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International Journal of River Basin Management
ISSN: 1571-5124 (Print) 1814-2060 (Online) Journal homepage: http://www.tandfonline.com/loi/trbm20
Temporal development of flood risk consideringsettlement dynamics and local flood protectionmeasures on catchment scale: An Austrian casestudy
Stefan Achleitner, Matthias Huttenlau, Benjamin Winter, Julia Reiss, ManuelPlörer & Michael Hofer
To cite this article: Stefan Achleitner, Matthias Huttenlau, Benjamin Winter, Julia Reiss, ManuelPlörer & Michael Hofer (2016): Temporal development of flood risk considering settlementdynamics and local flood protection measures on catchment scale: An Austrian case study,International Journal of River Basin Management
To link to this article: http://dx.doi.org/10.1080/15715124.2016.1167061
Accepted author version posted online: 06Apr 2016.
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Publisher: Taylor & Francis & International Association for Hydro-Environment Engineering and Research Journal: Intl. J. River Basin Management DOI: 10.1080/15715124.2016.1167061
Temporal development of flood risk considering settlement dynamics and local flood protection measures on catchment scale: An Austrian case study Stefan Achleitner1*, Matthias Huttenlau2,3, Benjamin Winter2,3, Julia Reiss2,3, Manuel Plörer1 and Michael Hofer4 1Unit of Hydraulic Engineering, Institute of Infrastructure, University of Innsbruck, Technikerstrasse 13, 6020, Innsbruck, Austria. T: 0043/512/507/62215, Email: [email protected] 2alpS – Centre for Climate Change Adaptation, Grabenweg 68, 6020 Innsbruck, Austria. Tel: 0043/512/392929-32; Email: [email protected]; [email protected] 3Institute of Geography, University of Innsbruck, Innrain 52f, Innsbruck, Austria. Email: [email protected] 4Ingenieurbüro Dipl.- Ing. Günter Humer GmbH, 4682 Geboltskirchen, Feld 16 Österreich. Email: [email protected] *Corresponding author: Stefan Achleitner, Tel: 0043/512/507/62202, Email: [email protected] Abstract
With respect to urban development a common practice is to exclude flood-prone areas from further construction for flood safety reasons. Granting exemptions when local flood safety measures are applied is a topic of continued debate. The Ottnager-Redl/Upper Austria case study investigates various future settlement scenarios with or without Local Flood Protection Measures (LFPM). In accordance with the legal situation in the Federal Province of Upper Austria, construction permits require flood safety up to a 100-year flood level plus 20 cm. Estimations of potential flood damage in the catchment’s residential areas are based on damage functions used to describe the structural vulnerability at an object level. Impacts are simulated with a distributed hydrological and a 2D-hydraulic model, which incorporate future settlement dynamics. In addition to linking losses to return periods, the cumulative damages within design periods are estimated using a Monte-Carlo modelling framework. Event-based and cumulative losses increase with the different settlement scenarios. The LFPM tested visibly reduce the cumulative losses as they are triggered by high frequency/low impact events. Considering single events, the positive effects of LFPM, specifically flexible flood barriers, generally vanish when they exceed the design level. Thus, the increased flood risk due to intensified settlement in the flood-prone area cannot be compensated by LFPM. Keywords: Flood damage, settlement scenario, vulnerability, local flood protection measure, Monte-Carlo, flood risk [BODY]
Introduction Hazard and risk mapping has become a widely applied approach to serve as a foundation for flood risk management. Driven by an increasing number of damaging flood events especially within the last decades, the analysis, assessment, and management of flood risk has been enforced. The main legal driver therein is the EU Directive on the assessment and management of flood risks (EU/2007/60/EC 2007) requiring that individual member states (i) pursue a preliminary flood risk assessment (until
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2011), (ii) establish flood hazard and risk maps (until 2013), and (iii) provide flood risk management plans (until 2015) in the first management cycle. Flood risk analyses are an essential part of the Integrated Flood Management (IFM) approach and the prerequisite for effective risk mitigation and adaptation decisions (Merz et al. 2010, Thieken et al. 2015, Schneeberger et al. 2015). The application of full modelling chains from rainfall runoff to damage modelling is a vital tool to gain spatial coherence when estimating losses (Falter et al. 2015, Gems et al. 2009, de Bruijn et al. 2014). Hydraulic modelling simulates the effects of flood defence measures (Delenne et al. 2012, de Bruijn et al. 2014) considering the probability of measure failure as well(Vorogushyn et al. 2011, Vorogushyn et al. 2012, Dawson et al. 2005). Then evaluation and comparison of the effects of the measures on flood protection is done in a risk based context (Tsakiris 2014, Bachmann and Schüttrumpf 2014). Results are usually displayed including their probabilistic nature (Domeneghetti et al. 2013, Beven et al. 2013, WMO 2013) supporting integrated flood management. IFM inter alia helps to reduce and mitigate potential adverse consequences of floods and enables communities to be prepared for future challenges with respect to Disaster Risk Reduction (DRR) and Climate Change Adaptation (CCA). Legislation at both the national and state levels thereby provides the legal foundation for IFM. As a result, local flood protection measures (LFPM) can be an effective and efficient approach to preventing damages to buildings (Bründl and Ettlin 2014, Schimek-Hickisch and Glinsner 2013) and thus to reducing flood risk. The case study presented was conducted in the catchment of the Ottnanger Redl, located in the Austrian Federal Province of Upper Austria. The Provincial Act for Construction Engineering and Materials (LBGl. Nr. 35/2013 2013) in Upper Austria covers the regulations for the flood-safe design of buildings (§ 47). Following this act, the new construction of buildings within flood planes with recurrence intervals of 100 years is permitted when "sufficient flood safety standards of the planned building are given when located below the flood flow level". The definition of flood-safe design includes that (i) the building is sealed or has an elevated design, (ii) openings require sealing and protective measures against water ingress, and (iii) the top edge of the ground floor is located 20 cm above the water level in the flood-prone area. The study area is characterized by a typical pre-alpine catchment situation with an elevation varying between 400 and 720 m a.s.l. It is north-south oriented with a size of 59.9 km2 , ending at the point at which the Redl river discharges into the Ager river. In total, 18,500 inhabitants live in eight communities, with the primary settled part being the community Attnang-Puchheim located downstream. A spatial overview of the catchment including available precipitation gauges and the relevant discharge gauge in the area is given in Figure 1. Figure 1: Catchment Ottnanger Redl: Overview with precipitation gauges and the discharge gauge Attnang. Considering the existing provincial act on flood safe design standards of buildings, the following questions in the context of IFM arose: What are potential pathways of future settlement development and how do they interact with the positive effects of LFPM?
