Characterization and prediction of stormwater runoff quality in sub-tropical rural catchments
- Authors: Cheema P.P.1, Reddy A.S.2, Kaur S.1
- 
							Affiliations: 
							- Department of Civil Engineering
- School of Energy and Environment
 
- Issue: Vol 44, No 2 (2017)
- Pages: 331-341
- Section: Water Quality and Protection: Environmental Aspects
- URL: https://journals.rcsi.science/0097-8078/article/view/174185
- DOI: https://doi.org/10.1134/S0097807817020129
- ID: 174185
Cite item
Abstract
Due to scarcity of local data on stormwater pollution levels and rainfall-runoff generation process, very few attempts have been made towards the management of stormwater in sub-tropical rural catchments. An attempt has been made in the present study to characterize and predict the stormwater runoff characteristics using regression modeling from five rural catchments in north-west India. Stormwater samples and flow data were collected from 75 storm events. Samples were analyzed for pH, total suspended solids (TSS), 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), total kjeldhal nitrogen (TKN), total phosphorous (TP), nitrate-nitrogen (NO3-–N), total coliform count (TC), fecal coliform count (FC), Zn, Cu and Fe. It was found that size of the catchment and the land use practices influenced the stormwater quality even in predominantly rural areas, otherwise thought to be homogeneous. The results obtained were related with the antecedent dry days (ADD) and average rainfall. ADD was found to be positively correlated with pollutant loads whereas average rainfall showed negative correlation. The study highlights the importance of ADD in causing greater mean pollutant concentrations except for TKN, TP and NO3-–N. Regression models were developed for the studied catchments to estimate mean pollutant concentrations as a function of rainfall variables. Results revealed that measured pollutant concentrations demonstrated high variability with ADD and average rainfall in small rural catchments, whereas in large catchments, factors like land use, extent of imperviousness etc. resulted in low predictability of measured parameters.
About the authors
Puneet Pal Singh Cheema
Department of Civil Engineering
							Author for correspondence.
							Email: ppsc390@gmail.com
				                					                																			                												                	India, 							Ludhiana, Punjab, 141006						
Akepati S. Reddy
School of Energy and Environment
														Email: ppsc390@gmail.com
				                					                																			                												                	India, 							Ludhiana, Punjab, 147001						
Sukhpreet Kaur
Department of Civil Engineering
														Email: ppsc390@gmail.com
				                					                																			                												                	India, 							Ludhiana, Punjab, 141006						
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