Major ion chemistry of Renuka Lake and weathering processes, Sirmaur District, Himachal Pradesh, India

Renuka Lake in the Lesser Himalaya, Himachal Pradesh is in a valley surrounded by mountains comprised of highly crumpled, shattered, crushed, folded and dislocated rocks consisting of carbonaceous shales-slates often pyrite-ferrous, limestone, quartzites, boulder beds, etc. A detailed and systematic study of the major ion chemistry of the lake, clay mineral composition of the bed and core sediments and the Pb²¹⁰ isotope estimation in the latter was conducted. The chemistry is dominated by carbonate weathering and (Ca + Mg) and (HCO₃ + SO₄) accounts for about 90% of the cations and anions. The SO₄ content is almost the same as the HCO₃. The low contribution of (Na + K) to the total cations and the (Ca + Mg) and HCO₃ data tends to indicate that silicate weathering has not been the potential source of major ions to the lake waters. This difference may be related to the increasing susceptibility to weathering of carbonate over silicate rocks exposed in the catchment and also seepage of water at the bottom. The high sulphate content in waters is derived from dissolution of pyrite-ferrous reduced black shales, which constitute a significant lithology in the catchment. The chemical index of alteration (CIA) value in core sediments is on an average 76, which is comparable with average shale (70-75) and the rate of sedimentation 3.3 mm/year based on measurement of Pb²¹⁰, indicating a fairly high weathering rate in the catchment. Illite is the dominant clay mineral (52-90%) in the bed and core sediments, chlorite constitutes 7-48% and the kaolinite-chlorite mixed silicate layer is l-2%. This is consistent with the shale-slate, sandstone lithology in the valley.     

Rainfall erosivity and erosivity density in Eastern Ghats Highland of east India

The rainfall erosivity (R-factor in USLE) is the long-term average of the sum of the product of rainfall kinetic energy and its maximum 30-min intensity. Therefore, at most 30-min time intervals pluviograph records are required to calculate R-factor. But, such high-resolution data are scarce in many parts of the world and require lengthy processing period. In this study, R-factor was correlated with daily, monthly and annual rainfall, and its spatial variability in Eastern Ghats Highland of east India was mapped. The result showed that power regression models predicted satisfactorily the daily, monthly and annual R-factor, of which annual R-factor model performed best (model efficiency 0.93). Mean monsoon season R-factor was 15.6 and 10.0 times higher than the pre- and post-monsoon season R-factor, and thus remained highly critical with respect to erosion. Annual R-factor values ranged from 3040 to 10,127 MJ mm ha^?1 h^?1 year^?1, with standard deviation of 1981 MJ mm ha^?1 h^?1 year^?1. Rainfall intensity was positively correlated with erosivity density, and numerical value of rainfall intensity was almost double of the erosivity density value. The combination of rainfall and erosivity density was used to identify flood, erosion and landslide-prone areas. The developed iso-erosivity, erosivity density and risk maps can be opted as a tool for policy makers to take suitable measures against natural hazards in Eastern Ghats Highland of east India and elsewhere with similar rainfall characteristics.

     

Winter fog over the Indo-Gangetic Plains: mapping and modelling using remote sensing and GIS

Almost every year in the winter months (December–February), the vast Indo-Gangetic Plain south of the Himalaya is affected by dense fog. This fog is considered as radiational fog, and sometime it becomes smog (when it mixes with smoke). The typical meteorological, topographic and increasing pollution conditions over the Indo-Gangetic Plain are perhaps the common contributing factors for fog formation. In the present study, the North Indian fog has been successfully mapped and analysed using NOAA-AVHRR satellite data. In the winter seasons of 2005–06, 2006–07 and 2007–08, the fog-affected area has been found to cover about 575,800 km², 594,100 km² and 478,000 km², respectively. Less fog in 2007–08 may be the consequence of high fluctuations in the meteorological parameters like temperature, relative humidity and wind speed as related to the prevailing synoptic regime for that season. The dissipation and migration pattern of fog in the study area has also been interpreted on the basis of the analysis of both meteorological and satellite data. Further analysis of the fog-affected area allowed identifying more fog-prone regions. Analysis of past fog-affected days and corresponding meteorological conditions enabled us to identify favourable conditions for fog formation viz. air temperature 3–13°C, relative humidity >87%, wind speed <2 m/s and elevation <300 m. Based on the observations of past fog formation and corresponding governing parameters, fog for few selected days could be predicted in hind-sight and later verified with NOAA images.     

Weathering potential index for rocks based on density and porosity measurements

Rock samples belonging to ten lithological types under different stages of weathering, were collected from different stratigraphical horizons at Bhagalpur. Their densities and porosities were determined experimentally and the data obtained were fitted empirically in a linear equation for each lithological type. The slopes of the curves, which were negative in each case, showed that the increase in porosity for the same decrease in density were in the order, white sandstone > ferruginous sandstone > white claystone > porphyritic gneiss > quartzite > pegmatite > amphibolite ≅ biotite gnejss > basalt ≅ dolerite. A new weathering potential index based on the density-porosity data was proposed and the values for a specific stage of weathering for all the lithological types studied fall within the same range.