Groundwater Level Prediction Using Support Vektor Machines and Autoregressive (AR) Modelss

Author(s):  
Fatih Üneş ◽  
Mustafa Demirci ◽  
Yunus Ziya Kaya ◽  
Eyup Ispir ◽  
Mustafa Mamak

Water resources managers can benefit from accurate prediction of the availability of groundwater. Ground water is a major source of water in Turkey for irrigation, water supply and industrial uses. The ground water level fluctuations depend on several factors such as rainfall, temperature, pumping etc. In this study, Hatay Amik Plain, Kumlu region was evaluated using Autoregressive (AR) and Support Vektor Machines (SVMs) methods. The monthly groundwater level was used the previous years data belonging to the Kumlu region.

2020 ◽  
Vol 174 ◽  
pp. 01039
Author(s):  
Olga Puhova ◽  
Vladimir Lebedev

The article evaluates the weather and hydrological impact on geotechnology when fragmented peat is milled and dried at a peat deposit. The amount of moisture feeding the fragmented peat of a deposit was studied and was determined to depend on the ground water level. The influence of drainage on the water regime of a high-more peat deposit and that of weather conditions on ground water level fluctuations over time have been evaluated at production sites with an open drainage network. When a peat deposit is drained, under the action of gravitation (the pressure differential in the ground and a drain), ground water seeps into the drains and is transported along them, down-grade, to the collection network and diverted from the drained area. The processes of moisture movement at a peat deposit help evaluate and justify measures to improve its water-air regime which is used in the development of intensive draining methods for a peat deposit and the maintenance of the necessary water regime in peat deposits.


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