Spatial Pattern of Sediment Yield by Sediment Structural Connectivity Model in the Taleghan Watershed, Iran

Nowadays, due to the importance of sediments in watersheds, the integrated watershed management in the country requires a specific framework in planning related to monitoring and control of sediments.One of the most effective methods is the use of sediment connectivity index (IC). Connectivity process is an innovative concept to understand the processes which occur in the watershed area that affect water flow and sediment movement at different spatial-temporal scales. This index explains the degree of connection of the sediment flow throughout the watershed, especially between the sediment source and the downstream area, and in a way, expresses the sediment delivery ratio. Therefore, the current research is conducted with the aim of investigating the sediment connectivity in Taleghan watershed of Alborz province to extract the sediment connectivity index map and also verify the results with field investigations.

In this research, in order to investigate the spatial pattern of sediment production in the watershed, the sediment connectivity map of the basin was drawn from the method presented by Borselli et al. and the definition of connectivity index (IC). For this purpose, at first, topographic data from 30-Meter Digital Elevation Model and vegetation data at 10- and 30-meters spatial resolution are obtained with Sentinel-2A and Landsat 8 images, respectively, and by using data layers such as the average slope gradient, the average weighting factor and the upslope contributing area the amount of upstream component of the flow starting path in sediment transport was calculated. Then, using the layers of the length towards the downslope path, the weight factor of each cell and finally the slope gradient of each cell, the downstream component in the sediment connectivity network was calculated and by referring to catchment outlet in the ArcGIS 10-2-2 software, the connectivity index for all pixels Calculated and the sediment connectivity map was drawn. The IC can assume values ranging from -∞ to +∞ and as IC grows toward +∞, the connectivity increases, finally in order to evaluate the results of the field connection index model (FIC), it is implemented in 30 points of the watershed and the correlation between the IC index and FIC in these points are evaluated. 

According to the findings of this research as well as the fitting of IC sediment connectivity index values with FIC field sediment connectivity index in 30 points, the relationship between these two indicators is linear. The coefficient of determining the output of the model with a spatial accuracy of 30 meters was obtained with a numerical value of 0.62, It shows the higher accuracy of the sediment connectivity index results with a spatial resolution of 10 meters compared to 30 meters. Although the distribution of the points is irregular in some cases, the general trend of the results shows that with the increase in the amount of IC connection, the amount of FIC field computing sediment connection has also increased linearly. In calculating the index of connectivity, the factors such as the shape, slope and roughness of the basin which are easily accessible due to the less data requirement and high efficiency, can be the basis for improving the estimation of sedimentation models.

In this research, the results show that the sediment connectivity index with a spatial accuracy of 10 meters has a higher accuracy than the connectivity index with a spatial accuracy of 30 meters. In addition, the results demonstrate the slope and the vegetation factor are critical parameters in the sedimentation of the Taleghan watershed. It is also worth mentioning that in order to investigate the effect of the watershed area and the principal waterway length, the results of the sediment connectivity index can be evaluated more precisely at the sub-basin and even the hillslopes. Considering the importance of these items in the sedimentation of each sub-basin, including the flow direction map and flow accumulation in the assumptions of this model, is one of the advantages of this technique. The other important advantage of this model is its low data requirement, which can greatly reduce the complexity and data requirements of existing erosion and sedimentation models.