Showing 24 results for Drought
Shamsollah Asgari, Tayeb Raziei, Mohamadreza Jafari, Ahmad Hosini,
Volume 9, Issue 1 (5-2022)
Abstract
Introducing the appropriate model of oak forest and drought relations
in Ilam province
Introduction
The forest ecosystems of the Zagros vegetation region have a very long history of exploitation in various
forms. The material of the Zagros vegetation region is Iranian oak. In recent years, a significant
proportion of oak forests have dried up or have experienced drought. Although the main cause of drought
in these forests has not been determined yet, in the preliminary studies, factors such as climate change,
increasing dust, increasing drought periods, pest infestation and disease, high user changes have been
cited as reasons for drought in the Zagros forests. (Hosseinzadeh and Pourhashemi, 1396). Iran's location
in the arid and semi-arid zone of the world (sub-tropical region) has often been associated with
fluctuations in climatic and atmospheric elements and under the influence of atmospheric currents,
synoptic patterns, irregularities in precipitation and temperature patterns (Rahmati, 2016; 1383).
Comparison of the effect of climatic variables on healthy masses and affected by the decline of oak in
Khorramabad city based on rainfall and temperature data using Pearson correlation coefficient, on annual
growth rings of oak trees Effectiveness of drought of oak trees from both series In general, healthy trees
have been more affected by monthly and seasonal temperatures and have shown the highest coefficient of
correlation with the temperature of the region (Naseri Karimvand et al., 2016). , And the Standardized
Rainfall Index (SPI) and the correlation between these two indicators in assessing and monitoring drought
in different areas of Isfahan province, the results showed that NDVI plant index can be a good alternative
to climatic indicators in drought assessment and monitoring) with the conclusion and colleagues, 2011:
79).
Data and Method
So from SPI and NDVI indicators and Moran index and statistical regression statistics and satellite
images of Modis and Landsat have used to analyze the relationship between dieback of Ilam forests and
happened drought in the region. The precipitation data of 93 rain gauge stations were analyzed during the
statistical period and according to the dry coefficients of SPI index, drought zoning layers of Ilam
province were prepared for two time series of 2000 to 2009 and 2010 to 2019. Greenery's raster layers
were prepared from Modis satellite imagery for the mentioned time series. The results of analysis of
Moran's statistical showed a significant correlation between the SPI index and the NDVI index in spatial
dimensions. By a simple random method, 143 points of oak dieback with dimension of 30 m 2 , which each
point was equivalent to a pixel-size, were recorded with a GPS device, and by simulating in satellite
imagery, the droplet layer of oak dieback was extracted.
Result and Discussion
What is debatable about the results of the implementation of methods for obtaining drought ranges and its
relationship with oak drought points or masses is that the results of the models show a statistically close
and direct relationship between drought and oak drought. . The general trend of oak drought and drought
in these two decades has been from the southeast to the northwest of Ilam province, with increasing
temperature and decrease in rainfall in the southern and eastern regions of the province and increasing
rainfall and decrease in temperature in the central and northwestern regions of Ilam province. The data of
the synoptic stations are consistent. Analysis of satellite imagery and declining greenery in the models
although the study was aimed at meteorological drought and precipitation fluctuations, but spatial
changes of arid points and masses in the province were adapted to field visits and human intervention,
especially in the southeast with agriculture. Under the rubble and the remnants of the dried trees, the ax
has been placed on the roots of these trees, and this trend is spreading in almost other parts of the arid
areas of the province. Therefore, due to the irregularity in the pattern of precipitation and temperature of
the research country (Rahmati, 2016; Zandi Army, 2004) and the effect of monthly and seasonal
نشریه تحلیل فضایی مخاطرات محیطی، سال نهم، شماره 1، بهار 1401 2
temperature on the growth and decline of oak trees in the study (Naseri Karimvand et al., 2016) and other
related research and The flooding situation in the basins of Ilam province, the rainfall, the impermeability
of the soil and their erosion, and finally the lack of moisture in the months before the oak trees grow in
the soil and the increase in temperature in the dry season, which leads to reduced humidity and eventually
greenery. Variables affecting oak drying in linear regression are not responsive, but more accurate results
will be obtained in multivariate regression, although regression analyzes are spatially empty, and X and Y
represent a one-way, quantitative analysis based on the number of dried trees with pixel counts. Drought
range is measured which this defect in SPI method despite its spatial and statistical analysis using Moran
statistical index due to non-compliance in the coefficients of this index with the range of changes in
Moran statistical analysis in statistical analysis is a more appropriate explanatory coefficient than The
regression models showed but at a lower level than the NDVI method it placed. The advantage of NDVI
method with Moran statistical analysis is the relationship between pixel and pixel, ie in spatial analysis,
all pixels that have green changes have been analyzed in the same domain of spatial changes with oak
trees. High results and higher statistical explanation coefficient were obtained than other models.
Conclusion
Although linear regression between extracted oak dieback points with SPI and Moran statistical indicators
was significant, but the relationship between NDVI index and Moran statistic has the effect of
independent variable of drought trend in spatial and temporal dimensions on the dependent variable
process of oak drought with spatial analysis. And nonlinear regression has a more appropriate and
accurate statistical significance and explanation. So this method as desirable method has been introduced
for analyzing of drought and oak dieback.
