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Dimri, A. P.

Understanding the Linkages between Climate Change and Forest

Abstract Views :314 | PDF Views:80

Authors

Rinku Moni Devi ¹, Maneesh Kumar Patasaraiya ¹, Bhaskar Sinha ², Sameer Saran ³, A. P. Dimri ⁴, Rajeev Jaiswal ⁵

Affiliations
1 Indian Institute of Forest Management, Bhopal 462 003, IN
2 Centre for Climate Change Studies, Indian Institute of Forest Management, Bhopal 462 003, IN
3 Indian Institute of Remote Sensing, Dehradun 248 001, IN
4 School of Environmental Sciences, Jawaharlal Nehru University, New Delhi 110 067, IN
5 Indian Space Research Organisation, Bengaluru 560 094, IN

Source

Current Science, Vol 114, No 05 (2018), Pagination: 987-996

Abstract

The present study reviews the application of various regional climate models and remote sensing techniques to understand and define impacts of climate change on the forest resources with specific reference to India. It illustrates the potentials and limitations of regional climate models, vegetation models and remote sensing techniques like normalized difference vegetation index time-series analysis, change detection method and phenological attributes in assessing and monitoring the impacts of climate change on vegetation. The study recommends that regional climate models and remote sensing techniques need to be integrated in tandem for understanding the present and future impacts of climate change on forest ecosystems. This could help to improve the accuracy and prediction, which can contribute to planning effective adaptation strategies in the forestry sector.

Keywords

Climate Change, Forest, Regional Climate Models, Remote Sensing.

Full Text

References

Stern, N., The Economics of Climate Change: The Stern Review, Cambridge University Press, Cambridge, UK, 2007.

Edenhofer, O. et al., Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment, Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom, 2014.

Bellassen, V. and Luyssaert, S., Carbon sequestration: managing forests in uncertain times. Nature, 2014, 506(7487), 153–155.

Shriner, D. S. and Street, R. B., The Regional Impacts of Climate Change, Cambridge University Press, New York, 1998, pp. 253–330.

Hansen, A. J., Neilson, R. P., Dale, V. H., Flather, C. H., Iverson, L. R., Currie, D. J. and Bartlein, P. J., Global change in forests: responses of species, communities, and biomes interactions between climate change and land use are projected to cause large shifts in biodiversity. BioScience, 2001, 51(9), 765–779.

Ravindranath, N. H., Joshi, N. V., Sukumar, R. and Saxena, A., Impact of climate change on forests in India. Curr. Sci., 2006, 90(3), 354–361.

Chen, I. C., Hill, J. K., Ohlemüller, R., Roy, D. B. and Thomas, C. D., Rapid range shifts of species associated with high levels of climate warming. Science, 2011, 333(6045), 1024–1026.

Dale, V. H., Tharp, M. L., Lannom, K. O. and Hodges, D. G., Modelling transient response of forests to climate change. Sci. Total Environ., 2010, 408(8), 1888–1901.

Hanewinkel, M., Hummel, S. and Cullmann, D. A., Modelling and economic evaluation of forest biome shifts under climate change in Southwest Germany. For. Ecol. Manage., 2010, 259(4), 710–719.

Betts, R. A., Malhi, Y. and Roberts, J. T., The future of the Amazon: new perspectives from climate, ecosystem and social sciences. Philos. T. R. Soc. London, Ser. B, 2008, 363(1498), 1729–1735.

Bonan, G. B., Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science, 2008, 320(5882), 1444–1449.

Goldstein, A. H., Hultman, N. E., Fracheboud, J. M., Bauer, M. R., Panek, J. A., Xu, M. and Baugh, W., Effects of climate variability on the carbon dioxide, water, and sensible heat fluxes above a ponderosa pine plantation in the Sierra Nevada (CA). Agric. For. Meteorol., 2000, 101(2), 113–129.

Hanninen, H., Climate warming and the risk of frost damage to boreal forest trees: identification of critical eco-physiological traits. Tree Physiol., 2006, 26(7), 889–898.

Fearnside, P. M.. Plantation forestry in Brazil: the potential impacts of climatic change. Biomass Bioenerg., 1999, 16(2), 91–102.

Canadell, J. G. and Raupach, M. R., Managing forests for climate change mitigation. Science, 2008, 320(5882), 1456–1457.

Sykes, M. T., Prentice, I. C. and Cramer, W., A bioclimatic model for the potential distributions of north European tree species under present and future climates. J. Biogeogr., 1996, 23, 203–233.

INCCA, Indian Network for Climate Change Assessment. Report 2. Climate Change and India: a 4  4 Assessment – a sectoral and regional analysis for 2030s. Ministry of Environment and Forests, Government of India. November, 2010.

Sukhdev, P., Costing the earth. Nature, 2009, 462(7271), 277.

Joshi, P. K., Rawat, A., Narula, S. and Sinha, V., Assessing impact of climate change on forest cover type shifts in Western Himalayan eco-region. J. For. Res., 2012, 23(1), 75–80.

Chakraborty, A., Joshi, P. K., Ghosh, A. and Areendran, G., Assessing biome boundary shifts under climate change scenarios in India. Ecol. Indic., 2013, 34, 536–547.

Panigrahy, S., Anitha, D., Kimothi, M. M. and Singh, S. P., Timberline change detection using topographic map and satellite imagery. Trop. Ecol., 2010, 51(1), 87–91.

Gopalakrishnan, R., Jayaraman, M., Bala, G. and Ravindranath, N. H., Climate change and Indian forests. Curr. Sci., 2011, 101(3), 348–355.

Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., Van Vuuren, D. P. and Meehl, G. A., The next generation of scenarios for climate change research and assessment. Nature, 2010, 463(7282), 747–756.

Ghosh, S. and Mujumdar, P. P., Future rainfall scenario over Orissa with GCM projections by statistical downscaling. Curr. Sci., 2006, 90(3), 396–404.

Parry, M. L. (ed.), Climate Change 2007 – Impacts, Adaptation and Vulnerability: Working Group II Contribution to the Fourth Assessment Report of the IPCC, Cambridge University Press, Vol. 4, 2007.

