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Introduction Floods cause financial losses and countless lives in the world every year. Identifying flood-prone areas is one of the basic steps in flood management. In the past, careful observation and note-taking of the mechanism of occurrence and the natural course of the cause and effect of the effective factors that led to the final occurrence of the phenomenon in a chain manner helped to understand the pattern and process of the occurrence to some extent. Because the processes of creating floods are numerous and affected by various factors and the flood phenomenon is multidimensional and dynamic, all-natural, human, and organizational-management factors affect the occurrence, intensity, extent, and continuity of floods. So far, many efforts have been made to use data-mining models and artificial intelligence in the spatial prediction of floods. The models try to better and more accurately estimate the distribution of the flood phenomenon by examining the relationships between each flood event (dependent factor) and the set of underlying and stimulating factors (independent factors) and fitting them to educational evidence. Since the applicability of the flexible discriminant analysis model has not been fully investigated in the field of flood susceptibility prediction, this research quantitatively evaluated its performance using real-world flood data. Materials and Methods Based on the availability of periodic history of flood events, the Zarrineh-Rood Watershed of Kurdistan Province, Iran, was chosen as the study area. It was tried to select the factors based on different criteria such as familiarity with the process of flood inundation, ease of data preparation, having the most spatial variability at the regional level (not uniform), and containing the most information for the model should be selected to separate areas with different levels of flood susceptibility. Thirteen diverse geo-environmental factors including elevation, aspect, slope percent, land use, drainage density, lithology, plan curvature, profile curvature, mean annual precipitation, soil texture, stream power index, distance from the stream, and topographic wetness index were used as independent variables. The maps of elevation, aspect, slope percent, plan and profile curvatures, stream power index, and topographic wetness index were produced using a digital elevation model. Hydrological layers including distance from the stream and drainage density were produced using the stream network layer. The location of the flooding events was also collected as the dependent variable. The spatial data of flooding were randomly divided into two groups of training and validation with a ratio of 70:30. After running the model (i.e., Flexible Discriminant Analysis) based on the training group, the flood susceptibility map was produced. The validation of the model results was conducted using the area under the receiver operating characteristic curve (AUROC) and the true skill statistic (TSS) metrics. Results and Discussion The results indicated that the FDA model with the value of AUROC= 0.96 and TSS= 0.86 efficiently and accurately produced the flood susceptibility map. The flexible nature of the model in the selection of regression equations, as well as the possibility of weighting, and determining the priority of the evidence of presence over the evidence of absence, are among the special capabilities of the FDA model, which many machine learning models lack. Using probability distribution estimation algorithms in the model is very important and can not only extract the hidden spatial pattern of occurrence from a set of data but also help to predict flood-prone areas in datascarce Watersheds. Based on the results, about 14% (62 thousand ha) of the study area was categorized in the high and very high flood susceptibility zones, which include the northern, northwestern, and southeastern areas. Spatial analysis of the flood susceptibility map showed that in total 25897 ha (18.12%) of agricultural lands, 343 ha (50.91%) of garden lands, and 2126 ha (39.93%) of residential areas located in high and very high susceptible zones. Considering the successfulness of the FDA model in goodness-of-fit and validation phases, the flood susceptibility map can be used as a basis for planning flood control and management measures. Conclusion The findings of this study proved that the flexible discriminant analysis model provides the possibility of processing diverse and big geo-environmental data to predict the flood susceptibility of Watersheds and it had a high efficiency in this context. There is a lot of spatial correspondence between the vegetation status map and the flood susceptibility map; in such a way that the places that had a high flood susceptibility degree, their upstream areas were generally destroyed in terms of vegetation. The results of this research showed that a significant area of the Zarineh-Rood Watershed had a high and very high flood potential, which was characterized by the interaction of low slope and flat areas, formations and soils with low penetration and dense drainage network, and more importantly, flood-prone areas located in the northern, northwestern and southeastern parts of the Watershed. The situation of the flood probability of the Zarineh-Rood Watershed has been determined and managers and decision-makers must put the critical areas in the priority of flood management programs. More flood-driver factors are suggested to be used as predictor variables in flood susceptibility modeling in future studies. On the other hand, it is very important to determine the role of predictor variables in the flood susceptibility degree at the Watershed scale, which can be investigated in future research. [ABSTRACT FROM AUTHOR]

