Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene

Globally, many different kinds of water resources management issues call for policyand infrastructure-based responses. Yet responsible decision-making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadalto century-long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems. These models must be constrained to yield useful insights, despite the many likely sources of uncertainty in their predictions. Chief among these uncertainties are the impacts of the increasing role of human intervention in the global water cycle – a defining challenge for hydrology in the Anthropocene. Here we present a research agenda that proposes a suite of strategies to address these challenges from the perspectives of hydrologic science research. The research agenda focuses on the development of co-evolutionary hydrologic modeling to explore coupling across systems, and to address the implications of this coupling on the long-time behavior of the coupled systems. Three research directions support the development of these models: hydrologic reconstruction, comparative hydrology and model-data learning. These strategies focus on understanding hydrologic processes and feedbacks over long timescales, across many locations, and through strategic coupling of observational and model data in specific systems. We highlight the value of use-inspired and team-based science that is motivated by real-world hydrologic problems but targets improvements in fundamental understanding to support decision-making and management. Fully realizing the potential of this approach will ultimately require detailed integration of social science and physical science understanding of water systems, and is a priority for the developing field of sociohydrology. 1 Predictions under change The effect of human activities on the water cycle is deepening and widening rapidly across the planet, driven by increased demands for energy (King and Webber, 2008; Koutsoyiannis et al., 2009), water (Jackson et al., 2001), food (Vörösmarty et al., 2001) and living space (Zhao et al., 2001), and the unintended consequences and secondary effects of land use and Published by Copernicus Publications on behalf of the European Geosciences Union. 5014 S. E. Thompson et al.: Use-inspired hydrologic science for the Anthropocene climate change. Cumulatively, these demands result in increased human appropriation of water resources, significant modification of landscapes, and a strong human imprint on water cycle dynamics from local to global scales (Carpenter et al., 2011; Falkenmark and Lannerstad, 2005; Röckstrom et al., 2009; Vörösmarty et al., 2010). The combination of these effects mean that the world faces a sharp decline in water security (Gleick and Palaniappan, 2010; Postel and Wolf, 2001), which is likely to be most severe in the least resilient of nations (Milly et al., 2002, 2008; Sheffield and Wood, 2008). The increasing human impacts on the water cycle demand effective management, such as the development of infrastructure, policy and law to respond to contemporary problems and create frameworks for future management. Management actions taken today – whether infrastructureor policyrelated – will have long legacies (Swyngedouw, 2009). The lifetimes of artificial reservoirs, for instance, are on the order of 10s to 100s of years (Einsele and Hinderer, 1997). Similarly, the laws governing water rights in the western United States have had decadalto century-scale effects (∼ 200 yr for the Prior Appropriation Act, ∼ 90 yr for the Law of the River), where incorrect assumptions about flow continue to constrain water management (Garner and Ouellette, 1995; Hundley, 2009; Tarlock, 2002). Thus, the legacies of historical water resource management decisions contribute to contemporary water management problems (Srinivasan et al., 2012). It is likely that humankind will be constrained by water resource availability for the foreseeable future. Contemporary water resources management decisions should therefore attempt to account for their impacts on time horizons commensurate with those of their legacies. These time horizons encompass a period in which we anticipate dramatic changes in climate, population, land uses, and energy and food demand (Huang et al., 2011). Indeed, the human-driven changes in water, nutrient, energy cycles, and landscape evolution may now overwhelm natural variability, leading to the contemporary geologic era being labeled the Anthropocene – the human era (Crutzen and Stoemer, 2000; Poff et al., 2013; Röckstrom et al., 2009; Vitousek et al., 1997; Vörösmarty et al., 2010; Zalasiewicz et al., 2010). To make good decisions about water management today requires a drastic improvement in our ability to predict the dynamics of water resources on long timescales, in the presence of rapid change in multiple elements of the water system, and subject to the direct and indirect influence of human activity (Milly et al., 2008; Wagener et al., 2010). To continue to