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Trend analysis of climatic variables in an arid and semi-arid region of the Ajmer District, Rajasthan, India

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Warianty tytułu
PL
Analiza trendu czynników klimatycznych na suchych i półsuchych obszarach dystryktu Ajmer w Radżasthanie, Indie
Języki publikacji
EN
Abstrakty
EN
In the present study, trends and variations in climatic variables (i.e. rainfall, wet day frequency, surface temperature, diurnal temperature, cloud cover, and reference and potential evapotranspiration) were analyzed on seasonal (monsoon and non-monsoon) and annual time scales for the Ajmer District of Rajasthan, India. This was done using non-parametric statistical techniques, i.e. the Mann–Kendall (MK) and Modified Mann–Kendall (MMK) tests, over a period of 100 years. The MK test with prewhitening (MK–PW) of climatic series was also applied to climatic variables and the results were compared to those obtained through the MK and MMK tests in order to assess the performance of trend detection methods. The Pettitt–Mann–Whitney (PMW) test was applied to detect the temporal shift in climatic series. The trend analysis revealed that annual and seasonal rainfall did not show any statistically significant trend at a 10% significant level. A noticeable trend increase was found in wet day frequency, surface temperature and reference evapotranspiration (ET) during the non-monsoon season from the three non-parametric statistical tests at a 10% significance level. A statistically significant decrease in maximum temperature was found during the non-monsoon season by the MK–PW test alone. This analysis of several climatic variables at the district scale is helpful for the planning and management of water resources and the development of adaptation strategies in adverse climatic conditions.
PL
W pracy analizowano trendy i zmienność czynników klimatycznych (opad, częstotliwość dni wilgotnych, temperaturę powierzchni ziemi, temperaturę dobową, zachmurzenie oraz ewapotranspirację wskaźnikową i potencjalną) w skali sezonowej i rocznej w dystrykcie Ajmer, w Radżasthanie (Indie). Analizę przeprowadzono za pomocą nieparametrycznych technik statystycznych Manna–Kendalla (MK) i zmodyfikowanej techniki MK (MMK) dla 100-letniego okresu. Test MK z eliminacją korelacji serii klimatycznych (prewhitening – MK–PW) zastosowano także do zmiennych klimatycznych, a wyniki porównano z uzyskanymi z użyciem testów MK i MMK, co pozwoliło na ocenę wiarygodności wykrywania trendu zmian w czasie. W celu wykrycia czasowych przesunięć serii klimatycznych zastosowano test Pettitta–Manna–Whitneya (PMW). Na podstawie analizy trendu stwierdzono, że opady roczne i sezonowe nie wykazywały statystycznie istotnego trendu na poziomie istotności 10%. Wykorzystując trzy testy nieparametryczne, stwierdzono rosnący trend w przypadku częstości występowania wilgotnych dni, temperatury powierzchni i ewapotranspiracji wskaźnikowej w okresie pozamonsunowym na poziomie istotności 10%. Statystycznie istotny spadek maksymalnej temperatury w tym okresie stwierdzono jedynie, gdy stosowano test MK–PW. Przedstawiona analiza kilku zmiennych klimatycznych w skali dystryktu może być pomocna w planowaniu i zarządzaniu zasobami wodnymi i w rozwoju strategii adaptacji do niekorzystnych warunków klimatycznych.
Wydawca
Rocznik
Tom
Strony
3--18
Opis fizyczny
Bibliogr. 66 poz., rys., tab.
Twórcy
  • Arba Minch University, Department of Water Resources and Irrigation Engineering, Arba Minch, Ethiopia
autor
  • Indian Institute of Technology Roorkee, Department of Water Resources Development and Management, Roorkee 247 667 (UA), India
autor
  • Malaviya National Institute of Technology, Department of Civil Engineering, Jaipur, Rajasthan, India
autor
  • McGill University, Faculty of Agricultural and Environmental Sciences, Department of Bioresource Engineering, Quebec, Canada, H9X 3V9
Bibliografia
  • ADAMOWSKI J., ADAMOWSKI K., BOUGADIS J. 2010. Influence of trend on short duration design storms. Water Resources Management. Vol. 24. Iss. 3 p. 401–413.
  • ADAMOWSKI J., CHAN H., PRASHER S., SHARDA V.N. 2012. Comparison of multivariate adaptive regression splines with coupled wavelet transform artificial neural networks for runoff forecasting in Himalayan microwatersheds with limited data. Journal of Hydroinformatics. Vol. 14. Iss. 3 p. 731–744.
  • ADAMOWSKI J., PROKOPH A. 2013. Assessing the impacts of the urban heat island effect on streamflow patterns in Ottawa, Canada. Journal of Hydrology. Vol. 496 p. 225–237.
