Digital Terrain Model (DTM) of the North Alborz region based on its underneath faulting

Panahi Vaghar Ch, B. Voosoghi, S. Haji Aghajany

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Topography is usually resulted from the patterns of the plate tectonics and faults in relation to each other. If we can produce a model for these actions and reactions after the complete recognition of the fault charactersitics based on their slip rates in the considered region, an applied model is obtained which reconstructs the topography of the region. A more important fact is that this model which illustrates the relation between topography (as the super-structure) and faults interaction of the considered region (as the infra-structure), can be used as a criterion to recognize the undiscovered fault's structures of the study area. It can provide us a chance to determine the fault parameters such as slip rates. Iran is known as an area which is subjected to the high possibility of the earthquakes as a natural hazard. Thus earthquake studies are important to investigate this hazard. In this study, a model of the topography is constructed in the region which is prone to earthquakes. The model is compared with the digital terrain models (DTM) of the area resulted from the satellite image data sets. This comparison provides us a structural control on the faults of the region. Our case study is modeling the relationship between faulting and the topography in the North Alborz. Results of the study let us obtain criteria for understanding and prediction of the fault structures that have created the topography. In order to achieve this goal, we consider a DTM of Alborz region. With variation of the parameters of the faults and creating various fault models, an estimate of the elevation model of the region is constructed for the life time of the faults. We consider the variation domains for five parameters of the activity period, slope, horizontal slip rates in length and slope directions and the vertical slip rate of the main faults of the region. The optimum values of these parameters are obtained based on the neural network optimization method. Then, the topography of the region is modeled based on the numerical results of the method for the unknown fault parametrs. We use the algorithm of the method with some selected variation ranges for the values of the parameters for each selected fault of the region. For the slope parameter of the faults, a range of 30 to 90 degrees, for the horizontal slip rate on the length direction and the slope direction of the fault, a range of -3 to +3 mm per year and for the vertical slip rate, a range of -0.5 to +2 mm per year have been considered as variation ranges of the unknown parameters in the algorithm. These variation ranges are considered based on the previous studies on geodynamic setting of the region. The parameters of the nine main acitive faults in the North Alborz region make the assumed fault system of the region and the modeled topography of the region to be generated. Comparison of the modeled topography with the real elevation model of the region can be evaluated as how changing the data of fault parameters and the possible reconfiguration of these parameters, such as the slip rate, time activity and the slope fault can obtain more suitable results in the modeling. In other words, the method can be used to determine which configuration and fault structure in study region will lead us to a more consistent model and provides us the possibility of modeling the topography of the region based on the fault structures. The numerical results show the differences from -85 m to 236 m between the model result and the real elevation model. In addition, the root mean square error between the DTM and the model is 61.1 m which is an acceptable result, due to the fact that only five parameters are variable and just nine faults are calculated while ignoring the effects of erosion and sedimentation of soil in the final format of the earth topography. More accurate results can be obtained by increasing the number of faults and their parameters in the model.

Original languageEnglish
Pages (from-to)229-244
Number of pages16
JournalJournal of the Earth and Space Physics
Volume43
Issue number2
DOIs
Publication statusPublished - 2017
Externally publishedYes

Keywords

  • Fault parameters
  • Neural network
  • Plate tectonics
  • Topography

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