Methods The study framework follows a risk-based approach in which risk is defined as a product of hazard, elements at risk, and vulnerability (Huttenlau et al. 2010). Beyond the current settlement situation, reconstruction of past and future scenarios with respect to the spatio-temporal patterns of elements at risk are considered. The monetary benefit of various options of LFPM was evaluated considering the structural vulnerability of buildings under different boundary conditions (for instance settlement scenarios or impact magnitudes). Figure 2 provides an overview of the modelling concept and shows the overall study workflow. The hydrological model together with the 2D hydraulic model is used to estimate the 100-year design flows and resulting inundations (see section 0 and 0). The derived hydro-meteorological (section 0) and settlement scenarios (section 0) provide additional input to simulate scenario-based inundation maps (see section 0). The final damage modelling and risk evaluation
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(section 0) combines results of the hydraulic simulations (section 0), the asset assessment (section 0), and the damage models (see sections 0and 0). Therein, evaluations are made considering past and future settlement scenarios in which different LFPM are applied. Figure 2: Modelling concept and work flow (numbers in parentheses indicate chapters).
Hydrological and Hydraulic Modelling With respect to hydrology, the northern headwater catchment of the study area can be characterized as forested hillsides. The gravel material typical of the Hausruck-quarter is characterized by a high infiltration capacity. Further downstream, marl dominates the landscape as the main geological formation. In the southern part located further downstream, quaternary gravel terraces of the Ager river constitute the main geomorphological features. The stream network is comprised of two main streams, the Ottnanger Redl and the Rötelbach, which converge and flow into the Redl river near Kreuth. The Ottnanger Redl is fed by the two headwater streams Simmeringerbach and Engelfingerbach, which converge upstream in Bruckmühl. The entire network has a total length of approx. 56 km (see also Figure 1).
Hydrological modelling and design flood estimation The setup for the hydrological model covers 35 sub-catchments (Figure 3 (a)), enabling flood flows and the subsequent inundation mapping to be addressed in a spatially distributed manner. Here HEC-HMS (2010) was applied, which allows modelling with the SCS-CN procedure (USDA 2004) or with the Soil Moisture Accounting (SMA) method (Chu and Steinman 2009). The model selection was made because the HEC-HMS allows the spatially distributed modelling of rainfall runoff generation, flow accumulation and channel routing. The SCS-CN procedure is an event based method for the simulation of single flood events; the SMA method allows continuous water balance modelling. The SMA is of special interest here due to the temporal characteristic of the flood event in 2002. Two consecutive rainfall events occurred within one week, resulting in two pronounced flood hydrographs (Figure 4), The second flood hydrograph was not only triggered by the rainfall intensity, but also by critical system states, especially antecedent soil moisture. Therefore, the SMA method was used to simulate the two events continuously, considering canopy interception, surface depression storage, infiltration, evapotranspiration, as well as soil water and groundwater percolation. The model parameters were estimated based on existing maps for land use, geology, and a digital terrain model (DTM). For flow routing, the Muskingum-Cunge routing scheme (Roberson et al. 1995, Cunge 1969) was used primarily For selected segments along the Redl river the lag-time concept was applied, based on calculations using the 2D- hydraulic model, showing almost no wave attenuation effects. Figure 3: Overview of (a) the hydrological model (HEC HMS) and (b) the bounds of the 2D-hydraulic model (Hydro-AS). Figure 4: Observed and simulated discharge Q at the gauge Attnang during the flood event in August 2002. The calibration was based on the discharge gauge Attnang-Puchheim using spatially distributed rainfall patterns originating from five precipitation gauges in the area surrounding the catchment(see Figure 1). Distributed rainfall as model input allows a better estimation of local flood flows and demonstrated as well an increased performance in simulating the discharge at the gauging station. The gauge Attnang located within the city boundaries receives the discharge from a catchment area of 53.99 km2. The 25 years in total of observations available at that gauge were used for statistical analysis; additionally, the findings of the HORA project (Merz et al. 2008) were incorporated. The annual maximum series of floods given, however, allows a limited prediction of low frequency events (recurrence intervals of 100 years and less). Therefore, the hydrological model was used to further estimate characteristic discharges based on design rainfall events. The estimation of design discharges follows the approach applied to process official flood hazard maps (Humer 2008). Finally, the
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definition of the 100-year design discharge was based on simulations of the hydrological model. Discharges for other recurrence intervals were estimated with the Generalised Extreme Value distribution (GEV) and adapted with a scaling factor based on the hydrological model application. The design discharges for selected recurrence intervals are shown in Table 1. Table 1: Design discharge QD at gauge Attnang for selected recurrence intervals Following the statistics of the design discharges, the 2002 flood event has an estimated recurrence interval of T=21.3 years.
