Applications of Bayesian Networks as Decision Support Tools for Water Resource Management under Climate Change and Socio-Economic Stressors: A Critical Appraisal

Bayesian networks (BNs) are widely implemented as graphical decision support tools which use probability inferences to generate “what if?” and “which is best?” analyses of potential management options for water resource management, under climate change and socio-economic stressors. This paper presents a systematic quantitative literature review of applications of BNs for decision support in water resource management. The review quantifies to what extent different types of data (quantitative and/or qualitative) are used, to what extent optimization-based and/or scenario-based approaches are adopted for decision support, and to what extent different categories of adaptation measures are evaluated. Most reviewed publications applied scenario-based approaches (68%) to evaluate the performance of management measures, whilst relatively few studies (18%) applied optimization-based approaches to optimize management measures. Institutional and social measures (62%) were mostly applied to the management of water-related concerns, followed by technological and engineered measures (47%), and ecosystem-based measures (37%). There was no significant difference in the use of quantitative and/or qualitative data across different decision support approaches (p = 0.54), or in the evaluation of different categories of management measures (p = 0.25). However, there was significant dependence (p = 0.076) between the types of management measure(s) evaluated, and the decision support approaches used for that evaluation. The potential and limitations of BN applications as decision support systems are discussed along with solutions and recommendations, thereby further facilitating the application of this promising decision support tool for future research priorities and challenges surrounding uncertain and complex water resource systems driven by multiple interactions amongst climatic and non-climatic changes. View Full-Tex

PARTICIPATORY MODELLING TO SUPPORT DECISION MAKING IN WATER MANAGEMENT. A CASE STUDY IN THE MIDDLE GUADIANA BASIN, SPAIN.

Resource /Energy Economics and Policy,

Recommendation domains for pond aquaculture

This publication introduces the methods and results of a research project that has developed a set of decision-support tools to identify places and sets of conditions for which a particular target aquaculture technology is considered feasible and therefore good to promote. The tools also identify the nature of constraints to aquaculture development and thereby shed light on appropriate interventions to realize the potential of the target areas. The project results will be useful for policy planners and decision makers in national, regional and local governments and development funding agencies, aquaculture extension workers in regional and local governments, and researchers in aquaculture systems and rural livelihoods. (Document contains 40 pages

Bayesian networks for spatio-temporal integrated catchment assessment

Includes abstract.Includes bibliographical references (leaves 181-203).In this thesis, a methodology for integrated catchment water resources assessment using Bayesian Networks was developed. A custom made software application that combines Bayesian Networks with GIS was used to facilitate data pre-processing and spatial modelling. Dynamic Bayesian Networks were implemented in the software for time-series modelling

Groundwater vulnerability assessment: A review including new statistical and hybrid methods

The concept of groundwater vulnerability was first introduced in the 1970s in France to recognize sensitive areas in which surface pollution could affect groundwater, and to enable others to develop management methods for groundwater protection against surface pollutants. Since this time, numerous methods have been developed for groundwater vulnerability assessment (GVA). These can be categorized into four groups: (i) overlay and index-based methods, (ii) process-based simulation models, (iii) statistical methods, and (iv) hybrid methods. This work provides a comprehensive review of modern GVA methods, which in contrast to previous reviews, examines the last two categories in detail. First, the concept of groundwater vulnerability is defined, then the major GVA methods are introduced and classified. This includes detailed accounts of statistical methods, which can be subdivided into orthodox statistical, data-driven and Bayesian methods, and their advantages and disadvantages, as well as modern hybrid methods. It is concluded that Bayesian inference offers many advantages compared with other GVA methods. It combines theory and data to give the posterior probabilities of different models, which can be continually updated with new data. Furthermore, using the Bayesian approach, it is possible to calculate the probability of a proposition, which is exactly what is needed to make decisions. However, despite the advantages of Bayesian inference, its applications to date have been very limited

Stochastic hydro-economic model for groundwater quality management using Bayesian networks

A strong normative development in Europe, including the Nitrate Directive (1991) and the Water Framework Directive (WFD) (2000), has been promulgated. The WFD states that all water bodies have to reach a good quantitative and chemical status by 2015. It is necessary to consider different objectives, often in conflict, for tackling a suitable assessment of the impacts generated by water policies aimed to reduce nitrate pollution in groundwater. For that, an annual lumped probabilistic model based on Bayesian networks (BNs) has been designed for hydro-economic modelling of groundwater quality control under uncertain conditions. The information introduced in the BN model comes from different sources such as previous groundwater flow and mass transport simulations, hydro-economic models, stakeholders and expert opinion, etc. The methodology was applied to the El Salobral-Los Llanos aquifer unit within the 'Easter Mancha' groundwater body, which is one of the largest aquifers in Spain (7,400 km(2)), included in the Júcar River Basin. Over the past 30 years, socioeconomic development within the region has been mainly depending on intensive use of groundwater resources for irrigating crops. This has provoked a continuous groundwater level fall in the last two decades and significant streamflow depletion in the connected Júcar River. This BN model has proved to be a robust Decision Support System for helping water managers in the decision making process.The authors gratefully acknowledge the contributions of the following people and organizations. The study has been partially supported by the European Community 7th Framework Project GENESIS (226536) on groundwater systems and from the subprogram Juan de la Cierva (2010, 2011) of the Spanish Ministry of Science and Innovation as well as from the Plan Nacional I + D + i 2008-2011 of the Spanish Ministry of Science and Innovation (subprojects CGL2009-13238-C02-01 and CGL2009-13238-C02-02). Finally, thanks to the Jucar River Basin Authority (CHJ), IDR of Univ. of Castilla-La Mancha, the Junta Central de Regantes de la Mancha Oriental, and all the different stakeholders who have collaborated on the data and information provided in this research.Molina, J.; Pulido-Velazquez, M.; Llopis Albert, C.; Peña Haro, S. (2013). Stochastic hydro-economic model for groundwater quality management using Bayesian networks. Water Science and Technology. 67(3):579-586. https://doi.org/10.2166/wst.2012.598S57958667