IntroductionFlood is one of the most destructive natural disasters that has a negative impact on social, economic and environmental dimensions. Floods usually occur following a prolonged period of rain or snowmelt in combination with unfavorable conditions. In this regard, all over the world, the occurrence of floods has intensified by 40% in the last two decades. In Asia, almost 90% of all human casualties caused by natural disasters are due to floods. The increase in flooding is usually due to increased environmental degradation such as urbanization, increased population growth, and deforestation. Periodic and regular occurrences of floods over a certain timeframe significantly amplify the detrimental impacts on living organisms. Urban areas in close proximity to rivers bear the brunt of these damages, owing to high population density, economic infrastructure, and transportation networks. However, these consequences can be alleviated through meticulous vulnerability analysis. One of the primary objectives pursued by researchers and policymakers is the precise modeling and zoning of floods to mitigate associated risks. Consequently, a myriad of methods and approaches have been devised for flood risk modeling and zoning to address this pressing issue. Among them, hydrological methods such as rainfall-runoff modeling and data-based techniques, which are unable to comprehensively analyze rivers and flood zones due to their one-dimensional nature. This is despite the fact that the morphology of the river is not stable and due to its high erosion potential, it also has a dynamic characteristic. In addition, these methods require fieldwork and large budgets for data collection. Hence, comprehensive flood management is necessary to reduce these effects. Therefore, this study was conducted with the aim of identifying areas sensitive to the risk of flooding in Famnat watershed located in Gilan province. Fomanat watershed is located in Gilan province and is considered a part of the first grade watershed of the Central Plateau. This area is located in the range of 36.89 to 37.57 degrees north latitude and 48.77 to 49.69 degrees east longitude. This region has an area of 3595 square kilometers, the highest point of which is 3088 meters and the lowest point is -69 meters. Materials and Methods To carry out the current research, firstly, by reviewing the sources and history of the research, as well as knowing the region, a map and layers of information related to the factors affecting flood susceptibility zoning were prepared. These layers include land use map, slope degree, geology, distance from waterway, digital map of height, direction, shape of land curvature, land curvature profile, rainfall and topographic humidity index, which are created using the collected data and also various additions in the environment. Geographic information system (Arcgis 10.4) was prepared. In this regard, machine learning models such as generalized linear model (GLM), multivariate adaptive regression model (MARS) and classification and regression tree model (CART) were used to zone the sensitivity of the watershed to floods. Also, among 100 flood events, 70% (70) were considered for training and 30% (30) for validation. In the following, using field survey and review of previous studies, 10 factors influencing the occurrence of floods in the watershed area were identified and used. Finally, the area under the ROC curve and the TSS index were used to evaluate the models.Results and Discussion The results of the evaluation of the most important factors affecting the sensitivity of the watershed to floods indicated that the distance from the river, the height and the curvature profile had the greatest impact on the sensitivity of the region, and on the other hand, the factors of slope, geology and topographic humidity index had the least impact. Based on the obtained results, the areas covered by very low, low, medium, high and very high classes in the CART model were 26.6, 17.6, 21.2, 0.1 and 34.0%, respectively. These results for the GLM model were 13.6, 12.7, 16.2, 25.1 and 32.4 percent, respectively. Based on the obtained results, the CART model performed better than other models, so that AUC for MARS model was equal to 0.76, CART model was equal to 0.9 and GLM model was equal to 0.84. Also, the better performance of CART model compared to other models was confirmed by other indicators. So, based on TSS, MARS model equal to 0.52, CART model equal to 0.77 and GLM model equal to 0.66 were obtained.ConclusionImplementing the findings of this study can facilitate the adoption of effective management strategies to mitigate losses and casualties. Moreover, in developing nations grappling with restricted access to hydrogeological and soil data, the utilization of geographic information systems (GIS) and data mining techniques assumes a pivotal role in conducting comprehensive studies. These technologies offer valuable insights and support decision-making processes, enabling proactive measures to address flood risks and enhance disaster resilience in vulnerable regions.

