The occurrence of a great number of floods in rivers on the one hand, and industrial, commercial and social activities’ accumulation, just near the rivers, on the other hand, reveal the obligation of applying appropriate flood management strategies (before, during and after the flood). The role and importance of employing Flood management strategies on flood damage reduction could be observed clearly, at the Nekaroud River over flow which had occurred in 1999. In this year two floods occurred in June and August in Nekarood’s basin, respectively. The first one destroyed the city center’s bridge and obstructed the river which finally caused back water at the second flood which was the reason of extremely major damage in the city of Neka. In this article, the effects of city main bridge destruction on exacerbation of flood damage, in August 1999, have been modeled using HEC-RAS software; therefore, the geometric characteristic of 25 river cross sections at the upstream of the bridge, Manning's roughness coefficient, flow type and the boundary conditions, were inputted. Besides, the model was calibrated using discharge-stage at the existing hygrometry station on the river. Then, the water surface profile were calculated in two different conditions first normal river condition and 70 percent blockage at the bridge section, then, compared with measured water stage of the flood occurred in August. The results show that the amount of the second flood discharge was not the original factor which led to such extremely flood damage, but it was the bridge blockage, as a consequence of the second flood. Eventually, a flood with 970 CMS caused severe damage equal to a flood with 2450 CMS and if the bridge spans were cleaned after the first flood, no back water and such damage would not be happened at the second flood.

INTRODUCTION: Sponge city, a fundamental strategy for solving water and environmental challenges, has attracted the attention of researchers around the world in recent years. Hence, the aim of this research is to examine the sponge city as a paradigm in urban flood crisis management. METHODS: In this applied study, the research method is both descriptive and analytical. Data were collected from review articles, book chapters, grey literature, online pages, and newspaper articles. For qualitative content analysis, an inductive method was used, which combines data collection, extraction, and analysis, and gradually generates a discussion. FINDINGS: According to the findings, the sponge city model involves comprehensive improvement of urban water resources and the aquatic environment in urban areas and a way to respond to water challenges and environmental degradation, promising to resolve environmental problems, increase welfare, growth and development, and achieve sustainability in societies. It emphasizes the integration of environmental considerations into all physical structures in urban spaces with the aim of harmonizing city development with the natural environment and advancing the principle of sustainability through the alignment of human and ecological processes in urban environments. CONCLUSION: The results show that the sponge city and its principles can contribute to sustainable development in environmental, social and economic dimensions. A sponge city construction can improve the ability of cities to adapt to environmental changes and cope with floods, encouraging the development of cities towards a healthier and more sustainable direction.

