Author:
Mukherjee Sourav,Amatya Devendra M.,Jalowska Anna M.,Campbell John L.,Johnson Sherri L.,Elder Kelly,Panda Sudhanshu,Grace Johnny M.,Kikoyo Duncan
Abstract
AbstractUrgency of Precipitation Intensity-Duration-Frequency (IDF) estimation using the most recent data has grown significantly due to recent intense precipitation and cloud burst circumstances impacting infrastructure caused by climate change. Given the continually available digitized up-to-date, long-term, and fine resolution precipitation dataset from the United States Department of Agriculture Forest Service’s (USDAFS) Experimental Forests and Ranges (EF) rain gauge stations, it is both important and relevant to develop precipitation IDF from onsite dataset (Onsite-IDF) that incorporates the most recent time period, aiding in the design, and planning of forest road-stream crossing structures (RSCS) in headwaters to maintain resilient forest ecosystems. Here we developed Onsite-IDFs for hourly and sub-hourly duration, and 25-yr, 50-yr, and 100-yr design return intervals (RIs) from annual maxima series (AMS) of precipitation intensities (PIs) modeled by applying Generalized Extreme Value (GEV) analysis and L-moment based parameter estimation methodology at six USDAFS EFs and compared them with precipitation IDFs obtained from the National Oceanic and Atmospheric Administration Atlas 14 (NOAA-Atlas14). A regional frequency analysis (RFA) was performed for EFs where data from multiple precipitation gauges are available. NOAA’s station-based precipitation IDFs were estimated for comparison using RFA (NOAA-RFA) at one of the EFs where NOAA-Atlas14 precipitation IDFs are unavailable. Onsite-IDFs were then evaluated against the PIs from NOAA-Atlas14 and NOAA-RFA by comparing their relative differences and storm frequencies. Results show considerable relative differences between the Onsite- and NOAA-Atlas14 (or NOAA-RFA) IDFs at these EFs, some of which are strongly dependent on the storm durations and elevation of precipitation gauges, particularly in steep, forested sites of H. J. Andrews (HJA) and Coweeta Hydrological Laboratory (CHL) EFs. At the higher elevation gauge of HJA EF, NOAA-RFA based precipitation IDFs underestimate PI of 25-yr, 50-yr, and 100-yr RIs by considerable amounts for 12-h and 24-h duration storm events relative to the Onsite-IDFs. At the low-gradient Santee (SAN) EF, the PIs of 3- to 24-h storm events with 100-yr frequency (or RI) from NOAA-Atlas14 gauges are found to be equivalent to PIs of more frequent storm events (25–50-yr RI) as estimated from the onsite dataset. Our results recommend use of the Onsite-IDF estimates for the estimation of design storm peak discharge rates at the higher elevation catchments of HJA, CHL, and SAN EF locations, particularly for longer duration events, where NOAA-based precipitation IDFs underestimate the PIs relative to the Onsite-IDFs. This underscores the importance of long-term high resolution EF data for new applications including ecological restorations and indicates that planning and design teams should use as much local data as possible or account for potential PI inconsistencies or underestimations if local data are unavailable.
Publisher
Springer Science and Business Media LLC
Subject
General Environmental Science,Safety, Risk, Reliability and Quality,Water Science and Technology,Environmental Chemistry,Environmental Engineering
Reference88 articles.
1. Adams MB, Loughry L (2008) Experimental forests and ranges of the USDA Forest Service. General Technical Rep. No. NE-321. Washington, DC: USDA, Forest Service, Northeastern Research Station.
2. Adeel Z, Alarcón AM, Bakkensen L, Franco E, Garfin GM, McPherson RA, Méndez K, Roudaut MB, Saffari H, Wen X (2020) Developing a comprehensive methodology for evaluating economic impacts of floods in Canada, Mexico and the United States. Int J Disaster Risk Reduct 50:101861. https://doi.org/10.1016/j.ijdrr.2020.101861
3. AghaKouchak A, Nasrollahi N (2010) Semi-parametric and Parametric Inference of extreme value models for rainfall data. Water Resour Manage 24:1229–1249. https://doi.org/10.1007/s11269-009-9493-3
4. Alexander RR, Watkins RK (1977) The Fraser experimental forest, Colorado. Department of agriculture, forest service, Rocky Mountain Forest and Range
5. Amatya DM, Walega A (2020) Long-term data–the key for evaluating runoff peak discharge estimation tools and parameters for watersheds on forest lands. Adv Civil Eng Technol. https://doi.org/10.31031/ACET.2020.04.000584