Maine Stormwater Conference (Portland, ME, 2015) Development of LID facilities Decision Support System using Multiple Attribute Decision Making(MADM)Method LID DSS TOOL BOX: Facility Ver. 1.0 LID DSS TOOL BOX: Product Ver. 1.0 Lee kyoungdo, Park Jongpyo, Choi Jongsoo, Lee Jungmin, Hwang Soodeock 1 / 17
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1. Purpose of the research The purpose of this study is to help the decision makers choose the best and the easiest LID facilities and products for reducing non-point pollution in their communities (BEST) Reduction facilities for non-point pollution (BEST) Reduction products for nonpoint pollution 3 / 17
2. Introduction: LID DSS TOOL BOX LID Decision Support Systems have developed by Web Based LID Decision Support Systems are composed of 2 parts both facilities and products selection Both systems can link together the information & management system(nps- LID) for reduction facilities LID DSS TOOLBOX (Facilities) LID DSS TOOLBOX (Products) 4 / 17
3. Introduction : Information management system(nps-lid) Sharing information: Reduction facilities and Reduction products for non point pollution Contents of Information management system (Definition, Kinds of Facilities, Registration of products, Reference, etc) The number of registered products : 50 5 / 17
4. LID DSS TOOL BOX (Facilities) LID DSS TOOL BOX (Facilities) To plan and choose reduction facilities for non point pollution 15 factors (basin characteristics, rainfall runoff management, Treatment efficiency, maintenance, etc.) need to be considered Comparing evaluations and various decision making variables require technical knowledge Basin characteristics Basin Area faicility Area LandUse Rainfall Best LID Facility Runoff Reduction Variable for Decision Making Rainfall-runoff management Treatment efficiency Maintenance Hydrologic Cycle Improvement Nonpoint Pollutant Removal 6 / 17
4. LID DSS TOOL BOX (Facilities) Decision Making: AHP Logic Analytic hierarchy process Algorithm capable of assisting complex decision-making problems To helps decision makers find one that best suits their goal and their understanding of the problem BMP Comparison Matrix Comparison Matrices : Retention (example) Retention 1 2 3 4 5 6 7 8 9 10 11 12 13 Average Standard Rank score Stormwater Pond(1) 1.000 1.000 1.000 2.250 9.000 1.000 1.500 1.000 2.250 1.500 1.500 1.500 1.000 1.962 0.103 1 Underground Storage Tank(2) 1.00 1.000 1.000 2.250 9.000 1.000 1.500 1.000 2.250 1.500 1.500 1.500 1.000 1.962 0.103 1 Constructed Wetland(Surface flow) (3) 1.00 1.00 1.000 2.250 9.000 1.000 1.500 1.000 2.250 1.500 1.500 1.500 1.000 1.962 0.103 1 Constructed Wetland(Subsurface flow) (4) 0.44 0.44 0.44 1.000 4.000 0.444 0.667 0.444 1.000 0.667 0.667 0.667 0.444 0.872 0.046 11 Porous Pavement(5) 0.11 0.11 0.11 0.25 1.000 0.111 0.167 0.111 0.250 0.167 0.167 0.167 0.111 0.218 0.011 13 Infiltration Basins(6) 1.00 1.00 1.00 2.25 9.00 1.000 1.500 1.000 2.250 1.500 1.500 1.500 1.000 1.962 0.103 1 Infiltration Trench(7) 0.67 0.67 0.67 1.50 6.00 0.67 1.000 0.667 1.500 1.000 1.000 1.000 0.667 1.308 0.069 7 Infiltration Tank(8) 1.00 1.00 1.00 2.25 9.00 1.00 1.50 1.000 2.250 1.500 1.500 1.500 1.000 1.962 0.103 1 Vegetated Filter Strip(9) 0.44 0.44 0.44 1.00 4.00 0.44 0.67 0.44 1.000 0.667 0.667 0.667 0.444 0.872 0.046 11 Vegetated Swale(10) 0.67 0.67 0.67 1.50 6.00 0.67 1.00 0.67 1.50 1.000 1.000 1.000 0.667 1.308 0.069 7 Bioretention(11) 0.67 0.67 0.67 1.50 6.00 0.67 1.00 0.67 1.50 1.00 1.000 1.000 0.667 1.308 0.069 7 Tree Box Filter(12) 0.67 0.67 0.67 1.50 6.00 0.67 1.00 0.67 1.50 1.00 1.00 1.000 0.667 1.308 0.069 7 Planter Box(13) 1.00 1.00 1.00 2.25 9.00 1.00 1.50 1.00 2.25 1.50 1.50 1.50 1.000 1.962 0.103 1 Virginia's Stormwater Impact Evaluation(Virginia water resources research center, 2009) 7 / 17
