Change Detection in Hydrological Time Series Data

dc.contributor.authorPaul, Rupak Kumar
dc.contributor.editorIsmile, MD
dc.contributor.editorSiddiqui, Azizur Rahman
dc.contributor.editorMiah, Chhahir Ali
dc.date.accessioned2024-02-10T07:57:06Z
dc.date.available2024-02-10T07:57:06Z
dc.date.issued2022
dc.description.abstractScientists are accustomed to use statistical tools and techniques to detect change in hydrological time series, but these available techniques are not the panacea for resolving such issues since the concerned techniques provide expressions of probability and not certainty. For instance, the change in annual discharge has been detected for long term dataset but this change might not be due to alteration of any one or more components like land use land cover, or climate or change in agri-technology - of the system in basin scale, rather it happened due to change in methodology of concerned data generation or shifting of gauge station etc...en_US
dc.extentpp. 131-166
dc.identifier.isbn978-81-956639-1-0
dc.identifier.urihttps://ir.nbu.ac.in/handle/123456789/5132
dc.language.isoenen_US
dc.publisherR K Booksen_US
dc.relation.ispartofGeography as a Discipline: Opportunities and Challenges
dc.subjectChange detectionen_US
dc.subjectTime seriesen_US
dc.subjectHydrologicalen_US
dc.titleChange Detection in Hydrological Time Series Dataen_US
dc.title.alternativeGeography as a Discipline: Opportunities & Challenges, 2022, p. 131en_US
dc.typeBook Chapteren_US

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