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1. Stormwater control impacts on runoff volume and peak flow: A meta‐analysis of watershed modelling studies

   https://doi.org/10.1002/hyp.13784  

   Bell, Colin D.; Wolfand, Jordyn M.; Panos, Chelsea L.; Bhaskar, Aditi S.; Gilliom, Ryan L.; Hogue, Terri S.; Hopkins, Kristina G.; Jefferson, Anne J. (May 2020, Hydrological Processes)

   Abstract Decades of research has concluded that the percent of impervious surface cover in a watershed is strongly linked to negative impacts on urban stream health. Recently, there has been a push by municipalities to offset these effects by installing structural stormwater control measures (SCMs), which are landscape features designed to retain and reduce runoff to mitigate the effects of urbanisation on event hydrology. The goal of this study is to build generalisable relationships between the level of SCM implementation in urban watersheds and resulting changes to hydrology. A literature review of 185 peer‐reviewed studies of watershed‐scale SCM implementation across the globe was used to identify 52 modelling studies suitable for a meta‐analysis to build statistical relationships between SCM implementation and hydrologic change. Hydrologic change is quantified as the percent reduction in storm event runoff volume and peak flow between a watershed with SCMs relative to a (near) identical control watershed without SCMs. Results show that for each additional 1% of SCM‐mitigated impervious area in a watershed, there is an additional 0.43% reduction in runoff and a 0.60% reduction in peak flow. Values of SCM implementation required to produce a change in water quantity metrics were identified at varying levels of probability. For example, there is a 90% probability (high confidence) of at least a 1% reduction in peak flow with mitigation of 33% of impervious surfaces. However, as the reduction target increases or mitigated impervious surface decreases, the probability of reaching the reduction target also decreases. These relationships can be used by managers to plan SCM implementation at the watershed scale. 

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2. Assessing urban rainfall‐runoff response to stormwater management extent

   https://doi.org/10.1002/hyp.14287  

   Miller, Andrew J.; Welty, Claire; Duncan, Jonathan M.; Baeck, Mary Lynn; Smith, James A. (July 2021, Hydrological Processes)

   Abstract We report an empirical analysis of the hydrologic response of three small, highly impervious urban watersheds to pulse rainfall events, to assess how traditional stormwater management (SWM) alters urban hydrographs. The watersheds vary in SWM coverage from 3% to 61% and in impervious cover from 45% to 67%. By selecting a set of storm events that involved a single rainfall pulse with >96% of total precipitation delivered in 60 min, we reduced the effect of differences between storms on hydrograph response to isolate characteristic responses attributable to watershed properties. Watershed‐average radar rainfall data were used to generate local storm hyetographs for each event in each watershed, thus compensating for the extreme spatial and temporal heterogeneity of short‐duration, intense rainfall events. By normalizing discharge values to the discharge peak and centring each hydrograph on the time of peak we were able to visualize the envelope of hydrographs for each group and to generate representative composite hydrographs for comparison across the three watersheds. Despite dramatic differences in the fraction of watershed area draining to SWM features across these three headwater tributaries, we did not find strong evidence that SWM causes significant attenuation of the hydrograph peak. Hydrograph response for the three watersheds is remarkably uniform despite contrasts in SWM, impervious cover and spatial patterns of land cover type. The primary difference in hydrograph response is observed on the recession limb of the hydrograph, and that change appears to be associated with higher storm‐total runoff in the watersheds with more area draining to SWM. Our findings contribute more evidence to the work of previous authors suggesting that SWM is less effective at attenuating urban hydrographs than is commonly assumed. Our findings also are consistent with previous work concluding that percent impervious cover may have greater influence on runoff volume than percent SWM coverage. 

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3. Flood Impacts on Critical Infrastructure in a Coastal Floodplain in Western Puerto Rico during Hurricane María

   https://doi.org/10.3390/hydrology8030104  

   Mejia Manrique, Said A.; Harmsen, Eric W.; Khanbilvardi, Reza M.; González, Jorge E. (September 2021, Hydrology)

   null (Ed.)