Hydro-meteorological scenario building The event of 2002 was used as a basis for an event-based flood scenario approach considering different flow magnitudes. Therefore, the intensities of the distributed precipitation field were scaled, maintaining a realistic spatial distribution of precipitation and local discharges in the sub-catchments. Scaling of rainfall intensities with factors from 0.4 to 1.4 resulted in peak discharges at the gauge location ranging from 3.1 m3/s to 104.5 m3/s. Thus, extreme flood situations with discharges larger than a 300-year flood were covered.
Hydraulic modelling Flood plain simulations were made using the 2D numerical software HYDRO_AS-2D (Nujic 2009) using the Shallow Water Equation (Abbott 1979). The used irregular simulation net is derived on basis of a 1x1 m Digital Terrain Modell (DTM). It's discretized area represents a band along the basin’s main streams comprising ~600,000 nodes (~1 mill. cells), which cover a total area of 13.09 km2 (see Figure 3 (b)). Cell sizes vary between 1 m2 and ~450 m2 with a mean cell size of 20 m2. The numerical scheme employed is the Finite Volume Method for spatial discretization. To solve the temporal discretization, a predictor - corrector method equivalent to the second order Runge-Kutta scheme – is applied. The algebraic turbulence model implemented calculates the eddy viscosity based on shear velocity and water depth. The friction slope is determined with the Darcy-Weisbach equation (Chow 2009). The model calibration was based on (i) gauge observations as well as (ii) inundation observations from local residents during the 2002 event. Discharges from the hydrological model at 35 nodes drive the hydraulic model. Mainly roughness values set for areas with different land use were adapted within the calibration procedure. Inundation maps considering a 100-year recurrence interval is derived based on discharge from hydrological simulations using design rainfall. The model setup includes the consideration of the current settlement situation (state 2012) within the hydraulic net. Four different setups of the hydraulic model were applied, incorporating the settlement scenarios 1999, 2012, S2 and S4 as described below. Buildings were removed from the numerical net and therefore considered as impervious area with no associated flow. Each of the four model setups were driven with varying discharge hydrographs of the hydrological modelling procedure, covering the second flood period between the 11th and the 14th of August, 2002. Depending on the scenario, the simulation time varied between 15 h and 60 h using a Intel Pentium 4-Core @ 2.4 Ghz, 3.00 GB RAM. Exchange nodes between the hydrological and the hydraulic model are illustrated in Figure 3 (b) (red dots). Downstream boundaries were set with fixed energy gradients of 5 %0 at the foreland bounds. The outflow from the receiving stream River Ager follows a stage-discharge relation.
Settlement scenarios Different temporal periods were compared in order to identify the evolution of elements at risk and damage potential. All scenarios were mapped on a single-object basis, characterized by their specific functionality and monetary value. Based on data availability, a past (1999) and a current (2012) settlement situation were derived. The current settlement structure was pre-processed using official data sets. The most relevant data sources were the address-based building and house register, catastral map, land-use plan, digital terrain model (DTM), digital surface model (DSM), and orthophotos of 1999 and 2012. The high resolution
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DTM and DSM originate from airborne laser scanning. From the comprehensive database for 2012, the settlement structure of 1999 was reconstructed by means of orthophotos and interviews. Four possible future settlement scenarios for 2030 were developed. Three of them (S1, S2 and S3) consider local development concepts, official population and housing projections, identified building land reserves as well as exclusion criteria from existing hazard maps and protected areas. The fourth scenario (S4) addresses an extreme case, assuming the complete development of all existing building land reserves. The main limitations of the approach applied are that only residential buildings were considered within the scenario development and further activities are restricted to existing building land reserves. As there are extensive building land reserves in the study area today, no additional creation of building land reserve is considered. The settlement scenarios, (a) minimum development (scenario S1), (b) mean development (scenario S2), (c) strong development (scenario S3), and (d) maximum development (scenario S4), were created in accordance with the projections of the Austrian Conference on Spatial Planning ÖROK (2010) ((a) all risk, (b) all safety, (c) all competition and (d) all growth). Mean per-capita land use values (Steinnocher et al. 2004) and mean property-building size relationships were calculated for the eight individual communities. The individual household projections and the person-to-housing-unit relationship, which differentiates between rural communities and the more urban Attnang-Puchheim, were then used to define building developments for the individual settlement scenarios. To reflect the current building structure within the building development approach, clusters of similar buildings were formed for the individual building areas in the study area. Thus, the assumed future building structure resembles the current status of the surrounding area, for example higher building densities in the current town centers. The scenarios developed were discussed and verified with local experts (heads of municipalities) in the development phase and after completion. For the results presented here, the mean development (S2) and the maximum development (S4) were used to conduct the risk analysis and to describe the potential changes in flood risk. Those two scenarios represent a realistic scenario (S2) and a worst-case scenario (S4). The selection of the scenarios was made together with the responsible public authorities in Upper Austria.
