دانشگاه اصفهان جغرافیا و برنامه ریزی محیطی 2008-5362 37 2 2026 06 22 Assessment and Evaluation of Flood Risk Factors (Case Study: Dashtiari Watershed) سنجش و ارزیابی عوامل تأثیرگذار در خطر سیلاب (مطالعه موردی: حوضه دشتیاری) 1 28 30496 10.22108/gep.2026.144627.1714 FA صمد فتوحی دانشیار گروه جغرافیای طبیعی، دانشکده جغرافیا و برنامه‌ریزی محیطی، دانشگاه سیستان و بلوچستان، زاهدان، ایران لیلی لطیفی دانشجوی دکتری ژئومورفولوژی، دانشکده جغرافیا و برنامه‌ریزی محیطی، دانشگاه سیستان و بلوچستان، زاهدان، ایران مسعود سعیدی دانشجوی دکتری ژئومورفولوژی، دانشکده جغرافیا و برنامه‌ریزی محیطی، دانشگاه سیستان و بلوچستان، زاهدان، ایران Journal Article 2025 08 26 Abstract Given the increasing frequency of floods in many watersheds, there is a growing need to examine the key factors contributing to flood risk in these areas. Assessing these factors is essential for evaluating vulnerability and exposure and provides critical information for effective flood management. In this context, the present study aimed to assess and evaluate the factors influencing flood risk with the Dashtiari Watershed selected as the case study. This research was descriptive-analytical in nature and applied in purpose. Data were collected through both library research and field surveys. Flood hazard zoning and risk assessment were carried out by using 13 parameters—including slope, elevation, and soil texture—and analyzed with ArcGIS software, the IGR index, and the Random Forest (RF) algorithm. The results indicated that approximately 5.40% of the study area fell into the very high-risk, 33.63% high-risk, 37.94% moderate-risk, 18.70% low-risk, and 4.31% very low-risk categories. Notably, about 50% of residential areas were situated within high-risk zones, which, in the event of flooding, could lead to severe human casualties and substantial economic losses. Keywords: Flood, Natural hazards, Influencing factors, Dashtiari Basin. Introduction Natural hazards, particularly floods, present serious challenges to communities around the world. These events often result in the destruction of infrastructure, social and economic disruption, and widespread environmental degradation. The occurrence and severity of floods are governed by a combination of geomorphological, hydrological, and atmospheric factors. Key determinants include land slope, soil type, land use, and rock permeability, all of which influence the magnitude and intensity of flooding. In Iran, certain regions are inherently more susceptible to flooding due to their geographic and geological characteristics. One such area is the Dashtiari watershed located in the southern part of Sistan and Baluchestan Province. This vast floodplain, which includes the Kajoo River and several other flood pathways, has historically experienced alternating periods of severe drought and extreme rainfall. Over time, local communities have developed adaptive strategies to mitigate the impacts of such hydrological extremes. Hydromorphometric analyses have shown that examining the physiographic attributes of drainage basins can provide valuable insights into their hydrological behavior. This understanding is critical for assessing flash flood risks and designing appropriate control measures. In this context, flood hazard zoning maps serve as essential tools for sustainable land-use planning and enhancing community resilience. Furthermore, hydraulic models play a key role in evaluating flow distribution patterns across floodplain areas, thereby supporting the development of effective flood mitigation strategies. Ultimately, sound water resource management and comprehensive hazard mitigation planning are vital for reducing both human casualties and economic losses. Implementation of early warning systems, construction of flood-resilient infrastructure, and timely evacuation of high-risk zones rank among the most effective responses to flood crises. Special attention to the calibration of relevant risk factors—particularly in flood-prone regions like Dashtiari—represents a crucial step toward sustainable development and minimization of flash flood damage. Materials and Methods This study integrated diverse datasets from multiple sources to develop a comprehensive flood risk analysis model for the study area. The compiled data encompassed topographic parameters—including slope, elevation, and proximity to river networks—hydrological variables, such as annual precipitation, river discharge, and groundwater levels, as well as geological attributes like soil type, permeability, and lithological structure. In addition, land use and vegetation cover data—including vegetation density, land utilization patterns, and anthropogenic modifications—were incorporated to ensure a holistic representation of watershed characteristics. All spatial data were processed and analyzed within the ArcGIS software environment. For flood hazard modeling, the Random Forest (RF) algorithm, a robust machine learning technique, was employed due to its high predictive performance and ability to handle complex interactions among variables. To further evaluate the relative contribution of each predictor to flood susceptibility, the Information Gain Ratio (IGR) was calculated, providing insight into variable importance. The methodological framework proceeded through several sequential stages: (1) collection and preprocessing of spatial data within a GIS framework; (2) selection of influential variables based on statistical relevance; (3) application