Jones, N., Climate assessments: 25 years of the IPCC. Nature, 2013, 501, 298–299.

Hennessey, K. J., Whetton, P. H., Katzfey, J. J., McGregor, J. L., Jones, R. N., Page, C. M. and Nguyen, K. C., Fine resolution climate change scenarios for new South Wales. Annual Report. CSIRO, Australia, 1998, p. 48.

Hay, L. E., Wilby, R. L. and Leavesley, G. H., A comparison of delta changes and downscaled GCM scenarios for three mountainous basins in the United States. J. Am. Water Resour. Assoc., 2000, 36, 387–397.

Thomson, A. M., Brown, R. A., Ghan, S. J., Izaurralde, R. C., Rosenberg, N. J. and Leung, L. R.., Elevation dependence of winter wheat production in eastern Washington State with climate change: a methodological study. Climate Change, 2002, 54(1–2), 141–164.

Wotton, B. M., Stocks, B. J., Flannigan, M. D., Laprise, R. and Blanchet, J. P., Estimating future 2  CO2 fire climates in the boreal forest of Canada using a regional climate model. In proceedings of Third International Conference on Forest Fire Research and the 14th Conference in Fire and Forest Meteorology, University of Coimbra, Portugal, 1998, pp. 1207–1221.

Arnell, N. W., Hudson, D. A. and Jones, R. G., Climate change scenarios from a regional climate model: estimating change in runoff in southern Africa. J. Geophys. Res: Atmos., 2003, 108(D16), 4519–4528.

Jacob, D., Bärring, L., Christensen, O. B., Christensen, J. H., de Castro, M., Deque, M. and van den Hurk, B., An intercomparison of regional climate models for Europe: model performance in present-day climate. Climate Change, 2007, 81(1), 31–52.

Lucas-Picher, P., Christensen, J. H., Saeed, F., Kumar, P., Asharaf, S., Ahrens, B. and Hagemann, S., Can regional climate models represent the Indian monsoon? J. Hydrometeorol., 2011, 12(5), 849–868.

Mathison, C., Wiltshire, A., Dimri, A. P., Falloon, P., Jacob, D., Kumar, P. and Yasunari, T., Regional projections of North Indian climate for adaptation studies. Sci. Total Environ., 2013, 468, S4–S17.

Giorgi, F., Mearns, L. O., Shields, C. and McDaniel, L., Regional nested model simulations of present day and 2 x CO₂ climate over the central plains of the US. Climate Change, 1998, 40(3–4), 457–493.

Mearns, L. O., Giorgi, F., Whetton, P., Pabon, D., Hulme, M. and Lal, M., Guidelines for use of climate scenarios developed from regional climate model experiments, IPCC Guideline Paper, 2003.

Stone, M. C., Hotchkiss, R. H. and Mearns, L. O., Water yield responses to high and low spatial resolution climate change scenarios in the Missouri River Basin. Geophys. Res. Lett., 2003, 30(4).

Zacharias, M., Kumar, S. N., Singh, S. D., Rani, D. S. and Aggarwal, P. K., Evaluation of a regional climate model for impact assessment of climate change on crop productivity in the tropics. Curr. Sci., 2015, 108(6), 1119.

Hay, J., Extreme weather and climate events, and farming risks. In Managing Weather and Climate Risks in Agriculture (eds Sivakumar, M. V. K. and Motha, R. P.), Springer, Berlin, 2007, pp. 1–19.

Hertzler, G., Adapting to climate change and managing climate risks by using real options. Crop Pasture Sci., 2007, 58(10), 985–992.

Geethalakshmi, V., Lakshmanan, A., Rajalakshm, D., Jagannathan, R., Sridhar, G., Ramaraj, A. P. and Anbhazhagan, R., Climate change impact assessment and adaptation strategies to sustain rice production in Cauvery basin of Tamil Nadu. Curr. Sci., 2011, 101(3), 342–347.

Chaturvedi, R. K., Gopalakrishnan, R., Jayaraman, M., Bala, G., Joshi, N. V., Sukumar, R. and Ravindranath, N. H., Impact of climate change on Indian forests: a dynamic vegetation modelling approach. Mitig. Adapt. Strat. Global Change, 2011, 16(2), 119–142.

Iverson Louis, R. and Prasad, A. M., Potential changes in tree species richness and forest community types following climate change. Ecosystems, 2001, 4(3), 186–199.

Solomon, A. M., West, D. C. and Solomon, J. A., Simulating the role of climate change and species immigration in forest succession. In Forest Succession: Concepts and Application (eds West, D. C. Shugart, H. H. and Botkin, D. B.), Springer, New York, 1981, pp. 154–177.

Solomon, A. M. and Bartlein, P. J., Past and future climate change: response by mixed deciduous–coniferous forest ecosystems in northern Michigan. Can. J. For. Res., 1992, 22, 1727–173.

Solomon, A. M., Transient response of forests to CO₂ induced climate change: simulation modelling experiments in eastern North America. Oecologia, 1986, 68, 567–579.

Smith, T. M., Smith, J. B. and Shugart, H. H., Modelling the response of terrestrial vegetation to climate change in the tropics. In Tropical Forests in Transition-Ecology of Natural and Anthropogenic Disturbance Processes (ed. Goldammer, J. G.), Birkhauser Verlag, Basel-Boston, 1992, pp. 253–268.

Fischlin, A. and Gyalistras, D., Assessing impacts of climatic change on forests in the Alps. Global. Ecol. Biogeogr., 1997, 6, 19–37.

Lindner, M., Maroschek, M., Netherer, S., Kremer, A., Barbati, A., Garcia-Gonzalo, J. and Lexer, M. J., Climate change impacts, adaptive capacity, and vulnerability of European forest ecosystems. For. Ecol. Manage., 2010, 259(4), 698–709.

Madhya Pradesh (MP) State Action Plan on Climate Change – Integrating Concern – Converging Possibilities, State Knowledge Management Centre on Climate Change, Environmental Protection and Coordination Organization, Housing and Environment Department, Government of MP, 2014.

Loehle, C. and LeBlanc, D., Model-based assessments of climate change effects on forests: a critical review. Ecol. Model., 1996, 90(1), 1–31.

