|
了解东盟主席国菲律宾的水务GIS系统的发展
Digital Surface Model (DSM) Construction and Flood Hazard Simulation for Development Plans in Naga City, Philippines
Muhammad Zulkarnain Abd Rahman
Remote Sensing Department
Faculty of Geoinformation Science and Engineering
Universiti Teknologi Malaysia
Dinand Alkema
International Institute for
Geoinformation Science and Earth Observation (ITC),
Enschede, the Netherlands
Abstract
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.
1. INTRODUCTION
Rapid and uncontrolled urbanization in developing countries has become one of the major issues in hazard and risk management. This is certainly one of the major environmental problems in the developing world, today and in the years to come. A huge concentration of people, business activities and properties has made hazard management in urban area more difficult and complex. With an increased value of property, for instance, buildings and other structures, potential damage from prolonged and severe flooding can easily extend into the million of dollars. Besides, flooding in crowded area due to rapid urbanization would dramatically increase the loss. Urbanization has a great influence on rainfall runoff and flood behaviour. The flow of the floodwater becomes complex as a result of complicated buildings distribution and structures in an urban area. Heavy rainfall is easily converted to run-off over paved surface, and due to improper urbanization planning, water will accumulate and increase the potential of flooding. As a consequence, it is a great challenge to forecast urban flooding and calculate the potential damage. Improper development planning, in developing countries, might ignore its impact on flood hazard and risk to the surrounding community.
Advancement in computer processing power, accurate terrain data acquisition and the integration between 1 dimensional (1D) and 2 dimensional (2D) flood modelling make possible to model dynamic flooding in a complex urban environment. The 2D flood modeling requires information on terrain, which quality depends on the acquisition techniques and the terrain of the study area. Complex and densely populated urban areas require more detailed terrain elevation data compared to rural area. In urban areas, the characteristics of floodwater flow are controlled by the distribution of buildings, roads, elevated area and etc. This requires the basis on defining the spatial resolution and accuracy of Digital Terrain Model (DTM). Changes in urban area as a result of urbanization can be simulated trough modification of the existing DTM and/or land use or land cover information.
The main objective of this research is to generate DTM and DSM of the study area with consideration on current and future developments, followed by simulating the flood events and development impact assessment. The development impact assessment was made based on three methods; 1) Changes in flood characteristics 2) Changes in flood risk perception by the Naga City Community and 3) Changes in flood hazard area.
2. STUDY SITE
Naga City is located in Bicol region, at the south-eastern tip of the Philippine island of Luzon. Naga City, located about 377 km to the south of Manila, is well known as a fast-growing area (see figure 2.1). Naga City has the largest population among 35 municipalities in Camarines Sur, which population covers about 8.9 percent of the total population of the province (Naga City Government Philippines Business for Social Progress, 2001). Naga is considered the heart of the Bicol region, consists of 27 Barangays on the land of 7,748 hectares. The main portion of The Naga city is located in low and flat topography that usually inundated by flood when water from the Naga and Bicol River overflow. Thus, substantial discharge and heavy rainfall during monsoon commonly causes severe flood in this city.
Figure 2.1: Naga City
Apart from the current developments in Naga City, several other developments are being introduced and aimed at giving better facilities for the community. According to the Naga City Development Plan, the developments are divided into 6 main zones; 1) Central Business District I (CBD I), 2) Central Business District II (CBD II), 3) South Riverfront Growth Area, 4) Concepcion Growth Corridor, 5) East Highland Tourism Zone and 6) Naga City Agro-Industrial Zone. Some of these zones are located in flood prone area, for instance CBD II.
3. DATA COLLECTION RESEARCH METHODOLOGY
In this research the data collection is divided into 4 major groups as follow.
- Elevation or topographical data
- Landuse or landcover
- Recent and future developments
- Rainfall and floodwater depth during the Super Typhoon Nanmadol.
Apart from the available topographical data, additional elevation information is needed to fill gaps in the available data and to update terrain information due to recent and future developments. Other necessary data for instance Landuse or Landcover, Rainfall, flood depth and extent and flood risk perception are needed in flood modeling and development impact assessment.
This study is divided into 4 main phases, namely, 1) Data preparation and analysis, 2) DTM and DSM modelling, 3) flood model calibration and modelling and 4) development impact assessment (see figure 3.1). The first phase focuses on data preparation, analysis and integration. The main data is divided into landuse and landcover, flood information, terrain data, hydrological data and flood hazard data. The second phase of the research methodology concerns on the construction of DTM and DSM based on different sources of elevation data, which were derived from both primary and secondary sources. The primary data collection aims at filling the gaps in the available data and to update terrain changes in the study area as a result of recent developments. In general, the elevation data is derived in various forms, for instance points, line and polygons, and these data are then aggregated into ground terrain and man-made features. Further aggregation is made to separate the elevation data into two terrain situations; current and future situations. The DTMs are produced using different terrain interpolation methods. The best product is selected and integrated with man ?made features to produce DSMs of the study area.
