Streamflow duration is used to differentiate reaches into discrete classes (e.g., perennial, intermittent, and ephemeral) for water resource management. Because the depiction of the extent and flow duration of streams via existing maps, remote sensing, and gauging is constrained, field-based tools are needed for use by practitioners and to validate hydrography and modeling advances. Streamflow Duration Assessment Methods (SDAMs) are rapid, reach-scale indices or models that use physical and biological indicators to predict flow duration class. We review the scientific basis for indicators and present conceptual and operational frameworks for SDAM development. Indicators can be responses to or controls of flow duration. Aquatic and terrestrial responses can be integrated into SDAMs, reflecting concurrent increases and decreases along the flow duration gradient. The conceptual framework for data-driven SDAM development shows interrelationships among the key components: study reaches, hydrologic data, and indicators. We present a generalized operational framework for SDAM development that integrates the data-driven components through five process steps: preparation, data collection, data analysis, evaluation, and implementation. We highlight priorities for the advancement of SDAMs, including expansion of gauging of nonperennial reaches, use of citizen science data, adjusting for stressor gradients, and statistical and monitoring advances to improve indicator effectiveness.

In response to water quality standard violations linked to excessive organic matter (OM) and a lack of sampling data informing the Total Maximum Daily Load (TMDL), an organic matter budget was created to quantify and identify sources of OM in the lower Jordan River (Salt Lake City, UT). By sampling dissolved, fine, and coarse particulate OM, as well as measuring ecosystem metabolism at seven different sites, the researchers aimed to identify the origin of excess OM, and understand pathways by which different size classes of the OM pool are generated. The dissolved fraction (DOM; 94 %) was found to be the dominant form of OM transported within the river with fine particulate organic matter (FPOM; 6 %) the second most abundant, and coarse particulate organic matter (CPOM; 1 %) transport relatively insignificant in the overall OM budget. Primary production exceeded respiratory losses in the upper river, and this, along with OM inputs from two tributaries (where water reclamation facilities discharge into the river) delivered excess OM to the impaired lower reaches. Increasing stream metabolism index (SMI) with distance downstream (>1 in the lower river) further demonstrated that transport of excessive organic matter into the lower river was from upstream sources and not due to lateral inputs. This simple approach to characterizing the organic matter budget as it relates to water quality in the Jordan River was effective and could serve as a model for future studies attempting to quantify and identify sources of OM in urban ecosystems.Keywords Water quality impairment . Organic matter budget . Urban stream syndrome Urban Ecosyst (2016) 19:1623-1643 DOI 10.1007 A TMDL study defines the relationship between pollutant sources and in-stream water quality conditions. Based on this relationship, a permissible load is defined that will result in meeting state water quality standards and restore aquatic life beneficial use support for impaired segments of the river (UT DWQ 2012).

Terrestrially derived organic matter (OM) is known to dominate the OM pool in reference watersheds. Urban watersheds are known to receive large OM loads compared to reference watersheds, but the proportion of terrestrial, autochthonous, and anthropogenic (e.g., wastewater effluent) sources of OM in urban watersheds remains unknown. Organic matter was identified as a pollutant of concern in the Jordan River, an urban river in the Salt Lake Basin, U.S.A. Our objective was to identify autochthonous, terrestrial, and anthropogenic sources of three size-classes of OM to the Jordan River to inform OM reduction strategies within the watershed. Samples of coarse particulate OM (CPOM), fine particulate OM (FPOM), and dissolved OM (DOM) were analyzed for stable isotopes of carbon, nitrogen, and hydrogen. Stable isotope values of OM were used for Bayesian and graphical gradient-based mixing models to identify autochthonous, terrestrial, and anthropogenic sources. Fluorescent properties of DOM were also used to characterize the sources and composition of DOM. CPOM was primarily terrestrially derived with increased autochthonous inputs from macrophytes in warm months. FPOM was a mixture of terrestrial, autochthonous, and wastewater effluent throughout the year. DOM was primarily from wastewater effluent as well as DOM with isotope signatures unique to DOM from Utah Lake. Characterization of OM in urban rivers will help inform conceptual models of OM dynamics and load management in urban ecosystems.

