Probable maximum precipitation (PMP) is considered the maximum precipitation possible for a location/area over a specific duration at a particular time of year. The National Weather Service, Army Corps of Engineers, Bureau of Reclamation, among others, developed the Hydrometeorological Reports’ (HMRs) series specifically for calculating the PMP for different regions across the United States. In addition, site-specific, state level, and regional PMP analyses continue to be conducted across the United States to update existing estimates from the HMRs – some of which are 40+ years old (e.g., HMR51, 1978).

The staff at Weather & Water have conducted: site-specific PMP analyses for reservoirs across the United States; served as a member on regional extreme precipitation studies (Colorado-New Mexico); been the Agency Technical Reviewer for multiple US Army Corps of Engineers’ PMP projects; and, calculated the probability of PMP for nuclear and dam safety applications. These PMP estimates and associated precipitation patterns are key to producing PMFs for design criteria across the nation and abroad.  Let us help your firm with either or both!


The Hydrometeorological Design Studies Center, a division of NOAA, has published NOAA Atlas 2 and Atlas 14 for the United States, providing point-precipitation frequency at locations for probabilities of 1-in-1 to 1-in-1000 years. In recent years, developments in the production of precipitation-frequency analyses has led to modernized methods for assessing frequency for different storm types (i.e., durations of storms that drive local climate). With extensive expertise in statistical methods,

Weather & Water has developed storm typing methodology using quantitative method techniques above-and-beyond others in the field. Automation of these processes through machine learning algorithms allows ease of application for your project across the global domain. We continue to implement the L-Moments-based methods of NOAA Atlas 14 while improving the selection and application of these methods through filters. We can perform site-specific, basin-specific, or regional studies from data collection through QA-QC and extreme value fitting. Weather & Water can also perform hydrologic frequency for you using similar well-known techniques applied at agencies such as the Army Corps of Engineers and Bureau of Reclamation.


In the image above, there is an example of an F-N chart – a representation of the probability of a specific event (e.g., flood) vs. a quantity of loss (e.g., lives lost, economic impacts, etc.). The incremental change in impacts relative to a specific event or level of an event is key to decision-making processes. There may be a few – to even as many as hundreds – variables to consider when making an engineering decision for design of a structure, corrective action, or issue evaluation.

Weather & Water has a variety of tools to support risk-informed decision-making (RIDM) processes and has participated in Probabilistic Flood Hazards Workshops at the federal level multiple years over the past decade. With access to a variety of stochastic modeling software coupled with frequency-based tools mentioned above – we can serve your every need in risk assessments.


The impacts to a particular system – whether that be a fishery, a neighborhood, a city, a country, etc – can be assessed through a combination of water resources data and geographic information (e.g., Census data, zoning laws, building codes, among others).

The Data Acquisition, Archival, and Reformatting Tool (DAART) in combination with the Comprehensive Reanalysis, Analysis, and Forecast Tool for Engineering Applications (CRAFTEA) offer a seamless solution for combining diverse datasets through complex statistical methods to generate impact-based information to your decision-making process. Couple these tools with existing modeling software – and the wealth of criteria you seek can be captured for basin-wide planning studies, updates to local building practices, and optimization of operations to maximize value and minimize risk.