The 1D2D SOBEK flood model is used to simulate 5 recurrence intervals flood events. The flood calibration is made base on flood depth information derived from recent field observations (this data were collected by Saut Sagala and Peters Guarin Graciela) after the flood event caused by the Super typhoon Nanmadol (with an equivalent to 10 years return period flood). The flood depth information was collected through interviews with the local community in Barangay Triangulo and Barangay Sabang few months after the flood event. The flood calibration is based on two aspects; surface roughness and building structure. The calibrated surface roughness and the suitable building representation will be used for further flood modelling. The surface roughness value of the study is based on landuse or landcover. This updated information is used together with development plans to create recent and future landuse or landcover in Naga City.
The final phase emphasizes on development impact assessments based on detailed investigation of flood characteristics before and after the development. This is supported by additional assessment focuses on changes of flood hazard areas for current and future situation of Naga City. The definition of flood hazard is based on the combination of flood velocity and flood depth.
Figure 3.1: Overall research methodology
3.1 DTM and DSM construction
DTM and DSM of the study area were generated in 4 major steps; 1) elevation data preparation and analysis, 2) elevation data interpolation, 3) accuracy assessment and reporting and finally 4) integrating natural terrain with man made terrain to produce DSM.
3.1.1 Elevation data preparation and analysis
The elevation dataset for DTM generation is derived through the integration of various elevation data sources and these data vary in both horizontal and vertical accuracies (see appendix 1). Blomgren (1999), in his study used a rectilinear grid over the contour lines to transfer elevation information from contour lines to point forms. The point was digitized as close as possible to the overlaid grid. Therefore, more evenly distributed elevation samples were derived, and it improved the interpolation performance (Blomgren, 1999). On the other hand, the arrangement of elevation data will influence the shape of the variogram model. In this case, the clustered elevation data, which were found around dunes, road embankments and other local abrupt changes in topography, were removed from the dataset (Blomgren, 1999). Wilson and Atkinson (2003) in their research, ?Prediction the uncertainty of DEM on flood inundation modelling?, used the ordinary kriging to interpolate the elevation data in the floodplain area. The elevation data was the combination between the contour lines and the elevation points that were derived from GPS measurement. The original experimental semi-variogram of the contour lines had quite general shape. However this general shape or trend was reduced (increased variance at shorter lags than globally) when the elevation points derived from GPS measurements were added to the dataset.
Ten set elevation data were used and integrated to produce DTM. These datasets vary in scale and contour interval which remarks difference in horizontal (planimetric) and vertical accuracies. Besides the elevation information derived from the available topographical maps, additional elevation measurements using geodetic levelling were done to fill the gaps and update terrain information of recently developed area. The problem of integrating elevation data from different sources with different scales and accuracies lies on the fact that the elevation values in the combined dataset may lie close to each other. The challenge is to identify an appropriate approach to prioritize the datasets, to identify which of those datasets represent the true terrain elevation and to combine the entire datasets. Thus, the datasets are prioritized with 2 steps; 1) Prioritization based on Nominal horizontal and vertical accuracies (based on the National Standard Data Accuracy (NSSDA)), 2) Prioritization based on data forms (spot heights and contour lines) and production date (see table 3.1).
Table 3.1: Available elevation data sources for DTM generation
The contour lines are converted to points and then combined with other point form data (spot heights). Data with higher priority score would replace the lower priority score data. The replacement is done when 2 or more elevation points fall within 3 meters radius. The effect of the integration of the multi-sources elevation data is assessed by mean of semi-variogram analysis. The assumption is points that are close together should have less difference or high autocorrelation. Thus, high nugget value would reveal strong effect of disagreement between the elevation datasets. Certainly, the nugget effect could also attribute to the complexity of terrain features. However it was found that, the effect of data disagreement still appear when datasets with complex geomorphological features are removed. Several attempts with different integration method were used (see table 3.2) to decrease the nugget value. However, for the sake of the terrain complexity information, the nugget value was reduced from 2.9 to 2.2.
Table 3.2: The value of Semi-variogram model parameters for each dataset; the 2nd and the 3rd datasets will be used for the DTM interpolation
At this stage, the integrated elevation datasets with low nugget value are assumed to have less disagreement between elevation dataset, less overlapping dataset, good elevation data in representing the real terrain and inevitably contain less degraded complex terrain features. |
|