Magnitude Of Peak Flows Research Articles

Development of Synthetic Unit Hydrographs Using Spatial Proximity Regionalization for the Makiling Forest Reserve, Philippines

There is a dearth of streamflow data in the Philippines to generate hydrographs needed for flood forecasting and water resources assessment. A method of generating and calibrating synthetic hydrographs using model simulations and spatial proximity regionalization is presented. Synthetic unit hydrographs of four storm events in the gauged watershed of Makiling Forest Reserve were generated using Soil Conservation Service Unit Hydrograph, Clark Unit Hydrograph, and Snyder’s Unit Hydrograph methods. The generated synthetic hydrographs for each runoff modeling technique were calibrated with the actual hydrographs of the watershed. Snyder’s Unit Hydrograph model results were the most acceptable based on the Nash-Sutcliffe Efficiency, Index of Volumetric Fit, and Relative Error of Peak Flow. The weighted values of the calibrated watershed parameters computed using spatial proximity regionalization technique and the hyetographs derived from the Rainfall Intensity Duration Frequency Curve of the University of the Philippines Los Baños-National Agrometeorological Station were used to generate the synthetic unit hydrographs for three neighboring ungauged watersheds at 2-, 5-, 10-, 15-, 20-, 25-, 50, 100-year return periods. Total runoff volume, the magnitude of peak flows, and time to peak derived from the generated hydrographs can be used in watershed planning, water resources management, flood forecasting and the design of various water control structures.

The directional unit hydrograph model: Connecting streamflow response to storm dynamics

Storm velocity (i.e., direction and speed) and structure (i.e., shape and intensity) play a critical role in streamflow response. These characteristics determine the timing and magnitude of precipitation fluxes across the watershed that drive runoff generation and conveyance along the river network. While previous efforts have used spatially explicit hydrologic models to assess the role of storm properties in streamflow magnitude, their computational demand significantly limits the range of scenarios that can be explored, hindering our ability to systematically identify critical conditions leading to extreme events. To address this technical gap, we introduce the Directional Unit Hydrograph (Directional-UH) model, a parsimonious approach based on the classic theory of the Unit Hydrograph. The Directional-UH extends the original theory by relaxing the assumption of spatial uniform rainfall and incorporating storm direction and speed into the unit hydrograph function. The model conceptualizes storms as rectangular structures with constant intensity moving along a linear trajectory with constant speed. We verify and validate our conceptualization by comparing with simulations, based on observations of extreme rainfall events, of the distributed hydrological model Hillslope-Link-Model (HLM) in the Turkey River basin in Iowa, USA. Then, the Turkey River basin is used as a testbed to illustrate three practical applications of the Directional-UH model. First, we identify the storm trajectory that produces the highest peak flow response. Second, we determine the storm characteristics that maximize the peak flow response by synchronizing storm motion and flood wave; we refer to this as the resonance condition. Third, we systematically explore the compounding effects of consecutive storm events with different trajectories to identify critical combinations that exacerbate the peak flow magnitude. The results on our testbed demonstrate that storm velocity has the potential to increase by a factor of two the peak flow magnitude when compared to stationary storm events. Overall, the parsimonious nature of the Directional-UH model offers a unique and valuable tool for modeling, predicting, and interpreting rainfall-runoff dynamics through the lens of storm direction, speed, and structure.

Exploring the effects of catchment morphometry on overland flow response to extreme rainfall using a 2D hydraulic-hydrological model (IBER)

