Dynamic Storm Simulation

Due to a complex interaction between Bay of Fundy tides, ice jamming and dyke constrictions, Truro – a low-lying urban development area in Nova Scotia – experiences widespread and frequent flooding from the Salmon River estuary and its river tributaries.

The Joint Flood Advisory Committee (JFAC) therefore decided to commission one of the most comprehensive flood risk studies ever undertaken in Atlantic Canada, which involved extensive 1D, 2D and 3D hydrodynamic modeling to simulate the various floodplain processes.

PCSWMM was used for its capacity to develop over 7,000 river and floodplain cross sections and a 17km² 2D mesh with over 14,000 cells. A radar-rainfall model of the calibration flood event was also developed using PCSWMM based on 1km² resolution historical radar data. The radar analysis found that rainfall amounts in upper regions of the watershed were twice as much as those recorded at the rain gauges located at the downstream end of the watershed.

The completed PCSWMM model not only demonstrated the importance of simulating spatial variations in rainfall for calibration purposes, but it was also used in developing floodplain mapping, running nearly 200 simulations and assessing over 40 large-scale potential flood mitigation solutions – providing the JFAC with numerical support for recommendations to alleviate flood risk.

With continuing urbanization and climate change, it’s critical that the dynamics of urban flooding be better understood to improve prediction and mitigate water-related hazards under changing conditions. The large number of human-created structures and hydrologic, hydraulic and hydrometeorological processes involved makes real-time prediction of flood inundation in urban areas particularly challenging.

For the Dallas-Fort Worth metroplex (DFW), accurate prediction of the extent and depth of flooding and related hazards is equally imperative. In response, PCSWMM was utilized to assess the impact of variations in precipitation and impervious cover on simulated urban flood inundation maps.

The main study area was the 3.3 km² Forest Park–Berry catchment in North Central Texas, which has a high density of underground storm drainage. Storm drainage network performance between current conditions and altered conditions under continuing urbanization and climate change were studied.

PCSWMM, which combines a semi-distributed hydrologic routing model, a 1D hydraulic model for the storm drainage network and a 2D overland flow model, was chosen to create the 1D-2D integrated model based on its capacity to connect junctions, nodes, conduits and links to a 2D overland flow model for 1D-2D dual drainage modeling, and the need to account for both types of flow in the study basins.

Findings of this project are now being used as part of the flash flood warning system under implementation for the area. The sensitivity analyses undertaken are helping to assess the feasibility of real-time operation of a 1D-2D model, to identify potential alternatives for reduced complexity and computational requirements, and to increase lead time by the use of rainfall nowcasts.

Each year, the Brazilian City of São Paulo suffers from the impact of heavy rains. Flooding occurs in various parts of the city due to the large number of culverts, canals and bridges with insufficient sections for stormwater, silted streams and obstructions by debris.

To promote stormwater management efficiency and avoid the social and economic losses as well as land use issues associated with flooding, the São Paulo City Hall (PMSP) invested in a flood management system centered on evaluation, monitoring, forecasting and warning.

Hydrological modeling of the system’s subcatchments and hydraulic modeling of its main channels were performed using PCSWMM. The software’s Real-Time feature was utilized to disclose prediction results for flood inundation sites addressed to the Emergency Management Center (CGE). PCSWMM was chosen due to the software’s intuitive graphical interface, ease of allowing access to information and ability to analyze large, complex problems.

Rain forecast was taken every 10 minutes to a prediction horizon of 3 hours, and PCSWMM delivered hydraulic gradelines and hydrographs along the simulated channels, reservoir states, flood inundation extents and affected buildings of six priority watersheds. Rainfall and prediction data were obtained, processed and disclosed by the Flooding Alert System of São Paulo (SAISP).

Serving as an important assistance to emergency management during floods and while forecasting heavy rains, the model provides real-time, user-friendly information on affected areas. It is also able to identify inefficiencies and failures of hydraulic structures and operating rules and/or procedures - indicating the best improvement opportunities.

In addition, the developed system allows for fast access to subcatchment data and alerts CGE technicians of vulnerable areas in advance so that preventive and contingency measures can be taken.

Flooding and overflows are a recurring problem in São Paulo, Brazil due in part to increased impervious surface areas, inefficiency of drainage structures and channel obstructions. The Anhangabaú Watershed contains a major interconnection passage where heavy rains create a chaotic situation for the population as well as losses to the national economy.

