Reservoir evaporation prediction modeling based on artificial intelligence methods

Mohammed Falah Allawi, Faridah Binti Othman, Haitham Abdulmohsin Afan, Ali Najah Ahmed, Md Shabbir Hossain, Ming Fai Chow, Ahmed El-Shafie

Research output: Contribution to journalArticle

Abstract

The current study explored the impact of climatic conditions on predicting evaporation from a reservoir. Several models have been developed for evaporation prediction under different scenarios, with artificial intelligence (AI) methods being the most popular. However, the existing models rely on several climatic parameters as inputs to achieve an acceptable accuracy level, some of which have been unavailable in certain case studies. In addition, the existing AI-based models for evaporation prediction have paid less attention to the influence of the time increment rate on the prediction accuracy level. This study investigated the ability of the radial basis function neural network (RBF-NN) and support vector regression (SVR) methods to develop an evaporation rate prediction model for a tropical area at the Layang Reservoir, Johor River, Malaysia. Two scenarios for input architecture were explored in order to examine the effectiveness of different input variable patterns on the model prediction accuracy. For the first scenario, the input architecture considered only the historical evaporation rate time series, while the mean temperature and evaporation rate were used as input variables for the second scenario. For both scenarios, three time-increment series (daily, weekly, and monthly) were considered.

Original languageEnglish
Article number1226
JournalWater (Switzerland)
Volume11
Issue number6
DOIs
Publication statusPublished - 01 Jun 2019

Fingerprint

artificial intelligence
Artificial Intelligence
Artificial intelligence
evaporation
Evaporation
evaporation rate
scenario
prediction
modeling
Malaysia
time series
Rivers
Time series
methodology
Temperature
neural network
neural networks
time series analysis
river
method

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Geography, Planning and Development
  • Aquatic Science
  • Water Science and Technology

Cite this

Allawi, Mohammed Falah ; Othman, Faridah Binti ; Afan, Haitham Abdulmohsin ; Ahmed, Ali Najah ; Hossain, Md Shabbir ; Chow, Ming Fai ; El-Shafie, Ahmed. / Reservoir evaporation prediction modeling based on artificial intelligence methods. In: Water (Switzerland). 2019 ; Vol. 11, No. 6.
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Reservoir evaporation prediction modeling based on artificial intelligence methods. / Allawi, Mohammed Falah; Othman, Faridah Binti; Afan, Haitham Abdulmohsin; Ahmed, Ali Najah; Hossain, Md Shabbir; Chow, Ming Fai; El-Shafie, Ahmed.

In: Water (Switzerland), Vol. 11, No. 6, 1226, 01.06.2019.

Research output: Contribution to journalArticle

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