The intention of the thesis paper is to assess the presumed benefits of strategically implemented types of Low Impact Development (LID) within an urban watershed through the use of remote sensing, specifically; photogrammetry and Light Detection and Ranging (Lidar) data. The ultimate theoretic goal is to strategically reduce Effective Impervious Area (EIA) based on remotely collected data. This goal will be attained by identifying marginal sites, those that most contribute to surface water runoff, and theoretically implementing one or more appropriate LID to the site. Marginal areas will be identified based on a combination of slope, land use classification, surface material, and relative spatial location to stormwater infrastructure inflows and watercourses. Identification will be made by overlaying municipal GIS data sets on highly detailed three dimensional Digital Surface Models (DSMs). Four highly detailed and spatially accurate models will be constructed. The first will be an accurate representation of the watershed in its current state. The second will be the watershed with realistically applied LID retrofits. The third model will represent a possible futuristic scenario of unabated development. The fourth model will reflect universally applied LID. Post model construction, a variety of rainfall/runoff simulations will be designed from the data obtained from the models. Results of the scenarios carried out on each model will be compared, analyzed, and evaluated for effectiveness of applied LID strategies. If this paper yields meaningful results, a universally applicable watershed assessment process may be designed to aid municipalities in strategically locating marginal areas and applying effective solutions at the local scale.
In urban centers around the globe, growth has intensified and increased. Large scale land use changes have been a natural byproduct of this development. Furthermore, “urbanization and land use planning has historically occurred apart from a watershed context and without regard for ecological consequences” (Miltner, White & Yoder, 2004, p.87). Collectively, drastic porosity alteration associated with urbanization, including parking lots, rooftops, driveways and sidewalks, have dramatic effects on local ecosystems, hydrological cycles and climates, which are difficult to mitigate or reverse (Booth & Jackson, 1997). In particular, the increased runoff from impervious surfaces, combined with traditional methods of stormwater management often intensifies the problem. Curbs and gutters “can cause an increase in volume, frequency, and velocity of runoff flows, resulting in flooding, high erosion and a reduction in groundwater infiltration, as well as a reduction in water quality and habitat degradation” (EPA, 2000, p.9). Furthermore, natural watercourses are frequently made more efficient for transporting water downstream faster through channel straightening, deepening, and concrete and culvert installation, which further exacerbates stormwater runoff problems (Booth, & Jackson, 1997). An increase of impervious surface area in urbanized watersheds is the most pervasive and consistent cause of damage to the associated aquatic environments (Paul & Meyer, 2001). The outcomes of increased impervious surface areas will be discussed below.
Negative physical and chemical effects
Booth, D & Jackson, R., (1997) suggest that in humid regions “approximately 10 percent effective impervious area in a watershed typically yields demonstrable, and probably irreversible, loss of aquatic-system function” (p.1084). Many of these catastrophic effects on the structure and function of aquatic environments are attributed to the much higher peak flows of shorter duration and greater frequency, a reduction of infiltration and therefore a loss of base flows (Paul & Meyer, 2001). Greater frequency of flooding leads to higher rates of erosion, sediment flows, bank incision, loss of woody debris, less sinuosity, shallower and wider channels, all of which physically contribute to habitat destruction (Hartley, Jackson, & Lucchetti, 2001).
Along with the physical loss of habitat from altered runoff patterns is the serious but perhaps not as readily identifiable problem of pollution. Pollution may include such contaminants as hydrocarbons, pesticides, synthetic estrogen, heavy metals, organotins, dioxins and nitrogen. These pollutants build up on impervious surfaces through ‘wet’ deposition such as chemical leaks and spillage, and are also deposited from dry atmospheric deposition. During a rainstorm, these toxic pollutants are ‘flushed’ off the landscape in highly concentrated doses, which directly reach many natural aquatic environments with no treatment or lag time (Gobel, Dierkes & Coldewey, 2006). Impervious surfaces serve as collection areas for pollutants and, due to their high runoff coefficients, quickly transfer their toxic savings into stormwater conveyance systems and the environment with devastating and yet unforeseen consequences.
