Erratum to: Climate change projections over India by a downscaling approach using PRECIS

The author “Bhaski Bhaskaran” and his affiliation “Fujitsu Laboratory of Europe, Middlesex, UK” should be replaced by “Balakrishnan Bhaskaran”, “Fujitsu Laboratories of Europe Limited, Hayes Park, Middlesex, UK”, respectively.The corrected name and affiliation are shown in this erratum.     

Proximal Remote Sensing of Herbicide and Drought Stress in Field Grown Colocasia and Sweet Potato Plants by Sunlight-Induced Chlorophyll Fluorescence Imaging

Chlorophyll fluorescence is an indicator of plant photosynthetic activity and has been used to monitor the health status of vegetation. Several studies have exploited the application of red/far-red chlorophyll fluorescence ratio in detecting the impact of various types of stresses in plants. Recently, sunlight-induced chlorophyll fluorescence imaging has been used to detect and discriminate different stages of mosaic virus infection in potted cassava plants with a multi-spectral imaging system (MSIS). In this study, the MSIS is used to investigate the impact of drought and herbicide stress in field grown crop plants. Towards this control and treatment groups of colocasia and sweet potato plants were grown in laterite soil beds and the reflectance images of these crop plants were recorded up to 14-days of treatment at the Fraunhofer lines of O₂ B at 687 nm and O₂ A at 759.5 nm and the off-lines at 684 and 757.5 nm. The recorded images were analyzed using the Fraunhofer Line Discrimination technique to extract the sunlight-induced chlorophyll fluorescence component from the reflectance images of the plant leaves. As compared to the control group, the chlorophyll fluorescence image ratio (F ₆₈₇/F ₇₆₀) in the treatment groups of both the plant varieties shows an increasing trend with increase in the extent of stress. Further, the F ₆₈₇/F ₇₆₀ ratio was found to correlate with the net photosynthetic rate (Pn) and stomatal conductance (g_s) of leaves. The correlation coefficient (R ²) for the relationship of F ₆₈₇/F ₇₆₀ ratio with Pn were found to be 0.78, 0.79 and 0.78, respectively for the control, herbicide treated and drought treated colocasia plants, while these were 0.77, 0.86 and 0.88, respectively for sweet potato plants. The results presented show the potential of proximal remote sensing and the application F ₆₈₇/F ₇₆₀ fluorescence image ratio for effective monitoring of stress-induced changes in field grown plants.     

Planetary waves in the mesosphere lower thermosphere during stratospheric sudden warming: observations using a network of meteor radars from high to equatorial latitudes

Climate Dynamics - In the present communication, characteristics of mean winds and planetary waves in the mesosphere lower thermosphere (MLT) region during sudden stratospheric warming (SSW) events...     

http://www.sciencedirect.com/science/article/pii/S1674987111001034

A comprehensive methodology that integrates Revised Universal Soil Loss Equation（RUSLE） model and Geographic Information System（GIS） techniques was adopted to determine the soil erosion vulnerability of a forested mountainous sub-watershed in Kerala,India.The spatial pattern of annual soil erosion rate was obtained by integrating geo-environmental variables in a raster based GIS method.GIS data layers including,rainfall erosivity（R）,soil erodability（K）,slope length and steepness（LS）,cover management （C） and conservation practice（P） factors were computed to determine their effects on average annual soil loss in the area.The resultant map of annual soil erosion shows a maximum soil loss of 17.73 t h^-1 y^-1 with a close relation to grass land areas,degraded forests and deciduous forests on the steep side-slopes（with high LS ）.The spatial erosion maps generated with RUSLE method and GIS can serve as effective inputs in deriving strategies for land planning and management in the environmentally sensitive mountainous areas.     

Terrain evaluation through the assessment of geomorphometric parameters using DEM and GIS: case study of two major sub-watersheds in Attapady, South India

Spatial pattern of geomorphometric parameters of two sub-watersheds in the Attapady valley, Kerala, is evaluated using the Geographical Information System. Both the aspatial and spatial morphometric and hypsometric measurements of the sub-watershed are compared. The analysis of geomorphometric parameters coupled with DEM and GIS suggests that the two sub-watersheds are structurally complex with high relief and the denuded hills are undergoing severe soil erosion. Terrain analysis enables evaluation of landform changes in the two sub-watersheds which indicate differences in the denudational history of adjoining watersheds. It is demonstrated that the domainal variations in the lithology and structural complexity are reflected in differences in the denudational history which in turn is manifested in the geomorphic parameters. The study also helps in developing functional relationships between geomorphometric parameters and hydrological variables.     

