Mahshid karimi; Kaka Shahedi; Tayebe Raziei; Mirhassan Miryaghoobzadeh
Abstract
Drought is one of the natural disasters that may occur in any climate. In recent decades, Iran has been affected by severe droughts and its harmful effects in various sectors, such as agriculture, environment and water resources of the country. Today, vegetation indices, which are obtained through remote ...
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Drought is one of the natural disasters that may occur in any climate. In recent decades, Iran has been affected by severe droughts and its harmful effects in various sectors, such as agriculture, environment and water resources of the country. Today, vegetation indices, which are obtained through remote sensing technology, are used to identify and analyze agricultural droughts. Accordingly, the aim of this study was to investigate the effectiveness of NDVI, EVI and VCI vegetation indices in agricultural drought identification and analysis in Karkheh basin. In order to calculate these indices, MODIS sensor Images (Terra satellite, MOD13A2 product) were used during the 2000-2017 statistical period. The accuracy of these profiles was evaluated with the ZSI index calculated at 11 meteorological stations located in Karkheh basin for the statistical period of 2000-2017. The results showed that the changes of NDVI, EVI and VCI in the studied stations were approximately the same during the statistical period. Based on NDVI, EVI and VCI values, the lowest and highest vegetation cover was observed in 2000, dehno station and 2001, helilan-seymareh station, respectively. The ZSI survey showed that most stations Faced with droughts from 2000 to 2008, and the most severe drought occurred in 2008, nazarabad station. Then, in order to validation of the results, the vegetation indices with ZSI index were evaluated. Pearson correlation between mean vegetation indices of NDVI, EVI and VCI with mean ZSI was 0.766, 0.725 and 0.776, respectively, and all vegetation indices with ZSI index are significant at 0.99% confidence level. As seen, according to the results, the ZSI index confirms the results of NDVI, EVI, and VCI. So, according to the results, there is no conformity of meteorological and agricultural droughts in all years, Therefore, in addition to other precipitation, climate variables should also be considered.
Zahra hemmati; Karim solaimani; Mir hasan Miryaghoubzadeh
Abstract
Takab watershed basin is one of the most important basins of Lake Urmia. The basin is quite hilly and mountainous, and the runoff from its snow melting is of substantial significance. Snow accumulation in winter is considered to be crucial in the spring of the following year, and the water from snow ...
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Takab watershed basin is one of the most important basins of Lake Urmia. The basin is quite hilly and mountainous, and the runoff from its snow melting is of substantial significance. Snow accumulation in winter is considered to be crucial in the spring of the following year, and the water from snow melting is especially important for water facilities in a way that it results in serious floods when the snow melts with warm spring rain. Therefore, the prediction of snow melting seems necessary. Furthermore, managing water resource and reservoirs as well as planning of rivers hydrology would not be possible without considering this factor. The SRM snow melt runoff model was used to simulate the flow considering the 83-84 water years. Furthermore, to test the validity of the model, the 84-85 water years was used. Due to the fact that the MODIS images have the appropriate time resolution, such images have been used to estimate the underlying snow area. Results of the study showed that the use of snow cover maps, derived from MODIS images, is useful in predicting the runoff of the basin. The findings also show that the model has the ability to simulate the snowmelt runoff. To evaluate the model, two indexes, namely, the coefficient of determination and volume difference were used which were obtained as 0.75 and 27.84%, respectively. The obtained values indicate that the model has high accuracy in estimating the runoff from snow melting in this basin and represents the applicability of the model to other basins in the region.
