Testing of the Storm Water Management Model Low Impact Development Modules.

Stormwater infrastructure designers and operators rely heavily on the United States Environmental Protection Agency's Storm Water Management Model (SWMM) to simulate stormwater and wastewater infrastructure performance. Since its inception in the late 1970s, improvements and extensions have been tested and evaluated rigorously to verify the accuracy of the model. As a continuation of this progress, the main objective of this study was to quantify how accurately SWMM simulates the hydrologic activity of low impact development (LID) storm control measures. Model performance was evaluated by quantitatively comparing empirical data to model results using a multievent, multiobjective calibration method. The calibration methodology utilized the PEST software, a Parameter ESTimation tool, to determine unmeasured hydrologic parameters for SWMM's LID modules. The calibrated LID modules' Nash-Sutcliffe efficiencies averaged 0.81; average percent bias (PBIAS) -9%; average ratio of root mean square error to standard deviation of measured values 0.485; average index of agreement 0.94; and the average volume error, simulated vs. observed, was +9%. SWMM accurately predicted the timing of peak flows, but usually underestimated their magnitudes by 10%. The average volume reduction, measured outflow volume divided by inflow volume, was 48%. We had more difficulty in calibrating one study, an infiltration trench, which identified a significant limitation of the current version of the SWMM LID module; it cannot simulate lateral exfiltration of water out of the storage layers of a LID storm control measure. This limitation is especially severe for a deep LIDs, such as infiltration trenches. Nevertheless, SWMM satisfactorily simulated the hydrologic performance of eight of the nine LID practices.

A flexible modeling framework for hydraulic and water quality performance assessment of stormwater green infrastructure.

A flexible framework has been created for modeling multi-dimensional hydrological and water quality processes within stormwater green infrastructure (GI) practices. The framework conceptualizes GI practices using blocks (spatial features) and connectors (interfaces) representing functional components of a GI. The blocks represent spatial features with the ability to store water (e.g., pond, soil, benthic sediments, manhole, or a generic storage zone) and water quality constituents including chemical constituents and particles. The hydraulic module can solve a combination of Richards equation, kinematic/diffusive wave, Darcy, and other user-provided flow models. The particle transport module is based on performing mass-balance on particles in different phases, e.g., mobile and deposited in soil with constitutive theories controlling their transport, settling, deposition, and release. The reactive transport modules allow constituents to be in dissolved, sorbed, bound to particles, and undergo user-defined transformations. Four applications of the modeling framework are presented that demonstrate its flexibility for simulating urban GI performance.

PySWMM: The Python Interface to Stormwater Management Model (SWMM).

Stormwater management seeks to reduce runoff from rain or melted snow and improve water quality. Where it can absorb into soil, runoff is filtered and returns to streams, rivers, and aquifers, but in developed areas, precipitation often cannot soak into the ground because impervious surfaces (e.g., pavement, buildings), and already saturated soils can create excess runoff. This water, which can contain pollutants, then runs across urban surfaces and into storm drains, drainage ditches, and sewer systems. Stormwater runoff can cause flooding, erosion, infrastructure and habitat damage, and contamination (including combined and sanitary sewer overflows). In urban and developed areas, effective stormwater management that routes and detains stormwater helps to mitigate these impacts and improve water quality.

Storm Water Management Model: Performance Review and Gap Analysis.

The storm water management model (SWMM) is a widely used tool for urban drainage design and planning. Hundreds of peer-reviewed articles and conference proceedings have been written describing applications of SWMM. This review focuses on collecting information on model performance with respect to calibration and validation in the peer-reviewed literature. The major developmental history and applications of the model are also presented. The results provide utility to others looking for a quick reference to gauge the integrity of their own unique SWMM application. A gap analysis assesses the model's ability to perform water-quality simulations considering green infrastructure (GI)/low impact development (LID) designs and effectiveness. It is concluded that the level of detail underlying the conceptual model of SWMM versus its overall computational parsimony is well balanced-making it an adequate model for large and medium-scale hydrologic applications. However, embedding a new mechanistic algorithm or providing user guidance for coupling with other models will be necessary to realistically simulate diffuse pollutant sources, their fate and transport, and the effectiveness of GI/LID implementation scenarios.

A reactive species model for chlorine decay and THM formation under rechlorination conditions.

Chlorine is typically used within drinking water distribution systems to maintain a disinfectant residual and minimize biological regrowth. Typical distribution system models describe the loss of disinfectant due to reactions within the water matrix as first order with respect to chlorine concentration, with the reactants in excess. Recent work, however, has investigated relatively simple dynamic models that include a second, hypothetical reactive species. This work extends these latter models to account for discontinuities associated with rechlorination events, such as those caused by booster chlorination and by mixing at distribution system junction nodes. Mathematical arguments show that the reactive species model will always represent chlorine decay better than, or as well as, a first-order model, under single dose or rechlorination conditions; this result is confirmed by experiments on five different natural waters, and is further shown that the reactive species model can be significantly better under some rechlorination conditions. Trihalomethane (THM) formation was also monitored, and results show that a linear relationship between total THM (TTHM) formation and chlorine demand is appropriate under both single dose and rechlorination conditions. This linear relationship was estimated using the modeled chlorine demand from a calibrated reactive species model, and using the measured chlorine demand, both of which adequately represented the TTHM formation.