PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Assessing the changing pattern of hydro-climatic variables in the Aghanashini River watershed, India

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Growing population and climate change have altered the hydro-climatic trend from past decades. This manuscript analyses the abrupt shift in these time series and their changing pattern using historical data sets. The Pettitt test and the Standard Normal Homogeneity Test were used to evaluate the time series' homogeneity. The Concentration Index, Precipitation Concentration Index and Seasonality Index were employed to analyse the spatial variability of daily, monthly and seasonal rainfall patterns over the Aghanashini River watershed. Furthermore, the temporal trend in the rainfall, streamflow, and temperature time series was investigated using Mann–Kendall (MK) and the graphical Innovative-Şen (IŞ) test. Clear evidence of climate change impact on the rainfall and streamflow pattern was recognized, as there is an upward shift in the maximum temperature time series and a downward shift in the rainfall and streamflow time series after 2001. The rainfall indices showed that the watershed has fewer percentage of rainy days and stronger rainfall seasonality, indicating a possible risk of flash floods in the downstream of the watershed. Additionally, the results of the MK and IŞ trend tests paralleled each other and provided support for the findings emphasized by rainfall indices.
Czasopismo
Rocznik
Strony
2971--2988
Opis fizyczny
Bibliogr. 58 poz., rys., tab.
Twórcy
  • Department of Water Resources and Ocean Engineering, National Institute of Technology Karnataka, Surathkal, Mangalore, India
  • Department of Water Resources and Ocean Engineering, National Institute of Technology Karnataka, Surathkal, Mangalore, India
Bibliografia
  • 1. Achite M, Caloiero T, Toubal AK (2022) Rainfall and runoff trend analysis in the Wadi Mina Basin (Northern Algeria) using non-parametric tests and the ITA method. Sustain 14:1–23. https://doi.org/10.3390/su14169892
  • 2. Alexandersson H (1986) A homogeneity test applied to precipitation data. J Climatol 6:661–675. https://doi.org/10.1002/joc.3370060607
  • 3. Bekuma Abdisa T, Mamo Diga G, Regassa Tolessa A (2022) Impact of climate variability on rain-fed maize and sorghum yield among smallholder farmers. Cogent Food Agric 8:1–16. https://doi.org/10.1080/23311932.2022.2057656
  • 4. Buffoni L, Maugeri M, Nanni T (1999) Precipitation in Italy from 1833 to 1996. Theor Appl Climatol 63:33–40
  • 5. Chow VT, Maidment DR, Mays LW (1988) Applied Hydrology. McGraw-Hill, USA
  • 6. Coscarelli R, Caloiero T (2012) Analysis of daily and monthly rainfall concentration in Southern Italy (Calabria region). J Hydrol 416–417:145–156. https://doi.org/10.1016/j.jhydrol.2011.11.047
  • 7. Deng S, Chen T, Yang N et al (2018) Spatial and temporal distribution of rainfall and drought characteristics across the Pearl River basin. Sci Total Environ 619–620:28–41. https://doi.org/10.1016/j.scitotenv.2017.10.339
  • 8. Desbureaux S, Rodella AS (2019) Drought in the city: the economic impact of water scarcity in Latin American metropolitan areas. World Dev 114:13–27. https://doi.org/10.1016/j.worlddev.2018.09.026
  • 9. Ebodé VB (2022) Impact of rainfall variability and land-use changes on river discharge in Sanaga catchment (forest–savannah transition zone in Central Africa). Hydrol Res 53:1017–1030. https://doi.org/10.2166/nh.2022.046
  • 10. Feng X, Porporato A, Rodriguez-Iturbe I (2013) Changes in rainfall seasonality in the tropics. Nat Clim Chang 3:811–815. https://doi.org/10.1038/nclimate1907
  • 11. Gholami H, Moradi Y, Lot M (2022) Detection of abrupt shift and non-parametric analyses of trends in runoff time series in the Dez river basin. Water Supply 22:1216–1230. https://doi.org/10.2166/ws.2021.357
  • 12. Guhathakurta P, Saji E (2013) Detecting changes in rainfall pattern and seasonality index vis-à-vis increasing water scarcity in Maharashtra. J Earth Syst Sci 122:639–649. https://doi.org/10.1007/s12040-013-0294-y
  • 13. Hegde G V, Subhash Chandra KC (2021) Ill-conceived projects could be disastrous for Aghanashini’s ecosystem. Deccan Her.
