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LIFESim 201

DAM AND LEVEE SAFETY RISK ASSESSMENT EVALUATION ROUTING AND LIFE LOSS ESTIMATION USING LIFESIM

Woodrow Fields, P.E.1

Chris Bahner, P.E., D. WRE2 Jason Needham3

Christopher R. Goodell, P.E., D. WRE4

ABSTRACT LIFESim is a modular, spatially-distributed, dynamic simulation system for estimating potential life loss from dam and levee failure or non failure flood events that explicitly considers the primary factors contributing to life loss in a flood situation. LIFESim is the U.S. Army Corps of Engineers (USACE) most rigorous approach for estimating potential life loss due to dam failure, and it can be used to provide inputs for dam safety risk assessment. LIFESim considers detailed flood dynamics, loss of shelter, warning and evacuation, and uses historically-based fatality rates to estimate life loss. The Warning and Evacuation Module spatially redistributes the population at risk from its initial distribution at the time that a warning is issued, to a new distribution with assigned flood zone categories at the time of arrival of the flood. USACE is in the process of improving the LIFESim evacuation-transportation process to account for defining initial escape routes based on shortest travel time and allowing evacuees to turn around if they come to a flooded road. USACE is also in the process of performing a comparison study to demonstrate that LIFESim is appropriate for a breach and/or overtopping scenario of a levee structure. In support of the comparison study, LIFESim was applied to two highly urbanized areas. This paper provides an overview of LIFESim, discusses the changes to the evacuation-transportation process in LIFESim and their expected effects on life loss estimation, and presents development and results of LIFESim models for the one of the urbanized areas.

INTRODUCTION

There are presently about 4,000 deficient dams in the United States that would require about $12.5 billion dollars to repair and rehabilitate, and approximately 100,000 miles of levees that have an unknown reliability (average age of 50 years) and an estimated cost of $50 billion to repair and rehabilitate (ASCE, 2010). Addressing the aging infrastructure

1 Hydraulic Engineer, U.S. Army Corps of Engineers, Institute For Water Resources, Hydrologic Engineering Center, 609 Second Street, Davis, CA 95616; ph: 530 756-1104; [email protected]. 2 Senior Hydraulic Engineer, WEST Consultants, Inc., 2601 25th Street SE, Suite 450, Salem, OR 97302, ph: 503-485-5409, [email protected]. 3 Senior Consequence Specialist, U.S. Army Corps of Engineers, Risk Management Center, 609 Second Street, Davis, CA 95616, ph: 503-756-1104, [email protected]. 4 Portland Office Manager/Senior Hydraulic Engineer, WEST Consultants, Inc., 103000 SW Greenburg Rd., Suite 470, Portland, OR 97223, ph: 503-946-8536, [email protected].

202 Innovative Dam and Levee Design and Construction

will be a challenging task to accomplish due to the sheer number of dams and levees that need to be repaired, regulatory and environmental requirements, and funding limitation. Prioritization should be an important component during the process to reduce the risk for economic and social impacts, infrastructure damage, and loss of life associated with potential future dam or levee failures. One of the important components for assessing flood risk is to properly estimate the loss of life from a dam or levee failure. Various empirical equations that are based on population at risk (PAR) and the warning time have been developed to estimate the life loss for a dam failure. McCelland and Bowles (2002) provide a detailed review of these equations and identify several limitations with the empirical life-loss estimation approach. LIFESim was developed to overcome the limitation of the empirical life-loss estimation approach. LIFESim is a spatially-distributed dynamic simulations modeling system for estimating life-loss. LIFESim is currently being developed by the USACE. The prototype application developed by Aboelata and Bowles (2005) was created for the ArcView3 geographic information systems (GIS) platform. The first stages of the LIFESim extension development by USACE involved the upgraded from AcView3 to the ArcGIS ArcMap (Version 9.3) platform. Future development will include the incorporation of additional methodology and/or improvements to the existing modules. LIFESim has been applied to several dams under a range of failure and exposure scenarios. The USACE Risk Management Center (RMC) in collaboration with the Hydrologic Engineering Center (HEC) is in the process of performing a comparison study to demonstrate that LIFESim is appropriate for a breach and/or overtopping scenario of a levee structure. In support of the comparison study, LIFESim was applied to two highly urbanized areas: (1) Saint Paul Flood Control Project in St. Paul, MN, and (2) Sacramento River Flood Project (Natomas Basin) in Sacramento, CA. With the incorporation of updates necessary to evaluate levee failures, LIFESim will become an important tool for performing dam and levee safety risk assessment and for improving the effectiveness of emergency action planning and responses.