The hydrological response of a catchment to heavy rainfall is determined by many environmental and climatic variables, including the catchment size, shape and morphology, land use, soil depth and type, and prevailing weather conditions. As a result of the interaction between these variables, the hydrological response of a catchment is unique and can be highly variable depending on the antecedent conditions and characteristics of the meteorological event. This complexity makes it problematic to identify the significance of individual drivers of hydrological response. Here, the role of catchment morphometry in controlling hydrological response was explored by creating abstract catchments so the impact of morphometry could be isolated from the confounding impacts of other parameters that are known to impact hydrological response and flood risk. A procedure was developed to select catchments that represent a range of global morphometries, and these were then simplified and treated as synthetic catchments. A coupled hydrological-hydraulic model (IBER) was used to model the hydrological response to 4 constructed rainfall events (one magnitude, four distribution types), consistent across all catchments, and representing torrential rainfall (60 mm h−1). Designed rainfall were equally distributed across the whole area in each catchment. Catchments were statistically partitioned into groups based on their morphometry (i.e. shape, slope, size, hypsometric slope, etc) and distinct hydrological responses were observed between groups. Catchment size was significantly related to peak flow or lag time with a power law, in line with previous studies, and relationships with other morphometric parameters were stronger when catchments were assessed in separate size groupings. Area and the average slope of catchments were key parameters in controlling peak flow magnitudes. Variation in hydrological response was much greater between catchments for the same rainfall event, than within the same catchment for different rainfall events. The results suggest that hydrological response can be broadly characterised using morphometric variables, increasingly obtainable using Earth Observation methods, providing potential benefits for flood prediction, flood alerts, and focusing where more detailed flood modelling is required.

Different responses of event-based flood to typhoon and non-typhoon rainstorms under land use change in Xixi Basin of southeastern China

There are two major types of rainstorms in the Asia-Pacific region –typhoon induced rainstorm and non-typhoon rainstorm. This study investigated and separated the different flood responses to these two types of rainstorms, based on a scheme that combined the classification of typhoon and non-typhoon rainstorm floods, the simulation from a distributed hydrological model, and a method to forward restore the impact of land use change on flood frequency analysis. For flood events in a typical basin on the southeast coast of China, the flood characteristics in response to typhoon and non-typhoon rainstorms were significantly different in three aspects: (1) The key parameters in the HEC-HMS model were systematically different. The initial loss and wave velocity of the model were apparently larger for the typhoon rainstorm flood than for the non-typhoon rainstorm flood. (2) The impacts of land use change were different, with smaller effect on typhoon induced floods than on non-typhoon floods under the same magnitude of flood peak flow. (3) Classification of two types of floods resulted in more reasonable frequency analysis affected with the land use change because the annual maximum flood series is the mixture of typhoon and non-typhoon rainstorms. Frequency analysis for the forward-restored mixture flood series showed that the land use change with the decrease in the area of forest land and the increase of garden and construction land resulted in the increase of the mean maximum flow from 2266.6 to 2510.19 m3/s, but the values of coefficient of variation were slightly altered, the ratio of skewness coefficient to variation coefficient were unchanged. The results provide new ideas and methods for a deeper understanding of the impact of land use change on flooding in typhoon and non-typhoon co-action regions.

Hydrological Modelling to Inform Forest Management: Moving Beyond Equivalent Clearcut Area

Forest disturbance can alter the hydrologic conditions of a watershed, including the frequency, magnitude, and timing of peak and low flows. Equivalent Clearcut Area (ECA) has been routinely used in watershed assessments to estimate hydrologic alteration due to forest disturbance. ECA analyses typically rely on broad regional assumptions, qualitative observations, and/or expert judgement, making it difficult to provide accurate quantitative estimates of hydrologic change. Process-based hydrological models offer an improved approach since they replicate watershed processes, can simulate land cover and climate change scenarios, and provide quantitative estimates of hydrologic change, including at ungauged points of interest. A workflow using a regionally calibrated hydrological model to investigate forest disturbance and future climate change scenarios is demonstrated. Results are contrasted with ECA-based outputs and emphasize that in addition to the amount of forest disturbance, watershed physical characteristics and the location of disturbance within a watershed influence the hydrologic response. This approach provides forest managers with quantitative outputs that support risk-based forest management decisions and presents a substantial improvement over ECA-based methods. Keywords: hydrological modelling, ECA-based analysis, watershed assessment, forest disturbance, cumulative effects, risk-based forest management

Motor Performance During Sensorimotor Training for Airway Protection in Parkinson's Disease.

