Document Type : Research
Authors
1
Associate Professor, Department of Watershed Management, Water Management Research Center, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
2
Former M.Sc. Student, Department of Range and Watershed Management, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
3
Former Ph.D. Student, Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Tehran, Karaj, Iran
4
Ph.D. Student, Department of Range and Watershed Management, Faculty of Natural Resources, Urmia University, Urmia, Iran
10.22092/wmrj.2024.364724.1570
Abstract
Introduction and Objective
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 country's watershed databases. 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 46 years (1971-2016) were used. Based on the principle of station extraction and considering the reasonableness of minimum density and uniformity, five stations were determined as the minimum number of stations, and next, 10, 20, 30, and 40 stations were randomly extracted to compare the relationship between the precipitation barycenter distribution and the density of the station network. The aforementioned statistics 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. A more uniform and dense stational network distribution leads to higher conventional correlation coefficients. The proposed approach can be effective in designing the observation network of a wide range of environmental variables.
Keywords
Main Subjects
)