Paleoclimatic investigation of the Quaternary period reflects fluctuation in climatic conditions during geological periods. Abrupt climatic changes, viewed as problem causing global incidents bring about adverse side effects in sensitive climatic zones such as Iran. Droughts and unpredictable floods that damage natural resources as well as human life become common yearly occurrences. Apart from influences of natural physical factors, human activities, if not properly controlled, add to the destructive power of the floods too. This happened in the Nekaroud basin mainly due to deforestation and damaging changes in landuse during the last century. The huge magnitude flood of summer 1999 which caused irreparable downstream damage and death of citizens is a sad incident of such environmental changes. The present study is an investigation into some characteristics of Nekaroud basin, an analysis of the reasons behind the occurrence of the catastrophic flood, ways to predict and prevent similar disastrous incidents in other catchments basins in Mazandaran as well as in other regions with similar conditions in Iran.

Among the various natural hazards, floods may be considered as the most devastating factor that inflicts great damage on human societies. Therefore, the importance of estimating flood damage and its scope in planning to reduce damages and determine points with high risk is very important. The aim of this study is to determine the extent of flood hazard using OLI satellite data. For this reason, a window of OLI satellite images of Landsat 8 was acquired before and after the Dezful flood of April 25, 2016. First, preprocessing operations include radiometric and atmospheric corrections of images were done, and the principal component analysis was then used to reduce the correlation of the data. Data processing was performed using a Support Vector Machine algorithm with linear and polynomial kernels. In order to train the Support Vector Machine algorithm, training samples for each class (agricultural land, flood extent, water resources, settlement areas, and recreational areas along the river boundary) were harvested at the user level. In order to evaluate the similarity of the classes and the degree of correlation between the samples, the quantitative assessment method of the Jeffries Matusita was performed. The results showed that the flood area was 11593. 26 ha, the highest damage was due to agricultural land with a destruction of 8467. 45 ha and recreational and tourist areas along the riverbank with a destruction of 2659. 14 ha.

Global climate change leads to an increasing in the number and severity of weather events such as floods. Floods have been reported one-half of all weather-associated disasters with high impacts on countries. Global warming causes a different pat-tern of rainfall in Iran caused long-term drought since 30 years ago and recent heavy raining which lead to a massive flood in this country. It is predicted that health subsequences of Iran 2019 flood such as communicable diseases vary due to the geo-graphical extent and different climates of flooded areas. However, observing long term and short term preventive measures can be effective to reduce the high impact of flood in Iran.

Natural disasters threatening and endangering human communities has resulted in the study and research of such disasters through the related sciences and present methods of forecasting their behavior with time and place and also from a qualification and quantity viewpoint. To this end, numerous methods for the determination of the maximum flood in various return periods has been made available which can be refered to as flood frequency analysis methods. One of these methods is the regional flood frequency analysis in which instead of using the data from a single station, it considers the data and characteristics of a group of similar stations. In the case under the research this method uses L-Moments and Index Flood in North, Razavi and South Khorasan water basins and MATLAB software. Maximum annual flood statistics were used from 68 Hydrometric stations with minimum and maximum statistical periods of 6 and 39 years. Using Cluster analysis the region under study was divided to 7 partitions. Discordance test has conducted and only one station in region C was found as discordance station. Because of knowing the homogeneity of the regions, the parameter of Kappa distribution were estimated and with using the simulation method of Monte Carlo with 500 times, the homogeneity measure was tested in 7 regions. Using homogeneity test all regions was found homogen. Using goodness-of-fit measure z and Kolmogrove-Smirnov the Log normal 3 parameters distribution were selected for two regions of A and B, GEV for C, Generalized Pareto for D and E, Generalized logistic for F and Pearson III for G. Besides, GEV distribution was found appropriate for all of the regions, only their parameters are different in any regions. For estimating of index flood a logarithmic model has found for each region with 4 variables of area, height, average slop and form factor. Using of these models, the index flood can be estimated in each region and it can be used for standardize the statistics of maximum flood values.

