Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/34071
Title: | Meteorological time series: an exploratory statistical and critical analysis |
Author: | Gonçalves, A. Manuela Pereira, F. Catarina Costa, Marco Leão, Celina P. |
Keywords: | Exploratory data analysis Meteorological variables Imputation Irrigation Time series |
Issue Date: | 2023 |
Publisher: | Springer |
Abstract: | Increasingly, reduction of water availability has been a real- ity, and population growth, pollution, and climate change have con- tributed to exacerbating this problem. Dry periods, which occur when precipitation is lower than expected in a given territory, have become more frequent and prolonged, and therefore it is crucial to efficiently manage water use in response to environmental concerns. The main chal- lenge in this work is to present the irrigation problem as an optimal control problem along with the presentation of preliminary results based on an exploratory statistical and critical analysis of daily meteorological variables. The variables considered are: maximum air temperature, min- imum air temperature, and total precipitation recorded during the last ten years (2010–2019). The methodology followed, based on state-space models, shows flexibility to allow the integration of new data, updat- ing in real time the model, and the incorporation of covariates that are important to explain the process in analysis. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/34071 |
DOI: | 10.1007/978-3-031-09360-9_17 |
Publisher Version: | https://link.springer.com/chapter/10.1007/978-3-031-09360-9_17#citeas |
Appears in Collections: | CIDMA - Capítulo de livro ESTGA - Capítulo de livro PSG - Capítulo de livro |
Files in This Item:
File | Description | Size | Format | |
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2023 Meteorological Time Series- An Exploratory Statistical and Critical Analysis.pdf | 304.75 kB | Adobe PDF | View/Open |
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