequency distribution suggesting infrequent short-duration, high-intensity cells within storm systems. These cells average out in large drainage basins, but may be critical events in small runoff basins. It might be useful to explain why floodplain mapping of smaller drainage basins requires more refined data evaluation emphasizing short-duration precipitation intensity and local conditions at the higher elevations of small drainages causing increased precipitation and lower temperatures preserving snowpack. Thewellman (talk) 22:17, 6 July 2015 (UTC)Reply

• The essential word in this article title is flood. Precipitation, its time and space distribution, natural and artificial channels, hydraulic structure design, and other topics we have mentioned are all relevant to floods, but none of them is completely contained within the flood idea. Each touches on floods and each also touches on other topics. Thus to my mind, the 100-year flood article should include rather complete information on floods with an average return period of 100 years and should also mention all the related topics, but the complete information on those topics should be elsewhere. WP has several relevant articles already, where the points you raise should be explained, with appropriate citations. Unless you get to it first, I will edit this and other articles over the next few days in light of our discussion, then comment here with the links. If at that point you are too uncomfortable with it, we can revert to present status. Cheers. Justaxn (talk) 20:26, 7 July 2015 (UTC)Reply

• I suggest you avoid acting unilaterally without gaining consensus for what is, at present, merely an individual opinion. Thewellman (talk) 20:49, 7 July 2015 (UTC)Reply

The proposal to remove certain parts of this article appears to be based upon belief this article should focus on statistics, uncertainty and flood. While the 100-year flood is a useful example of application of the first two subjects to the latter phenomenon, all three have separate articles. Suggesting that material on other aspects of this subject is inappropriate for this article would skew this article toward theory and neglect the practical problems of applying probability theory to this real-life situation. Thewellman (talk) 05:13, 8 July 2015 (UTC)Reply

• I don't see why at least some of the information (under discussion above) in this article here should be copied and/or transferred to one or more other Wikipedia articles. I spent some time on this section of the Flood article a while back, but it needs expansion for sure. The other likely candidates for article expansion appear to be Flood forecasting and Hydrological modelling with maybe some more "main article" links needed from here. While some explanation of some of the various factors that go into defining a return period like a 100-year flood seem necessary here in this article, I don't think that those descriptions need to be overly long. One can get a return period of 100-years or more in both short and longer-term flood scenarios. I would note that both the 100 & 500-year flood return periods are currently being used for publicly-available inundation mapping by the NWS, but I've never been enough of an expert in hydrology to understand fully all the uses and ins & outs of return periods myself. Guy1890 (talk) 06:28, 9 July 2015 (UTC)Reply

• Parts of the following titles in a previous version were moved to the more general article Flood#Principal types and causes. These remaining parts address precipitation frequency or models to calculate runoff from specified precipitation inputs, but not the 100-year flood as such. They might usefully be merged with Rain#Return_period, Hydrology#Modeling, Hydrological modeling, or Runoff model, but I leave that task for others. Justaxn (talk) 16:07, 25 July 2015 (UTC)Reply

Upslope factors: Most precipitation records are based on a measured depth of water received within a fixed time interval. Frequency of a precipitation threshold of interest may be determined from the number of measurements exceeding that threshold value within the total time period for which observations are available. Individual data points are converted to intensity by dividing each measured depth by the period of time between observations. This intensity will be less than the actual peak intensity if the duration of the rainfall event was less than the fixed time interval for which measurements are reported. Convective precipitation events (thunderstorms) tend to produce shorter duration storm events than orographic precipitation. Duration, intensity, and frequency of rainfall events are important to flood prediction. Short duration precipitation is more significant to flooding within small drainage basins.^[1]

Downslope factors: Water flowing downhill ultimately encounters downstream conditions slowing movement. The final limitation is often the ocean or a natural or artificial lake. Elevation changes such as tidal fluctuations are significant determinants of coastal and estuarine flooding. Less predictable events like tsunamis and storm surges may also cause elevation changes in large bodies of water.

Prediction: Statistical analysis requires all data in a series be gathered under similar conditions. Even without analyzing the statistical uncertainty of a given 100-year flood, scientists and engineers can decrease the uncertainty by using two practical rules. First, forecast an extreme event which is no more than double the number of observation years (e.g. from 27 observed river measurements, so a 50-year event can be estimated since 27×2=54, but not a 100-yr event). The second way to decrease the uncertainty of the extreme event is to forecast a value which is less than the maximum observed value (e.g. the maximum rainfall event on record is 5.25 inches/hour, so the 100-year storm event should be less than this). Note that these rules cannot help in estimating Q100 if the maximum observed flood (or storm) had a shorter recurrence interval.

A simple prediction model might be based upon observed flows within a fixed channel geometry.^[2] Alternatively, prediction may rely upon assumed channel geometry and runoff patterns using historical precipitation records. The rational method has been used for drainage basins small enough that observed rainfall intensities may be assumed to occur uniformly over the entire basin.

Extreme flood events often result from coincidence such as unusually intense, warm rainfall melting heavy snow pack, producing channel obstructions from floating ice, and releasing small impoundments like beaver dams.^[3] Coincident events may cause flooding outside the statistical distribution anticipated by simplistic prediction models.^[4]

This article appears to focus exclusively on flooding from riverine sources. However, the concept of a 100-year flood applies to flooding from lakes and oceans. Beyond only explicitly referring to riverine flooding, the issue manifests in various other forms, such as relating a 1% flood to flow (as opposed to elevation). Tfocker4 (talk) 01:10, 12 February 2016 (UTC)Reply

Good point. I've added a bit for balance in a few places. Please add other ideas as you see fit. Justaxn (talk) 00:04, 8 March 2016 (UTC)Reply

Is the probability of an X-year flood occurring in an X-year period actually binomial, or is it Poisson distributed?

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A 100-year flood can occur multiple times within a year. The expected value is 1%, which means that in the arithmetic mean there are 1% events every year, however this means that there is a change of about 0.01% that two or more events occur and in about 0.98% of the cases exactly one event happes a year. Therefore we have a total of about 0.99% that at least one event is occuring. The English literature, different to e.g. the German one, does not destinglish between that, and is incosistent.

• However, the expected value of the number of 100-year floods occurring in any 100-year period is 1.

does not agree with

• A 100-year flood is a flood event that has a 1 in 100 chance (1% probability) of being equaled or exceeded in any given year.

This differences are huge is huge the 2-year food. Yes we can round numbers in the 100year flood, but we have to be precise in how it is defined, and what is numerially derived from that.  — Johannes Kalliauer - contrib. 22:02, 11 April 2023 (UTC)Reply