چکیده:
The agricultural drought, severely affecting human life, occurs unpredictably at
different times with different intensities. The conventional methods for
assessing drought often relay on indices obtained using meteorological data,
but due to the low spatial coverage, incompleteness and inaccuracy of these
data, meteorological indices cannot be considered as a comprehensive method.
Therefore, it is suggested that remote sensing constitute more versatile
approach, as it allows to assess the drought using the adequate spatial and
temporal coverage for the study area. In the study, performed for the Panjshir
river basin in Afghanistan, the 2010-2019 period is used to evaluate vegetation
rate using NDVI data from MODIS. To calculate agricultural drought indices
(DSI, VCI and TCI), May and June were selected, as the peak vegetation time
occurs for these months. On the base of the remote sensing indicators it was
shown that during the study period the drought conditions were normal in the
region, except for 2011, 2017, and 2018, which were the driest years, and for
2019, which was the wettest year. Agricultural drought indices were compared
to SPI index calculated using winter and spring precipitation data recorded at
the meteorological stations. It was observed that the remote sensing indices
showed the highest correlation with data from Kabul meteorological station,
which is located at the same altitude and climate as the dense vegetation zone.
Furthermore, the comparison showed that the ground precipitation data is
characterized by higher amplitudes than the remote sensing data. From the
above it steams that the vegetation in the Panjshir basin is influenced by both
seasonal rainfall and rivers that continuously flood the area, The agricultural drought, severely affecting human life, occurs unpredictably at different times with different intensities. The conventional methods for assessing drought often relay on indices obtained using meteorological data, but due to the low spatial coverage, incompleteness and inaccuracy of these data, meteorological indices cannot be considered as a comprehensive method. Therefore, it is suggested that remote sensing constitute more versatile approach, as it allows to assess the drought using the adequate spatial and temporal coverage for the study area. In the study, performed for the Panjshir river basin in Afghanistan, the 2010-2019 period is used to evaluate vegetation rate using NDVI data from MODIS. To calculate agricultural drought indices (DSI, VCI and TCI), May and June were selected, as the peak vegetation time occurs for these months. On the base of the remote sensing indicators it was shown that during the study period the drought conditions were normal in the region, except for 2011, 2017, and 2018, which were the driest years, and for 2019, which was the wettest year. Agricultural drought indices were compared to SPI index calculated using winter and spring precipitation data recorded at the meteorological stations. It was observed that the remote sensing indices showed the highest correlation with data from Kabul meteorological station, which is located at the same altitude and climate as the dense vegetation zone. Furthermore, the comparison showed that the ground precipitation data is characterized by higher amplitudes than the remote sensing data. From the above it steams that the vegetation in the Panjshir basin is influenced by both seasonal rainfall and rivers that continuously flood the area.
خلاصه ماشینی:
It was observed that the remote sensing indices showed the highest correlation with data from Kabul meteorological station, which is located at the same altitude and climate as the dense vegetation zone.
The study concluded that DSI can be used for agricultural drought monitoring and can be used as an alternative index to estimate crop yield Normalized Difference Vegetation Index Moderate Resolution Imaging Spectroradiometer Advanced Very-High-Resolution Radiometer Drought Severity Index Evapotranspiration Tropical Rainfall Measuring Mission Agricultural Drought indices [%%ابتدای جدول%%drought index, used bands and indices, interval, Normal condition, severE drought, dense vEgetation NDVI, MODIS 1 and 2 bands, -1 to +1, Related to the area, -1, +1 DSI, NDVI and its long time mean, -1 to +1, 0, -1, +1 VCI, NDVI and its long-time min and max, 0 to 100%, 50%, 0%, 100% TCI, LST and its long-time min and max, 0 to 100%, 50%, 0%, 100% In Table 2 the drought classification based on the values of DSI and SPI indices is shown (Johnson et al.
The spatial and temporal development of vegetation density in the Panjshir River basin in 2019 Distribution of agricultural drought indices (DSI, VCI and TCI) Since the peak of vegetation coverage in the region of interest is seen in the remotely sensed data (NDVI) in May and June, thus DSI, VCI and TCI indicators were calculated for these months for each year of the study, from 2010 to 2019.