01-09-13 *NRCS-CO* Colorado Water Supply Outlook Report January 1, 2013…
Posted by Brian Allmer on January 9, 2013
The water year got off to a very slow start in Colorado. With winter storm tracks failing to favor us, snowpack and mountain precipitation were tracking well below normal throughout October and November. Winter finally arrived to Colorado in mid December and conditions steadily improved throughout the month. Unfortunately it was not quite enough, and as of January 1, snowpack readings remain below normal in all of the state’s major river basins. Due to the dry start to the water year, water supplies are currently expected to be below normal across the state this spring and summer. Adding to the water supply concerns, statewide reservoir storage is well below average as a result of last year’s poor snowpack and drought conditions. While it is still early in the season and anything can happen, water users should pay close attention to this winters weather patterns as well as the state’s snowpack and plan accordingly.
Dry conditions across Colorado during the fall and early winter season have resulted in below normal snowpack totals statewide. The storm systems that moved across the state in mid to late December greatly improved statewide totals; boosting the statewide snowpack from just 36 percent of normal on December 1 to 70 percent of normal on January 1. While this was a welcome change to the persisting dry weather patterns, as you can see, it was not nearly enough to bring statewide snowpack totals to near normal conditions. Current readings are only 91 percent of last year’s January 1 readings and this year’s January 1 snowpack replaced 2012 as the fourth lowest recorded in the last 32 years. The highest snowpack readings, as a percent of normal, are in the combined Yampa, White and North Platte basins. They recorded a snowpack at 85 percent of normal as of January 1. The lowest reading statewide is 61 percent of normal recorded in the Arkansas basin. In general, the Colorado, Gunnison and Yampa, White and North Platte basins have a slightly better snowpack than they had last year at this same time. The South Platte, Arkansas, Upper Rio Grande and combined southwest basins (San Juan, San Miguel, Animas, & Dolores) have received less snow this year compared to what they had accumulated last year on January 1. Given the current snowpack deficit, the state needs to receive above normal snowfall over the next few months in order to reach normal conditions by spring.
Precipitation in the mountains of Colorado was sparse during October, November, and the first part of December. Statewide monthly precipitation totals measured at SNOTEL sites were just 50 percent of average for October, and only 41 percent of average for November. The state finally received some moisture in mid December and total precipitation for the month of December ended up at 112 percent of average. Conditions were fairly consistent across the state during these months, with some variability during December. Monthly precipitation for December ranged from 99 percent of average in the Arkansas basin to 123 percent of average in the combined Yampa, White and North Platte basins. Year to date precipitation totals reflect the dry conditions in October and November. Statewide totals as of January 1 are just 68 percent of average. The combined San Miguel, Dolores, Animas, and San Juan basins have received the lowest precipitation, as a percent of average, at 59 percent of average. The Yampa, White and North Platte basins came in with the highest totals on January 1, as a percent of average, at 81 percent of average.
How forecasts are made
Most of the annual streamflow in the western United States originates as snowfall that has accumulated in the mountains during the winter and early spring. As the snowpack accumulates, hydrologists estimate the runoff that will occur when it melts. Measurements of snow water equivalent at selected manual snow courses and automated SNOTEL sites, along with precipitation, antecedent streamflow, and indices of the El Niño / Southern Oscillation are used in computerized statistical and simulation models to prepare runoff forecasts. These forecasts are coordinated between hydrologists in the Natural Resources Conservation Service and the National Weather Service. Unless otherwise specified, all forecasts are for flows that would occur naturally without any upstream influences. Forecasts of any kind, of course, are not perfect. Streamflow forecast uncertainty arises from three primary sources: (1) uncertain knowledge of future weather conditions, (2) uncertainty in the forecasting procedure, and (3) errors in the data. The forecast, therefore, must be interpreted not as a single value but rather as a range of values with specific probabilities of occurrence. The middle of the range is expressed by the 50% exceedance probability forecast, for which there is a 50% chance that the actual flow will be above, and a 50% chance that the actual flow will be below, this value. To describe the expected range around this 50% value, four other forecasts are provided, two smaller values (90% and 70% exceedance probability) and two larger values (30%, and 10% exceedance probability). For example, there is a 90% chance that the actual flow will be more than the 90% exceedance probability forecast. The others can be interpreted similarly.
The wider the spread among these values, the more uncertain the forecast. As the season progresses, forecasts become more accurate, primarily because a greater portion of the future weather conditions become known; this is reflected by a narrowing of the range around the 50% exceedance probability forecast. Users should take this uncertainty into consideration when making operational decisions by selecting forecasts corresponding to the level of risk they are willing to assume about the amount of water to be expected. If users anticipate receiving a lesser supply of water, or if they wish to increase their chances of having an adequate supply of water for their operations, they may want to base their decisions on the 90% or 70% exceedance probability forecasts, or something in between. On the other hand, if users are concerned about receiving too much water (for example, threat of flooding), they may want to base their decisions on the 30% or 10% exceedance probability forecasts, or something in between. Regardless of the forecast value users choose for operations, they should be prepared to deal with either more or less water. (Users should remember that even if the 90% exceedance probability forecast is used, there is still a 10% chance of receiving less than this amount.) By using the exceedance probability information, users can easily determine the chances of receiving more or less water.