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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/75097
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Deepesh Machiwal | en_US |
dc.contributor.author | H.M. Meena | en_US |
dc.contributor.author | D.V. Singh | en_US |
dc.date.accessioned | 2022-11-14T09:03:58Z | - |
dc.date.available | 2022-11-14T09:03:58Z | - |
dc.date.issued | 2022-10-21 | - |
dc.identifier.citation | Machiwal, D., Meena, H.M. and Singh, D.V. (2022). Overview of Trend and Homogeneity Tests and Understanding Rainfall Variability in a Hot Arid Region of India. In: Zakwan, M., Wahid, A., Niazkar, M. and Chatterjee, U. (Editors), Water Resource Modeling and Computational Technologies, Elsevier, pp. 599-620. | en_US |
dc.identifier.issn | Not Available | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/75097 | - |
dc.description | Not Available | en_US |
dc.description.abstract | This chapter provides an overview of the parametric and non-parametric statistical tests used for investigating the homogeneity and the trend in hydrological variables with a focus on the Mann-Kendall (M-K) test and innovative trend analysis (ITA) method. Modifications suggested in both the M-K and ITA tests are also briefly discussed. Furthermore, a case study is presented where the seasonal (monsoon, post-monsoon, winter and pre-monsoon) and annual rainfall of a hot arid region of India are examined for the presence of trends using two tests, i.e., variance-corrected M-K test and ITA test and for the homogeneity using four tests, i.e., Tukey, Link-Wallace, Bartlett, and Hartley tests. The M-K test depicts positive (increasing) trends at 90 and 87% sites in the monsoon and annual rainfall, respectively, and statistically significant trends at 4 sites (p<0.05). However, the ITA method is found over-sensitive in identifying the significantly rising rainfall trends. Furthermore, the Link-Wallace and Tukey tests perform better than the Hartley and Bartlett tests in examining rainfall homogeneity. Accordingly, the seasonal and annual rainfall in the hot arid region of India is found mostly homogeneous while the significant non-homogeneity in rainfall at a few sites is observed due to the rising rainfall. The dissimilar findings obtained by different tests emphasize the need of employing more than one test for detecting every property of a time series. Hence, use of the adequate number of tests for the trend and homogeneity detection is justified for arriving at a right conclusion. The pros and cons of the employed trend and homogeneity tests are discussed. Findings of the study revealed that the rainfall in this traditionally water-short arid region has been rising over the recent years, and therefore, there is a need to develop the suitable strategies and feasible policies to conserve and harvest the surplus rainwater and manage it sustainably. Moreover, limitations, future challenges and recommendations in the field of hydrologic time series analysis are discussed. | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | Arid region | en_US |
dc.subject | Box-whisker plot | en_US |
dc.subject | Homogeneity testing | en_US |
dc.subject | Seasonal and annual rainfall | en_US |
dc.subject | Trend identification | en_US |
dc.subject | Trend quantification | en_US |
dc.title | Overview of Trend and Homogeneity Tests and Understanding Rainfall Variability in a Hot Arid Region of India | en_US |
dc.title.alternative | Not Available | en_US |
dc.type | Book chapter | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.volumeno | Not Available | en_US |
dc.publication.pagenumber | 599-620 | en_US |
dc.publication.divisionUnit | Division of Natural Resources | en_US |
dc.publication.sourceUrl | https://doi.org/10.1016/B978-0-323-91910-4.00034-0 | en_US |
dc.publication.sourceUrl | https://www.sciencedirect.com/science/article/abs/pii/B9780323919104000340 | en_US |
dc.publication.authorAffiliation | ICAR::Central Arid Zone Research Institute | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
Appears in Collections: | NRM-CAZRI-Publication |
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