Long-term quantitative assessment of the ecological impacts of floodwater spreading on vegetation in Iran has consistently been challenged by the lack of continuous in-situ field data. The primary objective of this study was to quantitatively evaluate the effect of floodwater spreading on the Normalized Difference Vegetation Index (NDVI) in the Soh aquifer (Meymeh, Isfahan Province) over the period 2015–2024, using Sentinel-2 time-series data and comparing the treated area with a homogeneous adjacent control site. To this end, monthly (110 observations), seasonal, and annual NDVI time series were derived from Sentinel-2 L2A imagery (10 m spatial resolution, <5% cloud cover) by generating median composites within the Google Earth Engine platform. Trend analyses were performed using Ordinary Least Squares (OLS) linear regression and the robust Theil–Sen slope estimator. Moreover, due to the non-normal distribution of the data (confirmed by the Shapiro–Wilk test), the non-parametric Mann–Whitney U test was employed for statistical comparison of NDVI distributions between the two areas. The results indicated that the long-term mean NDVI in the floodwater spreading area (0.078) differed only negligibly from that of the control area (0.079), and the Mann–Whitney U test revealed no statistically significant difference between the two areas (U = 7959.5, p = 0.057). Nevertheless, the spreading area exhibited lower temporal variability (standard deviation: 0.011 vs. 0.012; coefficient of variation: 0.141 vs. 0.152) and a higher maximum NDVI (0.119 vs. 0.115) compared to the control site. Trend analysis at annual, seasonal, and monthly scales revealed no significant increasing or decreasing trends in either area (all p-values > 0.05). Overall, although floodwater spreading over the 9-year period failed to significantly increase the mean greenness index, it effectively enhanced ecosystem resilience and stability against climatic stresses by reducing temporal fluctuations and increasing maximum greenness. The proximity of the significance level to the 0.05 threshold indicates the gradual emergence of management effects, underscoring the necessity of extending long-term monitoring (at least 15 years) and shifting vegetation composition toward deep-rooted species as the primary management recommendations of this study.
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