Introduction Flood is one of the most destructive natural disasters that has a negative impact on social, economic and environmental dimensions. Floods usually occur following a prolonged period of rain or snowmelt in combination with unfavorable conditions. In this regard, all over the world, the occurrence of floods has intensified by 40% in the last two decades. In Asia, almost 30% of all human casualties caused by natural disasters are due to floods. The increase in flooding is usually due to increased environmental degradation such as urbanization, increased population growth, and deforestation. Periodic and regular occurrences of floods over a certain timeframe significantly amplify the detrimental impacts on living organisms. Urban areas in close proximity to rivers bear the brunt of these damages, owing to high population density, economic infrastructure, and transportation networks. However, these consequences can be alleviated through meticulous vulnerability analysis. One of the primary objectives pursued by researchers and policymakers is the precise modeling and zoning of floods to mitigate associated risks. Consequently, a myriad of methods and approaches have been devised for flood risk modeling and zoning to address this pressing issue. Among them, hydrological methods such as rainfall-runoff modeling and data-based techniques, which are unable to comprehensively analyze rivers and flood zones due to their one-dimensional nature. This is despite the fact that the morphology of the river is not stable and due to its high erosion potential, it also has a dynamic characteristic. In addition, these methods require fieldwork and large budgets for data collection. Hence, comprehensive flood management is necessary to reduce these effects. Therefore, this study was conducted with the aim of identifying areas sensitive to the risk of flooding in Famnat watershed located in Gilan province. Fomanat watershed is located in Gilan province and is considered a part of the first grade watershed of the Central Plateau. This area is located in the range of 36.83 to 37.57 degrees north latitude and 48.77 to 43.63 degrees east longitude. This region has an area of 3535 square kilometers, the highest point of which is 3088 meters and the lowest point is -63 meters. Materials and Methods To carry out the current research, firstly, by reviewing the sources and history of the research, as well as knowing the region, a map and layers of information related to the factors affecting flood susceptibility zoning were prepared. These layers include land use map, slope degree, geology, distance from waterway, digital map of height, direction, shape of land curvature, land curvature profile, rainfall and topographic humidity index, which are created using the collected data and also various additions in the environment. Geographic information system (Arcgis 10.4) was prepared. In this regard, machine learning models such as generalized linear model (GLM), multivariate adaptive regression model (MARS) and classification and regression tree model (CART) were used to zone the sensitivity of the watershed to floods. Also, among 100 flood events, 70% (70) were considered for training and 30% (30) for validation. In the following, using field survey and review of previous studies, 10 factors influencing the occurrence of floods in the watershed area were identified and used. Finally, the area under the ROC curve and the TSS index were used to evaluate the models. Results and Discussion The results of the evaluation of the most important factors affecting the sensitivity of the watershed to floods indicated that the distance from the river, the height and the curvature profile had the greatest impact on the sensitivity of the region, and on the other hand, the factors of slope, geology and topographic humidity index had the least impact. Based on the obtained results, the areas covered by very low, low, medium, high and very high classes in the CART model were 26.6, 17.6, 21.2, 0.1 and 34.0%, respectively. These results for the GLM model were 13.6, 12.7, 16.2, 25.1 and 32.4 percent, respectively. Based on the obtained results, the CART model performed better than other models, so that AUC for MARS model was equal to 0.76, CART model was equal to 0.9 and GLM model was equal to 0.84. Also, the better performance of CART model compared to other models was confirmed by other indicators. So, based on TSS, MARS model equal to 0.52, CART model equal to 0.77 and GLM model equal to 0.66 were obtained. Conclusion Implementing the findings of this study can facilitate the adoption of effective management strategies to mitigate losses and casualties. Moreover, in developing nations grappling with restricted access to hydrogeological and soil data, the utilization of geographic information systems (GIS) and data mining techniques assumes a pivotal role in conducting comprehensive studies. These technologies offer valuable insights and support decision-making processes, enabling proactive measures to address flood risks and enhance disaster resilience in vulnerable regions. [ABSTRACT FROM AUTHOR]

