Effect of various structures and input on the estimation of daily discharge of Amameh watershed

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motamednia mahboubeh; NOHEGAR AHMAD; MALEKIAN ARASH; saberi anari maryam

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Journal: Journal of Range and Watershed Managment Year:2018 | Volume:70 | Issue:4 Page(s): 1045-1066

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Information Journal Paper

Title

Effect of various structures and input on the estimation of daily discharge of Amameh watershed

Author(s)

motamednia mahboubeh | NOHEGAR AHMAD | MALEKIAN ARASH | saberi anari maryam | Issue Writer Certificate

Keywords

Amame representative watershedQ1

Artificial Neuron NetworkQ1

Error Back PrapagationQ1

Rainfall-runoff relationshipQ1

Abstract

One of the most important of hydrological computing in ecosystem is estimation of the relationship between rainfall and runoff. So that investigation occurred processes in it and the estimate of important outputs such as flood and sediment is considered one the most important mission of a watershed project. Because of variable spatial and temporal characteristics of incident in the water cycle and the nonlinear relationship and uncertainties, none of the statistical and conceptual models are able to be a better and capable model for that. But today using nonlinear networks as intelligent system for forecasting such complicated event can be efficient and effective in many problems of ecology. For this aim it is used variables such as precipitation, temperature, evartanspiration, relative humidity and discharges in daily scale over 42 years period and assessment 62 different suggested structures for surveying river flow in Amame representative watershed. For comparison it used Multi Layer Perceptoron (MLP) and Radial Basis Function (RBF). The results show that out of 6000 available models for estimation river flow model number 54 with 8-9-8-1 network structure and 8 types of input variable such as precipitation (Pt), precipitation with two lags (Pt-1 and Pt-2), temperature (Tt), evartanspiration (ETt), relative humidity (Rht), and discharge with two lags (Qt-1 and Qt-2) with Multi Layer Perceptoron method has the best function. The error of model was 0. 03, 0. 18 and 0. 04 in training and 0. 02, 0. 14 and 0. 02 for testing stage for MSE, RMSE and MAE, respectively.

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APA: Copy

motamednia, mahboubeh, NOHEGAR, AHMAD, MALEKIAN, ARASH, & saberi anari, maryam. (2018). Effect of various structures and input on the estimation of daily discharge of Amameh watershed. JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), 70(4 ), 1045-1066. SID. https://sid.ir/paper/162527/en

Vancouver: Copy

motamednia mahboubeh, NOHEGAR AHMAD, MALEKIAN ARASH, saberi anari maryam. Effect of various structures and input on the estimation of daily discharge of Amameh watershed. JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES)[Internet]. 2018;70(4 ):1045-1066. Available from: https://sid.ir/paper/162527/en

IEEE: Copy

mahboubeh motamednia, AHMAD NOHEGAR, ARASH MALEKIAN, and maryam saberi anari, “Effect of various structures and input on the estimation of daily discharge of Amameh watershed,” JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), vol. 70, no. 4 , pp. 1045–1066, 2018, [Online]. Available: https://sid.ir/paper/162527/en

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