Delineation of long-wavelength magnetic anomalies over central India by rectangular harmonic analysis

The method of rectangular harmonic analysis is applied to the geomagnetic field data from central India to isolate long wavelength magnetic anomalies associated with largescale crustal structures. The long-wavelength anomalies have accounted for approximately 20 % of the spatial variability of the residual magnetic field over the International Geomagnetic Reference Field. On the magnetic anomaly map, reflecting the surface expression of longwavelength anomalies, the Tapi-Narmada-Son zone is characterized by a feeble positive anomaly bounded by a strong negative anomaly. The anomaly pattern is believed to be caused by the large-scale undulation in Moho and related variations in the thickness of the lower (basaltic) crust. The other two prominent anomalies, the magnetic low striking northwest and the magnetic high trending east-northeast, appear to be related to the deep structural feature of the Godavari graben and the eastern Rajasthan lineament respectively.     

Current Status and Future Challenges of Weather Radar Polarimetry: Bridging the Gap between Radar Meteorology/Hydrology/Engineering and Numerical Weather Prediction

After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve weather observations,quantification, forecasting, and warnings. The weather radar networks in China and other countries are also being upgraded with dual-polarization capability. Now, with radar polarimetry technology having matured, and PRD available both nationally and globally, it is important to understand the current status and future challenges and opportunities. The potential impact of PRD has been limited by their oftentimes subjective and empirical use. More importantly, the community has not begun to regularly derive from PRD the state parameters, such as water mixing ratios and number concentrations, used in numerical weather prediction(NWP) models.In this review, we summarize the current status of weather radar polarimetry, discuss the issues and limitations of PRD usage, and explore potential approaches to more efficiently use PRD for quantitative precipitation estimation and forecasting based on statistical retrieval with physical constraints where prior information is used and observation error is included. This approach aligns the observation-based retrievals favored by the radar meteorology community with the model-based analysis of the NWP community. We also examine the challenges and opportunities of polarimetric phased array radar research and development for future weather observation.     

Inclusion of earthquake strong ground motion in a geographic information system-based landslide susceptibility zonation in Garhwal Himalayas

Garhwal Himalayas are seismically very active and simultaneously suffering from landslide hazards. Landslides are one of the most frequent natural hazards in Himalayas causing damages worth more than one billion US$ and around 200 deaths every year. Thus, it is of paramount importance to identify the landslide causative factors to study them carefully and rank them as per their influence on the occurrence of landslides. The difference image of GIS-derived landslide susceptibility zonation maps prepared for pre- and post-Chamoli earthquake shows the effect of seismic shaking on the occurrence of landslides in the Garhwal Himalaya. An attempt has been made to incorporate seismic shaking parameters in terms of peak ground acceleration with other static landslide causative factors to produce landslide susceptibility zonation map in geographic information system environment. In this paper, probabilistic seismic hazard analysis has been carried out to calculate peak ground acceleration values at different time periods for estimating seismic shaking conditions in the study area. Further, these values are used as one of the causative factors of landslides in the study area and it is observed that it refines the preparation of landslide susceptibility zonation map in seismically active areas like Garhwal Himalayas.     

Lake outburst and debris flow disaster at Kedarnath,June 2013: hydrometeorological triggering and topographic predisposition

Heavy rainfall in June 2013 triggered flash flooding and landslides throughout the Indian Himalayan state of Uttarakhand, killing more than 6000 people. The vast majority of fatalities and destruction resulted directly from a lake outburst and debris flow disaster originating from above the village of Kedarnath on June 16 and 17. Here, we provide a systematic analysis of the contributing factors leading to the Kedarnath disaster, both in terms of hydrometeorological triggering and topographic predisposition. Topographic characteristics of the lake watershed above Kedarnath are compared with other glacial lakes across the north-western Himalayan states of Uttarakhand and Himachal Pradesh, and implications for glacier lake outburst hazard assessment in a changing climate are discussed. Our analysis suggests that the early onset of heavy monsoon rainfall (390 mm, June 10–17) immediately following a 4-week period of unusually rapid snow cover depletion and elevated streamflow was the crucial hydrometeorological factor, resulting in slope saturation and significant run-off into the small seasonal glacial lake. Between mid-May and mid-June 2013, snow-covered area above Kedarnath decreased by around 50 %. The unusual situation of the lake being dammed in a steep, unstable paraglacial environment but fed entirely from snowmelt and rainfall within a fluvial dominated watershed is important in the context of this disaster. A simple scheme enabling large-scale recognition of such an unfavourable topographic setting is introduced. In view of projected 21st century changes in monsoon timing and heavy precipitation in South Asia, more emphasis should be given to potential hydrometeorological triggering of lake outburst and debris flow disasters in the Himalaya.     