Neilson, R. P. and Marks, D., A global perspective of regional vegetation and hydrologic sensitivities from climatic change. J. Veg. Sci., 1996, 5(5), 715–730.

Quillet, A., Peng, C. and Garneau, M., Toward dynamic global vegetation models for simulating vegetation–climate interactions and feedbacks: recent developments, limitations, and future challenges. Environ. Rev., 2010, 18(NA), 333–353.

Atkin, O. K., Atkinson, L. J., Fisher, R. A., Campbell, C. D., Zaragoza‐Castells, J. O., Pitchford, J. W. and Hurry, V., Using temperature‐dependent changes in leaf scaling relationships to quantitatively account for thermal acclimation of respiration in a coupled global climate–vegetation model. Global Change Biol., 2008, 14(11), 2709–2726.

Sitch, S., Huntingford, C., Gedney, N., Levy, P. E., Lomas, M., Piao, S. L. and Jones, C. D., Evaluation of the terrestrial carbon cycle, future plant geography and climate–carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs). Global. Change Biol., 2008, 14(9), 2015–2039.

Bunn, A. G., Goetz, S. J. and Fiske, G. J., Observed and predicted responses of plant growth to climate across Canada. Geophys. Res. Lett., 2005, 32(16), 1–4.

Bounoua, L., Collatz, G. J., Los, S. O., Sellers, P. J., Dazlich, D. A., Tucker, C. J. and Randall, D. A., Sensitivity of climate to changes in NDVI. J. Climate, 2000, 13(13), 2277–2292.

Gonzalez-Orozco, C. E., Pollock, L. J., Thornhill, A. H., Mishler, B. D., B. Knerr, N., Laffan, S.W. and Kujala, H., Phylogenetic approaches reveal biodiversity threats under climate change. Nature Climate Change, 2016, 6(12), 1110–1114.

Warszawski, L., Frieler, K., Huber, V., Piontek, F., Serdeczny, O. and Schewe, J., The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): project framework. Proc. Natl. Acad. Sci. USA, 2014, 111(9), 3228–3232.

Reed, B. C., Brown, J. F., Vander Zee, D., Loveland, T. R., Merchant, J. W. and Ohlen, D. O., Measuring phenological variability from satellite imagery. J. Veg. Sci., 1994, 5(5), 703–714.

Bawa, K., Rose, J., Ganeshaiah, K. N., Barve, N., Kiran, M. C. and Umashaanker, R., Assessing biodiversity from space: an example from the Western Ghats, India. Conserv. Ecol., 2002, 6(2), 7.

Salunkhe, O., Khare, P. K., Sahu, T. R. and Singh, S., Above ground biomass and carbon stocking in tropical deciduous forests of state of Madhya Pradesh, India. Taiwania, 2014, 59(4), 353–359.

Turner, D. P., Ritts, W. D., Cohen, W. B., Gower, S. T., Running, S. W., Zhao, M. and Ahl, D. E., Evaluation of MODIS NPP and GPP products across multiple biomes. Remote Sensing Environ., 2006, 102(3), 282–292.

Thiam, A. K., The causes and spatial pattern of land degradation risk in southern Mauritania using multi temporal AVHRR‐NDVI imagery and field data. Land Degrad. Dev., 2003, 14(1), 133–142.

Lucht, W. et al., Climatic control of the high-latitude vegetation greening trend and Pinatubo effect. Science, 2002, 296, 1687–1689.

Myneni, R. B., Dong, J., Tucker, C. J., Kaufmann, R. K., Kauppi, P. E., Liski, J. and Hughes, M. K., A large carbon sink in the woody biomass of northern forests. Proc. Natl. Acad. Sci., 2001, 98(26), 14784–14789.

Nemani, R. R., Keeling, C. D., Hashimoto, H., Jolly, W. M., Piper, S. C., Tucker, C. J. and Running, S. W., Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science, 2003, 300(5625), 1560–1563.

Zhang, J., Dong, W., Congbin, F. and Lingyun, W., The influence of vegetation covers on summer precipitation in China: a statistical analysis of NDVI and climate data. Adv. Atmos. Sci., 2003, 20(6), 1002–1006.

Zhang, J., Dong, W., Ye, D. and Fu, C., New evidence for effects of land cover in China on summer climate. Chin. Sci. Bull., 2000, 48(4), 401–405.

Liu, Y., Wang, X., Guo, M., Tani, H., Matsuoka, N. and Matsumura, S., Spatial and temporal relationships among NDVI, climate factors, and land cover changes in Northeast Asia from 1982 to 2009. GISci. Remote Sensing, 2011, 48(3), 371–393.

Eklundh, L. and Olsson, L., Vegetation index trends for the African Sahel 1982–1999. Geophys. Res. Lett., 2003, 30(8), 1430–1433.

DeFries, R. S. and Townshend, J. R. G., NDVI-derived land-cover classifications at a global-scale. Int. J. Remote Sensing, 1994, 15(17), 3567–3586.

Potter, C. S., Terrestrial biomass and the effects of deforestation on the global carbon cycle. BioScience, 1999, 49(10), 769–778.

Kasischke, E. S., French, N. H., Harrell, P., Christensen, N. L., Ustin, S. L. and Barry, D., Monitoring of wildfires in boreal forests using large area AVHRR NDVI composite image data. Remote Sensing Environ., 1993, 45(1), 61–71.

Weishou, S., Di, J., Hui, Z., Shouguang, Y., Haidong, L. and Naifeng, L., The response relation between climate change and NDVI over the Qinghai–Tibet plateau. J. World Acad. Sci., Eng. Technol., 2011, 59, 2216–2222.

Jessica, P. K., Porwal, M. C., Roy, P. S. and Sandhya, G., Forest change detection in Kalarani round, Vadodara, Gujarat – a remote sensing and GIS approach. J. Indian Soc. Remote Sensing, 2001, 29, 129–135.

Macleod, R. D. and Congalton, R. G. A., Quantitative comparison of change detection algorithms for monitoring Eelgrass from remote sensed data. Photogramm. Eng. Remote Sensing, 1998, 64, 207–216.

