1. Introduction
Development increases impervious land cover [
1]. Urban impervious surfaces have aggregated stormwater problems. Specifically, surface runoff volume is significantly increased as infiltration is hindered. This decreases groundwater recharge and accordingly reduces the amount of base flow [
2]. Significant water-bound pollutants are conveyed to nearby water bodies by the increased urban runoff flowing over the impervious surfaces [
3]. It is necessary to take corrective action in response to these stormwater problems. Installation of low-impact development (LID) practices is one method to offset the adverse impact caused by urbanization. LID practices help to achieve both development and environmental protection by imitating the hydrology of a pre-developed state. Research on the effects of LID practices has been active and has comprehensively been addressed in a variety of studies. Most studies have demonstrated the benefits of LID practices by showing an increase of recharge rate [
4] and reductions in runoff volume and pollutant loadings [
5,
6,
7,
8].
However, the degree of the effectiveness of LID practices can be affected by various factors. Some studies, for example, have reported the different effects of LID practices on water quantity and quality under different types of soil [
9,
10] and under various rainfall patterns [
11,
12,
13]. A few studies have pointed out that different effects of LID practices could exist depending on how urban areas are designed [
9,
14,
15]. Seo et al. [
16] also evaluated the effectiveness of LID practices on hydrology and water quality under three land uses with different types of urban patterns (compact high-density, conventional medium-density, and conservational medium-density) using the Soil and Water Assessment Tool (SWAT) and presented the optimal land use.
In addition to these external conditions, the effectiveness of LID practices can also be expected to vary as a result of various LID planning and design factors such as type, location, area, and so forth. Gilroy and McCuen [
14] simulated the spatial and quantitative effects of cisterns and bioretention areas using a developed spatio-temporal model and provided information on the spatial arrangements and volumes needed to achieve effective results in reduction of runoff volumes and peak discharge rates. Endreny and Collins [
17] examined groundwater recharge and mounding by adjusting the spatial arrangements of bioretention areas as distributed, clustered, and single units using a MODFLOW model in an urban residential area of New York, USA. They determined that groundwater mounding was highest when bioretention areas were arrayed as single units and lowest when they were fully distributed. Brander et al. [
9] identified the impact of the number of infiltration practices by demonstrating that runoff differences among different urban types could be overcome by implementing a number of infiltration practices. Ahiablame et al. [
18] also evaluated the effects of LID practices on runoff and pollutant loads according to the percent implementation of rain barrel/cistern and porous pavement. While the above studies showed that studies addressing proper distribution and placement of LID practices are needed, none provided an approach that would optimize the area of LID needed, as a function of location and type, to meet a target runoff and pollutant reduction rate.
The establishment of proper watershed-scale strategies for LID conditions is required to obtain optimal results for reductions of runoff volume and nutrient loadings. Cost is an essential factor that must be considered along with the strategies because a restricted budget is usually given for performing the strategies [
19]. Gilroy and McCuen [
14], in their study, simply determined several scenarios for placing cisterns and bioretention areas according to the places where water was intercepted, and Chaubey et al. [
20] stated that random placement was normally used. However, such methods can make a cost-effective scenario for LID conditions (which may result in better outcomes in reduction with minimal cost) be missed as it is among unconsidered scenarios. Liu et al. [
21] indicated that they found the best effective scenario of LID and best management practices (BMP) conditions showing the greatest reduction in runoff and pollutant loadings among 16 scenarios, but it was not a cost-effective scenario. Therefore, optimization would be necessary. Many researchers have performed optimization to accomplish the best effect close to a required target reduction goal at minimum cost [
19,
22,
23,
24,
25,
26]. However, most studies have been for optimization of agricultural best management practices (conventional stormwater treatment systems akin to LID practices) and have drawn the optimal scenario (or the best solution) by utilizing various optimization tools, such as the genetic algorithm (GA), through model development. While the use of tools enables evaluation of a myriad of probable options for various LID conditions, it makes the process complex and increases the simulation time [
24]. In particular, it becomes an inefficient method when considering just a few conditions or small watersheds. In this regard, a manual technique for optimization is required, which can simplify the complexity and easily provide information on cost-effective LID conditions at any watershed.
The purpose of this study was to present the optimal LID conditions that can attain targeted reduction goals with minimal cost and to evaluate the effectiveness of LID practices under the optimal conditions and the consequential cost on a watershed scale. A manual optimization was conducted for identifying the optimal conditions of LID practices, using a Microsoft Excel spreadsheet. Five targeted reduction goals were determined by using the results of reduction amounts by LID practices from the Soil and Water Assessment Tool (SWAT). Three LID conditions were taken into account in the manual optimization process: types of LID practices (rain gardens, rainwater harvesting tanks, and permeable pavements), locations (residential and commercial areas), and percent allocation of LID practices at each location. The study was processed for surface runoff (SURQ), nitrate (NO3), and total phosphorus (TP).