Asset assessment Prior to the monetary assessment of buildings for all settlement scenarios, a characterization of the individual buildings was carried out. First, the data were used for an automated derivation of gross volumes, gross floor areas, and functional categories for all objects. Second, a subsequent manual verification was done to identify single objects that are assessed insufficiently. The final setup includes manually corrected data sets resulting from additionally conducted field work. Initially, a detailed differentiation was applied to assess the monetary values of the buildings precisely including their inventory. Following the monetary assessment, the building categories were aggregated to correspond with the building categories of the vulnerability approaches considered. For the monetary assessment of the building assets, four different approaches, adapted to the study area if necessary, were applied (see Table 2). Table 2: Overview of approaches for the building asset assessment The BFW approach applies standard values for individual buildings, the BMVBS approach considers gross floor area values, and the OOV approach considers cross volume values. In contrast, the WLV approach is based on gross volume values for residential buildings and on gross floor area values for all other building categories. In the BFW, BMVBS and the OOV approaches, a mean inventory standard was considered for residential buildings. Similarly, in the BMVBS approach, a mean value was used for all other object categories (e.g. Garages, Services, Industry,..). Buildings located on agricultural property were considered separately within the OOV approach. Technically, flat rate values apply, which are derived from the ratio of the total construction area of the residential building and the area of all buildings located on the property. For the subsidiary buildings considered in the WLV approach, prices for simple inventory were applied. For commercial and industrial buildings in the WLV approach, a mean value of 475 EUR/m2 of gross-floor area was used. Similarly, a mean value of 168 EUR/m2 was used
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for buildings on agricultural property. The inventory was included using a percentage method for both building types, according to Oberndorfer et al. (2007). All monetary values of the different (temporal) scenarios are indexed to the reference year 2012. For the BFW approach numbers were corrected for inflation, currency and value of money using the Big-Max-Index for Austria. Indexing is based on the building cost index for structural engineering (Statistik Austria 2013) for the BFW, the OOV and the WLV approaches. For the BMVBS approach indexing is based on the building cost index for structural engineering in Germany (DESTATIS - Statistische Bundesamt Deutschland 2013) and was transferred to Austria using the consumer price index of June 2012 (EUROSTAT 2013).
Structural vulnerability
Ensemble of damage functions To evaluate the potential flood damage, the concept of damage functions to describe structural vulnerability (Huttenlau and Stötter 2011) was applied at an object level. Damage functions express the relation between one or more flood impact parameters and the expected building damages. In this study, relative damage functions describing the degree of damage as a percentage of the building value (Huttenlau et al. 2010) were applied. Absolute damage functions are not used since no sufficient data exist for the study area and the application of existing absolute functions to other study areas is considered to be more difficult (Meyer and Messner 2007). The most common impact parameter is water depth (Merz et al. 2010). Further factors are, for example, the duration of inundation, the contamination effects, or the flow velocity. According to Kreibich et al. (2009), however, flow velocities are not considered to have strong influence on monetary building damages especially if flow velocities are low in the relevant study areas (Cammerer et al. 2013). Although the study area is located in a pre-alpine catchment, simulated flow velocities in the relevant inundation areas are considered to be low. Thus, water depth dependent damage functions were applied. In this study, eight different published damage functions from continental Europe are applied. They range (i) from step to continuous functions, (ii) from differentiating between many building categories to considering all buildings with one general category, and (iii) from considering the content separately to evaluating the global building value. The damage functions are, if appropriate, adapted to match given building categories and available data. The damage functions used are presented in Table 3. Table 3: Overview of applied damage functions
Altered vulnerability with Local Flood Protection Measures (LFPM) Two types of LFPM were implemented and evaluated, both following the minimum requirements of the Upper Austrian Law for Construction Engineering and Materials (LBGl. Nr. 35/2013 2013). The first type of LFPM evaluated (LFPM1) were flexible barriers (sealing of building openings, walls, inflatable barriers, etc.), assuming an upper safety level equivalent to the 100-year maximum water level plus 20 cm (HQ100+20cm). The damage function was altered to reflect that no damage occurs until the upper level is reached. After which, the original, not adapted, damage function was applied. The benefit of this measure is that the implementation is not restricted to newly constructed buildings but can be applied for existing properties as well. The second measure (LFPM2), in contrast, is mainly applicable to new constructions. The measure assumes an altering of the local topography or an elevated construction of a house itself, such that the ground floor is again at the desired level of HQ100+20cm. To consider the effect of this measure, the typical characteristic, of the damage functions were elevated to that level. The principles of these two applied approaches are illustrated in Figure 5. The scenario with no measures implemented (LFPM0) is used as a baseline scenario. Figure 5: Schematic on the implementation of altered damage functions due to Local Flood Protection Measures (a) flexible barriers (LFPM1) and (b) elevated construction (LFPM2).
