Elham Rafiei Sardooi; Mina Eghtedarnejad; Shapour Kohestani
Abstract
Since that the traditional methods are based on meteorological station data and more investigate meteorological drought, hence, the application of remote sensing techniques and satellite images have been considered as a useful tool for monitoring of agricultural drought. In this study, the relationship ...
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Since that the traditional methods are based on meteorological station data and more investigate meteorological drought, hence, the application of remote sensing techniques and satellite images have been considered as a useful tool for monitoring of agricultural drought. In this study, the relationship between the meteorological drought index (SPI) and remote-sensing-based indices (VCI, TCI and VHI) has been studied in Bam plain. In this regard, using Terra satellite images (Modis sensor) and precipitation data of synoptic and rain gauge stations in the study area, the occurred changes were detected over the 15-year period. In this study, with respect to high temporal accuracy and spectral coverage and accessibility, MOD13A3 and MOD11A1 products extracted from MODIS sensor were used during 2009 to 2023. Then, indices of VCI, TCI and VHI were compared with Standard Precipitation Index (SPI). The results of drought mapping with the SPI index during 2010 to 2024 showed that the drought severity has increased from north to south in the study area. So that, extremely drought is detected in the southern regions of the plain and extremely wet is detected in the northern regions. The annual correlation coefficient between SPI, VCI and SPI indices is 0.70 and 0.53, respectively. It shows high significant positive correlation at level of 0.05. The correlation coefficient between SPI and TCI is 0.11 which shows a weak correlation but significant positive at level of 0.05. Therefore, VCI and VHI Indices have more correlation with annual precipitation and have acceptable results compared with TCI Index.
Farhad Hasani Dorabad; Naser Mashhadi; AmirReza Keshtkar
Abstract
The desert environment is aeolian, being dominated by the wind. The dynamics of wind erosion are driven by both natural processes, including climate and its fluctuations, and human activity. Separating the climatic and anthropogenic causes of wind erosion can improve the understanding of its driving ...
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The desert environment is aeolian, being dominated by the wind. The dynamics of wind erosion are driven by both natural processes, including climate and its fluctuations, and human activity. Separating the climatic and anthropogenic causes of wind erosion can improve the understanding of its driving mechanisms. The aim of current research is to evaluate the spatio-temporal dynamics of the aeolian process based on the sand dunes morphology and the analysis of the spatial correlation between wind erosion dynamics and climate fluctuations. Based on meteorological, remote sensing and field observations data, the impacts of climate fluctuations on the temporal and spatial changes of the aeolian process were evaluated according to the indicator of the creation and expansion of sand dunes .MODIS remote sensing data was used to study the sand dunes morphology. The temperature, precipitation, wind speed and other meteorological data used in this study were all derived from two synoptic stations of Qom and Kashan. The analysis of the elongation and form of the sand dunes as the wind direction indicator showed that the studied area is affected by the winds region of the Qom (northwest and west). The results of climate studies showed that over the last 27 years, the region has a rising temperature trend, while the average precipitation in the region has decreased in the same period. The relationship between drought conditions and aeolian process showed that the region experienced severe drought conditions more than normal or abnormally dry conditions during 1369 to 1395.
Ahmad Gillvare; Gholamreza Zehtabian; Hassan Khosravi; Hossein Azarnivand; Salman Zare
Abstract
Due to the importance of vegetation cover in these areas, the aim of this study was to investigate the effect of drought, on vegetation of HablehRood watershed.Initially, NDVI index obtained from MODIS sensor was used to study vegetation cover and then SPI index based on rainfall data of two basins in ...
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Due to the importance of vegetation cover in these areas, the aim of this study was to investigate the effect of drought, on vegetation of HablehRood watershed.Initially, NDVI index obtained from MODIS sensor was used to study vegetation cover and then SPI index based on rainfall data of two basins in two arid and semi-humid climates was used for drought assessment (2001-2018) using image processing methods. The results showed that during this 18-year period, 53% of the region had droughts on average. Also during the period 2001-2003, drought was more severe than other periods (2003-2018). In addition, the highest vegetation index occurred in 2005, indicating that vegetation was affected by rainfall fluctuations in the region. The correlation matrix between the three indices indicated that NDVI had the same correlation with SPI and annual rainfall. The results of this correlation in dry and semi-humid climates showed that the correlation was 0.38 and 0.25, respectively. These results indicate that this relationship is positive and robust in different climates of a region؟. On the other hand, drought class is mainly located in dry and semi-humid climates, with 55.55% and 50% in relatively normal drought class, respectively. Based on the above, it can be concluded that using remote sensing data can monitor the response of semi-humid and dry arid ecosystems to climate change. The study also showed that arid and semi-arid regions are highly susceptible to climate change and human anomalies. Therefore, the destruction of these lands will have many environmental and economic consequences.
