عنوان مقاله [English]
Base flow is one of the most important criteria which is used for assessment, utilization and management of river flow in drought periods. The base flow amount and its variations depends on several factors. Base flow modeling and estimation can be used in assessment of river health as well as planning of surface water utilization. Base flow refers to the flow of the river in times without rainfall. The base flow of the river is the infiltration of groundwater to the river banks or the river bed. The base flow may be significant and flow continuously throughout the year in the permanent rivers. The base flow has reached the underground water table with its deep penetration, and with the increase in the level of the aquifers, it can be connected with the drainage network, they create their own excess water during a long period of time, which sometimes takes several months. Determining the amount of river flow in dry periods, and the proportion of total runoff is one of the important topics in river hydrology. The base flow plays an important role in the river ecosystem, and is critical to human communities and ecosystems. This is especially important for watersheds that are not fed by snowmelt. Different ecological processes occur in different parts of the river's hydrograph. During base flow and during low water seasons, river ecosystems and habitats are dependent on river flow. Land change affect hydrologica; processes such as infiltration rates, groundwater recharge, groundwater and runoff levels. Also, climatic factors can affect the water yield of river basins. The most common method for regionalization in hydrology is bivariate or multivariate regression. Regression analysis is a useful approach to develop the desired factors in the regionalization of ungauged basins. Regression analysis is also one of the most common statistical methods in predicting values based on most important influencing factors. In this study, the multiple regression was used to model the base flow amount and determining the effective factors on base flow discharge. Ardabil province is considered one of the cold mountainous areas and the amount of precipitation in Ardabil province fluctuates on average between 250 and 600 mm/year in different parts of the province. Therefore, the aim of the current research is to model the effective factors in the amount of base flow and its estimation in the watersheds of Ardabil province.
The topographic maps were used to extract parameters of slope, area, average height of sub-basin, drainage density, length of main river, area percentage of different land uses in each sub-basin, precipitation, daily discharge (as independent variables) was used to analyze the factors affecting the amount of base flow. The daily discharge data recorded in 22 hydrometric stations were used. The base flow was calculated from the daily flow hydrograph by one-parameter algorithm method and programming in Excel software. The one-parameter algorithm method is one of the reverse numerical filter methods that are used in the flow rate signal processing, and separating the base flow from the fast flows using a recursive digital filter. In the following, the physiographic characteristics of the basins have been considered as independent variables, and base flow amount has been modelled using regression analaysis. The necessary statistical tests were performed in the screening stage, and the logarithm of the variables and the Box-Cox method were used to normalize the data. Then, collinearity between independent variables was tested using Pearson's correlation coefficient at 99% confidence level and the VIF values has been examined in SPSS software. Therefoe, independent variables with significant correlation (Sig<0.01) and (VIF>10) were excluded from the regression analysis due to collinearity. The multivariable regression model is an extended type of the bivariate linear regression model, in which it is tried to estimate the dependent variable based on several independent variables, Then, the stepwise regression approach has been considered for the modelling purpose. Then, considering base flow as dependent variables, and other physiographic parameters as independent variables, the most suitable methods has been chosen according to the efficiency assessment criteria.
Result and Discussion
The ANOVA table of the modelling showed that there is a significant relationship between independent and dependent variables. The obtained value showed that the rangeland percentage amount had a significant effect on the base flow amount. The degree of linear relationship between independent variables is measured by the tolerance index. Standardized β shows a very important role in predicting the dependent variable, so the daily discharge variable had a much greater contribution compared to other variables in the estimation of the dependent variable (base flow). According to the results, all the mentioned factors were considered in proposed regression model considering the VIF value less than 10. Based on the value (β), the contribution of independent was interpretated. The results revealed that the discharge, area, the percentage of medium to good rangelands, and the percentage of agriculture-residential area-garden are among the effective factors. The main river length, average height, and average slope were removed from the modelling procedure due to collinearity effect, and then the stepwise multiple regression was performed and the produced model accuracy were proved as significant (p-value <0.005). Also, the results indicate the positive and direct impact of vegetation and land use on the amount of base flow amount. The results of base flow modeling nased on presented model can be used in the ungauged areas adjacent to the studied watersheds in Ardabil province.
It should be noted that the hydrological response of the basins will be different on hourly, daily, monthly or yearly scales. Therefore, modeling can be done in different time scales, which will help to better understanding of base flow contribution in river flow regime. It should also be noted that considering the influence of factors such as extraction or river flow diversion can affect the accuracy of the results. In addition, the effect of human modifications on the change of the contribution of the river's base flow is important that is usually not considered in modeling and will be the source of a significant error. Also, the changes of climatic factors can affect the water flow of the river, and therefore, the study of the changes in the river flow over time can determine the effects of changes in climatic factors.