Current Science

K. K. Singh ¹, A. Kumar ², A. V. Kulkarni ³, P. Datt ¹, S. K. Dewali ¹, V. Kumar ¹, R. Chauhan ¹

Affiliations
1 Snow and Avalanche Study Establishment, Chandigarh 160 036, IN
2 National Institute of Technology, Kurukshetra 136 119, IN
3 Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru 560 012, IN

Abstract

Snow depth is an important parameter for avalanche forecast and hydrological studies. In the Himalaya, manual snow depth data collection is difficult due to remote and rugged terrain and the severe weather conditions. However, microwave-based sensors in various satellites have the capability to estimate snow depth in all weather conditions. In the present study, experiments were performed to establish an algorithm for snow depth estimation using ground-based passive microwave radiometer with 6.9, 18.7 and 37 GHz antenna frequencies at Dhundhi and Patseo, Himachal Pradesh, India. Different layers in the snowpack were identified and layer properties, i.e. thickness, density, moisture content, etc. were measured manually and using a snow fork. Brightness temperature (T_B) of the entire snowpack and of the individual snow layers was measured using passive microwave radiometer. It was observed that T_B of the snow is affected by various snow properties such as depth, density, physical temperature and wetness. A decrease in T_B with increase in snow depth was observed for all types of snow. T_B of the snowpack was observed higher at Dhundhi in comparison to Patseo. Based on the measured radiometer data, snow depth algorithms were developed for the Greater Himalaya and Pir-Panjal ranges. These algorithms were validated with ground measurements for snow depth at different observatory locations and a good agreement between the two was observed (absolute error: 7 to 39 cm; correlation: 0.95).

Keywords

Brightness Temperature, Microwave Radiometer, Snow Depth Algorithm, Snowpack.

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P. K. Singh ¹, K. K. Singh ¹, L. S. Rathore ¹, A. K. Baxla ¹, S. C. Bhan ¹, Akhilesh Gupta ², G. B. Gohain ¹, R. Balasubramanian ³, R. S. Singh ⁴, R. K. Mall ⁴

Affiliations
1 Agromet Service Cell, India Meteorological Department, Lodhi Road, New Delhi 110 003, IN
2 Deparment of Science and Technology, New Delhi 110 016, IN
3 Agrimet Pune, New Delhi 411 005, IN
4 Banaras Hindu University, Varanasi 221 005, IN

Abstract

The CERES (crop estimation through resource and Environment Synthesis)-rice model incorporated in DSSAT version 4.5 was calibrated for genetic coefficients of rice cultivars by conducting field experiments during the kharif season at Jorhat, Kalyani, Ranchi and Bhagalpur, the results of which were used to estimate the gap in rice yield. The trend of potential yield was found to be positive and with a rate of change of 26, 36.9, 57.6 and 3.7 kg ha^-1 year^-1 at Jorhat, Kalyani, Ranchi and Bhagalpur districts respectively. Delayed sowing in these districts resulted in a decrease in rice yield to the tune of 35.3, 1.9, 48.6 and 17.1 kg ha^-1 day^-1 respectively. Finding reveals that DSSAT crop simulation model is an effective tool for decision support system. Estimation of yield gap based on the past crop data and subsequent adjustment of appropriate sowing window may help to obtain the potential yields.

Keywords

Agroclimatic Zones, Genetic Coefficients, Rice Model, Yield Gap.

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P. K. Singh ¹, K. K. Singh ¹, S. C. Bhan ¹, A. K. Baxla ¹, Sompal Singh ², L. S. Rathore ¹, Akhilesh Gupta ³

Affiliations
1 Agromet Service Cell, India Meteorological Department, Lodhi Road, New Delhi 110 003, IN
2 Department of Agriculture Meteorology, Punjab Agriculture University, Ludhiana 141 004, IN
3 Department of Science and Technology, New Delhi 110 016, IN

