Investigating the controlling factors of the suspended sediment of Gharasu River in Ardabil province using principal component analysis and multivariate regression

Water erosion is the result of interactions between various environmental factors such as topography, soil characteristics, climate characteristics, runoff and land use and management. Sediment production is highly dependent on runoff, so doubling the speed of runoff increases its leaching capacity and transportability up to five and six times. Knowing the effective factors in sediment production plays an important role in determining the amount of sedimentation of a watershed and understanding the phenomenon of erosion and its consequences, and it can be used in prioritizing the sub-basins of a watershed. The purpose of this research is to investigate the relationship between morphological characteristics and the amount of sediment production in the catchment area of the Gharasu River in Ardabil using principal component analysis and multivariate regression, in this regard, using 16 independent variables and 1 dependent variable in 13 sub-basins of the Gharasu River.

As one of the sub-basins of the Aras catchment basin, Gharasu catchment is located in the geographical coordinates of 47°31' to 48°47' east longitude and 37°47' to 38°52' north latitude. In this study, 1:100,000 scale geological maps, 1:25,000 scale topographic maps, and discharge and suspended sediment statistics and information of 13 hydrometric stations of Gharasu River sub-basin were used in the 50-year period from 1350 to 1399. In order to check the correlation between independent and dependent variables and to test the normality and normal distribution of data, Shapiro-Wilk and Kolmogorov-Smirnov tests were used in SPSS software. Also, in this research, the OLI Landsat 8 satellite images were used to extract the vegetation cover index (NDVI). For this purpose, step-by-step linear regression is used to determine the most effective variables and to determine the most appropriate statistical relationship between suspended sedimentation and the variables used, and principal component analysis is used to determine the most effective factors of suspended sediment production in the watershed.

In this study, the average annual suspended sediment of the basin was considered as dependent variable and other parameters as independent variables, and Pearson correlation method was used to check the correlation between independent variables and dependent variable. The variables of time of concentration, length of the main waterway, area, Slenderness ratio, perimeter and slope have a higher correlation with the amount of sediment production in the basin than other variables. Based on the models obtained from sediment correlation analysis, the amount of sediment produced with the concentration time variable had a positive correlation and was significant at the 5% level. The results of the analysis of the principal components show that the four factors of area, length of the main waterway, concentration time and slenderness ratio of the basin have an eigenvalue greater than 1, and the number of extracted factors is 4 factors. The first factor (area) has been able to explain 37.230 percent of the variance of all research variables. This value is 24.735, 16.950 and 9.849 percent for the second factor (length of the main waterway), the third factor (concentration time) and the fourth factor (slenderness ratio) respectively.

The present research was conducted with the aim of investigating the relationship between geomorphic parameters, vegetation and erodible formations of selected sub-basins of Gharasu basin with the average annual sediment. For this purpose, the statistics and information of 17 variables (16 independent variables and 1 dependent variable) were obtained for 13 sub-basins of Gharasu basin from the regional water of Ardabil province. The relationship between geomorphic parameters and annual precipitation was determined using stepwise multivariate regression method. The research results indicate that geomorphic parameters have a high correlation with the amount of annual sediment production and can be used in sediment prediction. Meanwhile, the variables of concentration time, length of the main waterway, area, slenderness ratio, perimeter and slope have a higher correlation with the amount of sediment production in the basins than other variables. Among these variables, the basin concentration time variable was used in the final step-by-step regression model and was selected as the sediment predictor variable. This variable alone can predict 98% of annual precipitation. In order to ensure the appropriateness of the data, the KMO coefficient was used to analyze the main components. The value of KMO = 0.78, as a result, the data will be suitable for factor analysis. The results showed that the four factors of area, main waterway length, concentration time and elongation factor could explain 88.754% of the variance of all research variables.