Excellent question.
Freshwater science is undergoing rapid changes that are associated with increases in technology. For example, data collection has traditionally been limited by logistical capacity— the ability to get to the research site (sometimes by boat or float plane) and return to the laboratory with a water sample. While these types of activities still occur, they are now increasingly supplemented by automated sensors that can connect to satellites. These sensors often collect data at much higher frequencies than traditional methods and they can be available in ‘real time’ for decision makers. An example of this is for drinking water facilities that now monitor source water for algal blooms or high levels of suspended particles in real time, which allows them to adjust their processes like the amount of chlorination required. The large increase in data from sensors will mean that science disciplines like Machine Learning and Artificial Intelligence will become increasingly important.
Although it might seem like a small thing, there have already been large improvements in the accessibility of data (open data) which have led to an upsurge in global analyses of freshwater (for example, how climate change is affecting the properties of lakes at a global scale). We expect this trend to continue. Some additional advancements in the past 10 years, like the ability to reliably measure environmental DNA, are increasingly being incorporated into research and monitoring and hold great promise for our discipline. It may be that the use of eDNA becomes commonplace to measure biodiversity and the abundance of species not only present currently, but also back in time (through the evaluation of eDNA in sedimentary records).