Rahman, M. M., Temporal change detection of vegetation coverage in Patuakhali coastal area of Bangladesh using GIS and remotely sensed data. Int. J. Geomat. Geosci., 2013, 4(1), 36.

Amin, A. and Singh, S. K., Study of urban land use dynamics in Srinagar city using geospatial approach. Bull. Environ. Sci. Res., 2012, 1(2), 18–24.

Acharjee, S., Changmai, M., Bhattacharjee, S. and Mahanta, J., Forest cover change detection using remote sensing and GIS – a study of Jorhat and Golaghat Districts, Assam. Int. J. Environ. Resour., 2012, 1(2), 45–49.

Roy, D. P., The impact of misregistration upon composited wide field of view satellite data and implications for change detection. IEEE Trans. Geosci. Remote Sensing, 2000, 38(4), 2017–2032.

Fitter, A. H. et al., Relationship between first flowering date and temperature in the flora of a locality in central England. Funct. Ecol., 1995, 9, 55–60.

Kushwaha, C. P. and Singh, K. P., India needs phenological stations network. Curr. Sci., 2008, 95, 832–834.

Myneni, R., Keeling, B. C. D., Tucker, C. J., Asrar, G. and Nemani, R. R., Increased plant growth in the northern high latitudes from 1981 to 1991. Nature, 1997, 386(6626), 698–702.

Lechowicz, M. J. and Koike, T., Phenology and seasonality of woody plants: an unappreciated element in global change research? Can. J. Bot., 1995, 73, 175–182.

Kramer, K., Phenology and growth of European trees in relation to climate change. Ph D thesis, Landbouw Universiteit, Wageningen, 1996.

Parmesan, C. and Yohe, G., A globally coherent fingerprint of climate change impacts across natural systems. Nature, 2003, 421, 37–42.

Lal, M., Nozawa, T., Emori, S., Harasawa, H., Takahashi, K., Kimoto, M. and Numaguti, A., Future climate change: implications for Indian summer monsoon and its variability. Curr. Sci., 2001, 81(9), 1196–1207.

Ovaskainen, O., Skorokhodova, S., Yakovleva, M., Sukhov, A., Kutenkov, A., Kutenkova, N. and del Mar Delgado, M., Communitylevel phenological response to climate change. Proc. Natl. Acad. Sci., 2013, 110(33), 13434–13439.

Emanuel, W. R., Shugart, H. H. and Stevenson, M. P., Climatic change and the broad-scale distribution of terrestrial ecosystem complexes. Climate Change, 1985, 7(1), 29–43.

Thuiller, W., Biodiversity: climate change and the ecologist. Nature, 2007, 448(7153), 550–552.

Lavorel, S., McIntyre, S., Landsberg, J. and Forbes, T. D. A., Plant functional classifications: from general groups to specific groups based on response to disturbance. Trends Ecol. Evol., 1997, 12(12), 474–478.

Zeng, X., Shaikh, M., Dai, Y., Dickinson, R. E. and Myneni, R., Coupling of the common land model to the NCAR community climate model. J. Climate, 2002, 15(14), 1832–1854.

Foley, J. A., Levis, S., Prentice, I. C., Pollard, D. and Thompson, S. L., Coupling dynamic models of climate and vegetation. Global Change Biol., 1998, 4(5), 561–579.

Sitch, S. et al., Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Global Change Biol., 2003, 9(2), 161–185.

Clark, D. B. et al., The Joint UK Land Environment Simulator (JULES), model description-part 2: carbon fluxes and vegetation dynamics. Geosci. Model Dev., 2011, 4(3), 701.

Lotka, A. J., Elements of Physiological Biology, Dover Publications, New York, 1925.

Volterra, V., Fluctuation in the abundance of a species considered mathematically. Nature, 1926, 118(2972), 558–560.

Piao, S., Wang, X., Ciais, P., Zhu, B., Wang, T. A. O. and Liu, J. I. E., Changes in satellite‐derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006. Global Change Biol., 2011, 17(10), 3228–3239.

Eckert, S., Husler, F., Liniger, H. and Hodel, E., Trend analysis of MODIS NDVI time series for detecting land degradation and regeneration in Mongolia. J. Arid Environ., 2015, 113, 16–28.

Ning, T., Liu, W., Lin, W. and Song, X., NDVI variation and its responses to climate change on the northern loess plateau of China from 1998 to 2012. Adv. Meteorol., 2015, 1–10.

Li, Z., Nadon, S. and Cihlar, J., Satellite-based detection of Canadian boreal forest fires: development and application of the algorithm. Int. J. Remote Sensing, 2000, 21(16), 3057–3069.

Guo, Z. X., Wang, Z. M., Song, K. S., Zhang, B., Li, F. and Liu, D. W., Correlations between forest vegetation NDVI and water/thermal condition in Northeast China forest regions in 1982–2003. Chin. J. Ecol., 2007, 26(12), 1930–1936.

Effect of Reduced Traffic Density on Characteristics of Particulate Matter Over Delhi

Abstract Views :200 | PDF Views:85

Authors

Vikas Goel ¹, Sumit Kumar Mishra ¹, Ajit Ahlawat ¹, Chhemendra Sharma ¹, N. Vijayan ¹, S. R. Radhakrishnan ¹, A. P. Dimri ², R. K. Kotnala ¹

Affiliations
1 Environmental Sciences and Biomedical Metrology Division, CSIR-National Physical Laboratory, Dr K. S. Krishnan Marg, New Delhi - 110 012, IN
2 School of Environmental Sciences, Jawaharlal Nehru University, New Delhi - 110 067, IN

Source

Current Science, Vol 115, No 2 (2018), Pagination: 315-319

Abstract

Road rationing policy, implemented in Delhi from 1 to 15 January 2016, reduced the traffic density. This particular event serves an opportunity to study the effect of reduced traffic density over particulate matter (PM) characteristics. The mean PM_2.5 and black carbon (BC) mass concentration before, during and after the event were observed as 163.51 μg/m³ and 14.01 μg/ m³, 186.98 μg/ m³ and 19.87 μg/m³, 197.45 μg/m³ and 17.79 μg/m³ respectively. During the first week (1–7 January 2016), high PM_2.5 mass concentration was observed while in the second week (8–15 January 2016), the concentration was relatively low. The concentration of elements like P, Cu, As and Pb was observed to be minimum during the event.

