A general architecture for collection and processing of water resources data, in terms of quality and quantity, is presented and discussed. The proposed architecture includes the sensing of physical and chemical water parameters, data communications, and high levels of information processing, namely machine learning. The architecture adopts an Internet of Things perspective and resulted from a survey of the most commonly measured water quality parameters, processing and data acquisition computing modules, and communications hardware and software protocols. It integrates state of the art technologies in the fields of long distance communications, software containers and blockchain technologies. Geographical information is associated with the sensor data. The top layer joins data analysis and machine learning of all the gathered information. Visualization of the raw data and of the results of the data analysis and machine learning procedures is also part of the system. The integration of weather and remote sensing data, and offline biochemical information is presented in this architecture. The architecture is supported on common commercial of the shelf components and open source software.