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

Stefano Larsen,Maria Cristina Bruno,Guido Zolezzi,Elisa Stella,Patrick Zulian,Bruno Majone,Alberto Bellin

doi:10.1029/2020wr028496

Stefano Larsen, Maria Cristina Bruno + Show 5 more

Open Access

https://doi.org/10.1029/2020wr028496

Copy DOI

Abstract

AbstractFlow 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.

Highlights

The flow regime of streams and rivers has been modified by human activities at a global scale (Grill et al, 2019; Tonkin et al, 2019)
The capability of HYPERstreamHS hydrological model to reproduce the observed daily streamflow time series in the Adige River was validated in the period 1991–2013 by computing Nash-Sutcliffe efficiency index (NSE) at the nine gauging stations described in Section 2.4 (Figure 1)
The parameters of the hydrologic model were inferred by maximizing the average NSE at Vermiglio, Rio Funes, Aurino, and Gadera gauging stations

Summary

Introduction

The flow regime of streams and rivers has been modified by human activities at a global scale (Grill et al, 2019; Tonkin et al, 2019). Streams and rivers are under increasing anthropogenic pressure and are among the most threatened ecosystems worldwide, with high rates of species extinctions (Tickner et al, 2020). The ongoing global climate change is expected to further exacerbate this situation by increasing the frequency of extreme hydrologic events such as floods and droughts that act synergistically with other stressors affecting aquatic ecosystems Navarro-Ortega et al, 2015) This is of particular concern since freshwater ecosystems support about 10% of all known species (Strayer & Dudgeon, 2010) and are essential for human well-being, providing a wealth of ecosystem services (Green et al, 2015). Understanding and limiting the ecological effects of flow alteration is fundamental for sustainable use of water resources

Objectives

Results

Conclusion