IntroductionChoosing an optimal decision-making method for watershed management is a problem that has always attracted the attention of researchers, and various methods have been used to achieve this goal. Participatory management is a collaborative process to participate in gathering information, making decisions, and carrying out projects that lead to solving complex social and environmental problems. As it is known, the integrated watershed management approach is a method to achieve sustainable development. Considering the existence of challenges such as floods, one of the useful approaches to solve the existing challenges is to use the approach of integrated watershed management, which is agreed upon by most of the scientific and executive community. The multidimensionality of the watershed system, its integration with socio-economic systems, and the involvement of stakeholder opinions are one of the most important components in the watershed operation and conservation. Therefore, the present study seeks to investigate the necessity of using inter-sectorial management and benefit from the consensus of the main stakeholders using game theory algorithms in 15 sub-watersheds of the Cheshmeh-Kileh Watershed in Tonekabon City. Sehezar and Dohezar rivers are the most important rivers of the Cheshmeh-Kileh Watershed which originate from the Takht-e-Soliman, Alamut, and Khashchal mountain regions. The high capacity of the riverside lands and the limitation of suitable lands in the watershed have caused many agricultural activities to be concentrated along the river, which is severely affected by floods. Materials and MethodsIn the present study, semi-structured interviews were used to collect information about the flood generation potential. The stakeholders included local stakeholders, policy makers, and the executive organization. Game theory algorithms including the Condorcet algorithm, Borda scoring, and Fallback bargaining were used to prioritize the sub-watersheds. First, the prioritization of each of the three groups was analyzed, and then the results of the consensus of the group and their comparison with the sectional decisions were examined. In this connection, first, the sample size was determined using Cochran and the opinion of the stakeholders was asked regarding the flood generation potential of the sub-watersheds. The number of interviewees in subgroups of local users, policy making institutions, and executive organizations were 75, 13, and 6 respectively. It is worth mentioning that in order to eliminate the effect of the number of interviewees in the final results; the priorities were standardized and dimensionless. In order to prioritize by the stakeholders, first, various maps of sub-watersheds, roads, and even the location of villages were prepared with appropriate quality. Then, they were asked to prioritize the sub-watersheds in terms of flood generation potential based on their personal experiences, local knowledge, technical and policy. In the group of local watershed users and residents, random sampling was done from 21 Cheshmeh-Kileh Watershed villages in Tanekabon city and Mazandaran province. Results and DiscussionBased on the study findings, by comparing the two priorities of the stakeholders and the differences between the popular, institutional and policy-making sectors, it can be said that in the Condorcet algorithm, the rate of differences in the voting of local users with policy-making institutions, local users with the executive organization and policy-making institutions with executive organization is 33.33, 66.67, and 80 %, respectively. These differences based on Borda scoring algorithms and Fallback bargaining are 53.33, 66.67, and 93.33 %, respectively. According to the local operators, in all three algorithms based on game theory, Takht-e-Soleiman, Garmarood, and Selajanbar sub-watersheds have the highest flood generation potential in the Sehezar River. Meanwhile, Ketehroud, Holian, and Yandasht sub-watersheds have a low flood generation potential in this river. Regarding the Dohezar River, it can be said that the results of all three algorithms based on the theory of games were almost the same, and Niardareh, Khashchal, and Nosha have the highest potential, and Miankooh, Daryasar, and Golestan-Mohalleh sub-watersheds have the lowest flood generation potential. The second group of interviewees was the executive organization that used the opinions of technical and watershed management experts of the General Department of Natural Resources and Watershed Management of West Mazandaran-Nowshahr. The opinions of this department were different from those of local users. Also, in the Dohezar River, the Niardareh, Khashchal, and Nosha sub-watersheds were given the highest priority, and the Miankooh, Daryasar, and Golestan-Mahalleh sub-watersheds were the lowest priority. ConclusionDue to the fact that in the watershed system and in optimal decision-making, there is a wide variety of opinions and differences of opinion, on this basis, the conceptual basis of the application of multi-objective decision-making methods such as game theory algorithms appears. Therefore, the game theory provides an optimal compromise mode based on different opinions, at the same time, the opinions of different interest groups are considered to an acceptable extent without mixing. This basis clearly confirms the necessity of using participatory management. Because when the number of votes and interest groups increases, it becomes difficult to make a decision, and in this regard, by using multi-objective decision-making methods, a general consensus can be reached to identify the optimal pattern of prioritizing sub-watersheds. The first point is that the amount of differences in voters was the same based on two algorithms, Borda and Fallback, which, of course, the Condorcet algorithm has provided more balanced and acceptable values ​​in terms of comparison. Another point was that in all three algorithms, the amount of differences between the two local user groups and the policy-making body was less, and somehow their opinions were close to each other, and they had high differences with the executive organization. In all three algorithms, the amount of disagreement between the two local user groups and the policy-making institution was less, and in a way, their views were close to each other and had high differences with the executive organization. Also, a different prioritization was observed between the final consensus and the inter-sectorial and inter-institutional views. In general, it can be said that using the opinions of stakeholders in the watershed is fundamental for optimal and efficient decision-making and integrated watershed management, and this framework can be used in various issues in the watershed.

