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Volume 6, Issue 2 (9-2019)
The application of Extreme value analysis method in heat wave hazard climatology; case study in Mid-Southern Iran
Abstract
Greenhouse warming poses the main cause of atmospheric hazards’ exacerbation and emergence in recent years. Earth planet has been witnessing frequent and severe natural hazards from the distant past; however, global warming has strongly influenced the occurrence of some atmospheric hazards, especially the ones induced by temperature and has increased the frequency and severity of those risks. Such extreme risks arising from temperature element and being affected by global warming could be referred to hot days and their frequency more than one day which undergo heat waves. Of the studies conducted worldwide in conjunction with the phenomenon of heat waves, the following can be pointed out; Schär (2015) has focused his studies on the Persian Gulf and the worst heat waves expected in this area. The recent work revealed an upper limit of stability which enables the adaptability of human body with heat stress and humidity. If people are exposed to a combination of temperature and humidity over long periods higher than this level, they will lead to hyperthermia and death, because heat dissipation from the body is physically impossible. Paul and al-Tahrir (2015) using a high-resolution regional climate model demonstrated that such a situation can occur much earlier. In Iran, in relation to heat waves, Ghavidel (2013) analyzed climatic risk of Khuzestan province in 2000 regarding super heat waves using the clustering approach. The obtained results unveiled the establishment of a low pressure at ground level and high pressure dominance at mid-altitudes up to 500 hp as well as the increase in atmosphere thickness having led to the ground overheating. Added to that, the source of heat entering into Khuzestan is advective and hot and dry air transport through Arabian Peninsula, Iraq and Africa. Ghavidel and Rezai (2014) addressed in a study to determine the temperature-related threshold and analyze the synoptic patterns of super heat temperatures in southeast region of Iran; the results of study approved that the only pattern effective on the occurrence of super heat days in Iran’s southeast is the establishment of the Grange’s heat low-pressure at ground level and subtropical Azores high elevation dominance at 500 hPa level. In this study, absolute statistical indicators, also recognized as above-threshold values approach, were used in order to identify, classify and heat waves synoptic analysis in the warm period of the year in the southern half of Iran. To use above-mentioned indicators, firstly daily maximum temperature statistics of studied stations with the highest periods were averaged every day once in June to September and once for the months of July and September. Using statistical indicators of long-term mean and standard deviation or base period, indicators would be defined for the classification of heat waves and days with peak extreme temperatures. In such classifications, usually long-term average or base period is multiplied by 1 to 3 to 4 times standard deviation and each time is account for the factor of each class.
To select the days for synoptic analysis, averaging was performed of all classified waves into four heat wave categories of low, intermediate, strong and super heat; accordingly based on the maximum blocks in each class of heat waves, days that had the highest temperature values were selected as the class representative for mapping and synoptic analysis.
This study dealt with investigating heat waves synoptic during the year’s warm period in the southern half of Iran. Studies showed that a variety of synoptic systems in the year’s warm period affect the study area. As well as, synoptic analyses concluded that in the southern half of Iran over the year’s warm period when occurring heat waves, low-pressure status dominates the ground level (caused by Gang’s low-pressure and local radiant mode); thus high-pressure status with closed curves is prevailing in atmosphere’s upper levels that gives rise to the divergence, air fall and Earth's surface heating. Studying the status of the atmosphere thickness in the days with the heat wave in the study area indicates its high altitude and thickness that this itself implies the existence of very hot air and susceptibility of the conditions for the occurrence of heat waves. In addition, wind maps at atmosphere’s different levels well illustrate the wind of very warm and hot air masses from the surrounding areas to the southern part of Iran; therefore it can be noted that aforementioned hot air masses mainly wind from places like different regions of the Arabian Peninsula, Iraq, North Africa and the low latitudes to the study area.
Keywords: Synoptic analysis, heat waves, maximum blocks, southern half of Iran.
Volume 9, Issue 3 (12-2022)
Determination of flood-prone areas using Sentinel-1 Radar images
(Case study: Flood on March 2019, Kashkan River, Lorestan Province)
Introduction
Although natural hazards occur in all parts of the world, their incidence is higher in Asia than in any other part of the world. Natural phenomena are considered as natural hazards when they cause damage or financial losses to human beings. Iran is also one of the high-risk countries in terms of floods. Until 2002, about 467 floods have been recorded by the country's hydrometric stations. In addition to natural factors such as rainfall, researchers consider human impacts such as destruction of vegetation cover, soil destruction, inefficient management, destruction of pastures and forests, and encroachment on the river are the most important factors for the occurrence and damage of floods in the country. One of the most efficient and emerging tools in flood surveys is the use of radar images. SAR images and flood maps produced by radar images provide researchers valuable and reliable information. Moreover, maps obtained from SAR images help officials to manage the crisis and take preventive measures against floods. The Sentinel-1 satellite is part of the Copernicus program, launched by the European Space Agency, and is widely used in mapping flood-prone areas. The contribution of Sentinel-1 to the application of flood mapping arises from the sensitivity of the backscatter signal to open water. This study aims to determine high-risk and flood-prone areas along the Kashkan River using Sentinel-1 radar images.
Data and Methods
The study area includes a part of the Kashkan river from Mamolan city to the connection point of this river to Seymareh river, after Pol-dokhtar city. The average annual discharge of the Kashkan river is 33.2 cubic meters per second based on the data of the Pole-Kashkan Station. The length of the river in the study area is about 100 km. To investigate flood-prone areas, we applied pre-processing and image-processing steps to each flood event including SAR images belonging to March 25th, 2019, March 31st 2019, and April 2nd, 2019. SAR images were acquired from ESA Copernicus Open Access Hub. climatic data was downloaded from power.larc.nasa.gov. To create meander cross-sections, the Digital Elevation Model of the studied area was utilized. Cross-sections were created using QGIS software. Pre-processing steps include: applying orbit data, removing SAR thermal noise, calibration of SAR images, de-speckling and topographic correction. In image processing, we applied the Otsu thresholding method to distinguish water pixels from land pixels. In thresholding methods, the histogram of each image is divided into two parts according to the amount of gray composition. The higher the amount of gray (i.e., the pixel tends to be darker), the more pixels represent water, and conversely, the lighter-toned pixels (i.e., pixels that tend to whiten) represent land. The Otsu thresholding method is a commonly used method for water detection in SAR images. It uses an image histogram to determine the correct threshold. The most important feature of the Otsu method is that it is capable of determining the threshold automatically. The Otsu algorithm was applied to all images using MATLAB.
Results
According to the flood maps, on March 25th, 6.51 percent of the study area was flooded, while on March 31th, only 3.96 percent was flooded. This is mainly due to less precipitation on the 31st. On March 25th the average daily precipitation was 47.46 mm while on 31st of March the average daily precipitation was 31.64 mm. On April 2nd, however, there was no rainfall, on the day before more than 63 mm of precipitation has occurred. This massive amount of precipitation on the previous day has led to more than 25km2 being flooded in the studied area.
Conclusion
Results showed that meanders and their surrounding areas are the most dangerous sections in terms of flooding. The meander's dynamic and the river's hydrologic processes are essential factors affecting flooding in those sections. Generally, various factors affect flooding and the damage caused by it. This study aimed to determine flooded and flood-prone areas (according to flooded areas in previous events) using new methods in a short time and with high accuracy to use this tool for more accurate zoning and efficient planning in the future. The results showed that radar images are practical, robust, and reliable tools for determining flooded areas, especially for rapid and near-real-time studies of flood events.
Keywords: Floods, Radar images, Sentinel-1Satelitte, Kashkan river
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