  • 14. Herath SM, Sarukkalige R, Van NVT (2018) Evaluation of empirical relationships between extreme rainfall and daily maximum temperature in Australia. J Hydrol 556:1171–1181. https://doi.org/10.1016/j.jhydrol.2017.01.060
  • 15. Hilal A, Vakitbilir N, Akıntuğ B (2021) Spatial and temporal analysis of daily, monthly, and seasonal rainfall characteristics across Northern Cyprus. J Hydrol Eng 26:1–12. https://doi.org/10.1061/(asce)he.1943-5584.0002136
  • 16. IMD (2021) Statement on climate of India during 2021. 1–5
  • 17. Jacomazzi MA, Zuffo AC, Imteaz MA et al (2022) Maximum extreme flow estimations in historical hydrological series under the influence of decadal variations. Hydrology 9:1–15. https://doi.org/10.3390/hydrology9080130
  • 18. Jenifer MA, Jha MK (2021) Assessment of precipitation trends and its implications in the semi-arid region of Southern India. Environ Challenges 5:100269. https://doi.org/10.1016/j.envc.2021.100269
  • 19. Kang HM, Yusof F (2012) Homogeneity tests on daily rainfall series in Peninsular Malaysia. Int J Contemp Math Scie 7:9–22
  • 20. Kendall MG (1962) Rank correlation methods. Hafner Publishing Company, New York, NY
  • 21. Kirchmeier-Young MC, Zhang X (2020) Human influence has intensified extreme precipitation in North America. Proc Natl Acad Sci U S A 117:13308–13313. https://doi.org/10.1073/pnas.1921628117
  • 22. Kocsis T (2020) Homogeneity tests and non-parametric analyses of tendencies in precipitation time series in Keszthely, Western Hungary. Theor Appl Climatol 139:849–859
  • 23. Krishnan R, Sanjay J, Gnanaseelan C, et al (2020) Assessment of climate change over the Indian region: A report of the ministry of earth sciences (MOES), government of India
  • 24. Kumar S, Merwade V, Kam J, Thurner K (2009) Streamflow trends in Indiana: effects of long term persistence, precipitation and subsurface drains. J Hydrol 374:171–183. https://doi.org/10.1016/j.jhydrol.2009.06.012
  • 25. Lettenmaier DP, Wood EF, Wallis JR (1994) Hydro-climatological trends in the continental United States, 1948–88. J Clim 7:586–607. https://doi.org/10.1175/1520-0442(1994)007%3c0586:HCTITC%3e2.0.CO;2
  • 26. Malede DA, Agumassie TA, Kosgei JR, et al (2022) Analysis of rainfall and streamflow trend and variability over Birr River watershed, Abbay basin, Ethiopia. Environ Challenges 7:100528. https://doi.org/10.1016/j.envc.2022.100528
  • 27. Mandal U, Sena DR, Dhar A, et al (2021) Assessment of climate change and its impact on hydrological regimes and biomass yield of a tropical river basin. Ecol Indic 126:107646. https://doi.org/10.1016/j.ecolind.2021.107646
  • 28. Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259
  • 29. Marcolini G, Bellin A, Chiogna G (2017) Performance of the standard normal homogeneity test for the homogenization of mean seasonal snow depth time series. Int J Climatol 37:1267–1277. https://doi.org/10.1002/joc.4977
  • 30. Martin-Vide J (2004) Spatial distribution of a daily precipitation concentration index in peninsular Spain. Int J Climatol 24:959–971. https://doi.org/10.1002/joc.1030
  • 31. Masroor M, Rehman S, Avtar R, et al (2020) Exploring climate variability and its impact on drought occurrence: evidence from Godavari Middle sub-basin, India. Weather Clim Extrem 30:100277. https://doi.org/10.1016/j.wace.2020.100277
  • 32. McLeod S (2019) What a p-value tells you about statistical significance. https://www.simplypsychology.org/p-value.html#:~:text=The%20level%20of%20statistical%20significance,%E2%89%A4%200.05)%20is%20statistically%20significant. Accessed 23 June 2022
  • 33. Michiels P, Gabriels D, Hartmann R (1992) Using the seasonal and temporal precipitation concentration index for characterizing the monthly rainfall distribution in Spain. CATENA 19:43–58. https://doi.org/10.1016/0341-8162(92)90016-5
  • 34. Mitchell Jr J, Dzerdzeevskii B, Flohn H, et al (1966) Climatic Change, WMO Tech. Note, 79. WMO No. 195. TP-100, Geneva
  • 35. Mondal A, Mujumdar PP (2015) On the detection of human influence in extreme precipitation over India. J Hydrol 529:1161–1172. https://doi.org/10.1016/j.jhydrol.2015.09.030
  • 36. Myhre G, Alterskjær K, Stjern CW et al (2019) Frequency of extreme precipitation increases extensively with event rareness under global warming. Sci Rep 9:1–10. https://doi.org/10.1038/s41598-019-52277-4
  • 37. Napoli A, Crespi A, Ragone F et al (2019) Variability of orographic enhancement of precipitation in the Alpine region. Sci Rep 9:1–8. https://doi.org/10.1038/s41598-019-49974-5
