Dynamic Bayesian Networks as a Decision Support tool for assessing Climate Change impacts on highly stressed groundwater systems

Molina, José-Luis; Pulido-Velázquez, David; Aróstegui, J.L. García; Pulido-Velázquez, Manuel

doi:10.1016/j.jhydrol.2012.11.038

Cited by 86 publications

(60 citation statements)

References 27 publications

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“…Nowadays, many of those concepts and methodologies are valid benchmarks in stochastic amount of data from dynamic and nonlinear systems, so they are useful for identifying physical relationships which are not completely understood [36]; and finally, it is relatively simple to define the relationship in sophisticated systems [37].…”

Section: Introductionmentioning

confidence: 99%

“…BNs have been frequently and successfully applied to environmental studies [37][38][39], and to deal with problems within the water resources management field [40][41][42][43][44].…”

Section: Introductionmentioning

confidence: 99%

“…BNs permit the computation of probability distributions over subsets of their variables' conditional. Mathematical fundamentals and formal aspects in Bayes's theorem are discussed in detail in [37,51].…”

Section: Introductionmentioning

confidence: 99%

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Innovative Analysis of Runoff Temporal Behavior through Bayesian Networks

Molina

Zazo

Rodríguez‐Gonzálvez

et al. 2016

Water

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Hydrological series are largely characterized by a strong random component in their behavior. More noticeable changes in the behavior patterns of rainfall/runoff temporal series are recently being observed. These modifications are not a trivial issue, especially in regards to peculiarities, non-linearities, diffused influences or higher time orders of dependence. This study mainly aimed to analyze the temporal dependence of an annual runoff series dynamically. This approach comprises a coupling between classic techniques (Autoregressive Moving Average Model, ARMA) and novel ones, based on Artificial Intelligent for hydrological research (Bayesian Networks, BNs). An ARMA model was built to provide reliable data to populate BNs. Then, causal reasoning, through Bayes's theorem, allows the identification of the logic structure of temporal dependences within time series. Furthermore, the resultant conditional probability permits the quantification of the relative percentage of annual runoff change, and provides the right time order of dependence. This research introduces an original methodology able to build a logic structure for a stochastic analysis of temporal behavior. This approach also aimed to provide a powerful and graphic modeling method for improving the understanding of the dynamic runoff series temporal behavior. This was successfully demonstrated in two unregulated river basin stretches, belonging to the Duero river basin which is the largest basin in Spain.

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Section: Introductionmentioning

confidence: 99%

“…BNs have been frequently and successfully applied to environmental studies [37][38][39], and to deal with problems within the water resources management field [40][41][42][43][44].…”

Section: Introductionmentioning

confidence: 99%

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Innovative Analysis of Runoff Temporal Behavior through Bayesian Networks

Molina

Zazo

Rodríguez‐Gonzálvez

et al. 2016

Water

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“…Other future scenarios could also be analyzed taking into account the influence of climate change on the aquifer recharge Molina et al, 2013;Colombani et al, 2016),…”

Section: Limitationsmentioning

confidence: 99%

A Methodology to Analyse and Assess Pumping Management Strategies in Coastal Aquifers to Avoid Degradation Due to Seawater Intrusion Problems

Renau‐Pruñonosa

Morell

Pulido-Velázquez

2016

Water Resour Manage

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In this paper we will focus on an interesting and complex problem, the analysis of coastal aquifer management alternatives in aquifers affected by seawater intrusion problems. A systhematic method based on an approximation of the safe yield concept for coastal aquifers and a simple model approach to the problem is proposed to help in the decision The methodology was applied to a well-known Spanish Mediterranean aquifer, the Oropesa-Torreblanca Plain aquifer. The optimization problem was solved using an iterative process from a constant density flow simulation model of the aquifer, assuming a direct relationship between piezometric drawdown and seawater intrusion.

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“…Decision Support Systems (DSS) for groundwater applications have been the focus of several studies assessing aquifers vulnerability to potential or effective contaminations [6][7][8] and the sustainability of actual or planned water extractions [9][10][11][12], taking into account also economic constraints [13,14] and climate change scenarios [15]. The present work focuses on the effects of some stress conditions for the aquifer on three assessment criteria: the commonly used depth to water (DTW) and recharge/discharge criteria, supplemented by a newly introduced sustainability parameter (S).…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Estimation and Evaluation of Shallow Aquifers’ Exploitability: The Case Study of the Adige Valley Aquifer (Italy)

Castagna¹,

Bellin

Chiogna

2015

Water

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Evaluating the sustainability of water uses in shallow aquifers is fundamental for both environmental and socio-economic reasons. Groundwater models are the main tools to sustain informed management plans, yet simulation results are affected by both epistemic and parametric uncertainties. In this study, we aim at investigating the effect of model uncertainties on three assessment criteria: depth to water (DTW), recharge/discharge analysis and a newly defined sustainability index S. We consider, as a case study, the shallow aquifer of the Adige Valley, which is highly influenced by surface water dynamics, water withdrawals from pumping wells and a dense network of ditches. Both direct measurements and soft data are used to reduce uncertainty associated to the limited knowledge about the spatial distribution of the hydraulic parameters. Simulation results showed that the aquifer is chiefly influenced by the interaction with the Adige River and that the influence of anthropogenic activities on vulnerability of groundwater resources varies within the study area. This calls for differentiated approaches to water resources management. Uncertainty related to the three assessment criteria is chiefly controlled by uncertainty of the hydrogeological model, although it depends also on the strategy adopted for the management of water resources. OPEN ACCESSWater 2015, 7 3368

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Dynamic Bayesian Networks as a Decision Support tool for assessing Climate Change impacts on highly stressed groundwater systems

Abstract: 17Bayesian Networks (BNs) are powerful tools for assessing and predicting consequences of water 38

Cited by 86 publications

References 27 publications

Innovative Analysis of Runoff Temporal Behavior through Bayesian Networks

Innovative Analysis of Runoff Temporal Behavior through Bayesian Networks

A Methodology to Analyse and Assess Pumping Management Strategies in Coastal Aquifers to Avoid Degradation Due to Seawater Intrusion Problems

Uncertainty Estimation and Evaluation of Shallow Aquifers’ Exploitability: The Case Study of the Adige Valley Aquifer (Italy)

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