EconPapers    
Economics at your fingertips  
 

SCS-CN Based Quantification of Potential of Rooftop Catchments and Computation of ASRC for Rainwater Harvesting

Piyush Singh, B. Yaduvanshi, Swati Patel and Saswati Ray

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2013, vol. 27, issue 7, 2012 pages

Abstract: Rooftop rainwater harvesting, among other options, play a central role in addressing water security and reducing impacts on the environment. The storm or annual storm runoff coefficient (RC/ASRC) play a significant role in quantification of potential of rooftop catchments for rainwater harvesting, however, these are usually selected from generic lists available in literature. This study explores methodology/procedures based on one of the most popular and versatile hydrological model, Soil Conservation Service Curve Number (SCS-CN) (SCS 1986 ) and its variants, i.e., Hawkins SCS-CN (HSCS-CN) model (Hawkins et al. 2001 ), Michel SCS-CN (MSCS-CN) model (Michel et al. Water Resour Res 41:W02011, 2005 ), and Storm Water Management Model-Annual Storm Runoff Coefficient (SWMM-ASRC) (Heaney et al. 1976 ) and compares their performance with Central Ground Board (CGWB) (CGWB 2000 ) approach. It has been found that for the same amount of rainfall and same rooftop catchment area, the MSCS-CN model yields highest rooftop runoff followed by SWMM-ASRC > HSCS-CN > SCS-CN > CGWB. However, the SCS-CN model has close resemblance with CGWB approach followed by HSCS-CN model, SWMM-ASRC, and MSCS-CN model. ASRCs were developed using these models and it was found that MSCS-CN model has the highest value of ASRC (= 0.944) followed by SWMM-ASRC approach (=0.900), HSCS-CN model (=0.830), SCS-CN model (=0.801), and CGWB approach (=0.800). The versatility of these models lies to the fact that CN values (according to rooftop catchment characteristics) would yield rooftop runoff and therefore ASRC values based on sound hydrological perception and not just on the empiricism. The models have inherent capability to incorporate the major factors responsible for runoff production from rooftop/urban, i.e., surface characteristics, initial abstraction, and antecedent dry weather period (ADWP) for the catchments and would be better a tool for quantification rather than just using empirical runoff coefficients for the purpose. Copyright Springer Science+Business Media Dordrecht 2013

Keywords: Rooftop rainwater harvesting; SCS-CN method; Runoff coefficient; Rainwater harvesting (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11269-013-0267-6 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:27:y:2013:i:7:p:2001-2012

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11269

DOI: 10.1007/s11269-013-0267-6

Access Statistics for this article

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) is currently edited by G. Tsakiris

More articles in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) from Springer, European Water Resources Association (EWRA)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-30
Handle: RePEc:spr:waterr:v:27:y:2013:i:7:p:2001-2012