scholarly journals Coupled effects of observation and parameter uncertainty on urban groundwater infrastructure decisions

2021 ◽  
Author(s):  
Marina R. L. Mautner ◽  
Laura Foglia ◽  
Jonathan D. Herman
Keyword(s):  
Decision Making ◽  
Parameter Uncertainty ◽  
Urban Areas ◽  
Urban Groundwater ◽  
Model Parameters ◽  
Model Errors ◽  
Aquifer Management ◽  
Environmental Models ◽  
Management Objectives ◽  
Management Alternatives

Abstract. Urban groundwater management requires complex environmental models to represent interactions between hydrogeological processes and infrastructure systems. While the impacts of external uncertainties have been widely studied, there is limited understanding of how decision support is altered by endogenous uncertainties arising from model parameters and observations used for calibration. This study investigates (1) the importance of observation choice and parameter values on aquifer management objectives when controlling for model error, and (2) how the relative performance of management alternatives varies when exposed to endogenous uncertainties, individually and in combination. We use a spatially distributed groundwater model of the Valley of Mexico, where aquifer management alternatives include demand management, targeted infiltration, and wastewater reuse. The effects of uncertainty are evaluated using global sensitivity analysis, performance ranking of alternatives under a range of human-natural parameters, and identification of behavioral parameter sets filtered with an error metric calculated from varying subsets of observations. Results show that the parameters governing hydraulic conductivity and total water use in the basin have the greatest effect on management objectives. Model errors are not necessarily controlled by the same parameters as the objectives needed for decision-making. Additionally, observational and parameter uncertainty each play a larger role in objective variation than the management alternatives themselves. Finally, coupled endogenous uncertainties have amplifying effects on decision-making, leading to larger variations in the ranking of management alternatives than each on their own. This study highlights how the uncertain parameters of a physically-based model and their interactions with uncertain observations can affect water supply planning decisions in densely populated urban areas.

Contaminants of emerging concern in urban Aquifers: are they a pRoblem for groundwater usE? (CARE)

2020 ◽  
Author(s):  
Anna Jurado ◽  
Enric Vázquez-Suñé
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Urban Areas ◽  
Illicit Drugs ◽  
Groundwater Resources ◽  
Urban Groundwater ◽  
Contaminants Of Emerging Concern ◽  
Field Scale ◽  
Groundwater Environment ◽  
Wide Range

<p>This abstract aims to present the project CARE. Often, urban areas must pump water resources to cover various aspects of the growing urban water demand and as a strategic resource at specific times (e.g., droughts). These considerations lead one to wonder whether urban groundwater can be safely used, including its potential use as drinking water because urban aquifers usually contain a wide range of pollutants (e.g., heavy metals, nutrients, pathogens, and organic contaminants). Currently, there is a growing interest for the contaminants of emerging concern (CECs) (i.e., pharmaceuticals, personal care products, illicit drugs, etc.,) because most of them are not included in the watch lists of priority pollutants due to existing regulatory gap. Moreover, even detected at trace levels (ng/L-µg/L), they might pose ecological risk such as interference with the endocrine system of high organisms, microbiological resistance, accumulation in soil, plants and animals and, the effects of CEC mixtures are assumed to have unforeseen consequences on ecosystems.</p><p>Since CECs reach groundwater environment, their attenuation occurs mainly through microbial degradation because adsorption is reversible and only retards the contaminants’ transport. Moreover, although the long residence time of water in aquifers might result in strong attenuation of some CECs, others are persistent in urban groundwater. This requires appropriate understanding of all the processes that control the fate of CECs at field scale but, so far, most research is conducted at the laboratory scale, which misses potential synergetic effects associated with the heterogeneous and complex hydrochemical conditions that are inherent in urban aquifers. Considering the raising demand of secure freshwater and the concurrent increase of CECs use, understanding the factors that most influence their efficient removal in urban aquifers are of paramount importance to assure adequate protection of human health and the environment.</p><p>In this context, the main objectives of CARE are to: (1) identify the most suitable conditions that contribute to the natural bioremediation of selected CECs in urban groundwater at field scale and (2) propose and develop solutions for the sustainable management of urban groundwater resources by means of numerical modelling facilitating the decision making and improving its management. A suitable area for CARE is the pilot zone of Sant Adria del Besòs (Barcelona, Spain) because there is a huge amount of urban groundwater is routinely pumped (6 Hm<sup>3</sup>/y) and discharged into the sewage system. Moreover, our previous investigations have demonstrated the presence of a wide range of CECs in this aquifer reaching concentrations up to 2 µg/L. The main outcome of CARE  will be an integrated method for urban groundwater management using monitoring, measuring and modelling approaches that will support improved decision-making to ensure the long-term availability of water resources to the water authorities. This method can be applied in other urban aquifers.</p>

