Exploring pathways for sustainable water management in river deltas in a changing environment

Exploring adaptation pathways into an uncertain future can support decisionmaking in achieving sustainable water management in a changing environment. Our objective is to develop and test a method to identify such pathways by including dynamics from natural variability and the interaction between the water system and society. Present planning studies on long-term water management often use a few plausible futures for one or two projection years, ignoring the dynamic aspect of adaptation through the interaction between the water system and society. Our approach is to explore pathways using multiple realisations of transient scenarios with an Integrated Assessment Meta Model (IAMM). This paper presents the first application of the method using a hypothetical case study. The case study shows how to explore and evaluate adaptation pathways. With the pathways it is possible to identify opportunities, threats, timing and sequence of policy options, which can be used by policymakers to develop water management roadmaps into the future. By including the dynamics between the water system and society, the influence of uncertainties in both systems becomes clearer. The results show, among others, that climate variability rather than climate change appears to be important for taking decisions in water management

Microeconomic Motives of Land Use Change in Coastal Zone Area: Agent Based Modelling Approach

Economic growth causes growing urbanization, extension of tourist sector, infrastructure and change of natural landscape. These processes of land use change attract even more attention if they take place in coastal zone area. In that case not only the efficient allocation and preservation of natural area, but also reduction of potential damage from flooding is important. Driven forces of land use at macro and micro levels should be taken into account. This paper presents an agent based model (ABM), which is designed to simulate land use change in coastal zone area based of human behaviour. The aim is to understand motives, types of connections and interactions between different actors and natural environment in order to get a feeling how different policy options and natural conditions might affect land use configuration. Microeconomic motives of land use decisions are in the focus of the research. Individual land use decisions are guided by economic and geomorphologic conditions, spatial planning and coastal protection policy. Each location choice is done according to a set of defined rules and land attributes. Space is represented as a grid of cells. Self-interested economic agents interact with each other trying to benefit from a certain type of land-use. We introduce the perception of risk of flooding in the model of land use as an innovative aspect of ABM simulations for water management problems. Based on decisions of spatially distributed individual economic agents operating in a policy framework, the model produces aggregated land-use patterns as an outcome. Understanding the factors that affect land use decisions will help policy makers design incentives to achieve policy objectives in coastal zone area. The proposed ABM will be applied to a study area in the province of North Holland in the Netherlands

Flood risk modeling of urbanized estuarine areas under uncertainty: a case study for Whitesands, UK

Aims: The impacts of catastrophic flooding have steadily increased over the last few decades. This work investigated the effectiveness of flood modeling, with low dimensionality models along with a wealth of soft (qualitative) and hard (quantitative) data. In the presence of very low resolution or qualitative data this approach has the potential of assessing a plethora of different scenarios with little computational cost, without compromise in prediction accuracy. Study Design: A flood risk modeling approach was implemented for the urbanized and flood prone region of Whitesands, at the Scottish town of Dumfries. This involved collection of a wide range of data: a) topographical maps and data from field visits were used to complement existing cross-sectional data, for building the river’s geometry, b) appropriate hydrological data were employed to run the simulations, while historical information about the extent, depth and impacts of flooding were utilized for calibrating the hydraulic model, and c) a wealth of photographic data obtained during the most recent December 2013 flood, were used for the model’s validation. Place and Duration of Study: Desk study: School of Engineering, University of Glasgow; September 2013 to May 2014. Field study: Dumfries; November 2013 to January 2014. Methodology: The HEC-RAS 1D model has been used to represent the hydraulics of the system. Flood maps were produced considering the local topography and predicted inundation depths. Flood cost and risk takes further into account the type and value of inundated property as well as the extent and depth of flooding. Results: The model predictions (inundation depths and flood extents presented in the flood maps) were in fairly good agreement with the observed results along the studied section of the river. Conclusion: This study presented a flood modeling approach that utilized an appropriate range of accessible data in the absence of detailed information. As the level of performance was comparable to other inundation models the results can be used for identification of flood mitigation measures and to inform best management strategies for waterways and floodplains

Distributed simulation of city inundation by coupled surface and subsurface porous flow for urban flood decision support system

We present a decision support system for flood early warning and disaster management. It includes the models for data-driven meteorological predictions, for simulation of atmospheric pressure, wind, long sea waves and seiches; a module for optimization of flood barrier gates operation; models for stability assessment of levees and embankments, for simulation of city inundation dynamics and citizens evacuation scenarios. The novelty of this paper is a coupled distributed simulation of surface and subsurface flows that can predict inundation of low-lying inland zones far from the submerged waterfront areas, as observed in St. Petersburg city during the floods. All the models are wrapped as software services in the CLAVIRE platform for urgent computing, which provides workflow management and resource orchestration.Comment: Pre-print submitted to the 2013 International Conference on Computational Scienc

Enhancement of urban pluvial flood risk management and resilience through collaborative modelling: a UK case study

This paper presents the main findings and lessons learned from the development and implementation of a new methodology for collaborative modelling, social learning and social acceptance of flood risk management technologies. The proposed methodology entails three main phases: (1) stakeholder analysis and engagement; (2) improvement of urban pluvial flood modelling and forecasting tools; and (3) development and implementation of web-based tools for collaborative modelling in flood risk management and knowledge sharing. The developed methodology and tools were tested in the Cranbrook catchment (London Borough of Redbridge, UK), an area that has experienced severe pluvial (surface) flooding in the past. The developed methodologies proved to be useful for promoting interaction between stakeholders, developing collaborative modelling and achieving social acceptance of new technologies for flood risk management. Some limitations for stakeholder engagement were identified and are discussed in the present paper

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio