Optimum parametrization of the soil conservation service (SCS) method for simulating the hydrological response in arid basins. Issue 1 (31st December 2022)

• Record Type: Journal Article
• Authors: Niyazi, Burhan; Khan, Abdul A.; Masoud, Milad; Elfeki, Amro; Basahi, Jalal; Zaidi, Syed
• Is Part Of: Geomatics, natural hazards & risk. Volume 13:Issue 1(2022)
• Page Start: 1482
• Page End: 1509
• Publication Date: 2022-12-31
• Subjects: Rainfall-runoff modeling -- SCS-CN method -- unit hydrograph theory -- arid zone hydrology -- Al-Lith basin -- Saudi Arabia; Geomatics -- Periodicals; Geomatics; Periodicals; 526.905
• DOI: 10.1080/19475705.2022.2080005
• Languages: English
• ISSNs: 1947-5705

Abstract

Abstract: The use of the soil conservation service (SCS) curve number (CN) model for estimation of the rainfall excess and the SCS-unit hydrograph (UH) model are common tools for flood studies in arid regions. In this research, we are investigating the capability of these models to simulate flood events in the arid region under the common parametrization provided by the SCS model (SCS-CN, the initial abstraction ratio, λ, and UH theory) and the optimum parameterization for best simulating the hydrologic response. A case study is performed in Al-Lith basin in the west of Saudi Arabia (SA). The study simulates measured rainfall-runoff events in the area using seven scenarios (various SCS-CN estimation methods: least-squares method (CNLSM ), asymptotic fitting method (CN∞ ), SCS-CN tables (CNdesign ), and antecedent moisture content CN (CNI, CNII, and CNIII ), λ = 0.2 and 0.01, and SCS-UH and UH derived from streamflow data) and a comparison is made between the observations and model results under the common parameterization of the SCS model and parameterization estimated from the Saudi arid environment. The comparison between simulated and observed peak flow and runoff volume of the studied events shows high scatter which is a common feature in arid regions due to the inherent uncertainties in the hydrological processes which are not yet resolved due to the lack of detailed measurements of the rainfall-runoff processes. Statistical analysis showed that λ = 0.01 provides a minimum root mean square error (RMSE) in the peak flow (24.8 m 3 /s) and the runoff volume (0.31 million m 3 ) with CNLSM obtained by LSM. CN∞ is bad to simulate the hydrologic response. The SCS-CN Tables cannot be used for hydrological simulation. They can rather be used for the design purposes of mitigation structures. HIGHLIGHTS: The high scatter between observations and simulations in arid regions is due to the inherent uncertainties in the hydrological processes that are not yet resolved. The asymptotic CN (CN∞ ) is not a good estimation for curve numbers to simulate the hydrologic response. The SCS-CN Tables cannot be used for hydrological simulation. They can rather be used for the design purposes of mitigation structures. The dry condition (AMC I) is the best for the hydrological simulation in arid regions since it is the predominant condition in the region.