  • ADAMOWSKI J., PROKOPH A., ADAMOWSKI K. 2012. Influence of the 11 year solar cycle on annual streamflow maxima in Southern Canada. Journal of Hydrology. Vol. 442 p. 55–62.
  • ADAMOWSKI K., PROKOPH A., ADAMOWSKI J. 2009. Development of a new method of wavelet aided trend detection and estimation. Hydrological Processes. Vol. 23. Iss. 18 p. 2686–2696.
  • ALLEN R.G., PEREIRA L.S., RAES D., SMITH M. 1998. Crop evapotranspiration: Guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper. No 56. Rome, Italy.
  • ARAGHI A., ADAMOWSKI J., NALLEY D., MALARD J. 2015. Using wavelet transforms to estimate surface temperature trends and dominant periodicities in Iran based on gridded reanalysis data. Atmospheric Research. Vol. 155 p. 52–72.
  • ARORA M., GOEL N.K., SINGH P. 2005. Evaluation of temperature trends over India. Hydrological Sciences Journal. Vol. 50. Iss. 1 p. 81–93.
  • BASISTHA A., ARYA D.S., GOEL N.K. 2009. Analysis of historical changes in rainfall in the Indian Himalayas. International Journal of Climatology. Vol. 29. Iss. 4 p. 555–572.
  • BASISTHA A., GOEL N.K., ARYA D.S., GANGWAR S.K. 2007. Spatial pattern of trends in Indian sub-divisional rainfall. Jalvigyan Sameeksha. Vol. 22 p. 47–57.
  • BELAYNEH A., ADAMOWSKI J., KHALIL B., OZGA-ZIELINSKI B. 2014. Long-term SPI drought forecasting in the Awash River Basin in Ethiopia using wavelet-support vector regression models. Journal of Hydrology. Vol. 508 p. 418–429.
  • BURN D.H., ELNUR M.A. 2002. Detection of hydrologic trends and variability. Journal of Hydrology. Vol. 255 p. 107–122.
  • BUTLER C., ADAMOWSKI J. 2015. Empowering marginalized communities in water resources management: Addressing inequitable practices in Participatory Model Building. Journal of Environmental Management. Vol. 153 p. 153–162.
  • CAMPISI S., ADAMOWSKI J., ORON G. 2012. Forecasting urban water demand via wavelet- denoising and neural network models. Case study: City of Syracuse, Italy. Water Resources Management. Vol. 26. Iss. 12 p. 3539–3558.
  • CUNDERLIK J.M., BURN D.H. 2004. Linkages between regional trends in monthly maximum flows and selected climatic variables. Journal of Hydrologic Engineering. Vol. 9. Iss. 4 p. 246–256.
  • DASH S.K., JENAMANI R.K., KALSI S.R., PANDA S.K. 2007. Some evidence of climate change in twentieth-century India. Climatic Change. Vol. 85. Iss. 3 p. 299–321.
  • DE U.S., RAO G.S.P. 2004. Urban climate trends – The Indian scenario. Journal of Indian Geophysical Union. Vol. 8. No 3 p. 199–203.
  • DUHAN D., PANDEY A. 2013. Statistical analysis of long term spatial and temporal trends of precipitation during 1901–2002 at Madhya Pradesh, India. Atmospheric Research. Vol. 122 p. 136–149.
  • GHOSH S., LUNIYA V., GUPTA A. 2009. Trend analysis of Indian summer monsoon rainfall at different spatial scales. Atmospheric Science Letters. Vol. 10. Iss. 4 p. 285–290.
  • GOWDA K.K., MAJUANTHA K., MANJUNATH B.M., PUTTY Y.R. 2008. Study of climate changes at Davangere region by using climatological data. Water and Energy International. Vol. 65. Iss. 3 p. 66–77.
  • HAIDARY A., AMIRI B.J., ADAMOWSKI J., FOHRER N., NAKANE K. 2013. Assessing the impacts of four land use types on the water quality of wetlands in Japan. Water Resources Management. Vol. 27. Iss. 7 p. 2217–2229.
  • HALBE J., ADAMOWSKI J., BENNETT E., PAHL-WOSTL C., FARAHBAKHSH K. 2014. Functional organization analysis for the design of sustainable engineering systems. Ecological Engineering. Vol. 73 p. 80–91.
  • HALBE J., PAHL-WOSTL C., SENDZIMIR J., ADAMOWSKI J. 2013. Towards adaptive and integrated management paradigms to meet the challenges of water governance. Water Science and Technology: Water Supply. Vol. 67 p. 2651–2660.