scholarly journals Joint calibration of a hydrological model and rating curve parameters for simulation of flash flood in urban areas

RBRH ◽  
2019 ◽  
Vol 24 ◽  
Author(s):  
Fernando Neves Lima ◽  
Wilson Fernandes ◽  
Nilo Nascimento
Keyword(s):  
Urban Areas ◽  
Hydrological Model ◽  
Flash Flood ◽  
Point Of View ◽  
Model Parameters ◽  
Model Errors ◽  
Rainfall Runoff ◽  
Rating Curves ◽  
Rainfall Runoff Model ◽  
Available Information

ABSTRACT Calibration process is usually time demanding and as much streamflow information as possible in rainfall-runoff models. Nevertheless, from a practical point of view, the available information is measurement of water level, which is essential to design rating curves. This manuscript proposes a set of joint calibration of hydrological model parameters with a range of rating curves, developed for the main channel of the catchment in a crowded urban area. As an alternative of free calibration, the simulations were carried out based on a list of proficient parameters. Four streamflow gauging stations were analysed and used to subdivide the basin. The hourly lumped rainfall-runoff model GR4H was applied to four critical flash flood events to create a rank of Nash-Sutcliffe efficiency criteria (NSE) applying the best set of parameters. The results indicated that the hydrological model errors were compensated by hydraulics errors and they presented an equifinality in the process.

scholarly journals Towards reduced uncertainty in catchment nitrogen modelling: quantifying the effect of field observation uncertainty on model calibration

2004 ◽  
Vol 8 (4) ◽  
pp. 751-763 ◽  
Author(s):  
K. J. Raat ◽  
J. A. Vrugt ◽  
W. Bouten ◽  
A. Tietema
Keyword(s):  
Measurement Uncertainty ◽  
Parameter Uncertainty ◽  
Monitoring Program ◽  
Field Measurements ◽  
Model Parameters ◽  
Sufficient Information ◽  
Model Errors ◽  
N Transformations ◽  
Model Parameter ◽  
Multi Objective

Abstract. The value of nitrogen (N) field measurements for the calibration of parameters of the INCA nitrogen in catchment model is explored and quantified. A virtual catchment was designed by running INCA with a known set of parameters, and field "measurements" were selected from the model run output. Then, using these measurements and the Shuffled Complex Evolution Metropolis algorithm (SCEM-UA), four of the INCA model parameters describing N transformations in the soil were optimised, while the measurement uncertainty was increased in subsequent steps. Considering measurement uncertainty typical for N field studies, none of the synthesised datasets contained sufficient information to identify the model parameters with a reasonable degree of confidence. Parameter equifinality occurred, leading to considerable uncertainty in model parameter values and in modelled N concentrations and fluxes. Fortunately, combining the datasets in a multi-objective calibration was found to be effective in dealing with these equifinality problems. With the right choice of calibration measurements, multi-objective calibrations resulted in lower parameter uncertainty. The methodology applied in this study, using a virtual catchment free of model errors, is proposed as a useful tool foregoing the application of a N model or the design of a N monitoring program. For an already gauged catchment, a virtual study can provide a point of reference for the minimum uncertainty associated with a model application. When setting up a monitoring program, it can help to decide what and when to measure. Numerical experiments indicate that for a forested, N-saturated catchment, a fortnightly sampling of NO3 and NH4 concentrations in stream water may be the most cost-effective monitoring strategy. Keywords: INCA, nitrogen model, parameter uncertainty, multi-objective calibration, virtual catchment, experimental design

scholarly journals Comparing impacts of parameter and spatial data uncertainty for a grid-based distributed watershed model

