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Geospatial Analysis of the Impact of Flood and Drought Hazards on Crop Land and Its Relationship with Human Migration at the District Level in Uttar Pradesh, India
Corresponding Author(s) : Sudhir Kumar Singh
Geomatics and Environmental Engineering,
Vol. 15 No. 4 (2021): Geomatics and Environmental Engineering
Abstract
The main objective was to explore the connection between flood and drought hazards and their impact on crop land and human migration. The Flood and Drought effect on Cropland Index (FDCI), hot spot analysis and the Global Regression Analysis method was applied for the identification of the relationship between human migration and flood and drought hazards. The spatial pattern and hot and cold spots of FDCI, spatial autocorrelation and Getis-OrdGi* statistic techniques were used respectively. The FDCI was taken as an explanatory variable and human migration was taken as a dependent variable in the environment of the geographically weighted regression (GWR) model which was applied to measure the impact of flood and drought hazards on human migration. FDCI suggests a z-score of 4.9, which shows that the impact of flood and drought frequency on crop land is highly clustered. In the case of the hot spots analysis, out of seventy districts in Uttar Pradesh twenty-one were classified as hot spot and eight were classified as cold spots with a confidence level of 90 to 99%. Hot spot indicate maximum and cold spots show minimum impact of flood and drought hazards on crop land. The impact of flood and drought hazards on human migration show that there are fourteen districts where migration out is far more than predicted while there are ten districts where migration out is far lower.
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- Adamo S.B., Izazola H.: Human migration and the environment. Population and Environment, vol. 32(2–3), 2010, pp. 105–108. https://doi.org/10.1007/s11111-010-0130-0.
- Lonergan S.: The role of environmental degradation in population displacement. Environmental Change and Security Project Report, iss. 4, Spring 1998, pp. 5–15.
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- Lewandowska-Gwarda K.: Geographically weighted regression in the analysis of unemployment in Poland. ISPRS International Journal of Geo-Information, vol. 7(1), 2018, pp. 1–16. https://doi.org/10.3390/ijgi7010017.
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References
Adamo S.B., Izazola H.: Human migration and the environment. Population and Environment, vol. 32(2–3), 2010, pp. 105–108. https://doi.org/10.1007/s11111-010-0130-0.
Lonergan S.: The role of environmental degradation in population displacement. Environmental Change and Security Project Report, iss. 4, Spring 1998, pp. 5–15.
Lehner B., Döll P., Alcamo J., Henrichs T., Kaspar F.: Estimating the impact of global change on flood and drought risks in Europe: a continental, integrated analysis. Climatic Change, vol. 75(3), 2006, pp. 273–299. https://doi.org/10.1007/s10584-006-6338-4.
Yang C., Yu Z., Hao Z., Zhang J., Zhu J.: Impact of climate change on flood and drought events in Huaihe River Basin, China. Hydrology Research, vol. 43(1–2), 2012, pp. 14–22. https://doi.org/10.2166/nh.2011.112.
United Nations Development Programme (UNDP): India. https://www.adaptation-undp.org/explore/india [access: 30.04.2020].
Parthasarathy B., Sontakke N.A., Monot A.A., Kothawale D.R.: Droughts/floods in the summer monsoon season over different meteorological subdivisions of India for the period 1871–1984. Journal of Climatology, vol. 7(1), 1987, pp. 57–70. https://doi.org/10.1002/joc.3370070106.
Nath R., Nath D., Li Q., Chen W., Cui X.: Impact of drought on agriculture in the Indo-Gangetic Plain, India. Advances in Atmospheric Sciences, vol. 34(3), 2017, pp. 335–346. https://doi.org/10.1007/s00376-016-6102-2.
Perch-Nielsen S.L., Bättig M.B., Imboden D.: Exploring the link between climate change and migration. Climatic Change, vol. 91(3–4), 2008, 375. https://doi.org/10.1007/s10584-008-9416-y.
Reza M.I.H., Alatas S.M.: Migration in the Context of Disaster Management: Governance, Vulnerabilities and Security a Malaysian perspective. [in:] International Conference, On the Move: Critical Migration Themes in ASEAN, Chulalongkorn University, Thailand, 2012. http://dx.doi.org/10.13140/2.1.3997.1846.
Leighton M.: Desertification and migration. [in:] Johnson P.M., Mayrand K., Paquin M. (eds.), Governing Global Desertification: Linking Environmental Degradation, Poverty and Participation, Ashgate, Hampshire 2006, pp. 43–58. https://doi.org/10.4324/9781315253916.
Tran T.A.: Land use change driven out-migration: Evidence from three flood-prone communities in the Vietnamese Mekong Delta. Land Use Policy, vol. 88, 2019, 104157. https://doi.org/10.1016/j.landusepol.2019.104157.
Sarkar P.: An overview of out-migration from Uttar Pradesh using census 2011. Journal of Migration Affairs, vol. II(2), 2020, pp. 58–66. https://doi.org/10.36931/jma.2020.2.2.58-66.
Maharjan A., Kochhar I., Chitale V.S., Hussain A., Gioli G.: Understanding rural outmigration and agricultural land use change in the Gandaki Basin, Ne- pal. Applied Geography, vol. 124, 2020, 102278. https://doi.org/10.1016/j.apgeog.2020.102278.
Berlemann M., Tran T.X.: Climate-Related Hazards and Internal Migration Em- pirical Evidence for Rural Vietnam. Economics of Disasters and Climate Change, vol. 4(2), 2020, pp. 385–409. https://doi.org/10.1007/s41885-020-00062-3.
Ramankutty N., Evan A.T., Monfreda C., Foley J.A.: Global Agricultural Lands: Croplands, 2000. NASA Socioeconomic Data and Applications Cen- ter (SEDAC), Palisades, NY, 2010. https://doi.org/10.7927/H4C8276G.
Center for Hazards and Risk Research – CHRR – Columbia University, and Center for International Earth Science Information Network – CIESIN – Columbia University: Global Flood Hazard Frequency and Distribution. NASA So- cioeconomic Data and Applications Center (SEDAC), Palisades, NY, 2005. https://doi.org/10.7927/H4668B3D [access: 5.04.2020].
Islam Z., Ranganathan M., Bagyaraj M., Singh S.K., Gautam S.K.: Multi- decadal groundwater variability analysis using geostatistical method for ground- water sustainability. Environment, Development and Sustainability, 2021, pp. 1–19. https://doi.org/10.1007/s10668-021-01563-1.
Lewandowska-Gwarda K.: Geographically weighted regression in the analysis of unemployment in Poland. ISPRS International Journal of Geo-Information, vol. 7(1), 2018, pp. 1–16. https://doi.org/10.3390/ijgi7010017.
Columbia Public Health: Population Health Methods – Geographically Weighted Regression. https://www.publichealth.columbia.edu/research/population-health-methods/geographically-weighted-regression/ [access: 27.08.2021].