Scientific Investigations Report 2006–5274
U.S. GEOLOGICAL SURVEY
Scientific Investigations Report 2006–5274
The U.S. Geological Survey (USGS), in cooperation with the Bureau of Reclamation (Reclamation), developed a precipitation-runoff model for the Salmon Creek Basin that can be used to simulate daily unregulated streamflows in the basin. The precipitation-runoff model is a component of a Decision Support System (DSS) that includes a water-operations model Reclamation plans to develop to study the water resources of the Salmon Creek Basin. The DSS will be similar to the DSS that Reclamation and the USGS developed previously for the Yakima River Basin in central southern Washington. The precipitation-runoff model that was developed is a modified version of the Precipitation-Runoff Modeling System (PRMS; Leavesley and others, 1983) and was run within the Modular Modeling System (MMS; Leavesley and others, 1996). The model can be used to simulate historical streamflows and streamflows for as far as 1 year in the future using the Extended Streamflow Prediction (ESP) technique in MMS.
Model input time series were based on historical records of daily precipitation and daily minimum and maximum air temperatures for three National Weather Service stations, a Natural Resources Conservation Service SNOTEL station, a Bureau of Reclamation AgriMet station, and a Bureau of Reclamation Hydromet station. Model-calibration and testing time series were estimated records of monthly mean unregulated streamflow for Salmon Creek at Conconully Dam [referred to as uncorrected unregulated streamflow (UUS) in this study] based on reservoir outflows and storage changes (Dames and Moore,1999; U.S. Department of Energy, 2004; this study) and records of daily snowpack water-equivalent for the SNOTEL station. A second estimated time series of monthly mean unregulated streamflow for Salmon Creek at Conconully Dam was generated by adding estimates of ground-water losses and evaporative losses to the uncorrected time series [referred to as corrected unregulated streamflow (CUS) in this study]. The total of the corrections was about 9 percent of the long-term mean uncorrected unregulated streamflow. The time series of estimated monthly mean uncorrected unregulated streamflow has several potential sources of error (Dames and Moore, 1999; U.S. Department of Energy, 2004). However, the estimates were the best available and were used in this study as a surrogate for the missing long-term unregulated streamflows for Salmon Creek at Conconully Dam.
Salmon Creek Basin was subdivided into 179 Modeling Response Units (MRUs), each with similar physical, soil, and vegetation characteristics. Initial model parameters were assigned by applying the GIS (Geographic Information System) Weasel program (Viger and others, 1998), computing values from measured data, and using parameters from the Methow River precipitation-runoff model (Ely and Risley, 2001; Ely, 2003). The precipitation-runoff model was calibrated for water years 1950–89 (a water year starts October 1 and ends September 30) and tested for water years 1990–96. A subset of the initial model parameters was adjusted during the calibration process with the goal of simulating monthly unregulated streamflows for Salmon Creek at Conconully Dam that were more than the estimated UUS and less than the estimated CUS.
Model calibration and testing indicate that daily streamflows simulated using the precipitation-runoff model described in this report should be used only to analyze historical and forecasted annual mean and April–July mean streamflows for Salmon Creek at Conconully Dam. Because of the paucity of model input data and uncertainty in the estimated unregulated streamflows, the model is not adequately calibrated and tested to estimate monthly mean streamflows for individual months, such as during low-flow periods, or for shorter periods such as during peak flows.
For the calibration period, water years 1950–89, both the simulated mean annual streamflow and the simulated mean April–July streamflow compare well with the estimated values for UUS and CUS. The simulated mean annual streamflow exceeds UUS by 5.9 percent and is less than CUS by 2.7 percent. Similarly, the simulated mean April–July streamflow exceeds UUS by 1.8 percent and is less than CUS by 3.1 percent. A comparison of the estimated and simulated mean monthly streamflows, however, shows that streamflow is significantly undersimulated during the low-flow, baseflow-dominated months of November through February when simulated monthly streamflows are as much as 57.2 percent less than UUS and significantly oversimulated during August and September when simulated monthly streamflows are as much as 193.6 percent more than CUS. During the low-flow months, however, estimated mean monthly streamflow is only a small percentage of the estimated mean annual streamflow and absolute errors are relatively small even though the percentages of error are large.
The precipitation-runoff model was tested for water years 1990–96 using model input time series for the same climate stations as for model calibration, except that measured temperatures were used for the AgriMet station instead of synthetic temperatures. The data set used for this testing is referred to as “TESTING 1.” For TESTING 1, the model simulated a close fit for the mean annual streamflow and a good fit for the mean April–July streamflow. The simulated mean annual streamflow exceeds UUS by 10.7 percent and is the same as CUS. The simulated mean April–July streamflow exceeds UUS by 5.1 percent and is less than CUS by 0.8 percent. The precipitation-runoff model was tested three more times to determine if adding different combinations of daily precipitation for the real-time AgriMet and SNOTEL stations to the input time series for TESTING 1 would improve the fit between estimated and simulated streamflows for water years 1990–96. For all three tests, the simulated mean annual and mean April–July streamflows were significantly larger than the estimated streamflows. The oversimulation was largest when precipitation for the AgriMet and SNOTEL stations was added (the simulated mean annual and mean April–July streamflows exceeded CUS by 20.7 percent and 21.3 percent, respectively) and smallest when precipitation for the Agrimet station was added (the simulated mean annual and mean April–July streamflows exceeded CUS by 6.0 percent and 5.3 percent, respectively). The testing results indicate that the precipitation-runoff model is adequately calibrated for the purpose of simulating annual mean and April–July mean streamflows using the input time series used for model calibration and testing. The addition of precipitation data for the AgriMet and/or SNOTEL stations to the input time series results in oversimulated annual mean and April–July mean streamflows.