LIFESIM OVERVIEW LIFESim is a modular, spatially distributed, dynamic simulation system built around databases. Each module exchanges data with other modules through the database, which include various layers and tables containing information on population, structure types, roads, warning systems, and time profiles of flood depth and velocity. Development of LIFESim has been sponsored by the USACE and the Australian National Committee on Large Dams (ANCOLD). LIFESim models are developed and run in the ArcGIS environment. As presented in the LIFESim Users Manual (USACE, 2010), the methodology implemented in LIFESim is based on research and development efforts of Maged A. Aboelata and Dr. David Bowles of the Institute for Dam Safety Risk Management of Utah State University and is described in the report, LIFESim: A Model for Estimating Dam Failure Life Loss, Draft (Aboelata and Bowles, 2005).

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A schematic of the LIFESim approach to life-loss estimation is shown in Figure 1. LIFESim is comprised of three major modules. The following discussion related to each of the modules is summarized from a paper prepared by Aboelata and Bowles (2005) that contains a more detailed discussion of each module.

Figure 1. Schematic of Life-loss Estimation Approach in LIFESim (Aboelata and

Bowles, 2005). Population at Risk (PAR) LIFESim requires an estimate of the spatial and temporal distribution of population at the time of the initiation of the first evacuation warning for a specific failure scenario. To facilitate gathering these data, LIFESim uses readily available data. Specifically, LIFESim was built to gather this information from the extensive database that accompanies FEMAs HAZUS-MH software program (Aboelata and Bowles 2006). The HAZUS database includes a polygon shapefile that delineates census blocks for an area as well as the population and building characteristics for each of those census blocks. Variations in the number of people within the flooded area throughout the day can have a significant effect on loss of life. Moreover, the activities that people are engaged in can affect the efficiency at which the warning spreads through an area. Accordingly, LIFESim is designed to take into account both 1) the distribution of people among census blocks throughout the inundated area based on time of day and 2) estimates in the percentage of population involved in various activity types including: at home, outdoors, working/shopping and in transit.


To determine the number of people in a census block at any given time, LIFESim pulls relevant data from the HAZUS-MH database. The HAZUS-MH database contains three time-of-day activity distributions. These distributions are as follows: 0200, representing night time; 1400, representing day time; and 1700, representing commuting time. LIFESim takes the data and uses relationships to calculate the number of people in each occupancy class on the census block level. Variables used in distributing people are as follows: Census block population taken from census data stored in HAZUS-MH database Daytime residential population inferred from census data Nighttime residential population inferred from census data Number of people commuting inferred from census data Number of people employed in the commercial sector Number of people employed in the industrial sector Number of students in grade schools (K-12) Number of students on college and university campuses in the census tract Number of people staying in hotels in the census tract A factor representing the proportion of commuters using automobiles, inferred from

profile of the community (0.60 for dense urban, 0.80 for less dense urban or suburban, and 0.85 for rural). The HAZUS-MH default value is 0.80.

Number of regional residents who do not live in the study area, visiting the census tract for shopping and entertainment. The HAZUS-MH default value is zero.

LIFESim interpolates the estimates obtained by applying the HAZUS-MH population data for the three HAZUS-MH time-of-day distributions to obtain estimates for every two-hour interval throughout a 24-hour period. Population estimates for each of the four LIFESim activity types are then computed using the mapping shown in Table 1.