A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas

Landslides are one of the most destructive phenomena of nature that cause damage to both property and life every year, and therefore, landslide susceptibility zonation (LSZ) is necessary for planning future developmental activities. In this paper, apart from conventional weighting system, objective weight assignment procedures based on techniques such as artificial neural network (ANN), fuzzy set theory and combined neural and fuzzy set theory have been assessed for preparation of LSZ maps in a part of the Darjeeling Himalayas. Relevant thematic layers pertaining to the causative factors have been generated using remote sensing data, field surveys and Geographic Information System (GIS) tools. In conventional weighting system, weights and ratings to the causative factors and their categories are assigned based on the experience and knowledge of experts about the subject and the study area to prepare the LSZ map (designated here as Map I). In the context of objective weight assignments, initially the ANN as the black box approach has been used to directly produce an LSZ map (Map II). In this approach, however, the weights assigned are hidden to the analyst. Next, the fuzzy set theory has then been implemented to determine the membership values for each category of the thematic layer using the cosine amplitude method (similarity method). These memberships are used as ratings for each category of the thematic layer. Assuming weights of each thematic layer as one (or constant), these ratings of the categories are used for the generation of another LSZ map (Map III). Subsequently, a novel weight assignment procedure based on ANN is implemented to assign the weights to each thematic layer objectively. Finally, weights of each thematic layer are combined with fuzzy set derived ratings to produce another LSZ map (Map IV). The maps I–IV have been evaluated statistically based on field data of existing landslides. Amongst all the procedures, the LSZ map based on combined neural and fuzzy weighting (i.e., Map IV) has been found to be significantly better than others, as in this case only 2.3% of the total area is found to be categorized as very high susceptibility zone and contains 30.1% of the existing landslide area.     

Anomalous geomagnetic variations and possible causative structures along foothills of Himachal Pradesh-Kumaun-Himalaya

This paper presents the results of a magnetometer array study covering Kangra region to supplement information already available on the nature of geoelectrical structure at the foothills of Himachal Pradesh-Kumaun-Himalaya. The observed induction pattern across the Himalayan frontal fault is found to be the expression of a psuedo-geomagnetic coast effect associated with the edge of sheet current flowing in the sediments of the IndoGangetic Plains. An additional conductive sheet that is required beneath the frontal folded belt may represent increased hydration of certain sedimentary layers.     

Benthic coverage and bottom topography of coral reef environment over Pirotan reef,Gulf of Kachchh region,India

Remote sensing measurements in coral reef environments commonly confront the problem of overlying atmosphere and modification of spectral signal due to water column over the bottom substrates. In order to correct these problems, hyperspectral observations offer an advantage over multispectral observations. Airborne hyperspectral remote sensing data from Airborne Visible Infrared Imaging Spectrometer- Next Generation (AVIRIS-NG) sensor was acquired during low tidal condition on 14 February 2016 at Pirotan reef, Gulf of Kachchh region, India. The objective of this study is to map benthic coverage and bottom topography over Pirotan reef. The methodology involved atmospheric correction, simultaneous retrieval of water parameters, bathymetry, water column correction and mapping. Atmospheric correction was performed by removing path radiance and aerosol contribution and dividing by atmospheric transmittance and incoming solar irradiance to obtain remote sensing reflectance. Model derived error minimization technique was used for simultaneous retrieval of water parameters and bathymetry. Derived water parameters were used to account for water column attenuation and retrieve concomitant true bottom signature.     

Estuarine sediment deposition during wetland restoration: A GIS and remote sensing modeling approach

Restoration is currently underway in the industrial salt flats of San Francisco Bay, California. Remote sensing of suspended sediment concentration and other GIS predictor variables were used to model sediment deposition within recently restored ponds. Suspended sediment concentrations were calibrated to reflectance values from Landsat TM 5 and ASTER satellite image data using three statistical techniques—linear regression, multivariate regression, and Artificial Neural Network (ANN) regression. Multivariate and ANN regressions using ASTER proved to be the most accurate methods, yielding r² values of 0.88 and 0.87, respectively. Predictor variables such as sediment grain size and tidal frequency were used in the Marsh Sedimentation (MARSED) model for predicting deposition rates. MARSED results show a root mean square deviation (RMSD) of 66.8 mm (<1σ) between modeled and field observations. This model was applied to a pond breached in November 2010 and indicated that the pond will reach sediment equilibrium levels after 60 months of tidal inundation.     

Changing river temperatures in northern Germany: trends and drivers of change

Climate change is one of the main drivers of river warming worldwide. However, the response of river temperature to climate change differs with the hydrology and landscape properties, making it difficult to generalize the strength and the direction, of river temperature trends across large spatial scales and various river types. Additionally, there is a lack of long‐term and large‐scale trend studies in Europe as well as globally. In this study, we investigated the long‐term (25 years; 132 sites) and the short‐term (10 years; 475 sites) river temperature trends, patterns and underlying drivers within the period 1985–2010 in seven river basins of Germany. The majority of the sites underwent significant river warming during 1985–2010 (mean warming trend: 0.03 °C year^?1, SE = 0.003), with a faster warming observed during individual decades (1985–1995 and 2000–2010) within this period. Seasonal analyses showed that, while rivers warmed in all seasons, the fastest warming had occurred during summer. Among all the considered hydro‐climatological variables, air temperature change, which is a response to climate forcing, was the main driver of river temperature change because it had the strongest correlation with river temperature, irrespective of the period. Hydrological variables, such as average flow and baseflow, had a considerable influence on river temperature variability rather than on the overall trend direction. However, decreasing flow probably assisted in a faster river temperature increase in summer and in rivers in NE basins (such as the Elbe basin). The North Atlantic Oscillation Index had a greater significant influence on the winter river temperature variability than on the overall variability. Landscape and basin variables, such as altitude, ecoregion and catchment area, induced spatially variable river temperature trends via affecting the thermal sensitivity of rivers, with the rivers in large catchments and in lowland areas being most sensitive. Copyright © 2016 John Wiley & Sons, Ltd.