make good water management decisions as projected changes impact water systems behavior also requires detecting and attributing emergent changes (Maurer et al., 2007), making predictions about their effects on hydrology, and altering management decisions accordingly. The complexity of these issues means that we have taken a broad view of the term “prediction”. At one extreme, we recognize that traditional, deterministic forecasts are likely to be impossible for complex systems containing human agents, particularly on long timescales. At the other extreme, we disagree with the assertion that deep uncertainty would render improved understanding, modeling and predictive assessments meaningless. Instead, we suggest a middle path that asserts that the combination of specific initial and boundary conditions and process interactions among physical, socio-cultural and ecological domains, will constrain the possible future trajectories of water systems, rendering some outcomes more (or less) likely. Identification of the critical initial and boundary conditions and interacting processes is a non-trivial task that itself requires a significant research focus (see Sect. 3). Assuming the problem can be suitably defined, and depending on the timescale of the prediction, which affects the development of uncertainty, such constraints may provide a basis for visualization, understanding and intervention, and for the formulation of a constrained range of potential future scenarios for analysis. Indeed, the lead-time of the prediction is the fundamental driver of the interactions between model structure, prediction goals and increase of uncertainty. We refer to these modest goals as the development of predictive insights, which include predictions of a phenomenological or qualitative nature (Kumar, 2011). The hydrological prediction frameworks that are widely applied for managing water resources today derive from a reductionist paradigm that attempts to upscale microscopic process knowledge to large spatial and temporal scales (Wagener et al., 2010), and may not be well aligned towards developing predictive insight into complex systems. Several commentators have already called for new ways to do water science that are based on exploration of patterns, macroscopic or “top-down” hydrologic prediction and comparative approaches (Blöschl, 2006; McDonnell et al., 2007; Sivapalan et al., 2003), with the intention that such techniques could support hydrologic predictions in the Anthropocene (Killeen and Abrajano, 2008; Wagener et al., 2010; Reed and Kasprzyk, 2009). Such a research approach, however, raises pragmatic questions. For instance, the respective roles of single-investigator research approaches versus community-wide “big science” endeavors in this arena must be better defined, since team science approaches may be better suited to synthesis research (Blöschl, 2006; Torgersen, 2006). Use-inspired hydrologic science must also be careful to avoid devaluing “pure science” approaches to hydrology (Dunne et al., 1998). Thus, developing predictive insight to support water management in the Anthropocene not only poses fundamental scientific challenges, but also non-trivial practical challenges for the water science community. As a response to these issues, we convened a series of workshops for the hydrologic community in 2009–2010 to discuss the grand challenge of making hydrological predictions in the Anthropocene (Sivapalan, 2011). This article represents a distillation of the ideas generated from this large, grassroots effort. Here we firstly identify core impediments to hydrologic prediction in the Anthropocene and argue that Hydrol. Earth Syst. Sci., 17, 5013–5039, 2013 www.hydrol-earth-syst-sci.net/17/5013/2013/ S. E. Thompson et al.: Use-inspired hydrologic science for the Anthropocene 5015 there are tangible research methods available to the hydrologic research community that can begin to address these problems. Secondly, we propose that a “use-inspired” approach towards the planning and execution of this research (Stokes, 1997) provides a way to simultaneously advance fundamental knowledge and its applicability to water resources management, and thus navigating some of the tensions that arise between doing science to expand fundamental knowledge, and doing science to improve human and environmental well-being. The agenda outlined here aspires to improve the capacity of hydrologic researchers to meet the prediction needs posed by water resources management challenges. It is focused, however, on addressing gaps that can be identified within the current portfolio of physical hydrologic science, its theory, tools, methods and capabilities. It does not attempt to address improved and integrated approaches for water resources management or the science–policy interface. Numerous authors have highlighted the importance of water resources management that accounts for socio-cultural contexts, needs and equity (Gual and Norgaard, 2010; Lane, 2013; O’Brien, 2013; Pahl-Wostl et al., 2007; Pahl-Wostl and Hare, 2004; Tippett et al., 2005) by recognizing that social and hydrologic systems are in many cases inseparable. How to most effectively communicate and collaborate across science, policy and stakeholder communities to achieve beneficial water resource management outcomes is a critically important question, but one that lies beyond the scope of this scientifically oriented paper. 