Table 1. Mapping of HAZUS-MH occupancy classes to LIFESim activity types. LIFESim activity type HAZUS occupancy class Residential-indoors Residential-indoors Hotels-indoors Outdoors Residential-outdoors Hotels-outdoors Working/shopping Commercial-indoors Commercial-outdoors Industrial-indoors industrial-outdoors Education-indoors Education-outdoors In transit Commuting-own car Commuting-public transportation

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Finally, population is distributed among activity types using a set of activity factors. These values are based on research from Rogers and Sorensen (1988). Their research described how a given warning system has a penetration capability that can be distinguished for the following five fundamental locations or activities:

1) Home asleep 2) Indoors at home or in the neighborhood 3) Outdoors in the neighborhood 4) In transit 5) Working or shopping

They also added two other activities: watching television and listening to radio, which override the first set of five locations or activities. Loss of Shelter The Loss of Shelter Module simulates the exposure of people in buildings during a flood event as a result of structure damage, building submergence, and toppling of people in partially damaged buildings. The module utilizes historical fatality-rate probability distribution for three distinct flood zones: (1) Chance Zone, which is the zone where victims are impacted by the floodwaters and survival is depended mainly on chance (fatality rate of 50 to 100% with an average of 90%); (2) Compromised Zone, which is the zone where victims are exposed to floodwaters as a result of damage to the shelter by the flooding (fatality rate of 0 to 50% with an average of 10%); and (3) Safe Zone, which is the zone that is either dry or consists of shallow, tranquil floodwaters (virtually no life loss in this zone). LIFESim includes two different methodologies for building damage criteria: (1) USACE, or (2) RESCDAM. The USACE criteria consists of a set of collapse curves based on depth and flow velocity for one, two, and three story buildings of four different types of buildings. The RESCDAM criteria are based on a detailed study completed in Finland, and it defines when a wood-frame or masonry, concrete, brick building would be partially or totally damaged based on depth and flow velocity data. Warning and Evacuation The Warning and Evacuation Module simulates the spatial redistribution of the population at risk following the intuition of being warned. This is accomplished through simulation of the warning dissemination, mobilization, and evacuation-transportation processes. Current improvements in the LIFESim evacuation-transportation process account for defining initial escape routes based on shortest travel time and allowing evacuees to turn around if they come to a flooded road. The following will discuss in more detail the warning, mobilization, and evacuation process. The warning initiation time is the time at which an evacuation warning is first issued to the PAR. It is defined to be positive if the warning is issued after failure occurs, or to be


negative if the warning is issued before failure occurs. The warning module start time at time step zero is the earliest warning initiation time. Any emergency planning zone (EPZ) with a later initiation time is offset accordingly. The rate at which the warning is received throughout an area is represented in LIFESim using a warning diffusion curve, which is the cumulative percentage of the PAR that receives the warning message versus time where time 0 is the warning initiation time. After receiving the warning message, people who are willing and able to leave will prepare to leave. The rate of mobilization is represented in LIFESim using a mobilization curve, which is a cumulative percentage of the warned PAR that starts moving away from the area of potential flooding towards safe destinations. A mobilization curve represents two important pieces of information: (1) how long it takes people after they received a warning to leave their home, and (2) what percentage of the population will not mobilize (1 minus the maximum mobilization %). Typically a mobilization curve will not reach 100% until enough time has passed to allow emergency responders to physically enter every home and remove people that are either unable or unwilling to mobilize on their own. The evacuation-transportation process commences with mobilization and ends with either clearance of the flooding area or entrapment if the evacuation route becomes blocked by flooding. People who clear the flooding area are assigned to a safe flood zone and people who are trapped on the road are assigned to a flood zone that depends on their mode of evacuation and the most severe flooding conditions for the event. Three modes of evacuation are included in LIFESim: cars, sports utility vehicles (SUVs) and pedestrians. The Greenshield (1935) transportation model is used in LIFESim to represent the effects of traffic density and road capacity on vehicle speed. The original model was modified to represent congestion and traffic jams, as described in Aboelata and Bowles (2005), by introducing a minimum stop-and-go speed (Vjam) if the jam density (Djam) for a road class is exceeded. Each road class is assigned default values of the number of lanes, free flow speed (ffs), Djam and Vjam based on the Highway Capacity Manual (HCM) (TRB 2000), although these can be overridden if more detailed information is available for the road system. In the case where traffic jams occur, a minimum stop-and-go speed is used when jam density is exceeded. A road segment is determined to be blocked when the vehicle stability criteria has been exceeded. A road network in the form of a GIS polyline shapefile is provided in which each segment of the network contains information such as road category, segment length, number of lanes, and interconnectivity. The road segment end points must be snapped together so that the shortest path algorithm knows that they are connected. LifeSim also has the capability for the user to create a driveway segment which draws a line from the census block centroid to the nearest road segment. The driveway segment road category is user defined at the time of creation.

