The future of water resources systems analysis: Toward a scientific framework for sustainable water management

Abstract

This paper presents a short history of water resources systems analysis from its beginnings in the Harvard Water Program, through its continuing evolution toward a general field of water resources systems science. Current systems analysis practice is widespread and addresses the most challenging water issues of our times, including water scarcity and drought, climate change, providing water for food and energy production, decision making amid competing objectives, and bringing economic incentives to bear on water use. The emergence of public recognition and concern for the state of water resources provides an opportune moment for the field to reorient to meet the complex, interdependent, interdisciplinary, and global nature of today's water challenges. At present, water resources systems analysis is limited by low scientific and academic visibility relative to its influence in practice and bridled by localized findings that are difficult to generalize. The evident success of water resource systems analysis in practice (which is set out in this paper) needs in future to be strengthened by substantiating the field as the science of water resources that seeks to predict the water resources variables and outcomes that are important to governments, industries, and the public the world over. Doing so promotes the scientific credibility of the field, provides understanding of the state of water resources and furnishes the basis for predicting the impacts of our water choices.

Planning for climate change impacts on hydropower in the Far North

“…Flexible and adaptable operations rules. One of the most consistent messages in the literature related to climate change and hydropower is that operations need to adapt their rules if they want to manage for optimal productivity (Gaudard et al, 2013;Vicuna et al, 2011;Madani, 2010;Minville et al, 2009Minville et al, , 2010aRaje and Mujumdar, 2010;Alfieri et al, 2006;Burn and Simonovic, 1996). For example, operational rules should allow for management changes to facilities utilizing glacially fed basins, once the glaciers have significantly receded and glacial melt has declined.…”

“…Several suggestions that have emerged in the literature include adaptive licensing, shorter-term licenses, and more integrative licenses across basins. Explicit adaptive licensing could include specific operational responses to thresholds (Rheinheimer et al, 2013) or more frequent assessment of performance (ICOLD, 2013;Brekke et al, 2009;Madani, 2011). Brekke et al (2009) and these other studies reiterate that we can no longer assume a stationary hydrological future and licensing structures need to reflect this.…”

“…Basin-level studies have also revealed shifts in flow timing and hydropower production (Finger et al, 2012). Hydropower modeling can provide specific information, at the plant level, to assess changing potential due to climate change (Chernet et al, 2013), and tailor management in order to maintain efficient production (Burn and Simonovic, 1996). Plant-level modeling can also integrate electricity market information in order to understand the economic impact of climate change on both the supply and demand for power (Gaudard et al, 2013).…”

“…For both precipitation and temperature, there is some debate whether non-stationarity (change in the long-term mean) persists over the period of instrumental record (Rhines and Huybers, 2013;Hansen et al, 2012) and this has obvious implications for reservoir construction and management (Brekke et al, 2009). However, changes in climate variability, including location, timing, magnitude, and extreme events also have implications for reservoir construction (i.e., design capacity) and management (i.e., timing of generation, flood control, and water spilling).…”

Long-term ensemble forecast of snowmelt inflow into the Cheboksary reservoir under the differently constructed weather scenarios

“…Utilizing the ensemble methodology allows forecaster to provide user not only the most likely value of the forecasted variable, but also yield a range of possible values, account for the forecast uncertainty and dispel, thereby, the "illusion of certainty in a user's mind" (Krzysztofowicz, 2001, p.3). Recent studies illustrating ability of the ensemble, hydrological model-based forecasts to increase the decision making efficiency of reservoir management and operations, including snow dominated basins, are presented, for instance, by Graham and Georgakakos (2010), Georgakakos et al (2012), Zhao and Zhao (2014), Brown et al, (2015), Anghileri et al (2016).…”