A final comparison between estimated and simulated streamflows was made for the entire simulation period, water years 1950–2004. The input time series used for this simulation is referred to as “COMPOSITE” and is identical to the input time series for model calibration (water years 1950‑89) and for TESTING 1 (water years 1990–96). For water years 1997–2004, the input time series consists of data for the same climate stations as CALIBRATION and TESTING 1, except that for water years 2000–04 daily precipitation and minimum and maximum air temperatures for one of the stations were replaced with data for the nearby real-time Hydromet station that were assumed to be equivalent. For COMPOSITE, the model simulated a good fit for the mean annual streamflow and a close fit for the mean April–July streamflow. The simulated mean annual streamflow exceeds UUS by 2.8 percent and is less than CUS by 5.7 percent. The simulated mean April–July streamflow is less than UUS by 0.7 percent and less than CUS by 5.6 percent. For forecasting purposes, Reclamation will expand the COMPOSITE data set to include the most recent real-time precipitation and air-temperature data for the Hydromet station and the most recent real-time air-temperature data for the AgriMet station.
During the driest 4 water years (1964, 1977, 1979, and 1985) and the wettest 4 water years (1951, 1971, 1982, and 1983) of the 40-year calibration period, the model simulated poor fits for the annual mean streamflows and April–July mean streamflows based on the percentages of errors with respect to UUS and CUS. However, during the driest 4 water years, the large percentages of error are with respect to relatively small streamflows for Salmon Creek at Conconully Dam. During the driest 4 water years, the absolute errors ranged from an undersimulation of annual mean streamflow with respect to UUS of 8.0 ft3/s (46.8 percent error) in water year 1964 to an oversimulation of annual mean streamflow with respect to CUS of 3.4 ft3/s (31.2 percent error) in water year 1985. The absolute errors ranged from an undersimulation of April–July mean streamflow with respect to UUS of 13.6 ft3/s (39.7 percent error) in water year 1964 to an oversimulation of April–July mean streamflow with respect to CUS of 4.2 ft3/s (24.0 percent error) in water year 1985. During the wettest 4 water years, the absolute errors ranged from an undersimulation of annual mean streamflow with respect to UUS of 2.8 ft3/s (4.7 percent error) in water year 1951 to an oversimulation of annual mean streamflow with respect to CUS of 26.6 ft3/s (73.1 percent error) in water year 1971. The absolute errors ranged from an undersimulation of April–July mean streamflow with respect to UUS of 19.8 ft3/s (13.1 percent error) in water year 1951 to an oversimulation of April–July mean streamflow with respect to CUS of 74.1 ft3/s (75.6 percent error) in water year 1971.
No data were available to test the accuracy of simulated streamflows for lower Salmon Creek. Thus, although the simulated streamflows appear reasonable, the model should not be relied on to analyze historical and forecasted streamflows for Salmon Creek downstream of Conconully Dam. Instead, simulated streamflows for Salmon Creek at Conconully Dam should be considered a base estimate of streamflows that can be expected in lower Salmon Creek. The estimated streamflows may be reduced in reaches of lower Salmon Creek that are losing water and increased in reaches that are gaining water or that receive runoff from tributaries in lower Salmon Creek subbasin.
The precipitation-runoff model described in this report is expected to be used for simulating historical streamflows and ESP forecasting of streamflows. ESP forecasting requires accurate simulation of initial hydrologic conditions on the basis of real-time precipitation and air-temperature data, and forecasting the probability of streamflows for as far as 1 year in the future by assuming that historical records of daily precipitation and air temperature will recur with the same probability as in the past. The historical record that can be used for ESP forecasts includes water years 1950–2004 and can be extended to the present by adding the most recent real-time data. The simulation of historical streamflows, initial hydrologic conditions, and the ESP forecast rely on the calibrated precipitation-runoff model described in this report and are subject to the model limitations that result from model error, data error, and parameter error.
The precipitation-runoff model described in this report could be improved in the future if additional data were collected. Specifically, it is suggested that year-round collection of climate data be resumed at Conconully station and that a stream gage be installed in Salmon Creek downstream of the spillway of Conconully Dam to measure all runoff from the upper Salmon Creek Basin. Improved availability of climate and streamflow data for the Salmon Creek Basin should enable improved calibration of the precipitation-runoff model, which would make the model a more reliable component of the DSS that Reclamation plans to use to study the water resources of the Salmon Creek Basin.
U.S.
Department of the Interior | U.S. Geological
Survey
Persistent URL: https://pubs.water.usgs.gov/sir20065274
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