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A GIS point shapefile represents a set of safe destinations for evacuees to go. LIFESim models the movement of people to destination points using the shortest travel time available. The destination points are not required to be snapped to a road segment, they can be placed directly on the safe location. People who reach a safe destination are considered as the cleared group. During each time step at the user defined interval t, groups move as far as the model allows until a destination point is reached. If a flooded road is encountered, a new route is determined. The population group then keeps the flooded road in memory so that it will not try to evacuate through the road again. If no new route can be found, the population group is stranded. The evacuation routes are determined by computing the shortest travel time as if all the roads were capable of free flow speed. The shortest path algorithm that is used to compute the evacuation routes is the Dijkstra with Approximate Buckets method (Cherkassky et al. 1993). This algorithm was chosen for its stability and speed. Also, it was chosen based on a comparison effort of various shortest path algorithms (Zhan and Noon, 1998). Loss of Life The final step in LIFESim is the estimation of loss of life. Previously described modules simulate the spatial redistribution of people existing within the study area through the processes of warning and evacuation and assign loss-of-shelter category/flood zones based on the effect of flood water on the buildings, vehicles and pedestrians throughout the study region. These results are combined in the Loss-of-Life (LOL) Module with the probability distribution of fatality rates for each loss-of-shelter category/flood zone to obtain estimates of the expected number of fatalities within the study area. For this analysis, the expected value (mean) of the fatality rate distributions developed by McClelland and Bowles (2000), updated Aboelata et al (2003) and displayed in Figure 2 were applied. The mean values for the safe, compromised and chance flood zones are 0.0002, 0.1200, and 0.9145, respectively.


COMBINED DATA

0.00.10.20.30.40.50.60.70.80.91.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Relative Frequency of Exceedance

Prop

ortio

nal L

ife L

oss,

Pr(

zone

)

Prcz Prcoz Prsz

Figure 2. Probability distributions for fatality rates for each flood zone.

LIFESIM APPLICATION LIFESim was applied to two highly urbanized areas to evaluate the applicability of the program to areas protected by levees: (1) Saint Paul Flood Control Project in St. Paul, MN, and (2) Sacramento River Flood Project (Natomas Basin) in Sacramento, CA. However for this paper, the necessary steps for the development of a LIFESim model and results from the LIFESim simulation are presented only for the Natomas Basin in Sacramento, CA. Study Site The Natomas Basin is shown in Figure 3. It is located just north of the confluence of the American and Sacramento Rivers. The Natomas Basin has a total protected area of about 83.2 mi2, and it includes portions of the city of Sacramento, Sacramento County, and Sutter County. The Natomas Basin is bordered on the south by the American River, on the west by the Sacramento River, on the north by the Natomas Cross Canal (NCC), and on the east by the Pleasant Grove Creek Canal (PGCC) and the Natomas East Main Drainage Canal (NEMDC). The Natomas Basis is protected from high flood flows by an interconnected perimeter levee system. The levees are divided into four major units: (1) Levee Unit 1 is located along the east bank of the Sacramento River for a total length of 18.6 miles, (2) Levee Unit 2 is located along the north bank of the American River for a total length of 2.3 miles, (3) Levee Unit 3 is located along the west bank of the NEMDC and Pleasant Grove Creek Canal for a total length of 17.3 miles, and (4) Levee Unit 4 is located along the south bank of the NCC for a total length of 4.4 miles. This levee system was originally created to promote agricultural development. However, the Natomas Basin presently contains three major public transportation facilities: (1) Interstate 5 (I-5), (2)

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Figure 3. Natomas Basin

Interstate 80 (I-80), and (3) State Route 99 (SR-99); the Sacramento International Airport; the Arco Arena; and several commercial and residential developments. About 30% of the basin consists of developed urban uses, mostly in the southern portion of the basin in the city of Sacramento. The remaining portion of the basin is in some form of developed agricultural or open space. Model Development LIFESim was utilized to evaluate various breach scenarios at three different locations. The locations considered are shown in Figure 3, and consist of Sacramento River near the Cross Canal confluence (northern location), Sacramento River near the Sacramento Weir (middle location), and lower reach of the American River/NEMDC (southern location). The breach scenarios considered included Sunny Day Failure, Expected Failure from