   Flooding during extreme weather events damages critical infrastructure, property, and threatens lives. Hurricane María devastated Puerto Rico (PR) on 20 September 2017. Sixty-four deaths were directly attributable to the flooding. This paper describes the development of a hydrologic model using the Gridded Surface Subsurface Hydrologic Analysis (GSSHA), capable of simulating flood depth and extent for the Añasco coastal flood plain in Western PR. The purpose of the study was to develop a numerical model to simulate flooding from extreme weather events and to evaluate the impacts on critical infrastructure and communities; Hurricane María is used as a case study. GSSHA was calibrated for Irma, a Category 3 hurricane, which struck the northeastern corner of the island on 7 September 2017, two weeks before Hurricane María. The upper Añasco watershed was calibrated using United States Geological Survey (USGS) stream discharge data. The model was validated using a storm of similar magnitude on 11–13 December 2007. Owing to the damage sustained by PR’s WSR-88D weather radar during Hurricane María, rainfall was estimated in this study using the Weather Research Forecast (WRF) model. Flooding in the coastal floodplain during Hurricane María was simulated using three methods: (1) Use of observed discharge hydrograph from the upper watershed as an inflow boundary condition for the coastal floodplain area, along with the WRF rainfall in the coastal flood plain; (2) Use of WRF rainfall to simulate runoff in the upper watershed and coastal flood plain; and (3) Similar to approach (2), except the use of bias-corrected WRF rainfall. Flooding results were compared with forty-two values of flood depth obtained during face-to-face interviews with residents of the affected communities. Impacts on critical infrastructure (water, electric, and public schools) were evaluated, assuming any structure exposed to 20 cm or more of flooding would sustain damage. Calibration equations were also used to improve flood depth estimates. Our model included the influence of storm surge, which we found to have a minimal effect on flood depths within the study area. Water infrastructure was more severely impacted by flooding than electrical infrastructure. From these findings, we conclude that the model developed in this study can be used with sufficient accuracy to identify infrastructure affected by future flooding events. 

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

   https://doi.org/10.3390/hydrology10020027  

   Aliev, Annushka; Koya, Sinan Rasiya; Kim, Incheol; Eun, Jongwan; Traylor, Elbert; Roy, Tirthankar (February 2023, Hydrology)

   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. 

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5. Developing a Modeling Framework to Simulate Compound Flooding: When Storm Surge Interacts With Riverine Flow

   https://doi.org/10.3389/fclim.2020.609610  

   Loveland, Mark; Kiaghadi, Amin; Dawson, Clint N.; Rifai, Hanadi S.; Misra, Shubhra; Mosser, Helena; Parola, Alessandro (February 2021, Frontiers in Climate)

   null (Ed.)

   Compound flooding is a physical phenomenon that has become more destructive in recent years. Moreover, compound flooding is a broad term that envelops many different physical processes that can range from preconditioned, to multivariate, to temporally compounding, or spatially compounding. This research aims to analyze a specific case of compound flooding related to tropical cyclones where the compounding effect is on coastal flooding due to a combination of storm surge and river discharge. In recent years, such compound flood events have increased in frequency and magnitude, due to a number of factors such as sea-level rise from warming oceans. Therefore, the ability to model such events is of increasing urgency. At present, there is no holistic, integrated modeling system capable of simulating or forecasting compound flooding on a large regional or global scale, leading to the need to couple various existing models. More specifically, two more challenges in such a modeling effort are determining the primary model and accounting for the effect of adjacent watersheds that discharge to the same receiving water body in amplifying the impact of compound flooding from riverine discharge with storm surge when the scale of the model includes an entire coastal line. In this study, we investigated the possibility of using the Advanced Circulation (ADCIRC) model as the primary model to simulate the compounding effects of fluvial flooding and storm surge via loose one-way coupling with gage data through internal time-dependent flux boundary conditions. The performance of the ADCIRC model was compared with the Hydrologic Engineering Center- River Analysis System (HEC-RAS) model both at the watershed and global scales. Furthermore, the importance of including riverine discharges and the interactions among adjacent watersheds were quantified. Results showed that the ADCIRC model could reliably be used to model compound flooding on both a watershed scale and a regional scale. Moreover, accounting for the interaction of river discharge from multiple watersheds is critical in accurately predicting flood patterns when high amounts of riverine flow occur in conjunction with storm surge. Particularly, with storms such as Hurricane Harvey (2017), where river flows were near record levels, inundation patterns and water surface elevations were highly dependent on the incorporation of the discharge input from multiple watersheds. Such an effect caused extra and longer inundations in some areas during Hurricane Harvey. Comparisons with real gauge data show that adding internal flow boundary conditions into ADCIRC to account for river discharge from multiple watersheds significantly improves accuracy in predictions of water surface elevations during coastal flooding events. 

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