Cough dysfunction is highly prevalent in Parkinson's disease (PD) and associated with pneumonia, a leading cause of death. Although research suggests that cough can be volitionally upregulated, patterns of improvements that occur during cough skill training and potential correlates remain unexamined. Therefore, we sought to characterize changes to peak flow during cough skill training, examine whether early variability predicted motor performance trajectories during treatment, and explore the relationship between peak flow during cough skill training and motor learning on a similar but untrained task (i.e., reflex cough testing). This secondary analysis of treatment data from a randomized controlled trial included 28 individuals with PD who participated in five sessions of sensorimotor training for airway protection (smTAP). During this novel cough skill training, participants completed 25 repetitions of coughs targeting peak flow 25% above their baseline. Reflex and voluntary cough testing was performed pre- and posttreatment. Bayesian multilevel growth curve models provided group and individual-level estimates of peak flow during training. The magnitude and consistency of peak flow increased during cough skill training. Variability in peak flow during the first treatment session was associated with greater improvements to peak flow in later sessions. There was no relationship between changes to peak flow during cough skill training and motor learning. Individuals with PD improved the strength and variability of cough peak flow during cough skill training. These findings provide a clinically relevant characterization of motor performance during cough skill training and lend insight into potential correlates to guide future treatment paradigms.

Multi-decadal changes in river morphology in an urbanizing watershed: Highland Creek, Toronto, Canada

Urban land development causes significant changes to river channel form and function. Outcomes are strongly conditioned by local circumstances although responses such as channel enlargement and incision are common but are highly variable in extent and detectability. Many case studies focus on small watersheds (or short reaches) and before-after conditions, and direct causation and temporal trajectories of change are not well known but often presumed to be a single step change and response. Well-documented examples in fully-urban, larger watersheds are rare, and rarer still are cases covering the full trajectory from pre-urban to fully urban land cover with accompanying data on the direct drivers of change such as discharge and stream power. Highland Creek, Toronto, has a drainage area of 102 km2 and between the early 1950s and 2000s underwent a land cover change from agricultural to completely urban in very low relief terrain with channels in narrow valleys incised locally into glacial sediments. Streamflow monitoring, land cover data and aerial photography over this seven-decade period, along with a calibrated runoff model and digital elevation data, give a complete picture over multiple epochs of the causes and changes in fluvial hydrology and geomorphology. The complete transformation of the flow regime, along with channel straightening and steepening, resulted in increases in average stream power (total and specific) of the order of ten and six times, respectively. The channel is now exceptionally energetic with maximum total and specific stream power for 2-year flood approaching 5000 Wm−1 and 300 Wm−2, respectively. The semi-alluvial and supply-limited character of the channels is also influential. Channel response is variable along the 20–25 km of channel measured and is notably different between the sub-watersheds, related to timing of development and its intersection with engineering intervention, and changing conceptions of the channel over time. In places the channel widened by a factor of four or five and changed from high sinuosity meanders to wide, bar-chute morphology, consistent with regime expectations for gravel-bed channels. In other places the process of urbanization has involved progressive engineering of the channel to convey stormwater (channelized), protect infrastructure and mitigate erosion, so that responses in these reaches are much more restricted and fluvial functions such as bend and bar development have been eliminated. Substantial channel transformation can be seen to have occurred episodically resulting from two major flood events as well as the increases in magnitude and frequency of peak flows, which limit post-flood recovery. Urbanization effects and consequences have developed gradually over a long period, rather than in a single urbanization step change, and they do not match simple models of channel evolution. In many ways urbanization of the river is ongoing, particularly in the form of geomorphically-referenced design of the channels as a response to damage from large floods and overall institutional watershed planning. The ongoing urbanization story of Highland Creek illustrates some extreme effects of urbanization as well as the complexity and contingency of response to the physical and institutional processes influencing the trajectory of urban river evolution.

