Improving runoff estimation by raster-based natural resources conservation service-curve number adjustment for a new initial abstraction ratio in semi-arid climates

• Main Authors: Akbari, Abolghasem, Daryabor, Farshid, Abu Samah, Azizan, Aliakbarkhani, Zahra Shirmohammadi
• Format: Article
• Published: Wiley 2021
• Subjects: Q Science (General)
• Online Access: http://eprints.um.edu.my/26523/
• Institution: Universiti Malaya

The Natural Resources Conservation Service Curve Number (NRCS-CN) is a popular rainfall-runoff modeling method. In this study the performance of the NRCS-CN method in runoff estimation for single storms based on a new initial abstraction ratio (lambda=0.05) in the semi-arid climate of Khorasan Razavi, Iran, is presented. The method utilizes public domain Geographic Information Systems (GIS) software for the Geospatial analysis and generating the CN map of the study area. CN values provided in the standard Service Curve Number-tables (CN0.2) were found to overestimate runoff potential compared to modified tables of CN0.05. Evaluation of the performance of CN0.05 for runoff estimation was undertaken using data collected in thirty-five rainfall-runoff events in the Kardeh watershed. A strong correlation (R = 0.97) was found between the observed and estimated direct runoff when CN0.05 was used for the runoff estimation as well as between the observed and estimated runoff based on Nash-Sutcliffe efficiency (0.88). Overall, runoff predictions were improved with the revised NRCS-CN method in semi-arid climatic settings when lambda is set to 0.05. We provide an easy-to-use relationship between CN0.2 and CN0.05 that improves Runoff estimation from NRCS-CN.