Along with the physical loss of habitat from altered runoff patterns is the serious but perhaps not as readily identifiable problem of pollution. Pollution may include such contaminants as hydrocarbons, pesticides, synthetic estrogen, heavy metals, organotins, dioxins and nitrogen. These pollutants build up on impervious surfaces through ‘wet’ deposition such as chemical leaks and spillage, and are also deposited from dry atmospheric deposition. During a rainstorm, these toxic pollutants are ‘flushed’ off the landscape in highly concentrated doses, which directly reach many natural aquatic environments with no treatment or lag time (Gobel, Dierkes & Coldewey, 2006). Impervious surfaces serve as collection areas for pollutants and, due to their high runoff coefficients, quickly transfer their toxic savings into stormwater conveyance systems and the environment with devastating and yet unforeseen consequences.
Urban heat island creation and associated effects
The other serious outcome of large percentages of impervious land cover is the creation of an urban heat island effect (UHI), which is defined as “heightened air and surface temperatures in urban areas relative to surrounding suburban and exurban areas” (Solecki, et al., 2005, p. 39). Higher impervious surface areas associated with urban areas and traditional stormwater management strategies tend to have lower albedos and higher heat capacities. These surfaces absorb solar shortwave radiation and slowly release the energy in the form of long wave radiation (Solecki, et al., 2005). UHI conditions resulting from impervious land cover have many malignant environmental effects which directly impact human health since “heat kills more people than any other weather-related hazard, even in developed countries” (Yow, 2007, p.11). Rising urban temperatures intensify fossil fuel use through increased air conditioning, energy and water consumption. These increases in consumption exacerbate global climate change, which is thought to magnify and worsen UHI effects, all serving as drivers of positive feedback loops. Increased urban air temperatures have also been found responsible for increased cloud cover and convective precipitation, associated with higher intensity precipitation events at greater frequency (Yow, 2007). This variability is highly problematic for stormwater management because conveyance systems are often designed based on runoff capacities of a designed maximum discharge such as the 1-in -100 year flood. With localized climatic alterations that increase precipitation intensity and frequency, traditional design parameters will no longer be effective because the 1-in-100 year storms could turn into 1-in-25 year events (Denault, Millar & Lence, 2006). Many LID practices serve to reduce UHI intensity because they provide greater green space, which provides cooling, flood control, and air and water quality improvements (Yao, 2007).
The other serious outcome of large percentages of impervious land cover is the creation of an urban heat island effect (UHI), which is defined as “heightened air and surface temperatures in urban areas relative to surrounding suburban and exurban areas” (Solecki, et al., 2005, p. 39). Higher impervious surface areas associated with urban areas and traditional stormwater management strategies tend to have lower albedos and higher heat capacities. These surfaces absorb solar shortwave radiation and slowly release the energy in the form of long wave radiation (Solecki, et al., 2005). UHI conditions resulting from impervious land cover have many malignant environmental effects which directly impact human health since “heat kills more people than any other weather-related hazard, even in developed countries” (Yow, 2007, p.11). Rising urban temperatures intensify fossil fuel use through increased air conditioning, energy and water consumption. These increases in consumption exacerbate global climate change, which is thought to magnify and worsen UHI effects, all serving as drivers of positive feedback loops. Increased urban air temperatures have also been found responsible for increased cloud cover and convective precipitation, associated with higher intensity precipitation events at greater frequency (Yow, 2007). This variability is highly problematic for stormwater management because conveyance systems are often designed based on runoff capacities of a designed maximum discharge such as the 1-in -100 year flood. With localized climatic alterations that increase precipitation intensity and frequency, traditional design parameters will no longer be effective because the 1-in-100 year storms could turn into 1-in-25 year events (Denault, Millar & Lence, 2006). Many LID practices serve to reduce UHI intensity because they provide greater green space, which provides cooling, flood control, and air and water quality improvements (Yao, 2007).