Investigating how river flow regimes impact on river delta salinization through idealized modeling

IntroductionExcessive salinity can harm ecosystems and compromise the various anthropogenic activities that take place in river deltas. The issue of salinization is expected to exacerbate due to natural and/or anthropogenic climate change. Water regulations are required to secure a sufficient water supply in conditions of limited water volume availability. Research is ongoing in seek of the optimum flow distribution establishing longer lasting and fresher conditions in deltas.MethodsIn this study a three–dimensional (3D) numerical model built for an idealized delta configuration was utilized to investigate how different river discharge annual distributions affect saltwater in deltas. Five simulations were carried out by implementing annual distributions of equal water volume but different shape.ResultsThe results showed that peak flow magnitude, time of occurrence and the length of a hydrograph’s tails can be important parameters affecting stratification, freshwater residence, and renewal times. Hydrographs of small flow range and light tails were the most successful in keeping the delta and its trunk channel fresher for longer periods. Salinity distributions showed a slower response to decreasing rather than increasing river discharges. An increase in the flow rate can result in salinity standards demanded for certain activities (e.g., farming, irrigation etc.) in much shorter times. On the other hand, hydrographs with heavy tails can push the salt intrusion limit further away and be more efficient in mixing the water column. However, they present low freshwater residence and high-water renewal times.DiscussionThese results provide strong indications that it is possible to improve the freshwater conditions in deltas without seeking for additional water resources but by modifying the water distribution. The main outcomes of this work may be able to support and assist coastal scientists and stakeholders dealing with the management of freshwater resources in river deltas across the world.

Comparative analysis and risk assessment of dam-break floods: Taking Pingshuijiang Reservoir as an example

Abstract Due to the huge potential energy associated with water storage in reservoirs, dam-break floods are often catastrophically destructive for people and structures downstream. This study aims to simulate and compare floods generated under various dam-break scenarios and their downstream impacts, taking Pingshuijiang Reservoir in southeastern China as an example. A two-dimensional hydrodynamic model is used to simulate the downstream evolution of floods under three dam-break scenarios, and the breach flood and downstream inundation process are analyzed. Gradual failure of the main dam leads to near-total inundation of the nearby town over c. 1 h, allowing time for warning and evacuation. Instantaneous failure of the main dam results in larger peak flow, greater submergence depth and faster inundation (20 min), leaving little time for warning/evacuation. Instantaneous failure of the auxiliary dam generates a much lower peak flow magnitude and, although the town is still largely submerged within 45 min, the shallow water depth and low velocity are conducive to rescue/evacuation. The results show significant variation in flood process and submergence due to dam size and failure mode that provide guidance for dam-break flood risk assessment and disaster avoidance planning.

Application of Neural Networks for Hydrologic Process Understanding at a Midwestern Watershed

The Shell Creek Watershed (SCW) is a rural watershed in Nebraska with a history of chronic flooding. Beginning in 2005, a variety of conservation practices have been employed in the watershed. Those practices have since been credited with attenuating flood severity and improving water quality in SCW. This study investigated the impacts of 13 different controlling factors on flooding at SCW by using an artificial neural network (ANN)-based rainfall-runoff model. Additionally, flood frequency analysis and drought severity analysis were conducted. Special emphasis was placed on understanding how flood trends change in light of conservation practices to determine whether any relation exists between the conservation practices and flood peak attenuation, as the strategic conservation plan implemented in the watershed provides a unique opportunity to examine the potential impacts of conservation practices on the watershed. The ANN model developed in this study showed satisfactory discharge–prediction performance, with a Kling–Gupta Efficiency (KGE) value of 0.57. It was found that no individual controlling variable used in this study was a significantly better predictor of flooding in SCW, and therefore all 13 variables were used as inputs, which resulted in the satisfactory ANN model discharge–prediction performance. Furthermore, it was observed that after conservation planning was implemented in SCW, the magnitude of anomalous peak flows increased, while the magnitude of annual peak flows decreased. However, more comprehensive assessment is necessary to identify the relative impacts of conservation practices on flooding in the basin.

