Comparing the performance of Artificial Neural Network (ANN) to predict the long term Meteorological Drought using Climatic Parameters and teleconnection (case study: South of Qazvin Province)

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maghsoud fatemeh; YAZDANI MOHAMMAD REZA; RAHIMI MOHAMMAD; MALEKIAN ARASH; ZOLFAGHARI ALI ASGHAR

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Journal: Journal of Range and Watershed Managment Year:2018 | Volume:70 | Issue:4 Page(s): 1015-1030

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Title

Comparing the performance of Artificial Neural Network (ANN) to predict the long term Meteorological Drought using Climatic Parameters and teleconnection (case study: South of Qazvin Province)

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Keywords

DroughtQ2

Gamma-TestQ1

predictionQ1

Artificial NetworkQ1

Climatic SignalQ1

Abstract

Overview, Drought is effected an unusual dry period which is enough continued and causes imbalance in the hydrologic status, as depletion of surface water and groundwater resources. The purpose of this research is modeling meteorological Drought prediction using Neural Network-Multi layer Perceptron, parameters and Climatic Signals in three time scales include short, middle and long term in a rain-gauge station located at south plain of Qazvin Province. Three different scenarios were tested as inputs model. Optimal combination of variables was determinate by Gamma-Test after identification of input variables using cross-correlation. Results showed, influence of Climatic Signals increased and against the influence of meteorological parameters decreased when time scale were increased from short-term to long-term. MEI (Multivariate ENSO Index) and rainfall were introduced as the most effective Climatic Signals and meteorological parameter for each scale, respectively. Neural Network modeling which has hidden layer with enough neurons, Sigmoid Function in middle layer and linear function at output layer was used. The most appropriate of the number neurons was determined in each scenario and wasn’ t observed significant correlation between increasing or decreasing the error and number of neurons. Finally, the most appropriate network structure was determined based on evaluation indexes in three scenarios and each time scale.

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APA: Copy

maghsoud, fatemeh, YAZDANI, MOHAMMAD REZA, RAHIMI, MOHAMMAD, MALEKIAN, ARASH, & ZOLFAGHARI, ALI ASGHAR. (2018). Comparing the performance of Artificial Neural Network (ANN) to predict the long term Meteorological Drought using Climatic Parameters and teleconnection (case study: South of Qazvin Province). JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), 70(4 ), 1015-1030. SID. https://sid.ir/paper/162535/en

Vancouver: Copy

maghsoud fatemeh, YAZDANI MOHAMMAD REZA, RAHIMI MOHAMMAD, MALEKIAN ARASH, ZOLFAGHARI ALI ASGHAR. Comparing the performance of Artificial Neural Network (ANN) to predict the long term Meteorological Drought using Climatic Parameters and teleconnection (case study: South of Qazvin Province). JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES)[Internet]. 2018;70(4 ):1015-1030. Available from: https://sid.ir/paper/162535/en

IEEE: Copy

fatemeh maghsoud, MOHAMMAD REZA YAZDANI, MOHAMMAD RAHIMI, ARASH MALEKIAN, and ALI ASGHAR ZOLFAGHARI, “Comparing the performance of Artificial Neural Network (ANN) to predict the long term Meteorological Drought using Climatic Parameters and teleconnection (case study: South of Qazvin Province),” JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), vol. 70, no. 4 , pp. 1015–1030, 2018, [Online]. Available: https://sid.ir/paper/162535/en

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