Amir Alambeigi; Mohsen Malekli
Abstract
The phenomenon of climate change, especially the drought in Iran during the past decades are increasingly on the rise. In this respect the role of institutions and institutional entrepreneurship in areas that suffer from drought are can be used as the perfect solution for the management of drought. The ...
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The phenomenon of climate change, especially the drought in Iran during the past decades are increasingly on the rise. In this respect the role of institutions and institutional entrepreneurship in areas that suffer from drought are can be used as the perfect solution for the management of drought. The aim of this study was to analyze the institutional management of drought with approach of social network analysis. The statistical research community is smallholder farmers of Saveh town. The dominant statistical method in this study is to measure and extract the total network indexes through the network analysis technique. Based on information obtained from the institutional rankings were determined that the most current information on educational information network two-sided with ministry of agriculture and veterinary. In the context of the flow of information, banks and credit institutions support the centrality of the ranking. In terms of information flow as well as the largest specialized veterinary related role information to current technical and specialized in order to catch up with climate change. The research results show that the different dimensions of social networks effect on the mobilization of resources and on the other hand, the lack of institutional entrepreneurship can damage caused by climate change will intensify. At the end, suggestions are made to improve the management of droughts.
Fatemeh bahreini; Fatemeh Panahi; Mohammad Jafari; Arash Malekian
Abstract
The complexity of drought phenomenon hinders our full understanding of its impact. Field sampling, Geographic Information Systems, SPI and NDVI, EVI and SAVI indices derived from 16-day interval MODIS images during 2000-2015 were used to better understand the effects of drought on vegetation In recent ...
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The complexity of drought phenomenon hinders our full understanding of its impact. Field sampling, Geographic Information Systems, SPI and NDVI, EVI and SAVI indices derived from 16-day interval MODIS images during 2000-2015 were used to better understand the effects of drought on vegetation In recent study, ground true map was prepared by sampling and field surveys and vegetation cover data was obtained from 32 sampling units in 320 plots over the entire study area. Then, the correlation between field sampling data and vegetation indices was estimated and vegetation cover models were produced for different indices. In this study, precipitation data of 14 stations within and around the study area were used and SPI was calculated at the same time scales with the vegetation indices to study the effect of drought on vegetation. The results showed that NDVI has had the highest correlation coefficient (R2=0.56) amongst the indices so it was selected for vegetation cover percentage mapping. Investigating NDVI rates and drought index in different temporal periods, 9-month SPI was found to have the best correlation with NDVI. On the basis of SPI analysis, it was found that the study area had the most severe drought in 2012 and the best wet condition in 2004. The similar trend was observed in NDVI. The comparison of classified images between 2004 and 2012 (with 42 % changes in poor vegetation) indicates the effect of drought on vegetation in the study area.
Fatemeh Maghsoud; Mohammad Reza Yazdani; Mohammad Rahimi; Arash Malekian; ali asghar zolfaghari
Abstract
Overview, drought is effected an unusual dry period which is enough continued and causes imbalance in the hydrologic status, as depletion of surface water and groundwater resources. The purpose of this research is modeling meteorological drought prediction using Neural Network- Multi layer Perceptron, ...
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Overview, drought is effected an unusual dry period which is enough continued and causes imbalance in the hydrologic status, as depletion of surface water and groundwater resources. The purpose of this research is modeling meteorological drought prediction using Neural Network- Multi layer Perceptron, parameters and climatic signals in three time scales include short, middle and long term in a rain-gauge station located at south plain of Qazvin Province. Three different scenarios were tested as inputs model. Optimal combination of variables was determinate by Gamma-Test after identification of input variables using cross-correlation. Results showed, influence of climatic signals increased and against the influence of meteorological parameters decreased when time scale were increased from short-term to long-term. MEI (Multivariate ENSO Index) and rainfall were introduced as the most effective climatic signals and meteorological parameter for each scale, respectively. Neural Network modeling which has hidden layer with enough neurons, Sigmoid Function in middle layer and linear function at output layer was used. The most appropriate of the number neurons was determined in each scenario and wasn’t observed significant correlation between increasing or decreasing the error and number of neurons. Finally, the most appropriate network structure was determined based on evaluation indexes in three scenarios and each time scale.
Leila Fazel Dehkordi; Hossein Azarnivand; Mohammad Ali Zare Chahouki; Farhad Mahmoudi Kohan; Shahram Khalighi Sigaroudi
Abstract
To identify an appropriate index for monitoring and evaluation of drought, rainfall data obtainedfrom meteorological stations of Ilam Province from 2000 to 2011 and MODIS satellite images with16-day intervals were collected and processed. The Standardized Precipitation Index (SPI) wascalculated based ...