Application of PCSWMM for assessing the impacts of urbanization and climate changes on the efficiency of stormwater drainage systems in managing urban flooding in Robe town, Ethiopia

Study regionThis study was conducted in Robe town, Ethiopia. Study focusIn this, the PCSWMM was used to investigate the potential effects of climate change and land-use change on the peak flow magnitude and efficiency of stormwater drainage systems in managing urban flooding. Four simulation scenarios were developed to demonstrate the changes in the flooding volume and adequacy of existing systems. Moreover, the effectiveness of three low-impact developments: rain barrels, rain gardens, and a combination of both practices as a mitigation strategy in reducing flooding volume were investigated. New hydrological insights for regionThe trend of landuse change showed that the increased peak flow and flooding volume of junctions increased from 45.13 to 68.72 m3/s and 35,418–50,106 × 106 Ltr respectively, due to the imperviousness increasing from 10% to 70%. Similarly, in response to climate change, the simulated peak runoff increased by 46.9%, 34.8%, and 37.5% for, RCA4, RACMO22T, and REMO2009, respectively. This findings showed that if the current landuse and climate changes continue in the coming years, the study area threatened by the increased flooding due to the drainage systems will fail to accommodate increased peak runoff. The present study suggests the adopted LIDs can be significantly reduced the effects of flooding problems in the town.

Disentangling aggregated uncertainty sources in peak flow projections under different climate scenarios

Evaluation of peak flood magnitude and frequency in the future at a catchment scale under global warming is crucial for water resource management and flood risk management. Climate model outputs provide a leading source of information to quantify the effect of the foreseen natural and anthropogenic climate change on the environment and natural systems. However, modelling climate change impact on peak flow is subject to considerable uncertainties from the climate model discrepancies, bias correction methods, and hydrological model parameters. This study develops a framework to examine changes and disentangle uncertainties in peak flow, which is tested at five Awash catchments in Ethiopia, a region exposed to extreme flood risk. The results showed that projected extreme precipitation and peak flow magnitude could increase substantially in the coming decades by 30% to 55%. The uncertainty analysis confirms that the dominant factor in peak flood projection is climate models in catchments like Akaki (55%) and Awash H (51%), but the bias correction methods in Awash B (58%) and Kela (50%), respectively. The least important factor is the hydrological parameter set for flood projections. Moreover, the findings reveal that peak flood risks would noticeably increase in the near and far future in all catchments, in Awash located in the Tropical dry region. Therefore, various state water agencies from local to national scales must take certain non-structural/structural measures to mitigate flood risks in the future, and to adapt to future climate.

Climate impact emergence and flood peak synchronization projections in the Ganges, Brahmaputra and Meghna basins under CMIP5 and CMIP6 scenarios

The densely populated delta of the three river systems of the Ganges, Brahmaputra and Meghna is highly prone to floods. Potential climate change-related increases in flood intensity are therefore of major societal concern as more than 40 million people live in flood-prone areas in downstream Bangladesh. Here we report on new flood projections using a hydrological model forced by bias-adjusted ensembles of the latest-generation global climate models of CMIP6 (SSP5-8.5/SSP1-2.6) in comparison to CMIP5 (RCP8.5/RCP2.6). Results suggest increases in peak flow magnitude of 36% (16%) on average under SSP5-8.5 (SSP1-2.6), compared to 60% (17%) under RCP8.5 (RCP2.6) by 2070–2099 relative to 1971–2000. Under RCP8.5/SSP5-8.5 (2070–2099), the largest increase in flood risk is projected for the Ganges watershed, where higher flood peaks become the ‘new norm’ as early as mid-2030 implying a relatively short time window for adaptation. In the Brahmaputra and Meghna rivers, the climate impact signal on peak flow emerges after 2070 (CMIP5 and CMIP6 projections). Flood peak synchronization, when annual peak flow occurs simultaneously at (at least) two rivers leading to large flooding events within Bangladesh, show a consistent increase under both projections. While the variability across the ensemble remains high, the increases in flood magnitude are robust in the study basins. Our findings emphasize the need of stringent climate mitigation policies to reduce the climate change impact on peak flows (as presented using SSP1-2.6/RCP2.6) and to subsequently minimize adverse socioeconomic impacts and adaptation costs. Considering Bangladesh’s high overall vulnerability to climate change and its downstream location, synergies between climate change adaptation and mitigation and transboundary cooperation will need to be strengthened to improve overall climate resilience and achieve sustainable development.

