*3.4. Quantity/Scale Determination*

Among the 67 planning studies reviewed, only 14 included the step of quantity/scale determination. However, most of these studies simply designated the areas where GSI, entirely or in part, can be built as planned areas; thus, the selected quantity or scale was not calculated and evaluated in detail, which means large randomness and subjectivity. In these articles, providing enough expected ES cannot be guaranteed, and the interest of stakeholders cannot be enhanced by minimizing GSI investment either. There are also studies that made efforts to attain the quantity or scale via calculation or evaluation. Men et al. [64] combined and optimized the SWMM model by using the preference-inspired co-evolutionary algorithm using goal vectors (PICEA g) in accordance with the maximum buildable area of PP, and GR, compared with the study area, and calculated the optimal construction areas of GSI regarding four objectives, i.e., total runoff reduction, peak flow reduction, the removal of suspended solids (SS), and total cost. Guerrero et al. [21] constructed a decision-support system to simulate the runoff volume reduction performance of different construction areas with porous concrete pavement, bioretention, and bioswales, which can be used to determine the construction areas of GSI according to the objective of runoff volume control. It is worth noting that most of these quantitative studies refer to the relevant GSI water quality and quantity regulation capabilities given by existing studies, such as the runoff coefficient of various types of facilities [34], or the default GSI performance that is calculated by parameter settings with large uncertainties in the hydrological model [64,65]. A method supporting the idea that GSI can provide the same amount of ES in different planning scenarios is bound to be flawed, as the discussion regarding performance discrepancy in different studies in Sections 3.2 and 3.3 revealed. Fundamentally speaking, a considerable amount of uncertainty between GSI and ES results in these shortcomings. On the one hand, the ambiguity of the number of ES that GSI can provide leads to the ambiguity of objective formulation, which makes the quantity/scale determination lack accurate objective constraints. On the other hand, even if a certain quantitative objective is given, the planning is still subject to uncertainty and unable to determine the precise quantity or scale. An increasing number of studies [20,66] point to a consensus that the function of GSI is ES production, and they agree that it is necessary to quantify the relationship between the two, as they believe quantification will help incorporate GSI into relevant environmental policies more widely and enhance the interest of stakeholders, so as to understand and implement effective GSI practices; however, they have not achieved breakthrough results yet.
