Allafta et al. (2026) Rainfall–Surface Runoff Estimation Using SCS-CN Model and Geospatial Techniques: A Case Study of the Shatt Al-Arab Region, Iraq–Iran

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Earth
• Year: 2026
• Date: 2026-02-19
• Authors: Hadi Salim Aoubid Allafta, Christian Opp, Buraq Adnan Al-Baldawi
• DOI: 10.3390/earth7010032

Research Groups

[Information not provided in the paper text.]

Short Summary

This study addresses the scarcity of runoff data in the Shatt Al-Arab Region by applying the Soil Conservation Service–Curve Number (SCS–CN) method integrated with remote sensing and GIS to predict surface runoff over 35 years, finding an average annual runoff of 233 mm and demonstrating the method's suitability for the region.

Objective

• To predict surface runoff in the Shatt Al-Arab Region using the SCS–CN method in conjunction with remote sensing and geographic information systems, thereby overcoming the significant obstacle of runoff data paucity in Iraq and Iran.

Study Configuration

• Spatial Scale: Regional scale, encompassing the Shatt Al-Arab Region defined as the drainage areas and lateral sub-basins contributing direct surface runoff to the main channel between Qurna city and the Arabian Gulf.
• Temporal Scale: 35 years (1979–2013).

Methodology and Data

• Models used: Soil Conservation Service–Curve Number (SCS–CN) method.
• Data sources: Remote sensing (RS) and Geographic Information System (GIS) for developing and processing rainfall, land use/land cover (LULC), hydrologic soil group (HSG), and slope maps.

Main Results

• Annual surface runoff ranged between 163 mm (in 2008) and 300 mm (in 1982).
• The average annual surface runoff was 233 mm per year.
• The average annual surface runoff volume in the study area was 33.657 km³.
• A significant positive correlation was found between annual rainfall and annual runoff (coefficient of determination (r²) = 0.67, probability value (p) < 0.05).
• Runoff potential was observed to be low in the southern parts of the study area and gradually increased towards the northern parts.
• Cross-validation of the modeled annual runoff with annual runoff data showed reasonably close matches (r² = 0.73, p < 0.001), confirming the procedure's suitability.

Contributions

• Provides a crucial methodology for quantifying surface runoff in data-scarce regions like Iraq and Iran, which is essential for water resource management.
• Offers a comprehensive 35-year dataset of predicted surface runoff for the Shatt Al-Arab Region, filling a significant data gap.
• Demonstrates the effectiveness and suitability of integrating the SCS–CN method with RS and GIS for runoff prediction in this specific geographical context.
• Generates valuable information for the design of storage structures, irrigation patterns, waterways, erosion control, water harvesting, and groundwater development schemes in the region.

Funding

[Information not provided in the paper text.]

Citation

@article{Allafta2026RainfallSurface,
  author = {Allafta, Hadi Salim Aoubid and Opp, Christian and Al-Baldawi, Buraq Adnan},
  title = {Rainfall–Surface Runoff Estimation Using SCS-CN Model and Geospatial Techniques: A Case Study of the Shatt Al-Arab Region, Iraq–Iran},
  journal = {Earth},
  year = {2026},
  doi = {10.3390/earth7010032},
  url = {https://doi.org/10.3390/earth7010032}
}