Multiscale and multi event evaluation of short-range real-time flood forecasting in large metropolitan areas

Many large metropolitan areas are especially susceptible to floods generated by heavy, short-duration rainfall. The high density of people, buildings and infrastructure in these areas underline the importance of developing flood resilient cities and communities. An accurate real-time flood forecasting system can support decision making for launching preparedness and response actions in short-range (hours to days), and assist mitigating the disturbances caused by floods. This study explores the short-range predictive capability of a real-time flood forecast system by coupling the High-Resolution Rapid Refresh (HRRR) meteorological forecasted variables with a fully distributed hydrological model (WRF-Hydro). We provide a comprehensive analysis of short-range (36 h) forecasts for 19flood events generated by heavy rainfall in small urban and suburban watersheds (<200 km2) in the National Capital Region of the United States. Flood forecast performance are then assessed using different metrics based on observed data from U.S. Geological Survey stream gauges and reanalysis simulations using the StageIV quantitative precipitation estimates. Results show that despite the high variability of the HRRR cycle-to-cycle precipitation forecasts, the real-time flood forecast system can produce skillful forecasts with similar overall performance as the reanalysis simulations, achieving 65 % of flood detection rate. This variability had more impact on forecast skill in smaller subbasins, and flood forecasts were more consistent for longer duration and larger spatial extent rainfall. Hourly flood forecasts performed well even in smaller watersheds, correctly detecting flood occurrence with up to 34 h lead time and resulting in low peak flow magnitude and timing errors.

Evaluating the impact of post-processing medium-range ensemble streamflow forecasts from the European Flood Awareness System

Abstract. Streamflow forecasts provide vital information to aid emergency response preparedness and disaster risk reduction. Medium-range forecasts are created by forcing a hydrological model with output from numerical weather prediction systems. Uncertainties are unavoidably introduced throughout the system and can reduce the skill of the streamflow forecasts. Post-processing is a method used to quantify and reduce the overall uncertainties in order to improve the usefulness of the forecasts. The post-processing method that is used within the operational European Flood Awareness System is based on the model conditional processor and the ensemble model output statistics method. Using 2 years of reforecasts with daily timesteps, this method is evaluated for 522 stations across Europe. Post-processing was found to increase the skill of the forecasts at the majority of stations in terms of both the accuracy of the forecast median and the reliability of the forecast probability distribution. This improvement is seen at all lead times (up to 15 d) but is largest at short lead times. The greatest improvement was seen in low-lying, large catchments with long response times, whereas for catchments at high elevation and with very short response times the forecasts often failed to capture the magnitude of peak flows. Additionally, the quality and length of the observational time series used in the offline calibration of the method were found to be important. This evaluation of the post-processing method, and specifically the new information provided on characteristics that affect the performance of the method, will aid end users in making more informed decisions. It also highlights the potential issues that may be encountered when developing new post-processing methods.

Temporal disaggregation of daily rainfall measurements using regional reanalysis for hydrological applications

