In collaboration with Iranian Watershed Management Association

Document Type : Research Paper

Authors

1 MSc Student, Faculty of Natural Resources and Environment, Ferdowsi University of Mashhad, Iran

2 Assistant Professor, Faculty of Natural Resources and Environment, Ferdowsi University of Mashhad,Iran

3 Associate Professor, Faculty of Engineering, Ferdowsi University of Mashhad, Iran

Abstract

Landscape is one of the main factors influencing hydrological processes of the watershed. Changes in structure and spatial pattern of land use play important role in surface runoff and sediment yield. Determining the relationship between landscape patterns and hydrological processes can be used as an indicator of watershed soil erosion and sediment yield. Therefore, due to the problems in field measurement of sediment yield, its estimation using landscape properties and land use pattern is an appropriate alternative for current estimation methods. The purpose of this research is to determine the relationship between watershed sediment yield and landscape metrics in the selected sub-watersheds of Golestan Province. To this end, suspended sediment concentration data for all hydrometric stations of the studied province were obtained from the relevant resources and appropriate sub-watersheds were selected. Then, using the land use map of Golestan Province, 15 landscape metrics related to sediment yield were determined for different land uses by Fragstats 4.2 software. In order to determine the relationship between watershed sediment yield and landscape metrics, a partial least squares regression was used which combines the methods of principal component analysis and multiple linear regression. The relative importance of landscape metrics was determined through examining the values of Variable Importance for the Projection (VIP) and Regression Coefficients (RCs). The results of this study indicated that the watershed sediment yield is densely associated with land use patterns. The main indices in reducing sediment yield were the Largest Patch Index (LPI), the average of the nearest neighbor distance (ENN-MN) and the average of perimeter-area ratio (PARA –MN) with values of VIPs of 1.296, 1.184 and 1.747,  and regression coefficients of -0.014, -0.039, and -0.002, respectively. The main indices in incrising sediment yield were Landscape Shape Index (LSI) and mean patch size (AREA-MN) with regression coefficients of 0.020 and 0.017, respectively. The landscape characteristics in watersheds could account for as much as 71% of the variation in sediment yield of watershed. The results of study showed that the landscape characteristics can be used for watershed sediment yield modeling.

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