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An Analysis on the Precipitation Barycenter in the Network of Rain Gauge Stations of Ardabil Province | ||
| پژوهش های آبخیزداری | ||
| Article 5, Volume 37, Issue 4 - Serial Number 145, January 2025, Pages 54-70 PDF (2.49 M) | ||
| Document Type: Research | ||
| DOI: 10.22092/wmrj.2024.364724.1570 | ||
| Authors | ||
| Zeinab Hazbavi* 1; Vahideh Moradzadeh2; Mahin Hanifepour3; Nazila Alaei4 | ||
| 1Associate Professor, Department of Range and Watershed Management, Faculty of Agriculture and Natural Resources, Water Management Research Center, University of Mohaghegh Ardabili, Ardabil, Iran | ||
| 2Former M.Sc. Student, Department of Range and Watershed Management, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran | ||
| 3Former Ph.D. Student, Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Tehran, Karaj, Iran | ||
| 4Ph.D. Student, Department of Range and Watershed Management, Faculty of Natural Resources, Urmia University, Urmia, Iran | ||
| Abstract | ||
| Introduction and Goal The decreasing trend of precipitation in many regions of the country, including the northwestern provinces, has made it more necessary to investigate new methodologies to complete the databases of the country's watersheds. In this regard, understanding the changes in precipitation barycenters, as an emerging concept, that indicates the long-term spatial distribution of regional precipitation is especially important for the administration of watershed management issues such as reducing drought effect, flood control, and water resource conservation. To this end, the present study analyzes the precipitation barycenter and its relationship with the spatial distribution of the rain gauge network in Ardabil Province. Materials and Methods To calculate the precipitation amount, the statistics of 49 meteorological stations during the statistical period of 45 years (1971-2016) were used. Based on the principle of station extraction and considering the rationality of the lowest density and uniformity, five stations were determined as the minimum possible number. Then, densities of 10, 20, 30, and 40 stations were extracted randomly to compare the distribution of precipitation centroids with the density of the station network. The statistics above were used to implement the gravity center model, calculate the standard deviation ellipse in the ArcMap 10.8 software environment, and conventional correlation analysis on monthly, seasonal, and annual time scales using XLSTAT. Results and Discussion The results showed that in spring (April to June), the direction of movement of the precipitation barycenter was significantly different and the movement distance was 18.17 km. In summer (July to September), the precipitation barycenter mainly moved 20.18 km to the north. In autumn (October to December), the precipitation barycenter mainly moves 20.49 km to the south and has the longest movement distance among the seasons. In winter (December to March), the precipitation barycenter moves in different directions and has the smallest movement distance (8.35). The annual precipitation barycenter migrated mostly in the southeast direction. The maximum migration of barycenter for 1979 was towards the northwest with 111.78 km. Besides, the annual precipitation barycenter in Ardabil Province in the three decades of 1971-1981 migrated mostly to the northwest and in the other decades to the southeast. The stational network density was positively correlated with changes in the precipitation barycenter (CCA = 0.65 at a significance level of 5%). Conclusion and Suggestion The highest conventional correlation coefficient of 0.80 was obtained for the density of 40 stations among different densities of 5, 10, 20, 30, 40, and 50, and the lowest coefficient of 0.04 was obtained for the minimum density of 5 stations. Based on the results of this study, changes in the movement of precipitation patterns that can be effective in drought and wet periods were identified. It is suggested that the relationship between climate change and elevation factors with spatial-temporal changes in the precipitation center of gravity be investigated. | ||
| Keywords | ||
| Clustering; Migration direction; Mountainaous watersheds; Spatial pattern; Stational density | ||
| References | ||
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