IDENTIFYING THE GULLY EROSION POTENTIAL BY USING ARTIFICIAL NEURAL NETWORK (ANN), CASE STUDY: TROUD WATERSHED

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SHADFAR SAMAD

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Paper Information

Journal: WATERSHED ENGINEERING AND MANAGEMENT Year:2016 | Volume:8 | Issue:3 Page(s): 256-263

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Information Journal Paper

Title

IDENTIFYING THE GULLY EROSION POTENTIAL BY USING ARTIFICIAL NEURAL NETWORK (ANN), CASE STUDY: TROUD WATERSHED

Author(s)

SHADFAR SAMAD | Issue Writer Certificate

Keywords

GULLYQ1

HIDDEN LAYERQ1

LEVENBERG-MARQUARDT (LM)Q1

MULTI LAYER PERCEPTRONQ1

RANGELANDQ1

SIGMOIDQ1

Abstract

GULLY erosion is a type of water erosion that causes significant sedimentation in watersheds and damages in agricultural lands, RANGELANDs, and infrastructures. This study was conducted to determine the potential of GULLY erosion by artificial neural network. The Levenberg-Marquardt (LM) algorithm and Multi-Layer Perceptron were used employing soil, geology, land use, distance to fault, slope, aspect, distance from roads, distance from drainage, and elevation data as its variables. Results showed that the structure of 1-13-9 with SIGMOID activation function in the HIDDEN LAYER is more suitable for GULLY erosion potential assessment. Zonation of GULLY erosion revealed that the watershed area was divided into different classes of different extent, including 70. 26% in very low, 1. 71% in low, 2. 45% in medium, 2. 65% in high, and 22. 93% in very high potential class. Furthermore, results indicated that slope less than 10%, 50 m distance from the stream, RANGELAND area, and lithological units of EM and M2 had the greatest impact on the occurrence of GULLY erosion.

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APA: Copy

SHADFAR, SAMAD. (2016). IDENTIFYING THE GULLY EROSION POTENTIAL BY USING ARTIFICIAL NEURAL NETWORK (ANN), CASE STUDY: TROUD WATERSHED. WATERSHED ENGINEERING AND MANAGEMENT, 8(3 ), 256-263. SID. https://sid.ir/paper/234775/en

Vancouver: Copy

SHADFAR SAMAD. IDENTIFYING THE GULLY EROSION POTENTIAL BY USING ARTIFICIAL NEURAL NETWORK (ANN), CASE STUDY: TROUD WATERSHED. WATERSHED ENGINEERING AND MANAGEMENT[Internet]. 2016;8(3 ):256-263. Available from: https://sid.ir/paper/234775/en

IEEE: Copy

SAMAD SHADFAR, “IDENTIFYING THE GULLY EROSION POTENTIAL BY USING ARTIFICIAL NEURAL NETWORK (ANN), CASE STUDY: TROUD WATERSHED,” WATERSHED ENGINEERING AND MANAGEMENT, vol. 8, no. 3 , pp. 256–263, 2016, [Online]. Available: https://sid.ir/paper/234775/en

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