Introduction Choosing an optimal decision-making method for watershed management is a problem that has always attracted the attention of researchers, and various methods have been used to achieve this goal. Participatory management is a collaborative process to participate in gathering information, making decisions, and carrying out projects that lead to solving complex social and environmental problems. As it is known, the integrated watershed management approach is a method to achieve sustainable development. Considering the existence of challenges such as floods, one of the useful approaches to solve the existing challenges is to use the approach of integrated watershed management, which is agreed upon by most of the scientific and executive community. The multidimensionality of the watershed system, its integration with socio-economic systems, and the involvement of stakeholder opinions are one of the most important components in the watershed operation and conservation. Therefore, the present study seeks to investigate the necessity of using inter-sectorial management and benefit from the consensus of the main stakeholders using game theory algorithms in 15 sub-watersheds of the Cheshmeh-Kileh Watershed in Tonekabon City. Sehezar and Dohezar rivers are the most important rivers of the Cheshmeh-Kileh Watershed which originate from the Takht-e-Soliman, Alamut, and Khashchal mountain regions. The high capacity of the riverside lands and the limitation of suitable lands in the watershed have caused many agricultural activities to be concentrated along the river, which is severely affected by floods. Materials and Methods In the present study, semi-structured interviews were used to collect information about the flood generation potential. The stakeholders included local stakeholders, policy makers, and the executive organization. Game theory algorithms including the Condorcet algorithm, Borda scoring, and Fallback bargaining were used to prioritize the sub-watersheds. First, the prioritization of each of the three groups was analyzed, and then the results of the consensus of the group and their comparison with the sectional decisions were examined. In this connection, first, the sample size was determined using Cochran and the opinion of the stakeholders was asked regarding the flood generation potential of the sub-watersheds. The number of interviewees in subgroups of local users, policy making institutions, and executive organizations were 75, 13, and 6 respectively. It is worth mentioning that in order to eliminate the effect of the number of interviewees in the final results; the priorities were standardized and dimensionless. In order to prioritize by the stakeholders, first, various maps of subwatersheds, roads, and even the location of villages were prepared with appropriate quality. Then, they were asked to prioritize the sub-watersheds in terms of flood generation potential based on their personal experiences, local knowledge, technical and policy. In the group of local watershed users and residents, random sampling was done from 21 Cheshmeh-Kileh Watershed villages in Tanekabon city and Mazandaran province. Results and Discussion Based on the study findings, by comparing the two priorities of the stakeholders and the differences between the popular, institutional and policy-making sectors, it can be said that in the Condorcet algorithm, the rate of differences in the voting of local users with policy-making institutions, local users with the executive organization and policy-making institutions with executive organization is 33.33, 66.67, and 80 %, respectively. These differences based on Borda scoring algorithms and Fallback bargaining are 53.33, 66.67, and 93.33 %, respectively. According to the local operators, in all three algorithms based on game theory, Takht-e-Soleiman, Garmarood, and Selajanbar sub-watersheds have the highest flood generation potential in the Sehezar River. Meanwhile, Ketehroud, Holian, and Yandasht sub-watersheds have a low flood generation potential in this river. Regarding the Dohezar River, it can be said that the results of all three algorithms based on the theory of games were almost the same, and Niardareh, Khashchal, and Nosha have the highest potential, and Miankooh, Daryasar, and Golestan-Mohalleh sub-watersheds have the lowest flood generation potential. The second group of interviewees was the executive organization that used the opinions of technical and watershed management experts of the General Department of Natural Resources and Watershed Management of West MazandaranNowshahr. The opinions of this department were different from those of local users. Also, in the Dohezar River, the Niardareh, Khashchal, and Nosha sub-watersheds were given the highest priority, and the Miankooh, Daryasar, and Golestan-Mahalleh sub-watersheds were the lowest priority. Conclusion Due to the fact that in the watershed system and in optimal decision-making, there is a wide variety of opinions and differences of opinion, on this basis, the conceptual basis of the application of multi-objective decisionmaking methods such as game theory algorithms appears. Therefore, the game theory provides an optimal compromise mode based on different opinions, at the same time, the opinions of different interest groups are considered to an acceptable extent without mixing. This basis clearly confirms the necessity of using participatory management. Because when the number of votes and interest groups increases, it becomes difficult to make a decision, and in this regard, by using multi-objective decision-making methods, a general consensus can be reached to identify the optimal pattern of prioritizing sub-watersheds. The first point is that the amount of differences in voters was the same based on two algorithms, Borda and Fallback, which, of course, the Condorcet algorithm has provided more balanced and acceptable