Stochastic-fuzzy multi criteria decision making for robust water resources management

2008 ◽  
Vol 23 (3) ◽  
pp. 329-339 ◽  
Author(s):  
Mahdi Zarghami ◽  
Ferenc Szidarovszky
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Water Resources Management ◽  
Multi Criteria Decision Making ◽  
Resources Management

A stochastic multi-criteria decision making framework for robust water resources management under uncertainty

2019 ◽  
Vol 576 ◽  
pp. 287-298 ◽  
Author(s):  
Feilin Zhu ◽  
Ping-an Zhong ◽  
Qing Cao ◽  
Juan Chen ◽  
Yimeng Sun ◽  
...  
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Water Resources Management ◽  
Multi Criteria Decision Making ◽  
Resources Management ◽  
Decision Making Framework

scholarly journals Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene

2013 ◽  
Vol 17 (12) ◽  
pp. 5013-5039 ◽  
Author(s):  
S. E. Thompson ◽  
M. Sivapalan ◽  
C. J. Harman ◽  
V. Srinivasan ◽  
M. R. Hipsey ◽  
...  
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Water Resources Management ◽  
Research Agenda ◽  
Water Systems ◽  
Coupled Systems ◽  
Model Data ◽  
Resources Management ◽  
Long Timescales ◽  
Insight Into

Abstract. Globally, many different kinds of water resources management issues call for policy- and infrastructure-based responses. Yet responsible decision-making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadal- to century-long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems. These models must be constrained to yield useful insights, despite the many likely sources of uncertainty in their predictions. Chief among these uncertainties are the impacts of the increasing role of human intervention in the global water cycle – a defining challenge for hydrology in the Anthropocene. Here we present a research agenda that proposes a suite of strategies to address these challenges from the perspectives of hydrologic science research. The research agenda focuses on the development of co-evolutionary hydrologic modeling to explore coupling across systems, and to address the implications of this coupling on the long-time behavior of the coupled systems. Three research directions support the development of these models: hydrologic reconstruction, comparative hydrology and model-data learning. These strategies focus on understanding hydrologic processes and feedbacks over long timescales, across many locations, and through strategic coupling of observational and model data in specific systems. We highlight the value of use-inspired and team-based science that is motivated by real-world hydrologic problems but targets improvements in fundamental understanding to support decision-making and management. Fully realizing the potential of this approach will ultimately require detailed integration of social science and physical science understanding of water systems, and is a priority for the developing field of sociohydrology.

Evolutionary Bayesian Belief Networks for Participatory Water Resources Management under Uncertainty

2011 ◽  
pp. 524-539
Author(s):  
R. Farmani ◽  
D.A. Savic ◽  
H.J. Henriksen ◽  
J.L. Molina ◽  
R. Giordano ◽  
...  
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Water Resources Management ◽  
Bayesian Belief Networks ◽  
Decision Making Process ◽  
Causal Loop Diagram ◽  
Belief Networks ◽  
Trade Off ◽  
Resources Management ◽  
Conflicting Objectives

A participatory integrated (social, economic, environmental) approach based on causal loop diagram, Bayesian belief networks and evolutionary multiobjective optimisation is proposed for efficient water resources management. The proposed methodology incorporates all the conflicting objectives in the decision making process. Causal loop diagram allows a range of different factors to be considered simultaneously and provides a framework within which the contributions of stakeholders can be taken into account. Bayesian belief networks takes into account uncertainty by assigning probability to those variables whose states are not certain. The integration of Bayesian belief network with evolutionary multiobjective optimisation algorithm allows analysis of trade-off between different objectives and incorporation and acknowledgement of a broader set of decision goals into the search and decision making process. The proposed methodology is used to model decision making process for complex environmental problems, considering uncertainties, addressing temporal dynamics, uncovering discrepancies in decision analysis process (e.g. completeness or redundancy of the model based on utility function) and generating policy options that trade-off between conflicting objectives. The effectiveness of the proposed methodology is examined in several water resources management problems. The case studies include optimum water demand management, UK; management of groundwater contamination of Copenhagen source capture zone areas, Denmark and simultaneous optimum management of four overexploited aquifers in Spain. It is shown that the proposed methodology generates large number of management options that trade-off between different objectives. The remaining task is to choose, depending on the preference of decision makers, a group of solutions for more detailed analysis.

Hydrogeological Modeling and Water Resources Management: Improving the Link Between Data, Prediction, and Decision Making

2019 ◽  
Vol 55 (12) ◽  
pp. 10340-10357 ◽  
Author(s):  
Bradley Harken ◽  
Ching‐Fu Chang ◽  
Peter Dietrich ◽  
Thomas Kalbacher ◽  
Yoram Rubin
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Water Resources Management ◽  
Resources Management ◽  
Data Prediction

Operationalising uncertainty in data and models for integrated water resources management

2007 ◽  
Vol 56 (9) ◽  
pp. 1-12 ◽  
Author(s):  
M.W. Blind ◽  
J.C. Refsgaard
Keyword(s):  
Water Management ◽  
Risk Assessment ◽  
Decision Making ◽  
Water Resources ◽  
Water Resources Management ◽  
Integrated Water Resources Management ◽  
Integrated Water Management ◽  
Resources Management ◽  
Broad Objective ◽  
Parameter Values

Key sources of uncertainty of importance for water resources management are (1) uncertainty in data; (2) uncertainty related to hydrological models (parameter values, model technique, model structure); and (3) uncertainty related to the context and the framing of the decision-making process. The European funded project ‘Harmonised techniques and representative river basin data for assessment and use of uncertainty information in integrated water management (HarmoniRiB)’ has resulted in a range of tools and methods to assess such uncertainties, focusing on items (1) and (2). The project also engaged in a number of discussions surrounding uncertainty and risk assessment in support of decision-making in water management. Based on the project's results and experiences, and on the subsequent discussions a number of conclusions can be drawn on the future needs for successful adoption of uncertainty analysis in decision support. These conclusions range from additional scientific research on specific uncertainties, dedicated guidelines for operational use to capacity building at all levels. The purpose of this paper is to elaborate on these conclusions and anchoring them in the broad objective of making uncertainty and risk assessment an essential and natural part in future decision-making processes.

GIS-Based System to Better Guide Water Resources Management and Decision Making

2014 ◽  
Author(s):  
Georges F. Comair ◽  
Daene. C. McKinney ◽  
David R. Maidment ◽  
Gonzalo Espinoza ◽  
Harish Sangiredy ◽  
...  
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Water Resources Management ◽  
Resources Management
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