Hydrograph separation and precipitation source identification using stable water isotopes and conductivity: River Ganga at Himalayan foothills

The observed retreat of several Himalayan glaciers and snow packs is a cause of concern for the huge population in southern Asia that is dependent on the glacial‐fed rivers emanating from Himalayas. There is considerable uncertainty about how cryospheric recession in the Himalayan region will respond to climate change, and how the water resource availability will be affected. As a first step towards quantifying the contribution of glacier‐melt water, hydrograph separation of River Ganga at Rishikesh into its constituent components, namely (i) surface runoff, (ii) glacial ice‐melt and (iii) groundwater discharge has been done in this paper. A three‐component mixing model has been employed using the values of δ¹⁸O and electrical conductivity (EC) of the river water, and its constituents, to estimate the time‐varying relative fraction of each component. The relative fraction of the surface runoff peaks (70–90%) during winter, due to the near‐zero contribution of glacial ice‐melt, essentially represents the melting of surface snow from the catchment. The contribution of glacial ice‐melt to the stream discharge peaks during summer and monsoon reaches a maximum value of ～40% with an average of 32%. The fraction of groundwater discharge varies within a narrow range (15 ± 5%) throughout the year. On the basis of the variation in the d‐excess values of river water, it is also suggested that the snow‐melt and ice‐melt component has a significant fraction derived from winter precipitation with moisture source from mid‐latitude westerlies (also known as western disturbances). Copyright © 2010 John Wiley & Sons, Ltd.     

Location specific forecasting of maximum and minimum temperatures over India by using the statistical bias corrected output of global forecasting system

The output from Global Forecasting System (GFS) T574L64 operational at India Meteorological Department (IMD), New Delhi is used for obtaining location specific quantitative forecast of maximum and minimum temperatures over India in the medium range time scale. In this study, a statistical bias correction algorithm has been introduced to reduce the systematic bias in the 24–120 hour GFS model location specific forecast of maximum and minimum temperatures for 98 selected synoptic stations, representing different geographical regions of India. The statistical bias correction algorithm used for minimizing the bias of the next forecast is Decaying Weighted Mean (DWM), as it is suitable for small samples. The main objective of this study is to evaluate the skill of Direct Model Output (DMO) and Bias Corrected (BC) GFS for location specific forecast of maximum and minimum temperatures over India. The performance skill of 24–120 hour DMO and BC forecast of GFS model is evaluated for all the 98 synoptic stations during summer (May-August 2012) and winter (November 2012–February 2013) seasons using different statistical evaluation skill measures. The magnitude of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) for BC GFS forecast is lower than DMO during both summer and winter seasons. The BC GFS forecasts have higher skill score as compared to GFS DMO over most of the stations in all day-1 to day-5 forecasts during both summer and winter seasons. It is concluded from the study that the skill of GFS statistical BC forecast improves over the GFS DMO remarkably and hence can be used as an operational weather forecasting system for location specific forecast over India.     

Real-time nowcast of a cloudburst and a thunderstorm event with assimilation of Doppler weather radar data

Extreme weather events such as cloudburst and thunderstorms are great threat to life and property. It is a great challenge for the forecasters to nowcast such hazardous extreme weather events. Mesoscale model (ARPS) with real-time assimilation of DWR data has been operationally implemented in India Meteorological Department (IMD) for real-time nowcast of weather over Indian region. Three-dimensional variational (ARPS3DVAR) technique and cloud analysis procedure are utilized for real-time data assimilation in the model. The assimilation is performed as a sequence of intermittent cycles and complete process (starting from reception, processing and assimilation of DWR data, running of ARPS model and Web site updation) takes less than 20 minutes. Thus, real-time nowcast for next 3 h from ARPS model is available within 20 minutes of corresponding hour. Cloudburst event of September 15, 2011, and thunderstorm event of October 22, 2010, are considered to demonstrate the capability of ARPS model to nowcast the extreme weather events in real time over Indian region. Results show that in both the cases, ARPS3DVAR and cloud analysis technique are able to extract hydrometeors from radar data which are transported to upper levels by the strong upward motion resulting in the distribution of hydrometeors at various isobaric levels. Dynamic and thermodynamic structures of cloudburst and thunderstorm are also well simulated. Thus, significant improvement in the initial condition is noticed. In the case of cloudburst event, the model is able to capture the sudden collisions of two or more clouds during 09–10 UTC. Rainfall predicted by the model during cloudburst event is over 100 mm which is very close to the observed rainfall (117 mm). The model is able to predict the cloudburst with slight errors in time and space. Real-time nowcast of thunderstorm shows that movement, horizontal extension, and north–south orientation of thunderstorm are well captured during first hour and deteriorate thereafter. The amount of rainfall predicted by the model during thunderstorm closely matches with observation with slight errors in the location of rainfall area. The temporal and spatial information predicted by ARPS model about the sudden collision/merger and broken up of convective cells, intensification, weakening, and maintaining intensity of convective cells has added value to a human forecast.     

Discriminating the invasive species, ‘Lantana’ using vegetation indices

Invasive species have been the focus of environmentalists due to their undesired impact on the ecosystem. Spread of Lantana (Lantana camara L.), an invasive plant species, has been found in diverse geophysical environments causing a threat to the native flora. Various eradication programmes have been attempted such as burning, chemical sprays, bio-control agents and physical plugging mechanism for removing such invasive species in India. The efforts and success of these programmes need to be augmented with a correct, quick and cost effective technique of mapping in order to locate them, understand their spatial extent and hence make the process comprehensive. Also Lantana’s appearance as dense vegetation patches in remote sensing data causes problems for estimating forest canopy density. Remote sensing provides a possible solution in qualitatively and quantitatively evaluating terrestrial surface vegetation cover using spectral measure-ments. This research paper addresses issues and techniques adopted to detect and extract Lantana, and can be used for various applications in forestry as well as in eradication programmes. This study attempted to understand the appropriate band combination using Landsat data and generating vegetation indices in order to extract Lantana patches in an accurate manner. Twenty nine different vegetation indices were analyzed for their effectiveness in differentiating Lantana from other classes. The study showed that SAVI (Soil Adjusted Vegetation Index) is most favorable in discriminating Lantana followed by Perpendicular Vegetation Index-3 in the optimum bio-window (February to April).     

