Change Detection in Hydrological Time Series Data
dc.contributor.author | Paul, Rupak Kumar | |
dc.contributor.editor | Ismile, MD | |
dc.contributor.editor | Siddiqui, Azizur Rahman | |
dc.contributor.editor | Miah, Chhahir Ali | |
dc.date.accessioned | 2024-02-10T07:57:06Z | |
dc.date.available | 2024-02-10T07:57:06Z | |
dc.date.issued | 2022 | |
dc.description.abstract | Scientists 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.extent | pp. 131-166 | |
dc.identifier.isbn | 978-81-956639-1-0 | |
dc.identifier.uri | https://ir.nbu.ac.in/handle/123456789/5132 | |
dc.language.iso | en | en_US |
dc.publisher | R K Books | en_US |
dc.relation.ispartof | Geography as a Discipline: Opportunities and Challenges | |
dc.subject | Change detection | en_US |
dc.subject | Time series | en_US |
dc.subject | Hydrological | en_US |
dc.title | Change Detection in Hydrological Time Series Data | en_US |
dc.title.alternative | Geography as a Discipline: Opportunities & Challenges, 2022, p. 131 | en_US |
dc.type | Book Chapter | en_US |
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