Introduction: Increasing frequency and intensity of flooding due to urbanization and climate change have led to serious damages in urban areas. Flooding in urban catchments is different from other types of flooding in terms of intensity and volume. Due to the high percentage of impervious areas in these catchments, the flood peak is roughly 1. 8-8 times and the volume is six times larger than flooding in non-urban catchments. One of the major challenges in urban flood analysis is the two-dimensional (2D) simulation of surface runoff caused by surcharged flows from urban drainage systems. Thus, development of an urban flood simulation model, which can rout the water flow on complex topography of urban catchments and determine flooded areas with acceptable computational time and accuracy is important. In this study, a flood simulation model based on Cellular Automata approach (CA) is developed to reduce time and computational effort compared with other 2D conventional hydraulic models. The developed model performance is compared with HEC-RAS, shallow water equations and TUFLOW models which simulate the water movement using conventional numerical schemes. Also, the stability of the model is assessed by considering different time steps and mesh sizes. Methodology: Because of the complexity in both conventional hydraulic models and urban catchments topography, urban flood simulation using these hydraulic models is highly computational-intensive task. To overcome these drawbacks, in this study an urban flood simulation model based on CA was developed. In CA flood simulation, the study domain was discretized into regular grids which is called ‘ cell’ . The flow direction in each cell is determined comparing the water level in the objective cell and its neighbors. Then, the inflow and outflow of each cell is computed in x and y directions at each time step. The volume and depth of water in each cell is calculated based on the discharge into and out of the cell and the considered time step length. The process of calculating flow depth and volume in the cells continues till the end of simulation period. The neighborhood condition which is used for developing the proposed hydraulic model is Von-Neumann type. In this type of neighboring condition, four neighbors are considered (up, down, right and left sides) at each side of the cell. The amount of water which flows into or out of the cells depends on the width of the cells sides that water passes through. Results and Discussion: In this section, the performance of the model is evaluated in four different tests. In the first test, the models performance is compared with HEC-RAS model in which the water flow is one-dimensionally simulated in a channel and the water level variation during simulation was compared with HEC-RAS simulation. In the second test, the proposed the performance of the model in 2D flow simulation was compared with shallow water equations. The third test was about evaluating the model’ s ability in simulating water movement on a complex topography, and comparing the results with TUFLOW simulation. In the last test, CA performance was tested by simulating the flood propagation on a hypothesis floodplain-like domain, and the water level variation was assessed at six points and compared with that of obtained by TUFLOW simulation. The obtained results show that the proposed model, using topographic and surface roughness data as inputs, can simulate water movement with acceptable accuracy one-and two-dimensionally. In addition, the computational time is reduced up to almost 60 times compared to the model which was based on shallow water equations in test 2. Conclusion: In this study, an urban flood simulation model was developed and its performance was evaluated in four different tests. The obtained results showed that this model is capable of one and two dimensionally water movement simulation with acceptable computational time and accuracy. This model was developed following two main goals: First, proposing a simple and efficient model which is able to simulate flood on complex urban catchments accurately with low computational cost. The second goal was to develop a model that could be applied as an opensource software that provides researchers with the availability of modifying and combining it with various hydrologic models. In conclusion, based on obtained results, the proposed model could be considered as a valuable tool in determining flood-prone areas, managing urban runoff, designing flood warning systems and many other different applications.

Aims Urban runoff and flood damage is one of the most important and fundamental issues in the field of urban management, which in recent decades has been strongly affected by the rapid growth of cities and increasing urbanization. Today, to show these processes, in the design and evaluation of urban drainage network system, the use of existing computer models has a special place to simulate the flow. The purpose of this study is to use the SWMM model to quantitatively simulate rainfall floods for District 4 of Tehran. Methodology In this research, using the capabilities of SWMM model for region 4 of Tehran, according to environmental factors, two plans of the best management strategies (BMP) under the garden and green roof climate scenario and a combination of both scenarios for maximum control Runoff has been done quantitatively and finally their efficiency in reducing the total volume of runoff out of the basin has been investigated. Findings The results of sensitivity analysis of the model showed that among the seven parameters studied in this study, the amount of CN, the percentage of impermeable areas, the roughness coefficient in impermeable areas and the equivalent width had a greater effect on peak flow change, respectively. According to the obtained results, the third scenario (simultaneous combination of the first and second scenarios) will have the greatest impact on reducing the flow depth and flow rate in the entire surface water collection network. Conclusion Considering the depth factor, in a total of four modes of model implementation, the third scenario has the most impact on Tehranpars channel (output 7) and the least impact on Yakhsaran channel (output 3) and if we consider the peak discharge factor for evaluation In general, the third scenario has the most impact on Tehranpars channel (output 7) and the second scenario has the least impact on output 4.

Urban flood is the volume of water that is out of the capacity of the drainage network of the city and results in many problems and damages. Most researches around the world shows an increase in urban floods, especially metropolitan areas. The concentration of human population in urban areas with urbanization and changing the face of the earth's nature has caused an increase in impervious surfaces and change in hydrological cycle. This study was done to simulate runoff of Ilam City Catchment using of the SWMM hydrologic-hydraulic model. The model validation results showed that the simulated peak discharge and flow volume are in good correspondence with the observed value (BIAS= 3. 25, RE= 0. 065). According to the results obtained from the analysis of the sensitivity of the important parameters of the model, the factors affecting the flood occurrence in the study area include the inadequate size of urban channels, increase of impervious areas, coefficient of roughness of permeable areas, slope, area, equivalent width and roughness coefficient of impermeable areas. The results of the study show that sub-area 2 has the highest risk of flood due to land use changes, non-standard construction and inappropriate drainage network, which results in an increase in impervious surfaces, and in the absence of attention, the city of Ilam face severe flood risks due to the drainage network infrastructure and the lack of observance of the urbanization developments criteria. Also, the SWMM model has the accuracy required for urban flood simulation and it can be used for urban runoff management plans and designing superficial water collection and disposal networks.

