• Jagdish Chandra Kuniyal

      Articles written in Journal of Earth System Science

    • Seasonal variability in aerosol optical and physical characteristics estimated using the application of the Ängström formula over Mohal in the northwestern Himalaya, India

      Raj Paul Guleria Jagdish Chandra Kuniyal Nand Lal Sharma Pitamber Prasad Dhyani

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      Investigations of aerosol optical and physical characteristics using the application of Ängström formula and second order polynomial fit were carried out from April 2006 to March 2009 at Mohal in the Kullu valley. The measurements of spectral aerosol optical depths (AODs) were conducted using multiwavelength radiometer (MWR). The AOD at 0.5 𝜇 m wavelength on daily basis (mean ± standard deviation) for the entire three-year study period is obtained as 0.24 ± 0.08. Seasonal variations show the highest AOD at 0.5 𝜇 m wavelength with ∼0.34 ± 0.08 during pre-monsoon (April–July), followed by ∼0.26 ± 0.08 during monsoon (August–September), ∼0.21 ± 0.05 during post-monsoon (October–November) and ∼0.20 ± 0.07 during winter (December–March). The seasonal values indicate that the AOD at 0.5 𝜇 m wavelength is decreasing from pre-monsoon to winter with a notable reduction around 41%. The Ängström parameters using least square method is not found appropriate for size distribution particularly when coarse mode aerosols dominate. The coefficients of second order polynomial fit are more appropriate for the discrimination of aerosol size or irrespective to the dominance of either of the aerosols size. The difference in coefficient of polynomial fit is used to get confirmation on the dominant mode during different seasons. Study reveals that about 93%, 72% and 59% of AOD spectra are dominated by a wide range of fine mode fractions or mixture of modes during post-monsoon, winter and monsoon, respectively. On the other hand, during pre-monsoon, 72% of AOD spectra are found to be dominated by coarse mode aerosols.

    • Vulnerability assessment of forest ecosystems focusing on climate change, hazards and anthropogenic pressures in the cold desert of Kinnaur district, northwestern Indian Himalaya


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      Forest resources are the primary livelihood sources for native communities. These are rich in biodiversity, hence are accredited as the green pearl of the Himalayan region. This life-supporting system is under great biotic stress and has become vulnerable due to an ever-increasing anthropogenic pressure. This study, therefore, aims to identify critically assessing indicators, their role in forest degradation of Kinnaur district, Himachal Pradesh in terms of climate, hazards and anthropogenic activities using prioritisation matrix survey. Interview of the communities, direct field observation, secondary data sources, Global Positioning System (GPS) surveys, and Remote Sensing and Geographic Information System (RS${\And}$GIS) applications have been the major tools and techniques used in this study. The results showed that a total of 49.64 km$^2$ area is under stress and the forest ecosystem has become vulnerable due to landslides and soil erosion among forest and non-forest land use and land cover classes. Similarly, climatic variability was also found to be high in the study area. The construction of hydropower projects has caused rampant felling of large trees at both the dam and powerhouse sites leading to frequent landslides and soil erosion. Besides, the study area has been hit by earthquakes more than 28 times from 1964 to 2009 with a magnitude of >4.0 on the Richter scale. These incidences, directly or indirectly, have, therefore, an impact on forest vulnerability and biodiversity loss.


      $\bullet$ Forest resources are the major source of livelihood options to the local communities.

      $\bullet$ About 49.64 km2 area got affected and became vulnerable due to a variety of hazards.

      $\bullet$ HEPs construction caused large trees felled at dam site (Lamber) and powerhouse site (near Rispa).

      $\bullet$ Maximum temperature increased 0.05°, minimum 0.07°C year$^{−1}$ and precipitation 1.48 mm year$^{−1}$.

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