*3.2.1. Stormwater*

**Figure 2.** The various phases for site development.

flow issues along Medical Mile.

NW, north of I-196 [11].

66 Sustainable Urbanization

generates more costs.

**3.2. Methods**

Phase II is Medical Mile along Michigan Street, where the Secchia Center is located. It raised \$50M for development and MDOT is awarding TEDF grant of \$6,171,966 for addressing traffic

Phase III is along the Grand River. Grand Rapids identifies potential \$1.5M funding source together for Grand River dam removal and restoration of rapids from the National Fish and Wildlife Foundation [11]. In addition, Grand Rapids seeks \$10 million from state grant to purchase about 4 acres at the riverfront of the Grand River on the west side of Monroe Avenue

Phase IV accommodates many local business stakeholders and is beside the Business routes of U.S. Route 131. The vacant lots and concrete ground-level parking present opportunities for implementing and imbedding green infrastructure within the site. The private ownership might lead the long-term land requirements, while the removal of impervious pavements

Based upon the program for the project, the study began preparing a design for completion on the 18th of December 2015. The competition's critical goal was to improve stormwater management treatments. The team specifically designed a series of LID controls and examined the stormwater quantitate changes by the U.S. Environmental Protection Agency (EPA) National Stormwater Calculator (SWC). Another specific topic for this competition was climate change. Many urban activities and elements influence climate change: the traffic loads, gasoline oil and grease, land use, and others. This study measured the variables relating to trees, shades, and land-use changes to examine the impacts brought by different designs. The methods include the before-and-after area changes and the Simplified Landscape Irrigation

Demand Estimation (SLIDE) to calculate the tree water consumption.

The United States Environmental Protection Agency National Stormwater Calculator (SWC) can be utilized by any user who intends to reduce runoff from their properties, such as site developers, landscape architects, urban planners, and homeowners. Users could access to databases for soil, topography, rainfall, and evaporation information that already installed in the SWC. LID controls employ green infrastructures that mimic natural system of water movements; hence, they help purify water and reduce the burden of storm drains. Other data in SWC that users need to specify are the types of LID controls they use, and there are seven green infrastructure practices: disconnection, rain harvesting, rain gardens, green roofs, street planters, infiltration basins, and porous pavement.

When users consider how runoff varies under different scenarios, the SWC estimates the results based on information of soil type, size of green infrastructure, landscape and land-use information, and historical weather or future weather indication [13]. The procedure of SWC is to (1) locate the site's location, (2) identify the site's soil type, (3) specify how quickly the site's soil drains, (4) characterize the site's surface topography, (5) select a nearby rain gage to supply hourly rainfall data, (6) select a nearby weather station to supply evaporation rates, (7) select a climate change scenario to apply, (8) specify the site's land cover for the scenario being analyzed, (9) select a set of LID control options, along with their design features, to deploy within the site, and (10) run a long-term hydrologic analysis and display the results [14].

The team employed the SWC to compute the stormwater for 25-year 24-h storm events and to compute the volumes of annual runoff (lower is better) under different scenarios: existing, traditional design, and design employing LID controls. The calculator also computes the number of days with runoff from a site (lower is better) and the percentage of water infiltration into the site (higher is better). The design developed used many LID controls for stormwater management. The result shown from the SWC indicated that the postdevelopment design with LID treatments decreased the predevelopment's volume of runoff from 53 to 15%.

#### *3.2.2. Tree water consumption*

The team had a goal to increase the area covered by trees from 4.73 to 8.26%, with an increase in trees from 590 to 1030, which exceeds the government's goal of 7% tree cover for the city center in Grand Rapids. With a change in tree species, the goal was to eliminate invasive tree species and to actually utilize less water per tree.

The team roughly observed the tree species and the quantities from the site and Google Earth street-view photos and calculated the water demand using the SLIDE method. The SLIDE approach estimates the water demand for water-conserving irrigation plans and irrigations, based on researches of "landscape plant water requirements" and "plant water-use physiol‐ ogy" [15, 16]. It is even applicable for non-irrigated landscaping plans when it can estimate whether the anticipated precipitation is sufficient for any landscape or not [16].

There are four SLIDE rules to frame SLIDE:

*SLIDE Rule #1***.***Reference evapotranspiration (ETo) accurately estimates water demand of lawns and other uniform turf areas, but it marginally represents water demand of non-turf, non-uniform, physically and biologically diverse landscapes.*

*SLIDE Rule #2*. *Plant Factors (PFs) alone accurately adjust ETo to estimate landscape water demand, and they are assigned by general plant type categories, not by individual species (see Table 1)*.