Background: Misunderstanding of disaster hinders people from devoting enough attention to disaster preparedness programs. Flood is one of the main natural hazards in Iran. Objectives: The present study aimed to determine flood risk perception among residents of a flood-prone area in Iran in 2021. Methods: This cross-sectional study was conducted on 201 inhabitants of three villages along the Hesar-Golestan River in northeast Iran. A researcher-made questionnaire was used to assess their flood risk perception and opinions about the causes of the flood. Flood risk perception was assessed using ten questions with a 5-point Likert scale. Risk perception was calculated at three levels: low (scores 10 to 23), medium (scores 24 to 37), and high (scores 38 to 50). Multi-stage sampling technique was used for sampling. Results: The majority of participants (81%) had a moderate risk perception. The mean risk perception score was 30±, 5, which indicates a moderate risk perception. According to the participants, the three main causes of floods were environmental degradation and soil erosion, unplanned development and construction in flood-prone areas, and heavy seasonal rainfall, respectively. There was a significant relationship between gender and age with some opinions about the causes of floods. Conclusion: The risk perception of participants was at a moderate level. Low or moderate flood risk perception can lead to insufficient attention, inaction, or insufficient efforts to reduce the risk and increase preparedness for floods. Taking measures such as educating people about the causes and consequences of floods using appropriate and effective methods can help to manage disasters better.

Background and Objectives: The complex knowledge of local communities on the full cycle of disaster risk management has been proven valuable in various researches. However, the scientific literature still lacks studies that examine how to use Local Knowledge (LK) and the local people capabilities for crowdsourcing in Flash Flood Early Warning Systems (FFEWS) studies. Hence the main target of this research is investigation on the capacity of crowdsourcing for FFEWS and identification of Flash Flood Hotspots (FFHs) by LK across a flood prone area in northeast of Iran. Materials and Methods: In this study, a questionnaire with three different themes was designed. The first theme was related to the individual characteristics as independent variables, the second theme addressed the residents’ LK in determining the FFHs, the type and the predominant time of the flood occurrence in the region, through asking open ended questions with short-answers. The last theme addressed the assessment of people's capacity in Flash Flood Crowdsourcing (FFC), through asking questions with a Likert scale of 0-5. The face-to-face questionnaire administration mode was used for public survey through conducting oral interviews and live discussions.Results: The results showed that there was no significant correlation between the individuals’ characteristics and their willingness and motivation to participate in FFC. Comparing residents’ LK with the 31-year flood report and literature review showed that the residents’ LK about the flood occurrence location, time and type on a local scale was very promising. The research results indicated that the respondents show highest level of willingness for participation in the release of flood warning messages with an average score of 4.23 and the most important motivating factor for their willingness to participate was introduced saving relatives, fellow villagers, and human being from flood hazards with an average score of 4.84.Conclusion: In most of previous studies that have focused on the development of FFEWS, very little attention has been paid to understanding the needs of citizens and promoting their participation. In fact, there is a research gap regarding the method of citizen’s participation and their potential support for FFEWS. Hence in this research, an attempt was made to take a small step towards filling this gap by investigating LK, motivation and willingness of local residents to participate in various aspects and steps of FFEWS. Our findings indicate that involving local people in FFEWS has various unknown aspects that should be explored through more extensive and detailed studies.

Among natural disasters, floods have the highest human toll. The economic impacts of floods are greater in developing countries, including Iran, and are particularly severe in the colder months of the year in the west of the country. The purpose of the present study is to analyze the most severe historical synoptic floods that occurred in Karkheh Basin  (1 April, 2019). Descriptive - analytical research method and its environmental approach into circulation. Analysis of synoptic systems of large floods such as the April 12, 2019 floods show that Western Europe's high-pressure systems, Black sea, East of the Caspian and low pressure north of the Red Sea, Eastern Mediterranean in harmony with the high-rise systems of Western Europe, Low Mediterranean East with a temperature drop of about 50 degrees Celsius(The temperature at sea level In the eastern Mediterranean and Red Sea about 25 degrees Celsius and in the middle of the atmosphere -25 degrees Celsius) also the climb Humidity from the Arabian Sea, North Indian Ocean, Red Sea, Oman Sea and Persian Gulf and Along with Mid-width cold air loss On the area and the establishment of the Polar jet stream) Core up to 70 m(And the establishment of the front jet stream And positive rotation area On the area shows the structure of the synoptic systems causing the flood in the area.