  • HAMED K.H., RAO A.R. 1998. A modified Mann-Kendall trend test for auto correlated data. Journal of Hydrology. Vol. 204 p. 182–196.
  • HELSEL D.R., HIRSCH R.M. 2002. Statistical methods in water resources. Techniques of water resources investigations. Book 4. Hydrologic analysis and interpretation. Chapter A3. U.S. Geological Survey pp. 522.
  • INAM A., ADAMOWSKI J., HALBE J., PRASHER S. 2015. Using causal loop diagrams for the initialization of stakeholder engagement in soil salinity management in agricultural watersheds in developing countries: A case study in the Rechna Doab watershed, Pakistan. Journal of Environmental Management. Vol. 152 p. 251–267.
  • IPCC 2001. Climate change 2001: The scientific basis. Contribution of Working Group to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Vol. 1. Cambridge Univ. Press. ISBN 0521014 956 pp. 881.
  • IPCC 2007. Climate change 2007: The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge Univ. Press. ISBN 978-0-521-70596-7 pp. 996.
  • JAIN S.K., KUMAR V., SAHARIA M. 2013. Analysis of rainfall and temperature trends in northeast India. International Journal of Climatology. Vol. 33. Iss. 4 p. 968–978.
  • KARPOUZOS D.K., KAVALIERATOU S., BABAJIMOPOULOS C. 2010. Trend analysis of precipitation data in Pieria region (Greece). European Water. Vol. 30 p. 31–40.
  • KENDALL M.G. 1955. Rank correlation methods. 2nd ed. London. Charles Griffin pp. 196.
  • KENDALL M.G. 1975. Rank Correlation Methods. 4th ed. London. Charles Griffin pp. 202.
  • KIELY G., ALBERTSON J.D., PARLANGE M.B. 1998. Recent trends in diurnal variation of precipitation at valentina on the West Coast of Ireland. Journal of Hydrology. Vol. 207. Iss. 3–4 p. 270–279.
  • KOLINJIVADI V., ADAMOWSKI J., KOSOY N. 2014a. Juggling multiple dimensions in a complex socioecosystem: The issue of targeting in payments for ecosystem services. GeoForum. Vol. 58 p. 1–13.
  • KOLINJIVADI V., ADAMOWSKI J., KOSOY N. 2014b. Recasting payments for ecosystem services (PES) in water resource management: A novel institutional approach. Ecosystem Services. Vol. 10 p. 144–154.
  • KOTHAWALE D.R., KUMAR R. 2005. On the recent changes in surface temperature trends over India. Geophysical Research Letters. Vol. 32. Iss. 18. L18714. DOI: 10.1029/2005GL023528.
  • KOTHYARI U.C., SINGH V.P. 1996. Rainfall and temperature trends in India. Hydrological Processes. Vol. 10. Iss. 3 p. 357–372.
  • KUMAR V., JAIN S.K., SINGH Y. 2010. Analysis of longterm rainfall trends in India. Hydrological Sciences Journal. Vol. 55. Iss. 4 p. 484–496.
  • LUDWIG W., SERRAT P., CESMAT L., ESTEVES J.G. 2004. Evaluating the impact of the recent temperature increase on the hydrology of the Têt River (Southern France). Journal of Hydrology. Vol. 289. Iss. 1. p. 204–221.
  • LUO Y., LIO S., SHENG L., FU S., LIU J., WANG G., ZHOU G. 2008. Trends of precipitation in Beijiang River Basin, Guangdong Province, China. Hydrological Processes. Vol. 22. Iss. 13 p. 2377–2386.
  • MANN H.B. 1945. Non-parametric test against trend. Econometrica. Vol. 13 p. 245–259.
  • MCBEAN E., MOTIEE H. 2008. Assessment of impacts of climate change on water resources: a long term analysis of the Great Lakes of North America. Hydrology and Earth System Sciences. Vol. 12. Iss. 1 p. 239–255.
  • MITCHELL T.D., JONES P.D. 2005. An improved method of constructing a database of monthly climate observations and associated high resolution grids. International Journal of Climatology. Vol. 25. Iss. 6 p. 693–712.
  • MODARRES R., DA SILVA R.V.P. 2007. Rainfall trends in arid and semi-arid regions of Iran. Journal of Arid Environment. Vol. 70. Iss. 2 p. 344–355.
  • NALLEY D., ADAMOWSKI J., KHALIL B. 2012. Using discrete wavelet transforms to analyze trends in streamflow and precipitation in Quebec and Ontario (1954–2008). Journal of Hydrology. Vol. 475 p. 204–228.