*SLIDE Rule #3*. *A landscape area or zone controlled by one irrigation valve (hydrozone) is the smallest water management unit in a landscape; when plant types are mixed in a hydrozone, the water demand is governed by the plant type with the highest PF*.

*SLIDE Rule #4*. *Water demand of dense plant cover (canopy covers ≥80% of the ground surface) comprised of mixed plant types is that of a single 'big leaf' governed by the plant type category in the mix with the highest PF; demand of sparse plant cover (canopy covers <80% of the ground surface) is that of individual plants and is governed by their leaf area and the PF of their plant type category [16]*.


**Table 1.** National Stormwater Calculator (SWC) parameters.

Eq. (1) is as follows:

$$\text{Landscape water demand (gal.)} = \text{ETo} \times \text{PF} \times \text{LA} \times 0.623 \tag{1}$$

where ETo is the historical average or real-time evapotranspiration for the period, measured in inches; PF is the Plant Factor; LA is the landscape area, in square feet; 0.623 is the factor to convert inches of water to gallons; omit this factor if the estimated water demand is desired in inches.

Eq. (1) is the basic SLIDE equation. If complex water requirement and irrigation demand within a larger landscape are required, sequential sub-equations can be applied Eqs(Eq. (2) and Eq. (3)):

The team roughly observed the tree species and the quantities from the site and Google Earth street-view photos and calculated the water demand using the SLIDE method. The SLIDE approach estimates the water demand for water-conserving irrigation plans and irrigations, based on researches of "landscape plant water requirements" and "plant water-use physiol‐ ogy" [15, 16]. It is even applicable for non-irrigated landscaping plans when it can estimate

*SLIDE Rule #1***.***Reference evapotranspiration (ETo) accurately estimates water demand of lawns and other uniform turf areas, but it marginally represents water demand of non-turf, non-uniform,*

*SLIDE Rule #2*. *Plant Factors (PFs) alone accurately adjust ETo to estimate landscape water demand, and they are assigned by general plant type categories, not by individual species (see Table 1)*.

*SLIDE Rule #3*. *A landscape area or zone controlled by one irrigation valve (hydrozone) is the smallest water management unit in a landscape; when plant types are mixed in a hydrozone, the water demand*

*SLIDE Rule #4*. *Water demand of dense plant cover (canopy covers ≥80% of the ground surface) comprised of mixed plant types is that of a single 'big leaf' governed by the plant type category in the mix with the highest PF; demand of sparse plant cover (canopy covers <80% of the ground surface) is that of individual plants and is governed by their leaf area and the PF of their plant type category [16]*.

Landscape water demand (gal.) ETo×PF×LA 0.623 = ´ (1)

where ETo is the historical average or real-time evapotranspiration for the period, measured in inches; PF is the Plant Factor; LA is the landscape area, in square feet; 0.623 is the factor to convert inches of water to gallons; omit this factor if the estimated water demand is desired in

**Variables Existing Traditional Low impact development**

Percent of forest 1.34 6.68 11.47 Percent of meadow 0.00 4.39 7.77 Percent of lawn 14.34 7.50 10.31 Percent of pervious 0.00 0.00 21.54 Percent of impervious 84.32 81.43 48.91 Total area (acres) 98.50 98.50 107.04

whether the anticipated precipitation is sufficient for any landscape or not [16].

There are four SLIDE rules to frame SLIDE:

68 Sustainable Urbanization

*physically and biologically diverse landscapes.*

*is governed by the plant type with the highest PF*.

**Table 1.** National Stormwater Calculator (SWC) parameters.

Eq. (1) is as follows:

inches.

$$\text{Landscape water demand (gal.)} = \sum ((\text{ETo} \times \text{PF}) \times \text{LA}) \text{l} - x \times 0.623 \tag{2}$$

where ETo is the historical average or real-time evapotranspiration data in inches for the period of interest; PF is the Plant Factor from **Table 1** for the plant category represented in a hydrozone or a landscape area, 1 through x; when plant categories are mixed in a landscape or a hydrozone it is the highest PF among the plant categories represented; LA is the landscape area or hydrozone planted with the respective PF, in square feet; 0.623 is the factor to convert depth of water to volume (gal./[in.×sq. ft.]); omit this factor if the estimated water demand is desired in inches.

