1,720,980 research outputs found
Modeling the behavior of water reservoir operators via eigenbehavior analysis
No full textThe large number of dammed rivers worldwide emphasizes the need to couple models of natural processes with models describing human behaviors. However, such behavioral models are often simplistic and lack proper validation against observational data. In this work, we contribute a new approach to infer the typical operations of water reservoirs from historical observations, using data-driven behavioral modeling based on eigenbehavior analysis. The approach is demonstrated using monthly storage data from 172 reservoirs in California, USA. Results show that the proposed method identifies four typical behavioral profiles, which are strongly linked to key features of the reservoirs. Moreover, we show how the identified models can be used for discovering behavioral profiles, and associated reservoir characteristics, that are vulnerable to drought conditions
Policy tree optimization for threshold-based water resources management over multiple timescales
No full textWater resources systems face irreducible uncertainty in supply and demand, requiring policies to respond to changing conditions on multiple timescales. For both short-term operation and long-term adaptation, thresholds or âdecision triggersâ where a policy links observed indicators to actions, have featured prominently in recent studies. There remains a need for a general method to conceptualize threshold-based policies in an easily interpretable structure, and a corresponding search algorithm to design them. Here we propose a conceptual and computational framework where policies are formulated as binary trees, using a simulation-optimization approach. Folsom Reservoir, California serves as an illustrative case study, where policies define the thresholds triggering flood control and conservation actions. Candidate operating rules are generated across an ensemble of climate scenarios, incorporating indicator variables describing longer-term climate shifts to investigate opportunities for adaptation. Policy tree optimization and corresponding open-source software provide a generalizable, interpretable approach to policy design under uncertainty
Policy tree optimization for adaptive management of water resources systems
No full textWater resources systems must cope with irreducible uncertainty in supply and demand, requiring policy alternatives
capable of adapting to a range of possible future scenarios. Recent studies have developed adaptive policies
based on “signposts” or “tipping points” that suggest the need of updating the policy. However, there remains
a need for a general method to optimize the choice of the signposts to be used and their threshold values. This
work contributes a general framework and computational algorithm to design adaptive policies as a tree structure
(i.e. a hierarchical set of logical rules) using a simulation-optimization approach based on genetic programming.
Given a set of feature variables (e.g., reservoir level, inflow observations, inflow forecasts), the resulting policy
defines both the optimal reservoir operations and the conditions under which such operations should be triggered.
We demonstrate the approach using Folsom Reservoir (California) as a case study, in which operating policies
must balance the risk of both floods and droughts. Numerical results show that the tree-based policies outperform
the ones designed via Dynamic Programming. In addition, they display good adaptive capacity to the changing
climate, successfully adapting the reservoir operations across a large set of uncertain climate scenarios
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
A diagnostic assessment of evolutionary algorithms for multi-objective surface water reservoir control
Full text linkGlobally, the pressures of expanding populations, climate change, and increased energy demands are motivating significant investments in re-operationalizing existing reservoirs or designing operating policies for new ones. These challenges require an understanding of the tradeoffs that emerge across the complex suite of multi-sector demands in river basin systems. This study benchmarks our current capabilities to use Evolutionary Multi-Objective Direct Policy Search (EMODPS), a decision analytic framework in which reservoirs' candidate operating policies are represented using parameterized global approximators (e.g., radial basis functions) then those parameterized functions are optimized using multi-objective evolutionary algorithms to discover the Pareto approximate operating policies. We contribute a comprehensive diagnostic assessment of modern MOEAs' abilities to support EMODPS using the Conowingo reservoir in the Lower Susquehanna River Basin, Pennsylvania, USA. Our diagnostic results highlight that EMODPS can be very challenging for some modern MOEAs and that epsilon dominance, time-continuation, and auto-adaptive search are helpful for attaining high levels of performance. The ε-MOEA, the auto-adaptive Borg MOEA, and ε-NSGAII all yielded superior results for the six-objective Lower Susquehanna benchmarking test case. The top algorithms show low sensitivity to different MOEA parameterization choices and high algorithmic reliability in attaining consistent results for different random MOEA trials. Overall, EMODPS poses a promising method for discovering key reservoir management tradeoffs; however algorithmic choice remains a key concern for problems of increasing complexity
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