Estimation of Above Ground Biomass for Central Indian Deciduous Forests Using ALOS PALSAR L-Band Data

Reliable and accurate estimates of tropical forest above ground biomass (AGB) are important to reduce uncertainties in carbon budgeting. In the present study we estimated AGB of central Indian deciduous forests of Madhya Pradesh (M.P.) state, India, using Advanced Land Observing Satellite – Phased Array type L-band Synthetic Aperture Radar (ALOS-PALSAR) L-band data of year 2010 in conjunction with field based AGB estimates using empirical models. Digital numbers of gridded 1?×?1° dual polarization (HH & HV) PALSAR mosaics for the study area were converted to normalized radar cross section (sigma naught - σ⁰). A total of 415 sampling plots (0.1 ha) data collected over the study area during 2009–10 was used in the present study. Plot-level AGB estimates using volume equations representative to the study area were computed using field inventory data. The plot-level AGB estimates were empirically modeled with the PALSAR backscatter information in HH, HV and their ratios from different forest types of the study area. The HV backscatter information showed better relation with field based AGB estimates with a coefficient of determination (R²) of 0.509 which was used to estimate spatial AGB of the study area. Results suggested a total AGB of 367.4 Mt for forests of M.P. state. Further, validation of the model was carried out using observed vs. predicted AGB estimates, which suggested a root mean square error (RMSE) of ±19.32 t/ha. The model reported robust and defensible relation for observed vs. predicted AGB values of the study area.     

Impact of satellite observed microwave SST on the simulation of tropical cyclones

The impact of realistic representation of sea surface temperature (SST) on the numerical simulation of track and intensity of tropical cyclones formed over the north Indian Ocean is studied using the Weather Research and Forecast (WRF) model. We have selected two intense tropical cyclones formed over the Bay of Bengal for studying the SST impact. Two different sets of SSTs were used in this study: one from TRMM Microwave Imager (TMI) satellite and other is the weekly averaged Reynold’s SST analysis from National Center for Environmental Prediction (NCEP). WRF simulations were conducted using the Reynold’s and TMI SST as model boundary condition for the two cyclone cases selected. The TMI SST which has a better temporal and spatial resolution showed sharper gradient when compared to the Reynold’s SST. The use of TMI SST improved the WRF cyclone intensity prediction when compared to that using Reynold’s SST for both the cases studied. The improvements in intensity were mainly due to the improved prediction of surface latent and sensible heat fluxes. The use of TMI SST in place of Reynold’s SST improved cyclone track prediction for Orissa super cyclone but slightly degraded track prediction for cyclone Mala. The present modeling study supports the well established notion that the horizontal SST gradient is one of the major driving forces for the intensification and movement of tropical cyclones over the Indian Ocean.     

Investigation on spectral character of ELF electromagnetic radiations during Leonid 2009 meteor shower

The problem of solitary electron acoustic (EA) wave propagation in a plasma with nonthermal hot electrons featuring the Tsallis distribution is addressed. A physically meaningful nonextensive nonthermal velocity distribution is outlined. It is shown that the effect of the nonthermal electron nonextensivity on EA waves can be quite important. Interestingly, we found that the phase speed of the linear EA mode increases as the entropic index q decreases. This enhancement is weak for q>1, and significant for q<1. For a given nonthermal state, the minimum value of the allowable Mach numbers is lowered as the nonextensive nature of the electrons becomes important. This critical limit is shifted towards higher values as the nonthermal character of the plasma is increased. Moreover, our plasma model supports rarefactive EA solitary waves the main quantities of which depend sensitively on q. This dependency (for q>1) becomes less noticeable as the nonthermal parameter decreases. Nevertheless, decreasing α yields for q<0 a different result, a trend which may be attributed to the functional form of the nonthermal nonextensive distribution. Our study (which is not aimed at putting the ad hoc Cairns distribution onto a more rigorous foundation) suggests that a background electron nonextensivity may influence the EA solitons.     

