Proposed river-linking project of India: a boon or bane to nature

India is a vast country and is highly diversified in terms of natural resources and socio-economic setup. Moreover, its water resources are unevenly distributed in space and time. With increasing population and increasing aspiration for improved standard of living, there is an acute pressure on the demand and availability of water. Though the idea of interlinking of rivers is not a new concept in India, it had rather persisted long back as much as in other countries of ancient civilization. National Water Development Agency (NWDA) has given the real shape to the proposal of the interlinking of rivers of the country. In India the river-linking project in a sensible and scientific manner will not only allow the prevention of the colossal wastage of a vitally important natural resource, mitigate the flood and inundation by detaining flowing surface water of rainy seasons, but also ensure availability of water to drier areas; combating both flood and drought simultaneously. Moreover, this project will generate 34,000 MW of hydropower and irrigation of an additional 35 million hectares (135,135 square miles) of land. Though linking of rivers may initially appear to be a costly proposition in ecological, geological, hydrological and economical terms, in the long run the net benefits coming from it will far outweigh these costs or losses. However, in the absence of any definite international legal framework, Bangladesh has raised objections against the project. This paper aims at looking at this long-term plan, the project proposal, its involvement and impact not only on the states of India, India as a whole, but also on its neighbouring nations which are linked with India through the waterways, and share the common climatic conditions and economic status.     

Simplified SMA-inspired 1-parameter SCS-CN model for runoff estimation

This study proposes a simplified 1-parameter SCS-CN model (M5) based on Mishra-Singh (2002) model and soil moisture accounting (SMA) procedure for surface runoff estimation and compares its performance with the existing SCS-CN method (SCS, 1956) (M1), Michel 1-P model (Water Resour Res 41:1-6, 2005) (M2), Sahu 1-P model (Hydrol Process 21:2872-2881, 2007) (M3), and Ajmal et al. model (J Hydrol 530:623-633, 2015) (M4) using large rainfall–runoff dataset of 48,763 events from123 USDA-ARS watersheds. The performance of models was evaluated using three statistical error indices such as Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE), percentage bias (PBIAS), and rank and grading system (RGS). Based on the results obtained, the models can be ranked as follows: M5?>?M4?>?M3?>?M1?>?M2, i.e., model M5 outperformed all the remaining four models M1–M4 and hence is recommended for field applications.     

Letting failure be: COVID-19, PhD fieldwork and to not (want to) learn from failures

The ongoing COVID-19 pandemic has prompted researchers to rethink their fieldwork. My doctoral fieldwork plans, which involved conducting ethnographic research amongst Afghan refugees and migrants in New Delhi and Kolkata, were upended because of the recurring waves of the pandemic and the lockdowns/curfews that were imposed in their wake (2020−2022). Locked out of my field, my inability to conduct my research as planned amounted to a failure that could not be redeemed, especially because of time constraints. Using autoethnographic vignettes of my encounters in the lead up to the eventual suspension of in-situ fieldwork, I critically reflect on how I approached and felt towards failures in/of field and how these encounters speak back to the discourse on failure in academia. In doing so, this article advocates for the need to revisit failures simply for what they are, without necessarily demanding and/or (self) expecting that we recast them as stepping stones towards success. By challenging the neo-liberal desire to re-present failures in a productive light, I argue we can make greater room for more supportive discussions around failures without committing ourselves to the task of having to find triumph in (every) adversity.     

Characteristics of ambient ammonia over Delhi,India

In the present paper, we have characterized the ambient ammonia over Delhi along with other trace gases (NH₃, NO, NO₂, SO₂ and CO) and particulates (PM_2.5 and PM₁₀) measured during December 2011 to June 2012. The average mixing ratios of ambient NH₃, NO, NO₂, SO₂ and CO were recorded as 21.2 ± 5.4, 19.5 ± 4.9, 17.4 ± 1.4, 1.7 ± 0.5 ppb and 1.6 ± 0.7 ppm, respectively, during winter, whereas the average mixing ratios of ambient NH₃, NO, NO₂, SO₂ and CO were recorded as 20.8 ± 4.7, 21.7 ± 6.3, 16.8 ± 3.1, 2.2 ± 0.8 ppb and 1.8 ± 0.9 ppm, respectively, during summer. In the present case, non-significant seasonal and diurnal variations of NH₃, NO, NO₂, SO₂ and CO were observed during both the seasons. The average monthly NH₃/NH₄ ⁺ ratios varied from 0.28 to 2.56 with an average value of 1.46 in winter. The higher NH₃/NH₄ ⁺ ratio (3.5) observed in summer indicates the abundance of NH₃ in the atmosphere during summer. The higher fraction of particulate NH₄ ⁺ observed in winter than summer attributes to the conversion of gaseous NH₃ into NH₄ ⁺. The results emphasized that the traffic could be one of the significant sources of ambient NH₃ at the urban site of Delhi as illustrated by positive correlations of NH₃ with traffic-related pollutants (NO, NO₂ and CO). Surface wind analysis and wind directions also support the roadside traffic and agricultural activities at the nearby area indicating possible major sources of ambient NH₃ at the study site.     

Bathymetry Data Correction Using Global Optimization Method

The bathymetry data of marine bodies have been collected over a century, and the collected data have a wide range of resolution and accuracy. Acquisition of bathymetry data is very costly and time-consuming. One can use the old, low-quality bathymetry data to fill the gap in high-quality, recently acquired bathymetry data after correcting the old data to improve its quality so that it is comparable to the high-quality data. The old data correction can be treated as a nonlinear inverse problem. Simulated annealing (SA) global optimization method was used here in solving this problem. The two sets of data that were used are project survey (PS) and Vietnamese Navy Chart (VNC) data. The PS data were collected in 2000 in an offshore survey from the Vietnam coast in the South China Sea (SCS). The VNC data were obtained by digitizing VNC that was published in 1981. Inverse distance weighted (IDW) interpolation method was used for forward modeling. Weperformed the SA algorithm run starting at a high "temperature," then lowering the "temperature" gradually up to the "critical temperature" and then staying there for the rest of the run. The best model chosen by the algorithm showed an improvement of 63% from the original model. We then constructed a digital bathymetry model (DBM) of the study area with the combined corrected VNC and the PS data.     

Rationale for measurement of midocean tsunami signature

Abstract

Arguments are presented to justify midocean tsunami measurements and related investigations aimed toward improvement of tsunami prediction and warning. It is postulated that midocean tsunami signatures be measured simultaneously at several locations and correlated with high‐accuracy onshore measurements.     

Some theoretical approaches to delineate tsunami hazard in the Pacific Ocean

Abstract

In the recent seismological literature, several articles appeared which suggested that major earthquakes are likely to occur in the near future, in the various seismic gaps around the rim of the Pacific Basin. Although the direct effects of these earthquakes may be confined to local areas, the tsunamis that will generate are expected to travel Pacific Ocean wide and cause great destruction even at far off places around the Pacific Ocean. Here, the various approaches to delineating the tsunami hazard are discussed and some suggestions are made.