Accurate rainfall datasets with high temporal and spatial resolutions are crucial for most hydrological applications. One potentially valuable source of rainfall data that has consistent spatial and temporal resolutions are atmospheric reanalysis products. However, while such data sets can provide a physically consistent representation of rainfall over large spatial and temporal extents, they are generally less accurate than observed datasets at daily scales. In contrast, while the gauge measurements are accurate source of rainfall data, sub-daily observations are spatially sparse and are of shorter length than daily observations. While the temporal resolution of daily observations can be enhanced using temporal disaggregation methods, they are often applied stochastically with a focus on capturing the fine-scale statistical properties rather than generating a best estimate time series useful for hindcasting purposes. The increasing availability of high resolution regional reanalysis products prompts the question whether they can be used to temporally disaggregate daily observations to derive high-resolution estimates of sub-daily rainfalls suitable for hydrologic applications. This study investigates the efficacy of a simple disaggregation approach to temporally disaggregate daily rainfalls to hourly values using a regional reanalysis at moderate spatial resolutions. The approach is tested on attributes relevant to a wide range of hydrological applications. The selected performance metrics include the distribution and frequency of various sub-daily rainfall accumulations, statistics characterising the sequencing and central tendency of sub-daily rainfalls, and the efficacy of areal estimates of sub-daily rainfalls for simulating catchment streamflows. Categorical evaluation shows that the disaggregated rainfalls reduce the frequency of false alarms and improves the probability of detection compared to the use of raw reanalysis estimates. However, a mixed performance in capturing fine-scale statistical characteristics suggests that the disaggregation approach is less robust for applications that rely solely on high-resolution rainfall characteristics. In hydrological evaluation, when compared to estimates based on raw reanalysis or uniformly disaggregated daily observations, the disaggregated catchment rainfalls improve the simulation of the magnitude and timing of peak flows, and the accuracy of derived flood frequency estimates. The proposed disaggregation method is easily applied to any high-resolution dataset and has the potential to be used in hydrological applications that rely heavily on sub-daily characterisation, with a varying performance across the target applications.

Spatiotemporal variations in water sources and mixing spots in a riparian zone

Abstract. Riparian zones are known to modulate water quality in stream corridors. They can act as buffers for groundwater-borne solutes before they enter the stream at harmful, high concentrations or facilitate solute turnover and attenuation in zones where stream water (SW) and groundwater (GW) mix. This natural attenuation capacity is strongly controlled by the dynamic exchange of water and solutes between the stream and the adjoining aquifer, creating potential for mixing-dependent reactions to take place. Here, we couple a previously calibrated transient and fully integrated 3D surface–subsurface numerical flow model with a hydraulic mixing cell (HMC) method to map the source composition of water along a net losing reach (900 m) of the fourth-order Selke stream and track its spatiotemporal evolution. This allows us to define zones in the aquifer with more balanced fractions of the different water sources per aquifer volume (called mixing hot spots), which have a high potential to facilitate mixing-dependent reactions and, in turn, enhance solute turnover. We further evaluated the HMC results against hydrochemical monitoring data. Our results show that, on average, about 50 % of the water in the alluvial aquifer consists of infiltrating SW. Within about 200 m around the stream, the aquifer is almost entirely made up of infiltrated SW with practically no significant amounts of other water sources mixed in. On average, about 9 % of the model domain could be characterized as mixing hot spots, which were mainly located at the fringe of the geochemical hyporheic zone rather than below or in the immediate vicinity of the streambed. This percentage could rise to values nearly 1.5 times higher following large discharge events. Moreover, event intensity (magnitude of peak flow) was found to be more important for the increase in mixing than event duration. Our modeling results further suggest that discharge events more significantly increase mixing potential at greater distances from the stream. In contrast near and below the stream, the rapid increase in SW influx shifts the ratio between the water fractions to SW, reducing the potential for mixing and the associated reactions. With this easy-to-transfer framework, we seek to show the applicability of the HMC method as a complementary approach for the identification of mixing hot spots in stream corridors, while showing the spatiotemporal controls of the SW–GW mixing process and the implications for riparian biogeochemistry and mixing-dependent turnover processes.

