scholarly journals Role of measurement uncertainty in the comparison of average areal rainfall methods

Metrologia ◽  
2021 ◽  
Author(s):  
Alvaro Ribeiro ◽  
Maria Céu Almeida ◽  
Maurice G Cox ◽  
Joao Alves Sousa ◽  
Luis Lages Martins ◽  
...  
Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1787
Author(s):  
Leena J. Shevade ◽  
Franco A. Montalto

Green infrastructure (GI) is viewed as a sustainable approach to stormwater management that is being rapidly implemented, outpacing the ability of researchers to compare the effectiveness of alternate design configurations. This paper investigated inflow data collected at four GI inlets. The performance of these four GI inlets, all of which were engineered with the same inlet lengths and shapes, was evaluated through field monitoring. A forensic interpretation of the observed inlet performance was conducted using conclusions regarding the role of inlet clogging and inflow rate as described in the previously published work. The mean inlet efficiency (meanPE), which represents the percentage of tributary area runoff that enters the inlet was 65% for the Nashville inlet, while at Happyland the NW inlet averaged 30%, the SW inlet 25%, and the SE inlet 10%, considering all recorded events during the monitoring periods. The analysis suggests that inlet clogging was the main reason for lower inlet efficiency at the SW and NW inlets, while for the SE inlet, performance was compromised by a reverse cross slope of the street. Spatial variability of rainfall, measurement uncertainty, uncertain tributary catchment area, and inlet depression characteristics are also correlated with inlet PE. The research suggests that placement of monitoring sensors should consider low flow conditions and a strategy to measure them. Additional research on the role of various maintenance protocols in inlet hydraulics is recommended.


2004 ◽  
Vol 9 (6) ◽  
pp. 384-384
Author(s):  
H�kan K�llgren ◽  
Margreet Lauwaars ◽  
Bertil Magnusson ◽  
Leslie Pendrill ◽  
Phillip Taylor

2019 ◽  
Vol 116 (32) ◽  
pp. 15985-15990 ◽  
Author(s):  
Milad Memarzadeh ◽  
Gregory L. Britten ◽  
Boris Worm ◽  
Carl Boettiger

Current and future prospects for successfully rebuilding global fisheries remain debated due to uncertain stock status, variable management success, and disruptive environmental change. While scientists routinely account for some of this uncertainty in population models, the mechanisms by which this translates into decision-making and policy are problematic and can lead to unintentional overexploitation. Here, we explicitly track the role of measurement uncertainty and environmental variation in the decision-making process for setting catch quotas. Analyzing 109 well-sampled stocks from all oceans, we show that current practices may attain 55% recovery on average, while richer decision methods borrowed from robotics yield 85% recovery of global stocks by midcentury, higher economic returns, and greater robustness to environmental surprises. These results challenge the consensus that global fisheries can be rebuilt by existing approaches alone, while also underscoring that rebuilding stocks may still be achieved by improved decision-making tools that optimally manage this uncertainty.


Author(s):  
Dylan F. Williams ◽  
Richard A. Chamberlin ◽  
Wei Zhao ◽  
Jerome Cheron ◽  
Miguel E. Urteaga

2017 ◽  
Vol 131 ◽  
pp. 79-91 ◽  
Author(s):  
Luciano Molognoni ◽  
Leandro Antunes de Sá Ploêncio ◽  
Antonio Marcelo Lemos Machado ◽  
Heitor Daguer

2011 ◽  
Vol 208 (1-3) ◽  
pp. 108-123 ◽  
Author(s):  
Luca Zamengo ◽  
Giampietro Frison ◽  
Maria Gregio ◽  
Giorgio Orrù ◽  
Rocco Sciarrone

2016 ◽  
Author(s):  
Milad Memarzadeh ◽  
Carl Boettiger

AbstractOver the past 30 years, researchers have used various approximations to address the impact of measurement uncertainty on optimal management policy.This literature has consistently suggested the counter-intuitive proposition that increasing harvest levels in the presence of measurement error is often optimal. Here, we use state-of-the art algorithms for Partially Observed Markov Decision Processes (POMDPs) to provide the first complete solution to this classic problem, and demonstrate that contrary to previous work, the resulting policy is usually more conservative than without measurement error. We demonstrate that management which underestimates the measurement error results in both low economic returns and high frequency of stock collapses, while overestimating the role of measurement error can still result in nearly-optimal economic performance while avoiding stock collapse.


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