Dating ads in Szczecin Poland

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Accuracy of the database in terms of location and minimum size of objects approaches a , topographic map. This is enough to represent the natural and socio-economic environment down to a single parcel, road and building. The database used here corresponds to the state of January—July , depending on location. Data on buildings include their area, functional characteristic and, in most cases, the number of storeys.

In case the latter is missing, the building was assumed to have only one storey. Roads are represented in the database as a linear object, but for each section, their width is given, so that they could be transformed into a surface. Only paved roads were included in the calculation. Railway and tramlines were transformed into polygons according to the gauge of the tracks. Roads and tracks located on bridges or similar above-ground structures were excluded. Flood hazard analysis involves calculation of the inundation extent and other hydrological parameters of the flooding, such as water depth.

It is assumed that the sea at a certain scenario will cover all land lying below the assumed water level, as long as there is a direct connection with the source of flood. For the analysis of inundation caused by sea level rise, that is an accurate description. However, for storm surges it is a straightforward simplification.

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The method does not take into account the kinematics of the flow or sedimentation processes and considers flooding as an instantaneous process. The temporal change in water levels is also an important factor determining the inundation extent. Unfortunately, the data required to include time in such a calculation were not available to the authors.

In effect, the storm surge scenarios constitute a description of the worst-case event Apel et al. The biggest advantage of the chosen method is a possibility of a direct comparison of achieved results with previous studies performed in the Baltic coast. The possibility of directly implementing the method in the geographical information systems is also useful.

On the other hand, dynamic effects such as erosion and sedimentation were not included. The resolution of the DEM is fine enough to include flood defences; therefore, isolated locations, i. These areas were discarded to create the final flood zone using a four-side rule, which means that no water flow was allowed in diagonal directions Poulter and Halpin Naturally, dikes and other structures could fail and flood the hinterland, but that aspect was not considered in this article.

Also, the situation when water floods the land behind structures through culverts was not analysed. Protection from flood defences such as dikes, banks and other earthworks, as well as sluices and weirs is included in the calculation. Raster datasets with information on elevation CODGiK were combined to generate a complete grid of the study area.

The grid was then reclassified into two distinct classes: above and below the analysed sea level. The result was a two-coloured map showing the land and the inundation. The latter class was transformed into a vector polygon, and its connection with the sea was investigated by selecting only those polygons that are intersecting with the water at normal level. The resulting polygons were clipped with a mask representing Polish borders in order to delimit the final area at country level.

Further analysis included intersections between inundated area for each water level and different layers representing buildings, land types, etc. In this way, the exposure of population and assets at different elevations could be assessed in detail. The 5-m value was chosen as the rounded value of the maximum possible SLR indicated in the literature 1.

The results are also juxtaposed here with future sea level rise scenarios included in the latest IPCC report Church et al. Three scenarios are considered: the medium projection for RCP4. However, Polish coast is subject to the glacial isostatic adjustment, which causes a yearly uplift by about 0.

Increase in water levels is also uneven regardless of the movement of the coast; satellite-measured SLR trend during — was between 4. These two effects translate to a difference of only a few centimetres in a perspective of a century.

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Bigger spatial differences in SLR can be caused by ground subsidence, which is a very local factor; no large-scale data are available on this matter. Therefore, IPCC scenarios were applied in the analysis without modifications. For the analysis of coastal floods, the return periods of storm surges were calculated. They vary along the coast and lagoons; therefore, the return periods were calculated from annual maximum water levels recorded at eight gauges during — To each station 5 coastal, 1 in the Szczecin Lagoon and two on Odra river , the nearest basic administrative units were assigned.

Hazard, i. Vulnerability, i. In this section, we present the methodology to calculate exposure and vulnerability in order to obtain an estimate of risk caused by sea level rise and coastal floods in context of SLR. Permanent losses of natural capital: market value of land, including an estimate of the area of protected habitats,. Permanent loss of physical capital: gross replacement cost of immovable and movable fixed assets,. Value of aforementioned assets was calculated here using data, the latest year for which complete statistics required here were available.

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Values of land under different types of use are an estimate of their market price. Average sale price calculations made by CSO were used for arable land, meadows and pastures.