Overtopping, and No Failure (Strong Levee). The three breach scenarios were considered for the northern and southern breach locations. The Sunny Day Failure scenario was the only failure scenario considered for the middle location since the levee at this location would not be overtopped during the 0.2 annual chance flood event and significant overtopping of the other levee segments would be occur when the levee at this location would be overtopped. The general steps and procedure in developing the LIFESim models are presented in the following paragraphs. Map Projection. As previously discussed, LIFESim runs in an ArcGIS environment. So, it is important that the various shapefiles and raster files have the same projection. The hydraulics for the Natomas Basin was estimated using HEC-RAS and FLO-2D. Both of these models were developed using data with a horizontal datum of the NAD 1983 California II State Plane, feet. Therefore, this datum was utilized for the LIFESim models of the Natomas Basin. HAZUS Database. Populations and building information utilized by the LIFESim program is based on information available from various databases developed as part of the Federal Emergency Management Agencys Hazards U.S. Multi-Hazard (HAZUS-MH) application (FEMA, 2003). The HAZUS-MH application and supporting database files were obtained from FEMA. The tables and database files used from the HAZUS system include: (1) hzDemographicsB table, (2) hzBldgCountOccupB table, and (3) hzCensusBlock table from the bndrygbds.mdb database; and (4) hzGenBldgScheme from the MSH.mdb database. Census Block Layer. A census block polygon shapefile was developed from the Census Blocks feature class in the bndrygbs.mdb HAZUS-MH database. The shapefile was defined to contain only the polygons that are inundated for the maximum flooding conditions. Also, the attribute table was revised as follows: (1) a field named Block_id was added to the table and populated with values in the modified CensusBlock field in the HAZUS-MH database, (2) a field for the percent of elders in each census block was added and populated using information contained in the hzDemogrphaicsB table of the bndrygbs.mdb HAZUS-MH database, and (3) a field for the emergency planning zone (EPZ) was added and populated with the same value for all census block to represent a single warning and evaluation scenario. Presently, no information has been obtained related the Emergency Action Plan (EAP) for the Natomas Basin. LIFESim requires a point shapefile that represents the centroid of each census block. This shapefile was created using the Generate Centroid tool available as part of the spatial preprocessing capabilities of the LIFESim software. Evacuation Destination Layer. LIFESim requires a point shapefile that represents the locations to which people will evacuate. The evacuation destination locations are shown in Figure 4, and they were defined to be at the end of most of the roads entering and leaving the basin.

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Road Layer. The existing roads within the Natomas Basin are shown in Figure 4. The roads layer shapefile representing the transportation network was provided by the U.S. Army Corps of Engineers, Hydrologic Engineering Center (HEC). The shapefile included the necessary field to link the Census Feature Class Codes for each road element. The weight of the lines for the roads in the figure corresponds to the capacity of the road system with thicker lines having a higher vehicle capacity and maximum speed limit. LIFESim requires that the road lines extend to the center of each census block. This was accomplished using Add Driveway tool available as part of the spatial preprocessing capabilities of the LIFESim software. First Floor Height Grid. Information related to the first floor elevations is provided as a raster dataset that must have the same cell size as the raster datasets of the flood water depth and velocity. The first floor raster was developed using the FLO-2D grid, which was used to define the flood water depth and velocity raster datasets, and assuming that the first floor of the structures are 3 feet above the existing ground. Flood Profile Data. LIFESim requires a time series of water depth and velocity data in raster format. The time series data must cover the time of evacuation being modeled, and it can be defined using 30 time steps. The depth and velocity raster files must be named using the convention of , i.e., names for the depth are dp001 and dp002 and for the velocity are vp001 and vp002; and they must be located in the same directory. The raster dataset was defined using the unsteady flow HEC-RAS and FLO-2D models provided by Sacramento District (SPK) of the U.S. Army Corps of Engineers. The unsteady flow HEC-RAS model was used to define the inflow hydrograph to the FLO-2D model. The HEC-RAS model was developed by SPK as part of the American River Common Features GRR study (USACE, 2002). The provided model consisted of only one plan for the 0.002 exceedance probability flood event. The model covers the lower reach of the Sacramento River, from Colusa at the upstream end to the upper portion of the Sacramento-San Joaquin Delta at the downstream end. The model also includes major tributaries (Feather, Bear, Yuba, and American Rivers), several of the smaller tributaries (Putah and Cache), and various interconnecting waterways. The upstream boundaries consist of an unsteady flow hydrograph; the internal boundaries consist of either a steady or unsteady flow hydrograph or gate control structure, and the downstream boundaries consist of an unsteady stage hydrograph. The downstream boundaries are based on the stage hydrograph measured during the 1997 flood event and adjusted using the results of frequency analysis on the tidal data located near each of the boundary locations.