Keywords

Black Carbon, Elemental Composition, PM_2.5.

Full Text

References

Beelen, R. et al., Long-term effects of traffic-related air pollution on mortality in a Dutch Cohort (NLCS-AIR Study). Environ. Health Perspect., 2007,116, 196–202.

Nemery, B., Hoet, P. H. and Nemmar, A., The Meuse Valley fog of 1930: an air pollution disaster. The Lancet, 2001, 357, 704–708.

Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D. and Pozzer, A., The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature, 2015, 525, 367–371.

Dee, D. P. et al., The ERA-interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc., 2011, 137, 553–597.

Sander, S. P. and Seinfeld, J. H., Chemical kinetics of homogeneous atmospheric oxidation of sulfur dioxide. Environ. Sci. Technol., 1976, 10, 1114–1123.

Tiwari, S., Srivastava, A. K., Bisht, D. S., Parmita, P., Srivastava, M. K. and Attri, S. D., Diurnal and seasonal variations of black carbon and PM2.5 over New Delhi, India: influence of meteorology. Atmospheric Res., 2013, 125–126, 50–62.

Bano, T. et al., Variation in aerosol black carbon concentration and its emission estimates at the mega-city Delhi. Int. J. Remote Sens., 2011, 32, 6749–6764.

Surendran, D. E., Beig, G., Ghude, S. D., Panicker, A. S., Manoj, M. G., Chate, D. M and Ali, K. A., Radiative forcing of black carbon over Delhi. Int. J. Photoenergy., 2013, 1–7.

Chan, D. and Stachowiak, G. W., Review of automotive brake friction materials. Proc. Inst. Mech. Eng. Part J. Automob. Eng., 2004,218, 953–966.

Figi, R., Nagel, O., Tuchschmid, M., Lienemann, P., Gfeller, U. and Bukowiecki, N., Quantitative analysis of heavy metals in automotive brake linings: a comparison between wet-chemistry based analysis and in-situ screening with a handheld X-ray fluorescence spectrometer. Anal. Chim. Acta., 2010, 676, 46–52.

Chen, J., Wang, W., Liu, H. and Ren, L., Determination of road dust loadings and chemical characteristics using resuspension. Environ. Monit. Assess., 2012, 184, 1693–1709.

Gunawardana, C., Goonetilleke, A., Egodawatta, P., Dawes, L. and Kokot, S., Source characterization of road dust based on chemical and mineralogical composition. Chemosphere, 2012, 87, 163–170.

Seinfeld, J. H. and Pandis, S. N., Atmospheric Chemistry and Physics: from Air Pollution to Climate Change. Wiley, 2006.

Li, W. and Shao, L., Characterization of mineral particles in winter fog of Beijing analyzed by TEM and SEM. Environ. Monit. Assess., 2010, 161, 565–573.

Shao, L., Shi, Z., Jones, T. P., Li, J. Whittaker, A. G. and Berube, K. A., Bioreactivity of particulate matter in Beijing air: results from plasmid DNA assay. Sci. Total Environ., 2006, 367, 261–272.

Wyzga, R. E. and Folinsbee, L. J., Health effects of acid aerosols. Water Air. Soil Pollut., 1995, 85, 177–188.

Cotton Crop in Changing Climate

Abstract Views :259 | PDF Views:90

Authors

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

Source

Current Science, Vol 115, No 5 (2018), Pagination: 948-954

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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References

Chapin III, F. S., Environmental controls over growth of tundra plants. In Proceedings of Symposium of Research in Arctic Life and Earth Sciences: Present Knowledge and Future Perspectives. Ecological Bulletins, No. 38, 1987, pp. 69–76.

Guinn, G., Hormonal relations during reproduction. In Cotton Physiology (eds Mauney, J. R. and Stewart, J. McD.), The Cotton Foundation, Memphis, TN, USA, 1986, pp. 113–136.

Hearn, A. B. and Constable, G. A., Irrigation for crops in a subhumid environment VII. Evaluation of irrigation strategies for cotton. Irrig. Sci., 1984, 5(2), 75–94.

Kramer, P. J., Drought, stress, and the origin of adaptations. Adaptation of plants to water and high temperature stress. 1980, pp. 7–20.

Kramer, P. J., Water deficits and plant growth. In Water Relations of Plants, Academic Press, New York, USA, 1983, pp. 342–389.

Turner, N. C. and Kramer, P. J. (eds), Drought Stress, and the Origin of Adaptations, John Wiley, 1980, pp. 7–20.

Khan, M. A., Soomro, A. W. and Arain, A. S., Effect of sowing dates on the yield components of some cotton genotypes. Pakistan Cotton, 1988.

Channa, M. H. and Baluch, A. H., Effect of different sowing dates on the yield of seed cotton under Sakrand [Pakistan] conditions. Pakistan Cotton, 1981.

Karim, A., Saeed, M., Tariq, A. and Shakir, Z. R., Effect of different sowing dates on the yield of seed cotton (Gossypium hirsutum L.) under Bahawalnagar conditions. Pak. Cotton, 1983, 27, 105– 109.

Farooq, A. et al., An overview of cotton leaf curl virus disease (CLCuD), a serious threat to cotton productivity. Austr. J. Crop Sci., 2011, 5(13), 1823.

Prasad, H., Nehra, P. L., Gothwal, D. K. and Singh, H., Effect of dates of sowing and spacing on seed cotton yield. J. Cotton Res. Dev., 2000, 14(2), 232–234.

Boote, K. J., Jones, J. W., Hoogenboom, G. and Pickering, N. B., The CROPGRO model for grain legumes. In Understanding Options for Agricultural Production. Systems Approaches for Sustainable Agricultural Development (eds Tsuji, G. Y., Hoogenboom, G. and Thornton, P. K.), Springer, 1998, vol. 7, pp. 99– 128.

