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.

Ice cores from mid-latitude mountain glaciers provide detailed information on past climate conditions and regional environmental changes, which is essential for placing current climate change into a longer term perspective. In this context, it is important to define guidelines and create dedicated maps to identify suitable areas for future ice-core drillings. In this study, the suitability for ice-core drilling (SICD) of a mountain glacier is defined as the possibility of extracting an ice core with preserved stratigraphy suitable for reconstructing past climate. Morphometric and climatic variables related to SICD are selected through literature review and characterization of previously drilled sites. A quantitative Weight of Evidence method is proposed to combine selected variables (i.e. slope, local relief, temperature and direct solar radiation) to map the potential drilling sites in mid-latitude mountain glaciers. The method was first developed in the European Alps and then applied to the Asian High Mountains. Model performances and limitations are discussed and first indications of new potential drilling sites in the Asian High Mountains are provided. Results presented here can facilitate the selection of future drilling sites especially on unexplored Asian mountain glaciers towards the understanding of climate and environmental changes.

In some sectors of the water resources management, the digital revolution process is slowed by some blocking factors such as costs, lack of digital expertise, resistance to change, etc. In addition, in the era of Big Data, many are the sources of information available in this field, but they are often not fully integrated. The adoption of different proprietary solutions to sense, collect and manage data is one of the main problems that hampers the availability of a fully integrated system. In this context, the aim of the project is to verify if a fully open, cost-effective and replicable digital ecosystem for lake monitoring can fill this gap and help the digitalization process using cloud based technology and an Automatic High-Frequency Monitoring System (AHFM) built using open hardware and software components. Once developed, the system is tested and validated in a real case scenario by integrating the historical databases and by checking the performance of the AHFM system. The solution applied the edge computing paradigm in order to move some computational work from server to the edge and fully exploiting the potential offered by low power consuming devices.