Figure 4. Evacuation Destination Point and Roads for Natomas Basin

The HEC-RAS model is highly complex and includes about 96 reaches, 3,930 cross sections, 159 storage areas, 582 lateral structures, 186 storage connection features, and 146 bridge and/or culvert structures. The Mannings n-values for the main channel range from 0.035 to 0.06 and 0.035 to 0.30 for the overbank areas. The weir coefficients of the lateral weir structures range from 1.4 to 3.0. There is also one diversion structure with 48 gates that is located on the right bank of the Sacramento River about 2,700 feet upstream of the Highway 80 Bridge. The levees are simulated in the model using lateral structures. Therefore, the levee breach tool available in HEC-RAS was used to breach the levee. Piping failure mode was utilized for the Sunny Day failure scenarios, while the overtopping failure mode was considered for the Overtopping failure scenarios. Each breach was assumed to be 500

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feet wide and with vertical side slopes that is formed over a duration of 1 hour. Also the breach weir coefficient was assumed to be 2.6 and final bottom elevation set by the interior ground elevation where the breach occurs. The resulting hydrograph was placed into Excel and converted to an ASCII format for easy input into the FLO-2D model. FLO-2D software (FLO-2D, 2009) was utilized to define the hydraulics dataset of the Natomas Basin for the LIFESim application. FLO-2D is a horizontal 2-D flood routing model developed by Dr. Jim OBrien. It numerically routes a flood hydrograph over a computational domain while predicting the area of inundation and simulating floodwave attenuation. It is a volume conservation model that moves the flood volume from upstream to downstream on a series of computational cells (elements). Floodwave progression over the flow domain is controlled by topography and resistance to flow. Flood routing in two dimensions is accomplished through an explicit numerical integration of the equations of motion and the conservation of fluid volume. The model can solve either the diffusive wave equation (neglecting the acceleration terms in the momentum equations) suitable for simple overland flow on a mild slope, or the full dynamic wave equation for simulating complex flow hydraulics. The FLO-2D model provided by SPK consisted of 36,475 square elements that are 400 feet by 400 feet (210 mi2). The model covers the entire Natomas Basin (about 83 mi2) and storage areas of the NEMDC, the area between the Sacramento River and Yolo Bypass, and the area between the American River and Arcade Creek. The FLO-2D model included levee, inflow and outflow elements; Area Reduction Factors (ARF) to reflect blockage associated with buildings within urbanized areas, and a channel reach to represent the NEMDC. New FLO-2D models were developed for the various breach locations and failure scenarios by revising the inflow conditions to the model. The outflow hydrographs from the HEC-RAS were reflected as an inflow hydrograph to FLO-2D. The FLO-2D software has the capability (Mapper program) to create shapefiles for specific time increments. The process, however, is fairly time intensive. Therefore, a macro was developed in Excel to extract the FLO-2D output at selected time increments and create ASCII files in a format that can easily be converted to a shapefile and then into a raster format in ArcGIS. Model Setup. Prior to running LIFESim, the input parameters need to be defined in the model setup in terms of the initial settings, spatial/population data, warning/evacuation, and depth/velocity data. Brief information related to the model setup is presented as follows. Initial Settings. Some of the basic information is defined in the initial settings dialog, including the model output directory, time of day options, building damage criteria, and spatial extents. As previously mentioned, there are two different types of building damage criteria available within LIFESim: (1) USACE, or (2) RESCDAM. The USACE method was selected for the evaluation of the Natomas Basin. The spatial extents specified in the initial setting dialog define the area of the computation limits, and it


