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The variations in vegetation coverage (defined as the area with Normalised Difference Vegetation Index (NDVI) > 0.2) and atmospheric patterns occurring during various vegetation seasons in the Kabul River Basin (KRB) in Afghanistan during 2001–2019 were analyzed. The analysis was done based on the NDVI, land surface temperature (LST), precipitation images from the remote sensing data, and geopotential height and temperature at 500 hPa from the retrospective datasets. The results revealed that the vegetation dynamics in KRB are impacted by both precipitation and LST. In the winter season, the LST has a more substantial role in shaping the vegetation dynamics than precipitation, while it is on contrary during the summer season. Cluster analysis showed that the four atmospheric patterns (e.g., Sub-Tropical High Pressure (STHP), Western European ridge-the Eastern Mediterranean and the Black Sea trough, Caspian Sea ridge (CSR), and the Mediterranean Sea trough-Central to Eastern Iran trough) can be identified and connected with the periods with the highest and the lowest vegetation coverage (VC) anomalies in the study area. The CSR and the Mediterranean Sea trough-the Central to Eastern Iran trough are the patterns responsible for the most positive VC anomalies. At the same time, the STHP and Western Europe ridge-the Eastern Mediterranean and the Black Sea trough are responsible for the most negative VC anomalies. As the atmospheric patterns have a significant role in shaping the vegetation status, a quick alert system to prevent agricultural areas from water or temperature stresses can be developed based on observations of them. [ABSTRACT FROM AUTHOR]

Drought has severe impacts on human society and ecosystems. In this study, we used data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) sensors to examine the drought effects on vegetation in Afghanistan from 2001 to 2018. The MODIS data included the 16-day 250-m composites of the Normalized Difference Vegetation Index (NDVI) and the Vegetation Condition Index (VCI) with Land Surface Temperature (LST) images with 1 km resolution. The TRMM data were monthly rainfalls with 0.1-degree resolution. The relationship between drought and index-defined vegetation variation was examined by using time series, regression analysis, and anomaly calculation. The results showed that the vegetation coverage for the whole country, reaching the lowest levels of 6.2% and 5.5% were observed in drought years 2001 and 2008, respectively. However, there is a huge inter-regional variation in vegetation coverage in the study period with a significant rising trend in Helmand Watershed with R = 0.66 (p value = 0.05). Based on VCI for the same two years (2001 and 2008), 84% and 72% of the country were subject to drought conditions, respectively. Coherently, TRMM data confirm that 2001 and 2008 were the least rainfall years of 108 and 251 mm, respectively. On the other hand, years 2009 and 2010 were registered with the largest vegetation coverage of 16.3% mainly due to lower annual LST than average LST of 14 degrees and partially due to their slightly higher annual rainfalls of 378 and 425 mm, respectively, than the historical average of 327 mm. Based on the derived VCI, 28% and 21% of the study area experienced drought conditions in 2009 and 2010, respectively. It is also found that correlations are relatively high between NDVI and VCI (r = 0.77, p = 0.0002), but slightly lower between NDVI and precipitation (r = 0.51, p = 0.03). In addition, LST played a key role in influencing the value of NDVI. However, both LST and precipitation must be considered together in order to properly capture the correlation between drought and NDVI. [ABSTRACT FROM AUTHOR]