Classifying Streamflow Duration: The Scientific Basis and an Operational Framework for Method Development

Identifying invertebrate indicators for streamflow duration assessments in forested headwater streams

Streamflow-duration assessment methods (SDAMs) are rapid, indicator-based tools for classifying streamflow duration (e.g., intermittent vs perennial flow) at the reach scale. Indicators are easily assessed stream properties used as surrogates of flow duration, which is too resource intensive to measure directly for many reaches. Invertebrates are commonly used as SDAM indicators because many are not highly mobile, and different species have life stages that require flow for different durations and times of the year. The objectives of this study were to 1) identify invertebrate taxa that can be used as SDAM indicators to distinguish between stream reaches having intermittent and perennial flow, 2) to compare indicator strength across different taxonomic and numeric resolutions, and 3) to assess the relative importance of season and habitat type on the ability of invertebrates to predict streamflow-duration class. We used 2 methods, random forest models and indicator species analysis, to analyze aquatic and terrestrial invertebrate data (presence/absence, density, and biomass) at the family and genus levels from 370 samples collected from both erosional and depositional habitats during both wet and dry seasons. In total, 36 intermittent and 53 perennial reaches were sampled along 31 forested headwater streams in 4 level II ecoregions across the United States. Random forest models for family- and genus-level datasets had stream classification accuracy ranging from 88.9 to 93.2%, with slightly higher accuracy for density than for presence/absence and biomass datasets. Season (wet/dry) tended to be a stronger predictor of streamflow-duration class than habitat (erosional/depositional). Many taxa at the family (58.8%) and genus level (61.6%) were collected from both intermittent and perennial reaches, and most taxa that were exclusive to 1 streamflow-duration class were rarely collected. However, 23 family-level or higher taxa (20 aquatic and 3 terrestrial) and 44 aquatic genera were identified as potential indicators of streamflow-duration class for forested headwater streams. The utility of the potential indicators varied across level II ecoregions in part because of representation of intermittent and perennial reaches in the dataset but also because of variable ecological responses to drying among species. Aquatic invertebrates have been an important field indicator of perennial reaches in existing SDAMs, but our findings highlight how including aquatic and terrestrial invertebrates as indicators of intermittent reaches can further maximize the data collected for streamflow-duration classifications.

Headwater streams and inland wetlands: Status and advancements of geospatial datasets and maps across the United States

Headwater streams and inland wetlands provide essential functions that support healthy watersheds and downstream waters. However, scientists and aquatic resource managers lack a comprehensive synthesis of national and state stream and wetland geospatial datasets and emerging technologies that can further improve these data. We conducted a review of existing United States (US) federal and state stream and wetland geospatial datasets, focusing on their spatial extent, permanence classifications, and current limitations. We also examined recent peer-reviewed literature for emerging methods that can potentially improve the estimation, representation, and integration of stream and wetland datasets. We found that federal and state datasets rely heavily on the US Geological Survey's National Hydrography Dataset for stream extent and duration information. Only eleven states (22%) had additional stream extent information and seven states (14%) provided additional duration information. Likewise, federal and state wetland datasets primarily use the US Fish and Wildlife Service's National Wetlands Inventory (NWI) Geospatial Dataset, with only two states using non-NWI datasets. Our synthesis revealed that LiDAR-based technologies hold promise for advancing stream and wetland mapping at limited spatial extents. While machine learning techniques may help to scale-up these LiDAR-derived estimates, challenges related to preprocessing and data workflows remain. High-resolution commercial imagery, supported by public imagery and cloud computing, may further aid characterization of the spatial and temporal dynamics of streams and wetlands, especially using multi-platform and multi-temporal machine learning approaches. Models integrating both stream and wetland dynamics are limited, and field-based efforts must remain a key component in developing improved headwater stream and wetland datasets. Continued financial and partnership support of existing databases is also needed to enhance mapping and inform water resources research and policy decisions.