Extended AbstractIntroductionA flood is a widespread and dramatic natural disaster that affects the life, infrastructure, economy, and local ecosystems of the world. In this paper, a method for flood detection in urban (and suburban) environments using the intensity and coherence of SAR based on a convolutional neural network is introduced, and from the time series of SAR intensity and coherence to draw flood without obstruction (e.g. Flooded bare soils and short vegetation) are used. Non-cohesive areas blocked by floods (e.g., flooded vegetation) and cohesive areas with flood-blocked areas (e.g., frequently constructed flooded areas) are distinguished.This method is flexible according to the time period of the data sequences (at least one pair of pre-event and event intensities and one pair of pre-event and in-event coherence are required). The increasing number of SAR missions in orbit that have a fixed viewing scenario with a short retry time increases the chances of seeing a flood event, while also having a good pre-event scene achieved by the same sensor. This makes this method desirable for operational emergency responses.Materials & MethodsCNN algorithm is a multilayer perceptron that is designed to identify two-dimensional information of images and includes: input layer, convolution layer, sample layer, and output layer. The CNN algorithm has two main processes: collection and sampling.The convolution process involves the use of a trainable Fx filter, deconvolution of the input image (the first step of image input, input after image convolution, is the feature of each layer called Feature Map), then by adding bx can be hand convolution of the CX layer Found. Sampling process: n pixels are collected from each neighborhood to form a pixel, then weighted with a scalar weight of Wx + 1 and a bx + 1 bias is added, then a map of The Narrow n times feature map properties are generated.Three images of Sentinel-1A VV polarization, wide width interference (IW), and mode (SLC) data were used in this study. Intensity images were pre-processed with radiometric calibration, noise reduced with a spell-filter (window size 5.5 pixels), and converted from linear units to decibels. Coherent images were obtained with a pair of consecutive images with a window of 7.28 (range _ azimuth). Validation data set due to the lack of other data in two separate sections of ground data in the urban area of GonbadKavous that have been collected to identify homes damaged by floods and terrestrial reality data from gamma image thresholds for output validation were extracted.Results & DiscussionIn this section, the results of the study are qualitatively and quantitatively analyzed. Because the simultaneous display of SAR data over time in the form of RGB compounds is widely used in the qualitative interpretation of land cover and surface dynamics, RGB compounds are used to provide evidence of flood magnitude in terms of intensity and coherence. For both cases, the results of combining intensity and coherence and intensity alone and coherence alone are quantitatively analyzed. Overall accuracy (OA), kappa correlation coefficient, false-positive rate (FPR), precision (e.g., correctly predicted positive patterns out of the total predicted patterns in a positive class), recall (e.g., a fraction of properly classified positive patterns), and an F1 score (ie the harmonic mean between precision and recall). Flood reference and ground data are mentioned and reported based on the reference.ConclusionIn this paper, a method for mapping floods in urban environments based on SAR intensity and interferometry coherence was introduced. A combination of intensity and coherence extracts flood information in different types of land cover and outlet. This method was tested on the KavousGonbad flood incident obtained by various SAR sensors and the flood maps were confirmed by the flood reference resulting from thresholding and ground harvesting and satisfactory results were shown in this case study. The findings of this experiment show that the shared use of SAR intensity and coherence provides more reliable information than the use of SAR intensity and coherence alone in urban areas with different landscapes. In particular, flood detection in less cohesive / non-cohesive areas (e.g., bare soils, vegetation, vegetated areas) relies heavily on multi-temporality, while multi-temporal coherence provides more comprehensive flood information in areas Create coherence (e.g., mostly built-up areas). However, some flood-specific situations, such as flooded parking lots and flooded dense building blocks, are still challenging in terms of intensity and coherence. Also, since the proposed method is sensor and scene independent, with very frequent and regular observations of SAR missions such as Sentinel-1 and RADARSAT (RCM), there are opportunities to map global floods on a global scale, especially in small countries. Provides income.

