Some geothermal springs of Nepal

Almost all known thermal springs in Nepal are localized close to and south of either the Main central Thrust or the Main Boundary Fault, and therefore they fall broadly into two major groups. The results from four thermal springs — two from each group — are discussed here. The temperature of the spring water is up to 50°C above normal atmospheric temperature. The waters of almost all springs are alkaline. The dissolved silica content and atomic ratio of Na and K do not indicate any high subsurface temperature and therefore the thermal springs are considered to be of tectonic origin.     

Recession of samudra tapu glacier, chandra river basin, Himachal Pradesh

Himalayas possess one of the largest resources of snow, ice and glaciers that act as a huge freshwater reservoir. Monitoring the glaciers is important to assess the overall reservoir health of the Himalayas. Samudra Tapu is one of the largest glaciers in Chandra basin of district Lahaul and Spiti, Himachal Pradesh. Based on the field investigations and the remote sensing techniques. features such as accumulation area, ablation area snowline/equilibrium line, moraine-dammed lakes and permanent snowfields were mapped. The glacial terminus was identified using moraine-dammed lake, as lake is located at down streamside of the terminus. The total recession of glacier during the period of 38 years (1962–2000) is about 742 m with an average rate of 19.5 m/yr. In addition, glacial extent is reduced from 73 to 65 km² between 1962 and 2000. suggesting overall deglaciation of 11%. During field investigation. three stages of glaciation using terminal moraine were identified. These moraines were mapped by merging LISS-II1 and PAN data. At the peak of glaciation. the glacial terminus was extended 3.18 km downstream of terminus position in year 2000. Total area during peak of glaciation period has been observed to be 77.67 km², which is 12.67 km² higher than the present glacier extent.     

Stochastic modeling of length of day and universal time

We propose a general stochastic model for the UT1/LOD system and derive the corresponding Kalman filter model. This stochastic model consists of an arbitrary sum of continous time autoregressive moving average (ARMA) processes, each chosen to characterize a different frequency band. The transition matrix which corresponds to the overall system and the time-dependent process noise covariance matrix are derived.Based on the general formulation, several models for UT1 were derived from spectral analysis of the Space 92 UT1 series (Gross,1993). Using Space 92 as the reference series, the candidate models were compared based on their ability to predict UT1 and LOD up to 30 days in the absence of data. These candidate models were compared with the JPL operational Kalman Earth Orientation Filter (KEOF) which assumes a random walk model for LOD (Morabito et al.,1987). The results of the comparison revealed that autoregressive modeling the 40–50 day oscillation in the LOD reduces the LOD prediction error by 10prediction.     

Advances in atmospheric, hydrographic and vegetation remote sensing with lidar

Lidar has evolved as one of the powerful and versatile techinqne for atmospheric monitoring and geophysical and hydrographic studies from different observational platforom. This paper discusses the recent advances that have taken place in the lidar technology for rnulti-dimensional atmospheric, hydragraphic and vegetation monitoring together with the results of some specific atmospheric studies carried our for the past ten years using the lider systems built at the Indian Institute of Tropical Meteorotogy (IITm) Pune.     

A study on the sensitivity of the radar scattering coefficient to oceanic winds

Sensitivity of the radar scattering coefficient to the oceanic wind vector in the midangular range for frequencies from L- to Ku- band is studied. This is based on computations of scattering coefficient via the two-scale scattering theory employing a semi-empirical model for the ocean spectrum suggested by Fung and Lee and the slope distribution by Cox and Munk. Higher frequency and incident angles of over 45 degrees seem to yield better wind sensitivity.     