Keywords: Ilam province, oak forest drought, drought, Moran index
Mr Sayyed Mahmoud Hosseini Seddigh, Mr Masoud Jalali, Mr Hossein Asakereh,
Volume 9, Issue 3 (12-2022)
Abstract
The expansion of the pole toward the tropical belt is thought to be due to climate change caused by human activities, in particular the increase in greenhouse gases and land use change. The variability of the tropical belt width to higher latitudes indicates the expansion of the subtropical arid region, which indicates an increase in the frequency of drought in each hemisphere. In order to change the width of the tropical belt of the Northern Hemisphere in the middle offerings, indices of precipitation minus evaporation, wind vector orbital component, stream function, tropopause surface temperature, OLR, and SLP have been used. Findings showed that the expansion of tropical belt latitude with stream function to higher latitudes with 1° to 3° latitude and the effect of Hadley circulation subsidence has increased the amplitude of evaporation minus precipitation has shown that the fraction of precipitation minus evaporation 1° to 3° latitude geographically increased. The subtropical jet has increased the movement of the upper branches of troposphere from the Hadley circulation by 2° to 4° latitude, which can have a negative effect on transient humidification systems as well as on the amount of precipitation. The extension of the pole towards the tropical belt, which is a consequence of climate change and hazards, will lead to the displacement of the pole towards the tropical side of the river, thus providing dry tropical belts to the pole; Also, the long-wave radiation of the earth's output has increased by 1° to 2° latitude and has caused an increase in heat in the upper troposphere, which has increased the dryness and slightly reduced the clouds in the upper troposphere and also caused the tropical belt to expand to higher latitudes. Has been. In general, the research findings showed that most tropical belt indicators have been increasing since 1979.
Dr Ebrahim Yousefi Mobarhan, Dr Mansor Ghodrati, Dr Mohamad Khosroshahi,
Volume 9, Issue 4 (3-2023)
Abstract
In the study of the trend of dust storm index, the results showed that the study period of 2003-2007 in Semnan province has an increasing trend and has shown significant changes in the 95% confidence range, but the lack of significant changes in the last decade shows the effects of various events. In cross-cutting decisions in the field of dust in the region. The zoning of the DSI index changes in different regions of the province in a 15-year statistical period indicates that from the west to the east of the province due to the increase in the frequency of stormy days with moderate dust (MDS), dust has increased. The correlation between drought and DSI index in Semnan province showed that although DSI index increased during the period under analysis with increasing drought intensity and its correlation with drought during the 15-year period was not significant, but the pattern of DSI index is consistent with It is the pattern of the drought process. According to the results, it can be acknowledged that the dust situation has always been affected by climate, but the relationship between drought and the DSI index has always fluctuated with respect to droughts and wetlands. However, different climatic parameters are different and their impact is different. In addition to human activities, the main role of wind in the amount of dust or the existence of another source of dust should be considered.
Dr Seyed Keramat Hashemi Ana,
Volume 10, Issue 1 (5-2023)
Abstract
Abstract
Introduction and issue: In today's century when the effects of climate change on different sectors are undeniable, investigating and analyzing the behavior during dry spells is always of special importance and basic priority. On the other hand, the occurrence of extreme events such as precipitation can accelerate the occurrence of climate change. In Iran, rainfall is one of the basic variables for evaluating the potential availability of water resources, but its temporal and spatial distribution is very uneven. The change of dry Spells depending on precipitation always have different fluctuations in different seasons of the year. It seems that this is due to the inherent behavior of precipitation, which generally shows itself as an unstable and unruly variable. This feature causes changes and differences in the temporal and spatial distribution of precipitation in arid and semi-arid regions such as Iran. This inconsistency will face fundamental challenges to regularize dry spells on a seasonal and monthly scale. With a detailed understanding of the behavioral mechanism of dry spells, it is possible to know more precisely the climatic condition of different regions in order to plan in sectors such as; Water resources, agriculture, health, transportation and etc we able to do basic and preventive measures compatible with climate change. It is hoped that this research and related studies will be a positive step towards a more accurate understanding of the climate and its behavior in different seasons of the year.
Data and method: In order to investigate the seasonal behavior of the duration of dry spells, we used daily precipitation data for 44 synoptic stations of Iran and a 30-year statistical period (1988-2018). To reveal the behavior of dry spells, the precipitation data after validation and temporal integration were classified on a seasonal scale.
After the statistical integration of the data, dry spells related to precepitation were extracted and long-term periods lasting more than 20 days were the basis of the study. In the next step, to determine the seasonal weight of courses was used, the step-by-step evaluation method of Swara's fuzzy-numerical logic (SWARA). Thus, in the first step, the longest and most frequent periods are sorted based on relative importance. In the second step, the initial weights of the courses are determined, and in the third and fourth steps, the final and normalized weights of the courses in different seasons are determined, and unrealistic results are removed from the final analysis for proper explanation.
Findings and Results: The effectiveness and weight of each of the criteria with the Swara method in the fuzzy environment showed that in the western and northern regions of the country, winter and spring seasons and criteria such as reversibility and percentage of probability of occurrence have the most initial weight in explaining the periods. In the final explanation, these two season,s had a high weight. These two seasons explain more than 65% of the weight of courses in these regions. In the southern regions and parts of the center (Isfahan, East Fars and West Kerman), winter and autumn explain more than 71% of the weight of periods. Among the criteria explaining the weight of the courses, the reversibility criterion and the probability of occurrence have taken more than 55% of the weight. The northern and humid regions of the country vary in criteria from periods such as; Reversibility, continuity and probability of occurrence are more apparent and this indicates that the border of dry areas in the future of Iran's climate will move towards northern areas. It can be acknowledged that the behavior of long-term dry periods is more a function of two criteria of reversibility and probability of their occurrence. The weighting of the criteria affecting dry periods showed that the return period and the continuation of periods in the cold seasons of the year in dry areas have a more irregular behavior than in wet areas and have more weight in explaining the periods. By determining the weight of seasons in explaining dry periods, we can have better planning and management in related sectors such as water and agriculture.
Key words: dry spells, weighing, precipitation, climate, Swara method, Iran.