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A Statistical Technique for Interpreting Streamflow Timing Using Streambed Sediment Thermographs

^a USGS, Tucson, AZ 85719
^b Department of Hydrology and Water Resources, University of Arizona, Tucson, AZ 85721

View larger version (27K): [in a new window]   Fig. 1. Thermal responses from within a streambed divided into the case when streamflow is absent (primarily conductive heat transport through the sediments) and the case when streamflow is present (primarily advective heat transport through the sediments). Note the reduction in the thermal amplitude at the streambed surface caused by the transference of heat to the overlying water column and corresponding increase in thermal amplitude at depth caused by percolating water.

View larger version (29K): [in a new window]   Fig. 2. (A) Advective and conductive diurnal temperature wave amplitudes as a function of depth propagating through coarse-grained stream channel sediments. The radiant thermal amplitude at the surface is 1°C. The solid black line describes conductive transport during no-flow conditions. The no dampening case considers zero reduction of the diurnal thermal amplitude during the presence of streamflow. The 50% dampening case considers a 50% reduction during the presence of streamflow. The 50% dampening/50% fluid flux reduction considers a 50% diurnal thermal amplitude reduction and a reduction in the fluid flux from the previous two cases by 50%. (B) Difference between the advective and conductive diurnal temperature wave amplitudes as a function of depth. Intersections between the solid diurnal temperature wave amplitude segments and the dashed transition line represent depths corresponding to equivalent advective and diurnal temperature wave amplitudes during flow and no-flow conditions respectively.

View larger version (28K): [in a new window]   Fig. 3. Thermograph for (A) a depth above the transition depth and (B) a depth below the transition depth. The gray areas denote observed periods of streamflow.

View larger version (55K): [in a new window]   Fig. 4. Six-hour moving standard deviation window for temperature data measured at (A) a depth above the transition depth and (B) a depth below the transition depth. The gray areas denote observed periods of streamflow.

View larger version (53K): [in a new window]   Fig. 5. Location of Rillito Creek study area and view of Rillito Creek within the Tucson Basin, Tucson, AZ.

View larger version (25K): [in a new window]   Fig. 6. Thermograph from 16 Sept. through 15 Dec. 2000 for (A) a depth of 0.15 m and (B) a depth of 0.75 m. The gray areas denote observed periods of streamflow.

View larger version (22K): [in a new window]   Fig. 7. A sensitivity analysis for the moving standard deviation technique considering: (A) the moving standard deviation window length, (B) the threshold multiplier, (C) the minimum flow duration parameter, and (D) the minimum inter-event duration parameter. Timing error is presented as the percentage of time over a year the method incorrectly infers the presence or absence of streamflow. Generally this error occurs at the onset and cessation of flow by either overestimating or underestimating the period of streamflow.

View larger version (49K): [in a new window]   Fig. 8. (A) Thermograph from 16 Sept. 2000 through 15 Sept. 2001 for a depth of 0.75 m, (B) 1-h, (C) 4-h, and (D) 12-h moving standard deviation windows for temperature data measured at a depth of 0.75 m. (E) Close-up of two identified events that provide an example of how moving standard deviation parameters can be selected. The gray area denotes periods of identified streamflow events.