Given the sensitivity of natural environments to freshwater availability in the Southeast US, as well as the reliance of many municipal and commercial water consumers on surface water supplies, specific issues related to low river streamflow are apparent. As a result, the need for quantifying the spatial distribution, frequency, and intensity of low flow events (a.k.a., hydrologic drought) is critical to define areas most susceptible to water shortages and subsequent environmental and societal risk. To that end, daily mean discharge values from the National Water Model (NWM) retrospective data (v. 2.0) are used to assess low flow frequency, intensity, and spatial distribution within the Southeast US. Low flow events are defined using the US EPA 7Q10 approach, based on the flow duration curve (FDC) developed using a 1993–2018 period of record. Results reflect the general climatological patterns of the region, with a higher probability of low flow events occurring during the warm season (June–August) while low flow events in the cool season (January–March) are generally less common and have a higher average discharge. Spatial analysis shows substantial regional variability, with an area from southeastern Mississippi through central South Carolina showing higher low flow event frequency during the cool season. This same area is also highlighted in the warm season, albeit along a more expansive area from central Alabama into the piedmont region of North Carolina. Results indicate that the NWM retrospective data are able to show general patterns of hydrologic drought across the Southeast US, although local-scale assessment is limited due to potential issues associated with infiltration and runoff during periods of warm-season convective rainfall.

The objective of this study is to quantify the seasonal and multi-annual variability and trends of low-flow river conditions in southeastern Poland. The study was performed using daily values of river discharge at 29 gauging stations for hydrological years 1976–2014. The results show regionally specific patterns, such that seasonality is high for the lowland rivers (low flows occur during the warm season), while in the upland rivers a 10- to 15-year cycle is observed. Increasing trends in warm-season temperature and a decrease in humidity were observed; however, no direct correlation with low flows was found. These results suggest that the initiation and maintenance of low-flow events over some regions are more sensitive to local surface water and groundwater circulation conditions than to atmospheric drivers, especially when the recurrence interval of events is low, and that the primary mechanisms driving and maintaining low-flow conditions can change over relatively small spatial scales.

Low flow events (a.k.a. streamflow drought) are described as episodes where stream flows are lower or equal to a specified minimum threshold level. This threshold is usually predefined at the methodological stage of a study and is generally applied as a chosen flow percentile, determined from a flow duration curve (FDC). Unfortunately, many available methods for choosing both the percentile and FDCs result in a large range of potential thresholds, which reduces the ability to statistically compare the results from the different methods while also losing the natural character of the phenomenon. The aim of this work is to introduce a new approach for low flow threshold calculation through the application of an objective approach using breakpoint analysis. This method allows for the identification of an environmental moment of river transition, from atmospheric feed flows to base flow, which characterizes the moment at the beginning of the hydrological drought. The method allows for not only the capture of the genesis of a low flow event but, above all, unifies the approach toward threshold levels and completely excludes the impact of the subjective researcher’s decisions, which occur at the methodological stage when selecting the threshold criteria or when choosing a respective percentile. In addition, the method can be successfully used in datasets characterized by a high level of discretization, such as numerical model data, where the subsurface runoff component is not described in sufficient detail. Results of this work show that the objective identification method is better able to capture the occurrence of a low flow event, improving the ability to identify hydrologic drought conditions. The proposed method is published together with the Python module objective_thresholds for broad use in other studies.

Understanding the patterns of streamflow drought frequency and intensity is critical in defining potential environmental and societal impacts on processes associated with surface water resources; however, analysis of these processes is often limited to the availability of data. The objective of this study is to quantify the annual and monthly variability of low flow river conditions over the Southeastern United States (US) using National Water Model (NWM) retrospective simulations (v2.1), which provide streamflow estimates at a high spatial density. The data were used to calculate sums of outflow deficit volumes at annual and monthly scales, from which the autocorrelation functions (ACF), partial autocorrelation functions (PACF) and the Hurst exponent (H) were calculated to quantify low flow patterns. The ACF/PACF approach is used for examining the seasonal and multiannual variation of extreme events, while the Hurst exponent in turn allows for classification of “process memory”, distinguishing multi-seasonal processes from white noise processes. The results showed diverse spatial and temporal patterns of low flow occurrence across the Southeast US study area, with some locations indicating a strong seasonal dependence. These locations are characterized by a longer temporal cycle, whereby low flows were arranged in series of several to dozens of years, after which they did not occur for a period of similar length. In these rivers, H was in the range 0.8 (+/−0.15), which implies a stronger relation with groundwater during dry periods. In other river segments within the study region the probability of low flows appeared random, determined by H oscillating around the values for white noise (0.5 +/−0.15). The initial assessment of spatial clusters of the low flow parameters suggests no strict relationships, although a link to geologic characteristics and aquifer depth was noticed. At monthly scales, low flow occurrence followed precipitation patterns, with streamflow droughts first occurring in the Carolinas and along the Gulf Coast around May and then progressing upstream, reaching maxima around October for central parts of Mississippi, Alabama and Georgia. The relations for both annual and monthly scales are better represented with PACF, for which statistically significant lags were found in around 75% of stream nodes, while ACF explains on average only 20% of cases, indicating that streamflow droughts in the region occur in regular patterns (e.g., seasonal). This repeatability is of greater importance to defining patterns of extreme hydrologic events than the occurrence of high magnitude random events. The results of the research provide useful information about the spatial and temporal patterns of low flow occurrence across the Southeast US, and verify that the NWM retrospective data are able to differentiate the time processes for the occurrence of low flows.

The objective of this paper is the assessment of the effect of a multifunctional mid-size retention reservoir on the occurrence of floods and low flows. The study object was moderate size...