In seeking a solution to flooding in the 540-ha basin, São Paulo City Hall hired the Hydraulics Technology Center Foundation (FCTH) to evaluate the performance of two traditional alternatives and to offer a new alternative based on modern concepts of water resources management.

A complex PCSWMM modeling network was developed, representing 110 km of roads, 50 km of drainage networks and 2,800 joint structures such as curb inlets and drainage grates. Subsequently, the PCSWMM 2D module was applied to the entire watershed to represent surface flooding while considering DTM and buildings as restrictions to the water flow.

Three alternatives intended to mitigate the flooding problem in the lower valley were evaluated: (A) 2 flood detention reservoirs and reinforcement of the main gallery system – designed to ensure safety against 25-year return period events; (B) reinforcement of the main gallery and flow derivation tunnel leading to the Tamanduateí River for a 100-year return period; and (C) distributed linear retention spread over the watershed in stages of return periods of 10-/25-/100-years.

By using a multi-criteria analysis technique – and considering the solution efficiency as well as prevented damages and factors such as cost, environmental impacts and public attention – the project pointed to alternative C as the most effective method to solve the drainage problems Brazil faces. The solution has since been implemented to help reduce flooding throughout São Paulo’s Anhangabaú Watershed.

The Humber River Watershed is no exception to the downstream flood risk from impervious surface creation. Working together with the Toronto Region Conservation Authority (TRCA), AMEC Foster Wheeler retained PCSWMM to utilize radar-generated rainfall to support the evaluation of stormwater management practices for quantity (flood) control in the Toronto Region.

PCSWMM was selected due to its widespread usage, urban and rural hydrologic algorithms, GIS data structure interface and event and continuous modeling capabilities. SUSTAIN’s Best Management Practice (BMP) Siting tool was used to support the selection of suitable BMP locations that meet user-defined site suitability criteria such as size of drainage area, slope, hydrological soil group, groundwater table depth, property type and buffer distance from buildings, roads and streams.

PCSWMM’s radar-rainfall tools were used to transpose recent significant regional storms to the watershed. The transposed radar-rainfall data sets were found to be an excellent surrogate to stress test watersheds. In addition, radar data – used in place of point gauge data – successfully represented both the temporal and spatial variability of the storms, while showing a moderate increase (0% - 20%) in regional storm peaks.

The calibrated Humber River stormwater management model was deemed suitable for use in assessment of future land use changes on flood flows. It has also resulted in a better understanding of the effects of proposed new developments on flooding and has helped to confirm the level of stormwater control needed before expanding urban settlement boundaries.

Flooding in urban areas can cause significant property damage and human injury. Historical extreme precipitation events in the Toronto area have highlighted the need for enhanced warning systems to inform decision making prior to a storm’s arrival.

In response, Computational Hydraulics International (CHI) and the Toronto and Region Conservation Authority developed a high resolution, deterministic, physically-based, remote-sensing, real-time flood forecasting and web-based decision support system. This system has since been applied to the Don River watershed, which is home to 1.2 million people and covers 360 km² of drainage area – 80% of which is highly urbanized.

The project goal was to enable flood duty officers to make more informed decisions by providing them with predicted peak flows of a storm event at least two hours, and as much as 24 hours in advance. Integrating PCSWMM Real-Time, NEXRAD radar data, US EPA SWMM5, HTML5 and Google Maps, the system forecasts near-future water surface elevations and relays the information to a web-based platform for analysis and decision making.

Key features of the flood forecasting system include: real-time radar-rainfall acquisition, processing and forecasting, real-time flow and rain gauging, continuous hydrologic modelling, flood vulnerable asset analysis and predictive weather modelling.

RADAR acquisition and processing capabilities in PCSWMM allowed use of high spatial and temporal resolution rainfall and the ability to track storm speed and direction, as well as the ability to “ground-truth” or calibrate rainfall estimates using a network of ground-based rain gages in the watershed. CHI used the HEC-RAS model import tools of PCSWMM to generate the hydraulic components for the model.

The Don Valley flood forecasting model computed eight of the ten highest peak flows within a 10% margin of error and the remaining two within 20%. Performance of the PCSWMM model for historical events provided sufficient confidence to Toronto and Region Conservation Authority officials to use the methodology in real-time flood forecasting and warning.