Understanding groundwater resources and their informed management ask for regular monitoring of groundwater state variables, both quantity and quality. Collected observations need to be stored, processed and shared among stakeholders. The Global Groundwater Monitoring Network (GGMN) assists (already since 2007) in improving the quality and accessibility of groundwater information and eventually the understanding of the state of groundwater resources (www.un-igrac.org/ggmn). This abstract summarises some advances in data collection, processing and sharing, accounted within GGMN activities.
Although automatic groundwater monitoring and even telemetric transmission of data are becoming widely used, manual collection of data is still present or even predominant, the choice depending on parameters and purpose of the monitoring, groundwater regime, available resources, and others. In order to facilitate data collection in the field and data transmission to the GGMN Portal, a mobile (smartphone) application is recently developed. This GGMN App enables users to geo-reference and register groundwater monitoring wells, store groundwater monitoring data in the field and (immediately or later if WIFI is not available) transfer data to GGMN and store it there. In GGMN, data can be processed and optionally shared with other data providers and stakeholders.
One of the most effective ways to share time series data among online data portals is through an automated Sensor Observation Service (SOS). This service has been recently implemented in GGMN and tested by connecting GGMN and the Groundwater Information Network (GIN) of the Geological Survey of Canada. Since GGMN aims to serve as a global monitoring focal point, the ultimate goal is establishing the same or comparable data sharing services with as many as possible national groundwater services around the world.
IGRAC is preparing a global overview of national groundwater services with a focus on temporal and spatial processing of groundwater observations. It is a general impression that collected observations are not processed sufficiently. On the other hand, some services exhibited creative approaches in the processing of (in particular) spatial variability of groundwater variables. These approaches will be promoted through the IGRAC global overview and some of them are considered to be implemented in GGMN soon.