Integrated approach for low impact development locating in dense residential areas based on sustainable development criteria

The study proposed a practical approach for low impact development (LID) placement in dense residential urban catchments considering social, economic, and technical criteria. The objective is to shift the current technical orientation in LIDs' locating to a practical one with a specific level of residents' cooperation. Four stages were conducted, including (i) acquiring the residents' socio-economic information; (ii) hydraulic simulation of the stormwater collection system in the status quo, (iii) regionalization of the urban catchment using data mining, and (iv) proposing specific LIDs locating scenarios. The field study lasted around four months in a dense residential area with a combination of old/new buildings in the eastern Tehran metropolis. Regionalization was conducted by combining pre-processing/clustering techniques, resulting in six regions (preliminary results) and four regions after the clustering integration in the post-processing study. The regions have different priorities for the LIDs locating, including (i) cooperative cluster, 57 sub-catchments (SCs) and appropriate for rain barrel (RB) and green roof (GR) locating; (ii) semi-cooperative cluster, 12 SCs, appropriate for RB or GR locating; (iii) 15 SCs with infrastructural constraints in the third cluster and appropriate for RB; and (iv) non-cooperative cluster, 34 SCs, inappropriate for LIDs locating. Accordingly, seven locating scenarios were specified, and the developed EPA-SWMM model was modified to evaluate the scenarios for mitigating the study area's node flooding problems. The finding shows that the overflow volume reduced in a range of 36.7–93.1%, 28.3–78.7%, and 16.3–66.4% under the rainfall with 2, 5, and 10 years return periods, respectively. HIGHLIGHTS A practical approach was proposed for LID placement considering social, economic, and technical criteria.; The decision support component included data mining approach.; PCA method was included to prioritize the criteria.; K-means clustering was employed for the catchment's regionalization considering the prioritized criteria.; The approach enables the municipality to consider a wide range of preferences in the LIDs type selection.;

Abstract licence: CC BY-ND

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