scholarly journals A Bayesian Decision Model for Optimum Investment and Design of Low-Impact Development in Urban Stormwater Infrastructure and Management

2021 ◽  
Vol 9 ◽  
Author(s):  
Mo Wang ◽  
Yu Zhang ◽  
Dongqing Zhang ◽  
Yingsheng Zheng ◽  
Shiqi Zhou ◽  
...  
Keyword(s):  
Service Life ◽  
Low Impact Development ◽  
Decision Makers ◽  
Risk Averse ◽  
Technological Advancement ◽  
Bayesian Decision ◽  
Urban Stormwater ◽  
Initial Stage ◽  
Porous Pavement ◽  
Stable Performance

Uncertainties concerning low-impact development (LID) practices over its service life are challenges in the adoption of LID. One strategy to deal with uncertainty is to provide an adaptive framework which could be used to support decision-makers in the latter decision on investments and designs dynamically. The authors propose a Bayesian-based decision-making framework and procedure for investing in LID practices as part of an urban stormwater management strategy. In this framework, the investment could be made at various stages of the service life of the LID, and performed with deliberate decision to invest more or suspend the investment, pending the needs and observed performance, resources available, anticipated climate changes, technological advancement, and users’ needs and expectations. Variance learning (VL) and mean-variance learning (MVL) models were included in this decision tool to support handling of uncertainty and adjusting investment plans to maximize the returns while minimizing the undesirable outcomes. The authors found that a risk-neutral investor tends to harbor greater expectations while bearing a higher level of risks than risk-averse investor in the VL model. Constructed wetlands which have a higher prior mean performance are more favorable during the initial stage of LID practices. Risk-averse decision-makers, however, could choose porous pavement with stable performance in the VL model and leverage on potential technological advancement in the MVL model.

scholarly journals Simulating the effects of low impact development approaches on urban flooding: a case study from Tehran, Iran

2019 ◽  
Vol 80 (8) ◽  
pp. 1591-1600 ◽  
Author(s):  
Maryam Movahedinia ◽  
Jamal Mohammad Vali Samani ◽  
Fakhreddin Barakhasi ◽  
Saleh Taghvaeian ◽  
Raffi Stepanian
Keyword(s):  
Urban Areas ◽  
Peak Flow ◽  
Low Impact Development ◽  
Hydraulic Modeling ◽  
Decision Makers ◽  
Urban Flooding ◽  
Urban Stormwater ◽  
Rainfall Events ◽  
Storm Water Management Model

Abstract Low impact development (LID) methods have been shown to be efficient in reducing the peak flow and total volume of urban stormwater, which is a top priority for effective urban stormwater management in many municipalities. However, decision-makers need information on the effects of LIDs and their associated costs before allocating limited resources. In this study, the Storm Water Management Model (SWMM) was used to investigate the effects of five different LID scenarios on urban flooding in a district in Tehran, Iran. The LID scenarios included rain barrel (RB) at two sizes, bio-retention cell (BRC), and combinations of the two structures. The results showed that significant node flooding and overflow volume would occur in the study area under the existing conditions, especially for rainfall events with longer return periods. BRC and combinations of BRC and RBs were the most effective options in reducing flooding, while the smaller-size RB was the cheapest alternative. However, normalized cost, obtained through dividing the total cost by the percent reduction in node flooding and/or overflow volume, was smallest for BRC. The results of this study demonstrate how hydraulic modeling can be combined with economic analysis to identify the most efficient and affordable LID practices for urban areas.

Urban stormwater: the analysis of the failure of the alternative techniques and the management of quality

1995 ◽  
Vol 32 (1) ◽  
pp. 33-39
Author(s):  
E. Alfakih ◽  
S. Barraud ◽  
Y. Azzout ◽  
B. Chocat
Keyword(s):  
Stormwater Management ◽  
Difficult Problem ◽  
Management Approach ◽  
Alternative Technique ◽  
Urban Stormwater ◽  
Urban Stormwater Management ◽  
Porous Pavement ◽  
Alternative Techniques ◽  
Design Construction

The implementation of alternative techniques in urban stormwater management is a difficult problem in terms of choice, design, construction, and operating. We applied a quality management approach to try and have a better understanding of these techniques. The quality of an alternative technique in urban stormwater management is defined; the factors that lead to failures were identified and analysed. In order to reduce these factors, tools were developed, and measures that allow the achievement of the necessary standard of quality are suggested. In this article, all the illustrations refer to the porous pavement technique.

scholarly journals Evaluation of Low Impact Development and Nature-Based Solutions for stormwater management: a fully distributed modelling approach

