Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems and reliable water supplies for people, but there is a lack of comprehensive model comparison studies that quantify differences in streamflow predictions among model applications developed to answer management questions. We assessed differences in daily streamflow predictions by four fine‐scale models and two regional‐scale monthly time step models by comparing model fit statistics and bias in ecologically relevant flow statistics (ERFSs) at five sites in the Southeastern USA. Models were calibrated to different extents, including uncalibrated (level A), calibrated to a downstream site (level B), calibrated specifically for the site (level C) and calibrated for the site with adjusted precipitation and temperature inputs (level D). All models generally captured the magnitude and variability of observed streamflows at the five study sites, and increasing level of model calibration generally improved performance. All models had at least 1 of 14 ERFSs falling outside a +/−30% range of hydrologic uncertainty at every site, and ERFSs related to low flows were frequently over‐predicted. Our results do not indicate that any specific hydrologic model is superior to the others evaluated at all sites and for all measures of model performance. Instead, we provide evidence that (1) model performance is as likely to be related to calibration strategy as it is to model structure and (2) simple, regional‐scale models have comparable performance to the more complex, fine‐scale models at a monthly time step. Copyright © 2015 John Wiley & Sons, Ltd.

The Watershed Flow and Allocation model (WaterFALL®) provides segment‐specific, daily streamflow at both gaged and ungaged locations to generate the hydrologic foundation for a variety of water resources management applications. The model is designed to apply across the spatially explicit and enhanced National Hydrography Dataset (NHDPlus) stream and catchment network. To facilitate modeling at the NHDPlus catchment scale, we use an intermediate‐level rainfall‐runoff model rather than a complex process‐based model. The hydrologic model within WaterFALL simulates rainfall‐runoff processes for each catchment within a watershed and routes streamflow between catchments, while accounting for withdrawals, discharges, and onstream reservoirs within the network. The model is therefore distributed among each NHDPlus catchment within the larger selected watershed. Input parameters including climate, land use, soils, and water withdrawals and discharges are georeferenced to each catchment. The WaterFALL system includes a centralized database and server‐based environment for storing all model code, input parameters, and results in a single instance for all simulations allowing for rapid comparison between multiple scenarios. We demonstrate and validate WaterFALL within North Carolina at a variety of scales using observed streamflows to inform quantitative and qualitative measures, including hydrologic flow metrics relevant to the study of ecological flow management decisions.

A method was developed to characterize fish and invertebrate responses to flow alteration in the state of North Carolina. This method involved using 80th percentile linear quantile regressions to relate six flow metrics to the diversity of riffle‐run fish and benthic Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness. All twelve flow‐biology relationships were found to be significant, with both benthos and fish showing negative responses to ecodeficits and reductions in flow. The responses of benthic richness to reduced flows were consistent and generally greater than that of fish diversity. However, the riffle‐run fish guild showed the greatest reductions in diversity in response to summer ecodeficits. The directional consistency and differential seasonal sensitivities of fish and invertebrates to reductions in flow highlight the need to consider seasonality when managing flows. In addition, all relationships were linear, and therefore do not provide clear thresholds to support ecological flow determinations and flow prescriptions to prevent the degradation of fish and invertebrate communities in North Carolina rivers and streams. A method of setting ecological flows based on the magnitude of change in biological condition that is acceptable to society is explored.

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Hydroecological classification systems are typically based on an assemblage of streamflow metrics and seek to divide streams into ecologically relevant classes. Assignment of streams to classes is suggested as an initial step in the process of establishing ecological flow standards. We used two distinct hydroecological river classification systems available within North Carolina to evaluate the ability of a hydrologic model to assign the same classes as those determined by observed streamflows and to assess the transferability of such systems to ungaged streams. Class assignments were examined by rate of overall matches, rate of class matches, spatial variability in matches, and time period used in class assignment. The findings of this study indicate assignments of stream class: (1) are inconsistent among different classification systems; (2) differ between observed and modeled data; and (3) are sensitive to the period of record within observed data. One clear source of inconsistency/sensitivity in class assignments lies with the use of threshold values for metrics that distinguish stream classes, such that even small changes in metric values can result in different class assignments. Because these two hydroecological classification systems are representative of other classification systems that rely on quantitative decision thresholds, it can be surmised that the use of such systems based on stream flow metrics is not a reliable approach for guiding ecological flow determinations.