Bentonite as a Natural Adsorbent for the Sorption of Iron from the Ground Water Exploited from Aswan Area, Egypt

Sorption of dissolved Fe²⁺ on bentonite was studied using a batch technique. The distribution coefficient, K_d , was evaluated for a bentonite-iron system as a function of contact time, pH, sorbent and sorbate concentrations, and temperature. Sorption results were interpreted in terms of Freundlich's and Langmuir's equations. Thermodynamic parameters for the sorption system were determined at three temperatures: 298°, 308°, and 318°K. The values of ΔH°(-4.0 kjmol⁻¹) and ΔG°(-2.46 Kjmol⁻¹) at 298°K (25°C) suggest that sorption of iron on bentonite is an exothermic and a spontaneous process. The ΔG° value became less negative at higher temperatures and, therefore, less iron was sorbed at higher temperatures. The desorption studies with 0.01 M CaCl₂ and deionized water at iron loading on bentonite showed that more than 90 wt% of the iron is irreversibly sorbed, probably due to the fixation of the iron by isomorphous replacement in the crystal lattice of the sorbent.     

Assessment of glacier stored water in Karakoram Himalaya using satellite remote sensing and field investigation

Karakoram Himalaya(KH) has continental climatic conditions and possesses largest concentration of glaciers outside the polar regions. The melt water from these glaciers is a major contributor to the Indus river. In this study, various methods have been used to estimate the ice volume in the Karakoram Range of glaciers such as Coregistration of Optically Sensed Images and Correlation(COSI-Corr) method and Area-Volume relations. Landsat 8 satellite data has been used to generate the ice displacement, velocity and thickness map. Our study for 558 Karakoram glaciers revealed that the average ice thickness in Karakoram is 90 m. Ground Penetrating Radar(GPR) survey has been conducted in one of the KH glacier i.e. Saser La glacier and the collected GPR data is used for the validation of satellite derived thickness map. GPR measured glacier thickness values are found comparable with satellite estimated values with RMSE of 4.3 m. The total ice volume of the Karakoram glaciers is estimated to be 1607±19 km3(1473±17 Gt), which is equivalent to 1473±17 km3 of water equivalent. Present study also covers the analysis of glacier surface displacement, velocity and ice thickness values with reference to glacier mean slope.     

Stochastic modelling of relative water permeability in vegetative soils with implications on stability of bioengineered slope

Vegetation is known to influence the hydrological state variables, suction \( \left( \psi \right) \) and volumetric water content (\( \theta_{w} \)) of soil. In addition, vegetation induces heterogeneity in the soil porous structure and consequently the relative permeability (\( k_{r} \)) of water under unsaturated conditions. The indirect method of utilising the soil water characteristic curve (SWCC) is commonly adopted for the determination of \( k_{r} \). In such cases, it is essential to address the stochastic behaviour of SWCC, in order to conduct a robust analysis on the \( k_{r} \) of vegetative cover. The main aim of this study is to address the uncertainties associated with \( k_{r} \), using probabilistic analysis, for vegetative covers (i.e., grass and tree species) with bare cover as control treatment. We propose two approaches to accomplish the aforesaid objective. The univariate suction approach predicts the probability distribution functions of \( {\text{k}}_{\text{r}} \), on the basis of identified best probability distribution of suction. The bivariate suction and water content approach deals with the bivariate modelling of the water content and suction (SWCC), in order to capture the randomness in the permeability curves, due to presence of vegetation. For this purpose, the dependence structure of \( \psi \) and \( \theta_{w} \) is established via copula theory, and the \( k_{r} \) curves are predicted with respect to varying levels of \( \psi - \theta_{w} \) correlation. The results showed that the \( k_{r} \) of vegetative covers is substantially lower than that in bare covers. The reduction in \( k_{r} \) with drying is more in tree cover than grassed cover, since tree roots induce higher levels of suction. Moreover, the air entry value of the soil depends on the magnitude of \( \psi - \theta_{w} \) correlation, which in turn, is influenced by the type of vegetation in the soil. \( k_{r} \) is found to be highly uncertain in the desaturation zone of the relative permeability curve. The stochastic behaviour of \( k_{r} \) is found to be most significant in tree covers. Finally, a simplified case study is also presented in order to demonstrate the impact of the uncertainty in \( k_{r} \), on the stability of vegetates slopes. With an increment in the parameter \( \alpha \), factor of safety (FS) is found to decrease. The trend of FS is reverse of this with parameter \( n \). Overall FS is found to vary around 4–5%, for both bare and vegetative slopes.