Comparative evaluation of SCS-CN-inspired models in applications to classified datasets

• Published in: Agricultural water management Vol. 97; no. 5; pp. 749 - 756
• Main Authors: Sahu, R.K., Mishra, S.K., Eldho, T.I.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01-05-2010; Amsterdam; New York: Elsevier; Elsevier
• Series: Agricultural Water Management
• Subjects: Accounting; accuracy; Agricultural and forest climatology and meteorology. Irrigation. Drainage; agricultural watersheds; Agronomy. Soil science and plant productions; Biological and medical sciences; Curve number method; depth; equations; estimation; Fundamental and applied biological sciences. Psychology; General agronomy. Plant production; Land use; Mathematical models; Physical properties; Physics, chemistry, biochemistry and biology of agricultural and forest soils; Precipitation; rain; Rainfall-runoff modeling Curve number method Soil moisture accounting (SMA); Rainfall–runoff modeling; runoff; Soil (material); soil conservation; Soil Conservation Service Curve Number; Soil moisture; Soil moisture accounting (SMA); Soil science; soil types; soil water content; Stores; surface water; Water and solute dynamics; water flow; Water management; United States; USA; Rainfall–runoff modeling; Soil moisture accounting (SMA); Curve number method; Evaluation; Accounting; Soil moisture; Rainfall-runoff modeling; Property of soil; Data set; Data; Runoff water; Method; Physical properties; Modeling; Soil water properties; Water engineering; Models; Application; Comparative study
• ISSN: 0378-3774; 1873-2283
• DOI: 10.1016/j.agwat.2010.01.005

One of the popular methods for estimating the depth of surface runoff for a given rainfall event is the Soil Conservation Service Curve Number (SCS-CN) method. Of late, several inconsistencies in its soil moisture accounting procedure have been pointed out by
Michel et al. (2005), and a more rational procedure suggested. Recently, a modification incorporating an expression for estimation of initial soil moisture store level, a crucial parameter, was suggested by
Sahu et al. (2007). The present study compares this modification with the original SCS-CN model and the other available variants on a large set of data of 76 small agricultural watersheds of the United States and finally suggests an improved model. The comprehensive comparison between these models reveals the proposed improvement to perform better than all other versions in all classified applications based on land use, soil type, combinations of land use and soil type, and precipitation regimes. A simplified version of the model is further suggested for practical applications.