Höllermann, Britta: Decision-making under uncertainty in model-based water management : The science-practice interface. - Bonn, 2018. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
Online-Ausgabe in bonndoc: https://nbn-resolving.org/urn:nbn:de:hbz:5n-51394
@phdthesis{handle:20.500.11811/7602,
urn: https://nbn-resolving.org/urn:nbn:de:hbz:5n-51394,
author = {{Britta Höllermann}},
title = {Decision-making under uncertainty in model-based water management : The science-practice interface},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2018,
month = jul,

note = {Balancing the different needs and demands of water users and managing the supply side under temporal and spatial variability and extremes has always been a challenging task for water managers. However, accelerated environmental and societal change aggravates water management as uncertainties increase even further. Decision-making in water management must integrate uncertainty information to base decisions on and be prepared for surprise and ambiguity. While it is often considered that decision-makers do not understand or – at least sometimes – ignore uncertainty analysis, this research shows that uncertainties do in fact matter for water managers and that they already cope with them and acknowledge them as an integral part of their planning. This doctoral research aims at improving the understanding of how scientific uncertainties find better integration into planning and decision-making processes in model-based water management. The thesis hereby follows the hypothesis that understanding and identifying the plurality of practitioners and the diversity of their approaches, perspectives, and reasoning are key aspects to close the science-practice gap.
Extensive expert elicitation, a quantitative survey and qualitative system modelling present the applied methods to answer the research questions. The intensive engagement with practitioners plays a crucial role for the thesis to assess uncertainty perception and handling strategies of water managers. Even though the results are mainly demonstrated at the case of reservoir management under changing intra-annual and annual conditions, the findings can easily be transferred to other water-related management objectives.
The main finding of this research is that water managers acknowledge uncertainties. However, the degree of acknowledgement and handling capacity varies per level of working experience, educational background, type of employer and affiliation to business unit. In close relation to their background, water managers have developed different strategies to handle uncertainties, approaches which may seem less obvious to scientists. Additionally, tacit knowledge plays a major role in handling uncertainties as well as the implicit handling of process uncertainties. A lack of transparency, regulations and constraints in a highly politicized decision-making environment present limitations of uncertainty integration. Thus, the use of uncertainty strategies and routines applied by the practitioners differs regarding group membership and time-frame of the management objective. In the course of this doctoral thesis, three major tools were developed to increase the transparency and integration of uncertainties: 1) a 2x2 uncertainty matrix, 2) an integration and analytical framework, and 3) a qualitative system model. This compilation has identified criteria, described prerequisites and provided a practical strategy to improve the integration of scientific uncertainties into planning and decision-making processes in model-based water management. It gives implications for increasing usability of uncertainty information and enables second or third loop learning for adaptive or transformative water management by fostering cross-communication within practice and between science and practice. This research also presents a theoretical construct to rethink uncertainty implications and their interrelations with respect to a plurality of perspectives, especially, regarding the diversity of practitioners. Furthermore, this research contributed to the science-practice gap research by emphasising the plurality of practitioners' uncertainty perception and handling. Acknowledging this plurality overcomes the thinking of a linear causal chain of information and makes room for a plurality of knowing and, hence, different ways to cope with and to integrate uncertainties into final decisions.},

url = {http://hdl.handle.net/20.500.11811/7602}
}

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