“The water is murky, the water is not moving”: Qualitative water quality assessment by citizen scientists

Abstract (English)

Without quantitative measurements, people develop their own water quality assessment, often based on memories, habits, everyday uses, and sensorial experiences (Boyer et al., 2019; Morales-Magaña, 2019; West, Nolan and Scott, 2016; Westling et al., 2014). As a result, humans have developed a cultural and historical understanding of water quality. By following the standard quantitative methods for water quality monitoring, the social, cultural, and political realities of water and rivers (and thus the causes of poor water quality conditions) are not represented but rather simplified or overlooked altogether (Molle, Lankford and Lave, 2024). While for many analyses it is important to obtain traditional physical-chemical or biological measurements (e.g., to determine the presence of harmful substances due to pollution by industry, mining, or agriculture and presence), the understanding of water quality is a cultural and political process as well. Therefore, qualitative data can deepen the understanding of the causes of poor water quality, and provide information on subjective and sensorial experiences that are key drivers of how people make decisions and relate to water (Strang, 2004; Barnett, Jackson-Smith and Haeffner, 2018; Quandt, 2022). Recent discussions in hydrology have acknowledged that water research and monitoring have social, cultural, and political implications, requiring epistemological and methodological interdisciplinarity (Krueger et al., 2016). Building on these discussions, we analyze the potential of less explored qualitative water quality data. We investigate what water quality indicators citizen scientists are most interested in and what key water quality indicators influence the assessment and perspectives of a river’s water quality. This study evaluates qualitative water quality descriptors collected through the citizen science smartphone app CrowdWater and analyses how citizen scientists perceive and assess water quality in the app. The analysis does not only indicate that some citizen scientists already take quantitative physical-chemical measurements of water quality (even though this is not part of the app) but also that they frequently report their perception of water quality based on visual indicators and local (i.e., place-based) knowledge. After the analysis of the data, we draw upon literature in critical water geographies and political ecology, to reflect on the relevance of qualitative data (e.g. local knowledge) within hydrological studies, particularly citizen science for water quality monitoring, as a venue to explore the complexity of water-human relations.