An enhanced SMA based SCS-CN inspired model for watershed runoff prediction
- 1. National Institute of Industrial Engineering-Mumbai, Environmental Engineering and Management Group (India)
- 2. Indian Institute of Technology, Department of Water Resources Development and Management (India)
- 3. National Institute of Hydrology, Water Resources Systems Division (India)
- 4. G. B. Pant National Institute of Himalayan Environment and Sustainable Development, National Mission of Himalayan Studies (India)
Description
Incorporation of initial soil moisture (V0) in the Soil Conservation Service Curve Number (SCS-CN) methodology helps to avoid the sudden jumps in Curve Number (CN) and, in turn, in computed runoff. It invoked the development of an enhanced (yet simple) Soil Moisture Accounting (SMA) procedure-based-SCS-CN inspired model, by incorporating initial moisture (V0). Its performance is tested using a dataset of 152 small to large watersheds of USDA (total 38,169 storm events), and compared with original SCS-CN method, Mishra and Singh (Acta Geophys Polon 50(3):457–477, 2002), Michel et al. (Water Resour Res 41(2):W02011, 2005) and Singh et al. (Water Resour Manag 29(11): 4111–4127, 2015) model using four statistical indices (RMSE, R2, PBIAS and NSE) and rank grading system (RGS). The proposed model scores highest (= 691 marks out of maximum 2280 marks) (Rank I) followed by Singh et al. (Water Resour Manag 29(11):4111–4127, 2015) model with 642 marks (Rank II), Michel et al. (Water Resour Res 41(2):W02011, 2005) model with 376 marks (Rank III) and Mishra and Singh model with 362 marks (= Rank IV). The original SCS-CN model, however, performs the poorest of all with 209 marks (Rank V).
Additional details
Identifiers
Publishing Information
- Journal Title
- Environmental Earth Sciences
- Journal Volume
- 76
- Journal Issue
- 21
- Journal Page Range
- p. 1-20
- ISSN
- 1866-6280
INIS
- Country of Publication
- Germany
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 51019239
- Subject category
- S54: ENVIRONMENTAL SCIENCES;
- Descriptors DEI
- DATASETS; FORECASTING; MOISTURE; RUNOFF; SOIL CONSERVATION; SOILS; STORMS; WATERSHEDS
- Descriptors DEC
- DOCUMENT TYPES; ENVIRONMENTAL TRANSPORT; MASS TRANSFER; RESOURCE CONSERVATION
Optional Information
- Copyright
- Copyright (c) 2017 Springer-Verlag GmbH Germany