values in terms of comparison. Another point was that in all three algorithms, the amount of differences between the two local user groups and the policymaking body was less, and somehow their opinions were close to each other, and they had high differences with the executive organization. In all three algorithms, the amount of disagreement between the two local user groups and the policy-making institution was less, and in a way, their views were close to each other and had high differences with the executive organization. Also, a different prioritization was observed between the final consensus and the inter-sectorial and inter-institutional views. In general, it can be said that using the opinions of stakeholders in the watershed is fundamental for optimal and efficient decision-making and integrated watershed management, and this framework can be used in various issues in the watershed. [ABSTRACT FROM AUTHOR]

IntroductionThe world population has grown rapidly over the last 150 years and continues to do so, resulting in impacts on hydrologic resources at both a local and global scale (Yang et al., 2012). The competition for water between humans and ecosystems leads to complex interactions between hydrologic and social systems (liu et al., 2015). From the beginning of human history, it is located in floodplains. Floods can have large societal impacts, such as severe damage to urban areas, which are expected to grow around the world (Alfieriet al., 2018). In traditional hydrology, humans are either conceptualized as an external force to the system under study or taken into account as boundary conditions (Peel and Blöschl, 2011). Sivapalan et al. (2012) proposed a new model for investigating the interactions of the hydrological system and the social system. It explores the procedure coupled human-water system evolves and possible trajectories of its co-evolution, including the possibility of generating emergent, even unexpected, behaviors. Socio-hydrology must strive to be a quantitative science. There are several methods to control and mitigate flood risk, one of these methods is flood zoning (Jha et al., 2012). In last two decates, The Kalat city is flooded almost every year and many houses and historical sites in the city are damaged. Therefore, the main purpose of thisWe paper is to show investigated how changing human behavior with nature can affect the behavior of the natural system.Method and MaterialsKalat city located in 59° 43' 23" to 59° 47' 41" northern latitude and 36° 59' 35" to 37° 00' 05" eastern longitude. The city is divided into 11 sub-basins. The city has experienced fast and inappropriate urbanization over the past few years. To collect our data, the annual reports of the Regional Water Organization and the Environment Organization of Khorasan Province were used.SCS method was used to estimate the runoff peak discharge. Precipitation has been estimated for seven return periods: 2, 5, 10, 25, 50, 100, and 200 years. In this study, to analyze the sensitivity of runoff, we considered precipitation and curves number from 20% less to 20% more than the actual values in the study basin (at intervals of 5 %). We used the Cowan method to determine the roughness coefficient in this study. HEC-RAS model has been used for flood zoning. To determine the impact of various factors on the intensification of floods in Kalat city, we obtained questionnaires from relevant authorities. Likert scale was used to measure the results of the questionnaires. We prepared two questionnaires; first one is related to the inner city zone and includes the factors that intensify the occurrence of floods inside the city of Kalat, and it was classified into the following parts: 1) Local community 2) Managerial 3) Physical; and the second one includes the factors that intensify the flood in the upper part of Kalat city. We classified these factors into three parts: 1) Non-local community 2) Managerial 3) Environmental .Results and DiscussionResults of sensitivity analyzes demonstrated that land-use and land cover change had a further effect on peak discharge. In sub-basin 1, by 20% increase in the curve number, the level of peak dumping increased by more than 111%, with a return period of 2 year; while a 20% increase in precipitation, in the same return period, rises the peak discharge only 3%. The peak discharge time in some sub-basins was brief due to the presence of impermeable surfaces, so that in sub-basins 4, 6, 7, and 8, the peak discharge time was less than 30 minutes. These results highlight the dangers of these floods and the need for proper flood planning and management in these sub-basins. The results of the Manning coefficient demonstrated that we can reduce flood damage by applying management measures in the future, as well as paying attention to the feedback between urbanization and the flood zone. Roughness control by applying management programs can reduce the area of flood zones to 0.1 square kilometers. In this case, buildings should be removed from the river, and there should be no structure in the path of the river. According to the questionnaires in the inner city part, the most fundamental factor in intensifying the flood damage was related to “activities of local people” with the average of 3.59. In the upper part of the city, the most influential factors were ascribed to “managerial factors” with the average of 3.79.ConclusionIn a general conclusion, it can be concluded that the role of human factors in the occurrence and intensification of floods was much greater than rainfall. Therefore, in order to manage and control floods, it is necessary to prevent the change of land use and the reduction of permeability. And management programs should be aimed at increasing surface permeability. We suggest that more research be done on the role of economic and social factors in increasing flood risk in other climate zones.

