Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Simplified SMA-inspired 1-parameter SCS-CN model for runoff estimation

Verma, Sangeeta ; Singh, Pushpendra Kumar ; Mishra, Surendra Kumar ; Jain, Sanjay Kumar ; Berndtsson, Ronny LU orcid ; Singh, Anju and Verma, Ravindra Kumar (2018) In Arabian Journal of Geosciences 11(15).
Abstract

This study proposes a simplified 1-parameter SCS-CN model (M5) based on Mishra-Singh (2002) model and soil moisture accounting (SMA) procedure for surface runoff estimation and compares its performance with the existing SCS-CN method (SCS, 1956) (M1), Michel 1-P model (Water Resour Res 41:1-6, 2005) (M2), Sahu 1-P model (Hydrol Process 21:2872-2881, 2007) (M3), and Ajmal et al. model (J Hydrol 530:623-633, 2015) (M4) using large rainfall–runoff dataset of 48,763 events from123 USDA-ARS watersheds. The performance of models was evaluated using three statistical error indices such as Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE), percentage bias (PBIAS), and rank and grading system (RGS). Based on the results obtained,... (More)

This study proposes a simplified 1-parameter SCS-CN model (M5) based on Mishra-Singh (2002) model and soil moisture accounting (SMA) procedure for surface runoff estimation and compares its performance with the existing SCS-CN method (SCS, 1956) (M1), Michel 1-P model (Water Resour Res 41:1-6, 2005) (M2), Sahu 1-P model (Hydrol Process 21:2872-2881, 2007) (M3), and Ajmal et al. model (J Hydrol 530:623-633, 2015) (M4) using large rainfall–runoff dataset of 48,763 events from123 USDA-ARS watersheds. The performance of models was evaluated using three statistical error indices such as Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE), percentage bias (PBIAS), and rank and grading system (RGS). Based on the results obtained, the models can be ranked as follows: M5 > M4 > M3 > M1 > M2, i.e., model M5 outperformed all the remaining four models M1–M4 and hence is recommended for field applications.

(Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Curve number, SCS-CN method, Soil moisture accounting, Surface runoff
in
Arabian Journal of Geosciences
volume
11
issue
15
article number
420
publisher
Springer
external identifiers
  • scopus:85051145988
ISSN
1866-7511
DOI
10.1007/s12517-018-3736-7
language
English
LU publication?
yes
id
fc348bcd-c288-4504-b95f-281b543023e8
date added to LUP
2018-08-22 13:34:47
date last changed
2023-09-08 05:08:25
@article{fc348bcd-c288-4504-b95f-281b543023e8,
  abstract     = {{<p>This study proposes a simplified 1-parameter SCS-CN model (M5) based on Mishra-Singh (2002) model and soil moisture accounting (SMA) procedure for surface runoff estimation and compares its performance with the existing SCS-CN method (SCS, 1956) (M1), Michel 1-P model (Water Resour Res 41:1-6, 2005) (M2), Sahu 1-P model (Hydrol Process 21:2872-2881, 2007) (M3), and Ajmal et al. model (J Hydrol 530:623-633, 2015) (M4) using large rainfall–runoff dataset of 48,763 events from123 USDA-ARS watersheds. The performance of models was evaluated using three statistical error indices such as Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE), percentage bias (PBIAS), and rank and grading system (RGS). Based on the results obtained, the models can be ranked as follows: M5 &gt; M4 &gt; M3 &gt; M1 &gt; M2, i.e., model M5 outperformed all the remaining four models M1–M4 and hence is recommended for field applications.</p>}},
  author       = {{Verma, Sangeeta and Singh, Pushpendra Kumar and Mishra, Surendra Kumar and Jain, Sanjay Kumar and Berndtsson, Ronny and Singh, Anju and Verma, Ravindra Kumar}},
  issn         = {{1866-7511}},
  keywords     = {{Curve number; SCS-CN method; Soil moisture accounting; Surface runoff}},
  language     = {{eng}},
  month        = {{08}},
  number       = {{15}},
  publisher    = {{Springer}},
  series       = {{Arabian Journal of Geosciences}},
  title        = {{Simplified SMA-inspired 1-parameter SCS-CN model for runoff estimation}},
  url          = {{http://dx.doi.org/10.1007/s12517-018-3736-7}},
  doi          = {{10.1007/s12517-018-3736-7}},
  volume       = {{11}},
  year         = {{2018}},
}