2016 ◽  
Vol 18 (6) ◽  
pp. 961-974 ◽  
Author(s):  
Younggu Her ◽  
Conrad Heatwole
Keyword(s):  
Land Cover ◽  
Parameter Uncertainty ◽  
Input Data ◽  
Hydrologic Model ◽  
Data Uncertainty ◽  
Model Parameters ◽  
Model Output ◽  
Model Errors ◽  
Land Cover Data ◽  
The Impact

Parameter uncertainty in hydrologic modeling is commonly evaluated, but assessing the impact of spatial input data uncertainty in spatially descriptive ‘distributed’ models is not common. This study compares the significance of uncertainty in spatial input data and model parameters on the output uncertainty of a distributed hydrology and sediment transport model, HYdrology Simulation using Time-ARea method (HYSTAR). The Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm was used to quantify parameter uncertainty of the model. Errors in elevation and land cover layers were simulated using the Sequential Gaussian/Indicator Simulation (SGS/SIS) techniques and then incorporated into the model to evaluate their impact on the outputs relative to those of the parameter uncertainty. This study demonstrated that parameter uncertainty had a greater impact on model output than did errors in the spatial input data. In addition, errors in elevation data had a greater impact on model output than did errors in land cover data. Thus, for the HYSTAR distributed hydrologic model, accuracy and reliability can be improved more effectively by refining parameters rather than further improving the accuracy of spatial input data and by emphasizing the topographic data over the land cover data.

Updating the soil hydraulic parameters in a 3D subsurface model

2021 ◽  
Author(s):  
Natascha Brandhorst ◽  
Insa Neuweiler
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Parameter Uncertainty ◽  
Unsaturated Flow ◽  
Model Parameters ◽  
Hydraulic Parameters ◽  
Model Errors ◽  
Model Predictions ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

<p>Soil moisture is an important variable for land surface processes. To make good model predictions of soil moisture, the flow processes in the subsurface need to be captured well. Flow in the subsurface strongly depends on the soil hydraulic parameters. Information about model parameters is often not available, at least not for the entire domain of interest. The resulting parameter uncertainty needs to be accounted for in the applied model. Data assimilation can account for parameter and model errors as well as for all other possible sources of uncertainty if observations are available that can be used to condition the model states. Thus, the parameter uncertainty might be reduced and model predictions improved. However, including the parameters increases the size of the state vector and thus the computational burden. Especially for large models, this can be a problem. Furthermore, the updates can produce unphysical parameter combinations which in unsaturated zone models often lead to numerical problems.</p><p>In this work, we test the effect of updating the soil hydraulic parameters along with soil moisture in a 3D subsurface hillslope model. We use the ensemble Kalman filter for data assimilation and synthetic observations of soil moisture. In a similar study using a 1D unsaturated flow model, parameter updates were found to be the best way to handle parameter uncertainty. Updating parameters resulted in improved predictions of soil moisture, although not necessarily in more realistic model parameters. The parameter updates should rather be considered a method of treating parameter uncertainty than a method for parameter identification. In the 1D settings, updating all uncertain parameters led to the best results. Whether this still holds and is feasible for a more complex 3D model is the question addressed in this presentation.</p>

scholarly journals Community Preferences for Urban Systems Transformation in Australia

2021 ◽  
Vol 13 (9) ◽  
pp. 4749
Author(s):  
Milo Costanza-van den Belt ◽  
Tayanah O’Donnell ◽  
Robert Webb ◽  
Eleanor Robson ◽  
Robert Costanza ◽  
...  
Keyword(s):  
Decision Making ◽  
Urban Areas ◽  
Online Survey ◽  
Shared Vision ◽  
Urban Systems ◽  
Urban Structure ◽  
Sustainable Cities ◽  
Community Needs ◽  
National Workshop ◽  
Systems Transformation

Civil society engagement is important for enabling urban systems transformations that meet community needs. The development of Future Earth Australia’s Sustainable Cities and Regions: A 10-Year Strategy for Urban Systems was underpinned by cross-sectoral workshops in 7 Australian urban areas and interviews with key stakeholders to create a shared vision of both current and desired future urban structure and policy. We then created an online survey to gauge broader community feedback on the vision which emerged from these workshops and interviews, to compare their outcomes with the views of community members who could be directly impacted by urban decision-making. The survey consisted of 35 questions, which were shaped by the issues emerging from the workshops and interviews. The sample was self-selected, and the 641 respondents represented a cross-section of individuals interested in sustainable cities. Our survey results supported and expanded on the major conclusions of FEA’s National workshop and interview processes, including the need to develop transparent and responsive decision-making processes, limit waste and pollution and develop effective housing and transport alternatives with mixed-use neighborhoods and adequate green space.