$$\text{Irregion demand(gal.)} = \sum(\text{(IETo} \times \text{PF} \text{)-P}) \text{J-D} \times \text{LA} \times (\text{l/DU}) \text{(l}-\text{x} \times 0.623 \tag{3}$$

where ETo is the historic or real-time annual or monthly average evapotranspiration data in inches for months January through December, or other period of interest; PF is the Plant Factor from **Table 1** for the plant category represented in a hydrozone or occupying a portion of landscape area, 1 through x; when plant categories are mixed in a landscape or a hydrozone; it is the highest PF among the plant categories represented; P is optional; it is the historical average or real-time effective precipitation in inches for months January–December, or other period of interest; usually 50% or similar percentage of P is considered effective and is the amount used in the equation; LA is the landscape area or hydrozone, in square feet, devoted to the respective PF; 0.623 is the factor to convert depth of water to volume (gal./[in. × sq. ft.]); omit this factor if the estimated water demand is desired in inches; DU is the distribution uniformity of irrigation in the landscape area or hydrozone 1 through x (often mandated to be ≥0.7).

In our case, we used Eq. (1) because it is a simple, scientifically logical theory to provide accurate plant factors and effective water conservation suggestions that can be applied nationally. Otherwise, it does not require a large database of plant factors.

#### *3.2.3. Change in land cover and reduction in heat island effect*

To utilize the six best management practices (BMPs) tools, green roof, constructed wetland, cisterns for water harvesting, permeable pavement, bioretention or rain gardens, and dry and wet bioswales to mimic natural system treating the runoff, the surface cover for the site was modified. In such a design, the runoff does not just flow into a single treatment, but a series of BMP elements for larger efficiencies. More permeable pavements, green spaces, and green roofs in the design should result in a more effective solution to climate change resilience. The decrease of impervious pavement and increase of green areas, including where employ LID controls can promote climate change resilience for a site.

Under the impact of climate change, the heat island effect becomes one of the influential issues in urban environments. The increasing portions of buildings, infrastructures, impervious land covers, and decreasing green areas put the urban environments for human living under a huge crisis.

To minimize the heat island effect in the urban environment of Grand Rapids, the intent is to balance the ratio of the shaded portion of the site with the amount directly exposed to the sun. The design focuses on increasing green areas that do not only reduce runoff, but also promote the urban environment adapting to climate change resilience. The expanding green areas and a long skywalk, which connects the incomplete urban fabric in Grand Rapids, provide shadow to decreasing temperature on ground; thus, these contribute to reducing the urban heat island effect and saving energy costs for cooling [17, 18].

Trees are important in the urban environment and vital to climate change resilience. Urban forests generate environmental, health, and social benefits. The shaded surface can be cooler (25–45°F) than the peak temperatures of the unshaded surfaces [19]. Trees combined with LID controls can reduce stormwater infrastructure costs and improve the quality of runoff entering natural waterways, improve the walkability of the communities, and provide habitat for biodiversity. Tree canopy can mitigate the increasing extreme hot weather that causes the degradation of air quality, which triggers the exacerbation of chronic health conditions such as asthma and diabetes [17]. The leaves absorb carbon and dust from the air and generate oxygen.

#### *3.2.4. Habitat suitability—field sparrow and fox squirrel*

Field Sparrow (*Sciurus niger* L. 1758) inhabits old fields with scattered woody vegetation and forages perches, such as shrubs. Seeds and vegetative materials account for their diets: 80–90% of fall or winter diets and 45–49% of spring or summer diets. Breeding habitats are a mixture of shrubs and herbaceous plants with a few large trees. They usually require trees with a maximum diameter at breast height (dbh) of 2.5 cm (1 in.) and height range of 2–8 m (6.6–26.2 ft) for nesting and small stems with diameter stem density ranging from 350 to 700 stems/ha (142–283 stems/acre) [20, 21].

Fox squirrel (*Spizella pusilla* (Wilson) 1810) inhabits open forest setting and would be better interspersed with understory vegetation and agricultural lands, so does its breeding habitats. Their living options are leaf nests and tree cavities. They require 2–121.4 ha (5–300 acres) farm woodlots [20, 22].

Habitat suitability index (HSI) model assumes that reproductive habitat needs are met and uses the reproductive habitat that needs to determine the overall habitat quality. Each cover type within the site can provide the habitats of field sparrow and fox squirrel, and nearby shrub, grassland, or wooded areas may add to the habitat suitability [20, 21, 22].