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For both types of LFPM (LFPM1 and LFPM2), two options were simulated. In the first option (Y06), all properties located in the 100-year floodplain and constructed after 2006 were considered to have local flood protection. This is due to the fact that the provincial act came into force in 2006. In the second option, all properties were considered to be equipped with local flood safety measures (Y-All). The combination of Y-All with flexible barriers (LFPM1) is possible since existing properties can be retrofitted through that measure. In contrast, the combination of Y-All with type LFPM 2 is to be seen as a theoretical combination that allows for the quantification of the reduced losses for the case that protection type LFPM 2 would have been applied for all properties at the time of construction.
Damage modelling and risk evaluation Independent of the type of LFPM considered, the choice of methodological approach to quantify damage-reducing effects is an important issue. Within the damage modelling concept introduced, scenario-based inundation maps (Figure 2, section 0), assets (Figure 2, section 0), and vulnerability (Figure 2, sections 0 and 0) were systematically brought together. Typically, risk is evaluated with representative flood scenarios for given recurrence intervals. Loss-reducing effects of implemented measures were compared with a baseline scenario without measures (Bründl and Ettlin 2014). Although the benefit of a measure can be quantified for certain event magnitudes (the flood scenarios considered), cost-benefit analysis requires going beyond considering the potential spectrum of scenarios and their stochastic nature of occurrence. When evaluating an implemented mitigation measure, the life span or design period of such a measure additionally needs to be considered. For such evaluations, an adapted stochastic damage modelling approach (Achleitner et al. 2010, Gems et al. 2009) was developed and applied . Therein, flood losses over a certain design period were assessed based on Monte-Carlo simulations. Synthetic series of annual maximum flood peaks were generated at gauge locations following the given statistical properties. In the next step, the annual maximum peak flows were transferred into losses and cumulated over the design period. However, the application of the full modelling chain (hydrology, hydraulics, and damage modelling) would lead to impractical simulation times. Therefore, the framework considers the scenarios described above as nodes. Between those calculated nodes, actual loss values for corresponding annual maximum peak flows of the synthetic series were interpolated. The scenarios cover flood impacts for (i) various settlement scenarios and (ii) scaled flood scenarios applying different methods for asset assessment and damage modelling. Although only the 2002 storm event was used in this case study, the framework enables the use of different spatially varying weather (and consequently flooding) situations. As a result, accumulated damages in a defined time period can both be evaluated without LFPMs and compared with different options of LFPMs.
Results
Flood plain modelling As a result of the hydraulic flood modelling procedure, 24 sets of flood hazard maps in total were produced. The results cover four different modelling nets, representing the settlement scenarios 1999, 2012, and the two future scenarios S2 and S4. Figure 6 serves to illustrate the flood plain derived from the 2012 scenario with an approximate HQ100 flood flow at the gauging station Attnang. Six different precipitation and consequent flood magnitudes were simulated, driven by spatially consistent precipitation fields. The intensities of the spatially distributed precipitation field from the storm event in 2002 were scaled with factors 0.4, 0.6, 0.8, 1.0, 1.2 and 1.4. These scaled precipitation fields were used as input for the modelling chain of the hydrological and hydraulic model.
Figure 6: Flood plain at main urban settlement Attnang-Puchheim. Using the storm event 2002 scaled by factor 1.2; (~HQ100). For the simulated hydraulic scenarios, specifically their peak flow at the gauge location, the recurrence intervals were estimated as summarized in Table 4:
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Table 4: Hydraulic scenarios with various precipitation scaling factors (sf[-]) and corresponding recurrence interval (T) with regard to the peak design discharge (QD)
Sensitivity of different asset assessment and vulnerability approaches The approach described above for (i) asset assessment and (ii) consideration of the structural vulnerability yields a wide range of results. Figure 7 exemplifies the losses calculated with different combinations of (a) and (b), using the 2012 settlement scenario without any LFPM applied (LFPM0). The flood flow applied is approximately within the range of the 100-year design flow.
Figure 7: Calculated flood losses of a 100-year flood in the catchment Ottnanger Redl with varying (a) methods for monetary asset assessment and (b) damage functions; Settlement scenario 2012 without LFMP. For loss calculations made in the catchment of the study, the combination of OOV and BUWAL was considered to be representative. The OOV approach, based on data from a regional insurance company, was chosen due to its local relevance in the catchment. The BUWAL approach for damage modelling is expected to provide the best fit based on previous investigations conducted in the Austrian Federal Province of Vorarlberg (Huttenlau et al. 2015). It should be noted that inasmuch as only relative differences between settlement scenarios and/or associated LFPMs are of interest, similar findings and conclusions can be drawn, albeit using other approaches.
