Citation:

Malin, J., S. Kaushal, P. Mayer, C. Maas, S. Hohman, AND M. Rippy. Longitudinal Stream Synoptic (LSS) Monitoring to Evaluate Water Quality in Restored Streams. ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, 196:437, (2024). https://doi.org/10.1007/s10661-024-12570-w

Impact/Purpose:

We describe a novel approach to monitoring water quality in urban watersheds that better elucidates sources and sinks of pollutants along flowpaths.  Our approach improves upon traditional methods of sampling that rely on limited spatial and temporal sampling in favor of longitudinal synoptic sampling (LSS) that expands sampling networks across complete stream flowpaths and over ecologically relevant time frames and seasonal influences such as road salt events.  When used in concert with statistical approaches like principal components analysis, LSS monitoring reveals changes in chemical mixtures (e.g., salts, metals, and nutrients), that are locally responsive to restoration projects but can be obscured at the watershed scale and overwhelmed during storm events.

Description:

Impervious surface cover increases peak flows and degrades stream health, contributing to a variety of hydrologic, water quality, and ecological symptoms, collectively known as the urban stream syndrome. Strategies to combat the urban stream syndrome often employ engineering approaches to enhance stream-floodplain reconnection, dissipate erosive forces from urban runoff, and enhance contaminant retention, but it is not always clear how effective such practices are or how to monitor for their effectiveness. In this study we explore the potential of longitudinal stream synoptic monitoring (LSS), an approach where multiple samples are collected along flowpaths in both space and time, to narrow this knowledge gap. Specifically, we investigate: (1) whether LSS can be used to detect changes in water chemistry along longitudinal flowpaths in response to stream-floodplain reconnection, and (2) which monitoring scales best elucidate the effectiveness of stream-floodplain reconnection efforts. We present results for four different classes of water quality constituents (carbon, nutrients, salt ions, and metals) across five watersheds with varying degrees of stream-floodplain reconnection. Our work suggests that LSS monitoring can be used to evaluate stream restoration strategies when implemented at meter to kilometer scales. As streams flow through restoration features, concentrations of nutrients, salts and metals significantly decline (p < 0.05) or remain unchanged. This same pattern is not evident in unrestored streams, where salt ion concentrations (e.g. Na+, Ca2+, K+) significantly increase with increasing impervious cover. When used in concert with statistical approaches like principal components analysis, we find that LSS reveals changes in entire chemical mixtures (e.g., salts, metals, and nutrients), not just individual water quality constituents. These chemical mixtures appear to be locally responsive to restoration projects but can be obscured at the watershed scale and overwhelmed during storm events.

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