According to the Environmental Protection Agency’s (EPA) Low Impact Development Center “Low Impact Development: A Literature Review” (2000),
LID is a site design strategy with a goal of maintaining or replicating the pre-development hydrologic regime through the use of design techniques to create a functionally equivalent hydrologic landscape. Hydrologic functions of storage, infiltration, and ground water recharge, as well as the volume and frequency of discharges are maintained through the use of integrated and distributed micro-scale stormwater retention and detention areas, reduction of impervious surfaces, and the lengthening of flow paths and runoff time. (p.1)
Examples of LID include greenroofs, permeable pavements, bioretention, and infiltration swales. The goal of LID techniques applied in this thesis is to reduce the Effective Impervious Area (EIA), areas that are directly connected to stormwater infrastructure and watercourses. Localized LID approaches to stormwater management reduce peak floods associated with high surface runoff volumes, filter pollution and help to increase groundwater infiltration. They also have many side benefits such as habitat creation, high aesthetic value, CO2 sinks, UHI mitigation and superior economic performance. “Municipal Stormwater Management Second Edition” (Debo & Reese, 2003) will be used to supplement this section. In the thesis, the LID strategies which will be theoretically implemented will be discussed in detail.
LID is a site design strategy with a goal of maintaining or replicating the pre-development hydrologic regime through the use of design techniques to create a functionally equivalent hydrologic landscape. Hydrologic functions of storage, infiltration, and ground water recharge, as well as the volume and frequency of discharges are maintained through the use of integrated and distributed micro-scale stormwater retention and detention areas, reduction of impervious surfaces, and the lengthening of flow paths and runoff time. (p.1)
Examples of LID include greenroofs, permeable pavements, bioretention, and infiltration swales. The goal of LID techniques applied in this thesis is to reduce the Effective Impervious Area (EIA), areas that are directly connected to stormwater infrastructure and watercourses. Localized LID approaches to stormwater management reduce peak floods associated with high surface runoff volumes, filter pollution and help to increase groundwater infiltration. They also have many side benefits such as habitat creation, high aesthetic value, CO2 sinks, UHI mitigation and superior economic performance. “Municipal Stormwater Management Second Edition” (Debo & Reese, 2003) will be used to supplement this section. In the thesis, the LID strategies which will be theoretically implemented will be discussed in detail.
Study Site Description
The Swan Lake watershed is a sub drainage basin of the larger Colquitz River watershed, located in the municipality of Saanich near Victoria BC. The Swan Lake watershed is approximately 12 sq. kilometers in area (CRD Natural Areas Atlas, 2007). Land use is a mix of single family residential, apartment complexes, commercial, light industrial, agriculture land reserve and parks.
Remote Sensing Description
According to the American Society for Photogrammetry and Remote Sensing (ASPRS), the formal definition of remote sensing and photogrammetry is “the art, science, and technology of obtaining reliable information about physical objects and the environment, through the process of recording, measuring and interpreting imagery and digital representations of energy patterns derived from noncontact sensor systems” (Jensen, 2000, pp. 3).
The Swan Lake watershed is a sub drainage basin of the larger Colquitz River watershed, located in the municipality of Saanich near Victoria BC. The Swan Lake watershed is approximately 12 sq. kilometers in area (CRD Natural Areas Atlas, 2007). Land use is a mix of single family residential, apartment complexes, commercial, light industrial, agriculture land reserve and parks.
Remote Sensing Description
According to the American Society for Photogrammetry and Remote Sensing (ASPRS), the formal definition of remote sensing and photogrammetry is “the art, science, and technology of obtaining reliable information about physical objects and the environment, through the process of recording, measuring and interpreting imagery and digital representations of energy patterns derived from noncontact sensor systems” (Jensen, 2000, pp. 3).