Value of forests was taken from estimates of the State Forests, the manager of the vast majority of Polish woods Ministry of Treasury Their calculations include both the value of land parcels and the trees covering them. Value of areas covered by buildings, transport infrastructure or non-built-up areas ready for construction was estimated using the relation between the sale price of those types of land use and the sale price of arable land in Germany in Statistisches Bundesamt As a result, woodlands or bushes are assumed to be worth equal to poor-quality arable land.

Orchards were assigned the same value as arable land, while wastelands and other unutilized land were considered as equal to poor-quality meadows. Loss of inland surface water was not taken into consideration.

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Agricultural build-up areas do not form a separate category in the topographic database; it was assumed that build-up areas adjacent to arable land and permanent crops fall into this category. Value of housing is the average construction cost of new houses as calculated by CSO. Stock of movable assets is difficult to estimate, and no national statistics in this matter are available. GDP and housing area statistics from CSO were used in order to obtain the amount of movable assets per m 2 in Commercial buildings were divided into three branches industry, services and agriculture , and for each type, its value was calculated using the following formula:.

Fixed assets estimates were obtained from Eurostat Land use data for Poland is from CSO , while for the study area, the corresponding types of land use from the topographic database were used. Finally, building area was extracted from the topographic database, taking into account the multiple storeys several buildings contain. In case of rising average water levels, land and immovable fixed assets i. Movable fixed assets, which include machine tools, household goods, vehicles or livestock, can be evacuated from the endangered area given the gradual nature of SLR.

Therefore, no losses in this category are assumed. In case of coastal floods, no losses are assumed for land, as water covers it only temporarily. Some productivity of land may be lost and consequently its market value could decrease; however, this aspect was not analysed here. Damage to crops is not analysed too, as they are not considered fixed assets, similarly to stocks of produced goods. Losses of fixed assets are calculated using damage functions, which relate losses to water depths Apel et al. They were selected for this study, because there are no corresponding functions created from Polish empirical data.

Additionally, they are similar to damage curves created as a combination of various European methodologies by Huizinga and suggested for use in countries without national damage functions. The only exception is the damage function for transportation, which is a constant value rather than a damage function. Total value of losses for a building can be described as:.

Additionally, the number of people affected by sea level rise and coastal floods was estimated. Population data from the census CSO provide information down to settlement level. By combining these data with housing area from the topographic objects database, it was possible to further disaggregate the data and obtain the average number of persons per housing area in settlements and towns. All persons living in a residential building even partially covered by water were assumed as being affected by the event.

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Similarly, the amount of tourism traffic potentially lost was estimated by disaggregating the number of tourists and nights spent in establishments at basic administrative unit-level using the size of appropriate categories of buildings. Currently existing flood defences will be put under pressure from rising sea levels. In this section, we outline the methodology to estimate costs of adaptation to the that phenomena.

We look at the most popular means of protection, namely dikes. We estimate the length of flood defences using GIS as follows. Firstly, continuous flood zones that contain any buildings are selected. Then, those zones are intersected with a layer representing water at normal conditions including channels and streams. The length of the intersection lines between the layers was considered as the dike length required for full protection. Because only flood zones with buildings are considered here, some land and pieces of infrastructure will remain unprotected.

However, these flood zones are very numerous, yet very small, and would therefore seriously overestimate of the required investments in flood defences. Dikes have a high marginal cost, which varies enormously depending on location Jonkman et al. Using annual sea level rise projections, yearly cost of raising the flood defences could be calculated. It is assumed that an upgrade or new construction will be built overnight with a cm safety margin and will be serve without further upgrades until the year A different approach was used for analysing the adaptation to increased storm surge heights.

Protection standards of dikes are often chosen arbitrarily. However, it is possible to calculate a flood defence standard in a given location that would be optimal from an economic point of view. In this approach Van Dantzig ; Eijgenraam , investments in flood defences are added to flood damages during the same given period of time. The sum of the two elements reaches a minimum at a certain dike crest elevation; this level constitutes the optimal flood protection.

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It can be expected that the optimum will shift due to sea level rise. Investments were calculated for each water level as described in the previous paragraph. Risk to assets for each protection standard and SLR scenario was obtained using the following procedure. Firstly, a Monte Carlo simulation was used to estimate the annual losses due to coastal floods D i :.

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