Extreme values help to get insight into the upper and lower bounds, form and equations associated with frequency curves, and for some things have great importance. At other times, when conducting statistical or other analyses, these extreme values can have or contribute to a high degree of variability, and be frustrating to explain as whether an important value exists in characterizing some specific relationship, or should be explained as an outlier that maybe was a mistake, error, or lacks importance, needs explanation and/or should be disregarded with or without justification. As far as publications with extreme values, it would be unusual to have enough from one area or station to have much. There are a few publications that use extreme values for a region or physiographic area such as developing and using envelop curves, which plots the extreme flood from area stream gauging stations by watershed size, and the enveloping curve over all these points helps to display the historic extremes of record for a certain time period. In a few instances, they may plot some paleofloods or other extremes that have been estimated, but not actually measured. Luna Leopold wrote a paper that discussed sediment extremes, found not to be in rainy, wet periods when vegetation in SWUSA covered the landscape, but during dry periods with little land cover. Extremes dont always occur as you might expect. Near lethal stream temperatures may occur and should kill fish in river, but the cooler tributies sometimes provide refuge areas where fish congregate to survive. The Wagon Wheel Gap, Colorado studies in the early 1900s found desired benefits in water yield increases from clearcutting, but concluded the practice was not worthwhile because of the sediment generated from the clearing practices. Extreme tides, storm surges as well as tsunami can produce unexpected effects, but the frequency and extent in estimating these help to define coastal flood frequency maps, which has publication worthiness. Measuring, estimating, designing for extremes can be some of the most important work.

William Hansen above provides a nice answer.

Rainfall Intensity, Frequency, Duration (IFD) curves used for hydrologic design of hydraulic structures, erosion control, etc are based on historical records of extreme rainfall values. In my experience, leading the development, and publication of NOAA Atlas 14, Precipitation Frequency Atlas of the United States, there are a number of issues I'll raise here:

1. There are few places in the world where comprehensive, reliable, publicly available, and up-to-date IFD curves exist. There is a need to extend such estimates.

2. State of the art relies on an assumption of a stationarity. There have been a variety of attempts to account for future climate change but there is nothing I'm aware of that satisfactorily answers the question while matching properly analyzed historical trends. Such matching must account for trends at a full range of durations and frequencies used by engineers for design, to be useful.

3. Even if one were able to determine trends in the historical data, one must then relate those trends to meaningful statistics from estimates of historical and future climate change. Given the uncertainty of future climate change estimates, this presents a difficulty. It may well be that the errors associated with estimating IFD itself significantly outweigh the range of historical trends at durations and frequencies relevant to hydrologic design.

4. There are meaningful differences in the definition of rainfall frequency between the climate and hydrologic communities and within the climate community itself, which obscure this issue.

5. I'm not aware of successful approaches to incorporate time based trend into L-moment statistics, used in most state of the art approaches. The math is difficult. A number of alternative approaches to L-moment statistics have been tried such as maximum likelihood estimation (MLE), however MLE addresses a fundamentally different conception of error and as a result doesn't match the results derived using L-moments, even without modification for trend.

6. Rainfall extremes that are in the range required for hydrologic design are "rare" and so it is important that the historical data we do have is properly quality controlled. This is not a trivial task. The results of such quality control should be made publicly available to allow peer review.

7. The error associated with derivation of IFD grows large as the frequency becomes more rare. Some have discounted this issue and extrapolate IFD curves beyond reasonably rare frequencies despite the range of the error. Others have made claims to be able to reduce these errors. Such approaches must be peer reviewed and verified.

8. Rainfall frequency is based on rainfall, whereas precipitation frequency accounts for all types of precipitation. In locations where precipitation types such as snow contribute significantly, it must be accounted for. However observations of rare snow accumulation events generally present greater quality problems than for rainfall observations. Furthermore, snow does not immediately melt and contribute to runoff in the same manner as rainfall. This introduces an additional difficulty in estimating runoff, for example in hydraulic design of roadways in Alaska.

9. Extremely rare rainfall values are critical in the estimation of probable maximum precipitation (PMP) used in the design of large dams. The meteorological rainfall producing mechanisms that produce extreme rainfall are difficult to model at appropriate time and space scales for hydrologic design. However there is some recent work that appears to produce reasonable results in some locations and cases. There is much work that is yet to be done in this area.

Hansen and Bonnin provided comprehensive answers. In addition, you can consult this book:

"Extreme Hydrology and Climate Variability"

https://www.sciencedirect.com/book/9780128159989/extreme-hydrology-and-climate-variability

Hansen and Bonnin have given good insights - mainly from a scientific view point. From a practitioner's viewpoint, I would note that the construction of future IDF curves is based on several other steps: generating and selecting climate scenarios, downscaling climate data, using the climate scenario to generate rainfall series, analyzing the rainfall series to construct IDF curves. Needless to say, the accuracy, reliability and utility of IDF curves derived in such a fashion will be highly dependent on the preceding calculations. The question is: can such IDF curves be used for any practical purpose? I guess not. At least I have not seen any so far.

Regarding the possibility of publication, it is very likely you will be able to publish your investigation. The proliferation of scientific 'journals' almost guarantees that.