of the RF model for flood hazard zoning; (4) validation of model performance using standard statistical metrics, including prediction accuracy, sensitivity, and specificity; and (5) interpretation of the resulting outputs to inform flood management strategies tailored to the region. This systematic approach not only enables precise flood risk assessment, but also supports the development of evidence-based mitigation measures. By integrating advanced modeling techniques with sound spatial analysis, the study contributes to sustainable planning and the design of protective interventions aimed at reducing flood-related damages. Research Findings The modeling results revealed a heterogeneous distribution of flood risk across the Dashtiari watershed with varying levels of vulnerability identified among different areas. According to the RF model outputs, approximately 50% of residential and agricultural lands were situated within high- or very high-risk zones, underscoring a significant exposure to potential flood events. Flood hazard zoning further indicated that 5.40% of the total study area was classified as very high risk, predominantly comprising regions adjacent to river channels and areas characterized by gentle slopes. An additional 33.63% of the watershed fell into the high-risk category attributed largely to the dense drainage network and prevalence of impermeable soil types, which together facilitated rapid runoff generation. In contrast, 37.94% of the area was designated as moderate risk, while 18.70% and 4.31% were classified as low and very low risk, respectively. The analysis of contributing factors using the IGR identified annual precipitation as the most influential variable in promoting surface runoff and triggering flood events. The Topographic Wetness Index (TWI) and land elevation also played critical roles with lower-lying areas and zones of water accumulation demonstrating heightened susceptibility. Proximity to river networks emerged as another key determinant of flood risk. Furthermore, soil characteristics—particularly clay content and low permeability—significantly enhanced runoff potential. Land use and vegetation cover also exerted a direct influence on flood dynamics; irrigated agricultural lands and bare surfaces, in particular, displayed increased sensitivity to flooding. The predictive performance of the RF model proved to be robust, achieving an overall accuracy of 85% and a kappa coefficient of 0.82. These metrics confirm the model’s strong capability in delineating flood-prone areas and provide a reliable basis for risk assessment and subsequent planning efforts. Discussion and Conclusion: The modeling results indicated that flood risk distribution in the Dashtiari watershed was heterogeneous with varying levels of vulnerability across different areas. According to the RF model, approximately 50% of residential and agricultural lands were situated in high- or very high-risk zones. Flood hazard zoning further revealed that 5.40% of the study area was classified as very high risk, predominantly comprising areas near rivers and regions with gentle slopes. An additional 33.63% fell into the high-risk category, which was attributed to the dense drainage network and impermeable soils that facilitated flooding. In contrast, 37.94% of the area was designated as medium risk, while 18.70% and 4.31% were categorized as low and very low risk, respectively. The analysis of influential factors using the IGR index identified annual precipitation as the most significant driver of surface runoff and flood generation. The TWI and land elevation also played crucial roles as lower elevations and zones of water accumulation would increase flood susceptibility. Proximity to rivers emerged as another key determinant of flood risk. Furthermore, soil type and permeability substantially influenced flood formation with clayey and impermeable soils contributing to heightened surface runoff. Land use and vegetation cover also exerted a direct effect, particularly irrigated agricultural lands and bare areas, which exhibited increased sensitivity to flood events. The RF model demonstrated strong predictive performance, achieving an overall accuracy of 85% and a kappa coefficient of 0.82 and confirming its reliability in delineating flood-prone areas and supporting its applicability for risk assessment and planning purposes. چکیده امروزه با توجه به وقوع سیلاب‌ در بیشتر حوضه‌های آبخیز، به‌ضرورت بررسی عوامل تأثیرگذار در این حوضه‌ها بیش از پیش توجه شده است. ارزیابی عوامل تأثیرگذار در خطر سیلاب به‌منظور بررسی میزان آسیب‌پذیری و مواجهه با خطر، اطلاعات ارزشمندی را برای مدیریت سیلاب فراهم می‌کند. در این راستا هدف از این تحقیق، سنجش و ارزیابی عوامل تأثیرگذار در خطر سیلاب (مطالعه موردی: حوضه دشتیاری) است. تحقیق حاضر از نظر روش تحقیق توصیفی‌تحلیلی و لحاظ هدف، کاربردی است. روش گردآوری داده‌ها، کتابخانه‌ای و میدانی است. در این تحقیق که با استفاده از 13 عامل (شیب، ارتفاع، بافت خاک و ...) به پهنه‌بندی و ارزیابی خطر سیلاب در منطقه دشتیاری اقدام شد. برای تجزیه‌وتحلیل داده‌ها از نرم‌افزار Arc GIS و شاخص IGR و از الگوریتم جنگل تصادفی (Random forest) استفاده شد. طبق نتایج حدود 5.40 درصد از منطقه مورد مطالعه دارای بیشترین خطر، 33.63 درصد در معرض خطر بالاتر، 37.94 درصد در معرض خطر متوسط، 18.70 درصد در معرض خطر کمتر و 4.31 درصد دارای کمترین خطر هستند. حدود 50 درصد از مناطق مسکونی در مناطق پرخطر واقع شده است که در صورت وقوع سیل منجر به خسارات جانی و مالی شدید می‌شود.

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