  • NALLEY D., ADAMOWSKI J., KHALIL B., OZGA-ZIELINSKI B. 2013. Trend detection in surface air temperature in Ontario and Quebec, Canada during 1967–2006 using the discrete wavelet transform. Atmospheric Research. Vol. 132–133 p. 375–398.
  • NAPCC 2008. National Action Plan for Climate Change [online]. [Access 15.12.2015]. Available at: http://www.moef.nic.in/downloads/home/Pg01-52.pdf
  • PANT G.B., KUMAR K.R. 1997. Climates of South Asia. John Wiley. ISBN 978-0-471-94948-0 pp. 344.
  • PATRA J.P., MISHRA A., SINGH R., RAGHUWANSHI N.S. 2012. Detecting rainfall trends in twentieth century (1871–2006) over Orissa State, India. Climatic Change. Vol. 111. Iss. 3 p. 801–817.
  • PETTITT A.N. 1979. A non-parametric approach to the change-point problem. Applied Statistics. Vol. 28. No. 2 p. 126–135.
  • PINGALE S., ADAMOWSKI J., JAT M., KHARE D. 2015. Implications of spatial scale on climate change assessments. Journal of Water and Land Development. No. 26 p. 37–56.
  • PINGALE S., KHARE D., JAT M., ADAMOWSKI J. 2014. Spatial and temporal trends of mean and extreme rainfall and temperature for the 33 urban centres of the arid and semi-arid state of Rajasthan, India. Atmospheric Research. Vol. 138 p. 73–90.
  • RAI R.K., UPADHYAY A., OJHA C.S.P. 2010. Temporal variability of climatic parameters of Yamuna River basin: spatial analysis of persistence, trend and periodicity. Open Hydrology Journal. Vol. 4. Iss. 1 p. 184–210.
  • Registrar General, India. 2011. Census of India 2011: provisional population totals-India data sheet. Office of the Registrar General Census Commissioner, India. Indian Census Bureau.
  • SAADAT H., ADAMOWSKI J., BONNELL R., SHARIFI F., NAMDAR M., ALE-EBRAHIM S. 2011. Land use and land cover classification over a large area in Iran based on single date analysis of satellite imagery. Journal of Photogrammetry and Remote Sensing. Vol. 66. Iss. 5 p. 608–619.
  • SEN P.K. 1968. Estimates of the regression coefficient based on Kendall’s tau. Journal of the American Statistical Association. Vol. 63. Iss. 324 p. 1379–1389.
  • SINGH P., KUMAR V., THOMAS T., ARORA M. 2008. Basinwide assessment of temperature trends in northwest and central India. Hydrological Sciences Journal. Vol. 53. Iss. 2 p. 421–433.
  • STRAITH D., ADAMOWSKI J., REILLY K. 2014. Exploring the attributes, strategies and contextual knowledge of champions of change in the Canadian water sector. Canadian Water Resources Journal. Vol. 39. Iss. 3 p. 255–269.
  • THEIL H. 1950. A rank-invariant method of linear and polynomial regression analysis. I, II, III. Proceedings of the Royal Netherlands Academy of Sciences. No 53 p. 386–392, 521–525, 1397–1412.
  • TIWARI M., ADAMOWSKI J. 2014. Urban water demand forecasting and uncertainty assessment using ensemble wavelet-bootstrap-neural network models. Water Resources Research. Vol. 49. Iss. 10 p. 6486–6507.
  • WAGESHO N., GOEL N.K., JAIN M.K. 2013. Temporal and spatial variability of annual and seasonal rainfall over Ethiopia. Hydrological Sciences Journal. Vol. 58. Iss. 2 p. 354–373.
  • YEVJEVICH V. 1972. Stochastic processes in hydrology. Fort Collins: CO. Water Resources Publications pp. 276.
  • YOON W.S., LEE D.K. 2003. The development of the evaluation model of climate changes and air pollution for sustainability of cities in Korea. Landscape and Urban Planning. Vol. 63. Iss. 3 p. 145–160.
  • YUE S., HASHINO M. 2003. Long term trends of annual and monthly precipitation in Japan. Journal of the American Water Resources Association. Vol. 39. Iss. 3 p. 587–596.
  • YUE S., PILON P. 2004. A comparison of the power of the test, Mann–Kendall and bootstrap tests for trend detection. Hydrological Sciences Journal. Vol. 49. Iss. 1 p. 21–37.
  • ZHANG X.B., ZWIERS F.W., LI G.L. 2004. Monte Carlo experiments on the direction of trends in extreme values. Journal of Climate. Vol. 17 p. 1945–1952.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-adc78696-9ee3-47be-88ba-14388078522d
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