Animesh Kumar Kumar Gain

We propose a conceptual framework, KR-FWK (i.e. KULTURisk Framework from the name of the European project within which it originated) and its implementation methods SERRA (Socio-Economic Regional Risk Assessment) for integrated (physical and economical) risk assessment, and economic valuation of risk prevention benefits on multiple receptors. The KR-FWK and the SERRA approach are characterised by: (i) integration of physical-environmental dimensions and the socio-economic ones in risk assessment; (ii) consideration of the role of social capacities (adaptive and coping capacity) in reducing risk and related costs, (iii) quantitative (even monetary) assessment of risks and of the benefits of risk reduction measures, and (iv) solutions to deal with multiple sources of uncertainty in view of including the change dimension in decision support. Building on a widely adopted conceptual model, Risk is here considered as the combination of Hazard, Vulnerability and Exposure. In turn, Vulnerability is the result of the interactions between physical characteristics (susceptibility) and the capacities of the socio-economic system to adapt and cope with a given natural hazard. Exposure quantifies the natural and anthropogenic assets, which may be subject to the hazard. Whenever possible and desirable, exposure can be assessed in monetary terms, and thus the multiplicative combination of two indices ranging between 0 and 1 (H and V) with a third one (E) expressed in monetary terms produces a monetary quantification of risk. KR-FWK and SERRA have been applied to a series of case studies to test and consolidate the approach in various contexts of data availability, scale, etc.

According to EEA (European Environmental Agency), flood is the most dangerous natural hazard in Europe in terms of economic losses. TheKULTURisk Project (EU FP7) has dev eloped a nov el methodology for evaluating the integrated benef its of risk prev ention of water related natural hazards: SERRA (i.e. Socio-Economic Regional Risk Assessment). The proposed methodology enhances the traditional flood risk assessment by integrating the missing socio-economic dimension into the established regional risk assessment. Several case studies across Europe allowed for the consolidation, validation, and refinement of SERRA. This paper presents the results of its application to assess the benefits derived from the installation of an Early Warning System in Vipacco river basin in Friuli Venezia Giulia (Italy). Social, economic and physical data are used to assess the total expected risk for several receptors such as economic activities, cultural heritage, people, etc. The collected socio-economic data are stored in Geographic Inf ormation System (GIS) and processed according to SERRA algorithms to produce maps of various categories of costs (beyond physical-environmental damages) in order to assist the Decision Makers (DMs) in making more informative decisions. The visualization of total risk through GIS maps allows the DMs to understand the spatial distribution of social vulnerability, risk, and associated costs.

Climate change impacts on the Venice Lagoon Watershed (VLW), an area of 2,038 km2 in the north-eastern part of Italy, are expected to be particularly relevant for agriculture, given that approximately two-thirds of the total area is devoted to field crops, horticulture and market gardens. Farmer’s irrigation behaviour plays a crucial role for the sustainability of crop productions and water consumption. In this study, an agent-based model is developed to explore how farmers’ decisions affect future water consumption in the VLW. The model is an “agentized version” of a soil water balance model based on the FAO-56 procedure.

A climatic projection representing the IPCC A1B scenario is used to produce future daily data about relative humidity, precipitation, temperature and wind speed. In order to inform the farmers about the simulated future weather conditions, two types of meteorological services are made available: (1) a bi-weekly bulletin and (2) the seasonal forecasts. The precision of these services varies according to the selected exogenous information scenario which simulates different conditions, from perfect knowledge to poor forecasts. Using the available forecasts, farming agents take adaptation decisions concerning irrigation and crop management on the basis of their own risk and water saving attitudes. Farmer’s attitudes are characterized by fuzzy classification depending on age, relative income and crop profitability.

Farming agents’ adaptation decisions directly affect the crop and irrigation parameters, which in turn affect future water needs of the area. By incorporating available and future meteorological services, the model allows to investigate farmers’ decision making process and the consequent future irrigation water demand for the period 2015 to 2030. This paper describes the conceptual model following the ODD D protocol. Preliminary results are under analysis.