Numerical Assessment of the Impact of Kani Goozhan and Chouman Dams on Floodplain Mapping and Flood Hazard in the Chouman Watershed

Document Type : Research Paper

Authors

• Kiyoumars Roushangar ¹
• Faezeh Shabani ²
• Aydin Panahi ¹
• Javad Taherpour ¹

¹ Department of Water Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran

² Department of Water Science and Engineering, Faculty of Agriculture, Birjand University, Birjand, Iran

Abstract

Keywords

• Remote Sensing
• HEC-HMS
• HEC-RAS
• Risk Management

Main Subjects

• منابع آب

Introduction

Floods represent one of the most devastating natural hazards, posing severe threats to human lives and infrastructure, particularly in mountainous regions where data scarcity complicates accurate risk assessment. Effective floodplain delineation is vital for informed flood risk management and mitigation strategies. In areas with limited ground-based observations, integrating remote sensing (RS) and geographic information systems (GIS) with advanced numerical modeling provides a robust alternative for generating reliable hazard maps. This approach leverages satellite-derived datasets to supply essential inputs, such as high-resolution land cover and topographic information, for hydrological and hydraulic simulations. The present investigation centers on the Chouman Watershed in Kurdistan Province, Iran, situated between the upstream Kani Goozhan Dam and the downstream Chouman Dam. The core objective is to evaluate the dams' influence on flood routing characteristics while delineating vulnerable zones in the inter-reservoir reach, thereby supporting enhanced decision-making in flood-prone rural settings.

Method

Encompassing roughly 860 km² of predominantly rugged terrain, the study area required spatially detailed inputs to overcome observational constraints. High-resolution (10 m) land use classification from the ESRI global dataset was employed to estimate runoff curve numbers (CN) via the Soil Conservation Service (SCS) methodology in hydrological modeling, alongside distributed Manning's roughness values for hydraulic computations. The ALOS digital elevation model (30 m resolution) facilitated basin delineation and reservoir geometry extraction. Intensity-duration-frequency relationships were derived from long-term records at the nearby Baneh synoptic station. Hydrological simulations were conducted using HEC-HMS v4.8, partitioning the watershed into 77 sub-basins and incorporating storage routing for the dams under multiple release scenarios. Two-dimensional unsteady hydraulic modeling in HEC-RAS v6.1 solved the shallow water equations, applying outflow hydrographs from HEC-HMS as upstream boundaries. Model calibration and validation utilized statistical frequency analysis (including log-Pearson Type III distributions) of available hydrometric data. Post-processing in ArcGIS yielded detailed inundation extents for return periods of 25, 50, 100, and 200 years.

Results

Validation efforts indicated strong model performance, with peak flow discrepancies typically under 20%. Key findings underscored the substantial attenuating effect of the upstream Kani Goozhan reservoir: for the 200-year event, peak outflows dropped markedly by around 50% (420 to 210 m³/s), accompanied by a notable 4.5-hour lag in hydrograph timing. Downstream hydraulic analyses showed peak velocities reaching 19 m/s in unregulated conditions, but manageable to approximately 13 m/s—or lower through phased releases—via coordinated spillway and bottom outlet activation. Reservoir levels at the Chouman Dam fluctuated between 30 and 40 m across simulated events, affording extended response windows. Inundation mapping exposed several rural communities positioned directly within high-hazard zones during extreme floods, emphasizing elevated vulnerability along the river corridor.

Conclusions

By fusing remote sensing products (including ESRI land cover and ALOS topography) with coupled HEC-HMS and 2D HEC-RAS frameworks, this work establishes a practical, resource-efficient pipeline for flood hazard delineation in challenging, data-poor terrains. The tandem dam system proves instrumental in moderating flood peaks, curtailing velocities, and prolonging lead times for evacuation and intervention, ultimately bolstering community resilience. The resulting hazard maps furnish actionable insights for synchronized reservoir operations, early warning infrastructure, and targeted protective measures in exposed settlements. This integrated methodology holds broad applicability for sustainable water resource stewardship and disaster preparedness in comparable mountainous contexts.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Authorship contribution

Kiomars Roshangar: Project management, study design, and result interpretation. Faezeh Shabani: Methodology development, data analysis, and result interpretation. Aydin Panahi: Data collection, and manuscript drafting and manuscript review. Javad Taherpour: Methodology development, data analysis, and result interpretation.

Declaration of Generative AI and AI-assisted technologies in the writing process

During the preparation of this work the authors used ChatGPT in order to rewrite and edit the Persian and English text. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.

Data availability statement

Data used in this study are available from the corresponding author upon request.

Ethical considerations

The authors avoided data fabrication, falsification, and plagiarism, and any form of misconduct.

Conflict of interest

The authors declare no conflict of interest.