Development of damages Figure 8 shows the development of flood losses with respect to increasing settlement for different event magnitudes. As expected, the changes across settlement scenarios increase the potential losses with respect to equal peak flows. The results presented in Figure 8 show losses for different settlement scenarios without LFPM. For the 2012 and the 1999 scenarios, nearly the same loss of around 8.8 m EUR is estimated for a T=100-year flood scenario. Expected losses of the T=100-year flood increase to around 10.1 and 14.4 m EUR respectively for the scenarios S2 and S4. This is an increase of around 15% and 64% compared to 2012. For the T>300-year flood event, losses increase from 22.9 m EUR in 2012 to 26 m EUR (scenario S2) and 34 m. EUR (scenario S4) in 2030. This is an increase of 13% and 48%. Counting the number of affected houses, the T=100-year flood event would mean an increase from 240 affected houses to 306 comparing the 2012 to the S4 settlement scenario; 260 buildings would be affected considering the S2 scenario.
Figure 8: Development of event-based flood losses with increased discharge under consideration of the individual settlement scenarios.
Development of damages considering LFPM Figure 9 compiles the results of four temporal scenarios, showing that flood damages are altered logically in accordance with the event magnitude and the type of LFPM (0, 1 or 2) implemented. Each Figure 9, (a), (b), (c) and (d), represents a specific settlement scenario with LFPM implemented for buildings constructed after 2006 (Y06). As prescribed by the legislative LFPM definition, significant effects are observed at impact magnitudes below the 100-year flood event. The damages to the designated buildings decrease towards zero. Considering all buildings to be flood safe would make this effect visible on the catchment scale as well. Considering only buildings built after 2006 to be flood safe results in far fewer damage reductions. For the latter, almost no difference is observed for damages with or without LFPM in the 2012 scenario (Figure 9 (b))due to the fact that only a few new buildings were constructed in flood-prone areas between 2006 and 2012. Considering growing settlements (S2 and S4, Figure 9 (c) and (d)), losses with LFPM remain the same until a T=100-year flood event. Beyond that, damages increase as well for scenarios with LFPM. Reaching flood
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scenarios above T=300 years, the positive effect of the LFPM1 (Figure 9 (c) and (d) - red line) largely disappears. Looking at the S4 scenario (Figure 9 (c)), the resulting loss for LFPM1 is 31.8 m. EUR compared to 33.9 m. EUR without measures (compare blue and red line). The LFPM2 (green line) performs slightly better accounting for 24.6 m. EUR. Figure 9: Development of event-based flood damages with/without LFPM for different settlement scenarios (a) 1999 (b) 2012, (c) S2 and (d) S4.
Cumulative damages considering different design periods and LFPM Cumulative damages of the evaluation periods of 20 and 100 years are shown in Figure 10. Overall, the losses generated show a wide range of outliers. The standard deviation indicated is less but still, remarkably, within the range of +- 5 m. EUR (for D=20 years) and +- 12-15 m. (for D=100 years). For settlement scenarios 1999, 2012, S2 and S4, an increase in losses is observed for the cases without measures, comparing the grey shaded boxes in each Figure 10 (a), (b), (c) and (d). In contrast, cumulative losses for options considering the two measures remain at the same level, independent of the settlement scenario. Again, significant loss reductions are gained only when all buildings are considered flood safe (compare grey and white shades boxes in Figure 10 (b) and (d)). For both options LFPM1 and LFPM2, significant loss reductions are the case, whereby the reductions are still larger for LFPM2. This can be explained by the fact that a large number of events with small flood magnitudes are relevant for the calculated losses. Consequently, high cumulative losses over time are the case. Further, the resulting loss reductions are largely triggered by many small events and less so by single large events. Figure 10: Cumulative losses over design periods of D=20 years ((a) and (b)) and D=100 years ((c) and (d)), considering varying types of flood protections applied to different settling scenarios. For the worst-case settlement scenario, S4, the resulting effects – compared to the recent settling scenario 2012 – are shown in Figure 11. Comparatively, both options LFPM1 and LFPM2 are simulated, aiming to compensate for the extreme settling option. The implementation employed considers buildings constructed after 2006 (Figure 11 (b) and (c)). Focusing on the extreme flood situation (T>300 years), the S4-LFPM2 (see Figure 10 (c)) results in losses that fall within the range but are slightly above the losses for the 2012 scenario. In contrast, the LFPM1 shows very limited loss-reduction potential under extreme flood situations (see Figure 10 (b)). The majority of buildings considered with LFPM1 experience damages, far exceeding the losses of scenario 2012. Further, LFPM1 was tested assuming that not only new buildings, but also existing buildings are considered to be flood safe (LFPM1- Y-All, Figure 10 (a)). It can again be seen that for the T>300 years flood scenario, the loss reduction potential given at lower flows largely decreases. Expected losses in the extreme settlement scenario (S4) considering LFPM1 are calculated to be 26.8 m. EUR. They exceed the expected losses of the 2012 scenario without implemented LFPMs (calculated to be 24.7 m. EUR). The application of LFPM2 to all buildings was not evaluated since this is a theoretical case, requiring elevated construction for existing buildings. Figure 11: Comparison of settlement scenarios 2012 and S4 when applying (a) LFPM1 to all properties and applying (b) LFPM1 or (c) LFPM2 to properties constructed after 2006.
