The study of annual damage statistics due to floods in Iran and the world shows the extent of flood damage to natural and human resources in different regions. Determining the flood zone of rivers in order to protect national resources and reduce flood damage provides the possibility of protecting the river from encroachment and the construction of any unauthorized facilities in it. Therefore, in the present study, the capability of numerical models in simulating the flood zone of rivers was evaluated in the range of Azarshahr Qushqura river and the two-dimensional hydraulic model HEC-RAS 5.0.7 and one-dimensional HEC-RAS model were compared. Changes in the hydraulic characteristics of the flood flow including depth and velocity of the flow at different cross sections of the models were evaluated. The results showed that the water surface level (flow depth) of the two-dimensional model HEC-RAS compared to the one-dimensional model had the lowest error as compared to other hydraulic parameters of flood flow. The two-dimensional HEC-RAS model showed the highest error rate in the flow velocity parameter in comparison to the one-dimensional model. The results indicated that two-dimensional HEC-RAS model V5.0.7 determined the surface of the flood zone 12.46 % more than the one-dimensional HEC-RAS model. The confirmation of the resulting zones on the current state of the river and comparison with the river aerial photo of 1346 indicated the higher accuracy of the two-dimensional HEC-RAS model in estimating the flood zone of the river.

The purpose of present research work is to study the hydraulic properties of River Simineh and its process using HEC-RAS model, in a combination with ArcGIS software using HEC-GeoRAS extension to simulate the hydraulic parameters of river having a catchment area of 3726 km2. For that mean, since multi-dimensional models require long time and high cost in river bends, by using a combination of satellite images and HEC-RAS model a multi-dimensional simulation was prepared. Among those, 58 cross-sections are considered along the river lane that main data required in this research are elevation maps, satellite images, boundary conditions and River Simineh hydrometric stations. The results showed that at the upstream of river, the discharge was 316.3 m3/s and water level was 12.85 m, and at the downstream the flow rate and water level are 313.6 m3/s and 11.52 m, respectively. On the other side of the river bend, the water level variation is around 50 cm and the flow velocity is directly proportion to a distance from the river bank; so that the maximum flow velocity of 2.2 m/s occurred at a distance nearby 1.5 m. To verifying the model, a statistical parameter of NSE coefficient for the water level and flow depth were 0.805 and 0.845, respectively; which shows the accuracy of model. Those results indicate a high accuracy of HEC-RAS model in hydraulic simulation of River Simineh flow. Also, simulations prepared in GIS background have significant impacts on the accuracy of outputs

Surface runoff drainage is one of the management problems in Rasht City. Also, one of the urban flood factors is drainage channel obstruction through water level rising. The purpose of presented study is to investigate the probability of drainage channels obstruction and site selecting new outlets along Goharrood and Siahrood rivers. So, the rivers bed of Goharrood and Siahrood and their bank terrains were simulated by using HEC-GeoRAs extension and digital map (scale: 1000). Pick discharges with different return periods were estimated by using stochastic analysis. Then, river hydraulic behavior was simulated by using HEC-RAS model. Finally, unsuitable and suitable sites for runoff drainage were identified.

Due to their susceptibility to flooding, alluvial fan surfaces present unique challenges for development. The scope of Pardisan is also expanded in these areas, necessitating a comprehensive location and development plan. To address this, a robust methodology was employed, incorporating flood risk modeling using HEC-RAS and the Soil Conservation Service (SCS) method to calculate the flow rate of a 100-year flood event. In addition to the flood factor, 13 other criteria were included based on expert opinions to assess the suitability of the land for development. These criteria were analyzed using the Analytical Hierarchy Process (AHP) in conjunction with fuzzy logic, facilitating an accurate comparison of potential sites for expansion. The findings reveal that, despite existing watershed management efforts, the current residential areas in Pardisan remain vulnerable to flooding and inadequately address the volume and sediment challenges posed by potential flood events. This research underscores the deficiencies in current flood prevention measures and highlights the necessity for enhanced strategies and further studies. The results of the Fuzzy Analytical Hierarchy Process (FAHP) model identified the southeastern part of Pardisan as the most suitable area for development, which contradicts the current development plan. This recommendation is based on a thorough evaluation of the specified criteria and indicates significant potential for targeted and optimal urban development. Finally, it is important to note that the integrated HEC-RAS-SCS-FAHP model can serve as a valuable roadmap for urban area development.

Studying the role of drops as one of the important hydraulic structures for flood control is essential. In the present study, the effects of drops on inundation depth and extension have been investigated in a reach of the Kan River with 7 Km in length. The hydraulic characteristics of flow were computed for floods with 5 to 700 year return periods using the HECRAS computer model for both upstream and downstream sections of the structures. The results of this study verified a different role of drops as well as an incremental and reductive impact on inundation depth and extension in upstream and downstream, respectively.

