By Dr Kwok Chun
Environmental datasets provide critical information about our physical environment, helping us to monitor progress towards achieving global environmental targets, such as the United Nations Sustainable Development Goals (SDGs). Yet, reliable climate and water data are not available in many parts of the world. In many developed countries, such as the UK and US, there are dense environmental monitoring networks. However, these networks are expensive to establish and maintain. Where on-the-ground data is not readily available, satellite images can help us to fill gaps in data. Moreover, as well as helping us to monitor current conditions it is possible to use remote sensing (RS) datasets to predict future environmental conditions. Even more to the point, such RS-based analyses can help us understand potential climate change threats to ongoing efforts to achieve SDGs, such as SDG6: Clean Water and Sanitation for All.
For example, in many parts of East Africa, including Uganda, water services development includes options for rainwater harvesting (see Staddon et al, 2018 and Healthy Waters blog, 11/4/2022). Yet, many climatic factors, such as air temperature, affect household water generation potential from rainwater harvesting as higher temperatures increase water loss from evaporation. If we compare historical air temperature averages (1970-2000) in Uganda with those projected for 2070 (Figure 1), it is clear that without significant change, water loss due to increased evaporation could undermine water harvesting efforts.
To prevent a global crisis, most governments are committed to keeping the average temperature increase at less than a 1.5°C, yet the projections for Uganda indicate temperatures are consistently expected to increase well above this target (Figure 2). This indicates that country-wide water action is urgently needed.
In regions where the temperature increase is projected to be 5°C or more, this could result in significant evaporation loss (approximately equivalent to the volume of an Olympic-sized swimming pool per year). Efforts should be focused on collaborating with local communities to combat potential increases in climate change related water stress, especially in Uganda’s Eastern Region, which is expected to see the highest average temperature increase by 2070 (Figure 2).
A limitation of some modelled environmental datasets is their coarse spatial resolution (e.g. each pixel in Figure 2 is 50km by 50km). This is therefore not high enough resolution to allow for local projections that could inform water planning. To further explore how possible climate change scenarios will affect local environmental conditions, UWE Bristol staff and intern students have collaborated with the University of Rouen Normandy. This collaboration has allowed the for the creation of numerical models to simulate local weather conditions to better investigate African water issues, that help to provide real-life solutions for problems such as rain harvesting. If such numerical models successfully simulate the regional climate conditions, the team hopes to conduct water trials with local communities to generate safe and healthy waters.