2 Scientific needs and challenges Several scientific challenges derive directly from the need to develop predictive insight on the decadalto century-scale time frames commensurate with the lifetimes of our water management decisions. As argued above, century-long timescales encompass periods of time over which multiple environmental subsystems are anticipated to change as a direct or indirect result of human activity. These changes mean that the hydrologic system, taken as a whole, is characterized by time-dependent properties that may change rapidly relative to the timescales on which prediction is desired. Following Milly et al. (2008), we will refer to this time-dependence of system properties as “non-stationarity”. Although there is a long literature dealing with non-stationary modeling in hydrology (Clarke, 2007; Cohn and Lins, 2005; Klemes, 1974; Koutsoyiannis, 2006), coping with non-stationarity still generates several specific challenges related to its interpretation and description: (i) firstly, predicting the effects of change in interconnected environmental subsystems on hydrologic behavior. To do this, we must (ii) secondly identify and develop functional descriptions for change, which may imply parameterizing the interactions and feedbacks between interconnected subsystems. Thirdly, (iii) the interaction of multiple interconnected subsystems with many degrees of freedom is likely to amplify uncertainty in our predictions, and techniques to constrain this uncertainty must be developed. Finally, (iv) interconnected environmental subsystems include the special case of human–water interactions. Improving our understanding of these interactions is a particularly difficult and important challenge worthy of special consideration (Leung et al., 2013). 2.1 Challenge 1: non-stationarity Over the next 10–100 yr, most hydrologic systems will be exposed to continuous (albeit uncertain) changes in climatic forcing. Climate change signals are now detectable in some global and regional hydrologic processes (Maurer et al., 2007; Seneviratne et al., 2010). New patterns of rainfall extremes are predicted in many regions of the world (Dominguez et al., 2012; Huntingford et al., 2006). Although their behaviors do not exhibit a consistent global tendency (Sun et al., 2012), such patterns have a direct impact on rainfall statistics, which will no longer reflect their historical distribution. Making predictions on century-long timescales requires propagating these changes into hydrological predictions, carrying out impact studies which involve significant unknowns and uncertainties (Blöschl and Montanari, 2010). Significantly non-linear responses to these climatic changes alone are anticipated (Fig. 1a), making the extrapolation of historical data to future scenarios challenging. Contemporary approaches that perform this extrapolation directly, e.g., historically based frequency analysis approaches (Milly et al., 2008), or indirectly, through calibrating models to historical data (Wagener, 2007), are thus problematic. Climate and land use change directly impact hydrology through changing the forcing and response of hydrologic systems. Moreover, they are also likely to induce further changes in a range of physical, ecological and social processes. Making hydrologic predictions on century-long timescales is therefore not only a matter of developing modeling approaches that are robust to non-stationarity in the forcing variables, but also requires addressing how these changes propagate into the structure and properties of catchments (Sivapalan et al., 2003). For example, climate and land use changes are likely to promote changes in vegetation and ecological communities and their properties (Loarie et al., 2009; Donohue et al., 2013). Vegetation composition in a catchment can change over decadal timescales, (Foley et al., 2000; Rose et al., 1995; Thompson and Katul, 2008). Vegetation composition can also have large impacts on water resources – e.g., 30 % decline in annual runoff and 60 % decline in peak flows following pine invasion of grasslands (Fahey and Jackson, 1997). “Second-order” effects of climate change on hydrology – such as a climate-induced change in vegetation community composition that alters land surface water budget partitioning – can thus occur rapidly compared to the 100 yr prediction horizon. Describing second-order effects requires a predictive framework that extends beyond www.hydrol-earth-syst-sci.net/17/5013/2013/ Hydrol. Earth Syst. Sci., 17, 5013–5039, 2013 5016 S. E. Thompson et al.: Use-inspired hydrologic science for the Anthropocene 1998 200