In low-income and developing countries, inadequate weather monitoring systems adversely affect the capacity of managing natural resources and related risks. Low-cost and IoT devices combined with a large diffusion of mobile connection and open technologies offer a possible solution to this problem. This research quantitatively evaluates the data quality of a non-conventional, low-cost and fully open system. The proposed novel solution was tested for a duration of 8 months, and the collected observations were compared with a nearby authoritative weather station. The experimental weather station is based in Arduino and transmits data through the 2G General Packet Radio Service (GPRS) to the istSOS which is a software to set-up a web service to collect, share and manage observations from sensor networks using the Sensor Observation Service (SOS) standard of the Open Geospatial Consortium (OGC). The results demonstrated that this accessible solution produces data of appropriate quality for natural resource and risk management.

A case study of glacial lakes outburst flood (GLOF) hazard assessment by satellite Earth observation (EO) and numerical modelling is presented for the supraglacial and ice-contact lakes on Thangothang Chhu glacier, Chomolhari area (Bhutan). Detailed geomorphological mapping, including landslide and rock glacier inventories, as well as surface displacement determination using an interferometric SAR (InSAR) satellite, allowed a GLOF hazard assessment for lake Wa-007 to be performed. Outburst scenario modelling was achieved by combining both empirical and numerical modelling approaches, revealing that only a flood wave can have an impact on the two human settlements located downslope of Wa-007 lake. The worst-case scenario, modelled thanks to r.damflood, allowed the wave-front arrival time, the maximum water depth and the arrival time of maximum water height for the two human settlements to be quantified. A long-term monitoring strategy based entirely on EO data, with an update cycle of 5 years, is proposed to assess the future evolution of the area.

Because of the spatial nature of groundwater-related data and their time component, effective groundwater management requires the application of methods pertaining to the Information and Communication Technologies sector, such as spatial data management and distributed numerical modelling. The objective of this paper is to demonstrate the effectiveness of the QGIS-integrated FREEWAT platform and an approach combining spatial data management and numerical models to target groundwater management issues. FREEWAT is a free and open source platform integrated in a Geographic Information System environment and embedding tools for pre- and post-processing of spatial data and integrating numerical codes for the simulation of the hydrological cycle, with a main focus on groundwater. To this aim, this paper briefly presents the FREEWAT platform, introduces the FREEWAT approach, and showcases 13 case studies in European and non-European countries where the FREEWAT platform was applied. Application of the FREEWAT platform to real-world case studies is presented for targeting management of coastal aquifers, ground- and surface-water interaction, climate change impacts, management of transboundary aquifers, rural water management and protection of groundwater-dependent ecosystems. In this sense, compared to other existing software suites, FREEWAT allows data analysis and visualization to accomplish each step of the modelling workflow, i.e., from data analytics, to conceptual model definition, to numerical modelling and reporting of results. The presented experiences demonstrate that improved access to data and the portability of models and models’ results can help to promote water sustainability from the local- to the basin-scale. Furthermore, FREEWAT may represent a valuable tool to target the objective of increasing the capabilities of public authorities and private companies to manage groundwater resources by means of up-to-date, robust, well-documented and reliable software, without entailing the need of costly licensing, nowadays seldom affordable by public water authorities. Based on the strengths highlighted, the FREEWAT platform is a powerful tool for groundwater resources management, and for data collection, sharing, implementation and comparison of scenarios, for supporting planning and decision-making.

A high frequency monitoring (HFM) system for the deep subalpine lakes Maggiore, Lugano and Como is under development within the EU INTERREG project SIMILE. The HFM system is designed to i) describe often neglected but potentially relevant processes occurring on short time scale; ii) become a cost-effective source of environmental data; and iii) strengthen the coordinated management of water resources in the subalpine lake district. In this project framework, a first HFM station (LM1) consisting of a monitoring buoy was placed in Lake Maggiore. LM1 represents a pilot experience within the project, aimed at providing the practical know-how needed for the development of the whole HFM system. To increase replicability and transferability, LM1 was developed in-house, and conceived as a low-cost modular system. LM1 is presently equipped with solar panels, a weather station, and sensors for water temperature, pH, dissolved oxygen, conductivity, and chlorophyll-a. In this study, we describe the main features of LM1 (hardware and software) and the adopted Quality Assurance/Quality Control (QA/QC) procedures. To this end, we provide examples from a test period, i.e., the first 9-months of functioning of LM1. A description of the software selected as data management software for the HFM system (IstSOS) is also provided. Data gathered during the study period provided clear evidence that coupling HFM and discrete sampling for QA/QC controls is necessary to produce accurate data and to detect and correct errors, mainly because of sensor fouling and calibration drift. These results also provide essential information to develop further the HFM system and shared protocols adapted to the local environmental (i.e., large subalpine lakes) and technical (expertise availability) context. Next challenge is making HFM not only a source of previously unaffordable information, but also a cost-effective tool for environmental monitoring.