Use of Spray Applied Pipe Linings as a Structural Renewal for Gravity Storm Water Conveyance Conduits

2019 ◽  
Author(s):  
Jeffrey Syar ◽  
Mohammad Najafi ◽  
Zahra Kohankar Kouchesfehani ◽  
Seyed Korky ◽  
Amin Darabnoush Tehrani
Keyword(s):  
Storm Water ◽  
Water Conveyance

scholarly journals Effects of Rainfall onE. coliConcentrations at Door County, Wisconsin Beaches

2009 ◽  
Vol 2009 ◽  
pp. 1-9 ◽  
Author(s):  
Gregory T. Kleinheinz ◽  
Colleen M. McDermott ◽  
Sarah Hughes ◽  
Amanda Brown
Keyword(s):  
Lake Michigan ◽  
Water Discharge ◽  
Storm Water ◽  
Water Runoff ◽  
E Coli ◽  
Storm Water Runoff ◽  
Water Conveyance ◽  
Beach Closures ◽  
The Impact ◽  
Beach Water

Rainfall and its associated storm water runoff have been associated with transport of many pollutants into beach water. Fecal material, from a variety of animals (humans, pets, livestock, and wildlife), can wash into beach water following rainfall and result in microbial contamination of the beach. Many locales around the world issue pre-emptive beach closures associated with rainfall. This study looked at eight beaches located in Door County, Wisconsin, on Lake Michigan to determine the impact of rainfall onE. coliconcentrations in beach water. Water samples were collected from beach water and storm water discharge pipes during rainfall events of 5 mm in the previous 24 hours. Six of the eight beaches showed a significant association between rainfall and elevated beach waterE. coliconcentrations. The duration of the impact of rainfall on beach waterE. coliconcentrations was variable (immediate to 12 hours). Amount of rainfall in the days previous to the sampling did not have significant impact on theE. coliconcentrations measured in beach water. Presence of storm water conveyance pipes adjacent to the beach did not have a uniform impact on beach waterE. coliconcentrations. This study suggests that each beach needs to be examined on its own with regard to rain impacts onE coliconcentrations in beach water.

Evaluating a Sewershed Urban Storm Water Model for Variability in Parameter Sensitivity and Resolution Effects

2020 ◽  
Author(s):  
Zhaokai Dong ◽  
Daniel Bain ◽  
Murat Akcakaya ◽  
Carla Ng
Keyword(s):  
Pipe Flow ◽  
Peak Flow ◽  
Model Performance ◽  
Parameter Sensitivity ◽  
Geometric Parameters ◽  
Storm Water ◽  
Parameter Estimates ◽  
Kappa Statistics ◽  
Thiessen Polygon ◽  
Urban Storm

A high-quality parameter set is essential for reliable stormwater models. Model performance can be improved by optimizing initial parameter estimates. Parameter sensitivity analysis is a robust way to distinguish the influence of parameters on model output and efficiently target the most important parameters to modify. This study evaluates efficient construction of a sewershed model using relatively low-resolution (e.g., 30 meter DEM) data and explores model sensitivity to parameters and regional characteristics using the EPA’s Storm Water Management Model (SWMM). A SWMM model was developed for a sewershed in the City of Pittsburgh, where stormwater management is a critical concern. We assumed uniform or log-normal distributions for parameters and used Monte Carlo simulations to explore and rank the influence of parameters on predicted surface runoff, peak flow, maximum pipe flow and model performance, as measured using the Nash–Sutcliffe efficiency metric. By using the Thiessen polygon approach for sub-catchment delineations, we substantially simplified the parameterization of the areas and hydraulic parameters. Despite this simplification, our approach provided good agreement with monitored pipe flow (Nash–Sutcliffe efficiency: 0.41 – 0.85). Total runoff and peak flow were very sensitive to the model discretization. The size of the polygons (modeled subcatchment areas) and imperviousness had the most influence on both outputs. The imperviousness, infiltration and Manning’s roughness (in the pervious area) contributed strongly to the Nash-Sutcliffe efficiency (70%), as did pipe geometric parameters (92%). Parameter rank sets were compared by using kappa statistics between any two model elements to identify generalities. Within our relatively large (9.7 km^2) sewershed, optimizing parameters for the highly impervious (>50%) areas and larger pipes lower in the network contributed most to improving Nash–Sutcliffe efficiency. The geometric parameters influence the water quantity distribution and flow conveyance, while imperviousness determines the subcatchment subdivision and influences surface water generation. Application of the Thiessen polygon approach can simplify the construction of large-scale urban storm water models, but the model is sensitive to the sewer network configuration and care must be taken in parameterizing areas (polygons) with heterogenous land uses.

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