| Popis: |
This study aimed to assess the coherence between groundwater levels and various factors during two distinct periods, 2002–2020 and 2025–2050, in Miandoab aquifer in northwestern of the Iran. Partial wavelet coherence and multi-wavelet coherence analyses were employed to assess the coherence between individual parameters and their simultaneous coherence. The factors considered in the study were derived from remote sensing data, including Gravity Recovery and Climate Experiment data and Landsat data, which were utilized to examine water storage anomalies and anthropogenic activity, respectively. Additionally, General Circulation Models were employed to predict groundwater levels under future climate change scenarios via a feedforward neural network. To streamline the modeling process and categorize piezometers, with each group reflecting different patterns, clustering techniques were applied to group multiple piezometers. There were four final clusters, and representative piezometers from each cluster were chosen as targets for modeling and future predictions. Finally, the differences in coherence between past and future periods were compared and analyzed. The results revealed decreasing trends in groundwater level, precipitation and soil moisture index in 2025–2050; however, there were increasing trends in normalized difference vegetation index and temperature. In addition, wavelet analysis indicated that during the period 2025–2050, the delay in interaction between groundwater level and various factors decreased to 0–4 months, whereas longer delays were observed for the period 2002–2020. The analysis of multi- wavelet coherence showed that the combination of climate change and anthropogenic activity may have more significant coherence (0.9–1) with groundwater level than the combination of gravity recovery and climate experiment data and soil moisture index. The results highlight the greater significance of gravity recovery and climate experiment data in terms of coherence with groundwater levels compared to other factors. |