One of the important relationships which are used in the estimation of river discharges and floods is Intensity-Duration-Frequency (IDF). The accuracy of this relation is dependent on the accuracy of its parameters which need to be found based on short-duration rainfall depths (such as 15, 30, 60 minutes, and so on) for a long term (i. e. 30 consecutive years). Unfortunately, only 24-hour rainfall depths are available in many rainfall stations in Iran. Various empirical relations are available to convert 24-hour rainfall depth to sub-daily. One of these methods is IMD and its accuracy in some regions is low. In this research, the IMD method was transformed into a single-parameter equation and then, this parameter is evaluated for some rainfall stations in Iran. To do this, maximum 24, 12, 6, and 3-hour rainfall depths were extracted and their frequencies were calculated using Weibull and Gumbel methods. Regional coefficients in the modified IMD method were estimated using a linear regression method. Although the power of the IMD method is 0.33, results showed that this parameter for the rainfall stations ranged from 0.28 to 0.35. To make more comparison, the IDF relation of Kordan’s watershed was calculated using the short-duration rainfall depth which was estimated using the modified IMD, and then, this IDF was compared to observed data and Ghahraman’s relation which is commonly used in Iran. The comparison showed that the modified IMD relation could estimate the short-duration rainfall data better than Ghahraman’s relation. After calibration of the modified IMD relation for various regions in Iran, the sub-daily rainfall depth can be obtained with high accuracy.

One of the important relationships which are used in the estimation of river discharges and floods is Intensity-Duration-Frequency (IDF). The accuracy of this relation is dependent on the accuracy of its parameters which need to be found based on short-duration rainfall depths (such as 15, 30, 60 minutes, and so on) for a long term (i. e. 30 consecutive years). Unfortunately, only 24-hour rainfall depths are available in many rainfall stations in Iran. Various empirical relations are available to convert 24-hour rainfall depth to sub-daily. One of these methods is IMD and its accuracy in some regions is low. In this research, the IMD method was transformed into a single-parameter equation and then, this parameter is evaluated for some rainfall stations in Iran. To do this, maximum 24, 12, 6, and 3-hour rainfall depths were extracted and their frequencies were calculated using Weibull and Gumbel methods. Regional coefficients in the modified IMD method were estimated using a linear regression method. Although the power of the IMD method is 0.33, results showed that this parameter for the rainfall stations ranged from 0.28 to 0.35. To make more comparison, the IDF relation of Kordan’s watershed was calculated using the short-duration rainfall depth which was estimated using the modified IMD, and then, this IDF was compared to observed data and Ghahraman’s relation which is commonly used in Iran. The comparison showed that the modified IMD relation could estimate the short-duration rainfall data better than Ghahraman’s relation. After calibration of the modified IMD relation for various regions in Iran, the sub-daily rainfall depth can be obtained with high accuracy. [ABSTRACT FROM AUTHOR]

Floods are a natural phenomenon that causes heavy losses of life and property and ‎human societies every year and people have accepted it as an inevitable event. In this research, to predict the flooding in Sardabrood basin ‎ SWAT hydrological model was used. Information needed for this research, ‎including topographic maps, land use, soil data, and meteorological data, data about daily ‎rainfall, temperature, and flow rate were prepared beforehand. SUFI2 program was used for model ‎calibration. After the calibration and optimization of the model, validation of the model in the ‎study area was done. The calibration of the model wad performed for the years 2003 to 2009 and validation was performed for ‎the years 2010 to 2013. To analyze the results of statistical indicators R2, bR2, and Nash Sutcliffe ‎coefficient were used. After model calibration the respective coefficients were, 0.77, 0.63, and 0.77 and ‎the respective validation coefficients were 0.79, 0.76, and 0.71. The sensitivity results of 31 parameters that are influential on runoff water showed that fixed parameters of groundwater base flow, its time, and the minimum amount of water necessary for groundwater base flow are more sensitive than other parameters. Number Sardabrood parameter curves were used for flood basin. Sardabrood basin was divided into 24 areas to study the flooding pattern. Finally using the above mentioned models it was concluded that sub basin No. (6) had the first-rank with runoff 123.05, ‎‎sub basin No. (10) had the second rank with runoff in terms of flooding and sub basin No. 1 with a 12.33 has the least amount of runoff.‎

