Hydrological monitoring and real-time access to Wireless Sensor data are valuable for hydrological research and water resources management. In the recent decades, Wireless Sensor rapid developments in digital technology, micro-electromechanical systems, low power micro-sensing technologies and improved industrial manufacturing processes have resulted in retrieving real-time data through Wireless Sensor Networks (WSNs) systems. In this study, a remotely operated low-cost and robust WSN system was developed to monitor and collect real-time hydrologic data from a small agricultural watershed in harsh weather conditions and upland rolling topography of Southern Ontario, Canada. The WSN system was assembled using off-the-shelf hardware components, and an open source operating system was used to minimize the cost. The developed system was rigorously tested in the laboratory and the field and found to be accurate and reliable for monitoring climatic and hydrologic parameters. The soil moisture and runoff data for 7 springs, 19 summer, and 19 fall season rainfall events over the period of more than two years were successfully collected in a small experimental agricultural watershed situated near Elora, Ontario, Canada. The developed WSN system can be readily extended for the purpose of most hydrological monitoring applications, although it was explicitly tailored for a project focused on mapping the Variable Source Areas (VSAs) in a small agricultural watershed.
Long-term, high-quality climatic and hydrological data are essential for hydrological research and the implementation of effective water management strategies at both field and watershed scale. Monitoring and collecting long-term data from remotely located watersheds are time-consuming and expensive; due to the need for frequent visits to the sites for maintaining and monitoring the instruments and for data collection . Though this approach involves a significant amount of time and resources; it is imperative and valuable. Currently, a number of data acquisition technologies are being used to obtain hydrological data. Accuracy, resolution, and scalability are some of the significant issues that need to be addressed in developing an efficient and robust hydrological monitoring system  . In the earlier techniques, analog type network with cables and a number of sensors wired to data loggers were used for hydrological monitoring. The need for cabling in the field increases costs and restricts the spatial size of the monitoring area   , whereas the digital wireless networks can be deployed to collect long-term data at larger scale and resolution while maintaining robust and reliable network performance   .
In recent years, the rapid development of WSN technology has created new opportunities for sensing, computing, and communication in a wide range of applications in the field of science and engineering. WSNs integrate real-time sensing, computing, and communicating processes and provide an efficient and cost-effective observation technique, monitoring, gathering data, performing local computations and relaying the aggregated data capabilities  .
WSNs comprise of few to several “nodes” (known as a Mote in North America) where each node is connected to one or more sensors . Each sensor node has four key components: 1) the microprocessor & ADC (analog to digital converter), 2) transceiver & antenna, 3) memory unit, and 4) external sensors . The individual sensor node consists of a number of hard-wired sensors. Each node is wirelessly connected to other nodes, and finally to a central base station (Figure 1). A digital WSNs comprised of spatially distributed nodes connected to sensors communicates bi-directionally to the central location . As WSN does not require cables, they are cheaper and easier to install, in addition to requiring low maintenance. Flexibility, easy and rapid deployment, self-organization, high sensing reliability, and low-cost characteristics of WSNs make them a promising technology for various applications  .
WSNs can be used with many diverse types of sensors, such as thermal, optical, acoustic, seismic, magnetic, infrared, pressure and radar . Sensors used in WSNs convert physical parameters like temperature, soil moisture, pressure, light, speeds, etc. into a signal and measure them electrically .