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| Format: | Recurso digital |
| Language: | English |
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2026
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| Online Access: | https://doi.org/10.5281/zenodo.20393170 |
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| _version_ | 1866902125777256448 |
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| author | Zarei Doudeji, Somayeh |
| author_facet | Zarei Doudeji, Somayeh |
| contents | <p><span>Groundwater depletion in semi‑arid regions is a global crisis demanding accurate forecasting and proactive intervention. This study develops a transferable hybrid SARIMA‑wavelet framework to forecast water levels (WLs) and evaluate managed aquifer recharge (MAR) scenarios. The framework is demonstrated on the critically stressed Galedar aquifer (southern Iran, 2006‑2024) as a test case. Wavelet decomposition reveals that decadal variability dominates regional flow zones (48.5% of variance), while annual variability dominates high‑recovery zones (45%). Manual Box‑Jenkins SARIMA models, built with seasonal differencing (D=1), achieve out‑of‑sample RMSE of 0.062–0.162 m. Sensitivity analysis identifies specific yield (Sy) as the most influential parameter globally (Sobol’ ST = 0.58–0.71). The hybrid model reduces RMSE by 16‑31% compared to standard SARIMA, MODFLOW, and LSTM. Under business‑as‑usual (BAU), the mean WL declines 2.6 m (0.26 m/year) by 2034. MAR scenarios show: high‑recovery zone recharge (+1.41 m, 71% decline reduction); distributed recharge (1.8‑fold greater storage recovery per unit recharge); episodic recharge (+1.11 m, 40% lower efficiency). Cost‑benefit analysis confirms positive net present value (BCR 1.4‑3.4). The proposed framework is generalizable to any overexploited aquifer in arid/semi‑arid regions and supports risk‑based, spatially stratified management (SDG 6 & 13).</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20393170 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | A hybrid SARIMA wavelet framework for groundwater level forecasting and managed aquifer recharge assessment in semi arid regions: Application to the Galedar Aquifer, southern Iran Zarei Doudeji, Somayeh <p><span>Groundwater depletion in semi‑arid regions is a global crisis demanding accurate forecasting and proactive intervention. This study develops a transferable hybrid SARIMA‑wavelet framework to forecast water levels (WLs) and evaluate managed aquifer recharge (MAR) scenarios. The framework is demonstrated on the critically stressed Galedar aquifer (southern Iran, 2006‑2024) as a test case. Wavelet decomposition reveals that decadal variability dominates regional flow zones (48.5% of variance), while annual variability dominates high‑recovery zones (45%). Manual Box‑Jenkins SARIMA models, built with seasonal differencing (D=1), achieve out‑of‑sample RMSE of 0.062–0.162 m. Sensitivity analysis identifies specific yield (Sy) as the most influential parameter globally (Sobol’ ST = 0.58–0.71). The hybrid model reduces RMSE by 16‑31% compared to standard SARIMA, MODFLOW, and LSTM. Under business‑as‑usual (BAU), the mean WL declines 2.6 m (0.26 m/year) by 2034. MAR scenarios show: high‑recovery zone recharge (+1.41 m, 71% decline reduction); distributed recharge (1.8‑fold greater storage recovery per unit recharge); episodic recharge (+1.11 m, 40% lower efficiency). Cost‑benefit analysis confirms positive net present value (BCR 1.4‑3.4). The proposed framework is generalizable to any overexploited aquifer in arid/semi‑arid regions and supports risk‑based, spatially stratified management (SDG 6 & 13).</span></p> |
| title | A hybrid SARIMA wavelet framework for groundwater level forecasting and managed aquifer recharge assessment in semi arid regions: Application to the Galedar Aquifer, southern Iran |
| url | https://doi.org/10.5281/zenodo.20393170 |