Rainfall–Surface Runoff Estimation Using SCS-CN Model and Geospatial Techniques: A Case Study of the Shatt Al-Arab Region, Iraq–Iran

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Authors: Hadi Salim Aoubid Allafta, Christian Opp, Buraq Adnan Al-Baldawi
Cited by: 2
References: 95

Abstract

Accurate quantification of surface runoff is required for the appropriate design of storage structures, irrigation patterns, waterways, erosion control structures, water harvesting projects, and groundwater development schemes. However, the paucity of runoff data in Iraq and Iran is a serious obstacle. The soil conservation service–curve number (SCS–CN) method is applied in conjunction with remote sensing (RS) and geographic information system (GIS) to predict the surface runoff in the Shatt Al-Arab Region. In the present study, the Shatt Al-Arab Region is defined as the drainage areas and lateral sub-basins that contribute direct surface runoff to the main channel between Qurna city and the Arabian Gulf. Rainfall, land use/land cover (LULC), hydrologic soil group (HSG), and slope maps are developed in a GIS platform and processed to produce surface runoff for 35 years (1979–2013). The surface runoff ranges between 163 mm (2008) and 300 mm (1982) with an average of 233 mm yr−1. The average annual surface runoff in the study area is 33.657 km3. A scatter plot constructed to visualize the connection between annual rainfall and annual runoff reveals a significant positive relation (coefficient of determination (r2) = 0.67, probability value (p) < 0.05). The runoff potential is low in the southern parts of the study area and gradually rises towards the northern parts. Cross-validation of the modeled annual runoff with the annual runoff data shows reasonably close matches (r2 = 0.73, p < 0.001) demonstrating the procedure’s suitability.

Fields of Study & Subjects

Groundwater and Watershed Analysis Hydrology and Watershed Management Studies Flood Risk Assessment and Management

Publication details

Journal / source
Earth
Publisher
MDPI AG
Volume
7
Issue
1
Pages
32–32
Publication date
19 February 2026
Language
EN