Developing a sustainability science approach for water systems

Abstract

We convened a workshop to enable scientists who study water systems from both social science and physical science perspectives to develop a shared language. This shared language is necessary to bridge a divide between these disciplines' different conceptual frameworks. As a result of this workshop, we argue that we should view socio-hydrological systems as structurally coconstituted of social, engineered, and natural elements and study the "characteristic management challenges" that emerge from this structure and reoccur across time, space, and socioeconomic contexts. This approach is in contrast to theories that view these systems as separately conceptualized natural and social domains connected by bi-directional feedbacks, as is prevalent in much of the water systems research arising from the physical sciences. A focus on emergent characteristic management challenges encourages us to go beyond searching for evidence of feedbacks and instead ask questions such as: What types of innovations have successfully been used to address these challenges? What structural components of the system affect its resilience to hydrological events and through what mechanisms? Are there differences between successful and unsuccessful strategies to solve one of the characteristic management challenges? If so, how are these differences affected by institutional structure and ecological and economic contexts? To answer these questions, social processes must now take center stage in the study and practice of water management. We also argue that water systems are an important class of coupled systems with relevance for sustainability science because they are particularly amenable to the kinds of systematic comparisons that allow knowledge to accumulate. Indeed, the characteristic management challenges we identify are few in number and recur over most of human history and in most geographical locations. This recurrence should allow us to accumulate knowledge to answer the above questions by studying the long historical record of institutional innovations to manage water systems.

Toward Urban Water Security: Broadening the Use of Machine Learning Methods for Mitigating Urban Water Hazards

“…Nevertheless, understanding the development of sustainable urban water management planning, we can draw lessons from history and devise sensible approaches for the future that include ML. If we view hydrological systems as "structurally co-constituted of natural, engineered, and social elements, " (Brelsford et al, 2020), we may more readily employ ML to integrate disparate data and discover new perspectives on management practices based on the new patterns these methods reveal. In the near future, We also envision an increase in the applications of the hybrid modeling approaches (i.e., theory-guided ML) (Mekonnen et al, 2012;Karpatne et al, 2017;Frame, 2019) in the urban water management sector through the integration of data-driven ML methods and conventional process-based domain models.…”

Water management, hydrological extremes, and society: modeling interactions and phenomena

“…This leads to an incomplete understanding of past hydrological risk changes, as well as unrealistic projections of future scenarios (Di Baldassarre et al 2015, Schlüter et al 2019). To fill this gap, numerous scholars have developed sociohydrological models exploring human-water interactions over the past few years (see, e.g., reviews by Blair and Buytaert 2016, Pande and Sivapalan 2017, Lu et al 2018, Hall 2019, Brelsford et al 2020. Kates et al 2006, Montz and Tobin 2008, Ludy and Kondolf 2012, flood adaptation (Penning-Rowsell 1996, Wind et al 1999, IPCC 2012, Mechler and Bouwer 2014, Kreibich et al 2017, Wens et al 2019, supply-demand cycle (Kallis 2010, Dumont et al 2013, reservoir effect (Gohari et al 2013, van Dijk et al 2013, sequence effect, i.e., flood after drought ( Van den Honert and McAneney 2011, Bohensky et al 2014, Mateo et al 2014.…”

The controversial debate on the role of water reservoirs in reducing water scarcity

“…They present water cycles mainly in the form of causal‐loop diagrams (Di Baldassarre et al, 2018; Gohari et al, 2013; Kuil, Carr, Viglione, Prskawetz, & Blöschl, 2016) or conceptual frameworks (Di Baldassarre et al, 2013; Di Baldassarre et al, 2015; Di Baldassarre, Kooy, Kemerink, & Brandimarte, 2013), which are very illustrative and easily comprehensible, but running the risk to oversimplify complex interconnections (Gober & Wheater, 2015; Loucks, 2015; Yu, Sangwan, Sung, Chen, & Merwade, 2017). These studies do not integrate institutions and collective decision‐making and use a limited view on human action in the form of fairly deterministic rules for the dynamics of variables at the population level or for behavior at the individual level (Brelsford et al, 2020). Social science literature, in contrast, tends to focus on case studies without integrating systematically hydrological outcomes.…”

“…Major steps were achieved in incorporating human factors in the analyses (e.g., Davies & Simonovic, 2011; Di Baldassarre et al, 2015). However, they conceptualize social and natural domains separately and couple models using bidirectional feedbacks between the social and physical components (Brelsford et al, 2020). They present water cycles mainly in the form of causal‐loop diagrams (Di Baldassarre et al, 2018; Gohari et al, 2013; Kuil, Carr, Viglione, Prskawetz, & Blöschl, 2016) or conceptual frameworks (Di Baldassarre et al, 2013; Di Baldassarre et al, 2015; Di Baldassarre, Kooy, Kemerink, & Brandimarte, 2013), which are very illustrative and easily comprehensible, but running the risk to oversimplify complex interconnections (Gober & Wheater, 2015; Loucks, 2015; Yu, Sangwan, Sung, Chen, & Merwade, 2017).…”

“…Such reservoirs have the potential to mitigate projected changes in seasonal water availability from melting glaciers by managing runoff. Against this background, the understanding of interactions and feedbacks between engineered (e.g., infrastructures like reservoirs), social (e.g., institutions, governance processes), and natural (water and associated natural resources) elements becomes increasingly important (Brelsford et al, 2020).…”