Investigation of Sea Level Changes due to Climate Parameters Using Decision Tree Algorithm, Makran Coast, the Northern Oman Sea

Document Type : Full length article


1 PhD Candidate in Physical Geography, Faculty of Geographical Sciences and Planning, University of Isfahan, Isfahan, Iran

2 Associate Professor of Physical Geography, Faculty of Geographical Sciences and Planning, University of Isfahan, Isfahan, Iran

3 Assistant Professor of Physical Geography, Faculty of National Defense, University of National Defense, Tehran, Iran

4 Professor of Strategic Management, Faculty of National Defense, University of National Defense, Tehran, Iran


The relationship between form and process is very important in geomorphology. By changing in the process, the forms will be changed and new processes will be created in reponse to the new forms. Sea level changes mainly include tidal variations and changes due to atmospheric factors. Tidal flows are also affected by coastal washing during their daily advancement and retreat on tidal slopes and tidal zones. The formation of many coastal geomorphologic forms is the result of their involvement. Climatic factors cause short time fluctuations and tidal cycles and long term fluctuations in medium level of sea. Sea level fluctuations influence important aspects of coastal climate, economic planning, agricultural issues, environmental problems and all other affairs related to sailing and marine constructions.
Torabi Azad and Honarmand (2016) performed a concise investigation about sea level changes in Bandar Abbas and Booshehr Stations in a period of 11 years (2000 to 2010) and analyzed and computed barometric effects, wind force and temperature on the sea level mean. The results showed that sea level mean in these stations has incremental trend by 5 cm and 4 cm respectively in the mentioned seaports.
Srivastava (2016) investigated the combined use of quantitative forecasting methods for sea level rise using exponential smoothing state space models (ESMs) and an Autoregressive Integrated Moving Average (ARIMA) model with sea level data over 17 years (1994–2010). The results of this present study suggest that the rate of Arabian Sea level rise is high, and if this is not taken into consideration, many coastal areas may be affected by climate-change-induced habitat loss in future.
Akbari et al (2017) applied 3D FVCOM Model in order to investigate and analyze important tidal components in a vast area including Persian Gulf, Hormuz Strait, Oman Sea and Arab sea. The results of this research showed that there is four kinds of tides in Persian Gulf including Daily, semi-Daily, daily compounded and semi-daily compounded tides. On the other regions, there is just semi-daily compounded tide. The purpose of this research is to investigate the effects of climate change parameters (temperature, pressure, and wind rate) on the sea level fluctuations in an annual, seasonal and monthly intervals and 20-year period in northern coasts of Oman Sea.
 Matarials and methods
The study area of this research is stretched from Jask port (with longitude of 570 46' E and latitude of 250 40' N) to Gowatre Bay in the terminal point of southeast Iran and at Pakistan border (with longitude of 570 46' E and latitude 250 10' N).
The sea level changes have been obtained from tide gauges of IOC (Intergovernmental Oceanographic Commission) in the stations of hydrography of Jask and Chabhar ports during 1997 to 2016. The tide gauges for the mentioned stations presented 1440 datum. In fact, they registered sea level in every minutes. In order to compute the data based on monthly averages, the tidal effects should be deleted and computed into level fragment that means sea level minus tidal effect. According to the presented information in meteorological organization since 1997 to 2016, we used pressure, temperature and wind data in research stations as monthly means and the monthly, seasonal and annual diagrams.  
In this research, Meta heurestic-Algorithm (Decision Tree Algorithm) and CARD regression tree decomposition algorithm (Classification and regression tree) is used as a type of regression decision tree for prediction purposes. Different elements have been used in simulation using decision tree model. These elements have been introduced as independent variables to the model and simulations have been made to predict the target variable. In order to verify the relationship between the final decision trees based on the statistical index, graphical graphs and correlation coefficients were obtained from the field operation method, visual inspection, ground monitoring and verification of control points.
Results and discussion
The model has been executed with three independent variables including temperature, pressure and wind in 240 data rows. It should be noted that we have used these 72 rows in the training phase and 168 rows in the test phase. The decision tree model in the Jask area has three parameters of wind pressure and wind speed, and the tree is based on these two parameters that the model did not use the temperature parameter in the decision tree. It was not selected as an effective parameter. In Chabahar region, all three parameters are used in the model. The above-mentioned model has a very high performance in predicting values. In most of the 12-month intervals, the model performed its predictions close to real values; in other words, the tree created using the data has a good prediction process and can simulate the changes well. According to the above figure, the predictions were evaluated. The results indicate that this model can be predicted with high accuracy in 95% confidence level for the region. Since the temperature parameter has not been able to predict the response variable in the decision tree, the model has been eliminated, and the final equation of Jask and Chabahar is as follows.
MSL(Jask) =13.197+5.619T(1.102)-11.092P(0.195)+7.208W(0.71)
MSL(Chabahar)=  4.520+1.529 T (1.089)-1.596P(0.87)+2.776 W(0.316)
The fluctuations of MSL are among the general methods of analysis. Therefore, accurate prediction can provide conditions for assessing the status. The purpose of this study was to investigate the effects of data pre-processing on the performance of nonlinear decision tree model in predicting MSL in Jask and Chabahar. The results of this study in all simulations show that pressure and wind parameters are more effective in the final model. This indicates the importance of these parameters in predicting future MSL. The close relationship between wind speed and water level changes is evident with the strong positive correlation coefficient of the Jask station compared with the Chabahar station in the annual windfall of both regions. The relationship between the final models is derived from the decision tree algorithm in MSL prediction using available data. Investigating the related geomorphologic forms in the study area, the tidal range fluctuations in the Chabahar region are ranged from 1 to 1.5 meters. Therefore, in a closer examination of the processes governing the environments around the coastline, it is necessary to study the status of the tidal region and the influential climatic parameters.


Main Subjects

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Volume 51, Issue 1
April 2019
Pages 105-122
  • Receive Date: 27 January 2018
  • Revise Date: 02 December 2018
  • Accept Date: 02 December 2018
  • First Publish Date: 21 March 2019