Evaluating the impact of artificial groundwater recharge structures using geo-spatial techniques in the hard-rock terrain of Rajasthan,India

Groundwater levels in hard-rock areas in India have shown very large declines in the recent past. The situation is becoming more critical due to a paucity of rainfall, limited surface water resources and an increasing pattern of groundwater extraction in these areas. Consequently, the Ground Water Department with the aid of World Bank has implemented the water structuring programme to mitigate groundwater scarcity and to develop a viable solution for sustainable development in the region. The present study has been undertaken to assess the impact of artificial groundwater recharge structures in the hard-rock area of Rajasthan, India. In this study groundwater level data (pre-monsoon and post-monsoon) of 85 dug-wells are used, spread over an area of 413.59 km². The weathered and fractured gneissic basement rocks act as major aquifer in the area. Spatial maps for pre- and post-monsoon groundwater levels were prepared using the kriging interpolation technique with best fitted semi-variogram models (Spherical, Exponential and Gaussian). The groundwater recharge is calculated spatially using the water level fluctuation method. The entire study period (2004–2011) is divided into pre- (2004–2008) and post-intervention (2009–2011) periods. Based on the identical nature of total monsoon rainfall, two combinations of average (2007 and 2009) and more than average (2006 and 2010) rainfall years are selected from the pre- and post-intervention periods for further comparisons. All of the water harvesting structures are grouped into the following categories: as anicuts (masonry overflow structure); percolation tanks; subsurface barriers; and renovation of earthen ponds/nadis. A buffer of 100 m around the intervention site is taken for assessing the influence of these structures on groundwater recharge. The relationship between the monsoon rainfall and groundwater recharge is fitted by power and exponential functions for the periods of 2004–2008 and 2008–2011 with R ² values of 0.95 and 0.98, respectively. The average groundwater recharge is found to be 18% of total monsoon rainfall prior to intervention and it became 28% during the post-intervention period. About 70.9% (293.43 km²) of the area during average rainfall and more than 95% (396.26 km²) of the area during above-average rainfalls show an increase in groundwater recharge after construction of water harvesting structures. The groundwater recharge pattern indicates a positive impact within the vicinity of intervention sites during both average and above-average rainfall. The anicuts are found to be the most effective recharge structures during periods of above-average rainfall, while subsurface barriers are responded well during average rainfall periods. In the hard-rock terrain, water harvesting structures produce significant increases in groundwater recharge. The geo-spatial techniques that are used are effective for evaluating the response of different artificial groundwater recharge techniques.     

Cryptosporidium Oocysts in Drinking Water Supply of Chennai City,Southern India

Cryptosporidium is an enteric parasitic protozoan capable of causing chronic diarrhea. One of the most common modes of transmission is through faeces‐contaminated water. This study determines the distribution of Cryptosporidium oocysts for the first time in Chennai City's drinking water supply. 199 drinking water samples were collected from ten zones of the city. In the water samples Cryptosporidium, a common pathogenic protozoan of the gastrointestinal tract, has been analyzed physico chemically as well as microbiologically for heterotrophic organisms and total coliforms (TC). The studies revealed that three zones of the city were highly contaminated with coliforms and parasitic protozoa. A statistical analysis was done to find any correlation between heterotrophic organisms, total coliforms, and oocysts. Even though a positive correlation exists between oocysts and bacteriological parameters, a regression equation shows that heterotrophic plate count (HPC) and total coliforms were only 20% responsible for the presence of oocysts. The level of Cryptosporidium oocysts isolated from the water samples may present a public health hazard although no major outbreaks have so far been reported in Chennai City. Routine surveillance of water quality throughout the city is needed to curb the pollutants.     

Sensitivity of Mesoscale Model Forecast During a Satellite Launch to Different Cumulus Parameterization Schemes in MM5