Abstract

Climate change is projected to alter the growing conditions of rice crop in different regions of India. Crop growth simulation model (DSSATv4.6) was calibrated and evaluated with four rice cultivars: PR 118 in Amritsar, Ludhiana; HKR 126 in Hisar and Ambala; Pant 4 in Kanpur and Sugandha-1126 in Modipuram on different sowing dates. The average yield of the selected optimum dates was 6391, 6531, 7751, 7561, 4347 and 4131 kg/ha for Amritsar, Ludhiana, Hisar, Ambala, Modipuram and Kanpur respectively. Both temperature and CO₂ have increased. The combined effect of temperature and CO₂ indicates decreased yield rate in the future decades. The present study shows that rice yield will decrease in the future and this may be due to increase in temperature. According to projection results, for all the locations average yield is higher in the decade 2010, except Amritsar in the decade 2030 and Ludhiana in the decade 2050. The average yield at Hisar, Ambala, Modipuram and Kanpur in 2010 was 7744, 7654, 4347 and 4021 kg/ha respectively. Amritsar and Ludhiana showed maximum average yield of 6880 and 6877 kg/ha respectively, in the decade 2030. Such yield reductions in rice crops due to climate change are mediated through reduction in crop duration, grain number and grain filling duration. These projections nevertheless provide a direction of likely change in crop productivity in future climate change scenarios.

Keywords

Agroclimatic Zones, Climate Change, Crop Simutation Models, Rice.

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K. K. Singh ¹, H. S. Negi ¹, A. Kumar ², A. V. Kulkarni ³, S. K. Dewali ¹, P. Datt ¹, A. Ganju ¹, S. Kumar ¹

Affiliations
1 Snow and Avalanche Study Establishment, Chandigarh 160 036, IN
2 National Institute of Technology, Kurukshetra 136 119, IN
3 Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru 560 012, IN

Abstract

In this study an airborne ground penetrating radar (GPR) is used to estimate spatial distribution of snow accumulation in the Samudra Tapu glacier (the Great Himalayan Range), Western Himalaya, India. An impulse radar system with 350 MHz antenna was mounted on a helicopter for the estimation of snow depth. The dielectric properties of snow were measured at a representative site (Patseo Observatory) using a snow fork to calibrate GPR data. The snow depths estimated from GPR signal were found to be in good agreement with those measured on ground with an absolute error of 0.04 m. The GPR survey was conducted over Samudra Tapu glacier in March 2009 and 2010. A kriging-based geostatistical interpolation method was used to generate a spatial snow accumulation map of the glacier with the GPR-collected data. The average accumulated snow depth and snow water equivalent (SWE) for a part of the glacier were found to be 2.23 m and 0.624 m for 2009 and 2.06 m and 0.496 m for 2010 respectively. Further, the snow accumulation data were analysed with various topographical parameters such as altitude, aspect and slope. The accumulated snow depth showed good correlation with altitude, having correlation coefficient varying between 0.57 and 0.84 for different parts of the glacier. Higher snow accumulation was observed in the north- and east-facing regions, and decrease in snow accumulation was found with an increase in the slope of the glacier. Thus, in this study we generate snow accumulation/SWE information using airborne GPR in the Himalayan terrain.

Keywords

Glacier, Ground Penetrating Radar, Snow Accumulation, Snow Water Equivalent.

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P. K. Singh ¹, K. K. Singh ¹, K. K. Gill ², Ram Niwas ³, R. S. Singh ⁴, Sanjay Sharma ⁵

Affiliations
1 Agromet Service Cell, India Meteorological Department, New Delhi 110 003, IN
2 School of Climate Change and Agri Meteorology, Punjab Agricultural University, Ludhiana 141 004, IN
3 Department of Agri Meteorology, CCSHAU, Hisar 125 004, IN
4 Department of Geophysics, Banaras Hindu University, Varanasi 221 005, IN
5 Department of Soil Science & Chemistry, College of Agriculture, Indore 452 001, IN

Abstract

The CERES-wheat crop growth simulation model has been calibrated and evaluated for two wheat cultivars (PBW 343 and PBW 542) for three sowing dates (30 October, 15 November and 30 November) during 2008-09 and 2009-10 to study partitioning of leaf, stem and grains at Ludhiana, Punjab, India. The experimental data and simulated model data were analysed on partitioning of leaf, stem and grains, and validated. It was found that the model closely simulated the field data from phenological events and biomass. Simulated biological and grain yield was in accordance with-field experiment crop yield within the acceptable range. The correlation coefficient between field-experiment and simulated yield data and biomass data varied significantly from 0.81 and 0.96. The model showed overestimation from field-experimental yield for both cultivars. The cultivar PBW 343 gave higher yield than cultivar PBW 542 on 15 November during both years. The model performance was evaluated and it was found that CERES-wheat model could predict growth parameters like days to anthesis and maturity, biomass and yield with reasonably good accuracy (error less than 8%) and also correlation coefficient between field-experimental and simulated yield data and biomass data varied from 0.94 and 0.95. The results showed that the correlation coefficient between simulated and districts yield varied from 0.41 to 0.78 and also significantly at all six selected districts. The results may be used to improve and evaluate the current practices of crop management at different growth stages of the crop to achieve better production potential.

