(1) Background: river ice has a significant impact on nearly 66% of rivers in the Northern Hemisphere. Ice builds up during winter when the flow gradually reduces to its lowest level before the spring melt is initiated. Ice-induced floods can happen quickly, posing a risk to infrastructure, hydropower generation, and public safety, in addition to ecological repercussions from the scouring and erosion of the riverbeds. (2) Methods: we used the annual daily hydrograph to develop a RiTiCE tool that detects the break-up date and develops indices to analyze timing characteristics of extreme flow in the Tana and Tornio Rivers. (3) Results: the study showed that low-flow periods in two rivers had a significant trend with a confidence level of 95%. Additionally, it was observed that the occurrence date of seasonal 90-day low- and high-flow periods occurred earlier in recent years. Conversely, the Tana River showed a negative trend in its annual minimum flow over the century, which is the opposite of what happened with the Tornio River. (4) Conclusions: the method can be used to detect the date when the river ice breaks up in a given year, leading to a better understanding of the river ice phenomenon.
<p>Water Quality Management (WQM) in the 21st century is a growing challenge because of the large number of chemicals used in our everyday lives and industry, which often make their way into our waters&#160; outbreaks of waterborne infectious diseases are still a public health concern in developed countries. More than 50% of European surface water bodies are either in less than good ecological status or potentially in worse condition. These trends reflect the need to shift from basic responsiveness to a comprehensive, multidisciplinary approach that involves communities to improve access to safe water and improve the quality of water bodies. In this research project, we will design a mobile app platform for a Smart Water Quality Monitoring/Warning System based on Remote Sensing (RS) images and available in situ data for City of Oulu as one of the leading smart cities in Europe. This platform will forecast Water Quality (WQ) parameters for open lakes that people often use for swimming and leisure activities. It works as an early warning system to notify people about WQ in advance. The following parts will constitute the proposed Smart Water Quality Monitoring/Warning System (SWQMS): 1) Data collection from Landsat and Sentinel-2, 2) Data processing and information extraction about WQ criteria, 3) Designing a user interface to notify WQ condition to the community before planning for activities &#160;4) real-time updating based on the inhabitant feedback on appearence water condition (Color, Turbidity etc.).&#160; Along with the processing steps, this project faces some challenges on 1) Finding the best algorithm for WQ measurement in Nordic regions, 2) Improving temporal frequency in mid-resolution satellites in the cloudy sky, 3) Identifying the best machine learning approach to monitor and predict WQ in remote sensing, 4) combining remote sensing and GIS technology to designing a web-based early warning platform.</p><p>Two open lakes in north of Oulu City have been considered: 1) Kuivasj&#228;rvi and 2) Pyykosj&#228;rvi. These lakes are located in a populated area and are widely used for swimming and fishing in summertime. Eutrophication problems significantly face lakes due to the low oxygen content of the water and the prolonged water circulation because of specific layouts and geometry. Besides, due to their specific locations at the heart of densely populated areas, their quality are important for inhabitants&#8217; health and the City of Oulu. Two lakes are connected through a narrow stream, and the lower lake (kuivasj&#228;rvi) is mainly fed by upper lakes and drain water of the watershed. The outlet of kuivasj&#228;rvi discharges into the Bay of Bothnia.</p><p>Finally, this platform is going to help to have a safe leisure activities in open lakes and even coastal regions so it can be extended to all around the world. By this application, it is expected to significantly reduce the number of water related disease outbreakes which are caused by swimming in open lakes and coastal regions.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.