Multiscale coherence analysis of reference evapotranspiration of north-western Iran using wavelet transform. Issue 2 (24th November 2021)

• Record Type: Journal Article
• Authors: Sreedevi, V.; Adarsh, S.; Nourani, Vahid
• Is Part Of: Journal of water and climate change. Volume 13:Issue 2(2022)
• Page Start: 505
• Page End: 521
• Publication Date: 2021-11-24
• Subjects: evapotranspiration -- Tabriz -- Urmia -- wavelet coherence; Water -- Periodicals; Hydrology -- Periodicals; Climatic changes -- Periodicals; Climatic changes; Hydrology; Water; Electronic journals; Periodicals; 333.9116
• DOI: 10.2166/wcc.2021.379
• Languages: English
• ISSNs: 2040-2244

Abstract

Abstract: This study applies different wavelet coherence formulations for investigating the multiscale associations of reference Evapotranspiration (ET0 ) of Tabriz and Urmia stations in North West Iran with five climatic variables: mean temperature (T), pressure (P), relative humidity (RH), wind speed (U) and Solar Radiation (SR). The relationships between different variables are quantified using the Average Wavelet Coherence (AWC) and the Percentage of Significant Coherence (PoSC). The Bivariate Wavelet Coherence (BWC) analysis showed that mean temperature (AWC = 0.73, PoSC = 59.18%) and wind speed (AWC = 0.63, PoSC = 49.55%) are the dominant predictors at Tabriz and Urmia stations. On considering the Multiple Wavelet Coherence (MWC) analysis, it is noticed that among the two-factor combinations, the T-P and P-RH combinations resulted in the highest coherence values for Tabriz and Urmia stations. T-U-SR combination produced the highest multiple wavelet coherence values among the three-factor cases for both the stations. The Partial Wavelet Coherence (PWC) analysis indicated a drastic reduction in coherence from the values of respective BWC analysis, indicating a strong interrelationship between different variables and ET0 . The interrelationship between meteorological variables and ET0 is more apparent at Tabriz, while it is controlled more by the local-scale meteorology at Urmia. HIGHLIGHTS: Presents coherence relationship between the meteorological variables and ET0 for the first time. Accounts standalone, concurrent and partial role of variables using bi-, multiple- and partial wavelet coherence approaches. Interrelationships between variables are more apparent at the Tabriz station, while they are controlled more by the proximity to the lake at Urmia.