Raffaele Giordano

A fuzzy GIS-based system to integrate local and technical knowledge in soil salinity monitoring

The increasing awareness of the complexity and uncertainty of environmental processes is changing the role of information production to support decision-making. Monitoring systems need to gather reliable information, adopting a multi-scale and integrated approach. Using exclusively technical monitoring methods to collect the information could result in unsustainable monitoring costs. In order to minimize the costs and to address the scale issue, the integration of local and technical knowledge is proposed in this work. For the implementation of this approach, a tool based on the use of fuzzy logic and geographic information system (GIS) technologies was developed. The willingness of the local community to participate in monitoring activities was ensured by keeping these activities as simple and close to local knowledge as possible. The fuzzy GIS-based system enhances both the comprehensibility of the local knowledge for the decision-makers and its reliability, making it usable for the decision-making process. The tool was developed to support soil salinity monitoring in the lower Amudarya River Basin in Uzbekistan.

Integrating local and technical knowledge to support soil salinity monitoring in the Amudarya river basin

The role of monitoring is changing due to the increasing awareness of complexity and uncertainty in environmental resources management. Monitoring systems are required to support critical reflection about the effectiveness of actions toward the achievement of management objectives. To this aim, monitoring should be based on a strong integrated and multi-scale approach. Monitoring costs could be prohibitive if the monitoring is only based on traditional scientific methods of measurements. To deal with these issues, the design of an innovative monitoring system should be based on the integration between different sources of knowledge and information. In this work the usability of local knowledge to support environmental monitoring is investigated. A multi-step participatory monitoring design process has been implemented aiming to design a program for soil salinity monitoring in the lower Amudarya river basin in Uzbekistan. Although there is an increasing awareness of the importance of stakeholders being involved in decision processes, the current socio-cultural and institutional context is not favourable to the participatory approach. The choice of method to be implemented in this work was influenced by such conditions. The analysis of the lessons learned from the experiences gained in this project revealed some important clues concerning the development of a locally-based monitoring program. These lessons can be subdivided according to three fundamental issues: the long term involvement of local community members in monitoring activities, the acceptance of locally-based monitoring systems by decision makers, and the reliability of monitoring information.

A Bayesian vulnerability assessment tool for drinking water mains under extreme events

Drinking water security is a life safety issue as an adequate supply of safe water is essential for economic, social and sanitary reasons. Damage to any element of a water system, as well as corruption of resource quality, may have significant effects on the population it serves and on all other dependent resources and activities. As well as an analysis of the reliability of water distribution systems in ordinary conditions, it is also crucial to assess system vulnerability in the event of natural disasters and of malicious or accidental anthropogenic acts. The present work summarizes the initial results of research activities that are underway with the intention of developing a vulnerability assessment methodology for drinking water infrastructures subject to hazardous events. The main aim of the work was therefore to provide decision makers with an effective operational tool which could support them mainly to increase risk awareness and preparedness and, possibly, to ease emergency management. The proposed tool is based on Bayesian Belief Networks (BBN), a probabilistic methodology which has demonstrated outstanding potential to integrate a range of sources of knowledge, a great flexibility and the ability to handle in a mathematically sound way uncertainty due to data scarcity and/or limited knowledge of the system to be managed. The tool was implemented to analyze the vulnerability of two of the most important water supply systems in the Apulia region (southern Italy) which have been damaged in the past by natural hazards. As well as being useful for testing and improving the predictive capabilities of the methodology and for possibly modifying its structure and features, the case studies have also helped to underline its strengths and weaknesses. Particularly, the experiences carried out demonstrated how the use of BBN was consistent with the lack of data reliability, quality and accessibility which are typical of complex infrastructures, such as the water distribution networks. The potential applications and future developments of the proposed tool have been also discussed accordingly.

Participatory Research for Adaptive Water Management in a Transition Country - a Case Study from Uzbekistan

Participatory research has in recent years become a popular approach for problem-oriented scientific research that aims to tackle complex problems in a real management context. Within the European Union project NeWater, stakeholder processes were initiated in seven case studies to develop approaches for adaptive water management. The Uzbek part of the Amudarya River basin was one of the studied river basins. However, given the current political and cultural context in Uzbekistan, which provides little room for stakeholder participation, it was unclear to what extent participation could be realized there. In this paper, we present an evaluation of the participatory research carried out in the Amudarya case study with respect to (i) the choice and application of different participatory methods and their adaptation to the given political, socioeconomic, and cultural environment, (ii) their usefulness in improving system understanding and developing strategies and measures to improve water management and monitoring, and (iii) their acceptance and suitability for enhancing policy-making processes in the Amudarya River basin context. The main lessons learned from the comparison of the different participatory methods were (1) the stakeholder process provided an opportunity for meetings and discussions among stakeholders from different organizational levels and thus promoted communication between different levels and organizations, and (2) in a context where most stakeholders are not generally involved in policy-making, there is a danger of raising expectations that a research project cannot meet, e.g., of transferring local interests to higher levels. Our experience shows that in order to choose participatory methods and adapt them to the Uzbek cultural and political setting (and most likely this applies to other post-Soviet transition countries as well), four aspects should be taken into account: the time required to prepare and apply the method, good information about the participants and the context in which the method will be applied, knowledge of the local language(s), and careful training of local moderators. While these aspects are relevant to any application of participatory methods, they become even more important in a political and socio-cultural setting such as that found in Uzbekistan. One added value of the activities and a crucial aspect of a participatory research processes was the capacity building of local scientists and practitioners, which facilitates the further application of the methods.