2019 ◽  
Author(s):  
Yangzi Qiu ◽  
Abdellah Ichiba ◽  
Igor Da Silva Rocha Paz ◽  
Feihu Chen ◽  
Pierre-Antoine Versini ◽  
...  
Keyword(s):  
High Resolution ◽  
Stormwater Management ◽  
Low Impact Development ◽  
Peak Discharge ◽  
Small Scale ◽  
Spatial Distributions ◽  
Land Uses ◽  
Runoff Volume ◽  
Total Runoff ◽  
Porous Pavement

Abstract. Currently, Low Impact Development (LID) and Nature-Based Solutions (NBS) are widely accepted as sustainable approaches for urban stormwater management. However, their complex impacts depend on the urban environmental context as well as the small-scale heterogeneity, which need to be assessed by using the fully distributed hydrological model and high resolution data at small scale. In this paper, a case study (Guyancourt), located in the South-West of Paris, was explored. Three sets of high resolution X-band radar data were applied to investigate the impact of variability of spatial distribution of rainfall. High resolution geographic information has been processed to identify the suitable areas that can be covered by the LID/NBS practices, porous pavement, green roof, and rain garden. These individual practices, as well as the combination of the three, were implemented as scenarios in a fully distributed and physically-based Multi-Hydro model, which takes into consideration the variability of the whole catchment at 10 m scale. The performance of LID/NBS scenarios are analysed with two indicators (total runoff volume and peak discharge reduction), with regards to the hydrological response of the original catchment (baseline scenario). Results are analysed with considering the coupling effect of the variability of spatial distributions of rainfall and land uses. The performance of rain garden scenario is better than scenario of green roof and porous pavement. The most efficient scenario is the combination of the three practices that can reduce total runoff volume up to 51 % and peak discharge up to 53 % in the whole catchment, and the maximum values of the two indictors in three sub-catchments reach to 60 % and 61 % respectively. The results give credence that Multi-Hydro is a promising model for evaluating and quantifying the spatial variability of hydrological responses of LID/NBS practices, because of considering the heterogeneity of spatial distributions of precipitation and land uses. Potentially, it can guide the decision-making process of the design of LID/NBS practices in urban planning.

Strategies for Restoring River Ecosystems: Sources of Variability and Uncertainty in Natural and Managed Systems

2003 ◽  
Keyword(s):  
Social Context ◽  
Problem Solving ◽  
Adaptive Management ◽  
Decision Problem ◽  
Decision Processes ◽  
Decision Makers ◽  
Bayesian Decision ◽  
Watershed Restoration ◽  
The Social ◽  
Social Concerns

<em>Abstract</em>.—Decisions about watershed restoration projects often are complicated by competing interests and goals, gaps in scientific knowledge, and constraints on time and resources. Under these circumstances, there is no best approach to decision making and problem solving. Appropriate decision processes need not always be analytically complex, but instead depend on the characteristics of the external social context, the decision makers, and the decision problem itself. Because social concerns so often prevail in restoration decisions, we begin with a discussion of issues characterizing the social context. Next, in three increasingly broad contexts for watershed restoration, we discuss the application of several methods for facilitating decisions and solving problems involving uncertainty: Bayesian decision analysis, active adaptive management, passive adaptive management, and evolutionary problem solving.

Rainwater Management to Mitigate the Effects of Development on the Urban Hydrologic Cycle

2007 ◽  
Vol 2 (1) ◽  
pp. 37-52 ◽  
Author(s):  
Andrea Bradford ◽  
Chris Denich
Keyword(s):  
Water Quality ◽  
Stormwater Management ◽  
Rainwater Harvesting ◽  
Low Impact Development ◽  
Green Roofs ◽  
Hydrologic Cycle ◽  
Porous Pavement ◽  
Rainwater Management ◽  
Management Approaches ◽  
Stream Erosion

Traditional stormwater management approaches that rely on rapid conveyance and end-of-pipe detention have not adequately mitigated the effects of urbanization on water resources and the aquatic and human communities that rely upon them. Low-impact development techniques that can support a shift to management of the post-development hydrologic cycle and runoff volumes offer better opportunities to prevent stream erosion and protect groundwater recharge, characteristics of the flow regime and water quality. The application and design of four techniques—porous pavement, bioretention cells, green roofs and rainwater harvesting— in the management of the post-development water balance are presented.