Discussion The common approach to quantifying flood magnitudes is the definition of recurrence intervals with flood peak flows. This approach is applied in the presented case study as well, linking the calculated losses to the peak flows observed. However, losses that arise may vary as the flood plain characteristic is not fully describable solely by peak flows of design precipitation events (Plörer et al. 2012). To consider that, the 2002 event was used within this study to represent a realistic spatial distribution of the corresponding rain event. Further possible event characteristics may affect results, but the
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application of further varying storm events was limited due to the lack of observed data. Considering findings by Plörer et al. (2012), a certain additional variation is introduced when different spatially and temporal distributed storm event were used. The different random conditions with respect to precipitation events (design events versus event-based approach) becomes visible when comparing different LFPM effects which rely on the official T=100-year flood plain. However, the implementation of the LFMPs (HQ100+20cm) considered is based on the official flood hazard map with a recurrence interval of T=100 to correspond with the regulations of the Provincial Act of Upper Austria. The standard procedure to derive flood hazard maps in Austria is the application of a design event approach (in this case, spatially and temporally uniformly distributed rainfall events). The 2002 flood event, in contrast, reflects the hydrological basis for the scenarios investigated with a spatial and temporal dynamic. Thus, although the peak flow at the gauge may be the same, it is not necessarily the case that all parts in the catchment receive the same inundation effect as the standard procedure considers homogenous events whereas the event-based approach applied here considers more heterogeneous event characteristics. A second kind of spatial variation which is considered only to a limited extent is the distribution of future settlement. This is covered by pragmatically developed settlement scenarios representing different intensities of future development. Considering dynamic urban development concepts (Mikovits et al. 2014) using a varying spatial distribution of properties over time could cover a broader set of scenarios. Consequently, this would allow for better accounts of the uncertainty in future settlement development. Together, the various damage functions presented above reveal a large variability in the results (Figure 7). When aiming for accurate absolute losses, a limitation is given with the inherent uncertainty while transferring damage functions from other region to the investigated catchment (Cammerer et al. 2013). The verification of the used combination of asset assessment and damage functions is limited due to missing reference data. The presented results however are focused on the asset assessment approach of the regional insurance company in the study area, and thus reflects the most suitable and applicable approach for the study area. The considered damage functions seem to be the best fit among all the other introduced damage functions, at least in the Austrian Federal Province of Vorarlberg (Huttenlau et al. 2015). Therefore, using the findings to quantify absolute losses bears uncertainties. Still, the relative comparisons of cases with or without LFPM applied give an insight to the bound of application. For the measures investigated, simplified assumptions were applied. All properties use the same elevation level (water level of the official hazard maps HQ100+20cm) until flood safety is achieved. Secondly, the permanent functioning and in-time installation of all local barriers was assumed. Thus, the effects of local flood barriers may be less than estimated here. The stochastic approach used considers a fixed statistical distribution of floods in an Annual Maximum Series (AMS). Any future altering of the catchment characteristic with respect to the impacts of land use or climate change are not considered.
Conclusion and Outlook The methods employed bear uncertainties with regard to the precise analysis of absolute loss values but allow the quantification and comparison of orders of losses. Nevertheless, the relative impact of settlement scenarios or mitigation measures implemented can be investigated. The consideration of damages that accumulate over certain design periods shows an increase across different settlement scenarios. The measures applied prove to be very efficient and appear well suited on first view. Yet this could also be a catchment-specific situation as it is characterized through high frequency/low impact events rather than low frequency/high impact events. Thus, the total damage in a design period is less triggered by large events than by many small events causing damages. With respect to the analysis of single events, it can be stated that the positive effects of LFPM, specifically flexible flood barriers (type LFPM1), largely decrease for large flood events exceeding the design level. However, the measure is still beneficial for many smaller events and can as well be applied to existing buildings located in the flood-prone area. The expected basin-wide loss-reduction potential of the retrofitable LFPM1 approach seems to be high for all high frequency/low impact
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events and low frequency/high impact events until the threshold of the water level (here HQ100+20cm) is reached. The analysis is based on scenarios derived from the 2002 storm event incorporating its temporal and spatial characteristics. Considering other storm scenarios could introduce a varying impact, attributable to a certain peak flow. Still the basin remains sensitive to high frequency/low impact events, regardless of the specific event data used. Intensified settlement in the flood-prone area leads to an increase in flood risk (compare scenarios 2012 (LFPM0), S2 (LFPM0) and S4 (LFPM0)). This increase cannot be compensated for, neither by the LFPM type 1 nor 2. This leads to the conclusion that flood losses can be reduced with appropriate LFPM, but from a sustainable perspective further construction activities should be avoided in flood-prone areas. This argument is additionally stressed by the Austrian flood insurance market, where flood losses over a very limited threshold are not covered (Holub et al. 2011). Although such claims significantly increase with the magnitude of an event, for existing buildings, LFPM are a vital option to reduce basin-wide losses at small impact magnitudes.
Acknowledgements This study is part of the project "Stochastische Schadensmodellierung Ottnanger Redl" supported by the Austrian Federal Province of Upper Austria.
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List of figures Figure 12: Catchment Ottnanger Redl: Overview with precipitation gauges and the discharge gauge Attnang. Figure 13: Modelling concept and work flow (numbers in parentheses indicate chapters). Figure 14: Overview of (a) the hydrological modell (HEC HMS) and (b) the bounds of the 2D hydraulic modell (Hydro-AS). Figure 15: Observed and simulated discharge Q at the gauge Attnang during the flood event in August 2002. Figure 16: Schematic on the implementation of altered damage functions due to Local Flood Protection Measures (a) flexible barriers (LFPM1) and (b) elevated construction (LFPM2). Figure 17: Flood plain at main urban settlement Attnang-Puchheim. Using the storm event 2002 scaled by factor 1.2; (~HQ100). Figure 18: Calculated flood losses of a 100 year flood in the catchment Ottnanger Redl with varying (a) methods for monetary asset assessment and (b) damage functions; Settlement scenario 2012 without LFMP.
