Recognizing the relationship between the groundwater level and hydrological time-series: a case study of the Ardabil Plain

Autor: Farnaz Daneshvar Vousoughi
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Journal of Water and Climate Change, Vol 13, Iss 7, Pp 2700-2712 (2022)
Druh dokumentu: article
ISSN: 2040-2244
2408-9354
DOI: 10.2166/wcc.2022.067
Popis: Two approaches were used in the Ardabil Plain to determine the relationship between hydrological time-series (rainfall and runoff) and the groundwater level (GWL). The wavelet-entropy measure (WEM) and the wavelet transform coherence (WTC) were used as two approaches of the wavelet transform (WT). The WEM was considered as a criterion for the degree of fluctuation of the time-series and the WTC represents a common time–frequency space. In the calculation of the WEM, the monthly rainfall, runoff, and the GWL time-series were divided into three different time periods and decomposed into several frequent time-series. Wavelet energies were then calculated for each sub-series. The WEM results show a decrease in rainfall, runoff, and the GWL. The reduction in the WEM represents the reduction in the natural variation of the time-series. The reduction of entropy for runoff, rainfall, and the GWL time-series was about 1.58, 1.36, and 29%, respectively. It can be concluded that the reduction in the fluctuation of the hydrological time-series has relatively little effect on the oscillation patterns of the GWL signal. In this regard, it could be concluded that human activities such as pumping water from wells play a main role in reducing the GWL in the Ardabil Plain. The WTC results show that runoff has the highest coherence (0.9–1) among hydrological variables with the GWL time-series in the frequency bands of 4–8 and 8–16 months. HIGHLIGHTS The wavelet-entropy measure (WEM) as a criterion is used to investigate the effect of hydrological parameters on groundwater level.; Wavelet transform coherence (WTC) is used to determine the frequency relationship between hydrological time-series and the groundwater level.;
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