Low flow controls on stream thermal dynamics

Water level fluctuations in surface water bodies, and in particular low flow drought conditions, are expected to become more frequent and more severe in the future due to the impacts of global environmental change. Variations in water level, and therefore in-channel water volume, not only have the potential to directly impact stream temperature, but also aquatic vegetation coverage which, in turn, may affect stream temperature patterns and dynamics. Manipulation experiments provide a systematic approach to investigate the multiple environmental controls on stream temperature patterns. This study aims to use temperature data loggers and fibre optic distributed temperature sensing (FO-DTS) to investigate potential drought impacts on patterns in surface water and streambed temperature as a function of change in water column depth. To quantify the joint impacts of water level and associated vegetation coverage on stream temperatures, investigations were conducted in outdoor flumes using identical pool-riffle-pool features, but with spatially variable water levels representative of different drought severity conditions. Naturally evolved vegetation growth in the flumes ranged from sparse vegetation coverage in the shallow flumes to dense colonization in the deepest. Observed surface water and streambed temperature patterns differed significantly within the range of water levels and degrees of vegetation coverage studied. Streambed temperature patterns were more pronounced in the shallowest flume, with minimum and maximum temperature values and diurnal temperature variation being more intensively affected by variation in meteorological conditions than daily average temperatures. Spatial patterns in streambed temperature correlated strongly with morphologic features in all flumes, with riffles coinciding with the highest temperatures, and pools representing areas with the lowest temperatures. In particular, the shallowest flume (comprising multiple exposed features) exhibited a maximum upstream-downstream temperature warming of 3.3 °C (T in = 10.3 °C, T out = 13.5 °C), exceeding the warming observed in the deeper flumes by ∼ 2 °C. Our study reveals significant streambed and water temperature variation caused by the combined impacts of water level and related vegetation coverage. These results highlight the importance of maintaining minimum water levels in lowland rivers during droughts for buffering the impacts of atmospheric forcing on both river and streambed water temperatures

Advancing river corridor science beyond disciplinary boundaries with an inductive approach to catalyse hypothesis generation

A unified conceptual framework for river corridors requires synthesis of diverse site-, method- and discipline-specific findings. The river research community has developed a substantial body of observations and process-specific interpretations, but we are still lacking a comprehensive model to distill this knowledge into fundamental transferable concepts. We confront the challenge of how a discipline classically organized around the deductive model of systematically collecting of site-, scale-, and mechanism-specific observations begins the process of synthesis. Machine learning is particularly well-suited to inductive generation of hypotheses. In this study, we prototype an inductive approach to holistic synthesis of river corridor observations, using support vector machine regression to identify potential couplings or feedbacks that would not necessarily arise from classical approaches. This approach generated 672 relationships linking a suite of 157 variables each measured at 62 locations in a fifth order river network. Eighty four percent of these relationships have not been previously investigated, and representing potential (hypothetical) process connections. We document relationships consistent with current understanding including hydrologic exchange processes, microbial ecology, and the River Continuum Concept, supporting that the approach can identify meaningful relationships in the data. Moreover, we highlight examples of two novel research questions that stem from interpretation of inductively-generated relationships. This study demonstrates the implementation of machine learning to sieve complex data sets and identify a small set of candidate relationships that warrant further study, including data types not commonly measured together. This structured approach complements traditional modes of inquiry, which are often limited by disciplinary perspectives and favour the careful pursuit of parsimony. Finally, we emphasize that this approach should be viewed as a complement to, rather than in place of, more traditional, deductive approaches to scientific discovery

Enhanced hyporheic exchange flow around woody debris does not increase nitrate reduction in a sandy streambed

Anthropogenic nitrogen pollution is a critical problem in freshwaters. Although riverbeds are known to attenuate nitrate, it is not known if large woody debris (LWD) can increase this ecosystem service through enhanced hyporheic exchange and streambed residence time. Over a year, we monitored the surface water and pore water chemistry at 200 points along a ~50m reach of a lowland sandy stream with three natural LWD structures. We directly injected 15N-nitrate at 108 locations within the top 1.5m of the streambed to quantify in situ denitrification, anammox and dissimilatory nitrate reduction to ammonia, which, on average, contributed 85%, 10% and 5% of total nitrate reduction, respectively. Total nitrate reducing activity ranged from 0-16µM h-1 and was highest in the top 30cm of the stream bed. Depth, ambient nitrate and water residence time explained 44% of the observed variation in nitrate reduction; fastest rates were associated with slow flow and shallow depths. In autumn, when the river was in spate, nitrate reduction (in situ and laboratory measures) was enhanced around the LWD compared with non-woody areas, but this was not seen in the spring and summer. Overall, there was no significant effect of LWD on nitrate reduction rates in surrounding streambed sediments, but higher pore water nitrate concentrations and shorter residence times, close to LWD, indicated enhanced delivery of surface water into the streambed under high flow. When hyporheic exchange is too strong, overall nitrate reduction is inhibited due to short flow-paths and associated high oxygen concentrations