4. LID DSS TOOL BOX (Facilities) LID DSS TOOL BOX (Facilities): UI The LID Facility Decision Support System can calculate both space requirements of LID facilities, construction cost and the ranking for the best choice. Input data Basic input data Variable for Decision making Basic input data - Basin Area, Faicility Area, LandUse, Design Rainfall Variable for decision making - Basin characteristics (Impermeable area rate, Soil type, etc) - Rainfall-runoff management (Detention, Percolation, Infiltration, etc) - Treatment efficiency (BOD, TSS, TN, TP) - Maintenance (Maintenance cycle, Manpower demand, etc) Results Rank Space requirements Construction cost Output data Basic input data - Space requirements - Construction cost - Ranking for best choice 8 / 17
4. LID DSS TOOL BOX (Facilities) Applicable Facilities Retention type Constructed Wetland Infiltration type Natural type Vegetation type Apparatus type Stormwater Pond Underground Storage Tank Constructed Wetland(Surface flow) Constructed Wetland(SubSurface flow) Porous Pavement Infiltration Basins Infiltration Trench Infiltration Tank Vegetated Filter Strip Vegetated Swale Bioretention Tree Box Filter Planter Box Filter Continuous deflective separation Downstream Defender 9 / 17
5. LID DSS TOOL BOX (Products) LID DSS TOOL BOX (Products): Input & output To help the decision makers to choose the best and the easiest reduction products for non-point pollution Based on TOPSIS Logic Input data Kinds of facility - Natural type (Retention, Infiltration, Vegetation, etc) - Apparatus type (Filter, Continuous deflective separation, Downstream Defender) Weighting of the variables - Treatment efficiency for pollutant - Maintenance efficiency - Construction ability - Economic feasibility Output data Score of products Rank of products 10 / 17
5. LID DSS TOOL BOX (Products) LID DSS TOOL BOX (Products) : Detail results Prodcuct comparison : Score, Rank This system can be possibly linked to the information management system(nps LID) Selected results Comparison of Prodcucts 11 / 17
6. Application in Goduk New-town in Korea Introducion: Goduk New-town Goduk New-town is developed by Korea Land and Housing Corporation Goduk New-town is planning to apply reduction facilities for non-point pollution Area: 13.4 km2 (3,300 acres), Construction period: 2008-2020 12 / 17
6. Application in Goduk New-town in Korea Application in a parking lots Variables for Decision Making 1 Results 1 Land Use Parking lot Basin Area 1,827m2 Facility Area 100m2 Soil type Group A Impermeable area rate 100% Depth of groundwater 4.2m Basin slope 4.3% Rainfall-runoff management Infiltration Treatment efficiency TN, TP Maintenance Maintenance cycle Rank 1 Rank 2 Rank 3 Rank 4 1 Porous Pavement Infiltration Trench Infiltration Tank Vegetated Swale 13 / 17
6. Application in Goduk New-town in Korea Application in residential zone Variables for Decision Making 2 Results 2 Land Use Residential zone Basin Area 20,946m2 Facility Area 200m2 Soil type Group A Impermeable area rate 800% Depth of groundwater 5.7m Basin slope 9.0% Rainfall-runoff management Retention Treatment efficiency BOD Maintenance - Rank 1 Rank 2 Rank 3 Rank 4 2 Infiltration Basins Infiltration Tank Tree Box Filter Bioretention 14 / 17
7. Conclusion We developed the LID Decision Support System including facilities and products selection. We will help the decision makers to choose the "best" and the easiest reduction facilities for non-point pollution. Also, We plan to apply those systems to other test-beds. We have to verify the system, continuously. LID DSS TOOL BOX User AHP Logic Variable for Decision Making TOPSIS Logic NPS LID Database(Link) (BEST) Reduction facilities for non-point pollution (BEST) Reduction products for non-point pollution 15 / 17
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