Sensitivity of streamflow patterns to river regulation and climate change and its implications for ecological and environmental management

Streamflow patterns support complex ecosystem functions and services. However, the direct impacts of flow regulation and climate change on patterns of streamflow are less studied. This study aims to analyse the sensitivity of streamflow patterns to the effects of flow regulation and climate change in the Goulburn-Broken catchment in Victoria, Australia. Daily streamflow was classified into low, medium, high, and overbank flow metrics using a statistical quantile-based approach. Trends and percent changes in streamflow metrics during the 1977-2018 period were analysed, and effects of change in rainfall, regulation, and flow diversion on streamflow patterns were predicted using a generalized additive model and path analysis. Low flows and medium flows increased by 26%, and high flows and overbank flows decreased by 31% during the period between 1977 and 2018. While current river regulation and flow diversion practices would dominate future change in magnitude, duration, and frequency of the streamflow, the timing of flow metrics would be dominated by variation in rainfall. These could bring a new ecological and environmental risk to the riverine ecosystem. It is recommended to increase the duration of high flows (90-120 days) and overbank flows (10-30 days) and the frequency of overbank flows to at least once every 1-2 years during wet periods to mitigate ecological and environmental risks of climate change and flow regulation in the Goulburn-Broken catchment.

Implementing an Operational Framework to Develop a Streamflow Duration Assessment Method: A Case Study from the Arid West United States

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.

Macroinvertebrates at the source: flow duration and seasonality drive biodiversity and trait composition in rheocrene springs of the Western Allegheny Plateau, USA

Documenting flow regimes and the ecology of source headwater streams has gained considerable attention for scientific and regulatory purposes. These streams do not appear on standard maps, and local physiographic and climatologic conditions can control their origins. We investigated macroinvertebrate assemblages seasonally and in relation to flow duration, catchment and habitat variables within 14 source headwaters (< 1 ha) in the Western Allegheny Plateau over a 19-month period. We classified 6 perennial (P) and 8 intermittent (I) streams directly with continuous flow data loggers. Several biological and trait-based metrics could distinguish flow class, but few instream physical measures could. Macroinvertebrate metrics and assemblage dispersion varied seasonally and responded significantly along a gradient of total flow duration. Separate indicator species analyses generated 22 genera and 15 families with significant affinities to P streams. Richness of P-indicator taxa was also strongly correlated with flow duration gradients, and we estimated a total flow duration changepoint at 77% (3 indicator families) followed by a sharp increase in richness. Two rapid field-based flow duration methods (NC Stream Identification index and OH Headwater Habitat Evaluation index) could distinguish upstream ephemeral reaches from P and I reaches, but misclassified P as I more frequently. Our findings highlight that diverse coldwater macroinvertebrate assemblages inhabited extremely small, low-discharge springs in the region, and responded with flow duration. These source headwater habitats are susceptible to human disturbance and should be monitored as is routinely done in larger lotic systems.

Beyond Streamflow: Call for a National Data Repository of Streamflow Presence for Streams and Rivers in the United States

Observations of the presence or absence of surface water in streams are useful for characterizing streamflow permanence, which includes the frequency, duration, and spatial extent of surface flow in streams and rivers. Such data are particularly valuable for headwater streams, which comprise the vast majority of channel length in stream networks, are often non-perennial, and are frequently the most data deficient. Datasets of surface water presence exist across multiple data collection groups in the United States but are not well aligned for easy integration. Given the value of these data, a unified approach for organizing information on surface water presence and absence collected by diverse surveys would facilitate more effective and broad application of these data and address the gap in streamflow data in headwaters. In this paper, we highlight the numerous existing datasets on surface water presence in headwater streams, including recently developed crowdsourcing approaches. We identify the challenges of integrating multiple surface water presence/absence datasets that include differences in the definitions and categories of streamflow status, data collection method, spatial and temporal resolution, and accuracy of geographic location. Finally, we provide a list of critical and useful components that could be used to integrate different streamflow permanence datasets.

Classification and Prediction of Natural Streamflow Regimes in Arid Regions of the USA

Understanding how natural variation in flow regimes influences stream ecosystem structure and function is critical to the development of effective stream management policies. Spatial variation in flow regimes among streams is reasonably well understood for streams in mesic regions, but a more robust characterization of flow regimes in arid regions is needed, especially to support biological monitoring and assessment programs. In this paper, we used long-term (41 years) records of mean daily streamflow from 287 stream reaches in the arid and semi-arid western USA to develop and compare several alternative flow-regime classifications. We also evaluated how accurately we could predict the flow-regime classes of ungauged reaches. Over the 41-year record examined (water years 1972–2013), the gauged reaches varied continuously from always having flow > zero to seldom having flow. We predicted ephemeral and perennial reaches with less error than reaches with an intermediate number of zero-flow days or years. We illustrate application of our approach by predicting the flow-regime classes at ungauged reaches in Arizona, USA. Maps based on these predictions were generally consistent with qualitative expectations of how flow regimes vary spatially across Arizona. These results represent a promising step toward more effective assessment and management of streams in arid regions.