Holistic-integrated approaches are needed to apply state-of-the-art knowledge to explain, explore, and predict hydrological phenomena in the landscape. Specific location- based environmental information is required to ensure a proper understanding of hydrological processes in time and space (Klug and Kmoch, 2014). Wireless sensor networks can monitor the environment in-situ and are available since decades and have been regularly reviewed and continuously improved (Klug and Kmoch, 2015). From a holistic and integrated science view, the mentioned approaches often do not consider energy autarchic field installations corresponding with low cost, open source developments and near real-time data transmission capabilities with the provision of standard compliant data for direct integration with environmental modelling tools.

With this presentation we provide a science base structure to organise and technically implement a near real-time transmission of information from wind direction, wind speed, air temperature, rainfall, soil moisture and soil temperature in three different depths, and the groundwater level. The whole system is based on low cost sensors and has been implemented on a platform independent and open source basis. For data transmission the ZigBee protocol is used but other protocols such as Wi-Fi, Bluetooth or mobile networks are available, too.

A SOS site has been established in the Upper Rangitaiki catchment. It comprises of a field computer (Raspberry Pi) with a direct internet link and a sensor board (Waspmote), that has 12 typical meteorological, hydrological and pedological sensors attached to it (i.e., wind speed, wind direction, rainfall, 1x groundwater probe, 5x temperature and 3x soil moisture). The Raspberry Pi and Waspmote can be monitored and reprogrammed from a browser allowing, for example, remote adjustment of the sampling interval (Klug et al., 2015). This SOS site setup allows scaling up to a multitude of low cost, low energy, sensor stations throughout a catchment, with only one field computer that serves as data logger for backup.

The Upper Rangitaiki SOS site was co-located with a Bay of Plenty Regional Council climate monitoring station (Rangitaiki at Kokomoka, elevation 760 m) for comparison purposes. The Kokomoka station measures rainfall, soil moisture, soil temperature and groundwater recharge in lysimeters.

The Raspberry Pi, running a standard Linux operating system, transferred observation data in 10 minute intervals in near real-time via a 3G mobile data connection to an online SOS server. The Waspmote, a microprocessor and a custom circuit board with the sensors connected to it, has collected data and forwarded this data to the field computer in 10-minute intervals via robust, low power, ZigBee wireless protocol. From this service the observations were available in a standardised open format. The website accessed the raw data from the SOS server and plotted data points within 5-10 minutes of field measurement. This website was easily accessible via browsers and smartphones.

Datasets are provided in the OGC standards compliant data encodings Observations & Measurements and Water Markup Language 2.0 (Kmoch et al. 2015). The sensor metadata is available in Sensor Markup Language. Energy autarchy is ensured with a small solar panel and a battery connected to the sensor units. The low cost setup enables us to allow for more hydro-climate stations to be spread in designated case study areas, like in the Alpine / pre-Alpine border where especially rainfall is varying extremely. Thus, large-scale variations of environmental parameters can be captured at higher resolution with a greater spatial accuracy.

SMART Data Portal Sensor series

References

Kmoch, A., Klug, H., Ritchie, A. B. H., Schmidt, J., & White, P. A. (2015). A Spatial Data Infrastructure Approach for the Characterization of New Zealand’s Groundwater Systems. Transactions in GIS, Early View, http://doi.org/10.1111/tgis.12171

Klug, H., & Kmoch, A. (2015). Operationalizing environmental indicators for real time multi-purpose decision making and action support. Ecological Modelling, 295(0), 66–74. http://dx.doi.org/10.1016/j.ecolmodel.2014.04.009

Klug, H., & Kmoch, A. (2014). A SMART groundwater portal: An OGC web services orchestration framework for hydrology to improve data access and visualisation in New Zealand. Computers & Geosciences, 69(0), 78–86. http://dx.doi.org/10.1016/j.cageo.2014.04.016