Lidar Description
Light Detection and Ranging (Lidar) is a “measurement of laser pulse travel time from the transmitter to the target and back to the receiver” (Jensen, 2000, pp. 327). Lidar is a form of active remote sensing as it actively sends information and records returning data. The sensor is mounted on an aerial platform, usually a helicopter or fixed wing aircraft. As the aircraft advances, a scanning mirror directs high frequency laser pulses back and forth perpendicular to the flightline of the aircraft (Jensen, 2000). The resulting data set is millions of individually georeferenced XYZ coordinates, organized along scan lines within individual flightlines. Resolution and data point density depends on the altitude and the speed of the aircraft during data acquisition. Other factors that are also recorded during collection are:
“the scan angle of the Lidar at the time of the laser pulse, the effect of atmospheric refraction on the speed of light, the attitude (pitch, roll and heading) of the aircraft at the time of the laser pulse, and the position of the Lidar instrument in three-dimensional space at the time of the laser pulse” (Jensen, 2000, pp. 327).
Light Detection and Ranging (Lidar) is a “measurement of laser pulse travel time from the transmitter to the target and back to the receiver” (Jensen, 2000, pp. 327). Lidar is a form of active remote sensing as it actively sends information and records returning data. The sensor is mounted on an aerial platform, usually a helicopter or fixed wing aircraft. As the aircraft advances, a scanning mirror directs high frequency laser pulses back and forth perpendicular to the flightline of the aircraft (Jensen, 2000). The resulting data set is millions of individually georeferenced XYZ coordinates, organized along scan lines within individual flightlines. Resolution and data point density depends on the altitude and the speed of the aircraft during data acquisition. Other factors that are also recorded during collection are:
“the scan angle of the Lidar at the time of the laser pulse, the effect of atmospheric refraction on the speed of light, the attitude (pitch, roll and heading) of the aircraft at the time of the laser pulse, and the position of the Lidar instrument in three-dimensional space at the time of the laser pulse” (Jensen, 2000, pp. 327).
Acquisition
The first step in the planning process was to define the area that comprises the Swan Lake watershed. The boundary was chosen based on the polygon that delineates the watershed in the Saanich Municipality GIS database, which has been extended to account for the engineered stormwater systems that extend beyond the natural watershed boundaries. For collection purposes the boundary was extended by approximately 25 meters. The data was collected on October 5th, 2007 by Terra Remote Sensing Inc., a local company based out of Sidney BC. The fall was chosen for collection because the models will rely on the highest vegetation penetration possible. Winter is not an ideal collection time, due to standing water, saturated ground and weather conditions. The collected data consists of 20cm resolution orthophotographs and Lidar. The platform used for collection was Terra’s Piper Navajo aircraft (figure 3) with Terra’s suit of onboard integrated sensors (table 1). The specifics of the aircraft’s speed, altitude, and number of flightlines will be included in the thesis, along with all relevant meteorological data. A field team was deployed to collect ground control data which was used in the data calibration process.
The first step in the planning process was to define the area that comprises the Swan Lake watershed. The boundary was chosen based on the polygon that delineates the watershed in the Saanich Municipality GIS database, which has been extended to account for the engineered stormwater systems that extend beyond the natural watershed boundaries. For collection purposes the boundary was extended by approximately 25 meters. The data was collected on October 5th, 2007 by Terra Remote Sensing Inc., a local company based out of Sidney BC. The fall was chosen for collection because the models will rely on the highest vegetation penetration possible. Winter is not an ideal collection time, due to standing water, saturated ground and weather conditions. The collected data consists of 20cm resolution orthophotographs and Lidar. The platform used for collection was Terra’s Piper Navajo aircraft (figure 3) with Terra’s suit of onboard integrated sensors (table 1). The specifics of the aircraft’s speed, altitude, and number of flightlines will be included in the thesis, along with all relevant meteorological data. A field team was deployed to collect ground control data which was used in the data calibration process.
