PUBLICATIONS Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE Large snowmelt versus rainfall events in the mountains 10.1002/2014JD022753 Steven R. Fassnacht1,2 and Rosemary M. Records3 Key Points: 1ESS-Watershed Science, Colorado State University, Fort Collins, Colorado, USA, 2Cooperative Institute for Research in the • Large daily snowmelt equals or 3 exceeds precipitation in the mountains Atmosphere, Fort Collins, Colorado, USA, Department of Geosciences, Colorado State University, Fort Collins, Colorado, USA • Daily precipitation equals or exceeds rainfall in the mountains Abstract While snow is the dominant precipitation type in mountain regions, estimates of rainfall are used for design, even though snowmelt provides most of the runoff. Daily data were used to estimate the 10 and Supporting Information: • Readme 100 year, 24 h snowmelt, precipitation, and rainfall events at 90 Snow Telemetry stations across the Southern • Table S1 Rocky Mountains. Three probability distributions were compared, and the Pearson type III distribution yielded the most conservative estimates. Precipitation was on average 33% and 28% more than rainfall for Correspondence to: the 10 and 100 year events. Snowfall exceeded rainfall at most of the stations and was on average 53% and S. R. Fassnacht, [email protected] 38% more for the 10 and 100 year events. On average, snowmelt was 15% and 8.9% more than precipitation. Where snow accumulation is substantial, it is recommended that snowmelt be considered in conjunction with rainfall and precipitation frequencies to develop flood frequencies. Citation: Fassnacht, S. R., and R. M. Records (2015), Large snowmelt versus rainfall events in the mountains, J. Geophys. Res. 1. Introduction Atmos., 120, 2375–2381, doi:10.1002/ 2014JD022753. Extreme rainfall events are considered to be more intense than snowmelt and depth duration frequencies of rainfall or precipitation [e.g., Perica et al., 2013] and are used to predict and model floods, especially in Received 22 OCT 2014 watersheds with poor streamflow records [U.S. Soil Conservation Service, 1973]. However, in cold climates and Accepted 20 FEB 2015 at high elevations, seasonal snow accumulation magnitude and melt rate can also influence flood hazards Accepted article online 26 FEB 2015 Published online 28 MAR 2015 [Hirschboeck et al., 2000]. In the United States, some examples of high-damage snowmelt-related floods occurred on the Red River, North Dakota and Minnesota in 1997 (U.S. Geological Survey, A History of Flooding in the Red River Basin, U.S. Department of the Interior, General Information Product 55, 2007, available at http://pubs.usgs.gov/gip/2007/55/pdf/finalWebGIP55.pdf) costing US$3.5 billion in damage [Shelby, 2004] and in the Appalachian region between 1993 and 2003, with over 15 separate floods causing >US$50,000 each in damages [Graybeal and Leathers, 2006]. In areas where floods occur from more than one hydrologic process (e.g., from both rainfall and snowmelt), it may not be appropriate to group all peak flow data into a single statistical population for flood frequency analysis [Waylen and Woo, 1982]. The government standard on the precipitation frequency estimates recently published includes both rainfall and precipitation frequency estimates but not snowmelt estimates for the state of Colorado [Perica et al., 2013]. However, previous paleohydrology and streamflow studies have shown that floods at higher elevations in this region are caused by snowmelt, not rain [e.g., Jarrett, 1990; England et al., 2010]. Above a threshold estimated at about 2300 m, there is a large decrease in the magnitude of extreme rainfall [Jarrett, 1990]; intensities of snowmelt approach those of rainfall [Payton and Brendecke, 1985], and there is an abrupt transition from rainfall- to melt-dominated stream peak flows, although rainfall flood peaks are larger on a per unit area basis [Jarrett, 1990; England et al., 2010]. Incomplete understanding of these elevation thresholds and their influence on regional hydrology could have a direct effect on engineering designs and land use planning in the mountains. Should infrequent snowmelt events prove to be large, using rainfall or precipitation frequencies alone from high-elevation stations to assess flood probability might underestimate the magnitude of potential runoff events. To our knowledge, the magnitude of extreme snowmelt has not been compared to extreme rainfall or precipitation events in the Southern Rocky Mountain region of Wyoming, Colorado, and New Mexico. For flood frequency assessments, comparison of snowmelt to rainfall amounts is more relevant than comparisons of snowmelt to precipitation, because the latter can include snowfall which is not immediately available for runoff generation. However, we also analyze precipitation frequencies to allow our results to be readily compared to existing precipitation frequency guidelines [e.g., Perica et al., 2013]. In this paper, we quantify the magnitude of precipitation, rainfall, and snowmelt amounts for 24 h durations and 10 and 100 year return periods at higher-elevation locations across the Southern Rocky Mountain region FASSNACHT AND RECORDS ©2015. American Geophysical Union. All Rights Reserved. 