Understanding the spatial variation of the flood source area within watersheds as they affect of the flood characteristics at the outlet is an important issue in flood control studies. Determining the flood severity index in a watershed requires study of hydrogeomorphic properties, recorded rainfall-runoff events and use of mathematical models in the context of the methodology to delineate various watersheds areas with respect to the flood downstream. In this paper, Roodzard watershed was selected as the case study since it has suitable rainfall-runoff record. The watershed consists of five tributary subwatershed and three intermediate subwatersheds. ModClark distributed hydrologic model was calibrated in subwatersheds with hydrometric stations. Using HECRAS routing model the whole of the Roodzard watershed model was calibrated at Mashin Hydrometric Station at the outlet. Following the “Unit Flood Response” approach, 2*2 km2 grid squares within the watershed were removed one by one in the simulation process and their effect on the flood peak at the outlet was determined. Such effect was quantified by a flood index and used for preparing the map of “flood severity”. Furthermore, the profile of flood index along the main stream was plotted in grid-scale as well as for each sub-basin.

Introduction Urban floods have been exacerbated by climate change and urbanization, as well as restrictions on the drainage of urban infrastructure, and over the past decade have had many negative effects on cities around the world [4]. As a result, the demand for more resilience has not been successful in many cases [2]. Accordingly, the resilience of key urban buildings is one of the necessities of urban resilience [3]. In this regard, research on urban resilience in events such as floods was reviewed, some of the most important of which are mentioned below. In 2019, Wang and colleagues evaluated the resilience of the urban basin to floods, and the CADDIES model was used to simulate floods. Based on the results, vulnerable basins were identified and strategies were developed to increase the city's resilience to floods [4]. In 2019, Barajas et al. worked on an article on the resilience of urban buildings in the face of flood risk in the Mexican metropolitan area, and addressed the resilience of buildings in Mexico City during the floods of recent decades. Findings show that building resilience is a complex and sequential process that of course depends on social, economic and institutional conditions [1]. Research Methods In this research, in order to achieve the model of resilience of important buildings against floods, data analysis is performed in several stages, which include the following: 1- Identification of significant assets 2- Modeling river flow using HecRAS software 3- Adaptation of assets and modeling results from rivers in different return periods 4- Counting assets affected by floods 5- Modeling of building resilience components using structural equation modeling of LISREL software 6-Counting and ranking the components extracted from the model using AHP-TOPSIS combined method 7- Ranking of key buildings affected by floods using AHP-TOPSIS combined method Discussion and conclusion The asset layers of the city of Hamedan and the rivers of the city have been adapted in the GIS context and five buildings of the University of Technology, the Faculty of Art and Architecture, Payam-e Noor University, the Blood Transfusion Building and the Amiran Hotel have been identified as vulnerable centers of Hamedan. Conclusion Components (adaptability-flexibility, connection of failure-safe feedback, dependence on environmental ecosystems, diversity, learning-memory-prediction, performance, response speed, fragmentation redundancy, resourcefulness, and robustness) are effective variables on flood resilience of buildings. In testing the hypothesis using the structural equation model, the software output indicates the suitability of the fitted structural model to test the research hypotheses. Weighting indicators Resilience components Sub-components of resilience Weight Compatibility - Flexibility Change while maintaining or improving performance 0.049 Evolution 0.045 Adopt alternative strategies quickly 0.05 Timely response to changing circumstances 0.027 Open design and flexible structures 0.049 Connection - Feedback - Safety - Failure Shock absorption 0.007 Absorb the cumulative effects of challenges with a slow start 0.012 Avoid catastrophic failure if you exceed the threshold 0.007 Gradual failure instead of sudden 0.013 Failure without cascading effects (demino effect) 0.024 Parallel analysis of technology system - human 0.005 Identify locking effects and possible discrepancies with reduction 0.014 Identify synergies with other city policies, value added estimation 0.015 Dependence on local ecosystems Flood control 0.012 Bioclimatic design and management 0.006   Resilience components Sub-components of resilience Weight Variety Spatial diversity - key assets and tasks that are physically distributed and not all of them are affected by a specific event at any time 0.0146 Functional Diversity - Multiple methods of dealing with a particular need 0.021 Balance variation with potential cascading effects 0.013 Learning-Memory - Prediction Learn from past experiences and failures 0.003 Use information and experience to create fresh compatibility 0.003 Avoid repeating past mistakes 0.005 Collect, store, and share experiences 0.009 Construction based on long-term value and city history 0.007 Integrate resilience into long-term development scenarios 0.02 Function Performance capacity 0.056 System quality in a suitable and efficient way 0.013 Self-sufficiency - reducing external dependence 0.019 It performs better than other buildings 0.039 Response speed In taking casualties, including mortality and disease 0.007 Reorganize 0.015 Maintain performance and re-establish it 0.032 Restore structure 0.017 Establish public order 0.013 Prevent disruption in the future 0.005 Redundancy - fragmentation Systems replacement or systems agents 0.054 Buffer from external shocks or changes in demand 0.013 Replacing components with modular parts 0.026 Balance redundancy with potential cascading effects 0.077 plan Identify and predict problems 0.013 Prioritize 0.011 Mobilize resources of visualization, planning, collaboration and action 0.014 re-evaluation 0.006 Integrate resilience into work and management processes 0.052 Getting cooperation from citizens 0.03 Strength Surface resistance to stress 0.003 No degradation and loss of performance 0.015 Capacities that ensure adequate margins 0.006

