Low-Flow Frequency Statistics at Gaging Stations

Low-flow frequency statistics are determined using the annual minimum mean flows for any given number of days (N-day low flows) during an annual period. The mean flow for each N-day period throughout the annual period is computed and the minimum value is used for that period. The series of annual minimum N-day values are then fit to a log-Pearson Type III distribution to determine the recurrence intervals (Riggs, 1972). The annual period referred to as a climatic year (April 1 through March 31) is often used in low-flow analyses because the annual low-flow period in most parts of the country occurs during the late summer and autumn months. Use of the climatic year allows for inclusion of the entire low‑flow period in the same year, whereas use of the traditional water year (October 1 through September 30) may artificially separate the low-flow period into two different years.

Updated relevant low-flow frequency statistics (1Q₁₀, 7Q₂, 7Q₁₀, and 30Q₅) were computed for 234 gaging stations located throughout Idaho and portions of the adjacent States (fig. 1). This included all of those gaging stations located in Idaho and those in adjacent States within about an 80‑mi buffer surrounding Idaho that, in general, had 10 or more years of record through water year 2003, exhibited little or no signs of trends, and were unaffected by regulations and/or diversions. A small number of gaging stations with fewer than 10 years of record were included in the analyses after the data were analyzed and found to contain a broad enough range of streamflow conditions that they would not bias the statistical results. Selected information for each gaging station included in the final dataset are presented in table 6 (at back of report) and the relevant low-flow frequency statistics for each gaging station are presented in table 7 (at back of report).

Streamflow data were analyzed for trends using Kendall’s tau hypothesis test. Trends in the data could introduce an element of error into the frequency analyses, since a major assumption is that annual low flows are independent and stationary over time. The Kendall’s tau test measures the monotonic relationship between two data sets, in this case, streamflow and time (Helsel and Hirsch, 1992). A relatively stringent P-value threshold of 2 percent (α = 0.02) was used in this study. Data from gaging stations that exhibited trends based on this criteria were analyzed further and compared to data from nearby gaging stations to determine inclusion or exclusion from the dataset.

Streamflow data were screened to prevent data affected by regulations and/or diversions from biasing the dataset. Decisions to include or exclude data from a specific gaging station were made using hydrologic judgment based on all available information regarding the occurrence, timing, and magnitude of regulations and diversions upstream of the gaging stations. No specific criteria were used. In general, all gaging stations with data affected by upstream regulations were removed from the dataset, as well as those with data affected by upstream diversions during typical low-flow periods. The information available was not always complete and the accuracy was questionable in some cases, especially with regard to magnitudes of upstream diversions. Therefore, it is possible that data affected by regulations or diversions could have been included in the final datasets. However, the overall effects on the data are believed to be minimal.

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