Integration of local and scientific knowledge to support drought impact monitoring: some hints from an Italian case study

According to the Hyogo Framework for Action, increasing resilience to drought requires the development of a people-centered monitoring and early warning system, or in other words, a system capable of providing useful and understandable information to the community at risk. To achieve this objective, it is crucial to negotiate a credible and legitimate knowledge system, which should include both expert and local knowledge. Although several benefits can be obtained, the integration of local and scientific knowledge to support drought monitoring is still far from being the standard in drought monitoring and early warning. This is due to many reasons, that is, the reciprocal skepticism of local communities and decision makers, and the limits in the capacity to understand and assess the complex web of drought impacts. This work describes a methodology based on the sequential implementation of Cognitive Mapping and Bayesian Belief Networks to collect, structure and analyze stakeholders’ perceptions of drought impacts. The methodology was applied to analyze drought impacts at Lake Trasimeno (central Italy). A set of drought indicators was developed based on stakeholders’ perceptions. A validation phase was carried out comparing the perceived indicators of drought and the physical indicators (i.e., Standard Precipitation Index and the level of the lake). Some preliminary conclusions were drawn concerning the reliability of local knowledge to support drought monitoring and early warning.

Natural Assurance Scheme: A level playing field framework for Green-Grey infrastructure development

This paper proposes a conceptual framework to systematize the use of Nature-based solutions (NBS) by integrating their resilience potential into Natural Assurance Scheme (NAS), focusing on insurance value as corner stone for both awareness-raising and valuation. As such one of its core goal is to align research and pilot projects with infrastructure development constraints and priorities. Under NAS, the integrated contribution of natural infrastructure to Disaster Risk Reduction is valued in the context of an identified growing need for climate robust infrastructure. The potential of NAS benefits and trade-off are explored by through the alternative lens of Disaster Resilience Enhancement (DRE). Such a system requires a joint effort of specific knowledge transfer from research groups and stakeholders to potential future NAS developers and investors. We therefore match the knowledge gaps with operational stages of the development of NAS from a project designer perspective. We start by highlighting the key role of the insurance industry in incentivizing and assessing disaster and slow onset resilience enhancement strategies. In parallel we place the public sector as potential kick-starters in DRE initiatives through the existing initiatives and constraints of infrastructure procurement. Under this perspective the paper explores the required alignment of Integrated Water resources planning and Public investment systems. Ultimately this will provide the possibility for both planners and investors to design no regret NBS and mixed Grey-Green infrastructures systems. As resources and constraints are widely different between infrastructure development contexts, the framework does not provide explicit methodological choices but presents current limits of knowledge and know-how. In conclusion the paper underlines the potential of NAS to ease the infrastructure gap in water globally by stressing the advantages of investment in the protection, enhancement and restoration of natural capital as an effective climate change adaptation investment.

Modelling the complexity of the network of interactions in flood emergency management: The Lorca flash flood case

Abstract There is growing awareness that fast response to emergency situation requires effective coordination among several institutional and non-institutional actors. The most common approaches, based on innovating technologies for information collection and management, are not sufficient to cope with the increasing complexity of emergency management. This work demonstrates that effective cooperation claims for a shift from information management to interaction management. Therefore, methods and tools are required in order to better understand the complexity of the interactions taking place during an emergency, and to analyse the actual roles and responsibilities of the different actors. This paper details the design and implementation of an integrated approach aiming to unravel the complexity of the interaction network based on Storytelling, the Problem Structuring Method, and Social Network Analysis. The potential of the integrated approach has been investigated in the Lorca (Spain) flood risk management case study.

Emergency Management of Drinking Water Infrastructures Based on a Bayesian Decision Support System

The present work summarizes the theoretical development process and the preliminary results of a research activity oriented to the definition of a Decision Support System (DSS) to be used for managing drinking water systems exposed to different hazard classes. The core of such DSS is a probabilistic vulnerability assessment tool based on Bayesian Belief Networks, mainly developed integrating expert knowledge and literature information. This vulnerability assessment tool proved able to define a reliable map of vulnerability levels for complex and interconnected infrastructures, thus helping decision-makers in the selection of the optimal strategies to respond to emergencies. The DSS is based also on the implementation of hydraulic models, both for gravity and pressurized water mains, which should provide information regarding the changes in the hydraulic behavior of the network due to a specific event or an action. A case study is described, confirming the potentialities of the proposed tool.

Dealing with Uncertainty in Decision-Making for Drinking Water Supply Systems Exposed to Extreme Events

The availability and the quality of drinking water are key requirements for the well-being and the safety of a community, both in ordinary conditions and in case of disasters. Providing safe drinking water in emergency contributes to limit the intensity and the duration of crises, and is thus one of the main concerns for decision-makers, who operate under significant uncertainty. The present work proposes a Decision Support System for the emergency management of drinking water supply systems, integrating: i) a vulnerability assessment model based on Bayesian Belief Networks with the related uncertainty assessment model; ii) a model for impact, and related uncertainty assessment, based on Bayesian Belief Networks. The results of these models are jointly analyzed, providing decision-makers with a ranking of the priority of intervention. A GIS interface (G-Net) is developed to manage both input spatial information and results. The methodology is implemented in L’Aquila case study, discussing the potentialities associated to the use of the tool dealing with information and data uncertainty.

A fuzzy conflict measure for conflict dissolution in drought management

In the real world, environmental decision-making takes place in a highly interconnected environment, in which neither the decisional ramifications of a management action, nor the complexity of its impact, can be neglected. A fuzzy conflict measure is proposed in this contribution to support drought management. The proposed approach allows to detect, analyse and measure conflicts between the different actors involved in drought management, and to support the process of conflict dissolution.