Data Calibration
Post acquisition, the data will be processed by professional surveyors using a suite of proprietary TRSI developed software and techniques. This process will tie multiple flightlines together and georeference all the data. TRSI Lidar data is guaranteed to have a relative accuracy of twenty centimeters. For security reasons the details of this process will not be elaborated on.
Post acquisition, the data will be processed by professional surveyors using a suite of proprietary TRSI developed software and techniques. This process will tie multiple flightlines together and georeference all the data. TRSI Lidar data is guaranteed to have a relative accuracy of twenty centimeters. For security reasons the details of this process will not be elaborated on.
Data Processing and Model Construction
Using Bentley Microstation V8, a powerful geospatial program, appropriate programs with user defined parameters, based on slope and vegetation, will be run on the georeferenced Lidar. The programs will define a ground surface based on the lowest points. Due to variances in terrain and surface features, manual editing will be carried out until an accurate ground surface has been defined. From this surface, buildings and vegetation can be defined and measured based on their height above the ground. The final orthophotographs will be rectified to this surface.
Using Bentley Microstation V8, a powerful geospatial program, appropriate programs with user defined parameters, based on slope and vegetation, will be run on the georeferenced Lidar. The programs will define a ground surface based on the lowest points. Due to variances in terrain and surface features, manual editing will be carried out until an accurate ground surface has been defined. From this surface, buildings and vegetation can be defined and measured based on their height above the ground. The final orthophotographs will be rectified to this surface.
Based on Saanich GIS data, orthophotographs and the generated ground DEM, the ground and buildings will be accurately separated into unique classes, which are ultimately based on their porosity characteristics. The ground classification scheme could include: Bare rock, short grass, moderate vegetation, heavy vegetation, watercourses, wetland areas, agriculture land use, unpaved roads, paved roads and sidewalks, driveways, impervious residential area, paved lots, gravel lots and a natural ground class. Rooftops will be the only non ground surface feature that will be separately classified; a digital surface model (DSM) for buildings will also be generated. The remaining Lidar points will be classified to vegetation. For the purposes of this study, other features defined by Lidar, such as telephone poles, street lamps, cars, and other temporally sensitive objects will not be separated from the vegetation class. This classification scheme is based on the “Site design parameters” input in a water balance model, defined in the 2002 publication “Stormwater Planning: A Guidebook for British Columbia”. The inputs used in the water balance model were land use type, road width, rooftop coverage, surface parking coverage and population density.
From the DSMs, a highly detailed (0.2m resolution) drainage map will be generated for each surface class. After this has been completed, an accurate depiction of the watershed in its current state is finished. Rather than trying to estimate pre development conditions, the current conditions will be used for the baseline for comparison with other models. This is reasonable because “pre-impact conditions can seldom be restored in these systems, and projects designed to replicate historic conditions are likely to fail” (Fischenich, 2001, pp.1).
Not all impervious surfaces contribute equally to runoff due to micro drainage characteristics and proximity to stormdrains and watercourses, furthermore, certain areas will be cheaper and more easily retrofitted with site specific LID strategies.
After the marginal areas have been identified, appropriate methods of onsite water management will be decided and theoretically applied to the model. The selected LID strategy will be based on drainage characteristics, land use, construction material, relative implementation price, and size of area.
After the marginal areas have been identified, appropriate methods of onsite water management will be decided and theoretically applied to the model. The selected LID strategy will be based on drainage characteristics, land use, construction material, relative implementation price, and size of area.
The previously generated attributes for the now mitigated areas will be modified to reflect new surface materials, such as permeable paving and green roofing. Impervious areas which are effectively mitigated through the use of bioretention landscaping and infiltration swales will also be changed to reflect the mitigation. All large commercial and apartment complex roof tops with acceptable slopes (less than 45 degrees) will be retrofitted with green roofs. After this has been completed, the total area of the new surface areas for the entire watershed can be calculated based on the changes to each lot.