Observations of peculiar sporadic sodium structures and their relation with wind variations

Resonance lidar observations of sodium density in the upper mesosphere region over Gadanki (13.5°N, 79.2°E) rarely show complex structures with rapid enhancements of sodium density, completely different from normal sporadic sodium structures. The hourly averaged meteor radar zonal winds over Trivandrum (8.5°N, 76.5°E) show an eastward shear with altitude during the nights, when these events are formed. As suggested by Kane et al. [2001. Joint observations of sodium enhancements and field-aligned ionospheric irregularities. Geophysical Research Letters 28, 1375–1378], our observations show that the complex structures may be formed due to Kelvin–Helmholtz instability, which can occur in the region of strong wind shear.     

Identification of Artificial Recharge Sites for Noyyal River Basin Using GIS and Remote Sensing

The water is a nature’s valuable gift to all life forms. Water quality and quantity plays a major role for the growth and development of community. Both natural and human factors influence the quality and quantity of water source. Depending upon the quality and quantity of groundwater it can be used for various purposes, such as drinking, agricultural and industrial. Due to revolution in industries and various anthropogenic sources in the past decades, groundwater has been polluted and depleted. Remote sensing and Geographical Information System (GIS) has become one of the leading tools in the field of hydrogeological science, which helps in assessing, monitoring and conserving groundwater resources. GIS technology provides suitable alternatives for efficient management of large and complex databases. In recent years, the increasing use of satellite remote sensing data has made it easier to define the spatial distribution of different groundwater prospect classes on the basis of geomorphology and other associated parameters. Analysis of remotely sensed data along with Survey of India(SOI) topographical sheets and collateral information with necessary field checks helps in generating the base line information for artificial recharge. The artificial recharge sites were identified by integrating thematic maps of geology, geomorphology, slope, drainage density and lineament density of the study area. The study focuses on the development of remote sensing and GIS based analysis and methodology for identifying artificial recharge studies in Noyyal river basin.     

Climate change projections over India by a downscaling approach using PRECIS

This study presents a comprehensive assessment of the possible regional climate change over India by using Providing REgional Climates for Impacts Studies (PRECIS), a regional climate model (RCM) developed by Met Office Hadley Centre in the United Kingdom. The lateral boundary data for the simulations were taken from a sub-set of six members sampled from the Hadley Centre’s 17- member Quantified Uncertainty in Model Projections (QUMP) perturbed physics ensemble. The model was run with 25 km × 25 km resolution from the global climate model (GCM) - HadCM3Q at the emission rate of special report on emission scenarios (SRES) A1B scenarios. Based on the model performance, six member ensembles running over a period of 1970-2100 in each experiment were utilized to predict possible range of variations in the future projections for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095) with respect to the baseline period (1975-2005). The analyses concentrated on maximum temperature, minimum temperature and rainfall over the region. For the whole India, the projections of maximum temperature from all the six models showed an increase within the range 2.5°C to 4.4°C by end of the century with respect to the present day climate simulations. The annual rainfall projections from all the six models indicated a general increase in rainfall being within the range 15-24%. Mann-Kendall trend test was run on time series data of temperatures and rainfall for the whole India and the results from some of the ensemble members indicated significant increasing trends. Such high resolution climate change information may be useful for the researchers to study the future impacts of climate change in terms of extreme events like floods and droughts and formulate various adaptation strategies for the society to cope with future climate change.     

Probabilistic analysis of groundwater and radionuclide transport model from near surface disposal facilities

As per the regulatory requirements controlling the disposal of radioactive waste, the performance of waste disposal facilities needs to be assessed quantitatively using predictive models. This estimates the potential impact of disposal on the environment and public health. Near Surface Disposal Facilities (NSDFs), constructed to contain the low level radioactive waste are considered to model the radionuclide migration from the system to the geo-sphere. The radiation dose experienced by an individual through drinking water pathway is the endpoint of assessment of the model. A three dimensional groundwater contaminant transport model with a decaying source is modelled numerically to determine the radiation dose for short-lived and long-lived radionuclides. The consideration of uncertainties constitutes an intrinsic part of modelling. The uncertain input parameters include porosity, longitudinal dispersivity, transverse dispersivity, diffusion coefficient and distribution coefficient. The uncertainty propagation and quantification is carried out using collocation based stochastic response surface method (CSRSM). To run the simulations for the huge set of input, a code is developed using built-in python interface in the numerical model. The results are processed further to obtain the sensitive parameters affecting the output concentrations. Further, the probability of radiation dose exceeding permissible value is estimated by subset simulation.