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Figure 19: Development of event-based flood losses with increased discharge under consideration of the individual settlement scenarios. Figure 20: Development of event based flood damages with/without LFPM for different settlement scenarios (a) 1999 (b) 2012, (c) S2 and (d) S4. Figure 21: Cumulative losses over design periods of D=20 years ((a) and (b)) and D=100 years ((c) and (d)), considering varying types of flood protections applied to different settling scenarios Figure 22: Comparison of settlement scenarios 2012 and S4 when applying (a) LFPM1 to all properties and applying (b) LFPM1 or (c) LFPM2 to properties constructed after 2006.
Tables (For literature cited in tables see last page) Table 5: Design discharge QD at gauge Attnang for selected recurrence intervals
T [years] QD [m3/s]
10 45.6 30 62.4 100 81.5 300 100.0
Table 6: Overview of approaches for building asset assessment
Abbreviation Origin Description
BFW Switzerland This method for building asset assessment from Oberndorfer et al. (2007) is based on
asset values from a swiss study (Borter et al. 1999a, Borter et al. 1999b). Assets are
differentiated for the type of building structure and inventory to derive mean asset values
for specific uses.
BMVBS Germany This approach applies the concept of standard construction costs according to the
guidelines of the German Federal Ministry of Transportation, Building and Urban
Development as part of the official asset value method of the Property Valuation
Regulation (Sachwertrichtlinie – SW-RL 2012). It designates a specific asset value per
gross floor area (EUR/m2) for different types of buildings. The inventory quality and
building age are considered for residential buildings.
OOV Austria This detailed approach is based on internal insurance policy guidelines of the regional
insurance company in the study area, the Oberösterreichische Versicherungs AG. The
asset assessment for residential buildings is based on the built-up area, number of floors
and basement and attic conversion (Oberösterreichische Versicherung AG 2012a). A
categorization is made for main and subsidiary buildings (e.g. Garage, Garden shed,...)
and with regard to the inventory (simple, medium and good). The construction cost for
commercial buildings are based on the gross volume of enclosed space
(Oberösterreichische Versicherung AG 2011). Additional flat rate values are provided for
the assessment of buildings on agricultural properties. (Oberösterreichische Versicherung
AG 2012b).
WLV Austria This asset assessment method is based on a report discussing suggestions to improve the
cost-benefit analysis of the Austrian Forest Engineering Service in Torrent and
Avalanche Control (Hübl and Kraus 2004). Therein prices of construction costs are used
for the monetary assessment (Kranewitter 2002). For residential buildings country-
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specific construction costs per gross-volume of enclosed space are used. Furthermore, the
quality of the inventory (simple, medium and good) and the room height (2.6 or 3.2 m)
are considered. In this study, prices for residential buildings in Upper Austria with good
inventory and room heights according to the object type (detached house=2.6 m, multiple
family house=3.2 m) are used. Commercial and industrial buildings can be subjected to
reductions and surcharges according to inventory and the type of construction.
Table 7: Overview of applied damage functions
Abbreviation Source Country Number of
Object
Categories1)
Inventory
considered
separately 2)
Reference
BUWAL Bundesamt für Umwelt, Wald
und Landschaft (Swiss Federal
Office for the Environment,
Forests and Landscape)
Switzerland 7 Yes (Borter et al. 1999a, Borter
et al. 1999b)
DASC Damage Scanner Netherlands 8 No (Klijn et al. 2007)
FLEMI Flemish Model Belgium 7 Yes (Vanneuville et al. 2006)
FLEMO Flood Loss Estimation Model Germany 8 Yes (Büchele et al. 2006)
(Kreibich et al. 2009)
HUBL University of Natural Resources
and Applied Life Sciences
(BOKU) , Hübl und Kraus
Austria 1 No (Hübl and Kraus 2004)
IKSE Internationale Kommission zum
Schutz der Elbe (International
Commission for the Protection of
the Elbe)
Germany 5 No (IKSE 2003)
MURL Ministerium für Umwelt,
Raumordnung und
Landwirtschaft des Landes
Nordrhein-Westfalen (Ministry
for Environment, Regional
Planning and Agriculture of
North Rhine-Westphalia)
Germany 7 Yes (MURL 2000)
RHEI Rhine Atlas Germany 7 Yes (IKSR 2001)
1) For details on the considered object categories, the reader is please see the original literature 2) [Yes] Inventory is considered in a separate damage function, [No] Inventory is included in the total damage function Table 8: Hydraulic scenarios with various precipitation scaling factor (sf[-]) and corresponding recurrence interval (T) with regard to the peak design discharge (QD)
sf [-] T [years] QD [m3/s]
0.4 1.1 3.2 0.6 1.8 18.4 0.8 6.5 39.0 1.0 21.3 57.1 1.2 99.5 80.2
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1.4 390.0 104.5
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