Hydrological Simulation and LID Evaluation
Using hydrological simulation software such as HydroCAD or Vflo, several precipitation/runoff simulations will be run using input data from the four models. Each DSM (Bare rock, short grass, moderate vegetation, heavy vegetation, watercourses, wetland areas, agriculture land use, unpaved roads, paved roads and sidewalks, driveways, impervious residential area, rooftops, paved lots, gravel lots and natural ground class) will be assigned a curve number (CN) based on their porosity. The percentage of each class will be multiplied by their CN to get a single weighted CN for the entire watershed. A very similar approach was taken in a study by Carter, T.A., & Rhett, J.C. (2006), titled “Vegetated roofs for stormwater management at multiple spatial scales.” In the study, CN numbers were derived from the Soil Conservation Service, a branch of the US Department of Agriculture, and reached experimentally for green roofs specifically for the study. There is also a valuable section on assigning CN values to soils and surfaces in “GIS Applications for Water, Wastewater, and Stormwater Systems” by Shamsi, U.M. (2005).
Using hydrological simulation software such as HydroCAD or Vflo, several precipitation/runoff simulations will be run using input data from the four models. Each DSM (Bare rock, short grass, moderate vegetation, heavy vegetation, watercourses, wetland areas, agriculture land use, unpaved roads, paved roads and sidewalks, driveways, impervious residential area, rooftops, paved lots, gravel lots and natural ground class) will be assigned a curve number (CN) based on their porosity. The percentage of each class will be multiplied by their CN to get a single weighted CN for the entire watershed. A very similar approach was taken in a study by Carter, T.A., & Rhett, J.C. (2006), titled “Vegetated roofs for stormwater management at multiple spatial scales.” In the study, CN numbers were derived from the Soil Conservation Service, a branch of the US Department of Agriculture, and reached experimentally for green roofs specifically for the study. There is also a valuable section on assigning CN values to soils and surfaces in “GIS Applications for Water, Wastewater, and Stormwater Systems” by Shamsi, U.M. (2005).
Despite differences within each LID strategy (varying depths of green roofs, differences in porosity for various types of permeable pavements, and various types and depths of bioretention methods); curve numbers for each LID will be held at constant values. Also, because there will be no in situ measurements of soil depth, type, evapotranspiration, temperature, and saturation, these variables will also be assigned constant values for all simulations. Due to the scope of this study and associated models, water that is infiltrated and evaporated will be represented as a loss to the system. As there are no flow meters that can be used to calibrate the models, latent groundwater flows are not being considered. These water balance models will be validated by simple thermodynamics: runoff values + water lost to evaporation + water lost to infiltration are equal to the initial input value of precipitation. Information for this part of the project will use material from a 2007 seminar put on by the Association of Professional Engineers and Geoscientists of BC titled “Stormwater Modeling.”
Several design storms will be created based on historical rainfall data in the area. They will differ in duration and intensity; however they will be spatially uniform. This is a realistic assumption due to the small size of the watershed. The design storms will be realistic representations of various storm events characteristic to the region. Detailed precipitation records for the area can be obtained through the UVic School Based Weather Station Network, which is a network of weather monitoring stations set up at local schools on Vancouver Island and the Gulf Islands (http://www.victoriaweather.ca/, 2007). There are several of these monitoring stations within the Swan Lake watershed. There will also be a few precipitation simulations designed around future scenarios of global climate change. These design storms of varying intensity and duration will be run on the three models and the results will be examined to determine the effectiveness of the strategically applied LID.