This study aims to determine the design strategy of a nuclear power plant near the river by assessing flood risk as a design precondition and the Darkhovin Nuclear Site near the Karoun River in Khuzestan Province was considered as a case study. In this study, by sampling the probabilistic space fitted to the flow rate and by filtering and removing flood flows that does not overflow from the river to the flood plain, the two-dimensional HEC-RAS hydraulic model was used to determine the depth and flow velocity within the power plant site. Frequency analysis of flood depth simulated by the model for different discharges showed that the frequency distribution of flow depth and the generating flood are different from each other. The safe design of a power plant site requires consideration of the many uncertainties that make it difficult to use conventional methods. In this research, for the first time, the Rosenbluet technique was used to evaluate the uncertainty and finally to determine the maximum possible water level for locating the reactor core. The results show that to create the maximum probable depth with a return period of 100 years, there should be a flood with a return period of 10,000 years in Karoun downstream of Ahvaz. The method presented in this research can be the basis of a standard for the safe design of nuclear power plants in the vicinity of rivers considering flood hazards.

1. Introduction Flood zoning determines flood advance, elevation, and characteristics in different return periods. Flood zoning tends to subdivide all areas around the river and flood plains into different hazardous areas in order to control land use and land development. These areas are used to determine land use, identify the area in flood insurance, and establish mandatory restrictions in hazardous areas. Rasht, with an annual precipitation of nearly 1, 400 mm, is one of the rainiest areas in Iran. In high intensity and in short time, these precipitations cause river flood in ranges of the river and flooded areas of the city. Flooded streets, houses and urban roads, slowing down of vehicle movements, destruction of urban facilities and many other problems are all results of these precipitations. Using mathematical models, digital elevation models (DEMs), GIS software and HECGeo-RAS extension, flooding zone map is discussed in a part of the main range of the Goharrood River at the beginning of the entrance to its outlet out of Rasht. 2. Materials and Methods The studied area was a range of the Goharrood River, one of the main branches of the Pirbazar River in Rasht, north of Iran. According to objectives of the study and investigation of the flood zone at the Goharrood riverside, the data included hydrometric statistics of the Lakan station during the statistical period of 1989-2013 (25 years) and river hydrometric characteristics using a 1: 2000 map and field surveys and layers were required to plot a flood zoning map. Using mapped data of the area, including river planning maps at a scale of 1: 2000, bed conditions, such as main flow line of the river, sides and cross sections, etc., geometric data required for simulation determined by TIN map was obtained; then, data were inserted into the HEC-RAS model. Subsequently, flow data and boundary conditions were included in the system and hydraulic calculations were carried out. The results were presented in the form of input formats into the GIS environment and the necessary processing was done using HEC-GeoRas extension. Finally, maps of water depth, water velocity, shear stress and flow power along the river range were plotted. These maps were presented in both GIS and Google Earth for better clarity. These maps precisely presented flood zone with different return periods. Moreover, the ranges of the river in which flood spread and caused watering were identified with the depth of watering and areas with low, medium and high risk of flood. 3. Results and Discussion To determine flood status of Rasht and Pirbazar Basin, a precipitation map of Rasht was plotted in GIS environment. The results show that the average annual precipitation is 1350 mm in Rasht which can cause flooding and problems such as flooding of streets due to precipitation regime and severe rainfall. Using statistics of the Lakan hydrometric station, maximum instantaneous discharges were determined by Smada software; after analyzing the distribution of Log Pearson Type III, the best statistical distribution was determined to estimate maximum instantaneous discharges in different return periods. Using geographic information system (HEC-GeoRAS), the river planning maps were plotted for physical model of the bed and riversides. Based on mathematical simulations performed by HEC-RAS software and results of the obtained data, the model was developed to determine hydraulic conditions. For this purpose, sections of the river were first identified in the urban environment by considering longitudinal and transverse profiles of the river as well as field observations. Next, the sections were modified according to the shape of adjacent sections and engineering judgment. Finally, the model was run for this condition and the results and output of hydraulic parameters of the model were obtained for discharge with a return period of 50 years. The files generated in the GIS environment using the HECGeoRAS extension included flood maps with a 50-year return period of discharge, indicating a river flood in a 500-meter range in the northern part of the city called Siah Estalakh. This hazardous area is located where the river passes the Shohadaye Gomnam Blvd. Extreme changes in the river's width in this area indicate a flood in this part of the river range. 4. Conclusion Plotting of flood zoning maps for identifying hazardous areas is one of the first tasks of responsible organizations to deal with floods. Data analysis and results of the model show that the only part of the 15 km range of the Goharrood River which is at risk of flooding with a 50-year return period of discharge is a 500 m range of the river after the Shohadaye Gomnam Blvd northward in Siah Estalakh. Considering land uses of the area, flood-exposed regions were identified as low-risk, moderate-risk and high-risk regions. Thus, any structural attempt on this river should be prioritized in this area.