The identification of the model discrepancy and skill is crucial when a forecast is issued. The characterization of the model errors for different cumulus parameterization schemes (CPSs) provides more confidence on the model outputs and qualifies which CPSs are to be used for better forecasts. Cases of good/bad skill scores can be isolated and clustered into weather systems to identify the atmospheric structures that cause difficulties to the forecasts. The objective of this work is to study the sensitivity of weather forecast, produced using the PSU-NCAR Mesoscale Model version 5 (MM5) during the launch of an Indian satellite on 5th May, 2005, to the way in which convective processes are parameterized in the model. The real-time MM5 simulations were made for providing the weather conditions near the launch station Sriharikota (SHAR). A total of 10 simulations (each of 48 h) for the period 25th April to 04th May, 2005 over the Indian region and surrounding oceans were made using different CPSs. The 24 h and 48 h model predicted wind, temperature and moisture fields for different CPSs, namely the Kuo, Grell, Kain-Fritsch and Betts-Miller, are statistically evaluated by calculating parameters such as mean bias, root-mean-squares error (RMSE), and correlation coefficients by comparison with radiosonde observation. The performance of the different CPSs, in simulating the area of rainfall is evaluated by calculating bias scores (BSs) and equitable threat scores (ETSs). In order to compute BSs and ETSs the model predicted rainfall is compared with Tropical Rainfall Measuring Mission (TRMM) observed rainfall. It was observed that model simulated wind and temperature fields by all the CPSs are in reasonable agreement with that of radiosonde observation. The RMSE of wind speed, temperature and relative humidity do not show significant differences among the four CPSs. Temperature and relative humidity were overestimated by all the CPSs, while wind speed is underestimated, except in the upper levels. The model predicted moisture fields by all CPSs show substantial disagreement when compared with observation. Grell scheme outperforms the other CPSs in simulating wind speed, temperature and relative humidity, particularly in the upper levels, which implies that representing entrainment/detrainment in the cloud column may not necessarily be a beneficial assumption in tropical atmospheres. It is observed that MM5 overestimates the area of light precipitation, while the area of heavy precipitation is underestimated. The least predictive skill shown by Kuo for light and moderate precipitation asserts that this scheme is more suitable for larger grid scale (>30 km). In the predictive skill for the area of light precipitation the Betts-Miller scheme has a clear edge over the other CPSs. The evaluation of the MM5 model for different CPSs conducted during this study is only for a particular synoptic situation. More detailed studies however, are required to assess the forecast skill of the CPSs for different synoptic situations.     

A method of obtaining a velocity-depth envelope from wide-angle seismic data

Summary. Due to the non-uniqueness of traveltime inversion of seismic data, it is more appropriate to determine a velocity-depth ( v-z ) envelope, rather than just a v-z function. Several methods of obtaining a v-z envelope by extremal inversion have been proposed, all of which invert the data primarily from either x-p , or T-p , or both domains. These extremal inversion methods may be divided into two groups: linear extremal and non-linear extremal. There is some debate whether the linearized perturbation techniques should be applied to the inherently non-linear problem of traveltime inversion. We have obtained a v-z envelope by extremal inversion in T-p with the constraint that the inversion paths also satisfy x-p observations. Thus we use data jointly in r-p and x-p , and yet avoid the linearity assumptions.
This joint, non-linear extremal inversion method has been applied to obtain a v-z envelope down to a depth of about 30 km in the Baltimore Canyon trough using x-t data from an Expanding Spread Profile acquired during the LASE project. We have found that the area enclosed by the v-z envelope is reduced by about 15 per cent using x-p control on the T-p inversion paths, compared to the inversion without x-p control.     

Theoretical analysis of telluric anomaly of a basin structure

The solution of a boundary value problem modelling a two-dimensional basin structure has been obtained by using the Schwartz-Christoffel conformal transformation technique and numerical methods of solving non-linear differential equations. Utilizing this solution, the telluric field and its first horizontal derivative have been theoretically computed for field directions perpendicular to the strike of the structure. On the basis of systematic analysis of a large number of such anomaly curves, two nomograms have been prepared to be used in the quantitative interpretation of telluric data. An interpretation procedure to evaluate the geometric parameters of the basin from the observed telluric data is outlined. This procedure is demonstrated on an actual field example.     

A hierarchical model for estimating methane emission from wetlands using MODIS data and ARIMA modeling

A three-step hierarchical Semi Automated Empirical Methane Emission Model (SEMEM) has been used to estimate methane emission from wetlands and waterlogged areas in India using Moderate Resolution Imagine Spectroradiometer (MODIS) sensor data onboard Terra satellite. Wetland Surface Temperature (WST), methane emission fluxes and wetland extent have been incorporated as parameters in order to model the methane emission. Analysis of monthly MODIS data covering the whole of India from November 2004 to April 2006 was carried out and monthly methane emissions have been estimated. Interpolation techniques were adopted to fill the data gaps due to cloudy conditions during the monsoon period. AutoRegressive Integrated Moving Average (ARIMA) model has been fitted to estimate the emitted methane for the months of May 2006 to August 2006 using SPSS software.