Combining Hydrologic Simulations and Stream‐network Models to Reveal Flow‐ecology Relationships in a Large Alpine Catchment

Flow regimes profoundly influence river organisms and ecosystem functions, but regulatory approaches often lack the scientific basis to support sustainable water allocation. In part, this reflects the challenge of understanding the ecological effects of flow variability over different temporal and spatial domains. Here, we use a process‐based distributed hydrological model to simulate 23 years of natural flow regime in 100 bioassessment sites across the Adige River network (NE Italy), and to identify typical nivo‐glacial, nivo‐pluvial, and pluvial reaches. We then applied spatial stream‐network models (SSN) to investigate the relationships between hydrologic and macroinvertebrate metrics while accounting for network spatial autocorrelation and local habitat conditions. Macroinvertebrate metrics correlated most strongly with summer, winter, and temporal variation in streamflow, but effects varied across flow regime types. For example (i) taxon richness appeared limited by high summer flows and high winter flows in nivo‐glacial and pluvial streams, respectively; (ii) invertebrate grazers increased proportionally with the annual coefficient of flow variation in nivo‐glacial streams but tended to decline with flow variation in pluvial streams. Although local land‐use and water quality also affected benthic communities, most variation in macroinvertebrate metrics was associated with spatial autocorrelation. These findings highlight the importance of developing environmental flow management policies in ways that reflect specific hydro‐ecological and land use contexts. Our analyses also illustrate the importance of spatially‐explicit approaches that account for auto‐correlation when quantifying flow‐ecology relationships. Key Points The hydrological model HYPERstreamHS was used to simulate natural streamflow series at 100 bio‐assessment sites across a large Alpine basin Three flow‐regime classes were identified, representing typical nivo‐glacial, nivo‐pluvial, and pluvial streams Spatial stream‐network models identified distinct flow‐ecology relationships and relevant spatial autocorrelation across classified regimes, which can aid in the implementation of targeted water management schemes