Abstract
As the severity of water-related disasters increases in urban watersheds due to climate change, reducing flood damage in urban watersheds is one of the important issues. This study focuses on prioritizing the optimal site for permeable pavement to maximize the efficiency of reducing flood damage in urban watersheds in the future climate environment using multi-criteria decision making techniques. The Mokgamcheon watershed which is considerably urbanized than in the past was selected for the study area and its 27 sub-watersheds were considered as candidate sites. Six General Circulation Model (GCM) of Coupled Model Intercomparison Project 6(CMIP6) according to two Shared Socioeconomic Pathway (SSP) scenarios were used to estimate future monthly precipitation for the study area. The Driving force-Pressure-State-Impact-Response (DPSIR) framework was used to select the water quantity evaluation criteria for prioritizing permeable pavement, and the study area was modeled using ArcGIS and Storm Water Management Model (SWMM). For the values corresponding to the evaluation criteria based on the DPSIR framework, data from national statistics and long-term runoff simulation value of SWMM according to future monthly precipitation were used. Finally, the priority for permeable pavement was determined using the Fuzzy TOPSIS and Minimax regret method. The high priorities were concentrated in the downstream sub-watersheds where urbanization was more progressed and densely populated than the upstream watersheds.
| Original language | English |
|---|---|
| Pages (from-to) | 159-170 |
| Number of pages | 12 |
| Journal | Journal of Korea Water Resources Association |
| Volume | 55 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 6 Clean Water and Sanitation
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SDG 11 Sustainable Cities and Communities
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SDG 13 Climate Action
Keywords
- DPSIR
- Fuzzy TOPSIS
- General circulation model
- Minimax regret
- Permeable pavement
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