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Estimating potential reference evapotranspiration using time series models (case study: synoptic station of Tabriz in northwestern Iran)
The potential evapotranspiration is considered as an important element of the hydrological cycle, which plays an important role in agricultural studies, management plans of irrigation and drainage networks, and hydraulic structures. Estimating the potential evapotranspiration reference of particular...
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Published in: | Applied water science 2022-09, Vol.12 (9), p.1-8, Article 212 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The potential evapotranspiration is considered as an important element of the hydrological cycle, which plays an important role in agricultural studies, management plans of irrigation and drainage networks, and hydraulic structures. Estimating the potential evapotranspiration reference of particular climatic regions at different time scales, which is one of the most important atmospheric parameters, is of a particular importance in the optimal use of resources. The time series analysis method, GARCH model, is applied in order to investigate changes and estimate the potential evapotranspiration. In the present study, the efficiency of GARCH series model related to processes of modeling and estimating potential evapotranspiration, which is estimated by FAO Penman–Monteith and Hargreaves methods, was investigated. Also, future values of potential evapotranspiration are modelled and estimated at the synoptic station of Tabriz. Results showed that Time Series is considered as a precise tool to estimate evapotranspiration values. It was found that GARCH (1.1) time series has better results for FAO Penman–Monteith and Hargreaves methods compared to other models; also, it simulates the process of time series changes with less error. Observed and predicted evapotranspiration charts of both methods indicated that observational evapotranspiration was highly close to the lower limit of estimated evapotranspiration. Therefore, applying lower limit estimation as a prediction value was suggested. |
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ISSN: | 2190-5487 2190-5495 |
DOI: | 10.1007/s13201-022-01736-x |