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Introduction Flooding is a natural phenomenon, but human activity has significantly altered the natural drainage processes thereby occasionally causing greater flood risk. Urban flooding has become more frequent due to a number of factors including climate change, urban growth and an increase in paved surfaces. Pluvial flooding results from heavy rainfall when water that does not infiltrate into the ground ponds in hollows or flows over the ground. In flood damage estimation, the concept of damage curves or damage functions is applied. Such functions give the building damage due to inundation. Most damage assessment models have in common that the direct monetary damage is obtained from the type of the element at risk and the inundation depth. Problem definition Flood damage assessment models do not focus solely on pluvial flood damage estimation. In addition, the existing flood damage models and developed depth-damage curves have not been tested for application of pluvial flood events. Research This study is carried out with the main objective to test the flood damage assessment model HOWAD-PREVENT in a case study in Rotterdam and to evaluate the uncertainty and sensitivity of this model. The model applicability and sensitivity was tested by running the model with two building type files together with three water level files.

Introduction Flood risks can be reduced by either reducing the probability or the consequences of a flooding. These consequences can be quantified with flood damage models. Such models determine flood damage based on the water depth and the land use. This thesis will investigate the need to also use the flood duration as input parameter. Problem definition Besides the water depth, also other factors determine the resulting flood damages. These factors are often not taken into account in flood damage models. One of these influences is the flood duration. The longer a flooding lasts, the larger the material damage, and especially damage due to interruption will be. Flood duration causes interruptions and extra material damages. Taking into account flood duration can, therefore, theoretically make flood damage models more accurate. Flood duration predictions are, however, at the moment rarely done. This thesis aims to get both a qualitative and quantitative understanding of flood duration and the importance of flood duration for damage assessments. Research This thesis aims to explore the possibilities of assessing flood duration for flood risk management. This is approached by the following steps. 1. Development of a better understanding of flood duration. By looking at different areas and flood threats, a flood type categorization was developed and durations were estimated for each flood type 2. Exploration of the influence of flood duration on damage. A modeling method to roughly estimate the duration-dependent damage was developed. The framework of this method may also be useful for future duration dependent flood damage models. 3. Two case studies were carried out to study flood duration and its influence on damage in more detail: First the Betuwe and Tieler & Culemburgerwaard area was studied and secondly the area threatened by a breach at the Parksluizen in Rotterdam was focused on. Different scenarios were used with varying breach locations, measures and use of outlet and drainage structures. Results 1. The most important factors which determine the flood duration are duration necessary to repair the breaches, the possibilities for drainage by gravity, the elevation and elevation variation in the area and the magnitude of the flood event. Flooding durations in the Netherlands vary between hours and about one year. 2. Adding flood duration as input to flood damage models adds a little extra accuracy. This is limited because flood duration is correlated with the water depth. With the current flood damage accuracy, incorporating flood duration is only useful for specific cost benefit analysis related to measures that aim to change the flood duration. Conclusions and recommendations Flood duration can be significant for large floods in low and endyked areas. In these cases flood duration can also have a significant impact on the damage. However, a complex economic model is necessary to quantify this. Therefore, flood duration can only reach its full value as an input, in combination with better economic modeling.

Drainage- and storm runoff water is partly guided into the Right Main Canal of the Lam Pao irrigation project (Northeast Thailand). Measures are required to limit the chances on cross drainage flood damage. In the first reaches of the RMC (KM 0+000 - KM 37+130) there are 6 gated drainage outlet structures, but only one (at KM 4+893) is operational. It is found that an extra diversion discharge capacity of 13 cms is required. Therefore it is recommended to equip 3 of the existing drainage outlets (at KM 12+530, KM 17+140 and KM 20+440) with automatic Begemann gates. Outlet 5 (at KM 23+100) is close to a check structure and can simply be upgraded again with manually operated gates. It can be used in case supplementary spillway capacity is required. This study presents the hydraulic and structural design of the gates and substructure. It is found that relatively small gates can profitably be applied. Therefore the structures are each provided with 3 gates, each having a width of 1.00m. Sill elevation is 0.50m below full supply level.

Insurance databases form a promising data source that can be used to improve pluvial flood damage estimations. This paper describes the key characteristics of an insurance database on water related damages to private buildings and content in the Netherlands that has been made available for research. The paper presents preliminary results of a case study where insurance data are explored to find relationships between rainfall characteristics and pluvial flood damage. The results show that variations in damage are partly related to rainfall characteristics. More research on rainfall characteristics and other explanatory variables of flood damage is needed to capture the processes causing damage.

This study presents a first attempt to quantify tangible and intangible flood damage according to two different damage metrics: monetary values and number of people affected by flooding. Tangible damage includes material damage to buildings and infrastructure; intangible damage includes damages that are difficult to quantify exactly, such as stress and inconvenience. The data used are representative of lowland flooding incidents with return periods up to 10 years. The results show that monetarisation of damage prioritises damage to buildings in comparison with roads, cycle paths and footpaths. When, on the other hand, damage is expressed in terms of numbers of people affected by a flood, road flooding is the main contributor to total flood damage. The results also show that the cumulative damage of 10 years of successive flood events is almost equal to the damage of a singular event with a T = 125 years return period. Differentiation between urban functions and the use of different kinds of damage metrics to quantify flood risk provide the opportunity to weigh tangible and intangible damages from an economic and societal perspective.

Flood damage estimation is essential to flood risk analysis. Flood hazards, values of elements at risk and vulnerability of elements determine flood damage. However, these determinants entail uncertainties. In this study, water depth, values of elements at risk and damage function are selected as three key parameters. The local sensitivity method, which changes the value of one parameter at one time, is adopted to determine the sensitivity degrees of parameters for flood damage estimation in downtown Shanghai, China. The variance of 25% for water depth as a function of different return periods of 50,100, 200,500,1000 and 10,000 years, values of elements at risk and damage functions (piecewise function and square-root function) are uniformly taken into account in the sensitivity analysis. Sensitivity value (SV) for three parameters, which stands for the influential degree to the results of flood damage, are obtained by the largest damage being divided by the smallest damage if only changing one parameter at one time separately. The results show damage function has largest influential degree among the three parameters with SV of 2.69; while parameters of values of elements at risk (SV: 2.22) and water depth (SV: 1.81) are also significant. This suggests future research to focus first on reducing uncertainties in the flood damage functions.