Increasing the accuracy of predicting sediment yield in watem/sedem model using image fusion algorithm (case study: Darkesh watershed)

Subject Areas : Farm water management with the aim of improving irrigation management indicators

عاطفه بهزادفر ¹ , Abdulvahed Khaledi Darvishan ² , علیرضا قره گوزلو ³

1 - دانش آموخته کارشناسی ارشد سنجش ازدور وسیستم اطلاعات جغرافیایی، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات، تهران، ایران
2 - Department of Watershed Management Engineering, College of Natural Resources, Tarbiat Modares University
3 - دانشیار آموزشکده سازمان نقشه برداری‌کشور

Received: 2016-09-22 Accepted : 2017-06-14 Published : 2017-10-23

Keywords: sediment delivery ratio, multispectral images, panchromatic images, Soil Erosion,

Abstract :

Nowadays, knowing the amount of soil erosion is an important part of the comprehensive management ofwatersheds. Due to the lack of sufficient information and data relating to water and sediment discharges inwatersheds, soil erosion is estimated using user-friendly models and new technologies. The aim of this study isto predict erosion and sediment yield in the Darkesh watershed, North Khorasan province, usingWaTEM/SEDEM model and RS and GIS and image fusion algorithm. At the first, the crop management factor(C) was mapped based on land use map. The Gram-Schmidt algorithm was used to combining multispectralimages Landsat 7 and 8 with panchromatic images for the two satellite images with 12-year time distance (2003and 2015) and a scale of 1:25,000. The maps of other input factors were then prepared using ArcGIS and ENVIsoftware and the model was run and the rates of erosion and sediment yield with the scale of 1:25,000 waspredicted with and without image fusion algorithm and were compared with the observed rates in the watershed.Comparing observed sediment data in Darkesh watershed with predicted amounts showed that the final map oferosion classification by applying image fusion algorithm led to better and more accurate identification oferosion sensitive areas. Based on the results of this study, high-performance of WaTEM/SEDEM model topredict of sediment yield was proved and it was found that image fusion algorithm was also led to increase theaccuracy of the results.

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