Geomorphic effects of a run-of-the-river dam in a multi-driver context: The case of the Upper Garonne (Central Pyrenees)

In this paper, we evaluate morphological changes related to the Plan d'Arem dam (1970), a run-of-river (RoR) dam located on the Upper Garonne (central Pyrenees), and disentangle its morphological effects from other drivers (post-Little Ice Age [LIA] climate change, changes in agricultural practice, catchment afforestation, upstream damming, and bypassing). The work is based on a before-after-control-impact approach, a space-time framework that allowed the stating of four hypotheses distinguishing the effects of the considered dam from other pressures. We first examined the potential reduction to the flow regime (QL) and bedload transport (QS) from these pressures, then assessed planimetric changes (1942–2019), vertical evolution (1922–2014), and sediment size within the channel. The results show the river completed adjustments related to post-LIA climate change and catchment afforestation at the beginning of the study period, with channel narrowing affecting the whole study reach and ranging from 0.6% to 1.2% yr−1. Upstream dams and catchment afforestation reduced both the frequency and magnitude of peak flows and sediment supply, resulting in an increase in the channel narrowing rate on the upstream sub-reach (−1.2% yr−1). However, downstream tributaries buffered these changes, and no downstream propagation was found. The effects of the Plan d'Arem started around 15 yr after its construction, with channel narrowing at a rate of 0.9% yr−1 until the 2010s. The exceptional flood of June 2013 resulted in important channel widening followed by a new period of narrowing upstream of the Plan d'Arem dam, combined with channel stability downstream caused by a new dam management regime (flushing actions). We conclude that the before-after-control-impact approach is effective for isolating the effects of an RoR dam from those of other pressures, and that flushing actions mitigated the effects of the dam.

Barriers to Real-Time Control of Stormwater Systems

Real-time control of stormwater infrastructure is an emerging technology that can improve stormwater system function. However, this technology has not been adopted widely, nor is it typically addressed within current stormwater regulations. This study addressed these gaps by identifying barriers to the adoption of real-time controls of stormwater and exploring ways in which real-time controls of stormwater can fit within current regulatory frameworks. To identify barriers, a survey was distributed to municipal and consultant stormwater engineers in Wisconsin. The results indicated that cost, operations and maintenance, and failure to qualify for regulatory credits are significant perceived barriers to real-time control of stormwater. Municipal engineers were reluctant to adopt real-time controls and were concerned with regulatory credits for real-time controls. In light of these concerns, a case study was performed to evaluate how a detention pond augmented with a real-time control valve at the outlet performed in terms of common stormwater design standards and regulatory criteria, including peak flow reduction and total suspended solids (TSS) removal. Model results indicated that the controlled pond reduced the magnitude of peak flows. It also improved annual total suspended solids removal from 70% to 96%, thereby exceeding the 80% TSS removal requirement for municipal separate storm sewer systems in many US states. Given the identified barriers and model performance, this study discussed potential paths forward for overcoming barriers in attributing regulatory credits to real-time controls of stormwater.

Parsing Weather Variability and Wildfire Effects on the Post‐Fire Changes in Daily Stream Flows: A Quantile‐Based Statistical Approach and Its Application

Determining wildland fire impacts on streamflow can be problematic as the hydrology in burned watersheds is influenced by post-fire weather conditions. This study presents a quantile-based analytical framework for assessing fire impacts on low and peak daily flow magnitudes, while accounting for post-fire weather influences. This framework entails (a) the bootstrap method to compute the relative change in the post-fire annual flow and weather statistics, (b) Double Mass analysis to detect if post-fire baseflow and quick flow yield ratios are significantly altered, and (c) a quantile regression method to parse fire effects on flow at a specific quantile. We illustrate the applicability of this analytical framework using 44 western US streams with at least 5% of their watershed area burned. Results indicate that large, high-severity burns in upland watersheds can raise the streamflow magnitude at the 0.05 th and 0.95 th quantiles for at least the five post-fire years. Quantile regression results show that the median fire-related increase in flow for the five post-fire years can be up to 5000% (Standard Error; SE < 2%) at the 0.05 th quantile and 161% (SE < 10%) at the 0.95 th quantile. The fire-related increase in flow was often pronounced at the 0.05 th quantile for streams in the Pacific Northwest and California regions. The difference in fire effects on flow (at both quantiles) across streams was related to post-fire weather, pyrology, physiography, and land cover. The proposed analytical framework can be useful for detecting and quantifying fire effects on the low and peak stream flows in burned watersheds without overlapping disturbances.