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Showing 2 results for Paimozd

R. Ziaee, M. Moghaddasi, S. Paimozd, M. H. Bagher,
Volume 22, Issue 4 (Winter 2019)
Abstract

Evaporation is one of the important components in water body’s management, leading to changes in the water level and water balance. Also, its accurate estimation is faced with certain difficulties and complexities. Because of the limitations of physical and empirical methods based on the meteorological data, remote sensing technology can be widely used for evaporation calculation due to its capabilities for spatial data estimation and minimization of the meteorological data application. Many models have been developed to estimate evapotranspiration using remote sensing technology. Regarding the use of these algorithms for estimating evaporation from water surface, a few studies have been done; however, there is yet no comparison between them to estimate evaporation from the water surface. For this purpose, in this study, the output from two models estimating spatially distributed evaporation of water surfaces from remotely sensed imagery is compared. In order to implement these models, Terra/MODIS Images for four months including June, July, August and September in of 2006, 2007, 2008 and 2009 were prepared. Comparisons were made using pan data from Urmia synoptic station. In general, there was a reasonable agreement between the evaporation outputs from both models versus a pan data observation. The statistical analysis also showed that the SEBS algorithm (by applying the salinity factor), despite being simple in its implementation, has higher accuracy than the SEBAL algorithm.

H. Babajafari, Sh. Paimozd, M. Moghaddasi, M. Hosseini Vardanjani,
Volume 26, Issue 3 (Fall 2022)
Abstract

Drought is one of the most complex natural disasters due to its slow onset and long-term impact. Today, the use of remote sensing techniques and satellite imagery has been considered a useful tool for monitoring agricultural drought. The objective of the present study was to evaluate spatial and temporal monitoring of agricultural drought in the lake Urmia catchment area with the ETDI drought index which is calculated from Nova satellite images based on actual evapotranspiration from the SEBS algorithm and compared with the ground index SPI. For this purpose, 248 AVHRR sensor images and NOAA satellites during the statistical period of 1998-2000 and 17 meteorological stations with a statistical period of 30 years were used to calculate the indicators. To determine agricultural lands, six thousand points were marked for different uses and their actual evapotranspiration was calculated using the SEBS algorithm. The results showed that with the onset of the drought period in 1998, the ETDI index indicated 9.4% in weak drought conditions in May and 90.6% in normal conditions. Over time, in June of 1998, the situation was different with 95% in a weak drought situation and 5% in a normal situation for the city of Tabriz. In July, the entire catchment area experiences a slight drought. Then, in August, 84% of the basin is in normal condition and 16% in Tabriz and Urmia are declared weak drought. It was also founded that the ETDI drought index due to the combination of visible and infrared bands and its combination with terrestrial data has a physical meaning and has high certainty and predicts drought faster and more accurately.


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