The occurrence of the flood is considered as one of the most important environmental hazards with high impact in urban areas that threatens the environment, human beings, and human assets permanently. In this research, using AHP model, fuzzy logic and its integration with GIS, the flood phenomenon in Lamerd city in the south of Fars province has been analyzed. For micro-zoning flood hazard, eight important criteria such as natural criteria (distance from the waterways, geology, and slope) and human criteria (road network, urban bridges, residential, agricultural and forest uses, land suitability) have been used. The results show that the flood-hazard area stretches in a broad strip along the northwest-southeast and covers most of Lamerd's urban area. This zone starts from the Zanganeh and Niraiee areas in the northwest of the Lamerd suburbs and includes Mohr -Lamerd highways, Ahmedabad and Ziarat areas. This area stretches along Motahari Street, Jomhuori Street and Moallem boulevard to the south end of the city of Lamerd. Therefore, an important part of Lamerd city and its suburbs are prone to flood hazard and at least half of the city is in a warning condition and the conditions of flooding is very possible.

Flood prone area identification in the watersheds is one of the basic solutions for destructive flood control and mitigation. Flood mapping is one of the best methods for flood prone area planning and identifying. For this purpose, flow boundary conditions, peak instantaneous discharge with different return periods, cross sections and their distance and roughness coefficients for each cross section were entered to HEC-RAS hydraulic model in Khorramabad watershed located in Lorestan province, Iran, and this model was then run and flood water surface profile at different return periods were estimated. The results obtained from flood mapping showed that flood prone area in return period of 2-year with 145.125 m3s-1 and return period of 100-year with 553.781 m3 s-1 effect 8.63 and 10 km2 in area, respectively. So that about 4.4 km2 of the total rain-fed farming area, 2.4 km2 of total rangeland area and 1.4 km2 of total residential, 1.6 road area and 0.2 km2 abandoned effect by flood in return period of 100-year. Similarly for other flood return periods was also observed that the most flood prone areas are related to rain-fed farming, rangeland, road, residential area and abandoned the land.

Natural disasters are considered as part of the inescapable facts the control of whose occurrence is largely outside of human power. Therefore, natural disasters always have been important issues in biological communities and confronting with the disasters, and harmful effects have been the long-term goals of the communities. The flood phenomenon is considered as one of the unforeseen events and devastating in rural areas of the country. Management of natural disasters, especially floods, is a collection of actions that occurred before, during and after the occurrence of disasters to reduce more effects and damages.Today the approach of response to disasters as command-control structure, has been focused and technology-oriented and is displaced with a new approach called community-based management. It emphasizes on cultures, abilities, knowledge and capacity of existing local communities. In fact, without a comprehensive and systematic look, regarding all aspects of economic, social-institutional and environmental problems in large part is far from achieving. In this regard, the rural communities isn’t far this process and always has been subjected to flooding and its effects, and the other hand, rural area in this study (Zangmar River Basin) and livelihood and activities of residents are affected by flooding constantly and create many financial damages and losses of life for villagers. In this study, for data requirements, both library and field mode (questionnaires and observations) have been used. To cover the whole basin among villages (that were in three ranges of high, medium and lowvulnerability intotal of 63 villages), 21 villages were randomly selected. Then, by using the Cocoran formula taotal of 292 households were identified as samples. Also from 50 groups of officials among 5 organizations related to flood affairs in villages we selected samples and correlation test, we used one sample T test and variance analysis. The results of this research indicate that in all aspects of participation, both villagers and officials group believe in participation in the period before and after the flood disaster, and also there are largel similarities between approaches of two groups of officials and rural people into rate, type and period of participation in flood management in flood risk areas in the field of case study