should be large enough to contain the census block, evaluation destinations and roads to the destinations. Spatial and Population Data. The Spatial and Population Data dialog defines what spatial data layers and population data files that will be used in the LIFESim analysis. Warning and Evacuation Setup. The Warning and Evaluation Setup dialog consist of two tabs. The first tab is for defining the parameters related to the Warning/Mobilization. The type of warning system, warning issuance, mobilization curve, and population activity distribution is defined for each EPZ. There are eight types of warning systems available: (1) Sirens; (2) Tone Alert Radios; (3) Emergency Broadcast System (EBS); (4) EBS and Sirens; (5) EBS and Auto-Dial Telephones (Landlines) (ADT); (6) EBS, Siren, and ADT; (7) EBS, Sirens, and ADT (Landlines and Mobile); and (8) User Define. It was assumed that the Natomas Basin had only one EPZ with an EBS warning system, and the warning issuance, which defines the time in minutes between when the warning is issued and dam/levee failure that the warning issuance, would be instantaneous (0 minutes). The mobilization curve defines the relationship between the percent mobilized over time. There are three pre-defined mobilization curves to choose from (Default, Below Average, and Above Average) plus one user defined option. The default curve was utilized for the Natomas Basin. Finally, the population activity distribution is utilized to define the percentage of the population engaged in each of seven activities in 2-hour increments over a 24-hour time period. As in the mobilization curve, the default distribution was assumed for the Natomas Basin. The second tab is for defining the control settings of the evacuation model including the model duration, vehicle characteristics, and additional evacuation parameters. The model time includes the computation time step and the total simulation time in minutes. The computational time step should range between 1 to 10 minutes with a larger time step being considered for larger areas. The total simulation time defines the total time in minutes to perform the warning and evacuation process in the model. The Natomas Basin was evaluated with a computational time step of 10 minutes and a total simulation time varied dependent on the breach conditions. The vehicle characteristics includes: (1) the vehicle occupancy rate, which is the average number of people per vehicle (default of 3); (2) the fraction of people in vehicles, which is the fraction of people that will evacuate using vehicle rather than on foot (default of 1); and (3) the fraction of people in cars versus SUVs/trucks (default value of 0.5). Finally, the additional evacuation parameters dialog can be utilized to revise: (1) the road characteristics, which includes information of the number of lanes, free flow speed in mi/hr, and jam density; (2) the stability factors for humans, cars and SUVs (set as depth times velocity factor, and default value of 1, 1.35, and 0.9 for humans, cars, and SUVs, respectively); and (3) speed adjustment factors, which are used to scale the model pedestrian speed of 4 mi/hr and the vehicle free flow speed defined in the road characteristic table (default values of 1). For the LIFESim evaluation of the Natomas Basin Default values were assumed for the vehicle characteristics and additional evacuation parameters.

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Depth/Velocity Data. The Depth and Velocity Profile Information dialog is utilized to define the location of the raster depth and velocity files, what the starting depth and velocity raster file, number of profiles and time in hours associated with each profile, and time in hours of the dam/levee failure with respect to the hydraulic model start. Model Results The LIFESim results for the time of failure that resulted in the greatest loss of life are summarized in Table 2.

Table 2. Summary of LifeSim Results.

Breach Scenario Variable

Northern Location

(Sacramento River near Cross

Canal)

Southwest Location

(Sacramento near Sac Weir)

Southern Location

(American River and NEMDC

Combined Reach)

Sunny Day

Time of Failure 18:00 18:00 18:00 Cleared 44,756 41,842 42,289 Survived 812 887 2,973 Loss of Life 104 35 397

Expected (Overtopping)

Failure

Time of Failure 18:00 - 0:00 4:00(1) Cleared 45,283 - 36,633 Survived 853 - 4,308 Loss of Life 71 - 476

Strong Levees

Time of Failure 18:00 - 0:00 4:00(1) Cleared 3,735 - 36,733 Survived 76 - 3,285 Loss of Life 0 - 296

Notes: 1. For the Southern Location, the results were the same for the time of failure occurring at 0:00, 2:00, and 4:00

for the Expected (Overtopping) and Strong Levee breach scenarios. 2. The Expected (Overtopping) and Strong Levee breach scenarios were not considered for the Southwest

Location. A review of the LIFESim results indicate the following: (1) the greatest loss of life would occur for the breach and/or overtopping conditions occur at the southern location, which is anticipated since it the closest location to a populated area; (2) the breach condition with the greatest loss of life for the southern levee location would be from a Overtopping failure; (3) the breach condition with the greatest loss of life for the northern levee location would be from a Sunny Day failure; (4) the time of failure that results in the greatest loss of life is either at the early morning or early evening hours; (5) no lives will be lost if the levee adjacent to the Sacramento River is protected against overtopping failure; and (6) there will be about a 38 percent reduction in the potential loss of lives if the levee adjacent to the American river and NEMDC are protected against overtopping failure.