Comparing a Machine Learning Predictive Model with Federal Transit Administration (FTA)’s Default Useful Life Benchmark to Predict Replacement Costs for Revenue Vehicles

2020 ◽  
Vol 2674 (2) ◽  
pp. 181-190
Author(s):  
Dilip Mistry ◽  
Jill Hough
Keyword(s):  
Machine Learning ◽  
Service Life ◽  
Predictive Model ◽  
Learning Algorithm ◽  
The State ◽  
Decision Makers ◽  
Machine Learning Algorithm ◽  
Useful Life ◽  
Transit Agencies ◽  
The U.S

A predictive model is developed that uses a machine learning algorithm to predict the service life of transit vehicles and calculates backlog and yearly replacement costs to achieve and maintain transit vehicles in a state of good repair. The model is applied to data from the State of Oklahoma. The vehicle service lives predicted by the machine learning predictive model (MLPM) are compared with the default useful life benchmark (ULB) of the U.S. Federal Transit Administration (FTA). The model shows that the service life predicted by the MLPM provides relatively more realistic predictions of replacement costs of revenue vehicles than the predictions generated using FTA’s default ULB. The MLPM will help Oklahoma’s transit agencies facilitate the state of good repair analysis of their transit vehicles and guide decision makers when investing in rehabilitation and replacement needs. The paper demonstrates that it is advantageous to use a MLPM to predict the service life of revenue vehicles in place of the FTA’s default ULB.

scholarly journals The Risk of Failure: Trial and Error Learning and Long-Run Performance

2019 ◽  
Vol 11 (1) ◽  
pp. 44-78 ◽  
Author(s):  
Steven Callander ◽  
Niko Matouschek
Keyword(s):  
Sufficient Conditions ◽  
Decision Makers ◽  
Risk Averse ◽  
Trial And Error ◽  
Improve Performance ◽  
Risk Of Failure ◽  
Long Run ◽  
Error Learning ◽  
And Performance ◽  
The Impact

Innovation is often the key to sustained progress, yet innovation itself is difficult and highly risky. Success is not guaranteed as breakthroughs are mixed with setbacks and the path of learning is typically far from smooth. How decision makers learn by trial and error and the efficacy of the process are inextricably linked to the incentives of the decision makers themselves and, in particular, to their tolerance for risk. In this paper, we develop a model of trial and error learning with risk averse agents who learn by observing the choices of earlier agents and the outcomes that are realized. We identify sufficient conditions for the existence of optimal actions. We show that behavior within each period varies in risk and performance and that a performance trap develops, such that low performing agents opt to not experiment and thus fail to gain the knowledge necessary to improve performance. We also show that the impact of risk reverberates across periods, leading, on average, to divergence in long-run performance across agents. (JEL D81, D83, O31, O38)

scholarly journals The paradox of being on the glass cliff: why do women accept risky leadership positions?

2018 ◽  
Vol 23 (4) ◽  
pp. 397-426 ◽  
Author(s):  
Maral Darouei ◽  
Helen Pluut
Keyword(s):  
Decision Makers ◽  
Risk Averse ◽  
Job Seekers ◽  
Leadership Positions ◽  
Apparent Paradox ◽  
Content Type ◽  
Working Adults ◽  
Glass Cliff ◽  
Shed Light

PurposeRecent evidence from glass cliff research suggests that women are more willing than men to accept risky leadership positions. The purpose of this paper (based on three studies) is to reveal and resolve the apparent paradox that women are more risk averse than men yet end up in risky leadership positions.Design/methodology/approachIn Study I, risk attitudes of 125 participants were surveyed to understand gender differences in risk taking. In two experimental vignette studies, 119 university students (Study II) and 109 working adults (Study III) were offered a leadership position in either a risky or successful company and asked to rate their willingness to accept the job.FindingsTogether, the results showed that although women are generally more risk averse than men, women who scored low on career self-efficacy were more likely to perceive a risky job as a promotional opportunity and were therefore more willing to accept such a job. These findings shed light on the role of women’s career decision making in the glass cliff phenomenon.Originality/valueGlass cliff research has focused almost exclusively on organizational decision makers. The authors aim to better understand the glass cliff phenomenon by incorporating the perspective of job seekers.

scholarly journals Comparison of Conventional and IPM Cropping Systems: A Risk Efficiency Analysis

2020 ◽  
Vol 52 (3) ◽  
pp. 385-397
Author(s):  
Ming Su Lavik ◽  
Gudbrand Lien ◽  
Audun Korsaeth ◽  
J. Brian Hardaker
Keyword(s):  
Pest Management ◽  
Cropping Systems ◽  
Efficiency Analysis ◽  
Decision Makers ◽  
Risk Averse ◽  
Conventional System ◽  
Using Data ◽  
Initial Results ◽  
Term Field

AbstractTo support decision-makers considering adopting integrated pest management (IPM) cropping in Norway, we used stochastic efficiency analysis to compare the risk efficiency of IPM cropping and conventional cropping, using data from a long-term field experiment in southeastern Norway, along with data on recent prices, costs, and subsidies. Initial results were not definitive, so we applied stochastic efficiency with respect to a function, limiting the assumed risk aversion of farmers to a plausible range. We found that, for farmers who are risk-indifferent to moderately (hardly) risk averse, the conventional system was, compared to IPM, less (equally) preferred.

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