Data integration

Processes on the planet Earth are complex phenomena that are taking place in space and in time, i.e. in four dimensions. In many of these processes, differences in one dimension (e.g. height above the geoid) can be disregarded, so that two spatial dimensions and the dimension time remain. Despite this simplification, the physical description of the phenomena remains a difficult task. To better understand the processes it often helps if the same geographic region is viewed repeatedly and, if possible, also from different directions and in different wavelength regions. Integration of data from a variety of sources can be a means to retrieving information about processes that would otherwise remain undetected

Digital Surface Model (DSM) Construction and Flood Hazard Simulation for Development Plans in Naga City, Philippines

A 2D-hydraulic flood propagation models require accurate elevation data. One of the main problems is frequent changes of land use in major cities, where frequent updating of the digital terrain model (DTM) for flood modelling might be needed. On the other hand the assessment should be based on realistic flood hazard indicator that would help to reflect the real impact of urban development on the surrounding areas. This paper presents an example of assessing the impact of flood for future developments in Naga City, the Philippines. The elevation data is constructed through integrating various elevation data derived from many sources. The development impact assessment begins with the detailed observation on changes in flood characteristics. This is supported by the analyses on the community-based flood risk perception and investigation on changes of flood hazard (based on the flood velocity and depth). In the DTM construction the natural terrain is separated from the man-made terrain. The geostatistical approach is used to investigate the effect of integrating multi-sources of elevation data by evaluating the nugget values. The data sources are prioritized based on the nominal horizontal and vertical accuracy, and form of data. In this paper, there are 4 interpolation methods used, namely Australian National University's Digital Elevation Model algorithm (ANUDEM), Kriging, Polynomial and Triangulated Irregular Network (TIN). The assessments are based on percentile vertical accuracy assessment, error point’s distribution and visual assessment. As a result, the kriging interpolation method has produced the best DTM and it full-filled the requirements for hydrological flood modelling purpose. Finally the Digital Surface Model (DSM) of the study area was constructed by integrating both man-made and natural terrains. The DSM was also generated to simulate the new developments in Naga City. The 1D2D SOBEK flood model was used to simulate flood events for 2, 5, 10 and 17.5 years return period flood. In addition, the flood depths and flood extent during Supertyphoon Nanmadol were used in flood model calibration. Flood calibration results revealed that the calibrated flood model was able to simulate the real flood event up to 0.35 m accuracy of flood depth. In the development impact assessment, it was found that the impact of the developments is larger for a larger flood magnitude. Furthermore the pattern of the changes in flood behaviour depends on the location from the main developments. The Almeda Highway acted as a barrier, that obstructs the flood water from go farther. In addition the small scale construction, for instance the Drainage System in Barangay Triangulo had played a major role in changing the flood behaviour, especially in a small magnitude flood. Through this study, it was proved that by simply elevating ground terrain only can solve the flood problem in a particular area. However, the flood problem is transferred to another area

RURAL FLASH-FLOOD BEHAVIOR IN GOUYAVE WATERSHED, GRENADA, CARIBBEAN ISLAND

Flash-flood is considered as one of the most common natural disasters in Grenada, a tropical small state island in Caribbean Island. Grenada has several areas which are susceptible to flooding. One of them is Gouyave town which is located in the north-west of Grenada. Its land-use types are highly dominated by green areas, especially in the upper-part of the region. The built-up areas can only be found in the lower-part of Gouyave watershed, near the coastal area. However, there were many land conversions from natural land-use types into built-up areas in the upper-part region. They affected the decrease of water infiltration and the increase of potential run-off, making these areas susceptible to flash-flood. In addition, it is also influenced by the phenomenon of climate change. Changes in extreme temperature increase higher potential of hurricanes or wind-storm, directly related to the potential escalation of flash-flood. To develop effective mitigation strategies, understanding the behavior of flash-flood is required. The purpose of this paper was to observe the behavior of flash-flood in Gouyave watershed in various return periods using OpenLISEM software. It was used to develop and analyse the flash-flood characteristics. The result showed that the climatic condition (rainfall intensity) and land-use are influential to the flash-flood event. Flash-flood occurs in 35 and 100 years return period. Flash-flood inundates Gouyave’s area in long duration, with below 1 m flood depth. The flood propagation time is slow. This condition is also influenced by the narrower and longer of Gouyave basin shape. To develop flash-flood reduction strategies, the overall understanding of flash-flood behavior is important. If the mitigation strategy is adapted to their behavior, the implementation will be more optimum

Flood hazard simulation for development plans in urban environment: a case study in Naga City, the Philippines

Accurate and detailed terrain model are essential for hydrodynamics modelling especially in urban area. However, one of the main problems is frequent changes of land use in major cities, where frequent updating of the digital terrain model (DTM) for flood modelling might be needed. This paper presents one of the feasible approaches to assess the impact of developments on flood behaviours in an urban area. The input terrain model for hydrodynamic modelling is constructed through integrating different elevation datasets derived from various sources. Finally, the impact of the development on flood behaviour is made through detailed investigation on changes in flood hazard area. In the Digital Terrain Model development, the semivariogram of the geostatistical approach is used to investigate the effect of integrating various sources of elevation datasets. Furthermore, four interpolation methods were used for terrain interpolation, namely Australian National University's Digital Elevation Model algorithm (ANUDEM), Kriging, Polynomial and Triangulated Irregular Network (TIN). The assessments of the terrain models are based on the “Percentile Vertical Accuracy Assessment�, the distribution of errors and visual assessment of the DTMs. In this study, it was found that the DTM produced by Kriging is better than the DTMs produced by other interpolators and it fits with the requirements for the flood modelling purpose. In conjunction, two sets of Digital Surface Model (DSM) were constructed to represent the situation of Naga City, before and after the developments. The flood modelling is based on the 1D and 2D SOBEK flood model that used to simulate the flood events of 2, 5, 10 and 17.5 years return period flood. According to the results, it was proved that by simply elevating ground terrain in particular areas might not be a good solution for flood mitigation. This approach could create another flood problem in vicinity area

A new flood type classification method for use in climate change impact studies

Flood type classification is an optimal tool to cluster floods with similar meteorological triggering conditions. Under climate change these flood types may change differently as well as new flood types develop. This paper presents a new methodology to classify flood types, particularly for use in climate change impact studies. A weather generator is coupled with a conceptual rainfall-runoff model to create long synthetic records of discharge to efficiently build an inventory with high number of flood events. Significant discharge days are classified into causal types using k-means clustering of temperature and precipitation indicators capturing differences in rainfall amount, antecedent rainfall and snow-cover and day of year. From climate projections of bias-corrected temperature and precipitation, future discharge and associated change in flood types are assessed. The approach is applied to two different Alpine catchments: the Ubaye region, a small catchment in France, dominated by rain-on-snow flood events during spring, and the larger Salzach catchment in Austria, affected more by rainfall summer/autumn flood events. The results show that the approach is able to reproduce the observed flood types in both catchments. Under future climate scenarios, the methodology identifies changes in the distribution of flood types and characteristics of the flood types in both study areas. The developed methodology has potential to be used flood impact assessment and disaster risk management as future changes in flood types will have implications for both the local social and ecological systems in the future