Based on a quick sensitivity analysis of the warning time for the Sunny Day failure condition at the southern levee, a 30 percent reduction in loss of life will occur if the warning is issued 30 minutes prior to the failure and a 40 percent increase in loss of life will occur if the warning is issued 30 minutes after the failure.

CONCLUSION Due to the current state of several dams and levees within the United States, there will be an increasing demand and necessity for dam and levee risk assessments, improving the effectiveness of emergency planning and responses to dam or levee failures, and prioritizing the order of what dams and levees should be rehabilitated. Thus, a credible estimation of life-loss from dam or levee failures is important. LIFESim has been developed to meet this need. It has been formulated using the important processes that can affect life loss, addresses many of limitations associated with existing empirical approaches, utilizes readily-available data sources, and requires only a reasonable level of effort to implement (Aboelata and Bowles, 2005). It is a fairly new tool that has been successfully applied to estimate life-loss for several dams under a range of failure and exposure scenarios, and recently to levee structures. There is on-going work to improve the capabilities of the tool, such as the evacuation-transportation process discussed in this paper, and USACE is committed in making LIFESim a powerful and easily accessible tool. Some general conclusions related to the application of LIFESim to the Natomas Basin include: (1) the model run time could be extremely long (several days) for large interior areas with failure that occur near populated areas; (2) the recommended upper limit of simulation time (24 hours) for the warning and evacuation module could prevent the use of the program for large interior areas where it could take several days for flooding of the interior area; and (3) LIFESim relies on the HAZUS data, which is readily available but could be outdated or contain erroneous information.

REFERENCES Aboelata, M., and D. S. Bowles, 2008. LIFESim: A Tool for Estimating and Reducing Life-Loss Resulting from Dam and Levee Failures Proceedings of the Association of State Dam Safety Officials Dam Safety 2008 Conference, Indian Wells, CA. Aboelata, M., and D. S. Bowles, 2005. LIFESim: A Model for Estimating Dam Failure Life Loss Draft Report to Institute for Water Resources, US Army Corps of Engineers and Australian National Committee on Large Dams. Aboelata, M., D.S. Bowles and D.M. McClelland, 2004b. A Model for Estimating Dam Failure Life Loss. ANCOLD Bulletin 127:43-62. August. Aboelata, M., D.S. Bowles and D.M. McClelland, 2003. Life-loss Estimation for Floods including Dam Failure. GIS Model for Estimating Dam Failure Life Loss. In Y.Y. Haimes and D.A. Moser, (Eds.), American Society of Civil Engineers.

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American Socity of Civil Egineers. 2010. Report Card for Americans Infrastructure. FEMA (Federal Emergency Management Agency), 2003. HAZUS-MH flood technical manual. Department of Homeland Security, Emergency Preparedness and Response Directorate, FEMA, Mitigation Division, Washington, D.C. FLO-2D Software, Inc., 2009 (January). FLO-2D Users Manual for Version 2009.06. Hydrologic Engineering Center, 2010. HEC-RAS, River Analysis System Users Manual. U.S. Army Corps of Engineers, Hydrologic Engineering Center, Davis, California. McClelland, D.M., and D.S. Bowles, 2000. Estimating Life Loss for Dam Safety and Risk Assessment: Lessons from Case Histories. In Proceedings of the 2000 Annual USCOLD Conference, U.S. Society on Dams (formerly U.S. Committee on Large Dams), Denver, CO. McClelland, D.M., and D.S. Bowles, 2002. Estimating Life Loss for Dam Safety Risk Assessment - a Review and New Approach. Institute for Water Resources, U.S. Army Corps of Engineers, Alexandria, VA. U.S. Army Corps of Engineers, 2010. Draft LIFESim Extension Version 1.2 for ArcGIS Users Manual. U.S. Army Corps of Engineers, Hydrologic Engineering Center, Davis, California. U.S. Army Corps of Engineers, 2002. Sacramento and San Joaquin River Basins Comprehensive Study, Sacramento District.

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