  • 38. Nourani V, Danandeh Mehr A, Azad N (2018) Trend analysis of hydroclimatological variables in Urmia lake basin using hybrid wavelet Mann-Kendall and Şen tests. Environ Earth Sci 77:1–18. https://doi.org/10.1007/s12665-018-7390-x
  • 39. Oliver JE (1980) Monthly precipitation distribution : a comparative Index. Prof Geogr 32:300–309
  • 40. Ostad-Ali-Askari K, Ghorbanizadeh Kharazi H, Shayannejad M, Zareian MJ (2020) Effect of climate change on precipitation patterns in an arid region using GCM Models: case study of Isfahan-Borkhar Plain. Nat Hazards Rev 21:04020006. https://doi.org/10.1061/(asce)nh.1527-6996.0000367
  • 41. Otto FEL, Wolski P, Lehner F, et al (2018) Anthropogenic influence on the drivers of the Western Cape drought 2015–2017. Environ Res Lett 13:124010. https://doi.org/10.1088/1748-9326/aae9f9
  • 42. Pandžić K, Kobold M, Oskoruš D et al (2020) Standard normal homogeneity test as a tool to detect change points in climate-related river discharge variation: case study of the Kupa River Basin. Hydrol Sci J 65:227–241. https://doi.org/10.1080/02626667.2019.1686507
  • 43. Peleg N, Skinner C, Fatichi S, Molnar P (2020) Temperature effects on the spatial structure of heavy rainfall modify catchment hydro-morphological response. Earth Surf Dyn 8:17–36. https://doi.org/10.5194/esurf-8-17-2020
  • 44. Pettitt, (1979) A non-parametric to the approach problem. Appl Stat 28:126–135
  • 45. Rana A, Foster K, Bosshard T et al (2014) Impact of climate change on rainfall over Mumbai using distribution-based scaling of global climate model projections. J Hydrol Reg Stud 1:107–128. https://doi.org/10.1016/j.ejrh.2014.06.005
  • 46. Şen Z (2012) Innovative trend analysis methodology. J Hydrol Eng 17:1042–1046. https://doi.org/10.1061/(asce)he.1943-5584.0000556
  • 47. Shrestha BB, Kawasaki A, Inoue T et al (2022) Exploration of spatial and temporal variability of rainfall and their impact on rice production in Burma in 1901–1939 during the colonial period. Prog Earth Planet Sci 9:1–26. https://doi.org/10.1186/s40645-022-00506-2
  • 48. Svetlana D, Radovan D, Ján D (2015) The economic impact of floods and their importance in different regions of the world with emphasis on Europe. Procedia Econ Financ 34:649–655. https://doi.org/10.1016/s2212-5671(15)01681-0
  • 49. Tao Y, Wang W, Song S, Ma J (2018) Spatial and temporal variations of precipitation extremes and seasonality over China from 1961–2013. Water (switzerland) 10:1–19. https://doi.org/10.3390/w10060719
  • 50. Te CV, Maidment DR, Mays LW (1988) Applied hydrology. McGraw-Hill, USA
  • 51. Teegavarapu RSV (2018) Methods for analysis of trends and changes in hydroclimatological time-series. Elsevier Inc., Amsterdam
  • 52. Usha B, Mudgal B V. (2015) Climate variability and its impacts on runoff in the Kosasthaliyar sub-basin, India. Earth Sci Res J; 18:45–49. https://doi.org/10.15446/esrj.v18n1.39966
  • 53. Venkatappa M, Sasaki N, Han P, Abe I (2021) Impacts of droughts and floods on croplands and crop production in Southeast Asia: an application of Google Earth Engine. Sci Total Environ 795:148829. https://doi.org/10.1016/j.scitotenv.2021.148829
  • 54. Venkatesh B, Nayak PC, Thomas T et al (2021) Spatio-temporal analysis of rainfall pattern in the Western Ghats region of India. Meteorol Atmos Phys 133:1089–1109. https://doi.org/10.1007/s00703-021-00796-z
  • 55. Vijay A, Sivan SD, Mudbhatkal A, Mahesha A (2021) Long-term climate variability and drought characteristics in tropical region of India. J Hydrol Eng 26:05021003. https://doi.org/10.1061/(asce)he.1943-5584.0002070
  • 56. Villarini G, Smith JA, Serinaldi F, Ntelekos AA (2011) Analyses of seasonal and annual maximum daily discharge records for central Europe. J Hydrol 399:299–312. https://doi.org/10.1016/j.jhydrol.2011.01.007
  • 57. Xie Y, Liu S, Fang H et al (2022) A study on the precipitation concentration in a Chinese region and its relationship with teleconnections indices. J Hydrol 612:128203. https://doi.org/10.1016/j.jhydrol.2022.128203
  • 58. Zhang Q, Xu CY, Gemmer M et al (2009) Changing properties of precipitation concentration in the Pearl River basin, China. Stoch Environ Res Risk Assess 23:377–385. https://doi.org/10.1007/s00477-008-0225-7
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-982125b4-98f2-42c0-a545-ddf051ac3391
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.