Hoogenboom, G. et al., Decision support system for agrotechnology transfer version 4.0. University of Hawaii, Honolulu, HI, USA (CD-ROM), 2004.

Pathak, T. B., Fraisse, C. W., Jones, J. W., Messina, C. D. and Hoogenboom, G., Use of global sensitivity analysis for CROPGRO cotton model development. Trans. ASABE, 2007, 50(6), 2295–2302.

Swami, P., Maharshi, A. and Niwas, R., Effect of weather variability on phenological stages and growth indices in Bt-cotton under CLCuD incidence. J. Pure Appl. Microbiol., 2016, 10(2).

Kumar, N., Niwas, R., Khichar, M. L., Biswas, B. and Bishnoi, O. P., Performance of cotton varieties under different growing environments based on agrometeorological indices in semi arid conditions of Hisar. J. Cotton Res. Dev., 2012, 26(2), 199– 201.

Pettigrew, W. T., Physiological consequences of moisture deficit stress in cotton. Crop Sci., 2004, 44(4), 1265–1272.

Loka, D. A., Oosterhuis, D. M., Fernandez, C. J. and Roberts, B. A., The effect of water-deficit stress on the biochemistry of the cotton flower. In Summaries of Arkansas Cotton Research, 2011.

Loka, D., Effect of water-deficit stress on cotton during reproductive development. Theses and Dissertation, University of Arkansas, Fayetteville, 2012, vol. 5.

Pearson, R. W., Ratliff, L. F. and Taylor, H. M., Effect of soil temperature, strength, and pH on cotton seedling ischolar_main elongation. Agron. J., 1970, 62(2), 243–246.

On the Recent Floods in India

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Authors

Kamaljit Ray ¹, P. Pandey ², C. Pandey ³, A. P. Dimri ⁴, K. Kishore ⁵

Affiliations
1 India Meteorological Department, New Delhi 110 003, IN
2 CSIR-National Geophysical Research Institute, Hyderabad 500 007, IN
3 Wadia Institute of Himalayan Geology, Dehradun 248 001, IN
4 School of Environmental Sciences, Jawaharlal Nehru University, New Delhi 110 067, IN
5 National Disaster Management Agency, New Delhi 110 029, IN

Source

Current Science, Vol 117, No 2 (2019), Pagination: 204-218

Abstract

Floods in the Indian subcontinent have affected habitat, population, economy, etc. Due to the detrimental effects of recent floods on the economy, governance, etc., it is imperative to understand the associated dynamics, manifestations and fallouts for proper policy planning recommendations. The present study endeavours to provide an integrated rationale of meteorological and geomorphological aspects associated with four recent extreme floods in Uttarakhand (2013), Srinagar (2014), Chennai (2015) and Gujarat (2017). It is important to mention here that these floods occurred under different atmospheric circulations and geomorphological setting, and had an entirely different gambit for policy planning and governance. Consolidation of these issues will help policy planners and technologists, in case advance warning system based on these findings can be developed.

Keywords

Advance Warning System, Disaster Management, Floods, Governance, Policy Planning.

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References

Berz, G. et al., World map of natural hazards – a global view of the distribution and intensity of significant exposures. Nat. Hazards, 2001, 23, 443–465; doi:10.1023/A:1011193724026.

Valdiya, K. S., Geology, Environment and Society, University Press, Hyderabad, 2004, p. 229.

Korup, O. and Clague, J. J., Natural hazards, extreme events, and mountain topography. Quaternary Sci. Rev., 2009, 28(11), 977–990.

Goswami, B. N., Venugopal, V. and Sengupta, D., Increasing trend of extreme rain events over India in a warming environment. Science, 2006, 314, 1442–1445.

Rao, S. R., Dhakate, A. R., Saha, S. K., Mahapatra, S., Chaudhari, H. S., Pokhrel, S. and Sahu, S. K., Why is Indian Ocean warming consistently. Climate Change, 2012, 110, 709–719.

Roxy, M. K., Ritika, K., Terray, P., Murtugudde, R., Ashok, K. and Goswami, B. N., Drying of Indian subcontinent by rapid Indian Ocean warming and a weakening land–sea thermal gradient. Nature Commun., 2015, 6(7423), 1–10.

Gupta, A. K. and Nair, S. S., Urban floods in Bangalore and Chennai: risk management challenges and lessons for sustainable urban ecology. Curr. Sci., 2011, 100, 1638–1645.

Pai, D. S., Sridhar, L., Rajeevan, M., Sreejith, O. P., Satbhai, N. S. and Mukhopadhyay, B., Development of a new high spatial resolution (0.25° × 0.25°) long period (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region. MAUSAM, 2014, 65(1), 1–18.

Dhar, O. N. and Nandargi, S., Hydrometeorological aspects of floods in India. Nat. Hazards, 2003, 28, 1–33.

Sikka, D. R., Ray, K., Chakravarthy, K., Bhan, S. C. and Tyagi, A., Heavy rainfall in the Kedarnath valley of Uttarakhand during the advancing monsoon phase in June 2013. Curr. Sci., 2015, 109(2), 2353–2361.

Chevuturi, A. and Dimri, A. P., Investigation of Uttarakhand (India) disaster – 2013 using weather research and forecasting model. Nat. Hazards, 2016, 82(3), 1703–1726.

Pattanaik, D. R. and Rajeevan, M., Variability of extreme rainfall events over India during southwest monsoon season. Meteorol. Appl., 2010, 17(1), 88–104.

Niyas, N. T., Srivastava, A. K. and Hatwar, H. R., Variability and trend in the cyclonic storms over north Indian Ocean. Meteorological Monograph No. 3 Cyclone Warning-3/2009, 2009.

Karuna, S. S., Rajeevan, M. and Rao, S. V. B., On increasing monsoon rainstorms over India. Nature Hazards, 2016, doi:10.1007/s11069-016-2662-9.

Sen Roy, S. and Balling Jr, R. C., Trends in extreme daily precipitation indices in India. J. Climate, 2004, 24(4), 457–466.

Rakhecha, P. R. and Soman, M. K., Trends in the annual extreme rainfall events of 1 to 3 days duration over India. Theoret. Appl. Climatol., 1994, 48(4), 227–237.