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To identify an appropriate index for monitoring and evaluation of drought, rainfall data obtainedfrom meteorological stations of Ilam Province from 2000 to 2011 and MODIS satellite images with16-day intervals were collected and processed. The Standardized Precipitation Index (SPI) wascalculated based on rainfall data; therefore, the rainfall data were used for measuring SPI andsatellite images were used for calculating NDVI. Also, the percentages of canopy cover in rangetypes were selected from the information of the National Evaluation of rangelands in differentclimatic zones. The correlation between SPI and NDVI and also canopy cover and NDVI wasexamined. The relationship between vegetation index (NDVI) and SPI was determined byregression. The results of SPI showed that in 2000 a severe drought and in 2006 a medium wetoccurred in rangelands of Ilam Province. NDVI value variations have as well confirmed it. Theresults showed that NDVI and life form (annual forb and annual grass) has the highest percentage ofcorrelation. Also examining of result showed that most correlation of SPI and NDVI was in 3 and 6-months intervals. Evaluation of regression models performance in range types described thatmodels in 3 and 6- months intervals was suitable for monitoring drought. The result of regressionconfirmed that NDVI was an appropriate index for monitoring and assessment of drought.
samaneh Mohammadi Moghaddam; Abolfazl Mosaedi; Mohammad Jankju; Mansour Mesdaghi
Abstract
Although precipitation is the most important factor which effects rangeland production, but there is little information on the relationship between production and the interactions of climatic factors and specially drought indices. .In this research, the relation between production and climatic ...
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Although precipitation is the most important factor which effects rangeland production, but there is little information on the relationship between production and the interactions of climatic factors and specially drought indices. .In this research, the relation between production and climatic factors of rainfall, temperature, evapo- transpiration, and as well as drought indices of Standardized Precipitation Index )SPI) and Reconnaissance Drought Index (RDI) were investigated in Noudoshan Rangelands.Then the data with 33 variables were generated for different time periods of one to four months based the years of available production data. PCA was employed to decrease the number of variable and based on further component analysis, some variable were selected. To find the relation between production and climatic factors, regression analysis was used. Finally, the model with least IPE was selected as preferred model. By comparison equations based on rainfall, temperature, evapo- transpiration, and drought indices, the model resulted from RDI, selected as preferred range production estimator (R=0.969, MARE=0.111).
Maryam Azarakhshi; Behnoush Farokhzadeh; Mohammad Mahdavi; Hossein Arzani; Hassan Ahmadi
Abstract
Iran is located in dry belt of the earth and always involved with drought in different sections. Drought has already caused many losses to natural plant cover, agriculture and human society. For drought monitoring, we can use some drought indecies. In this research, the Standard Index of Annual Precipitation)SIAP),Sandardized ...
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Iran is located in dry belt of the earth and always involved with drought in different sections. Drought has already caused many losses to natural plant cover, agriculture and human society. For drought monitoring, we can use some drought indecies. In this research, the Standard Index of Annual Precipitation)SIAP),Sandardized Precipitation Index (SPI) and Palmer Drought Severity Index (PDSI) were used for assessment of drought effects on rangeland plant production. The research area is located in Qom province that contains eight rangeland sites. Plant production and soil factors were measured in rangeland readiness period from 1997-1998 to 2005-2006 annualy. Regression techniques were used between drought indices and total production and also production of different vegetation forms in seven time scales (early March to late July (growth season) and early February to late July (growth season and the previous month), March to June, March to May, March to April and March (start of growth season). The best drought index was then selected based on the highest correlation coefficient and lowest standard error. The result showed that the best drought indices in Qom rangelands are SPI-3, PDSI, SPI-24 and SPI-6, respectively. Also the most significant time step was resulted growth season and specially early stage of growth season.
S. Saadati; S. Soltani; S. eslamian
Volume 62, Issue 2 , October 2009, , Pages 257-270
Abstract
Drought is universal phenomenon that can occur everywhere and can cause harmful impacts on human beings and natural ecosystems. Thus, it is very important to study drought character ristics part of for water resources management. In this study, the Standardized Precipitation Index (SPI) is used for drought ...
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Drought is universal phenomenon that can occur everywhere and can cause harmful impacts on human beings and natural ecosystems. Thus, it is very important to study drought character ristics part of for water resources management. In this study, the Standardized Precipitation Index (SPI) is used for drought frequency analysis in Isfahan province. After collecting the precipitation data in the province stations and removing those stations with incomplete data, frequency analysis of drought was carried out by 12-month SPI time series scale end of March. Then, the maps of drought return periods were prepared and analyzed by SURFER software. These maps show that moderate and severe drought with long return period mainly in the west the province and extreme drought events in the east and north east of the province with short return periods which indicate high sensitivity and the necessity for suitable managing programs to deal with the problem of drought.
