# Multitemporal SAR Data and 2D Hydrodynamic Model Flood Scenario Dynamics Assessment
## 1 Introduction  
Floods are one of the most frequently occurring and costliest hazards worldwide. Between 1998 and 2009 alone, the European Environment Agency estimated that 213 flood events in Europe caused about 1126 fatalities, affected more than 3 million people, and caused at least 52 billion in losses [1]. Moreover, the United Nation [2] has estimated that one third of the world's population (around 2.3 billion people) has been affected by floods in the last 20 years. The expectation that large-scale flood damage will increase over time due to climate and land-use change and social growth in flood-prone areas has raised public and policymaker awareness withregard to operationalization of procedures and actions that will reduce flood effects and increase urban resilience [3]. Since budgets for risk management are limited, the choice of appropriate measurements (structural and non-structural), the assessment of the costs and effects of such measurements, and their prioritization are crucial for decision makers [4], who must keep overall spending to a minimum for all stages of the flood risk management cycle (i.e., risk analysis and reduction, emergency response, recovery, and reconstruction [5]). In this context, accurate prior damage evaluation has emerged as a necessity for the cost-effective risk reduction actions ([6; 7]). Moreover, prompt assessment of damage in the early-recovery response phase is becoming decisive for coping with residual risk, in particular, for rescue organization and relief efforts ([8; 9]). In this context, during the monitoring and relief stages of a disaster risk reduction (DRR) cycle, an accurate representation is required of the flood event in terms of spatio-temporal dynamics and with regard to forecasting consequences [10]. Despite active research in this technical and research field, the combination of the complex and chaotic nature of flooding, the (often) fast dynamics of the phenomenon, and the increasing need for on-demand, in situ high spatial resolution data make particularly complicated to perform rapid and accurate flood analysis in what are usually complex topographies of flat terrain, such as urbanized areas located at river delta [11]. In the light of this, hydrodynamic modeling has become an indispensable tool for the forecasting and monitoring of spatio-temporal flood dynamics ([12; 13]). Theoretically, a comprehensive set of data useful for flood damage estimation, such as physically based maps of the extent of the flood, water depth, flow direction and velocity can be provided by two-dimensional numerical hydraulic models, even in extremely flat and complex topographies [14]. However, to be reliable, bi-dimensional (2D) hydraulic models need to be controlled, for example, through a calibration process that adjusts model parameters, assumptions, or equations to optimize concordance between observed data and model predictions. Calibration techniques and challenges depend on the nature of the flood (e.g., riverine vs. flash floods, coastal, urban or groundwater floods) since for each flood type the most relevant parameters may be different [15]. In an operational context, calibration is usually performed using in situ observation points, such as recorded hydrographs at hydrometric stations. However, this approach only evaluates the simulation of bulk flow routing to those specific points, and as a consequence the flood propagation dynamic in floodplains cannot be measured [16]. Moreover, during a calamitous flood event, the information recorded by ground sensors is often not available due to malfunctions caused by the impact of the flood flow. Aerial photography might be used as a source of data on extent of inundation on the floodplain, but airborne campaigns are generally very expensive and often unaffordable.