Comparison of on-site versus NOAA’s extreme precipitation intensity-duration-frequency estimates for six forest headwater catchments across the continental United States

Abstract Urgency of Precipitation Intensity-Duration-Frequency (IDF) estimation using the most recent data has grown significantly due to intense precipitation and cloud burst circumstances impacting infrastructure caused by climate change. Given continually available digitized up-to-date, long-term, fine resolution dataset from United States Department Agriculture Forest Service’s (USDAFS) Experimental Forests Ranges (EF) rain gauge stations, it is both important relevant develop IDF onsite (Onsite-IDF) that incorporates time period, aiding in design, planning forest road-stream crossing structures (RSCS) headwaters maintain resilient ecosystems. Here we developed Onsite-IDFs for hourly sub-hourly duration, 25-yr, 50-yr, 100-yr design return intervals (RIs) annual maxima series (AMS) intensities (PIs) modeled applying Generalized Extreme Value (GEV) analysis L-moment based parameter methodology at six USDAFS EFs compared them with IDFs obtained National Oceanic Atmospheric Administration Atlas 14 (NOAA-Atlas14). A regional frequency (RFA) was performed where multiple gauges are available. NOAA’s station-based were estimated comparison RFA (NOAA-RFA) one NOAA-Atlas14 unavailable. then evaluated against PIs NOAA-RFA comparing their relative differences storm frequencies. Results show considerable between Onsite- (or NOAA-RFA) these EFs, some which strongly dependent on durations elevation gauges, particularly steep, forested sites H. J. Andrews (HJA) Coweeta Hydrological Laboratory (CHL) EFs. At higher HJA EF, underestimate PI RIs amounts 12-h 24-h duration events Onsite-IDFs. low-gradient Santee (SAN) 3- RI) found be equivalent more frequent (25–50-yr as dataset. Our results recommend use Onsite-IDF estimates peak discharge rates catchments HJA, CHL, SAN EF locations, longer events, NOAA-based This underscores importance long-term high new applications including ecological restorations indicates teams should much local possible or account potential inconsistencies underestimations if