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Groundwater discharge though streambeds is often focused toward discrete zones, indicating that preliminary reconnaissance may be useful for capturing the full spectrum of groundwater discharge rates using point-scale quantitative methods. However, many direct-contact reconnaissance techniques can be time-consuming, and remote sensing (e.g., thermal infrared) typically does not penetrate the water column to locate submerged seepages. In this study, we tested whether dozens of groundwater discharge measurements made at &#8220;uninformed&#8221; (i.e., selected without knowledge on high-resolution temperature variations at the streambed) point locations along a reach would yield significantly different Darcy-based groundwater discharge rates when compared with &#8220;informed&#8221; measurements, focused at streambed thermal anomalies that were identified a priori using fiber-optic distributed temperature sensing (FO-DTS). A non-parametric U-test showed a significant difference between median discharge rates for uninformed (0.05 m&#183;day^&#8722;1; <i>n</i> = 30) and informed (0.17 m&#183;day^&#8722;1; <i>n</i> = 20) measurement locations. Mean values followed a similar pattern (0.12 versus 0.27 m&#183;day^&#8722;1), and frequency distributions for uninformed and informed measurements were also significantly different based on a Kolmogorov&#8722;Smirnov test. Results suggest that even using a quick &#8220;snapshot-in-time&#8221; field analysis of FO-DTS data can be useful in streambeds with groundwater discharge rates &lt;0.2 m&#183;day^&#8722;1, a lower threshold than proposed in a previous study. Collectively, study results highlight that FO-DTS is a powerful technique for identifying higher-discharge zones in streambeds, but the pros and cons of informed and uninformed sampling depend in part on groundwater/surface water exchange study goals. For example, studies focused on measuring representative groundwater and solute fluxes may be biased if high-discharge locations are preferentially sampled. However, identification of high-discharge locations may complement more randomized sampling plans and lead to improvements in interpolating streambed fluxes and upscaling point measurements to the stream reach scale.