Assessing climate change effects on declining groundwater levels using wavelet entropy (case study of Khorramabad city)

Abstract

Changing global climate predicts a warmer future which may alter the hydrological cycle, surface water as well as groundwater resource. The Entropy wavelet criterion is a new indicator to analyze the time series fluctuations. In this study, the effective factors of decreasing the groundwater level in Khorramabad city during the years 2005–2018 have been evaluated by the use of Entropy wavelet criterion. In general, it can be said that the decreasing of Entropy wavelet criterion or time series complexity of a phenomenon shows the time series decrease of fluctuations natural amounts, which it leads to an unfavorable trend. In this regard, in order to identify the affecting factors of the groundwater level decrease in Khorramabad, the groundwater level has been divided into 4 time periods, and after being investigated, the monthly time series of runoff, temperature, and precipitation of this city were divided into 4 periods. Each of these subset were decomposed into other several subsets at different time scales under the wavelet transform, and finally, after calculation of the normalized wavelet energy for this subset, its Entropy wavelet criterion was calculated for each period. Investigation of Entropy wavelet complexity shows a 21.3% decrease in groundwater level in the second period, but in the third and fourth periods, it has increased by 145 and 272%, respectively. Also, according to the results of Entropy wavelet changes analyzing for the precipitation time series, 35.2, 32.8, and 10.06% decrease in the second, third, and fourth periods were shown. The air temperature time series complexity decreased of 26.8% only in the third time period and in the second and fourth period, it shows an increase of 29.65 and 34.7%, respectively. However, the runoff time series did not show any reduction complexity according to the entropy wavelet criterion. These results indicate that the impact of climatic factors has been more effective than human factors in reducing the groundwater level of Khorramabad.

Exploring Groundwater Quality Trends in Valliyar Sub-Basin, Kanniyakumari District, India through Advanced Machine Learning Techniques

“…The consistent pattern across residential areas highlights the need for better wastewater treatment and urban planning to mitigate these impacts. The weak correlations between climatic factors and water quality parameters indicate that, although climate plays a role [39,40], the primary drivers of water quality changes in Villukuri are related to urbanization and residential activities [41,42].…”