Keywords

Biomass Partitioning, Genetic Coefficient, Phenology Stages, Soil Parameters.

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K. K. Singh ¹, D. K. Singh ¹, H. S. Negi ¹, A. V. Kulkarni ², H. S. Gusain ¹, A. Ganju ¹, K. Babu Govindha Raj ³

Affiliations
1 Snow and Avalanche Study Establishment, Chandigarh 160 036, IN
2 Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru 560 012, IN
3 Indian Space Research Organization, Head Quarters, New BEL Road, Bengaluru 560 231, IN

Abstract

In the present study we estimate the velocity and thickness of the Patseo glacier, Himachal Pradesh, India. The average velocity of the glacier was estimated as ~5.47 m/year using co-registration of optically sensed images and correlation (COSI-Corr) method. The glacier thickness was found to vary between 12 and 278 m, with an average value 59 m. The total glacier ice volume was estimated as ~15.8 × 10⁷ m³, with equivalent water reservoir of ~14.5 × 10⁷ m³. Ground penetrating radar (GPR) surveys were conducted during 2004 and 2013 for validation of the estimated glacier thickness. The glacier thickness estimated using COSI-Corr method was found to be in agreement with GPR-retrieved glacier thickness (RMSE = 4.75 m; MAE = 3.74 m). The GPR profiles collected along the same geographic locations on the glacier during 2004 and 2013 showed a reduction in ice thickness of ~1.89 m, and thus resulting in an annual ice thickness decrease of ~0.21 m. The glacier area was estimated for 2004 and 2013 using LISS IV satellite data and found to be ~2.52 and ~2.30 sq. km respectively. This shows an annual reduction of ~0.024 sq. km in glacier area. The total annual loss in glacier ice volume was estimated as ~4.55 × 10⁵ m³. This loss in the glacier ice volume of the Patseo glacier is supported by the snow and meteorological observations collected at a nearby field observatory of Snow and Avalanche Study Establishment (SASE). The climate data collected at SASE meteorological observatory at Patseo (3800 m), between 1993–94 and 2014–15 showed an increasing trend in the mean annual temperature and a decreasing trend in winter precipitation.

Keywords

Glaciers, Ground Penetrating Radar Surveys, Velocity and Thickness Estimation, Winter Precipitation.

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A. Shikha ¹, P. Maharana ², K. K. Singh ³, A. P. Dimri ¹, R. Niwas ⁴

Affiliations
1 School of Environmental Sciences, Jawaharlal Nehru University, New Delhi - 110067, IN
2 DCAC, Delhi University, New Delhi - 110023, IN
3 India Meteorological Department, New Delhi - 110003, IN
4 Chaudhary Charan Singh Haryana Agricultural University, Hisar - 125004, IN

Abstract

Cotton is a major cash crop of global significance. It has a peculiar and inherent growth pattern with coinciding physiological growth stages. This study is based upon modelling and simulation for Hisar region. Stage-wise water stress has been quantified for three Bt-cotton cultivars with three sowing dates under both irrigated and non-irrigated (rainfed) conditions to assess the most sensitive stage. As per model output, it was observed that, at some stages stress value during excess years remains below 0.3 which is characterized as mild stress, in contrast with drought years where it is above 0.3, impacting potential crop productivity. Thus, rainfall impacts the productivity of cotton even in irrigated semi-arid region. Irrigation measures practiced, could partially alleviate influence of stress. Also, early sowing is found beneficial. The most water-sensitive period is ball formation and maturity stage followed by flowering stage.

Keywords

Cotton, Irrigation, Temperature, Water.

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Rupsha Bhattacharyya ¹, K. K. Singh ¹, R. B. Grover ², K. Bhanja ³

Affiliations
1 Applied Systems Analysis, Homi Bhabha National Institute, Mumbai 400 094, India; Chemical Engineering Group, Bhabha Atomic Research Centre, Mumbai 400 085, IN
2 Applied Systems Analysis, Homi Bhabha National Institute, Mumbai 400 094, IN
3 Chemical Engineering Group, Bhabha Atomic Research Centre, Mumbai 400 085, IN

Abstract

Determining minimum energy consumption per capita to support high development is a crucial activity for energy planners and policy makers working within resource, environmental and budgetary constraints. A composite metric like the human development index (HDI) of a nation is positively correlated with its energy consumption. The present study focuses on the estimation of minimum energy requirement for India to attain net-zero and a HDI value of 0.9 by 2070. The final energy requirement is found to be about 18,900–22,300 TWh/yr, indicating more than three-fold rise from the current consumption. About 30–40% of the final energy may be consumed in the form of hydrogen, whereas the rest will be used directly as electricity. Rapid infrastructure creation for high development and extensive digitalization may require additional 4400–4800 TWh/yr in the initial phases of rapid growth.