scholarly journals Landscape Evaluation as a Complementary Tool in Environmental Assessment. Study Case in Urban Areas: Salamanca (Spain)

2020 ◽  
Vol 12 (16) ◽  
pp. 6395
Author(s):  
Marco Criado ◽  
Antonio Martínez-Graña ◽  
Fernando Santos-Francés ◽  
Leticia Merchán
Keyword(s):  
Decision Making ◽  
Environmental Assessment ◽  
Urban Areas ◽  
Territorial Planning ◽  
Assessment Study ◽  
Management Measures ◽  
Study Case ◽  
Partial State ◽  
Landscape Units ◽  
Objective Methodology

In recent years, the landscape has become another environmental resource, so it is important to incorporate it into planning actions. However, its broad sense of study has made it difficult to develop methodologies that precisely diagnose the state of the landscape and its management requirements, especially in dynamic spaces like urban areas. In order to develop a method capable of providing information that can be incorporated into environmental assessment and territorial planning tasks so that the needs of the landscape are taken into account in the decision-making stages, an objective methodology is presented based on the study of different parameters (biotic, abiotic and socioeconomic) analyzed in the field and subsequently geoprocessed through Geographic Information Systems according to their influence on the landscape. Through the proposed methodology it is possible to determine the quality, fragility and need of protection of the landscape, as well as to identify the diverse landscape units that form the landscape of a territory. Based on these results, a landscape diagnosis can be drawn up to quantify its overall and partial state, carry out monitoring analyses and make comparisons between different landscape units, so that management measures can be adopted according to the obtained scenarios.

Hierarchical Bayesian Parameter Estimation for Modeling and Analysis of User Affective Influence

2013 ◽  
Author(s):  
Feng Zhou ◽  
Jianxin (Roger) Jiao
Keyword(s):  
Decision Making ◽  
Interior Design ◽  
Computational Models ◽  
Human Perception ◽  
Model Parameters ◽  
Hierarchical Bayesian ◽  
Affective States ◽  
Modeling And Analysis ◽  
Human Decision

Traditional user experience (UX) models are mostly qualitative in terms of its measurement and structure. This paper proposes a quantitative UX model based on cumulative prospect theory. It takes a decision making perspective between two alternative design profiles. However, affective elements are well-known to have influence on human decision making, the prevailing computational models for analyzing and simulating human perception on UX are mainly cognition-based models. In order to incorporate both affective and cognitive factors in the decision making process, we manipulate the parameters involved in the cumulative prospect model to show the affective influence. Specifically, three different affective states are induced to shape the model parameters. A hierarchical Bayesian model with a technique called Markov chain Monte Carlo is used to estimate the parameters. A case study of aircraft cabin interior design is illustrated to show the proposed methodology.

scholarly journals Exploring Factors Influencing Customers Decision Making towards Online Grocery Retail Services in Kolkata

2020 ◽  
pp. 280-283
Keyword(s):  
Decision Making ◽  
Factor Analysis ◽  
Customer Service ◽  
Urban Areas ◽  
Retail Sector ◽  
Analysis Method ◽  
Factors Influencing ◽  
Service Convenience ◽  
Prime Objective ◽  
Retail Services

Online grocery retail services are a new trend in Indian urban cities. The two large players namely Grofersand Big Basket attracting customers. The study is an attempt to understand the changing scenario in grocery retail sector. The prime objective of the study is to explore the factors that are attracting customers to choose e retail for Groceries. The data was collected through questionnaire from 100 respondents. Factor analysis (Principle Component Analysis method) was used to explore the influencing factors. These results have shown that mainly customer service, convenience, loyalty rewards, product vailability and payment options are attracting the customers to choose Grophers and Big Basket. These companies have a huge untapped markets and will easily convert the habits of customers in Urban areas.

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