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

A Methodological Approach to Determine Sound Response Modalities to Coastal Erosion Processes in Mediterranean Andalusia (Spain)

Human occupation along coastal areas has been greatly increasing in recent decades and, in many places, human activities and infrastructures are threatened by erosion processes that can produce relevant economic and human losses. In order to reduce such impacts and design sound management strategies, which can range from the "no action" to the "protection" option, coastal managers need to know the intrinsic coastal sensitivity and the potential vulnerability and value of land uses. In this paper, in a first step, coastal sensitivity was determined by calculating the following: (i) the spatial distribution at the coast of the wave forcing obtained by using the ERA5 wave dataset and defined as the energy associated with the 50-year return period storm. Two storm conditions were considered, that is, one for the eastern and one for the western parts of the Andalusia Mediterranean coast, respectively, characterized by a height of 8.64-7.86 m and 4.85-4.68 m and (ii) the existence of a buffer zone, namely the dry beach width expressed as a multiple of the 20-year predicted shoreline position that was calculated using a dataset of aerial photographs covering a time span from 1956 to 2016. Coastal sensitivity values were divided into five classes with class 1 indicating the lowest sensitivity (i.e., the presence of a wide buffer zone associated with low wave energy flux values) and class 5 the highest sensitivity (i.e., a narrow buffer zone associated with very high wave energy flux values). In a second step, land uses were obtained from the official Land Use Map of the Andalusia Region, based on the results of the "Coordination of Information on the Environment" (CORINE) European Project. Such uses were divided into five classes from class 1 including natural areas (typologies "A" and "B" of the CORINE Project) to class 5 including very capital land uses (typologies "E1" and "E2"). In a third step, information concerning coastal sensitivity and land uses was crossed to determine the best mitigation strategies to cope with erosion processes. The "no action" option was observed at the westernmost area of Cadiz Province and at some areas from the west coast of Almeria Province, where both coastal sensitivity and land use classes show low values; the "adaptation" option was recorded along more than one half of the coast studied, essentially at natural areas with high sensitivity and at urbanized areas with low sensitivity; and the "protection" option was observed especially at some areas from the center and eastern part of Malaga Province and at the easternmost areas of Almeria Province, where both coastal sensitivity and land use classes presented high values

Stochastic modeling of soil salinity

A minimalist stochastic model of primary soil salinity is proposed, in which the rate of soil salinization is determined by the balance between dry and wet salt deposition and the intermittent leaching events caused by rainfall events. The long term probability density functions of salt mass and concentration are found by reducing the coupled soil moisture and salt mass balance equation to a single stochastic differential equation driven by multiplicative Poisson noise. The novel analytical solutions provide insight on the interplay of the main soil, plant and climate parameters responsible for long-term soil salinization. In particular, they show the existence of two distinct regimes, one where the mean salt mass remains nearly constant (or decreases) with increasing rainfall frequency, and another where mean salt content increases markedly with increasing rainfall frequency. As a result, relatively small reductions of rainfall in drier climates may entail dramatic shifts in long-term soil salinization trends, with significant consequences e.g. for climate change impacts on rain-fed agricultur

Managed Aquifer Recharge as a Tool to Enhance Sustainable Groundwater Management in California

A growing population and an increased demand for water resources have resulted in a global trend of groundwater depletion. Arid and semi-arid climates are particularly susceptible, often relying on groundwater to support large population centers or irrigated agriculture in the absence of sufficient surface water resources. In an effort to increase the security of groundwater resources, managed aquifer recharge (MAR) programs have been developed and implemented globally. MAR is the approach of intentionally harvesting and infiltrating water to recharge depleted aquifer storage. California is a prime example of this growing problem, with three cities that have over a million residents and an agricultural industry that was valued at 47 billion dollars in 2015. The present-day groundwater overdraft of over 100 km3 (since 1962) indicates a clear disparity between surface water supply and water demand within the state. In the face of groundwater overdraft and the anticipated effects of climate change, many new MAR projects are being constructed or investigated throughout California, adding to those that have existed for decades. Some common MAR types utilized in California include injection wells, infiltration basins (also known as spreading basins, percolation basins, or recharge basins), and low-impact development. An emerging MAR type that is actively being investigated is the winter flooding of agricultural fields using existing irrigation infrastructure and excess surface water resources, known as agricultural MAR. California therefore provides an excellent case study to look at the historical use and performance of MAR, ongoing and emerging challenges, novel MAR applications, and the potential for expansion of MAR. Effective MAR projects are an essential tool for increasing groundwater security, both in California and on a global scale. This chapter aims to provide an overview of the most common MAR types and applications within the State of California and neighboring semi-arid regions

"Last-Mile" preparation for a potential disaster

Extreme natural events, like e.g. tsunamis or earthquakes, regularly lead to catastrophes with dramatic consequences. In recent years natural disasters caused hundreds of thousands of deaths, destruction of infrastructure, disruption of economic activity and loss of billions of dollars worth of property and thus revealed considerable deficits hindering their effective management: Needs for stakeholders, decision-makers as well as for persons concerned include systematic risk identification and evaluation, a way to assess countermeasures, awareness raising and decision support systems to be employed before, during and after crisis situations. The overall goal of this study focuses on interdisciplinary integration of various scientific disciplines to contribute to a tsunami early warning information system. In comparison to most studies our focus is on high-end geometric and thematic analysis to meet the requirements of small-scale, heterogeneous and complex coastal urban systems. Data, methods and results from engineering, remote sensing and social sciences are interlinked and provide comprehensive information for disaster risk assessment, management and reduction. In detail, we combine inundation modeling, urban morphology analysis, population assessment, socio-economic analysis of the population and evacuation modeling. The interdisciplinary results eventually lead to recommendations for mitigation strategies in the fields of spatial planning or coping capacity

The coastal environmental profile of Segara Anakan-Cilacap, South Java, Indonesia

Coastal zone, Coastal zone management, Environmental profile, Segara Anakan, Cilacap, Java, Indonesia,

Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone