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2024 | Vol. 72, no. 2 | 1143--1158
Tytuł artykułu

Characterizing spatiotemporal properties of precipitation in the middle Mahanadi subdivision, India during 1901-2017

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Języki publikacji
EN
Abstrakty
EN
Long-term historical data and their interpretation are crucial aspects of understanding any kind of variation that exists as a result of changing environmental behaviour. The focus of the study is to characterize precipitation properties in the middle subdivision of the Mahanadi River basin (MRB). An eigen-based technique, also known as the maximum loading value approach, and gridded precipitation data with a resolution of 0.25° X 0.25° are presented to analyze the spatiotemporal properties of precipitation at different timeslot intervals. The meteorological data (gridded precipitation for 117 years from 1901 to 2017) has a special “k” field for spatial and temporal modes of spatial pattern analysis, which aids in the recognition of precipitation properties. The identified characteristics of the exclusive timeslot periods have been assessed for any dispersion as a function of annual precipitation. To cross-validate the identified patterns for distinctness and pairwise comparison, the Kolmogorov-Smirnov’s D test was used. Southwest Mahanadi does not experience much variation in pattern size (± 3-5%), with a maximum variance of 39.09% during timeslot 2 (1940-1978). Similarly, the southeast Mahanadi observed a continuous increase in pattern size and was above 10% with a maximum variance of 28.53% during timeslot 3 (1979-2 017). While north-eastern Mahanadi experienced a continuous and significant decrease of > 14% of the total variance, with a maximum (42.48%) during timeslot 1 (1901-1939) and a minimum (28.14%) during timeslot 3 (1979-2017). There is no spatial pattern variability from summer to any of the timeslot intervals.
Wydawca

Czasopismo
Rocznik
Strony
1143--1158
Opis fizyczny
Bibliogr. 57 poz.
Twórcy
  • Civil Engineering Department, National Institute of Technology Raipur, Great-Eastern Road, Raipur, Chhattisgarh 492010, India, ramgopal_sahu@yahoo.com
  • Civil Engineering Department, National Institute of Technology Raipur, Great-Eastern Road, Raipur, Chhattisgarh 492010, India, shashiv50@gmail.com
  • Civil Engineering Department, National Institute of Technology Raipur, Great-Eastern Road, Raipur, Chhattisgarh 492010, India, manikverma.ce@nitrr.ac.in
  • Civil Engineering Department, National Institute of Technology Raipur, Great-Eastern Road, Raipur, Chhattisgarh 492010, India, iahmad.ce@nitrr.ac.in
Bibliografia
  • 1. Aher S, Shinde S, Gawali P, Deshmukh P, Venkata LB (2019) Spatio-temporal analysis and estimation of rainfall variability in and around upper Godavari River basin. India Arabian J Geosci 12(22):1-16. https://doi.org/10.1007/s12517-019-4869-z
  • 2. Azharuddin M, Verma S, Verma MK, Prasad AD (2022) A synopticscale assessment of flood events and ENSO—Streamflow Variability in Sheonath River Basin, India. In: Rao CM, Patra KC, Jhajharia D, Kumari S (eds) Advanced Modelling and Innovations in Water Resources Engineering. Lecture Notes in Civil Engineering, vol 176. Springer, Singapore, 93-104, https://doi.org/ 10.1007/978-981-16-4629-4_8
  • 3. Bharath R, Srinivas VV (2015) Regionalization of extreme rainfall in India. Int J Climatol 35(6):1142-1156. https://doi.org/10.1002/ joc.4044
  • 4. Cattell RB (1966) The scree test for the number of factors. Multivar Behav Res 1(2):245-276. https://doi.org/10.1207/s15327906m br0102_10
  • 5. Conover WJ (1998) Practical nonparametric statistics. John Wiley & Sons, New York
  • 6. Dhiwar BK, Verma S, Prasad AD (2022) Identification of flood vulnerable area for kharun river basin by GIS Techniques. In: Rao CM, Patra KC, Jhajharia D, Kumari S (eds) Advanced Modelling and Innovations in Water Resources Engineering. Lecture Notes in Civil Engineering, vol 176. Springer, Singapore, 385-408, https:// doi.org/10.1007/978-981-16-4629-4_27
  • 7. Gabriele S, Arnell N (1991) A hierarchical approach to regional flood frequency analysis. Water Resour Res 27(6):1281-1289. https://doi.org/10.1029/91WR00238
  • 8. Gadgil S, Yadumani JNV (1993) Coherent rainfall zones of the Indian region. Int J Climatol 13(5):547-566. https://doi.org/ 10.1002/joc.3370130506
  • 9. Gadgil S, Gowri R, Yadumani (1988) Coherent rainfall zones: case study for Karnataka. Proceed Indian Acad Sci- Earth Planetary Sci 97(1):63-79. https://doi.org/10.1007/BF02861628
  • 10. Garcia-Marin AP, Ayuso-Munoz JL, Taguas-Ruiz EV, Estevez J (2011) Regional analysis of the annual maximum daily rainfall in the province of Malaga (southern Spain) using the principal component analysis. Water and Environ J 25(4):522-531. https://doi.org/10.1111/j.1747-6593.2011.00251.x
  • 11. Goswami UP, Goyal MK (2022) Relative Contribution of Climate Variables on Long-Term Runoff Using Budyko Framework. In: Kumar P, Nigam GK, Sinha MK, Singh A (eds) Water Resources Management and Sustainability. Advances in Geographical and Environmental Sciences. Springer, Singapore, 147-159, https://doi.org/10.1007/978-981-16-6573-8_7
  • 12. Goswami UP, Hazra B, Goyal MK (2018) Copula-based probabilistic characterization of precipitation extremes over North Sikkim Himalaya. Atmos Res 212:273-284. https://doi.org/10.1016/j. atmosres.2018.05.019
  • 13. Gupta K, Kar A, Jena J, Jena D (2017) Forecasting the rainfall pattern on Upstream of Hirakud reservoir using L-moment for accessing the inflow. J Water Resour Prot 9:1335-1346. https:// doi.org/10.4236/jwarp.2017.912085
  • 14. Horn JL (1965) A rationale and test for the number of factors in factor analysis. Psychometrika 30:179-185. https://doi.org/10. 1007/BF02289447
  • 15. Huang Y, Wang H, Xiao W, Chen LH, Yan DH, Zhou YY, Jiang DC, Yang MZ (2018) Spatial and temporal variability in the precipitation concentration in the upper reaches of the Hongshui River basin, southwestern China. Adv Meteorol. https://doi.org/ 10.1155/2018/4329757
  • 16. Kaiser HF (1960) The application of electronic computers to factor analysis. Educ Psychol Measur 20(1):141-151. https://doi.org/ 10.1177/001316446002000116
  • 17. Khaniya B, Priyantha HG, Baduge N, Azamathulla HM, Rathnay-ake U (2020) Impact of climate variability on hydropower generation: a case study from Sri Lanka. ISH J Hydraulic Eng 26(3):301-309. https://doi.org/10.1080/09715010.2018.14855 16
  • 18. Kosambi, DD (2016) Statistics in function space. In: Ramaswamy, R (eds) D.D. Kosambi. Springer, New Delhi, https://doi.org/10. 1007/978-81-322-3676-4_15
  • 19. Kumar MD, Bassi N (2021) The Climate Challenge in Managing Water: Evidence Based on Projections in the Mahanadi River Basin India. Front Water 3:662560. https://doi.org/10.3389/frwa. 2021.662560
  • 20. Lawley DN (1956) Tests for significance for the latent roots of covariance and correlation matrices. Biometrica 43(1-2):128-136. https://doi.org/10.1093/biomet/43.1-2.128
  • 21. Lee J, Kim S, Ikehara M, Horikawa K, Asahara Y, Yoo CM, Khim BK (2023) Indian monsoon variability in the Mahanadi Basin over the last two glacial cycles and its implications on the Indonesian throughflow. Geosci Front 14(1):101483. https://doi.org/10. 1016/j.gsf.2022.101483
  • 22. Mehta D, Yadav SM (2021a) An analysis of rainfall variability and drought over Barmer District of Rajasthan. Northwest India Water Supply 21(5):2505-2517. https://doi.org/10.2166/ws.2021.053
  • 23. Mehta D, Yadav SM (2021b) Meteorological drought analysis in Pali District of Rajasthan State using standard precipitation index. Int J Hydrol Sci Technol 15(1):1-10. https://doi.org/10.1504/IJHST. 2023.127880
  • 24. Mehta D, Yadav SM (2021c) Analysis of long-term rainfall trends in Rajasthan, India. In: Jha R, Singh VP, Singh V, Roy LB, Thendi-yath R (eds) Climate Change Impacts on Water Resources. Water Science and Technology Library, vol 98. Springer, Cham, 293306. https://doi.org/10.1007/978-3-030-64202-0_26
  • 25. Mehta D, Yadav SM (2022a) Temporal analysis of rainfall and drought characteristics over Jalore District of SW Rajasthan. Water Practice Technol 17(1):254-267. https://doi.org/10.2166/wpt.2021.114
  • 26. Mehta D, Yadav SM (2022b) Long-term trend analysis of climate variables for arid and semi-arid regions of an Indian State Rajasthan. Int J Hydrol Sci Technol 13(2):191-214. https://doi.org/10.1504/ IJHST.2022.120639
  • 27. North GR, Bell TL, Cahalan RF, Moeng FJ (1982) Sampling errors in the estimation of empirical orthogonal functions. Mon Weather Rev 110(7):699-706. https://doi.org/10.1175/1520-0493(1982) 110%3C0699:SEITEO%3E2.0.CO;2
  • 28. Pastagia J, Mehta D (2022) Application of innovative trend analysis on rainfall time series over Rajsamand district of Rajasthan state. Water Supply 22(9):7189-7196. https://doi.org/10.2166/ws.2022. 276
  • 29. Pearson K (1901) LIII. On lines and planes of closest fit to systems of points in space. The London, Edinburgh, and Dublin Philosophical Magazine and J Sci 2(11):559-572. https://doi.org/10.1080/ 14786440109462720
  • 30. Perera A, Mudannayake SD, Azamathulla HM, Rathnayake U (2020) Recent climatic trends in Trinidad and Tobago, West Indies. Asia-Pacific J Sci Technol 25(2):1-11
  • 31. Prabhakar AK, Singh KK, Lohani AK, Chandniha SK (2019) Assessment of regional-level long-term gridded rainfall variability over the Odisha State of India. Appl Water Sci 9(4):1-15. https://doi. org/10.1007/s13201-019-0975-z
  • 32. Pradhan D, Sahu RT, Verma MK (2022) Flood inundation mapping using GIS and Hydraulic model (HEC-RAS): a case study of the Burhi Gandak river, Bihar, India. In: Kumar R, Chang WA, Sharma TK, Verma OP, Agarwal A (eds) Soft Computing: Theories and Applications. Lecture Notes in Networks and Systems, vol 425. Springer: Singapore, https://doi.org/10.1007/978-981-19-0707-4_14
  • 33. Rajeevan M, Bhate J, Kale JD, Lal B (2005) Development of a high resolution daily gridded rainfall data for the Indian Region (version 2), Meteorol. Monogr. Climatol. 22/2005, India Meteorol. Dep., New Delhi.
  • 34. Rajeevan M, Bhate J, Kale JD, Lal B (2006) High resolution daily gridded rainfall data for the Indian region: analysis of break and active monsoon spells. Current Sci 91(3):296-306
  • 35. Raziei T (2018) A precipitation regionalization and regime for Iran based on multivariate analysis. Theoret Appl Climatol 131(3):1429-1448. https://doi.org/10.1007/s00704-017-2065-1
  • 36. Roushangar K, Alizadeh F, Adamowski J (2018) Exploring the effects of climatic variables on monthly precipitation variation using a continuous wavelet-based multiscale entropy approach. Environ Res 165:176-192. https://doi.org/10.1016/j.envres.2018.04.017
  • 37. Sahu N, Panda A, Nayak S, Saini A, Mishra M, Sayama T, Sahu L, Duan W, Avtar R, Behera S (2020) Impact of indo-pacific climate variability on high streamflow events in mahanadi river basin. India Water 12(7):1952. https://doi.org/10.3390/w12071952
  • 38. Sahu RT, Verma MK, Ahmad I (2021a) Some non-uniformity patterns spread over the lower Mahanadi River basin. India Geocarto Int 37(25):8792-8814. https://doi.org/10.1080/10106049.2021. 2005699
  • 39. Sahu RT, Verma MK, Ahmad I (2021b) Regional Frequency Analysis Using L-Moment Methodology—A Review. In: Pathak KK, Bandara JMSJ and Agrawal R (eds) Recent Trends in Civil Engineering. Lecture Notes in Civil Engineering, vol 77. Singapore, Springer, 811-832, https://doi.org/10.1007/978-981-15-5195-6_ 60
  • 40. Sahu RT, Verma MK, Ahmad I (2021c) Segmental variability of precipitation in the Mahanadi River basin during 1901-2017. 24 August 2021c, PREPRINT (Version 1) available at Research Square. https://doi.org/10.21203/rs.3.rs-542786/v1
  • 41. Sahu RT, Verma MK, Ahmad I (2021d) Characterization of precipitation in the sub-divisions of the Mahanadi River basin India. Acta Sci Agriculture 5(12):50-61. https://doi.org/10.31080/ASAG. 2021.05.1085
  • 42. Sahu RT, Verma MK, Ahmad I (2022a) Segmental variability of precipitation in the Mahanadi River basin from 1901 to 2017. Geo-carto Int 37(27):14877-14898. https://doi.org/10.1080/10106049. 2022.2091163
  • 43. Sahu RT, Verma S, Kumar K, Verma MK, Ahmad I (2022b) Testing some grouping methods to achieve a low error quantile estimate for high resolution (0 25° x 0 25°) precipitation data. J Phys Conf Ser 2273:012017. https://doi.org/10.1088/1742-6596/2273/1/ 012017
  • 44. Sahu RT, Verma MK, Ahmad I (2022c) Interpreting different timeslot precipitation characteristics in the Seonath River basin, Chhattisgarh during 1901-2017. In Reddy, K.R., Kalia, S., Tangellapalli, S., Prakash, D., editors. Recent Advances in Sustainable Environment. Lecture Notes in Civil Engineering. vol 285. Springer: Singapore, pp. 21-37. https://doi.org/10.1007/978-981-19-5077-3_3
  • 45. Sahu RT, Verma MK, Ahmad I (2023a) Density-based spatial clustering of application with noise approach for regionalisation and its effect on hierarchical clustering. Int J Hydrol Sci Technol. https:// doi.org/10.1504/IJHST.2022.10048476
  • 46. Sahu RT, Kumar K, Verma MK (2023b) Impact of long-distance interaction indicator (monsoon indices) on spatio-temporal variability of precipitation over the Mahanadi River basin [Manuscript submitted for publication]. Civil Engineering Department, National Institute of Technology, Raipur
  • 47. Sahu RT, Kumar K, Verma MK (2023c) Trend analysis of rainfall in India with wavelet synopsis [Manuscript submitted for publication]. Civil Engineering Department, National Institute of Technology, Raipur
  • 48. Shepard D (1968) A two-dimensional interpolation function for irregularly spaced data. In: 23rd ACM National Conference, January 1968, Association for Computing Machinery, New York, 517524. https://doi.org/10.1145/800186.810616
  • 49. Shukla J (1987) Interannual variability of monsoons. In: Fein JS, Stephens PL (eds) Monsoons. Wiley and sons, New York, Chapter 14, 399-464.
  • 50. Singh G, Panda RK, Nair A (2020) Regional scale trend and variability of rainfall pattern over agro-climatic zones in the mid-Mahanadi River basin of eastern India. J Hydro-Environ Res 29:5-19. https://doi.org/10.1016/j.jher.2019.11.001
  • 51. Verma S, Prasad AD, Verma MK (2021) Trend Analysis and Rainfall Variability of Monthly Rainfall in Sheonath River Basin, Chhattisgarh. In: Pathak KK, Bandara JMSJ, Agrawal R (eds) Recent Trends in Civil Engineering. Lecture Notes in Civil Engineering, vol 77. Singapore, Springer, 770-790, https://doi.org/10.1007/ 978-981-15-5195-6_58
  • 52. Verma S, Prasad AD, Verma MK (2022) Trends of Rainfall and Temperature over Chhattisgarh During 1901-2010. In: Rao CM, Patra KC, Jhajharia D, Kumari S (eds) Advanced Modelling and Innovations in Water Resources Engineering. Lecture Notes in Civil Engineering, vol 176. Springer, Singapore, 3-19, https://doi.org/ 10.1007/978-981-16-4629-4_1
  • 53. Wambura FJ, Dietrich O, Lischeid G (2017) Evaluation of spatiotemporal patterns of remotely sensed evapotranspiration to infer information about hydrological behaviour in a data-scarce region. Water 9(5):333. https://doi.org/10.3390/w9050333
  • 54. Wotling G, Bouvier C, Danloux J, Fritsch JM (2000) Regionalization of extreme precipitation distribution using the principal components of the topographical environment. J Hydrol 233(1-4):86-101. https://doi.org/10.1016/S0022-1694(00)00232-8
  • 55. Yang J, Chen Y, Chen M, Yang F, Yao M (2018) A segmented processing approach of eigenvector spatial filtering regression for normalized difference vegetation index in central China. ISPRS Int J Geo-Inf 7(8):330. https://doi.org/10.3390/ijgi7080330
  • 56. Yin Y, Pan X, Yang X, Wang X, Wang G, Sun S (2019) Spatiotemporal Changes and Frequency Analysis of Multiday Extreme Precipitation in the Huai River Basin during 1960 to 2014. Advances in Meteorology 2019:Article ID 6324878, 12 pages, https://doi.org/ 10.1155/2019/6324878
  • 57. Yuan L, Yang G, Li H, Zhang Z (2016) Spatio-temporal variation analysis of precipitation during 1960-2008 in the Poyang Lake basin. China Open J Modern Hydrol 6(2):115-127. https://doi. org/10.4236/ojmh.2016.62010
Typ dokumentu
Bibliografia
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Identyfikator YADDA
bwmeta1.element.baztech-324b99c2-a0ea-45b1-bbaf-4d598cd857fe
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