Tales from the field: when environmental sensors help and hinder science

Stories from Burkina Faso & High Elevation Switzerland

Presentation by Dr. Natalie Ceperley & Anthony Michelon
University of Lausanne, Institute of Earth Surface Dynamics

The quality of weather predictions, climate change assessments, and natural resource management depends on the quality of hydrological and meteorological data. Systematic biases in the location of measurement stations, for example in wealthy countries or in places that are road accessible, will result in systematic errors in scientists’ ability to provide these crucial services to society. Two of the largest gaps in current global monitoring are: (1) high elevation sites and (2) the African continent, specifically anywhere outside of airports, in most sub-Saharan countries besides Benin and South Africa, and in rural areas. These two gaps have particularly high stakes for society. First, high elevation sites are often considered “the water towers of the world” since most of the world’s rivers and streams are generated in the mountains and represent meteorological irregularities that would be hard to predict even with the best data. Second, people living in rural sub-Saharan Africa are the some of the most vulnerable to climate change, given the high environmental dependence of rain-fed subsistence farming and lack of social services, and the gap in hydro-meteorological data and correspondingly in predictions renders these populations even more sensitive to disease, floods, famine, and droughts. In this presentation, we will explore two sites that have been instrumented for hydro-meteorological research. We will present the nuts and bolts of our current and past monitoring networks including wireless sensors, eddy-covariance, dendrology, and corresponding sampling for stable isotopes in water. We will discuss the basic challenges to get power, collect data, and access remote areas and our solutions. We will highlight our failures and inspire you with our dreams of an ideal monitoring network.