Performance Evaluation of Low Impact Development Practices Using Linear Regression

Aims: To develop a modelling methodology for evaluating the cumulative stormwater performance of Low Impact D evelopment technologies on a watershed basis to address stormwater impacts of urban development. Stu dy Design : A method is presented to perform hydrological modelling on large watersheds. Hydrological modelling simulations and linear regression analyses of a small sample of randomly selected lots were performed to generate results which were extrapolated to the entire watershed. Place and Duration of Study: Department of Civil Engineering, Ryerson University, between September 2010 and September 2012. Methodology: Urban hydrological response units were developed by using the K - means cluster analysis procedure to group 6926 lot parcels amenable to the residential rain barrel Low Impact D evelopment practice into clusters. Two versions of a Microsoft Excel macro were d eveloped to run simulations for thousands of lots s imultaneously before and after Low Impact D evelopment implementation to determine the total runoff produced by all lots for both cases. The results of computer modelling all lots were compared with the res ults from developing calculation methods to be used after computer modelling subsets of lots. Two calculation methods based on clustering lots to form urban hydrological response units were developed. A random sample of 5 % of all lots was then extracted from 6616 lots a menable to the porous pavement Low Impact D evelopment. Stepwise linear regression and linear regression were performed on the ran dom sample for each case of no Low I m pact D evelopment and with Low Impact D evelopment. Regression equations we re used to extrapolate results from the sample to Original Research Article

[1]  H. N. Holtan,et al.  Geomorphic grouping of soils in watershed engineering , 1969 .

[2]  Fabrice Rodriguez,et al.  A distributed hydrological model for urbanized areas - Model development and application to case studies , 2008 .

[3]  G. W. Milligan,et al.  A study of standardization of variables in cluster analysis , 1988 .

[4]  Richard H. McCuen,et al.  Spatio-temporal effects of low impact development practices , 2009 .

[5]  Jianhong Wu,et al.  Data clustering - theory, algorithms, and applications , 2007 .

[6]  Alexander H. Elliott,et al.  Effect of Aggregation of On-Site Storm-Water Control Devices in an Urban Catchment Model , 2009 .

[7]  A. H. Elliott,et al.  A review of models for low impact urban stormwater drainage , 2007, Environ. Model. Softw..

[8]  M. Eric,et al.  Modeling low impact development potential with hydrological response units. , 2013, Water science and technology : a journal of the International Association on Water Pollution Research.

[9]  Uri Shamir,et al.  Water‐sensitive planning: integrating water considerations into urban and regional planning , 2010 .

[10]  Z. Easton,et al.  Re-conceptualizing the soil and water assessment tool (SWAT) model to predict runoff from variable source areas , 2008 .

[11]  Michael E. Dietz.  Low Impact Development Practices: A Review of Current Research and Recommendations for Future Directions , 2007 .

[12]  M. Sivapalan,et al.  Catchment classification: Empirical analysis of hydrologic similarity based on catchment function in the eastern USA , 2011 .

[13]  Uri Shamir,et al.  Water-Sensitive Urban Planning: Modeling On-Site Infiltration , 2001 .