4. Impact of LID Use on Detention Requirements and Cost
Thus far, the effectiveness of LID practices and the consequential costs according to the optimized LID conditions have been analyzed. However, the water volumes detained by LID practices under the optimized conditions are small (
Table 7) because the maximum capacities and allowable areas of LID practices are limited. Thus, for heavy rainfall, a considerable amount of water that is not treated by LID practices would be generated as surface runoff, directly entering channels. Such a large amount of water that cannot be detained by LID practices needs to be taken into account by other methods for controlling stormwater in the region. Therefore, detention ponds were incorporated in the study area to reflect the water volume that could not be addressed by LID practices, and 100-year 24-h rainfall (13 inches) was assumed in this region as the standard for heavy rainfall for the purpose of calculating the volume that should be captured by detention ponds. First, the required detention volume by urbanization was estimated by the difference between pre- and post-development states in surface runoff. The volume that should be captured by detention ponds was then calculated by subtracting the volume detained by LID practices from the required detention volume. The total cost of detention ponds for addressing the calculated volume capacity was calculated using the following equation developed by Brown and Schueler [
47] (Equation (3)):
where C is the establishment cost including construction, design, and authorization (
$) and V is the pond volume (ft
3). For the calculation of annual cost, a 5% ratio for maintenance (rm) and a design life of 20 years (td), obtained from the USEPA website, were considered and the same interest rate (s) of 4.5% was applied. Additionally, the cost savings for the amount controlled by LID practices was computed by the difference between the costs for the calculated detention volume and the required detention volume. Total cost of detention ponds was greatest in Case 1 and accordingly cost savings were the smallest in Case 1 (
Figure 5). This was because the volume that should be captured by detention ponds was increased by the smallest volume detained by LID practices in Case 1. The same trend was indicated in all variables and all constraint conditions. Total phosphorus showed the greatest difference in the cost of detention ponds between Case 4 and Case 5 under the medium and minimum conditions. This was seen because the difference in the optimized LID conditions between two cases caused the difference in the volume detained by LID practices. The volume detained by LID practices is affected by percent allocation and storage depth of LID practices, and thus it could vary depending on the optimized LID conditions even with the same targeted goal. Why the costs of detention ponds in total phosphorus were higher than those in the other variables could also be explained by the results of the optimized LID conditions.
LID practices installed in urban areas generally are more expensive than detention ponds. This study does not to compare LID practices to detention ponds. City authorities are being forced to deal with stormwater generated from their regions for new urban developments. Thus, this section presented the volumes that should be captured (that is, the volumes that exceed LID capacities) for heavy rainfall and the consequential costs using detention ponds as a secondary stormwater management method.
5. Conclusions
The study has presented the cost-effective LID conditions found through optimization and has analyzed the effectiveness of LID practices on a watershed scale and the consequential costs. To attain the goal, five targeted goals were set and LID conditions for type, location, and percent allocation were optimized. The optimization ultimately came up with the most cost-effective and efficient guidelines for LID planning in the study watershed. For example, if the region is given a budget of $600,000 in dealing with surface runoff, it could consider the LID conditions of Case 1 for both maximum and medium conditions. Or, if the region decides to allow maximum adoption to treat the targeted goal, Case 3, for nitrate, it could apply the LID conditions of Case 3 and need at least $1,047,000.
In general, what could be learned through the study was that maximizing the treatment effect of each LID practice should be a priority as cost benefits increase linearly for each unit of surface runoff that is captured. For each LID practice that is implemented, water managers thus need to focus on maximizing the amount of runoff captured for each plot in order to increase cost effectiveness. In addition, the cost-effective results of this study would be generated differently by other conditions such as different types of LID practices besides RGs, PPs and RWHs, different limitations for the allocation of LID practices, different treatment goals, watershed characteristics, and so forth. Therefore, adequate studies for a variety of conditions should be done in advance to achieve cost-effective results within a given budget before the installation of LID practices. Such studies would likely suggest planning and design of LID projects that accomplish a balance between environmental and economic aspects on a development or watershed scale.
As accounted for in the Manual Optimization section, the optimization method employed is very simple and practical in providing cost-effective conditions. It is likely that this method would be applicable in many studies and would easily assist watershed managers in determining the best solution for the establishment of LID practices for their watershed management. In addition, this study has been based on simple calculations using the results of modeling work. If field work had been performed, it would have been possible to validate our results. Such an additional study would be a very meaningful work in that it could lay the groundwork for studies on other watersheds.