期刊
HYDROLOGICAL SCIENCES JOURNAL
卷 64, 期 12, 页码 1504-1518出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/02626667.2019.1651933
关键词
groundwater-level prediction; time series forecasting; Prophet; Donana wetland; groundwater management; pumping
资金
- Spanish National Plan for Scientific and Technical Research and Innovation
- Ministry of Education, Youth and Sport of Community of Madrid [PEJ15/AMB/AI-0218]
- Youth Employment Operational Programme
- Youth Employment Initiative
- European Social Fund (ESF)
- Consejeria de Educacion, Juventud y Deporte, Comunidad de Madrid [PEJ15/AMB/AI-0218]
- Secretaria de Estado de Investigacion, Desarrollo e Innovacion [CGL2016-77473-C3-1-R]
There is an increasing need for accurate groundwater-level (GWL) prediction to support effective seasonal water management. It is desirable for forecasting tools to be not only accurate but also accessible for decision-makers. We test the Prophet forecasting procedure, an open-source code released by Facebook, to address these challenges. It is based on an additive model considering non-periodic changes and periodic components in a Bayesian framework with easily-interpretable parameters. Predictions of daily GWL data in an area affected by pumping near a tourist complex in the Ramsar wetland area of Donana (Spain) are compared to other forecasting methods. Prophet outperforms most methods in predicting GWL making it a fast and flexible forecasting tool for hydrologists and water managers. Furthermore, it allows gaining insight into the influence of each component of the forecast separately, helping to assess the hydrodynamic response to external drivers such as groundwater pumping.
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