Ramaswamy, C., Meteorological aspects of severe floods in India 1923–1979. Meteorological Monograph Hydrology No. 10/1987, India Meteorological Department (IMD), New Delhi, 1987.

Dhar, O. N. and Nandargi, S. S., The zones of severe rainstorm activity over India. Int. J. Climatol., 1993, 13(3), 301–305.

De, U. S., Singh, G. P. and Rase, D. M., Urban flooding in recent decades in four mega cities of India. J. Indian Geophys. Union, 2013, 17(2), 153–165.

Jenamani, R. K., Bhan, S. C. and Kalsi, S. R., Observational/ forecasting aspects of the meteorological event that caused a record highest rainfall in Mumbai. Curr. Sci., 2006, 90, 1344– 1362.

Lal, B., Jayanthi, N., Thakur Prasad, Rajeevan, M., Sunitha Devi, Srivastava, A. K. and Pai, D. S., Monsoon 2005, A Report, National Climate Centre, Indian Meteorological Department, Pune, 2006, pp. 42–57.

Shyamala, B. and Bhadram, C. V. V., Impact of mesoscale– synoptic scale interactions on the Mumbai historical rain event during 26–27 July 2005. Curr. Sci., 2006, 12, 1649–1654.

Vaidya, S. S. and Kulkarni, D. R., Simulation of heavy precipitation over Santacruz Mumbai on 26 July 2005 using Mesoscale model. Meteorol. Atmos. Phys., 2007, 98, 55–56.

Mohapatra, M., Kumar, N. and Bandyopadhyay, B. K., Role of mesoscale low and urbanization on exceptionally heavy rainfall event of 26 July 2005 over Mumbai: some observational evidences. MAUSAM, 2009, 60(3), 317–324.

Rao, Y. P., Southwest Monsoon, Meteorological Monograph. Synoptic Meteorology IMD, Pune, 1976, p. 367.

Mooley, D. A., The role of western disturbances in the production of weather over India during different seasons. Indian J. Metero. Geophys., 1957, 8, 253–260.

Dimri, A. P., Niyogi, D., Barros, A. P., Ridley, J., Mohanty, U. C., Yasunari, T. and Sikka, D. R., Western disturbance: a review. Rev. Geophys., 2015, 53(2), 225–246; http://dx.doi.org/10.1002/2014RG000460.

Sikka, D. R., Synoptic and mesoscale weather disturbances over south Asia during the southwest summer monsoon season. In The Global Monsoon System: Research Forecast (Chang, C. P. et al.), World Scientific, New Jersey, USA, 2011, 2nd edn, pp. 183–204.

Yadav, B. P., Khole, M. and Kumar, N., Unusual weather over northwest and west India during, November 2010. MAUSAM, 2013, 64(4), 699–710.

Dobhal, D. P., Gupta, A. K., Mehta, M. and Khandelwal, D. D., Kedarnath disaster: facts and plausible causes. Curr. Sci., 2013, 105(2), 171–174.

Dimri, A. P. et al., Cloudburst in Indian Himalayas: a review. Earth-Sci. Rev., 2017, 168, 1–23.

Houze Jr, R. A., Rasmussen, K. L., Medina, S., Brodzik, S. R. and Romatschke, U., Anomalous atmospheric events leading to the summer 2010 floods in Pakistan. Bull. Am. Meteorol. Soc., 2011, 92, 291–298; doi:10.1175/2010BAMS3173.1.

Medina, S., Houze Jr, R. A., Kumar, A. and Niyogi, D., Summer monsoon convection in the Himalayan region: terrain and land cover effects. Q. J. R. Meteorol. Soc., 2010, 136(648), 593–616.

Ananthakrishnan, R. and Bhatia, K. L., Tracks of monsoon depressions and their recurvature towards Kashmir. Monsoon of the World. India Meteorological Department, New Delhi, 1960, pp. 157–172.

Ghosh, S. K. and Veeraraghavan, K., Severe floods in Jammu and Kashmir in August 1973. Indian J. Meterol. Hydrol. Geophys., 1975, 26(2), 203–207.

Ray, K., Bhan, S. C. and Bandopadhyay, B. K., The catastrophe over Jammu and Kashmir in September 2014: a meteorological observational analysis. Curr. Sci., 2015, 109(3), 580–591.

Das, P. K., The Monsoon, National Book Trust of India, New Delhi, 1995, pp. 143–160.

Sengupta, S., Localised floods in Rajasthan owing to exceedingly heavy rains: case study of small scale accentuations in the Indian summer monsoon fields associated with intense upper anticyclonic shear zones. MAUSAM, 1986, 37(3), 385–390.

Ray, K., Mohanty, M. and Chincholikar, J. R., Climate variability over Gujarat, India. In ISPRS Archives XXXVIII-8/W3, Workshop Proceedings: Impact of Climate Change on Agriculture, Space Applications Centre (ISRO), Ahmedabad, 2009, pp. 38–43.

Mohanty, M., Ray, K. and Chakravarthy, K., Analysis of increasing heavy rainfall activity over western India, particularly Gujarat State in the past decade. In High-Impact Weather Events over the SAARC Region (eds Ray et al.), Springer, Cham, 2015; doi:10.1007/978-3-319-10217-7_17.

Rajeevan, M., Unnikrishnan, C. K., Bhate, J., Kumar, N. and Sreekala, P. P., Northeast monsoon over India: variability and prediction. Meteorol. Appl., 2012, 19, 226–236.

Krishnamurti, T. N., Jha, B., Rasch, P. J. and Ramanathan, V., High resolution global reanalysis highlighting the winter monsoon – Part I: reanalysis field. Meteorol. Atmos. Phys., 1997, 64, 123–150.

Krishnamurti, T. N., Jha, B., Rasch, P. J. and Ramanathan, V., High resolution global reanalysis highlighting the winter monsoon – Part II: transients and passive tracer transport. Meteorol. Atmos. Phys., 1997, 64, 151–171.

Krishnamurti, T. N., Tewari, N., Rajendran, K. and Gadgil, S., A heavy winter monsoon rainfall episode influenced by easterly waves, a westerly trough, blocking and the ITCZ. Weather, 2002, 57, 367–370.