2375 Journal of Geophysical Research: Atmospheres 10.1002/2014JD022753 Figure 1. Ratio of (a) the 100year, 24h snowmelt to the 100year, 24h precipitation and (b) the 100year, 24h rainfall for 90 SNOTEL stations across the Southern Rocky Mountains, USA. Data points are derived using the Pearson type III distributions for 1982–2013 (described in text). Values <1.0 show that snowmelt is less than precipitation (or rainfall); values ≥1.0 show that snowmelt exceeds precipitation (or rainfall). Stations that show approximately the same ratio between Figures 1a and 1b indicate that the 100 year, 24 h precipitation is similar to the 100 year, 24 h rainfall. Stations that show a smaller ratio (warmer color) in Figure 1b than in Figure 1a indicate that the 100year, 24h rainfall exceeds the 100 year, 24 h precipitation. to (1) compare the relative magnitudes of rainfall to precipitation events, (2) compare the relative magnitudes of snowmelt to precipitation events, and (3) compare the relative magnitudes of snowmelt to rainfall events. We are interested in water added to the system from melt and/or rain that has the potential to contribute to overland flow, groundwater recharge, and/or streamflow. 2. Methods We used the daily time series of Snow Telemetry (SNOTEL) precipitation and snow water equivalent (SWE) data from 90 stations in the Southern Rocky Mountains, USA, for the years 1982–2013. All stations had at least 26 years of record and most a complete 32 years. Stations ranged from ~2300 to 3500 m in elevation, averaged ~3000 m, and were located on both western (48 stations) and eastern sides of the Continental Divide (42 stations) (Figure 1 and Table S1 in the supporting information). At each station and for each water year (October of the previous year through September), we calculated the following to derive three annual time series: (1) the maximum daily precipitation, (2) the maximum daily rainfall (precipitation when SWE equaled 0), and (3) the maximum daily snowmelt (decrease in SWE). Since stationarity of the data is an underlying assumption of most frequency analyses [Khaliq et al., 2006], we tested each of the annual time series for trends with the nonparametric Mann-Kendall test at the 5% significance level. Where trends were significant, we identified the slope of the trend (Sen’s slope). For annual time series where there was a significant trend for a particular station, we detrended each value in the series using the Sen’s slope and maintained the time series average. We then calculated the skew coefficient for each station for each of the three detrended annual time series. We used the Pearson type III distribution to evaluate the magnitude of precipitation, rainfall, and snowmelt events for 10 and 100 year (24 h) return periods using the skew to determine the K factor for each time series [Chow, 1951; Hoffmann et al., 1981; Interagency Advisory Committee on Water Data, 1982]. Durations of up to 24 h are of most interest for projects designed to peak flows [Perica et al., 2013]. The L moment method [Hosking and Wallis, 1997] was not used since it is utilized for regional analysis, while the present study FASSNACHT AND RECORDS ©2015. American Geophysical Union. All Rights Reserved. 2376 Journal of Geophysical Research: Atmospheres 10.1002/2014JD022753 examined each station individually. Since the focus of this study was to compare the magnitude of snowmelt to precipitation and to rainfall, we also evaluated the effect of using different distributions (the Log-Pearson type III and the Gumbel) on the estimated magnitude of precipitation, rainfall, and snowmelt events as well as the magnitude of event ratios. The results presented here are for the Pearson type III distribution except where noted. 3. Results and Discussion Figure 2. The 10 and 100 year, 24 h rainfall versus precipitation for 90 SNOTEL stations across the Southern Rocky Mountains, USA. Data points are from There were significant decreasing Pearson type III distributions for 1982–2013 (described in text). trends in annual maximum daily snowmelt and rainfall at 31% and 6% of SNOTEL stations, respectively, and significant decreasing or increasing trends in annual maximum daily precipitation at 8% of the stations. Trends were small (À14 to À6.4 mm/decade for snowmelt, À4.8 to À2.7 mm/decade for rainfall, and À6.0 to +5.1 mm/decade for total precipitation). Detrending had little effect on the estimated events; averaged among the 90 stations, the original snowmelt annual time series 10 and 100 year events were 0.07 mm and 1.55 mm more than the detrended values, and coefficients of determination between original and detrended values were greater than 0.97 for both of the 10 and 100 year snowmelt events. Effects of detrending on rainfall and total precipitation were smaller than for snowmelt.