Flood can be the result of weather changes, heavy rainfall, rapid melting of snow, ice, or damming of dams. For whatever reason, when it enters urban areas, it causes damage and sometimes the death of individuals, as the city attacks natural hydrologic spaces during its development. The city of Gonbad-e-Kavoos has been threatened by urban floods over the past few years, in particular the floods 1991, 2000 and 2001 and the type of flood has been a mixed of river flood and abrupt. The lack of attention to the threat of Gonbad due to inside and outside factors in flood risks, has led to the study of the potential urban flood risks in the city of Gonbad. Based on the characteristics of the natural and human flooding of Gonbad-e-Kavoos and considering all aspects involved in the potential of flood risk and risk in urban development, the flood risk reduction for the city of Gonbad-e-Kavoos was evaluated in 54 factors using AHP hierarchical analysis and in a specialist community 35 people consisting of senior officials, directors and experts from all relevant organizations. Among the three main criteria, the criterion of studying and planning of operating systems has the highest weight (0. 75), the most important role in the issue of urban flood risk reduction, as well as flood risk map for Gonbad-e-Kavoos, which is produced using nine parameters which is shown that Gonbad-e-Kavoos is in a high potential hazard area. The results and recent flood events indicate that the city is vulnerable to the risk of external flood, which in recent years has not been focused on improving the city's safety and downstream. Therefore, comprehensive studies and planning should be put in place by the relevant executive agencies.

Water management in urban areas includes wastewater control and developing efficient drainage systems. Developing the maps of areas with potential of flood-inundation could be an appropriate tool for urban planning and urban developing strategies. Vulnerability analysis of different urban areas is a complex process because it depends on several spatial and temporal parameters and criteria. The purpose of this research is to prepare flood hazard maps to determine more accurate decisions in urban flood management using a combination of multi-criteria decision making and geographic information system (GIS) as a planning support system (PSS). The final flood hazard map shows that regions in the southeastern of the study area have a high hazard with regarding to the flood potential map. It should be mentioned that these regions are located in low-land (with low elevation) areas that their slope are less than 2.5 percent. In addition, in order to evaluate the spatial multi criteria decision making model, the capability of spatial modeling by an intelligent model, artificial neural network, is assessed. The advantages of using the SMCDM (Spatial Multi Criteria Decision Making) model in developing flood management strategies are discussed using the case study.

The conventional approach to River Basin Flood Management (RBFM) primarily focuses on enhancing the structural integrity of drainage systems to mitigate the impacts of heavy rainfall events. However, recent floods in urban catchments have revealed the necessity for a more resilient approach that incorporates the consequences of flooding. Resilience in the context of RBFM refers to the system's ability to endure diverse precipitation events, minimize flood damage, and restore normal conditions. This research presents a framework for selecting flood management options within a hierarchical system, with a specific emphasis on social resilience indicators. The study defines resilience by examining the response and recovery behaviors of RBFM systems during varying rainfall events. To implement the framework, a set of indicators related to social response, social recovery capacity, resistance points, and warning points has been established. A hierarchical fuzzy system has been developed to quantify these indicators, accounting for uncertainties in social variables and addressing dimensional inconsistencies. Application of this approach in the Gorganrood River basin demonstrates the efficacy of selected flood risk management options in terms of resilience, as compared to conventional decision-making methods. Analyzing the response-recovery curves for different management options underscores the importance of delineating distinct resilience indicators to evaluate the behavior of RBFM systems following performance failures. The findings of this study suggest that the proposed indicators can serve as decision-making criteria for selecting management options based on the behavior of the river basin system under rainfall events with varying return periods.