Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Plant and Environmental Science

Committee Member

Dr. A. Bulent Koc, Committee Chair

Committee Member

Dr. Calvin B. Sawyer

Committee Member

Dr. Charles V. Privette

Committee Member

Dr. Christopher Post


Water quality assessment for the management of water resources requires the collection of water samples for physical, chemical, and biological analysis. It is essential to reduce the cost of water quality monitoring by minimizing the number of grab samples and to reduce the sampling time by rapidly accessing the sampling points. Adaptive, remote, and smart water sampling systems can provide more effective water quality monitoring programs. An adaptive water sampling system with an unmanned aerial vehicle integrated with sensor nodes was developed and tested in this research. Individual phases of this research were; in-situ water quality measurements with a UAV-integrated sensor node; autonomous water sample collection with a UAV-integrated water sampler; and integration of water sampler and sensor node sub-systems for UAV-assisted adaptive water sampling. The UAV-assisted adaptive water sampling system consists of a hexacopter UAV, a triple water sampling cartridge, and a sensor node. The payload capacity and endurance of the UAV were determined using an indoor test station. The UAV was able to hover 10 min while producing 64 N of thrust at 4.61 kg of takeoff weight with no payload attached. The thrust-to-weight ratio of the UAV was measured as 1.41 at 50% throttle level. The adaptive water sampling method depended on computerbased automated decision making. The decision to activate the water sampling cartridge for water sample collection was made based on pH, dissolved oxygen (DO), electrical conductivity (EC), and temperature sensor inputs from the sensor node. The adaptive sampling enabled selective water sample collection only when the water constituent measurements exceeded the assigned allowable limits during indoor tests. Field experiments were conducted to test the systems to achieve adaptive water sampling from a 1.1 ha fishing pond and a 11 ha portion of a 36 ha lake. Instantaneous decision making for sample collection based on in-situ pH, DO, EC and temperature measurements would eliminate unnecessary water sample collection while providing data with high spatial resolution for assessing water quality in surface waters.



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