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<p>Understanding temporal and spatial variability of river flow is essential for sustainable water resource management, especially in regions with diverse hydro-climatic conditions. This study analyzed flow seasonality across 32 hydrometric stations in Ardabil Province, Iran, over a 50-year period (1971–2020) using the seasonality index (SI) and entropy to assess flow distribution and predictability. Temporal trends were evaluated with the Mann-Kendall test, and K-means clustering grouped stations with similar flow regimes. Results revealed substantial spatial variation in SI and entropy values, with SI ranging from 0.32 at Viladaragh to 1.38 at Neur (average 0.84), indicating moderate seasonality overall. High entropy values (up to 3.46 at Lai) reflected more unpredictable flows, while lower values (1.66 at Neur) indicated stable flow patterns. Clustering identified distinct flow regimes, with central and southeastern areas exhibiting more stable flows compared to the northwest and west. Spatial analysis highlighted that low SI regions are predominantly located in the northwest and west, suggesting higher seasonal variability. These findings provide insights into flow regime variability, which can guide environmental flow allocation, timing of water releases, and management of excess water. The results support evidence-based strategies for water resource planning, particularly in areas prone to fluctuating flows, and contribute to sustainable environmental management in the province.</p>

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Long-term seasonality of river flow regimes: spatio-temporal variability and trend over a complex hydro-climatic-topographic region

  • 期刊论文

  • 发表日期：

    2025年10月15日

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  • Raoof Mostafazadeh,
  • Nazila Alaei

摘要

Understanding temporal and spatial variability of river flow is essential for sustainable water resource management, especially in regions with diverse hydro-climatic conditions. This study analyzed flow seasonality across 32 hydrometric stations in Ardabil Province, Iran, over a 50-year period (1971–2020) using the seasonality index (SI) and entropy to assess flow distribution and predictability. Temporal trends were evaluated with the Mann-Kendall test, and K-means clustering grouped stations with similar flow regimes. Results revealed substantial spatial variation in SI and entropy values, with SI ranging from 0.32 at Viladaragh to 1.38 at Neur (average 0.84), indicating moderate seasonality overall. High entropy values (up to 3.46 at Lai) reflected more unpredictable flows, while lower values (1.66 at Neur) indicated stable flow patterns. Clustering identified distinct flow regimes, with central and southeastern areas exhibiting more stable flows compared to the northwest and west. Spatial analysis highlighted that low SI regions are predominantly located in the northwest and west, suggesting higher seasonal variability. These findings provide insights into flow regime variability, which can guide environmental flow allocation, timing of water releases, and management of excess water. The results support evidence-based strategies for water resource planning, particularly in areas prone to fluctuating flows, and contribute to sustainable environmental management in the province.