In response to water quality standard violations linked to excessive organic matter (OM) and a lack of sampling data informing the Total Maximum Daily Load (TMDL), an organic matter budget was created to quantify and identify sources of OM in the lower Jordan River (Salt Lake City, UT). By sampling dissolved, fine, and coarse particulate OM, as well as measuring ecosystem metabolism at seven different sites, the researchers aimed to identify the origin of excess OM, and understand pathways by which different size classes of the OM pool are generated. The dissolved fraction (DOM; 94 %) was found to be the dominant form of OM transported within the river with fine particulate organic matter (FPOM; 6 %) the second most abundant, and coarse particulate organic matter (CPOM; 1 %) transport relatively insignificant in the overall OM budget. Primary production exceeded respiratory losses in the upper river, and this, along with OM inputs from two tributaries (where water reclamation facilities discharge into the river) delivered excess OM to the impaired lower reaches. Increasing stream metabolism index (SMI) with distance downstream (>1 in the lower river) further demonstrated that transport of excessive organic matter into the lower river was from upstream sources and not due to lateral inputs. This simple approach to characterizing the organic matter budget as it relates to water quality in the Jordan River was effective and could serve as a model for future studies attempting to quantify and identify sources of OM in urban ecosystems.Keywords Water quality impairment . Organic matter budget . Urban stream syndrome Urban Ecosyst (2016) 19:1623-1643 DOI 10.1007 A TMDL study defines the relationship between pollutant sources and in-stream water quality conditions. Based on this relationship, a permissible load is defined that will result in meeting state water quality standards and restore aquatic life beneficial use support for impaired segments of the river (UT DWQ 2012).

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Stream bacterioplankton communities, a crucial component of aquatic ecosystems and surface water quality, are shaped by environmental selection (i.e., changes in taxa abundance associated with more or less favorable abiotic conditions) and passive dispersal (i.e., organisms’ abundance and distribution is a function of the movement of the water). These processes are a function of hydrologic conditions such as residence time and water chemistry, which are mediated by human infrastructure. To quantify the role of environmental conditions, dispersal, and human infrastructure (dams) on stream bacterioplankton, we measured bacterioplankton community composition in rivers from sub-alpine to urban environments in three watersheds (Utah, United States) across three seasons. Of the 53 environmental parameters measured (including physicochemical parameters, solute concentrations, and catchment characteristics), trace element concentrations explained the most variability in bacterioplankton community composition using Redundancy Analysis ordination. Trace elements may correlate with bacterioplankton due to the commonality in source of water and microorganisms, and/or environmental selection creating more or less favorable conditions for bacteria. Bacterioplankton community diversity decreased downstream along parts of the stream continuum but was disrupted where large reservoirs increased water residence time by orders of magnitude, potentially indicating a shift in the relative importance of environmental selection and dispersal at these sites. Reservoirs also had substantial effects on community composition, dissimilarity (Bray-Curtis distance) and species interactions as indicated by co-occurrence networks. Communities downstream of reservoirs were enriched with anaerobic Sporichthyaceae, methanotrophic Methylococcaceae, and iron-transforming Acidimicrobiales, suggesting alternative metabolic pathways became active in the hypolimnion of large reservoirs. Our results identify that human activity affects river microbial communities, with potential impacts on water quality through modified biogeochemical cycling.

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Streamflow duration information underpins many management decisions. However, hydrologic data are rarely available where needed. Rapid streamflow duration assessment methods (SDAMs) classify reaches based on indicators that are measured in a single brief visit. We evaluated a proposed framework for developing SDAMs to develop an SDAM for the Arid West United States that can classify reaches as perennial, intermittent, or ephemeral. We identified 41 candidate biological, geomorphological, and hydrological indicators of streamflow duration in a literature review, evaluated them for a number of desirable criteria (e.g., defensibility and consistency), and measured 21 of them at 89 reaches with known flow durations. We selected metrics for the SDAM based on their ability to discriminate among flow duration classes in analyses of variance, as well as their importance in a random forest model to predict streamflow duration. This approach resulted in a “beta” SDAM that uses five biological indicators. It could discriminate between ephemeral and non-ephemeral reaches with 81% accuracy, but only 56% accuracy when distinguishing 3 classes. A final method will be developed following expanded data collection. This Arid West study demonstrates the effectiveness of our approach and paves the way for more efficient development of scientifically informed SDAMs.