Kripalani, R. H. and Kumar, P., Northeast monsoon rainfall variability over south peninsular India vis-à-vis Indian Ocean dipole mode. Int. J. Climatol., 2004, 24, 1267–1282.

Kamalji, R., Kannan, B. A. M., Stella, S., Sen, B., Sharma, P. and Thampi, S. B., Heavy rains over Chennai and surrounding areas as captured by Doppler weather radar during Northeast Monsoon 2015: a case study. In Remote Sensing of the Atmosphere, Clouds and Precipitation VI, International Society for Optics and Photonics, 2016, vol. 9876, p. 98762G; http://dx.doi.org/10.1117/12.2239563.

Valdiya, K. S., Damming rivers in the tectonically resurgent Uttarakhand Himalaya. Curr. Sci., 2014, 106(12), 1658– 1668.

Rana, N., Singh, S., Sundriyal, Y. P. and Juyal, N., Recent and past floods in the Alaknanda valley: causes and consequences. Curr. Sci., 2013, 105(9), 1209–1212.

Jones, E. J., Notes on the Kashmir earthquake of 30 May 1885. Rec. Geol. Surv. India, 1885, 18, 153–156.

Bilham, R. and Bali, B S., A ninth century earthquake-induced landslide and flood in the Kashmir Valley, and earthquake damage to Kashmir’s medieval temples. Bull. Earthq. Eng., 2013, 11, 1–31.

Bhatt, C. M. et al., Satellite-based assessment of the catastrophic Jhelum floods of September 2014, Jammu and Kashmir, India. Geomat. Nat. Haz. Risk, 2016; doi:10.1080/19475705.2016.1218943.

Farooq, M. and Muslim, M., Dynamics and forecasting of population growth and urban expansion in Srinagar city – a geospatial approach. Int. Arch. Photogramm., Remote Sensing Spat. Inf. Sci., 2014, XL-8, 709.

Meraj, G., Romshoo, S. A., Yousuf, A. R., Altaf, S. and Altaf, F., Assessing the influence of watershed characteristics on the flood vulnerability of Jhelum basin in Kashmir Himalaya. Nat. Haz., 2015, 77, 153–175; doi:10.1007/s11069-015-1605-1.

Joshi, P. K., Rashid, H. and Roy, P. S., Landscape dynamics in Hokersar wetland, Jammu and Kashmir – an application of geospatial approach. J. Indian Soc. Remote Sensing, 2002, 30, 1–5.

Romshoo, S. A., Ali, N. and Rashid, I., Geoinformatics for characterizing and understanding the spatio-temporal dynamics (1969 to 2008) of Hokersar wetland in Kashmir Himalayas. Int. J. Phys. Sci., 2011, 6, 1026–1038; doi:10.5897/IJPS10.378.

Dar, R. A., Romshoo, S. A., Chandra, R. and Ahmad, I., Tectonogeomorphic study of the Karewa Basin of Kashmir Valley. J. Asian Earth Sci., 2014, 92, 143–156.

The Upper Indus Basin Network

Climate Change, Cryosphere and Impacts in the Indian Himalayan Region

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Authors

A. P. Dimri ¹, S. Allen ², C. Huggel ³, S. Mal ⁴, J. A. Ballesteros-Cánovas ⁵, M. Rohrer ⁵, A. Shukla ⁶, P. Tiwari ⁷, P. Maharana ¹, T. Bolch ⁸, R. J. Thayyen ⁹, M. Stoffel ¹⁰, Aayushi Pandey ¹

Affiliations
1 School of Environmental Sciences, Jawaharlal Nehru University, New Delhi 110 067, IN
2 Department of Geography, University of Zurich, CH
3 Department of Geography, University of Zurich, SZ
4 Department of Geography, Shaheed Bhagat Singh College, University of Delhi, Delhi 110 017, IN
5 Institute for Environmental Sciences, University of Geneva, SZ
6 Ministry of Earth Sciences, New Delhi 110 003, IN
7 Department of Geography, Kumaon University, Nainital 263 001, IN
8 School of Geography and Sustainable Development, University of St Andrews, Scotland, GB
9 National Institute of Hydrology, Roorkee 247 667, IN
10 Department of Earth Sciences, University of Geneva, SZ

Source

Current Science, Vol 120, No 5 (2021), Pagination: 774-790

Abstract

Climate change and related impacts over the Indian Himalayan Region (IHR) remains poorly quantified. The present study reviews observed and modelled changes in the climate, cryosphere and impacts related to hazards, agriculture and ecosystems. An increasing temperature trend over the IHR is reported, which over a few locations is found to be higher than the global average. For precipitation, a complex and inconsistent response with considerable variation in the sign and magnitude of change is observed. Future projections show significant warming. Climate-driven changes and impacts are clearly observed. Snow cover has declined since the 1960s, with an enhanced decreasing trend during the 1990s and variable trends since 2000. Glaciers are losing mass and retreating at varying rates since the early 20th century, with an exception over the Karakoram region. An observed heterogeneous response of glaciers to atmospheric warming is controlled by regional variations in topography, debris cover, circulation and precipitation. Initial assessments of permafrost extent of 1 million km² across the IHR roughly translate into 14 times the glacier area. Extreme floods represent the most frequent natural disaster in the IHR. Studies have highlighted the significant threat from glacial lakes. Landslides occur in combination with heavy rainfall and flooding, with poor land-use practices such as road-cutting and deforestation being additional drivers. Climate change has also stressed traditional subsistence agriculture and food systems. Improving systematic and coordinated monitoring of climate and related impacts is crucial to contribute to effective climate change adaptation and response strategies.

Keywords

Climate Change, Cryosphere, Glacier, Permafrost, Run-off.

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Dimri, A. P.

Understanding the Linkages between Climate Change and Forest

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Effect of Reduced Traffic Density on Characteristics of Particulate Matter Over Delhi

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Cotton Crop in Changing Climate

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On the Recent Floods in India

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The Upper Indus Basin Network

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Climate Change, Cryosphere and Impacts in the Indian Himalayan Region

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