Integration of Remote Sensing, GIS, and SCS-CN Model for Runoff Volume Estimation in Al-Deir Valley Basin, Iraqi Jazira Desert

Abstract

Iraq's Jazira Desert faces a severe water security challenge, a problem exacerbated by a significant lack of field-based hydrological data that critically hinders effective water resource management. This study addresses this gap by presenting the first quantitative assessment of water harvesting potential in the ungauged 114 km² Al-Deir Valley Basin, a representative arid catchment. The significance of this research lies in its potential to provide actionable data for mitigating water scarcity. The study integrates Remote Sensing (RS), Geographic Information Systems (GIS), and the Soil Conservation Service-Curve Number (SCS-CN) model. Land cover and hydrological soil groups (HSG) were derived from Landsat imagery and the Harmonized World Soil Database (HWSD), respectively, while rainfall data was spatially interpolated using the Inverse Distance Weighting (IDW) method. The derived Curve Number (CN) values ranged from 77 to 90, indicating high runoff potential. Based on these parameters, the model estimated a mean annual runoff depth of 81.40–115.28 mm, corresponding to a total harvestable volume of up to 4.96 million m³. Sensitivity analysis confirmed the model's robustness, showing that a ±5% variation in CN values resulted in an ~11% change in runoff depth. The findings highlight the basin's high suitability for water harvesting projects and provide a foundational geospatial baseline for developing strategic interventions to enhance water security and drought resilience in this data-scarce region.