Several design storms will be created based on historical rainfall data in the area. They will differ in duration and intensity; however they will be spatially uniform. This is a realistic assumption due to the small size of the watershed. The design storms will be realistic representations of various storm events characteristic to the region. Detailed precipitation records for the area can be obtained through the UVic School Based Weather Station Network, which is a network of weather monitoring stations set up at local schools on Vancouver Island and the Gulf Islands (http://www.victoriaweather.ca/, 2007). There are several of these monitoring stations within the Swan Lake watershed. There will also be a few precipitation simulations designed around future scenarios of global climate change. These design storms of varying intensity and duration will be run on the three models and the results will be examined to determine the effectiveness of the strategically applied LID.
This section will compare and analyze the changes in runoff volumes between models and between precipitation events. From the changes in precipitation/runoff ratios the effectiveness of the applied LID can be discussed. There will also be an evaluation of the efficiency of model construction and classification. From these results, conclusions and recommendations for future studies, such as automated classification, or the application of a similar study at larger scales. There will also be a section that will describe some of the inherent errors and limitations associated with this type of theoretical modeling.
Conclusions and Recommendations
If the process is efficient, accurate, and applicable, the potential for future development of a set method for urban watershed analysis is great. If the strategically applied theoretical LID proves to be effective, the digital models with this relevant information could be exported as .KML files that are viewable by anyone with Google Earth software. This would serve to generate local and international interest in future watershed development and restoration projects. It would also help to bridge the gap between scientific information and public understanding and awareness. GIS and Remote Sensing is a very powerful tool for conveying complex information in a meaningful and comprehensible mode. This type of information could be very useful to municipalities because runoff from sites is not solely dependant on horizontal impervious surface area. Slope, surface roughness, and proximity to natural water courses and stormwater conveyance inflows largely determine how much of a ‘contributor’ the site is. Through the use of these highly detailed models, municipalities could discern which properties contribute the most to surface runoff and quite easily determine the dollar value of mitigating runoff at very specific locations and apply the most cost effective and site appropriate method of localized stormwater control based on the calculated benefits. The public would be receptive to being ‘paid’ by the municipality to install LID on their property, through cash up front for approved projects, or later reimbursement through property tax breaks (amounts dependant on site retrofits vs. runoff contribution).
If the process is efficient, accurate, and applicable, the potential for future development of a set method for urban watershed analysis is great. If the strategically applied theoretical LID proves to be effective, the digital models with this relevant information could be exported as .KML files that are viewable by anyone with Google Earth software. This would serve to generate local and international interest in future watershed development and restoration projects. It would also help to bridge the gap between scientific information and public understanding and awareness. GIS and Remote Sensing is a very powerful tool for conveying complex information in a meaningful and comprehensible mode. This type of information could be very useful to municipalities because runoff from sites is not solely dependant on horizontal impervious surface area. Slope, surface roughness, and proximity to natural water courses and stormwater conveyance inflows largely determine how much of a ‘contributor’ the site is. Through the use of these highly detailed models, municipalities could discern which properties contribute the most to surface runoff and quite easily determine the dollar value of mitigating runoff at very specific locations and apply the most cost effective and site appropriate method of localized stormwater control based on the calculated benefits. The public would be receptive to being ‘paid’ by the municipality to install LID on their property, through cash up front for approved projects, or later reimbursement through property tax breaks (amounts dependant on site retrofits vs. runoff contribution).
Due to the relatively permanent nature of urban development and traditional stormwater controls, as well as the high level of investment in these systems, cities are usually ‘locked in’ to their stormwater management and development choices. For this reason, LID can be very effective because they can be retrofitted into previous design and development with relative ease. LID effects are cumulative, as are the effects of impervious surfaces, thus widespread adoption of LID is needed to realize their full potential. Due to their prevalence, residential and private areas are key to successful source control stormwater management. The publication “Stormwater Planning: A Guidebook for British Columbia” (2002) states that “residential development often has the greatest cumulative impact on stormwater management because it covers the greatest land area” (section 3, p.8). Therefore, LID must be effectively implemented in these areas around the world to reduce the wide ranging impacts of increasing urbanization; using remote sensing is one way of achieving this.
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