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Abstract Streambed biogeochemical processes strongly influence riverine water quality and gaseous emissions. These processes depend largely on flow paths through the hyporheic zone (HZ), the streambed volume saturated with stream water. Boulders and other macroroughness elements are known to induce hyporheic flows in gravel‐bed streams. However, data quantifying the impact of these elements on hyporheic chemistry are lacking. We demonstrate that, in gravel‐bed rivers, the amount of dissolved oxygen (DO) in the bed depends chiefly on changes in bed shape, or morphology, such as the formation of scour and depositional areas, caused by the boulders, among other factors. The study was conducted by comparing DO distributions across different bed states and hydraulic conditions. Our experimental facility replicates conditions observed in natural gravel‐bed streams. We instrumented a section in the bed with DO sensors. Results generally indicate that boulder placement on planar beds has some effects, which are significant at high base flows, on increasing hyporheic oxygen amount compared to the planar case without boulders. Conversely, boulder‐induced morphological changes noticeably and significantly increase the amount of oxygen in the HZ, with the increase depending on sediment inputs during flood flows able to mobilize the sediment. Therefore, streambeds of natural, plane‐bed streams may have deeper oxic zones than previously thought because the presence of boulders and the occurrence of flood flows with varying sediment inputs induce streambed variations among these elements. 

High resolution topographic data are necessary to understand benthic habitat, quantify processes at the water-sediment interface, and support computational fluid dynamics models for both surface and hyporheic hydraulics. In riverine systems, these data are typically collected using traditional surveying methods (total station, DGPS, etc.), airborne or terrestrial laser scanning, and photogrammetry. Recently, handheld surveying equipment has been rapidly acquiring popularity in part due to its processing capacity, price, size, and versatility. One such device is the iPhone LiDAR, which could have a good balance between precision and ease of use and is a potential replacement for conventional measuring tools. Here, we evaluated the accuracy of the LiDAR sensor and a Structure from Motion (SfM) method based on photos collected using the iPhone Cameras. We compared the LiDAR and SfM elevations to those from a high-precision laser scanner for an experimental rough water-worked gravelbed channel with boulder-like structures. We observed that both the LiDAR and SfM methods captured the overall streambed morphology and detected large (Hs
15 cm) and macro (5cm  Hs < 15cm) scales of topographic variations (Hs, roughness). The SfM technique also captured small scale (Hs <5cm) roughness whereas the LiDAR consistently simplified it with errors of 3.7 mm.