Two‐dimensional physically based finite element runoff model for small agricultural watersheds: II. Model testing and field application

Mathematical models are useful analysis tools to understand problems in watersheds associated with runoff, and to find solutions through land use changes and best management practices. However, before a model is applied in the field, it must be tested and checked to ensure that the model represents the real world adequately. In this paper, a two‐dimensional physically based finite element runoff model ROMO2D has been verified and validated by comparing the model output with analytic solution under simplified conditions, published data, and field measurements. Calibration of the model was done manually through a multi‐objective calibration procedure, using observed field data. Before going for field validation/application of ROMO2D, analysis was carried out to determine the optimum number of finite elements into which the watershed should be discretized and the size of the time step. A sensitivity analysis of the model was performed using the observed values of watershed parameters. The model was applied to a 1·45 ha agricultural watershed located in the Shiwalik foothills (India) to simulate runoff. The results demonstrated the potential of the model to simulate runoff from small agricultural watersheds for individual storm events with reasonable accuracy. Copyright © 2008 John Wiley & Sons, Ltd.     

<Emphasis Type="Italic">Rhizopalmoxylon nypoides</Emphasis> – a new palm root from the Deccan Intertrappean beds of Sagar,Madhya Pradesh,India

A new species of fossil palm rhizome having root-mat under the organ genus Rhizopalamoxylon (Rhizopalmoxylon nypoides sp. nov.) is reported. The specimen shows the closest resemblance with the modern monotypic genus Nypa Wurmb of the Arecaceae. The specimen was collected from the late Maastrichtian–early Danian sediments of Deccan Intertrappean beds, Mothi, Sagar district, Madhya Pradesh, India. Nypa is a mangrove palm naturally found in estuaries and swamps of the tropical region and represents one of the oldest records of the genus from the Deccan Intertrappean beds of central India. The abundance of palms, including Nypa and previously recorded coastal and mangrove elements such as Acrostichum, Barringtonia, Cocos, Sonneratia and marine algae (Distichoplax and Peyssonellia) from the Deccan Intertrappean beds indicate marine influence and existence of tropical rainforest ecosystem in the vicinity of fossil locality in contrast to the deciduous forests occurring there at present.     

Water quality of the Chhoti Gandak River using principal component analysis,Ganga Plain,India

Chhoti Gandak is a meandering river which originates in the terai area of the Ganga Plain and serves as a lifeline for the people of Deoria district, Uttar Pradesh. It travels a distance of about 250 km and drains into Ghaghara near Gothani, Siwan district of Bihar. It has been observed that people of this region suffer from water-borne health problems; therefore water samples were collected to analyse its quality along the entire length of Chhoti Gandak River.     

Hydrogeochemistry of groundwater and anthropogenic control over dolomitization reactions in alluvial sediments of the Deoria district: Ganga plain,India

Groundwater is a critical resource in Deoria district, as it is the main source of drinking water and irrigation. The aquifer has deteriorated to a high degree, during the last two to three decades, in quality and quantity due to high population growth and environmental pollution. More than 90% of the population get their drinking water from subsurface waters. Fifteen wells were sampled in June 2006 to probe the hydrogeochemical components that influence the water quality. The results show that groundwater have EC, TDS, Na⁺, Mg²⁺, HCO₃⁻ and TH higher than the WHO, 1997 maximum desirable limits. A hydrogeochemical numerical model for carbonate minerals was constructed using the PHREEQC package. The regression analysis shows that there are three groups of elements which are significantly and positively correlated. The main hydrochemical facies of the aquifer (Ca + Mg–HCO₃) represents 33.33% of the total wells. The geochemical modeling demonstrated that the reactions responsible for the hydrochemical evolution in the area fall into three categories: (1) dissolution of salts, (2) precipitation of dolomite, (3) ion exchange. Solubility of dolomite, calcite, aragonite and gypsum were assessed in terms of the saturation index. The thermodynamic prerequisites for dolomite supersaturation reactions are satisfied by subsurface waters, since they are supersaturated with respect to dolomite, undersaturated (or in equilibrium) with respect to calcite, and undersaturated with respect to gypsum. The Ca²⁺ versus SO₄²⁻ and Mg²⁺ versus SO₄²⁻ trends are also compatible with homologous trends resulting from dolomite supersaturation.     

Remote sensing of mountain snow using active microwave sensors: a review

This work provides an overview of various methods for estimating snow cover and properties in high mountains using remote sensing techniques involving microwaves. Satellite-based remote sensing with its characteristics such as synoptic view, repetitive coverage and uniformity over large areas has great potential for identifying the temporal snow cover. Many sensors have been used in the past with various algorithms and accuracies for this purpose. These methods have been improving with the use of Synthetic Aperture Radar sensors, working in different microwave frequencies, polarisation and acquisition modes. The limitations, advantages and drawbacks are illustrated while error sources and strategies on how to ease their impacts are also reviewed. An extensive list of references, with an emphasis on studies since 1990s, allows the reader to delve into specific topics.