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

被引:10
|
作者
Verma, Sangeeta [1 ]
Singh, Pushpendra Kumar [2 ]
Mishra, Surendra Kumar [3 ]
Jain, Sanjay Kumar [2 ]
Berndtsson, Ronny [4 ]
Singh, Anju [1 ]
Verma, Ravindra Kumar [1 ]
机构
[1] Natl Inst Ind Engn, Environm Engn & Management Grp, Bombay 400087, Maharashtra, India
[2] Natl Inst Hydrol, Water Resources Syst Div, Roorkee 247667, Uttarakhand, India
[3] Indian Inst Technol, Dept Water Resources Dev & Management, Roorkee 247667, Uttarakhand, India
[4] Lund Univ, Dept Water Resources Engn, Ctr Middle Eastern Studies, Lund, Sweden
关键词
SCS-CN method; Soil moisture accounting; Surface runoff; Curve number; SERVICE-CURVE NUMBER; MOISTURE ACCOUNTING PROCEDURE; TERM HYDROLOGIC-SIMULATION; A-S RELATION; ANTECEDENT MOISTURE; HETEROGENEOUS WATERSHEDS; CATCHMENT; FLOW; QUANTIFICATION; INFILTRATION;
D O I
10.1007/s12517-018-3736-7
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
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.
引用
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页数:19
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  • [1] Simplified SMA-inspired 1-parameter SCS-CN model for runoff estimation
    Sangeeta Verma
    Pushpendra Kumar Singh
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    Sanjay Kumar Jain
    Ronny Berndtsson
    Anju Singh
    Ravindra Kumar Verma
    [J]. Arabian Journal of Geosciences, 2018, 11
  • [2] An enhanced SMA based SCS-CN inspired model for watershed runoff prediction
    Verma, S.
    Mishra, S. K.
    Singh, A.
    Singh, P. K.
    Verma, R. K.
    [J]. ENVIRONMENTAL EARTH SCIENCES, 2017, 76 (21)
  • [3] An enhanced SMA based SCS-CN inspired model for watershed runoff prediction
    S. Verma
    S. K. Mishra
    A. Singh
    P. K. Singh
    R. K. Verma
    [J]. Environmental Earth Sciences, 2017, 76
  • [4] Application of SCS-CN Model in Runoff Estimation
    Wang, Dake
    Qin, Liangqiong
    Chang, Bao
    Wang, Mingxing
    Zhang, Weihua
    [J]. PROCEEDINGS OF THE 2015 INTERNATIONAL SYMPOSIUM ON MATERIAL, ENERGY AND ENVIRONMENT ENGINEERING (ISM3E 2015), 2016, 46 : 50 - 54
  • [5] Investigation of SCS-CN and its inspired modified models for runoff estimation in South Korean watersheds
    Ajmal, Muhammad
    Moon, Geon-woo
    Ahn, Jae-hyun
    Kim, Tae-woong
    [J]. JOURNAL OF HYDRO-ENVIRONMENT RESEARCH, 2015, 9 (04) : 592 - 603
  • [6] THE SCS-CN MODEL ASSISTED BY GIS - ALTERNATIVE ESTIMATION OF THE HYDRIC RUNOFF IN REAL TIME
    Craciun, A. I.
    Haidu, I.
    Bilasco, St.
    [J]. GEOGRAPHIA TECHNICA, 2007, 2 (01): : 1 - 7
  • [8] Application of the SCS-CN Model to Runoff Estimation in a Small Watershed with High Spatial Heterogeneity
    Xiao Bo
    Wang Qing-Hai
    Fan Jun
    Han Feng-Peng
    Dai Quan-Hou
    [J]. PEDOSPHERE, 2011, 21 (06) : 738 - 749
  • [9] Estimation of surface runoff in Malattar sub-watershed using SCS-CN method
    R. Amutha
    P. Porchelvan
    [J]. Journal of the Indian Society of Remote Sensing, 2009, 37 : 291 - 304
  • [10] Estimation of Surface Runoff in Malattar Sub-watershed using SCS-CN Method
    Amutha, R.
    Porchelvan, P.
    [J]. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2009, 37 (02) : 291 - 304