Environmental variables tend to fluctuate randomly and exhibit multiscale structures in space and time. Whereas random fluctuations arise from variations in environmental properties and phenomena, multiscale behavior implies that these properties and phenomena possess hierarchical structures. Understanding and quantifying such random, multiscale behavior is critical for the analysis of fluid flow as well as mass and energy transport in the environment. The multiscale nature of randomly fluctuating variables that characterize a hierarchical environment (or process) tends to be reflected in the way their increments vary in space (or time). Quite often such increments (a) fluctuate randomly in a highly irregular fashion; (b) possess symmetric, non-Gaussian frequency distributions characterized by heavy tails, which sometimes decay with separation distance or lag; (c) exhibit nonlinear power-law scaling of sample structure functions (statistical moments of absolute increments) in a midrange of lags, with breakdown in such scaling at small and large lags; (d) show extended power-law scaling (linear relations between log structure functions of successive orders) at all lags; (e) display nonlinear scaling of power-law exponent with order of sample structure function; and (f) reveal various degrees of anisotropy in these behaviors. Similar statistical scaling is known to characterize many earth, ecological, biological, physical, astrophysical, and financial variables. The literature has traditionally associated statistical scaling behaviors of the aforementioned kind with multifractals. This is so even though multifractal theory (a) focuses solely on statistical scaling of variable increments, unrelated to statistics of the variable itself, and (b) explains neither observed breakdown in power-law scaling at small and large lags nor extended power-law scaling of such increments. A novel Generalized sub-Gaussian scaling model is introduced that does not suffer from such deficiencies, and some of its key aspects are illustrated on microscale surface measurements of a calcite crystal fragment undergoing dissolution reaction due to contact with a fluid solution.
Statistical Scaling of Randomly Fluctuating Hierarchical Variables
Shlomo P. Neuman, Monica Riva, Alberto Guadagnini, Martina Siena, and Chiara Recalcati
Hybrid Modes of Urban Water Delivery in Low- and Middle-Income Countries
Alison Post and Isha Ray
Most urban residents in high-income countries obtain piped and treated water for drinking and domestic use from centralized utility-run water systems. In low- and middle-income countries (LMICs), however, utilities work alongside myriad other service providers that deliver water to hundreds of millions of city-dwellers. Hybrid modes of water delivery in urban areas in low- and middle-income countries are systems in which a variety of state and nonstate actors contribute to the delivery of water to households, schools, healthcare facilities, businesses, and government offices. Historically, the field has evolved to include within-utility networks and outside-the-utility provision mechanisms. Utilities service the urban core through network connections, while nonstate, smaller-scale providers supplement utility services both inside and outside the piped network. The main reform waves since the 1990s—privatization and corporatization—have done little to alter the hybrid nature of provision. Numerous case studies of nonutility water providers suggest that they are imperfect substitutes for utilities. They reach millions of households with no access to piped water, but the water they deliver tends to be of uncertain quality and is typically far more expensive than utility water. Newer work on utility-provided water and utility reforms has highlighted the political challenges of private sector participation in urban water; debates have also focused on the importance of contractual details such as tariff structures and investor incentives. New research has produced numerous studies on LMICs on the ways in which utilities extend their service areas and service types through explicit and implicit relationships with front-line water workers and with supplemental nonstate water suppliers. From the nonutility perspective, debates animated by questions of price and quality, the desirability or possibility of regulation, and the compatibility (or lack thereof) between reliance on small-scale water providers and the human right to safe water, are key areas of research. While understanding the hybrid nature of water delivery is essential for responsible policy formulation and for understanding inequalities in the urban sphere, there is no substitute for the convenience and affordability of universal utility provision, and no question that research on the conditions under which particular types of reforms can improve utility provision is sorely needed.
Use of Experimental Economics in Policy Design and Evaluation: An Application to Water Resources and Other Environmental Domains
Economics conceptualizes harmful effects to the environment as negative externalities that can be internalized through implementation of policies involving regulatory and market-based mechanisms, and behavioral economic interventions. However, effective policy will require knowledge and understanding of intended and unintended stakeholder behaviors and consequences and the context in which the policy will be implemented. This mandate is nontrivial since policies once implemented can be hard to reverse and often have irreversible consequences in the short and/or long run, leading to high social costs. Experimental economics (often in combination with other empirical evaluation methods) can help by testing policies and their impacts prior to modification of current policies, and design and implementation of new ones. Such experimental evaluation can include lab and field experiments, and choice experiments. Additionally, experimental policy evaluation should pay attention to scaling up problems and the ethical ramifications of the treatment. This would ensure that the experimental findings will remain relevant when rolled out to bigger populations (hence retaining policy makers’ interest in the method and evidence generated by it), and the treatment to internalize the externality will not create or exacerbate societal disparities and ethical challenges.
A Century of Evolution of Modeling for River Basin Planning to the Next Generation of Models, Methods, and Concepts
Caroline Rosello, Sondoss Elsawah, Joseph Guillaume, and Anthony Jakeman
River Basin models to inform planning decisions have continued to evolve, largely based on predominant planning paradigms and progress in the sciences and technology. From the Industrial Revolution to the first quarter of the 21st century, such modeling tools have shifted from supporting water resources development to integrated and adaptive water resources management. To account for the increasing complexity and uncertainty associated with the relevant socioecological systems in which planning should be embedded, river basin models have shifted from a supply development focus during the 19th century to include, by thes 2000s–2020s, demand management approaches and all aspects of consumptive and non-consumptive uses, addressing sociocultural and environmental issues. With technological and scientific developments, the modeling has become increasingly quantitative, integrated and interdisciplinary, attempting to capture, more holistically, multiple river basin issues, relevant cross-sectoral policy influences, and disciplinary perspectives. Additionally, in acknowledging the conflicts around ecological degradation and human impacts associated with intensive water resource developments, the modeling has matured to embrace the need for adequate stakeholder engagement processes that support knowledge-sharing and trust-building and facilitate the appreciation of trade-offs across multiple types of impacts and associated uncertainties. River basin models are now evolving to anticipate uncertainty around plausible alternative futures such as climate change and rapid sociotechnical transformations. The associated modeling now embraces the challenge of shifting from predictive to exploratory tools to support learning and reflection and better inform adaptive management and planning. Managing so-called deep uncertainty presents new challenges for river basin modeling associated with imperfect knowledge, integrating sociotechnical scales, regime shifts and human factors, and enabling collaborative modeling, infrastructure support, and management systems.