Keywords

Decent living standards, greenhouse gases, human development index, minimum energy requirement, net-zero emissions.

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K. K. Yadav ¹, N. Chouhan ², R. Thubstan ², S. Norlha ², J. Hariharan ², C. Borwankar ², P. Chandra ², V. K. Dhar ¹, N. Mankuzhyil ², S. Godambe ², M. Sharma ², K. Venugopal ², K. K. Singh ¹, N. Bhatt ², S. Bhattacharyya ¹, K. Chanchalani ², M. P. Das ², B. Ghosal ², S. Godiyal ², M. Khurana ², S. V. Kotwal ², M. K. Koul ², N. Kumar ², C. P. Kushwaha ², K. Nand ², A. Pathania ², S. Sahayanathan ¹, D. Sarkar ², A. Tolamati ², R. Koul ³, R. C. Rannot ⁴, A. K. Tickoo ⁵, V. R. Chitnis ⁶, A. Behere ⁷, S. Padmini ⁷, A. Manna ⁷, S. Joy ⁷, P. M. Nair ⁷, K. P. Jha ⁷, S. Moitra ⁷, S. Neema ⁷, S. Srivastava ⁷, M. Punna ⁷, S. Mohanan ⁷, S. S. Sikder ⁷, A. Jain ⁷, S. Banerjee ⁷, Krati ⁷, J. Deshpande ⁷, V. Sanadhya ⁸, G. Andrew ⁸, M. B. Patil ⁸, V. K. Goyal ⁸, N. Gupta ⁸, H. Balakrishna ⁸, A. Agrawal ⁸, S. P. Srivastava ⁹, K. N. Karn ⁹, P. I. Hadgali ⁹, S. Bhatt ⁹, V. K. Mishra ⁹, P. K. Biswas ⁹, R. K Gupta ⁹, A. Kumar ⁹, S. G. Thul ⁹, R. Kalmady ¹⁰, D. D. Sonvane ¹⁰, V. Kumar ¹⁰, U. K. Gaur ¹⁰, J. Chattopadhyay ¹¹, S. K. Gupta ¹¹, A. R. Kiran ¹¹, Y. Parulekar ¹¹, M. K. Agrawal ¹¹, R. M. Parmar ¹¹, G. R. Reddy ¹², Y. S. Mayya ¹³, C. K. Pithawa ¹⁴

Affiliations
1 Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai 400 085, India; Homi Bhabha National Institute, Mumbai 400 085, India, IN
2 Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
3 Formerly at Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
4 Raja Ramanna Fellow at Astrophysical Sciences Division, Mumbai 400 085, India, IN
5 Deceased, IN
6 Department of High Energy Physics, Tata Institute of Fundamental Research, Mumbai 400 005, India, IN
7 Electronics Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
8 Control and Instrumentation Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
9 Center for Design and Manufacture, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
10 Computer Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
11 Reactor Safety Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
12 Formerly at Reactor Safety Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
13 Formerly at Reactor Control Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
14 Formerly at Electronics Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN

Abstract

The MACE telescope has recently been commissioned at Hanle, Ladakh, India. It had its first light in April 2021 with a successful detection of very high energy gamma-ray photons from the standard candle Crab Nebula. Equipped with a large light collector of 21 m diameter and situated at an altitude of ~4.3 km amsl, the MACE telescope is expected to explore the mysteries of the non-thermal Universe in the energy range above 20 GeV with very high sensitivity. It can also play an important role in carrying out multi-messenger astronomy in India.

Keywords

Gamma-ray astronomy, high energy radiative processes, non-thermal Universe, telescope.

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Rupsha Bhattacharyya ¹, K. K. Singh ¹, R. B. Grover ¹, K. Bhanja ²

Affiliations
1 Applied Systems Analysis, Homi Bhabha National Institute, Mumbai 400 094, IN
2 Chemical Engineering Group, Bhabha Atomic Research Centre, Mumbai 400 085, IN

Abstract

No Abstract.

Keywords

No Keywords.

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